San Diego International Airport Expansion Sustainability Analysis

San Diego InternationalAirport ExpansionSustainability Analysis

A G l o b a l A l l i a n c e

February 2008

San Diego International Airport Expansion

San Diego International Airport Expansion – Sustainability Analysis February 2008 Prepared for:

California Independent Voter Project

Report Prepared By:

Malcolm Pirnie, Inc. 8001 Irvine Center Drive Suite 1100 Irvine, CA 92618 Sinclair Knight Merz 590 Orrong Road Armadale Melbourne VIC 3143 Australia

6189001

A Global Alliance

Table of Contents

San Diego International Airport Expansion: Sustainability Analysis i

Contents

Executive Summary 1

1. Introduction 1-11.1. Background................................................................................................................... 1-1 1.2. Expansion Alternatives ................................................................................................. 1-3

1.2.1. DEIR No Project Alternative.......................................................................... 1-4 1.2.2. DEIR Preferred Alternative (Proposed Project with Parking Structure) ........ 1-5 1.2.3. Proposed Lindbergh Intermodal Transportation Center................................ 1-5

1.3. Report Objectives and Content................................................................................... 1-10

2. Transportation Analysis 2-12.1. Background................................................................................................................... 2-1

2.1.1. Regional Transportation................................................................................ 2-1 2.2. Airport Ground Transportation ...................................................................................... 2-3

2.2.1. Road Network................................................................................................ 2-3 2.2.2. Transit............................................................................................................ 2-5 2.2.3. Trolley............................................................................................................ 2-7 2.2.4. Bus ................................................................................................................ 2-9 2.2.5. Coaster .......................................................................................................... 2-9 2.2.6. Amtrak ........................................................................................................... 2-9 2.2.7. SDCRAA Airport Transit Plan ..................................................................... 2-10 2.2.8. Mitigation Measures to Address Airport Related Traffic.............................. 2-10

2.3. Scenario Modeling ...................................................................................................... 2-12 2.3.1. Modeling Approach ..................................................................................... 2-12 2.3.2. Modeled Scenarios...................................................................................... 2-13

2.4. Results and Discussion............................................................................................... 2-15 2.4.1. Mode Share................................................................................................. 2-15

2.4.1.1. Transit Demand...................................................................... 2-20 2.4.1.2. Transit Capacity...................................................................... 2-24

2.4.2. Vehicle Miles Traveled (VMT) ..................................................................... 2-25 2.4.3. Level of Service........................................................................................... 2-27

2.4.3.1. Traffic Analysis – Road Network Level of Service for Scenario 3 (DEIR Preferred Alternative) .................................................. 2-28

2.4.3.2. Traffic Analysis – Road Network Level of Service for Scenario 4 (Lindbergh ITC) ...................................................................... 2-30

2.4.4. Impact of Assumptions ................................................................................ 2-30 2.4.5. Equity and Wider Sustainability Benefits..................................................... 2-32

3. Greenhouse Gas and Criteria Pollutant Emissions 3-13.1. Greenhouse Gases....................................................................................................... 3-1

3.1.1. Background ................................................................................................... 3-1 3.1.2. Methods......................................................................................................... 3-2 3.1.3. Results........................................................................................................... 3-4

3.2. Criteria Pollutant Emissions from Airport-Related Ground Transportation................... 3-6 3.2.1. Background ................................................................................................... 3-6 3.2.2. Methods......................................................................................................... 3-7

Table of Contents

ii San Diego International Airport Expansion: Sustainability Analysis

3.2.3. Results and Discussion................................................................................. 3-9

4. Sustainability and Green Airport and Green Building Opportunities for SDIA Expansion 4-1

4.1. Why Sustainability?....................................................................................................... 4-1 4.1.1. Local to Global Context ................................................................................. 4-2 4.1.2. Opportunities for Sustainability ..................................................................... 4-3

4.2. Green Airport Concept and Framework........................................................................ 4-5 4.3. Green Buildings and the LEED System at Airports ...................................................... 4-7

4.3.1. LEED-Certified and LEED-Registered Projects Related to Airports and Transit Centers.......................................................................................................... 4-8

4.4. Sustainability Opportunities for SDIA Expansion Alternatives...................................... 4-8 4.4.1. Scenario 2 (No Project Alternative @ 2030) ................................................. 4-9 4.4.2. Scenario 3 (DEIR Preferred Alternative) ....................................................... 4-9 4.4.3. Scenario 4 (Lindbergh ITC)......................................................................... 4-10

5. Summary and Discussion 5-1

6. References 6-1

Table of Contents

San Diego International Airport Expansion: Sustainability Analysis iii

Tables

Table 2-1. Level-of-Service (LOS) Descriptions........................................................................... 2-5 Table 2-2a. Transit Mode Shares by Scenario (Conservative Assumptions)............................. 2-17 Table 2-2b.Transit Mode Shares by Scenario (Optimistic Assumptions)…………… ………….2-18 Table 2-3. Transit Mode Share for Commuting in Major U.S. Cities (U.S. Census Data, 2000)..................2-23 Table 2-4a. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by Scenario - Conservative Assumptions…………………………………………………………………………….2-26 Table 2-4b. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by Scenario - Optimistic Assumptions ……………………………………………………………………………….2-26 Table 3-1.Change in Average Daily Greenhouse Gas Emissions by Scenario ........................... 3-4 Table 3-2. Current Designation for Selected Criteria Pollutants .................................................. 3-7 Table 3-3. Estimated Percent Change in Daily Criteria Pollutant Emissions from 2005 to 2030 with No Infrastructure Pollutant Changes (Scenario 1 versus Scenario 2) .................................. 3-9 Table 3-4. Estimated Percent Change in Daily Criteria Pollutant Emissions - Passenger Cars ..3-9 Table 4-1. Comparison of Sustainability Opportunities for Alternatives ....................................... 4-9 Table 5-1.Sustainability Components Summary for Scenarios 2 Through 6 ............................... 5-3

Figures

Figure 1-1: San Diego Region Transportation System................................................................. 1-2 Figure 1-2: Map of San Diego International Airport and Vicinity ................................................. 1-3 Figure 1-3: Map of Proposed Lindbergh Intermodal Transportation Center. .............................. 1-6 Figure 1-4: High Oblique Rendering of Lindbergh Intermodal Transportation Center ................ 1-7 Figure 1-5: Vertical Rendering of the Lindbergh Intermodal Transportation Center ................... 1-8 Figure 2-1: Study Area Transport Network.................................................................................. 2-2 Figure 2-2: Current Percent Airport Related Traffic by Road Segment (SDIA DEIR, 2007) ....... 2-4 Figure 2-3: Airport Related Traffic with Current LOS (SDIA DEIR, 2007)................................... 2-4 Figure 2-4: Airport Passenger Ground Transportation Mode Shares at SDIA (HNTB, 2007)..... 2-6 Figure 2-5: Ground Transportation Mode Shares for Employees at SDIA (HNTB, 2007) .......... 2-6 Figure 2-6: Entrance to Existing Old Town Transit Center.......................................................... 2-8 Figure 2-7: Tested Trolley Networks ......................................................................................... 2-14 Figure 2-8: Mode Share for Conservative Scenario .................................................................. 2-16 Figure 2-9: Mode Share for Optimistic Scenario ....................................................................... 2-16 Figure 2-10: Airport Related Traffic with Current (LOS) (SDIA DEIR,2007)……….…………….2-29 Figure 2-11: Traffic Level of Service - Preferred Alternative in 2030……………………………..2-29 Figure 2-12 Traffic Level of Service - Lindberg ITC in 2030……………………………………….2-29 Figure 3-1: Greenhouse Gas Emissions on a Per Day Basis by Scenario ................................. 3-5 Figure 4-1: Airport Sustainability and its Local to Global Context ............................................... 4-3 Figure 4-2: Relationship of Sustainable Design Value and the Cost of Impact Mitigation.......... 4-4 Figure 5-1: Additional Average Daily Vehicle Miles Traveled in 2030 Compared to the 2005 Baseline. ....................................................................................................................................... 5-4 Figure 5-2: Greenhouse Gas Emissions Percent Change from Scenario 2 (No Project @2030)5-6 Figure 5-3: Proportion of Passengers and Employees Using Transit………………………………5-6

Table of Contents

iv San Diego International Airport Expansion: Sustainability Analysis

Appendices

A. Case Studies

B. Transportation Modeling

C. Calculations of Greenhouse Gas Emissions

D. Calculations of Criteria Air Pollutants

E. LEED Background Information

F. Worldwide Airport Environmental Initiatives from the Airports Council International

Table of Contents

San Diego International Airport Expansion: Sustainability Analysis v

Abbreviations and Acronyms

ACI Airports Council International ACI-NA Airports Council International-North America ACRP Airport Cooperative Research Program CAP Clean Airport Partnership, Inc. CAIVP California Independent Voter Project CFCs Chlorofluorocarbons CI Commercial Interiors CS Core and Shell DEIR Draft Environmental Impact Report EB Existing Building EIRs Environmental Impact Reports HCFCs Hydrochlorofluorocarbons HFCs Hydrofluorocarbons HOV High-occupancy vehicle ITC Intermodal Transportation Center LAX Los Angeles International Airport LEED Leadership in Energy and Environmental LOS Level-of-service MTS Metropolitan Transit System NCTD North County Public Transit District ND Neighborhood Development OAK Oakland International Airport SANDAG San Diego Association of Governments SDCRAA San Diego County Regional Airport Authority SDIA San Diego International Airport SFO San Francisco International Airport TSA Transportation Security Administration USGBC United States Green Building Council VMT Vehicle miles traveled

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vi San Diego International Airport Expansion: Sustainability Analysis

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Executive Summary

San Diego International Airport Expansion – Sustainability Analysis

The San Diego International Airport/Lindbergh Field (SDIA) is the major commercial airport for business, personal, and cargo transportation servicing the San Diego region; therefore, SDIA is vital to prosperity and growth of the community. SDIA is the smallest major airport in the U.S. yet provided service to 17.7 million passengers in 2006. Growth in demand is expected to reach 28.2 million passengers by 2030 (SH&E 2004; SDCRAA 2007)1. The San Diego County Regional Airport Authority (SDCRAA) is in the planning process for meeting demand through an update of the Airport Master Plan. The Master Plan objectives are to:

Provide adequate facilities to accommodate air service demand through 2015 while improving airport levels of service, airport safety and security, and enhancing airport access;

Develop facilities that effectively utilize the current airport property and facilities and are compatible with surrounding land uses; and

Provide for future public transit options in airport land use planning.

SDCRAA issued a Draft Environmental Impact Report (DEIR) for public comment in October, 2007 (SDCRAA 2007) which evaluated five alternatives for airport facility expansion to accommodate air service through 2015 and provide for future public transit options in airport land use planning. The DEIR analyzed impacts through 2030 to allow comparison to regional transportation plans. The key elements of two DEIR proposed alternatives (the No Project Alternative, and the Proposed Project (Preferred Alternative)) and a third alternative (Lindbergh Intermodal Transportation Center (LTC)) independently developed by the California Independent Voter Project (CAIVP) are described below and evaluated in this study.

Master Plan DEIR No Project Alternative - The SDIA DEIR No Project Alternative proposes no new projects to improve airport infrastructure and maintains the airport facility ‘as is’ over the DEIR planning horizon of 2015 even though airport passenger traffic is expected to rise 2.8 percent per year. Under this alternative, the level of service within the airport would be expected to deteriorate and the traffic congestion around the airport would be expected to increase. The No Project Alternative serves as a baseline for comparison of the other alternatives and scenarios.

1 References are available in the main report and are not included in the Executive Summary.

San Diego International Airport Expansion - Sustainability Analysis

ES-1

Executive Summary

ES-2


Master Plan DEIR Proposed Project (Preferred Alternative) - The DEIR Preferred Alternative includes the following components:

Expand existing Terminal Two West with 10 new jet gates;

Construct new aircraft parking and replacement Remain-Over-Night aircraft parking apron;

Construct a new apron and aircraft taxi lane;

Construct a second level road/curb and vehicle circulation serving Terminal Two;

Construct a new parking structure (providing approximately 4,300 new parking spaces) and vehicle circulation serving Terminal Two;

Relocate and reconfigure SAN Park Pacific Highway parking facility providing approximately 500 additional parking spaces;

Construct a new access road from Sassafras Street/Pacific Highway intersection to provide access to the SAN Park Pacific Highway and new general aviation facilities;

Construct new general aviation facilities including access, terminal/hangers, and apron to improve Airport safety for Airport customers/users;

Demolish the existing general aviation facilities to improve airport safety and circulation airfield; and

Reconstruct Taxiway C, construct new apron hold areas, and new taxiway east of Taxiway D.

The proposed airport modifications remain completely within the existing SDIA property boundary, which consists of 661 acres and is constrained by its proximity to San Diego Bay and downtown. Traffic congestion resulting from the airport operations will be addressed partly through local road and intersection improvements but also through proposals outlined in a separate draft Airport Transit Plan.

Draft Airport Transit Plan - In cooperation with regional transportation agencies, SDCRAA has been involved in the development of an Airport Transit Plan to reduce traffic congestions in the vicinity of the airport. The draft Transit Plan aspires to increase air passenger transit ridership from 1.2 percent to 4-6 percent in the next 3-5 years based on a series of measures designed to increase public transit use. These include near-term measures (until the end of 2009) such as increased marketing efforts, free rides for arriving passengers and extending bus service to the convention center. Mid-term measures (2010 to 2011) include reducing bus service interval times to 10 minutes, adding evening and weekend Coaster trips, and providing a shuttle to the Old Town Transit Center and remote parking sites.

Executive Summary

Proposed CAIVP Lindbergh ITC - Given the significant financial investment required for SDIA expansion needs, the California Independent Voter Project (CAIVP) was concerned that implementation of SDCRAA proposed plans without a more rigorous evaluation of alternative sustainable designs might reduce future community options due to high sunk project costs. To stimulate further evaluation, CAIVP prepared a conceptual additional alternative to address airport expansion and traffic congestion, the Lindbergh Intermodal Transportation Center (Lindbergh ITC or ITC).

The proposed CAIVP Lindbergh ITC Alternative is not a “final plan” but instead an alternative vision of what might be done to improve the efficiency of SDIA for its passengers, reduce adverse consequences, and improve the quality of life for the community. The concept includes moving the existing terminals to the opposite (north) side of the runway adjacent to Pacific Highway and developing an intermodal transit facility (Figures ES-1 and ES-2). The ITC would be a five-story parking facility that would consolidate all parking, rental cars, and public transit access into one enclosed facility with direct access to the newly located terminals. More specifically, it would include the following:

Long-term parking for more than 20,000 vehicles and short-term parking for 2,000 vehicles;

Room for on-site car rental agencies and their vehicles;

Bi-level drop-off and pick-up roads for plane, train, bus and trolley passengers;

Direct access from the Lindbergh ITC to airport terminals via sky bridges that would include moving sidewalks;

Provide new off ramps and on ramps directly to Interstate 5 and Pacific Highway for vehicular access to and from the new terminal location;

Room for a downtown people mover and a high-speed rail between airports;

Trolley stops where one can catch the Orange, Blue, Green and special event lines;

An Amtrak Pacific Surfline stop (serving San Luis Obispo, Santa Maria, Santa Barbara, Ventura, Oxnard, Camarillo, Simi Valley, Van Nuys, Los Angeles, Santa Ana, and points in-between; and

A Coaster stop bringing people in from Oceanside, Carlsbad, Encinitas, Solana Beach and Sorrento Valley.


ES-3

Executive Summary

The Lindbergh ITC would require an additional 90 acres of land adjacent to the airport on the north side bounded by Pacific Highway, Interstate 5, Washington Street, and Laurel Street. Approximately half of this land is presently owned by public agencies and much of the remainder is currently used for airport parking and rental cars. Additionally, the ITC would require a 27-acre strip of land owned by the Marine Corps Recruit Depot to allow taxiway C to be extended to the end of the runway.

Figure ES-1. Map of Proposed Lindbergh Intermodal Transportation Center.

CAIVP believes the Lindbergh ITC would provide the following benefits:

Provide airport passengers and workers more efficient and environmentally friendly alternatives to reach the airport;

Reduce automobile congestion in the vicinity of the airport;

Encourage the use of transit;

Provide SDIA an opportunity to reduce its carbon and environmental footprint; and

Improve the quality of life and traffic congestion along the waterfront.

Study Approach and Objectives - CAIVP requested Malcolm Pirnie and Sinclair Knight Merz (SKM) prepare an independent analysis of selected expansion alternatives developed in support of the SDCRAA Airport Master Plan and the Airport Transit Plan along with a third alternative, the Lindbergh ITC. This report provides an independent and objective analysis of key sustainability components of the SDIA expansion.

ES-4


Executive Summary

Figure ES-2. High Oblique Rendering of Lindbergh Intermodal Transportation Center.

Figure ES-2. The ITC is in light blue and is located at the right. The turquoise blue color is the short-term parking area. The drop-off and pickup areas are in red and green. The existing airport terminals occur to the left of the runway in this rendering. Source: California Independent Voter Project.

The major sustainability components evaluated in this report include:

The ability to increase public transit ridership (mode share);

Changes in daily vehicle miles traveled (VMT) by airport passengers and workers commuting to and from the airport;

Changes in road traffic congestion on the streets around the SDIA;

Impact of passenger and airport worker travel changes on greenhouse gas emissions;

Impact of passenger and airport worker travel changes on air quality; and

Lessons learned from a qualitative review of the experience at other international airports to implement “green airport” practices into a modified airport infrastructure.

Other positive sustainability components result from the above and these are also identified.

Transportation Modeling and Analyses - To compare the basic metrics or differences in the impacts of the three expansion alternatives, we conducted quantitative transportation modeling. The model examines transit choices of travelers to the airport and from SDIA,


ES-5

Executive Summary

ES-6


in turn, the traffic congestion that these choices would generate. This model predicts travelers mode choices based on the travel times, costs and other factors that are important in a traveler’s decision-making process. Based on these choices, the model calculated values for average daily vehicle miles traveled (VMT) by airport passengers and workers traveling to and from the airport. In addition, the transport mode choice model predicts the traffic level of service (LOS), which is an indicator of how well traffic flows on individual city streets based on the cumulative use by airport passengers and workers, as well as other users of the transportation system. LOS predictions range from LOS A (free-flowing traffic) to LOS F (major traffic disruption with long lines of stopped traffic). LOS E and F are typically considered unacceptable for efficient roadway operation.

Modeled Scenarios - To understand the impacts of the expansion alternatives and their sensitivity to possible variations, several current and future transport scenarios were developed. These modeled scenarios evaluate the effect of varied travel times, costs and other factors on a traveler’s transportation decisions.

• Scenario 1 (2005 Baseline) – Modeled existing conditions in 2005 based on infrastructure as it exists presently.

• Scenario 2 (No Project Alternative @ 2030) – Same as the DEIR No Project Alternative at 2030. Predicted traffic based on no changes in infrastructure or in the Airport Transit Plan. Scenario 2 differs from Scenario 1 based on increases in demand and how increased congestion may influence passenger and airport worker choices without any changes in transportation infrastructure or incentive programs.

• Scenario 3 (Preferred Alternative) – This scenario included recommendations from the DEIR Master Plan Preferred Alternative at 2030 but does not include the traffic mitigation measures or draft Airport Transit Plan.

• Scenario 4 (Preferred Alternative with Airport Transit Plan) – Same as Scenario 3 except with an Old Town shuttle bus service, free Flyer fares, reduced Flyer headways from 12 to 10 minutes, evening and weekend Coaster rail service and FlyAway sites at Escondido Transit Center, I-15/SR52 and I-805/SR54 junctions. These measures are part of the draft Airport Transit Plan.

• Scenario 5 (Lindbergh ITC) – Predicted traffic in 2030 based on the Lindbergh ITC with the removal of the 992 Flyer route, extension of the Trolley Green line south from Old Town Transit Center to the ITC, extension of the Orange line north to the ITC and transit improvements from Scenario 4 (except for Old Town shuttle).

Executive Summary

Predicted Transit Mode Share and Daily Average Vehicle Miles Traveled (VMT) – Based on our quantitative transportation modeling, the only scenario that both increased public transit ridership (Figure ES-3) and substantially reduced the increase in daily VMT (Table ES-1) was the Lindbergh ITC (Scenario 5). Figure ES-3 (for conservative assumptions) shows that the Lindbergh ITC increased transit ridership by 1.4 percent more than Scenario 4 (Preferred Alternative with Airport Transit Plan). More than 48 percent of the transit ridership for the ITC is on the Trolley system which reduces traffic on the streets around the airport while Scenario 4 (Preferred Alternative with Airport Transit Plan) has 54 percent of transit ridership on the bus.

Table ES-1 shows the daily average VMT among the five scenarios with conservative assumptions. Table ES-1 also shows the differences in both miles and percent for the scenarios in comparison to the 2005 Baseline, the No Project Alternative at 2030, and the Preferred Alternative (also for conservative assumptions). These values reflect the effect of travel times, costs and other factors on a traveler’s transportation decision. The DEIR No Project Alternative at 2030 (Scenario 2) indicates increased demand for air travel would result in an additional 685,000 average daily miles driven to or from SDIA per day (or 250 million VMT annually). This represents a 57 percent increase in daily average VMT traveled by airport passengers and workers over the 2005 Baseline. The Preferred Alternative at 2030 with Airport Transit Plan (Scenario 4) was 1.6 percent less than a no project alternative in that daily average VMT were reduced by only 30,000 miles per day compared to the No Project Alternative at 2030 (Scenario 2).

The Lindbergh ITC scenario reduced daily average VMT by 169,000 miles per day or 9.0 percent and 139,000 miles per day or 7.5 percent compared to the No Project Alternative at 2030. (Scenario 2) and the Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4), respectively. This represents a savings in annual VMT for the ITC.

Figure ES-3. Proportion of Passengers and Employees Using Different Modes of Public Transit (Conservative Assumptions)

00.5

11.5

22.5

33.5

44.5

Scenario 1 (2005Baseline)

Scenario 2 (NoProject @ 2030)

Scenario 3(Preferred

Alternative)


Alternative wAirport Transit

Plan)

Scenario 5(Lindbergh ITC)

Per

cent

FlyAwayCoasterTrolleyBus

1.2 1.3 1.3

2.6

4.0


ES-7

Executive Summary

ES-8


Table ES-1. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by Scenario (Conservative Assumptions)

Daily Ave. VMT

Change from 2005 Baseline

Daily Ave. VMT

Change from No Project @ 2 030 and PreferredAlter 030 native @ 2

Daily Ave. VMT Change from

Preferred Alternative with

Air an port Transit Pl@ 2030

Scenario Modeled

Daily Ave.

VMT

Miles

Perce

nt

Miles

Percent

Miles

Percent

1

2005 Baseline

1,204,040

---

---

---

---

---

---

2

No Project Alter@ 2030

native +685,463 +56.9

1,889,503

---

---

---

---

3

Preferred Alternative @2030

1,889,503

+685,463

+56.9

--- ---

---

---

4

Preferred Alternative with Airport Transit Plan

2030

-30,357 -1.6

@

1,859,146

+655,106

+54.4

---

---

5 1,720,364 +516,324 +42.9 -169,139 -9.0 -138,782 -7.5

Lindbergh ITC @ 2030

ompared to the No Project Alternative and Preferred Alternative with Airport Transit Plan of 61.7 million and 50.6 million miles, respectively. These reduced values reflect

he

f SDIA was also evaluated. Airport related traffic is currently a substantial percentage of the total traffic

demand for airport travel results in approximately 685,000 additional average daily VMT (equivalent to 250 million miles per year) from airport

d

c

the increase in transit use and the reduction of trip length by providing direct access to tairport terminal from I-5. However, even with alternative transportation choices available associated with the Lindbergh ITC scenario, average daily VMT was projected to increase by 516,000 miles (43 percent) over the 2005 Baseline.

The impact of changes in VMT on traffic congestion in the vicinity o

on downtown streets – ranging from 40 percent to 76 percent of total traffic on Grape Street, Hawthorn Street and Laurel Street (Figure ES-4). Presently, traffic on many streets in the vicinity of the airport currently operates at and beyond desirable levels ofservice (Figure ES-5).

The projected increase in

related ground transportation. Both the No Project Alternative at 2030 (Scenario 2) anthe Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4; Figure ES-6),

Executive Summary

would result in significant additional traffic congestion and further decline in the level ofservice on many streets in the vicinity of the airport. In contrast, the increased public transit use, reduced VMT, and placement of the airline terminals close to I-5 result in substantially reduced traffic volume and traffic congestion (i.e., increased levels of service) in the vicinity of SDIA as a result of the Lindbergh ITC (Figure ES-7). This improvement occurs despite the projected increase of 169,000 average daily VMT. most significant effect is due to re-routing traffic away from streets such as RosecransLaurel, and Hawthorn Streets with the ITC. LOS on these streets would improve to acceptable levels as a result of the ITC. Improvements are also seen on India, Kettner, Grape, Washington, and Hancock Streets.

Under Scenario 3 (Preferred Alternative) pot

The ,

ential mitigation to improve LOS on these streets (Figure ES-6) to acceptable levels (LOS D) is identified. These mitigation

es

sses ouse

measures include road widening, removing on street parking, increasing the number of lanes on these streets and intersection improvements. If implemented such measurcould improve the LOS but they do not improve VMT and thus maintain the traffic increase on streets adjacent to the airport making access for residents and local businemore difficult. The measures do not reduce local criteria pollutants or overall greenhgases (see below).


ES-9

Executive Summary

Figure ES-4. Percent airport related traffic by road segment in the vicinity of SDIA for 2005.

ES-10


Executive Summary

Figure ES-5. Traffic Level of Service for surface streets in the vicinity of SDIA for Scenario 1 – 2005 Baseline.

Figure ES-6. Traffic Level of Service for surface streets in the vicinity of SDIA for Scenario 3 – Preferred Alternative in 2030.

Figure ES-7. Traffic Level for surface streets in the vicinity of SDIA for Scenario 4 – Lindberg ITC in 2030.


ES-11

Executive Summary

ES-12


Estimation of Greenhouse Gas and Criteria Pollutant Emissions - Greenhouse gas emissions from gasoline-powered cars and vans and compressed natural gas buses used to transport passengers to and from SDIA are calculated for the modeled transport scenarios (Table ES-2). Similar to the VMT and LOS data, these results reflect the effect of travel times, costs and other factors on a traveler’s transportation decision. The greenhouse gas emissions are calculated as carbon dioxide equivalent (CO2e) reflecting the combined effect of CO2, CH4 (methane) and N2O (nitrous oxide) from vehicle emissions. The values are reported in the standard format of metric tons CO2e. The calculations also reflect a mix of more fuel efficient vehicles that will result from the new Corporate Average Fleet Economy (CAFE) standards passed by Congress and signed by the President in December 2007. The new CAFE standard requires new automobiles to achieve 35 miles per gallon vehicle average by 2020.

Table ES-2. Change in Average Daily Greenhouse Gas Emissions on a Per Day Basis by Scenario


Change from No

Project @ 2030 and Preferred

Alternative @ 2030

Change from Preferred

Alternative with Airport Transit Plan

@ 2030

Scenario Modeled

Daily Metric Tons CO2e

Metric Tons

Percent

Metric Tons

Percent

Metric Tons

Percent

1

2005 Baseline

479

---

---

---

---

---

---

2

No Project Alternative @ 2030

587

+108

+22.5

---

---

---

---

3

Preferred Alternative @ 2030

587

+108

+22.5

0

0

---

---

4

Preferred Alternative with Airport Transit Plan @ 2030

582

+103

+21.5

-5

-0.9

---

---

5


533

+54

+11.3

-54

-9.2

-49

-8.4

Executive Summary

The results show that the Lindbergh ITC provided the most benefits for reducing the rate of growth in greenhouse gas emissions. The daily average CO2e emissions from passenger vehicle travel to and from SDIA would increase by approximately 23 percent (108 metric tons per day, which is equivalent to 39,420 metric tons per year), under the No Project Alternative at 2030 (Table ES-2). The Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4) would result in approximately 103 metric tons of daily CO2e emissions above the 2005 Baseline. This represents a less than one percent (5 metric tons per day) reduction below the No Project Alternative at 2030 (Scenario 2; Table ES-2).

In contrast, the increased use of pubic transportation and reduced traffic through downtown and along Harbor Drive associated with the Lindbergh ITC (Scenario 3) would result in greenhouse gas emissions of 533 metric tons CO2e by 2030. This represents a 11.3 percent increase from the 2005 Baseline; however, this increase is 54 percent lower than the increase projected for the No Project Alternative at 2030 (Table ES-2). None of the Scenarios (3, 4, or 5) would reduce greenhouse gas emissions to the 2005 baseline or to the California Air Resources Board’s goal of 1990 levels. However, the estimated 8 percent reduction of greenhouse gas emissions in the Lindbergh ITC Scenario 5 could form an important component of an overall plan to decrease greenhouse gas emissions associated with the SDIA.

Ambient air quality standards are implemented to protect human health and the environment from the harmful impacts of air pollution. The standards apply to a subset of possible air contaminant called ‘criteria pollutants’. Criteria pollutants include: carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (less than 10 microns and less than 2.5 microns), and lead (Pb) among other state- listed pollutants. The screening-level evaluation estimated that some criteria pollutants from airport-related ground transportation can be expected to decrease by 2030 (CO = -56%, NOx = -65%, and ROG = -44%) under the No Project Alternative (Scenario 2). These values decline because of federal and state emission requirements. Other criteria pollutants would increase (SOx = +56%, PM10 = +79%, and PM2.5 = +91%) under the No Project Alternative. The Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4) resulted in less than a two percent reduction of criteria pollutants while the Lindbergh ITC Scenario resulted in an estimated 9.7 percent reduction in criteria pollutant emissions from the No Project Alternative at 2030 (Scenario 2). The transit analysis indicates the VMT reductions (and, therefore, associated emissions) would decrease most significantly in the residential neighborhoods and surface streets near the airport. From a qualitative perspective, the distribution of reduced VMTs suggests that residential exposure to air contaminants would also decrease in areas where VMTs are


ES-13

Executive Summary

ES-14


reduced. Overall, the Lindbergh ITC would be expected to provide a greater reduction in criteria pollutants than the Master/Transit Plan and no project scenarios.

Green Airport and Green Building Opportunities – The analysis presented in previous sections compared the No Project, the DEIR Preferred Project Alternative (both with and without the Transit Plan), and the Lindbergh ITC relative to sustainability criteria for public transit (mode share), average daily VMT, traffic congestion on streets around SDIA, and both greenhouse gas and air emissions by air passengers and airport workers traveling to and from SDIA. The other sustainability criteria evaluated in this report was a qualitative review of green airport practices being implemented by U.S. and international airports in order to compare opportunities for incorporating lessons learned under the various expansion scenarios evaluated in this report. Broad concepts and conclusions are summarized here while specific lessons learned are identified and discussed in the report.

The opportunities to deliver sustainability are greatest at the outset of a project (i.e. during the concept stage) and progressively declines through the following stages of feasibility, detailed design, procurement, construction, and operation. The No Project Alternative provides the least change in the physical facilities and, therefore, sustainability improvements are largely based on operational changes. The Preferred Alternative provides some new terminal space while maintaining most of the rest of the existing facilities. In contrast, the Lindbergh ITC proposal is essentially the development of a new airport terminal and consequently it provides the maximum ability to incorporate the newest efficiencies and most effective sustainable design concepts ranging from access to the airport, green design for built infrastructure, and improvements in the integrated processes of airport operation. It should be noted however, one-time emissions associated with new construction, which can offset operational gains, were not evaluated. It would be expected that one-time emissions would be highest under the ITC Scenario and lowest under the No Project Alternative. but would increase as the amount of new construction increased.

The most direct potential for green airport concepts is within the physical component of the airport (green buildings). Buildings account for a substantial percentage of overall resource use. Consequently, designing and constructing new buildings to the most up-to-date standards would substantially reduce the airport’s overall environmental footprint. Sustainable design can be applied to the physical building in addition to the specific processes occurring in the airport concerning energy, waste production, and water.

Energy use, which depletes natural resources and contributes to greenhouse gas emissions, is one of the first targets of efficient building design. Conserving energy used for heating, air-conditioning and lighting could be accomplished at the Lindbergh ITC using intelligent sensors and designs that use passive solar energy to heat and cool. The

Executive Summary

Vancouver Airport in Canada uses solar panels to heat hot water and the Chicago and San Francisco Airports produce electricity from solar energy. La Palma Airport in Spain generates the majority of electricity it uses from wind power generators. Green roofs can help to offset carbon emissions from other energy sources.

The circulation of resources and waste could also be implemented to reduce the airport’s overall ecological footprint. For example, certain waste streams could be separated and potentially re-used. Los Angeles International Airport has implemented an anaerobic digester to turn 8,000 tons of food waste produced each year into methane gas which can be used for on-site electricity. Hong Kong International Airport uses its food waste as fertilizer for landscaping. Other materials that are now recycled or re-used at other airports around the world include de-icing fluid, waste oil, excavated soil, airline pillows, coffee grounds, runway concrete, demolition debris, cut grass, food grease, and large batteries. Water can also be re-used and recycled. The Canberra Airport in Australia implemented an Aquacell Water System to recycle 26,400 gallons of water across the airport daily. Treated sewerage can re-routed and used for irrigation as is done at the Athens International Airport. The Auckland International Airport in New Zealand collects and passively treats its stormwater before discharging it into the bay.

The Lindbergh ITC concept provides the opportunity to obtain other unknown but potentially significant operational efficiencies in the re-designed airport. Instituting a ground-level up integrated system that enhances operational efficiencies through infrastructure, siting/location, staff allocation, and communication systems has the potential for other non-obvious synergistic improvements. From baggage transport/loading to security checkpoints, building from the ground up allows for complete restructuring to improve efficiency and sustainability of the new facility.

In addition to tangible reductions in energy use, water consumption, carbon emissions and waste generation, there are many social benefits to be recognized as a result of a comprehensive sustainable airport design. Societal pressure to reduce greenhouse gas emissions will almost certainly increase in the near future due to state, national and international pressures. Although public transit use in the California and the City of San Diego is much lower compared to the eastern U.S. and Europe, it will remain an important part of the tool box that society uses to reduce traffic congestion and greenhouse gas emissions in the future. The consolidation of transit types at the Lindbergh ITC would enhance the effectiveness of any future public transit expansions in the area and would also enhance their ridership by improving public perception of public transportation.

The combined effects of the increased public transit use and the ability to enhance future public transit expansions will also have positive benefits for redevelopment along the waterfront south of the SDIA. The overall improvements in traffic and access to


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Executive Summary

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integrated public transit would extend to this area and enhance the over quality of experience for visitors and residents.

The modeled increase in public transit ridership to the airport, coupled with the synergistic increase in overall public transit effectiveness provided by the ITC, would provide airport employees, particularly lower income employees, with more attractive transit access to the airport. Consequently, the social equity component of sustainability would be increased.

The extent of the infrastructure change (buildings, operations, transportation) influences the opportunity for environmental and social benefits. The Lindbergh ITC features both a replacement of existing infrastructure and a vast expansion of the system transportation design that maximizes opportunities and benefits. Although cost was not considered in this analysis, it is clear that the potential environmental and social benefits could be significantly enhanced by expanding the proposed design beyond the boundaries of the current infrastructure and addressing the entire airport system as a more comprehensive, interactive unit. Therefore, the feasibility of more expansive designs like the Lindbergh ITC should be considered as candidates for a full cost-benefit analysis.

Discussion

SDIA expansion and implementation of a new Airport Transit Plan are being proposed at a time when San Diegan’s are demanding greater environmental stewardship, including a more sustainable and carbon-neutral natural and built environment, as well as lifestyle. Examples of these mandates include: San Diego’s Sustainable Community Program; California AB 32 Global Warming Solutions Act; California AB 1493, a proposed state regulation contested by the U.S. Environmental Protection Agency and not implemented; and the international Bali Pact addressing global greenhouse gas emissions. AB 32 requires a reduction in California greenhouse gas emissions to 1990 levels by 2020 (an estimated 25 percent reduction). AB 32 mandatory greenhouse gas caps will begin in 2012 and the California Energy Commission and Air Resources Board are currently developing and releasing specific regulations. In addition, the Governor’s Executive Order S-3-05 mandates a reduction of greenhouse gas emissions to 80 percent below 1990 levels by 2050. At present these regulations do not address transportation. However, since passage of AB 32, the California Attorney General has been proactively engaging various levels of local government seeking the means to address greenhouse issues that are not now directly included by expected regulation

Transportation makes up a significant and growing component of greenhouse gas emissions, including 31.5 percent of the 2001 CO2 emissions in the U.S. (WRI, 2008). Transportation was the fastest growing source of greenhouse gas emissions between 1990 and 2002 with emissions of CO2 increasing by 24 percent over this period (WRI, 2005). Increasing demand associated with travel is forecast to exceed benefits accruing from

Executive Summary

improved vehicle efficiency such that by 2020 transportation emissions in North America are forecast to be 30 percent above 2002 levels (WRI, 2005). Forecasts suggest that air travel will grow by 60 percent between 2000 and 2025, well above projected increases in aircraft fuel efficiency (which have increased approximately one percent per year over the past ten years (FAA, 2005)).

The City of San Diego reported a 36 percent increase in average weekday VMT from 1990 to 2004 for the community (City of San Diego, No Date) which resulted in an average of 38.4 million miles per weekday. VMT to and from SDIA from our study was estimated to be 1.2 million miles per day in 2005 (approximately 3 percent of total miles not accounting for differences between weekday and daily averages and years). Although the SDIA ground transportation may be a small component of the total community transportation, the projected increase in SDIA related transportation demand and its proximity to downtown is expected to contribute to further deterioration of traffic congestion in the vicinity of the airport under the No Project and Preferred Alternatives. In contrast, the Lindbergh ITC appears to have the potential to result in significant reductions in traffic congestion around the airport.

A number of policy, marketing, and incentive-based programs from the Airport Transit Plan were not included in our analysis of the Preferred Alternative with Airport Transit Plan. Such policy, marketing, and incentive-based programs are expected to be at least as, but probably more, effective in the Lindbergh ITC Scenario than under the Preferred Alternative because more options and choices would exist with an integrated transportation system. This may be an added benefit to the ITC approach because any additional improvements would be on top of the reductions in congestion indicated under Scenario 5.

Modeling results predict airport passengers place a heavy priority on time compared to other parameters impacting their choice of transit mode. This reduces their sensitivity to standard incentive programs. The modeling results from our study suggested that the mode shares indicated in the Transit Plan will only be in the range of 2.6-3.0 percent without additional incentives or influences (whether intentional or from external influences outside the control of the SDCRAA). For example, our results predicted a mode share for the Old Town Shuttle Bus Service and the Coaster Service were approximately 20-30 percent of the mode shares anticipated by the Transit Plan and that modeled increases in mode share were predominantly in bus use. Together, our results indicate that the Draft Airport Transit Plan will not be adequate to mitigate increased traffic and congestion under the No Project and Preferred Alternatives.

The City of San Diego has developed a greenhouse gas inventory for 1990 and 2004 (City of San Diego, No Date). The transportation sector in San Diego was reported to contribute 7,864,800 greenhouse gas tons per year (approximately 21,547 greenhouse tons per day) in 2004. This represented 52 percent of the community’s total greenhouse


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Executive Summary

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gas emissions. Both past (1990 to 2004) and predicted (2005 to 2030) data indicates that the increase in fuel economy in vehicles has not and will not be adequate to keep up with the greenhouse gas emissions from increased VMT unless new policies, transportation alternatives, or behaviors are developed. Absent such dramatic change, the Lindbergh ITC provided the most benefits of the scenarios evaluated. However, the ITC was insufficient by itself to make sufficient reductions in VMT to reach even short-term goals for greenhouse gas reductions if goals were uniformly applied across each segment of society. However, the estimated 8 percent reduction of greenhouse gas emissions in the Lindbergh ITC Scenario 5 could form an important component of an overall plan to decrease greenhouse gas emissions associated with the SDIA.

This study is not a comprehensive evaluation of the sustainability of airport expansion alternatives. We have limited our analysis to the ability to increase public transit ridership, changes in VMT and LOS, greenhouse gas emissions, criteria pollutants, green airport and green building opportunities and other sustainability components which result from the above. The consideration of additional sustainability criteria and how they may influence airport expansion decisions is warranted given the significant capital costs for the project.

As stated previously, SDCRAA identified the following three objectives for the Master Plan:

Provide adequate facilities to accommodate air service demand through 2015 while improving airport levels of service, airport safety and security, and enhancing airport access;

Develop facilities that effectively utilize the current airport property and facilities and are compatible with surrounding land uses; and


Our analysis indicates that the Lindbergh ITC scenario meets the first and third SDCRAA objectives better than the Preferred Alternative with Airport Transit Plan (Scenario 4). The Lindbergh ITC provides opportunities to improve airport efficiencies, levels of service, and access and provides substantially more effective options for enhanced future public transit and land use planning. In addition, the Preferred Alternative with Airport Transit Plan (Scenario 4) may limit future public transit options because high capital costs for Terminal Two expansion and parking may preclude other options not rigorously investigated given the constraints associated with the second objective. The Lindbergh ITC is also generally compatible with adjacent land uses buy by design it does not stay within the existing airport property boundary. Staying within the existing airport boundary, however, is more a DEIR analysis constraint than an objective.

Executive Summary

The CAIVP identified the following potential benefits of the Lindbergh ITC scenario:



Encourage the use of transit;



Our analysis indicates that the Lindbergh ITC scenario fulfills the potential benefits that CAIVP identified. The transportation analysis shows that traveler public transit decisions and mode choices would be positively influenced by the ITC. These traveler decisions would result in reduced VMT, reduced congestion on in the vicinity of the airport and downtown and would also reduce transportation related greenhouse gases and criteria pollutants. The ITC improves public transit use and also enhances the effectiveness of any future public transit expansions in the area. Consequently, the Lindbergh ITC would also improve the opportunity to enhance the quality of life along the waterfront. The demonstrated improvements to traffic, greenhouse gases, criteria pollutants, and other sustainability components, coupled with the fact that the Lindbergh ITC meets the SDCRAA objectives better than the Preferred Alternative indicates that the Lindbergh ITC merits further detailed public discussion.


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Executive Summary

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San Diego International Airport Expansion: Sustainability Analysis 1-1

Intermodal refers to transportation system connecting or including different types or modes of transport. The Lindbergh ITC would link short-term parking, rental cars, and bi-level drop-off and pick-up roads

1. Introduction

This report analyzes several specific sustainability components related to the expansion of the San Diego International Airport/Lindbergh Field (SDIA), including the Lindbergh Intermodal Transportation Center (Lindbergh ITC or ITC) which has been independently proposed by the California Independent Voter Project (CAIVP). The main purpose for conducting this analysis is to provide the public, elected officials, and the San Diego County Regional Airport Authority (SDCRAA) with a broader understanding of the sustainability of the proposed airport expansion plan and how that may compare to an integrated approach to address customer demand, traffic congestion in the vicinity of the airport, emissions of greenhouse gases and other air toxics, and other aspects related to improving the sustainability of the greater San Diego community. This sustainability analysis compares their proposed Lindbergh ITC , the SDIA DEIR No Project Alternative and the DEIR Preferred Alternative. This chapter provides some background information for the SDIA, describes the expansion alternatives, and lastly describes the report objectives and contents.

1.1. Background The City of San Diego and surrounding communities are serviced by one major airport, SDIA, for commercial passenger and cargo traffic. Constrained by San Diego Bay and its proximity to downtown San Diego, it is the smallest major airport in the U.S. with only 661 acres of land and a single east-west runway. The airport, operated by the SDCRAA, served 17.7 million passengers in 2004. Passenger demand is expected to rise to 28.2 million by 2030 along with increases in cargo, general aviation, and military use (SH&E 2004; SDCRAA DEIR 2007). However, existing terminal facilities and the presence of a single runway presents logistical problems for SDIA to satisfy its direct clients (the airlines and cargo carriers) and their clients.

SDIA is a vital regional hub for business, personal and cargo transportation in the City of San Diego, San Diego County and southernmost “to” the airportCalifornia (Figure 1-1 and Figure 1-2). It generates approximately 26,000 person-trips on a typical weekday (or an assumed 52,000 trips to and from the airport). The airport is located within the City of San Diego adjacent to San Diego Bay with Pacific Highway and I-5 to the east. SDIA has two main passenger terminals, a commuter terminal, general aviation facilities, air cargo facilities, aviation support facilities as well as airport rescue and fire fighting facilities. Vehicular access to the airport is via surface streets through downtown or via Rosecrans Street on the west.

Chapter 1 Introduction

1-2 San Diego International Airport Expansion: Sustainability Analysis

As required by state law, SDCRAA conducted a county-wide survey of potential alternative airport sites from 2003 through 2006. They placed a measure on the 2006 ballot to share Marine Corps Air Station Miramar. That ballot measure did not pass, and the current SDIA will be the regional airport for the foreseeable future.

Figure 1-1: San Diego Region Transportation System.

Chapter 1

Introduction


Figure 1-2: Map of San Diego International Airport and Vicinity

1.2. Expansion Alternatives The SDCRAA is in the planning process for implementing their Airport Master Plan (www.san.org/airport_authority/airport master_plan/index.asp) and issued a Draft Environmental Impact Report (DEIR) for public comment in October 2007. The DEIR evaluates several alternatives for expanding SDIA within its existing boundaries. SDCRAA has also prepared a draft Airport Transit Plan with staff from all the regional transportation agencies (http://www.sdcraa.com/airport_authority/ airport_master_plan/transit_plan.asp) . This transit plan recommendation includes short-term (1 to 3 years), mid-term (3 to 5 years) and long-term (greater than 5 year) improvements. The plan’s target is to increase air passenger transit ridership from 1.2 percent to between 4 and 6 over the next three to five years.



The Master Plan objectives are to:

Provide adequate facilities to accommodate air service demand through 2015 while improving airport levels of services, airport safety and security and enhancing airport access;

Develop facilities that efficiently utilize the current airport property and facilities and that are compatible with adjacent land uses; and


The DEIR indicates that growth in passengers in 2004, 2005 and 2006 exceeded the projected amounts. Overall airport passengers are expected to increase by 2.8 percent each year for 2005 to 2015. The DEIR points out that the single runway constrains the maximum amount of take-offs and landings. Consequently, increasing the capacity efficiency of other airport components or having more terminal gates does not improve the airport’s ability to accept more arriving flights (i.e., its practical capacity). The projected demand increase for use of and access to the airport will continue despite constraints on practical capacity.

The Master Plan DEIR evaluated five approaches to modify airport facilities to accommodate increases in projected demand, ranging from a No Project Alternative, the Preferred Alternative (Proposed Project with Parking Structure), the Proposed Project without the Parking Structure, and an East Terminal with and without a Parking Structure. Although the 2007 draft plan represents the latest thinking by the SDCRAA for meeting the needs for airport services for San Diego and the surrounding communities through 2015, this is not a new subject for the community. The ability of SDIA to meet the needs of the community given its constraints and projected demand has been the subject of an on-going discussion for many decades.

1.2.1. DEIR No Project Alternative The No Project Alternative under the Master Plan DEIR proposed no new projects to improve the airport. Consequently the existing facilities at the airport would remain the same despite the increased demand. The airport would not be able to maintain adequate in-airport levels of service to airline passengers and airlines as the anticipated increase in demand occurred. As disclosed in the DEIR, ground loading of passengers would be required and terminal crowding and wait times would increase. No improvements to transportation avenues are proposed under the no project alternative; therefore, traffic congestion on all roadways leading to the airport would progressively increase. The DEIR analysis of direct airport greenhouse gas emissions indicates that they would increase by 41 percent from 2010 to 2030. Some criteria pollutants would exceed thresholds in 2030.

Chapter 1

Introduction


1.2.2. DEIR Preferred Alternative (Proposed Project with Parking Structure)

This DEIR Preferred Alternative includes the following components:

Expand existing Terminal Two West with 10 new jet gates;

Construct new aircraft parking and replacement Remain-Over-Night aircraft parking apron;

Construct a new apron and aircraft taxi lane;

Construct a second level road/curb and vehicle circulation serving Terminal Two;

Construct a new parking structure (providing approximately 4,300 new parking spaces) and vehicle circulation serving Terminal Two;

Relocate and reconfigure SAN Park Pacific Highway parking facility providing approximately 500 additional parking spaces;

Construct a new access road from Sassafras Street/Pacific Highway intersection to provide access to the SAN Park Pacific Highway and new general aviation facilities;

Construct new general aviation facilities including access, terminal/hangers, and apron to improve Airport safety for Airport customers/users;

Demolish the existing general aviation facilities to improve airport safety and circulation airfield; and

Reconstruct Taxiway C, construct new apron hold areas, and new taxiway east of Taxiway D.

The proposed airport modifications remain completely within the existing SDIA property boundary.

The DEIR Preferred Alternative accommodates forecast growth in on-airport use through 2015 and improves the in-airport level of service. Customer access would still be via I-5 via surface streets to Harbor Drive either from downtown San Diego or via Rosecrans Street. As noted by the DEIR, the increase in traffic congestion over the planning horizon is projected to be minimized by implementation of Airport Transit Plan measures. These measures have an aspirational goal of increasing transit use from the current 1.5 percent to 4-6 percent within 5 years. The DEIR analysis of direct airport greenhouse gas emissions would increase by 39 percent from 2010 to 2030. Similarly, some criteria pollutants exceed thresholds by 2030.

1.2.3. Proposed Lindbergh Intermodal Transportation Center Given the high costs of airport expansion and the increased public awareness and regulatory requirements to address the sustainability of new projects, including their potential impacts on climate change, the California Independent Voter Project (CAIVP) requested that Malcolm Pirnie and Sinclair Knight Merz (Pirnie/SKM) analyze selected



sustainability aspects of both the No Project and the Preferred Alternatives of the DEIR along with an alternative proposal prepared by the CAIVP. The CAIVP proposal is a quite different vision for the SDIA (Figures 1-3, 1-4, and 1-5). This vision includes a relocation of the airport terminals and their integration with a regional transportation hub called the Lindbergh Intermodal Transportation Center (Lindbergh ITC or ITC).

Figure 1-3: Map of Proposed Lindbergh Intermodal Transportation Center.

.

Chapter 1

Introduction


Figure 1-4: High Oblique Rendering of Lindbergh Intermodal Transportation Center.

The ITC is in light blue and is located at the right. The turquoise blue color is the short-term parking area. The drop-off and pickup areas are in red and green. The existing airport terminals occur to the left of the runway in this rendering. Source: California Independent Voter Project.



Figure 1-5: Vertical Rendering of the Lindbergh Intermodal Transportation Center.

The new terminal location can be seen fronting Pacific Highway. The footprint of the ITC is shown in gray. Source: California Independent Voter Project.

The ITC concept involves moving the airport’s terminals to the north side of the runway. The existing 41-jet-gate configuration on the Harbor Drive (south) side of the runway would be eliminated over time in a phased manner and a new 63-jet-gate terminal would be created between Pacific Highway, the Marine Corps Recruit Depot property line, and the runway. The existing fuel farm, Federal Aviation Administration control tower, general aviation facilities, and cargo operations would move to the south side of the runway, adjacent to Harbor Drive.

Ninety acres of land adjacent to the airport on the north side, bounded by Pacific Highway, Interstate 5, Washington Street, and Laurel Street, would become an intermodal transportation center, built over the existing train and trolley tracks. Approximately half of this land is already owned by public agencies and much of the remainder is already used for airport parking and rental cars. This structure would rise to

Chapter 1

Introduction


the elevation of Interstate 5 (five stories tall) and structurally would be a large parking facility. Under the CAIVP plan, the new airport terminals and the Lindbergh ITC would have direct freeway links from I-5 in both directions. The Lindbergh ITC would include the following features:

Long-term parking for more than 20,000 vehicles and short-term parking for 2,000 vehicles;

Room for all car rental agencies and their rental cars;

Bi-level drop-off and pick-up roads for plane, train, bus and trolley passengers;

Provide direct access from the Lindbergh ITC to airport terminals via sky bridges that would include moving sidewalks;

Provide new off ramps and on ramps directly to Interstate 5 to Pacific Highway for vehicular access to and from the new terminal location;

Room for a downtown people mover and a high-speed rail between airports;

Trolley stops where one can catch the Orange, Blue, Green and special event lines;

An Amtrak Pacific Surfline stop (serving San Luis Obispo, Santa Maria, Santa Barbara, Ventura, Oxnard, Camarillo, Simi Valley, Van Nuys, Los Angeles, Santa Ana, and points in-between; and

A Coaster stop bringing people in from Oceanside, Carlsbad, Encinitas, Solana Beach and Sorrento Valley.

The Lindbergh ITC would connect to all forms of transportation.

In addition to the 90 acres of public and private property described above, the Lindbergh ITC would require a 27-acre strip of land owned by the Marine Corps Recruit Depot to allow taxiway C to be extended to the end of the runway.

Because the Lindbergh ITC also includes constructing new airport terminals, it also provides the opportunity for the creation of an enhanced green and sustainable SDIA by incorporating up-to-date features to reduce energy use and carbon emissions. In addition the concept itself aims to reduce traffic, miles driven by automobiles, and the concurrent negative environmental impacts associated with vehicle use by transferring a portion of airport access to rail-based modes of transportation.

A similar concept, proposed by the Port of San Diego in 2001, was estimated to cost $1.2 billion (CAVIP). While no up-to-date estimates are available, with construction escalation, the CAIVP estimates that present costs may have tripled to roughly $3.5 billion.



CAIVP believes the Lindbergh ITC would provide the following benefits:



Encourage the increased use of transit;



1.3. Report Objectives and Content CAIVP requested that Malcolm Pirnie and Sinclair Knight Merz (SKM) (Pirnie/SKM) prepare an independent analysis of selected expansion alternatives developed in support of the SDCRAA Airport Master Plan and the Airport Transit Plan along with a third alternative, the Lindbergh ITC. This report provides an independent and objective analysis of key sustainability components of the SDIA expansion. The report is intended to stimulate further thinking and review about traffic, transit and sustainability opportunities. It is not intended to provide a complete analysis of airport sustainability nor provide a definitive analysis of all sources of greenhouse gas emissions and sustainability. The major sustainability components evaluated in this report include:



Changes in road traffic congestion on the streets around the SDIA;

Impact of passenger and airport worker travel changes on greenhouse gas emissions;

Impact of passenger and airport worker travel changes on air quality; and

Lessons learned from a qualitative review of the experience at other international airports to implement “green airport” practices into a modified airport infrastructure.

Other positive sustainability components result from the above and these are also identified.

This report is organized as follows:

Chapter 2 discusses the modeled changes in vehicular traffic and public transport associated with the Lindbergh ITC;

Chapter 3 discusses the changes in greenhouse gas emissions and criteria pollutants that occur as a result of the changes in vehicular traffic and public transport use;

Chapter 1

Introduction


Chapter 4 discusses a context for sustainability and describes the potential for sustainability benefits associated with green airport approaches and green building standards;

Chapter 5 summarizes the report’s conclusions;

Chapter 6 contains references;

Appendix A presents case studies on mass transit access to five airports;

Appendix B presents a detailed description of the transport modeling;

Appendix C presents detailed calculations of greenhouse gas emissions;

Appendix D presents detailed calculations of criteria pollutants;

Appendix E presents information on the Leadership in Energy and Environmental Design (LEED) system;

Appendix F presents information on worldwide airport environmental initiatives from the Airports Council International.


2. Transportation Analysis

This chapter describes the existing and possible future transportation conditions (traffic and transit) associated with the SDIA and the Lindbergh ITC concept proposal in comparison to the SDCRAA DEIR. The first section provides background on the San Diego area and the airport, the second discusses airport ground transportation, the third describes the scenario modeling including the modeling approach and the scenarios or alternatives analyzed, and the fourth presents the results and discussion. Appendices include case studies of airports in other U.S. cities for comparison with San Diego (Appendix A) and a description of the transportation model developed for this study (Appendix B).

2.1. Background 2.1.1. Regional Transportation The San Diego region had a metropolitan population of just over 3 million in 2007 with 1.3 million living in the city. The city and region have grown rapidly in population and the region is forecast to increase further to approximately 3.9 million residents in 2030 (SANDAG, 2004). Redevelopment of a number of areas, including the waterfront, will result in substantial increases in downtown population over this period. This increased population, along with increased employment in the area, is likely to increase traffic use on city roads already heavily used by airport traffic, such as North Harbor Drive, Grape Street and Hawthorn Street. In addition, total exposure to the local air quality pollutants and noise generated by airport related traffic movements through city streets is also likely to increase.

The transportation network around SDIA is illustrated in Figure 2-1. The existing highway network has not kept pace with increased travel demand resulting both from the rapidly rising population and increased prosperity of the region. The result is increasingly congested traffic conditions. According to the Texas Transportation Institute’s annual review of traffic congestion across the country, San Diego has the worst traffic congestion of all medium sized cities (one to three million residents) in the U.S. when measured as excess trip time in peak periods compared to off-peak periods. Peak period travelers in the San Diego region suffered from an average annual delay of 57 hours each in 2005 as a result of congestion. This compares unfavorably with other

Chapter 2 Transportation Analysis

Figure 2-1: Study Area Transport Network

rapidly growing cities such as Sacramento, where the average annual delay was 41 hours, and Las Vegas, where the average delay was 39 hours. A number of older, midsize cities that are experiencing stable or declining populations have lower average congestion delay; for example Pittsburgh experienced an average of 16 hours annual delay and Cleveland 13 hours. Car trips on freeways in San Diego were on average 31 percent longer in the peak period compared to free-flow conditions. In Sacramento, they were 26 percent longer and in San Francisco 25 percent longer.

Increased road traffic congestion has a direct negative impact on the operations of SDIA, by increasing the time and reducing the reliability for passengers and employees to travel to the airport. Road traffic congestion also adversely impacts San Diego’s competitive position by making it less attractive to air passengers who may have alternatives for vacations or business meetings. Cargo operators who rely on the airport road system to transport goods rapidly to and from the airport are also adversely affected by traffic congestion.

Traffic congestion also serves to erode the quality of life in the urban environment though degraded air quality, increased noise and unpleasant urban spaces. Given the highly populated inner urban nature of many of the roads which are most congested as a result of


Chapter 2

Transportation Analysis


airport traffic, especially Grape and Hawthorn Streets, the exposure to these negative aspects may be expected to be higher than in less populated suburban areas. Furthermore, congestion results in additional fuel consumption which results in higher costs to travelers and increased criteria pollutants and greenhouse gas emissions (see Chapter 4). Approaches to reducing congestion, as well as minimizing the distances driven, could help to alleviate these impacts.

2.2. Airport Ground Transportation 2.2.1. Road Network The location of the airport close to downtown San Diego, and directly to the south of the I-5 and near the I-8 highways offers an opportunity to improve public access to airport facilities by developing efficient access to the highway network, albeit a network that is increasingly capacity-constrained. However, the location of the airport terminals on the south side of the airfield results in the need for airport traffic coming from the freeway corridors to use a number of local streets, including through the downtown area. This physical layout has adverse implications for both congestion and the quality of life in urban environment in the vicinity of these streets.

Figure 2-2 illustrates the current proportion of airport related traffic on key road links in the vicinity of the airport. As shown, the airport is a dominant traffic generator in the local area and a major source of local traffic congestion.

Levels of congestion are commonly measured on a level-of-service scale that ranges from A for free flow conditions to F for major traffic disruption; the levels are described in Table 2-1. Levels of service of E and F are typically deemed unacceptable for efficient roadway operation. Figure 2-3 illustrates the level-of-service (LOS) that is currently experienced on the major roads in the area. A number of routes during peak periods, such as Grape Street and Rosecrans Street operate at LOS E or F. This has implications for trip times and reliability as well as of wider urban amenity resulting from the noise, emissions and adverse impacts on the streetscape that result. As airport traffic makes up substantial proportions of the traffic along many of these routes which are operating beyond capacity it follows that a reduction in airport traffic would help to alleviate congestion on some of these routes.

Chapter 2 Transportation Analysis Figure 2-2: Current Percent Airport Related Traffic by Road Segment (SDIA

DEIR, 2007)

Figure 2-3: Airport Related Traffic with Current LOS (SDIA DEIR, 2007)


Chapter 2



Table 2-1. Level-of-Service (LOS) Descriptions

LOS Description

A Free-flow conditions

B Reasonably free-flow conditions, ability to maneuver within the traffic stream is only slightly restricted.

C Traffic speeds remain close to free-flow but freedom to maneuver within the traffic stream is noticeably restricted, resulting in a need for added driver vigilance.

D Traffic speeds decline slightly with increasing flow and maneuvering becomes increasingly limited.

E Operating at capacity resulting in volatile road performance and no usable gaps in the traffic stream.

F Breakdown in traffic flow where lines are extensive and can extend significant distances upstream.

The location of the terminal buildings to the southeast of the airport makes access by car difficult from many locations. Traffic is required to circulate through city streets such as Hawthorn and Grape Streets, along arterials such as Rosecrans Street and along Kettner Boulevard to the north. Furthermore, the number of airport-related uses to the north of the airport, such as car rental and parking, results in additional shuttle van movements and inconvenience for air passengers in accessing the terminal buildings.

2.2.2. Transit Public transit use for airport access is low by comparison to other U.S. and international cities. Approximately 1 percent of air passengers use local bus services to access the airport, most predominantly the 992 Airport Flyer service. As shown in Figure 2-4, approximately 55 percent of passenger movements to and from the airport are made by private car (park on-airport, park off-airport, drop off) while another 28 percent are by rental car or taxi (HNTB, 2007). Similarly, as shown in Figure 2-5 airport employees predominantly use car to access the airport, with only approximately 2 percent using bus (HNTB, 2007). This fraction does, however, make up two thirds of total bus ridership to the airport. By comparison, Chicago O’Hare Airport has 4 percent share of rail and over 5 percent share of bus (local and express services) for air passenger access to the airport (Leigh River Associates et al., 2002).


Figure 2-4: Airport Passenger Ground Transportation Mode Shares at SDIA

(HNTB, 2007)

Private Car: park on-airport, 19.5%

Private Car: park off-airport, 10.0%

Private Car: drop off, 25.5%

Rental car, 19.1%

Taxi, 8.6%

Shared van, 9.5%

Bus, 1.0%

Charter/other bus, 1.0%Courtesy van, 5.8%

Figure 2-5: Ground Transportation Mode Shares for Employees at SDIA

(HNTB, 2007)

Private Car, 98%

Bus, 2%


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2.2.3. Trolley The San Diego Trolley, operated by the Metropolitan Transit System (MTS) is a light rail system consisting of three main lines:

Blue line which runs from the Mexican border at San Ysidro north through downtown and then to the north of the airport to Old Town Transit Center.

Orange line which runs from Gillespie Field to downtown, running in a loop from the 12th & Imperial Transit Center around the downtown area.

Green line, completed in 2005, which connects the Old Town Transit Center to Santee.

Bus feeder services provide connecting services to the trolley system at 34 of the 53 stations (64 percent) while parking is provided at 28 (53 percent) of the stations. Most stations provide free parking, and in the majority of cases there are no current capacity constraints on parking at the stations. There may, however, be issues for air passenger parking at these locations because air passengers may require parking for more than one day. This would introduce issues of parking security (particularly overnight) as well as increasing pressures on overall parking capacity. Changes in the way in which parking lots operate would be required. For example, while ample parking is available at Qualcomm Stadium when events are not taking place, there is currently no parking specifically allocated for the trolley station. It is likely that dedicated parking would be required should such a site be allocated for airport-related transit trips. Similarly, Old Town Transit Center does not currently provide long-term parking. Existing parking is relatively constrained and the site location would limit opportunities to substantially increase parking capacity at this site. An additional issue is that Old Town is operated by California State Parks and serves as parking for visitors to the Old Town State Park in addition to the transit center. This is reinforced by the signing at the site, which emphasizes the site as the location of the state park (Figure 2-6).

Major trolley interchanges are provided at Old Town Transit Center, Santa Fe Depot, and the 12th and Imperial Transit Center. The southbound Green line currently terminates at Old Town Transit Center, where the southbound Blue line service to downtown and San Ysidro begins. All Coaster services stop at Old Town, and some Amtrak Surfliner services also stop at the station. Santa Fe Depot is the terminus of the Coaster and Amtrak passenger services as well as servicing the Blue line. America Plaza station, located directly across Kettner Boulevard from the Santa Fe Depot, provides connections to the Orange line as well as a stop on the Blue line. The 12th and Imperial Transit Center provides a connection between the Orange and Blue lines on the south side of the downtown area. The system has among the highest levels of ridership of any light rail


Figure 2-6: Entrance to Existing Old Town Transit Center


system in the U.S. with 124,000 average weekday riders in the first three quarters of 2007 (APTA, 2007). This compares favorably with the 106,000 average daily riders on the light rail systems in Portland (OR) and 82,000 in Saint Louis (MO) over the same period (APTA, 2007).

A number of studies are, or have been completed, examining potential extensions of the trolley system including:

Green line extensions to downtown.

Mid-Coast Corridor Study to examine the potential for a trolley or bus rapid transit extension from old Town Transit Center north to University City.

While ridership has increased substantially over recent years, the network has excess capacity available across much of the day and could accommodate more frequent services on the current infrastructure should there be sufficient demand, sufficient subsidy and sufficient light rail vehicles acquired. The proposed ITC could leverage from this

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available capacity to provide additional trolley ridership at little marginal cost to the transit service provider. It is likely that the net operating subsidy required would decrease given that ridership is likely to increase at little marginal cost. However, as indicated by the analysis later in this chapter, extending the trolley system such that more lines would access the ITC would improve ridership further. The infrastructure required to achieve this enhancement would not appear to be insurmountable given that sufficient rolling stock and service paths are available on the existing alignment.

2.2.4. Bus Local bus services are provided by MTS. These services include feeder bus services to the Coaster and trolley system as well as standalone bus services such as the 992 Airport Flyer, which provides services at 12 minute intervals during the day on weekdays and at 15 minute headways at other times between 5am and 12am. The service connects the downtown area to the airport, serving all three airport terminal buildings. The service is now provided by dedicated low floor vehicles fitted with luggage storage and are clearly branded as airport services. Recent passenger surveys suggest that approximately 65 percent of users of the service are airport employees.

The 923 route also serves the airport, providing serves roughly every half hour between downtown and Ocean Beach. The service is not marketed as an airport service because it does not enter the terminal area, and the location of the nearest stops on North Harbor Drive are inconvenient for air passengers and airport employees.

2.2.5. Coaster The Coaster rail service, operated on behalf of North County Public Transit District (NCTD), provides a regional rail service between San Diego Santa Fe station and Oceanside. All services stop at the Old Town Transit Center. The rail alignment runs parallel to the trolley service between Santa Fe station and Old Town, passing directly to the north of the airport site. North of Old Town much of the alignment is single track, with several passing loops. In addition to sharing the tracks with Amtrak intercity services and freight trains, this imposes a cap on the number of daily trips available to the public and the services that can be provided. Currently eleven services are offered daily in each direction with a much reduced service on Saturdays and no service on Sundays.

2.2.6. Amtrak Amtrak provides intercity services from the San Diego Santa Fe station to Los Angeles and further north to Santa Barbara and Paso Robles on the Pacific Surfliner route. Twelve trains provide services operating on weekdays at least as far as Los Angeles, with a slightly reduced service of ten to eleven services per day per direction on weekends. This Amtrak route shares the alignment with the Coaster services operated by NCTD as far north as Oceanside.



2.2.7. SDCRAA Airport Transit Plan SDCRAA have been consulting on their draft Airport Transit Plan during 2007. The plan has an aspirational target of increasing air passenger transit ridership from 1.2 percent to 4-6 percent in the next 3-5 years. In order to achieve this goal, they describe a series of measures both near-term (until the end of 2009) and mid-term (2010 to 2011). They also identify more broadly longer term measures (beyond 2012) that may be considered. Of the near-term measures for which a quantified mode split target is given, the total increase in transit mode share would be 2.5 percent (accounting of 1.5 percent from marketing, 0.5 percent from offering free rides to arriving passengers and 0.5 percent from extending the bus service to the convention centre).

Mid-term measures for which quantified mode share targets are provided include reducing bus service intervals to 10 minutes (0.25 percent shift in mode share), adding evening and weekend Coaster trips (1.0 percent), providing a shuttle to Old Town Transit Center (1.0 percent) and remote parking sites (1.5 percent). This gives a total of 3.75 percent, or 6.25 percent when incorporating the near-term measures.

There may be additional positive influences from many of the other unquantified measures, such as using low floor buses and the introduction of NextBus signs. The assessment of transit mode shares achievable with each of these options was based on professional judgment in the Transit Plan.

SDCRAA along with other local stakeholders have also been exploring the using of remote park & ride facilities along major corridors, potentially including sites in North County (I-5), Escondido/Poway (I-15), Miramar/Mira Mesa and El Cajon/La Mesa (I-8). These may be similar to the ‘remote terminal’ concept as used by LAX at Van Nuys, where passengers can check-in their baggage and receive their boarding pass and then travel by dedicated bus service to LAX.

2.2.8. Mitigation Measures to Address Airport Related Traffic Measures to mitigate the adverse impacts of airport related traffic, particularly with regard to congestion relief, may include providing alternative or expanded roadway capacity. The DEIR proposes a number of measures to enhance roadway capacity in the vicinity of the airport, including targeted road widening, intersection improvements and removal of on street car parking. While these approaches are shown to satisfactorily address congestion to 2030 on all but North Harbor Drive no assessment is made of their viability financially, environmentally or in terms of public acceptability. The multi-use nature of most of the local road network would likely limit what could be achieved given the needs of local residents and businesses for the road network beyond airport access. It is unclear whether the FAA would contribute to the financing of such infrastructure given that it would be located outside the airport boundary. Any funding shortfall would most likely come from local sources such as SDCRAA, Caltrans and the City government. By

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comparison, mitigation measures that result in reduced traffic demand – such as the ITC proposal, may receive substantial financial contributions from the FAA, resulting in a much lower financial burden on SDCRAA, Caltrans and the City government.

Traffic flows on the I-5 corridor in the vicinity of the airport were studied in 2003 as part of the Central I-5 Corridor Study (URS, 2003), which made a number of recommendations in regard to airport access, including:

New I-5 on/off ramps between I-5 north and the Pacific Highway just south of the Old Town interchange. The southbound off-ramp would exit I-5 south of Old Town, cross over the trolley and railroad tracks and remain elevated until coming to grade at Pacific Highway, north of Washington Street. The on-ramp from Pacific Highway to northbound I-5 would also be on structure and would cross over I-5, requiring braiding with the northbound off-ramp to Old Town. It was recommended that this option also include enhancements to the I-5/Old Town interchange including realignment of the southbound on-ramp, as well as Hancock Street.

Modification of existing Pacific Highway viaduct to provide on/off ramps between south I-5 and the airport. The existing eastbound exit ramp from the Pacific Highway viaduct onto Pacific Highway to the east of Washington Street would need to be replaced as part of the works.

In addition, the study recommended the expanded use of parallel arterial routes to relieve short distance I-5 traffic in the central city area from needing to use the route as well as the development of high-occupancy vehicle (HOV) lanes either on the I-5 itself or, more likely, on Pacific Highway. Other related road infrastructure changes proposed include the redesign of the I-5/I-8 interchange, which could conceivably result in more airport traffic using Rosecrans Street when traveling from the north. Much of the analysis in the URS study was based on the assumption of the development of a north terminal that would operate in conjunction with the existing south terminal; the resulting new on/off ramps between the I-5 and Pacific Highway would, therefore, provide direct highway connection to the new north terminal.

The URS study noted that despite the cost and engineering complexity of the proposed road enhancements in the vicinity of the I-5 and Pacific Highway that much of the road network leading to the (existing) south terminal would remain at an unacceptable level of service, particularly at the intersections of Laurel Street and Pacific Highway and Laurel Street and Harbor Drive. The study recommended grade separation of these junctions, although it did note that such separation may not be consistent with other developments in the vicinity of the airport, where such separation may have adverse local noise and viewing corridor impacts.

The study identified a number of design deficiencies on the I-5 that serve to decrease its capacity, including substandard distances between interchanges (resulting in greater traffic weaving) and substandard ramp geometries which serve to exacerbate driver



confusion and weaving movements in the vicinity of the junctions. Redesign of the junctions in the vicinity may be expected to help with capacity, but given the present terminal locations would be unlikely to relieve congestion on Hawthorn, Grape and Rosecrans Streets.

While roadway expansion or other measures designed to improve traffic flow to the airport may well assist in enhancing access to the airport, it may also be desirable to improve access by providing efficient transit alternatives and in so doing reduce total vehicle movements. Mass transit can be more energy efficient than private cars and reduce emissions of local air pollutants and greenhouse gases. However, for transit to be an attractive alternative it must go to where air passengers and employees want to travel, be reliable, be safe, operate at hours when travelers wish to access the airport, be cost effective for the traveler and be visible (that is, travelers need to be aware that the transit alternative exists). Understanding the demand for transit alternatives is, therefore, a complicated process, requiring an understanding of how travelers perceive the attributes of different mode alternatives in making their travel decisions. Likewise, where multiple changes are being considered in parallel – for example, improved access to the trolley system as well as roadway enhancements, then it is important to consider such improvements together rather than in isolation. Improving access to the trolley system would be expected to improve trolley ridership, but improving road access as well may make travel by car sufficiently more attractive to negate any trolley ridership benefits. It is the role of modeling to evaluate these counterbalancing effects.

2.3. Scenario Modeling 2.3.1. Modeling Approach In order to examine the impact of the Proposed Alternative in the DEIR and the ITC on the choices of travelers to the airport, and in turn on the congestion and emissions impacts that these choices would have, a transit mode choice model was developed. This model predicts travelers mode choices based on the trip times, costs and other factors that are important in the decision-making process of travelers.

An understanding of the distribution of where people come from (travel origins) was required for both air passengers and airport employees in order to develop the model. Due to limited data availability, it was necessary to assume the same distribution for both groups. In reality, it would be expected that airport employees would tend to live closer to the airport. Other required data, such as travel times and costs, were obtained from the SANDAG regional transportation model and other public domain sources.

The sensitivity to time and cost will differ across different types of traveler. For example, those traveling on business would be expected to be more time sensitive than cost sensitive in comparison to leisure travelers. These sensitivities were obtained based on a model from San Jose International Airport and adjusted to reflect values of time

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found across other airports in the U.S. Ideally these sensitivities would be derived from local surveys of travelers to San Diego Airport; however, such a study was outside the scope of the present work. Reasonable assumptions can be made based on studies from other U.S. airports. More robust estimates could be developed later by initiating a local data collection and modeling study to obtain local sensitivities, which could then be incorporated into the model system developed for this study.

The model system was developed in a spreadsheet to allow rapid evaluation of various transportation improvements both in total, for specific types of travelers (for example, business travelers or non-residents) and along specific corridors. The region was divided into 78 zones such that the travel times and costs for each transport mode was determined for each scenario. The modeling approach is described in detail in Appendix B.

2.3.2. Modeled Scenarios Several current and future transport scenarios were developed for analysis:

Scenario 1 (2005 Baseline) – Or ‘As now’ with modeled conditions in 2005 based on infrastructure as it exists presently. There are no changes in ground transportation access to the airport.

Scenario 2 (No Project Alternative @ 2030) – Same as the DEIR No Project Alternative at 2030. Predicted traffic based on no changes in infrastructure or in the Airport Transit Plan. Scenario 2 differs from Scenario 1 based on increases in demand and how increased congestion may influence passenger and airport worker choices without any changes in transportation infrastructure or incentive programs.

Scenario 3 (Preferred Alternative) – This scenario included recommendations from the DEIR Master Plan Preferred Alternative at 2030 but does not include the traffic mitigation measures or draft Airport Transit Plan.

Scenario 4 (Preferred Alternative with Airport Transit Plan) – Same as Scenario 3 except with an Old Town shuttle bus service, free Flyer fares, reduced Flyer headways from 12 to 10 minutes, evening and weekend Coaster rail service and FlyAway sites at Escondido Transit Center, I-15/SR52 and I-805/SR54 junctions. These measures are part of the draft Airport Transit Plan.1

Scenario 5 (Lindbergh ITC) – Predicted traffic in 2030 based on the Lindbergh ITC with the removal of the 992 Flyer route, extension of the Trolley Green line south

1 Other proposed elements of the draft Transit Plan (including improved marketing, customer service training, ticket machines and NextBus signs) were not included in this scenario because they were not readily amenable to quantitative analysis and did not change the basic infrastructure-based options available to airport passengers and workers. While these types of policy, marketing and incentive-based programs are expected to have some influence on mode choice, they are at least, but probably more, effective in the Lindbergh ITC scenarios defined below than Scenario 4 because more options and choices would exist for travelers with an integrated transportation system. As in any modeling, the scenario results may not predict ‘absolute’ data but they are useful for comparative evaluations among the scenarios.


from Old Town Transit Center to the ITC, extension of the Orange line north to the ITC and transit improvements from Scenario 4 (except for Old Town shuttle).

Figure 2-7: Tested Trolley Network

he development to the trolley network as part of the ITC that were tested are shown in TFigure 2-7. This is an indicative network only for the purposes of estimating passenger demand; it is not proposed as a potential service pattern. There would be issues associated with introducing these extensions. For example, the Siemens SD70 vehicles currently used on the Green line would not be compatible with stations south of Old Town. However, it is expected that in the timescales of the proposed development that


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such modifications to stations could be incorporated as part of a fleet update strategy andpotential extensions of the Green line irrespective of any airport redevelopment.

The scenarios were analyzed using both a conservative and an optimistic set of

A conservative assumption that the intrinsic features of bus, trolley and rail services

services have features

The ail are valued as nal

2.4. Results and Discussion ssengers between 2005 and 2030 will add

n,

asing of the

2.4.1. Mode Share or each of the scenarios are detailed in Figure 2-8 and Figure

n total rs

assumptions. Specifically:

(such as ride quality, service reliability and other qualitative service characteristics) are the same aside from fare and trip time differences; and

An optimistic assumption that assumes that trolley and rail which makes them more attractive than bus services. These features include ride quality, permanence of routes and other onboard conveniences.

optimistic assumption estimates that these intrinsic benefits of rbeing equivalent to six minutes of trip time. This is consistent with SANDAG’s regiotransportation model and with findings from studies in other locations. It is, however, highly dependent on the specific services being compared; it would, for example, be possible for a very high quality bus service to be similarly attractive to a rail service.

The forecasted 60 percent growth in air pasubstantially to ground transportation demand within the vicinity of SDIA. In additiobackground traffic growth resulting from continued population growth and redevelopment in the vicinity of the airport will further add to demand, increcongestion on the local road and transit networks. This section presents the resultsmodeling for each scenario and discusses the implications on mode share, vehicle miles traveled (VMT) and transit ridership.

The forecast mode shares f2-9 for the conservative and optimistic scenarios, respectively. The forecast mode share values are summarized in Tables 2-2a and 2-2b for conservative and optimistic assumptions, respectively. If the Lindbergh ITC concept were implemented, thetransit ridership would increase from 2.6 percent to 4.0 percent (an additional 1,128 rideper day) using the conservative assumption and 5.2 percent using the optimistic assumption (an additional 1,986 riders per day).


Figure 2-8: Mode Share for Conservative Scenario (Air Passengers and Airport Employees)

0%

5%

10%

15%

20%

25%

30%

35%

Car - On-AirportPark

Car - Off-AirportPark

Car - Kiss& Fly

Car - rental Taxi Shared van Bus Trolley Coaster FlyAw ay

Mod

e sh

are

Scenario 2 (No Proj Alt @ 2030)

Scenario 4 (Preferred Alt)

Scenario 5 (Lindbergh ITC)

Figure 2-9: Mode Share for Optimistic Scenario (Air Passengers and Airport Employee)

0%

5%

10%

15%

20%

25%

30%

35%

Car - On-AirportPark

Car - Off-AirportPark

Car - Kiss& Fly

Car - rental Taxi Shared van Bus Trolley Coaster FlyAw ay

Mod

e sh

are

Scenario 2 (No Proj Alt @ 2030)

Scenario 4 (Preferred Alt)



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Table 2-2a. Transit Mode Shares by Scenario (Conservative Assumptions)

Bus Trolley Coaster FlyAway All Transit

Scenario Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

No Project

Alternative

@ 2030

0.8 --- 0.2 --- 0.3 --- --- --- 1.3 ---

Preferred

Alternative

with Airport

Transit

Plan @

2030

1.4 +491 0.3 +60 0.2 +98 0.5 +435 2.6 +1,084

Lindbergh

ITC @

2030

0.6 -234 1.9 +1,415 1.0 +632 0.5 +399 4.0 +2,212



Table 2-2b. Transit Mode Shares by Scenario (Optimistic Assumptions)

Bus Trolley Coaster FlyAway All Transit

Scenario Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

Mode share (%)

Boarding Change

No Project

Alternative

@ 2030

0.8 --- 0.2 --- 0.3 --- 0.0 --- 1.3 ---

Preferred

Alternative

with Airport

Transit

Plan @

2030

1.4 +490 0.4 +80 0.5 +128 0.7 +604 3.0 +1,303

Lindbergh

ITC @

2030

0.6 -234 2.6 +1,905 1.4 +849 0.7 +550 5.2 +3,070

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The increase in transit share for airport employees is somewhat lower than for air passengers, as the relative costs between the modes makes car the cheaper mode for many trips. For example, from Mission Valley the fare to the airport using transit is $2.50 while the distance by car is 4.2 miles and so assumed cost (based on $0.15/mile) is $0.632 3. The improvements made to the transit network result in trip time benefits (a reduction in transit in-vehicle time from 45 to 20 minutes) to make transit competitive with car (for which the trip time was assumed to be 15-20 minutes) before accounting for the additional time to access the transit service. There would, however, be no cost savings for transit users, and so the air passenger transit share increases more than that for airport employees because the former are more time sensitive.

A number of policy, marketing, and incentive-based programs from the Airport Transit Plan were not included in our analysis of the Preferred Alternative with Airport Transit Plan. Such policy, marketing, and incentive-based programs are expected to be at least as, but probably more, effective in the Lindbergh ITC Scenarios than under the Preferred Alternative because more options and choices would exist with an integrated transportation system. This may be an added benefit to the ITC approach because any additional improvements would be on top of the reductions in congestion indicated under Scenario 5. The Convention Center shuttle bus service was not included in the modeling because of the coarse nature of the zoning system in the downtown area, which was a result of limitations in the available data. While this exclusion will tend to understate the transit potential of the Preferred Alternative with Airport Transit Plan marginally, it is assumed to have no effect on the ITC scenario as the Trolley Orange line would serve the Convention Center directly from the ITC.

2 The assumed perceived cost per mile of $0.15 is to be consistent with the SANDAG regional transportation model. This is significantly lower than the rate of $0.485 per mile allowable for income tax purposes. The latter number attempts to account for perceptions regarding insurance, maintenance, depreciation and other costs not generally perceived on a per mile basis. At gas prices of approximately $3.00 per gallon, a typical car that achieves 25 mpg would cost approximately $0.12 per mile based on gas costs alone, which is broadly consistent with the value assumed here. Sensitivity tests with the value set to $0.485 per mile indicate that the reduction of VMT would be less than 1 percent. This low responsiveness to fuel prices is due to the relative cost insensitivity of air passengers, for whom timelines are more important than cost. 3 Background traffic forecasts, as well as the mode choices of airport travelers, assume car operating costs consistent with the SANDAG regional transportation model. This model assumes that fuel prices will increase from $1.70/gal in 2000 to $2.80/gal in 2030. Given that fuel prices were hovering around $3.00/gal in early 2008 it is not clear whether this assumption is robust. If in fact fuel prices were to be significantly above $2.80/gal in 2030 then it may be expected that background traffic levels would be somewhat lower than forecast and that the transit mode share to the airport would be higher. This may be particularly true for scenarios where the Lindbergh ITC is in place, as the improved transit alternatives combined with higher fuel prices would act to encourage greater transit use.



Modeling results predict airport passengers place a heavy priority on time compared to other parameters impacting their choice of transit mode. This reduces their sensitivity to standard incentive programs. Furthermore, our results indicated the mode shares obtainable as reported in the draft Airport Transit Plan may not achieve the plan’s aspirational goals. The quantified mode share contributions listed in the draft Airport Transit Plan add to 6.25 percent while our results suggest that the improvement in transit mode share would be significantly lower, leading to a total mode share of 2.6 to 3.0 percent. Together, our results suggest that the draft Airport Transit Plan will not be adequate to mitigate increased traffic and congestion under the No Project and Preferred Alternatives.

2.4.1.1. Transit Demand In the present study the approach taken is to model, even at a relatively high level, the potential impacts in order to evaluate the potential impacts in a neutral manner. We feel that this approach is more robust than the process of professional judgment applied as part of the draft Airport Transit Plan, at least for measures where there are readily quantifiable benefits (for example, the Old Town shuttle which would offer trip time benefits for users compared to current transit alternatives). Based on our modeling results, we feel that the assessment of mode shares obtainable as reported in the draft transit plan may be overly optimistic. We find that the increased mode share attributable to the introduction of an Old Town shuttle bus service would be in the order of 0.2 percent rather than the 1.0 percent anticipated by the transit plan. We do note, however, that the ridership of the shuttle service would be dependent on a host of factors – including service frequency and marketing, for which only crude assumptions are made in the present modeling.

Another indication that the anticipated mode shares in the transit plan may be overly optimistic is the forecast increase in mode share of 1.0 percent attributable to evening and weekend Coaster services. Our model assumes that the transit alternative would be available whenever passengers would wish to use the service, which in the case of the Coaster service is overly optimistic given that the last weekday service currently arrives at Santa Fe at 6:35 PM, there are only limited Saturday services and no Sunday services. Nevertheless, our model predicts only a 0.5 percent mode share by Coaster under this best-case scenario, significantly less than the 1.0 percent predicted in the transit plan.

Our analysis suggests that comparatively minor changes in transit services, such as a shuttle bus service from Old Town Transit Center, would tend to attract only limited numbers of users. This is primarily because there would be only minor trip time benefits to users, and even then this benefit would apply only to those for which transit is a viable option. Furthermore, the Old Town Transit Center as it is currently configured is poorly marked as a transit interchange for car drivers on Pacific Highway and the I-5, and there is no provision for long-term parking. Although there is adequate parking capacity for

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current use, it is not clear whether sufficient long-term parking could be allocated to upgrade the Old Town Transit Center to a fully fledged airport park & ride site. The built-up nature of the area would limit the ability to expand the site, and the need to facilitate short-term commuter parking in addition to airport use would complicate site management.

The number of passengers for whom public transit would be viable appears limited, partly because of the dispersed nature of the San Diego region and limited number of transit corridors (particularly with regard to the trolley system). In addition, trip times are uncompetitive for many travelers compared to car travel. For the majority of travelers, the total trip time by transit, accounting for access and waiting time as well as actual travel time, would be significantly longer by transit than by car such that traffic congestion, and hence delay, would need to increase very substantially (perhaps by 50 percent or more) for transit to become attractive. Nonetheless, assuming the trolley system was extended to connect the Green and Orange lines to the proposed ITC, modeling indicates that transit could account for 4.0 to 5.2 percent of the airport trips. This may be higher if traffic congestion levels deteriorate very significantly, fuel prices increase further than anticipated and enhancements to the transit system were incorporated (such as proposed trolley extensions).

This increase in transit mode share from under 2 percent currently to up to 5.2 percent would have a net effect of further decreasing total car VMT, but the impact would be approximately an additional 2 percent VMT reduction because most of the trips that would be attracted to transit would be relatively short trips. By contrast, the average reduction in VMT of 7 percent accruing from moving the terminal closer to the I-5 would make up the majority of the VMT savings.

While the trolley would account for much of the increase in transit ridership (providing 1,400-1,900 extra riders to the airport per day) the Coaster service is also likely to benefit by receiving an additional 600-850 riders per day to the airport. This assumes that the service would be extended to operate earlier on weekday mornings and later in evenings as well as on weekends. The service frequency is assumed to remain unaltered, such that during peak periods there are services approximately every half hour but outside this period service frequency is reduced such that there are one to two hour gaps between services. Infrequent service is likely to act as an impediment to consider using the service for many travelers, especially air passengers who are concerned with missing their flight connection. Should the Lindbergh ITC concept be developed further, there is merit in considering the option of improving the service frequency to make the service more attractive to airport travelers along the corridor. Significant infrastructure investment may be required as part of this process, such as dual tracking sections to the north of San Diego.



The forecast trolley and Coaster level of transit share is somewhat low when compared to some other airports in the U.S. with airport rail links, particularly in comparison to San Francisco International Airport (SFO) and Oakland International Airport (OAK), which both have transit shares between 6 and 7 percent (Leigh River Associates et al., 2002). Part of this difference may arise from the higher population densities in the Bay Area as well as a greater proportion of trips to the airports in these locations arising from routes along the rail corridors. The location of these airports further from the downtown area (a major attractor of trips) makes shared van, and particularly taxi, more expensive relative to public transit. A similar relationship does not exist at SDIA, which is very close to downtown and so the costs for these alternatives are not as high. For example, the transit fare to the airport from downtown is $2.25 but the taxi fare is approximately $11. If a group is traveling together the cost differences quickly reduce further. For many, the additional $8-$9 may be considered reasonable for the ease of traveling with baggage, fast trip and comfort of knowing the service will deliver them directly to the airport.

The transit mode shares for commuting trips in a number of U.S. cities is given in Table 2-3 (U.S. Census Data, 2000), and reflects the differences in transit usage across these cities. San Diego has a low mode share compared to many other cities, particularly in comparison to comparable airports with rail links examined in Appendix A. For example, the San Diego transit share of 3.4 percent is substantially lower than the 9.5 percent of the Bay Area, approximately half that of Portland (OR), and three quarters of that of Minneapolis-St. Paul (MN). This reflects a host of factors, including the extensiveness of the transit systems, land use policies (such as transit-oriented developments and population density) and local cultural factors. It is also lower than the national average of 4.7 percent (U.S. Census Data, 2000). It does, however, lend support to a lower predicted transit share to SDIA compared with a number of other airports.

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Table 2-3. Transit Mode Share for Commuting in Major U.S. Cities (U.S. Census Data, 2000)

City Transit share (%)

Atlanta (GA) 3.7

Chicago (IL) 11.5

Los Angeles – Riverside – Orange County (CA) 4.7

Minneapolis – St. Paul (MN) 4.6

New York – North New Jersey – Long Island 24.9

Phoenix (AZ) 2.0

Pittsburgh (PA) 6.2

Portland (OR) 5.7

San Diego (CA) 3.4

San Francisco – Oakland – San Jose (CA) 9.5

St. Louis (MO) 2.4

SDIA transit mode share of 4.0-5.2 percent with the Lindbergh ITC remains rather low compared with other airports in the U.S. (described in Appendix A). The modeling suggests that to raise it close to the levels of OAK and SFO (where transit shares are above 6 percent) would require both substantial increases to car trip times and costs and the presence of the Lindbergh ITC. For example, the Lindbergh ITC with the additional measures defined in the Airport Transit Plan, optimistic mode constant assumption for rail as well as a 50 percent increase in car trip times and doubling of perceived car operating costs would be required to achieve a transit mode share of 6.4 percent. There are, however, other less quantifiable changes that may make these predictions overly conservative. For example, attitudes towards environmental issues as well as increasingly stringent legislation may lead to greater interest in using non-car access modes. Further, effective marketing and branding campaigns may serve to increase awareness of the transit services and in combination with wider environmental awareness may serve to drive up the transit mode shares. Incentives can be negative, for example, parking rates that include offset carbon emission sequestration costs.

As stated previously, many of the measures proposed as part of the draft Airport Transit Plan would be equally applicable should the Lindbergh ITC concept be adopted. Given the improvements in transit accessibility provided by the ITC, it is possible that many



measures – such as improved marketing – would have an even greater effect than for the current transit services.

2.4.1.2. Transit Capacity Other than parking constraints at certain trolley stations, it is probable that the existing trolley and Coaster services could absorb a great deal of additional ridership without crowding becoming a major concern or requiring additional services. However, should additional services be desired, either to meet additional demand or to improve service quality, then there exists the opportunity to do so on the Trolley network without significant additional infrastructure. The Coaster service is more constrained by the presence of large sections of single track north of San Diego and the need to share this track with freight and Amtrak services. Should the proposed California High-Speed Rail Link be implemented, it may be feasible to consider dual tracking the low speed track as part of this project (or even independently of it).

The trolley network currently operates with excess capacity across much of the day, the most congested part of the network being the Blue line south of downtown. The current maximum service frequency is 10 vehicles/hour/direction during peak periods (equivalent to approximately 640 seats in total plus room for 860 standing). Total loadings across the day past Middletown were approximately 6,500 riders in each direction. Assuming that peak period loadings are approximately 2.5 times the daily average, then peak hour loadings would be approximately 1,000 riders in each direction. Although this implies standing room only in peak periods, up to an additional 875 riders (1,850 individual trips) from the Lindbergh ITC would be expected to be able to be accommodated assuming that less than 500 of these riders travel during the peak hours. This is inline with the maximum forecast increase in trolley ridership of 1,900 riders per day forecast for the Lindbergh ITC scenario with optimistic assumptions. Should demands necessitate it, additional services up to 30 vehicles/hour/direction, could potentially be handled, which would serve to increase the level of service through reduced trip times and further enhance demand.

Not included in this study were analyses of potential additional transit benefits that may arise from the opening of the Sprinter light rail service connecting Escondido to Oceanside. This service will provide a rail connection through the Coaster service at Oceanside to the proposed ITC and the proposed FlyAway service from Escondido Transit Center. Given the distance of this corridor from the airport, and the need to connect onto the (currently) infrequent Coaster rail service, it is not anticipated that the Sprinter would contribute significant additional transit share for airport trips.

The Mid-Coast Corridor Transit Project is another proposed transit improved not incorporated into the analysis. This would provide an 11-mile extension to the trolley system from Old Town Transit Center to University City. Should such an approach be

Chapter 2



developed, this may be expected to provide additional direct services from this corridor to the ITC. This latter project may well further enhance the attractiveness of transit in this corridor and further improve the airport transit mode share, which would otherwise require a bus service and connection onto the trolley system. We have not quantified how substantial the additional ridership may be.

2.4.2. Vehicle Miles Traveled (VMT) Table 2-4a shows the daily average VMT among the five scenarios with conservative assumptions while Table 2-4b shows the change in daily average VMT with optimistic assumptions. These tables show the differences in both miles and percent for the scenarios in comparison to the 2005 Baseline, the No Project Alternative at 2030, and the Preferred Alternative. These values reflect the effect of travel times, costs and other factors on a traveler’s transportation decision. The DEIR No Project Alternative at 2030 (Scenario 2) indicates increased demand for air travel would result in an additional 685,000 miles driven to or from SDIA per day (or 250.2 million VMT annually). This represents a 57 percent increase in daily average VMT traveled by airport passengers and workers over the 2005 Baseline. The Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4) reduced VMT only marginally compared with a no project alternative in that daily average VMT were reduced by only 30,000 miles per day, or just over one percent, compared to the No Project Alternative at 2030 (Scenario 2).

The Lindbergh ITC would reduce daily average VMT by approximately 169,000 miles and 139,000 miles per day compared to the No Project Alternative at 2030 (Scenario 2) and the Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4), respectively. This represents a savings in annual VMT for the ITC compared to the No Project and Preferred Alternatives of 61.7 million and 50.7 million miles, respectively. However, even with alternative transportation choices available associated with the Lindbergh ITC scenarios, average daily VMT was projected to increase by 516,000 miles (43 percent) over the 2005 Baseline.



Table 2-4a. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis

by Scenario – Conservative Assumptions

Daily Ave. VMT Change

from 2005 Baseline

Daily Ave. VMT

Change from No Project @ 2030 and Preferred Alternative @ 2030

Daily Ave. VMT

Change from Preferred Alternative

@ 2030 w Airport Transit Plan

Scenario Modeled

Daily Ave.

VMT

Miles

Perce

nt

Miles

Percent

Miles

Percent

2005 Baseline

1,204,040

---

---

---

---


1,889,503

+685,463

+56.9

---

---

---

---


1,889,503

+685,463

+56.9

---

---

---

---


1,859,146

+655,106

+54.4

-30,357

-1.6

---

---


1,720,364

+516,324

+42.9

-169,139

-9.0

-138,782

-7.5

Source: SKM/Pirnie

Table 2-4b. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by Scenario - Optimistic Assumptions

Daily Ave. VMT Change

from 2005 Baseline

Daily Ave. VMT

Change from No Project @

2030

Daily Ave. VMT

Change from Preferred Alternative

@ 2030 w Airport Transit Plan

Scenario Modeled

Daily Ave.

VMT

Miles

Perce

nt

Miles

Percent

Miles

Percent

2005 Baseline

1,204,040

---

---

---

---


1,884,994

+680,954

+56.6

---

---

---

---


1,884,994

+680,954

+56.6

---

---

---

---


1,848,733

+644,693

+53.5

-36,261

-1.9

---

---


1,700,861

+496,821

+41.3

-184,133

-9.8

-147,872

-8.0

Source: SKM/Pirnie

Chapter 2



The reduction in daily average VMT achieved with the ITC is partly as a result of increased transit mode share but also because total trip distances for many trips are reduced as a result of more direct road access to the terminal. Average car trip distances would reduce from 19.1 to 17.8 miles (a reduction of 7 percent) with the relocation of the terminal to the north side of the airfield. This reduction in trip length would make up the majority of the VMT savings achieved. As shown in Table 2-4a and Table 2-4b an additional 2-3 percent VMT saving would be achieved through the increase in transit usage over and above that achieved through trip length reductions achieved due to the closer proximity of the ITC to the road network.

The VMT reductions with the ITC compared to the non-ITC scenarios are significant, reducing VMT by over 147,000 miles per day compared to the Preferred Alternative with Airport Transit Plan (Scenario 4). To put these reductions in context the following potential policy changes, in VMT, were modeled under scenarios 2 (No Project Alternative @ 2030).

If transit fares were reduced to zero, then VMT would decrease by 7,559 miles (0.4 percent). .

If the perceived cost of car driving were to double, then daily average VMT would decrease by 7,077 miles (0.4 percent).

If road trip times (car, taxi, bus) increased by 50 percent, then VMT would decrease by 35,791 miles (1.9 percent).

Again, in contrast to the above 0.4 to 1.9 percent reductions, the Lindbergh ITC reductions in VMT are approximately 10 percent. Consequently, the important implication is that increasing the accessibility of the airport by transit, through step changes such as proposed by the ITC would be essential to achieving substantial reductions in daily average VMT. Furthermore, once the ITC were in place other effects – such as increasing car costs or trip times would all have a much greater positive effect on transit demand because the transit alternative would be more attractive (although, to an extent, so too would be car alternative given the improved road connections). The Lindbergh ITC alternative could contribute to an increase in airport operational efficiency, and hence sustainability, by providing incentives for taking public transit, for example, show your receipts and go to the head of the check in and security lines.

2.4.3. Level of Service The impact of changes in daily average VMT on traffic congestion in the vicinity of SDIA was evaluated as part of the modeling. Airport related traffic is currently a substantial percentage of the total traffic on downtown streets – ranging from 40 percent to 76 percent of total traffic on Grape Street, Hawthorn Street and Laurel Street (Figure 2-2). Presently, traffic on many streets in the vicinity of the airport currently operates at and beyond desirable levels of service (Figure 2-10).



In order to examine the potential benefits of the Lindbergh ITC concept on traffic route assignment, assumptions were required with regard to the routes travelers used from their origins to the airport. This decision would be based on travel time but also more difficult to quantify factors such as reliability, pleasantness of the route and traveler knowledge and experience.

Route Assignment: For many car trips travelers may have several routes available with which to make their trip. For the purposes of the present analysis the most obvious route (based on trip time) was assigned from each zone to the airport, involving primarily major roads.

Volume Correction: In order to ensure consistency with the DEIR forecasts, the SDCRAA Preferred Alternative was used to apply a correction factor to the link flows following the manual assignment procedure. This resulted in adjustments of approximately +/-20 percent to each link. In this way comparison could be made directly with the DEIR.

2.4.3.1. Traffic Analysis – Road Network Level of Service for Scenario 3 (DEIR Preferred Alternative)

Traffic circulation through the existing airport is limited by the location of the airport away from I-5. As a result much of the traffic accessing the airport must travel through downtown streets (particularly Hawthorn Street coming inbound and Grape Street outbound) and arterials with a largely retail, light industrial and residential nature such as Rosecrans Street (Figure 2-10).4 This has detrimental impacts on traffic congestion, access to local businesses, local air quality, greenhouse gas emissions and urban amenity.

The DEIR undertook detailed analyses of the traffic conditions currently and forecast to occur with the master plan. As part of that analysis it was determined that a number of streets in the vicinity of the airport were currently operating at and beyond desirable levels of service. As shown in Figure 2-2 this includes a number of streets where airport-related traffic constitutes a substantial component of the total. Such streets include Grape Street, Hawthorn Street and India Street. Forecasts developed for the DEIR, shown in Figure 2-11, suggest that the number of road links operating above capacity will increase in the future as a result of airport-related traffic growth as well as background traffic growth. Major airport access roads, such as North Harbor Drive, Grape and Hawthorn Streets would all be severely congested in these forecasts.

4 Non-airport related traffic on Rosecrans Street were incorrect in the DEIR. In order to correct for this error traffic volumes from Series 11 of the Regional Transportation Model were used in 2030 for this link. The non-airport traffic on other links remained consistent with the DEIR and are Series 10 forecasts.

Chapter 2


Figure 2-10. Traffic Level of Service for surface streets in the vicinity of SDIA for Scenario 1 – 2005 Baseline. (Note, this figure is the same as Figure 2-3.)

Figure 2-11. Traffic Level of Service for surface streets in the vicinity of SDIA for Scenario 4 – Preferred Alternative with Airport Transit Plan in 2030.

Figure 2-12. Traffic Level for surface streets in the vicinity of SDIA for Scenario 5 – Lindberg ITC in 2030.




2.4.3.2. Traffic Analysis – Road Network Level of Service for Scenario 5 (Lindbergh ITC)

The traffic volumes on major approach roads will differ with the proposed ITC both as a result of travelers choosing other modes (for example, trolley) and as a result of re-routing due to changes in road access. The levels of service on the road network with the ITC (Scenario 5) is presented in Figure 2-12. The most significant effect on traffic volumes and improvements in LOS is due to re-routing of traffic away from streets such as Rosecrans, Laurel and Hawthorn Streets with Scenario 5. The level of service on Rosecrans and Laurel Streets would reduce to acceptable levels with the Lindbergh ITC in place. A number of other streets, particularly Hawthorn Street, would see improvement on particular segments but background traffic growth would mean that traffic flow on this street would remain congested. Improvements are also seen on a number of other streets, particularly on India, Kettner, Grape, Washington, and Hancock.

Alternatives that would continue to require traffic to use the current access routes to the airport terminals, as well as only having minor impacts on transit mode shares, would not significantly alleviate traffic congestion on the road network. The Preferred Alternative with Airport Transit Plan, while reducing overall VMT by 1.6-1.9 percent would not significantly affect traffic volumes on the local road network. In order to alleviate traffic congestion along the routes, the types of measures discussed in the DEIR would be required – namely providing additional lane capacity and enhancements to signal timing. These mitigation measures would require additional land and have only minimal impacts on emission levels.

In summary, the projected increase in demand for airport travel results in approximately 681,000 additional average daily VMT from airport related ground transportation. Both the No Project Alternative at 2030 (Scenario 2) and the Preferred Alternative at 2030 (Scenario 3; Figure 2-11), would result in significant additional traffic congestion and further decline in the level of service on many streets in the vicinity of the airport. In contrast, the transport mode choice model predicts significant improvements in traffic volume and congestion in the vicinity of SDIA as a result of the Lindbergh ITC despite the projected increase of 497,000 average daily VMT (Figure 2-12).

2.4.4. Impact of Assumptions The assumption that trip times and costs by car will not alter in the future is conservative in so far as it is likely that both will increase in the long run compared with present values. In the case of trip times this is particularly likely given that traffic growth is likely to continue to outstrip road capacity growth (achieved both through improved road operation and new construction). However, quantifying exactly how much trip times would increase is particularly difficult. Trip times tend to increase in a highly nonlinear manner as roads become increasingly congested. The rate of increase in trip times depend to a significant extent on detailed road conditions such as at intersections and the

Chapter 2



extent of weaving in traffic. Furthermore, trip times are likely to increase more on the most congested links than on less congested links.

Sensitivity tests were performed to examine the impact of this critical assumption, in addition to assumptions such as future fuel prices. These tests indicated that transit mode shares would increase in the order of 1-2 percent. The impact on traffic congestion would be small as a result of this comparatively small reduction in road traffic.

The model is most sensitive to travel times – particularly for air passengers. To a large extent these would be outside the control of the airport authority. However, alternative policies the airport authority could consider to increase the transit share include pricing incentives. To test the impact such incentives may have a scenario was tested using the Lindbergh ITC proposal (Scenario 5) and optimistic assumptions about rail usage. This scenario differed by the following package of measures:

Incentivize the use of transit by providing free travel for both air passengers and airport employees

Discourage parking by quadrupling parking charges, both on and off-airport for all passengers and airport employees. It is assumed that the charges for non-SDCRAA off-airport car parking would also quadruple.

Introduce a $10 charge for car trips made to the airport to drop off passengers (i.e. kiss and fly). One way this could be implemented would be to apply the charge to private vehicles that drive along the terminal forecourt. It is assumed that the minimum parking charge would increase to match this amount (to prevent kiss & fly travelers from using the car park for drop-off). Such a charge is particularly effective on overall VMT because each kiss & fly movement generates twice as many miles traveled as self-drive or taking a taxi.

The results of this scenario increased the transit share from 5.2 to 8.2 percent using the optimistic assumptions. A total VMT reduction of 17.7 percent would be achieved in this scenario, around double the 9.8 percent achievable through the introduction of the ITC and extended transit systems alone.

If, in addition to the above scenarios, background traffic congestion levels were to increase such that car trip times would increase by 50 percent, the transit share would increase to 9.5 percent, and VMT would decrease by 20.0 percent compared to the No Project 2030 baseline (Scenario 2).

Another transit service improvement strategy may be to double the service frequencies. If this were done on all services (trolley, bus and Coaster and Amtrak) then the transit



share would increase to 11.2 percent. VMT would decrease by 21.4 percent compared with the No Project 2030 baseline scenario.

2.4.5. Equity and Wider Sustainability Benefits The development of the Lindbergh ITC makes public transit options more attractive which benefits lower paid airport employees thereby contributing to the social equity component of sustainability. A consolidated ITC potentially enhances security and safety because it isolates all of its components from the adjacent uncontrolled streets. Enhanced safety would be perceived by airport passengers using the consolidated parking and rental car facilities, and riders of public transit that would move through the ITC. The consolidation of transit types at the ITC would also enhance the effectiveness of any future public transit expansions in the area and would also enhance their ridership.


3. Greenhouse Gas and Criteria Pollutant Emissions

This chapter addresses greenhouse gas emissions and criteria pollutant emissions for airport-related ground transportation for the scenarios modeled in Chapter 2. Section 3.1 addresses greenhouse gases while Section 3.2 addresses criteria pollutant emissions. This chapter does not address greenhouse gas emissions associated with aircraft use as they fall under federal jurisdiction.

3.1. Greenhouse Gases 3.1.1. Background Currently, the most prominent regulatory driver relative to SDIA, is the State of California ‘AB 32 Global Warming Solutions Act’ of 2006. This law requires a reduction in California greenhouse gas emissions to 1990 levels by 2020 (an estimated 25 percent reduction). Mandatory greenhouse gas caps will begin in 2012 and the California Energy Commission and Air Resources Board (CARB) are currently developing and releasing specific regulations. At present the above regulations do not address transportation. Transportation accounted for 32.4 percent of greenhouse gas emissions in the State of California in 2004 (not including the contribution to greenhouse gases from airplanes themselves) (CEC, 2006). In addition, the Governor’s Executive Order S-3-05 mandates a reduction of greenhouse gas emissions to 80 percent below 1990 levels by 2050.

California also passed AB 1493 in 2002 requiring a 30 percent reduction in greenhouse gas emissions from new motor vehicles by 2016. The law would require automakers to improve fuel economy by an estimated 38 percent, to an average 35 mpg. This law was challenged in the courts and has not been implemented to date. A federal judge dismissed the blocking lawsuit in early December 2007 but implementation still required a waiver from the U.S. Environmental Protection Agency (EPA). EPA denied the California waiver request on December 19. They denied the waiver because Congress passed and the President signed a bill that increases the federal Corporate Average Fuel Economy (CAFE) standard to 35 miles per gallon by the year 2020, and the EPA considers this adequate. California and several other states disagree and sued the EPA on this matter so it will take additional time to fully resolve.

There are several other examples of the developing response to global change at the national level. In April 2007, the U.S. Supreme Court ruled that greenhouse gases should be regulated as an air pollutant under the federal Clean Air Act. EPA is currently reviewing the implication of this decision and the need for additional regulations beyond

Chapter 3 Greenhouse Gas and Criteria Pollutant Emissions


the new CAFE standards. In addition, both Houses of Congress are considering numerous bills that would regulate greenhouse emissions in some manner. These bills may or may not be signed into law in the next year but the discussion strongly suggests that some form of federal greenhouse gas regulation beyond the CAFE standards may be possible within the foreseeable future.

At the international level, the primary driver is the United Nations International Framework Convention on Climate Change. The first phase of this Framework is the Kyoto Protocol which is currently being implemented by many industrial nations although the treaty was not ratified by the U.S. The second phase of the Framework was addressed by an international meeting in Bali in December 2007. Although the final Bali Pact or road map does not include hard targets for greenhouse gas reductions, it does require agreement by 2009 for a treaty pushing for deep cuts in greenhouse gas emissions as well as actions to mitigate climate change in a measurable, reportable and verifiable manner. The U.S. is a signatory to this pact which may further accelerate actions to reduce greenhouse gas emissions within the country.

3.1.2. Methods The combustion of gasoline and diesel fuels in motor vehicles results in the emission of several pollutants. Included among a vehicle’s emissions are three greenhouse gases: carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). The concentration of these and other greenhouse gases in the atmosphere is directly related to global temperatures. According to the CARB, more than half of the fossil fuel emissions of CO2 in California are related in some way to transportation.

Greenhouse gas emissions were calculated for each of the five scenarios described in Section 2.3.2 of this report. These calculations are based on emissions from gasoline-powered cars and vans and compressed natural gas (CNG) buses used to transport passengers to and from SDIA. Airport deliveries and airport ground support equipment were not included in the calculations as they are not directly affected by the alternatives considered. In addition, the change in emissions from decreased use of the electric trolley in Scenario 5 (Lindbergh ITC) is insignificant compared to vehicle emissions, and therefore it was excluded from the calculations. The estimated change in greenhouse gas emissions from the trolley is detailed in Appendix C. No change in emissions is anticipated from commuter trains since they have sufficient capacity under existing routes and schedules to handle the expected increase in riders.

Although CO2 is the primary source of greenhouse gases from vehicles, these calculations also considered emissions of CH4 and N2O. Emissions of hydrofluorocarbons (HFCs), which are another type of greenhouse gas, were not considered because they are related to air conditioning systems and not fuel combustion. HFCs may be released from vehicle air conditioning systems during servicing, when the

Chapter 3

Greenhouse Gas and Criteria Pollutant Emissions


vehicle is scrapped, or during normal operation if there is a leak. HFCs are used as a substitute for ozone depleting substances which are being phased out. Since each greenhouse gas has a different potential to influence global warming, the total greenhouse gas emissions are reported in the standard units of metric tons of carbon dioxide equivalent (CO2e).

To better illustrate these terms, a typical car with 22.9 average miles per gallon generates one metric ton of CO2e in approximately 2,600 miles. Approximately 97 percent of the potential impact to global warming from the typical car comes from carbon dioxide emissions; whereas nitrous oxide contributes approximately 3 percent and methane contributes a fractional amount. If the average car is driven 12,000 miles per year, then 4.6 metric tons CO2e would be generated. The actual emissions of CO2e will depend on the vehicle type and fuel burned, as well as the individual make and model. Larger vehicles such as trucks and vans usually have lower fuel economy and generate more greenhouse gases.

The greenhouse gas calculations used in this report are shown below, and the assumptions are listed in Appendix C. All results are shown on a per day basis.

CO2 = vehicle miles traveled / fuel economy *emission factor (CO2 / gallon) * conversion factor

CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor

(CH4 / mile) * conversion factor * global warming potential

N2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

The calculations and most of the assumptions are taken from the California Climate Action Registry General Reporting Protocol. The results are based on the aggregate number of vehicle miles traveled. Distinctions between city and highway driving speeds and potential emissions decreases due to the greater use of alternative fuels were not considered.

In particular, the calculation of CO2 emissions is based largely on a vehicle’s fuel economy, or miles per gallon. In December 2007, Congress passed, and the President signed, a bill that increases the Corporate Average Fuel Economy (CAFE) standard to 35 miles per gallon (mpg) by the year 2020. Overall, fuel economy is expected to increase in the coming decades, but the 35 mpg CAFE standard does not reflect the actual fuel economy in a given year. This is because the CAFE standard is applicable to an automobile manufacturer’s current model year. It does not reflect the mix of older and newer cars on the road or other key factors. The calculations reflected in Table 3-1 are



based on the assumptions in Appendix C that a certain percentage of the CAFE standard will be met in the 2030 scenarios.

Although it may be assumed that cars will have higher fuel economy in the future, that increase in fuel economy would apply to all the 2030 scenarios. Thus, these results should be viewed from a comparative standpoint, and not necessarily from a quantitative standpoint. The use of different emission factors, assumptions, or models would yield different results, but the overall relative trends would not change.

3.1.3. Results The results of the approach described above and detailed in Appendix C are summarized in Table 3-1. Figure 3-1 graphically displays the total greenhouse gas emissions for the five scenarios that were modeled.

Table 3-1.Change in Average Daily Greenhouse Gas Emissions by Scenario


Change from No

Project @ 2030 and Preferred

Alternative @ 2030

Change from Preferred

Alternative with Airport Transit Plan

@ 2030

Scenario Modeled

Daily Metric Tons CO2e

Metric Tons

Percent

Metric Tons

Percent

Metric Tons

Percent

1

2005 Baseline

479

---

---

---

---

---

---

2


587

+108

+22.5

---

---

---

---

3


587

+108

+22.5

0

0

---

---

4


582

+103

+21.5

-5

-0.9

---

---

5


533

+54

+11.3

-54

-9.2

-49

-8.4

Source: Malcolm Pirnie/SKM data and assumptions in Appendix C.

Table 3-1 and Figure 3-1 show that by 2030, the emissions of CO2e from vehicle travel to and from SDIA is expected to increase by approximately 23 percent, or from 479 to 587 metric tons CO2e (108 metric tons per day which is equivalent to 39,420 metric tons per year), if no changes to the airport are made (i.e., Scenario 1 (2005 Baseline) compared to Scenario 2 (No Project Alternative @ 2030). This significant increase is attributed to the increase in transit demand. The new CAFE standards provide a reduction in future emission (23 percent increase in emissions compared to 57 percent increase in average

Chapter 3

Greenhouse Gas and Criteria Pollutant Emissions daily VMT). However, they do not provide sufficient reductions to maintain, let alone reduce, CO2e emissions.

The estimated greenhouse gas emissions from Scenario 3 (Preferred Alternative @ 2030) are equivalent to Scenario 2 (No Project Alternative @ 2030). Based on the assumptions outlined in Appendix C, Scenario 4 (Preferred Alternative with Airport Transit Plan @ 2030) would achieve less than a 1 percent reduction in greenhouse gases. Thus, the Scenario 4 does little to reduce emissions. The 9 percent reduction of greenhouse gases with the Lindbergh ITC (Scenario 5; Table 3-1) is a significant improvement compared to the Scenario 4. The increased use of public transportation and reduction in VMT under Scenario 5 (Lindbergh ITC) would result in greenhouse gas emissions of 533 metric tons CO2e by 2030. This represents an 11 percent increase from the 2005 Baseline and a reduction of 9 percent when compared to Scenarios 2 and 3. However, this increase is 50 percent lower than the increase projected for Scenario 2 (No Project Alternative @ 2030).

Figure 3-1: Greenhouse Gas Emissions on a Per Day Basis by Scenario

one of the proposed alternatives (Scenarios 3, 4, or 5) would reduce greenhouse gas

0

100

200

300

400

500

600

700


Scenario 2 (NoProject Alternative

@ 2030)


Alternative @2030)



Plan @ 2030)

Scenario 5(Lindbergh ITC @

2030)

Met

ric

tons

CO

2e p

er d

ay

Nemissions to the 2005 baseline or to CARB’s goal of 1990 levels because of projected population and traffic growth. The City of San Diego has developed a greenhouse gas inventory for 1990 and 2004 (City of San Diego, No Date). The transportation sector inSan Diego was reported to contribute 7,864,800 greenhouse gas tons per year (approximately 21,547 greenhouse tons per day) in 2004. This represented 52 percent ofthe community’s total greenhouse gas emissions. Both past (1990 to 2004) and predicted (2005 to 2030) data indicates that the increase in fuel economy in vehicles has not and will not be adequate to keep up with the greenhouse gas emissions from increased VMT




unless new policies, transportation alternatives, or behaviors are developed. Absent such dramatic change, the Lindbergh ITC provided the most benefits of the scenarios evaluated. However, the ITC was insufficient by itself to make sufficient reductiVMT to reach even short-term goals for greenhouse gas reductions if goals were uniformly applied across each segment of society. Even so, the estimated 8 percereduction of greenhouse gas emissions with the Lindbergh ITC (Scenario 5) could foan important component of an overall plan to decrease greenhouse emissions associated with the SDIA. Additionally, by providing a more robust public transit system the Lindbergh ITC could also contribute to other regional initiatives.

ons in

nt rm

3.2. Criteria Pollutant Emissions from Airport-Related Ground

Criteria nder the Clean Air Act are one of the several sustainability

nt

ons in

ded

less, the

3.2.1. Background the DEIR, the EPA and CARB have set ambient air quality

oxide

itor

he

Current attainment/non-attainment status for all criteria pollutants in San Diego County is described in Section 5.5.2.4 of the DEIR. Table 3-2 below shows the County’s

Transportation pollutant emissions u

components associated with a change in transit mode share across the five scenarios discussed in Chapter 2. This section briefly considers one segment of criteria pollutaemissions – the potential for change in emissions from airport-related ground transportation. Specifically, this report compares the change in relative emissiestimated for passenger vehicles for the five transport analysis scenarios described Chapter 2 and Appendix B. The screening-level nature of this comparison is not intento represent a complete air quality analysis of direct and indirect emissions from demolition, construction or operational phases of the various scenarios. Neverthecomparison does offer an indication of the potential effect of proposed changes in transit mode share on criteria pollutant emissions generated by what is described as “motor vehicles (off-airport)” in Section 5.5 of the DEIR.

As noted in Section 5.5 of standards (NAAQS/CAAQS) to protect public health and the environment from the harmful impacts of air pollution.1 The standards apply to a subset of possible air contaminants called “criteria pollutants”. Criteria pollutants include: carbon mon(CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (less than 10 microns and less than 2.5 microns), and lead (Pb), among other state-listed pollutants. CARB and the San Diego Air Pollution Control District (SDAPCD) monemissions of these pollutants in San Diego County, forecast emissions, establish an emissions budget, and develop implementation plans for attaining compliance with tstandards where a pollutant exceeds the federal or state limit.

1 See CARB website for current federal and state ambient air quality standards at: http://www.arb.ca.gov/research/aaqs/aaqs2.pdf, accessed December 2007.

Chapter 3



attainment status for those criteria pollutants considered in this screening-level evaluation.2 This table indicates that San Diego County is addressing maintenannon-attainment status for CO, O

ce or ically 3, and PM. Although this report does not specif

address conformity with federal or state requirements, opportunities for emissions reduction or offset for these pollutants are potentially beneficial to the airshed.

Table 3-2. Current Designation for Selected Criteria Pollutants

Criteria Pollutant

San Diego County Status (Federal/State)

Criteria Pollutant

San Diego County Status (Federal/State)

CO Maintenance/Attainment

SO2 Attainment/Attainment

NO2 Attainment/Attainment PM10 Unclassifiable/Non-attainment

O3 Non- ent attainment/Non-attainm PM2.5 Non-attainment/Non-attainment

.2.2. Methods This comparison was developed by producing rough order of magnitude estimates of

ions for the six scenarios presented in Chapter 2 of this report.

d

on-road passenger vehicles were utilized for this screening-level evaluation for the pollutants in Table 3-2 (see also Appendix D,

e

3

criteria pollutant emissThe emissions estimates were developed using the daily vehicle miles traveled (VMT)data produced for this report and generalized emission factors for on-road passenger vehicles and individual criteria pollutants posted.3 Generalized emission factors for theSDAPCD were not readily available. Instead, conservative emission factors developefor the South Coast Air Quality Management District’s (SCAQMD) CEQA Air Quality Handbook were used to estimate emissions for CO, NO2, O3, SO2, PM10, and PM2.5. Theconservative emission factors were applied for a relative comparison between emissions,not for an assessment of absolute values. Relative changes between scenarios were noted as a percent reduction in total emissions from the Scenario 2 (No Project Alternative @ 2030) and are presented in Section 3.2.3 below.

As noted above, SCAQMD emission factors for

Tables D-2 and D-3 of this report). The emission factors were developed using the EMFAC2007 model (v2.3), as currently recommended by CARB. Use of the factors offers one means for estimating mobile source emissions based on number of vehicltrips and miles per trip. These variables can be combined to reflect daily vehicle miles

2 See Section 3.2.2 below for information on the selection of criteria pollutants considered in this report. 3 See SCAQMD website for emission factors for onroad vehicles produced through the EMFAC2007 at http://aqmd.gov/CEQA/handbook/onroad/onroad.html.

http://aqmd.gov/CEQA/handbook/onroad/onroad.html



traveled or VMT. Consistent with standard practice, emission factors for Reactive Organic Gases (ROG) and oxides of Nitrogen (NOx) are provided as O3 precursors.4

Emission factors generated through the EMFAC2007 model take into account vehicle classes, speed improvements over time, mix of vehicle models and model years, and anticipated improvements in fuel economy. SCAQMD’s current web page for Emission Factors for On-Road Passenger Vehicles & Delivery Trucks further explains:

All the emission factors account for the emissions from start, running and idling exhaust. In addition, the ROG emission factors include diurnal, hot soak, running and resting emissions, and the PM10 & PM2.5 emission factors include tire and brake wear.5

In addition, SCAQMD’s web page explains that the emission factors provided represent the most conservative value generated for each criteria pollutant based on variations for annual, summer, or winter emissions. The CAFE standards discussed in Section 3.1 are incorporated in the generalized emission factors; however, the factors do not yet reflect the recent 2020 rule6. Note, however, that improved fuel economy is not expected to directly effect emissions of criteria pollutants from new vehicles. Federal and state laws require each new vehicle to meet federal emission standards on a gram per mile basis independent of fuel economy.7 Some research suggests that as vehicle emissions control systems age, there is a relationship between fuel economy and criteria pollutant emissions.8

Emissions from on-road vehicles were developed for this report using:

Emissions (pounds per day) = VMT x EF

where VMT = daily vehicle miles traveled (number of trips x trip length) and EF = emission factor (pounds per mile).

Daily VMT values used in this screening-level evaluation were obtained from the transit data generated for this report for passenger cars for all six scenarios. The VMT data was modified to reflect round trips. It is shown in Appendix D, Tables D-1 and D-4.

As noted above, the results of the screening-level evaluation were used to compare the proposed Lindbergh ITC (Scenario 5) with Scenario 3 (Preferred Alternative). These

4 Emissions estimates for these ozone precursors are used to develop the state and county ozone budgets. 5 See http://www.aqmd.gov/CEQA/handbook/onroad/onroad.html, accessed December 2007. 6 Air Resources Board, El Monte office, December 2007, personal contact. 7 National Research Council, Board on Energy and Environmental Systems, 2002, and U.S. DOT, National Highway Transportation Safety Administration, August, 2005. 8 See footnote 7.

http://www.aqmd.gov/CEQA/handbook/onroad/onroad.html

Chapter 3



results are not intended to provide a determination of conformity with federal or state air quality standards.

3.2.3. Results and Discussion Table 3-3 shows the relative changes in estimated emissions by criteria pollutant between Scenario 1 (2005 Baseline) and Scenario 2 (No Project @ 2030). This table provides a context for the comparison between the various ‘build-out’ scenarios in 2030. It shows that emissions of some criteria pollutants from airport-related passenger vehicles can be expected to decrease by 2030 (CO, NOx, and ROG), while emissions of SOx, PM10, and PM2.5 can be expected to increase without any project. The declines result from federal and state emission requirements. Calculations and assumptions are presented in Appendix D, along with the individual emission factors by year for each pollutant.

Table 3-3. Estimated Percent Change in Daily Criteria Pollutant Emissions from 2005 to 2030 with No Infrastructure Pollutant Changes (Scenario 1 versus

Scenario 2) Pollutant CO NOx ROG SOx PM10 PM2.5

% Change, Scenario 1 to Scenario

2 -56% -65% -44% 56% 79% 91%

Source: Malcolm Pirnie/SKM. See Appendix D, Table D-1 for calculations by pollutant.

Table 3-4 below compares the percent reduction anticipated for criteria pollutant emissions from airport-related ground transportation for Scenarios 3 to 5 and Scenario 2 (No Project Alternative @ 2030). These ‘build-out’ scenarios include the Lindbergh ITC (Scenario 5), Scenario 3 (Preferred Alternative) and Scenario 4 (Preferred Alternative with Airport Master Plan).

Table 3-4. Estimated Percent Change in Daily Criteria Pollutant Emissions - Passenger Cars

Scenario 1 2 3 4 5

Scenario Name

2005 Baseline

No Project Alternative

@ 2030 Preferred Alternative

Preferred Alternative w Airport

Master Plan

Lindbergh ITC

Year 2005 2030 2030 2030 2030 Assumed average daily VMT

1,132,440 1,769,337 1,769,337 1,735,523 1,596,914

% change from Scenario 2 (No Project Alt. @ 2030)

-0.0% -1.9% -9.7%

Source: Malcolm Pirnie/SKM. See Appendix D, Table D-2 for calculations by pollutant.



The assumed VMT in Table 3-4 is based on round trips for the daily “to airport” vehicle miles traveled in Chapter 2 and Appendix B of this report. The percent reduction in estimated emissions is the same for all criteria pollutants considered. Emissions reductions estimated for the Lindbergh ITC proposal (Scenario 5) are approximately 10 percent from the Scenario 2 (No project Alternative @ 2030). The estimated emissions reduction for Scenario 4 (Preferred Alternative with Airport Master Plan) is 1.9 percent for all criteria pollutants considered. The estimated percent reductions parallel what was observed in the greenhouse gas emissions estimates performed separately and presented in Section 3.1 of this report.

As noted above, changes in emissions between Scenario 1 (2005 Baseline) and Scenario 2 (No Project Alternative @ 2030) vary by pollutant. This means that the percentages also reflect a further reduction from 2005 emissions for CO, NOx, and ROG. By contrast, for SOx, PM10, and PM2.5, the percent change reflects a reduction in increased emissions. For example, Scenario 5 reflects a 9.7 percent reduction from the Scenario 2 (No Project Alternative @ 2030) values, which already represents a substantial reduction in CO, NOx, and ROG. The 9.7 percent change for the same scenario reflects a reduced increase in emissions of SOx (46 percent), PM10 (69 percent), and PM2.5 (81 percent) when compared to the percentages in Table 3-3. A small change in criteria pollutant emissions would be anticipated from implementation of Scenario 4 (Preferred Alternative with Airport Transit Plan).

In addition, the transit analysis presented in Chapter 2 indicates that VMT reductions (and, therefore, related emissions) would decrease most significantly in the residential neighborhoods and surface streets near the airport. From a qualitative perspective, the distribution of reduced VMTs suggests that residential exposure to air contaminants would also decrease in areas where VMTs are reduced. More detailed air quality modeling should be considered to verify results and identify geographic sensitivities or risks to public health.

In summary, this screening-level evaluation compares criteria pollutant emissions from airport-related passenger vehicles for the various ‘build-out’ scenarios. An estimated 8 percent reduction in criteria pollutant emissions could be achieved by implementing the Lindbergh ITC (Scenario 5) when compared to Scenario 2 (No Project Alternative @ 2030). By contrast, the reduction in criteria pollutant emissions predicted for implementation of Scenario 4 (Preferred Alternative with Airport Transit Plan) is 1.9 percent when compared to Scenario 2 (No Project Alternative @ 2030). The reductions approximate the percentages estimated for greenhouse gas emissions from airport-related ground transportation in presented in Section 4.1 of this chapter. Importantly, these criteria pollutant reductions would occur in areas where VMTs are reduced most, i.e., in residential and surface streets near the airport. Some of these changes in criteria pollutant emissions (CO, NOx, and ROG) also reflect a further reduction from estimated 2005

Chapter 3



emissions. On the basis of these comparisons, the increase of public transit mode share in the Lindbergh ITC scenario offer a greater reduction in these emissions than Scenario 4 (Preferred Alternative with Airport Transit Plan).


4. Sustainability and Green Airport and Green Building Opportunities for SDIA Expansion

This chapter reviews sustainability and green airport and green building concepts, including a review of experience at other major international airports, and discusses opportunities for their use with respect to the SDIA expansion alternatives. To meet the challenge of limiting or mitigating their impacts on the environment, airports have instituted a variety of sustainability measures. SDIA has adopted many active policies and programs to minimize its effects on air and water quality, wildlife, noise, energy consumption and waste materials (SDCRAA website www.san.org/Airport _Authority/; Manasjan 2006). We have made no attempt to directly evaluate these programs. However, several airports throughout the world have adopted sustainability programs that are recognized as valuable lessons to learn from, emulate as appropriate and improve upon. Therefore, this other information is presented as a benchmark for SDCRAA to consider in establishing its goals and evaluating its success.

This chapter is organized in four main parts. Section 4.1 provides background information on sustainability concepts which are applicable to the previous chapters and to green airport and green building concepts. Sections 4.2 and 4.3 briefly present the concept and framework of “green airport” and green buildings, respectively, and provide examples of the sustainability opportunities which may be worthy of additional consideration with respect to the expansion of the SDIA. Detailed background information on these is presented in Appendix E. Specific examples of the concepts presented in these sections are further documented in Appendix F. Section 4.4 briefly summarizes the sustainability opportunities for Scenario 2 (No Project Alternative @ 2030), Scenario 3 (Preferred Alternative), Scenario 4 (Preferred Alternative with Airport Transit Plan) and Scenario 5 (Lindbergh ITC).

4.1. Why Sustainability? There is no single universally accepted definition of what it means for a project, product, or activity to be sustainable. A widely accepted definition of sustainability is that provided by the Brundtland Commission (www.unece.org/oes/nutshell/2004-2005/focus_sustainable_development.htm) which defined sustainability as meeting the needs of the present society without compromising the ability of future generations to meet their needs. There are various other definitions but they all imply continuity – providing economic, environmental, and social benefits while eliminating (or at least minimizing) direct and indirect negative impacts. Therefore the pursuit of sustainability

http://www.san.org/Airport%20_Authority/

http://www.unece.org/oes/nutshell/2004-2005/focus_sustainable_development.htm

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Chapter 4 Sustainability and Green Airport and Green Building Opportunities for SDIA Expansion

needs to move beyond impact mitigation and address the key questions of “what is being sustained” and “for whom.” In doing so, project design considerations move beyond evaluating operational efficiency (traditionally a short term perspective) and move into the realm of effectiveness, ultimately creating enduring value, which is a longer term proposition.

There are many aspects one could consider when evaluating the sustainability of airport operations. In pursuit of sustainability the challenge is to reach an outcome that delivers value over both short-term and long-term timeframes. Clearly, economic, environmental and social concerns, coupled with political and technological ones, create multiple drivers of change that can affect this value. As noted by various airport managers, sustainability itself must also be cost-effective or it cannot be sustained (Hewitt 2007). Therefore the key attributes to pursue are:

Flexibility in maximizing opportunities over time;

Adaptability to changing regulatory, market, social and environmental conditions and technological opportunities; and

Longevity in considering the cost-value equation over the design life of SDIA to optimize resource use, recognize and internalize externalities and the capacity to meet projected growth in aviation demand.

The following provides an overview of the SDIA within its local, regional, national and global context and provides an overview of sustainability potential.

4.1.1. Local to Global Context The SDIA and SDCRAA operates within a social, political and economic framework that is inextricably linked to local communities, the region, and the state via the transportation services and associated economic benefits it provides, its nine-member board, its own codes, policies, programs and mission statements, and local and state laws (Figure 4-1).

As society adjusts to the implications of global climate change, all of its components are being called upon anew to address their sustainability and greenhouse gas emissions. These policies, programs, campaigns, regulations and laws are in an on-going state of development and adjustment. The City and County of San Diego, other regional entities

City of San Diego ‘Sustainable Community Program’ City of San Diego ‘Cities for Climate Protection Campaign’ City of San Diego ‘Climate Protection Action Plan’ San Diego Association of Governments (SANDAG)

‘Regional Comprehensive Plan’ SANDAG’s regional transportation plan ‘Mobility 2030’ Port of San Diego ‘Port Sustainability Program’ State of California AB 32 – Global Warming Solutions Act On-going national discussions that may result in some form of

federal greenhouse gas legislation Environmental Protection Agency - Potential regulation on

CO2 as pollutant Framework Convention on Climate Change - Bali California Attorney General and Port of Los Angeles

Memorandum of Understanding on Reducing Greenhouse Gases

SELECTION OF PROGRAMS, REGULATIONS AND LAWS

RELATED TO SUSTAINABILITY


Chapter 4Sustainability and Green Airport and

Green Building Opportunities for SDIA Expansion

and the State of California have been actively engaged in sustainability and greenhouse gas issues through a variety of initiatives (see Text Box). Many of these impact directly or indirectly on the SDIA, and conversely, many SDIA activities directly and indirectly impact these local, regional, state, federal and global processes.

Figure 4-1: Airport Sustainability and its Local to Global Context The upper level of this graphic shows the potential effects that an airport has with what can be called it direct environmental footprint, i.e., its energy use, waste streams, wildlife, air emissions, and water use and water discharge. However, as shown by the lower level an airport also has a wide variety of connections to the local, regional, national and global community. The graphic identifies some of the specific connections that SDIA can affect or that can, in turn, affect the SDIA.

4.1.2. Opportunities for Sustainability Implementing sustainability goals into daily activities increases the likelihood of mitigating and reducing adverse unintended consequences. The opportunities to deliver sustainability are greatest at the outset of a project (i.e., during the concept stage) and progressively decline through the following stages (Figure 4-2). If not incorporated early, the cost of future mitigation rises. Identification of sustainability goals after commitment of major financial resources generally will lead to significantly higher costs for mitigation or less effective avoidance of unintended consequences.




Figure 4-2: Relationship of Sustainable Design Value and the Cost of Impact Mitigation

Diagram showing how the greatest sustainable design value is obtained at the earliest stages in a project life cycle. Sustainable design value progressively declines the later it is addressed and the cost of impact mitigation progressively increases. A project life cycle progresses from concept, feasibility, detailed design, procurement, construction, and operations to decommissioning. The concept phase provides the greatest potential to deliver long-term sustainability. Source: Modified from Fleming (2007).

A good sustainability program must identify the values it seeks to sustain and the recipients of this value. Vehicle miles traveled, traffic congestion, greenhouse gas emissions and criteria pollutant reductions are the focus of our report even though these are but several of many potential sustainability criteria. Green airport and green building potentials are also addressed. The SDIA has a diverse set of on-going policies and programs underway to reduce its environmental footprint in many areas. These include storm water pollution prevention, hazardous waste and emergency response, air quality and industrial hygiene, environmental assessment and construction monitoring, site remediation, solid waste management and recycling, vector control, wildlife preservation, noise mitigation, water conservation, land use compatibility, and transport and roadway improvements (Figure 4-1; SDCRAA website www.san.org/Airport _Authority/; Manasjan 2006). We believe these as well as other elements are needed to create an effective sustainability program.

An organization’s environmental footprint can extend beyond its direct activities to influence the actions and consequences of its clients, its suppliers, and its community. This means that an organization needs to evaluate a “working boundary” for its planning process that is in sync with other organizations and entities it influences. In addition, costs and consequences can vary widely over time among alternative projects and actions. This in turn requires managers to establish a method to value present versus future costs and conditions. Together, these factors can make it difficult to frame the boundary of a sustainability analysis or program.

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4.2. Green Airport Concept and Framework Green airport practices benefit the environment by reducing the airport global environmental footprint, generate cost-savings to the airport through the use of renewable or more efficient power sources, and improve the community’s airport image as being environmentally-responsible. Sustainable initiatives at green airports address issues related to water quality, local air quality, greenhouse gas emissions, wetlands, noise and land use compatibility, recycling and waste management, wildlife, and sustainability and overall environmental management (Airports Council International (ACI), 2007a and c). The worldwide airport environmental initiatives tracker file prepared by ACI compiles and describes sustainability efforts conducted around the world. The tracker file current as of November 28, 2007, is included as Appendix F (ACI, 2007d). Over 70 initiatives are classified into nine categories:

Airfield emissions reductions

Intermodality and surface access

Recycling initiatives

“Smart” buildings and energy efficiency

Water pollution reduction

Winter services

Noise mitigation

Communications initiatives and airport-wide campaigns

Other environmental initiatives

The most pertinent to the present discussion are air emissions, intermodality and surface access, recycling initiatives, and some other environmental initiative examples. Specific examples are reviewed below.

Air emissions are addressed by initiatives such as using renewable energy sources and the use of alternative fuel or low emission vehicles, compressed natural gas vehicles, battery powered vehicles, and providing ground power and pre-conditioned air so that aircraft do not need to use their auxiliary power units. Vancouver International Airport in Canada uses solar panels to heat water and the Chicago and San Francisco International Airports produce electricity from solar panels. La Palma Airport in Spain generates the majority of its electricity from wind power generators. Auckland International Airport in New Zealand has a fuel reduction trial by allowing planes to have a glide descent profile with aircraft engines set at idle. Stockholm-Arlanda Airport has a similar aircraft coasting program from cruising altitude to the runway. As noted in the greenhouse gas discussion in Chapter 3, the use of ground power units (GPUs) to power the plane on the ground



minimizes the use of aviation fuel thereby reducing associated air emissions. Pre-conditioned air units may also work in tandem with GPUs. They provide automatically controlled air conditioning for ventilation, cooling, dehumidifying, filtering, and heating of air to parked aircraft. Dallas-Fort Worth International Airport has an energy plant upgrade with innovative technology that includes a large thermal energy tank and state-of-the art boilers and chillers which has projected high future energy reductions. The system also reduced NOx emissions by 95 percent. San Francisco International Airport has an aircraft towing trial with Virgin Atlantic, Boeing and the FAA. For the trial an aircraft was towed from the gate to near the runway providing substantial fuel and greenhouse gas emission savings.

Reducing airport-related traffic also reduces emissions. With respect to intermodality and surface access (i.e., getting to and from the airport) many airports have ambitious goals for public transit use. For example, Zurich Airport in Switzerland has 42 percent of persons reaching the airport via public transit. Madrid Spain’s airport expects a new subway terminal to be used by 20,000 people daily. Boston’s Logan Airport provides preferred parking to hybrid and alternative-fuel vehicles and hybrid taxis go to the head of the line twice during a 12-hour shift thereby promoting reduced greenhouse gas and criteria pollutant emissions. The “smart” buildings and energy efficiency category is also noteworthy as a growing and creative trend in airport development. Section 4.3 addresses this subject in detail.

Recycling initiatives continue a long history of working to improve use, reuse and recycling and there are many examples. At Seattle-Tacoma International Airport the recycling program increased their tonnage from 112 five years ago to 1,200 in 2007. Vendors also recycle their coffee grounds to a compost station. They now recycle 10 to 12 tons of coffee grounds per month. Seattle-Tacoma also has a program of providing left-over pre-packaged food to the cities needy. At Los Angeles International Airport food waste is used to produce methane gas which is recycled and turned into electricity. Athens International Airport in Greece recycles treated water from their sewage treatment plants and uses it for irrigation. The Canberra Airport in Australia implemented an Aquacell Water System to recycle 26,400 gallons of water across the airport daily. Oakland International Airport participated in a pillow recycling program so that rather than disposing of pillows in landfills they are used for insulation or in furniture. Portland International Airport also recycles its coffee and food waste but they also have a food grease recycling program where kitchen waste oils are collected and processed into biodiesel at an offsite facility. They also recycle foreign language periodicals from airlines for reuse in local schools.

With respect to other environmental programs Phoenix International Airport has participated in the testing of alternative pavements that are meant to reduce heat




adsorption. By reducing the amount of heat absorbed the amount of heat released is also reduced with the intent of reducing air temperatures (i.e., the urban heat island effect). Phoenix has also assisted in the design of concrete benches with crumb rubber that are both cooler and easier to move. The Hong Kong International Airport collaborated on a green roofing student competition intended to reduce building temperature and related air conditioning related energy use.

4.3. Green Buildings and the LEED System at Airports In the United States, buildings account for 65 percent of electricity consumption, 36 percent of energy use, 30 percent of greenhouse gas emissions, 30 percent of raw materials use, 30 percent of waste output (136 million tons annually), and 12 percent of potable water consumption (USGBC, 2007). These numbers should not be surprising considering that buildings include where we live and most of us work. However, because of their large environmental footprint, buildings provide a target where environmental improvements can have a large benefit.

In 2002, the United States Green Building Council (USGBC) defined the concept of “green building” as design and construction practices that significantly reduce or eliminate the negative impact of buildings on the environment and occupants. According to USGBC, the benefits of green buildings are three-fold: environmental, economic, and social. First, environmental benefits include the enhancement and protection of ecosystems and biodiversity, the improvement of air and water quality, the reduction of solid waste, and the conservation of natural resources. Second, economic benefits include the reduction of operating costs, the enhancement of asset value and profits, the improvement of employee productivity and satisfaction, and the optimization of life-cycle economic performance. Finally, the social benefits related to health and community include the improvement of air, thermal, and acoustic environments, the enhancement of occupant comfort and health, the minimization of strain on local infrastructure, and the contribution to overall quality of life.

The USGBC developed the Leadership in Energy and Environmental Design (LEED) green building rating system and certification process. LEED is a third party validation of achievement and LEED certification is a mark of recognition of quality buildings and environmental stewardship. The LEED Green Building Rating System is a nationally-accepted benchmark for the design, construction, and operation of high performance green buildings and it has standards for specific building types or uses (e.g., health care, office, schools, laboratory and retail). Various aspects of buildings, including design, materials, and water and energy efficiency, are assigned points related to specific performance criteria. Details of the rating system, performance criteria, different certification levels and other details are provided in Appendix E.



4.3.1. LEED-Certified and LEED-Registered Projects Related to Airports and Transit Centers

There are no explicit standards for airports or transit centers in the LEED system. Nonetheless some airports and transit centers have achieved LEED certification or registration for some buildings. Results of a search of LEED-certified and LEED-registered projects related to airports and transit centers are summarized below and included in Appendix F. To date, only five buildings related to airports and transit centers are LEED-certified. They are:

One airport terminal (Logan International Airport-Delta Terminal A Redevelopment) is LEED-certified at the certified level;

Two transit centers are LEED-certified at the certified level (Interurban Transit Partnership, Grand Rapids, Michigan and Salt Lake City Intermodal Passenger Hub, Salt Lake City, Utah);

One transit center is LEED-certified at the gold level (Colorado State University Transit Center, Fort Collins, Colorado); and

One radar control building is LEED-certified at the gold level (Seattle Terminal Radar Approach Control, Burien, Washington).

LEED-registered projects show a total of 19 projects. The results include all types of buildings at airports and transit centers, except for administration buildings. Out of these 19 projects, six buildings are terminals; six buildings are transit centers; four buildings are other types of buildings, such as maintenance facilities or operations facilities; and no additional information was available to determine the nature of the remaining three projects.

These examples of LEED-certified and LEED-registered buildings demonstrate that these standards can be met by airport buildings even though there are currently no specific criteria for airport or transit centers.

4.4. Sustainability Opportunities for SDIA Expansion Alternatives

This section addresses the sustainability opportunities for Scenario 2 (No Project Alternative @2030), Scenario 3 (Preferred Alternative), and Scenario 4 (Preferred Alternative with Airport Transit Plan) and Scenario 5 (Lindbergh ITC). Table 4-1 summarizes the conclusions presented in this section.




Table 4-1. Comparison of Sustainability Opportunities for Alternatives

Sustainability Opportunities

Scenario 2 (No Project Alternative @ 2030)

Scenarios 3 & 4 (Preferred Alternative

without and with Airport Transit Plan)


Operational + ++ +++

Structural (New Building)

- + +++

Overall Sustainability Lowest Increased Highest

4.4.1. Scenario 2 (No Project Alternative @ 2030) Under Scenario 2, the physical structures (e.g., terminals, runways, and other airport buildings and infrastructures) and access to SDIA will remain unchanged. This alternative provides the least sustainability opportunities for SDIA. While retrofitting of structures and infrastructures is an option, many potential projects may not be cost-effective on their own. Thus, unless major building renovations occur, there are fewest structural and infrastructural opportunities for this alternative. However, some sustainability opportunities for this scenario may exist in airport operations. Such opportunities will include the implementation or modification of some operational programs, for example:

Controlling or reducing air emissions by targeting landside vehicles, ground support equipment, aircrafts, auxiliary power units on aircrafts, electric power consumption associated with airport operation, alternative electricity supply, emissions shifting and time of day controls (CPA, 2002); and

Continuing to improve energy efficiency including buying green power and using renewable energy sources or biofuels.

4.4.2. Scenario 3 (Preferred Alternative) and Scenario 4 (Preferred Alternative with Airport Transit Plan)

Under Scenario 3 and Scenario 4 the SDIA footprint will remain very similar to present. There will be an addition to Terminal Two West, new general aviation facilities including access and hangers, and a new parking structure as well as the demolishing of the existing general aviation facilities. The rest of the airport buildings and infrastructures will remain unchanged. Similar to the No Project Alternative, many potential projects associated with retrofitting of existing structures and infrastructures may not be cost-effective unless major renovations occur. In addition, the opportunities listed for Scenario 2 can also be applied to Scenario 3 and Scenario 4. However, in addition to sustainable airport operational options described above for the No Project Alternative, this scenario also offers some additional sustainability opportunities in the new building additions and reconstruction, for example:



Design and integration of energy efficient building systems and green components in new buildings;

Re-use and recycle of materials from the demolished buildings for the construction of new buildings;

Installation of solar panels on existing buildings and on new buildings; and

Updating electrical systems with automatic on-off sensors.

Indeed, as mentioned in Section 6.1 – Significant Irreversible Environmental Changes of the SDIA DEIR, implementation of the Proposed Project will address high standards of efficiency and environmental design, consistent with LEED standards to reduce the use of renewable and nonrenewable resources. The two examples listed in the DEIR include the re-use of asphalt and concrete in new airfield aprons and taxiways, and the use of windows and window treatment in terminals to conserve energy. Although the DEIR mentions that the Preferred Alternative will follow LEED standards, it does not explicitly commit to LEED certification of any new buildings or terminals.

4.4.3. Scenario 5 (Lindbergh ITC) In this scenario there would be a complete redesign of the existing airport terminals as well as the development of the Lindbergh ITC. The airport terminals would be moved from the south side to the north side of the runway. Because the Lindbergh ITC scenario involves such a complete redesign of the airport there are substantial opportunities to include sustainable options into the new design and to streamline operational effectiveness from both a sustainability perspective such as energy efficiency and for overall employee and passenger ease. As noted in Section 4.1.2 the greatest opportunity to deliver sustainability is during the concept phase of a project. Consequently, this alternative is very different than Scenarios 2, 3 and 4.

While there are substantial sustainability benefits associated with this alternative, the current analysis does not include cost-benefit analysis which is a component of sustainability. Implementation of the Lindbergh ITC and use of any specific design, green building or operational efficiencies would need to be carefully evaluated and financing secured. However, in addition to the traffic, air quality and greenhouse gas benefits which are presented in Chapters 2 and 3, the redesign and rebuilding of the airport does provide substantial opportunity for incorporating highly sustainable LEED components strategies into their physical structure. These new terminals would provide the potential for a substantial increase in overall sustainable components compared to the current terminals. In addition, LEED components could be incorporated into the Lindbergh ITC itself making it a sustainable structure and contributing to an overall reduced airport carbon footprint and the potential to evaluate features such as construction of gray water lines and recycled water lines. Quantifying the actual net




reduction for the airport terminals would require a detailed design and accounting for them minus the footprint of demolition and recycling of the current infrastructure compared to the airport as it currently exists as well as to the developing plans for implementing the LEED program standards at the existing airport (Scenario 3 and Scenario 4).

Some of the green airport and green building opportunities are:

Re-use and recycle materials from the demolished buildings;

Incorporate LEED standards into the design, construction and operation to the maximum feasible extent;

Use the most energy efficient windows available;

Install solar panels on the Lindbergh ITC roof;

Install solar panels on the new airport terminal roof;

Use solar tubes to increase internal natural lighting during daylight hours and reducing electrical use;

Use the most up-to-date and energy efficient lighting systems and lights including automatic sensors;

Create green roofs on the new airport terminal and Lindbergh ITC that minimize their heat absorption characteristics thereby minimizing heat island effects;

Create rainwater collection systems on the airport and Lindbergh ITC roofs designed to allow reuse for landscaping irrigation or similar purposes;

Recycled water lines for airport landscaping; aned

Integrated food handling and recycling with the potential for on-site composting for use with airport landscaping.

In addition starting with a new footprint would allow numerous operational efficiencies to be incorporated which would have both positive sustainability effects and improved efficiencies for employees and airport customers contributing to an overall increase in satisfaction. For example, there would be opportunities for:

Newly designed traveler check in and security queuing areas providing efficiencies to airlines, Transportation Security Administration, and travelers;

More efficiency for caterers and their access to planes;

Increased efficiency in baggage handling providing convenience for travelers and potential savings to airlines;

An underground fuel hydrant system to reduce the use of fuel trucks; and



Increased cooperation and planning with airlines by designing the new airport to include developing technologies that assist in reducing the airside impacts associated with airlines, e.g., towing planes to the runway, using landside plug-ins so that airplane auxiliary power units do not need to power air conditioning and other plane electrical needs while at the gate.

Instituting a ground-level up integrated system that enhances operational efficiencies through infrastructure, siting/location, staff allocation, and communication systems has the potential for other non-obvious synergistic improvements.


5. Summary and Discussion

Although there are many potential sustainability goals and indicators associated with SDIA and the San Diego community, one goal which the community is required to address is the reduction of greenhouse gas emissions in order to reduce the potential impacts from climate change. California AB 32 requires an overall reduction in greenhouse gas emissions to 1990 levels (approximately a 25 percent reduction) by 2020. Additional local, state, federal, international, and market-driven drivers for reducing greenhouse gas emissions exist or emerge almost daily.

Transportation is a significant source of greenhouse gas emissions which contributes to global climate change. For example, the City of San Diego reported that in 2004 the transportation sector contributed 7.9 million tons of greenhouse gas emissions tons per year (approximately 21.5 thousand tons per day; City of San Diego, no date). This was equivalent to more than 50 percent of the community’s projected total greenhouse gas emissions. San Diego also has the worst traffic congestion of all medium sized cities which further exacerbates greenhouse gas emissions. The high proportion of San Diego, California and U.S. emissions that come from the transportation sector, added to projections for significant increased transportation needs which in turn are projected to yield further increases in emissions, make the probability of new restrictive policies and regulations on this sector significant. Indeed, implementation of California AB 1493 (which is in dispute with the EPA) and on-going development of other California initiatives, including those related to AB 32, are the beginning of a significant trend.

As a society, Americans enjoy the opportunity to travel freely and we exercise that right more every year. The draft Airport Master Plan for SDIA projects an increase in demand for air travel of approximately 60 percent by 2030, and the actual growth rate the past several years has exceeded annual projections. Results from our study project show that air passengers and airport employees will increase travel to and from SDIA by 57 percent, or 250 million miles annually in 2030 compared to 2005 levels under the No Project Scenario. Results from this study demonstrate substantial benefits associated with requirements to improve new vehicle fuel efficiency. Both past (1990 to 2004) and predicted (2005 to 2030) data indicates that the increase in fuel economy in vehicles will slow the rate of increase in greenhouse gas emissions. However, at the levels being required in the new regulations, they will not be adequate to maintain, let alone reduce greenhouse gas emissions if the level of increased transportation demand increases as projected unless radical new technologies, policies, transportation alternatives, or behaviors are developed.

Chapter 5 Summary and Discussions


Given the significant increase in projected demand for air travel at SDIA, the existing impact of airport related travel on traffic congestion on streets around the SDIA, and the contribution of the transportation sector to greenhouse gas emissions, this report focused on a comparison of the sustainability associated with ground transportation of airport passengers and employees. It evaluated the No Project and Preferred Alternatives from the Airport Master Plan DEIR, as well as the CAIVP proposed Lindbergh Intermodal Transportation Center. Similar to the DEIR Master Plan, emissions from actual air travel were not included in this study due to complexity and federal regulation of air travel.

The major sustainability components evaluated in this report include:



Changes in road traffic congestion (level of service) on the streets around the SDIA;

Impact of passenger and airport worker travel changes on greenhouse gas emissions; and

Impact of passenger and airport worker travel changes on air quality (criteria pollutants);

Other positive sustainability components resulted from the above and these were also identified, including lessons learned from a qualitative review of the experience at other international airports to implement “green airport” practices. We acknowledge the value of existing SDIA efforts to reduce its environmental footprint by minimizing its effects on air and water quality, wildlife, noise, energy consumption, and waste materials. The exclusion of these SDIA programs from our study is not intended as a judgment of the value of these programs.

A summary and comparison of the No Project Alternative, the DEIR Master Plan Preferred Alternative with Airport Master Plan and the Lindbergh ITC at 2030 with respect to various sustainability indicators is provided in Table 5-1.

Chapter 5

Summary and Discussion


Table 5-1.Sustainability Components Summary for Scenarios 2, 4 and 6

Sustainability Indicator

Scenario 2 (No Project @ 2030)

Scenario 4 (Preferred Alternative with Airport Transit Plan @ 2030)

Scenarios 5 (Lindbergh ITC @ 2030)

1. Transit Mode Share 1.3% (Baseline)

2.6-3.0% 4.0-5.2%

2. Daily Average Vehicle Miles Traveled

57% increase over 2005 Baseline

1.6-1.9% reduction from No Project at 2030

9.0-9.8% reduction from No Project @ 2030

3. Annual VMT 690 million 11.1 million less than No Project @ 2030

61.7 million less than No Project @ 2030

4. Traffic Congestion in Airport Vicinity

Reduced Levels of Service from 2005

Baseline

Similar to Scenario 2 Improved Levels of Service on Rosecrans, India, Kettner, Grape,

Hawthorne, Washington, Hancock

5. Traffic Congestion Beyond Airport

Level of Service decreases notably

Level of Service decreases but slightly

better than 2005 Baseline

Generally improved Levels of Service

compared to Scenarios 2 and 3

6. Greenhouse Gas Emissions from Airport Related Passenger Vehicles (CO2e)

22.6% increase over 2005 Baseline

< 1% reduction from Scenario 2

> 9% reduction from Scenario 2

7. Criteria Air Pollutants from Airport Related Passenger Vehicles

CO -56% NOx -65% ROG -44% SOx +56% PM10 +79% PM2.5 +91%

< 1.9% reduction in all pollutants from

Scenario 2

9.7% reduction in all pollutants from

Scenario 2

8. Opportunity to Increase Efficiency of Regional Transit

Baseline Modest Increase Most Significant

9. Opportunity for Incorporating Green Building Design

Minimal except for occasional renovation

Good on expanded Terminal 2 West and new general aviation

facilities. Implementation of

LEED certification for new and existing

buildings would reduce environmental footprint.

Substantial opportunity for reduced

environmental footprint from operation. One-time costs associated

with expanded demolition and

construction exist but not quantified.

10. Opportunity for Sustainability Improvements from Operational Efficiency

Baseline Some improvement over No Project

Alternative

Potentially substantial if incorporated in new

terminal and ITC design

Chapter 5 Summary and Discussions The DEIR Master Plan Preferred Alternative, with the Airport Master Plan provided small reductions in daily average VMT (1.6-1.9 percent) and greenhouse gas emissions (0.9 percent) at 2030 compared to the No Project Alternative at 2030 (Figures 5-1 and 5-2). The DEIR references the draft Airport Transit Plan as to how it will mitigate increased traffic and possible congestion by identifying measures to increase transit mode share. The draft Airport Transit Plan includes a variety of measures that, when implemented, have an aspirational goal of increasing transit mode share from 1.2 percent to 4-6 percent over the next 3-5 years. The modeling results from our study suggested that the mode shares indicated in the Transit Plan will only be in the range of 2.6-3.0 percent without additional incentives or influences (whether intentional or from external influences outside the control of the SDCRAA). For example, our results predicted a mode share for the Old Town Shuttle Bus Service and the Coaster Service measures that were approximately 20-30 percent of that included in the draft Airport Transit Plan and that modeled increases in mode share were predominantly in bus use. Consequently, the ability of the Preferred Alternative with the Airport Transit Plan to provide significant reductions in greenhouse gas emissions, average daily VMT, and traffic congestion appears low.

Figure 5-1: Additional Average Daily Vehicle Miles Traveled in 2030

Compared to the 2005 Baseline.


1,600,000

1,650,000

1,700,000

1,750,000

1,800,000

1,850,000

1,900,000

1,950,000

Scenario 2 (No Project@ 2030)

Scenario 3 (PreferredAlternative)

Scenario 4 (PreferredAlternative w Airport

Transit Plan)

Scenario 5 (LindberghITC)

Mile

s

Conservative AssumptionsOptimistic Assumptions

Chapter 5

Summary and Discussion Figure 5-2: Greenhouse Gas Emissions Percent Change from Scenarios 2

ives for the proposed Mas

(No Project @ 2030)

SDCRAA identified three object ter Plan:

hrough 2015 while t

2. facilities that effectively utilize the current airport property and facilities and

3. land use planning.

rport Master

the

t and Preferred Alternatives (including

the

-10-9-8-7-6-5-4-3-2-10

Scenario 3 (Preferred Alternative)Scenario 4 (Preferred Alt w Airport

Transit Plan) Scenario 5 (Lindbergh ITC)

Per

cent

Cha

nge

0

-1.9

-9

1. Provide adequate facilities to accommodate air service demand timproving airport levels of service, airport safety and security, and enhancing airporaccess;

Develop are compatible with surrounding land uses; and

Provide for future public transit options in airport

Our modeling results suggest that the DEIR Preferred Alternative with AiPlan does not effectively address “enhancing airport access” criteria under the first objective above. In addition, the DEIR Preferred Alternative may limit, rather than promote, future public transit options because high capital costs for Terminal Two expansion and parking may preclude other options not rigorously investigated given constraints associated with the second objective.

In comparison to the DEIR Master Plan No Projecwith Airport Transit Plan), the Lindbergh ITC provided substantial progress towards the sustainability indicators (Table 5-1). Based on our quantitative transportation modeling (which reflects the effect of travel times, costs, and other factors on traveler’s transportation decisions) the only scenarios that substantially increased public transit ridership (Figure 5-3) and reduced the rate of increase in average daily vehicle miles traveled (Figure 5-1) was the Lindbergh ITC scenario. The increase in transit use andreduction of trip length by providing direct access to the airport terminal from I-5 resulted in a reduction of 139 thousand average daily vehicle miles (or more than 50 million annual miles) traveled by airport passengers and employees compared to the Preferred Alternative with Airport Master Plan (Figure 5-1).


Chapter 5 Summary and Discussions The increased public transit use, reduced VMT, and placement of the airline terminals close to I-5 also result in substantially reduced traffic congestion (i.e., improved levels of service) on the streets in the neighborhoods surrounding SDIA for the Lindbergh ITC compared to DEIR Preferred Alternative without requiring mitigation measures such as the removal of on street parking and increasing the number of lanes. Details are shown in Figures 2-10, 2-11 and 2-12 in Chapter 2 Transportation Analysis. Specifically, the level of service on Rosecrans and Laurel Streets would improve to acceptable levels with the Lindbergh ITC in place. Hawthorn Street would experience improvements on particular segments and improvements are also projected on a number of other streets, particularly India, Kettner, Grape, Washington, and Hancock. Our modeling also shows that criteria pollutants are reduced approximately in proportion to the VMT so that they are reduced approximately 9.7 percent with the Lindberg ITC versus 1.9 percent for the Preferred Alternative with Airport Master Plan. Much of this reduction would be expected in the

Figure 5-3: Proportion of Passengers and Employees Using Transit

0

1

2

3

4

5

6

Con

serv

ativ

e

Opt

imis

tic

Con

serv

ativ

e

Opt

imis

tic

Con

serv

ativ

e

Opt

imis

tic

Con

serv

ativ

e

Opt

imis

tic

Con

serv

ativ

e

Opt

imis

tic


Scenario 2 (NoProject @ 2030)

Scenario 3(PreferredAlternative)



Scenario 5(Lindbergh ITC)

Per

cent

FlyAwayCoasterTrolleyBus

vicinity of the airport as a result of the reduced traffic congestion. The combination of reduced criteria pollutants, increased transit use, the redirection of airport related traffic, and less traffic congestion would all contribute to an overall enhanced quality of life in the area. Under the DEIR Preferred Alternative potential mitigation to improve LOS to acceptable levels on these streets includes road widening, removing on street parking, increasing the number of lanes and intersection improvements. If implemented such measures could improve LOS but they do not improve VMT and thus maintain the traffic increase on streets adjacent to the airport making access for residents and local businesses more difficult. The measures do not reduce local criteria pollutants or overall greenhouse gases.


Chapter 5

Summary and Discussion


The Lindbergh ITC provided the most benefits for reducing the rate of growth in greenhouse gas emissions. Specifically, the Lindbergh ITC resulted in an 8.4 percent reduction in greenhouse gases compared to Scenario 4 (Preferred Alternative with Airport Master Plan) or 9.2 percent less than Scenario 2 (No Project @ 2030) and Scenario 3 (Preferred Alternative) (Figure 5-2). However, while there are percent reductions from Scenario 2 there is still an overall substantial growth in the absolute amount of greenhouse gas emissions. The Lindbergh ITC would still have a 54 metric tons per day increase over 2005 Baseline. Thus, the ITC by itself was insufficient to make sufficient reductions in VMT to reach even short-term goals for greenhouse gas reductions if goals were uniformly applied across each segment of society. However, the estimated 8 percent reduction of greenhouse gas emissions in the Lindbergh ITC scenario could form an important component of an overall plan to decrease greenhouse gas emissions associated with the SDIA.

Since the Lindbergh ITC proposal is essentially the development of a new airport terminal it provides the maximum ability to incorporate the newest efficiencies and most effective sustainable design concepts of the alternatives evaluated. In addition, using the most energy efficient materials and systems would enhance overall sustainability. The design of new terminal and associated ITC also provides the opportunity for a variety of operational efficiencies.

This study is not a comprehensive evaluation of the sustainability of airport expansion alternatives. Modeling results are suitable for an initial high-level comparison of alternatives, but there are elements of a complete evaluation that were beyond the scope of this study. We have conducted a preliminary evaluation of a concept rather than a full evaluation and comparison of detailed plans. Our study does not include a detailed environmental assessment, cost benefit comparisons of the scenarios, nor an evaluation of other approaches to reduce traffic congestion and emissions. We have limited our analysis to the increase in public transit ridership, changes in VMT and levels of service, greenhouse gas emissions, criteria pollutants and other sustainability components which result from the above. The consideration of other sustainability criteria and how they may influence airport expansion is warranted given the significant capital costs for the project. However, the demonstrated improvements associated with the Lindbergh ITC indicate that it merits further detailed public consideration.

Chapter 5 Summary and Discussions




6. References

Airports Council International. 2007a. Airports and the Environment. March. http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/position%20brief_ENVIRONMENT.pdf

Airports Council International. 2007b. Climate Change. May.

http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/position%20brief_CLIMATECHANGE2.pdf

Airports Council International. 2007c. Going Green. November. http://www.aci-na.org/docs/Going%20Green%209-7-07.pdf Airports Council International. 2007d. Worldwide airport environmental initiatives

tracker file. November. http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/TRACKER%20FILE_Airport%20environment%20initiatives.pdf

APTA (2007) Light Rail Transit Ridership Report - Third Quarter 2007, American Public

Transportation Association. California Energy Commission. 2006. Inventory of California greenhouse gas emissions

and sinks: 1990 to 2004. CEC-600-2006-013-SF. 117 pp.

Cambridge Systematics. 2007. Bay Area/California High-Speed Rail Ridership and Revenue Forecasting Study. Prepared for Metropolitan Transportation Commission and the California High-Speed Rail Authority.

City of San Diego. No date. San Diego Greenhouse Gas Emission Inventory.

(www.sandiego.gov/environmental-services/sustainable/pdf/ghginventory.pdf)

Clean Airport Partnership, Inc. Green Airport Initiative. http://www.cleanairports.com/reports/GAI.pdf

Clean Airport Partnership, Inc. 2002. Dallas Fort Worth International: Building a Model

Green Airport. April. http://www.cleanairports.com/reports/gai_dfwforweb.pdf Clean Airport Partnership, Inc. 2003. Executive Summary: The Green Airport Initiative

at Fort Lauderdale-Hollywood International Airport. August. http://www.cleanairports.com/reports/gai_fllforweb.pdf

http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/position%20brief_ENVIRONMENT.pdf

http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/position%20brief_ENVIRONMENT.pdf



http://www.aci-na.org/docs/Going%20Green%209-7-07.pdf

http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/TRACKER%20FILE_Airport%20environment%20initiatives.pdf

http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/TRACKER%20FILE_Airport%20environment%20initiatives.pdf

http://www.cleanairports.com/reports/GAI.pdf

http://www.cleanairports.com/reports/gai_dfwforweb.pdf

http://www.cleanairports.com/reports/gai_fllforweb.pdf

Chapter 6 References


Davis Langdon. 2004. Costing Green: A comprehensive cost database and budgeting methodology. Lisa Fay Matthiesen and Peter Morris. July.

Davis Langdon. 2007. Cost of Green Revisited: Reexamining the feasibility and cost

impact of sustainable design in the light of increased market adoption. Lisa Fay Matthiesen and Peter Morris. July.

Dowling Associates, Inc. 2002. San Jose International Airport Transit Connection

Ridership. Prepared for San Jose International Airport, Lea Elliott and Walker Parking.

FAA (2005) Aviation & Emissions - A Primer, Washington, DC.

(www.faa.gov/regulations_policies/policy_guidance/envir_policy/media/AEPRIMER.pdf)

Fleming, N. 2007. Creating a world of difference, Part 2, Delivering enduring value. Prepared by Sinclair Knight Merz.

Gupta, S., Vovsha, P. and Donnelly, R. 2007. A Model for Joint Choice of Airport and

Ground Access Mode. 11th National Transportation Planning Applications Conference, Transportation Research Board.

Harvey, G. 1987. Airport choice in a multiple airport region. Transportation Research,

A21(6), pp. 439-449. Hess, S., and Polak, J.W. 2005. Mixed Logit Modeling of Airport Choice in Multi-airport

Regions. Journal of Air Transport Management, 11 (2), pp.59-68. Hewitt, W.F. 2007. Airports and airlines are going green. Planning. November 2007, pp.

22-25. HNTB. 2007. Airport Transit Plan – San Diego International Airport. Prepared for

Airport Transit/Roadway Committee; Sponsored by San Diego County Regional Airport Authority. November 2007.

HR&A (2006) 2005-2035 Airport Economic Analysis, Draft prepared for San Diego

County Regional Airport Authority. Leigh River Associates, M.A. Coogan, and MarketSense. 2002. Strategies for improving

public transportation access to large airports. TCRP Report 83, Transportation Research Board, Washington, D.C.

http://www.faa.gov/regulations_policies/policy_guidance/envir_policy/media/AEPRIMER.pdf

http://www.faa.gov/regulations_policies/policy_guidance/envir_policy/media/AEPRIMER.pdf

Chapter 6

References


Manasjan, P. 2006. San Diego International Airport: tracking our environmental footprint. Presented at the California Integrated Waste Management Board/Local Enforcement Agencies Annual Conference, August 1, 2006. http://www.ciwmb.ca.gov/Part2000/Events/06Conf/Presentation/Day1/Keynote.pdf

National Research Council, Board on Energy and Environmental Systems, Effectiveness

and Impact of Corporate Average Fuel Economy (CAFE) Standards, National Academy Press, 2002. http://www.nap.edu/openbook.php?record_id=10172 &page=R1, accessed December 2007.

SANDAG. 2004. 2030 Regional Growth Forecast. SANDAG SourcePoint, June 2004,

No. 4, 8 pp. San Diego County Regional Airport Authority. 2007. Airport Master Plan – San Diego

International Airport – Draft Environmental Impact Report. October 2007. Schrank, D and T. Lomax. 2007. The 2007 urban mobility report. Texas Transportation

Institute, Texas A&M University. SH&E, Inc. 2004. San Diego Airport Aviation Activity Forecasts. Prepared for San

Diego Regional Airport Authority. June 2004. U.S. Department of Transportation, National Highway Transportation Safety

Administration, "Draft Environmental Assessment, Proposed Corporate Average Fuel Economy Standards", August 2005. http://www.nhtsa.dot.gov/cars/rules/rulings/LightTrucksRuling-2008-2001/Assessment/index.html, accessed December 2007.

United States Green Building Council. 2006. LEED for New Construction Version 2.2.

November United States Green Building Council. 2007. Website. http://www.usgbc.org/ URS (2003). Central Interstate 5 Corridor Study. Prepared for SANDAG. WRI (2005) Navigating the Numbers - Greenhouse Gas Data and International Climate

Policy. World Resources Institute, Washington, DC. (http://pdf.wri.org/navigating_numbers.pdf)

WRI (2008) Climate Analysis Indicators Tool (CAIT US) Version 2.0. World Resources Institute, Washington, DC. (http://cait.wri.org/)

http://www.ciwmb.ca.gov/Part2000/Events/06Conf/Presentation/Day1/Keynote.pdf

http://www.ciwmb.ca.gov/Part2000/Events/06Conf/Presentation/Day1/Keynote.pdf

http://www.nap.edu/openbook.php?record_id=10172%20&page=R1

http://www.nap.edu/openbook.php?record_id=10172%20&page=R1

http://www.nhtsa.dot.gov/cars/rules/rulings/LightTrucksRuling-2008-2001/Assessment/index.html

http://www.nhtsa.dot.gov/cars/rules/rulings/LightTrucksRuling-2008-2001/Assessment/index.html

http://www.usgbc.org/

http://pdf.wri.org/navigating_numbers.pdf

http://cait.wri.org/

Chapter 6 References


Zweig White, 2004. Architecture, Engineering, and Construction (AEC) Industry Outlook. Strategy & Insight for Design and Construction Firms. November 2004.

Websites: Airport Cooperative Research Program. www.trb.org/news/blurb_detail.asp?ID=575 Airports Council International. www.airports.org/ California Independent Voter Project. www.caivp.org/index.html Clean Airport Partnership, Inc. www.cleanairports.com/ Green Skies. www.greenskies.org/ San Diego County Regional Airport Authority.

www.san.org/Airport_Authority/splash.asp

http://www.caivp.org/index.html

http://www.san.org/Airport_Authority/splash.asp

San Diego International Airport Expansion Sustainability Analysis

Appendix A - Case Studies

6189001

San Diego International Airport Expansion: Sustainability Analysis A-1

Appendix A - Case Studies

For purposes of comparison, five U.S. airports with transit connections were compared to SDIA. These airports vary widely in context – from large cities with major airports such as Chicago O’Hare to cities smaller than San Diego such as Portland. The key characteristics of the cities, airports and transit links are summarized in Table A-1.

Table A-1.Case Study Airports - Comparative Data Airport

Designator SAN SFO OAK PDX ORD STL

City San Diego San Francisco Oakland Portland Chicago St Louis

Annual passengers

- Total (million) 17.4 34.3 14.4 14.0 76.2 15.2

- O&D (million) 16.7 25.1 13.2 10.9 33.2 10.4

Purpose split (business) 45% 23% 28% n.a. n.a. n.a.

Distance to downtown (miles) 3.3 14.0 9.9 12.3 17.0 15.1

Proportion of residents 60% 56% 58% 40% 35% -

City characteristics

2005 population (million) 1.26 1.22 1.46 0.54 9.50 2.80

Popul’n density (persons/mi2) 668 1,976 1,549 359 1,619 410

Rail

Number of rail lines 3 n.a. 4 3 8 2

Track per 100,000 people 4.06 miles n.a. 6.65 miles 8.17 miles 3.69 miles 1.64 miles

Stations per 100,000 people 4.21 n.a. 1.99 11.9 5.01 1.32

Dedicated No n.a. No No No No

Ground transportation between downtown and airport

Taxi fare $11 $30-45 $20 $27-32 $35-40 $35

Shared van fare $11 $16 $17 $20 $25 $15

Journey time (car/taxi) 10-20 24-40 17-30 20 30-70 22

Public transit

Rail - type - Heavy Heavy Light Heavy Light

- fare - $5.15 $4.40 $2.05 $2.00 $3.50

- journey time (mins)

- 31 33 30 42 31

- headway (mins) - 20 15 15 7 10

- mode share - 6.3%1 8.0%2 6.7%3 4.0%4 5%5

Bus - fare $2.25 $4.00 $1.75 - $25 -

- journey time (mins)

16 35 15 - 40-80 -

- headway (mins) 12 30 15 - 5-10 -

- mode share 1.4% n.a. n.a. - n.a. -

Appendix A Case Studies Notes: Dedicated bus feeder to rail station 1. Percentage of average access/egress at SFO over nine months to March 2004. These values are total percentages (i.e., include air

passenger, airport employees, and “others” who use BART to get to and from SFO). 2. Passenger survey response, Oakland International Airport, 2002 3. Percentage of average access/egress at PDX over 22 months to November 2003. These values are total percentages. 4. Percentage mode shares, data from 1998 reported in TCRP, 2000 5. Passenger survey response, 2002

Comments on each airport, compared with San Diego, are made in the following paragraphs.

San Francisco, CA (SFO)

Context

SFO is the second largest airport in California after LAX. Its geographical location makes it a significant hub for international flights on the western seaboard and for connecting flights within the USA. As such, the airport operates with a high proportion of transfer/transit passengers relative to other ports of a comparable size.

As one of three airports in the Bay Area, SFO faces competition from Oakland International (OAK) and Mineta San Jose International (SJO), particularly in the low cost domestic airline market. This has impacted traffic in recent years; however positive growth in this market is expected from FY2008 as low cost carriers increase services from SFO. In comparison to San Diego, San Francisco Airport handles a greater proportion of international, non-business and connecting passengers.

The city of San Francisco is a fairly densely populated city of 740,000 with a wider metropolitan population of 1.22 million along the peninsula. BART (Figure A-1) is a metro rail system servicing the needs of Bay Area residents. It traverses the city and county of San Francisco along one corridor only, with limited connections to the MUNI Metro light rail system.

The airport is accessible by an adjacent freeway and by rail, integrated within the BART system. A dedicated BART station is located within the international terminal. The BART line extension connecting the airport, San Francisco and the greater Bay Area was opened in 2003.

San Diego is one third the population density of San Francisco, adversely affecting the ability of transit to conveniently serve a large proportion of the population. The

A-2 San Diego International Airport Expansion: Sustainability Analysis

Appendix A

Case Studies accessibility of San Diego airport, located only three miles from the downtown, somewhat differs from San Francisco, however each lies adjacent to major arterials.

Figure A-1: BART Rail Transit Network in the Bay Area

Source: Bay Area Rapid Transit

Success Factors

The city of San Francisco has a relatively high level of public transit usage by North American standards, at approximately 17 percent of trips. The density of the city, concentration of economic activity in the downtown area and a robust public transport network are contributing factors.

The expansion of the BART system to SFO was coupled with ridership estimates that have proven to be optimistic. In 2005 there were 7,116 daily boardings compared with the 2010 forecast of 17,800. Though ridership from the airport has been somewhat lower than predicted, it has been the much lower ridership from other travelers along the corridor that has hurt the forecasts the most. The line has been a significant dampener on the profitability of the BART system.

:San Diego International Airport Expansion: Sustainability Analysis

A-3

Appendix A Case Studies The current patronage levels from the airport link may be attributed to several factors:

Ease of accessibility to freeways and the small differential in mode journey times limits the system’s attractiveness.

The limited corridor through which BART connects to San Francisco; connections to other modes of transit are required from the single line if not within close proximity to the station.

The spread of stations per capita is low reflecting relatively poor geographical distribution of BART access.

Recent downward trend in traffic of low cost carriers into SFO may affect public transport patronage from price sensitive air travelers.

Low service frequency and non-dedicated rolling stock.

Despite the high visibility of the service and the strong positive brand recognition of the BART system, the integrated and accessible airport link is underutilized compared to capacity and prior estimates. The main disadvantage to this service is that the single BART line is not in close proximity to a majority of the population within San Francisco.

Oakland, CA (OAK)

Context

Oakland International Airport (OAK) is the second largest of the three commercial airports to service the Bay Area and the 24th largest origin and destination (O&D) airport in the United States. In recent years, Oakland has proven to be a popular alternative to SFO particularly within the low cost carrier market. The presence of ATA Airlines and JetBlue has buoyed strong growth in airport passenger numbers in the post-2001 airline era.

Oakland International draws primarily from ground access trip origins of Oakland and surrounding Alameda country. Significantly more passengers for OAK originate from San Francisco compared to SFO passengers who originate from Oakland. This may reflect the influence of low cost carriers on the travel preferences of Bay Area residents.

In comparison to San Diego airport, OAK is slightly smaller but of a similar O&D ratio. The purpose split for San Diego is much more business oriented while both are in urban locations.

Alameda County has a population of 1.22 million and has a fairly moderate density owing to the geography of the region. BART extensively services the city in addition to


Appendix A

Case Studies


A-5

connections to San Francisco. Approximately one hundred miles of track are located on the Oakland side of the bay alone, establishing a strong network effect for the system.

Accessibility to the airport is provided by freeway, local bus and the BART via the AirBART shuttle bus service. The current AirBART service, utilizing low floor buses which operate every 10 minutes throughout the day providing connections to the Coliseum/Oakland Airport station with a journey time that can vary widely depending on traffic conditions from 15 to 60 minutes. Events at the Oakland Coliseum can also adversely affect journey times, as well as making navigation through the BART station more difficult for air passengers. There are advanced plans for an automated people mover to be introduced to serve the 3.2 miles route, which could open around 2011.

Success Factors

The long running AirBART is one of the most successful public transport airport ground access services within the United States. Established in 1985, recent surveys have suggested a mode share of up to eight percent.

Ridership of the service may be explained by a number of reasons:

High visibility of service, with dedicated vehicles with ample baggage room

High frequency, high reliability and relatively fast service to downtown, particularly in high traffic.

Robust BART network in place throughout Oakland with a comparatively high density of track and stations per capita. This results in a readily accessible service for a higher proportion of the population.

High share of price sensitive passengers as a result of low cost carrier presence at OAK.

The relative success of the AirBART service has been despite circumstances which might otherwise have proven to be barriers to success. The non-integrated nature of the service, both in terms of ticketing and the required inter-modal connection lessens the perceived convenience. Further, once on BART, the rolling stock is non-dedicated and air passengers must compete for space alongside commuters. On the positive side, the network effect of the BART system throughout Oakland strongly augments the effectiveness of the AirBART service by making it attractive to travelers with destinations through a significant part of the Oakland area..

Appendix A Case Studies

Portland, OR (PDX)

Context

Portland International Airport (PDX) is a significant port in the northwest providing flights to major air hubs, smaller regional centers and increasingly, direct flights to overseas destinations. Total international passengers for year on year FY2007 grew by 13 percent with strong growth also in national passenger volumes. It is also the 27th largest O&D airport within the United States, with a ratio of 91 percent to total passengers. This proportion is similar to SDIA.

PDX faces negligible levels of competition for commercial services and accounts for approximately 90 percent of passenger air travel for Oregon.

Portland is a moderately dense city with a population of around 2.3 million within the metropolitan area. It is the second most populous US city in the Northwest after Seattle with a strong reputation for engaged urban planning and positive investment in public transport.

The Metropolitan Area Express (MAX) is a light rail system servicing the greater metro area of Portland (Figure A-2). With four lines extending from the city center the system enjoys a high level of public support, with one of the highest levels of ridership for a light rail system within the United States. The system shares many similarities with the San Diego trolley system. They are each distinct standalone light rail systems rather than a part of a larger subway network; San Diego has the highest level of ridership for a standalone system in the U.S. with Portland second. Further, both systems have three metro lines, with the miles of track, number of stations and distribution of network to the population being very similar.


Appendix A

Case Studies

Figure A-2: Portland MAX Light Rail Network

Source: Portland TriMet

Success Factors

The airport is accessible by an adjacent freeway and by light rail, with the Red line linking PDX to the downtown in less than 30 minutes. Constructed in 2001 in response to heavy traffic congestion along the connecting highway, the service enjoys a modal share to the airport of over six percent.

The level of mode split may be attributed to a number of factors:

The MAX system is a well regarded and highly patronized service, with strong positive brand recognition.

Fares are simple and extremely competitive compared to alternate modes of ground transportation from the airport.

Ticketing and services are integrated within the wider Portland public transport ticketing systems.

The MAX is strongly integrated with local land use plans and the urban environment.

A number of factors may work against the utilization of the MAX service. The light rail is non-dedicated and has no additional accommodating services or specific luggage space for air passengers. This may be significant, particularly during peak periods, at times when commuter usage of the line is likely to be at its highest. However it is asserted that the cumulative effect of strong public support for the MAX system and its effectiveness in connecting the airport and a high proportion of the population through a wholly integrated service more than compensates for these factors.


A-7


Chicago, IL (ORD)

Context

Chicago O’Hare International Airport (ORD) is the second largest airport by passenger volumes both in the United States and internationally with approximately 76 million passengers passing though its gates annually. Further, the airport is one of the largest international gateways within the country servicing over 60 international destinations. As such, it places third in terms of volume of domestic O&D passengers, behind Las Vegas and Los Angeles. The city of Chicago is the third largest city in the U.S. with a population in excess of nine million people.

Chicago O’Hare is well connected to the wider highway network in Chicago and by rail through the metro rail system (termed ‘L’) operated by the Chicago Transit Authority (Figure 0 3). The Blue line of the ‘L’ terminates at O’Hare and runs 24 hours a day from the airport through downtown Chicago. The service is also used by commuters. It does not have special luggage provision for air passengers and is not branded as an airport shuttle. Nonetheless, the service frequency and fare makes it an attractive option for those with a destination along the route. Once through the downtown area, the line continues into the south-western suburbs of the city or connections can be made for other areas of the city. However, travel times from these locations are such that it would be an unattractive option for most air passengers.


Appendix A

Case Studies

Figure A-3: Chicago CTA Metro Rail Network

Source: Chicago Transit Authority

Success Factors

For trips distant from the city center, taxi and private car quickly become the preferred modes. Ridership on the rail service thus suffers for a number of reasons:

The urban sprawl of much of Chicago makes effective public transit provision difficult and particularly limits the attractiveness of the service outside the specific corridors in which it operates.


A-9


Travel times for door-to-door in downtown Chicago are worse than road based modes in off peak. In peak travel times when trip times are most likely to be competitive, the trains are likely to be crowded with commuters

The service does not operate dedicated rolling stock or have any branding that associates the service with the airport, despite good signage and good levels of access from the airport terminals.

Air passengers must compete with commuters for space on the trains, particularly during peak periods when the service can be crowded.

The service suffers from the problem of not offering competitive journey times for many travelers, and from having to share highly utilized commuter train services. The system is inexpensive and frequent, yet not ideal for many airport access trips.

St. Louis, MO (STL)

Context

Lambert - Saint Louis International Airport (STL) is the largest airport in the state of Missouri. Much has changed since 2001 when the airport operated at twice present day capacity. A downturn in the air travel market, airline bankruptcy and acquisitions as well as service cut backs have strongly affected passenger volumes. Recent trends suggest the airport is rebounding, though far more slowly than the initial decline.

A moderately densely populated city, St Louis lies at the center of Greater St Louis, a sprawling region which encompasses several counties within both the states of Missouri and Illinois. The metropolitan region is the 18th largest in the U.S. with approximately 2.8 million residents.

Metrolink is the light rail public transport system which operates throughout greater St Louis. It is predominantly one line running east-west across the city, traversing the Mississippi River and the state border. An additional line was introduced in 2006, but is only around one fifth the length of the major line.

In comparison to the trolley system of San Diego, the linear nature of the St Louis service limits its attractiveness to passengers originating from locations distant from the rail corridor. Unlike San Diego, there are no network benefits from interchanging from other rail services, although bus feeder services are provided.

The airport is accessible by an adjacent freeway and by rail, fully integrated within the Metrolink system (Figure A-4). STL is served by two light rail stations located within the


Appendix A

Case Studies airport itself in both the Main and East Terminals, with regular service direct to downtown St Louis.

Figure A-1: St Louis Metro Network Map

Source: St. Louis Metro Service

Success Factors

The airport link was opened in 1994, one year after the section between North Hanley and 5th & Missouri stations. The overall service initially exceeded predicted ridership levels. Current modal share from the airport is approximately five percent.

This share may be attributed to a number of factors:

The Metrolink could not adequately be described as a network, there is effectively only one line.

This poor geographical distribution of service is reflected in both low miles of track and stations per capita.

The cost of competing transportation services, while somewhat higher than light rail, is still not very high in absolute terms and yet offers convenience of door-to-door travel.

The service operates on non-dedicated rolling, nor does it have specific branding associating the service with the airport.

It is contended that the success of this service is hampered by the limited distribution of the light rail system. The single linear line is not in close proximity to a majority of the population within St Louis. However, for trips to the city center, the service can offer moderately competitive travel times (particularly in peak periods) at low cost.


A-11


Appendix B - Transportation Modeling

6189001

San Diego International Airport Expansion: Sustainability Analysis B-1

Appendix B – Transportation Modeling

Overview

Transportation modeling is a quantitative framework that allows for predictions to be made of the likely impact on travel demand to changes in the transport tier system. In the case of SDIA, these may include improved transit or road access to the existing terminals, or a concept such as the Lindbergh ITC which may substantially improve airport access for air passengers and employees by providing ready access to the Trolley, Coaster and Amtrak rail services.

It is typical practice with airport surface access models to consider only trips made to the airport. It is possible that trips made away from the airport would be somewhat different (for example, there would be a ‘meet & greet’ component). However, consistent with the majority of other airport surface access studies it is assumed here that the inward and outward legs are symmetrical. Results are presented in Section 2 based on multiplying modeled mileage “to” the airport by a factor of two.

The modeling approach used a discrete choice modeling framework. Discrete choice models are probabilistic in nature. That is, they do not assume that an individual will definitely chose a particular mode. Rather, these models identify the probability that an individual will choose each mode available. So, for example, an individual living in downtown San Diego who owns a car may have a probability of 40 percent of driving their car to the airport, 20 percent getting dropped off by a friend or colleague, 20 percent of taking a taxi and 10 percent by the airport flyer bus. These probabilities would differ depending on the purpose of the journey (business or non-business) and, perhaps, their socioeconomic characteristics (such as income). The probabilistic nature of these models is a key benefit of the models. Travelers make mode choice decisions based on a host of factors, many of which are difficult to observe and which may vary from day to day (e.g., weather or availability of colleagues for dropping off).

Discrete choice models work on the basis of utility differences, that is, how different one service is from another. Within the family of discrete choice models, the logit formulation is most widely used, and has been used in this study. Consider as an example two travelers. One lives close to the airport and has a choice between two otherwise identical trips except one of which takes 10 minutes and the other takes 11 minutes. A second traveler may live further from the airport such that they have two otherwise identical alternatives that take 60 and 61 minutes respectively. Logit models would predict in both cases that the probability of selecting the faster trip would be 26 percent. Intuitively, we may expect that the one minute time difference would make little

Appendix B Transportation Modeling

B-2 San Diego International Airport Expansion: Sustainability Analysis

difference in the longer example and so the probability would be closer to 50 percent in this case. However, because only the differences are important (one minute in both case) the logit model does not consider the absolute travel times.

Experience from airport ground transportation studies elsewhere has suggested that dividing the utility by the square root of the trip distance helps to correct this problem. So, in the example above, if the shorter trip was 5 miles and the longer trip was 30 miles then the probability of choosing the faster journey for the short distance traveler would be 39 percent while for the longer distance traveler the probability would be 45 percent. This would result in probabilities that would more reasonably represent intuition, and evidence from studies elsewhere.

Data Availability

The quality of any model, and the robustness of the forecasts are dependent on the availability of appropriate data and the assumptions made. These are now summarized and referred to as required throughout the report.

Modeling future travel choices requires data about current choices and travel conditions as well as forecasts about how these conditions will alter in the future. High quality data is essential to robust model forecasts, and data limitations impose significant caveats on interpreting model outputs. Likewise, the further into the future that forecasts are made, the greater the uncertainty. It is, for example, particularly difficult to predict the price of fuel in the long run. A number of data sources were used in the present modeling effort:

SDCRAA

- Airport Master Plan Environmental Impact Report (EIR)

• Current and future background traffic forecasts

• Traffic distribution

- Transit Demand and Access Study (draft: November 2007)

- Passenger Satisfaction Survey (2007 – 2Q Results)

SANDAG Regional Transportation Model

- Mode Choice Model documentation

- Parameters

- Level-of-service (road travel times)

MTS/NCTD

- Timetables

- Fares

Appendix B

Transportation Modeling


B-3

Other sources

- Google Maps – road travel times, route assignment.

These data sources were compiled wherever possible to a base year of 2005 consistent with the EIR. For testing major airport developments such as the Lindbergh ITC concept, a horizon year of 2030 was used; it is assumed this would be a time by which should such a concept be developed it would be fully in operation. Future passenger traffic forecasts and background traffic levels for 2030 were based on those used in the EIR to ensure consistency.

Assumptions

Due to a lack of data in some instances, and the desire to undertake a top level analysis a number of assumptions were required. These assumptions are described in further detail throughout this chapter, but are summarized in Table B-1. Where appropriate an indication is provided of the likely impact these assumptions have both on the modeling accuracy and, if relevant, in which direction these may affect the results.



Table B-1. Summary of Modeling Assumptions

Assumption Importance Effect

Passenger and airport employee distributions are identical

●●●●● Very likely to overstate travel distances of employees and understate transit mode share potential

Mode share model parameters derived from other cities

●●● Specific local effects not accounted for such as passenger type mix, attitudes towards existing transit alternatives.

78 zone system ●●● Relatively coarse zoning system, may understate transit demand in some zones and overstate in others based on assumptions regarding access to transit services.

Interchange penalties ●● May tend to underestimate transit demand on some corridors where quality of interchange is high (e.g. America Plaza) and overstate on others where interchange quality is low.

Airport employee forecasts for 2030

● If economies of scale are less or greater than predicted as air passenger numbers grow then total employee numbers may differ.

Distribution of air passengers and employees does not change between 2005 and 2030

●●●● Increased urban density, particularly at locations currently well served by transit (such as much of the downtown and waterfront regeneration areas) may tend to increase transit share to the airport. Conversely, greenfield developments on the outskirts of the city may decrease the transit share.

No changes in transit or highway journey times across the day

●●● This assumption assumes that transit services operate across the day and that travel times both by transit and car do not change. This overestimates transit demand if travelers wish to access the airport outside existing transit service hours. Conversely, increased highway travel times during peak periods may tend to increase transit share.

Real car and transit costs remain unchanged

● It is assumed that there will be no real change in car or transit costs to 2030. This further implies no change in relative costs between the two modes. If oil prices are very much higher in 2030 then this assumption will tend to underpredict transit share; conversely, if transit fares increase faster than car costs then it will tend to overstate the transit share. This is more important for airport employees (who are more cost sensitive) than for air passengers.

Transit networks do not change unless stated

●● No changes in the transit network will occur (for example, cancelling bus routes or altering service frequencies). This may tend to understate the transit share if, for example, the Lindbergh ITC were to become a hub for trolley and bus services to the region. The proposed LRT/BRT extension from Old Town to University City is therefore not included.

Appendix B

Transportation Modeling The modeling process is illustrated in Figure B-1.

Figure B-1. Flow Chart of Modeling Process

Demand

For consistency with the EIR, the same air passenger forecasts for 2030 are assumed. This represents the unconstrained low growth forecast for the airport. Total origin & destination air passenger and airport employees are summarized in Table B-2.

Table B-2. O&D Air Passengers and Airport Employees

Air passengers Year

Annual (m) Avg Daily Airport employees

2005 16.7 45,830 5,000 2030 27.0 74,199 6,467

Based on data provided by SDCRAA, it was assumed that there were 5,000 airport employees working on or in the immediate vicinity of the airport site1. This was assumed to include off-airport parking and car rental facilities directly to the north of the airport site. Experience at SDIA and elsewhere has indicated that the number of airport employees relative to air passengers tends to decrease as airports increase in size due to greater efficiencies of scale. In the absence of employee forecasts it was assumed that the

:

1 The draft Airport Transit Plan assumes 4,900 employees.

San Diego International Airport Expansion: Sustainability Analysis B-5



number of passengers per employee would increase by 25 percent between 2005 and 2030, giving 6,467 employees in 2030.

The availability of transit to air passengers and airport employees alike will be dependent on the level of service provided at the times of day when passengers wish to travel. The first weekday service on the Blue line of the trolley currently passes through Middletown at approximately 04:50 southbound and 05:35 northbound. The last service of the day leaves in the southbound direction at 11:50 while the last northbound service stops at 01:48. Similarly, the first weekday 992 bus service arrives at the commuter terminal at 05:18 and the last service departs at 00:21. The existing services provide coverage across much of the day, including when the airport is busiest. In 2005 there were no aircraft movements between midnight and 04:00 after which there were seven aircraft movements before 06:00. In the evening, there were four flights between 23:00 and midnight. The absence of flights at night is largely due to a curfew that is imposed between 11:30 pm and 06:30 am. As the airport has minimal overnight operations it is likely that the trolley system would not need to extend its hours to facilitate air passenger and airport employee movements2. On weekends however the service frequency is reduced, particularly on the Coaster which operated a very reduced Saturday service and no service on Sundays.

The base year is taken as 2005 and future year as 2030. It is assumed that growth in air passengers is distributed evenly across all zones.

Background Traffic A significant number of developments are in various stages of construction, development or planning in the vicinity of the airport. These developments will all have an impact on background (non-airport) traffic growth in the area, which in turn will adversely affect traffic congestion. In order to maintain consistency with the DEIR, the background traffic forecasts used as part of that analysis were used in the present study. These forecasts were in turn based on SANDAG Series 10 forecasts. A number of developments are incorporated, such as those identified in:

Naval Training Center/Liberty Station Precise Plan EIR

North Embarcadero Visionary Plan Final EIR

However, as noted in the DEIR (Section 5.3.1.4), a number of developments were not explicitly included in the traffic forecasts (such as the CCDC Master Plan and Woodfin Suites Hotel). However, the general plan zoning assumed for these areas results in the

2 This assumption assumes that airport employees do not need to be present at the airport when there are not aircraft movements. This is clearly incorrect, but given the top level nature of the modeling this is considered a reasonable assumption.

Appendix B



B-7

generation of traffic equivalent or greater than that predicted by the EIRs for these sites. On this basis, given that proxy traffic generation was assumed for these zones, and consistency with the DEIR, the background traffic forecasts for the DEIR were used in this study. While specific developments may introduce additional traffic onto particular areas of the local road network and may have particularly important localized impacts on airport traffic, such impacts could not reliably be forecast as part of the present study. In addition, it was felt that these impacts would not materially affect the outcome of analysis.

An error was identified in the DEIR in reporting very significant decreases in non-airport traffic on Rosecrans Street after 2015. This error resulted in an improvement in LOS at 2030 compared with 2005 even after substantial increases in airport related traffic were accounted for. As a result, Series 11 traffic forecasts were used for Rosecrans Street.

Distribution

The distribution of trip origins is critically important to understanding the current and future travel patterns, as the origins will influence which roads will most likely be used to access the airport and the availability of transit alternatives. The EIR reported traffic origins across a 78-zone system based on the SANDAG Regional Transportation Model. This distribution is given in Table B-3 as are the assumed travel times.

Table B-3.Distribution of SDIA Traffic by Origin

Current Terminal

Location

Distribution (%)

Distance to

current terminal

(mi)

Distance to

proposed ITC (mi)

Car travel time

(mins)

Transit travel time

(mins)

Number of transit

interchanges

32nd St Naval Station 0.1 7.0 6.1 18.0 35 1

Balboa Park 0.0 4.2 3.4 13.2 28 1

Barrio Logan 0.1 5.5 5.5 16.8 28 1

Black Mountain Ranch 0.6 28.2 26.0 46.8 56 1

CARLSBAD 5.8 35.2 33.0 48.0 74 1

Carmel Mountain

Ranch

0.5 21.7 19.4 34.8 84 1

Carmel Valley 0.8 20.6 18.4 33.6 95 2

Center City 8.8 3.3 2.3 12.0 16 0



Current Terminal

Location

Distribution (%)

Distance to

current terminal

(mi)

Distance to

proposed ITC (mi)

Car travel time

(mins)

Transit travel time

(mins)

Number of transit

interchanges

CHULA VISTA 4.6 11.8 10.7 22.8 40 2

Clairemont Mesa 1.6 11.2 8.9 20.4 39 2

College Area 0.6 12.1 11.3 25.2 52 1

CORONADO 1.1 9.2 8.2 22.8 51 1

DEL MAR 0.3 20.7 18.5 34.8 102 3

Del Mar Mesa 0.2 20.9 18.7 34.8 89 2

East Elliott 0.0 18.6 16.2 36.0 65 2

EL CAJON 2.4 19.4 19.5 31.2 58 2

ENCINITAS 1.6 26.5 24.4 39.6 60 1

ESCONDIDO 2.9 33.8 31.5 50.4 62 1

Fairbanks Country Club 0.0 22.9 20.7 37.2 56 1

Flower Hill 0.0 21.5 19.3 32.4 56 1

Greater Golden Hill 0.3 6.0 5.0 14.4 33 1

Greater North Park 1.0 6.0 4.9 15.6 41 1

Harbor 0.0 7.6 7.4 18.0 36 1

IMPERIAL BEACH 0.4 17.4 16.3 28.8 66 1

Kearny Mesa 1.9 11.6 9.3 21.6 52 1

La Jolla 1.0 13.4 11.2 26.4 65 1

LA MESA 1.3 14.2 13.1 25.2 55 1

LEMON GROVE 0.5 12.0 11.0 22.8 50 1

Linda Vista 0.5 7.7 5.4 18.0 52 1

Lindbergh Field 1.2 1.0 1.0 6.0

Mid-City: City Heights 1.0 8.7 7.7 18.0 56 1

Mid-City: Eastern Area 0.7 9.9 8.9 21.6 51 1

Mid-City: Kensington-

Talmadge

0.3 11.7 10.7 21.6 55 1

Appendix B



B-9

Current Terminal

Location

Distribution (%)

Distance to

current terminal

(mi)

Distance to

proposed ITC (mi)

Car travel time

(mins)

Transit travel time

(mins)

Number of transit

interchanges

Mid-City: Normal

Heights

0.3 10.7 9.7 24.0 47 1

Midway-Pacific

Highway

0.5 4.5 2.5 13.2 11 1

Mira Mesa 3.1 19.8 18.1 33.6 81 2

Miramar Air Station 0.1 14.3 10.0 26.4 55 1

Miramar Ranch North 0.4 20.8 18.4 34.8 70 2

Mission Bay Park 1.5 6.0 5.9 19.2 48 2

Mission Beach 0.4 5.9 5.9 19.2 41 2

Mission Valley 4.1 7.0 4.2 18.0 46 1

NATIONAL CITY 1.1 8.8 7.7 16.8 36 1

Navajo 1.2 18.3 17.3 30.0 69 2

NCFUA Subarea 2 0.0 16.7 14.0 28.8 88 2

Ocean Beach 0.3 4.1 5.0 13.2 13 0

OCEANSIDE 4.1 38.6 36.9 54.0 78 1

Old San Diego 0.1 4.9 2.1 13.2 15 1

Otay Mesa 1.0 16.1 15.0 26.4 53 1

Otay Mesa-Nestor 0.8 19.2 14.9 32.4 56 1

OUTSIDE SD COUNTY 3.6 60.0 60.0 200.0

Pacific Beach 1.0 10.3 8.2 22.8 49 1

Pacific Highlands

Ranch

0.2 22.6 20.4 43.2 89 2

Peninsula 2.2 3.7 5.2 12.0 7 1

POWAY 1.3 24.3 21.9 40.8 123 2

Rancho Bernardo 1.4 25.3 25.3 37.2 55 1

Rancho Encantado 0.0 23.7 21.4 46.8 129 2



Current Terminal

Location

Distribution (%)

Distance to

current terminal

(mi)

Distance to

proposed ITC (mi)

Car travel time

(mins)

Transit travel time

(mins)

Number of transit

interchanges

Rancho Penasquitos 0.8 20.9 24.0 34.8 79 1

Sabre Springs 0.2 21.5 19.2 34.8 77 1

SAN MARCOS 1.8 37.5 35.2 54.0 62 1

San Pasqual 0.0 37.7 35.4 58.8

San Ysidro 0.6 19.5 18.5 30.0 53 1

SANTEE 1.2 23.3 23.3 40.8 75 2

Scripps Miramar Ranch 0.5 17.7 15.4 31.2 68 1

Serra Mesa 0.4 9.8 9.0 21.6 53 2

Skyline-Paradise Hills 0.8 12.7 14.1 26.4 52 1

SOLANA BEACH 0.5 22.2 20.0 33.6 56 1

Southeastern: Encanto

Neighborhoods

0.6 10.6 9.5 22.8 44 1

Southeastern:

Southeastern SD

0.7 6.2 5.2 15.6 34 1

Tierrasanta 0.5 15.3 13.2 26.4 54 1

Tijuana River Valley 0.0 18.8 17.8 32.4 52 2

Torrey Highlands 0.1 24.0 21.8 36.0

Torrey Hills 0.1 16.7 14.5 30.0 88 2

Torrey Pines 0.4 16.7 14.5 28.8 88 2

UNINCORPORATED 13.2 20.0 20.0 34.3

University 3.0 13.2 11.0 22.8 55 2

Uptown 1.2 3.3 1.8 10.8 21 1

Via De La Valle 0.0 23.9 21.7 37.2 56 1

VISTA 2.1 44.1 41.9 61.2 74 1

Weighted Average 19.1 17.8 37.2 43.7

Appendix B



B-11

For modeling purposes, the geographic center of each of these zones was used from which to define the travel times to SDIA. In the case of the trips from unincorporated areas and outside San Diego county it was assumed that private car was the only mode alternative available. This is a conservative assumption – it is possible that some travelers, for example who are traveling from south LA, may have the option of using the Amtrak service. Equally, this assumption excludes the possibility of construction of the proposed Californian High-Speed Rail (HSR) link, which would potentially connect Sacramento, San Francisco and Los Angeles directly to San Diego, possibly with a stop at an airport-related ITC. It is, however, unlikely that residents of Los Angeles or northern California would fly from SDIA even with a direct high speed rail link given their proximity to larger airports in central and northern California. More critically, as 13.2 percent of movements come from unincorporated areas assuming none of these journeys could use transit is a highly conservative assumption.

Critically, it was not possible to divide the distributions by air passengers and airport employees. These trip distributions are likely to be very different, with the latter more concentrated in the vicinity of the airport.

Future growth in air passenger demand will most likely not be generated equally across the region according to the current proportions. However, in the absence of forecast data on future population growth and passenger demand by zone, it was assumed that future demand would be distributed in the same manner as currently.

Mode Choice

The mode choice model takes the input demand from air passengers and airport employees for travel to the airport and estimates the likelihood that they will chose each of nine modes listed in Table B-4. ‘Kiss & Fly’ refers to escort trips to the airport where the air passenger receives a ride in a private car. This mode can be particularly important for traffic forecasting as every air passenger movement will generate two car movements (an inward and outward leg).

Table B-4.Modeled transport modes

Mode Description 1 Private car – park on-airport 2 Private car – park off-airport 3 Private car – Kiss & Fly 4 Rental car 5 Taxi 6 Shared van 7 Transit – Bus 8 Transit – Trolley 9 Transit – Coaster



Taxi and limousine services were treated together in the analysis although the cost profile of limousine services would be expected to be different. The latter was considered sufficiently minor that the services could be combined for forecasting purposes. Cycling and walking were not included as potential access modes, although there may be some potential for such low impact modes, particularly for airport employees who live in the vicinity of the airport.

The probability of choosing a particular mode for a trip to the airport will depend on a host of factors, including:

Trip characteristics Time In-vehicle time (IVT) Access time (transit) Egress time Waiting time (transit) Transfer time (transit) Cost Fuel cost Tolls Fares Purpose Business, non-business Individual/group characteristics Income Traveling party size Duration of stay away.

The factors listed above are easily quantified and were derived from the existing SANDAG regional transportation model and public domain sources.

Level-of-service Data

Level-of-service data are the travel times and costs by the various transport modes. These were compiled from various sources, including Google Maps, MTS, NCTD and SANDAG. The data represented current (2007) conditions apart from the SANDAG data, which represented 2004 conditions. For the purposes of the present analysis the data was considered to be equivalent to the 2005 base year for modeling purposes.

Appendix B

Transportation Modeling Parking

On-airport parking was defined as the parking provided directly in front of the terminal buildings by SDCRAA. Off-airport parking refers to sites operated by SDCRAA (three SAN Park sites) and by other operators (such as Aladdin Parking and San Diego Airport Parking). Average daily costs at these sites were obtained and used to derive the cost functions shown in Figure B-2. For all durations longer than one day the off-airport parking sites are cheaper. However, in the generalized cost calculations the additional time and hassle associated with needing to take a shuttle bus between the off-airport parking site and the terminals is accounted for, thereby making parking on-airport somewhat more attractive than a simple cost calculation alone would infer.

Figure B-2. Parking Cost Functions

$0

$100

$200

$300

$400

$500

$600

$700

$800

0 5 10 15 20 25 30

Days

Cos

t

On-AirportOff-Airport

SDCRAA charges a fee for the annual rental of airport employee parking. It is unlikely however that this charge is passed on by many employers to employees. For the purposes of the present study it was assumed that on average employees pay $2 per day to park at the airport. This charge may or may not be passed on in reality, rather it acts to represent the disutility associated with driving to the airport.

Parking search times and access to the terminal was assumed to be 10 minutes for air passengers and 5 minutes for airport employees. These times were applied only to parking on-airport; for off-airport parking a schedule of shuttle bus services of 10 minutes was assumed and a journey time of 7 minutes between the off-airport parking and terminal was assumed. In addition, an interchange penalty of one-third of the transit value was assumed; this was lower than that for transit on the assumption that the shuttle waiting facilities would be of high standard and there would be no confusion as to the


B-13

Appendix B Transportation Modeling destination of the shuttle service. The result of this series of assumptions is that parking off-airport has a disincentive equivalent to 17 minutes of travel time (as shuttle bus wait time is valued at twice in-vehicle time).

Taxi and Shared Van

Cost profiles for local taxi and shared van operators were obtained and functions derived based on distances traveled to obtain trip costs; as shown in Figure B-3. Taxi costs were assumed to increase linearly with distance traveled while for shared vans the rate increased at an exponential rate.

Figure B-3. Taxi and Shared Van Cost Profiles

y = 14.012e0.0425x

y = 2.6x + 2.4

$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

0 5 10 15 20 25 30

Miles

Cost

Taxi

Shared van

Transit Networks

The transit level-of-service was based on timetables for existing MTS, NCTD and Amtrak services in the region. Where there would be multiple transit alternatives, assumptions were made regarding the most likely alternative.

Transit fares are based on one-way fares. This is a reasonable assumption given that no discount applies for return fares. Period and bulk purchase tickets are available, and would reduce the cost to regular users. However, for the purposes of the present analysis it was assumed that the uptake of these alternative tickets was sufficiently small so as to be neglected.


Appendix B



B-15

Time-of-Day Variation

The current transit fare pricing strategy does not vary by time-of-day. However, traffic congestion on a number of key corridors (such as the I-5 and I-8) during peak periods would likely increase journey times by road-based modes compared with off-peak periods.

Modeling Framework

How these factors are perceived, and particularly how ‘valuable’ travelers consider their trip time to be are critical to the modeling process. The concept of value of time is very important in understanding the mode choices of air passengers, as they typically highly value the time required to access the airport as they have a fixed flight departure time. As the model is highly sensitive to the value of time assumptions, considerable effort was expended in determining appropriate values of time for the study.

Value of Time

It is widely recognized that air passengers tend to have higher values of time than other travelers. There may be several reasons for this, including:

An explicit need to be at the airport at a particular time

Higher average incomes of air passengers compared with the wider population

Higher proportion of business trips made by aircraft compared with other modes

High cost of air travel, resulting in lower cost sensitivity for ground transportation as it may form a small part of the total travel cost.

Experience from studies at airports in the U.S., Europe and Australia have all indicated that air passengers have a value of time that is typically at least twice that of other travelers. Similarly, these studies have indicated that air passengers making business trips tend to value their time much more highly than passengers making other types of trips (e.g. holidays, visiting friends and relatives). Typically, business travelers tend to value their time at about twice the rate of non-business travelers, although the evidence indicates wide variation between sites.

The implication of high values of time exhibited by air passengers to effective ground transportation policy is profound. For example, high values of time imply that travelers would significantly respond to changes in the relative travel times between modes, such that even marginal time savings by one mode would be highly regarded. Conversely, travelers would be relatively insensitive to travel costs. So, for example, decreasing transit fares would not result in significant changes in transit mode share unless combined with improvements to travel times. In the SDIA context, this implies that for a mode to be attractive it must offer travel time savings; cost savings alone are unlikely to lead to



significant increases in use of that mode. The relatively cheap cost of taxis (by international standards) mean that transit may not offer sufficiently substantial cost savings for many travelers to make it attractive, particularly where the travel times are uncompetitive. This is likely to be the case for travelers who do not have ready access to a convenient transit alternative.

SDIA’s proximity to the downtown area and much of the suburban area means that car trips are relatively short and, importantly, that taxi fares are low compared with airports in other cities (where the airport is often located a greater distance from the population center). Furthermore, in cities with successful airport rail links, there is often a disproportionate amount of travel to the downtown areas in some of the more successful international examples that is not present in more dispersed cities such as San Diego, where only around 9 percent of airport trips originate in the downtown area.

More difficult to quantify, travelers will tend to highly value the reliability of their travel time; that is, they place a high valuation on knowing their chosen method of transport to the airport will arrive in an expected time. How this should be valued is a subject of much research and so is not explicitly accounted for in this analysis, although indirectly it may be incorporated in the mode specific constants if a particular mode is perceived as unreliable.

The values of time (VOT) of air passengers were established based on existing studies at airports elsewhere in the U.S. and professional judgment. Table B-5 summarizes the VOTs reported in the literature after making two adjustments:

RPI adjustments to obtain 2005 prices

Factoring by median household income growth with an elasticity of 0.8, consistent with UK value of time experience.

Table B-5.Air Passenger Values of Time Reported in the Literature

Values of time (2005 $/hr) Study Year Region Employer’s

Business (EB) Non-EB EB / non-EB

California HSR 2006 California 26 13 2.0 Gupta, Vovsha and Donnelly

2007 New York City 61 40 1.5

Harvey 1987 San Francisco 74 Hess, Polak 2001 San Francisco 93 – 155 Dowling Assoc. 2002 San Jose 16 11 1.5

The wide variation in VOTs is indicative of the techniques used to obtain the values, analysis procedures, and location-specific factors. Values of time of $50/hr for EB and

Appendix B



B-17

$25/hr for non-EB purposes were selected for the present study. These VOTs are broadly consistent with the range reported in the literature, and are significantly higher than the value of time assumed for airport employees, as discussed below.

The SANDAG Regional Transport Model used 1/3 of the average wage rate to define the value of time for commuting purposes. In 2005 value and prices, this corresponds to a value of time of $6.44/hour . The resulting value of time for employees is around four times lower than for non-business air passengers and eight times smaller than business air passengers. These large differentials reflect the much greater sensitivity to time of air passengers in comparison to airport employees and lower sensitivity to cost.

Access and Wait Time

In addition to travel time in a vehicle (termed in-vehicle time, IVT), travelers typically must also travel to the vehicle and from it to their destination. In the case of public transit this may involve a walk or drive to the nearest bus stop or rail station, and then a walk at the airport to the terminal building. The traveler will more than likely also have to wait for their bus or train service when at the stop or station. In addition, it may be possible that a traveler may have to change vehicle in route, for example by transferring between train services or from a bus to a train. Experience from a wide range of studies elsewhere indicates that these components of a trip are perceived as more onerous than IVT. For example, the consensus is that access/egress time is valued at about twice IVT while time spent waiting for a transit service is valued at three times IVT. These values may differ somewhat depending on the context - including the quality of waiting facilities at stations and climatic conditions; however these ratios were deemed reasonable for the current analysis.

When transferring between transit services, there tends to be an additional disincentive in addition to the additional wait time as a result of having to wait for the connecting service. This additional disincentive may be attributed to the disruption to the trip, ‘hassle’ and additional stress involved with having to change service. The magnitude of this disincentive will depend on the difficulty of the transfer; at relatively small stations where simply walking across to the other side of a platform is required, the disincentive is likely to be small, while at larger stations the disincentive may be larger. Furthermore, in exposed locations, additional qualitative factors such as the prevalent weather conditions, perceived safety and cleanliness can all play a role. Quantifying such effects is difficult; however, previous experience would suggest that air passengers tend on average to associate an equivalent of 20 minutes of IVT with an interchange. To illustrate the implication of this assumption, consider two bus services, one of which is direct and takes one hour while another takes 40 minutes but requires a transfer. Assuming no other differences between the services, and that there would be no waiting required for the



transfer, both services would be considered equally attractive on the assumption that a transfer is considered to be equivalent to 20 minutes of IVT.

Airport employees are likely to consider transfer to be less of an impediment because the stress component is less clear – the traveler probably makes the trip regularly and so is more aware of where their connecting service would depart from. For this reason, it was assumed that employees considered a transit transfer to be equivalent to 10 minutes of travel time, half of that of air passengers.

In summary, the following assumptions were made regarding transit travel times:

Access time was valued twice as highly as in-vehicle time

Wait time was valued three times as highly as in-vehicle time

Interchanges were valued as equivalent to 20 minutes of IVT for air passengers and 15 minutes for airport employees.

In-Vehicle Times

The travel times by public transit were based on published timetables from the transit operators (MTS, NCTD and Amtrak). Where there was some variation across the day in travel times, a weighted-average time was used to represent the average travel time from each zone to the airport.

Group Size

It is assumed, consistent with other studies, that costs would be distributed among the traveling group. For this reason, costs such as car costs and taxi fares are divided across the group. Survey data had indicated that the average group size for business trips is 1.2 while for non-business trips the average group size is 2.1. These group sizes were assumed in the model.

For the purposes of the traffic analysis the occupancy of a shared van was assumed to be 6 persons and for a local bus 10 persons. These assumptions were based on observation of vehicles leaving the airport during site visits in November 2007; more extensive surveys would be warranted to verify these assumptions as part of any future analysis.

Duration of Stay

The duration of stay away was important in the assumption regarding parking costs. Airport survey data indicated that business travelers spent on average 1.5 days away while non-business travelers spent on average 3 days. The parking cost assumed for each trip leg was half of the total parking cost.

Appendix B



B-19

Distance

In the chosen generalized cost specification, the level-of-service variables related to distance (i.e. time and operating cost) were divided by the square root of trip distance. This is consistent with experience from some airport surface access studies in other locations, where it was found that this specification increased the accuracy of the model. The explanation for this improved model fit is that small changes in time or cost on longer trips would be less significant than for shorter trips.

Headways

Headway is the time between services, so for example the headway for a bus service that operates at 9:00, 9:20, 9:40 and 10:00 would be 20 minutes. As per standard practice, it was assumed that the average traveler experiences a wait time equivalent to half the headway. Real-world experience indicates that below about a 10 minute headway, travelers tend to just ‘turn up, wait briefly and go’ whereas with longer headways they plan their trips more carefully to ensure they arrive close to the departure of their service. For services with large headways such as the Coaster rail services where the average headway across the day is over 70 minutes, it is unlikely that a passenger would wait at the station for a period of time equivalent to half the headway (i.e. 35 minutes). However, there is an indirect disutility associated with the long headways that would tend to discourage travelers from using the service. For this reason the headway is not capped.

Kiss & Fly

It would be plausible to expect that at least some air passengers would assign a value to the escorting drivers’ time and perhaps also to the costs associated with driving the car. Research elsewhere has indicated that air passengers on employer’s business trips tend to fully consider the drivers’ time to and from the airport as if it were their own time. Likewise, they also tend to consider the return car cost. For non-employer’s business trips only the time spent taking the passenger to the airport is considered. In research undertaken elsewhere, it was found that some 15 percent of air passengers would directly contributing to the cost of the trip – for this reason in the model non-EB trips are assumed to incur 15 percent of the return trip car costs.

Zoning System

The zoning system is based on a relatively coarse 78 zones, consistent with survey data available on air passenger origins. The result is that some important zones, such as downtown, are represented as a single zone – resulting in coarse assumptions regarding access times and IVT from this zone.



Mode-Specific Constants

In addition to the basic travel attributes of time, cost and – in the case of transit – service headway and transfers, it may be expected that other less readily quantifiable mode attributes also contribute to selecting a particular alternative. These may include, but are not limited to:

Perceived safety, particularly at night

Accessibility at stations and to transit vehicles, particularly for mobility impaired travelers or air passengers carrying luggage

Cleanliness

Ride quality

Perceived service reliability.

These attributes are typically accounted for by assigning a constant to each mode which then ensures the mode shares match the base (i.e. known) situation. This process is known as calibration.

In considering transit modes, there is much disagreement about how these attributes affect ridership between bus-based and rail-based modes. While a number of factors may be considered to make rail services more attractive than local bus – perhaps their ride quality, permanent and highly visible infrastructure, this may not always be the case. This is particularly true for high quality bus services, which in the case of airport services may involve dedicated vehicles with unique branding (such as the existing 992 Flyer) and perhaps some form of physical segregation from the roadway which infers a degree of permanence and visibility to the service. The SANDAG Regional Transportation Model found that commuters in San Diego tended on average to favor rail and express bus over local bus. In terms of the mode-specific constants, this was reflected in a 6 minute equivalent travel time benefit for rail and 14 minutes for express bus. This illustrates both that rail may well be inherently preferred to local bus but that high quality, express bus services can be even more attractive. Because of the uncertainty surrounding any intrinsic difference in preference between rail and bus, both conservative and optimistic assumptions were made in the modeling. In the conservative scenario it was assumed that there is no intrinsic difference in preference between the modes, while in the optimistic assumption it was assumed that there is preference for rail equivalent to 6 minutes of travel time.

Model Parameters

The model parameters are values that indicate the relative weighting of the different service attributes. These parameters are used in logit-based discrete choice models, which are widely used for transportation modeling. They provide a mathematical

Appendix B



B-21

framework around which these factors come together to provide an indication of the overall likelihood of selecting each mode. As discussed earlier, this is an important advantage of this type of model – that it assigns probabilities to choices rather than inferring certainty. In a transport action context this is a significant advantage, as it helps to account for the factors that are more difficult to quantify and the wide variation of preferences across the population.

The model parameters are typically estimated using statistical techniques based on local data. This data is typically obtained using a dedicated survey and data collection procedure. We are not aware of such a procedure having been conducted at SDIA. The scope and schedule of this study precluded any primary data research and estimation of models from local data sources. Instead, model parameters were derived from relevant studies in other locations. The most useful of these was the air passenger model estimated for San Jose Airport (SJC) in 2002. This model provided parameter estimates across four air passenger segments – resident business journeys, resident non-business trips, non-resident business trips and non-resident non-business trips.

In order to tailor the model to San Diego the value of time was adjusted and the mode specific constants adjusted using a calibration procedure to ensure the existing mode shares were replicated. The resulting model parameters are given in Table B-6 for air passengers and Table B-7 for airport employees. The constants are presented both in terms of the parameters themselves and in parenthesis in terms of equivalent in-vehicle time. The latter provides a ‘physical’ indication of any intrinsic attractiveness of particular modes.

The IVT parameter was set to -0.028 for airport employees, which is consistent with that used in the SANDAG Regional Transportation Model for home-based work trips.

Other relevant model parameters that were used in the model and discussed in previous sections are summarized in Table B-8.



Table B-6. Air Passenger Model

Resident Non-Resident Business Non-Business Business Non-Business Units

Parameters Time -0.2272 -0.1078 -0.2108 -0.0975 mins Cost -0.2770 -0.2574 -0.2560 -0.2385 $ Constants Car – off-apt 0.47 0.47 -- -- (2.1) (4.4) -- -- mins PT -1.60 -2.20 0.40 -0.70 (7.0) (20.4) (1.9) (7.2) mins Kiss & Fly -1.95 0.05 -1.95 0.05 (8.6) (0.5) (9.3) (0.5) mins Rental car -2.80 -4.00 4.00 1.10 (12.3) (37.1) (19.0) (11.3) mins Taxi -2.80 -2.70 -0.30 -1.30 (12.3) (25.0) (1.4) (13.3) mins Shared van -2.66 -2.86 -0.86 -1.56 (11.7) (26.5) (4.1) (16.0) mins

Table B-7. Airport Employee Model

Parameter Value Units Time -0.0280 mins Cost -0.2608 $ Constants PT -2.25 (80.3) Mins

Appendix B



B-23

Table B-8. Summary of Model Parameters

Parameter Value Units Values of Time Air passenger – business 50 $/hr Air passenger – non-business 25 $/hr Airport employees 6.44 $/hr Transit Interchange penalty – air passengers 20 IVT mins Interchange penalty – airport employees

20 IVT mins

Access time factor 2 – Wait time factor 3 – Parking On-Airport Park search and access – air passengers

10 mins

Park search and access – airport employees

5 mins

Off-Airport Shuttle bus headway 10 mins Shuttle bus IVT 7 mins Interchange penalty 20 mins Group size Business trips 1.2 persons Non-business trips 2.1 persons Duration of stay Business trips 1.5 days Non-business trips 3.0 days Car rental Component of rental car cost 20 $

Model Structure

The model uses a sample enumeration-type approach for air passengers and airport employees. The samples are derived from the known purpose splits (business 4percent, non-business 55percent) and residency status (60percent of air passengers are from the greater San Diego area). Weights for each zone are applied consistent with surveys of staff and air passengers. Note that the distribution across zones of air passengers and airport employees are assumed to be identical due to a lack of data separating out the two categories.

The model implemented is multinomial logit; it is recognized that such an approach may lead to non-intuitive rates of substitution between alternatives. However, as no model estimations were undertaken it was not evident how nest coefficients could be derived.

Appendix B Transportation Modeling Model Specification

The model specification is a set of utility functions that define the total ‘attractiveness’ of each mode, taking into account the times, costs and other factors. These were defined as follows, based on experience from studies elsewhere:

offaptcar

parkwaitparkhwy

parkoffaptoffaptcar

searchparkhwyparkonapt

onaptcar

ASCVOT

D

htVOTaccfactortVOTtVOT

gcD

gdp

U

DaccfactortVOTtVOT

gcD

gdp

U

−

−−

−−

−

+⋅+

⋅⎟⎟⎠

⎞⎜⎜⎝

⎛⋅⋅+⋅⋅+⋅++=

⋅⎟⎟⎠

⎞⎜⎜⎝

⎛⋅⋅+⋅++=

3

122

12

τ

K

For business trips: flykisshwy

hwyflykiss ASCDg

cDgt

VOTtVOTU −− +⋅⎟⎟⎠

⎞⎜⎜⎝

⎛+⋅+⋅=

122

For non-business trips:

flykisshwy

hwyflykiss ASCDg

cDg

tVOTtVOTU −− +⋅⎟⎟

⎠

⎞⎜⎜⎝

⎛ ⋅⋅+⋅+⋅=

115.02

( )

ncourtesyvahwy

ncourtesyva

amtrakaccaccPT

waitPTamtrak

coasteraccaccPT

waitPTcoaster

trolleyaccaccPT

waitPTtrolley

busaccaccPT

waitPTbus

vanhwy

D

van

taxihwytaxi

renthwyrent

ASCD

tVOTU

ASCiVOTD

tVOThVOTtVOTfareU

ASCiVOTD

tVOThVOTtVOTfareU

ASCiVOTD

tVOThVOTtVOTfareU

ASCiVOTD

tVOThVOTtVOTfareU

ASCD

tVOTgeU

ASCD

tVOTg

DU

ASCD

tVOTU

+⋅

=

+⋅⋅+⋅⎟⎠⎞

⎜⎝⎛ ⋅⋅+⋅⋅+⋅+=

+⋅⋅+⋅⎟⎠⎞

⎜⎝⎛ ⋅⋅+⋅⋅+⋅+=

+⋅⋅+⋅⎟⎠⎞

⎜⎝⎛ ⋅⋅+⋅⋅+⋅+=

+⋅⋅+⋅⎟⎠⎞

⎜⎝⎛ ⋅⋅+⋅⋅+⋅+=

+⋅⎟⎟⎠

⎞⎜⎜⎝

⎛⋅+=

+⋅⎟⎟⎠

⎞⎜⎜⎝

⎛⋅+

+=

+⋅+⋅=

τθθ

τθθ

τθθ

τθθ

12

12

12

12

10124.14

14.26.2

115

04246.0


Appendix B



B-25

Where: D = distance to airport by car (miles) thwy = in-vehicle time by car (minutes) tPT = in-vehicle time by public transit (minutes) hhwy = total headway (minutes) τ = interchange penalty (minutes of IVT time equivalent) θwait = wait time factor (relative to IVT time) θacc = access time factor (relative to IVT time) i = number of interchanges VOT = value of time ($/minute) ASCx = alternative specific constant g = group size (persons) c = perceived car operating cost ($/mile)

Residents and non-residents are modeled as having different mode availabilities; non-residents are not allocated the car (park on-airport and park off-airport) alternatives while residents are not allocated the car rental and courtesy van alternatives.

As noted earlier, because logit models work on the basis of utility differences there is a concern that the model would not adequately reflect travel time savings for short and long distance trips appropriately. For this reason, and consistent with airport ground access models developed in other locations, the utilities were divided by the square root of travel distance. This has the effect of scaling the utility such that for longer trips a time saving of, say, one minute would be less important than for a shorter trip (where a one minute saving would represent a larger proportion of the whole travel time).

B.1 Distribution of Transit Ridership The model takes each of the 78 zones and determines the ridership based on the times and costs for each mode to the airport. In this way the introduction of the ITC, and improved trolley and rail connections, will result in increased transit ridership in those zones for which transit becomes an increasingly attractive alternative. Table B-9 below summarizes the ridership for the SDCRAA preferred alternative with transit plan and Lindbergh ITC and the optimistic assumptions.



Table B-9. Distribution of Transit Ridership

2030 Preferred Alternative with Transit

Plan 2030 Lindbergh ITC Difference

Location

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

32nd St Naval

Station

2 2.7 8 9.7 6 6.9

Balboa Park ─ ─ ─ ─ ─ ─

Barrio Logan 2 2.3 8 9.8 6 7.5

Black Mountain

Ranch

18 3.5 36 7.2 18 3.7

CARLSBAD 189 4.0 401 8.4 211 4.4

Carmel Mountain

Ranch

11 2.7 10 2.5 -1 -0.2

Carmel Valley 24 3.7 53 8.0 28 4.3

Center City 594 8.2 797 11.0 203 2.8

CHULA VISTA 71 1.9 123 3.3 52 1.4

Clairemont Mesa 42 3.2 40 3.0 0 0.0

College Area 17 3.5 51 10.3 34 6.8

CORONADO 17 1.8 17 1.8 0 0.0

DEL MAR 9 3.6 19 7.5 10 3.9

Del Mar Mesa 6 3.5 12 7.4 6 3.9

East Elliott ─ ─ ─ ─ ─ ─

EL CAJON 51 2.6 179 9.0 128 6.4

ENCINITAS 48 3.6 101 7.6 53 4.0

ESCONDIDO 76 3.2 73 3.0 -3 -0.1

Fairbanks Country

Club

─ ─ ─ ─ ─ ─

Flower Hill ─ ─ ─ ─ ─ ─

Greater Golden Hill 6 2.2 6 2.3 0 0.0

Greater North Park 16 1.9 16 1.9 0 0.0

Harbor ─ ─ ─ ─ ─ ─

Appendix B



B-27



Location

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

IMPERIAL BEACH 7 2.1 12 3.7 5 1.6

Kearny Mesa 33 2.1 32 2.0 -1 -0.1

La Jolla 14 1.7 13 1.6 -1 -0.1

LA MESA 29 2.7 102 9.5 72 6.7

LEMON GROVE 11 2.7 39 9.5 28 6.7

Linda Vista 11 2.6 9 2.2 -2 -0.4

Lindbergh Field ─ ─ ─ ─ ─ ─

Mid-City: City

Heights

15 1.9 16 1.9 0 0.0

Mid-City: Eastern

Area

4 0.6 11 1.8 7 1.2

Mid-City:

Kensington-

Talmadge

4 1.6 4 1.6 0 0.0

Mid-City: Normal

Heights

5 2.2 5 2.2 0 0.0

Midway-Pacific

Highway

8 2.0 32 7.9 24 5.9

Mira Mesa 52 2.0 48 1.9 -4 -0.2

Miramar Air Station 3 3.5 2 2.9 0 -0.6

Miramar Ranch

North

12 3.6 11 3.5 0 -0.1

Mission Bay Park 31 2.5 28 2.2 -4 -0.3

Mission Beach 9 2.7 8 2.3 -1 -0.4

Mission Valley 101 3.0 305 9.0 204 6.0

NATIONAL CITY 21 2.3 69 7.6 48 5.3

Navajo 19 1.9 34 3.4 15 1.5

NCFUA Subarea 2 ─ ─ ─ ─ ─ ─

Ocean Beach 16 6.4 15 6.1 -1 -0.3





Location

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

OCEANSIDE 144 4.3 315 9.3 171 5.1

Old San Diego 8 10.1 9 10.5 0 0.4

Otay Mesa 30 3.7 74 9.0 44 5.3

Otay Mesa-Nestor 27 4.1 55 8.4 28 4.3

OUTSIDE SD

COUNTY

49 1.6 47 1.6 -1 0.0

Pacific Beach 16 1.9 15 1.8 -1 -0.1

Pacific Highlands

Ranch

7 4.0 14 8.8 8 4.8

Peninsula 28 1.6 35 1.9 7 0.4

POWAY 23 2.1 21 2.0 -1 -0.1

Rancho Bernardo 33 2.9 34 3.0 1 0.1

Rancho Encantado ─ ─ ─ ─ ─ ─

Rancho Penasquitos 22 3.3 23 3.5 1 0.1

Sabre Springs 6 3.4 5 3.2 0 -0.1

SAN MARCOS 61 4.1 129 8.7 68 4.6

San Pasqual ─ ─ ─ ─ ─ ─

San Ysidro 21 4.2 51 10.2 30 6.0

SANTEE 46 4.7 118 11.9 71 7.2

Scripps Miramar

Ranch

14 3.5 14 3.3 -1 -0.2

Serra Mesa 5 1.6 5 1.6 0 0.0

Skyline-Paradise

Hills

5 0.7 14 2.2 10 1.5

SOLANA BEACH 14 3.3 29 6.9 15 3.6

Southeastern:

Encanto

Neighborhoods

14 2.9 51 10.2 36 7.3

Appendix B



B-29



Location

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

Ridership per day

Transit share (%)

Southeastern:

Southeastern SD

14 2.5 57 9.9 43 7.4

Tierrasanta 7 1.8 7 1.6 -1 -0.2

Tijuana River Valley ─ ─ ─ ─ ─ ─

Torrey Highlands 3 3.8 7 7.9 3 4.1

Torrey Hills 3 3.2 6 7.0 3 3.8

Torrey Pines 10 3.2 22 6.8 12 3.6

UNINCORPORATED 124 1.1 124 1.1 0 0.0

University 58 2.3 56 2.3 -2 -0.1

Uptown 17 1.8 15 1.5 -2 -0.2

Via De La Valle ─ ─ ─ ─ ─ ─

VISTA 76 4.4 163 9.4 86 5.0


Appendix C - Calculations of Greenhouse Gas Emissions

6189001

Table C-1: Greenhouse Gas Emission Calculations

Scenario: No ProjectYear: 2005Timeframe: All calculations are on a per day basis

CalculationsCO2 = vehicle miles traveled / fuel efficiency * emission factor (CO2 / gallon) * conversion factorCH4 (in CO2 equivalents) = vehicle miles traveled * emission factor (CH4 / mile) * conversion factor * global warming potentialN2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

Car Van Units Source Assumptions / Notes1132440 71600 miles SKM data (2007) round-trip mileage

22.9 16.2 miles / gallonTransportation Energy Data Book, Edition 26 , Oak Ridge National Laboratory, 2007 (ORNL-6978)

miles per gallon based on 2005 data

van miles per gallon includes vans, pickup trucks, and sport utility vehicles

49452 4420 gallons calculation

8.55 8.55 kg CO2 / gallon emission factor from CCAR, Table C.3 fuel is CA reformulated gasoline, 5.7% ethanol

422811 37789 kg CO2 calculation0.001 0.001 metric tons / kg conversion factor422.8 37.8 metric tons CO2 calculation


0.04 0.12 g CH4 / mile emission factor from CCAR, Table C.4

car is model year 2000-present, fuel is gasoline

van is a heavy-duty vehicle with GVWR >5751 lbs., model year is 1990-present, fuel is gasoline

45297.6 8592.0 g CH4 calculation0.000001 0.000001 metric tons / g conversion factor

0.045 0.009 metric tons CH4 calculation

23 23 GWP global warming potential from CCAR Table III.6.1

1.042 0.198 metric tons CO2 equivalent calculation


0.04 0.20 g N2O / mile emission factor from CCAR, Table C.4



45297.6 14320.0 g N2O calculation0.000001 0.000001 metric tons / g conversion factor

0.045 0.014 metric tons N2O calculation



Total by Vehicle 437.3 42.2 metric tons CO2 equivalent

Scenario Total

metric tons CO2 equivalent

CH4

CO2

N2O

479.5

C-1


Scenario: No ProjectYear: 2030Timeframe: All calculations are on a per day basis



29.1 27.4 miles / gallon

The new CAFE standard is 35 mpg by 2020. The fuel economy in this table assumes that by 2030, cars will achieve 83% of this standard and vans will achieve 78% of this standard. These percentages are based on the current CAFE standard: cars must exceed an average of 27.5 mpg and light trucks (i.e., vans) must exceed an average of 20.7.

60907 4220 gallons calculation

8.55 8.55 kg CO2 / gallon emission factor from CCAR, Table C.3 fuel is CA reformulated gasoline, 5.7% ethanol

520752 36078 kg CO2 calculation0.001 0.001 metric tons / kg conversion factor520.8 36.1 metric tons CO2 calculation


0.04 0.12 g CH4 / mile emission factor from CCAR, Table C.4



70773.5 13874.0 g CH4 calculation0.000001 0.000001 metric tons / g conversion factor

0.071 0.014 metric tons CH4 calculation




0.04 0.20 g N2O / mile emission factor from CCAR, Table C.4



70773.5 23123.4 g N2O calculation0.000001 0.000001 metric tons / g conversion factor

0.071 0.023 metric tons N2O calculation



Total by Vehicle 543.3 43.2 metric tons CO2 equivalent

Scenario Total


CH4

CO2

N2O

586.6

C-2


Scenario: Preferred AlternativeYear: 2030Timeframe: All calculations are on a per day basis


Car Van Bus Units Source Assumptions / Notes1769377 115617 miles SKM data (2007) round-trip mileage

29.1 27.4 3.1

miles / gallon

(for CNG bus, units in miles / gallon of gasoline equivalent)

bus miles per gallon of gasoline equivalent from Ten Years of Compressed Natural Gas (CNG) Operations at SunLine Transit Agency, National Renewable Energy Laboratory, January 2006 (NREL/SR-540-39180)


By 2030 all San Diego buses will run on compressed natural gas (CNG).

60908 4220 0 gallons calculation

8.55 8.55 6.86

kg CO2 / gallon

(for CNG bus, units in kg CO2 / gallon of gasoline equivalent)

emission factor from CCAR, Table C.3 fuel is CA reformulated gasoline, 5.7% ethanol

520763 36078 0 kg CO2 calculation0.001 0.001 0.001 metric tons / kg conversion factor520.8 36.1 0.0 metric tons CO2 calculation

Car Van Bus Units Source Assumptions / Notes1769377 115617 0 miles SKM data (2007) round-trip mileage

0.04 0.12 3.48 g CH4 / mile emission factor from CCAR, Table C.4



bus is a CNG/LNG heavy duty truck70775.1 13874.0 0.0 g CH4 calculation

0.000001 0.000001 0.000001 metric tons / g conversion factor0.071 0.014 0.000 metric tons CH4 calculation

23 23 23 GWP global warming potential from CCAR Table III.6.11.628 0.319 0.000 metric tons CO2 equivalent calculation


0.04 0.20 0.05 g N2O / mile emission factor from CCAR, Table C.4



bus is a CNG/LNG heavy duty truck70775.1 23123.4 0.0 g N2O calculation

0.000001 0.000001 0.000001 metric tons / g conversion factor0.071 0.023 0.00000 metric tons N2O calculation


Total by Vehicle 543.3 43.2 0.0 metric tons CO2 equivalent

Scenario Total


Note:The total CO2 equivalent includes emissions reductions from decreased bus usage.

CH4

CO2

N2O

586.6

C-3


Scenario: Preferred Alternative with Airport Transit PlanYear: 2030Timeframe: All calculations are on a per day basis



29.1 27.4 3.1

miles / gallon






8.55 8.55 6.86

kg CO2 / gallon



















Scenario Total


Note:The total CO2 equivalent includes emissions reductions from decreased bus usage.

CH4

CO2

N2O

581.5

C-4


Scenario: ITC (including FlyAway)Year: 2030Timeframe: All calculations are on a per day basis



29.1 27.4 3.1

miles / gallon






8.55 8.55 6.86

kg CO2 / gallon



















Scenario Total


Note:The total CO2 equivalent includes additional emissions from increased bus usage.

CH4

CO2

N2O

533.3

C-5

Table C-6: Greenhouse Gas Emission CalculationsNot Used

Calculation: Trolley EmissionsScenario: Lindberg ITC + Green and Orange Line (Scenario 5)Year: 2030Timeframe: All calculations are on a per day basis

CalculationsMWh = miles * power consumption (kWh / vehicle km) * conversion factorCO2 = MWh * emission factor (CO2 / MWh) * conversion factorCH4 (in CO2 equivalents) = MWh * emission factor (CH4 / MWh) * conversion factor * global warming potentialN2O (in CO2 equivalents) = MWh * emission factor (N2O / MWh) * conversion factor * global warming potential

Trolley Units Source Assumptions / Notes-22 miles SKM data (2007)

1.61 kilometers / mile conversion factor-35.4 kilometers calculation

3.23 kWh / vehicle km of operation City of Calgary Transportation Department

power consumption is for Siemens SD160 Light Rail Vehicle in Calgary, Canada; this model is similar to San Diego's S70 Light Rail Vehicle

power consumption is based on actual usage (not on technical specifications), in order to account for typical operating speeds and starts/stops

assuming one vehicle per train-114 kWh calculation

0.001 MWh / kWh conversion factor-0.114 MWh calculation

Trolley Units Source Assumptions / Notes-0.114 MWh see above

804.54 lbs CO2 / MWh emission factor from CCAR, Table C.1regional electricity generation emission factor based on EPA's Emissions and Generation Resource Integrated Database (eGRID) for the WECC California subregion

-91.99 lbs CO2 calculation0.000454 metric tons / lb conversion factor

-0.042 metric tons CO2 calculation

Trolley Units Source Assumptions / Notes-0.114 MWh see above

0.0067 lbs CH4 / MWh emission factor from CCAR, Table C.2

regional electricity generation emission factors from the Energy Information Administration, Updated State- and Regional-level Greenhouse Gas Emission Factors for Electricity (March 2002) for California

-7.66E-04 lbs CH4 calculation0.000454 metric tons / lb conversion factor-3.47E-07 metric tons CH4 calculation

23 GWP global warming potential from CCAR Table III.6.1

-7.99E-06 metric tons CO2 equivalent calculation

Trolley Units Source Assumptions / Notes-0.114 MWh see above round-trip mileage

0.0037 lbs N2O / MWh emission factor from CCAR, Table C.2

regional electricity generation emission factors from the Energy Information Administration, Updated State- and Regional-level Greenhouse Gas Emission Factors for Electricity (March 2002) for California

-4.23E-04 lbs N2O calculation0.000454 metric tons / lb conversion factor-1.92E-07 metric tons N2O calculation

296 GWP global warming potential from CCAR Table III.6.1

-5.68E-05 metric tons CO2 equivalent calculation

Total for Trolley -0.042 metric tons CO2 equivalent

Conclusion:The change in GHG emissions from decreased use of the electric trolley (in Scenario 5) is insignificant compared to vehicle emissions.

Note:

MWh

GHG emissions from utility companies will decrease in the future (i.e., in 2030) due to greater use of renewable energy sources, but this has not been factored into the calculations.

CH4

N2O

CO2

C-6


Appendix D - Calculations of Criteria Pollutant Emissions

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Table D-1: Summary of Daily Criteria Pollutant Emissions - Personal Cars only

Scenario 1 2 3 4 5

Scenario Name No Project No Project % Change in Emissions

Preferred Alternative

Preferred Alternative w Airport Transit Plan Lindbergh ITC

Year 2005 2030 2005 to 2030 2030 2030 2030

pounds CO per day 13081.5 5817.2 -56% 5817.2 5706.0 5250.3

percent reduction from 2030 baseline 0.0% 1.9% 9.7%

pounds N0x per day 1374.0 480.2 -65% 480.2 471.0 433.4


pounds ROG per day 1338.9 744.1 -44% 744.1 729.8 671.5


pounds S0x per day 12.2 19.0 56% 19.0 18.7 17.2


pounds PM10 per day

95.7 171.4 79% 171.4 168.1 154.7


pounds PM2.5 per day

59.4 113.5 91% 113.5 111.3 102.4


Source: SKM/Pirnie data and Tables D-2, D-3, and D-4.

D-1

Table D-2: Estimated Daily Emissions of Criteria Pollutants for Personal Cars

Scenario

Estimated VMTcar 1132440 1769337 1769337

Criteria PollutantEmission Factor

(lbs/mile)Estimated Daily

EmissionsEmission Factor




EmissionsCO 0.01155158 13081.46954926 0.00328779 5817.20817256 0.00328779 5817.20817256

NOx 0.00121328 1373.96201828 0.00027141 480.21516061 0.00027141 480.21516061ROG 0.00118234 1338.93014314 0.00042052 744.05018617 0.00042052 744.05018617SOx 0.00001078 12.20507891 0.00001076 19.03507735 0.00001076 19.03507735

PM10 0.00008447 95.66142930 0.00009687 171.40423137 0.00009687 171.40423137PM2.5 0.00005243 59.37605956 0.00006415 113.50218214 0.00006415 113.50218214

Scenario

Estimated VMTcar 1735523 1596914 0

Criteria PollutantEmission Factor






EmissionsCO 0.00328779 5706.034848 0.00328779 5250.317589 0.00328779 0

NOx 0.00027141 471.0377142 0.00027141 433.4178921 0.00027141 0ROG 0.00042052 729.8305587 0.00042052 671.542029 0.00042052 0SOx 0.00001076 18.67129583 0.00001076 17.18009713 0.00001076 0

PM10 0.00009687 168.1285057 0.00009687 154.7007816 0.00009687 0PM2.5 0.00006415 111.3330291 0.00006415 102.4413233 0.00006415 0

Sources : (1) VMT is daily vehicle miles traveled for personal vehicles, based on 2007 SKM transit data presented in this report.

(2) Emission Factors for On-Road Passenger Vehicles & Delivery Trucks, SCAQMD Projects 2007-2026, "Most Conservative" EMFAC2007 data,South Coast Air Quality Management District CEQA Handbook (http://aqmd.gov/CEQA/handbook/onroad, accessed December 2007); See Appendix D-1.

Notes :(1) VMT data is based on Year 2005 and 2030, however, available emission factors are based on years 2007 and 2026.(2) Emission Factors derived from Peak Emissions Inventory (Winter, Annual, Summer)

(2) 2030 - No Project

(3) 2030 - Lindbergh ITC

(4) 2030 - Lindbergh ITC + Green Line

(5) 2030 - Lindberg ITC + Green and Orange Line

(1) 2005 - No Project

(6) 2030 - SDCRAA Preferred Alternative with Old

Town Shuttle

D-2

CO 0.01155158 CO 0.02407553 CO 0.00328779 CO 0.00569435NOx 0.00121328 NOx 0.02508445 NOx 0.00027141 NOx 0.00589869

ROG 0.00118234 ROG 0.00323145 ROG 0.00042052 ROG 0.00088403SOx 0.00001078 SOx 0.00002626 SOx 0.00001076 SOx 0.00002716

PM10 0.00008447 PM10 0.00091020 PM10 0.00009687 PM10 0.00027657PM2.5 0.00005243 PM2.5 0.00078884 PM2.5 0.00006415 PM2.5 0.00020187

Source : Excerpt from SCAQMD website: http://www.aqmd.gov/CEQA/handbook/onroad/onroadEF07_26.xlsNotes : a) On the basis of DOT data reviewed, the gross vehicle weight (GVWR) of cars and 6-8 passenger SUVs is <8500; 10-15 passenger vans is >8500 pounds. b) The calculation is modified for the Lindbergh ITC report as follows - Emissions (pounds per day) = VMTcar (car vehicle miles traveled per day) * EF(passenger vehicles).

Table D-3: Highest (Most Conservative) EMFAC2007 (version 2.3) Emission Factors for On-Road Passenger Vehicles & Delivery Trucks

Projects in the SCAQMD (Scenario Years 2007 - 2026)Derived from Peak Emissions Inventory (Winter, Annual, Summer)

Passenger Vehicles (<8500 pounds) & Delivery Trucks (>8500 pounds)

The following emission factors were compiled by running the California Air Resources Board's EMFAC2007(version 2.3) Burden Model, taking the weighted average of vehicle types and simplifying into two categories:

Passenger Vehicles & Delivery Trucks.

This methodology replaces the old EMFAC emission factors in Tables A-9-5-J-1 through A-9-5-L inAppendix A9 of the current SCAQMD CEQA Handbook. All the emission factors account for the emissions

These emission factors can be used to calculate on-road mobile source emissions for the vehicle categorieslisted in the tables below, by use of the following equation:

Emissions (pounds per day) = N x TL x EF

Passenger Vehicles (pounds/mile)

Delivery Trucks(pounds/mile)

Passenger Vehicles (pounds/mile)

Delivery Trucks(pounds/mile)

Vehicle Class:

All model years in the range 1965 to 2007 All model years in the range 1982 to 2026

from start, running and idling exhaust. In addition, the ROG emission factors include diurnal, hot soak, runningand resting emissions, and the PM10 & PM2.5 emission factors include tire and brake wear.

Scenario Year: 2007 Scenario Year: 2026

where N = number of trips, TL = trip length (miles/day), and EF = emission factor (pounds per mile)

D-3

Table D-4: VMT totals

Scenario VMT Cars VMT Vans VMT Vans+delta1 1132440 71600 716002 1769337 115617 1156173 1769337 115617 1156174 1735523 113210 1158905 1596914 103947 105691

Source : SKM data, GHG emission tables VMT sum of vehicle classes.

Note : The column labeled "VMT Vans+ delta" includes changes in VMT anticipated for buses and trolleys. Absent an emission factor to assess buses and trolleys, the EMFAC2007 emission factor for delivery trucks is used in this report to cover the entire category of vans and other vehicles >8500 and <30,001 pounds.

D-4

Table D-5: Assumptions for Use of SCAQMD Emissions Factors

Number

1

2

3

4

5Emission factors are provided for years 2007 through 2026. For the purposes of this evaluation, the emission factor for 2007 is used to reflect year 2005 and the factor for 2026 to reflect year 2030.

Emissions estimates consider the build-out year 2030 and baseline years 2005 and 2030 without any airport project. Emissions during demolition and construction can be substantial, for example, as projected in the SDCRAA DEIR. These emissions are not included in this screening-level evaluation for any of the airport proposals.

AssumptionEmissions calculations for this evaluation were performed for passenger vehicles only (defined by SCAQMD as <8500 pounds). Passenger vehicles includes taxis.

There is no clear comparison for the vehicle classes of “vans”, “buses”, and “trolleys” as used in this report. The SCAQMD emission factors for “delivery trucks” (>8500 pounds) may not apply directly to the passenger vehicles considered for airport-related ground transportation; consequently, these factors were not used in this evaluation.

Airport-related ground transportation does not refer to ground transportation vehicles used by airlines or the SIA to move baggage; start, move, or maintain aircraft; or provide food service or fuel to aircraft.

D-5


Appendix E – LEED Background Information

6189001

San Diego International Airport Expansion: Sustainability Analysis E-1

Appendix E – Green Airports and Green Buildings

E.1. Green Airport Concept and Framework Airports in the United States are subject to many laws and regulations enforced by the United States Federal Aviation Administration, the United States Environmental Protection Agency and state and local government agencies. Environmental regulations concern air and water quality, solid waste and hazardous materials management, natural resources, and endangered species. Moreover, U.S. airports must evaluate the environmental impacts of any airport development as required by the National Environmental Policy Act (ACI, 2007c)1. The concept of green airports addresses the challenges that airports face to comply with environmental regulations. As airports grow and air traffic increases, airport environmental footprints also increase despite significant environmental progress pursued. Green airports are looking at globally minimizing their environmental footprint and implementing proactive measures fostering environmental stewardship to further minimize the environmental impacts (ACI, 2007c). Green airport practices benefit the environment by reducing the airport global environmental footprint, generate cost-savings to the airport through the use of renewable or more efficient power sources, and improve the community’s airport image as being environmentally-responsible.

Since the Clean Air Act Amendments passed in 1990, environmental programs targeting airports, such as the Clean Airports Program in 1996 and the International Centre for Aviation and Environment in 1997, have been developed in the United States. Today, through applied research, technical activities, consideration of innovative but proven technologies and operational practices, promotion and recognition of environmental innovation, regular information sharing, education, and/or publication of guidebooks, several organizations in the United States provide resources to airports to:

1. Help better understand and address many of the environmental issues airports face [Airport Cooperative Research Program (ACRP) and Airports Council International-North America (ACI-NA)].

2. Guide future airport development and promote environmental sustainability while taking into account the needs of the local communities (CAP).

GreenSkies, an active European organization, consists of a worldwide information network of environmental organizations concerned with aviation's environmental effects. The GreenSkies network works together to exchange information and raise awareness of the issues to promote the reduction of noise and contribution to global climate change

1 References are available in the main report and are not included in the appendix.

Appendix E Green Airports and Green Buildings

E-2 San Diego International Airport Expansion: Sustainability Analysis

(GreenSkies website). In December 2007, GreenSkies announced a launch to foster better aviation practices and environmental responsibility in North America, through a large conference event in May 2008.

E.2. Green Buildings Through an overview of green buildings and the LEED Green Building Rating System, this section summarizes existing information on “green” airports and sustainable practices in buildings and other areas related to the build environment.

E.2.1. Overview of Green Building Concepts Within the broad framework of sustainability, the concept of green buildings is an expanding practice. Recent experience and research have led scientists, builders, developers, governments, and communities to realize that the design, construction, and operation of buildings have an irreversible impact on the environment. Irreversible environmental impacts of a building include the use of non-renewable resources (e.g., construction materials, energy use), water consumption, and the adverse effects of building footprint to the local ecology and potentially biologically-diverse habitats. More precisely, in the United States alone, buildings account for 65 percent of electricity consumption, 36 percent of energy use, 30 percent of greenhouse gas emissions, 30 percent of raw materials use, 30 percent of waste output (136 million tons annually), and 12 percent of potable water consumption (USGBC, 2007). These numbers should not be surprising considering that buildings include where we all live and work. However, because of their large environmental footprint buildings provide a target where environmental improvements can have a large benefit. In 2002, the United States Green Building Council (USGBC) defined the concept of “green building” as design and construction practices that significantly reduce or eliminate the negative impact of buildings on the environment and occupants. According to USGBC, the benefits of green buildings are three-fold: environmental, economic, and social. First, environmental benefits include the enhancement and protection of ecosystems and biodiversity, the improvement of air and water quality, the reduction of solid waste, and the conservation of natural resources. Second, economic benefits include the reduction of operating costs, the enhancement of asset value and profits, the improvement of employee productivity and satisfaction, and the optimization of life-cycle economic performance. Finally, the social benefits related to health and community include the improvement of air, thermal, and acoustic environments, the enhancement of occupant comfort and health, the minimization of strain on local infrastructure, and the contribution to overall quality of life.

Appendix E

Green Airport and Green Buildings


E-3

E.2.2. LEED Green Building Rating System The LEED Green Building Rating System developed by USGBC is a nationally-accepted benchmark for the design, construction, and operation of high performance green buildings. LEED was created to:

Facilitate positive results for the environment, occupant health and financial return;

Define “green” by providing a standard for measurement,

Encourage and accelerates global adoption of sustainable green building and development practices through the creation and implementation of universally understood and accepted tools and performance criteria, and

Promote whole-building, integrated design processes (USGBC, 2007). Founded in 1993, USGBC started conducting research in green buildings.

Table E-1.Basis and Main Objectives of the Five Performance Criteria for New Construction

Performance Criteria for New Construction Basis and Main Objectives

Sustainable Sites

Development and construction processes often are destructive to local ecology Selection of an appropriate project location can reduce the need for cars and reduce urban sprawl Project integration into the surroundings and become a considerate and beneficial neighbor for the lifetime of the building

Water Efficiency

Strategies to reduce potable water usage for personnel and landscaping Innovative waste treatment technologies Adaptive landscaping not requiring irrigation

Energy and Atmosphere (Energy Efficiency)

Buildings consume 35% of the energy and 65% of the electricity produced in the United States with major impacts to the natural environment Chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) have major impact on the natural environment and human health Use of renewable and alternative energy



Performance Criteria for New Construction Basis and Main Objectives

Materials and Resources

Extraction, processing and transportation of materials have major environmental impacts 30% of landfill volume consists of construction and demolition waste Reduce, reuse and recycle Use of rapidly renewable materials

Indoor Air Quality

Americans spend 90% of their time indoors Indoor air can be as much as 100 times more polluted than outdoor air Focus on material off-gassing, personal comfort, productivity and health; minimum IAQ performance

Adapted from USGBC, 2006, LEED for New Construction Version 2.2. November.

Working with a committee of diverse professionals, such as architects, realtors, a building owner, an environmental professional, a lawyer, and industry representatives, USGBC developed the first LEED Pilot Project Program in August 1998 through an open, consensus-based process (USGBC, 2006). The Pilot Program matured and evolved into the LEED Green Building Rating System Version 2.0 released in March 2000, and then into the LEED Green Building Rating System for New Commercial Construction and Major Renovations, or LEED for New Construction Version 2.2 (LEED-NC), released in October 2005. Under the LEED-NC, application standards are available for specific types of buildings, such as healthcare, school, laboratory, and retail. In addition to the LEED-NC, the LEED rating system product portfolio include a LEED standard for Existing Buildings (EB), Commercial Interiors (CI), and three pilot LEED standards, namely, Core and Shell (CS), Home (H), and Neighborhood Development (ND). LEED standards are organized around five performance criteria, including sustainable site development, water efficiency, energy efficiency, materials and resources, and indoor environmental quality. Performance criteria for LEED rating systems other than New Construction are similar. Table E-1 highlights the basis and main objectives of each performance criteria for New Construction.

Each of these performance criteria contains a list of credits. If requirement(s) under a credit is achieved, points are accumulated towards LEED certification. The minimum number of points for a New Construction building to achieve certification is 26. There are four levels of certification under LEED-NC, with the number of points to obtain shown in Table E-2.

Appendix E

Green Airport and Green Buildings


E-5

Table E-2.LEED New Construction Certification Levels

Certification Level for New Point Range Certified 26-32

Silver 33-38

Gold 39-51

Platinum 52-69

Source: USGBC, 2006, LEED for New Construction Version 2.2. November.

As a third party validation of achievement, LEED certification is a mark of recognition of quality buildings and environmental stewardship. Nevertheless, perceived barriers exist in the adoption of LEED and limit the expansion of green buildings. Some of the perceived barriers are higher first costs, lack of “green” awareness principles, and the prevalent short term budget pressures. In a 2005 study, 70 percent of stakeholders interviewed saw costs as a perceived barrier; however, 80 percent agree on the economic payback of green design (Zweig White, 2004). In addition, recent trends have shown that construction costs per square foot of LEED-certified buildings are not consistently higher than a building with environmentally-friendly goals (Davis Langdon, 2004). Although construction costs have dramatically increased overall recently, buildings are still achieving LEED-certification, but the idea that green is an added feature continues to be a problem (Davis Langdon, 2007).

E.2.3. Who Uses LEED? LEED certification is voluntary, although several local governments around the United States have included LEED concepts in their codes and have passed city ordinances/executive orders that require LEED standards for new buildings. Indeed, local, state, and federal governments (which correspond to approximately 48 percent of all LEED users) are incorporating LEED standards into their design. Other LEED users include private sector (33 percent) and non-profit organizations (14 percent). From 2001 to 2007 (as of April 12, 2007), the total number of LEED-registered projects (which indicates an intent for a building to achieve LEED certification) jumped from 321 to 7,315; and the total number of LEED-certified projects (which indicates the building received a LEED certification plaque) raised from five to 1,004.


Appendix F - Worldwide Airport Environmental Initiatives from the Airports Council International

6189001

Last updated: Wednesday, 28 November 2007

Worldwide airport environmental initiatives tracker file Airports around the world are finding innovative ways to reduce their impact upon the environment in which they operate. Each initiative goes some way to reducing airport’s footprint and contributes to the larger steps that the whole aviation industry is making in the environmental area. The following is just a small sample of some of the different schemes in place at airports.

Airfield emissions reductions Noise mitigation Recycling initiatives Winter services Water pollution reduction “Smart” buildings and energy efficiency Communications initiatives and airport-wide campaigns Intermodality and surface access Other environmental initiatives

Airport Initiative Results / notes

2

Airfield emissions reductions Seattle-Tacoma International Airport USA

Powering its auto fleet with compressed natural gas

Phoenix International Airport, USA

Alternative fuels programme PHX has used compressed natural gas for its auto fleet and bus fleet, starting in 1994 with (at that time) the largest CNG fill station in the U.S. Currently PHX has 3 CNG fill stations, 2 of which are among the highest volume public access CNG stations in the country. PHX has increased its CNG bus fleet to 98 buses (Interterminal and to the Consolidated Rental Car Center). Besides giving access for the public (the U.S. Postal Service is among those users), PHX modified its contracting process for taxis and shuttles to require CNG use in those vehicles, and now has 90 SuperShuttle vans and 174 taxicabs using CNG as a condition of their contracts.

BAA’s airports, UK Emissions reduction targets At our airports, BAA has established an absolute CO2 emissions reductions target of 15% below 1990 levels by 2010, despite a projected growth in passenger numbers of around 70% during this period. This is being achieved through improvements in energy efficiency and conservation and through increasing the use of renewable energy sources. We also continue to invest in public transport alternatives for access to airports, to encourage passengers and staff to leave their cars at home.

Auckland International Airport, New Zealand

Air traffic management techniques

Airways New Zealand has been working with Air New Zealand and Qantas in a trial to reduce fuel use and emissions as the aircraft came into land. Some flights into Auckland would be spaced to allow a glide descent into the airport from their top of descent point. Airways New Zealand main trunk manager Lew Jenkins said, "These glide descent profiles will be flown with the aircraft engines set at idle, thereby significantly reducing fuel burn and emissions," The trial is to establish what the actual fuel burn was for an arriving flight and to gauge the potential fuel savings and associated emission reductions. The trial will target Air New Zealand and Qantas 747 aircraft which typically arrived when other traffic was light, meaning minimum disruption to other aircraft. – From NZPA


Use of ground power units In partnership with the Board of Airline Representatives New Zealand (BARNZ), Auckland Airport will be the first New Zealand airport to install ground power units (GPUs). GPUs reduce fuel consumption and fuel emissions as well as noise, aircraft maintenance costs and per-passenger costs. The installation of this technology negates the use of aviation fuel as aircraft would normally have to remain powered up to maintain internal operating conditions while on the stand. Pre-conditioned air (PCA) units work in tandem with GPU units. The PCA unit will be an electric, self-contained, automatically controlled airconditioning unit that provides ventilation, cooling, dehumidifying, filtering, and optional heating of air supplied to parked aircraft. The units will be located on 10 hard stands at the internal terminal pier. As a result of the installation, airlines will reduce emissions at Auckland Airport by up to 189 tonnes per annum.

Frankfurt Airport, Germany

Hydrogen vehicle trial As part of a long-term test program co-financed by the European Union (EU), Fraport AG has started using two hydrogen-powered vehicles at Frankfurt Airport (FRA). Two A-Class cars from DaimlerChrysler will undergo practical testing on and off the airport site until the end of 2009. Fraport received the keys to its fuel-cell test vehicles last Friday at the premises of Infraserv Höchst in Frankfurt-Höchst, where the first public hydrogen refueling station in the German state of Hesse was opened earlier by Hessian state minister of economics Dr. Alois Rhiel. Fraport will take delivery of two more of same hydrogen cars at the end of next year.

Hong Kong International Airport

Green Apron Policy The airport authority adopted a Green Apron Policy as part of a number of initiatives to demonstrate commitment to corporate social responsibility and to minimse air pollution. One of the programmes is to replace our existing 43 vehicle fleet with alternative fuel or low emission vehicles over the next five years. To date, there are 3 LPG and 4 hybrid vehicles in the fleet. We have in place fixed ground power and pre-conditioned air supply at each frontal gate such that aircraft can shut down their APUs while parked at the gate.


3

Dallas/Fort Worth International Airport USA

Boiler and ground fleet renewal Energy plant upgrade project Innovative technology included new 6 million gallon thermal energy tank storage and state-of-the-art boilers and chillers and yields a projected avoided future energy use of 25 million MMBTUs over the useful life of the facilities. This reduced NOx emissions by 95 percent. 100 percent of the light-to-medium duty fleet, 72 percent of heavy duty and off-road fleet; and 100 percent of the bus and shuttle van fleet were replaced with low emissions or alternative fuel vehicles. This reduced nitrogen oxide emissions by 39 tons a year with an 86% reduction in Air Emissions. DFW has achieved an estimated 2 tons per ozone season day (475 tons a year) reduction in NOx emissions from the fleet conversion programme.

Zurich Airport, Switzerland

Fixed energy systems for aircraft (FES)

Operation of aircraft APU is subject to gaseous emissions and noise, thus often contributing significantly to the local air quality impacts and site noise impacts. To mitigate emissions and noise, fixed energy systems (FES) can be designed that provide electrical energy and preconditioned air to aircraft. At Zurich Airport all hard stands (or terminal stands, connected to the concourses by passenger loading bridges) provide FES. The use of auxiliary power units (APU) is subject to certain restrictions and the airlines are obligated to use the FES primarily. The ecological benefits of the fixed ground power systems are convincing: In 2001, a total of 118,000 cycles of aircraft equipped with APU has been recorded (of a total of 309,000 aircraft movements and 21 million passengers). The use of the fixed energy system has saved 12,170 t of fuel amounting to 38,500 t of CO2 and 75 t of NOx. The NOx reduced equals 4.3% of all airport induced NOx-emissions and 60% of all APU induced NOx-emissions.

San Francisco Airport, USA

Taxiing trials In March 2007, the airport worked jointly with Virgin Atlantic, Boeing, and FAA to conduct the first aircraft towing trial in North America. In the trial, an aircraft was towed from the gate closer to the runway, reducing the time the aircraft engines were running on the taxiway. Preliminary calculations showed that 595 pounds of jet fuel were saved and 1,709 pounds of carbon dioxide emissions were prevented without causing delays or congestion. While further study is required, if only 30% of departing flights use this protocol at SFO, 16,000 tonnes of carbon dioxide emissions could potentially be eliminated each year.

Toronto International Airport, Canada

Alternative energy sources The Airport Authority constructed a three turbine cogeneration plant at Toronto Pearson International Airport for simultaneous production of electrical power and thermal energy from natural gas. The plant is the first in a series of natural gas turbine facilities built to meet Ontario’s pursuit for alternative clean electrical generation. The Airport Authority worked closely with both federal and provincial governments to develop an Environmental Assessment process satisfactory to both levels of government. Using natural gas instead of coal results in reduced greenhouse gas, particulate, and sulfur dioxide emissions.

Noise mitigation Oakland International Airport, USA

Residential sound insulation The airport has established a sound insulation program for noise impacts associated with aircraft noise and vibration, for all residences located within the 65 to 70 Community Noise Equivalent Level (CNEL) contour to reduce interior noise to acceptable levels. Noise insulation is also offered for certain school buildings that lie within the future 65 CNEL. In some areas homes and schools outside the 65 CNEL contour have been offered sound insulation partly due to historical reasons and separate agreements although federal funds cannot be used.

Hamburg Airport Noise budget The airport’s operating licence is subject to noise limits based on the surface area of land around the airport where the noise exposure exceeds a certain noise level – Leq 62 dBA. The airport conducts continuous noise monitoring and reports annually on its operation within the noise budget.

Hamburg Airport Noise surcharge Landing fees levied upon airlines are structured according to aircraft weight and noise. For some classes of aircraft, landing fees can be a factor or 4 to 10 higher than for other less noisy aircraft.

Vienna Airport , Austria Mediation for new runway approval

Vienna Airport emabarked on a mediation process between the airport, local government and local communities regarding a possible new runway. The process took five years and was successful in achieving, not only agreement on the location and operation of a new third runway, but far reaching cooperation on issues including runway and night time operation, flight tracks and the prevention of new housing in high noise areas.


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Detroit Metropolitan Airport, USA

Residential sound insulation The Residential Sound Insulation Programme (RSIP) is one element in a larger noise compatibility plan voluntarily initiated by DTW which included the installation of noise berms around the airport’s perimeter, the acquisition of homes most impacted by airport related noise, modified air traffic control procedures, preferential runway use and aircraft engine ground run-up procedures. Residential sound insulation typically includes new acoustic windows, primary and secondary doors, attic insulation and other architectural treatments. In most homes, it also included new heating, ventilation and air-conditioning systems, allowing homeowners to keep windows closed to block noise infiltration. Seven schools were also insulated and 265 homes most impacted by aircraft noise were acquired by the programme at the appraised market value.

Recycling initiatives Seattle-Tacoma International Airport USA

Vendors recycle their coffee grounds.

The original goal was to send two tons of coffee grounds to a compost station every month. Three years later, Sea-Tac recycles 10 to 12 tons of coffee grounds a month.

Seattle-Tacoma International Airport USA

Food-donation programme Vendors give leftover pre-packaged goods to a food bank for the city’s needy.


Major recycling programme Sea-Tac went from recycling 112 tons of material five years ago to an estimated 1,200 tons this year — everything from contaminated soil to motor oil. And this year's materials are expected to bring in $40,000, while saving about $130,000 in disposal fees.

Los Angeles International Airport, USA

Electricity from waste 8,000 tonnes of food waste produced each year at the airport is used to produce methane gas which is then recycled and turned into electricity

Jersey Airport, United Kingdom

Recycling concrete Old runway concrete is crushed and recycled to be used in footpaths and other pavements – approximately 30,000 square metres in one current project.


Recycling Since 1992 Zurich Airport is operating its waste management according to an airport wide waste management concept. It governs the organisation and generally applicable principles of waste management at Zurich Airport, and includes standard requirements concerning recycling in given areas. Regarding the results 2006, Zurich had a recycling quote of 0.71 (recycling to incineration, according to the ADV Guideline “environmental key figures for airports”). Collecting waste for recycling is only one part of a complete resource life cycle. For instance: If there is no demand for recycled paper on the market, separation does not make much sense. Due to this, Unique (Flughafen Zürich AG), owner and operator of Zurich Airport, supports paper recycling not only by waste management but also by consistent using recycling paper in its administration and offices. The quota of recycling paper was 86 percent in 2006.

Stansted Airport, United Kingdom

Re-using cut grass instead of fertiliser

UK airports operator, BAA, is required to keep grass areas around the runways at a particular height to prevent birds nesting and landing, which could interfere with aircraft. So, in 2003, it started composting and recycling 2,000 tonnes of cut grass from Stansted Airport, rather than having it removed by waste contractors. The compost is left to mature for five months, and then analysed before being recycled on to the grassy areas, replacing the artificial fertiliser previously used.


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Leeds Bradford Airport, United Kingdom

General waste recycling To encourage waste reduction at Leeds Bradford Airport in the UK, initiatives have been implemented that include both aircraft and terminal waste. The airport recycles cardboard, glass, newspapers, magazines, scrap metal and large batteries, and there is a further incentive for on-site business partners to reduce their waste through a scale of charges for waste disposal calculated on the quantities of waste produced and the amount recycled.


Composting and planting The airport authority recycles 60 tonnes of food waste per year from the passenger terminal building to produce compost for use in airport landscaping. The airport sponsored an organic farming project called ‘planting love and care” which was organised by the Hong Kong Sheng Kung Hui Tung Chung Integrated Services (SKH). Participants include families from Tung Chung and members of the airport community. Young plants are nursed at individuals’ homes with soil conditioners generated from the food waste composting program at HKIA. Training courses on organic farming were given to the participants. At the end of the competition period, mature plants will be placed at the HKIA Historic Garden. The planting ceremony and experience sharing session will be held at the HKIA Historic Garden on 31 Mar 07.

Athens International Airport “Eleftherios Venizelos”

Reuse and recycle 422,000 cubic meters of treated water from the airport’s sewage treatment plants are used for irrigation. Furthermore, the extensive airport recycling programme, which is based on the “polluter pays principle”, has lead to the recycling of more than 1,740 tons of materials, such as paper, wood, plastic, glass, etc. The new recycling centre, where employees can also bring recyclables from home, and the continuing office recycling programme (mainly for paper) contribute significantly to the achievement of the 20% recycling rate goal by 2008.


Reduced 2.5 million cubic yards of excavated soil.

At the beginning of DFW Airport’s 2.8 billion capital development program in the year 2001, a protocol was established to sort, segregate, manage, test and reuse excavated soil being generated by the project work. Approximately 2 million cubic yards of soil have been excavated and stockpiled on the Airport for future use. The reuse of this material to date has saved the Airport approximately $1,500,000 in disposal costs and avoided clean soil purchase costs for capital projects.


Recycled 355,000 tons of demolition debris for on-airport cement production

A concrete recycling program was also established to reuse demolition debris generated by DFW Airport’s capital development program. Concrete rubble being generated by the demolition of existing structures and pavements were crushed to provide usable material for use as bedding for underground utilities such as storm drain pipe, temporary roads, contractor lay down yards, as base under airfield runway extensions and taxiways. To date, approximately 190,000 tons of demolished concrete has been recycled as a result of this initiative; savings to the Airport of about $1,140,000 in disposal costs and materials acquisition costs.

Oakland International Airport, USA

Airline pillow recycling

OAK is one of the first airports in the nation to participate in a pillow recycling program. Normally, airline pillows are immediately disposed of following the completion of a flight. This waste goes directly into landfills. The pillow recycling programme collects these pillows for use as insulation or as material in making furniture.

Oakland International Airport, USA

Consolidated waste and recycling programme

Prior to 2003, each airline contracted separately with a waste company, resulting in inefficient garbage disposal and inconsistent recycling. Then, in 2003, OAK worked with the airlines to consolidate their waste and recycling into one coordinated program. The airlines now recycle magazines, newspaper, cardboard and bottles, diverting over 101 tons of recycling from landfills in 2004, resulting in less waste going to the landfills and about $14,000 in cost savings monthly.

Canberra Airport, Australia

Water recycling system Canberra International Airport announced (10-May-07) plans to become the first Australian airport to recycle its water. The airport will install an Aquacell Water System at a cost of AUD1.2 million. Around 100,000 litres of water will be recycled across the airport daily from the initiative.

Portland International Airport, USA

Recycling programme The waste management programme thrives through partnerships with passengers, airlines, tenants, and neighbours. It resulted in 770 tonnes of recycled materials being diverted from landfills in 2006 alone. The airport recycled 98 tonnes of paper, plastic, and glass and composted 157 tonnes of coffee and food waste. Through an innovative food grease recycling programme, kitchen waste oils are collected and sent offsite for processing into biodiesel. Foreign language periodicals are also distributed for reuse at local schools.


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Winter services Munich Airport, Germany Recycling de-icing fluid heats

the terminal building Aircraft are de-iced on specially designated, remote areas at the airport, which are provided with a recovery system for de-icing fluids. Sprayed fluid that falls onto the de-icing areas is channelled – along with melted ice and snow – via gutters into large subterranean storage tanks. This mixture is then trucked to the recycling facility, refined and distilled, enabling the glycol-based de-icing agent to be recovered. It is then mixed with additives to produce de-icing fluid, which, after laboratory analysis and clearance by the manufacturer, can be used again. This form of recycling produces between 60% and 70% of the airport’s annual de-icing fluid requirements. The process generates ‘waste heat’ as a by-product which helps keep Munich Airport warm. When this system is in full operation, it covers a substantial share of the airport's heating requirements.

Detroit Metropolitan Airport, USA

Recycling de-icing fluid DTW has a very effective de-icing fluid management program. Airlines have agreed to perform most of their aircraft de-icing operations at four runway-end de-ice pads, where the fluid is more concentrated and thus has a value to recyclers. Spent anti-freeze is collected at these pads by an outside contractor, taken off airport, and filtered and distilled. The company produces 99.9% pure propylene glycol, which then becomes a component in other products such as automotive dashboards, anti-freeze, etc. DTW has recycled more spent anti-freeze than any airport in the world for the past seven years.


Recycling de-icing fluid Following 10 years and over $60 million of construction, the Port of Seattle implements AKART for their treatment of aircraft de-icing fluids captured on their aircraft operations areas at the terminals. The Industrial Waste Treatment Plant (IWTP) AKART diverts industrial stormwater captured in over 20 miles of collection piping systems and segregates those flows containing high concentrations of aircraft de-icing fluids into two of three storage lagoons containing over 80 million gallons of storage. With this new system, in conjunction with other process improvements and a new 20,000 foot forced main pumping system to the local POTW, over 90% of the aircraft de-icing fluid that enters the system is removed from the estimated 300 million gallons per year of processed flow. The new system reduces the hydraulic loading to the POTW by approximately 80% over sending the entire annual flow to the POTW for treatment. The remaining low concentrated runoff is treated for the removal of fuels and suspended solids and is then discharged through a deep water outfall located in Puget Sound.

Hamburg Airport, Germany

Recycling de-icing fluid Winter de-icing only takes place on sealed apron surfaces that ensures no-one of the fluid run-off can reach the soil or groundwater. Hot water is used first and glycol is only used to prevent re-icing if necessary.

Dallas/Fort Worth International Airport, USA

Recycling de-icing fluid Captured and treated five million pounds of spent aircraft deicing fluids preventing discharge to the creeks and rivers surrounding the Airport over the past five years. DFW accomplished this pollution prevention and source reduction metric by constructing seven source isolation deicing pads, capturing and storing spent glycol-based deicing/anti-icing fluids in 1.5 million gallons of underground tanks and 20,000,000 gallons above ground storage ponds, constructing super-pipes to convey captured and stored spent glycol to treatment and constructed a reverse osmosis treatment facility to remove the glycol from the collected effluents before discharging the clarified effluent to the regional publicly-owned sewerage treatment plant.


Treatment of de-icing waste By the treatment of de-icing waste, Zurich Airport follows a new approach of a spray irrigation system. A major part of the de-icing sewage (moderately contaminated) is sprayed via a sprinkler system over suitable fields at the airport. As the waste water seeps through the ground, it is cleansed through natural processes to acceptable purity levels. The idea behind this method is based on the observation that for some time a considerable amount of the de-icing agents used at the airport have been blown by the wind into the surrounding meadowland, where they have seeped into the ground and decomposed without having a detectable impact on the condition of the ground water. The pollutants decompose through a natural process involving microbiological action as they are filtered in the upper 60-90 cm of ground layer. The decomposition processes are mostly aerobic. The purified de-icing waste water then flows via the drainage system into the receiving waterway. This method relies heavily on natural processes and is relatively inexpensive. Further information: Treatment of De-icing Sewage

http://www.unique.ch/dokumente/umw_Treatment_of_De-Icing_sewage.pdf


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Water pollution reduction Auckland International Airport, New Zealand

Storm water treatment ponds All water runoff from the airfield and a number of other areas is caught by the airport’s drainage system. There are fuel catchment pits in a number of areas, to collect any excess fuel if there is a spill and between the drainage system and the discharge are eight massive treatment ponds in which the wastewater is forced it through bales of wool – this removes impurities. It is often joked by airport staff that the water discharged into the Manukau Harbour (on which the airport sits) is cleaner than the water in the bay itself – but the likelihood is that this is a factual statement

“Smart” buildings and energy efficiency Phoenix International Airport, USA

Energy efficient terminals All terminals at PHX have sophisticated Energy Management Systems with digitised controls, electronic valves, etc. and centralised control rooms.

Vancouver Airport, Canada

Solar hot water heating Vancouver International Airport Authority has installed a solar powered hot water heating system which the airport has estimated contributes to savings of nearly $90,000 and 8,569 GJ per year. The 100 solar panels have been installed on the roof of the domestic terminal building and help to heat an average of 800 gallons of hot water each hour. The $500,000 project is paid for in part through $85,000 of incentive funding through BC Hydro’s Power Smart Programme. Since 2003, Vancouver International Airport Authority and BC Hydro have worked in tandem to reduce energy consumption and energy costs at the airport. The savings associated with the installation of the solar panel heating system will add to the nearly $2 million saved to-date through various Power Smart and energy reduction initiatives already put in place at the airport.

La Palma Airport, Spain Wind power La Palma Airport has become the first in Spain to be equipped with wind power generators. The plant consists of two 660kW nominal strength wind generators that produce most of the energy need to run the airport facilities. The wind generator turbines are situated in the eastern part of the airport where they do not interfere with air navigation. Between May and November 2003, 943 MWh were produced saving 34,000 Euros.


Energy efficient buildings Auckland Airport employs an energy manager, has an asset management and control team, and uses an energy conservation committee to review performance. The international terminal is the major user of energy at the airport. Ventilation, heating and air conditioning account for about 80 per cent of the energy use in the terminal. Most of the remaining 20 per cent is used for lighting. The challenge is to maintain a comfortable ambient temperature and a bright crisp environment. Features of the terminal climate control system: A combination of efficient building insulation and intelligent control systems make terminal buildings comfortable and energy efficient. The terminal system uses natural light as much as possible; integrates the flight information display system and the building management system. This means that temperature, air conditioning and lighting are automatically adjusted depending on weather, daylight, and the numbers of arriving and departing passengers; uses daylight sensors, timers and motion detectors to minimise unnecessary light use

Hamburg Airport New terminal features The new Terminal 1 now features a rainwater utilisation system, a thermo-labyrinth has been built to pre-warm or pre-cool outside air and to reduce air conditioning needs, and water-saving tap filters are used throughout the building. Other features include a new water softening plant, reduced indoor heating temperatures and hangar illumination levels.


Stabilisation of the energy consumption

One of the requirements attached to the building permit for expansion stage 5 was that, following its completion, energy consumption at Zurich Airport has to be stabilised at the 1994 level. An audit carried out 2006 validated that this ambitious objective has being met. Further information: Energy Management at Zurich Airport

Chicago Airports, USA Solar panels The Department of Aviation unveiled a 3,860 square-foot green roof and solar panel array atop the Chicago Fire Department’s Rescue Building #3 at O’Hare Airport. Recently, a solar panel array was installed on the roof of the firehouse at Midway Airport.

http://www.unique.ch/dokumente/umw_Energy_Management.pdf


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Arlanda Airport, Stockholm, Sweden

Climate neutral The LFV Group operates Arlanda Airport and is the first major Swedish business to choose to become climate neutral. This means that LFV is now able to offer goods and services that are produced without negative impact on the climate. A climate neutral enterprise calculates and reduces its carbon dioxide emissions via an effective action programme. An audit is carried out annually and those emissions that the enterprise could not eliminate can be compensated for by the purchase of emission reduction units or certificates that show emission reduction measures have occurred elsewhere. Actions taken to reduce emissions of such gases will lead to reduced costs as fewer certificates will have to be purchased. Greater emphasis is placed on, for example, energy-saving actions, as these will be more profitable than previously.

Boston Logan Airport, USA

LEED-certified terminal building The Massachusetts Port Authority and Delta Airlines opened the new Terminal A at Boston Logan International Airport in 2005. The Terminal was the first in the country to be certified by the Leadership in Energy and Environmental Design (LEED) rating system and the U.S. Green Building Council. The project included such elements of sustainable design as alternative transportation options, a special storm water filtration device, a heat island membrane, mechanisms to enhance water efficiency, daylighting for energy efficiency, use of sustainable materials, and measures to enhance indoor air quality. The airport has realized 12 percent energy savings, equating to almost $300,000 annually, and 36 percent water savings (or 1.7 million gallons per year).

San Francisco Airport, USA

Solar Panels on roof San Francisco International Airport Terminal 3 now boasts more than 2,800 solar panels on its rooftop. The solar panels were implemented as part of the San Francisco Public Utilities Commission and SFO's joint solar energy project to help reduce energy use. The new energy system will provide enough electricity for all of the daytime lighting needs within Terminal 3 with excess power to spare. The solar panels will save enough energy to power about 300 homes each year. In addition, utilising the solar panels as opposed to typical energy generating methods that require fossil fuels will save approximately 7,200 tonnes of carbon dioxide over a period of 30 years.

Airport-wide education or communications programmes

San Diego Airport, USA Recycling education programme

San Diego International Airport’s recycling programme boasts 50 recycling bins through the terminals collecting paper, glass bottles, cans and plastic drinks bottles. The airport doubled its recycling efforts to 250 tonnes per year in 2003 and has published an educational handbook in Spanish and English explaining how its recycling programme works and what can and cannot be recycled. The airport also promotes an educational anti-littering campaign called “Don’t Trash California”, the aim of which is to reduce the amount of litter in and around the airport by recycling wherever possible. Recent follow-up initiatives have included a sponsored ‘house-cleaning’ event at the airport that gave airport staff and tenants the opportunity to dispose properly of items that can no longer be classed as general rubbish, such as old computers, batteries and fluorescent light bulbs. More than three tonnes of electronic waste was collected and either recycled or disposed of during the week.

Aeroport de Paris Environment Partners Club As part of their work on the environment, Paris-Charles de Gaulle and Paris-Orly airports opened their Environment Partners Clubs in 2003 and 2005 respectively. The purpose of these structures is to commit companies operating at the airports to implementing an Environmental Management System covering their operations and to thereby make Paris-Charles de Gaulle and Paris-Orly truly environmentally friendly airports. Today, these Clubs, in addition to offering a resource centre for best environmental practices, are becoming the new driving forces behind the airport Environmental Management Systems. The Environment Partners Clubs at Paris-Charles de Gaulle and Paris-Orly airports operate on the basis of the three pillars that form an Environmental Management System: gathering information, training staff/raising their awareness and self-evaluation to foster improvements. www.ecoairport.fr (FR)

http://www.ecoairport.fr/


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Auckland Airport, New Zealand

“Greening the airport” programme

Greening the Airport is an Auckland International Airport Limited (AIAL) strategy developed to raise environmental awareness amongst staff. The strategy involves encouraging airport staff to participate in environmental initiatives and to build environmental awareness into their everyday working life. By motivating staff to carry out environmentally beneficial actions, the airport’s overall environmental impact is reduced. Greening the Airport focuses on resource efficiency, waste minimisation and energy conservation. Specific initiatives being developed include increasing recycling facilities, lowering office paper consumption, energy conservation education and such small initiative as replacing water cooler plastic or paper cups with glasses that can be washed and reused.. The long-term goal is to encourage other airport-based companies to implement the Greening the Airport programme.

Chicago Airports, USA Green education programme Green-themed kiosks are sprouting up throughout the terminals at O’Hare and Midway Airports as part of the Chicago Department of Aviation’s second annual “Month of Environment.” The informational kiosks aim to educate travellers about the City of Chicago’s green initiatives and provide information about what they can do to recycle while at the airports. In addition, the Department of Aviation’s Environment Office will distribute environmentally friendly-themed activity books to children, and bookmarks and postcards to travellers at both airports during the month of April. The Month of Environment kiosks are part of an ongoing public education campaign that encourages everyone to work together to conserve and protect the environment, and improve the quality of life for all Chicagoans. The 22 informational kiosks provide travellers with practical tips and ideas that promote best practices, such as: turning off water faucets when not in use; saving coffee grounds for compost; using public transportation to alleviate traffic and minimise air pollutants; purchasing recycled products; and recycling appropriately.


Airport Environmental Best Practice Competition

The 2007 competition is is the 4th airport-wide competition with our business partners. The purpose is to promote environmental best practice across the airport community. Past year’s themes include green office, energy management and green restaurant. This year’s theme is air quality management. All participants benefit from learning about and incorporating environmental best practices into their daily operation in terms of process improvement, waste reduction, as well as monetary and energy savings.

Intermodality and surface access – getting to and from the airport Heathrow Airport, UK “Changing Direction” – the

airport travel plan This airport staff travel plan covers the 70,000 employees at Heathrow Airport and covers travel to and from the airport as well as around the airport itself. Free and discounted travel on public transport, employee car pooling, incentives to walk or cycle to the airport and emissions checks for vehicles are all part of the scheme that has been running for a number of years. www.baa.com/assets//B2CPortal/Static%20Files/travelplan.pdf


Landside traffic (modal split) Another requirement attached to the building permit for expansion stage 5 was that the modal split of landside traffic at Zurich Airport has to be established at the level of 42%. The survey carried out in autumn 2003 and evaluated in spring 2004 showed that the proportion of people using public transport to travel to and from the airport (= modal split) has reached 43 percent, and has thus surpassed the level stipulated. It is estimated that more than 59 percent of passengers travel to the airport by rail or bus, while the proportion of employees using public transport is slowly increasing to around 28 percent.


“lift” – the airport travel plan Auckland International Airport has developed a staff travel plan for the airport. The travel plan, called lift, initially encompasses staff from Auckland International Airport Limited, Air New Zealand, Customs, the Ministry of Agriculture and Forestry (MAF) and the Aviation Security Service (AvSec) – these represent nearly 60% of the 10,000 people who work on-airport. The lift programme will find ways to make travel to work more attractive, fun and user-friendly. It is about taking steps to help airport employees to better understand travel choices and reduce their reliance on bringing their own vehicles to the airport. Initiatives include car pooling, encouragement of sue of public transport and more flexible working. The goal has been to encourage people to car pool once a week, or use public transport once a fortnight – setting a reasonable and achieveable goal that makes a difference. www.liftataucklandairport.com

http://www.baa.com/assets//B2CPortal/Static%20Files/travelplan.pdf

http://www.liftataucklandairport.com/


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Boston Logan, USA Preferred parking for environmentally friendly cars

Drivers of hybrid and alternative-fuel vehicles get preferred parking at Boston Logan. The airport has set aside about 100 parking spaces that are close to the elevators. The environmental programs are part of Massport's Earth Day celebration. Taxi drivers with hybrid cars can also get in front of the line twice in a 12-hour shift. Taxi drivers typically wait 30 to 60 minutes in the taxi line. Since last year, the city has been trying to encourage operators to buy more hybrid or alternative-fuel cabs.

Madrid Barajas Airport, Spain

Direct metro from city centre Barajas International's new Terminal 4 now has its own Metro subway station, in addition to the one in Terminal 1. The city expects more than 20,000 people daily (17 million a year) to use the extended Metro line. Travel from the airport to downtown takes about 20 minutes. Along with London Heathrow, Madrid's is one of the few airports in the world with two Metro stations.

Auckland Airport, New Zealand

Priority car parking for efficient vehicles

Auckland Airport is encouraging the use of hybrid and fuel-efficient vehicles as part of its mission to “green the airport”. The airport will set aside car parks specifically for hybrid and smaller-engine vehicles as part of its plan to reduce fuel consumption and engine emissions. Initially, 21 priority spaces will be allocated for use by low-emission vehicles in the public car park and 4 in the staff car park. Seven spaces will also be allocated for fuel-efficient cars (up to 1.8-litre capacity). New additions to the airport company’s vehicle fleet are a Hyundai Getz and a VW Polo BlueMotion – the world’s lowest carbon dioxide-emitting production car. The five-door Polo emits just 104g of CO2/km and can travel 1,184km on a single tank of diesel.

Other environmental programmes Phoenix International Airport, USA

Urban Heat Island Studies PHX is working with Arizona State University and the National Center for Excellence on the impacts of pavements to urban climate. Heat is retained in pavements and does not dissipate during the night, the build- up of which can cause changes in weather patterns around Cities. Design, materials testing and demonstration projects are being performed by ASU, and PHX has assisted by allowing alternative-type pavement installation and controlled testing of properties and temperature retention characteristics in areas of the airport. A report is forthcoming. Also, PHX and ASU worked together to design crumb rubber (recycled from auto tires) / concrete benches that result in cooler bench surfaces and are easier to move as needed for operational changes.


Waste Reduction Framework To further help waste minimisation and support the HKSAR Government’s waste reduction framework plan, the AA launched the “No Plastic Bag Shopping at HKIA” campaign in Mar 07 to retail shops at T1 and T2. Reusable shopping bags are available for sale inside both T1 and T2.

Athens International Airport, Greece

Green Areas In the last 5 years, five Green Area projects have been constructed (total area of 6 hectars) by the Airport, at the surrounding community. These projects, which include theatres, playgrounds, walking paths, planted areas, etc., contribute to the protection and improvement of environmental conditions.


Insulation programme The Hong Kong Airport Authority collaborated with Hong Chi Association and other corporations to organize the “2006/2007 Roof Greening Competition for Primary and Secondary Schools in Hong Kong”. The objective is to encourage students’ participation in roof greening to reduce building temperature. Training workshop was held at the Hong Kong Baptist University in Dec 06. Basic planting materials were provided to the schools and the award ceremony will be held at JW Marriott Hong Kong in May 07.

Chicago O’Hare Airport, USA

Modernisation programme The City of Chicago’s O’Hare International Airport Modernisation Program will reconfigure O’Hare’s intersecting airfield layout, reducing delays and increasing capacity at the airport. O’Hare developed a Sustainable Design Manual to achieve environmental improvements while providing long-term sustainability, economic benefits and improved quality of life for Chicago’s citizens and businesses. The Sustainable Design Manual addresses issues such as brownfield development, water efficiency, optimising energy performance, recycling, indoor environmental quality, air quality, and construction practices.


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Detroit Metropolitan Wayne County Airport, USA

Wetlands area development Received an award for a newly created wetlands area. Due to increased air traffic demand, expansion at the airport resulted in impacts to over three hundred acres of wetlands. The airport purchased land twelve miles southwest of the airport to create new wetlands (referred to as Crosswinds Marsh) to compensate for the losses due to expansion. Crosswinds Marsh, the largest wetland site in Michigan and the Midwest, provides sanctuary to wildlife while also providing outdoor activities enjoyed by members of the Detroit community.

Southwest Florida International Airport, USA

Nature reserve establishment Mitigation Park was established to offset environmental impacts associated with the long-term development of the airport. The park is 7,000-acres of preserve owned by the Lee County Port Authority that will be managed for the long-term by Florida Wildlife. Enhancement activities to be completed in the park will improve the quality of the natural environment and result in a net benefit to the region. Establishment of the park has led to streamlined permitting of airport development at Southwest Florida International Airport.

Atlanta International Airport, USA

Runway construction aggregate delivery

The airport turned to a state-of-the-art, overland belt conveyor system that transported 93 percent of the 21.5 million cubic yards of fill necessary for the runway’s construction. The programme resulted in reduced truck trips on local roads, elimination of truck-generated air emissions, and diversion of a significant amount of construction material waste from landfills.

Stockholm-Arlanda Airport

1,800 green flights completed at Stockholm-Arlanda

About 1,800 green flights have been implemented at Stockholm-Arlanda Airport, with aircraft “coasting” from cruising altitude down to the runway. This means less fuel consumption, emissions and noise. Green flights are based on collaboration between an aircraft’s flight management computer and the technical systems used by air traffic controllers. Through a data link, all affected parties can have real-time access to the same information about a given flight. Arrival time can be calculated more exactly, which simplifies ground handling at the airport. In a Boeing 737, the savings potential from green approaches averages 150 kilos of aircraft fuel or about 475 kilos of carbon dioxide emissions per landing at Arlanda. For a long-haul aircraft, which is larger and heavier, the savings potential is about 200- 300 kilos of aircraft fuel or some 600 – 950 kilos of carbon dioxide per landing.

Munich and Frankfurt Airports, Germany

Economic incentives Munich and Frankfurt airports have announced plans to introduce an emission-linked component in take-off and landing fees for a three-year test phase. The pilot project was developed by the German Airport Transport Initiative in consultation with the Ministry of Transport, Building and Urban Affairs, and will introduce a charge of 3 euros per kilogram of nitrous oxide (NOx) emissions for all airlines landing in Frankfurt and Munich effective January 1, 2008.

Johannesburg International Airport, South Africa

Soweto tree planting Airports Company South Africa (ACSA) has committed to the Soweto Greening Project in a bid to preserve and boost the appeal of the environment in the sprawling township. In a planting ceremony led by ACSA staff members, a total of 400 trees were committed to be planted along the June 16 tourist route which spans about four kilometres in total. The project is a partnership between ACSA and Johannesburg City Parks and aims to keep the environment tourist-friendly. The planting of the trees in Soweto is part of ACSA’s corporate social investment (CSI) programme.

If you know of environmental initiative that are occurring at airports and are not included on this list, please email details to Haldane Dodd or Xavier Oh at ACI World Headquarters for inclusion.

mailto:[email protected]?subject=Environment%20Tracker%20File%20addition

mailto:[email protected]?subject=Environment%20Tracker%20File%20addition

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San Diego International Airport Expansion Sustainability Analysis

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