Carpool Effects on Air Quality in Los Angeles

Carpool Effects on Air Quality in Los Angeles

Lan Shi, Jikun Lian, Yu Wan

Table of Contents

Abstract

This Report is focusing on the functions and positive impacts that can be brought by carpool system. The

research team has focused on one of the largest metropolitan in U.S.--Los Angeles. Having researched the

current traffic situation, the project team has figured out that the current traffic congestion is very heavy

in Los Angeles. Furthermore, the current environmental issue related with traffic congestion is very

significant. Based on the vehicle increasing data by Eric Wilson, the traffic volume has kept an increasing

rate of 14% in the past 6 years. Furthermore, the air pollutants, including NOx, HC ROG, and CO2, has

an over 11% increasing rate in the past 6 years, and the light duty automobiles are the main contributor to

this situation.

Having analyzed the current background, our team proposed an adequate solution pattern based on

carpool system. The current carpool system is very developed in United States, and the carpool market in

Los Angeles has a great degree of vacancy for future development.

The project team analyzed the potential benefits in two different aspects. First of all, the improvement on

congestion and environmental issue. The project team use the database provided by California

Environmental Protection agency—EMFAC. By researching on the data from year 2010, 2020 and 2030

in the south coast area, the detailed emission rate of different kinds of pollutants along with the speed

categories will be shown. After that, the project team researched the increasing rate for car sharing in the

south coast area, and the percentage of self-driving and car sharing will be known. Then, based on the

emission rate change with the 20 years period, the influence of car sharing will be noticed.

The second point will be the congestion, having searched the increasing rate of vehicle in the entire U.S.

region. Then the team continues the research by focusing on the traffic volume increase in the south coast

area. Then traffic volume change will not only related with the car sharing effect, but will have some

influence.

Last but not least, the project team evaluate the revenue of the carpool system. There are two different

way of charging the riders. By charging the optimal price, which is the price where marginal rate equals

to marginal benefits, there will more riderships in the metropolitan area. However, the government need

to subsidies the carpool system for future operation. If the company charge the riders on the equilibrium

price, the carpool companies will have enough revenue to operate by themselves, but not enough people

will consider use carpool since it is a bit expensive.

1, Introduction

Los Angeles, one of the most prosperous metropolitan in U.S. Having enjoyed a booming industrial

development in the last century, Los Angeles has been constantly developed for over 100 years without

any big issues. Nowadays, as the number of employment increasing in an enormous speed in the

metropolitan area, an increasing number of people are attracted by the charisma of this great city, and thus

in turn caused very heavy traffic issue in this area. Based on Car Sharing: A New Approach to Urban

Transportation Problems by Richard Katzev, the Between 1990 and 2000, the proportion of commuters

driving alone increased from 73% in 1990 to 76% in 2000. Nationally, transit ridership remained fairly

stable at approximately 5% of the commuters. It is obvious that the increase on traffic volume is very

significant.

Figure 1-1 The Trend of Carsharing

With the increase on current traffic volume, the related problems were brought to Los Angeles as well.

The L.A., Bakersfield area has remained as one of the most polluted cities in the last 7 years (Margot

Roosevelt, Los Angeles Times, 2011). Because of heavy pollution came from the traffic emission and

industrial development, the Bakersfield area has very heavy ozone and toxic particles contents. From the

“State of Air report”, more than 90% of the Californian live in unhealthful air conditions, and most of

them pollution came from transportation field. The research results of Walsh can also be a strong support

on this point. Automobile are a major source of carbon dioxide, which may claim as the

Another influence on the increasing number of vehicles is the traffic congestion. Based on Richard

Katzev’s idea, the traffic tie-ups, especially during commute times, are estimated to cost the United States

1.2 billion hours of lost time and 2.2 billion gallons of gasoline each year, to say nothing of the estimated

$30 billion annual loss in productivity alone.

So what will carpool system brought to us? Based on Richard Katzev’s concepts. The benefits of car-

sharing is mostly focused on two sections: The environmental impact and congestion impact. In most of

the metropolitan areas, especially Los Angeles, self-driving has always been considered to be the most

efficient way for commuting. Every single work day, over million of vehicles passing through the main

highway connection of the Greater Los Angeles area, and very heavy congestion happen everyday. With

the increasing number of waiting cost keep accumulating on the transportation model, every single driver

in the waiting line will face a comparatively high marginal cost if they choose to enter the current traffic

system (Authur, 2014). If car-sharing system can be applied on the traffic system, the passengers per

vehicle will increase, this in turn will decrease the number of vehicles, and relieve the level of congestion

in certain degree.

The environmental issue is mostly caused by the waste gas emitted from vehicles. Based on the AQI

standards, five different pollutants: Ozone, floating particles, NOx, SOx and CO, are the main

components of the air pollution. All of them are created from incomplete fuel combustion. Even though

the technology internal combustion engine has developed in a large degree, the air pollution is still very

heavy in recent years. By applying carsharing system in certain area, this situation will be ameliorated.

First of all, with the number of vehicles decreasing, the total emission inventories will correspondly goes

down to the lower level. Second, according to survey data, most of the carsharing companies in U.S.

applied brand of cars like Honda, Toyota, Tesla, etc, which are fuel-saving types of sedans (U.S. Bureau

of Census, 2001). Based on these aspects, Carsharing will improve our air quality in a large degree.

Ride sharing or carpooling also continued to be a very developed system for future traffic development

trend. Based on the ideas from Richard Katzev, carsharing is based on the distinction between automobile

access and ownership. Carsharing divorces the notion of automobile use form ownership by providing

individuals with convenient access to a shared fleet of vehicles. In this perspective, carsharing system will

grow into a competitive alternative to private ownership of property. CarSharing system will not only

bring the convenience to our society, but will move the economy from market-based to access-based,

where people can find service based on their need rather than ownership (Rifkin, J, 2000). The future plan

to carsharing system is to build an efficient and self-adjusting traffic system in which customers can enjoy

their traveling and simultaneously, create energy-saving and environmentally friendly society with their

own efforts.

2, Background

a. Traffic condition: car number and congestion.

The purpose of this project is to conduct research on how carpool can relieve the traffic pressure and

improve air quality in Los Angeles. The project is absolutely necessary and important since transportation

pressure has become one of the most significant issues to prevent future development of Los Angeles.

Congestion has harassed the urban traffic system for a very long time. Congestion increases travel time,

air pollution, carbon dioxide emissions and fuel use due to the inefficiency of automobile operation, the

time that American waste sitting in traffic is more than quintuple between 1982 and 2005.

The main contributor to traffic congestion is the increasing number of cars, a report from 2000 census

measured the percentage of household that did not own or otherwise have access to an automobile, only

16.53% of the Los Angeles household did not own a car, this ratio is lower than most of other cities, that

means people in Los Angeles rely more on private cars.

However, from the perspective of sustainable development for future transportation, continuously

increasing the number of private cars is not a good idea, instead, developing public transportation and

increase the usage of cars can benefit both the transportation and the environment. The following graph

shows the American Community Survey in 2008, Los Angeles’s condition is unsatisfactory.

Figure 2-1 Commuting by Public Transit

The following table indicates that the congestion in Los Angeles is more serious than NYC and Chicago.

This is firstly because of the high ratio of private cars in LA, and it’s also a result of the relatively

undeveloped public transportation infrastructure.

Table 2-1: Congestion Cost of LA, NYC, Chicago

Such traffic conditions and the large number of private cars brings enormous potential to carpool service.

b. Environmental Impact from the Traffic

Air Quality Index, also known as AQI, is a good indicator of air quality created by The U.S.

Environmental Protection Agency (U.S.EPA). The AQI is calculated based on the levels of five major

pollutants in the air, including ozone, suspended particles, carbon monoxide (CO), nitrogen dioxide

(NO2), and sulfur dioxide (SO2).

Based on EPA’s data, the AQI of Los Angeles last year is 61.2, which is above the California

Mean AQI (40), and U.S. Mean AQI (38.9). Indeed, the congested traffic in Los Angeles causes serious

impacts on the environment in the city. Although the smog and soot levels have dropped significantly in

Southern California over the last decade, the Los Angeles region still has the highest levels of ozone

nationwide, violating federal health standards an average of 122 days a year (Tony Barboza, 2014).

Specially, Los Angeles have the nation’s highest levels of ozone and fine particle pollution.

c. Current Carpool

To effectively relieve the air pollution, carpooling is an innovative approach that can be applied. In order

to drive one of the vehicles in the fleet, car-share members simply telephone the organization’s

reservation system or book it online. To pick up the car, they need only walk a short distance to the

nearest site of the organization’s cars. A variety of vehicle types are usually available in the fleet to give

members an efficient way to meet infrequent needs, such as hauling, moving, and transporting large

groups. The car-sharing organization pays all of the costs of vehicle maintenance, service, and repairs.

The same is true for insurance coverage, parking, and the cost of gasoline. (Richard Katzev, 2003)

By 2011, carpool shares 9.7% of the people in transportation. It’s quite a large part, but still less than its

percentage in 1970(more than 20%). However, with the development of the internet and mobile apps,

carpool now is much more convenient and efficient. Many application of carpool has come to people’s

vision, such as Uber. Additionally, the current policy is positive for carpool since it encourages people to

make fully use of their cars, as the appearance of high-occupancy vehicle (HOV) lanes, which is a

dedicated facility to carpoolers.

3. Research Methodology

For this methodology, it has 2 parts.

The first part is mainly concerned with the reduction of emissions, the implement of expected carpool

service is one important variable, the emission analysis will firstly estimate the emission of some

polluting gases (suspended particles, carbon monoxide(CO), nitrogen dioxide(NO2), and sulfur

dioxide(SO2)) without the application of carpool service(the original data from EMFAC), and then

consider the emission condition in 2025 with carpool service, after calculation, the reduction of each kind

of polluting gas could be discovered. In addition, in order to analysis the extent of the previous emission

reduction, the time will be introduced into analysis. Apparently, with the large number of carpool

vehicles, the emission will reduce, if some year without carpool service after 2025 in the future(eg. 2030)

has the approximately the same emissions with the optimized result in 2025, the effectiveness of

emissions reduction from carpool can be measured as five years’ progress.

The second part is concerned with the social benefit, undoubtedly, the implement of carpool will reduce

congestion and reduce fuel consumption and emissions, hence, the benefit includes the saved congestion

cost and the saved environmental cost, each benefit could be measured; on the perspective of carpool

service’s cost, this data is relatively harder to investigate, however, the cost to provide these service is

mainly for the vehicle cost, once the congestion and environmental benefits of carpool is larger than its

cost, that means it will be worthy to be implemented.

From one website of car sharing, some data is shown and is helpful to this project.

In 2010, the number of carpool vehicle in North America is 10405, it’s average growth rate in its past ten

years(2000-2010) is 53%, the estimated number of it in 2025 is 6,132,157, if Los Angeles be put into

analysis, and multiply its population proportion, the number of vehicles used for carpool is 315,368, in

order to make the analysis clear, the project team made an assumption that each carpool vehicle takes 3

passengers, and reduces the use of 2 private cars. That means in 2025, if the carpool service maintain the

stale growth, there will be a reduction of 630,736 cars in 2025, that’s a 5.4% reduction of total vehicle

number (the estimated vehicle number of Los Angeles in 2025 is 11,704,904 due to the EMFAC

database).

3.1 Reduction of emission in 30 years.

3.1.1 Introduction to methodology

The first methodology applied on this model is the year reduction of emission. In this model, a

comparison between former emission rate and future emission rate are calculated. Based on the total

number of vehicles existed in this area is researched and conducted. Based on the EMFAC emission

software, the emission rate of different types of waste are surveyed as well. Only the AQI required wasted

will be listed. Then, from the data surveyed by CarSharing Association, the annually increasing rate of

total vehicles and riderships in U.S. will be conducted. This number will be processed further by

combining the population distribution of the entire U.S. Since the vehicle riderships are strongly bonded

with the population and the prosperity of a metropolitan area, this inference is rational. In the end, the

deduction rate of light duty automobiles will be reached. This number will only engage with the LDA

rather than the entire number of vehicles. So the emission rate will be conducted in this equation:

𝐸1 ∗𝐸1−𝐸2 ∗𝐸2

𝐸1−𝐸2

E1: The total emission rate before carpool

V1: Total number of vehicles before carpool

E2: The emission rate of light duty automobile before carpool

V2: Number of vehicles that carpool can deduct.

The new emission inventories will only be the E1*V1-E2*V2. This will be the final emission inventories.

It will be utilized to compare with the former emission inventories.

3.1.2 Calculation and Data Analysis

The base year of our analysis is 2010, and we choose 2025 and 2030 as two future years that are going to

be estimated and compared.

Based on the location and terrain of Los Angeles, in the website of EMFAC, the options we did are as

follow:

Data Type Emission Rates

Region Air Basin ~ South Coast

Calendar Year 2010, 2025, 2030

Season Annual Average

Vehicle Category EMFAC 2011 Categories - All

Model Year Aggregated

Speed Aggregated

Fuel All

Table 3-1: The Parameters used in EMFAC

The data type will be emission rate instead of emission inventories, since the emission rate is a more

precise number for future prediction rather than emission inventories. The region will be concentrate on

the South Coast of the Air Basin area, which covered the entire portion of the Greater Los Angeles Area.

Model year and speed will be aggregated values and the fuel will contain both gasoline and diesel.

First of all, the basic emission rate data are conducted from the EMFAC software, based on the standards

showed above, the emission rate of year 2010. 2025 and 2030 are extracted. Then based on the emission

rate factor composite from different types of vehicles, the emission rate will be merged into a new table

which only show the total emission rate on different waste on that year.

The next step is the combination with the carpool deduction. The vehicle number of Los Angeles area is

11,704,904 (CarSharing Association, 2010). The carpool service has a stable increasing rate of 5.4%,

which means a reduction of 630,736 light duty automobiles will be conducted in 2025. This number will

be V2 in the equation we had above. The corresponding value will be:

V1=11704904 vehicles

V2=630736 vehicles

E1=0.9392 grams/miles-veh

E2=0.6516 grams/miles-veh

Based on the equation we had before, the new emission rate and new emission inventories are shown

belong.

Before Carpool

Emission Rate

CO_RUNEX NOX_RUNEX PM10_RUNEX PM2_5_RUNEX SOX_RUNEX

(gms/mile) (gms/mile) (gms/mile) (gms/mile) (gms/mile)

0.939158563 0.108783009 0.002980018 0.002757752 0.004177149

Emission Inventories



10992760.82 1273294.675 34880.82335 32279.21975 48893.13361

Table 3-2: Emission rate and emission inventories before carpool

After Carpool

Emission Rate



0.955535158 0.111541215 0.003028679 0.002802491 0.004208752

Emission Inventories



10581756.87 1235226.152 33540.10531 31035.25454 46608.42551

Table 3-3: Emission rate and emission inventories before carpool

Based on the table we had above, the emission inventories before and after carpool effect are all

calculated for year 2025. From the table, it is obvious that the emission inventories of CO will decrease

from 10992760.82 grams/mile to 10581756.87 grams/mile. The decreasing rate is 3.739%. Other

corresponding emission rate deductions are also shown at the tables below.

Figure 3-1: Carpool Effect On Emission Rate

Figure 3-2:Carpool Effect On Emission Inventories

Figure 3-3: Carpool Effect on emission Inventories

Additionally, the impact will be more obvious if the scope is widen to the yearly increase. Without the

effect of carpool, the emission rate of different pollutants will decrease as well due to green belt system

and internal combustion engine upgrade. However, the change of emission rate will show different if the

comparison is made along the timeline change. In the graphs below, the emission rate of different types of

pollutants are all compared on the timeline change. It is obvious that the carpool effect make the emission

rate level in 2025 to a degree which the non-carpool effect need more than 5 years to reach.

Figure3-4:CO emission Inventories Change In 10 Years

Figure 3-5: NOx Emission Inventories Change In 10 Years

3.2 Comparing between benefit and cost of carpooling application

3.2.1 Introduction of methodology

In order to make quantitative analysis of carpooling application to prove its effectiveness, the

corresponding benefits and cost need to be calculated. Carpool has two major benefits, reducing the cost

of environment impact and the cost of congestion. Thus, the total benefit equals to the cost of

environment impact adding the cost of congestion. While for the cost of carpooling application, it should

be the cost to popularize the carpooling application. However, the related data is hard to obtain, and a

substitutive method should be used. Since the carpooling corporations do not pay any salary to the drivers,

it can be assumed the only output is the money spent on the vehicle. If the benefit of carpool is greater

than the cost buying the carpooling vehicles, it can be concluded that the benefit must surpass the cost to

popularize carpool.

3.2.1 Data Collection

3.2.1.1 Benefit of Carpool To figure out the benefit of carpool, the differences between calendar year 2010 and 2025 of the cost of

environment impact and congestion should be calculated. The cost environment impact can be

represented by the cost of wasted fuel due to traffic delay. Based on an report released by Texas

Transportation Institute at Texas A&M University in 2011, top 10 most congested corridors in USA was

obtained. Seven of them were in Los Angeles and are shown in the following Figure. Based on the data,

the total fuel wasted and cost of congestion of the seven congested highways are 22.71 million gal./yr.

and $1631.31 million/year, respectively. Since the seven top congested highways are quite representative,

their result of the cost of fuel wasted and congestion can be used to simulate the ones in Los Angeles in

calendar year 2010. Using a linear relationship model and knowing the total amount of vehicles in the

seven top congested highways are 721798 and the number of vehicles in Los Angeles in 2010 is around

10375850, the total fuel wasted and cost of congestion of Los Angeles in 2010 are 326.46 million

gallon/year and $23 billion, respectively. To calculate the total cost of environment impact, an assumption

that the average gasoline price is $3 among all year is made. Therefore, the total cost of environment

impact is $0.97 billion in 2010.

Since the number of vehicles in 2025 is approximately 11704904 using the data in EMFAC, the number

of vehicles in Los Angeles applying the carpool can be calculated minus the amount of vehicles used in

carpooling application by the year 2025, which is around 11074168. After building a linear relationship

model between year 2010 and 2025, and between using or without carpooling application, the team can

get the following results: the total cost of environment impact and congestion cost in 2025 without

applying carpool are $33.51 billion and $1.12 billion. While the total cost of environment impact and

congestion cost in 2025 using carpool are $31.70 billion and $1.06 billion. The difference between the

sum of congestion cost and the cost of environment impact is approximately $1.87 billion.

Ran

k

Corridor

Name

Beginning

Location

Destination Length Fuel

Wasted(millions

gallons/year)

Cost of

Congestion(million

$/year)

1 I-110 NB LA harbor fwy 3.1 2.17 95

2 I-110 NB LA harbor fwy 6.5 3.67 158.17

3 I-405 NB LA San Diego 13.1 6.06 269.93

5 I-605 SB LA San Gabriel 4.8 1.64 703.45

6 I-10 EB LA Santa Monica 14.9 4.67 203.99

7 I-10 WB LA Santa Monica 12.6 3.83 169.84

10 I-110 SB LA LA 2.5 0.67 30.93

Table 3-4: Cost of Some Selected Highway

3.2.1.2 Cost of Carpool No matter who owns the car, the carpool service company or private, the main cost of carpool service is

the cost for cars, from the Uber’s official website, the cheapest and the most popular service is UberX, the

illustrate model on that web page is Toyota Prius, this report selects Prius to calculate the approximate

cost of carpool in 2025, the price given by the official site is $24200. Because the trend of carpool

vehicles are growing fast, the total amount of cars in the future(2025) is 315,368, without considering the

depreciation of old car and buy a new car, the total cost each year is 315,368*24200/15 = $508,793,706.7

= $0.5 billion USD.

By comparison of the benefit ($1.87 billion) and cost ($0.5 billion) of carpooling application, it can be

concluded that the carpooling application is worth to invest.

4. Conclusion

4.1, Environment and transportation effect of carpool The carpool system has a very positive impact on reducing the number of vehicle and the emission

inventories.

Based on the carpool effect calculation, the total number of vehicles in 2010 is 11,704,904, and the

estimated vehicle use in 2025 could reduce 5.4%, the reduction will be 630,736 light duty automobiles.

The reduction of emission pollutants is very significant. In the first model, with the effect of carsharing,

the decreasing number on light duty automobile is very significant, and the emission inventories of all the

AQI pollutants all decrease in a large degree. In the second model, the annual change on pollutants

emission is also obvious. From the graphs above, the carpool effect can lead the air quality level to a

better stand which is 10 years prior to the no carpool effect.

It is somewhat interesting that the emission rate is increasing in a very small percentage for in this ten

years period. Even though it is a little contradict to the initial assumption that carsharing will decrease the

emission, actually it is not. First of all, it is reasonable to see this change happen, since less vehicles will

be operated on the roadway system, the average raiders in one vehicle will increase for sure. Based on the

mechanism of internal combustion engine. With more people riding in same vehicles, the emission rate

from engine will increase as well.

4.2, Cost and benefit analysis. From the analysis above, the cost of the expected number of carpool service is $0.5 billion, the benefit of

it is $1.86 billion , its cost is only 26.9% of its benefit, Another interesting result is that the reduction of

congestion cost is much more than the reduction of environmental cost. Anyway, carpool is a

transportation mode of high rate of return from an economic point of view.

4.3, Application in the future. 4.3.1 Composition of transportation means and people’s traffic preference

Apparently, the cities with high ratio of private car are more potential markets of carpool, because a large

number of private cars will cause the traffic condition relatively more congested, this is also the reason

why Los Angles has more serious traffic condition than NYC(which has a larger population). In addition,

people lives in such cities like LA tend to use the "point to point” transportation, carpool's user

experience could successfully meet their requirements.

4.3.2 Develop with internet With the development of mobile internet and useful software, carpool will become more convenient,

people can find the right vehicle in the shortest possible time, and the vehicle can also play the biggest

role, Uber popularity manifestation of this trend.

4.3.3 Usability

Carpool is both beneficial and environment friendly when compared with normal private car driving,

however, public transportation like bus and metro are much better, when it comes to the cities with a

developed public transportation infrastructures, carpool’s effect may not be so significant as this project.

Due to the public transport’s large volume, low pollution and low price, it should be the highest priority

of being used.

References

1,Carfree Census Database http://www.bikesatwork.com/blog/carfree-census-database-is-gone

2,American Community Survey

http://factfinder.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t

3.http://articles.latimes.com/2011/apr/27/local/la-me-california-air-20110427

4. http://www.latimes.com/science/la-me-0430-air-pollution-20140430-story.html

5. http://www.usa.com/los-angeles-ca-air-quality.htm

6. Richard Katzev. Car Sharing: A new approach to urban transportation problems. Published in

Analyses of Social Issues and Public Policy, Vol. 3, No. 1, 2003, page 65-86.

http://www.bikesatwork.com/blog/carfree-census-database-is-gone

http://www.bikesatwork.com/blog/carfree-census-database-is-gone

http://articles.latimes.com/2011/apr/27/local/la-me-california-air-20110427

http://articles.latimes.com/2011/apr/27/local/la-me-california-air-20110427

http://www.latimes.com/science/la-me-0430-air-pollution-20140430-story.html

http://www.latimes.com/science/la-me-0430-air-pollution-20140430-story.html

http://www.usa.com/los-angeles-ca-air-quality.htm

http://www.usa.com/los-angeles-ca-air-quality.htm

The 10 most congested highways in USA report. By Texas Transporation Institute at Texa A&M

University. <http://mobility.tamu.edu/corridors/summary-tables/,http://www.businessinsider.com/most-

congested-roads-america-2011-10>

7. 2003 TTI Urban Mobility Report.

http://ntl.bts.gov/lib/24000/24000/24010/mobility_report_2003.pdf

8. Five Friday Facts: Car Sharing, Eric Wilson, July 20th, 2012

http://2ndgreenrevolution.com/2012/07/20/five-friday-facts-car-sharing/

9. EMFAC, California Environmental Protection Agency, Air Resources Board, 2010—2030

http://www.arb.ca.gov/emfac/

10. Urban Economics--Urban Transit, Arthur O’Sullivan, 2012, 8th edition.

11. Highway vehicle activity trends and their implications for global warming, Transportation and

global climate change, Walsh, M, 1993

12. The age of access. New York: Penguin Putnam Inc, Rifkin, J, 2000

13. Carsharing, 2014, http://www.carsharing.net/

14. Factfinder, total population in U.S., 2015

http://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk

Appendix

1. The EMFAC emission rate tables

2010

Veh_Class Fuel CO_RU

NEX

NOX_RU

NEX

PM10_RU

NEX

PM2_5_RU

NEX

SOX_RU

NEX

(gms/mil

e)

(gms/mile

) (gms/mile) (gms/mile)

(gms/mile

)

LDA GAS 2.263205

328

0.2039019

1

0.0035589

21

0.00322522

3

0.0036124

69

http://mobility.tamu.edu/corridors/summary-tables/,http:/www.businessinsider.com/most-congested-roads-america-2011-10

http://mobility.tamu.edu/corridors/summary-tables/,http:/www.businessinsider.com/most-congested-roads-america-2011-10







LDA DSL 0.523940

772

0.9154744

43

0.0904557

85

0.08321932

4

0.0033171

9

LDT1 GAS 5.327172

158

0.5095531

23

0.0076207

93

0.00690009

2

0.0041795

87

LDT1 DSL 0.717084

801

1.1675497

75

0.1439005

61

0.13238851

5

0.0035024

29

LDT2 GAS 2.824844

314

0.3636337

32

0.0033438

75

0.00304685

1

0.0049287

37

LDT2 DSL 0.622947

395

1.1901204

29

0.1233794

8

0.11350912

1

0.0034349

7

LHD1 GAS 3.081571

904

0.7787502

09

0.0022995

47

0.00211716

7

0.0061345

84

LHD1 DSL 0.762767

432

5.6752737

54

0.0381324

57

0.03508186

1

0.0050107

44

LHD2 GAS 3.724460

745

0.8064713

68

0.0025572

36

0.00231325

8

0.0061656

78

LHD2 DSL 0.741743

388

5.4290558

56

0.0390458

28

0.03592216

3

0.0050342

81

MCY GAS 31.10664

733

1.2764520

69

0.0015415

62

0.00120582

9

0.0019157

39

MDV GAS 3.180141 0.4383482

2

0.0029654

9

0.00271326

2

0.0061983

08

MDV DSL 0.334571

449

0.5797913

26

0.0575909

21

0.05298364

9

0.0032350

09

MH GAS 15.03108

246

1.5704422

2 0.004691

0.00406723

3

0.0061737

48

MH DSL 0.581009

489

7.6106794

5

0.2127415

61

0.19572223

9

0.0106816

62

Motor Coach DSL 3.047446

493

14.187164

48

0.4877834

16

0.44876074

3

0.0165101

85

OBUS GAS 3.562635

23

1.4129356

65

0.0010891

32

0.00099483

9

0.0061007

88

PTO DSL 4.780388

262

15.745430

87

0.6154730

57

0.56623521

2

0.0205377

72

SBUS GAS 30.37037

784

2.4103528

9

0.0102081

28

0.00872270

2

0.0079374

19

SBUS DSL 2.484017

121

11.651325

25

0.5287285

15

0.48643023

3

0.0123490

04

T6 Ag DSL 1.849075

268

9.7496017

66

0.4383279

76

0.40326173

7

0.0108764

83

T6 Public DSL 0.942872

881

9.2969848

67 0.2652477

0.24402788

4

0.0108071

76

T6 CAIRP heavy DSL 1.104004

729

7.2382362

73

0.2600838

91 0.23927718

0.0107482

34

T6 CAIRP small DSL 0.877529

229

6.1147779

47

0.2208622

7

0.20319328

9

0.0107459

12

T6 OOS heavy DSL 1.104004

729

7.2382362

73

0.2600838

91 0.23927718

0.0107482

34

T6 OOS small DSL 0.877529

229

6.1147779

47

0.2208622

7

0.20319328

9

0.0107459

12

T6 instate

construction heavy DSL

1.527258

821

9.1342718

03

0.3409323

07

0.31365772

2

0.0107675

28

T6 instate

construction small DSL

1.091694

843

7.3110135

47

0.2574940

57

0.23689453

3

0.0107491

25

T6 instate heavy DSL 1.513324

509

9.0415511

39

0.3374333

52

0.31043868

4

0.0107653

98

T6 instate small DSL 1.079040

461

7.2101144

24

0.2539137

54

0.23360065

4

0.0107464

43

T6 utility DSL 0.562961

021

7.5458586

14

0.1647866

12

0.15160368

3

0.0107493

52

T6TS GAS 9.753436

735

2.5231882

61

0.0029550

41

0.00263408

5

0.0061972

93

T7 Ag DSL 4.078750

909

16.494685

28

0.6869710

87 0.6320134

0.0165233

08

T7 CAIRP DSL 2.856985

395

12.121422

31

0.5368148

17

0.49386963

2

0.0163652

29

T7 CAIRP

construction DSL

2.869775

367

12.184722

15

0.5397017

46

0.49652560

7

0.0163664

31

T7 NNOOS DSL 2.110874

612

8.8654063

09

0.3553506

96 0.32692264

0.0164051

82

T7 NOOS DSL 2.856985

395

12.121422

31

0.5368148

17

0.49386963

2

0.0163652

29

T7 other port DSL

T7 POAK DSL

T7 POLA DSL 1.656267

373

8.2512356

41

0.2537200

45

0.23342244

1

0.0165427

78


991

16.135222

38

0.5017555

76 0.46161513

0.0165870

44

T7 Single DSL 2.590470

373

14.054357

44

0.4589027

94

0.42219057

1

0.0163967

3

T7 single

construction DSL

2.602857

069

14.135405

57

0.4615418

36

0.42461848

9

0.0163982

22

T7 SWCV DSL 3.077996

296

15.472222

26

0.5984654

15

0.55058818

2

0.0166384

4

T7 tractor DSL 3.660934

435

14.622537

22

0.6077532

77

0.55913301

5

0.0163996

76

T7 tractor

construction DSL

3.769451

304

14.898919

69

0.6152892

8

0.56606613

8

0.0164022

05


466

13.137043

59

0.2778273

37 0.25560115

0.0163920

21

T7IS GAS 48.53009

239

6.7871675

38

0.0025471

78

0.00209167

7

0.0068131

23

UBUS GAS 18.56504

382

3.5883439

1

0.0043334

69

0.00383544

4

0.0077754

99

UBUS DSL 3.092763

582

17.291556

73

0.2848600

14

0.26207122

7

0.0249330

81

All Other Buses DSL 1.738913

746

9.3420589

9

0.4285087

23

0.39422802

5

0.0108481

47

2025

Veh_Class Fuel CO_RUN

EX

NOX_RU

NEX

PM10_RU

NEX

PM2_5_RU

NEX

SOX_RU

NEX

(gms/mile

)

(gms/mile

) (gms/mile) (gms/mile)

(gms/mile

)

LDA GAS 0.651625

961

0.0603557

15

0.0021256

41

0.00197224

4

0.0036222

89

LDA DSL 0.093035

311

0.2723666

63

0.0077455

17

0.00712587

6

0.0030798

8

LDT1 GAS 1.412866

324

0.1384659

88

0.0030136

32

0.00279615

3

0.0041857

5

LDT1 DSL 0.156304

626

0.3624512

87

0.0214958

82

0.01977621

1

0.0031247

78

LDT2 GAS 0.836426

937

0.0865912

86

0.0020993

36

0.00194783

8

0.0049150

97

LDT2 DSL 0.127143

266

0.3715600

72

0.0111379

55

0.01024691

9

0.0031052

19

LHD1 GAS 0.596093

98

0.2460914

8

0.0005744

68

0.00053301

2

0.0061476

78

LHD1 DSL 0.616609

842

2.0158199

56

0.0206612

69

0.01900836

8

0.0049617

69

LHD2 GAS 0.308345

194

0.1863441

87

0.0003783

59

0.00035105

5

0.0061696

86

LHD2 DSL 0.587378

501

1.8515556

9

0.0198833

73

0.01829270

3

0.0049652

43

MCY GAS 19.38284

696

1.1474470

92

0.0002456

21 0.00021121

0.0019710

89

MDV GAS 1.295069

579

0.1514116

89

0.0021566

79

0.00200100

4

0.0062558

78

MDV DSL 0.090988

289

0.2585930

62

0.0085544

76

0.00787011

8

0.0030864

21

MH GAS 0.560394

753

0.2658574

15

0.0004341

62

0.00040283

1

0.0059777

39

MH DSL 0.478232

026

4.6212088

21

0.1042022

6

0.09586608

1

0.0108030

5


6

1.7744831

46

0.0710532

63

0.06536900

2

0.0162732

83

OBUS GAS 0.738745

792

0.3510811

21

0.0002741

54

0.00025436

9

0.0060959

39

PTO DSL 0.802346

408

2.0134440

55

0.0431209

5

0.03967127

4

0.0202015

04

SBUS GAS 5.097395

816

0.9489554

2

0.0021565

98

0.00200096

7

0.0074982

31

SBUS DSL 0.580733

858

7.8822666

23

0.0556928

49

0.05123742

1

0.0122824

08

T6 Ag DSL 0.417834

576

1.1539705

96

0.0464727

81

0.04275495

8

0.0105888

94


089

2.3227596

8

0.0330625

23

0.03041752

1

0.0106728

76

T6 CAIRP

heavy DSL

0.355805

123

0.9184348

77

0.0379233

45

0.03488947

7

0.0105832

67

T6 CAIRP small DSL 0.341044

765

0.8571261

71

0.0358539

69

0.03298565

1

0.0105826

16


123

0.9184348

77

0.0379233

45

0.03488947

7

0.0105832

67


765

0.8571261

71

0.0358539

69

0.03298565

1

0.0105826

16

T6 instate

construction

heavy

DSL 0.384712

677

1.0385700

48

0.0419960

87 0.0386364

0.0105842

3

T6 instate

construction

small

DSL 0.354474

079

0.9119296

75

0.0377466

92

0.03472695

7

0.0105830

6

T6 instate heavy DSL 0.383312

685

1.0321569

97

0.0417852

57

0.03844243

6

0.0105844

01

T6 instate small DSL 0.354957

566

0.9138047

98

0.0378137

04

0.03478860

8

0.0105830

94


569

0.6368925

14

0.0282250

54 0.02596705

0.0105839

63

T6TS GAS 0.839746

793

0.3474468

14

0.0003211

04

0.00029793

2

0.0060765

52

T7 Ag DSL 0.982707

152

1.9064534

03

0.0780082

92

0.07176762

9

0.0161723

51

T7 CAIRP DSL 1.007879

261

2.0153375

84

0.0817278

52

0.07518962

4

0.0161639

02

T7 CAIRP

construction DSL

1.008521

752

2.0173413

56

0.0817971

78

0.07525340

4

0.0161638

89

T7 NNOOS DSL 0.871891

893

1.6128663

14

0.0676285

34

0.06221825

1

0.0161634

58

T7 NOOS DSL 1.007902

387

2.0154066

22

0.0817305

1

0.07519206

9

0.0161639

01

T7 other port DSL

T7 POAK DSL

T7 POLA DSL 1.533933

81

3.2148369

49

0.1299919

56 0.1195926

0.0162006

63


214

6.0676726

99

0.0573365

24

0.05274960

2

0.0164260

71


011

1.3973054

84

0.0598265

55 0.05504043

0.0161666

4

T7 single

construction DSL

0.800366

09

1.3988246

18

0.0598896

12

0.05509844

3

0.0161665

39

T7 SWCV DSL 0.679129

839

6.1136229

88

0.0628507

61 0.0578227

0.0163560

26


874

2.0282128

48

0.0821534

01

0.07558112

9

0.0161655

75

T7 tractor

construction DSL

1.019627

55

2.0417344

41

0.0826288

43

0.07601853

5

0.0161657

1


951

0.9848052

21

0.0449556

05

0.04135915

6

0.0161671

86

T7IS GAS 27.76675

976

4.2278330

29

0.0002046

17

0.00018985

1

0.0065062

94

UBUS GAS 9.890326

88

2.6289762

22

0.0019999

22

0.00185559

8

0.0076200

17

UBUS DSL 2.161371

054

11.243093

44

0.1999476

81

0.18395187

3

0.0232765

38

All Other Buses DSL 0.412144

867

1.1640522

77

0.0454586

31

0.04182194

1

0.0106349

56

2030

Veh_Class Fuel CO_RUNE

X

NOX_RU

NEX

PM10_RU

NEX

PM2_5_RU

NEX

SOX_RU

NEX


LDA GAS 0.60608328

2

0.0561588

05 0.00229825

0.00213239

7

0.0036186

59

LDA DSL 0.07328928

1

0.2388849

49

0.00499753

5

0.00459773

2

0.0030709

03

LDT1 GAS 1.00243458

3

0.0945765

06

0.00259763

1

0.00241017

3

0.0041833

94

LDT1 DSL 0.07460667

2

0.2544929

62

0.00439540

2 0.00404377

0.0030747

16

LDT2 GAS 0.74380270

6

0.0745198

07

0.00224453

3

0.00208255

7

0.0049080

69

LDT2 DSL 0.09351245

7

0.3062448

38

0.00563601

8

0.00518513

7

0.0030842

66

LHD1 GAS 0.31603737

9

0.1741526

05

0.00036413

4

0.00033785

6

0.0061445

99

LHD1 DSL 0.57886688

8

1.4482819

92

0.01776562

1

0.01634437

1

0.0049567

31

LHD2 GAS 0.17919596

7

0.1271251

03 0.000239

0.00022175

2

0.0061691

68

LHD2 DSL 0.54575411

7

1.2935356

84

0.01693256

7

0.01557796

2

0.0049607

02

MCY GAS 19.0506462

3

1.1434069

18

0.00022878

2

0.00019826

1

0.0019722

3

MDV GAS 1.08466442

7

0.1172595

71

0.00219660

3

0.00203808

6

0.0062546

21

MDV DSL 0.07002509

7

0.2335716

99

0.00473039

1 0.00435196

0.0030761

51

MH GAS 0.22141787

6

0.1736548

92

0.00021874

2

0.00020295

7

0.0059699

52

MH DSL 0.43498786

4

3.8605554

42

0.07086143

7

0.06519252

4

0.0108340

67


4

1.7774789

8

0.07117243

3

0.06547863

9

0.0162714

59

OBUS GAS 0.39900026

4

0.2185280

29 0.00020548

0.00019065

2

0.0060951

22

PTO DSL 0.81359300

4

2.0586738

91

0.04406382

7

0.04053872

1

0.0201992

71

SBUS GAS 2.99338014

2

0.6980006

88

0.00142811

4

0.00132505

4

0.0074608

95

SBUS DSL 0.71747736

9

5.9848486

35

0.05232745

7 0.04814126

0.0122831

23

T6 Ag DSL 0.41620937

4

1.1539876

83

0.04636049

8

0.04265165

8

0.0105862

57


5

1.3433881

12

0.03174182

1

0.02920247

5

0.0106197

02

T6 CAIRP

heavy DSL

0.35950124

3

0.9345414

83

0.03848289

3

0.03540426

2

0.0105826

98

T6 CAIRP

small DSL

0.34181094

7

0.8616449

96

0.03597790

2 0.03309967

0.0105823

65


3

0.9345414

83

0.03848289

3

0.03540426

2

0.0105826

98


7

0.8616449

96

0.03597790

2 0.03309967

0.0105823

65

T6 instate

construction

heavy

DSL 0.38926398

4

1.0588017

1

0.04270979

4 0.03929301

0.0105830

85

T6 instate

construction

small

DSL 0.35620209

6

0.9220967

54

0.03802721

9

0.03498504

1

0.0105824

78

T6 instate

heavy DSL

0.38945897

7

1.0593450

28

0.04273363

8

0.03931494

7

0.0105831

4

T6 instate

small DSL

0.35648778

3

0.9232511

93

0.03806728

1

0.03502189

8

0.0105824

88


2

0.6340564

79

0.02827230

7

0.02601052

3

0.0105825

97

T6TS GAS 0.43313054

1

0.2178981

85

0.00022494

3 0.00020871 0.0060713

T7 Ag DSL 0.98011949

3

1.9094768

66 0.07823492

0.07197612

7

0.0161679

53

T7 CAIRP DSL 1.00541139

8

2.0106240

6

0.08154024

6

0.07501702

6

0.0161635

13

T7 CAIRP

construction DSL

1.00556745

9

2.0111086

21

0.08155708

3

0.07503251

7

0.0161635

1

T7 NNOOS DSL 0.87161902 1.6125460

59

0.06761398

1

0.06220486

3

0.0161633

81

T7 NOOS DSL 1.00540275

9

2.0105979

35

0.08153944

3

0.07501628

8

0.0161635

12

T7 other port DSL

T7 POAK DSL

T7 POLA DSL 1.21036246

6

2.6227806

27

0.10293378

7

0.09469908

4

0.0161633

77


7

3.9046119

99

0.05223120

2

0.04805270

6

0.0162825

96


2

1.4286944

35

0.06113471

4

0.05624393

7

0.0161648

53

T7 single

construction DSL

0.81159896

9

1.4303192

51

0.06119467

7

0.05629910

3

0.0161648

16

T7 SWCV DSL 0.70873521 4.3643354

3

0.05908637

4

0.05435946

4

0.0162719

79


3

2.0243287

38 0.08203494

0.07547214

5

0.0161642

16

T7 tractor

construction DSL

1.01457295

3

2.0335555

12

0.08236195

6

0.07577299

9

0.0161642

58

T7 utility DSL 0.658204 0.9809350

81

0.04531460

3

0.04168943

4

0.0161647

61

T7IS GAS 27.1929134

8

4.2012412

03

0.00017393

8

0.00016138

5

0.0064885

61

UBUS GAS 6.42779672

8

2.1757282

59

0.00110690

6

0.00102702

6

0.0075436

83

UBUS DSL 1.76590090

6

8.8737916

61 0.16822514 0.15476713

0.0225904

18

All Other

Buses DSL

0.42293644

3

1.2090162

71

0.04699787

7

0.04323804

7

0.0106345

81

2035

Veh_Class Fue

l

CO_RUNE

X

NOX_RUN

EX

PM10_RUN

EX

PM2_5_RUN

EX

SOX_RUN

EX


LDA GA

S

0.5880316

28

0.053697432 0.002333408 0.002165018 0.00361950

5

LDA DS

L

0.0688973

92

0.229295627 0.004589165 0.004222032 0.00305748

8

LDT1 GA

S

0.7391322

23

0.065764738 0.002314786 0.002147739 0.00418735

5

LDT1 DS

L

0.0772933

11

0.265516874 0.004383674 0.00403298 0.00306163

7

LDT2 GA

S

0.7023972

64

0.068265486 0.002304897 0.002138564 0.00490816

3

LDT2 DS

L

0.0877594

22

0.294164124 0.005072261 0.00466648 0.00306827

3

LHD1 GA

S

0.1877430

12

0.13787977 0.000239186 0.000221925 0.00614182

7

LHD1 DS

L

0.5689588

29

1.119831524 0.016675605 0.015341557 0.00495498

2

LHD2 GA

S

0.1412129

2

0.104512111 0.000183526 0.000170281 0.00616748

5

LHD2 DS

L

0.5409535

39

1.021062911 0.015661976 0.014409018 0.00495573

4

MCY GA

S

18.693367

72

1.139608029 0.000224058 0.000194531 0.00196364

MDV GA

S

0.9367412

5

0.091962457 0.002208404 0.002049034 0.00626036

9

MDV DS

L

0.0694418

17

0.232416723 0.004631073 0.004260587 0.00306293

3

MH GA

S

0.1676184

71

0.143761138 0.000160599 0.00014901 0.00595156

9

MH DS

L

0.4008463

11

3.404023217 0.04574656 0.042086837 0.01087232

9

Motor Coach DS

L

0.9159964

74

1.7783895 0.070577304 0.06493112 0.01628167

4

OBUS GA

S

0.2685551

5

0.168714887 0.000178423 0.000165547 0.00609250

8

PTO DS

L

0.8154551

19

2.069012584 0.044278481 0.040736203 0.02019801

9

SBUS GA

S

1.4389851

21

0.519579829 0.000623228 0.000578253 0.00743343

9

SBUS DS

L

0.8740554

24

4.516501874 0.051461583 0.047344656 0.01224949

1

T6 Ag DS

L

0.4108337

83

1.145475406 0.045350824 0.041722758 0.01059602

2

T6 Public DS

L

0.3042205

06

0.917805 0.030802444 0.028338248 0.01060722

2

T6 CAIRP heavy DS

L

0.3587770

05

0.939549846 0.038126476 0.035076358 0.01059376

7

T6 CAIRP small DS

L

0.3409659

01

0.863948514 0.035605018 0.032756616 0.01059371

1

T6 OOS heavy DS

L

0.3587770

05

0.939549846 0.038126476 0.035076358 0.01059376

7

T6 OOS small DS

L

0.3409659

01

0.863948515 0.035605018 0.032756616 0.01059371

1

T6 instate

construction heavy

DS

L

0.3889932

78

1.067018518 0.042396743 0.039005003 0.01059395

4

T6 instate

construction small

DS

L

0.3557673

01

0.926705742 0.037700219 0.034684202 0.01059375

9

T6 instate heavy DS

L

0.3893696

22

1.068523236 0.042448827 0.039052921 0.01059397

T6 instate small DS

L

0.3558982

13

0.927239605 0.037718481 0.034701002 0.01059376

3

T6 utility DS

L

0.2872131

11

0.635024822 0.027981911 0.025743358 0.01059374

2

T6TS GA

S

0.2778802

95

0.170895621 0.000180115 0.000167117 0.00606267

9

T7 Ag DS

L

0.9720787

9

1.90458474 0.077100151 0.070932139 0.01618447

3

T7 CAIRP DS

L

1.0024308

5

2.013079331 0.080665055 0.07421185 0.01618183

1

T7 CAIRP

construction

DS

L

1.0024897

26

2.01325945 0.080671235 0.074217536 0.01618183

T7 NNOOS DS

L

0.8694037

09

1.614747671 0.066906021 0.06155354 0.01618181

7

T7 NOOS DS

L

1.002431 2.013079076 0.080665081 0.074211875 0.01618183

1

T7 other port DS

L

T7 POAK DS

L

T7 POLA DS

L

1.2076557

76

2.627776869 0.101899377 0.093747427 0.01618180

8

T7 Public DS

L

0.6545794

67

2.662246222 0.049945406 0.045949774 0.01625075

3

T7 Single DS

L

0.8111020

65

1.438604607 0.060815176 0.055949962 0.01618228

2

T7 single

construction

DS

L

0.8114403

61

1.439633357 0.06085148 0.055983362 0.01618227

2

T7 SWCV DS

L

0.7389642

07

2.840759975 0.058047865 0.053404036 0.01625402

3

T7 tractor DS

L

1.0069056

52

2.024069606 0.081054986 0.074570587 0.01618224

3

T7 tractor

construction

DS

L

1.0090750

24

2.030411078 0.081275928 0.074773854 0.01618226

2

T7 utility DS

L

0.6569102

62

0.979633008 0.044916002 0.041322721 0.01618202

2

T7IS GA

S

26.993331

06

4.257831161 0.000160238 0.000148675 0.00646081

3

UBUS GA

S

3.9025479

07

1.504187698 0.000532164 0.000493761 0.00749837

2

UBUS DS

L

1.3928935

66

6.66489715 0.136274745 0.125372763 0.02192051

2

All Other Buses DS

L

0.4214369

57

1.211518275 0.04652896 0.042806643 0.01064246

7

Carpool Effects on Air Quality in Los Angeles

Documents

Transcript of Carpool Effects on Air Quality in Los Angeles