Going One Step Beyond in North Denver One Step Beyond in North Denver ... –AERMOD dispersion model...

Going One Step Beyond

in North Denver

Gregg W. ThomasMichael Ogletree

Lisa Clay

Denver Environmental HealthJanuary 19, 2016

A Neighborhood Scale Air Pollution Modeling Assessment

Part II : Predicted Ambient Concentrations in 2035

Purpose

• Estimate predicted concentrations using 2035 emissions

– AERMOD dispersion model (version 15181)

– Partial Cover Lowered (PCL)

• Address community concerns around near highway gradients and/or hot spots

– Estimate near highway gradients

– PM10, PM2.5, nitrogen dioxide (NO2), Benzene

• Includes projected 2035 traffic counts along I-70 between I-25 and Colorado Blvd

2January 19, 2016 Going One Step Beyond in Denver - Part II

Dispersion Modeling History

• Builds upon 15 years of work conducted by Denver

Environmental Health (DEH); – Focused on hazardous air pollutants (aka HAPs, mobile source air toxics)

– Unique for a local government

• Also builds upon work funded by CDOT & FHWA in

2004-2005– Focused geographic area including North Denver and Commerce City

– Onroad emissions confined to the major roadway footprints

• Model results were evaluated against air monitoring data– Good model to monitor performance in past years (within a factor of 2)

– Annual average concentrations a focus of past work

• Final Report: https://www.codot.gov/programs/research/pdfs/by-subject/by-

subject-d-k/environmental-assessments%20%20%20%20


https://goo.gl/k4GtzH


Good Neighbor Part II Update

• Focus on same geographic area

• Looks ahead to 2035 (fully operational I-70)

• 1-hr and 24-hr average concentrations– Generates up to 500,000+ data points with hourly data!

• Use updated traffic projections along I-70

• Use high resolution weather data from a site closer to the project area

• Particulate matter below 10 and 2.5 microns (i.e. millionths of a meter; PM10, PM2.5), nitrogen dioxide (NO2), benzene

• Predicted concentrations at over 5,000 different points both near and far from major roadways


Good Neighbor Part II Challenges

• Emissions projections for area, non-road mobile, and point sources don’t exist– Have to make assumptions; err to be protective of public health

• Existing datasets, while improved, still require a fair amount of manual analysis

• Datasets are complex and very large

• Did not have recent year point source emissions data in a model-ready format– Only able to include benzene point source emissions from 2006 inventory

– Background concentrations should make up for this for a few pollutants

• AERMOD has limitations in handling elevated or depressed roadways

• Additional detailed work will continue in 2016+


Project Area of Primary Focus


Methodology

• Start with 2011 county level emissions for all source categories– EPA National Emissions Inventory (NEI v2)

– CDPHE 2011 emission inventory

• Use DRCOG transportation analysis zones (TAZs) to apportion a fraction of the county level emissions to each TAZ– Surrogate data includes vehicle miles traveled (VMT), population and/or

population density, depending on the source category

• Use professional judgment to project forward to 2035 for area and non-road emissions sources– Nonroad emissions decline by 20%, railroad by 10%, area sources flat

• Use MOVES emission model data for specific road links in 2035– No double counting of onroad emissions in affected TAZs

• Use high resolution weather data from a site closer to the project area and from a more recent year (2004-2008 hourly data set)

• Predicted concentrations at over 5,000 different locations both on and off of the major roadways

• No future year monitored concentrations to compare with model


Major Roads within the Good Neighbor

Project Area

I-70

Co

lora

do

Blv

d

• I-70 and I-25 focus area TAZs shown in shaded region (light blue)

• 90% of onroademissions excluded from these TAZs; remaining 10% are from local roads

• Onroad emissions from MOVES were assigned to the approximate roadway footprint to generate hot-spots that help determine near road gradients


Major Roadway Footprints

• Use centerline file from DRCOG model to generate rectangular polygons that can be defined in AERMOD

• This underestimates the actual dimensions of the roadways (not designed for this specific purpose)

• For most situations, it doesn’t affect results

• For the PCL though, DEH created roadway polygons using approximate footprint of PCL and known frontage roads

• This gives us better resolution at nearby homes and Swansea Elementary school.


Partial Cover Lowered (PCL) Footprint

Purina

SwanseaElem

York

St

2035 PCL Footprint used in AERMOD (shaded area).


AERMOD Receptor Locations

• 5,174 receptors

• Both on and off the highways

• Heavy focus around I-70 and I-25

• Onroad receptors are not used to determine compliance with ambient air quality standards (NAAQS) but do help with estimating gradients

AERMOD Info (1 of 3)

• AERMOD v15181 using BEEST Suite v 11.03

• Generates predictions each hour of the day

– 24-hr averages capture each hour

• Results are run for a typical day in January

– Atmospheric dispersion usually worst in the winter

– Emissions for pollutants modeled in this study are

the same or higher in January

• PM10 and PM2.5 emissions include exhaust,

road dust and brake and tire wear



• Modeled both constant and varying hourly emissions

• Compared at grade I-70 versus below grade (PCL)

• Results are run for a typical day in January

– Atmospheric dispersion usually worst in the winter

– Emissions for pollutants modeled in this study are the same or higher in January

• PM10 and PM2.5 emissions include exhaust, road dust and brake and tire wear (see Part I)



• The PCL was modeled at a depth of 30 feet

compared to its surroundings

• “The Cover” has not been modeled yet

• DEH is testing various options

• AERMOD is not ideal for such modeling,

but we can make estimates

• Plan to include updates to this presentation

when work is complete (likely by Mar 2016)



Concentrations in micrograms per cubic meter; 1-hour averaging period

Predicted Nitrogen Dioxide (2035)

Predicted Nitrogen Dioxide (NO2) Summary

• Only modeled NO2 from MOVES model on roadways

• EPA NEI all other sources emissions produced unrealistic results;

– Mostly nitric oxide (NO) and not NO2

– Still working on how to resolve this in AERMOD

• Max predicted hourly concentration < 30% of the current NAAQS (188 micrograms/m3 or 100 ppbv)

• About 33% lower than current day max value at near road monitoring sites

• Slightly higher concentrations west of the PCL


NO2 Sensitivity Analysis: PCL vs at-grade

• One hypothesis is that the PCL will reduce concentrations in the neighborhood– Turbulence in the roadway channel from passing cars/trucks

and additional mixing due to winds and noise/safety walls

– Emissions can still be high near the road surface

• Method to test whether the above hypothesis is true is as follows:– Model an at-grade roadway first

– Drop roadway surface 30 feet, keeping receptor height as is

– Compare the two

• DEH did not model an elevated viaduct

• Result? Hypothesis confirmed



York

St

York

St

Concentrations decrease near the UPRR railroad tracks

Predicted NO2 At-Grade vs PCL (2035)

Concentrations in micrograms per cubic meter

At-Grade

PCL


EPA Wind Tunnel Simulations for

Different Highway ConfigurationsFigures a) and d) closely

match what was modeled

on the previous slide; at-

grade vs PCL (east of UPRR)


Depressed roadways with additional noise walls on top produce the least near

roadway impacts (largely due to increased mixing and turbulence).

EPA Wind Tunnel Simulations for

Different Highway Configurations

NO2 Additional Notes• Predicted 2035 concentrations for roadside NO2 are in

the approximate range expected when compared to today’s near road data and the predicted decrease in emissions.

• DEH will continue to investigate modeling area and non-road mobile sources of NO2/NOx. However, near road NO2/NO monitoring data today show dominant influence from on-road vehicles, as expected.

• DEH will also model/mimic the PCL as a cavity between two very long buildings. This will allow us to test downwash algorithms (i.e. pollutant trapping). This will be in the next update.



Predicted Benzene (2035)

Concentrations in micrograms per cubic meter; 24-hr averaging period

Predicted Benzene Summary• Higher concentrations near downtown

– Due to higher traffic density

– Generally matches air monitoring data spatial patterns

• Onroad receptors 2388 and 2396 show high concentrations as expected (see previous slide)

• Swansea Elem receptor 1188 is somewhat lower, but does not include any effects from the cover

• Large reductions from recent year concentrations, as per the inventory

– Cleaner fuels and vehicles

• Point sources (like gas stations) are noticeable



Predicted PM10 (2035)


Predicted Particulate Matter (PM10) Summary

• Road dust is the dominant contributor (~70%)

– See Part I for important road dust limitations

• For background, took max predicted conc. (24) for all nonroademissions sources and subtracted that from 89, which CDOT used as PM10 background in FEIS. Resulting DEH background is 65.

– Extremely conservative, but total concentrations still below NAAQS (150)

• Predicted hot-spots are in the expected locations

• PM versus gaseous (benzene) gradients between downtown and I-70 area are different

– Mainly due to road dust modeling for I-70

– Ambient monitoring data do not match the PM10 pattern (see next slide).

– Supports the statement that 2035 Total PM10 is conservative



0

10

20

30

40

50

1:0

0 A

M

2:0

0 A

M

3:0

0 A

M

4:0

0 A

M

5:0

0 A

M

6:0

0 A

M

7:0

0 A

M

8:0

0 A

M

9:0

0 A

M

10:0

0 A

M

11:0

0 A

M

12:0

0 P

M

1:0

0 P

M

2:0

0 P

M

3:0

0 P

M

4:0

0 P

M

5:0

0 P

M

6:0

0 P

M

7:0

0 P

M

8:0

0 P

M

9:0

0 P

M

10:0

0 P

M

11:0

0 P

M

12:0

0 A

M

Co

ncen

trati

on

(mic

rog

ram

s/m

3)

Hourly Avg PM10 Comparisons in Denver

(January 2014)

I-25 - 971 Yuma Dr

La Casa 4545 Navajo

Downtown - 21st Broadway

Welby - 78th Ave & Steele St

Measured PM10 Spatial Differences

24-hr avg. maximum concentrations in Jan

2014 are in the range of predicted total

concentrations, WITHOUT any background.

Inclusion of background concentration (65)

in modeled concentrations is conservative.

January 2014 24-hr Average 24-hr Avg Maximum

CAMP 23 78

La Casa 21 70

I-25 Near Road 26 75

Predicted PM2.5 (2035)


*Concentrations in micrograms per cubic meter; 24-hour averaging period


Predicted PM2.5 (2035)

*Concentrations in micrograms per cubic meter; 24-hour averaging period

York

St


Predicted Particulate Matter (PM2.5) Summary

• As with PM10, road dust is the dominant contributor for PM2.5 in 2035 (~75%)

– See Part I for important road dust limitations

• For background value, analyzed daily average concentrations from previous January monitoring data (see next slide)

– Background value (3.0), for emissions outside of the project boundary, were set at < ½ the January daily average value.

• Predicted hot-spots are in the expected locations

• Off roadway receptors do not exceed the 24-hr NAAQS (35 micrograms per cubic meter)


0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Co

nce

ntr

ati

on

(m

icro

gra

ms/

m3

)

PM2.5 Comparisons in Denver (Jan 2014)

I-25 - 971 Yuma Dr

La Casa 4545 Navajo

Downtown - 21st Broadway

January 2014 24-hr Average 24-hr Avg Maximum

CAMP 8.3 30.9

La Casa not enough data not enough data

I-25 Near Road 9.3 32.8

Measured PM2.5 Spatial Differences

24-hr avg. maximum concentrations in Jan

2014 are in the range of 2035 predicted

total concentrations. Jan 2014

measurements not likely driven by road

dust though, whereas 2035 predictions are.

Summary

• DEH modeled 1-hr and 24-hr average concentrations for pollutants of interest

– NO2, benzene, PM10, and PM2.5

• Captured onroad emissions in detail, blended with area and nonroad source emissions in the project area

• Able to approximate PCL (depressed) roadway configuration

• High spatial resolution allowed us to determine hot-spots and near-road gradients


Conclusions

• Predicted pollutant levels do not exceed health-based standards (NAAQS)– Even with conservative road dust estimates for

PM10 and PM2.5

• Gradients are fairly sharp within 100-200m of the highway– Highway contributions show 75% reduction within

200m (~1 city block) of the road

– Less of a reduction when all emissions included

• PCL is predicted to result in lower air pollution in the neighborhood due to added mixing and turbulence


Next Steps• DEH will model additional configurations for the PCL

and cover at Swansea Elem– DEH will post updates as they become available

• DEH will expand the link based emission modeling to the entire Good Neighbor project area

• Will also model 2011 baseline emissions year for additional model-to-monitor validation and to better understand road dust contributions

• DEH, CDOT, and CDPHE will collaborate on the operation of a long-term air monitor to collect data at Swansea Elementary starting in summer 2016 until project is complete

• That data will be used in part to evaluate and refine the near-road modeling completed for this project


Disclaimer: This work was performed by Denver Environmental Health (DEH) independently

from the Colorado Dept of Transportation (CDOT). CDOT did answer a few

technical questions along the way regarding some of the assumptions were

made. Similar modeling tools were used by both agencies (MOVES, AERMOD).

This project builds upon work that DEH completed in 2005 and was funded by

Federal Highway Administration (FHWA) and CDOT in 2004. FHWA/CDOT did not

provide funding for this phase of work. DEH did this work in response to citizen

and other interested stakeholders concerns regarding near highway gradients

and hot-spots. CDOT did review this presentation but otherwise has not formally

reviewed the technical work products. The materials produced are wholly owned

by the City and County of Denver Dept. of Environmental Health.

For more information Contact Michael Ogletree, Gregg Thomas, or Lisa Clay with the Denver

Department of Environmental Health at [email protected]


mailto:[email protected]

Going One Step Beyond in North Denver One Step Beyond in North Denver ... –AERMOD dispersion model...

Documents

Transcript of Going One Step Beyond in North Denver One Step Beyond in North Denver ... –AERMOD dispersion model...