Region 5 Overview of ORD’s Detroit Area Near Road...Region 5 Overview of ORD’s Detroit Area Near Road Research - Introduction. U.S. Environmental Protection Agency. 2. Office of

Dan Costa, Sc.D., DABTOffice of Research & Development

USEPA

[email protected]

Region 5 Overview of ORD’s Detroit Area Near Road Research - Introduction

2U.S. Environmental Protection AgencyOffice of Research and Development

Motor Vehicles are “Life-Blood” in the U.S.

There are over 250 million registered vehicles2

• Passenger vehicles, ~96%• Trucks and buses, ~4%

The current U.S. population is 310 million1 and growing

Over 45 million people live within 300 ft of an airport, railroad or major highway4

1U.S. Census; 2National Transportation Statistics; 3American Time Use Survey; 4American Housing Survey

Over 140 million people commute to work2,3

• Work, ~45 minutes• School, ~35 minutes


Policy Considerations

• Mobile Source Regulations• Transportation Conformity• National Environmental Policy Act (NEPA)• State and local planning

• Transportation systems

• School site requirements

• Child/elderly care facilities

• Urban planning


4

• The PM story until recently has largely had focused on biologic plausibility and its attributes (components and size)

• “Source attribution” studies brought insight into the potential links to transportation – mobile sources.

• European science community has been focused on diesel, traffic, and “ultrafine” particles

• Some outcomes associated with “near road” included:– Mortality (apparently stemming from myocardial events) – Asthma exacerbation and maybe initiation– Cancers – Lung growth retardation in children– Birth defects

• Uncertain role of co-pollutants - MSATs

Several Health Outcomes Now Associated

“Pressing” Uncertainty - Health


5

• Distance from roadway (residence, school, etc.)– Linear distance– Effective Radius– Angular distance

• Cumulative traffic over some temporal period• Numbers of vehicles per time (exposure rate)• Vehicle type, speed, etc.• Person hours within a varying distances or…• Person hours (~TWA) at locations: e.g., activity diaries• Any number of statistical models based on the metrics

above or land-use estimations• Emission data – part of the story but alone is not enough

Lack of Good Metrics to Assess Exposure

“Keystone” Uncertainty - Exposure


Near Road Uncertainties

• What do we really know about NR exposures?• Is this an issue of exhaust emission MSATs or PM?• What about dispersed roadway and mechanical materials? • Can we have establish reliable / transferable metrics?• What are the relevant temporal / spatial exposure profiles?

• Health Implications?• What in fact are the acute / chronic outcomes and risks?• Who is susceptible?• Is there biologic plausibility?

• Interventions may exist – what is their value?

Pressing Program & Regional Needs Seemingly Linked to MSAT and PM Exposures Associated with Mobile Sources


7

• van Vliet et al. 1997 Motor vehicle exhaust and chronic respiratory symptoms in children living near freewaysEnviron Res 74 (2):122-32

• Delfino et al., 2003. Respiratory symptoms and peak expiratory flow in children with asthma in relation to volatile organic compounds in exhaled breath and ambient air. J Exposure Anal Environ Epidemiol 13: 348-363.

• Gauderman et al., 2005. Childhood asthma and exposure to traffic and nitrogen dioxide. Epidemiol 16(6):737-743.

• Morgenstern et al., 2008 Atopic diseases, allergic sensitization, and exposure to traffic-related air pollution in children. Am J Resp Crit Care Med 177(12):1331-7.

• Singh et al. 2005 Effects of diesel exhaust particles and carbon black on induction of dust mite allergy in brown norway rats. J Immunotox 2(1):41-9.

Many Ties to Asthma


Traffic-related exposures are extensive and associated with adverse health outcomes

30-45% of people living in large North American cities live in traffic exposure areas

Conclusion: Traffic-related pollution may cause a range of health outcomes including cardiovascular and respiratory effects

Health Effects InstituteComprehensive Review of Traffic Research (2010)


9

• ORD FY06 Raleigh NR Pilot – Project & instrument ‘shakedown’– Analysis, Tox samples, various modeling efforts

• IAG w/ Federal Highway Admin. (FHWA)– Las Vegas (2009-10)

• Focus on near road emission profile– Detroit (2010-11) – FHWA & NEXUS

• NEXUS STAR project to assess health (asthma, indicators)• Coop allow coordination between ORD and awardee• Coordination with OAQPS, negotiations w/ NIEHS & others

• Intensive (targeted) ORD Study – Raleigh (~2013)

Implementation of ORD’s Near Road Action Plan


10

Draft Near Roadway Action Plan

• Source / Emissions – characterization (combustion and mechanically generated); source apportionment; impact of traffic conditions (e.g., volume, speed, fleet mix)

• Air Quality – spatial and temporal variability; atmospheric processes; impact of environmental conditions (e.g., topography, meteorology)

• Exposure Assessment – gradients; source apportionment; dispersion / AQ-linked models

• Health Effects – source apportionment; tox and epi panel studies

• Indoor Micro-environments – source impacts; mitigation

11

Intramural Program EPA STAR Program(PM Ctrs & RFAs)

EPA Partners:• Federal Agencies (FHWA)• NIEHS• Health Effects Institute• Academia• Industry

ORD Near Road Research

NRMRL - Emission Source Characterization

NERL - Exposure, Atmos. Measurement

and Models

OTAQ

Epidemiology Clinical and Animal Toxicology Studies Molecular

NHEERL


12

PM Centers – Near-Road Studies

University of Rochester PM Center– Epidemiological studies in Rochester and Germany – urban fine

and ultrafine particles, gaseous pollutants, with source apportionment to identify traffic component

– Controlled human exposure studies in Rochester, to be conducted in the early morning to capture rush hour exposures

– Animal studies using on-highway exposures

Harvard PM CenterTERESA tunnel study: Harvard's mobile facility transforms primary emissions from a large Boston tunnel to realistic atmospheric mixtures (with primary and secondary particles) for toxicological studies.

http://upload.wikimedia.org/wikipedia/commons/d/db/Tunnel-large.jpg�

Sue Kimbrough1, Richard Shores1, Donald Whitaker1, Bill Mitchell1, Gayle Hagler1,Daniel Vallero1, Alan Vette1, Carry Croghan1, Victoria Martinez2, Michael Claggett2.1U.S. Environmental Protection Agency, Office of Research and Development2Federal Highway Administration

EPA/FHWA Near Road CollaborationProject:

Region 5 Briefing

National Near Road MSAT Study

Office of Research and Development

Photo image area measures 2” H x 6.93” W and can be masked by a collage strip of one, two or three images.

The photo image area is located 3.19” from left and 3.81” from top of page.

Each image used in collage should be reduced or cropped to a maximum of 2” high, stroked with a 1.5 pt white frame and positioned edge-to-edge with accompanying images.

January 10, 2011

Who are the members of the EPA/FHWA Near Road team?

Project Team:

• Strategic Project/Science Management – Dan Costa– Carlos Nunez– Doug Mckinney– Richard Baldauf– David Kryak– Alan Vette

• NRMRL – Project Management– Sue Kimbrough

Office of Research and Development1

– Sue Kimbrough– Richard Shores

• EPA/FHWA Technical Working Group (including above)– Victoria Martinez (FHWA) -- IAG Project Officer– Dan Vallero (EPA IAG Project Officer)– Bill Mitchell– Donald Whitaker– Richard Baldauf– Gayle Hagler– James Hirtz– Jason Herrington– Paul Solomon– Other EPA technical staff as needed……..

Near Road Air Quality Background

• Estimate over 45 million people live within 100 meters of a major transportation system including 4+ lane highways – many more work or attend school near roads

• More than 1,000 compounds have been identified in exhaust and evap emissions from mobile sources

� Regulated Pollutants

�� Air ToxicsAir Toxics

� Particulate Matter


� Particulate Matter

• Air quality measurements have indicated elevated pollutant concentrations near roads

• Near-road exposures have been associated with numerous adverse health endpoints, including:

� Respiratory effects (e.g., asthma)

� Cardiovascular effects

� Adverse birth outcomes

� Premature mortality

� Cancer

Why are we involved in this project? --- Key Science Questions ---

• What is the spatial and temporal variability of traffic-related pollutants near roadways?

• How do traffic (volumes, speeds, fleet mix, etc.) and environmental (meteorology, topography, etc.) conditions affect vehicle emissions and near road air quality?

• What marker(s)/metric(s) can be used to identify exposures to traffic-related emissions?


• What marker(s)/metric(s) can be used to identify exposures to traffic-related emissions?

• What tools are available, or can be produced, to identify the relationship from traffic emissions to population exposures to adverse health effects for use in regulatory decision making and transportation planning?

• What are the concentration gradients at a fine(er) scale resolutions?

• How does urban topography and barriers impact these gradients?

• Are there mitigation techniques that can reduce exposures to susceptible populations?

Step Site Selection Steps Method Comment

1 Determine Site Selection Criteria Monitoring Protocol Developed by U.S. FHWA

2 Develop List of Candidate Sites GIS Data; Site Visit(s)Additional sites added as

information is developed.

3Apply Coarse Site Selection

Filter

Team Discussions,

Management Input

Eliminate sites below

acceptable minimums.

Site Selection Methodology


4 Site Visit Field TripApplication of Fine Site

Selection Filter5 Select Candidate Site(s)

Team Discussions,

Management Input

6 Obtain Site Access PermissionsContact Property

Owners

If property owners do not grant

permission, then the site is

dropped from further

consideration.

7

Site Logistics (i.e., physical

access, utilities – electrical and

communications)

Site Visit(s), Contact

Utility Companies

Outcomes Clients

Provide FHWA with data necessary to comply with Settlement

Agreement.FHWA

Understanding the relationship between traffic, meteorology

and near road air quality

FHWA,

NRMRL/NERL

What do we hope to get out of this effort?


and near road air quality NRMRL/NERL

Identify metrics used to relate traffic emission impacts on air

quality and adverse health effects for inclusion in risk and

health assessments

FHWA, OTAQ,

OAQPS, NHEERL,

HEI, states

Provide improved air quality dispersion algorithms for near-

road assessments and upgrade EPA’s regulatory dispersion

model AERMOD

OTAQ, OAQPS,

NOAA, FHWA, DOE,

states

Roadside Site (10 Meters)

100 Meter Downwind Site

300 Meter Downwind Site

Upwind Site (100 Meters)


Wind Flow

Concentration Gradient

Distance

Co

nce

ntr

ation

Concentration Gradient

Distance

Co

nce

ntr

ation

Selection Considerations Monitoring Protocol Criteria

AADT (> 150,000)Only sites with more than 150,000 annual average daily traffic (AADT) are considered as

candidates.

Geometric Design

The geometric design of the facility, including the layout of ramps, interchanges and similar

facilities, will be taken into account. Where geometric design impedes effective data

collection on MSATs and PM2.5, those sites will be excluded from further consideration.

Topology (i.e., Sound Barriers, Road

Elevation)

Sites located in terrain making measurement of MSAT concentrations difficult or that raise

questions of interpretation of any results will not be considered. For example, sharply sloping

terrain away from a roadway could result in under representation of pollutants.

Geographic LocationCriteria applicable to representing geographic diversity within the U.S. as opposed to within

Site Selection Criteria


Geographic LocationCriteria applicable to representing geographic diversity within the U.S. as opposed to within

any given city.

Availability of Data (Traffic Volume Data)

Any location where data, including automated traffic monitoring data, meteorological or

MSAT concentration data, is not readily available or instrumentation cannot be brought in to

collect such data will not be considered for inclusion in the study.

Meteorology

Sites will be selected based on their local climates to assess the impact of climate on

dispersion of emissions and atmospheric processes that affect chemical reactions and phase

changes in the ambient air.

Downwind Sampling

Any location where proper siting of downwind sampling sites is restricted due to topology,

existing structures, meteorology, etc., may exclude otherwise suitable sites for consideration

and inclusion in this study.

Potentially confounding air pollutant sourcesThe presence of confounding emission sources may exclude otherwise suitable sites for

consideration and inclusion in this study.

Site Access (Admin/Physical)Any location where site access, is restricted or prohibited either due to administrative or

physical issues, will not be considered for inclusion in the study.

While not explicitly included in the Monitoring Protocol, the following selection criteria were deemed important to the selection process and

were included.

I-15 Monitoring Site:


Meteorology

Winds generally from the SSW, although diurnal variations exist


I-15 Site


Instrument Deployment - Overview

Core Instruments 10 Meters @

I-96 Roadside

100 Meter

Downwind

300 Meter

Downwind

100 Meter

Upwind

TO-11A Cartridge sampling X X X X

TO-15 Canister sampling X X X X

Continuous GC X X X X

Continuous gas monitoring (CO, NOx ) X X X X

Continuous black carbon monitoring (Aethalometer) X X X X

Continuous fine particle (TEOM) X X X X

Integrated PM2.5 (FRM) X X X X


Integrated PM2.5 (FRM) X X X X

Wind speed/wind direction (sonic anemometer) X X X X

Meteorological monitoring (temp, RH, solar, etc.) X

Study Enhancements

Continuous Ultrafines (20nm – 200+ nm) X X

Water-based CPC X X

Continuous gas monitoring (CO2) X X X X

Michigan DOT -- Traffic Data

Vehicle Count, Vehicle Speed, Vehicle Class


Remote Data Streaming –WinAQMS/WinCollect, RealVNC Software


100

150

200

(pp

b)

NO

NO2

04/21 04/22 04/23 04/24 04/250

50

C

1

CO

0.5

C (

ppm

)

CO

04/21 04/22 04/23 04/24 04/250

10000

15000

volu

me

04/21 04/22 04/23 04/24 04/250

5000

Tra

ffic

10n

2

4

6

8

10

d (m

/s)

and

dire

ctio

n

wind from road

Office of Research and Development 304/21 04/22 04/23 04/24 04/25-2

0

2

Win

d sp

eed

50

100

150

NO

(pp

b)

Site 1

Site 4

04/22 04/23 04/24 04/250

50

0 5

1

ppb)

Site 1

Site 4

04/21 04/22 04/23 04/24 04/250

0.5

CO

(p

10000

Site 1

04/21 04/22 04/23 04/24 04/250

5000

BC

(ng

m-3

)

Site 4

4000

6000

8000

10000

12000

Tra

ffic

vol

ume

04/21 04/22 04/23 04/24 04/252000

4000

5

10

s) a

nd d

irect

ion

Office of Research and Development 4

04/21 04/22 04/23 04/24 04/25-5

0

Win

d sp

eed

(m/s

10

20

30

40

NO

(pp

b)

Site 1

Site 4

07/050

10

0.4

0.6

0.8

(ppb

)

Site 1

Site 4

07/050

0.2

0.4C

O

3000

4000

3 )

Site 1

Site 4

07/050

1000

2000

BC

(ng

m-

15000

5000

10000

Tra

ffic

vol

ume

R d07/050

5

10

(m/s

) an

d di

rect

ion

Radar –Instrument Issues

Office of Research and Development 507/05 07/06 07/07 07/08 07/09 07/10 07/11-5

0

Win

d sp

eed

(

10

20

30

40

NO

(pp

b)

Site 1

Site 4

07/050

10

0.4

0.6

0.8

(ppb

)

Site 1

Site 4

07/050

0.2

0.4C

O

3000

4000

3 )

Site 1

Site 4

07/050

1000

2000

BC

(ng

m-

15000

5000

10000

Tra

ffic

vol

ume

07/050

5

10

(m/s

) an

d di

rect

ion

Office of Research and Development 607/05 07/06 07/07 07/08 07/09 07/10 07/11-5

0

Win

d sp

eed

(

Average hourly traffic volume by week of year

12000

14000

Vol

ume

10000

12000

urly

Tra

ffic

V

6000

8000

erag

e H

ou

2000

4000

Av

0

2000


Week of Year

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52

Average daily traffic volume by weekday and weekendAverage daily traffic volume by weekday and weekend

220000

ume 180000

200000

y Tr

affic

Vol

120000

140000

160000

erag

e D

aily

80000

100000

Ave

40000

60000

Office of Research and Development 8Weekday Weekend

20000

Black Carbon Concentration Black Carbon(all wind directions)

12000

14000

(winds from road)

12000

14000

entra

tion

(ng

m3 )

4000

6000

8000

10000

entra

tion

(ng

m3 )

4000

6000

8000

10000

Con

ce

0

2000

4000

Con

ce0

2000

4000

- 100 Meters 20 Meters 100 Meters 300 Meters - 100 Meters 20 Meters 100 Meters 300 Meters


Hourly Average NO2 Concentrations Mean NO2 Concentations by Station( ll i d di i )(winds from road)

60

80

(all wind directions)

60

80

cent

ratio

n (p

pb)

20

40

60

cent

ratio

n (p

pb)

20

40

60

Con

c

0

Con

c

0

0



Hourly Average NO Concentations( ll i d di ti )

Hourly Average NO Concentrations(all wind directions)

250

300

(winds from road)

250

300

cent

ratio

n (p

pb)

100

150

200

cent

ratio

n (p

pb)

100

150

200

100 M t 20 M t 100 M t 300 M t

Con

c

-50

0

50

100 Meters 20 Meters 100 Meters 300 MetersC

onc

-50

0

50



Hourly Average NOX Concentations by Station( ll i d di ti )

Hourly Average NOX Concentrations(all wind directions)

300

400

y g(winds from road)

300

400

cent

ratio

n (p

pb)

200

300

cent

ratio

n (p

pb)

200

300

100 M t 20 M t 100 M t 300 M t

Con

c

0

100

100 Meters 20 Meters 100 Meters 300 Meters

Con

c0

100



Hourly Average CO Concentrations( i d f d)

Hourly Average CO Concentations by Station( ll i d di i ) (winds from road)

2.0

2.5

(all wind directions)

2.0

2.5

cent

ratio

n (p

pm)

1.0

1.5

cent

ratio

n (p

pm)

1.0

1.5

Con

c-0.5

0.0

0.5

100 M t 20 M t 100 M t 300 M t

Con

c

-0.5

0.0

0.5

- 100 Meters 20 Meters 100 Meters 300 Meters- 100 Meters 20 Meters 100 Meters 300 Meters


Black Carbon(all wind directions)

12000

14000

g m

3 )

8000

10000

12000

ntra

tion

(n

6000

8000

Con

cen

2000

4000

ter ng er all ter ng er all ter ng er all ter ng er all

0

-100 Meters 20 Meters 100 Meters 300 Meters

Office of Research and Development

Wint

erSpri

ngSum

mer FalW

inter

Spring

Summer Fal

Wint

erSpri

ngSum

mer FalW

inter

Spring

Summer Fal

14

Seasonal NO2 Trends -- Station 1(all wind directions)

80

ppb)

60

ntra

tion

(p

40

Con

cen

20

0

Office of Research and Development 15Winter Spring Summer Fall

Seasonal NO2 Trends(all wind directions)

80

(ppb

) 60

entra

tion

40

Con

ce

20

ter ng er all ter ng er all ter ng er all ter ng er all

0 -100 Meters 20 Meters 100 Meters 300 Meters


Wint

eSpri

ngSum

me FalW

inte

Spring

Summe Fal

Wint

eSpri

ngSum

me FalW

inte

Spring

Summe Fal

Preliminary Results: Criteria PollutantsCriteria Pollutants

Mean Carbon Monoxide Concentration by Hour

0.9

1.0Legend

station1

station2

station3

ppm

0 5

0.6

0.7

0.8 station4

NO2 gradient existed for hourly average concentrations over the

0.2

0.3

0.4

0.5

entire study

0.10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour

50

60

ppb)

CO hourly average concentrations (ppm)

NO/NO2/NOx Concentrations (ppb)

10

20

30

40

Con

cent

ratio

n (p

NO2NONOx

(pp )

CO gradients existed, with strong diurnal patterns even


0-100 0 100 200 300

Distance (m)

without similar traffic signals

250

300

350

400

7.0

8.0

9.0

10.0

NO Concentration Gradient: Feb 3, 2009, Day with Low Wind Speed

Wind SpeedNO Concentrations

Wind Direction

Approximate Direction of Influence:

Wind Direction


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100 Meter Downwind

300 Meter Downwind

100 Meter Upwind

Wind Direction

Wind Speed

Direction From Road

250

300

350

400

6.0

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8.0

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Wind Direction

Black Carbon Concentration Gradient: Feb 3, 2009, Day with Low Wind Speed

Black Carbon

Wind Speed

Wind Direction


Wind Direction


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10 Meter Roadside

100 Meter Downwind

300 Meter Downwind

100 Meter Upwind

Wind Speed

Direction From Road

250

300

350

400

6.0

7.0

8.0

9.0

10.0

SO2 Concentration Gradient:Feb 3, 2009, Day with Low Wind Speed

SO2 Concentrations

Wind SpeedWind Direction


Wind Direction


0

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200

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Wind Direction

100 Meter Downwind

100 Meter Upwind

Wind Speed

Direction From Road

250

300

350

400

6.0

7.0

8.0

9.0

10.0

10 Meter Roadside

100 Meter Downwind

NO Concentration Gradient: March 3, 2009, Day with High Wind Speed

Wind Speed

NO Concentrations

Wind Direction


Wind Direction From Road


0

50

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200

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300 Meter Downwind

100 Meter Upwind

Wind Direction

Wind Speed

From Road

250

300

350

400

6

7

8

9

10

Wind Direction

Black Carbon Concentration Gradient:March 3, 2009, Day with High Wind Speed

Black Carbon

Wind SpeedWind Direction


Wind Direction


0

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200

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5

6 Wind Direction

10 Meter Roadside

100 Meter Downwind

300 Meter Downwind

100 Meter Upwind

Wind Speed

Direction From Road

250

300

350

400

6.0

7.0

8.0

9.0

10.0

Wind Direction

SO2 Concentration Gradient:March 3, 2009, Day with High Wind Speed

SO2 Concentrations

Wind Speed

Wind Direction


Wind Direction From Road


0

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200

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0.0

1.0

2.0

3.0

4.0

5.0

Wind Direction

100 Meter Downwind

100 Meter Upwind

Wind Speed

From Road

Lessons Learned

• Site Selection / Access / Infrastructure: Never too early to start process, no such thing as perfect site (project manager, site operator, modelers, policy makers).

Property owners: Environmental Awareness – perhaps?p y p p

Liability, Insurance, Compensation, Hassle Factor(s), etc.

Electrical, Security, Communications…costs can be high.

• Timeline: Site Selection, access, infrastructure – always takes more time than originally , , y g yanticipated.

• Budget: Field projects are usually more costly than originally anticipated.

On-site operator costly (travel, lodging, per diem).

Integrated Sampling: Site-operator costs and laboratory analysis costs high (sample prep, shipping, sample analysis).

• Study Design: No perfect design.

• Database Management: Essential to data flow (from field site to data analysts).


Summary

• Appears to be concentration gradient for gaseous pollutants and black carbon associated with distance from roadway however more analysis is required.

• Appears to be associations with traffic volume (i.e., higher concentrations with higher traffic volumes).

• Effect of wind speed appears to be a factor with regards to concentration


• Effect of wind speed appears to be a factor with regards to concentration gradient (e.g., dilution effect) and needs to be investigated further.

• Train does not appear to be a substantial source.

• Non I-15 sources may be larger contributors than previously expected, for example: parking lot, airport, surrounding streets.

• Next Study City: Detroit – Study In Progress

Overview Map of Detroit


Detroit Site: Eliza Howell Park


Acknowledgements

We thank Brian Schumacher and Jeffery Lantz of the EPA Las Vegas Facility for their continuing support of this project. We thank American Ecotech for shelter/instrument operation support. We thank David Proffitt, Michal Derlicki, Richard Snow, Nikki Williams of ARCADIS for site-operation and logistical support,


ARCADIS for site-operation and logistical support, Hunter Daughtrey, Dennis Williams, Karen Oliver, Lydia Brouwer, Herb Jacumin, of Alion Science and Technology for preparation and analysis of sampling media and Jeff Baker of TSI for use of Ultrafine Particulate Samplers.

Office of Research and DevelopmentNational Risk Management Research Laboratory/Air Pollution Prevention and Control Division November 6, 2007

Rich BaldaufU.S. Environmental Protection Agency

January 11, 2011

Mitigation of Near-Road Air Pollution Impacts

2

One way to mitigate impacts: Roadway Design and Roadside Features?

3

One way to mitigate impacts: Roadway Design and Roadside Features?

(Heist et al., 2009; Baldauf et al., 2009)

4

Field studies showed the influence of noise barriers and

vegetation on both pollutant concentrations and gradients

20 nm size particles

0

100

200

300

400

500

600

700

800

900

20 40 60 80 100

120

140

160

180

200

220

240

260

280

300

Distance from I-440 (m)

PM c

onc

(num

ber/c

m3)

Open FieldNoise Barrier OnlyNoise Barrier & Vegetation

(Baldauf et al., 2008a; 2008b)

Noise Barrier Effects

Baldauf et al., (2008a)

Noise barrier effects most pronounced when winds from

the road and higher traffic volumes. Barriers and roadside

features may also trap pollutants behind the structure,

leading to higher on-road concentrations

Finn et al., (2010)5

6

Vegetation Effects

0

(Ongoing Work - Preliminary Data: do not cite, quote, or reference)

15%

10%

5%

WEST EAST

SOUTH

NORTH

Cut Section Effects

Preliminary data comparing at-grade and cut section NO2 shows high variability, although highest concentrations occurred at-grade

0

20

40

60

80

100

120

0 20 40 60 80 100 120

Cut Section NO2 (ppb)

At-G

rade

NO

2 (pp

b)

0.1

1

10

100

0 60 120 180 240 300 360

Wind Direction

At-

Gra

de/C

ut S

ecti

on R

atio

NONO2NOx

(Ongoing Work - do not cite, quote, or reference)

7

8

Future Work in Detroit

Two primary objectives:

• Quantify vegetation impacts on near-road air quality

• Assess concentration variability for varying neighborhood designs

Site 2: I-275 South• On-road and near-road mobile monitoring

with varying vegetation and neighborhood configurations

• Fixed and backpack monitoring for detailed vegetation assessment

9

Site 3: I-96 Eliza Howell Park

• On-road and near-road mobile monitoring with varying neighborhood configurations

• Comparison with EPA/FHWA fixed site measurements

10

Stationary and Backpack~22-24 hour stationary sampling~2 hours backpack samplingParticulate MatterParticle count in select size bins (HHPC)Black carbon (Micro-aethalometer)

Mobile Electric Vehicle ~3 hrs per day (3-4 driving routes)Particulate MatterUFP size distributions (EEPS)Coarse and fine size distributions (APS)Black carbon (Micro-aethalometer)

Gases

CO (Single Quantum Cascade Laser)NO2 (tentative)

Sampling and Schedule

Sampling scheduled to begin late May, 201111

12

For More Information

• EPA Contacts:

–Rich Baldauf ([email protected])–Gayle Hagler ([email protected])

• Websites:

–http://www.epa.gov/airscience/quick-finder/near-roadway.htm–http://www.epa.gov/nrmrl/appcd/nearroadway/workshop.html

• References– Baldauf, R.W., A. Khlystov, V. Isakov, et al. 2008a. Atmos. Environ. 42: 7502–7507.– Baldauf, R.W., E. Thoma, M. Hays, et al. 2008b. J. Air & Waste Manage Assoc. 58:865–878.– Baldauf, R.W., N. Watkins, D. Heist, et al. 2009. J. of Air Quality, Atmosphere, & Health. Vol. 2: 1-9.– Finn, D., K.L. Clawson, R.G. Carter et al., 2010. Atmos. Environ. 44: 204-214.

– Heist, D.K., S.G. Perry, L.A. Brixey, 2009. Atmos. Environ. 43: 5101-5111.

Documents

Region 5 Overview of ORD’s Detroit Area Near Road...Region 5 Overview of ORD’s Detroit Area Near Road Research - Introduction. U.S. Environmental Protection Agency. 2. Office of