0Office of Research and DevelopmentNational Exposure Research Laboratory

“MODELING OF TRAFFIC-RELATED

AIR POLLUTION AT URBAN SCALES”

DR VLAD ISAKOV,

U.S. ENVIRONMENTAL PROTECTION AGENCY, USA

EMAIL: ISAKOV.VLAD(AT)EPA.GOV

WEB: HTTPS://WWW.RESEARCHGATE.NET/PROFILE/VLAD_ISAKOV

DR. ISAKOV IS RESEARCH PHYSICAL SCIENTIST IN THE COMPUTATION EXPOSURE DIVISION OF THE EPA’S NATIONAL EXPOSURE RESEARCH

LABORATORY. HIS CURRENT RESEARCH FOCUSES ON THE DEVELOPMENT AND TESTING THROUGH APPLICATIONS INNOVATIVE APPROACHES TO MODEL

SPATIALLY AND TEMPORALLY RESOLVED AIR QUALITY CONCENTRATIONS IN SUPPORT OF EXPOSURE AND HEALTH STUDIES. VLAD HAS BEEN INVOLVED IN

A NUMBER OF AIR POLLUTION MITIGATION INVESTIGATIONS TO EXPLORE OPPORTUNITIES FOR REDUCING PERSONAL EXPOSURE IN THE URBAN

ENVIRONMENT.

DELVING INTO PASSIVE TECHNIQUES FOR AIR POLLUTION MITIGATION

PROGRAMME TALKS

INTRODUCTION

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WEBINAR

TALKS

Q&A AND

PANEL

DISCUSSION

AUT/WIN

SERIES

CLOSING

COMMENTS / WHAT NEXT?

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1Office of Research and DevelopmentNational Exposure Research Laboratory

Significance of Exposures due to

Traffic-Related Air Pollutants (TRAPs)

Note: In addition to traffic, there are other urban pollution sources that can have

similar impacts if emitted at ground level, but traffic is most common and ubiquitous

Percentage of population living within 500 m of a

roadway with > 25,000 AADT

Karner et al, ES&T, 2010

2Office of Research and DevelopmentNational Exposure Research Laboratory

Why Model TRAPs?

• Global mega-cities seeing extensive growth in mobile

source emissions and associated increases in exposures to

traffic-related air pollutants in the near-source environment✓ over 50 million people living near road and transport facility

✓ and over 4 million children within 150 m of road in the U.S.

✓ On average, people spend > 1hr/day commuting

• Community groups becoming increasingly active in local

initiatives that seek to mitigate potentially harmful

environmental conditions

• Modeling could help to study near-source pollution in an

easier manner, and explore the benefits of improvements to

air quality and exposures

3Office of Research and DevelopmentNational Exposure Research Laboratory

• This study compared the burden of

disease associated with on-road

PM2.5 in central North Carolina,

using a hybrid modeling approach

(including R-LINE) and traditional

chemical transport model

• Results suggest the potential for

previous studies to have

underpredicted premature mortality

from primary on-road PM2.5

Accounting for Near-road Exposure

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Modeling to Support Epidemiologic Studies

Background

Stationary

Onroad

Hybrid

Onroad

Hybrid

Stationary

5Office of Research and DevelopmentNational Exposure Research Laboratory

Community LINE Source Model (C-LINE)

• C-LINE allows users to run what-if scenarios:

✓ What will happen if diesel traffic

doubles on this roadway?

✓ How is near-road air quality affected by

a traffic jam?

• For C-LINE, the user is not required to

provide any input datasets, and they can

manipulate the existing ones or upload their

own if desired

Optimized for running on the web using typical inputs as screening-level model

(http://www.cmascenter.org/c-tools)

6Office of Research and DevelopmentNational Exposure Research Laboratory

City-scale Real-time Model

• Increased interest in city-scale mitigation of air pollution✓ Transportation planning: Congestion pricing, creation of fossil-fuel

free zones

• C-LINE framework adapted for C-REAL✓ Road network upgraded to use Open Street Map

✓ Real-time meteorology from NOAA’s HRRR Model

✓ Real-time traffic adjustment from Google’s Waze ®

• On-demand prediction of traffic-related air pollution for

3 areas (Kansas City, Houston, New York City) ✓ Road network with Annual Average Daily Traffic (AADT) from

FHWA’s HPMS 2013

✓ Emissions factors from EPA’s MOVES-2014 modeling system

✓ EFs as a function of 12 road types, 12 vehicle classes, T, RH

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C-REAL Snapshot for Kansas City

Near Real-time visualization of results with traffic and met updates for 3 urban areas

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Connections to Additional Datasets

• World Urban Database and Portal Tool (WUDAPT)

for building dimensions and canopy width

• Urban Multi-scale Environmental Predictor (UMEP)

for enhanced characterization of additional boundary

layer parameters

• Roadside noise and vegetation barriers

9Office of Research and DevelopmentNational Exposure Research Laboratory

Why Study Roadside Vegetation?

• Few “short-term” mitigation options for near-road air quality

concerns✓ Emission reductions take long time to implement (fleet turnover

required)

✓ Planning and zoning involved in rerouting and traffic reduction

programs

✓ Buffer/exclusion zones may not be feasible or effective

• Roadside vegetation may already be present

• Roadside vegetation has other positive benefits

10Office of Research and DevelopmentNational Exposure Research Laboratory

How Roadside Vegetation Affecting Near-road Air Pollution

✓ Field studies1

▪ Chapel Hill, NC (vegetation)

▪ San Francisco (vegetation)

✓ Wind tunnel assessments2

▪ Site-specific configurations

✓ Computational modeling 3

▪ Comprehensive Turbulent Aerosol Dynamics and

Gas Chemistry (CTAG) model with LES

▪ Generalized vegetative scenarios

1 Dr. Rich Baldauf, US EPA2 Dr. David Heist, US EPA3 Prof. Max Zhang, Cornell Univ.

11Office of Research and DevelopmentNational Exposure Research Laboratory

Chapel Hill Vegetation Barrier Study

12Office of Research and DevelopmentNational Exposure Research Laboratory

• Used CTAG model with LES to simulate the impacts of

vegetation barriers

✓ Evaluated model results against the Chapel Hill field study data1

✓ The results of model evaluation against the Chapel Hill data

provided us with the confidence in CTAG with LES to simulate

other scenarios

• Then used model to explore effects of vegetation barriers on

near-road particle concentrations using common near-road

configurations

• Modeling suggests two potentially viable design options as a

potential mitigation option for near-road particulates:

✓ A wide vegetation barrier with high Leaf Area Density

✓ Vegetation–solid barrier combinations, i.e., planting trees next to

a solid barrier

Chapel Hill Vegetation Barrier Study

1Tong et al., 2016, Science Tot. Environ., 541, 920-927

13Office of Research and DevelopmentNational Exposure Research Laboratory

San Francisco Vegetation Barrier Study

• On-road and near-road mobile and fixed monitoring with

varying vegetation types✓ Bush/tree combinations with varying porosity

14Office of Research and DevelopmentNational Exposure Research Laboratory

STOP 1

STOP 2

STOP 4

STOP 3

San Francisco Vegetation Barrier Study

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✓ Each distribution is based on a ~10,000 observations during the entire field campaign.

✓ Thus, the distributions represent a longer-term exposure over the range of varying

meteorological conditions

Distributions of observed CO and UFP concentrations from all 1-second

mobile measurements in Woodside across six locations behind the barrier

San Francisco Vegetation Barrier Study

16Office of Research and DevelopmentNational Exposure Research Laboratory

Modeling the Impact of Vegetation Barriers

• The results of San Francisco Vegetation Barrier Study were used to ✓ compute the effect of a vegetation barrier under different

meteorological conditions, and

✓ examine the applicability of solid barrier algorithms for vegetation

barriers

• We can quantify the effect of vegetation on reducing near road

concentrations by estimating the height of a solid barrier that would

result in the same reduction

• The primary effect of a solid barrier is to increase vertical dispersion

of the pollutants emitted from the road✓ A simple model of this effect adds the height of the barrier to the

vertical dispersion *

* Note: effective barrier height doesn’t include deposition

17Office of Research and DevelopmentNational Exposure Research Laboratory

where q is the emission rate per unit length of the

road, H is the height of the barrier, sw is the

standard deviation of the vertical velocity

fluctuations, U is the near surface wind speed, R is

the ratio of the concentration behind the vegetative

barrier to the concentration in the open section,

and H0=2 m corresponds to vehicle induced

turbulence in the open section

Effect of Vegetative Barriers on Concentrations

• Based on solid barrier model algorithms already developed

(Schulte et al., 2014), we used a simplified modelling approach to

quantify the effect of vegetation on near-road concentrations

observed in the California 2014 field study

• In this approach, the effect of vegetation on reducing near-road

concentrations was estimated by calculating the height of the

barrier that would result in the same reduction

18Office of Research and DevelopmentNational Exposure Research Laboratory

Effect of Vegetative Barriers on Concentrations

Stop # Height of

Vegetation (m)

Description Reduction

R

Equivalent Barrier

Height (m)

1 0 Clear 1 2.0

2 3-4 vegetation buffer ~6-7m with approx. 75% coverage 0.77 3.5

3 3-4 Wide gap (>4m) with highly porous mix of trees and thin

bushes (~6-7m with approx. 50% coverage)1 2.0

4 3-4 vegetation buffer ~6-7m with approx. 90% coverage 0.73 3.9

5 3-4 trees ~10m, thick vegetation buffer ~7m, and 1m wide

gap with little vegetation0.85 2.8

6 3-4 trees 10-12m, vegetation buffer ~7m with approx. 90%

coverage0.71 4.1

R refers to the mean of the reductions of the four species (CO, NO2, BC, UFP) at each of the stops

Thus, the concept of the “equivalent

barrier height” would allow using more

established dispersion models for solid

barriers (Venkatram et al., 2016) to compute

the effect of vegetative barriers under

different meteorological conditions with

porosities less than 50%

19Office of Research and DevelopmentNational Exposure Research Laboratory

20Office of Research and DevelopmentNational Exposure Research Laboratory

Impact of Vegetation Barriers

• A roadside vegetation barrier can affect downwind pollutant

concentrations in several ways: 1) enhance vertical dispersion by forcing the flow over the barrier

2) remove pollutants from the flow passing through the barrier through dry

deposition

3) inhibit vertical dispersion of the pollutants passing through the barriers by

reducing turbulent velocities in the flow

• While mechanisms (1) and (2) will reduce downwind concentrations,

the third mechanism can increase downwind concentrations relative to

those in the absence of a barrier

• The relative roles of these mechanisms (which depends on the physical

structure including the porosity of the barrier) are not well understood

• Thus, while roadside bushes can result in improved near-road air

quality if designed properly, some configurations might not enhance

dispersion or could even increase concentrations behind the barrier

relative to those in flat terrain

21Office of Research and DevelopmentNational Exposure Research Laboratory

Connection to EnvioroAtlas

22Office of Research and DevelopmentNational Exposure Research Laboratory

Connection to EnvioroAtlas

23Office of Research and DevelopmentNational Exposure Research Laboratory

Summary – Vegetation Barriers

• Research shows the ability for roadside vegetation to

reduce downwind pollutant concentrations near roads

• Models will be important in designing and evaluating

vegetative barriers✓ Simple model that adds the height of the barrier to the vertical dispersion

✓ San Francisco study results show that computed heights are consistent with

the heights of the vegetation

✓ This suggests that it might be possible to estimate the equivalent height of a

barrier using the actual height of the vegetative barrier and its porosity

• For complex urban environment, advanced modeling

approaches are needed

24Office of Research and DevelopmentNational Exposure Research Laboratory

“HOW CFD MODELLING CAN INFORM THE POSITION OF GREEN

INFRASTRUCTURE TO IMPROVE AIR QUALITY IN URBAN SPACES?”

DR VERA RODRIGUES,

UNIVERSITY OF AVEIRO, PORTUGAL

EMAIL: VERA.RODRIGUES(AT)UA.PT

WEB: WWW.CESAM.UA.PT/VRODRIGUES

DR. RODRIGUES IS A POST-DOCTORAL RESEARCHER AT THE CENTRE FOR ENVIRONMENTAL AND MARINE STUDIES (CESAM), UNIVERSITY OF AVEIRO.

HER RESEARCH EXPERTISE IS IN THE AREA OF ATMOSPHERIC PROCESSES AND MODELLING IN THE CONTEXT OF ENVIRONMENT AND PLANNING. VERA

HAS UNDERTAKEN RESEARCH ON AIR POLLUTION AND ENVIRONMENTAL MODELLING, EXAMINING THE INTERACTIONS BETWEEN POLLUTION DISPERSION,

URBAN MICRO-CLIMATE IMPACTS AND MITIGATION MEASURES TO REDUCE POPULATION EXPOSURE.

DELVING INTO PASSIVE TECHNIQUES FOR AIR POLLUTION MITIGATION

PROGRAMME TALKS

INTRODUCTION

S

WEBINAR

TALKS

Q&A AND

PANEL

DISCUSSION

AUT/WIN

SERIES

CLOSING

COMMENTS / WHAT NEXT?

0-

5

5-

55

55-

7070-

75