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Nohad A. Toulan School of Urban Studies and Planning

Winter 2009

Spatial patterns of air toxins in the region Spatial patterns of air toxins in the region

Linda Acha George Portland State University

Vivek Shandas Portland State University

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Citation Details Citation Details Vivek Shandas and Linda George,” Neighborhood, Neighborhood, Neighborhood: Spatial Patterns of Air Toxins and Implications for Metroscape Residents and Urban Planners”, Metroscape, Winter 2009.

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Periodic Atlas of the Metroscape

Metroscape Page 13

Studies from England to Boston to Los Angles have long documented health impacts associ-ated with dirty air, but an increasing number

of researchers are connecting air quality with urban form and human health. A recent landmark study found that children living near high-traffic areas in Los Angeles suffered long-term damage to lung tis-sue and contracted respiratory illnesses.

Ironically, while each breath we take is a product of the air quality in our immediate surroundings, few studies have described how the quality of air varies within a single city. Air quality research usually fo-cuses on isolated areas or large regional scales. These preferences are partly due to the fact that extensive monitoring of air quality is expensive, which makes it is difficult to know what the conditions are for neigh-borhoods around a city.

All of this changed when the Oregon Department of Environmental Quality (DEQ) decided to under-take a highly technical modeling exercise. Known as the Portland Air Toxics Assessment (PATA), DEQ used land use, topographical, transportation, and meteorological data in the metroscape to identify the possible sources of air toxics emissions and wind patterns, and then modeled the resulting air quality for nearly 1,000 sites in the region (Figure 1). It is important to note that the points on Figure 1 do not represent actual monitored data, but a modeled pre-diction as to what could be going on in those loca-tions. Monitoring throughout the city would be cost-prohibitive.

Thanks to the efforts of DEQ, the PATA study represents one of the highest resolution datasets of modeled air quality in the nation. Additional in-formation about the methods used for creating the air pollution data can be found on DEQ’s website (http://www.deq.state.or.us/aq/toxics/pata.htm). In essence, the study documents emission and disper-sion of 12 urban air pollutants in the Portland area known to have toxic health effects.

This Atlas draws on the PATA study to explore the regional variation of air quality. The PATA study presents an extraordinary opportunity to think about how the creation of new information can help us better plan our cities, but it also challenges us to think about the impacts of the choices we make.

Air Quality

Using a series of spatial analysis techniques, we are able to take individual points of information and create a “layer” of information. The layer provides additional information by drawing on known air quality data and estimating air quality in areas for which no data exist. We use this pro-cess to create several maps of different pollutants for our region. Here, our objective is not to look at every pollut-ant in the PATA study, but to highlight a few pollutants that represent different activities in the metroscape. While the range of concentrations may vary, the protocol for determining concentrations remains the same. We have mapped the "relative cancer risk" associated with each compound (for the cumulative risk map we added the risks). Relative risk refers to how many times the modeled concentrations exceed the baseline risk. The baseline risk is 1 excess cancer in 1 million population due to lifetime exposure to a pollutant. One in a million is baseline level of concern for the EPA. For instance, a relative risk value of "6" predicts 6 excess cancers in a million population as a result of lifetime exposure to a pollutant. The values can be interpreted as the severity of impact associated to exposure to that compound at that location.

Lake Oswego

I84

I5

I405

I5

I205

Portland

Gre

Beaverton

Tigard

TualatinWest Linn

Oregon City

Milwaukie

Fairv

Sherwood

Happy Valley

Gladstone

W

King City

Durham

Rivergrove

Maywood Park

Johnson City

Figure 1

Spatial Patterns of Air Toxins in the Regionby Vivek Shandas and Linda George

MetroscapePage 14

Lake Oswego

I84

I5

I405

I5

I205

Portland

Gre

Beaverton

Tigard

TualatinWest Linn

Oregon City

Milwaukie

Fairv

Sherwood

Happy Valley

Gladstone

W

King City

Durham

Rivergrove

Maywood Park

Johnson City

BenzeneValue

High : 30

Low : 2

Neighborhood Boundary

City Boundary

UGB

Neighborhood Boundary

City Boundary

UGB

Diesel ParticulatesValue

High : 82.6511

Low : 2.7104

Lake Oswego

I84

I5

I405

I5

I205

Portland

Gre

Beaverton

Tigard

TualatinWest Linn

Oregon City

Milwaukie

Fairv

Sherwood

Happy Valley

Gladstone

W

King City

Durham

Rivergrove

Maywood Park

Johnson City

Figure 2

Figure 3

Relative Cancer Risk:Concentration of Benzene

Relative Cancer Risk:Diesel Particulates

Source: DEQ

Source: DEQ

Metroscape Page 15

We begin by looking at mobile sources of air pollution. These are pollutants from cars, trucks, trains, and boats. One

byproduct of burning fossil fuels is illustrated in Figure 2, which shows the variation in benzene concentrations for the region. As might be ex-pected, the highest concentrations (darkest areas) are along highway corridors. A second byproduct is the creation of diesel particulate matter, tiny frag-ments of carbonaceous material that are created by burning diesel fuel (Figure 3). While both benzene and diesel come from internal combustion engines, one noticeable difference is the concentration of diesel along major truck routes, including inter-states 84 and 5. Most boats also use diesel fuel, and this fact is represented along the Willamette River, which also serves as a major transportation corri-dor. The largest source of diesel particulate matter comes from non-road engines, such as construc-tion equipment.

While mobile sources of air pollution tell one sto-ry about the driving and boating we do, stationary sources tell another. In this case we look specifically at Perchlorethylene (or ‘Perc’), a toxic compound used in the U.S. since the 1940s in several indus-trial processes, including dry cleaning. Unlike mo-bile sources, concentrations of Perc do not follow freeway corridors, but discrete areas throughout the region (Figure 4). Often the high concentrations of some air pollutants can be due to specific land uses that emit these compounds—in this case, probably dry cleaning facilities.

Lake Oswego

I84

I5

I405

I5

I205

Portland

Gre

Beaverton

Tigard

TualatinWest Linn

Oregon City

Milwaukie

Fairv

Sherwood

Happy Valley

Gladstone

W

King City

Durham

Rivergrove

Maywood Park

Johnson City

Neighborhood Boundary

City Boundary

UGB

PerchlorethyleneValue

High : 2.79444

Low : 0.314995

Figure 4

Relative Cancer Risk:Concentration

of Perchlorethylene

Source: DEQ

MetroscapePage 16

Figure 5

While these three examples provide a glimpse into specific concentrations of air pollutants in the metroscape, the PATA study contains

eight other compounds, including chloroform, chromi-um, formaldehyde, nickel and others. When we add up all of these compounds, we can assess their combined con-centration. Figure 5 illustrates an overall estimated health impact from these pollutants. While roadways seem to be the primary indicator for compromised air quality, the pat-terns vary considerably around the region. With a higher density of highways occurring in downtown Portland, it

may not be surprising that downtown has some of the highest concentrations of air pollutants; however, these trends are not confined only to downtown. In fact, Figure 6 illustrates that suburban areas such as those long High-way 217 near Beaverton, and at the interchange of inter-states 84 and 205 near Gresham, are also affected by high concentrations of air pollutants. Unfortunately, one story emerging from these studies is that we cannot avoid air pollution by moving away from downtown areas. Spread-ing out seems to only bring the problem elsewhere.

Lake Oswego

I84

I5

I405

I5

I205

Portland

Gre

Beaverton

Tigard

TualatinWest Linn

Oregon City

Milwaukie

Fairv

Sherwood

Happy Valley

Gladstone

W

King City

Durham

Rivergrove

Maywood Park

Johnson City

Source: DEQNeighborhood Boundary

City Boundary

UGB

Health ImpactValue

High : 183.061

Low : 12.3303

Health Impact Score

Combined Health Impact

Page 17

I5

SUNSET

I5

HALL

SUNSETCORN

ELL

HWY217

MURRAY

PACIFIC

CANYON

BARBUR

SCHOLLS FERRY

FARMINGTON

BURNSIDE

BARNES

BEAVERTON HILLSDALE

KRUSE

CARMAN

BOONESFERRY

TUALATIN VALLEY

WATSON

DURHAM

WALKER

BETHANY

UPPERBOONESFERRY

HWY217-I5

I5-HWY217

SUNSET-MURRAY

BALTIC

NICOLAI

SALTZMAN

I5

I5-HWY 217

CORNELL

SUNSET

HWY217

217

Metroscape

Metroscape

Beaverton

Portland

TigardHealth ImpactValue

High : 183.061

Low : 12.3303

Figure 6 Source: DEQ

Combined Health Impact: Hwy 217 Corridor

Health Impact Score

Lake Oswego

I84

I5

I405

I5

Portland

Beaverton

Tigard

TualatinWest Linn

Oregon C

Milwaukie

Sherwood

Gl

King City

Durham

Rivergrove

J

I5

I84

SUNSET

PO

PACIFIC

HALL

185TH

CORNELL

BURNSIDE

LOMBARD

HWY 217

SANDY

MURRAY

STHELENS

MCLO

UGHLIN

BARBUR

I405

STAFFORD

CORNELIUSPASS

A

FARMIN

GTON

HWY 224

CANYON

39TH

SCHOLL

S FERRY

BORLAND

YEON

GRAND

NAITO

BOONESFERRY

BROADWAY

TUALATIN VALLEY

TERWILLIG

ER

WILLAM

ETTE

MACADAM

BEAVERTON HILLSDALE

COLUMBIA

18TH

TUALATIN SHERWOOD

RIVER

SIDE

BARNES

KRUSE

HAWTHORNE

PORTLAND

STATE

WEIDLER

WILLAM

ETTE FA

LLS

CARMAN

MARTINLUTHERKING

7TH

CLAY

I205-I5

BRIDGE

DENVER

TACOMA

MCVEY

COUNTRY CLUB

WASHINGTON

LLOYD

CAPITOL

65TH

HWY 30

MARTIN

LUTHER

KINGJR

AMBERWOOD

DURHAM

VAUGHN

ROSS ISLAND

WALKER

I5-I84

BURGARD

ALDER

DENNEY

SELLWOOD

HWY217-I5

I5-HWY217

SUNSET-MURRAY

GERMANTOW

NPHILADELPHIA

BALTIC

MARQUAM

3RD

I5-ALBERTA

MAIN

STEEL

SUNSET

39TH

I5

PACIFIC

CORNELL

BOONESFERRY

HWY217

I405

HWY217

PORTLAND

Page 18

Figure 7

Traffic Volume and Air Quality Analysis

I205

Gr

ity

Fai

Happy Valley

adstone

Maywood Park

Johnson City

I205

MARINE

SR-14

OWELL

FOSTER

122ND

STARK

HWY 212

Y

DIVISION

REDLAND

SUNNYSIDE

AIRPORT

82ND

181ST

I-205

182ND

SPRINGWATER

CLACKAMASRIVER

HWY213

ON

KILLINGSWORTH

I84-I205

I205-SUNNYSIDE

I84-181ST

I205

82ND

82ND

SR-14

I-205

Metroscape Page 19

UGB

City Boundary

Neighborhood Boundary

Traffic Volume0 - 26

27 - 54

55 - 82

83 - 110

111 - 138

Clear

Traffic Volume and Air Quality Index

Sources: DEQ, ODOT

Towards Cleaner Air

How does new and better information affect our decision making? In the case of regional air quality, we are getting a clearer sense for how concentrations of different pol-lutants vary around the region. While it may be premature to think that cars, trucks, and boats will improve the pol-lutants in their exhaust any time soon, in the short term, these variations suggest that communities in our region are disproportionately affected by poor air quality. For example, some individuals may be able to choose where they live or work based on environmental quality. Many others may not be able to choose where they live because their financial or social conditions constrain them to live and work in highly polluted areas. Such examples illus-trate that individual choice is only one part of a larger social landscape that affects communities and individuals. If this new information about air quality does not benefit society equally, then what are other options for improving the quality of life for all metroscape residents?

One option may be to think about the connections be-tween health, planning, and pubic policy. Several urban areas, including our own region, have started to look more closely at ways that public health and planning can work together to achieve more sustainable urban forms. One result is the creation of tools, such as health impact as-sessment, that allow for planning and public health agen-cies to examine how specific decisions will affect human health. To assist in these efforts, researchers are develop-ing techniques to assist decision makers in thinking about human health impacts of planning decisions. By drawing on traffic volume data and PATA, we are able to assess the importance of automobile traffic in creating high concen-trations of toxic air pollutants. Although several factors interact to affect air quality, Figure 7 illustrates the extent to which air quality is affected by freeway traffic volume. Those areas in red, orange, and yellow show a strong con-nection between air quality and traffic, while the areas in green are less linked to automobile traffic. As a result, we can use this simplified analysis to rapidly assess the effect of roadways and traffic intensity on urban air quality.

The air we breathe affects our ability to live. Through-out the early 1900s the fields of public health and plan-ning were working together to improve the conditions of people living in urban areas. Over the past several decades, the two fields have slowly drifted apart in their manage-ment responsibilities. New information such as the PATA results suggest an urgency for linking the two fields in order to achieve a collaborative public policy that can im-prove the quality of life for all residents.

Vivek Shandas is an Assistant Professor in the School of Urban Studies and Planning at Portland State University. Linda George is an Associate Professor in Environmental Science at Portland State Universtiy.