2010 Washington State Ambient Air Monitoring

Network Assessment

Washington State Department of Ecology

Air Quality Program

July 1, 2010

Publication no. 10‐02‐016
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Publication and Contact Information

This report is available on the Department of Ecology’s website at www.ecy.wa.gov/pubs/1002016.pdf .   

For more information contact:

Air Quality Program

PO Box 47600  

Olympia, WA  98504‐7600  

Phone:  (360) 407‐6800  

Washington State Department of Ecology ‐ www.ecy.wa.gov  

Headquarters, Olympia       (360) 407‐6000

Northwest Regional Office, Bellevue    (425) 649‐7000

Southwest Regional Office, Olympia    (360) 407‐6300

Central Regional Office, Yakima      (509) 575‐2490

Eastern Regional Office, Spokane     (509) 329‐3400

To ask about the availability of this document in a format for the visually impaired, call the Air Quality

Program at (360) 407‐6800.  Persons with hearing loss can call 711 for Washington Relay Service.

Persons with a speech disability can call 1‐877‐833‐6341.
Table of Contents

Table of Contents..........................................................................................................................................3

Executive Summary.......................................................................................................................................6

Introduction ..................................................................................................................................................9

Ecology Policy Goal and Objectives ............................................................................................................ 10

Climate, Topography, and Sources............................................................................................................. 13

Air Quality Monitoring in Washington State (Past and Present)................................................................ 17

Carbon monoxide....................................................................................................................................17

Nitrogen Dioxide (NO2) ........................................................................................................................... 18

Ozone ......................................................................................................................................................19

Sulfur Dioxide..........................................................................................................................................21

Particulate Matter (PM).......................................................................................................................... 22

Fine Particulate Matter (PM2.5)........................................................................................................... 23

Lead.........................................................................................................................................................24

Chemical Speciation Network (CSN) ....................................................................................................... 25

Air Toxics Monitoring .............................................................................................................................. 26

Aethalometer Monitoring................................................................................................................... 26

Meteorological........................................................................................................................................26

Temporary Monitors............................................................................................................................... 27

Mobile Monitors.................................................................................................................................27

Portable Monitors............................................................................................................................... 28

Air Monitoring – The Next Five Years......................................................................................................... 29

Proposed and Final Rules Affecting Ambient Monitoring ...................................................................... 29

Ongoing NAAQS Reviews........................................................................................................................ 31

Analyses ......................................................................................................................................................33

Scope of Analysis.....................................................................................................................................33

Fine Particulate Matter (PM2.5)............................................................................................................... 34

Federal Reference Method (FRM) Fine Particulate Matter................................................................ 34

Continuous Fine Particulate Matter (PM2.5) ....................................................................................... 35

Updating PM2.5 Correlations........................................................................................................... 36

Supporting a Single Continuous Onsite Monitor ............................................................................ 36

PM2.5 Non‐FEM TEOM Bias Discussion............................................................................................ 36

Federal Equivalent Method (FEM) Fine Particulate Matter Monitoring ........................................ 37

The Agricultural Burning Network .................................................................................................. 38

PM2.5 Decision Matrix ......................................................................................................................... 39

Scoring.............................................................................................................................................40

Statewide Fine Particulate Matter Design Values .............................................................................. 41

PM2.5 Removal Bias Analysis ............................................................................................................... 44

Ozone ......................................................................................................................................................45

Ozone Decision Matrix........................................................................................................................ 45
Scoring.............................................................................................................................................46

Discussion .......................................................................................................................................46

Statewide Ozone Design Values (Ozone Season) ............................................................................... 47

Impact of lowered ozone NAAQS ....................................................................................................... 49

Ozone Removal Bias Analysis.............................................................................................................. 49

PM10 ........................................................................................................... Error! Bookmark not defined.

Discussion ...........................................................................................................................................51

Colville.............................................................................................................................................52

Burbank/Kennewick........................................................................................................................ 53

Yakima.............................................................................................................................................54

Carbon Monoxide ...................................................................................................................................55

Aerosol Nitrate (NO3

‐

) ............................................................................................................................. 57

Meteorological sites................................................................................................................................58

Findings and Recommendations................................................................................................................. 59

Acronyms, Abbreviations, and Terms......................................................................................................... 61

References ..................................................................................................................................................62

Appendices..................................................................................................................................................64

Appendix A – Continuous Fine Particulate Matter Decision Matrix ....................................................... 65

PM2.5 Decision Matrix Detail ............................................................................................................... 67

Appendix B – Ozone Decision Matrix...................................................................................................... 80

Ozone Decision Matrix Detail ............................................................................................................. 81

Figure 1: Washington State Climatic Zones and Network Monitors .......................................................... 14

Figure 2: Annual Maximum CO 8‐hour Average Concentrations ............................................................... 18

Figure 3: Annual Maximum 8‐hour Average Ozone Concentrations.......................................................... 20

Figure 4: Annual Maximum 1‐hour Average SO2 Concentrations (ppb)..................................................... 21

Figure 5: SO2 Emissions (Tons Per Year) ..................................................................................................... 22

Figure 6: Quarterly Maximum Lead Concentrations .................................................................................. 24

Figure 7: Estimated 2007‐2009 Annual PM2.5 FRM Design Values ............................................................. 35

Figure 8: Tacoma‐L Street Design Value Trend Comparison (TEOM vs. FRM)............................................ 37

Figure 9: Agricultural Burning Network PM2.5, Wind Speed and Acreage Burned Trends .........................39

Figure 10: PM2.5 Station Relative Ranking................................................................................................... 41

Figure 11: Polygons Drawn Around PM2.5 Monitors in and Around Washington State .............................42

Figure 12: 2009 PM2.5 24‐hour Design Values in Washington State........................................................... 44

Figure 13: Woodinville and Enumclaw PM2.5 Site Removal Bias................................................................. 45

Figure 14: Ozone Monitor Relative Ranking ............................................................................................... 47

Figure 15: 2009 Ozone Season 8‐Hour Design Values................................................................................ 48

Figure 16: La Grande Ozone Site Removal Bias .......................................................................................... 50

Figure 17: 24‐hour PM10 Concentrations at Colville (2007‐2009) .............................................................. 52

Figure 18: Colville PM10‐2.5 and Wind Speed (Kettle Falls) .......................................................................... 53
Figure 19: Different Analyses Showing Redundant PM10 Monitors at Burbank and Kennewick................54

Figure 20: Yakima PM10 Concentrations (2000‐2009) ................................................................................ 55

Figure 21: Spokane‐3rd St. S. 8‐hour Daily Maximum CO Concentrations.................................................. 56

Figure 22: Bellevue‐148th NE 8‐hour Daily Maximum CO Concentrations................................................ 57

Figure 23: Wintertime Ammonium Nitrate Fraction in PM2.5..................................................................... 58

Figure 24: Estimated 2009 PM2.5 24‐hour Design Values ........................................................................... 68

Figure 25: PM2.5 24‐hour NAAQS Exceedances (2007‐2009)...................................................................... 69

Figure 26: PM2.5 24‐hour Exceedances of Healthy Air Goal (2007‐2009)................................................... 71

Figure 27: PM2.5 Non‐Good Days (2007‐2009)............................................................................................ 73

Figure 28: Inter‐comparison of Bellevue and Woodinville PM2.5................................................................ 75

Figure 29: Percentage of Individuals Living Below FPL by Zip Code ........................................................... 77

Figure 30: Population Represented by PM2.5 Monitor................................................................................ 79

Figure 31: Estimated 2009 8‐hour Ozone Design Values............................................................................ 81

Figure 32: Ozone Monitor 8‐hour NAAQS Exceedances (2007‐2009)........................................................ 83

Figure 33: Ozone 8‐hour Daily Maximum Concentrations Above .060 ppm (2007‐2009) .........................84

Figure 34: Intercomparison of North Bend and La Grande Ozone ............................................................. 86

Table 1: Washington State Ambient Air Monitoring Network Partners..................................................... 11

Table 2: Number of Monitoring Locations by Monitor Type ...................................................................... 11

Table 3: PM2.5 CSN sites in Washington State............................................................................................. 25

Table 4: Network Meteorological Stations................................................................................................. 27

Table 5: FRM PM2.5 Network Stations and Estimated 2009 Design Values................................................ 34

Table 6: Washington State PM10 Monitoring Network............................................................................... 51

Table 7: 24‐Hour PM10 NAAQS Exceedances and Wind Speeds (2007‐2009)............................................. 51

Table 8: Criteria and ranking of each continuous PM2.5 site....................................................................... 65

Table 9: Ranking criteria for each Ozone monitoring site .......................................................................... 80
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Executive Summary

On October 17, 2006, the U.S. Environmental Protection Agency (EPA) amended its ambient air

monitoring regulations.  This amendment requires states to conduct detailed assessments of their air

monitoring networks every five years.  This document describes the Washington Department of

Ecology’s (Ecology’s) 2010 Washington State Ambient Air Monitoring Network Assessment.  This is the

first assessment of the Washington network under the requirement.   

Purpose of the Assessment  

Ecology’s policy goal is to characterize the health consequences of air pollution in Washington. Ecology

evaluated the effectiveness and efficiency of the Washington State monitoring network in relation to

this goal.  Ecology’s assessment provides decision‐makers with information needed to maximize the

effectiveness of Washington’s ambient air monitoring network.  The assessment also ensures Ecology

and its partners have the information needed to protect human health and the environment for current

and future generations in Washington.

The Washington State Network

Most of Washington’s monitoring network is dedicated to characterizing the two pollutants that have

been shown to pose the greatest risk to public health — Fine Particulate Matter (PM2.5) and ozone.  The

remainder of the network is made up of monitors that measure Larger Particles (PM10), Carbon

Monoxide (CO), Sulfur Dioxide (SO2), Reactive Oxides of Nitrogen (NOY), fine particle chemical

composition, air toxics, and meteorological parameters.

As of December 31, 2009, Ecology and its partners operated a network of 137 monitors at 71 monitoring

stations as part of Washington’s official ambient air monitoring network.  The data from these monitors

serve a variety of needs.  The data are used to:

• Determine if air quality is meeting federal standards

• Provide near‐real‐time air quality information for the protection of public health

• Forecast air quality

• Make daily burn decisions and curtailment calls

• Assist with permitting activities

• Evaluate the effectiveness of air pollution control programs

• Evaluate the effects of air pollution on public health

• Determine air quality trends

• Identify and develop responsible and cost‐effective pollution control strategies

• Evaluate air quality models

Assessment

To relate the value of its monitoring activities to the policy goal, Ecology evaluated the state network on

a pollutant‐by‐pollutant basis.  Ecology generally conducted its assessment in accordance with EPA

guidance, though other analyses and tools were also used.
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Findings

• Overall, the Washington State network is efficient and effective at meeting the monitoring

policy goal.  

• Wholesale network changes are not needed.

• Several specific, targeted changes will improve overall network effectiveness.

• If resource savings are achieved through improvements in network efficiency, they should be

reinvested to address monitoring gaps and high priority future monitoring requirements.

Recommendations

Retain:

Retain nearly all of the existing monitoring network.

Add:

Monitors:

• Install meteorological monitors at Colville in order to improve understanding of PM2.5

levels.

• Move meteorological monitors from Burbank to Kennewick.  

Activities:

• Establish temporary ozone monitor in NE Olympic Peninsula to assess accuracy of

modeled hot spot.

• Encourage research opportunities to further understand elevated nitrate levels in the

Columbia Basin.

• Prioritize and routinely update nephelometer‐PM2.5 correlations as needed in order to

maintain data quality.

• As funding or resources are available, prioritize which new federal monitoring

requirements will be implemented.

Replace:

Replace the PM2.5 Federal Reference Method (FRM) monitors with continuous Federal

Equivalence Method (FEMs) except at Seattle‐Beacon Hill and Tacoma‐ L St which should retain

FRMs in order to meet National Core Monitoring Station (NCore) and collocation requirements.

Remove:

Stations:

• Discontinue carbon monoxide stations in Bellevue and Spokane due to low values.

• Discontinue the continuous PM2.5 station at Woodinville as it is redundant to Bellevue.

• Discontinue the Burbank station and relocate the meteorological monitors to nearby

Kennewick station in order to achieve resource savings.

• Discontinue the ozone station at La Grande as it is redundant to other ozone monitors.

Monitors:

• Discontinue nephelometer and Aethalometer monitoring at Seattle‐Beacon Hill as these

monitors are redundant to other onsite monitors.

• Discontinue the continuous PM2.5 monitor at Enumclaw due to low values.

• Discontinue the PM10 FRM monitor at Yakima due to low values.

Reinvest:
8

Any resource savings achieved by removing existing stations and monitors should be reinvested

in order to address monitoring needs identified in this assessment.
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Introduction

On October 17, 2006, EPA amended its ambient air monitoring regulations.  This amendment requires

states to conduct detailed assessments of their monitoring networks every five years.  The purpose of

the 5‐year assessment is to evaluate the effectiveness and efficiency of monitoring networks in

accordance with stated monitoring objectives and goals.  The first 5‐year assessment is due on July 1,

2010.

To meet the new requirement, Ecology assembled a team to assess and evaluate the Washington State

ambient air quality monitoring network.   The team is comprised of Ecology staff with expertise in the

following areas:   

• Monitoring

• Quality assurance

• Modeling

• Planning

• Smoke management

• Permitting

To the extent that it was practical and helpful, this assessment was conducted in general accordance

with EPA guidance on monitoring network assessments.  However, Ecology deviated from EPA guidance

when more germane or robust analysis methodology was available.

This document is intended to provide decision makers with the information needed to maximize the

effectiveness of Washington’s ambient air monitoring network and serve as a guide for future network

changes.  In addition, the Recommendations section of this document identifies opportunities for overall

improved network efficacy through specific, targeted reductions in monitoring activities as well as the

identification of gaps in monitoring where new stations or monitors are needed.  To the extent possible,

any resource‐savings achieved through these targeted monitoring reductions should be leveraged to

address emergent monitoring needs such as the gaps in coverage identified in this document.  EPA has

identified new monitoring requirements for Nitrogen Oxides (NO2) and may issue additional monitoring

requirements resulting from its proposals dealing with the ozone, SO2, and lead National Ambient Air

Quality Standards (NAAQS).  As funding or resources are available, Ecology will prioritize which new

federal monitoring requirements will be implemented.
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Ecology Policy Goal and Objectives

Ecology evaluated the effectiveness and efficiency of the Washington State monitoring network in

accordance with its policy goal and objectives for ambient air monitoring.  Ecology’s policy goal and its

objectives for air monitoring are as follows:

Goal: Characterize the Health Consequences of Air Pollution in Washington

Monitoring objectives:

• Collect only credible data that has the greatest opportunities to benefit public health

• Increase public understanding of the health effects and costs of air pollution in Washington

• Focus monitoring where the information is critical to protect or assess public health

consequences of air pollution  

• Select continuous method monitoring over filter‐based monitoring methods

• Conserve limited financial and staff resources by using only one continuous method for each

pollutant

• Continue FRM filter‐based monitoring only at sites where projections show that future values

will be higher than 60 percent of the NAAQS or will exceed Air Quality Program health goals

and/or where exceedances have been seen in the last 2 years

The Washington State Network

As of December 31, 2009, the official Washington State ambient air monitoring network consisted of

137 monitors at 71 monitoring stations.  The network is funded, operated, and maintained by a diverse

group of entities with a vested interest in ensuring healthy air for present and future generations of

Washingtonians.  Partners in the Washington State network include Ecology, 7 local air agencies, 7 tribal

nations, EPA, the U.S. Department of the Interior, National Park Service, and the U.S. Department of

Agriculture, Forest Service.  Table 1 shows the Washington network partners.  It should be noted that

there are other entities within Washington State that monitor ambient air quality.  However, for reasons

discussed in detail in the Analyses section of this document, only official Washington State network

monitors were evaluated for the purpose of this assessment.  
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Table 1: Washington State Ambient Air Monitoring Network Partners

As stated previously, public health protection is the primary policy driver for the Washington State

monitoring network.  The network is therefore heavily weighted toward monitoring the pollutants that

are known to pose the greatest threat to public health; PM2.5 and ozone.

Ecology and its partners operate a variety of instruments as part of this network.  The majority of

monitors fall into two categories:

• Continuous monitors – “near‐real‐time” monitors that provide hourly or finer resolution data

• Daily filter‐based samplers – samplers that run for 24‐hours (midnight to midnight) on an EPA‐

defined schedule that varies from:

o Every day (1/1)

o Every third‐day (1/3)

o Every sixth‐day (1/6)

o Every twelfth‐day (1/12)

Table 2 presents a breakdown of the Washington State monitoring network by monitored parameter as

of December 31, 2009:

Table 2: Number of Monitoring Locations by Monitor Type

Monitored Parameter

Number of

Monitoring

Locations Monitor Type [Continuous or Daily (frequencies vary)]

PM2.5 56 56 continuous (8 of which also equipped with daily‐FRM)

Ozone 12 Continuous (3 year‐round and 9 seasonal stations)

Meteorological (PSD‐Quality wind speed, wind

direction, and ambient temperature) 11 Continuous

Chemical Speciation 5 Daily

PM10 5 3 continuous + 2 daily‐FRM

Nephelometer (without PM2.5 correlation) 3 Continuous

CO 2 Continuous

Trace Gas (NOY, CO, SO2) 2 Continuous

Air Toxics 1 Daily
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The data from the Washington State monitoring network serves a variety of needs.  Among other things,

it is used to:

• Determine if air quality is meeting federal standards

• Provide near‐real‐time air quality information for the protection of public health

• Forecast air quality

• Make daily burn decisions and curtailment calls

• Assist with permitting activities

• Evaluate the effectiveness of air pollution control programs

• Evaluate the effects of air pollution on public health

• Determine air quality trends

• Identify and develop responsible and cost‐effective pollution control strategies

• Evaluate air quality models
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Climate, Topography, and Sources

The location of the state of Washington on the windward coast in mid‐latitudes is such that the climatic

elements combine to produce a predominantly marine‐type climate west of the Cascade Mountains,

while east of the Cascades, the climate possesses both continental and marine characteristics.

Considering its northerly latitude, 46° to 49°, Washington’s climate is mild (DRI, 2008).

There are several climatic controls which have a definite influence on the climate, namely; (a) terrain, (b)

the Pacific Ocean, and (c) semi‐permanent high and low pressure regions located over the North Pacific

Ocean.  The effects of these various controls combine to produce entirely different conditions within

short distances.

The Cascade Mountains, 90 to 125 miles inland and 4,000 to 10,000 feet in elevation, are a topographic

and climatic barrier separating the state into eastern and western Washington.  The wet season begins

in October, reaches a peak in winter, and then gradually decreases in the spring. High peaks in the

Cascades are snowcapped throughout the year.  The Columbia River, draining approximately 259,000

square miles in the Pacific Northwest and second only to the Mississippi River in volume flow, enters

near the northeastern corner of the state and flows in a semi‐circular pattern through eastern

Washington.  Before reaching the Pacific Ocean, it drains all of eastern Washington and the western

slope of the Cascade Mountains between Mt. Rainier and the Oregon border.

Reservoirs on the windward slopes of the mountains provide an abundance of water for metropolitan

areas, and hydroelectric projects have been developed along several rivers. Hydroelectricity supplies

about two thirds of Washington’s electricity requirements.

The mountainous areas over the entire state and a major portion of the lowlands west of the Cascades

are covered by timber, ranging from large Douglas fir, spruce, hemlock and cedar, a dense undergrowth

of fern and moss in the rainforest on the Olympic Peninsula, to open stands of Ponderosa pine in

eastern Washington.  Logging and other forest management practices are major activities in these areas.

The Washington State Department of Natural Resources regulates silvicultural burning, while Ecology

and the local air agencies regulate agricultural and other outdoor burning.  

Western Washington: West of the Cascade Mountains, summers are cool and comparatively dry and

winters are mild, wet and cloudy.  Snowfall is light in the lower elevations and heavy in the mountains in

the interior valleys, measurable rainfall is recorded on 150 days each year and on 190 days in the

mountains and along the coast.  During July and August, the driest months, it is not unusual for two to

four weeks to pass with only a few showers; however, in November and December, the wettest months,

precipitation is frequently recorded on over 20 days each month.  

The highest summer and lowest winter temperatures are usually recorded during periods of easterly

winds.  Agriculture is confined to the river valleys and well‐drained areas in the lowlands.  
14

Although the Cascade Range divides the state into two major climatic regions, there are several climatic

areas within each of these regions.   Figure 1 presents a terrain map of Washington overlaid with

climatic zones (based on annual rainfall received) and locations of most network monitors.  

Meteorological sites, CO, trace gas and air toxics sites are not shown, to prevent overcrowding. The

salient zones 1‐5 are described below.

Figure 1: Washington State Climatic Zones and Network Monitors

(1) The West Olympic coastal area receives the full force of storms moving inland from over the ocean,

thus heavy precipitation and winds of gale force occur frequently during the winter season.  The

“rainforest” area along the southwestern and western slopes of the Olympic Mountains receives the

heaviest precipitation in the continental United States, with annual precipitation exceeding 150 inches

along the windward slopes.  

Air pollution sources in this sparsely populated area include a few industries, outdoor/ silvicultural

burning and smoke from woodstoves and other home heating devices in some communities.  

(2) The northeast Olympic‐ San Juan Islands area is shielded from winter storms moving inland from the

ocean by the Olympic Mountains and the extension of the Coastal Range on Vancouver Island.  This belt

1

3

2

4

5
15

in the “rain shadow” of the Olympic Mountains is the driest area in western Washington. The coldest

weather is usually associated with outflows of cold air from the interior of Canada.   

The few air quality concerns in the area are mostly caused by smoke from woodstoves and other home

heating devices in larger communities, outdoor burning and by some industrial facilities.

(3) The Puget Sound Lowlands includes a narrow strip of land along the west side of Puget Sound,

extending southward from the Canadian border to the Centralia area. Variations in the temperature,

length of the growing season, fog, rainfall and snowfall are due to such factors as distance from the

Sound, the rolling terrain, and influx of air from the ocean through the Strait of Juan de Fuca and the

Chehalis River valley.  Most of this area is near the eastern edge of the rain shadow of the Olympic

Mountains. The prevailing wind direction is south or southwest during the wet season and northwest in

summer.   

This is the most densely populated and industrialized area in the state. Vehicular, industrial, domestic,

and marine sources (shipping, ferries) and both vessels and traffic at ports are among the main

anthropogenic sources in the area. Summertime PM2.5 concentrations are usually low due to sufficient

atmospheric mixing, but PM2.5 can be elevated under conditions of clear skies, light wind and a sharp

temperature inversion during the home heating season (October ‐ March) when woodstoves and other

heating devices are typically used. Some sheltered valleys (such as Darrington, Kent and Duwamish) can

experience a buildup of pollutants even when most other areas are moderately ventilated. Some areas

with a high density of woodstove use (South Tacoma, Marysville, Lynnwood, Darrington, and

Bremerton) frequently experience rapid rises of PM2.5 levels in the home heating season, during periods

of poor dispersion. Emissions of ozone precursors in industrial and populated areas can result in

elevated ozone levels downwind on hot summer days characterized by low‐to‐moderate

northerly/easterly winds.  

Eastern Washington: This section of the state is part of the large inland basin between the Cascade and

Rocky Mountains. East of the Cascades, summers are warmer, winters are colder and precipitation is

less than in western Washington. The major agricultural areas are in eastern Washington.  

During most of the year, the prevailing direction of the wind is from the southwest or west.  The

frequency of northeasterly winds is greatest in the fall and winter.  Melting of the snow provides

irrigation water for orchards and other agricultural areas in the Okanogan, Wenatchee, Methow, Yakima

and Columbia River valleys.  Dry land farming practices are generally followed in the small‐grain growing

areas.  

(4) The Okanogan‐Big Bend area includes fruit‐producing valleys along the Okanogan, Methow and

Columbia rivers, grazing land along the southern Okanogan highlands, the Waterville Plateau and part of

the channeled scablands.  Major air pollution sources are outdoor burning (year round, except during

summer fire safety burn bans), agricultural burning (spring and fall burn seasons), orchard heaters,

smudge pots, silvicultural burning and woodstove use. In rare instances, smoke from some burns may

become entrained in evening downslope flow and settle in sheltered valleys (examples include

Wenatchee, Twisp, Winthrop, Omak and Leavenworth). Smoke from any combination of these sources,
16

if coupled with a strong temperature inversion and calm conditions often result in elevated PM2.5

concentrations.  

(5) The Central Basin includes the Ellensburg valley, the central plains area in the Columbia Basin south

from the Waterville Plateau to the Oregon border and east to near the Palouse River.  This is the lowest

and driest section in eastern Washington.   

Wheat and barley are the most widely grown crops in this area, while alfalfa, lentils and potatoes are

also grown on a smaller scale.  Agricultural and outdoor burns are the main PM2.5 sources.  Except for

the Tri Cities, Ellensburg and Walla Walla, smoke from home heating devices and prescribed burning is

not a major concern in this sparsely populated area. Tilling operations, windblown dust and re‐

suspended road dust sometimes give rise to elevated levels of PM10.
17

Air Quality Monitoring in Washington State (Past and Present)

This section describes the evolution of air quality monitoring in Washington over the last several

decades and provides background information that helps to explain the current network.

Carbon monoxide

CO sampling has been conducted in Washington since the 1960s.  Though much of the very oldest data

has not been electronically maintained, Figure 2 depicts the annual maximum 8‐hour averages for

representative areas throughout Washington.  CO presented a major air quality problem throughout the

1970s and 1980s.  In 1976 there were 33 CO monitoring stations, 28 of which measured values that

exceeded the NAAQS (9.0 Parts Per Million (ppm)).  That same year a single site in Seattle measured an

8‐hour maximum value of 24 ppm and recorded 48 days that exceeded the NAAQS.  In Spokane a single

site measured an 8‐hour maximum value of 35 ppm and recorded 118 days that exceeded NAAQS.   

Since 1970, when the federal Clean Air Act first mandated motor vehicle emission controls, tailpipe

emissions of CO, hydrocarbons and oxides of nitrogen have decreased.  Motor vehicle emission

inspection and repair programs also helped reduce tailpipe emissions.  These reductions of CO emissions

resulted in lower CO concentrations throughout the state.  During the 1990s, older vehicles were being

replaced by newer less‐polluting ones.  However, an increase in the number of automobiles and vehicle

miles traveled caused concern that overall CO emissions, and thus ambient concentrations, would

increase.  For this reason, CO saturation studies were conducted in Spokane and throughout the Puget

Sound area to determine if areas with higher CO concentrations were being missed by the monitoring

network.  As a result of these studies, CO stations were moved to locations where maximum CO

concentrations were expected.  Nevertheless, in contrast to concerns regarding CO concentrations,

monitored values continued to decrease.

As air quality improved the CO monitoring network was downsized.  Today, there are only two

remaining CO stations (Bellevue‐148th NE and Spokane‐3rd St. S.).  In 2009, the Bellevue‐148th NE station

measured a maximum 8‐hour value of 2.9 ppm and the Spokane station 3.1 ppm.
18

0

5

10

15

20

25

30

35

40

1972197419761978198019821984198619881990199219941996199820002002200420062008

CO, ppm

Bellevue

Everett 

Lynnwood 44th W

Seattle

Spokane 

Tacoma 

Vancouver

Yakima

CO NAAQS

Figure 2: Annual Maximum CO 8‐hour Average Concentrations

Nitrogen Dioxide  

NO2 sampling in Washington started in 1975.  At first there were several stations in Seattle and one in

Tulalip.  The values from these initial stations were very low (< 3 ppb).  Additional stations were

established in the early 1980s and in 1981 the all‐time maximum annual average value of 40.5 ppb was

recorded at a station in Seattle.    However, the NO2 monitors in Washington State never exceeded the

NAAQS and recorded relatively low concentrations.   Due to this fact and the high cost of operation and

maintenance, NO2 monitoring was discontinued in 1987.  NO2 monitoring was re‐established in 1995 at

the Seattle‐Beacon Hill (then a National Air Monitoring station, NAMS).   

During the 1990s, several NO2 studies were conducted to determine concentrations at potential hot

spots and evaluate downwind photochemistry.  The results from these studies revealed concentrations

well below the NAAQS in effect at the time.

In 2007 the existing NO2 monitor at Seattle‐Beacon Hill was replaced with a high sensitivity sampler

measuring reactive oxides of nitrogen (NOY = Nitric Oxide (NO) + NO2 + other oxidized nitrogen species),

as required by the station’s present classification as a NCore station.  Since Beacon Hill is located in an
19

urban area, there is little time for freshly emitted Nitrogen Oxides (NOx) to react with atmospheric

oxidants and form other oxidized nitrogen species. Consequently, NOY minus NO is a good

approximation of NO2 at this location.  NOY is also monitored at the Cheeka Peak station, which is a rural

background site located in the northwestern‐most corner of the state. As NOx may be oxidized en route

to this site, NOY minus NO represents the upper limit of NO2.  NO2 levels at these two stations are well

below the new NAAQS established on February 9, 2010.

Ozone

Ozone monitoring started in 1972 at a single station in Spokane.  The ozone network was rapidly

expanded to over 10 stations statewide.  Stations in the Puget Sound and the Portland, OR/Vancouver,

WA area violated the old one‐hour average NAAQS of 120 ppb.  As a result, EPA designated the

Portland, OR/Vancouver, WA area nonattainment.  After the 1990 Amendments to the Clean Air Act,

EPA also designated the Puget Sound area nonattainment.  Following successful control strategies and

accompanying reductions in ozone concentrations, EPA designated the Puget Sound area attainment in

1996 and the Portland–Vancouver area to attainment in 1997.

Though ozone has been monitored at over 50 different stations throughout the state, many of these

were exploratory in nature and only operated for a year or two.  On average there have been about 10

to 12 ozone stations operating during the ozone season (May to September).   

In an attempt to better understand the formation and the locations of maximum ozone concentrations,

Ecology has conducted ongoing studies that measure and model ozone and its precursors NO and

Volatile Organic Compounds (VOC).  In 1996 hydrocarbons and carbonyls were sampled at nine locations

throughout western Washington.  In addition, NO were measured continuously at the Beacon Hill,

Enumclaw, and Vancouver stations.  NO were also measured with portable samplers at several stations

in Thurston and Lewis counties.  Ozone was also measured with passive samplers at 20 locations in

major river drainages downwind from the Puget Sound metropolitan area.  That same year Washington

State University and the National Center for Atmospheric Research measured hydrocarbons and ozone

aloft.   

In 1997 EPA revised the ozone NAAQS from a 0.12 ppm 1‐hour maximum to an 8‐hour average

concentration of 0.080 ppm.  In 2008 the 8‐hour average NAAQS was lowered to 0.075 ppm.  

Compliance is based on the 3‐year average of the fourth‐highest daily maximum 8‐hour average ozone

concentrations measured at each monitor.   Washington is currently in attainment for ozone.

Between 2007 and 2009 portable ozone samplers were deployed to verify that the current monitoring

stations represent maximum ozone impacts.   

Figure 3 depicts the annual maximum 8‐hour average ozone concentrations for stations with more than

two years of data and the long‐term linear trend line is based on the annual maximum 8‐hour average

ozone concentrations from ozone monitoring stations in the Enumclaw area.  The trend line is flat.  The

Enumclaw stations have historically recorded the highest values in the ozone network.
20

0

20

40

60

80

100

120

140

1973197519771979198119831985198719891991199319951997199920012003200520072009

Ozone, ppb

Arlington Ashford Nat'l Park 

Belfair Bellingham 

Bothell Carbon River

Cedar River Watershed Cheney Turnbull 

Custer Darrington

Ellensburg Enumclaw

Fall City Fife 

Firwood Getchell

Gig Harbor Graham 

Issaquah Lk Sammamish Kent

LaGrande Pack Forest Lakewood 

Longmire Marblemount Nat'l Park 

McMicken Hts King Co Mount Vernon 

Mt Rainier Jackson Ctr Mt Rainier Longmire 

Neah Bay Cheeka Peak North Bend 

Olympia Pack Forest

Packwood Lake Hwy 12 Port Angeles

Ravensdale Seattle Beacon Hill 

Seattle E Marginal Wy 6770 Sequim 

Spokane Sumner 

Stanwood Tacoma

Tolt River Res Vancouver Blairmount Dr 

Wenatchee White Pass Hwy 12 

Whatcom Co. Wishram Hwy 14 

Woodland Dike Rd Yakima

Yelm NAAQS

Linear (Enumclaw)

Figure 3: Annual Maximum 8‐hour Average Ozone Concentrations
21

Sulfur Dioxide

By the early 1970s there were as many as 28 SO2 monitoring stations located throughout the State.  

Most areas exceeded the State one‐hour standard and several (Port Angeles, Tacoma, and Everett)

occasionally exceeded the federal 3‐hour secondary NAAQS.  Figure 4 depicts the annual maximum one‐

hour SO2 values for each of the historical and current monitoring areas.

Figure 4: Annual Maximum 1‐hour Average SO2 Concentrations (ppb)

Figure 5 depicts the tons per year of SO2 from the emission inventory.  Reductions in the emission

inventory are reflected by the measured ambient SO2 concentrations.  The emissions reductions were

realized as; (a) source control measures were implemented, (b) many of the larger SO2 sources shut‐

down, and (c) during the last decade gasoline and diesel fuel sulfur content was cut by nearly 90%.

As air quality improved and pollution levels dropped well below the NAAQS, SO2 monitoring for

compliance with the federal standards was discontinued.   Currently, there are two trace‐level SO2

monitors in the Washington State network at the Seattle‐Beacon Hill and Cheeka Peak stations.  The

Seattle‐Beacon Hill NCore station measures values representative of the overall region and Cheeka Peak

provides background and long‐range transport data.
22

Figure 5: SO2 Emissions (Tons Per Year)

Particulate Matter  

Particulate Matter (PM) monitoring in the form of gross particle fallout and Total Suspended Particulate

(TSP), PM with a nominal size of 25‐to‐45 μm) started in the 1960s.  PM presented a considerable air

quality problem.  By 1971 the State had over 100 TSP sampling stations.  Several of these exceeded the

primary or the secondary NAAQS for TSP.  The primary NAAQS standards were 75 μg/m3 (annual

average) and 260 μg/m3 (24‐hour average, not to be exceeded more than once a year).  The secondary

standard was 150 μg/m3 (24‐hour average, not to be exceeded more than once a year).  Throughout the

1970s and 1980s the following areas were designated nonattainment for TSP:

• Primary NAAQS:

o Annual Primary NAAQS

 Tacoma Tide Flats

 Seattle Duwamish industrial area (northern portion)

 Spokane

o 24‐hour Primary NAAQS

 Vancouver (small portions of the industrial port area)

• Secondary NAAQS:
23

o Seattle Duwamish (extending approximately 21⁄2 miles south of the primary

nonattainment area)

o Kent

o Renton

o Longview industrial area

o Clarkston

In the early 1980s, scientific research was emphasizing the adverse health effects of smaller particles.  

As a result, Ecology began PM10 sampling at 24 stations across the state in 1985. Many of the new PM10

monitoring stations exceeded the PM10 NAAQS (50 μg/m3 for the annual arithmetic mean) and (150

μg/m3 for the 24‐hour average) when it was promulgated in 1987.  EPA rescinded the TSP NAAQS in

recognition of the new health based PM10 NAAQS, and TSP sampling was phased out by 1996.

Exceedances of the PM10 NAAQS at the time of enactment of the 1990 Amendments to the Clean Air Act

resulted in nonattainment designations for Olympia–Lacey–Tumwater, Seattle, Kent, Tacoma, Yakima,

Spokane, and Wallula.  By 1993 PM10 was being measured at 40 locations.  By 1994 air pollution control

strategies, including programs to limit wood stove use, regulate outdoor burning, and better control

industrial emissions, resulted in only three exceedances of the NAAQS.

Despite this downward trend, occasional elevated 24‐hour PM10 values continue to be measured in the

Colville, Spokane, Tri‐Cities, and Yakima.  Recent elevated values are primarily attributable to windblown

dust natural events.

EPA revoked the annual PM10 standard in 2006 due to a lack of evidence linking PM10 to chronic health

problems but retained the 24‐hour standard to address acute health impacts.  PM10 is still monitored at

Burbank, Colville, Kennewick, Spokane, and Yakima.  See the Analyses section of this document for a

detailed discussion of the present PM10 network and analysis of the data.

Fine Particulate Matter  

In 1997 EPA issued a new PM standard for particles with an aerodynamic diameter of 2.5 microns or less

PM 2.5.  The new PM2.5 NAAQS were based on human population exposure and laboratory studies that

demonstrated the harmful effects of finer particles.  The 1997 standard limited PM2.5 to 65 μg/m3

averaged over 24 hours, and 15 μg/m3 averaged annually.  In 1999 PM2.5 monitoring was implemented

at 30 stations ‐ all of which were eventually determined to be below the 1997 standards.

In 2006 EPA revised the 24‐hour PM2.5 NAAQS to 35 μg/m3

.  This has resulted in one new nonattainment

area for PM2.5 (Wapato Hills‐Puyallup River Valley).  Two additional areas were near the revised 24‐hour

standard (Yakima, Vancouver) but were deemed unclassifiable.  Currently there are 56 PM2.5 monitoring

stations.

As of 12/31/2009 Ecology and its partners operated an extensive PM2.5 monitoring network.  The

network is comprised of 8 FRM and 56 continuous monitors at stations throughout Washington.  The

FRMs are filter‐based instruments that provide a 24‐hour sample while the continuous network provides

hourly data.  The continuous network represents Ecology’s single largest ongoing resource investment
24

for any pollutant and provides near‐real‐time data for a variety of users with a diverse array of data

needs and applications.  A primary driver for the use of the continuous monitors is public health

protection through the use of the near‐real‐time data.

Lead

Lead monitoring began in 1979.  Initially there were six lead monitoring stations in the Seattle/Tacoma

area, and one in Spokane.  Four stations in Seattle exceeded the NAAQS quarterly average of 1.5 μg/m3

.  

Over the years lead was monitored at 16 different locations.  Lead remained a problem in the Seattle

area through the mid‐1980s.  Due to the phase out of leaded gasoline and the regulation of industries

that produced lead, concentrations dropped drastically.  As lead concentrations decreased, the size of

the lead monitoring network was reduced.  By 1996 lead monitoring was being conducted only at one

station in Seattle.  The values from this last station were less than half the NAAQS. Consequently lead

monitoring was discontinued in 1997 (see Figure 6).   

Lead is currently monitored at the Seattle‐Beacon Hill station as part of the National Air Toxics Trends

Station (NATTS) and Chemical Speciation Network (CSN) programs.  However, EPA’s promulgation of a

revised lead NAAQS in 2009 will require a FRM lead monitor at the Seattle‐Beacon Hill Station in

addition to the existing NATTS and CSN lead monitoring.

0

2

4

6

8

10

12

1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998

Lead Concentrations, μg/m3

Bellevue

Medina

Maury Island

Seattle, Portage Bay

Seattle, LDS Church

Seattle, Marshall Scholl 

Seattle, Harbor Is.

Seattle, South Parks

Seattle (98th & Stone)

Seattle Harbor Island Texaco

Sumner

Tacoma, 26th & pearl

Tacoma, Benny's Nursery

Tacoma, 47th & Baltimore

Tacoma, Ruston School

Spokane

Quarterly NAAQS

Figure 6: Quarterly Maximum Lead Concentrations
25

Chemical Speciation Network  

The CSN is part of a national network that analyzes 24‐hour integrated, filter‐based PM2.5 samples for

several metals, Nitrate (NO3

‐

), Sulfate (SO4

2‐

), Elemental Carbon (EC) and Organic Carbon (OC). The main

objectives of this network are to:

• Determine the chemical makeup of PM2.5

• Understand which sources contribute to PM2.5 at each site

• Determine the spatial and temporal differences of PM2.5 composition between geographical

areas

• Provide representative PM2.5 speciation data to support exposure assessments (i.e. determine

health risks)

• Provide data for source apportionment

There are currently five CSN stations in Washington State.  They include one EPA‐designated CSN

monitoring station (Seattle‐Beacon Hill) and four supplemental stations.  Washington State CSN stations

are shown in Table 3.

Table 3: PM2.5 CSN sites in Washington State

Site Estimated 2009 PM2.5 FRM design value, μg/m3 CSN sampling started

Seattle‐Beacon Hill 18.5 February 9, 2000

Tacoma‐ L Street 45.7 January 11, 2006

Yakima‐ 4th Ave 37.2 November 8, 2007

Vancouver‐ 4th Plain Blvd 34.4 June 29, 2008

Marysville‐7th Ave 33.8 April 7, 2009

Seattle‐Beacon Hill operates on an every third‐day (1/3) schedule.  In addition to the filter‐based

sampler, an automated semi‐continuous organic and elemental carbon sampler is also operated at this

station. The four supplemental stations run on an every sixth‐day (1/6) schedule.  

Historical Speciation Stations – Supplemental speciation was previously conducted on a 1/6 schedule at

the following stations:

• Seattle‐Georgetown – From 4/30/2000 to 10/29/2004

• Lake Forest Park‐Town Center – From 10/15/2001 to 12/18/2005

• Seattle‐Maple Leaf Reservoir – From 8/11/2001 to 12/28/2002

• Seattle‐Olive St. – From 1/2/2003 to 9/9/2007

• Seattle‐Duwamish – From 6/1/2002 to 12/26/2007

• Spokane‐Ferry St. – From 1/6/2005 to 1/1/2009

Several source apportionment studies have been conducted with CSN data from historical and current

sites (Wu et al., 2006; Hopke et al., 2006; Naeher et al., 2007; Kim and Hopke, 2008; WA Dept of

Ecology, 2010).
26

Air Toxics Monitoring

As part of the National Air Toxics Monitoring Pilot Program, Ecology received an EPA grant to conduct an

extensive air toxics study in the Seattle area.  Air toxics sampling for VOCs, carbonyls, metals, Polycyclic

Aromatic Hydrocarbons (PAH), and Semi Volatile Organic Compounds (SVOCs) was conducted at six sites

between 2000 and 2002.  The study successfully characterized ambient air toxics concentrations, and

the results were used to evaluate modeling results, and determine health risks in the Seattle area.

After the Pilot Study the Seattle‐Beacon Hill station became a NATTS.  The primary purpose of the NATTS

network is to track trends in ambient air toxics levels to facilitate measuring progress toward emission

and risk reduction goals.  Long term goals of NATTS sampling include assessing the effectiveness of

emission reduction activities and evaluating and subsequently improving air toxics emission inventories

and model performance.  The NATTS program provides for long‐term sampling of VOC, carbonyl, PM10

metals, hexavalent chromium, PAH, and SVOC at the Beacon Hill NATTS.

Air toxics have been sampled at the Seattle‐Beacon Hill station since 1/13/2000.

In 2005, Ecology, in cooperation with the Spokane Regional Clean Air Agency, received a grant and

conducted an Air Toxics Community Assessment in Spokane, Washington.  The study successfully

characterized ambient air toxics concentrations and their spatial and temporal patterns, determined

base‐line air toxics concentrations, evaluated local area modeling results, and determined health risks

from exposure to the sampled air toxics.

Aethalometer Monitoring

Ecology currently operates an Aethalometer at the Seattle‐Beacon Hill station.  This instrument was

once a part of the NATTS network suite of monitors and provides a proximate measure of elemental

carbon concentrations.  However a separate onsite continuous analyzer makes direct measurements of

both elemental and organic carbon.  As the Aethalometer is no longer required for NATTS purposes and

is somewhat duplicative of the continuous elemental carbon monitor, Ecology expects to discontinue

Aethalometer monitoring at Seattle‐Beacon Hill.

There is an additional Aethalometer at the Spokane‐Augusta Ave station that is operated by the Spokane

Region Clean Air Agency.  While there is no collocated continuous elemental and organic carbon

analyzer at the station, Ecology is consulting with the agency to determine whether there is sufficient

interest in the data to warrant continued operation of the Aethalometer.

Meteorological

Ecology and its partners currently operate a network of eleven Prevention of Significant Deterioration

(PSD) ‐ quality meteorological stations equipped with a wind vane and anemometer.  These stations

serve permitting, air quality forecasting and burn management program needs.  They are located as

follows:
27

Table 4: Network Meteorological Stations

Station name Date established

Seattle‐Beacon Hill 1/1/1990

Tacoma‐Tower Dr 9/25/1991

North Bend‐North Bend Way 1/11/2000

Enumclaw‐Mud Mtn. 2/1/2004

Burbank‐Maple St 6/1/2004

Cheeka Peak 7/25/2006

Vancouver‐Blairmont Dr 12/20/2007

Toppenish 6/9/2009

Spokane‐Augusta Ave 7/14/2009*

Oakville 10/16/2009

White Swan 11/10/2009

*Initially operated at Ferry St. ~1 mile away, from 8/1/2001 to 3/24/2009

Temporary Monitors

Temporary monitors can provide a cost‐effective supplement or alternative to more permanent

monitoring stations.  They allow for relatively quick response to emergent air quality issues such as

monitoring smoke from wildfires or monitoring in areas with persistent public air quality complaints.  

They also represent a less‐costly approach to characterizing air quality in air sheds where air quality is

unknown.   

Ecology employs two types of temporary monitors for these purposes:

• Mobile monitors ‐ trailers equipped with nephelometers

• Portable monitors ‐ no shelter (monitors must be transported and housed)

Ecology currently uses these monitors for PM2.5 and ozone monitoring throughout the state.

Mobile Monitors

Ecology has three mobile monitors that are used primarily to characterize air quality in air sheds where

air quality is unknown, but air pollution problems are suspected based on complaints and other

information.  Each mobile monitor consists of a nephelometer housed in a trailer that can be hitched to

a vehicle.  They are therefore relatively quickly and easily deployed and are generally used for short‐

term monitoring.  Although nephelometers do not report absolute PM2.5 concentrations, they do report

Measurements of Light Backscatter (bscat), a measure of light‐scattering by fine particles.  For particles

with similar optical properties, the amount of scattering is proportional to the particle concentration.

Analysis of bscat data from the mobile monitors may therefore be used as a qualitative indicator of

possible PM2.5 problems, and help track day‐to‐day trends.

Among the many areas to which mobile monitors have been deployed, Omak, a rural community in the

Okanogan River valley in north central Washington, consistently recorded high bscat readings over two

successive home heating seasons.  High woodstove use and outdoor burning are the likely causes.  Data
28

collected with the mobile monitor was instrumental in motivating authorities from the Confederated

Tribes of the Colville Reservation, in collaboration with EPA, to establish a permanent PM2.5 monitor

with co‐located meteorological measurements in Omak. These data will help Ecology’s air quality

forecasting and burn management program efforts to protect public health in the area.

Portable Monitors  

Ecology currently has two portable, non‐Federal Reference Method (non‐FRM), Environmentally‐

Protected Beta Attenuation Monitors (EBAMs).  These monitors are used to investigate smoke

complaints, verify modeled hot spots, monitor smoke from wildfires or other fires, and identify

additional monitoring needs throughout the state.   

In addition, Ecology has two portable FEM ozone monitors.  These monitors are used to verify modeled

hot spots, track ozone plumes, verify that the current ozone network is adequate and sited properly,

and better understand ozone transport issues.  
29

Air Monitoring – The Next Five Years

Proposed and Final Rules Affecting Ambient Monitoring

The current monitoring network assessment reviews ambient air quality monitoring in Washington as of

the end of 2009.  Accordingly, the assessment reflects the current focus on particulate matter and

ozone.

EPA is taking or has taken actions that will impact ambient air quality monitoring in Washington―and

the rest of the country―over the next five years.  Completed and proposed regulatory actions are as

follows:

• Proposed revisions to lead ambient air monitoring requirements (U. S. EPA, 2009b)

• Proposed  revisions to the ambient ozone monitoring network design requirements (U. S.

EPA, 2009a)

• Monitoring requirements for the Primary NAAQS  for SO2 (U. S. EPA, 2010c)

• Monitoring requirements for the Primary NAAQS for  NO2 (U. S. EPA, 2010b)

All of these rules, proposed and final, specify a time frame for addressing monitoring requirements in

the annual monitoring network plan and for the deployment of the monitors.  The remainder of this

section provides more information on the requirements with the caveat that proposed monitoring

requirements are not adopted monitoring requirements and EPA can revise them before adoption of

final rules.  The section is organized chronologically by date of the impacted annual monitoring network

plan.

Spring 2011 Update to the 2010 Annual Monitoring Network Plan.  The proposed revisions to the lead

ambient air monitoring requirements require an update to the state’s annual monitoring network plan

six months after the effective date of the final rule.  EPA expects to adopt the revised lead monitoring

requirements in Fall 2010.  Since the annual monitoring network plan is submitted in July, Washington

will need to prepare an update to the 2010 plan in Spring 2011 to address revised lead monitoring

requirements.

The major proposed revisions to lead monitoring are:

• The reduction of the emission threshold for required monitoring of lead sources from 1.0 ton or

more of lead per year to 0.50 ton or more per year.

• Treatment of airports as sources of lead due to the use of lead in general aviation fuel.  The

NAAQS for lead; Final Rule required installation of monitors at sources of lead emitting 1.0 ton

per year or more by January 1, 2010 (U. S. EPA, 2008b).
30

While both the 2002 and 2005 inventories indicated that Washington had two qualifying airports, the

preliminary 2008 NEI indicates four airports at or above the 0.50 ton per year threshold.  The

discrepancy is being investigated.

The proposed rule requires deployment of the monitors one year after the rule is finalized.  Under EPA’s

expected timeline this would be Fall 2011.

July 1, 2011 Annual Monitoring Network Plan.  Under the proposed rules, Washington will be required

to address revised ozone monitoring requirements and monitoring for compliance with the primary

sulfur dioxide NAAQS in the 2011 monitoring network plan.

Ozone:

EPA proposed the following revisions to ozone network design in 2009:

• Monitoring in metropolitan statistical areas without current minimum monitoring

requirements, i.e., those with populations over 50,000 and under 350,000

• Three non‐urban monitors, each of which would address at least one of three following

monitoring goals:

o Monitoring of ozone‐sensitive vegetation and ecosystems

o Monitoring in micropolitan areas (counties with a core city or town and a population

of 10,000 to 49,999) with expected ozone concentrations within 85% of the

standard

o Monitoring in areas affected by transport

• For Washington, revision of the required ozone monitoring season to March through

September from May through September

The proposed rule calls for stations to be operational by January 1, 2012, or the first day of the required

ozone season in 2012.  This is currently May 1, 2012 but would be March 1, 2012 if EPA finalizes the

proposed revision to Washington’s monitoring season.

Ecology had a number of issues with this proposal.  First, the analysis of the state’s ozone network

presented in this assessment indicates good coverage of areas of elevated ozone levels that would not

benefit by placing monitors in smaller metropolitan areas.   Second, the revision to the ozone season is

not justified.  Elevated ozone levels in Washington are highly dependent on temperature and

meteorological conditions and the historical record indicate exceedances, even of a 0.060 ppm standard,

are not expected in March and April.    Third, the proposed revisions to the ozone network are costly

whether considered alone or in concert with other recent and forthcoming NAAQS monitoring

requirements.   

Ecology’s comments on the proposed non‐urban monitors were more specific.  EPA proposed that each

state operate at least 3 monitors that address the following monitoring objectives:  (1) ozone exposure
31

of ozone‐sensitive vegetation and ecosystems, (2) non‐urban areas affected by ozone transport, (3)

smaller population centers (10,000‐50,000) with ozone concentrations at least 85% of the 0.075 ppm

NAAQS.   Ecology could most easily meet the measurement of ozone concentrations in ozone‐sensitive

vegetation and ecosystems.  Non‐urban monitors could also be sited in areas affected by transport if

monitors are allowed in micropolitan areas (the proposal is not clear about this).  It is not possible to

identify a micropolitan area with ozone concentrations near the standard unless monitoring data are

available first because of the small populations of these areas.   

EPA has committed to finalizing the ozone network rule when it completes the reconsideration of the

ozone standard (U.S. EPA, 2010a).  EPA has committed to finalization of the ozone standard

reconsideration by August 31, 2010.   

SO2:

EPA signed a final rule on June 2, 2010 that strengthened the public health protection of the SO2 NAAQS,

especially for children, the elderly, and people with asthma.  The rule establishes a 1‐hour NAAQS of 75

ppb.  EPA is revoking the existing 24‐hour standard of 140 ppb and the existing annual standard of 30

ppb because they do not add additional public health protection to the new 1‐hour standard.

EPA has revised the monitoring requirements for SO2.  The number of required monitors is based on a

population‐weighted index that reflects population and total SOs emissions in a metropolitan area.  The

end result for Washington is the requirement for one monitor in the Seattle‐Tacoma‐Bellevue, WA

Metropolitan Statistical Area (MSA).  The monitor is to be deployed by January 1, 2013.

  

July 1, 2012 Annual Monitoring Network Plan.  The primary NO2 NAAQS adopted in January 2010 calls

for a two‐tier monitoring network structure.  The first tier specifies roadway monitoring.  One monitor is

required in any metropolitan statistical area with a population of or greater than 500,000.  A second

monitor is required if the population is at or exceeds 2,500,000.

The second tier requires area‐wide monitoring in any metropolitan statistical area with 1,000,000 or

more people.

The final rule requires monitors to be deployed by January 1, 2013.

Ongoing National Ambient Air Quality Standards Reviews

Three NAAQS reviews scheduled to be completed in 2011 and 2012 may result in new or revised

ambient monitoring requirements.  

   

• EPA is under court order (Communities for a Better Environment, et al. v. EPA) to propose a

revised CO NAAQS by October 28, 2010 and finalize the standard by May 13, 2011.   

The low ambient levels being measured by the existing CO monitoring network have raised
32

questions about the usefulness of the network for estimating exposure.   Consideration is

being given to the possible use of trace level CO methods for monitoring today’s low

ambient levels and to the possibility of roadway monitoring.

   

• EPA established an expedited timeline for the PM NAAQS review.  EPA plans to propose

revised PM standards in February 2011 and final standards in October 2011.   

EPA’s review focuses on both PM2.5 and Coarse Particulate Matter (PM10‐2.5).  PM10‐related

evidence is being used to provide a context for understanding health and welfare impacts of

fine and coarse particles.

The current review is finding a stronger causal link between PM2.5 and health effects than

the previous standards review in 2006.  EPA’s preliminary conclusion is the available

information clearly calls the adequacy of current PM2.5 standards into question.  It also

provides strong support for considering revisions to the current standards to increase public

health protection.

In previous reviews, EPA has concluded that while protection is warranted against potential

effects associated PM10‐2.5 particles, important uncertainties remain about associations with

mortality and morbidity.  EPA’s preliminary conclusion is that the available evidence could

support either revising the current PM10 standard to increase public health protection

against exposures to PM10‐2.5 or retaining the current PM10 standard depending on the

emphasis placed on different aspects of the evidence and associated uncertainties.

EPA is considering a secondary (or welfare) PM2.5 standard for urban visibility.  EPA has

consulted with the Clean Air Scientific Advisory Committee’s monitoring subcommittee

about measuring light extinction.

• EPA is under court order (Center for Biological Diversity, et al. v. EPA) to propose revised

secondary standards for both NO2 and SO2 by July 12, 2011 and to finalize these standards

by March 20, 2012.   

While primary standards protect public health, secondary standards protect welfare.  The

welfare impacts being examined by EPA are the acidification of lakes, streams, and other

aquatic environments and the nutrient enrichment of terrestrial ecosystems by nitrogen

deposition.  EPA is considering monitoring total reactive NOY and PM2.5 sulfate to judge

compliance.
33

Analyses

Ecology evaluated the Washington monitoring network in accordance with Ecology’s policy goal and

objectives.  The two pollutants of greatest concern for threats to public health in Washington are PM2.5

and ozone.  For this reason, PM2.5 and ozone comprise the majority of monitoring activities in

Washington State and Ecology’s assessment focuses primarily on these pollutants.

In general, Ecology conducted its assessment in accordance with EPA guidance but other analyses and

tools were also used.  Specifically, decision matrices were used to evaluate the PM2.5 and ozone

networks.  Decision matrices are designed to create a single ranking for stations based upon disparate

analyses.  Detailed descriptions of the decision matrix analyses for PM2.5 and ozone are included in the

appendices of this document.  Decision matrices and spatial patterns were constructed only to evaluate

the PM2.5 and ozone networks, as other networks are much smaller and relative importance between

monitors is more readily identifiable.  Ecology also performed removal bias analyses on its PM2.5 and

ozone networks.

It should be noted that the topography, meteorology and emissions in Washington, particularly Western

Washington, are quite heterogeneous as compared to other areas of the country, such as the Midwest.  

For this reason, the guidance and tools provided by EPA for identifying redundancies in monitoring were

not particularly useful for Washington State.  Specifically, cross‐comparing stations as suggested by EPA,

and calculating correlation matrices was of little utility as many stations with high R2 values nevertheless

represented unique air sheds, including those within the same metropolitan statistical areas.

Therefore, Ecology examined a variety of factors for monitors that were believed to be in the same air

shed to determine whether redundant information was being collected.  Ecology looked at how well

trends tracked each other as well as the magnitude of those trends in a variety of ways.  Sites with R2 >

0.7 from the EPA correlation matrices were also examined this way, even though many such site pairs

were clearly located in separate air sheds.

Scope of Analysis

Ecology decided to limit its analysis to the official Washington State network monitors for the following

reasons:

• It is unknown whether non‐network monitors are operated and maintained in accordance with

established Ecology data quality requirements for quality control and quality assurance.

• Ecology has little control over the decision making processes regarding the siting,

establishment, operation, relocation or removal of non‐network monitors.

• While resource‐savings could be achieved by leveraging non‐network monitors (i.e., turning off

Ecology monitors in air sheds where a non‐network monitor provides similar information), non‐

network monitors may be discontinued without input from Ecology and its partners.  This

situation could leave data users without potentially important information.
34

It should be noted that non‐network monitors often provide useful data for users in areas where

Ecology does not monitor.  Some non‐network monitor data were used to inform Ecology’s analysis of

spatial pollution patterns, removal bias analysis, and identification of potential gaps in monitoring.

Fine Particulate Matter  

Washington’s PM2.5 problems are primarily in relation to the 24‐hour NAAQS.  Washington’s PM2.5

pollution episodes are relatively short in duration and are most often associated with wintertime

stagnation events.  Unlike other areas of the country, secondary PM2.5 formation during summertime,

either from smog episodes or SO2 oxidation, does not cause concern. Depending on the area, PM2.5

pollution in Washington comes mainly from smoke associated with home heating devices, and

agricultural field stubble and outdoor (non‐agricultural) burning.  Transportation and other mobile (on‐ 

and off‐road) sources are also contributors but much less than smoke in its various incarnations.  

Because there is a great amount of epidemiologic data associating PM2.5 with adverse health effects,

Ecology has made reducing the health threats associated with PM2.5 a priority and has invested heavily

in PM2.5 monitoring.

In general, PM2.5 values are highest during the home heating season (October through March) and drop

off markedly during the warmer months.  However, high PM2.5 values occasionally occur at other times

of year, particularly east of the Cascade Mountains, during wildfires or agricultural field stubble burning.

Federal Reference Method Fine Particulate Matter

Ecology and its partners currently operate a network of 8 FRM PM2.5 monitors as listed in Table 5 below.  

Table 5 presents estimated design values based on 2007‐2009 monitoring data.

Table 5: FRM PM2.5 Network Stations and Estimated 2009 Design Values

Station Name

Sampling

Frequency

Estimated 2007‐2009

24‐hour Design Value

Tacoma‐L Street 1/3 45.7

Yakima‐4th Ave 1/3 37.3

Marysville‐7th Ave 1/1 33.8

Vancouver‐Fourth Plain Rd 1/1 34.4*

Darrington‐Fir St 1/3 38.1

Spokane‐Augusta Ave (combined with Ferry St) 1/3 27.3

Seattle‐Duwamish 1/3 25.8

Seattle‐Beacon Hill 1/3 18.5

*incomplete data

In 2009, EPA made PM2.5 attainment/nonattainment designations for the 2006 revised 24‐hour

standard.  These designations were based on the 2006‐2008 monitoring data.  The Tacoma‐L Street

monitor violated the 24‐hour standard based on 2006‐2008 data.  As a result, the surrounding area

known as the Wapato Hills‐Puyallup River Valley was designated as being in nonattainment for the 24‐

hour standard in 2009.  It is the only PM2.5 nonattainment area in Washington State.  Two additional
35

areas that were near the 24‐hour standard at the time – Yakima and Vancouver‐ were deemed

unclassifiable for the revised 24‐hour standard on account of incomplete data.   

As can be seen in Table 5, the Washington FRM PM2.5 network consists mainly of monitors that are near

the 24‐hour standard, the exceptions being Seattle‐Beacon Hill and Duwamish, and Spokane‐Augusta

Ave.  The Seattle‐Beacon Hill monitor is located at an NCORE station and is part of the suite of

monitoring required at NCORE stations.  The Spokane‐Augusta Ave (formerly Ferry St.) design value is

very close to 80% of the 24‐hour NAAQS, and could possibly be discontinued in favor of a continuous

FEM Tampered Elemental Oscillating Microbalances (TEOM), after the performance of such a monitor in

Eastern Washington is evaluated.  The Duwamish monitor was discontinued at the end of 2009 in favor

of a continuous FEM TEOM.   

As can be seen in Figure 7, all of Washington’s FRM PM2.5 monitors are in compliance with the annual

PM2.5 NAAQS of 15 μg/m3

.

Figure 7: Estimated 2007‐2009 Annual PM2.5 FRM Design Values

Continuous Fine Particulate Matter  

Ecology and its partners operate an extensive network of 56 continuous PM2.5 monitors statewide.  This

network represents Ecology’s single largest ongoing resource investment for any pollutant and provides

near‐real‐time data for a variety of users with a diverse array of data needs and applications. The
36

Washington State network consists of two types of continuous PM2.5 monitors.  Most of these monitors

are nephelometers that have been correlated with a FRM to produce FRM‐like PM2.5 concentrations, as

per EPA guidance (US EPA, 2002). The remaining continuous PM2.5 monitors are TEOM.  

Updating Fine Particulate Matter Correlations

Ecology relies heavily on its PM2.5‐correlated nephelometers because they are much less costly to

operate than TEOMs and FRMs.  However, aerosol composition can change over time.  In addition, most

of the nephelometer‐FRM correlations were established several years ago.  For these reasons, Ecology

believes it is important to prioritize the updating of its FRM‐ nephelometer correlations as resources

permit, to ensure reliable estimates of PM2.5 concentrations from this large network.

Supporting a Single Continuous Onsite Monitor

Ecology believes it is important to conserve limited financial and staff resources by using only one

continuous method for each pollutant.  There is one continuous PM2.5 monitoring redundancy at the

Seattle‐Beacon Hill station.  Specifically, the PM2.5‐correlated nephelometer is redundant to the

collocated PM2.5 TEOM monitor and should be discontinued.  As of the writing of this document, the

TEOM has been upgraded to FEM status and therefore is the preferred instrument.

PM2.5 Non­Federal Reference Method Tapered Elemental Oscillating Microbalances Bias

Discussion

In performing the analysis of the PM2.5 network, Ecology noted the extent to which the non‐FEM TEOM

underestimated PM2.5 compared to collocated FRM monitors.  Figure 8 presents a comparison of the

estimated design value trends from 2003 through 2009 at Tacoma‐L Street.
37

Figure 8: Tacoma‐L Street Design Value Trend Comparison (TEOM vs. FRM)

The TEOM data at Marysville‐7th Ave and Spokane, Augusta Ave. (formerly Ferry St.) were also biased

low as compared to the collocated FRMs.

As of the writing of this document, nearly all of the non‐FEM TEOMs in the network have either been

replaced with FEM TEOMs, or are scheduled to be replaced in the coming months.  Because the FEM

TEOM has received EPA equivalency, Ecology hopes the low bias issue has been resolved.  However, EPA

did not conduct testing of its FEM TEOMs in the woodsmoke dominated areas of the western US, and it

bears mentioning that aerosol composition may differ somewhat in Washington as compared to the test

environments.  As more data are collected, Ecology plans to track how the FEM TEOMs compare to the

FRMs, particularly during the home‐heating season when PM2.5 levels are generally highest in

Washington.

Federal Equivalent Method Fine Particulate Matter Monitoring

As mentioned above, as of the beginning of 2010, Ecology and its partners have begun the transition

away from FRM PM2.5 monitoring.  It is anticipated that within the 2010 calendar year, nearly all of the

FRM monitors listed in Table 5 above will be replaced with FEM TEOM monitors.  FRM monitoring will

continue at the Seattle‐Beacon Hill and the Tacoma‐L Street stations in order to meet NCore and EPA

collocation requirements, respectively.
38

FEM TEOMs offer the advantage of continuous data that can be used to provide near‐real‐time

information on PM2.5 pollution levels while still allowing for the determination of compliance with the

NAAQS.  In addition, it is expected that following an initial capital investment, the operational costs will

be significantly lower than that of the FRMs.  FRMs have an estimated cost of approximately $100 per

sample.  Any eventual cost savings associated with the implementation of FEMs at the former FRM

stations should be reinvested in order to address other monitoring activities such as filling data gaps

identified in this assessment.

For reasons stated in the PM2.5 Non‐FEM TEOM Bias Discussion section above, Ecology plans to pay close

attention to ensure that the FEM TEOM data compare well to that of the FRM.

The Agricultural Burning Network

As a result of a federal court case settlement, several years ago Ecology implemented a sub‐network of 8

continuous PM2.5 monitors to assist with smoke management associated with wheat stubble burning in

Eastern Washington.  This network deserves special mention because although the concentrations are

relatively low, this sub‐network allows Ecology to keep air quality levels safe from elevated PM2.5

episodes.

Historically, field stubble burning during post‐harvest field clearing was often the cause of elevated

PM2.5 levels in these areas. Following implementation of the agricultural burning monitoring network,

concentrations have been reduced. The monitors ‐ along with information from meteorological

monitors, field reports, burn permit applications and both meteorological and atmospheric dispersion

models – provide data that are used on a daily basis by Ecology to make burn decisions. These monitors

are both a vital resource for the proper implementation of the agricultural burn smoke management

program and for evaluating the performance thereof.

The PM2.5 levels recorded by these monitors are highest during the fall burning season, which typically

runs from late July to October. In addition, the Walla Walla station is also impacted by wintertime smoke

from home heating devices. To ascertain the presence of a trend in PM2.5 levels and the extent to which

such trends were driven by meteorology, we compared the number of days with impaired air quality

(defined as days on which the Washington Air Quality Advisory (WAQA) was anything other than

“Good”, when 24‐hour PM2.5 levels were ≤ 13.4 μg/m3

) from July‐October each year, with the 75th

percentile of the wind speed measured at the nearest available meteorological station. The 75th

percentile wind speed was chosen in an attempt to determine whether higher winds in particular years

helped suppress PM2.5 levels.

Figure 9 shows that in the absence of impacts from wildfires (in 2003 and 2006 Washington had a

multiple wildfires that burned for a long time), PM2.5 levels and corresponding wind speeds between July

and October have remained steady since 2002. This suggests that stronger winds did not consistently

suppress PM2.5 levels in any particular year.  Figure 9 also includes the number of acres authorized for

burning throughout the whole county during the fall burning season. There is no obvious correlation

between impaired air quality and the extent of burning, except perhaps for a period of time in Whitman

County (encompassing Pullman, Rosalia and La Crosse), where most wheat field stubble burning takes
39

place. Further, the number of days of impaired air quality in the region has been has been declining in

the last 3 years.

Ecology strongly feels that these monitors are vital to the continued success of the agricultural burn

smoke management program.  

Figure 9: Agricultural Burning Network PM2.5, Wind Speed and Acreage Burned Trends

Note that the station was located in Starbuck from September 2003‐ March 2009, before being moved

to Dayton

Fine Particulate Matter Decision Matrix

Ecology used a decision matrix to analyze the official PM2.5 monitoring network.  Stations were ranked in

order of value in relation to Ecology’s monitoring policy goal and objectives. Therefore, protection of

public health was emphasized.

The PM2.5 decision matrix should serve as a valuable tool for the purposes of network planning and a

guide for decisions regarding future monitoring network changes.

The Chehalis‐Market St. and White Swan PM2.5 monitors were not included in this assessment as

monitoring began too recently to compile meaningful summary statistics.
40

Scoring

The number of adverse health effects increase as PM2.5 concentrations rise.  Therefore, the decision

matrix was inherently weighted to reflect greater value for monitors that record higher levels of

pollution coupled with population exposure.  This was accomplished by the inclusion of multiple

categories that were driven by PM2.5 concentrations, as well as an estimate of the population

represented by each monitor; a surrogate for exposure and risk.  However, several other categories

encapsulating other factors were also incorporated into the decision matrix.  The categories for the

PM2.5 decision matrix are as follows:

Pollution/Public Health:

• Estimated 2009 design value (24‐hour)

• Number 24‐hour NAAQS exceedances (2007‐2009)

• Number Program Healthy Air Goal exceedances (2007‐2009)

• Percentage of days other than Good air quality

Other Factors:

Whether the monitor:

• Satisfies a forecasting/curtailment need

• Is part of Ecology’s partnership with EPA for monitoring on tribal lands

• Is part of Ecology’s partnership with USFS for monitoring silvicultural burning impacts

• Is used for decisions regarding whether to allow agricultural burning

• Is located at an NCORE/potential NCORE station

• Is the sole monitor in an air shed

• Is in an Environmental Justice area

• Has a long historical record

• Is collocated with other monitors

• Is in a densely populated area

• Is in an area with a rapidly growing population

EPA guidance recommended states analyze pollution trends as part of the network assessment.  Ecology

examined trends from its CO, PM10, PM2.5, and ozone networks.  Clear downward trends were

discernable in the case of CO (see Figures 21 and 22).  However, it is important to note that while

Ecology analyzed the trends for its largest networks, PM2.5 and ozone, upward or downward trends were

not clearly discernable and therefore trends analyses weren’t included in the matrices for PM2.5 and

ozone.

Each category in the matrix represents a separate analysis and constitutes a column in the worksheet.  

Scores for some categories were awarded on a relative‐ranking basis and other categories were all or

nothing meaning, for example, that a “Y” (or yes) constitutes a score of 1, and a blank (or no) is given no

score.  Scores were normalized across the disparate categories such that the maximum score for any

monitor in any column was “1”.  Because the decision matrix was inherently weighted to reflect greater

value for monitors recording higher pollution levels, analyses were not weighted between categories.  

Scores across the categories (i.e., columns in the worksheet matrix) were summed for each station and a
41

final PM2.5 station ranking established.  The highest‐scoring (highest ranked) stations are theoretically of

greatest value for meeting Ecology’s priorities and goals for PM2.5 monitoring.

The complete PM2.5 decision matrix worksheet can be found in Appendix A at the end of this document.   

Figure 10 below shows the relative ranking of PM2.5 monitors within the Ecology network based on the

decision matrix assessment.  Monitors are listed by stations name and are ranked in descending order

according to their relative importance in the Ecology network (i.e., higher score = greater importance in

the network).

Figure 10: PM2.5 Station Relative Ranking

Statewide Fine Particulate Matter Design Values

EPA suggested the use of Voronoi Polygons to determine the area represented by each monitor, as a

means of determining the spatial variability of pollutant concentrations statewide. Polygons are drawn

by splitting the distance between a given site and its nearest neighbor. While this technique may have

some value in relatively flat terrain, Figure 11 illustrates its shortcomings when used in areas of complex

terrain, with no consideration of meteorology and heterogeneity of emissions.  
42

Figure 11: Polygons Drawn Around PM2.5 Monitors in and Around Washington State

The Google terrain map in Figure 11 shows how this technique erroneously considers several monitors

in valleys/ lowlands to be representative of areas well into the high elevations of the Cascades or other

sparsely populated areas. The polygons around the Yakima, Methow Valley and Colville sites are but a

few examples. To address these shortcomings and obtain a reasonable representation of the spatial

distribution of PM2.5, Ecology:

• Calculated current design values from each PM2.5 monitor, using 2007‐2009 data.

FRM data were used instead of continuous PM2.5 data, where available. At sites where 2007‐2009

data were incomplete, the most recent 98th percentile value was used.

• Calculated the median modeled PM2.5 for each 12km x 12km grid cell, over same period.  

Washington State University runs a gridded photochemical atmospheric dispersion model

Community Multi‐Scale Air Quality Model (CMAQ) in predictive mode at a 12km spatial resolution,

every day (http://airpact‐3.wsu.edu). Predicted meteorological fields are available twice daily from

the University of Washington’s WRF model (http://www.atmos.washington.edu/mm5rt). A separate

gridded emissions module incorporates statewide land use patterns, traffic volumes, industrial and

biogenic emissions, all adjusted as appropriate by season, day of week, time of day and predicted

temperature and solar radiation. Ecology maintains several years of archived 24‐hour averages of

modeled PM2.5 concentrations throughout the modeling domain, which encompasses all of

Washington, Oregon and Idaho. Thus with the use of model data, this process is able to account for

the effects of terrain, meteorology, emissions and photochemistry on the spatial variability of PM2.5.  
43

Since the model constantly over‐predicts PM2.5 from wildfires, Ecology used modeled medians rather

than means, for each grid cell. This further served to reduce the impacts of poor model performance

in certain areas, seasons or events, yielding a more robust dataset.

• Performed a spatial interpolation, using the monitor to fix the value, and the monitor/ model

ratio to spatially scale the data.  

We used the Voronoi nearest neighbor and inverse distance squared (1/D2

) weighted averaging for

this part of the analysis. 1/D2 weighting was used instead of 1/D, to limit the radius of influence of a

given monitor, given the complex terrain throughout most of Washington State.  Even though the

dispersion model incorporates the effects of terrain, the spatial interpolation scheme does not

respect such barriers.  

Since the dispersion model serves to spatially scale the monitor data (i.e., is a grid cell higher or

lower than its neighbor), the process assumes that the dispersion model captures the spatial

variation of PM2.5 reasonably well. However the dispersion model is not required to accurately

predict PM2.5 concentrations at each monitor, since the interpolation result is most heavily weighted

by the concentration at the nearest monitor.  

Border monitors from British Columbia, Canada, Oregon, Idaho, and fictitious marine monitors

(assigned estimated background design values of 5 μg/m3

) were used to prevent unreasonable

values at border areas. The relevant algorithms were available for easy use in a separate EPA model

(BenMAP‐ US EPA, 2008).

The outcome of the model‐monitor interpolation, added as a semi‐transparent layer to a terrain map, is

shown in Figure 12. For color‐coding purposes, Ecology used breakpoints associated with the WAQA. It

can be seen that areas of PM2.5 concentrations over 35 μg/m3

, namely Tacoma, Darrington and Yakima,

are confined to the immediate grid cell(s) around the monitors. Upon closer examination, it was seen

that the high value near the Canadian site of Grand Forks is the result of a slight PM2.5 overprediction in

the area. The actual extent of areas experiencing PM2.5 concentrations over 20 μg/m3

, particularly in

eastern Washington, might be somewhat exaggerated owing to the relatively lower monitor density.

Nevertheless this spatial representation is far more realistic than using Voronoi polygons.
44

Figure 12: 2009 PM2.5 24‐hour Design Values in Washington State

Fine Particulate Matter Removal Bias Analysis

Analyses conducted for the decision matrix identified the Woodinville and Enumclaw continuous PM2.5

monitors as providing little additional useful information (see Appendix A). The above mentioned spatial

interpolation using monitors and dispersion modeling data, was rerun after omitting these sites. The

resulting change in the spatial distribution of PM2.5 (i.e. the removal bias, defined as PM2.5 from the

rerun minus PM2.5 in Figure 12) is displayed in Figure 13. A positive removal bias at a particular location

suggests increased PM2.5 levels, after the sites in question are omitted.  

A negative removal bias at the grid cell containing the Woodinville site in Figure 13 suggests that the

monitor there recorded concentrations higher than what could be interpolated from the surrounding

sites alone. Yet, since the Bellevue monitor could be used as a surrogate, the omission of this site does

not result in misleading information. Removal of the Enumclaw PM2.5 monitor appears to cause little

bias at the same grid cell. The remaining impacts are largely confined to the Cascades. These sparsely

populated areas are characterized by low PM2.5 concentrations, and an added uncertainty of a few

μg/m3 is unlikely to affect the PM2.5 pattern significantly.
45

Figure 13: Woodinville and Enumclaw PM2.5 Site Removal Bias

Ozone

Ecology and its partners operate a network of 12 continuous ozone monitors statewide.  This network

provides near‐real‐time data for a variety of users with a diverse array of data needs and applications.

The Washington State ozone network serves a wide variety of needs.  The data are used to determine

compliance with the NAAQS, provide near‐real‐time information on air quality for public health

protection through Ecology’s WAQA and EPA’s Air Quality Index (AQI), forecast air pollution episodes

and make ozone action‐day calls, and determine efficacy of control measures.  Ecology’s ozone network

consists of FEM monitors.

Ozone Decision Matrix

Ecology used a decision matrix to analyze the relative value of its continuous ozone monitoring network.  

Stations were ranked in order of value in accordance with established Ecology monitoring policy goal

and objectives.  Therefore, factors important for public health protection were emphasized.  Other

factors, such as whether the monitor is part of EPA’s NCore strategy, are also important and were

incorporated in the decision matrix.
46

Scoring

The ozone decision matrix was weighted to reflect greater value for monitors that record higher levels

of ozone.  Because all categories were worth the same amount of points, this weighting was

accomplished by the inclusion of three categories that were driven by ozone concentrations.

The categories for the ozone decision matrix are as follows:

Pollution/Public Health:

• Estimated 2009 design value

• Number of 8‐hour NAAQS exceedances (2007‐2009)

• Number of 8‐hour daily maximums above .060 ppm (2007‐2009)

Other Factors:

Whether the monitor:

• Is collocated with other network parameters

• Has a long historical record

• Satisfies a forecasting/Action Day need

• Is located at an NCore/potential NCore station

• Whether the monitor is redundant to other monitors

Each category in the matrix represents a separate analysis and constitutes a separate column in the

worksheet.  Scores for some categories were awarded on a relative‐ranking basis and other categories

were all or nothing meaning, for example, that a “Y” (or yes) constitutes a score of 1, and a blank (or no)

is given no score.  Scores were normalized across the different categories such that the maximum score

for any monitor in any column was “1”.  Because the decision matrix was weighted to reflect greater

value for monitors recording higher pollution levels, analyses were not weighted between categories.  

Scores across the categories (i.e., columns in the worksheet matrix) were summed for each station and a

final ozone station ranking established.  The highest‐scoring (highest ranked) stations are theoretically of

greatest value for meeting Ecology’s priorities and goals for ozone monitoring.

The ozone decision matrix can be found in Appendix B at the end of this document.   

Discussion

In contrast to Ecology’s analysis of its continuous PM2.5 monitoring network, ozone monitors were not

evaluated in terms of the population represented by a given monitor.  Public health protection is a key

policy goal for Ecology and estimates of the population represented by a monitor can serve as a

surrogate for exposure and health risk.  However, there are several factors that complicate these

estimates when it comes to ozone monitoring.  

In contrast to many states elsewhere in the U.S., ozone precursor sources in Washington State are

relatively less uniformly distributed. Ozone concentrations are relatively low in urban areas, because (i)

there are no major ozone‐precursor‐source regions upwind; (ii) precursors have not yet undergone

photochemical reactions during short travel times, and (iii) background ozone is subject to NOx titration.

The highest ozone concentrations in Washington State occur in the relatively sparsely populated

Western foothills of the Cascade Mountains, which lie downwind of the urban areas of the Puget Sound
47

lowlands. High ozone events occur on hot summer days with low to moderate winds with a northerly

component.  As ozone precursors originating in different areas undergo photochemical reactions during

transport, determining relative contributions of each source area is not straightforward.  As such

Ecology did not conduct any analyses relating to air sheds and population (i.e. sole monitor in the air

shed, population represented by each monitor, population growth trends and population living below

poverty level) that were included in the assessment of the continuous PM2.5 monitoring network.

However, Ecology did examine its ozone network for monitor redundancies by conducting trend

analyses of all monitor pairs that were reasonably expected to track each other.  

Figure 14 below shows the relative ranking of the ozone monitors within the Ecology network based on

the decision matrix assessment.  Monitors are listed by stations name and are ranked in descending

order according to their relative importance in the Ecology network (i.e., higher score = greater

importance in the network).

Figure 14: Ozone Monitor Relative Ranking

Statewide Ozone Design Values (Ozone Season)

Ecology followed the general procedures described in the Statewide Fine Particulate Matter Design

Values section, and used some historical monitors, those operated by external entities, and Ecology’s

portable monitors (2B‐Technologies Model 202) to improve the spatial coverage of measured data,
48

primarily in Western Washington. Only data from May 1st through September 30th (i.e., the ozone

season) were used.  

Archives of model data consisted only of 24‐hour ozone means, not daily maximum 8‐hour

concentrations. This could lead to an overestimate of ozone in some areas, as some photochemical

models are known to overestimate nighttime ozone, possibly due to poor handling of nighttime stable

boundary layer and/or underestimating nighttime NOx emissions (Chen et al., 2008; Mahmud, 2005).

However, this artifact would be less of a concern for this exercise in areas of higher monitor density.

Monitors were weighted using inverse‐distance as, unlike PM2.5, ozone is unlikely to be confined to

localized air sheds.

Figure 15: 2009 Ozone Season 8‐Hour Design Values

Figure 15 reveals a hotspot in the northeast corner of the Olympic Mountains, despite several nearby

monitors being available to ground‐truth modeled data.  Upon closer investigation it was seen that the

model consistently predicted a slight increase of ozone in this area, over its surroundings, since 2006.

While the theoretical reasons for ozone accumulation here are understandable (offshore flow damming

up against the Olympics, downwind of the ozone precursor source areas), Ecology intends to verify this
49

phenomenon using portable monitors in the summer of 2010. If the area is found to be a genuine

hotspot, Ecology may establish a permanent ozone monitor in the Brinnon area.

Due to the few monitors available in eastern Washington, it is possible that the slightly elevated

concentrations shown in Figure 15 are driven by the aforementioned model over‐predictions at night.

Portable samplers deployed for short stints have not recorded high ozone levels.  These results highlight

the nighttime over prediction issue. Areas to the south of the state are biased high for the same reasons,

as well as the occurrence of elevated values at a few monitors in the area.

Impact of lowered ozone National Ambient Air Quality Standards

EPA is in the process of considering a lower ozone NAAQS. Figure 15 also shows the areas that risk

exceeding a possible NAAQS of 0.060 ppm (yellow) and 0.070 ppm (orange). However for reasons stated

above, the geographic extent with design values in excess of these proposed NAAQS are probably

exaggerated, especially in areas of low monitor density.  

Ozone Removal Bias Analysis

Analyses conducted for the decision matrix identified the La Grande monitor as being duplicative of the

data provided by the North Bend monitor (see Appendix B).  As such, little information would be

sacrificed by shutting down the La Grande station, as comparable ozone concentrations are expected

either at Enumclaw, North Bend or Yelm on most high ozone days.  A removal bias analysis was

performed according to the procedures described in the section “PM2.5 Removal Bias Analysis” and the

result is presented in Figure 16. While the omission of this site yields a slightly higher estimate of ozone

design values (positive removal bias), it has little impact on the overall spatial pattern. We therefore

recommend removing the La Grande ozone site.
50

Figure 16: La Grande Ozone Site Removal Bias

Particulate Matter

In 1990 there were seven PM10 nonattainment areas in Washington State, all of which are now in

maintenance as concentrations have decreased due in part to successful control strategies.  As a result

of declining values and a greater emphasis on fine particles, Ecology has transitioned away from PM10

monitoring on a wide scale.  While PM10 concentrations have decreased over the years and PM10 is

thought to represent less of a health risk than fine particles, short‐term exposure remains a serious

threat to human health.  For this reason, EPA has maintained the 24‐hour NAAQS of 150 μg/m3 and

Ecology continues to monitor PM10 in a few locations that experience occasionally elevated

concentrations due primarily to windblown episodes.

Ecology and its partners currently operate and maintain five PM10 monitors as part of the Washington

ambient air quality network.  Two of these monitors are filter‐based (manual) FRM PM10 samplers and

three are continuous TEOM instruments.  The manual and continuous method PM10 network primarily

serves to meet PM10 monitoring requirements in maintenance areas [Spokane, Wallula (Burbank) and

Yakima] as well as provide information for public health protection during episodes of windblown dust
51

in the Columbia basin.  All monitors are located in Eastern Washington.  Table 6 presents the monitor

locations, monitor types, and frequency of operation.

Ecology did not use a decision matrix nor conduct any spatial analyses to evaluate its PM10 network

because the network is relatively small.

Table 6: Washington State PM10 Monitoring Network

Station Name Instrument Sampling Frequency

Burbank‐Maple St TEOM Continuous

Colville‐Oak St S TEOM Continuous

Kennewick‐Metaline St TEOM Continuous

Spokane‐Augusta Ave FRM 1/6; collocated 1/6

Yakima‐4th Ave FRM 1/6

It should be noted that in contrast to PM2.5, woodsmoke in Washington does not result in PM10 levels

close to the PM10 NAAQS. With the exception of Colville, all of the 24‐hour PM10 standard exceedances

measured at these stations in the last three years are attributable to high winds and resultant

windblown dust (Table 7).  High winds, a natural event and the primary driver of high PM10

concentrations at most of the stations, occur occasionally in Eastern Washington generating dust storms

during the relatively warm and dry months from April through October.  

Table 7: 24‐Hour PM10 NAAQS Exceedances and Wind Speeds (2007‐2009)

Station Name 24‐hr Conc. μg/m3 Collection Date 24‐hr WS (mph) Max 3‐hr WS (mph)

Kennewick‐Metaline 289 10/4/2009 12.3 18.0

Kennewick‐Metaline 192 4/9/2007 19.2 25.4

Burbank‐Maple St 169 4/9/2007 19.2 25.4

Burbank‐Maple St 168 7/10/2008 9.1 24.2

Spokane‐Ferry St (now Augusta Ave.) 161 8/18/2008 9.2 18.5

Colville‐Oak St S 266 2/19/2008 N/A N/A

Colville‐Oak St S 210 2/20/2008 N/A N/A

Colville‐Oak St S 200 2/21/2008 N/A N/A

Colville‐Oak St S 185 2/22/2008 N/A N/A

Colville‐Oak St S 180 2/14/2008 N/A N/A

Colville‐Oak St S 160 3/5/2008 N/A N/A

Discussion

The PM10 network generally addresses monitoring needs as they relate to Ecology’s goal and objectives,

and therefore, most of it should be retained.  The exceptions (Burbank, Yakima), are discussed in greater

detail below.
52

This section also describes unique monitoring considerations for Colville, which experiences elevated

levels of PM10 that, in contrast to the rest of the network, are unrelated to windblown dust events.

Colville

The Colville continuous PM10 monitor is unique in that it recorded six exceedances of the 24‐hour

NAAQS during the three year period from January 1, 2007 through December 31, 2009.  All of these

exceedances fell within a 3 week window from February 14th through March 5th, 2008.

Colville is a rural community of about 5,000 people (U.S. Census Bureau, 2000) located in Stevens

County in the northeast corner of Washington.  Extended periods of cold weather are common in

Colville and the traction material is applied to city streets to ameliorate icy conditions.  Several years

ago, the City agreed to apply a more dense traction material to its streets and better manage its overall

road traction operations in order to minimize the re‐entrainment of particulate.  As Figure 17 shows,

following the exceedances in early 2008, PM10 levels have been below the 24‐hour NAAQS.   

Figure 17: 24‐hour PM10 Concentrations at Colville (2007‐2009)

Figure 18 shows hourly PM10‐2.5 and wind speed during part of this 3 week period as recorded by the

closest available non‐network wind monitor located in Kettle Falls, a small community about 10 miles

northwest of Colville. It should be noted that during this high PM10 episode, PM2.5 concentrations did not

rise notably.  Therefore the most prevalent fine PM sources in the area (smoke from home heating
53

devices and various types of burning) are unlikely to blame.  Figure 18 shows that PM10‐2.5

concentrations at Colville rise rapidly during the early morning and late afternoon hours on weekdays

(except 18th February, which was the President’s Day holiday), irrespective of wind speeds.  As such, it is

very unlikely that windblown dust is responsible for these PM10 spikes.

After consulting with officials from the City of Colville, it was discovered that the City applied twice the

normal amount of traction material during the winter of 2007‐2008 and did not use the wash truck to

assist with street sweeping, due to very cold temperatures. Therefore, it is likely that the street sweeper

itself was partly responsible for elevated PM10 concentrations during this period.  Excess traction

material could also become re‐suspended in air during commute times (US 395, a major north‐ south

transportation route, passes within a few hundred meters of the monitor).  Ecology has been working

with the City officials to ensure that the real time PM10 data are used in the planning of street sweeping

operations.  It is noteworthy that there have been no wintertime PM10 exceedances since March 2008.

Figure 18: Colville PM10‐2.5 and Wind Speed (Kettle Falls)

Burbank/Kennewick

Two potential duplicate continuous PM10 monitors were identified‐ Kennewick and Burbank. These

monitors are located at stations within the same air shed, are about 7 miles apart, and can likely serve

as surrogates for each other.  Burbank records slightly higher concentrations overall though Kennewick

is sometimes higher during windblown dust events.  Reading left to right (top to bottom) in Figure 19,

the first graphic shows that with a few exceptions, there have been no pronounced differences between

24‐hour concentrations at the two stations, since 2007.  The second graphic is a quantile‐quantile plot
54

with a nearly straight line. This suggests that data at both sites for the past 3 years are distributed

similarly, although Burbank often reads slightly higher concentrations than Kennewick. The third and

fourth graphics show the difference in concentrations (Kennewick minus Burbank) as a function of wind

speeds and Kennewick PM10 concentrations, respectively. With the exception of one event that

impacted Kennewick and not Burbank, they do not appear to deviate on account of wind speeds, nor at

some threshold PM10 concentrations.   

Taken together, data shown in Figure 19 suggest there is reason to believe that the continuous PM10

TEOMs at Kennewick and Burbank consistently track each other quite closely.  Since the lower readings

at Kennewick are too small to be significant for operational purposes, these two TEOMs can be

considered duplicates. As such Ecology believes that the Burbank station could be discontinued with no

loss of important information.

Figure 19: Different Analyses Showing Redundant PM10 Monitors at Burbank and Kennewick

Yakima

The Yakima PM10 FRM monitor has recorded no exceedances of the standard during the period from

January 1, 2000 to December 31, 2009 and the maximum 24‐hour concentration for the same period

was 105 μg/m3

.  As can clearly be seen in Figure 20, PM10 levels are well below the NAAQS in Yakima.  

For this reason, Ecology recommends discontinuing PM10 monitoring in Yakima.
55

Figure 20: Yakima PM10 Concentrations (2000‐2009)

Carbon Monoxide

As of December 31, 2009, Ecology operated two CO monitors at the Bellevue‐148th NE and Spokane‐3rd

St. S. stations as part of the Washington ambient air quality network.  As a result of control strategies

and the gradual replacement of older vehicles with less‐polluting ones, CO pollution levels have fallen

dramatically in Washington State over the last two decades and are now far below the NAAQS.  In

addition, CO levels are expected to continue to fall as new vehicles being sold in Washington meet some

of the strictest emission standards in the U.S.

For these reasons, Ecology and its partners have divested of CO monitoring and will continue to do so in

favor of other emergent monitoring gaps and needs.   

Figures 21 and 22 below show these monitors are well below the NAAQS and the overall trends are

downward.
56

Figure 21: Spokane‐3rd St. S. 8‐hour Daily Maximum CO Concentrations
57

Figure 22: Bellevue‐148th NE 8‐hour Daily Maximum CO Concentrations

Aerosol Nitrate  

The daily air quality forecast model (AIRPACT‐ http://airpact‐3.wsu.edu) has often predicted high

aerosol nitrate fractions in PM2.5, particularly during wintertime in the Columbia Basin.  To ground truth

this with the limited monitoring data available, Ecology conducted the same spatial analysis as for PM2.5

and ozone (Figures 12 and 15 respectively), using:  

1. Aerosol nitrate and PM2.5 measured by speciation samplers as well as monitors from the Interagency

Monitoring of Protected Visual Environments (IMPROVE) network. Since measurements are made

mostly on a 1‐in‐6 day schedule, 2006‐2009 data plus 2 historical CSN and 1 historical IMPROVE

monitors were used. Only wintertime data were considered.

2. AIRPACT modeled NO3

‐

/PM2.5 ratio with 1/D2 spatial interpolation.

Figure 23 presents the spatial pattern of wintertime nitrate fraction in PM2.5.  All particulate nitrate is

assumed to be present in the form of Ammonium Nitrate (NH4NO3), most of which is formed as

secondary aerosol during the winter when the appropriate photochemical reactions are favored.  High

NO3

‐

/PM2.5 recorded at Yakima (in spite of high PM2.5 concentrations) and at the east end of the

Columbia River Gorge (moderate PM2.5 levels) provide some evidence to suggest the hotspot in the
58

Columbia Basin is not a model artifact.  Ecology encourages more detailed study to further understand

secondary nitrate and its precursors elsewhere in the Columbia Basin in order to verify the model.

Figure 23: Wintertime Ammonium Nitrate Fraction in PM2.5

Meteorological sites

Data from all eleven meteorological sites are routinely used and their continued operation is strongly

recommended. There is also an ongoing need for meteorological data in Colville for air quality

forecasting and data analysis purposes. There are no representative meteorological monitors in the

area, even outside Ecology’s official network. Though windspeeds from Kettle Falls were used in the

“PM10” section above (see Figure 18), it is uncertain if winds impacting Kettle Falls (mostly flowing along

the Columbia River valley) routinely penetrate into the Colville valley and assist with dispersion. The

establishment of a meteorological tower at the Colville Station is therefore a necessity.

It has been shown in Figure 19 that the PM10 monitor at Burbank can be eliminated, as the Kennewick

monitor appears to be a viable surrogate. The Burbank site also hosts a meteorological tower, while the

Kennewick site does not. Thus the process of consolidating the PM10 monitors at these two sites
59

provides an opportunity to relocate the meteorological tower to Kennewick. No loss of meteorological

information is expected with this move.  

Findings and Recommendations

Overall, the Washington State ambient air monitoring network is efficient and effective at meeting the

monitoring policy goal and objectives.  Therefore, wholesale network changes are not necessary.  

However, several specific, targeted changes will improve overall network effectiveness.

If resource savings are achieved through improvements in network efficiency, they should be reinvested

to address monitoring gaps and high priority future monitoring requirements:

• CO:

1. Discontinue Bellevue‐148th NE station – The data from this monitor is well below the

NAAQS, is of little value, and resources could best be used for monitoring elsewhere.

2. Discontinue Spokane‐3rd St. S. station – The data from this monitor is well below the

NAAQS, is of little value, and resources could best be used for monitoring elsewhere.

• PM10:

1. Discontinue Yakima‐4th Ave. monitor – The data from this monitor is well below the

NAAQS, is of little value, and resources could best be used for monitoring elsewhere.

2. Discontinue Burbank‐Maple St. station – Analysis shows that the nearby Kennewick

PM10 TEOM can be used to provide data generally representative of Burbank.  In

addition, the Kennewick monitor is located in a population center.  Resources saved by

discontinuing the Burbank station could best be used for monitoring elsewhere.

• PM2.5:

1. Complete the replacement of all FRM monitors with FEMs over the next year with the

following exceptions:

• Retain an FRM at Tacoma‐L Street ‐ needed for EPA collocation

requirements.

• Retain an FRM at Seattle‐Beacon Hill ‐ needed for NCore requirements.

2. Discontinue Woodinville station – The data from this continuous PM2.5 monitor are

somewhat duplicative of the Bellevue monitor, and are well below the NAAQS.

Resources could best be used for monitoring elsewhere.

3. Discontinue the Enumclaw PM2.5 monitor – PM2.5 concentrations are very low at this

site, as it is far away from most sources. However the onsite ozone and meteorological

measurements should be retained.  

4. Discontinue nephelometer at Seattle‐Beacon Hill – This is a duplicative monitor.  In

addition, the existing PM2.5 TEOM at this station has been upgraded to an FEM TEOM.

5. Encourage research opportunities to investigate the buildup of secondary nitrate in

the Columbia Basin – Model runs have consistently identified a particulate nitrate hot

spot in this area, verified to some extent by the Yakima and Columbia River Gorge

speciation monitors.

• Ozone:

1. Discontinue La Grande‐Pack Forest station – Although this monitor has the 2nd‐highest

2009 design value, analysis of the monitoring data show that this station’s trends are

represented mostly by the North Bend monitor.  Air flow in the area is such that ozone

rich plumes are usually detected at one of the other monitors in the region, in similar

concentrations as La Grande.   
60

2. Investigate hot spot in northeast Olympic Peninsula – Model runs have consistently

identified a hot spot in this area. Ecology first intends to verify this phenomenon with

the use of a portable ozone monitor in the summer of 2010.

• Meteorological:

1. Install meteorological parameters wind speed, wind direction, and ambient

temperature at existing Colville station – Meteorological data are needed in this area

to assist with air quality forecasting.  

2. Move Burbank‐Maple St. monitors to existing Kennewick‐Metaline station – Moving

the Burbank meteorological monitors at the Kennewick station could result in the

discontinuance of the Burbank station completely and result in considerable resource

savings.

• Other:

1. Discontinue Aethalometer monitoring at Seattle‐Beacon Hill – This instrument is no

longer required as part of the NATTS monitoring and is somewhat duplicative of the

preferred continuous elemental and organic carbon sampler onsite.

2. Verify nephelometer PM2.5 correlations – Verification of correlations is necessary to

ensure accurate estimations of PM2.5 concentrations and provide reliable public health

information from continuous PM2.5 network.

3. Work with partner agencies to collect data aimed at understanding secondary nitrate

and its precursors in the Columbia Basin.

• Wherever practical, resource‐savings obtained from discontinuing monitors/stations should

be reinvested in order to address the monitoring data gaps described above.

• As funding or resources are available, prioritize which new federal monitoring requirements

will be implemented.  Forthcoming requirements include those associated with the EPA rule

revision for NO2and potential new requirements for ozone, SO2, lead, and other criteria

pollutants that EPA is reviewing over the next 5 years.
61

Acronyms, Abbreviations, and Terms

AQI US Environmental Protection Agency’s Air Quality Index

bscat Measurement of Light Backscatter

CMAQ Community Multi‐Scale Air Quality model

CO Carbon Monoxide

CSN Chemical Speciation Network

EBAM Environmental Beta Attenuation Monitor

EC Elemental carbon

Ecology Washington State Department of Ecology

EPA Environmental Protection Agency

FEM Federal Equivalent Method

FRM Federal Reference Method

IMPROVE Interagency Monitoring of Protected Visual Environments

MSA Metropolitan Statistical Area

NAAQS National Ambient Air Quality Standard(s)

NATTS National Air Toxics Trends Station

NCore National Core Monitoring

NH4NO3 Ammonium Nitrate

NO Nitric Oxide

NO2 Nitrogen dioxides

NO3

‐ Nitrate ion

NOx Nitrogen oxides

NOY Reactive oxides of nitrogen

non‐FRM Non‐Federal Reference Method

OC Organic carbon

PAH Polycyclic Aromatic Hydrocarbons

PM Particulate matter

PM2.5 Fine Particles or particulate matter with an aerodynamic diameter of 2.5

microns or less

PM10‐2.5 Coarse particles or particulate matter with an aerodynamic diameter between

10 and 2.5 microns

PM10 Particulate matter with an aerodynamic diameter of 10 microns or more

ppm Parts per million

PSD Prevention of Significant Deterioration

SO2 Sulfur Dioxide

SO4

2‐ Sulfate ion

TEOM Tapered Elemental Oscillating Microbalances  

TSP Total Suspended Particulate

VOC Volatile organic compound

WAQA Washington Air Quality Advisory  
62

References

Center for Biological Diversity, et al. v. EPA, 1:05‐cv‐01814‐LFO (U. S. Dist. Ct., DC 2007).

Chen, J., J. Vaughan, J. Avise, S. O'Neill, and B. Lamb (2008). Enhancement and evaluation of the

AIRPACT ozone and PM2.5 forecast system for the Pacific Northwest. Journal of Geophysical Research,

113, D14305, doi:10.1029/2007JD009554.

Communities for a Better Environment et al. v. EPA, 07‐CV‐03678 JSW (U. S. Dist Ct. , N. Dist Ca., San

Francisco Div. 2008).

Desert Research Institute (DRI), 2010. "Climate of Washington".

http://www.wrcc.dri.edu/narratives/WASHINGTON.htm (Accessed 5/19/2010)

Grayskies, 2009. Pacific Northwest Weather data, available at http://www‐

k12.atmos.washington.edu/k12/grayskies/nw_weather.html (Accessed 5/19/2010)

Hopke et al., (2006). Analyses of PM‐Related Measurements for the Impacts of Ships. Available at

http://www.arb.ca.gov/research/seca/hopkefr.pdf (Accessed 5/19/2010)

Kim, E and Hopke, PK, (2008). Source characterization of ambient fine particles at multiple sites in the

Seattle area. Atmospheric Environment, 42(24), 6047‐6056.

Mahmud, A., 2005. “Evaluation of the Airpact2 air quality forecast system for the Pacific Northwest”. MS

Thesis, Washington State University. Available at

http://www.dissertations.wsu.edu/Thesis/Fall2005/a_mahmud_091605.pdf (Accessed 5/19/2010)

Naeher et al., (2007). Woodsmoke Health Effects: A Review. Inhalation Toxicology, 19 (1), 67 ‐ 106.

PSCAA, 2009. Air Graphing tool, available at http://airgraphing.pscleanair.org (Accessed 5/19/2010)

R, 2009. "R Foundation for Statistical Computing, v2.10.1". Available for free download at http://www.r‐

project.org (Accessed 5/19/2010)  

US Census Bureau.  American Fact Finder. 2000 Census information by zip code.  Available at  

http://factfinder.census.gov/home/saff/main.html?_lang=en (Accessed 5/19/2010)

US EPA, 2002. “Data Quality Objectives (DQOs) for Relating Federal Reference Method (FRM) and

Continuous PM2.5 Measurements to Report an Air Quality Index (AQI). Available at

http://www.epa.gov/ttnamti1/files/ambient/monitorstrat/aqidqor2.pdf (Accessed 5/19/2010)

US EPA, 2008a. "Environmental Benefits Analysis and Mapping Program (BenMAP) v. 3.0.14", available

for free download at http://www.epa.gov/air/benmap (Accessed 5/19/2010)

US EPA, 2008b.  National Ambient Air Quality Standards for Lead; Final Rule.  73 Federal Register 66964

(November 12, 2008).
63

US EPA, 2009a.  Proposed Ambient Ozone Monitoring Regulations: Revision to Network Design

Requirements.  74 Federal Register 34525 (July 16, 2009).

US EPA, 2009b.  Proposed Revisions to Lead Ambient Air Monitoring Requirements.  74 Federal Register

69050 (December 30, 2009).

US EPA, 2010a.  National Ambient Air Quality Standards for Ozone; Proposed  

Rule.  75 Federal Register 2938 (January 19, 2010).

US EPA, 2010b.  Monitoring requirements in the Primary National Ambient Air Quality Standards for  

Nitrogen Dioxide; Final Rule adopted in 2010.  75 Federal Register 6474 (January 22, 2010).

US EPA, 2010c.  Monitoring requirements in Primary National Ambient Air Quality Standard for Sulfur

Dioxide. (signed June 2, 2010).

WA Dept of Ecology, 2010. Sources of Fine Particles in the Wapato Hills‐Puyallup River Valley PM2.5

Nonattainment Area. Available at http://www.ecy.wa.gov/pubs/1002009.pdf (Accessed 5/19/2010)

Washington State Office of Financial Management.  2009 population estimates.  Available at

http://www.ofm.wa.gov/pop/april1/default.asp (Accessed 5/19/2010)

Wu et al., (2006). Source Apportionment of Seattle and Portland Air Toxics and PM2.5 Data.  Available at

http://www.epa.gov/ttnamti1/files/ambient/airtox/rgirept.pdf (Accessed 5/19/2010)
64

Appendices
65

Appendix A – Continuous Fine Particulate Matter Decision Matrix

Table 8: Criteria and ranking of each continuous PM2.5 site

Site Name Network Parameter 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

530530029 Tacoma- L Street FRM 1.00 1.00 0.80 0.68 1.00 1.00 0.20 0.92 0.38 0.70 0.04 7.71

530330057 Seattle-Duwamish FRM 0.56 0.06 0.39 0.53 1.00 1.00 1.00 1.00 0.50 0.63 0.05 6.71

530770009 Yakima-4th Ave FRM 0.81 0.64 0.86 0.81 1.00 1.00 0.28 0.53 0.25 0.14 0.13 6.46

530110013 Vancouver-Fourth Plain Rd FRM 0.75 0.40 0.61 0.59 1.00 1.00 0.13 0.94 0.13 0.53 0.10 6.17

530630021 Spokane-Augusta Ave FRM 0.60 0.00 0.52 0.71 1.00 1.00 0.32 1.00 0.56 0.33 0.04 6.08

530470009 Twisp-Glover St NPM25 0.53 0.00 0.72 1.00 1.00 1.00 1.00 0.24 0.48 0.06 0.00 0.04 6.08

530611007 Marysville-7th Ave FRM 0.74 0.36 0.61 0.57 1.00 1.00 0.07 1.00 0.13 0.17 0.35 5.99

530770015 Toppenish NPM25 0.51 0.00 0.36 0.65 1.00 1.00 1.00 0.43 0.37 0.25 0.05 0.00 5.63

530670013 Lacey-College St NPM25 0.68 0.24 0.48 0.59 1.00 1.00 0.13 0.93 0.06 0.16 0.18 5.46

530330080 Seattle-Beacon Hill FRM 0.40 0.00 0.11 0.31 1.00 1.00 0.22 0.70 1.00 0.63 0.05 5.44

530710005 Walla Walla-12th St NPM25 0.48 0.00 0.29 0.42 1.00 1.00 1.00 0.23 0.70 0.06 0.06 0.05 5.29

530332004 Kent-Central & James TPM25 0.52 0.04 0.38 0.57 1.00 1.00 0.20 1.00 0.06 0.38 0.08 5.23

530070010 Leavenworth-Evans St NPM25 0.49 0.00 0.30 0.59 1.00 1.00 1.00 0.10 0.42 0.06 0.01 0.08 5.06

530610005 Lynnwood-212th NPM25 0.51 0.06 0.30 0.39 1.00 1.00 0.12 0.95 0.06 0.61 0.04 5.04

530070006 Wenatchee-Alaska Way NPM25 0.60 0.02 0.61 0.80 1.00 1.00 0.20 0.52 0.06 0.16 0.08 5.04

530650004 Colville-Oak St S NPM25 0.53 0.06 0.49 0.89 1.00 1.00 0.20 0.70 0.13 0.02 0.01 5.01

530331011 Seattle-South Park NPM25 0.53 0.04 0.36 0.42 1.00 1.00 0.22 0.68 0.06 0.63 0.05 4.98

530610020 Darrington-Fir St FRM 0.83 0.32 0.48 0.48 1.00 1.00 0.15 0.32 0.13 0.00 0.23 4.94

530330024 Lake Forest Park-Town Center TPM25 0.44 0.02 0.21 0.32 1.00 1.00 0.09 1.00 0.06 0.61 0.00 4.76

530470010 Winthrop-Chewuch Rd NPM25 0.39 0.00 0.10 0.47 1.00 1.00 1.00 0.13 0.38 0.06 0.00 0.16 4.70

530530031 Tacoma-Alexander Ave NPM25 0.58 0.12 0.45 0.46 1.00 0.48 0.94 0.19 0.41 0.04 4.66

530090009 Port Angeles-W 14th St NPM25 0.46 0.04 0.21 0.49 1.00 1.00 0.17 0.70 0.06 0.05 0.03 4.22

530351005 Meadowdale-Blackbird Dr NPM25 0.57 0.10 0.39 0.46 1.00 1.00 0.09 0.25 0.06 0.19 0.00 4.13

530030004 Clarkston-13th St NPM25 0.55 0.02 0.45 0.57 1.00 1.00 0.22 0.17 0.06 0.00 0.00 4.06

530370002 Ellensburg-Ruby St NPM25 0.43 0.04 0.17 0.39 1.00 1.00 0.33 0.48 0.06 0.06 0.08 4.05

530450004 Shelton-Mt View Dr NPM25 0.44 0.04 0.18 0.30 1.00 1.00 0.19 0.68 0.06 0.05 0.04 3.99

530150015 Longview-30th Ave NPM25 0.40 0.00 0.12 0.26 1.00 1.00 0.21 0.67 0.06 0.14 0.03 3.90

530730015 Bellingham-Yew St NPM25 0.37 0.00 0.06 0.23 1.00 1.00 0.15 0.70 0.06 0.19 0.10 3.87

530531018 Puyallup-128th St NPM25 0.58 0.14 0.46 0.49 1.00 0.09 0.68 0.06 0.23 0.12 3.87

530330048 Seattle-Olive St NPM25 0.36 0.00 0.08 0.19 1.00 0.35 0.67 0.06 1.00 0.05 3.77

530251002 Moses Lake-Balsam St NPM25 0.36 0.00 0.03 0.24 1.00 1.00 0.23 0.59 0.06 0.02 0.19 3.72

530272002 Aberdeen-Division St NPM25 0.36 0.00 0.04 0.22 1.00 1.00 0.27 0.70 0.06 0.06 0.00 3.71

530050002 Kennewick-Metaline NPM25 0.44 0.00 0.19 0.32 1.00 0.23 1.00 0.13 0.17 0.16 3.64

530630047 Spokane-Monroe St NPM25 0.39 0.00 0.21 0.49 1.00 0.18 0.90 0.06 0.33 0.04 3.61

530210002 Mesa-Pepiot Way NPM25 0.34 0.00 0.01 0.18 1.00 1.00 0.26 0.67 0.06 0.00 0.05 3.59

530010003 Ritzville-Alder St NPM25 0.31 0.00 0.01 0.14 1.00 1.00 0.18 0.70 0.06 0.00 0.00 3.42

530750003 Pullman-Dexter SE NPM25 0.28 0.00 0.01 0.06 1.00 1.00 0.15 0.70 0.06 0.04 0.08 3.38

530270011 Taholah NPM25 0.24 0.00 0.03 0.03 1.00 1.00 0.47 0.55 0.06 0.00 0.00 3.38

530270008 Oakville NPM25 0.37 0.00 0.06 0.22 1.00 1.00 0.25 0.29 0.06 0.02 0.04 3.32

530650002 Wellpinit NPM25 0.31 0.00 0.03 0.13 1.00 1.00 0.45 0.30 0.06 0.00 0.00 3.28

530570015 Mt Vernon-S Second St NPM25 0.26 0.00 0.00 0.03 1.00 1.00 0.21 0.42 0.06 0.13 0.12 3.24

530090013 Cheeka Peak NPM25 0.15 0.00 0.00 0.00 1.00 1.00 0.34 0.56 0.00 0.00 3.05

530090014 Neah Bay NPM25 0.25 0.00 0.00 0.02 1.00 1.00 0.45 0.20 0.06 0.00 0.00 2.99

530510007 Usk NPM25 0.23 0.00 0.01 0.03 1.00 1.00 0.28 0.29 0.06 0.00 0.00 2.90

530310003 Port Townsend-San Juan Ave NPM25 0.40 0.00 0.11 0.26 1.00 0.16 0.70 0.06 0.04 0.05 2.79

530330017 North Bend-North Bend Way NPM25 0.29 0.00 0.01 0.08 1.00 0.06 0.98 0.31 0.02 0.00 2.76

530530022 Puyallup-66th NPM25 0.46 0.00 0.12 0.41 1.00 0.09 0.19 0.06 0.26 0.12 2.71

530130002 Dayton-W Main St NPM25 0.27 0.00 0.00 0.03 1.00 1.00 0.18 0.08 0.06 0.01 0.02 2.65

530110022 Yacolt-Yacolt Rd NPM25 0.46 0.02 0.09 0.22 1.00 0.12 0.24 0.06 0.02 0.28 2.51

530750006 Rosalia-Josephine St NPM25 0.26 0.00 0.00 0.03 1.00 0.19 0.70 0.06 0.00 0.00 2.25

530750005 LaCrosse-Hill St NPM25 0.27 0.00 0.01 0.05 1.00 0.12 0.70 0.06 0.00 0.00 2.21

530330023 Enumclaw-Mud Mtn. NPM25 0.19 0.00 0.00 0.01 1.00 0.49 0.31 0.01 0.02 2.04

530330037 Bellevue-Bellevue Way NPM25 0.31 0.00 0.03 0.13 0.07 0.67 0.06 0.45 0.07 1.80

530330028 Woodinville NPM25 0.34 0.00 0.01 0.12 0.04 0.17 0.06 0.37 0.06 1.18
66

Ranking Criteria

1. Estimated 2009 24‐hour Design value (normalized category)

2. 24‐hour NAAQS Exceedances (2007‐2009) (normalized category)

3. Program Healthy Air Goal Exceedances (2007‐2009) (normalized category)

4. Percentage of Days Other Than Good Air Quality (2007‐2009) (normalized category)

5. Forecasting/Curtailment Need? (“Y” or blank where “Y” =1)

6. Tribal Station? (“Y” or blank where “Y” =1)

7. USFS Station? (“Y” or blank where “Y” =1)

8. Agricultural‐Burning Network Station? (“Y” or blank where “Y” =1)

9. NCORE/Potential NCORE Station? (“Y” or blank where “Y” =1)

10. Sole Monitor Per Air shed

11. Percentage of Individuals Living Below Federal Poverty Level (normalized category)

12. Historical Record Length (normalized category)

13. Number of Collocated Parameters (normalized category)

14. Population Represented by Monitor (normalized category)

15. Population Trend (normalized category)

16. Total Score
67

PM2.5 Decision Matrix Detail

This section describes the analyses that were conducted on the PM2.5 monitoring network and were subsequently

incorporated into the decision matrix to determine the final ranking in Table 8 above.

1. Estimated 2009 24‐hour Design value

Ecology estimated 2009 design values (3‐year average of the 98th percentiles from the years 2007, 2008, and

2009) for official network PM2.5 monitors.  Federal Reference Method (FRM) data were used to estimate 2009

design values at the 8 stations that were equipped with an FRM (see Table 8).  The official network PM2.5

continuous monitor was used for all other stations.  The 2009 98th percentile value was used in cases where data

completeness was insufficient to calculate a design value.  Ecology used validated data exclusively for this

analysis as downloaded from EPA’s Air Quality System (AQS).  The statistical package “R” was used to calculate

design values.  

Scores for this category were determined as follows:  The monitor with the maximum design value was given a

top score of “1” and all other monitors received a relative score as determined by the relationship of a given

monitor’s design value to the maximum monitor’s design value (given monitor/maximum monitor).  It should be

noted that none of the Ecology network continuous PM2.5 monitors that were operated during this time period

were designated as Federal Reference or Equivalent Method (FRM or FEM).  Therefore, the calculated design

values cannot be used for determining compliance with the NAAQS and should be viewed only as surrogates of

what pollution levels might have been had air quality been monitored by an FRM/FEM.   

Figure 24 (below) presents the relative ranking for the estimated design value analysis.  Monitors are listed by

station name.   
68

Figure 24: Estimated 2009 PM2.5 24‐hour Design Values

2. 24‐hr NAAQS Exceedances (2007‐2009)

Ecology determined the number of exceedances of the 24‐hr PM2.5 National Ambient Air Quality Standard

(NAAQS) from 2007 through 2009 for each network monitor.  FRM data were used to estimate the number of

exceedances from 2007‐2009 at the 8 stations that were equipped with an FRM (see Table 8).  Because FRM

sampling frequencies vary (every day, every 3rd day, every 6th day, etc.), Ecology calculated rough estimates of

the number of exceedances of the 24‐hour standard.  As an example, in order to calculate the number of 24‐

hour exceedances for the three‐year period 2007 through 2009 at Yakima‐4th Ave. which operates on an every

3rd day sampling schedule, the number of recorded FRM 24‐hour NAAQS exceedances during the period (10)

was multiplied by the ratio of the total number of days (1096) to the number of valid collected samples (345)

during the three year period from 2007‐2009:

i.e., (10)*1096/(345) = ~32 exceedances

The official PM2.5 continuous monitor was used for all other stations and since these run continuously, the

number of exceedances was simply counted.  Ecology used validated data exclusively for this analysis as

downloaded from EPA’s Air Quality System (AQS).  Ecology used Excel to estimate the FRM exceedances and the

statistical package “R” to count the number of continuous monitor 24‐hour NAAQS exceedances.
69

Like design values, this analysis is an attempt to rank monitors in terms of the 24‐hour NAAQS and weight them

accordingly.  However, it is different from the design value analysis in one important regard:  Monitors that have

high 24‐hour NAAQS design values are very likely to record many (at least 8, on average per complete 365‐day

year) exceedances above the 24‐hour NAAQS.  However, some monitors that have lower design values may

nevertheless record several exceedances a year, exposing people to high levels of PM2.5 pollution.  This analysis

attempts to account for those monitors.

Scores for this category were determined as follows:  The monitor with the maximum number of exceedances

was given a top score of “1” and all other monitors received a relative score as determined by the relationship of

the count of a given monitor’s exceedances compared to the number of exceedances from the monitor with the

maximum number of exceedances (# of exceedances/maximum # of exceedances).  Figure 25 presents the

number of 24‐hour NAAQS exceedances during the three year period from 2007 through 2009.  Monitors are

listed by station name.   

Figure 25: PM2.5 24‐hour NAAQS Exceedances (2007‐2009)

3. Ecology Healthy Air Goal Exceedances (2007‐2009)

Hundreds of scientific studies have shown an association of health effects with PM2.5 pollution.  Data from these

studies show that death and illness from exposure to PM2.5 occur at levels lower than the EPA’s 24‐hour

standard of 35 μg/m3 and that health effects are not limited to highly sensitive populations.  Canada’s national
70

24‐hour Canada‐Wide‐Standard (CWS) for PM2.5 is 30 μg/m3 while the World Health Organization recommends

25 μg/m3

.  In fact, epidemiologic data have not identified a threshold for PM2.5 exposure below which no health

effects are observed.

For these reasons, Ecology has a non‐regulatory Healthy Air Goal (HAG) of keeping PM2.5 levels across

Washington State below 20 μg/m3

, based on a 24‐hour average.

This analysis attempts to identify monitors that, while not necessarily recording pollution levels high enough to

exceed the NAAQS, are representative of areas where people are nevertheless being exposed to unhealthy air.

Ecology calculated the number of times each network monitor recorded 24‐hour concentrations (midnight to

midnight) in excess of 20 μg/m3 from 2007 through 2009. FRM data were used to estimate the number of HAG

exceedances from 2007‐2009 at the 8 stations that were equipped with an FRM (see Table 8).  Because FRM

sampling frequencies vary (every day, every 3rd day, every 6th day, etc.), Ecology calculated rough estimates of

the number of HAG exceedances during the 3 year period using the same methodology as described above in for

the 24‐hour NAAQS exceedances.  The network PM2.5 continuous monitor was used for all other stations and

since these run continuously, the number of exceedances was simply counted.  Ecology used validated data

exclusively for this analysis as downloaded from EPA’s Air Quality System (AQS).  Ecology used Excel to estimate

the number of FRM station HAG exceedances and the statistical package “R” was used to count the number of

HAG exceedances from the continuous monitors.

Scores for this category were determined as follows:  The monitor with the maximum number of exceedances

above 20 μg/m3 was given a top score of “1” and all other monitors received a relative score as determined by

the relationship of the count of a given monitor’s number of exceedances above 20 μg/m3 as compared to the

maximum number of exceedances (# of HAG exceedances/maximum # of HAG exceedances).  Figure 26 presents

the number of days that a given monitor exceeded the HAG during the three year period from 2007 through

2009.  Monitors are listed by station name.
71

Figure 26: PM2.5 24‐hour Exceedances of Healthy Air Goal (2007‐2009)

4. Percentage of non‐Good Monitor Days

In December of 2006, EPA lowered the 24‐hour standard for PM2.5 from 65 to 35 μg/m3

.  EPA did not revise its

public information tool, the Air Quality Index (AQI) to reflect the new health‐based standard.  Ecology needed a

way to communicate accurate health risk information to Washington State citizens in lieu of federal action.  For

this reason, Ecology developed and implemented its own air quality public information tool known as the

Washington Air Quality Advisory (WAQA).  The WAQA is nearly identical to EPA’s AQI except that it shows

adverse health effects occurring at lower PM2.5 pollution levels.  The WAQA Good/Moderate breakpoint is

defined as 13.5 μg/m3

, while the AQI breakpoint is 15 μg/m3.

Ecology analyzed air quality conditions across the state from 2007 through 2009 to determine when PM2.5

pollution levels were higher than the Good category.  Ecology determined the number of times each monitor

recorded a 24‐hour average (midnight to midnight) in excess of 13.5 μg/m3 (i.e., the number of days that air

quality was anything other than Good) during the 3‐year period from 2007 through 2009.  FRM data were used

to estimate the number of non‐Good days from 2007‐2009 at the 8 stations that were equipped with an FRM

(see Table 8).  Because FRM sampling frequencies vary (every day, every 3rd day, every 6th day, etc.), Ecology

calculated rough estimates of the number of exceedances of the 24‐hour standard as described above.  The

network PM2.5 continuous monitor was used for all other stations and since these run continuously, the number

of exceedances was simply counted.  The number of non‐Good days was then divided by the total number of
72

complete monitor days possible during the 3‐year period to come up with a percentage of non‐Good days.  

Ecology used validated data exclusively for this analysis as downloaded from EPA’s Air Quality System (AQS).  

Ecology used Excel to estimate the number of non‐Good days from the FRMs and the statistical package “R” was

used to count the number of non‐Good days from the continuous monitors.

This analysis is unique in that several monitors that do not rank high in the previous three analyses rank high in

this analysis.  Many of the monitors with high design values are located in communities that experience several

short, relatively infrequent episodes of very high PM2.5 pollution concentrations but good air quality the majority

of the rest of the time.  The design value and exceedance analyses do a good job of identifying these monitors.  

However, these analyses don’t do well in identifying locations with longer episodes of impaired air at lower

(non‐Good) pollution levels.  A clear example of this phenomenon occurs in Wenatchee.  The Wenatchee

continuous PM2.5 monitor’s design value was 27.1 μg/m3

; well below the NAAQS.  For the same period (2007

through 2009), the monitor in Wenatchee recorded only a single exceedance above the 24‐hour standard of 35

μg/m3

.  Though it recorded a fairly large number of days over the Ecology Healthy Air Goal of 20 μg/m3 (86

days), by comparison, it recorded an extremely large number of days (214) that were outside the Good WAQA

category (over 20% of the monitored days).  Obviously, even though the air quality in Wenatchee is not close to

violating the NAAQS, on average, air quality is impaired to some degree one out of every 5 days over the last 3

years.  This analysis identifies monitors like the one in Wenatchee.

Scores for this category were determined as follows:  The monitor with the maximum percentage of non‐Good

days was given a top score of “1” while all other monitors received a relative score as determined by the

relationship of the percentage of a given monitor’s non‐Good days to the maximum percentage of non‐Good

days (percentage of non‐Good days/maximum percentage of non‐Good days).  Figure 27 presents the

percentage of days (24 hours, midnight to midnight) that were anything other than Good based on the monitor

data during the three year period from 2007 through 2009.  Monitors are listed by station name.
73

Figure 27: PM2.5 Non‐Good Days (2007‐2009)

5. Forecasting/Curtailment Need?

Along with its partners at EPA, local air agencies and tribes, Ecology uses its network continuous PM2.5 monitors

for the forecasting of air quality and for making woodstove/outdoor burn curtailment calls during episodes of

impaired air.

Making defensible curtailment calls is critical to Ecology and its partners’ work of protecting public health,

preventing exceedances and violations of the NAAQS, and ensuring our credibility with the public and the

regulated community.  Monitors that allow us to successfully conduct this work are very important.  This

analysis accounts for the importance of this need.

This is a yes or blank category.  Any monitor that is used for forecasting/curtailment calls received a “Y”.  A “Y”

(for yes) is worth 1 point.

6. Tribal Station?

Ecology partners with EPA to provide continuous PM2.5 monitoring on tribal lands located within the boundaries

of Washington State.  These monitors are used by EPA and tribal nations to ensure compliance with Federal Air

Rules for Reservations (FARR) and make curtailment calls.  It should be noted that while these air monitors are
74

located within tribal boundaries, they provide useful information for both those inside and outside the

reservation.

These monitors are funded by EPA.

This is a yes or blank category.  Any monitor that is part of Ecology’s contractual agreement with EPA for

conducting monitoring on tribal lands within Washington State received a “Y”.  A “Y” (for yes) is worth 1 point.

7. USFS Station?

Ecology partners with the U.S. Department of Agriculture Forest Service (USFS) to provide continuous PM2.5

monitoring on USFS lands located within the boundaries of Washington State.  These monitors are used by USFS

to characterize smoke impacts associated with prescribed silvicultural burning.  It should be noted that while

these air monitors are located on USFS land, they provide useful public health information for those living in

communities or recreating near national forests.

These monitors are funded by the USFS.

This is a yes or blank category.  Any monitor that is part of Ecology’s contractual agreement with the USFS for

conducting monitoring on USFS lands within Washington State received a “Y”.    A “Y” (for yes) is worth 1 point.

8. Agricultural Burning Station?

As a result of a federal court case settlement, several years ago Ecology implemented a sub‐network of 8

continuous PM2.5 monitors to assist with smoke management associated with agricultural burning in Eastern

Washington. Specifically, these monitors ‐ along with information from meteorological monitors, field reports,

burn permit applications and both meteorological and atmospheric dispersion models ‐ are used on a daily basis

by Ecology to make burn decisions. These monitors are both a vital resource for the proper implementation of

the agricultural burn smoke management program and for evaluating the performance thereof.

This is a yes or blank category.  Any monitor that is part of the agricultural burning network received a “Y”.  A “Y”

(for yes) is worth 1 point.

9. NCORE/Potential NCORE?

Ecology recognizes the importance of the EPA’s National Core Monitoring (NCORE) and that NCORE status

should be included as a factor in the prioritization of the PM2.5 monitoring network.  This category identifies

monitors located at stations that are, or are pending designation as, NCORE pursuant to EPA’s Core Monitoring

Strategy.

This is a yes or blank category.  Any monitor that is located at a station that is, or is pending, NCORE designation

received a “Y”.  A “Y” (for yes) is worth 1 point.

10. Sole monitor Per Air shed?

Ecology sought to identify redundancies in its PM2.5 monitoring network.  Resource savings may be achieved in

areas where monitors provide redundant information on air quality by the elimination of one or more of the

redundant monitors.
75

To this end, Ecology examined several monitors that appeared to be close enough in spatial proximity to yield

redundant information.  It should be noted that the topography, meteorology and emissions in Washington,

particularly Western Washington, are quite heterogeneous as compared to other areas of the country, such as

the Midwest.  For this reason, the guidance and tools provided by EPA for identifying redundancies in

monitoring were not particularly useful for Washington State.  Specifically, cross‐comparing stations as

suggested by EPA, and calculating correlation matrices was of little utility as many stations with high R2 values

nevertheless represented unique air sheds, including those within the same metropolitan statistical areas.

Therefore, Ecology examined a variety of factors for monitors that were believed to be in the same air shed to

determine whether redundant information was being collected.  Ecology looked at how well trends tracked each

other as well as the magnitude of those trends in a variety of ways.  Sites with R2 > 0.7 from the EPA correlation

matrices were also examined this way, even though many such site pairs were clearly located in separate air

sheds.  Ecology then ran the comparisons shown in Figure 28, and found that the majority of PM2.5 monitoring

stations in the Ecology network provided unique information.   

Figure 28: Inter‐comparison of Bellevue and Woodinville PM2.5

Figure 28 shows the inter‐comparison of Bellevue and Woodinville nephelometers. (a) Shows a scatterplot, with

different regression lines.  Forcing the intercept to zero does not change the slope much. (b) PM2.5 difference as

a function of time suggests that differences are not confined to a particular period. (c) PM2.5 difference as a

function of Bellevue PM2.5.  The plot suggests the sites deviate randomly, and not when Bellevue is more/less

polluted. (d) Quantile‐quantile plot, suggesting data are similarly distributed, as confirmed by the Kolmogorov‐
76

Smirnov (K‐S) Test. (e) No clear seasonal dependence of  differences between sites is seen. (f) While some data

deviate at lower wind speeds (i.e. suggesting localized sources impact one site and not the other), for the most

part the differences are not correlated with winds.

This is a yes or blank category.  Any monitor that was identified as being the sole monitor for an air shed/area

received a “Y”.  A “Y” (for yes) is worth 1 point.

11. Percentage of Individuals Living Below the Federal Poverty Level

Ecology believes it is important to consider issues of environmental justice when evaluating its air pollution

monitoring network.  EPA defines environmental justice as follows:

Environmental Justice is the fair treatment and meaningful involvement of all people

regardless of race, color, national origin, culture, education, or income with respect to

the development, implementation, and enforcement of environmental laws,

regulations, and policies. Fair Treatment means that no group of people, including racial,

ethnic, or socioeconomic groups, should bear a disproportionate share of the negative

environmental consequences resulting from industrial, municipal, and commercial

operations or the execution of federal, state, local, and tribal environmental programs

and policies. Meaningful Involvement means that: (1) potentially affected community

residents have an appropriate opportunity to participate in decisions about a proposed

activity that will affect their environment and/or health; (2) the public's contribution can

influence the regulatory agency's decision; (3) the concerns of all participants involved

will be considered in the decision‐making process; and (4) the decision‐makers seek out

and facilitate the involvement of those potentially affected (EPA, 2010).

Ecology analyzed the value of its PM2.5 monitors in terms of environmental justice.  Ecology determined the

appropriate representative zip code for each monitor and used the US Census Bureau’s American Fact Finder

website to determine the percentage of individuals living below the federal poverty level (FPL) within the zip

code in which each monitor was located.

There are some caveats that accompany this analysis:

• The metric of percentage of individuals living below the FPL may or may not be the best indicator of

environmental justice but was considered a reasonable surrogate for the purposes of this analysis.

• Zip codes vary in size and shape, monitors may straddle more than a single zip code, and zip codes

may encompass only a portion of the air shed that the monitor represents.  Nevertheless, for the

purposes of this analysis, zip codes were seen as a reasonable surrogate for spatial coverage of a

monitor.  In addition, this information was easily obtained via the US Census Bureau American Fact

Finder website.

• Because recent poverty estimates were unavailable for many monitor‐zip codes statewide, Ecology

used 2000 Census poverty information only.  This means that the information is somewhat out of

date.  However, for the purposes of this analysis, it was believed that 2000 data would provide

reasonable information, even though the magnitudes of individuals living in poverty may have

changed.

Areas with higher percentage of individuals living in poverty received higher scores
77

Scores for this category were determined as follows:  The monitor located within the zip code with the highest

percentage of individuals living in poverty received a top score of “1” while all other monitors received relative

scores as determined by the relationship of the percentage of individuals living in poverty for a given monitor‐

zip code to the maximum percentage individuals living in poverty (percentage of individuals in

poverty/maximum percentage).  Figure 29 presents the percentage of individuals living in poverty by monitor‐

zip code.  Monitors are listed by station name.

Figure 29: Percentage of Individuals Living Below FPL by Zip Code

12. Length of Historical Record

Monitors with long historical records are particularly useful for characterizing air quality over time and tracking

efficacy of control measures.  Likewise, monitors with long records can provide sound historical pollution

information for future policy choices.

Ecology evaluated the length of the historical record length for each of its network PM2.5 monitors.  Monitors

with longer records received higher scores.  Ecology downloaded monitor start dates from AQS for this analysis.

Scores for this category were determined as follows:  The monitor with the longest record received a top score

of “1” while all other monitors received relative scores as determined by the relationship of the length of given

monitor’s record to the longest record (length of record/maximum record length).
78

13. Number of Collocated Network Parameters

Cost‐savings are leveraged at stations with multiple monitors.  At these stations, operators can perform

maintenance or quality control checks on several instruments during the same visit, resulting in operational and

maintenance cost savings per‐monitor.  Therefore, Ecology evaluated the total number official network monitors

at each station equipped with a network PM2.5 monitor.  Ecology used AQS to count the number of network

parameters per station for this analysis.

Scores for this category were determined as follows:  The monitor collocated with the greatest number of

network monitors received a top score of “1” while all other monitors received relative scores as determined by

the relationship of a given monitor’s number of collocated network monitors to the maximum number of

collocated monitors (number of collocated monitors/maximum number of collocated monitors).

14. Population Represented By Monitor

Exposure increases as a function of population for a given area.  In other words, more people are likely to be

exposed to a given pollution concentration in a relatively densely populated area than in a less‐densely

populated one.

While it would have been ideal to determine exposure using air sheds, doing so for each monitor was deemed to

be too resource‐intensive and was therefore not pursued.  Instead, as a surrogate for human exposure, Ecology

used Office of Financial Management (OFM) 2007 Washington population estimates at the 12 km grid resolution

to determine the population represented by a given monitor.

In general, this analysis provided reasonable estimates of the number of people represented by a given monitor.  

It should be noted, however, that the vast majority of Ecology’s PM2.5 monitors are designated Neighborhood

Scale and therefore are technically only representative of air quality conditions within a 4 km radius from the

monitor.  In addition, estimates of represented population in urban areas such as Seattle were complicated by

the fact that one 12 km grid cell contained three monitors.  In such cases, each monitor within the grid cell was

estimated to represent the population for the entire grid cell and thus population exposure is probably

overestimated for these monitors.  However, because these monitors are located in densely populated areas,

Ecology believed that its analysis nonetheless provided reasonable approximations of relative exposure by

monitor and was a reasonable surrogate for more precise estimates.

Ecology used the Environmental Benefits Mapping & Analysis Program (BenMAP) to compile monitor‐

represented population estimates from the OFM census data at the 12 km grid resolution.

Scores for this category were determined as follows:  The monitor representing the largest population was

awarded a score of “1” and all other monitors received a relative score as determined by the relationship of the

population represented by the monitor (monitor‐population) to the maximum represented population (monitor‐

population/maximum monitor‐population).  As mentioned previously, there were three monitors that fell within

the same 12 km grid cell.  This grid cell had the maximum population and therefore, there were three monitors

with a score of “1”.  Figure 30 presents the estimated population represented by each PM2.5 monitor.  Monitors

are listed by station name.
79

Figure 30: Population Represented by PM2.5 Monitor

15. Population Trend

Communities with rapidly growing populations may be at higher risk of worsening air quality conditions over

time due to increases in vehicle traffic, industry, and other factors.

Ecology evaluated population trends by city in an attempt to identify areas of rapid population growth using

data available through the Washington State Office of Financial Management (OFM) website.  Ecology used

OFM’s 2009 estimates (2000 baseline), for the purposes of this analysis.

Cities with rapidly growing populations received higher scores.

Scores for this category were determined as follows:  The monitor located within the city (station‐city) with the

fastest growing population received a top score of “1” while all other monitors received relative scores as

determined by the relationship of a given monitor‐city’s population growth to the maximum population growth

(pop. growth/maximum pop. growth).
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Appendix B – Ozone Decision Matrix

Table 9: Ranking criteria for each Ozone monitoring site

AQS Number Site Name Network Parameter 1 2 3 4 5 6 7 8 9

530330023 Enumclaw-Mud Mtn. O3 1.00 1.00 1.00 0.31 0.72 1.00 1.00 6.03

530330010 Issaquah-Lake Sammamish O3 0.80 0.11 0.20 0.06 1.00 1.00 1.00 4.18

530330017 North Bend-North Bend Way O3 0.81 0.22 0.31 0.31 0.34 1.00 1.00 4.01

530330080 Seattle-Beacon Hill O3 0.62 0.00 0.00 1.00 0.38 1.00 1.00 4.00

530110011 Vancouver-Blairmount Dr O3 0.83 0.11 0.31 0.31 0.35 1.00 1.00 3.91

530531008 LaGrande-Pack Forest O3 0.89 0.44 0.71 0.06 0.72 1.00 3.83

530630046 Spokane-Greenbluff O3 0.82 0.00 0.31 0.06 0.58 1.00 1.00 3.78

530670005 Yelm-Northern Pacifc O3 0.79 0.11 0.20 0.06 0.37 1.00 1.00 3.54

530090013 Cheeka Peak O3 0.70 0.00 0.00 0.56 0.11 1.00 1.00 3.38

530530012 Mt Rainier-Jackson Visitors Ctr O3 0.74 0.00 0.14 0.06 0.34 1.00 1.00 3.29

530630001 Cheney-Turnbull O3 0.78 0.00 0.00 0.06 0.32 1.00 1.00 3.16

530730005 Custer-Loomis O3 0.63 0.00 0.00 0.06 0.61 1.00 2.30

Ranking criteria

1. Estimated 2009 Design Value (normalized category)

2. Number of 8‐hour Exceedances (2007‐2009) (normalized category)

3. Number of 8‐hour Daily Maximums Above .060 ppm (normalized category)

4. Number of Collocated Network Parameters (normalized category)

5. Historical Record Length (normalized category)

6. Forecasting/Action Day Need? (“Y” or blank where “Y” =1)

7. NCORE/Potential NCORE? (“Y” or blank where “Y” =1)

8. Non‐redundant Monitor? (“Y” or blank where “Y” =1)

9. Total Score
81

Ozone Decision Matrix Detail

This section describes the analyses that were conducted on the ozone monitoring network and were subsequently

incorporated into the decision matrix to determine the final ranking in Table 9 above.

1. Estimated 2009 8‐hour Design value

Ecology estimated 2009 8‐hour design values (3‐year average of the annual 4th‐highest daily maximum 8‐hour

average from the years 2007, 2008, and 2009) for ozone network monitors that met the 75% annual data

completeness criteria.  Ecology used validated data exclusively for this analysis as downloaded from EPA’s Air

Quality System (AQS).  The statistical package “R” was used to calculate design values.  

Scores for this category were determined as follows:  The monitor with the maximum design value was given a top

score of “1” and all other monitors received a relative score as determined by the relationship of a given monitor’s

design value to the maximum design value (given design value/maximum design value).  Figure 31 presents the

relative ranking for the estimated design value analysis.  Monitors are listed by station name.   

Figure 31: Estimated 2009 8‐hour Ozone Design Values
82

2. Number of 8‐hour NAAQS Exceedances (2007‐2009)

Ecology determined the number of exceedances of the 8‐hour ozone National Ambient Air Quality Standard

(NAAQS) of .075 ppm for the 3 year period from 2007 through 2009 for each network monitor.  Ecology used

validated data exclusively for this analysis as downloaded from EPA’s Air Quality System (AQS).  The statistical

package “R” was used to count the number of 8‐hour NAAQS exceedances.

Like design values, this analysis is an attempt to rank monitors in terms of the 8‐hour NAAQS and weight them

accordingly.  However, it is different from the design value analysis in one important regard:  Monitors that have

high 8‐hour NAAQS design values are very likely to record many exceedances above the 8‐hour NAAQS.  However,

some monitors that have lower design values may nevertheless record several exceedances a year, exposing people

to high levels of ozone pollution.  This analysis attempts to account for those monitors.

Scores for this category were determined as follows:  The monitor with the maximum number of exceedances was

given a top score of “1” and all other monitors received a relative score as determined by the relationship of the

count of a given monitor’s exceedances compared to the maximum number of exceedances (# of

exceedances/maximum # of exceedances).  Figure 32 presents the number of 8‐hour ozone NAAQS exceedances by

monitor.  Monitors are listed by station name.   
83

Figure 32: Ozone Monitor 8‐hour NAAQS Exceedances (2007‐2009)

3. Number of Daily Maximum 8‐hour Concentrations Above .060 ppm (2007‐2009)

Ecology analyzed the ozone network to determine when ozone pollution levels were anything other than Good as

defined by EPA’s Air Quality Sub‐index for ozone (the breakpoint of which is .060 ppm).   This analysis attempts to

identify monitors that, while not necessarily recording pollution levels high enough to exceed the NAAQS, are

representative of areas where people are nevertheless being exposed to unhealthy air.  Currently, EPA has proposed

a revised 8‐hour ozone standard between .060 and .070 ppm.  This analysis therefore also ranks monitors in terms

of the lower end of EPA’s proposed standard range.

Ecology determined the number of times each monitor recorded a daily maximum 8‐hour average in excess of .060

ppm during the 3‐year period from 2007 through 2009.  Ecology used validated data exclusively for this analysis as

downloaded from EPA’s Air Quality System (AQS).  The statistical package “R” was used to count the number of non‐

Good days.

Scores for this category were determined as follows:  The monitor with the maximum number of daily maximum 8‐

hour concentrations greater than .060 ppm was given a top score of “1” and all other monitors received a relative

score as determined by the relationship of the count of a given monitor’s daily maximums above .060 ppm as

compared to the maximum number of daily maximums above .060 ppm (# of daily maximums > .060/maximum # of
84

daily maximums > .060 ppm).  Figure 33 presents the number of days that monitors recorded a daily maximum 8‐

hour concentration in excess of .060 ppm (i.e., a day that was other than Good).  Monitors are listed by station

name.   

Figure 33: Ozone 8‐hour Daily Maximum Concentrations Above .060 ppm (2007‐2009)

4. Forecasting/Action‐Day Need?

Ecology and its partners use the network ozone monitors for the forecasting of air quality and for announcing

ozone action days during summertime episodes.

Making defensible action‐day calls is critical to Ecology and its partners’ work of protecting public health,

preventing exceedances and violations of the NAAQS, and ensuring our credibility with the public.  Monitors that

allow us to successfully conduct this work are very important.  This analysis accounts for the importance of this

need.

This is a yes or blank category.  Any monitor that is used for forecasting/action‐day calls received a “Y”.  A “Y”

(for yes) is worth 1 point.

5. NCORE/Potential NCORE?
85

Ecology recognizes the importance of the EPA’s National Core Monitoring (NCORE) and that NCORE status

should be included as a factor in the prioritization of the ozone monitoring network.  This category identifies

monitors located at stations that are, or are pending designation as, NCORE pursuant to EPA’s Core Monitoring

Strategy.

This is a yes or blank category.  Any monitor that is located at a station that is, or is pending, NCORE designation

received a “Y”.  A “Y” (for yes) is worth 1 point.

6. Length of Historical Record

Monitors with long historical records are particularly useful for characterizing air quality over time and tracking

the efficacy of control measures.  Likewise, monitors with long records can provide sound historical pollution

information for future policy choices.

Ecology evaluated the length of the historical record length for each of its network ozone monitors.  Monitors

with longer records received higher scores.  Ecology downloaded monitor start dates from AQS for this analysis.

Scores for this category were determined as follows:  The monitor with the longest record received a top score

of “1” while all other monitors received relative scores as determined by the relationship of the length of given

monitor’s record to the longest record (length of record/maximum record length).

7. Number of Collocated Network Parameters

Cost‐savings are leveraged at stations with multiple monitors.  At these stations, operators can perform

maintenance or quality control checks on several instruments during the same visit, resulting in operational and

maintenance cost savings per‐monitor.  Therefore, Ecology evaluated the total number official network monitors

at each station equipped with an ozone monitor.  Ecology used AQS to count the number of network parameters

per station for this analysis.

Scores for this category were determined as follows:  The monitor collocated with the greatest number of

network monitors received a top score of “1” while all other monitors received relative scores as determined by

the relationship of a given monitor’s number of collocated network monitors to the maximum number of

collocated monitors (number of collocated monitors/maximum number of collocated monitors).

8. Non‐redundant Monitor?

Ecology sought to identify redundancies in its ozone monitoring network.  Resource savings may be achieved in

areas where monitors provide redundant information on air quality by the elimination of one or more

redundant monitors.

To this end, Ecology examined several monitors that would reasonably be expected to yield redundant

information.  It should be noted that the topography, meteorology and emissions in Washington, particularly

Western Washington, are quite heterogeneous as compared to other areas of the country, such as the Midwest.  

For this reason, the guidance and tools provided by EPA for identifying redundancies in monitoring were not

particularly useful for Washington State.   

Of the eleven ozone site pairs that were compared, Figure 34 suggests that the North Bend and La Grande sites

may depict similar trends.  
86

Figure 34: Intercomparison of North Bend and La Grande Ozone

Figure 34 presents the intercomparison of North Bend and La Grande ozone monitors. (a) Shows a scatterplot,

with different regression lines.  Data appear somewhat similar. (b) Ozone difference as a function of time.  Other

than a few events, the differences are not pronounced during a particular period.  (c) Ozone difference as a

function of La Grande ozone. The plot suggests that there are a few instances (27 days in 10 years) when high

ozone events recorded at La Grande are not captured in North Bend*.  Otherwise, most of the differences

between sites appear to be random in nature. (d) Quantile‐quantile plot, suggesting data are similarly

distributed.  The K‐S test can be considered close to significant, if a probability of <95% is acceptable. (e)

Differences between sites by month shows no clear monthly dependence. (f) Differences by wind speeds

recorded at nearest met sites.  Other than the extreme events recorded at La Grande, which occurred during

moderate easterly winds*, for the most part the differences are not correlated with winds.

* Days when La Grande was over 60 ppb and North Bend lagged by at least 5 ppb. These events were

characterized by easterly cross‐Cascade flow, which, coupled with the northerly regional flow, drives the ozone

plume toward the south/southwest of the Puget Sound lowlands and away from North Bend.  Depending on the

strength of the easterly gradients, this pattern gives rise to comparable or higher ozone levels either at the Yelm

or Enumclaw monitors.  It is felt that little information will be sacrificed by shutting down the standalone ozone

station at La Grande, as comparable concentrations are expected either at Enumclaw, North Bend or Yelm on

most high ozone days.  
87

This is a yes or blank category.  Any monitor that is considered to provide non‐redundant data/information

received a “Y”.  A “Y” (for yes) is worth 1 point.