# Ambient Air Quality Monitoring and

Health Research:

Summary of April 16-17, 2008

Workshop to Discuss Key Issues

U.S. ENVIRONMENTAL PROTECTION AGENCY

Office of Research and Development

Office of Air and Radiation/Office of Air Quality Planning and

Standards

DECEMBER 2008

# December 2008 [This page intentionally left blank.]

# December 2008 EPA 452/S-08-001

December 2008



# Ambient Air Quality Monitoring and

Health Research:

Summary of April 16-17, 2008

Workshop to Discuss Key Issues

U.S. Environmental Protection Agency

Office of Research and Development

and

Air Quality and Assessment Division

Health and Environmental Impacts Division

Office of Air Quality Planning and Standards

Office of Air and Radiation

Research Triangle Park, North Carolina

# December 2008 

# DISCLAIMER

This workshop summary report serves to document recommendations presented at a

recent workshop held by the U.S. Environmenta l Protection Agency's Office of Research and

Development (ORD) and the Office of Air Qualit y Planning and Standard s (OAQPS) within the

Office of Air and Radiation (OAR). The recomme ndations described in this report have been

modified to reflect informati on developed during the review of this document and may be

modified in subsequent discussions with intern al and external experts. ORD and OAR will use

the recommendations presented in this document as a tool to consider and prioritize both shortand long-term actions for EPA and others to und ertake in the development and implementation

of ambient air monitoring and health research st rategies. Mention of trade names or commercial

products does not constitute endorsement or recommendation for use.

# December 2008 i 

# TABLE OF CONTENTS

LIST OF ACRONYMS ............................................................................................................... ........iii

AUTHORS AND CONTRIBUTORS ...................................................................................................v

INTRODUCTION................................................................................................................... ............. 1

Background ....................................................................................................................................................2

Workshop Structure, Objectives, and Outline of Session Summaries......................................................2

Initial Successes and Next Steps ............................................................................................... ....................3



# SESSION I: ELEMENTAL AND OR GANIC CARBON MEASUREMENTS ............................... 5

Background/Objectives.................................................................................................................................5

Session Overview ............................................................................................................... ............................5

Major Points Raised by Participants ............................................................................................ ...............6

Recommendations/Action s for Consideration ...................................................................................... ......9



# SESSION II: ACCESSING AMBIENT AIR MONITORING DATA............................................ 11

Background/Objectives.......................................................................................................... .....................11

Session Overview ............................................................................................................... ..........................11

Major Points Raised by Participants ............................................................................................ .............12

Recommendations/Action Items for Consideration................................................................................. .14



# SESSION III: AMBIENT AIR MONI TORING FOR HEALTH RESEARCH ............................ 17

Background/Objectives.......................................................................................................... .....................17

Session Overview ............................................................................................................... ..........................17

Major Points Raised by Participants ............................................................................................ .............17

Recommendations................................................................................................................ ........................19

Action Items for Consideration ................................................................................................. .................20



# SESSION IV: THORACIC COARSE PARTIC LE COMPONENTS AND POTENTIAL HEALTH

IMPACTS........................................................................................................................................... 22

Background/Objectives.......................................................................................................... .....................22

Session Overview ............................................................................................................... ..........................22

Major Points Raised by Participants ............................................................................................ .............24

Recommendations/Action s for Consideration ...................................................................................... ....26



# SESSION V: AMBIENT AIR MONITORING REALITIES – EPA/STATE/LOCAL

PERSPECTIVES – SUMMARY AND RECOMMENDATIONS.................................................... 30

Background/Objectives.......................................................................................................... .....................30

Session Overview ............................................................................................................... ..........................30

Major Points Raised by Participants ............................................................................................ .............30

# December 2008 ii Recommendations/Action s for Consideration ...................................................................................... ....35



# BACKGROUND MATERIALS......................................................................................................... 39

Appendix A: Workshop Agenda and Participant List......................................................................... A-1

Appendix B: Session I: Elemental and Organic Carbon Measurements - Chemical Speciation

Network (CSN) Carbon Issues .................................................................................................... .............B-1

Appendix C: Session II: Accessing Ambient Air Monitoring Data - Access to EPA’s Air Quality

Data for Health Researchers .................................................................................................... ............... C-1

Appendix C.1 – Other Data Access Mech anisms................................................................................. C-1 0

Appendix D: Session III: Ambient Air Monitoring for Health Research - Air Quality Sampling:

Benefits and Costs of Daily Health Targeted Monitors for Fine Particle Components ..................... D-1

Appendix E: Session V: Ambient Air Monitori ng Realities – EPA/State/Local Perspectives -

Ambient Air Monitoring Network: Network Design and Site Selection Approval .............................E-1

Appendix F: Session V: Ambient Air Monitori ng Realities – EPA/State/Local Perspectives -

Ambient Air Monitoring Method Implementation ................................................................................F-1

Appendix G: Preliminary Survey of Ambient Air Monitoring Sites Currently Being Considered in

EPA-funded Epidemiology Studies Feb 2008....................................................................................... .. G-1

# December 2008 iii 

# LIST OF ACRONYMS

The following acronyms have been used for th e sake of brevity in this document:

AMTIC Ambient Monitoring Technology Information Center

AQS Air Quality System

ARMs Approved Regional Methods

AQI Air Quality Index

BC Black carbon

BOSC Board of Scientific Counselors

CAA Clean Air Act

CAAAC Clean Air Act Advisory Committee

CASAC Clean Air Scientific Advisory Committee

CMAQ Community Multi scale Air Quality Model

CSN Chemical Speciation Network

DASH Denver Aerosol Sources and Health

DEARS Detroit Exposure and Aerosol Research Study

DRI Desert Research Institute

DRUM Davis Rotating Uniform size-cut Monitor

EC Elemental carbon

EPA Environmental Protection Agency

FDMS Filter Dynamic Measurement System

FEM Federal Equivalent Method

FRM Federal Reference Method

GEO Group on Earth Observations

GIS Geographic information systems

HEI Health Effects Institute

IMPROVE Interagency Monitoring of Protected Visual Environment

KML Keyhole markup language

MESA Multi-Ethnic St udy of Atherosclerosis

MYP Multi-year Plan

NAAQS National ambient air quality standards

NACAA National Association of Clean Air Agencies

NARSTO North American Research Strategy for Tropospheric Ozone

NCER National Center for Environmental Research

NCore National Core Monitoring Network

OAQPS Office of Air Qual ity Planning and Standards

OC Organic carbon

ORD Office of Research and Development

PM Particulate matter

PM 2.5 

# particles generally less than or equal to 2.5 μm in diameter

PM 10 

# particles generally less th an or equal to 10 micrometers (μm) in diameter

PM 10-2.5 

# particles generally larger than 2.5 and up to 10 μm in diameter

PQAO Primary Quality Assurance Organization

QA Quality assurance

SEM Scanning electron microscopy

SLAMS State and local air monitoring stations

# December 2008 iv STAR Science to Achieve Results

STN Speciation Trends Network

TC Total carbon

TEOM Tapered Element Oscillating Microbalance

TTN Technology Transfer Network

TOR Thermal-optical reflectance

TOT Thermal-optical transmittance

XRF X-ray fluorescence

# December 2008 v 

# AUTHORS AND CONTRIBUTORS

AUTHORS

Dr. Dan Costa, National Program Di rector for Air Research, Office of Research and Development,

US Environmental Protection Agen cy, Research Triangle Park, NC

Mr. Neil Frank, Office of Air Quality Planning a nd Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Dr. Barbara Glenn, National Cent er for Environmental Researc h, Office of Research and

Development, US Environmental Protection Agency, Washington, DC

Mr. Tim Hanley, Office of Air Quality Planning a nd Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Ms. Beth Hassett-Sipple, Office of Air Quality Pla nning and Standards, Office of Air and Radiation,

US Environmental Protection Agen cy, Research Triangle Park, NC

Dr. Bryan Hubbell, Office of Air Quality Planning and Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Mr. Phil Lorang, Office of Air Quality Planning a nd Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Mr. Nick Mangus, Office of Air Quality Planning and Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Dr. Lucas Neas, National Health and Environm ental Effects Research Laboratory, Office of

Research and Development, US Environmen tal Protection Agency, Chapel Hill, NC

Dr. Venkatesh Rao, Office of Air Qu ality Planning and Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Ms. Joann Rice, Office of Air Quality Planning a nd Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Mr. Geoffrey Sunshine, Health Effects Institute, Boston , MA

Mr. Tim Watkins, National Exposure Research La boratory, Office of Resear ch and Development,

US Environmental Protection Agen cy, Research Triangle Park, NC

Mr. Lewis Weinstock, Office of Air Quality Planning and Standards, Office of Air and Radiation,

US Environmental Protection Agen cy, Research Triangle Park, NC

# December 2008 vi 

# CONTRIBUTORS

Dr. Sherri Hunt, National Center for Environmental Research, Office of Research and Development,

US Environmental Protection Agency, Washington, DC

Ms. Sascha Lodge, National Cent er for Environmental Resear ch, Office of Research and

Development, US Environmental Protection Agency, Washington, DC

Ms. Stacey Katz, National Center for Envir onmental Research, Office of Research and

Development, US Environmental Protection Agency, Washington, DC

Dr. Marc Pitchford, Office of Air Quality Planning and Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Ms. Gail Robarge. National Center for Envi ronmental Research, Office of Research and

Development, US Environmental Protection Agency, Washington, DC

Mr. Rich Scheffe, Office of Air Quality Planning and Standards, Office of Air and Radiation, US

Environmental Protection Agency, Research Triangle Park, NC

Ms. Laurel Schultz, Office of Re search and Development, US Environmental Protection Agency,

Research Triangle Park, NC

Dr. William Wilson, National Center for Environmen tal Assessment, US Environmental Protection

Agency, Research Triangle Park, NC

Dr. Darrell Winner, National Center for Envi ronmental Research, Office of Research and

Development, US Environmental Protection Agency, Washington, DC

# December 2008 1 

# INTRODUCTION

Air pollution continues to have adverse impacts on the human and environmental health of

the United States, despite clear evidence that overall air quality has improved. To understand the

relationships between air pollutants and adverse h ealth and welfare effects, researchers utilize

ambient air measurement data collected through m onitoring networks operated almost exclusively

by State, local and Tribal air monitoring programs. These networks provide data for characterizing

ambient air concentrations of the criteria air po llutants (particulate matte r (PM), ozone, nitrogen

dioxide, sulfur dioxide, lead, and carbon monoxide) as well as toxic air pollutants. However, the

ambient air monitoring networks do not capture data everywhere orevery day. Thus, in April 2008,

the Environmental Protection Agency’s (EPA’s) Office of Research and Development (ORD) and

Office of Air Quality Planning and Standards (OAQPS) within the Office of Air and Radiation

(OAR) co-sponsored a workshop to discuss which m odifications to the curre nt ambient air quality

monitoring networks would advanc e our understanding of the impact s of criteria air pollutant

exposures on public health/welfare in the most m eaningful way. In partic ular, EPA sought advice on

concrete steps that could be ta ken to prioritize monitoring sites and/or specific fine particle

components for more frequent monitoring in orde r to improve our understa nding of the impact of

these components on public health 1



# .

The purpose of this document is to present a summary of the April 2008 workshop and the

recommendations emanating from the workshop discus sions. This document is not intended to be a

commitment to actually implement th e recommendations but rather it wi ll serve as a tool to consider

and prioritize near- and long-term actions for EPA a nd others to undertake. To the extent that these

recommendations can be incorporated into routin e monitoring networks, they will help expedite

research, better inform future reviews of the national ambient air quality standards (NAAQS), and,

ultimately, reduce air pollutant exposures that ar e associated with adverse health and welfare

effects. 2

1 

# Research specific to the protection of public health rema ins a top priority and EPA has targeted PM as a high-risk

pollutant. In the last PM NAAQS revi ew, EPA focused on particle mass and primarily distinguished between two

categories of particle pollution based on size (i.e., fine- and coarse-fraction particles), and conducted parallel evaluations

of the available scientific evidence relating to each categ ory. The importance of specific PM components and sources

was evaluated within the context of this basic size diff erentiation. In the current PM NAAQS review, EPA is

considering the extent to which new information has become available to assess and determine how particle pollution is

defined. Specific characteristics to consider will includ e particle size/mass, composition, and sources/environments

(e.g., urban and rural areas). This in formation will inform decisions related to whether sufficient evidence exists to

warrant consideration of alternative indicators for PM, an d, if appropriate, the development of new NAAQS. See

http://www.epa.gov/ttn/naaqs/standards/pm/data/2008_03_final_integrated_review_plan.pdf for more information.

2 

# In a related effort, EPA recently issued the Clean Air Research Multi-Year Plan 2008-2012 which describes the

objectives of leading-edge research to support regulatory decision-making. Th is plan outlines research that will provide

critical information to add to the existing scientific foundatio n to inform the reviews of the NAAQS; develop regulations

and advanced tools and models to implement the NAAQS; and improve methods to track progress in achieving health

and environmental improvements. (See http://www.epa.gov/ord/npd/pdfs/Air-MYP-narrative-final.pdf ) The multi-year

pl an builds upon recommendations from EPA’s OAR as well as several scientific advisory boards. See also National

Academy of Sciences (NAS) National Research Council (NRC): Research Priorities for Airb orne Particulate Matter at

http://books.nap.edu/catalog.php?record_id=10957 ; Board of Scientific Counselors ( B OSC) Report on the PM-Ozone

Program Review: April 2005 at http://www.epa.gov/osp/bosc/pdf/pm0508rpt.pdf ; and Clean Air Act Advisory

Co mmittee (CAAAC) Report on Air Quality Management in the United States at

http://www.nap.edu/catalog/10728.html.

# December 2008 2 

# Background

The EPA is interested in having an open and c ontinuing dialogue with representative experts

regarding health research prioriti es for ambient air quality monitori ng data that would best advance

our understanding of the impacts of air pollutant exposures on public health. This dialogue was

significantly advanced at an ini tial meeting co-sponsored by the He alth Effects Institute (HEI) and

EPA in late 2006. At that meeting, the primar y focus was to discuss how the use of the

accumulating data derived from nationwide mo nitoring of fine particulate matter (PM 2.5 

# )

components could facilitate current and future he alth effects studies and improve comparisons of

risk estimates across studies. The workshop illumi nated issues associated with accessing and

analyzing monitoring data and iden tified needs of the health effects research community regarding

monitoring of fine particle components. 3



# In April 2008, EPA’s ORD and OAQPS co-s ponsored a follow-up workshop bringing

together approximately 80 EPA and external air quality, monitoring, exposure, and health scientists 4



# . As briefly described above, the major goal of the workshop was to discuss recommendations for

modifications to the current ambient air quality m onitoring that would advan ce our understanding of

the impacts of criteria ai r pollutant exposures on pub lic health/welfare in the most meaningful way,

specifically for understanding the impact of PM and PM 2.5 

# components. In addition, the workshop

was designed to continue to facilitate communicati on and scientific interactions across disciplines

(e.g., epidemiology, toxicology, atmo spheric science, monitoring, risk/exposure assessment) to

improve the availability and inte rpretation of air quality monitori ng data for air pollution health

studies dependent upon the national networks.

The impetus for these two meetings was the growing recognition that current and future

changes to the air quality monitoring system could significantly affect ongoing and future

epidemiology research. This research serves as a foundation for EPA’s reviews of the NAAQS. Yet

resources at the Federal and State/local/Tribal levels for air pollution monitoring continue to

diminish, while increasing demands (such as poten tial expansion of the lead ambient air monitoring

network) tied to various asp ects of NAAQS compliance continue to grow. Prominent health

researchers have increasingly que stioned EPA’s commitment to health research in planning its

monitoring programs, while the State and local monitoring expe rts who design and operate the

monitoring programs wonder why some current data resources are no t fully or properly accessed to

explore opportunities to address some of the questions that are impor tant to the health researchers

with existing data sets. Clearly, improving the understand ing of the objectives/mandates of each of

these communities and fostering collaborative effo rts between these communities is critical to

moving forward in a positive manner.



# W orkshop Structure, Objectives, and Outline of Session Summaries

T he April 2008 workshop began with introduc tory remarks by EPA’s National Program

Director for Air Research, Dr. Dan Costa, and by senior OAQPS managers, Ms. Lydia Wegman and

Mr. Richard (Chet) Wayland, expressing their suppor t for this effort. Dr. Morton Lippmann from

New York University highlighted successful resear ch that has benefited from collaboration among

air quality experts and health researchers. Thoughtful discussions centered around five specific

panel sessions, each facilitated by two co-chairs (one EPA a nd one non-EPA representative),

addressing the following topic areas:

3 

# See http://www.healtheffects.org/AQDNov0 6/AQDWorkshop.html for more information.

4 

# The workshop agenda and list of participants is included in Appendix A.

# December 2008 3  Session I: Elemental and Organic Carbon Measurements

 Session II: Accessing Ambi ent Air Monitoring Data

 Session III: Ambient Air Monitoring for Health Research

 Session IV: Thoracic Coarse Particle Co mponents and Potential Public Health

Impacts

 Session V: Ambient Air Monitoring Rea lities – EPA/State/Local Perspectives

T he primary workshop objectives included:

 To reexamine and assess progress to date on key issues identified at the earlier HEI/

EPA-sponsored workshop and in follow-up conference calls with the PM Research

Center Directors, HEI National Particle Component Toxicity (NPACT) Principal

Investigators, and other researchers.

 To discuss specific recommendations for concre te steps that EPA a nd other organizations

could take in the ambient air monitoring pr ogram to advance health research for the

criteria air pollutants.

 To seek constructive feedback on five draft “white papers” 5 

# developed to aid in a

common understanding of the issues under discussion. These draft white papers are

included in Appendices B through F of this draft document.

T he summaries of the five workshop sessions presented below include:

 Session overview,

 Panel members,

 Major points identified by the workshop participants, and

 Recommendations

o Presented at the workshop and/or

o Developed by EPA staff base d upon the workshop discussions



# Initial Successes and Next Steps

T his workshop was a major step in a series of interactions to foster improved long-term

communication between air quality e xperts and health researchers. The air program has continually

emphasized integration across disciplines, labs and EPA programs. Although this requires

significant investment of time and ef fort for all involved, we believe su ch an investment is necessary

to ensure that the ambient air monitoring program offers, and health researchers use, the best and

most appropriate data possible to support the health rese arch that serves as a foundation for EPA’s

NAAQS reviews. While follow-up from this work shop continues, there are already demonstrable

outcomes from the efforts involved in planning, as well as holding the April workshop. A few

examples of initial successes include:

 Monitoring staff, in EPA and State/local ag encies, are becoming aware of the need for

daily measurements of PM components and ha ve expressed willingness to save filters

used for daily measurements of PM 2.5 

# mass so that they can be used to analyze PM

components for health researchers.

5 

# The draft white papers presented relevant background information and critical issues, opportunities for improvement

including draft EPA recommendations for po ssible short- and long-term activities, an d, as appropriate, charge questions

to stimulate discussion at the meeting.

# December 2008 4  Science to Achieve Results (STAR) grantees voluntarily analyzed data sets to help

determine whether changes to the measurement method for organic carbon would affect

the findings of ongoing epidemiological studies.

 Based on information they received from ai r quality experts at the workshop, STAR

grantees have acknowledged making changes to the designs of their health studies that

will improve validity of results as a result of better information on spatial variability of

PM components.

 OAQPS monitoring experts and ORD epidemio logists and exposure scientists are

working together to examine the covarian ce of specific PM components (e.g. metals)

across various cities to develop a network of sites for refined epidemiological study.

 ORD’s National Center for Environmental Res earch has conducted a preliminary survey

of EPA-funded health researchers to identify specific ambient monitoring sites that are

being used in current epidemiological studies 6 

# . This information will be useful to State

and local air agencies as they consider any fu ture changes to their monitoring networks.

A draft of this document was distributed to the workshop participants for review and

comment. This final summary document incorporat es the comments that were received. In

addition, EPA has identified additional next steps that will be taken, including:

 Stratifying the recommendations in this documen t as to their feasibility and prioritizing

actions to be taken. These include providing important input into the strategy for the

revised monitoring network (NCore 7 

# ). EPA’s ORD and OAQPS will work together to

facilitate the incorporation of these reco mmendations into both short- and long-term

monitoring strategies and leveraged program plan s. This will include EPA staff briefing

and receiving direction from senior ma nagement during planning cycles for both

monitoring network design and health research planning.

 Implementing data access improvements and co mmunication tools as soon as possible to

prevent disruption of data streams, loss of important monitoring sites, and developing a

clearinghouse for other datasets not readily fo rmatted to the Air Quality System (AQS)

data system.

 Requesting periodic consultations on the e nhanced monitoring program with the Clean

Air Scientific Advisory Committee (CAS AC) and its Ambient Air Monitoring and

Methods (AAMM) Subcommittee.

6 

# See Appendix G.

7 

# See http://www.epa.gov/ttn/amtic/ncore/index.html for more information on the NCore Multipollutant Monitoring

Network.

# December 2008 5 

# SESSION I: ELEMENTAL AND ORGANIC CARBON

MEASUREMENTS

B ackground/Objectives

E PA has made changes in the urban Chemi cal Speciation Network (CSN) carbon sampling

and analytical protocols for measurement of partic ulate carbon in order to address inconsistencies

between the procedures previously used in that program and the rural Interagenc y Monitoring of

Protected Visual Environments (IMPROVE) program. Health researchers have expressed concerns

about this methodological change and potential impacts on monitori ng data that are used for longterm time-series analyses. The session objectives were to:

 find ways to minimize disruption to epidemio logical studies, both current and future,

 determine the extent of measurement change/error that is problematic,

 determine which of the CSN changes are of most concern to epidemiological studies,

 assess whether past and planned measur ement comparisons are adequate, and

 consider how blank filters and sa mpling artifacts should be handled.



# Session Overview

This session contained two components: (1) a series of factual presentations on the

measurement methods, the changes and/or erro rs that may occur, and the importance of

carbonaceous aerosol sampling to the health rese arch community and (2) a panel discussion to

address approaches that can be used to assess potential types of measurement error, needed

measurement comparisons, impacts on epidemiologica l studies, and additional steps necessary to

identify and address information gaps.

T he presentations included:

 Overview and Introduction to Key Issues ---Venkatesh Rao (EPA) and Barbara Turpin

(Rutgers University)

 A Health Researcher’s Perspective: What’s so Special About Carbon? ---Ed Avol

(University of Southern California)

 CSN Carbon Monitoring Changes and Issues ---Joann Rice (EPA)

 Carbonaceous Aerosol Sampling Artifacts in the National Monitoring Networks ---John

Watson (Desert Research Institute)

 Transitions : Relating “Old” to “New” Methods ---Warren White (University of

California-Davis)

 Predicting Carbonaceous Species Con centrations with Partial Least Squares ---Philip

Hopke (Clarkson University)

 Impact of Method Transiti ons to Health Research ---Michael Hannigan (University of

Colorado-Boulder)

 Air Quality Monitoring: Perspectives from East and West ---Dirk Felton (NY Dept. of

Environmental Conservation)

M embers of the discussion panel included:

 Venkatesh Rao, co-chair, EPA, OAQPS

 Barbara Turpin, co-chair, Rutgers University

 Ed Avol, University of Southern California

# December 2008 6  Michelle Bell, Yale University

 Judith Chow, Desert Research Institute

 Neil Frank, EPA, OAQPS

 Philip Hopke, Clarkson University

 Michael Kleeman, University of California-Davis

 Allen Robinson, Carnegie Mellon University

 Warren White, University of California-Davis

This session provided a good forum for the excha nge of information among diverse interests

in monitoring, analysis, and health impacts. Th e panelists and those who spoke up from the floor

shared the view that the imp act of measurement changes on health research is unknown and

complex, as is how much detail is needed to be tter understand the impact on epidemiological studies

and resulting correlation s with health effects. There wa s also agreement among those speaking

about a need to: (1) collect more information fr om collocated measurements for an extended period

of time at multiple sites; in order to (2) better document uncertainty, and associated differences

between elemental carbon (EC) and organic car bon (OC) measurements for the new and old

methods. Spatial location and source dependent differences in monitoring sites are important

considerations, as are potential differences by seas on. Specific action items were not identified at

this session, but there was a general consensus am ongst the speakers about the proposal (see below)

for more extensive co-located mon itoring, and several researchers called for such analyses in a wide

range of locations and seasons. Little discussi on took place of other re lated issues that had

previously been identified in the agenda (this in cluded how to handle artifacts, how to handle field

blanks vs. back-up filter measurements, and whic h measurement errors are most problematic for

epidemiological studies). A dditional background information is provided in Appendix B.



# Major Points Raised by Participants

General

 Health endpoints are affected by the physical , chemical and toxico logical properties and

attributes of carbon-containing particles as well as by the emission sources represented by the

air quality measurements. These characteristic s are not routinely m easured, and currently

can only be inferred—very indire ctly—from the relative propor tions of EC and OC. The

reported proportions of EC and OC are likely to change as a result of the changes in the

measurement protocol; this coul d be more important in assess ing the impact on health than

individual uncertainties in the OC and EC measurements.

 Changes made in the CSN carbon measurements can be documented, but sampling artifacts

(organic vapors adsorbed within the filter) are still being expl ored. Charring of these vapors

within the filter is the main cause of di fferences between transmittance and reflectance

corrections for OC charring (Chow et al., 2004 Relating the results of “old” and “new”

methods is ongoing. The co-loca tion of old/new monitors can provide information important

to understanding the nature of changes in measurements.

 In the past, EPA used several samplers in th eir chemical speciation network, which resulted

in good agreement for EC, but poor agreement for OC and total carbon (TC) – which was a

function of the differing sampling flow ra tes and having no good way to address the

sampling artifacts. In the future, one sample r that is IMPROVE-like will be used for CSN

with a higher flow rate, smaller filter, back-up quartz filters, and better field blanks (this will

# December 2008 7 likely ensure uniformity of the OC measurements, but more work will likely be needed to

understand what is actua lly being measured).

 The change in the analytical protocol will change the OC-EC split in some cases, yielding

more reported EC and less reported OC. The an alytical change is not expected to change

reported TC. The changes in sampling protocol will affect the sampling artifact, and thereby

reduce reported TC and OC. The sampling change is not expected to ch ange reported EC.

 Hannigan et al. [2008] suggest that in the DASH (Denver, CO) study, EC would remain

significant as an indicator for health endpoints. Of course, Denver is only one location in

space, and generalizations cannot be made about the health eff ects of EC until more studies

are completed.

 For considering impacts of PM on health, measur es of bias and of unc ertainty are both

important in determining health outcomes.

 There is a need for semi-continuous OC/EC me asurements as well as other PM chemical

components. As important as the increased temp oral resolution that wi ll result from use of

semi-continuous methods is the affordability of these measurements (daily (and shorter

interval) sampling at multiple sites becomes more f easible). This can be important for better

understanding sources of carbon since more detaile d spatial and temporal information can aid

in source attribution studies. The shorter sa mpling times associated with semi-continuous

instruments also produce samples with much smaller variation in sampling conditions (good

in terms of minimizing the poten tial for redistribution between th e gas and particle phases).

 In addition, there currently are sites with S unset semi-continuous OC/EC analyzers, McGee

aethalometers, and Thermo-Scientific MAAPs operating through the transition period and

beyond. Some researchers suggested that the loca tions of these analyzers at sites important

for epidemiologic studies (cities where health effects have been shown) and at other

important sites should be identified so that th e usefulness of these data for epidemiological

studies and for “harmonizing” efforts can be identified. However, the Sunset Labs

instrument collects material at a somewhat hi gher than ambient temperature, like the TEOM

does. Thus, Sunset Labs’ OC values may be somewhat smaller than those made at ambient

temperature. Others noted that health resear ch should not be limited to the locations of ongoing studies due to the many st udies that are national in de sign and the need to understand

regional variation in health effects.

 One presenter indicated that the sub-fraction measurements of OC and EC made in the

IMPROVE and new CSN protocols can also add valuable inform ation to source attribution

studies. However, low temperature (i.e., volat ile) OC1 and OC2 fractions are most sensitive

to temperature changes during the analysis and during sample handling (Chow et al, 2007,

Dillner et al., 2008).

 The type of measurement error that is most important to a specific epidemiological study will

depend on the study design, and on the scientific questions it aims to address (e.g., acute

versus chronic effects). In othe r words, there is no single factor or set of factors that is the

critical need for epidemiological researcher s. The impact of measurement changes will

# December 2008 8 affect various epidemiological studies differently, depending on their design. This issue

needs to be sorted out and discussed further.

What types of measurement error are pr oble matic for epidem iologic studies?

 All types of measurement errors are of potentia l concern. There is a need for a qualitative

understanding of what the measurement error is comprised of, and how this might vary

spatially. The analytical measurement error of the monitor is usually much smaller than the

measurement error associated with using a centr ally located monitor to represent an entire

community, particularly when evaluating pollutant s that are measured on ce every three or six

days and in assessing pollutant s that are heterogeneously dist ributed in the ambient air.

Measurement error clearly matters when eval uating epidemiological evidence, but for timeseries analyses, most of measurement error is Berkson, and hence does not include bias, just

reduced power. The way to solve that problem is with more data, which again points to the

need for daily measurements.

 Changes in carbon components (bulk OC and EC ) are important, as are changes in the

percent measurement error of the components. Are there differential errors in EC and OC?

We need to define “error” better.

 Representativeness of sites is affected by spatial variability a nd by source types.

 Balance can be attained by a central PM 2.5 

# speciation monitor plus sa tellite sites (with lower

costs) that indicate how representative the info rmation collected at the central site is (and

address how spatially divergent some EC/OC and other components are). Satellite sites must

be based on lower-cost methodologies, for exam ple, should optical measurements from

Teflon filters be considered? Note: panelist s did not address how we can be certain that

relationships between “referen ce” and “cheap” methods observed at central sites will be the

same at satellite sites.

Are past and planned measurement comparisons adequate?

 In evaluating the transition between carbon monitoring methods, workshop participants

voiced concerns that the current process to c onduct two months of measurement comparisons

is too limiting, since seasonal variability is im portant; there is a need for more data to

compare the different methods and inform the epidemiological resear ch. There are 6 colocated CSN/IMPROVE sites ongoin g (as identified in the draft White Paper for Session I,

see Appendix B) and more discussion of how thes e could be used would be helpful. It is

unlikely that we will be able to afford one year’s worth of co-location at every site converted.

So, it’s important to specifical ly know where longer-term comparisons are required for health

research or to know how to generalize from a small set of locations to the larger network.

(see next bullet as well).

 It might be useful to consider a whole year of data with less frequent measurements; also

consideration of a limited number of samples at more individual sites would be helpful. As

such, there is a need to know what kinds of locations are of most importance for health

research studies. Some suggested that a wi de range of locations representing different

particle mixtures and sources would be useful.

# December 2008 9  There is a need to better unde rstand uncertainty information. Proportional changes in EC &

OC may create proportional ch anges in epidemiological studies; if changes are not

proportional for different components, then there may be a problem.

 In selecting sites for possibl e increased co-location of old and new measurements, the

influence of variations in sources needs to be considered. These could include sites

influenced by wood-smoke, mobile sources, large stationary sources, and a mix of all

sources.



# Recommendations/Actions for Consideration

Suggested by Workshop Participants:

 There was general consensus on a proposal to run co-located “old” and “new” CSN

measurements for a whole year; with cons ideration of potentially measuring every 6 th 

# (or

12 th 

# ) day at 6 – 9 sites. Many rese archers felt it was important to ensure that the specific sites

include those currently being used for epid emiological studies where associations or

relationships with OC or EC are being studi ed, although many other researchers noted the

need for selection of sites that represent a wide array of locations and particle mixtures, as

noted below. Inclusion of locations where carbon has been found to be associated with

health effects may allow us to more easily determine if the measurement change has an

impact on their health impact findings. Po tential sites include Seattle (Beacon Hill),

Rubidoux (CA), Bronx (New York City), Atlant a, Detroit, Cleveland, Denver, and an

additional southern location.

 Several individuals supported selecting site s based on source distribution/mix, not just ongoing or planned epidemiological studies. Using this approach, consideration could be given

to variations in soils, industries, and mob ile sources in the sour ce distribution. A site

selection process could incorporate both this concept and that listed above, to include

locations of ongoing studies.

 There was also general consensus that this pr oposal be reassessed af ter a year of data

collection in order to evalua te whether a longer study period or more sites are needed.

 A limited number of individuals al so supported an investigation of the availability of semicontinuous OC/EC data and its potential role in “harmonizing” old vs. new carbon

measurements.

 A limited number or participants also supporte d achieving better spatial resolution by

implementing a main site and satellite sites for species with large spatial variability, to better

characterize population exposures.

Developed by EPA Staff Base d on Workshop Discussions:

 Continue UC-Davis (January 2008) “Carbon Summit” process:

o Selected archived samples from IMPROVE and collocated IMPROVE/CSN network

sites will be analyzed by the new IMPROV E carbon analysis methodology to develop

# December 2008 10 additional data, which will be used along with the routine data collected by the two

networks to better characterize the rela tionships between the various old carbon

analysis methods and the new IMPROVE analyt ical method (i.e. the approach that is

used now for both networks).

o Changes will be made in the operations of both IMPROVE and CSN networks to

increase the number and utility of carbon bl anks and backup filters collected in order

to further investigate and if possible develop more credible approaches to adjust for

sampling artifacts.

o Continue to conduct periodic assessments of the quality and comparability of PM

carbon data from both networks and over time (i.e. as methods have changed) paying

particular attention to data from continue d operations of collocated monitoring sites.

The results of these efforts to be the subject of possible future joint network

workshops, publications and web postings.

 Further evaluate the performance of the Suns et EC/OC and other continuous analyzer and

determine the role of continuous measurements to support daily monitoring and harmonize

old and new CSN. Filter-based measurements will still be needed, but can be collected on a

much reduced frequency. This idea can then be extended to other semi-continuous

instruments, like the Aethelometer, MAAPs, and photoacoustic spectrometer which measure

light absorption, strongly correlated with EC.

 Make a more targeted request (with much more specificity than was done for this workshop)

to health researchers to help us better understand the sensitivity of their results to changes in

carbon measurements.

 Further discussion of the topic “optimal OC artifact correction for large networks” is

warranted.

# December 2008 11 

# SESSION II: ACCESSING AMBI ENT AIR MONITORING DATA

Background/Objectives

EPA’s Air Quality System (AQS) is designed to collect and store ambient air monitoring

information. EPA recently introduced the AQS Data Mart to facilitate ac cess to this monitoring

information. The AQS Data Mart is a generic “retri eval” tool that provides the ability to query any

information, but it does not provide significant data expl oration or analytic capabilities. These

capabilities are left to the “analy tical” tools. Various analytical to ols, or interfaces, are available

including the Health Effects Institute’s (HEI’s) Air Quality Database, which focuses on ambient air

measurements of PM 2.5 

# components and gaseous pollutants at and near STN and SLAMS sites.

This session focused on data access issues and how to help health research ers obtain monitoring data

for fine particle components and othe r critical pollutants more easily.



# S

ession Overview

I n general, access to ambient air monitoring data to support health research/ assessments falls

into four general categories:

 epidemiological studies,

 exposure/risk assessments,

 public health surveillance, and

 health impact assessments

K eeping these broad categories in mind, and und erstanding that the goal is to provide a

framework for delivering consistent, well-documente d monitoring data to user s including the health

research community, the broad topics discussed in this session included:

 To what key data do health researchers need access?

 What formats are most useful?

 What kind of access is most appropriate for health research uses?

 How can the overall data context be improved and preserved in delivering the data to users?

M embers of the discussion panel included:

 Michelle Bell, co-chair, Yale University

 Bryan Hubbell, co-chair, EPA, OAQPS

 Sara Adar, University of Washington

 Kaz Ito, New York University

 John Langstaff, EPA, OAQPS, Health and Environmental Impacts Division

 Nick Mangus, EPA, OAQPS, Outreach and Information Division

 Richard Poirot, Vermont Department of Environmental Conservation

 Betty Pun, AER

 Rich Scheffe, EPA, OAQPS

The panel members were asked to be specific in th eir data needs, e.g., to clearly identify what

specific documentation is needed, rather than ju st providing general recommendations to provide

“more documentation.” A special focus on versioni ng of the data was also recommended for the

discussion.

# December 2008 12 To lead off the session, two introductory pres entations were provided by Nick Mangus and

Rich Scheffe of EPA. Nick Mangus provided an overview of the draft white paper entitled “Access

to EPA’s Air Quality Data for Health Researchers (see Appendix C),” while Rich Scheffe provided a

summary of the outcomes from a recent EPA-spons ored Air Quality Data Summit, held in March

2008. 8



# Major Points Raised by Participants

Several persons mentioned the high value of EP A air pollution datasets, and noted that access

has greatly improved over the years. Several broad themes emerged from the discussion:

Versioning

T he most important theme seemed to be vers ioning of the EPA datasets. Several people

expressed concerns over the curre nt system, where researchers can download different datasets

without realizing they differ. Curre ntly, there is no way of knowing whether data files have changed,

or merely been updated. This causes problems with reproducible research a nd with researchers not

knowing whether to get new data due to corrections being made. It also is an issue when researchers

update an epidemiological analysis with a new year of data; they need to know if there have been

changes in the air quality database for previous years as well. It was noted that changes to data

include not only updates of new data , but corrections to old data, ev en 10 years previous. Multiple

options to address this issue were discussed:

 time/date stamp every observation

 version numbering (e.g., Version 10Jan08.7, etc.)

 maintenance of snapshot datasets that are static

 notice of changes to datasets

 maintenance of datasets used by researchers

Concerns were raised regarding the cost and storage of some of these options.

Data Availability

T he draft white paper included in Appendix C provided background information for this

session. This paper described and contrasted the data available through the AQS Data Mart and the

HEI Air Quality Data Base, and other sources of in formation. Specific issues discussed related to

data availability included:

 EPA vs. other organizations’ role s in providing access to data. Several participants

expressed support for HEI or some other orga nization outside the EP A continuing to support

analytical tools, or interfaces, to disseminate air quality data “packaged” with other relevant

data for health researchers

.

 Information previously available thro ugh AQS that is no longer available . There were some

concerns expressed that certain types of data, e.g. the TEOM data had been removed from the

AQS archive website. EPA clarified that TEOM and FRM data were different and that the

TEOM data were removed so unknowing users would not incorrectly compare it to FRM

data. EPA has mitigated this issue by changing how we identify PM 2.5 

# data and will

8 

# See http://wiki.esipfed.org/index.php/Air_Quality_Data_Summit#Documents

.

# December 2008 13 reconsider putting the TEOM data back on the we bsite. It was noted that some local TEOM

data are being adjusted to ma tch FRM data as part of the joint CDC/EPA PHASE project.

 Additional information for monitor locations . It was suggested that photographs of the

monitoring station be easily accessed and ke yhole markup language (KML) files be created.

While the land-use around monitors could change , this would provide researchers with some

guidance on the monitor location.

 Information from other sources. The concept of a data cl earinghouse providing links to nonEPA data sets was suggested, for example, access to additional State, local, and tribal air

quality data that are not entered into AQS (e.g., AirNowTech data), special studies data,

Supersites data, etc. EPA clarified that th e Supersites data are available on the NARSTO

website. However, workshop participants made it clear that the data on the NARSTO site is

not in a format that is comparable to the FR M data available on AQS. Workshop participants

noted that it would be helpful to have all the air quality data in one location, and provided in

a similar format or have scripts for reading da ta from different formats into common software

programs like SAS, R, or S-Plus. The need to leverage existing IT capabilities to gain

efficiencies in creating a da ta clearinghouse was highlighted. Please see discussion of this

issue below in the section Acti ons Items Under Consideration.

 Requesting data from State, local, tribal air agencies directly . EPA maintains a listing of

regional, State, and local level air quality da ta contacts available on its website. Workshop

participants noted that when going to State cont acts for data, some provide data faster than

others, and often in very different formats (sometimes still providing paper copies only). It

was suggested that it would help State/local ai r agencies if health researchers would share

final products (e.g., health studies ) with these agencies so they could be better informed

about how the air quality data are used and future research needs.

Data Quality

S ome mention was made of data quality, and the need for res earchers to be aware of data

quality problems, even in EPA-vetted datasets. Examples provided included:

 Quality and accurateness of existing metadata are varied, metadata can be wrong, and that

there are often not even flags to note suspicio us outlier values that might result from a

misplaced decimal. For example, if ozone data at low levels are a de cimal place off, this

could play a major role in studies of thre sholds and effects at low concentrations.

 Incorrect identification of latitude/longitude has been noted for a subset of monitor sites as

well as a high frequency of missing data in so me of the critical fi elds (e.g. no monitoring

objective listed for some sites). EPA notes th at all data in AQS passes the EPA’s QA checks

for the tests we need for regulatory purposes. This may not be sufficient for some scientific

applications. All metadata (and data) are ultimately controlled by the submitting

State/local/tribal agen cy and EPA cannot change it. So improving quality is a community

effort. This is another reason why researcher s might want to engage the agencies whose

monitors they are using for studies.

 It was recommended that the data be stored at the finest spatial and temporal granularity

possible, and then aggregated up as needed by the user.

# December 2008 14 User Friendliness and Documentation

It was noted that some data users are novices , some are expert, and each needs different

levels of data access and, therefore, would have different needs. Many participants voiced the

opinion that epidemiologists tend to be “very opportunistic,” making use of whatever air quality data

are provided. As such, epidemiologists will utili ze available data, but woul d like more guidance as

to what uses of the data are va lid and/or appropriate (e.g. provis ion of data on the percent valid

observations, monitoring objectives, monito r scale, use of flagged data).

The need to increase user friendliness was di scussed, such as with the ability to download

specific States’ data rather than data for the whole US for some data sources. Within the discussion

of user friendliness, there was a general consen sus that documentation needs to be improved. In

addition, documentation is perhaps a bit scattered throughout various EPA sites. The point was made

that "user-friendliness" is dependent on the needs a nd skill level of the user, so that no standard form

will be perfect for all users.

The issue is that it takes more effort to find and interpret documentation of the data than it

does to obtain the data; and missing de scriptive information can be deva stating to an analyst. There

are many attributes of the data th at are not well understood by us ers (metadata is not owned by EPA

and therefore can be outdated or data can be upd ated by the owner at any time; EPA data storage

labels are in flux with regulation and policy ch anges; etc.). Users having a single site for

documentation will greatly reduce the lik elihood of incorrect interpretation.

Secondary Data

The panel discussed whether non-air pollution data would be useful to include in the air

pollution datasets. Examples were weather, land -use, and census data. Some people thought this

would be useful. Others thought this was less useful, given that such data are available elsewhere.

This seemed to be far less of an issue than th e versioning. Thus, resources might better be spent on

the versioning issue than on incorporating secondary data.



# Recommendations/Action Items for Consideration

T he recommendations listed below include item s discussed at the workshop as well as

additional recommendations developed by EPA staff based upon the workshop discussions.

Data Versioning

 Explore options for adding the date (and time) of last modification to all data measurements

in AQS (and the AQS Data Mart).

N otes: Data in AQS can change at any time. Generally, EPA limits the ability of data

submitters to change data for only the last few (3-5) years. However, we do open time windows

where older data can be changed. There are implic ations to the submitter for changing data and the

volume of older data changes is low, but they do happen. Researchers need to know if these data

changes affect their analyses. Adding a date-of- change to each measurement would allow a data

user to query the space and time domain of their in itial query to see if any data had changed. EPA

would not keep a record of the change, but new or changed values would be i ndicated with their date

of creation/update. It would still be incumbent on the user to maintain the original data set and

compare changed data to assess possi ble ramifications. Any change to a measured value or metadata

(like the monitoring method or uncertainty) w ould trigger the date stamp to be updated.

# December 2008 15 Data Availability

 Continue to encourage HEI and other organizatio ns support of analytical tools and interfaces

to make the AQS data more useable for the he alth research community. Follow-up with HEI

regarding the plans for con tinuing to support the HEI Ai r Quality Data Base.

 Explore options for creating and mainta ining a Clearinghouse of non-EPA datasets

T here are a lot of air quality data which are not in AQS. Some of these data have been

collected by State and local air pol lution control agencies and have not been reported to AQS for one

reason or another (e.g., continuous data are collected on a minute ba sis, and EPA only requires that

hourly averages be submitted; the information does not pass the regulatory quality assurance

requirements, even though the quality may be high e nough to fill a gap in a rese arch time series; etc.)

Another source of data that EPA doe s not have is data collected from special research studies run by

academic or State/local public hea lth organizations. This is gene rally high density data (in space

and/or time) used to better understand the variab ility of measurements over smaller scales than

regulatory monitoring requires. Even the other Fe deral air quality storehouse, AirNow Gateway will

have State/local/tribal data that does not meet the policy requirements of AQS. Having a single

location as the starting point for a dataset clearinghouse will dramati cally help improve the inventory

of available air qua lity information.

 Location of Monitoring Sites

. Make keyhole markup language (KML) files with AQS air

monitoring site locations shoul d be made available.

K ML files describe locations and can be used by most modern map-dr awing applications.

Including links within the KML file will allow us ers to download the actual measurements. Making

these available would better allow people to visu alize the monitoring network they would also

confirm the monitor location when the listed latitude and longitude were suspect.

 Develop new content and format for data on AQS archive page . Request feedback from key

users on how to improve the AQS “Data Arch ive” (data download) page on EPA’s website

and update accordingly.

U sers complain about the limited number of para meters available, the frequency of updates,

the format, and the size of the files. If agreemen t can be reached on how to improve these problems,

EPA could make the appropriate changes.

 Continue Data Summit follow-up to provide a system-of-systems for data integration and

display. OAQPS will provide base data from Federal monitoring networks via the AQS Data

Mart.

T he purpose of the data summit work is to make use of “interoperability” frameworks like

GEO (Group on Earth Observations) for system devel opers to identify what part of the data valuechain they belong in and successfully connect wi th those up- and down-stream from them. The

value-chain has roughly these divi sions: base data provision, meta data provision, data integration,

data processing (aggregation), da ta visualization, and communicati on. It is expected that the

architecture standards board convened as a follo w up to the Air Quality Data Summit will adopt

specific recommendations on web services (machine que ries) of data that all participating systems

should support. If all systems agree to the web services, data integrators and interface builders

would have a much easier time obtaining data from multiple systems. For example, the HEI Air

# December 2008 16 Quality Database could be updated more freque ntly, and include more information about the

progeny of the data.

 Explore opportunities to encour age discussions between health researchers and State/local

monitoring experts. For example, encourage he alth researchers to share published results

with State/local monitoring community, specif ically studies that use monitoring data

collected by the State/local air ag encies and encourage participati on of a variety of experts in

regional and national meetings (e .g., health researcher participa tion in monitoring meetings).

User Friendliness and Documentation

 Explore ways to highlight if a significant change in AQS ha s occurred. For example, EPA

could provide an explanation on the AQS website so that regu lar AQS data users would be

aware and know where to go to access the data.

 Use the IMPROVE metadata as a model fo r developing AQS metadata, including the

IMPROVE “Data Advisories” noting any ch anges or issues with the data.

 Request that supplemental data be presente d in the same format as primary data.

# December 2008 17 

# SESSION III: AMBIENT AIR MONITORING FOR HEALTH

RESEARCH

Background/Objectives

The purpose of Session III was to provide a disc ussion among a panel of health and exposure

researchers who use ambient air monitoring data in their studies and to highlight the value of these

data for the continued progress of research linki ng particulate matter (PM) sources, exposure and

health effects. This session was intended to stimul ate a discussion of the issu es and identify creative

solutions for the provision of da ily speciation data in key locati ons while working within current

resource constraints faced by local , State and Federal air quality ag encies. For example, resolving

key policy questions about health effects of spec ific size fractions, components and gaseous copollutants related to PM, requires more intensive temporal and spatial air quality data than are

currently available. Background information for this session is included in Appendix D.



# Session Overview

The panelists discussed the major sources of uncertainty that must be considered when

designing and interpre ting the results of studies of ambient PM mass, components and health. A

number of important research questions were raised in this context that could be addressed if some

changes were made to monitoring networks in some locations. If daily measurements of PM species

were available in informative locations, studies would be better designed to detect the relative

importance/toxicity of PM species and size classes. Studies designed to detect health effects of shortterm exposure would develop more precise and valid exposure estimates and w ould be better able to

generate hypotheses that addres s possible mechanisms for the observed health responses to PM.

Although the panelists primarily focused on issues as they relate to epidem iology studies, the point

was made that toxicological assessment of ambi ent particles must be generalizable to human

exposure and be interpretable in re lation to epidemiological results.

Members of the discussion panel included:

 Barbara Glenn, co-chair, National Cent er for Environmental Research, EPA

 Joel Schwartz, co-chair, Harvar d School of Public Health

 John Godleski, Harvard Sc hool of Public Health

 Patrick Kinney, Columbia University

 Lucas Neas, National Health and Environmental Effects Research Lab, EPA

 Roger Peng, Johns Hopkins University

 George Thurston, New York University

 Jay Turner, Washington University in St. Louis



# Major Points Raised by Participants

Uncertainties

E pidemiology studies must deal with several sources of error in es timating personal exposure

to ambient PM. These include:

 Instrument measurement error . Is the monitoring technique adequately measuring pollutants

at the site of the monitor? The observation wa s made that while exposure measurement error

# December 2008 18 at the monitor introduces uncertainty in estimates of ambient concentrations, this error is

smaller than other measurement e rrors in epidemiology studies.

 Spatial variability . How geographically homogenous are the particle concentrations in the

cities where we are conducting epidemiology st udies? Is the concentration of PM species

measured at the monitor representative of th e ambient concentrations experienced by human

populations living and working in the city?

 Temporal variability . Monitoring schedules of every third or sixth day results in data gaps

that severely limit the ability to explore variat ions in the time lag of response for different

PM components. Different PM components are belie ved to target different biologic pathways

in generating health responses and the flexibility to explore a variety of time lags between

exposure and outcome is necessary to reveal thes e effects. In addition, health events relevant

to days with missing air quali ty data must be excluded, thus reducing sample size.

Alternatively, air quality concentr ations may be interpolated in some manner which increases

uncertainty in exposure estimates. Interpolation re sults in a reduction of daily variability in

PM concentration data with re sulting loss of statistical power , and increases the correlation

between concentration es timates for PM components in data sets. This inhibits efforts to

differentiate species-specific toxicity.

 Other errors in estim ation of personal exposure based on ambient measurements

. Infiltration

of PM components indoors, time-location duri ng the day etc. The comment was made that

use of air conditioning during the summer months has a large effect on health models for

certain geographic locations.

Time scale

Research has shown that the health effects of air pollution ex posure on one particular day are

spread out over several subsequent days. Therefore, the effects (e .g., death) observed on one day are

the result of air pollution that occurred during a period of days on and before the deaths were

recorded. Epidemiologists need to use pollution concentrations on a defined number of days before

the date of an effect to study hypotheses regardin g the relevant time between exposure and effect.

These time scales likely are different for different PM components and different health outcomes

(e.g., heart attack, asthma etc). The relevant time lags for a particular outcome also may vary by

season and location as well. The study of time lags informs mode of action.

In the absence of daily speciation data, PM co mponents with a very acute or immediate effect

(short-lags) on health would have less measurement e rror and thus an apparent ly stronger association

with health outcomes than PM components with more delayed effects spread over several days

(long-lags). This differential error could lead to a misattribution of PM effects to specific sources.

Monitoring on a daily basis is needed in a reasonab le number of cities to ev aluate this variation.

Statistical Power to differentiate between components

T he panel listed several key factors that infl uence the statistical power of an epidemiology

study. These include:

 Number of daily health events – need large population size.

 Variability in estimated exposure (indicated by variation in pollutant concentration across

space for long-term cohort studies or change in daily concentration for time-series studies).

We want to maximize variance and minimize covariance.

# December 2008 19  Maximize measurement of concentration variance. Daily speciation measurements in a

location will provide a dataset that documents th e day-to-day variation in concentration that

occurs at the monitoring site. The point was made that concentrations vary a great deal within

a 24-hour period and, therefore, temporal varia tion in PM species within an area could be

better quantified using continuous monitors. Continuous methods also would minimize

concerns about artifacts. Local sources are anot her determinant of variation in PM species

concentrations. Better spatial resolution in the data will be tter account for local sources.

 Minimize covariance between PM components in datasets. Panelis ts emphasized that studies

are not able to differentiate the relative importance of PM co mponents in associations with

health effects if concentrations are highly co rrelated in a study location. To avoid this

problem they recommended that study sites be selected where c ovariance between PM

components is minimized or different. The point was made that meteorol ogical factors are a

key determinant of correlation in daily concentration change for PM components, which

poses analytical difficulties. Toxicology studies will help to sort out relative toxicities among

PM components.

Spatial scales

For time-series studies, if daily change in pollutant concentrati on is homogenous across the

population, then one “central” m onitor will adequately characte rize daily change in ambient

concentration for that city. This assumption needs to be explored at multiple study sites. For longterm cohort studies, better within-city spatial reso lution provides better estimates of annual average

concentrations for individual study members, and increases the variation in exposure data. This

results in an increase in statistical power.

Some panelists emphasized that exposure es timates based on concentration data from one

PM speciation monitor in the middle of the city will not add much information for epidemiology

studies because exposure measurement error for the overall population is too large. Spatial

variability in PM component concentrations is an important issue. Participants also were urged to

integrate models that take into account meteorol ogy and source information over space, such as

CMAQ, into exposure estimation. At the same time, toxi cology studies will have to play a large role

in understanding PM component influences on healt h. Participants were ca utioned that toxicology

studies also are complex, and the use of pur e components in toxicology studies has been

disappointing. It is very difficult to generalize results from these st udies to draw conclusions about

responses to the ambient mixture.

The influence of local sources in the vicinity of a monitor needs to be understood before

those data are assumed to represent exposure for the population in a cit y. One panelist emphasized

that during certain periods of time, local sources have been observed to highly influence ambient

concentrations of a PM component measured by a speciation monitor. The poi nt was made that the

CSN monitors are sited to implement the NAAQS a nd assure compliance, not to support health

effects studies.



# Recommendations

Desirable Attributes of Locations Se lected for Daily Speciation Measurements

T he following location characteristics were su ggested as criteria for selecting a set of

metropolitan areas to support daily speciation monitoring:

# December 2008 20  Population size. This is the most important attribute sin ce the number of daily deaths in a city

is the major determinant of st atistical power of a time-series or case-crossover study. Large

metropolitan areas, including New York City, Los Angeles, and Chicago were proposed.

However, the comment was made that very larg e urban centers, such as New York City, have

characteristics, such as street canyons, that incr ease spatial variability. Other less large cities

with more homogenous geography may be better candidates. Once the population size is

relatively large, resulting in daily deaths of around 20, then other selection factors should

play a much greater role in the select ion of urban areas for additional sampling.

 Different covariance structure between PM species in different cities.

 A variety of sour ce contributions.

 Location of speciation monitor(s) in the city th at minimizes the influence of local sources of

PM.

 Topography and city attributes that increase th e likelihood that one or a few monitors will

characterize daily ch ange appropriately.

 Expertise and support of State and local air mon itoring personnel to collect daily filters and

maintain semi-continuous monitors.

 Existence of additional monitori ng data in that location to su pplement information on spatial

and temporal distribution of PM components and other pollutants.

 Special State/local or academic studies using multiple monitors may have been conducted in

the location to better characterize spatial a nd temporal variability and could be made

available for analysis. FRM filters may have been archived by State/local air quality agencies

and may be available for speciation analyses. Th e existence and availability of these studies

and filters needs to be explored. A panelist commented that these filters are a national

resource and need to be invent oried and kept, not thrown away.

 Consider the impact of weather and seasons, di fferences in behavior that affect exposure.

T he Children’s Health Study in Los Angeles wa s referred to during th e discussion of site

selection for additional monitoring. Twelve co mmunities were initially chosen based on the

hypotheses of interest for PM 2.5 

# mass, the need to obtain a 3 – 5 fold difference in ambient

concentrations, and an emphasis on long-term h ealth effects. Hypothese s concerning different

PM size fractions would result in selection of different commun ities. The design of the CHS was

considered innovative because a monitoring appr oach of 26 two-week sampling periods was

conducted which minimized the number of samples taken while capturing seasonal differences in

ambient concentration.



# A ction Items for Consideration

 Develop a recommendation on the best locations to conduct additional sampling. More

information must be collected to inform se lection of proposed study sites and the minimum

number of locations to conduct additional sampling.

 Agree and prioritize important criteria for site selection.

# December 2008 21 o Analyses and presentation of the correla tion structure between PM components and

between PM components and other pollutants at the CSN speciation monitors. Kaz Ito,

New York University, volunteered to assist with this effort. Analyses are currently being

conducted by EPA’s OAQPS and ORD.

o Identify locations with appropriate data from special studies on daily PM species

concentrations or spatial variability.

o Evaluate the feasibility of analyzing archiv ed FRM filters from specific locations (for

certain components as appropriate).

o Develop a table summarizing relevant information. Information characterizing additional

criteria will be obtained and th e table filled in (ORD, OAQPS).

* 

# Kunzli, N.; Avol, E.; Wu, J.; Gauderman, W.J.; Rappaport, E.; Millstein, J.; Bennion, J.; McConnell, R.; Gilliland,

F.D.; Berhane, K.; Lurmann, F.; Winer, A.; and Peters, J.M. (2006). Health effects of the 2003 Southern California

wildfires on children. Am. J. Respir. Crit. Care Med., 174(11):1221-1228.

Wu, J.; Lurmann, F.; Winer, A.; Lu, R.; Turco, R.; and Funk, T. (2005). Development of an individual exposure model

for application to the Southern California children's health study. Atmos. Environ., 39(2):259-273.

# December 2008 22 

# SESSION IV: THORACIC COARSE PARTICLE COMPONENTS

AND POTENTIAL HEALTH IMPACTS

Background/Objectives

In September 2006, the EPA revised the NAAQ S for PM and amended the associated

national air quality m onitoring requirements. 9 

# As part of the amended monitoring requirements,

EPA finalized a Federal Reference Method (FRM ) for thoracic coarse particles (i.e., PM 10-2.5 

# ), even

though a NAAQS for PM 10-2.5 

# was not adopted. This was done to facilitate consistent research on

PM 10-2.5 

# air quality and health effects and in prom oting the commercial development of Federal

Equivalent Methods (FEMs) (71 FR 61212). The amended monitoring requirements require the

addition of PM 10-2.5 

# measurements at 75 multi-pollutant monitoring sites (National Core or NCore

sites) starting on January 1, 2011. A subset of th ese monitoring sites will in clude speciated coarse

particle measurements. The purpose of this sessi on was to discuss issues related to and relative

priorities for EPA to consider as speciation of t horacic coarse particles is added to the monitoring

networks to support future exposure and health studies.

When discussing issues and prio rities of thoracic coarse par ticle measurements to support

health studies, it is important to acknowledge that we are starting fr om a different place than with

fine particle measurements. This presents both challenges and opportunities. Firs t, while there is an

extensive network to monitor PM 10 

# and PM 2.5 

# , there exists no national network with the specific

intent to consistently and accurately measure PM 10-2.5



# . 10 

# As a result, the amount of PM 10-2.5 

# air

quality data available and associated analys es are available at fewer locations than PM 10 

# or PM 2.5 

# measurements. Second, there have been fewer hea lth studies conducted to i nvestigate relationships

between thoracic coarse particle con centrations and health endpoints, wh ich is due in part to the first

challenge – limited available air quality data. Some health studies have been conducted using PM 10



# measurements in areas where the PM concentrati ons are dominated by thoracic coarse particles.

Other thoracic coarse particle ai r quality and health studies have relied upon data from locations

where co-located PM 10 

# and PM 2.5 

# monitors exist, but there are uncertainties in the consistency of

these data because the protocol for the PM 10 

# and PM 2.5 

# measurements is not usually identical. 11



# Despite these challenges, signifi cant opportunities exist to inform the design of future thoracic

coarse particle monitoring programs and to better harmonize thoracic coarse particle measurements

with the needs of health effect researchers.



# S

ession Overview

T o investigate health effects associated with exposures to thoracic coarse particles will

require an improved understanding of the intra-ur ban, inter-urban, and urba n-rural variability of

ambient thoracic coarse particle concentrations. Key uncertainties associated with intra-urban

ambient thoracic coarse particles concentrations include spatial, temporal, and compositional

variability, while key uncertainties with inter-city and urban-rural comparisons include variability in

9 

# See http://www.epa.gov/oar/par ticlepo llution/actions.html for more information on amendments to EPA’s National Air

Quality Monitoring Requirements.

10 

# U.S. EPA. (2005) Review of the National Ambient Air Quality Standards for Particulate Matter: Policy Assessment of

Scientific and Technical Information, OAQPS Staff Paper (June 2005). U.S. Environmental Protection Agency,

Washington, DC, EPA-452/R-05-005.

11 

# U.S. EPA. (2005) Review of the National Ambient Air Quality Standards for Particulate Matter: Policy Assessment of

Scientific and Technical Information, OAQPS Staff Paper (June 2005). U.S. Environmental Protection Agency,

Washington, DC, EPA-452/R-05-005.

# December 2008 23 composition and temporal differences (e.g., seasonal). Ambient air monitoring networks can provide

insights to address these uncertainties . As a result, general questions that were posed to the panelists

in this session were as follows:

 What is the relative value of thoracic coarse particle speciation at planned monitoring

locations versus additio nal mass measurements?

 What is the relative value of understanding intra-urban versus in ter-urban/rural variability in

thoracic coarse particle mass and composition?

 What recommendations can be made to inform the design of a thoracic coarse particle

monitoring network?

M embers of the discussion panel included:

 Timothy Larson, co-chair, Un iversity of Washington

 Tim Watkins, co-chair, EPA, ORD

 David Diaz-Sanchez, EPA, ORD

 Richard Flagan, CalTech

 Terry Gordon, New York University

 Michael Hannigan, University of Colorado

 Thomas Peters, University of Iowa

 Joann Rice, EPA, OAQPS

 Jamie Schauer, University of Wisconsin

There was a general consensus that thoracic coarse particles are very complex and pose

significant challenges for both air qu ality and health scientists. Thor acic coarse particles differ from

fine particles and, in many cases, pr esent greater challenges. For exam ple, thoracic coarse particles

may exhibit larger spatial and temporal variability than fine particles and the composition of thoracic

coarse particles can vary in rura l versus urban areas. The compos ition of thoracic co arse particles

can also differ from fine particles with introdu ction of biological materials and the increased

importance of metals. In addition, thoracic coarse particles also present new challenges related to

measurement technologies. The current FRM is based on the difference between measurements

taken with co-located PM 10 

# and PM 2.5 

# integrated filter samplers. While this method provides a good

measurement of thoracic coarse pa rticle mass, there is no direct thoracic coarse particle sample

collected. Other methods exist, such as dich otomous or continuous mass samplers, which can

provide valuable information abou t particle composition and temporal variability, but these methods

need to be evaluated further. In addition, the use of emerging passive monitoring approaches may

also provide opportunities for obtaini ng thoracic coarse particle data.

The thoracic coarse particle monitoring pr ogram is still evolving, and EPA’s OAQPS is

seeking feedback and input on thoracic coarse pa rticle network design issues. EPA should apply

lessons learned from the fine particle monito ring program and closely follow ongoing research

efforts, while moving forward with implementation of a thoracic coarse particle monitoring program.

The emerging thoracic coarse particle monito ring program should include continuous monitoring

technologies, where possible, and any speciati on efforts should use consistent methodologies.

Ongoing research may also yield important insigh ts for designing a thoracic coarse particle

monitoring program. The EPA’s ORD recently awarded a series of gran ts to investigate the sources,

composition, and health effects of thoracic coarse particulate matter. These grants integrate

atmospheric measurements with toxicological and epidemiological investigations. ORD’s in-house

research program will also produce relevant research results to consider when designing a thoracic

coarse particle monitoring program. Data from co mpleted field efforts, such as the Detroit Exposure

# December 2008 24 and Aerosol Research Study (DEARS) 12 

# and FRM evaluations, should be analyzed to provide

additional information about the intra- and inter-urban variability of t horacic coarse particles. Also,

ongoing and planned studies, such as the Birmi ngham Saturation Sampling study and Near Roadway

studies 13 

# , will also provide va luable information pertaining to t horacic coarse particles. Finally,

ORD’s in-house health research program includes thoracic coarse particle toxicological studies

integrated with exposure and source apportionment analyses. While these research programs may

produce results to inform decisions regarding thoracic coarse part icle measurements (e.g., methods,

monitoring locations, and components measured), the timing of the results w ill be critical since the

initial thoracic coarse particle measurements will be required at NCore sites on or before January 1,

2011.



# Major Points Raised by Participants

The following questions and the accompanying re sponses summarize the major points of this

session:

What lessons can be learned from the PM 2.5 

# chemical speciation network and applied to

designing a thoracic coarse particle speciation network?

 Monitoring Methods

o Use consistent monitoring methods

o Use continuous methods, where possible

o Evaluate speciation methods now a nd conduct hypothesis driven pilots

 Frequency of measurements

o Consider conducting daily measurements at so me thoracic coarse particle monitoring

locations.

 Archiving filters for future analyses

What is the relative value of thoracic coarse particle ma ss versus speciation measurements?

Initial efforts to monitor thoracic coarse particles should focus on mass measurements to

inform our understanding of spatial and temporal variability. We need to learn more about the

components of thoracic coarse particles and how com position varies across urban and rural areas, as

well as, speciation measurement techniques before making significant investments in speciation

monitoring. There is a significant am ount of variation in thoracic coarse particle toxicity and we do

not know enough to invest heavily in speciated thoracic coarse partic le measurements at this time.

What, potentially, are the most important thoracic coarse part icle components to measure?

Based on toxicology studies, metals , especially soluble metals, ma y play an important role in

effects associated with thoracic coarse particle exposures. In addition, the role of biological

materials in thoracic coarse particle health effects is unclear but it is also pot entially very important.

Analytical challenges limit our health-based hypothe ses. Organics are quite different in thoracic

coarse particles and difficult to measure. Furthe rmore, a significant mass fraction of many thoracic

coarse particle sample s is unknown/unidentified.

12 

# See www.epa.gov/dears for more information.

13 

# .add reference/link

# December 2008 25 What methods are available to meas ure thoracic coarse p articles?

There are several methods availa ble for thoracic coarse partic le measurements and we need

to continue to evaluate these methods for measuri ng thoracic coarse particle s. The current FRM for

thoracic coarse particle is ba sed upon the difference between PM 10 

# and PM 2.5 

# measurements (using

identical protocols and flow rate s). Dichotomous instruments provi de a separate measurement for

thoracic coarse and fine partic les. EPA studies show good agreement between the difference method

and dichotomous measurements for both thoracic coarse particle mass and speciation, although

additional analyses of speciation results from each method would be valuable. There are also

continuous methods (e.g., FDMS Dichotomous TEOM) available for thoracic coarse particle

measurement. In addition, other thoracic coar se particle sampling techniques may present

opportunities for collecting more data for potentially lower costs. For example, the DRUM sampler

may provide speciated size segregated measuremen ts with a reduced operational burden. However,

additional research is needed to evaluate the DRUM (Davis Rotating Uniform size-cut Monitor)

sampler and compare results with other methods. Another promising monitoring approach uses

passive techniques in combinati on with scanning electron microsc opy (SEM) to provide thoracic

coarse particle mass and speciation (elemental and morphological). These passive techniques can be

deployed at relative low cost in a variety of locations which provides opportunities for improved

spatial analyses of thoracic coarse particles.

In what locations should thoracic c oarse particle measurements be made?

Consider monitoring in areas that are not in attainment for PM 10 

# , but in attainment for PM 2.5 

# (see Table 1 below) or at least areas with higher PM 10 

# and lower PM 2.5 

# concentrations. Analyses of

data collected in these areas will provide insight s into the thoracic coarse particle components or

sources which are driving non-attainment (or high leve ls of thoracic coarse PM). Subsequent health

studies can then provide informa tion regarding the potential for h ealth effects associated with

exposure to these thoracic coarse particle components and sources. Rural locations should be

included as well to improve unders tanding of differences between ur ban and rural thoracic coarse

particle concentrations.

At what height should thoracic coarse particles be monitored?

Additional research is needed to understand the vertical profile of thoracic coarse particle

concentrations and to identify the effect of monitoring height on thoracic coarse particle

measurements (current requirements for thoracic coarse particle m onitoring height range from 2 to

15 meters).

How can the sources of thoracic co arse particles be identified?

Research is needed to identif y tracers or marker compounds for thoracic coarse particles for

source apportionment analyses. Thoracic coarse partic le sources likely fall into one of the following

categories: direct emissions from mechanical pr ocesses that crush or gr ind larger particles (e.g.,

from industrial operations, construction and demo lition activities, and ag ricultural and mining

operations), resuspension of dusts (e.g., traffic- related emissions from tire and brake wear),

biological materials, and secondarily formed aerosols. The influence of local sources will likely be

relatively more significant for thoracic coarse particles than for fine particles.

# December 2008 26 Why should State/Local/Tribal agencies be interested in thoracic coa rse particle monitoring?

Thoracic coarse partic le monitoring in PM 10 

# non-attainment areas (particularly areas that are

in attainment for PM 2.5 

# ) could provide valu able information for State and local agencies, while also

providing valuable information for air quality and health researchers that can be used in the design of

thoracic coarse partic le monitoring programs.

What other tools are available fo r analyses of ambient th oracic coarse particle concentrations?

Tools such as land use regression models, GIS, satellite data, and atmospheric dispersion

models can supplement thoracic coarse particle monitoring data to provide enhanced information

regarding spatial and temporal distributions of ambient thoracic coar se particles. However, it is

important to note that there are uncertainties with outputs from these tools and while these tools were

acknowledged at the workshop, detailed discussions regarding their poten tial application were

beyond the scope of this workshop. The applicati on of these tools may be included in future

workshop discussions, as appropriate.

Are there unique issues associated with th oracic coars e particle health studies?

There are some unique issues re lated to thoracic coarse partic le health studies. First, in vivo

toxicology studies are more difficu lt because efficient animal models are not available, in part

because inhalation toxicological studies are not possi ble in rodents. Differences in thoracic coarse

particles typically found in rural versus urban areas also present ch allenges. Epidemiological studies

in rural areas may not have enough statistical power. Fi nally, the role of e xposures to biological

components in health outcomes presents additional challenges.

Are there existing data available to analyze?

Various states, including Californian, New York, and Washington, have thoracic coarse

particle data available for mass and composition anal yses. For example, the state of California has

collected and analyzed thoracic coarse particle measurements for spatial, temporal, and

compositional patterns. 14 

# In addition, data and results from pr evious research studies that included

coarse particle measurements exist. One such study was conduc ted around major industries in

southern Chicago. 15 

# EPA also has thoracic coarse particle data available from pr evious field studies

(e.g., FRM evaluations, source apportionment studies). Key science questions need to be developed

for thoracic coarse particle monitoring and then the existing data sets need to be identified that could

potentially be analyzed to address some of these questions.



# Recommendations/Actions for Consideration

B uilding upon the general summary and major poi nts above, the following is a list of

recommendations expressed at the workshop or developed by EPA sta ff based on the workshop

discussions.

14 

# Croes, B.E. (2003). Particulate matter in California: Part 2 - Spatial, temporal, and compositional patterns of PM2.5,

PM10-2.5, and PM10. J. Air Waste Manage. Assoc.

, 53 (12):1517-1530.

15 

# Watson, J.G. ; Chow, J.C.; Kohl, S.D.; Kuhns, H.D.; Robinson, N.F.; Frazier, C.A.; and Etyemezian, V. (2000).

Annual report for the Robbins Particulate Study - October 1997 through September 1998. Prepared for Versar Inc.,

Lombard, IL, by Desert Research Institute, Reno, NV.

# December 2008 27  When making decisions regarding investment s in speciated thoracic coarse particle

measurements, consider the following:

o Analyze existing thoracic coarse particle data sets first. Such anal yses could begin to

address issues such as:

 How does thoracic coarse particle compos ition vary across cities and in urban and

rural areas?

 To what extent do speciation analyses us ing samples collected via the difference

methods differ from speciati on of dichotomous samples?

o Conduct targeted thoracic coarse particle speciation monitoring which is hypothesisdriven to decide what co mponents to monitor and how.

o Consider evidence generated from toxicologi cal studies to inform decisions on which

components to monitor.

.

 When evaluating potential locations for thoracic co arse particle monitors, consider areas that are

in attainment for PM 2.5 

# but not for PM 10 

# . Speciated thoracic coarse particle monitoring in these

locations may provide insights re garding sources that may be contributing to non-attainment.

 Consider a thoracic coarse partic le network design that includes a central site monitor collecting

mass and speciation measurements with satellite locations that could pot entially use alternative

lower cost methods (e.g., passive methods).

 Consider collecting daily thoracic coarse particle measurements at some subset of locations.

 Encourage the use of thoracic coarse part icle continuous methods, where possible.

 Continue to evaluate thoracic coarse pa rticle sampling and analytical methods.

o Sampling methods to be evaluated incl ude FDMS Dichotomous TEOM, DRUM, and

passive sampling approaches.

o Identify and evaluate potential methods to analyze biological components in thoracic

coarse particles.

 Incorporate thoracic coarse particle monitori ng objectives in planned research field work.

Examples objectives include:

o Identification of marker com pounds for thoracic coarse particle source categories.

o Characterization of vertical distribution of ambient thoraci c coarse particles and the

associated implications for monitoring height.

o Identification of composition a nd sources of unidentified thor acic coarse particle mass.

 Consider application of land use regression m odels, GIS, satellite images, and atmospheric

dispersion models in conjunction with ambient t horacic coarse particle measurements to conduct

spatial and temporal variability analys es and to inform monitor locations.

 Closely follow ongoing research fo r potential insights for thoraci c coarse particle monitoring

programs. The following research effo rts may be particularly valuable:

o EPA STAR Grants 16

16 

# See http://cfpub.epa.gov/n ce r_abstracts/index.cfm/fus eaction/display.rfa/rfa_id/450 for more information

# December 2008 28  Sources, composition, variabil ity and toxicological char acteristics of coarse

(PM 10-2.5 

# ) particles in Southern California (University of Southern California)

 Sources, composition, and hea lth effects of thoracic coarse particulate matter

(University of Colorado at Boulder)

 Cardiovascular effects of urban and rura l thoracic coarse particulate matter in

African American and white adults (University of Michigan)

 Spatial investigation of sources, composition and long- term health effects of

thoracic coarse particulate matter (PM 10-2.5 

# ) in the Multi-Ethnic Study of

Atherosclerosis (MESA) cohort (University of Washington)

 Comparative Toxicity of Thoracic coarse Particles (New York University)

o EPA In-House Research 17



#  Detroit Exposure and Aerosol Research Study (DEARS)

 Birmingham Coarse Particle Study

 Near Roadway Research Program

 Cleveland Source Apportionment Study

 Pinal County PMc Characterization Study (Region 9 RARE Project)

17 

# add a link to descriptions of these studies

# December 2008 29 Table 1. PM 10 

# Non-Attainment Areas with PM 2.5 

# Designations

(Source: EPA TTN Website)

# December 2008 30 

# SESSION V: AMBIENT AIR MONITORING REALITIES –

EPA/STATE/LOCAL PERSPECTIVES – SUMMARY AND

RECOMMENDATIONS

Background/Objectives

This session was designed for EPA and State/lo cal staff who manage monitoring programs to

share their reactions (i.e., a reality check) to topics discussed in ea rlier sessions of the ambient air

quality monitoring and health workshop. This included providing recommendations for addressing

“low hanging fruit” as well as identifying significa nt challenges to making progress in ambient air

monitoring to advance health rese arch for the criteria and relate d (e.g., chemical speciation) air

pollutants.



# Session Overview

For this portion of the workshop a panel of e xperts in ambient air monitoring was assembled

to provide their reaction to the papers, presentati ons, and discussions at the workshop. The panel

included several staff and managers from EPA and State and local ai r agencies who are responsible

for implementing and overseeing the operation of r outine ambient air monito ring programs for air

toxics, criteria, and other related air pollutants.

M embers of the panel included:

 Dirk Felton, co-chair, New York State De partment of Environmental Conservation

 Tim Hanley, co-chair, EPA, OAQPS

 Mike Gilroy, Puget Sound Clean Air Agency (Seattle, WA area local air agency)

 Richard Payton, EPA Region 8 (Lead Monitoring Region)

 Scott Reynolds, South Carolina Department of Health and Environmental Control

 Eric Stevenson, Bay Area Air Quality Management District (San Francisco, CA area local

agency)

 Susan Zimmer-Dauphinee, Georgia De partment of Natural Resources



# Major Points Raised by Participants

The panel provided input and reactions on a range of topics from the workshop. Common

themes across the panel members can be grouped in to four categories: daily speciation sampling,

PM 2.5 

# continuous mass data, data management, and communications.

Daily Speciation Sampling

One of the major needs identified by health re searchers is to have da ily speciation in up to

the largest 20 urban areas in th e country. EPA currently works w ith State and local agencies to

provide a Speciation Trends Network (STN) operating at midnight to midnight every third day at 53

locations around the country, plus an additiona l 120 locations identified as “supplemental

speciation” that mostly operate on a sample sche dule of every sixth day. Together the STN and

supplemental stations comprise the Chemical Speci ation Network (CSN). The CSN data together

with collocated criteria pollutant gas measurements reported to AQS form the largest single source

of ambient air pollution data used by the health community in researching the health effects of air

pollution.

# December 2008 31 Concerns

The panel overwhelmingly supported the value of speciation data for use in health studies as

well as to directly support State and local data uses such as sour ce apportionment of fine particles

and tracking control programs. However, the panel shared their concerns with the ability of State

and local agencies to take on the workload and cost associated with daily sampling via filter-based

speciation samplers. Even if funding were availabl e to support the cost of the laboratory analysis,

monitoring agencies would have a difficult time s upporting the field operations due to frequent site

visits and other logistical concer ns. The panel identified that m onitoring agencies were in some

cases already proposing to cut back on existing monitoring systems due to diminishing resources via

EPA grants and their own agency budgets. At th e same time EPA’s national contract laboratory has

a pre-negotiated price increase each year. Therefore, even under the best of scenarios, which is

usually flat funding, agencies are re ceiving less direct awards to s upport field activities every year.

While the panel expressed thei r doubts that anything substantive could be accomplished through

daily filter-based speciation, th ey did share thoughts on possibl e opportunities utilizing semicontinuous speciation methods.

The panel also discussed the comparative un certainty of health effect studies versus

uncertainty in the ambient air monitoring data. Panel members suggested, and no one disagreed, that

the uncertainty in the ambient air monitoring data was very small compared to the uncertainty in

health studies. Health researchers pointed out that it was not just an issue of not having daily data to

reduce uncertainty, but also an issue with interpre ting the potential lag of health effects if daily

characterization of particle specie s is not available. After the m eeting, panel members suggested that

through use of available PM 2.5 

# filter-based mass, continuous ma ss, and filter-based speciation,

reasonably good estimates of daily speciation coul d be derived (e.g., statis tically interpolating

chemical speciation on days 2 and 3 that the CSN sampler did not operate) for most major

metropolitan areas. EPA could work with a group such as HEI to make such estimates available.

Another option that could potentially support da ily speciation is the ro tating drum sampler,

discussed in the white paper found in Appendix D entitled “Air Quality Sampling: Benefits and

Costs of Daily Health Targeted Monitors for Fi ne Particle Components.” The drum sampler was

identified as a possible altern ative measurement technology to s upport high time resolution (every

six hours) of chemical speciation. The drum samp ler measures various size classes of PM mass and

PM components which would allow for a more comp rehensive characterization of the sizes of PM

by species. However, there is limited use of the dr um sampler in applications other than special

studies with anecdotal stories th at it does not perform well. The panel expressed co ncern that the

technology was not ready for routine application in State and local ai r monitoring networks, but were

open to reconsidering the technology farther down the road if additional development and testing

demonstrated that it would be easier to use than the current equipment and agencies would have at

least the same confidence in the data as is avai lable from the existing speciation sampling platform

(i.e., the Met One SASS/SuperSASS for elements and i ons). Even if the drum sampler advanced to

the point of having comparable sampling performa nce to the existing CSN samplers, there remain

two important issues that will need to be addressed. The first is the request made by health

researchers to have a consistent method over the en tire study period that they are researching and the

second is ensuring data reporting to the AQS data system for integration with other ambient air

monitoring data.

# December 2008 32 Opportunities

Acknowledging the value of highly time-resolved speciation data, the panel did express an

interest in characterizing speci ation on a daily basis utilizing so me combination of semi-continuous

and filter-based methods. Such an approach coul d be beneficial to both the health research

community as well as supporting data needs of State and local agencies; which is very important in

order to gain the support of senior management across monitoring agencies. The panel discussed

how several agencies are reporti ng good results with semi-continuous methods such as the Sunset

carbon analyzer, Aethelometer, and Thermo sulfat e analyzer. Other se mi-continuous speciation

samplers exist, but have not been demonstrated to be comparable to filter-based methods or are so

complex that data completeness and quality suffer due the instrument needing constant attention in

the field. Utilizing some combination of semi-c ontinuous carbon and sulfate characterization plus

providing for elemental analysis via XRF analysis on daily Teflon filters may provide a reasonably

complete characterization of the chemical specia tion of most interest. The major species missing

from such a protocol would be semi-volatile nitr ate and organic carbon. A possible surrogate for the

missing semi-volatiles could be the volatile channel of the Filt er Dynamic Measurement System

(FDMS) monitor, which provides highly time resolved characterization of stab le and volatile PM. A

protocol of semi-continuous and lim ited filter–based speciation for elemen ts would be of interest to a

number of State and local agencies to provide a more complete characterization of the source

apportionment of their networks, especially on days above the NAAQS. Resear chers are believed to

value such a data set on all days to improve our understanding of potential health/welfare effects

associated with ambient concentrations at or be low the current standards. Review of existing

collocated continuous speciation and filter-based method data (CSN or IMPROVE) available in

AQS or from Regional or State monitoring organi zations could provide an opportunity for health

researchers to evaluate the potential value of se mi-continuous speciated data and the need for filter

based, co-located sampling.

PM 2.5 

# Continuous Mass Data

Several of the panel members co mmented on the availability of PM 2.5 

# continuous mass data

and potential value to the health research commun ity. Some panel members were surprised to learn

that these data were not being widely used in he alth studies. Across the country there are over 600

PM 2.5 

# continuous mass monitors repor ting hourly data with every major city covered by one or more

stations. These data are stored and reported in near real-time th rough State and local agencies web

sites and nationally through the AirNow program; see www.airnow.gov 18 

# . Long-term archiving of

PM 2.5 

# continuous data is provided for in the AQS data base. Acknowledging the variety of PM 2.5 

# continuous methods used and their performance according to climate and measured aerosol

components across the country, EP A set–up new AQS data storage protocols in 2006 so agencies

could store their data in a way that allo wed data users to better utilize the PM 2.5 

# continuous mass

data. Principally among the data storage protocols, data users can pull hourly data for the parameter

“Acceptable PM 2.5 

# AQI & Speciation Mass” (parameter code 88502). This parameter code is

intended to represent the PM 2.5 

# continuous mass data where the method meets perf ormance criteria

18 

# www.airnow.gov provides illustrative maps of n ear-real time air pollution data an d forecasts according to the EPA’s

Air Quality Index (AQI). These maps are intended for the ge neral public and as such are color coded according to the

AQI. Detailed near real-time air pollution and meteorology da ta from across the United States and Canada are available

through www.airnowtech.org . This site is intended for technical users of the data. Health researchers or any other data

user with a valid use for the information can request access to the site through the log- in screen on the web site.

# December 2008 33 suitable for reporting the AQI 19 

# . In March of 2008, EPA-ORD approve d the first Federal Equivalent

Method (FEM) for PM 2.5 

# (Met One BAM 1020). Data from this method will be stored under the

parameter code “PM 2.5 

# at local Conditions” (88101) as are all currently reporting PM 2.5 

# FRM’s,

since these methods are approved for comparison to the NAAQS. All the avai lable parameter codes

(sometimes referred to as pollutant codes) for storing PM 2.5 

# continuous data in AQS are provided

below.

Parameter Name Parameter

Code Purpose ~Active Samplers/

Monitors

PM 2.5 

# LOCAL

CONDITIONS 88101 Code for all FRM’s, FEM, and

ARM’s. Continuous FEM’s

will be stored with this

parameter code. Data reported

to this parameter code are

generally eligible for

comparison to the NAAQS. 940 FRM’s

(~150 operate daily)

PM 2.5 

# TOTAL

ATMOSPHERIC 88500 Valid data from methods

measuring total PM 2.5 

# aerosols

in the atmosphere. FDMS is

the method currently stored

here 100

PM 2.5 

# RAW DATA 88501 Valid uncorrected data that does

not meet DQO’s for reporting at

least the AQI 300

ACCEPTABLE PM 2.5 

# AQI & SPECIATION

MASS 88502 Valid data that does meet the

DQO’s for AQI reporting with

or without a correction or the

mass data from the CSN

network. Data reported to this

parameter code are not eligible

for comparison to the NAAQS. 400 PM 2.5



# continuous

mass;

200 CSN

PM 2.5 

# VOLATILE

CHANNEL 88503 Store important related data

such as the FDMS reference

channel. 50 20 

# In total,

there are

~ 600

operating

PM 2.5



# continuous

monitors;

some

monitors

dual report



# With the availability of data from a large number of PM 2.5 

# continuous mass monitors, health

researchers could utilize highly time -resolved data that can be used as a surrogate for the types of

exposures in an urban area and combined with FRM data as a tool to better understand PM 2.5 

# continuous mass measurements with a pos itive bias relative to the FRM. PM 2.5 

# continuous mass data

can be used to characterize different types of e xposures by the time of day. For instance, weekday

morning rush hour would be an indicator of au tomotive emissions, while early mornings in the

winter might be an indicator of home hea ting (e.g., oil or wood smoke, depending on the

neighborhood). In some cases, the measurem ent principle and time resolution of a PM 2.5 

# continuous

method results in data that have a positive bias re lative to a 24-hour measurement on the filter-based

PM 2.5 

# FRM. The positive bias with PM 2.5 

# continuous methods are most li kely associated with semivolatile organics and nitr ate that are not fully captured on the FR M due to evaporative losses that are

exacerbated in warmer months when the sample filter is exposed at ambient conditions. These

differences should be explored and included in analysis to health research data as the data are

19 

# Where bias is controlled to within +/- 10% and correlation is at least 0.9 (R 2 

# of 0.81) compared to collocated filterbased FRM’s

20 

# Every FDMS monitor provides outputs of the volatile ch annel; however, some monitoring agencies have data

management system limitations at their sample station; therefore only half the FDMS units (50 out of 100) in operation

are reporting this channel. EPA will be working with monitoring agencies to improve reporting of this channel.

# December 2008 34 already available and would help fo cus future research efforts on the most important particle species

(e.g., to what extent do the semi-vol atile organics have a stronger or weaker association with health

effects?).

Data Management

The panel discussed several aspects of data management. One issue uncovered was the

discovery that at least two majo r metropolitan areas were providi ng for daily sampling and analyses

of the major fine particle speci es - elements, ions, and carbon (i.e., Los Angeles and Denver). The

panel suggested that the applicable State and lo cal agencies would highly value this additional

speciation data being utilized by h ealth researchers. To ensure data are utilized, it was suggested

that, where appropriate, these important measurem ents be reported to the AQS data system.

Specifically, in cases where health researchers ar e utilizing monitoring agen cy filters, plans should

be made to load the data to AQS. In cases where health researchers are performing their own

sampling, there would still be value in making the data available to a wider audience of users;

however, monitoring agencies and health researchers would need to ensure data comparability with

the existing network so other data user s understand the usefulness of the data.

Panel members offered that many agencies use EPA’s AQS data system as the sole long-term

repository of their data, but ther e were exceptions. While all rou tine State and local agency data

make their way to AQS, in some cases agencies have their own long-term data record with unique or

even routine measurements that are not in AQS. Health researchers should ask monitoring contacts

about any such data when discussing availability of ambient air mon itoring data with State and local

agencies

Panel members also offered that they can usuall y assist health researchers in the retrieval of

data from their network, even when data are located on the AQS data system.

Communications

Each major stakeholder group (EPA health and monitoring programs, external health

researchers, State and local air programs) has dozens of other groups that they communicate with.

One of the goals of this workshop is to establ ish better communication betw een decision makers in

routine ambient air monitoring progra ms and researchers that perform health effects studies that are

used to inform NAAQS reviews. EPA, the r outine ambient air monito ring programs, and the

external health research are all motivated to invest time to improve communication that can lead to

better use of ambient air monitori ng data; however, all gr oups also have responsibilities to other

stakeholders as well. So while monitoring prog rams and health researcher are making important

strides to improve the use of da ta and therefore provide better products that can inform NAAQS

reviews, each group also has a responsibility to ot her data users and clients of the health effects

research studies.

The panel suggested that there are already examples of good communications between health

researchers and State and local air monitori ng programs; however, communications could be

improved. Developing a collaborative relationship is critical to maximize the benefit of both kinds

of organizations. Health researchers will be ab le to better influence network decisions, and

monitoring agencies will be able to better utilize health research results produced from their own

ambient air monitoring system. Panel members cited examples where they had a good line of

communication between health resear chers and cases where they did not , even with their own sister

# December 2008 35 health agencies in State governments. Panel me mbers strongly support having health researchers

review their annual monitoring network plans and to develop a line of co mmunication as early as

possible for identifying the most important monito ring stations being used in a health study. Where

available, health and research community participation in plan review and development could be

advantageous to all parties. Panel members sugge sted that they do usually attempt to accommodate

the health research needs in cases where data are already being collect ed, especially if the

researchers can identify the specif ic need and product in advance of a planned change in monitoring

at a site.

A couple of panel members commented on Stat e/local review of grant proposals and how

early involvement of air programs may help strengthen this review. For example, if EPA, the

external health community, and State and local air monitoring programs already had a good line of

communication, then research plans for a specific research study could be strengthened by making

use of existing State and local monitors and data . Research resources co uld then be focused on

augmenting the State/local data by targeting measurem ents and activities not planned for in the State

air monitoring network. While this workshop has ha d a good deal of focus on what data are missing,

there are actually some redundancies between monito ring data collected for specific health studies

and State/local air monitoring prog rams. Future research work should focus on maximizing the use

of the State/local monitoring networks and identifyi ng the most critical “missing” data to collect.

Some panel members commented on the wide va riety of requests being made by the health

community (e.g., lots of daily speciation, need for multiple speciation sites across a city, need for

other measurements not currently being conducted su ch as ultrafines, etc.) and suggested that it

would be useful to have a prio ritized strategic plan of health research needs for ambient air

monitoring data. Such a plan should include commentary on the usef ulness of co-located

measurements such as pollutant gases and meteorological measurements.



# Recommendations/Actions for Consideration

Daily Speciation Sampling

Develop a protocol that utilizes a combina tion of semi-continuous and filter-based methods

to characterize daily speciation. Ensure such a pi lot has identified data users that can comment on

the expected data quality so that if successful, thes e methods can be applied in other areas. Initially

pilot this protocol in tw o or three major cities.

S pecific actions to develop hybrid semi-continuous and filter-based dail y speciation protocol:

 Inventory semi-continuous speciation methods operating across the country. Encourage

entry of data into AQS where possible (OAQPS)

 Perform data analysis and determine data quality on available co-located semi-continuous

and CSN data. (OAQPS)

 Evaluate intercomparability of Sunset carbon and Aethelometer data to CSN carbon data.

Provide recommendations for relative value of each method to provide carbon data on days

with no filter-based carbon sampling (ORD)

 Develop analytical protoc ol for XRF analysis on PM 2.5 

# FRM filters (ORD)

o Test protocol by retrieving filters from a small number of monitoring agencies where

there are co-located FRM and CSN data. Perh aps prioritize stations with collocated CSN

sampler.

o Analyze comparability of CSN and PM 2.5 

# FRM Teflon filters

# December 2008 36 o Provide recommendation on usefulness of XRF analysis on PM 2.5 

# FRM filter on days

when the CSN Teflon channel has operated and already has elemental assay

 Develop laboratory protocol for additional carbon assay – Thermal Optical Reflectance - on

PM 2.5 

# Teflon filter (ORD)

 Identify 2-3 test locations to pilot hybrid semi-continuous and filter-based daily speciation

protocol. Prioritize based on both:

o State/local partner(s) that will value daily speciation characterization for their program

o Health research studies that are already underway, or soon to be underway, utilizing

speciation data from an existing station

Other related actions

 Develop research action plan to address research questions from PM 10-2.5 

# chemical speciation

Whitepaper (ORD)

 Analyze data from co-located hourly PM 10-2.5 

# by difference

 Analyze data from FDMS Dichotomous monitor; focus on volatile channel

 Evaluate potential for a urban PM-10 S unset co-located with a PM-2.5 Sunset

 Demonstrate long-term (1-2 years) successful operation of the rotating drum sampler and

Synchrotron XRF analyses, including loading elemental data to AQS and comparability to

CSN data (ORD).

PM 2.5 

# Continuous mass data

T he availability of over 600 PM 2.5 

# continuous monitors provid es an opportunity to help

health researchers utilize an important data set that might provi de insights on the most important

exposures of PM 2.5 

# by time of day and averaging period. EPA has already set up data storage

protocols in AQS so that data can be retr ieved according to the performance of the PM 2.5 

# continuous

monitors and/or methods being utilized. EPA-OAQ PS is actively working to store already reported

PM 2.5 

# continuous data going back to 2004 21 

# under these new storage protocols.

S pecific actions that may help facilitate be tter use of these data in health studies:

 Provide recommendations on storage of PM 2.5 

# continuous mass data from years 2004 through

2006 under the appropriate parameter code so that data users retrieve data as expected

(OAQPS).

 Execute storage of PM 2.5 

# continuous mass data under new parameter codes in AQS from

years 2004 through 2006 (OAQPS and State/local agencies).

 Develop long-term plan for including PM 2.5 

# continuous mass data in next iteration of national

ambient air monitoring dataset used by health researchers (OAQPS and HEI).

Data Management

A vailability of ambient air monitoring data to facilitate a two way co mmunication of data can

be improved by taking on the following actions:

 EPA should include a discussion of data reporting expectations in the solicita tion of any new

long-term health studies where sp eciation data are involved. (ORD)

21 

# 2004 was the first full year of national PM 2.5 

# data reporting on AIRNow; the official launch date was October 1 of

2003. Prior to this date many agencies were just bringing their PM 2.5 

# continuous data on-line, including developing

statistical adjustments to have their data more closely resemble the PM 2.5 

# FRM data.

# December 2008 37 o In cases where the grant recipient will be utilizing methods cons istent with the CSN

network, the data will likely be highly valued, and provisions should be made to

quality assure and repo rt the data to AQS.

 Localized health effects studies should establis h a contact with the State or local monitoring

agency to facilitate access to data that may not necessarily be reported to AQS. (Health

Researchers)

 Data leads on health effects re search teams should be encourag ed to contact State and local

agencies for access to local data, even when the data are reported to AQS. (Health

Researchers)

Communications

M any of the possible improvements to communi cation are already underway. For emphasis,

the communication recommendations from the panel ar e provided here even if redundant or already

underway:

 EPA will facilitate a continued dialogue betw een health effects researchers and routine

ambient air monitoring pr ograms (OAQPS and ORD)

o Invite health effects researchers to share their work at monitoring conferences

o Invite leaders in the ambient air monito ring community to attend health effects

research meetings

o Engage the National Association of Clean Ai r Agencies (NACAA) at the Air Director

level to emphasize the importance of this work (OAQPS and ORD)

o Continue dedicated meetings between health effects researchers and routine ambient

air monitoring programs. (All)

o Encourage (State or PQAO) Air Monitoring Staff representation on science advisory

boards for health effects research programs that have significant monitoring data

needs. (Health Researchers, State/local agencies)

 Facilitate input of health effects researchers into annual monitoring network plans 22 

# (EPA

Regions, OAQPS, ORD, Health effects researchers)

o Maintain AMTIC web site with links to each State/local agencies’ annual monitoring

network plan

o In early 2008, EPA ORD’s National Center for Environmental Research (NCER)

conducted a preliminary survey of EPA-funded epidemiology studies to develop an

initial list of monitoring sites that are be ing used in current or planned health

studies 23 

# . ORD will consider options for expandi ng/updating this preliminary list and

ways to make it available to State/local air agencies when they are considering

changes to their monitoring networks.

o Health effects researchers should engage monitoring program early in the process

when they have specific needs for continued data availability.

22 

# Annual Monitoring Network Plans are due to the applicab le EPA Regional Office by Ju ly 1 of each year. These

documents represent the plans for monitoring in the subseque nt calendar year and are subject to EPA approval. Each

agency is required to make their plan available for public insp ection for at least 30 days prior to submittal to EPA. See

40 CFR §58.10. An internet link to plans is av ailable at: http://www.epa.gov/ttn/amtic/plans.html

23 

# See Appendix G.

# December 2008 38  Develop strategic plan for health effects rese arch ambient air monito ring data needs (ORD

and HEI with input from OAQPS)

o EPA and State/local agencies need to know the most valued data to help protect

monitoring resources and guide future monitoring investments. Such a plan would be

a guide for all monitoring investments in cluding those by EPA-ORD, health effects

researchers themselves and routine monitori ng programs. Example topics to address

include:

 are Aethelometer BC data adequate?

 is the UV channel useful?

 are nitrate data necessary at all, or only in certain geographical areas?

# December 2008 39 

# BACKGROUND MATERIALS

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite



# Appendix A: Workshop Agenda and Participant List

Ambient Air Quality Monitoring and Health Research:

Workshop to Discuss Key Issues

April 16 and 17, 2008

US EPA Main Campus, Building C-Audi torium, Research Triangle Park, NC

EPA is interested in having an open dialogue with a small group of representative experts

regarding health research priorities for ambien t air quality monitoring data that could best

advance our understanding of the impacts of air pollutant expos ures on public health. In

particular, we are interested in hearing comments and recomme ndations from experts on steps

that could be taken to improve our understanding of the impact of fine particle components and

other key air pollutants. These steps might incl ude prioritization of mon itoring sites and/or the

designation of sites for more frequent monitoring.

This meeting is another step in a series of interactions to foster improved long-term

communication between air quality experts and health research ers. This communication is

critical for ensuring that the ambient air monito ring program offers, and health researchers use,

the best and most appropriate da ta possible to suppor t the health research that serves as a

foundation for EPA’s reviews of the nationa l ambient air quality standards (NAAQS).

Primary Meeting Objectives

 To discuss specific recommendations for concre te steps that EPA a nd other organizations

could take in the ambient air monitoring program to advance health research for the criteria

air pollutants.

 To reexamine and assess progress to date on key issues identified at an earlier workshop

sponsored by the Health Eff ects Institute (HEI) and EPA 24 

# and in follow-up discussions with

the EPA-PM Center Directors, HEI National Particle Component Toxicity ( 

# NPACT)

Directors, and other researchers.

 To provide constructive feedback on the following draft “white papers” developed to aid in a

common understanding of th e issues under discussion:

 Chemical Speciation Network (CSN) - Carbon Issues

 Access to EPA’s Air Quality Data for Health Researchers

 Air Quality Sampling: Benefits and Costs of Daily Health Targeted Monitors for Fine

Particle Components

24 

# HEI and EPA co-sponsored a meeting in late 2006 to discuss how the use of the accumulating data derived from

nationwide monitoring of fine particulate matter (PM) comp onents can facilitate current and future health effects

studies and improve comparisons of risk estimates across studies. The workshop illuminated issues associated with

accessing and analyzing monitoring data and identified needs of the health effects research community regarding

monitoring of fine particle components. See http://www.healtheffects.org/ AQDNov0 6/AQDWorkshop.html for

more information.



# A-1

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite

 Long-term communication strategies for improving interactions between health

researchers and air quality staff on changes in ambient air monitoring specifically:

o Network Design and Site Selection Approval

o Methods Implementation

Expectations for Meeting Participants

This workshop is designed to inform EPA sta ff plans for the criteria pollutant ambient air

monitoring program to ensure that the most ef fective approaches for providing monitoring data

to support health research studi es are included. A large porti on of the workshop agenda is

devoted to discussion – the goal of which is to talk about recommendations for concrete steps

that could be made to move the alliance betw een health and monitori ng objectives forward.

Thus, to maximize the effectiveness of the meeti ng, workshop participants will be expected to be

familiar with background information distributed prior to the workshop, including draft white

papers. The workshop discussions will need to be forward looking – to identify specific nearand long-term steps that EPA’s health and monitori ng staff, as well as external organizations and

science communities, can take to improve the am bient air monitoring program to appropriately

advance our understanding of the health impacts of criteria air pollutant s. This workshop is

designed to be an honest and objec tive endeavor to address hea lth research needs, however,

participants must also understand that EPA resour ces are, and will most likely continue to be,

limited. Therefore, providing prioritization of recommendations for EPA and other

organizations to consider is essential if we ar e to make some clear st eps forward and, hopefully,

build from anticipated initial successes.



# Wednesday, April 16, 2008

8:30 – 9:45 Welcome/Introductory Remarks

8:30 – 8:45 Purpose of the Meeting/Overview of Key Issu es/Summary of Progress

Dr. Daniel Costa, EPA National Program Director for Air Research/ORD

8:45 – 9:00 EPA Program Office Perspective

Ms. Lydia Wegman, Director, Heal th and Environmental Impacts

Division/OAQPS

Mr. Richard Wayland, Director, Air Quality and Assessment

Division/OAQPS

9:00 – 9:45 Air Quality Experts and He alth Researchers Working Together:

Why Communication is Crit ical - Stories of Success

Dr. Morton Lippmann, New York University



# 9:45 – 10:00 BREAK

A-2

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite



# 10:00 – 2:45 Session I: Elemental and Or ganic Carbon Measurements

Background

In 2007, EPA made changes in the monitoring network to address inconsistencies in

carbon sampling and analysis procedures us ed in urban CSN (STN/SLAMS) and rural

IMPROVE programs. Health researchers have repe atedly raised concerns to EPA regarding this

methodology change and potential inte rruptions in monitoring data used for time-series analyses.

This session will include: (1) a brief overview of what measurements are currently being made;

(2) highlights from a recent CSN/IMPROVE: Carbon PM monitoring workshop with emphasis

on issues of most interest to the health research community 25 

# ; (3) approaches that are being

evaluated for relating different da ta sets and the potential impacts for on-going epidemiological

studies, and (4) opportunities to di scuss steps that are be ing taken or could be taken to identify

and address information gaps, incl uding continuous carbon measurements.

Background Information - Draft White Paper: “Chemical Speciation Network (CSN) -

Carbon Issues”

10:00 – 10:20 Overview and Introduction to Key Issues

Dr. Venkatesh Rao, EPA/OAQPS

Dr. Barbara Turpin, Rutgers University

10:20 – 10:40 A Health Researcher’s Pers pective: What’s So Special About

Carbon?

Dr. Ed Avol, University of Southern California

10:40 – 11:00 CSN Carbon Monitoring Changes and Issues

Ms. Joann Rice, EPA/OAQPS

11:00 – 11:20 Carbonaceous Aerosol Sa mpling Artifacts in the National

Monitoring Networks

Dr. John Watson, Desert Research Institute

11:20 - 11:40 Transitions: Re lating “Old” to “New” Methods

Dr. Warren White, Universi ty of California-Davis

11:40 – 11:50 Predicting Carbonaceous Sp ecies Concentrations with Partial

Least Squares

Dr. Philip Hopke, Clarkson University

11:50 – 12:10 Impact of Method Tr ansitions to Health Research

Dr. Michael Hannigan, University of Colorado-Boulder

12:10 – 12:30 Air Quality Monitoring: Perspectives from East and West

Mr. Dirk Felton, NY Department of Environmental Conservation

25 

# See http://vista.cira.colostate.edu/improve/Publicatio n s/Workshops/Carbon_Jan2008/CarbonMeeting2008.htm for

more information.



# A-3

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite



# 12:30 – 1:30 LUNCH

Session I: Elemental and Or ganic Carbon Measurements (cont.)

1:30 – 2:45 Panel Discussion

Dr. Ed Avol, Univ. of Southern California

Dr. Michelle Bell, Yale University

Dr. Judith Chow, Desert Research Institute

Mr. Neil Frank, EPA/OAQPS

Dr. Philip Hopke, Clarkson University

Dr. Michael Kleeman, University of CA-Davis

Dr. Allen Robinson, Carnegie Mellon Univ.

Dr. Warren White, University of CA-Davis

Suggested Issues for Discussion:

• What types of measurement error are problematic for epidemiology?

• Knowing this, what is of most concern (t o epidemiology) given the CSN changes?

• Step changes in detection limits/precision?

• Step changes in OC and EC (but not TC)?

• Bias due to sampling artifacts?

• Other?

• Are past and planned measurement comparisons adequate:

• to aid epidemiology study analyses?

• to “harmonize” results from old and new methods?

• How should blanks and sampling artifacts be handled?

• What other types of carbon measurements are good candidates for ex amination in large

epidemiology studies?



# 2:45 - 3:00 BREAK

3:00 – 4:30 Session II: Accessing Ambient Air Monitoring Data

Background

EPA’s Air Quality System (AQS) is designed to collect and store ambient air monitoring

information. EPA recently introduced the AQS Data Mart to facilitate ac cess to this monitoring

information. The AQS Data Mart is a generic “ret rieval” tool that provides the ability to query

any information, but it does not provide significan t data exploration or an alytic capabilities.

These capabilities are left to the “an alytical” tools. Various analyt ical tools, or interfaces, are

available including HEI’s Air Quality Da tabase, which focuses on levels of PM 2.5 

# components

and gaseous pollutants at and near STN and SLAMS sites. This discussion will focus on data

A-4

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite

access issues and how to help health research ers obtain m onitoring data for fine particle

components and other critical pollutants more easily.

Background Information - Draft White Paper: “Access to EPA’s Air Quality Data for

Health Researchers”



# 3 :00 – 3:10 Overview and Introduction to Key Issues

Dr. Bryan Hubbell, EPA/OAQPS

Dr. Michelle Bell, Yale University

3:10 – 3:20 Overview of Draft White Paper: “Access to EPA’s Air Quality

Data for Health Researchers”

Mr. Nick Mangus, EPA/OAQPS

3:20 – 3:30 Summary of Recent Data Summit

Mr. Rich Scheffe, EPA/OAQPS

3:30 – 4:30 Panel Discussion

Dr. Sara Dubowsky Adar, Univ. of Washington

Dr. Kaz Ito, New York University

Mr. John Langstaff, EPA/OAQPS

Mr. Nick Mangus, EPA/OAQPS

Mr. Richard Poirot, Vermont DEC

Dr. Betty Pun, AER

Mr. Rich Scheffe, EPA/OAQPS

Suggested Issues for Discussion:

I n general, we see that access to ambient air monitoring data needs to support health

research/assessments falls in to four general categories:

 

# epidemiological studies

 

# exposure/risk assessments

 

# public health surveillance

 

# health impact assessments

K eeping these broad categories in mind and und erstanding that the goal is to provide a

framework for delivering consistent, well-docum ented monitoring data to users including the

health research community, the issues discussed in this session will focus on data type/format,

access, and context including:

 

# What key data and formats do he alth researchers need access to?

 

# How user-friendly are the data bases currently available to health researchers? What

are the similarities/differences between th e various data bases and how are they

communicated?

A-5

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite

 

# What potential changes could be made to improve access to ambient air monitoring

data?

 

# What mechanisms are currently being used to communicate the limitations associated

with the ambient air monitoring data? Are there specific recommendations for

improving how the limitations are characterized?

 

# How can we improve the understanding of th e limitations, quirks, and context of the

ambient air monitoring data and assist end users in de termining the subsequent

appropriate use of the raw data?



# 4:30 ADJOURN

Thursday, April 17, 2008

8:00 – 8:30 Summaries of Day 1 Discussion s and Comments on Draft White

Papers/Next Steps

8:00 – 8:15 Session I: Elementa l and Organic Carbon Measurements

Dr. Barbara Turpin, Rutgers University

8:15 – 8:30 Session II: Accessing Ambient Air Monitoring Data

Dr. Bryan Hubbell, EPA/OAQPS

Dr. Michelle Bell, Yale University



# 8:30 – 10:15 Session III: Ambient Air Monitoring for Health Researc 

# h

Background

EPA has been measuring fine particle co mponents in urban areas since 2001. The

network consists of 54 sites inte nded to capture long-te rm trends (Speciation Trends Network or

STN) and approximately 150 other State and local air monitoring stations (SLAMS).

Collectively the urban locations are part of th e EPA Chemical Speciation Network (CSN). Due

to cost considerations the CSN was reduced in 2006 from its original size of approximately 240

stations to its present size. Currently, fine particle components are measured at each location

every third or sixth day. The Interagency M onitoring of Protected Visual Environments

(IMPROVE) network, covering background sites in national parks and wilderness sites in

addition to Washington, DC and the South Bronx in New York City, provide additional data of

great value to researchers. Health re searchers have requested EPA implement daily fine particle

speciation measurements, however resource constraint s have impeded any real plans to this end.

This session will explore opportunities to obtain thes e types of data in critical locations to make

true inroads in improving our understanding of th e temporal variability of fine particle

components in ambient air. The monitoring issue presently is fine particles (and components),

but looming ahead is the issue of thoracic coarse particles – what steps can we make to prepare

for this new data-source?

A-6

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite

Background Information - Draft White Paper: “A ir Quality Sampling: Benefits and Costs

of Daily Health Targeted Monitors for Fine P article Components”

8:30–8:45 Overview and Introduction to Key Issues

Dr. Barbara Glenn, EPA/ORD/NCER

Dr. Joel Schwartz, Harvard School of Public Health

8:45–10:15 Panel Discussion

Dr. Robert Devlin, EPA/ORD/NHEERL

Dr. Patrick Kinney, Columbia University

Dr. Lucas Neas, EPA/ORD/NHEERL

Dr. Roger Peng, Johns Hopkins University

Dr. George Thurston, New York University

D r. Jay Turner, Washington Univ. in St. Louis

Suggested Issues for Discussion:

 

# Sources of Error – which are the most limiting?

o 

# For time-series studies that rely on air m onitoring data collected every third or

sixth day from a single (or a few) centra l site monitors, which major sources of

error are the most important? Why? Which is the most important?

 Uncertainties in exposure a ssessment associated with:

 

# Missing days.

 

# Spatial variation.

 

# Monitor location.

 

# Instruments measurement erro r or analytic methods.

o 

# Could exposure modeling to “fill-in” missing days adequately address

uncertainties associated with every third or sixth day monitoring data?

 

# If daily monitoring was going to commence in a few cities in the U.S., what is the best

monitoring plan to study the re lative health importance of PM components in the ambient

mix of PM?

o 

# What are the best sites? Why? What site criteria are the most important?

o 

# What minimum number of lo cations for daily sampling is adequate to address a

particular research area?

o 

# What components would you evaluate first?

 

# Integrating previous or ongoing data collection to obtain retrospective data.

o 

# In some locations, FRM filters may have been archived and could be analyzed to

learn more about daily variation of fine particles and components.

o 

# In some areas, data from continuous mon itors for previous years is available.

o 

# In previous years, special studies or gr ant-funded studies have collected data on

PM species.

o 

# How could these data be integrated to pr ovide daily data for time-series studies?

If data from different instruments or methods were combined to obtain a set of

daily ambient concentration data for a c ity, would this introduce a significant

source of uncertainty/error?

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o 

# What components should be measured and what are the issues associated with

their measurement and use in analyses?



# 10:15-10:30 BREAK

10:30–12:00 Session IV: Thoracic Coarse Particle Components and

Potential Public Health Impacts

Background

On September 27, 2006, the U.S. Environmenta l Protection Agency (EPA) amended its

national air quality m onitoring requirements. 26 

# As part of these changes, EPA and the states will

add measurements of "thoracic coarse particles" (i.e. PM 10-2.5 

# ) at 75 multi-pollutant monitoring

sites (National Core or NCore sites). Some monitors will provide at least hourly measurements in

near real-time (continuous mass con centration monitoring); while ot her monitors will sample the

air over a 24-hour period and require laboratory processing of the sample (filter based sampling).

Filter-based monitoring will enable development of PM 10-2.5 

# methods for chemical speciation of

thoracic coarse particles. This session will explor e criteria to consider as EPA adds speciation of

thoracic coarse particles to the ambient air monitoring network.

10:30–11:00 Overview and Introduction to Key Issues

Dr. Timothy Larson, University of Washington

Mr. Timothy Watkins, EPA/ORD/NERL

11:00–12:00 Panel Discussion

Dr. David Diaz-Sanchez, EPA/ORD/NHEERL Dr. Michael Hannigan, Univ. of CO –

Boulder

Dr. Philip Fine, SCAQMD Dr. Thomas Peters, University of Iowa

Dr. Richard Flagan, CalTech Ms. Joann Rice, EPA/OAQPS

Dr. Terry Gordon, New York University Dr . Jamie Schauer, Univ. of WI – Madison

Suggested Issues for Discussion :

 

# What is the relative value of coarse partic le speciation at planned monitoring locations

versus additional mass measurements?

 

# What is the relative value of understandi ng Intra-urban versus Inter-urban/rural

variability in coarse particle compositi on and spatial and temp oral distributions?

 

# What are your recommendations for coarse particle network design?



# 12:00 – 1:00 LUNCH

26 

# See http://www.epa.gov/oar/par ticlepo llution/actions.html for more information on amendments to EPA’s

National Air Quality Monitoring Requirements.



# A-8

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# 1:00 – 2:30 Session V: Ambient Air Monitoring Realities –

EPA/State/Local Perspectives

Background

E PA works with State, local, and tribal air ag encies to design and implement ambient air

monitoring networks to meet severa l monitoring objectives including:

 

# Determining compliance with standards (i.e., the NAAQS)

 

# Providing air pollution data to th e general public on a timely basis

 

# Supporting the development and tracking of the effectiveness of emission control

programs

 

# Providing input data for health and welfar e effects and exposur e research studies

 

# Providing input data for health and welf are risk/exposure assessments conducted for

NAAQS reviews

 

# Measuring overall progress of air pollution control programs

Opportunities are available for interested parties to provide comments on monitoring

network plans to ensure input from health researchers and other inte rested users is considered in

the design of these plans. Two draft white pa pers review the current processes for public

comments on the monitoring network plans and changes to monitoring methodologies,

respectively, as well as options for future effo rts to improve communications with the health

research community regarding ambient air monitoring networks.

This session is designed for EPA and State /local staff who manage monitoring programs

to share their reactions (i.e., a reality check) to topics discussed in earlier sessions. This may

include providing recommendations for addressi ng “low hanging fruit” as well as significant

challenges that may need to be addressed in orde r to make considerable progress in the ambient

air monitoring program to advance health re search for the criteria air pollutants.

Background Information - Draft White Papers : “Ambient Air Monitoring Networks:

Network Design and Site Selection Appr oval” and “Ambient Air Monitoring Method

Implementation”

1:00 – 1:15 Overview and Introduction to Key Issues

Mr. Dirk Felton, NY DEC

Mr. Timothy Hanley, EPA/OAQPS

1:15 – 2:30 Panel Discussion

Dr. Philip Fine, SCAQMD

Mr. Michael Gilroy, Puget Sound CAA

Mr. Richard Payton, EPA/Region 8

Mr. Scott Reynolds, SCDHEC

Mr. Eric Stevenson, BAAQMD

Ms. Susan Zimmer-Dauphinee, GA DNR

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# 2:30 – 2:45 BREAK

2:45 – 3:30 Summaries of Day 2 Discussion s and Comments on Draft White

Papers/Next Steps

2:45 – 3:00 Session III: Ambient Air Monitoring for Health Research

Dr. Barbara Glenn, EPA/ORD/NCER

Dr. Joel Schwartz, Harvard School of Public Health

3:00 – 3:15 Session IV: Thoracic Coar se Particle Components and Potential

Public Health Impacts

Dr. Timothy Larson, University of Washington

Mr. Timothy Watkins, EPA/ORD/NERL



# 3:15 – 4:00 Concluding Remarks/Emerging Issues/Next Steps

Dr. Morton Lippmann, New York University

Ms. Lydia Wegman, EPA/OAQPS

Mr. Richard Wayland, EPA/OAQPS

Dr. Daniel Costa, National Program Director for Air Research, EPA/ORD



# 4:00 ADJOURN

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# Ambient Air Quality Monitoring and He alth Research: Workshop to Discuss

Key Issues - Participants

April 16-17, 2008

Last Name First Name Affiliation

Arnold Jeff EPA National Center for Environmental Assessment

Avol Ed University of Southern California

Baldauf Rich EPA NRMRL

Baxter Lisa EPA National Exposure Research Laboratory

Bell Michelle Yale University

Brook Jeffrey Environment Canada

Bucky Barbra EPA National Center for Environmental Assessment

Chow Judy Desert Research Institute

Costa Dan EPA Office of Research & Development

Devlin Robert EPA National Health & Environmental Effects Research

Laboratory

Diaz-Sanchez David EPA National Health & Environmental Effects Research

Laboratory

Dubowsky Adar Sara University of Washington

Felton Dirk New York State Departme nt of Environmental Conservation

Fine Phillip South Coast Air Qu ality Management District

Flagan Richard California Institute of Technology

Foley Kristen EPA National E xposure Research Laboratory

Frank Neil EPA Office of Air Quality Planning & Standards

Garbe Paul Centers for Disease Control & Prevention

Garcia Val EPA National Exposure Research Laboratory

Gilliland Alice EPA National E xposure Research Laboratory

Gilroy Mike Puget Sound Clean Air Agency

Glenn Barbara EPA National Center for Environmental Research

Godleski John Harvard School of Public Health

Gordon Terry New York University

Hall Eric S EPA National Expos ure Research Laboratory

Hanley Tim EPA Office of Air Quality Planning & Standards

Hannigan Michael University of Colorado at Boulder

Hansen Craig EPA National Center for Environmental Assessment

Hassett-Sipple Beth EPA Office of Air Quality Planning & Standards

Holland David EPA National E xposure Research Laboratory

Hopke Phil Clarkson University

Hubbell Bryan EPA Office of Air Quality Planning & Standards

Ito Kaz New York University

Jenkins Scott EPA Office of Air Quality Planning & Standards

Katz Stacey EPA National Center for Environmental Research

Kim Jee-Young EPA National Center for Environmental Assessment

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Last Name First Name Affiliation

Kinney Patrick Columbia University

Kirrane Ellen EPA National Center for Environmental Assessment

Kleeman Mike University of California-Davis

Kryak David EPA National Expos ure Research Laboratory

Lamason Bill EPA Office of Air Quality Planning & Standards

Langstaff John EPA Office of Air Quality Planning & Standards

Larson Tim University of Washington

Lippman Morton New York University

Long Tom EPA National Center for Environmental Assessment

Lorang Phil EPA Office of Air Quality Planning & Standards

Luben Tom EPA National Center for Environmental Assessment

Mangus Nick EPA Office of Air Quality Planning & Standards

Martin Karen EPA Office of Air Quality Planning & Standards

Mikel Dennis EPA Office of Air Quality Planning & Standards

Mintz David EPA Office of Air Quality Planning & Standards

Mukerjee Shailbal EPA National Exposure Research Laboratory

Neas Lucas EPA National Health & Environmental Effects Research

Laboratory

Ozkaynak Haluk EPA National E xposure Research Laboratory

Payton Richard EPA Region 8

Peltier Richard New York University

Peng Roger Johns Hopkins University

Peters Thomas University of Iowa

Pierce Tom EPA National Center for Environmental Assessment

Pinto Joe EPA National Center for Environmental Assessment

Poirot Rich Vermont Department of Environmental Conservation

Pun Betty Atmospheric and E nvironmental Research, Inc.

Rao Venkatesh EPA Office of Air Quality Planning & Standards

Reynolds Scott South Carolina Department of Health and Environmental

Control

Rice Joann EPA Office of Air Quality Planning & Standards

Richmond Harvey EPA Office of Ai r Quality Planning & Standards

Robarge Gail EPA National Center for Environmental Research

Robinson Allen Carnegie Mellon University

Ross Zev ZevRoss Spatial Analysis

Sacks Jason EPA National Center for Environmental Assessment

Schauer Jamie University of Wisconsin

Scheffe Rich EPA Office of Air Quality Planning & Standards

Schultz Laurel EPA Office of Research & Development

Schwartz Joel Harvard University

Sheldon Linda EPA National Expos ure Research Laboratory

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A-13 Last Name First Name Affiliation

Stanek Lindsay EPA National Center for Environmental Assessment

Stevenson Eric Bay Area Air Quality Management District

Stewart Michael EPA Office of Air Quality Planning & Standards

Stone Susan EPA Office of Air Quality Planning & Standards

Sunshine Geoffrey Health Effects Institute

Thurston George New York University

Tikvart Joe EPA Office of Air Quality Planning & Standards

Turner Jay Washington University in St. Louis

Turpin Barbara Rutgers University

Vandenberg John EPA National Center for Environmental Assessment

Vanderpool Robert EPA National Exposure Research Laboratory

Vette Alan EPA National Expos ure Research Laboratory

Watkins Tim EPA National Exposure Research Laboratory

Watson John Desert Research Institute

Wayland Richard

(Chet) EPA Office of Air Quality Planning & Standards

Wegman Lydia EPA Office of Air Quality Planning & Standards

Weinstock Lewis EPA Office of Air Quality Planning & Standards

White Warren University of California-Davis

Williams Ron EPA National Exposure Research Laboratory

Willis Robert EPA National Exposure Research Laboratory

Wilson William EPA National Center for Environmental Assessment

Winner Darrell EPA National Center for Environmental Research

Wyzga Ronald Electric Power Research Institute

ZimmerDauphinee Susan Georgia Department of Natural Resources

# DRAFT 4/02/08 – For Discu ssion Purposes Only – Do Not Quote or Cite



# Appendix B: Session I: Elementa l and Organic Carbon Measurements -

Chemical Speciation Netw ork (CSN) Carbon Issues

Questions on this draft white paper should be directed to Neil Frank, EPA/OAQPS,

frank.neil@epa.gov , (919) 541-5560.

Introduction

The purpose of this draft white paper is to provide an overview of urban and rural carbon

measurement protocols and to identify issues associated with data reporting and usage,

particularly with respect to the CSN transiti on to IMPROVE-protocol for carbon measurements.

This document will also serve as a discussion pi ece to gather input from the health research

community on related issues and next steps.

Background

State and local air agencies, under EPA grants , have been measuring organic carbon (OC)

and elemental carbon (EC) in urban areas since 2001. The network consists of 54 sites intended

to capture long-term trends (s peciation trends network or STN) and approximately 150 other

State and local air monitoring stat ions (SLAMS). Collectively, th e urban locations are part of

the EPA Chemical Speciation Network (CSN). To support the regional haze and PM 2.5 

# programs, EPA also funds a largely rural networ k called IMPROVE. Togeth er with support from

NPS and other Federal agencies, the IMPROVE network provides carbon measurements at

approximately 160 national park, wilderness, and other rural locations nationwide.

Two different thermal-optical analysis methods are currently used by the CSN and

IMPROVE networks for the analysis of carbon. The IMPROVE method is based on the Desert

Research Institute/Oregon Graduate Center (DRI/OGC) thermal-optical reflectance (TOR)

method 27 

# . The CSN method has historically used a modi fied version of the National Institute for

Occupational Safety and Health (NIOSH) 5040 thermal optical transmittance (TOT) method 28



# . The latter CSN method is differe nt from the NIOSH method in th at it has a different thermal

temperature profile. The CSN is transitioning to the IMPROVE sampling and analysis protocols

for carbon. Currently 56 sites have changed. A dditional sites will be changed in the future.

Research has shown that differences in the thermal profile, optical correction

(transmittance versus reflectance), and specific analyz er used will result in differences in the OC

and EC values obtained (Schmid et al, 2001; Cu rrie, et al., 2002). In addition, sampling and

sample handling differences also have an imp act, especially for OC. Other carbon monitoring

networks and measurement stud ies (e.g. SEARCH, Supersites) us e variations of the CSN and

IMPROVE protocols and ar e not discussed here.

For the first 6 years of CSN operation, urban and rural carbon have been collected with

different samplers and analyzed by different th ermal optical methods. For chemical analysis,

CSN has used the NIOSH-type thermal optical transmittance (TOT) method for measures of OC

27 

# The current IMPROVE_A method for Organic and Elemental carbon is described by the Standard Operating

Procedure (SOP) provided at: http://vista.cira.colostate.edu/impr o ve/Publications/SOPs/drisop2005.asp

28 

# The CSN method for Organic and Elemental Carbon is described in the SOP provided at:

http://epa.gov/ttn /amtic/files/ambient/p m25/spec/ocecsop.pdf



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and EC. IMPROVE m easurements are based on thermal optical reflectance (TOR) with a

different thermal evolution temperature prof ile. Both measurement protocols provide

operationally-defined measures of OC and EC. The IMPROVE protocol generally results in a

lower OC/EC ratio and also provides 4 sub-fr actions of OC (OC1, OC 2, OC3, OC4), pyrolized

organic carbon (OP), and 3 fracti ons of EC (EC1, EC2, EC3). These sub-fractions have been

used in source attribution st udies (Kim and Hopke, 2006). Star ting in 2005, however, IMPROVE

switched to an upgraded TOR analyzer with more accurate temperature settings. This change to

“IMPROVE_A” results in approximately the same to tal OC and total EC but relatively different

amounts of the sub-fractions (Chow et al., 2007 ). The new IMPROVE an alyzer also provides

TOT measurements which may have valu e in relating the tw o networks’ data.

In addition, the two networks have their diffe rent approaches to address various sampling

artifacts and public reporting of its carbon data. While CSN collect s field and trip blanks (but

with limited ambient exposure) at all sites as a measure of passively collected organic vapors

(positive artifact), the IMPROVE program uses longe r duration field blanks at all its sites, and

additionally has deployed secondary carbon (sc), i.e. backup quartz fi lters, at 6 of their sites to

provide a network-wide measure of sampling artifacts. IMPROVE data shows that sc is greater

than field blank carbon (fbc) and IMPROVE uses the monthly median sc value (by carbon subfraction) to correct the entire network’s organic and elemental carbon values. The adequacy of

using 6 sites to represent the entire network is currently under review by IMRPOVE. IMPROVE

reports publicly only the artifact adjusted data. EPA has been publicly reporting in AQS carbon

data produced by the primary collection filters, and separately the carbon values for the field and

trip blanks. 29 

# All field and trip blank data since 1 999 are now available in AQS. Until CSN sites

are transitioned to the new IMPROVE protocol, CSN sites are not measuring carbon on backup

filters. To correct for urban sampling artifacts, CSN data users have used the CSN fbc data

together with sampler specific flow rates to “bla nk correct” the reported CSN data and have also

used material balance or statistical approaches ( Frank, Solomon, Kim ). These sampling artifact

procedures have also considered the need to di fferentiate particulate carbon collected on quartz

vs. Teflon filters. Some users have not made any adjustments in some work ( Pun ). The

correction for sampling artifact can be as much as 30% of the organic carbon, as reported at the

2006 HEI meeting in Boston ( www.healtheffects.or g/AQDNov06/AQDWorkshop.htm l ). The

new CSN samplers whose quartz filters are anal yzed with “IMPROVE_A” are deploying sc and

24-hr duration fbc filters. The potential use of those filters to adjust for sampling artifact is

currently under study. EPA is also exploring wh at adjustments can/should be applied to oldprotocol-CSN data to best correct for samp ling artifacts and whether a single universally

acceptable approach or multiple approaches for ar tifact corrected data exists. A question to

pursue is: What is the impact of using CSN da ta that have not been corrected for sampling

artifacts in epi studies (i.e., inclusion of a la rge and variable positive bias which may possibly

have a seasonal component)?

To help understand the differences between CSN and IMPROVE carbon-protocol

measurements, EPA has collocated CSN samplers with IMPROVE samplers in various urban

and rural environments over a 1-3 year period (See Table 1). Because of the many separate

influences on carbon measurements (e.g., sample r, specific analytical method, and artifact

29 

# Arifact corrected CSN OC data, using netw ork average fbc values, are available on

http://www.epa.gov/airexplorer



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corre ction), the only definitive data to show comparisons between CSN and IMPROVE are these

data generated by the CSN and IMPROVE networks. From data analyzed to date, the results

show that the IMPROVE-protocol EC is generally higher (+10 to +30%), except at 3 locations

(Phoenix and Tonto, AZ and Rubidoux, CA) where th e IMPROVE EC is lower (-2 to -8%). The

average differences appear to vary by location a nd the difference may therefore be related to the

type or composition of the carbon aerosol. On th e other hand, OC concentration is greatly

affected by sampling artifact, sampler flow rate and filter size, and therefore the inter-network

differences are more difficult to characterize. Application of simp le adjustments, say using field

blanks, may not be sufficient to adjust CSN da ta to look like IMPROVE-p rotocol concentrations

(Flanagan). Chow, Watson (at DRI) and White (at UC Davi s) are also examining this issue for

EPA and recommendations will be forthcoming.

National consistency in carbon measurements for source attribution, model evaluation

and urban-rural comparisons is very importa nt. Starting in calendar year 2007, EPA began

transitioning the urban CSN to the IMPROVE analytical protocol, with an IMPROVE-like

sampler (i.e. URG3000N sampler, with identical PM 2.5 

# particle size separator, filter size and flow

rate, but with mass flow control) and will be em ploying secondary filters and 24-hr duration field

blanks to help estimate carbon sampling artifacts. Fifty-six sites have been established and

produced two months of collocated data during May-June 2007. Preliminary analysis of these

collocated data show similar IMPROVE-CSN relati onships as discussed a bove. The transition of

CSN will continue in two additional phases. Phas e 2 will begin early 2008 with the conversion of

about 65 sites and Phase 3 (the last phase of about 65 sites) will begin late 2008-early 2009. See

http://www.epa.gov/ttn/amtic/file s/ambient/pm 25/spec/faqcarbon.pdf for more information on

the conversion. EPA has also reor ganized the parameter codes and data field definitions in AQS

to better differentiate current and future carbon measurement data according to collection

sampler, analytical protocol and adjustments if any for sampling artifacts.

Closing the Gap in EC Monitoring to Support PM Health Effects Research

The association between ambient concentrations of EC in PM 2.5 

# and human health effects

is a subject of considerable inte rest. This section describes a numb er of possible steps that could

be taken towards minimizing the affects of CSN protocol changes on the ability of epidemiology

projects to report useful results for consider ation in planned period ic reviews of the PM 2.5 

# NAAQS. The purpose of this section is to faci litate communication about next steps along the

lines of these steps or alternatives that are more promising. In addi tion, the OAQPS Air Quality

Assessment Division (AQAD) convened an in-person workshop of CSN and IMPROVE

monitoring program experts and selected atmosp heric scientists in January 2008 to discuss

outstanding issues related to EC and OC measurement in the two networks. The participants in

this workshop are continuing the discussion by e-ma il and conference calls to develop a 1-2 year

research plan, possibly leading to changes in the operation of one or both monitoring networks

and/or the post-processing of their monitoring data.

In order to improve the data usability of EC for epidemiol ogical studies and subsequent

PM NAAQS reviews, the following steps may be explored:

Po ssible Data Analysis Steps

1. Relating Old CSN TOT and New CSN TOR Data: Available data should be rigorously

analyzed to determine if there is a reasona bly good method for predicting the former from

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the latter (including using sub-fraction inform ation and possibly using site/day variables)

or vice versa. Data that in cludes the effect of the samp ler difference should also be

analyzed. The purpose would be to determin e whether double laborat ory analysis of the

sort described in Items 2 and 3 below is actually needed to close the time series

discontinuity, versus relying on a ma thematical conversion or algorithm.

a. There are some data sets available now that can be used to address this question.

Discussion Question: If new and old protocol CSN car bon data cannot be quantitatively

related or adjusted so that a consistent time se ries is available for OC and EC, can epi studies

use the unadjusted time series as long as it recognizes or accounts for the changes or

intervention(s) in the measurement process?

2. Epidemiological Sensitivity Analysis: After some number (TBD ) of months of doublyanalyzed samples are available from Items 5 and 6 below, epidemiologists should test

whether the two physical measures of EC are similarly associated with health effects of

interest. This would help determine the le ngth of time and scope needed for items 4, 5

and 6 below.

Discussion Question: Can sensitivity testing of epi mode ls be done to explore whether the

change in carbon measurements has a significant impact on results?

Po ssible Pilot/Investigative Studies

3. Sampling Effects on EC measurements: Test the hypothesis that sampler model,

artifact correction (subtracti on of field blank or backup f ilter blank values), and quartz

filter brand (Whatman QMA vs. Pallflex) ha ve a small enough effect on measured EC,

such that epidemiology studies can span discon tinuities in these aspe cts provided there is

consistency in the EC thermal analysis, by ta king second punches fr om relevant filters

already in cold storage. There are 517 filter pairs available from 56 sites in May and June

2007, each pair consisting of an old-CSN filter and a new-CSN filter. The two kinds of

filters have already been tested for EC once each, with the old and new laboratory

method respectively. Of these, 53 sites used the old CSN method with the MetOne

sampler, which has the flow rate most di fferent from the new URG3000N sampler (~6.7

vs. ~22.7 L/min). The sensitivity of EC to sa mpler type (independent of lab analysis) can

be tested by taking a second punch from the old CSN filters and an alyzing them with

IMPROVE_A, and comparing the results to the IMPROVE_A result on the new CSN

filter. Alternatively or in addition, the co mparison can be done the other way by taking

the extra punch from the new CSN filter. This comparison may not be indicative of

sensitivities during other seasons.

4. There are about 250 site-months of collo cation data between old CSN TOT and

IMPROVE TOR (up until January 2005) and IMPROVE_A TOR (after January 2005),

spanning all seasons, in selected urban areas. 30 

# Some of these filters could be analyzed a

second time, as described immediately a bove to evaluate sampling effects on EC

measurements.

Di scussion Questions: What are the most important data a ssessment attributes or metrics for

the comparison to satisfy the needs for health studies? Can sensitivity testing of

30 

# Sites are in Atlanta, Birmingham, Allen Park , MI, Fresno, New York City, and Pittsburgh.



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epidem iologic models be done to explore whet her the change in carbon measurements has a

significant impact on results?

Po ssible Gap-Filling Data Collection (Short and Long-term) to Extend the Continuity of

the OC/EC time series

5. At some number (TBD) of converted CS N sites of most importance to ongoing

epidemiology studies, analyze some number (TBD) of quartz filters from the new

URG3000N sampler with the old CSN-TOT method, in addition to the IMPROVE_A

measurements. Double analysis is possible becau se a single filter can usually allow three

separate analyses using three separate punches from the filter. This would give a

continuous time series using the old CSN-TOT lab method. There would be a

discontinuity in sampling method.

a. Same-time, double analysis would be implemented for newly collected filters as

they are received. 31



# b. Filters collected since convers ion that have completed analysis would be retrieved

from cold storage and re-analyzed also.

6. (Additionally or Alternatively to Item 2 above) At some number (TBD) of converted

CSN sites of most importance to ongoing epid emiology studies, retr ieve pre-conversion

filters from cold storage and perform a sec ond analysis for EC using IMPROVE_A. This

would give a continuous time series usi ng the new IMPROVE_A lab method. There

would be a discontinuity in sampling method.

7. Depending on the outcomes of steps 3 and 4, the number of sites subject to double

analysis could be reduced (because no importa nt differences are discerned) or increased

to include more sites of interest (because it becomes clear that onl y consistent physical

measurements are useful.)

8. Presently, EPA has no plan for long term ope ration of any sites at which the old CSN

method (using the dominant old sampler type an d the old TOT analysis protocol) and the

new CSN method (URG300N and IMPROVE_A) ar e collocated. A possi ble step is to

establish some such sites and commit to thei r operation until these EC (and related OC)

issues are well settled. Depending on logistic s and monitoring agency agreement, these

could be the same 6 sites where IMPROVE and one CSN samplers already operated on a

collocation basis. 32



# Discussion Questions: What are the number and location of sites that are of most interest or

importance to ongoing epidemiological studies? If long-term comparisons of old and new

CSN are needed, where should collocated measur ements be obtained, and at what frequency,

and for how long? What are the most important data attributes or metrics for the comparison

of new vs. old CSN protocol measurements to satisfy the needs for epi studies (e.g.

sufficiently high correlation; cons istent day-day and seasonal vari ability)? What is judged to

be sufficiently high correlation; what is “consistent” temporal behavior?

31 

# It is not urgent to begin this same-time double analysis because any filters tested only with IMPROVE_A can be

retrieved from cold storage later if necessary.

32 

# Sites are in Atlanta, Birmingham, Allen Park , MI, Fresno, New York City, and Pittsburgh.



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9. As presented by Frank at the 2006 mee ting in Boston, carbon by material balance

between non-carbon species and FRM mass (“ SANDWICH” technique) may have value

in providing a consistent and independently derived time series of carbonaceous mass as

measured on Teflon filters. This alternative indicator can minimally assist with quality

control of newly derived procedures. To help isolate the OC and EC portions of the mass

balance estimates, new measurements from ar chived Teflon filters may be needed to

compensate for network changes in the thermal optical procedures used on collocated

CSN measurements (e.g., optical measures of black carbon in combina tion with statistical

procedures to establish site speci fic correction factor for “EC”).

What About Daily EC?

EPA ORD is investigating the feasibility of limited speciation on daily FRM collected

Teflon filters, where available. This may i nvolve performing XRF analyses and possibly an

additional optical measure of black carbon in combin ation with statistical procedures to establish

a site-specific correction factor fo r “EC”. This work has not star ted and is not expected to be

available by April 2008.

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Table 1. List of EPA CSN/IMPROVE Collocated Study Sites

Site Name AQS Site ID Urban/

Rural CSN Sampler Start

Date End Date

Atlanta

(Decatur), GA 13-089-0002 Urban Andersen RAAS

until 1/2006 then

MetOne SASS 4/2004 Ongoing *

Birmingham,

AL 01-073-0023 Urban MetOne SASS

(URG3000N for

carbon May 2007) 4/2004 Ongoing

Detroit (Allen

Park), MI 26-163-0001 Urban MetOne SASS 11/2003 Ongoing *

Fresno, CA 06-019-0008 Urba n MetOne SASS 9/2004 Ongoing

New York

(IS52), NY 36-005-0110 Urban R&P2300 until

1/2006 then

MetOne SASS

(URG3000N for

carbon May 2007) 8/2004 Ongoing

Pittsburgh, PA 42-003-0008 Urban MetOne SASS 4/ 2004 Ongoing *

Houston, TX 48-201-1039 Urban URG MASS 5/2004 9/2005

Chicago, IL 17-01-0076 Urban URG MASS 11/2003 9/2005

Rubidoux

(Riverside), CA 06-065-8001 Urban MetO ne SASS 9/2004 9/2005

Phoenix, AZ 04-013-9997 Urba n MetOne SASS 10/2001 12/2003

Tonto NP, AZ 04-007-0010 Rura l MetOne SASS 10/2001 12/2003

Seattle, WA 53-033-0080 Ur ban URG MASS 10/2001 12/2003

Mt. Ranier, WA 53-053-0014 Rural URG MASS 10/2001 12/2002

Washington DC 11-001-0042 Urban Andersen RAAS 10/2001 12/2003

Dolly Sods, WV 54-093-9000 Rural Andersen RAAS 10/2001 12/2003

* Continuing with IMPROVE carbon aerosol measurements starting July 2005. Full IMPROVE speciation at other

sites.



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B-8 References

Chow, J. C., Watson, J.G., Chen, L-W., Chang, M. C.O., Robinson, N.F., Trimble, D., Kohl, S.,

(2007) The IMPROVE_A Temperature Protocol for Thermal/Optical Carbon Analysis:

Maintaining Consistency with a Long-Term Database, J. Air & Waste Management Association ;

57: 1014-1023.

Currie , L. A., B.A. Benner, Jr.

, J.D. Kessler

, D.B. Klinedinst

, G.A. Klouda

, J.V. Maroif

, J.F.

Slater

, S.A. Wise

, H. Cachier

, R. Cary

, J.C. Chow

, J. Watson

, E.R.M. Druffel

, C.A.

Masiello

, T.I. Eglinton

, A. Pearson

, C.M. Reddy

, O. Gustafsson

, J.G. Quinn

, P.C. Hartmann

, J.I. Hedges

, K.M. Prentice

, T.W. Kirchstetter

, T. Novakov

, H. Puxbaum

, H. Schmid . (2002).

A critical evaluation of interla boratory data on total, elem enta l, and isotopic carbon in the

carbonaceous particle reference material, NIST SRM 1649a. J. Res. Natl. Inst. Stand. Technol.

, 107: 279-298.

Flanagan, Jam es B., Max R. Peterson, R.K.M. Ja yanty, and Ed E. Rickman. Analysis of PM2.5

Speciation Network Carbon Blank Da ta, Research Triangle Instit ute, Research Triangle Park,

North Carolina 27709 (2003). http://www. rti.org/pubs/OCEC_flanagan_2003.pdf

Frank, N. H., Retained Nitrate, Hydrated Sulf ates, and Carbonaceous Mass in Federal Reference

Method Fine Particulate Matter for Six Eastern U.S. Cities, J. Air & Waste Manage. Assoc. 2006,

56 , 500-511.

Frank, N. H., Carbon Measurements and Adjust ments. Presented at HEI/EPA Workshop on Air

Quality Data in Health Effects Research , Newton Marriott Hotel, Newton, MA, November 30-

December 1, 2006 http://www.healtheffects.org/AQDNov06/AQD_Frank.pdf

Kim, E. , P.K. Hopke and Y. Qin (2005). Estim ation of Organic Carbon Blank Values and Error

Structures of the Speciation Trends Ne twork Data for Source Apportionment. J. Air & Waste

Manage. Assoc. 55:1190–1199.

Kim, E. and P.K. Hopke (2006). Characterization of fine particle sources in the Great Smoky

Mountains area; Science of the Total Environment: 368: 781–794.

Pun, B. HEI Air Quality Database. http://hei.aer.com/aboutDatabase.php

Schmid, Heidrun, Lothar Laskus, Hans Jürgen Abraham, Urs Baltensperger, Vincent Lavanchy,

Mirko Bizjak, Peter Burba, Helene Cachier, Dale Crow, Judith Chow, et al. (2001). Results of

the “carbon conference” intern ational aerosol carbon round robin test stage I. Atmos. Environ.

35: 2111-2121.

Solomon, Paul. Organic Carbon Artifacts. Presen ted at Mid-Atlantic Regional Air Management

Assoc., June 29, 2004. http://oaqpswww.epa.gov/tom/wiki/pmtea m/files/MARAMA_O C_Artifacts_6-29-

04_Conf_Call.ppt

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# Appendix C: Session II: Accessing Am bient Air Monitoring Data - Access to

EPA’s Air Quality Data for Health Researchers

Questions on this draft white paper should be directed to Nick Mangus, EPA/OAQPS,

mangus.nick@epa.gov , (919) 541-5549.

Introduction

A common refrain from policymakers, analysts , and scientists is that obtaining the air

quality data which they need is a challenge. This paper outlines the current collection and

dissemination framework for air quality data and poses “charge questions” to the health-research/

epidemiology community. The answers to these que stions will help us at the EPA improve our

offerings.

To frame the charge questions, this document describes a relatively new EPA system, the

AQS Data Mart, and contrasts it with the HEI Air Quality Database, which was put in place to

provide access to PM components and other data for health res earchers. Finally, the charge

questions are presented.

Background

The collection, storage, and dissemination of air quality data is a complex process

achieved by a series of separate groups of hardware, software, and people. As technology has

advanced and the number of distinct sets of user groups (those with different data or analytical

needs) have proliferated, the problem for any individual finding precisely what they need has

only gotten more complex. Adding to this complexity are intermediate “value-added” providers

who may integrate, visualize, or otherwise post-process data fro m various sources. Thus, users

can invest in their own data gath ering and processing or they can rely on an ar ray of intermediary

providers. We also have data fr om special studies. The quality is (probably) high, but the data

may not be readily available to others. So, EPA w ill always be the provider of certain base data,

but we may not have it in the desired form, inte grated with other desirable data (emissions or

population), or presented in the de sired manner. There will always be the possibility for a valueadded provider to enhance the EPA data or integrate it with other data.

The following diagram is a simplified view of the components that accomplish the

collection and dissemination tasks at the EPA. It will be used to explain how data are collected,

stored, and provided by EPA a nd how the HEI acts as a value-added post-processor.

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The main part of the diagram shows the major components of the EPA’s Air Quality

System (AQS). Beginning from the left hand side, samples are collected in the field by monitors.

Some of these samples are analyzed in situ , others are collected by the State, tribal, or local

agency responsible for the monitor and analyzed at laboratories. Either way, the agency

responsible for the monitor is also responsible for ensuring the measurem ents are reported to

AQS. It should be noted that only monitors within the EPA national ambient air quality

monitoring network must have their data repor ted to AQS, for other monitoring networks or

special studies (e.g., The Texas PM 2.5 

# Sampling and Analysis St udy) it is optional and the

information may be stored in another system (e.g., NARSTO).

AQS is the EPA system designed to collect and store the monitored information. When

users are allowed unlimited access to download in formation from such collection systems, the

demands put on the system by voluminous requests can compromise the ability of the system to

fulfill its collection function. To alleviate this problem, softwa re engineers developed the AQS

Data Mart which stores a copy of the informati on from the AQS and allows users to download

data. It is a generic “retrieval” tool that provides the ability to query any information, but it does

not provide significant data exploration or analysis capabilities . These capabilities are left to

downstream “value-added” tools.

EPA is in the process of transitioning our user applications designed for downloading

information from the AQS database to the AQS Da ta Mart database. The right hand side of the

diagram represents the several places to query or download air quality information that EPA

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provides. E ach has been targeted to a specifi c audience: the general publ ic, data analysts, or

researchers. The diagram indicat es which ones are still connected to AQS and the ones that have

been transitioned to the AQS Data Mart. Note that the small cylinders by three of the systems

still getting their data from AQS i ndicate that they must copy data and store it separately so as

not to impose large loads on AQS. One of the advant ages of using a data mart is to alleviate the

need to store these data again.

As an example, raw PM 2.5 

# data collected by EPA is available to external users in three of

these EPA “front-ends”. Large text files can be downloaded from our website (The TTN Data

Page at http://www.epa.gov/ttn/airs/airsaq s/detaildata/downloadaqsdata.htm ). The AirExplorer

site can be used to query, plot, and map these da ta. Finally, the Data Mart Direct Interface can

be used to query the data. Each of these to ols has advantages and disadvantages depending on

the needs of the user. For more information a bout all of the front-ends listed in the diagram,

please see Appendix A.

Beyond AQS and the related EPA systems, there are many other stakeholders involved in

the collection and dissemination of air quality data, each with their own activities and possibly

systems. AQS is likely the largest repository, but there may be additional information of interest

to health researchers stored in other places. Th ese additional stakeholders are represented by the

other “layers” in the diagram. Elsewhere in EPA there are data collection and dissemination

systems (CASTNET and AirNow in the Office of Air and Radiation; RSIG and PHASE in the

Office of Research and Deve lopment; and Environmental Geoweb in the Office of

Environmental Information). Additionally, EP A has other systems th at present public and

management views of air quality data.

The next layer out represents EPA partners, those who operate in cooperation with EPA,

like the Health Effects Institute, Colorado State Un iversity, etc. who maintain data dissemination

systems (many that integrate data from outside of AQS). Also in this layer are special studies

(DEARS, NMMAPS, etc.) that manage the full li fecycle of air quality data management from

collection to dissemination. Ge nerally these non-governmental partners and EPA communicate

with each other and the action that one takes ma y influence the other. Considering again the

PM 2.5 

# example, the HEI Air Quality Database uses the EPA provided data for PM and the nearest

gas phase monitors, and integrates EPA emi ssions and non-EPA population and meteorological

information. This is a value-added service to provide a custom-tailore d solution to a specific

community. Finally, there is the layer entitled “Others,” which represents those stakeholders

who operate independently. These are the “unkn own unknowns” in terms of additional data that

may be collected or made available.

Each of these groups brings with them a di fferent list of what they can do easily, what

they can do with difficulty, and what they ca nnot do. That is, each provides a degree of

flexibility or constancy that makes them the best at providing a particul ar product or service.

Collaboration, building on the strengths of each organization, is critical and one organization

may have to take up the role of integrator and communicator so the research community knows

where to get vital information. That is, if a cl earinghouse listing all available databases, datasets,

and access systems is needed, someone will have to manage its creation and maintenance.

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The rem ainder of this paper discusses only one EPA access mechanism, the AQS Data

Mart Direct Interface, which was designed specif ically to address the needs of the research

community. EPA perceived these needs as primarily the ability to locate and extract large sets of

data. The Data Mart was made available for in ternal EPA use in mid-2006 and for external use,

along with the Direct Interface, in early 2007. Use has been growing steadily since then.

Overall, it has been well received by most of those who have accessed and used it. Initially a

pilot project, the reaction from users has been positive enough that EPA management has

committed to ongoing support for the system. Most of the negative reac tion falls into two

categories: the user friendliness of the system a nd the documentation of the data. To address the

first, we continue to add featur es and improve usability to make the Data Mart as friendly as

possible to the research communit y. Documentation of the data is not a problem inherent to the

Data Mart, but we realize it is much needed, so we are also addressing this as we can.

The remainder of this paper will introduce th e Data Mart Direct In terface, compare it to

the HEI Air Quality Database, and place “charge” questions to the research user community to

help us continue to improve these systems to meet your needs.

Contents of the Data Mart

The Data Mart contains every measured (“raw”) and aggregated (“daily and annual

summary”) value reported to AQS from January 01, 1980 to the present. It also contains all of

the same site and monitor descriptive data and measurement metadata in AQS. We have

converted most data-entry codes to plain Engl ish words to help with the interpretation of

downloaded data.

There are no additional quality assurance steps performed on the data in the Data Mart, as

the data in AQS are generally c onsidered to be of the highest quality. Data must undergo many

quality control steps as part of the loading pr ocess before it is saved in the AQS database.

Likewise, submitters are required to assure that the monitor is operating properly and has passed

precision and bias checks before loading the data. Finally, each year, EPA and the submitter

review the data for completeness and correctness before the data are “certified” for regulatory

use.

It should be noted that IMPROVE (visib ility network) and SANDWICH (modeled PM 2.5 

# species) data are not generally reported to AQS . However, EPA staff has recently loaded the

IMPROVE data for 1988-2005 into AQS and the load ing of SANDWICH data is planned. As of

January 14, 2008, there were 1.67 billion raw measurem ents for 885 different parameters in the

database (there is a profiling spreadsheet unde r the documentation section of the web page).

The Data Mart is refreshed from AQS each weekday night, so it always has the latest

available information. However, since data up to 4 years old can be submitted to AQS at any

time, and there are special windows for “historical” data updates, any of th e contents can change

at any time. That is, there is no freezing or sn apshotting of data into a static version in the

database.

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Accessing the AQS Data Mart

The AQS Data Mart can be accessed by visiting the webpage,

http://www.epa.gov/ttn/airs/aqsdatamart , and following the “Access” link. Registration is

required, and a user ID and password needed for access. You may sign up for your own account

or use a guest account with user = aqsdatam art@epa.gov and password = AQSdatamart1 (case

sensitive). Access is provided by an applicatio n that you can either run in your web browser or

download and run on a PC. The a pplication is used to submit a query. A query lets the user

select the geography, substance (parameter), time, metric, and optional data to return. The Data

Mart currently has five qu eries, summarized below.

Query Description

R ecommended, returns any single raw, daily, or annual variable with metadata and is very

efficient Values

Monitor Returns descriptions of the monitoring site and equipment

Annual

Summary Returns all annual summary aggregate statistics for the monitors selected

Raw Data Returns raw data in the AQS trans action format - recommended only for AQS users

Sites by

Threshold Returns a list of sites that meet a specific data-related threshold that you specify



# When the query is complete, results can be downloaded using the application or by

following a link in an email message sent to the user. All output is in XML format, but with

embedded links to stylesheets for user-friendly display.

The Data Mart is intended as an extraction system only and EPA does not plan to provide

analytic or graphical capabilities with the Data Ma rt. However, some of the other tools that EPA

provides do have these capabiliti es (see Appendix A for details).

Contents of the HEI Air Quality Database

In September 2005, a group funded by the Heal th Effects Institut e (HEI) and led by

Christian Seigneur and Betty Pun at Atmosphe ric and Environmental Re search (AER) launched

a website/database to facilitate health effects studies that require deta iled knowledge of air

pollutant levels and other relevant informati on at selected sites across the US. The HEI Air

Quality Database combines information on PM 2.5 

# components collected at monitoring sites in the

Chemical Speciation Network (CSN); meteorological variables; and levels of gaseous pollutants

(SO 2 

# , O 3 

# , NOx, and CO) from monitoring sites at or near each CSN site. Metadata are provided

for each monitoring site, such as its geographic coor dinates, state, as well as county, city location

information, population, and emissions data for n earby point, area, and mobile sources. AER

updates information in the HEI Database every few months and is currently funded to do this

through 2008.

Accessing the HEI Air Quality Database

The HEI Air Quality Database can be accessed by visiting the webpage,

http://hei.aer.com . Once you obtain an account by following the instructions on this page, you

can access the site browser and list building, data base queries, and users’ guides. The general

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data retrieval process consists of four steps: browsing sites, de fining and saving a list of sites,

extra cting data for the sites in a saved site lis t, and, downloading the extr acted air quality data.

Comparison of AQS Data Mart and the HEI Air Quality Database

The HEI Air Quality Database represents a value-added service over what EPA provides

for a scientist looking for specific speciated PM 2.5 

# data to evaluate in health research studies. So,

a natural starting point for such a user would be th e more tailored HEI system. If, however, that

system does not have some particular information th at the user needs, they can revert to using the

EPA system. The EPA system is broader, but less refined; the closer the us er gets to the source,

the more raw material they must process to get a finished product. The following table compares

some of the features of the HEI Air Quality Data base and the AQS Data Mart to illustrate some

of these trade-offs.

Feature HEI Air Quality Database AQS Data Mart

Site browser Yes, with maps to help No

Site finder Yes, with multiple-variable filter Yes, via a single-variable “sites by

threshold” query

Query from saved list Yes. Station lists may be saved and

re-used No. Query based on geography and

parameter or single site

Query by any geography Yes Yes

Air quality data for PM 2.5 

# , O 3 

# , CO, NOx, NO 2 

# , & SO 2 

# Yes Yes

Air quality data for all other

parameters No Yes

AQS met data Yes Yes

Integrated non-EPA met data Yes No

Emissions data Yes No

Census data Yes No

On-line help Yes No

Off-line help Yes Yes

File format CSV XML (CSV planned)

Data returned in one file No Yes

Update frequency (versions) Quarterly Daily

Build your own query Yes N o



# T o summarize the key differences:

 

# The HEI interface is more tailored to the PM 2.5 

# analyst.

 

# The HEI interface contains emissions, census, or NCDC meteorology data, the Data Mart

does not.

 

# The Data Mart contains all ambient data re ported to AQS (not just PM, meteorological,

and NAAQS gases).

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 

# The Data Mart only contains special studies data (e.g., supers ites) if it has been loaded

into AQS.

Interpreting the Data

Between data element names, report headings, and data transfer formats, there are almost

2000 named data elements relating to air quality th at EPA makes available. In addition, some of

the values in those fields need individual documentation to properly describe them (for example,

what is the difference between a SLAMS and a NAM S monitor type). To help the user identify

and perhaps understand the data they have, the EP A created an annotated, cross-referenced index

called the “Field Guide to Air Quality Data”. It is available in the documentation section of the

Data Mart web page. There is al so a list server that can be used to ask questions or monitored

for system status.

Charge Questions - Introduction

To help prioritize and define future activities so that we can better meet the needs of the

members of the research community, EPA has comp iled a list of “charge questions” for invitees

to this conference to consider. The overarching issue is connec ting the data users to the data

providers. For EPA and our partners to improve on this, we need to fu lly understand the data

needs of the health rese arch community. The more specifically the needs can be elucidated, the

more concrete actions that can be taken to improve the situation. We are interested in feedback

from users and potential users of air quality data and retrieval tools. This paper is concerned

only with access to existing data; possible new da ta collection activities are covered elsewhere.

Standout Charge Questions

In previous interactions with data users and the health research co mmunity, three questions

repeatedly come to the forefront as seemingly ubiqu itous and critical. These issues are also at a

high level and decisions on them will potentially impact decisions on the other charge questions.

To complicate matters, there is not a single unifyi ng idea that all agree is progress in the right

direction on these issues. Thus, these questions are presented in more detail and with possible

solutions to initiate discussions.

1. Data versioning/snapshotting : How often should EPA releas e data and how should we

indicate that it has changed? The EPA, HEI, and others cu rrently provide data via many

applications. The data in those applicati ons are generally update d on a schedule or as

new data become available. For example, th e AQS Data Mart is updated every day with

new submissions and changes to AQS. Howeve r, new data or changes coming into AQS

may be 10 years old. So a value in the AQS Da ta Mart representing a sample taken in the

late 1990s may change today. Likewise, th e HEI Air Quality Database is generally

updated as the EPA makes new AQS “flat file” da ta extracts availabl e on our web sites.

This is usually done quarterly and without not ice, thus the HEI database changes about

quarterly; and the same 10 year rule applies. The key differe nce is that if you get data

from the AQS Data Mart and your colleague ge ts the “same” data the next day, the data

may have changed. If you are using the HEI da tabase, the data may also have changed in

one day, but the odds are less and the data vi ntage is clear in the “about” pages of the

website. The stability of data for verifying and comparing research is essential, so the

charge question is this: How often should EPA release data and how should we

indicate that it has changed? One solution to this issu e is to only make new data

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available ou tside EPA once per year. Thes e data would be rel eased on Independence

Day and would be up-to-date through the prior year. Th is option provides greater

stability to the data but may not be tim ely enough for particul ar studies or NAAQS

revisions. A second solution is for EPA to contin ue to release data as it is received. Each

value would be date-stamped with the date it last changed along with the date it

represents. This allows for comparisons of data sets but requires more data to be

downloaded and analyzed by the user. There are many intermediate options that could be

implemented.

2. Topic-focused portals : Are topic focused portals needed fo r air quality data? If so, what

should those portals be and what should they contain? A strength of the HEI Air Quality

Database is that it is geared towards health researchers evaluating speciated PM 2.5 

# data

and the user interface provides tools and information specifically targeted to this user.

The AQS Data Mart, on the other hand, is ge neric and targeted at anyone wishing to

download air quality data. An annotated map of the PM 2.5 

# speciation sites on the HEI

page helps the user understand and find the da ta they need. An analogous map of all

5,000 sites represented in the AQS Data Mart would only overwhelm and confuse users.

Custom tailored “portals” into data, like HEI’s , are very helpful to the user, especially

when they have an interest limited to le ss than everything available. The EPA is

reasonably good at providing data but is ofte n constrained in the technology we can use

to provide descriptive and anal ytical tools. Li kewise, we are sometimes not able to

quickly secure funding to add tools to respond to developing areas of interest. This may

be a place where the flexibility of external organizations can be used to provide a more

custom, and therefore useful, experience. Are topic-focused porta ls needed for air

quality data? If so, what should those portals be and what should they contain? For

example, there could be portals specific to PM 2.5 

# speciation, ozone and precursors, toxics,

organic compounds, etc. Given the new technologies, a portal that resides outside of the

EPA can have live access to a single, consistent, stable database within EPA.

3. Accessibility of non-AQS data : The AQS Data Mart stores data from the national

ambient air quality monitoring network(s) a nd, as previously mentioned, has recently

begun to add some data from other networks and “special studies.” Is it important to

have access to data from local, short-term, air quality special studies? Examples

include MESA-Air, DEARS, Supersites, and ultr afine particle project s. If these data

should be included, how should it be done? For example, to be loaded into the AQS Data

Mart the data must match the monitor paradigm (no remote sensing or mobile monitors),

it must meet format and quality requirements , and it must have associated descriptive

data (e.g., method used, sampling schedule). Getting new data to match EPA’s data

standards are often labor-inten sive activities – are they wo rth it? Would EPA have to

correct and load these data into the AQS database (or a “research” copy of the AQS

database)? Would EPA be able to commit the resources to doi ng this? As an alternative,

EPA can provide information to managers of new studies about the data format and

content standards we have so that the data ca n be collected in a way that could be more

easily shared and compared with AQS data or other new data collected using the

standards. If this special study data remains out side of EPA systems, is there a role for a

clearinghouse? The clearinghouse could keep an up-to-date list of monitoring efforts,

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databases, contents, and appropr iate uses. Issues to be c onsidered include : how resource

intensive would this effort be and who w ould develop and m aintain this clearinghouse?

Ot her Charge Questions

Th e remaining charge questions are more st raight-forward than the standout charge

questions. They are related to how individuals gather and use da ta rather than community-wide

concerns.

4. What are the key data that you need? Is any of this currently collected but not

available?

5. Is there a particular way that you need data organized, grouped, or formatted?

6. W hat data elements other than measurements do you need?

7. W hat is the typical domain of the data you need ( time

, space , and parameter

selections; for example, 3 years, several ci ties, and 4 parameters; or 1 year, national,

44 parameters)?

8. Are there “profiling” reports – descriptions of which sites colle ct which data, how

complete the data are, etc. – that you need?

9. Would you rather query a database or have a large list of files that you can select

from to download (like

http://www.epa.gov/ttn/airs/airsaqs/ detaildata/do wnloadaqsdata.htm but with more

geographic resolution)?

10. What would your ideal query builder/interface look like?

11. Are there pieces of data that we provide or questions that we ask that confuse you?

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# Appendix C.1 – Other Data Access Mechanisms

EPA has many places to access air quality data. Each of these websites or applications was

designed for a specific target audience, for example, the general public con cerned with acute health

issues, the general public concerned with long-ter m air quality where they live, the general public

interested in air quality comparisons between multiple locations (for living, vacationing, etc.), data

analysts concerned with regulatory compliances, data analysts contributing to policy decisions, and health

researchers. We consider a researcher to be someone who is looking to download raw data; either in large

volume or in small, discrete sets that are difficult to tease out of large published datasets. Each of these

websites or applications presents a unique front end fo r queries, charts, or maps that are geared toward

their target audience.

EPA is developing a “portal” to list all of the sources of air quality (and emissions) data that are

available and link directly to their access pages. This portal is at the following web address:

http://www.epa.gov/oar/airpolldata.html . Below is a table comparing key information about each of the

available EPA-maintained systems for air quality da ta (including AirNow and CASTNET which contain

data not in AQS). The systems are described at the link above. (Key: a filled circle means “yes” and an

empty circle means “some”.)

System Level of

Detail Time Substances Outputs AudienceRaw (samples & NAAQS)Daily sums & avgsAnnual sums & avgsQATime range of most detaileddataOzone + PM2.5Other CriteriaToxicsPM2.5 Adj. SpecPM2.5 Unadj. SpecOtherCanned queries: tabularCanned queries: mapsAd hocPublicSLT AnalystsResearchers



# AQS ● ● ● ● 1994 – Present 

# ● ● ● ● ● ● ● ●

AirNow (Tech) ● ● 1999 – Present 

# ● ○ ● ● ●

AirData ● 1996 - 2006 

# ● ● ● ● ●

AirExplorer ● ● 1996 – 2006 

# ● ● ○ ● ● ● ● ●

AirCompare ● ● 2000 – Present 

# ● ● ● ● ●

AQS Data Page ● 1994 – 2006 

# ● ● ● ● ●

NATA (modeled) ● 1996 & 1999 

# ● ● ● ●

Air Trends ● 1990 – 2005 

# ● ● ● ● ●

AQS Data Mart ● ● ● 1980 – Present 

# ● ● ● ● ● ● ●

CASTNET ● ● 1987 - 2005 

# ○ ● ● ●

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# Appendix D: Session III: Ambient Ai r Monitoring for Health Research - Air

Quality Sampling: Benefits and Costs of Daily Health Targeted Monitors for

Fine Particle Components

Questions on this draft white paper should be directed to Dr. Barbara Glenn, EPA/NCER,

glenn.barbara@epa.gov ; (202) 343-9721.

INTRODUCTION

EPA’s air quality datasets are generally rec ognized and valued primarily for their use in

ascertaining compliance with the National Ambi ent Air Quality Standards (NAAQS), developing

State Implementation Plans for the improvement in air quality, and providing timely air quality

data to the public. EPA’s air quality datasets also are essential to extramural and intramural

health research addressing scientific uncerta inty related to the current NAAQS and to the

assessment of the possible health benefits of a ny new air quality standard. These health-related

uses of EPA’s air quality datasets are an importa nt consideration in the design and conduct of the

national air quality monitoring network. As sp ecialized monitoring networks have begun

providing information on the comp osition of particulate matter, epidemiologic researchers are

striving to address a major research priority defined by the National Academy of Sciences

National Research Council (NRC)—a ssessing the health effects of PM components and sources.

The NRC reports on “Research Priorities for Airborne Particulate Matter” repeatedly

emphasize the importance of research to assess the relationships betwee n particle composition

and health responses. According to the fourth report, “Progress on assessment of hazardous PM

components is central to the national research por tfolio and to any refinement of the current

mass-based NAAQS for PM....A better understanding of characteristics that modulate toxicity

could lead to targeted control strategies spec ifically addressing those sources having the most

significant adverse effects on public health.” (NRC 2004)

O n November 30, 2006, the Health Effects Inst itute (HEI) and EPA, in conjunction with

the annual EPA PM Centers meeting, convened a meeting of the rese arch and air quality

management communities to discuss the use of EPA’s air quality datasets for health research on

particulate matter (PM). Participants raised several issues that complicate the design and

interpretation of epidemiologic research on PM 2.5 

# mass, components, and sources. Participants

emphasized that the lack of daily concentra tion measurements for fine particle mass and

components in key locations was severely affecting their ability to design and conduct

epidemiologic studies that would address issues of scientific un certainties highlighted in air

quality standard setting at Fe deral and state levels. This paper summarizes these issues,

proposing a range of options to address the n eed for daily data based on the November 2006

meeting and subsequent information exchange with EPA grantees, state/local air quality

monitoring representatives, HEI and EPA staff. Th ese challenges would not exist if resources to

collect daily, speciated m onitoring data were readily available. The pressing needs for these data

are increasing at a time when resources ar e decreasing and monitoring costs are generally

increasing. This draft white paper provides background information to facilitate a broad

discussion on the benefits of obtaining daily fine particle speciation measurements and to

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encourage h ealth researchers and air quality e xperts to work together to creatively identify

solutions that address the need for daily data while understanding the resource constraints and

competing needs for monitoring data.

The goal of this discussion paper is to dr aw attention to the importance of specific

monitoring data needs in planni ng health research studies, speci fically related to evaluating

potential public health impacts of fine particles. Epidemiologic st udies relating daily variation in

ambient air pollutant concentrations with disease- specific mortality or morbidity have been very

important for providing the scientific basis for r ecent standard-setting for PM. Some of the key

policy relevant issues considered in evaluating the PM NAAQS include:

 What are the potential public health impacts associated with exposur es to specific size

fractions, chemical components, sources an d/or environments (e .g., urban and non-urban

areas) of PM?

 What is the relationship between various he alth endpoints and diffe rent lag periods (e.g.,

less than one day, single day, and multi-day distributed lags)?

 How does spatial and/or temporal heterogene ity of PM exposures vary with different

size fractions and/or components?

Providing daily ambient air monitoring data fo r fine particle components from several

cities to health researchers would reduce exposur e misclassification, allow the use of all health

events in statistical analyses, and thereby increas e the precision of risk estimates. In addition, the

availability of these data w ould significantly decrease the leng th of time necessary to produce

study results.

BACKGROUND

Epidemiologic studies of the adverse human heal th effects of short-term exposures to air

pollutants have generally relied upon air quali ty monitoring systems established to ensure

compliance with ambient air quality standards. These epidemiologic studies contributed to

decisions in 1987 to change the indicator for th e PM NAAQS from total suspended particles

(TSP) to PM 10 

# and to decisions in 1997 to add new st andards to consider fine and coarse

fractions of PM 10 

# separately, using PM 2.5 

# as the indicator for fi ne particles and using PM 10 

# as the

indicator for purposes of regula ting thoracic coarse particles.. As regulatory efforts have

increasingly focused on reducing the mass of fi ne particles from combustion sources, the air

quality monitoring network has successfully respo nded, at considerable cost and human effort, to

the monitoring challenges. Since promulgation of the fine particle NAAQS in 1997, subsequent

epidemiologic and toxicologic research has c onfirmed the earlier scientific findings and

validated the substantial investment in ambient air monitoring.

The 2004 Air Quality Criteria Document (CD) for PM highlighted the importance of

epidemiologic studies in its evaluation of the scientific evidence. In particular, the CD

emphasized new multi-city studies that investigated the effects of short-term human exposures to

PM on mortality and morbidity using data from multiple locations with varying climate and air

pollution mixes. These epidemiologic studies we re valued because they provided information

about areas not previously studi ed, reported risk estimates for all study locations, and used the

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sam e analytical approach at each location allowing comparisons . In addition, multi-city studies

contributed to an increased understanding of the role of various potenti al confounders, including

gaseous co-pollutants, on observed associations. These studies, which combined risk estimates

across all locations, provided more precise estimates of the magnitude of an effect of exposure to

PM than most smaller-scale individual city stud ies because of their larg er sample size. Because

model results were reported for all study locations regardless of the magnitude of the observed

risk estimate, these studies also avoi ded the potential for publication bias.

The National Mortality and Morbidity Ai r Pollution Study (NMMAPS) was the first

multi-city time-series study of ai r pollution and health and serv es to illustrate the dataavailability issues highlighted in this discussion paper. NM MAPS, funded by HEI, evaluated

associations between daily mortal ity rates in 90 U.S. cities wi th the largest population and the

daily level of PM 10 

# reported for that locality in the EPA Air Quality System (Samet et al, 2000,

Dominici et al, 2003). Mortality data from 1987 to 1994 was obtained from CDC’s National

Center for Health Statistics. While location-specific risks were reported, the objective was to

construct precise national and regional estimates of mortality risk from da ily changes in ambient

PM and other criteria pollutants , thus increasing confidence in th e values of the disease-specific

risk estimates, and that these estimates were representative of those experienced by the U.S.

population as a whole. In 14 cities with da ily monitoring on at least 50% of study days,

NMMAPS also evaluated the associa tion of hospital admissions with PM 10 

# (Samet et al., 2000;

Schwartz et al., 2003).

Despite its national scope, NMMAPS was lim ited by the amount of air quality data

available for analysis. The 90-city mortality anal yses were based on air quality data in the AQS

primarily collected using 1-in-6 day sampling schedules. The 8-year mortality dataset was

necessarily restricted to only those days where PM 10 

# data were availabl e between 1987 and 1994

in each county. County-specific mean PM 10 

# concentrations were calculated for each day with

PM 10 

# measurements contributed by one or more mon itors. Almost half (43) of the 90 cities had

data from only one or two monitors and only 28 c ities had the equivalent of two or more years

(730 days) of monitoring days available. The dataset for the 20 city analysis of PM 10 

# adjusting

for other pollutants was further restricted fo r multi-pollutant models because data on all

pollutants had to be available on the same day. C onsequently, these adjusted risk estimates were

less precise. Even with these limitations, the risk estimates were determined to be robust in

several sensitivity analyses to investigate residual confounding and expos ure misclassification.

An NMMAPS sub-study of ten cities with PM 10 

# monitoring on a daily schedule (New

Haven, Birmingham, Pittsburgh, Detroit, Canton , Chicago, Minneapolis/St. Paul, Colorado

Springs, Spokane, and Seattle) systematically eval uated the potential bias associated with the use

of a single day PM concentration (Samet et al., 2000, Appendix B, pp. 54-61). Mortality data

was fit using a generalized additive Poisson regression model and polynomial constrained and

unconstrained lag models for ambient PM. Risk estimates from these models were compared to

those obtained using 1 or 2 day means. Overall e ffects estimated using the distributed lag models

were larger compared to effects estimated using the single or two-day mean lags. These analyses

showed that the mortality effect s of an increase in pollution levels on a single day are spread

over several succeeding days, or conversely, that d eaths on a single day are the result of pollution

over several preceding days. For the 90-cities, the NMMAPS mortality analyses estimated

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incre ased mortality per each 10 μg/m 3 

# increase in daily PM 10 

# using a specified lag structure (0, 1

or 2 days prior to the day deaths occurred). The 10 city sub-study using distributed lags

demonstrated that the larger multi-city study underestimated the risk associated with PM 10 

# . In

addition, consistent with prev ious reports, the NMMAPS results for morbidity in 14 cities

demonstrated that use of PM 10 

# concentrations on a single day (a one day lag) resulted in an

underestimation of the cumulative PM 10 

# effect on hospitalizations. Therefore, the flexibility to

analyze effects in relation to PM concentratio ns over several days is key to a complete

understanding of the magnitude of risk and the relevant time period for exposure to PM

components.

Many of the other times-series st udies reviewed in the CD also relied on 1-in-6 day PM

measurements including the Cana dian eight cities study (Burne tt et al., 2000; Burnett and

Goldberg, 2003). The 2004 CD was ab le to cite very few studies that relied on daily ambient

concentrations for PM indicators. As a consequence, the CD discu ssed in depth the trade-offs of

increased representativeness and precision provided by the larger, multi-site studies with the

increased uncertainties in the reported risk estimates due to expos ure misclassification.

MISSING AMBIENT CONCE NTRATION DATA AND STATISTICAL POWER

Data collection frequency is a key component of statistical power for time-series studies,

and missing data results in increased uncertainty in study results (discussed in PM Staff Paper,

Dec. 2005, p. 3-39 and CD, p. 9-41). The Staff Paper concluded that, “consistent with the CD’s

observation that uncertainty is increased in stud ies using infrequently co llected PM data, staff

judges that greater weight should be placed on thos e studies with daily or near-daily PM data

collection in drawing quantitati ve conclusions.” Daily PM m easurements in locations where

enough health events occur will support future health studies that re duce uncertainties and

thereby improve our understanding of the public health impacts of PM. Such studies will

provide important information on specific compone nts within the ambient mix of particles to

inform the review of the PM NAAQS and strate gies to implement these standards.

Statistical Power and Potential Bias

The statistical power of any proposed study is the probability that the completed study

will correctly reject the null hypothesis with a specified confidence level, usually 95%

confidence or a p-value of less than 0.05. In the calculation of statistical power, one must

specify the expected magnitude of the exposur e-health association, th e expected exposure

gradient, the sample size, the variability of the health outcome measure, and the specified

confidence level. The minimum desired statisti cal power is usually 80 %, and the formula may

be inverted to calculate the necessary minimum sample size for a specif ied statistical power.

Generally, increased exposure variab ility is associated with an increased exposure gradient and

with increased statistical power. However, exposure variability due to measurement error and

unmeasured exposure variability does not increase statistical power. For many epidemiologic

study designs, sample size is di rectly related to th e person-time of observation. For time-series

studies of air pollution in a larg e metropolitan area, the usable samp le size is largely determined

by the number of days with complete exposure information. The variability of the health

outcome measure depends on the type of measure (e.g., mortality counts or continuous biological

indicators) and on the precision with which the outcome is measure d. For time-series studies of

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the daily var iation in mortality for large urban ar eas, the variability of the outcome measure is

largely determined by the average number of da ily deaths. Everything else held constant,

statistical power for a time series study increase s relative to the square root of the average

number of daily deaths. Hence, the weights in tables 1 and 2 are the square root of the estimated

number of daily deaths, or 1% of the population (In the US, about 1% of the population dies each

year) / 365.

For air pollution time-series studies, when air quality measurements are missing, the

deaths or heart attacks that w ould be studied for those days mu st be excluded. Therefore, the

sample size (number of mortality-days) available to analyze in a locality is reduced because the

exposure data may not exist for the desired lag days. For example, if one wants to evaluate

deaths in relation to ambient pollution levels on the same day, the day before, and the day before

that (lags 0, 1 and 2), then air po llution concentrations must be available at that location for three

consecutive days. Statistical power has implications for the selection of cities in epidemiologic

studies. The cities that can be analyzed become restricted to locations with a high number of

daily events (e.g., deaths, hospital admissions, et c.) so that the required sample size will be

obtained in a reason able time period.

Dr. Kazuhito Ito, NYU, presented a slide at the November 2006 meeting that showed

statistical power curves for hypothetical time-series studies by the number of daily deaths in a

location and study duration (see Figure 1). These cu rves indicate statistical power achieved to

evaluate a hypothesized increase in daily total (non-accidenta l) deaths of 2.5% per 25 μg/m 3



# increase in PM 2.5 

# . The hypothesized increase in mortality rate was derived from city-specific

relative risks reported in the PM literature. With 1-in-3 day monitors, six years of monitoring

data would be required to achieve 80% statistical power to evaluate non-a ccidental mortality in

cities with 100 mean daily d eaths (6 years x 365 days/year x 1⁄3 monitoring days = 730 days). For

example, a study in New York City, with 180 to 200 deaths per day, would achieve 80% power

to evaluate the effect of PM 2.5 

# on nonaccidental mortality in a bout three years (3 years x 365

days/year x 1⁄3 monitoring days = 365 days). Conversel y, a study conducted in a city the size of

Seattle, with about 30 deaths per day would not achieve 50% power ev en if the study were

extended beyond six years! Furthermore, study power decreases when the focus of study is

cause-specific mortality or the iden tification of susceptible subgroups.

For many fine particle components, temporal and spatial variati on within and between

localities may be different than the variation for PM 2.5 

# mass. With greater temporal exposure

variation and spatial variation betw een cities, the statistical power to study specific fine particle

components is likely higher than for PM 2.5 

# mass. Statistical power is also enhanced if the

mortality risk associated with a spec ific component is higher than for PM 2.5 

# mass.

However, exposure error caused by uncertainti es in a study’s exposure assessment can

result in an attenuation of risk estimates and an inability to reject the null hypothesis. Exposure

error also may lead to biased risk estimates. Within a metropolitan area, some PM ambient air

measurements, such as total PM 2.5 

# mass or sulfates, show less spatial variability and a

metropolitan area may be well characterized by a single central-site monitor. Other PM 2.5 

# components, such as elemental carbon, show cons iderable spatial variability and a metropolitan

area may not be well characterized by a single centra l-site monitor. However, this uncertainty in

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exposure assessm ent related to the unmeasured spatia l variability will be differential with respect

to PM 2.5 

# component; and PM 2.5 

# components with less spatial variability would have less

exposure uncertainty. For a multi-city study focu sed on regional air pollution gradients, city-tocity differences in exposure uncertainty related to monitor location coul d affect city-to-city

differences in the observed associations with he alth outcomes and hence could be misinterpreted

as related to city-to-city di fferences in PM components.

Within the PM 2.5 

# ambient air monitoring network, th ere are approximately 900 Federal

Reference Method (FRM) f ilter-based samplers that provide 24-hour PM 2.5 

# mass concentration

data and about 600 continuous PM 2.5 

# mass monitors that provide hour ly data on a near real-time

basis. Due to the complex nature of fine particles, EPA implemented the Chemical Speciation

Network (CSN) to better understand the components of fine partic le mass at selected locations.

Chemical speciation measurements are made at 54 ‘‘Speciation Trends Network (STN)’’ sites

that are intended to remain in operation inde finitely and about 150 other, potentially less

permanent sites used to support State Implem entation Plan (SIP) development and other

monitoring objectives. 33 

# Specific components of fine partic les also are measured through the

Interagency Monitoring of Protected Visual Environments (IMPROVE ) monitoring program

which supports regional haze character ization and tracks changes in vi sibility in Class I areas as

well as many other rural and some urban areas. Together, the CSN and IMPROVE data provide

chemical species information for fine partic les that are critical fo r use in health and

epidemiologic studies to help in form reviews of the PM NAAQS.

The cities where the CSN monitoring sites are located are very important for studying

health effects associated with fi ne particle exposures. There are more than 200 sites in the CSN.

Table 1 (see associated pdf file) lists the Pr imary Metropolitan Statistical Areas (PMSAs) and

Metropolitan Statistical Areas (MSAs) ordered by population size and a weight determined by

the contribution to precision that area would make to a statistical analysis of risk. The site

locations for CSN monitors are listed within th e relevant PMSA where they operate. It is

encouraging that more than 50% of the U.S. popul ation resides in census ar eas with at least one

CSN monitor. There also are some large popul ation centers where PM components are not

measured such as Orange County and Oakland in California, northern New Jersey, and Long

Island, New York (PMSAs and MSAs where no speci ation monitors are located are highlighted

in red on Table 2). Currently, the CSN sites m easure fine particle mass and components every

third day or every sixth day. A ch ange to daily sampling would in crease the statistical power for

time-series studies.

In evaluating criteria for identifying pot ential locations for increased monitoring,

consideration could be given to CSN locations re presenting varied fine particle sources in the

eastern, western, mid-western and so uthern parts of the U.S. Futu re epidemiologic studies that

examine PM exposures at or below the current level of the PM 2.5 

# NAAQS will contribute

significantly to reducing scientific uncertainty concerning health effects. Most major US

metropolitan areas are below or close to the current PM NAAQS and can contribute useful

information on the public health impact of PM exposures. The collection of daily measurements

for PM 2.5 

# mass and key PM 2.5 

# components in metropolitan areas with high numbers of deaths and

33 

# See http://www.epa.gov/ttn/amtic/speciepg.html for more information on the PM 2.5 

# speciation monitoring

program.



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in loca tions with variation in ambient concentrati ons near the current stan dard and in the mix of

PM 2.5 

# components would inform our understanding of the relative health si gnificance of specific

PM 2.5 

# constituents and sources of PM 2.5



# .

MISSING DAYS: IMPACT ON VALUE OF RISK ESTIMATES

Missing days of sampling data presents pr oblems for epidemiology studies of health

effects associated with PM exposures over and above a decrease in statistical power and the

problems are compounded for studies of fine particle components. PM 2.5 

# components are likely

to present a large degree of va riation involving associations with different health endpoints and

time from exposure to response. This requires flex ibility in constructing statistical models and

lag structures. In addition, varia tion between localities presents co mplexities in the interpretation

of the results of multi-site time series studies. Different components predominate in different

regions of the U.S. and the correlation between PM components in each area will vary. Finally,

the temporal and spatial variability of each PM co mponent of interest within a city will vary and,

if not adequately captured in sampling data, wi ll result in exposure misclassification and an

effect on the value of risk estimates.

The NMMAPS study and other time-series studies of mortality and morbidity indicate

that risk estimates may vary between metropolitan areas or regions. There are multiple

explanations for these observ ations including, random variat ion (chance), residual confounding,

exposure misclassification, and the existence of real source-specific differences in risk. The

differences in the precision of city-specific estim ates of mortality risk associated with daily

change in PM concentration complicate the interp retation of heterogeneity in risk reported by

multi-city time-series studies or when single-city estimates show differences between localities.

Some authors have used interpolation appro aches to fill in the missing days of ambient

concentration data in order to avoid excluding ca ses for days with no air quality measurements.

These imputation methods are often based on hourly or daily air quality measurements of PM

mass or gaseous co-pollutants. Unfortunately, imputed values never carry as much information

about population exposures as measured values and any evaluation of the improved health

associations with speciated PM would be d iluted by the high proportion of imputed values.

Moreover, the error in imputation is not likely to be constant for each specific PM component;

some components will be imputed with more e rror than other components. For example, filling

in missing data with imputed values may be asso ciated with more error in studies of coarse

particle mass and fine particle components which are associated with larg er spatial and day-today variation than fine PM mass. Along with the simple imprecision of the imputed values, any

use of the gaseous co-pollutants in an imputation algorithm will necessarily increase the colinearity between the measured values for the ga seous co-pollutants and the imputed values for

various PM components. Thus, imputation methods will generally tend to bias any

epidemiologic studies of the di fferential associations of PM components with human health

outcomes.

The 2004 CD discussed results from a study c onducted in Chicago, IL, which illustrates

the impact on risk estimates caused by the use of 1-in-6 day ambient concen tration data. In this

study, a significant association was re ported between daily change in PM 10 

# concentration and

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mortality between 1985 – 1990 using data from one monitor collected on a daily basis (Ito et al.,

1995). However, when the data set was divided into 6 subsets representing a 1-in-6 day

monitoring frequency, the e ffect estimates for the PM 10 

# -mortality association were quite

variable. Moreover, the c onfidence intervals were wider and anal ysis of only one of the subsets

indicated a statistically significant association. Th is analysis indicates re duced precision due to

the markedly decreased number of events available for analysis, but also indicates that risk

estimates may be affected by exposure misclassificat ion, chance, or selection bias. Selection bias

could occur if the analyzed group associated with any part icular sampling schedule were

different from the unanalyzed group in a way that was systematically a ssociated with exposure

estimates. However, selection bias is not as pr evalent a concern for time- series studies as is

exposure misclassification due to inadequate characteri zation of the spatial variation of the PM

exposure measure within a locality.

Exposure Misclassification and Spatial Variability

Exposure misclassification can occur when am bient concentration from one or only a few

monitors in a geographic area is assigned to estimate the PM exposure of the individuals who

died in that area. If the ambi ent concentration that is calculate d for a particular day is higher

than what some of those who died actually expe rienced, but lower than what others who died

experienced, the resulting “noise” in the PM indicat or makes it harder to di stinguish a statistical

association with mortality. If th e calculated ambient concentrati on is not consistently higher or

lower than the concentration experienced by thos e who died on that day (that is, nondifferential

misclassification), the size of the relative risk may be attenuated. The importance of the

attenuation depends on the degree of spatial vari ability characteristic of the pollutant under

analysis and the resulting amount of exposure misclassification. While the impact of spatial

variability on estimates of e xposure is of less concern for studies of fine PM mass, a PM

exposure with relatively homogenous local di stribution, this is an important issue for

epidemiology studies of PM 2.5 

# components or thoracic coarse pa rticle mass and components. The

NCER STAR program is funding five studies beginning in early 2008 that will provide

information about spatial variability in coar se particle mass and components and effects on

health. Additional studies, to be awarded in 2008, will address stra tegies to incorporate data on

spatial and temporal variability of PM co mponents in atmospheric and exposure models.

Evaluation of Cumulative Effects of Air Quality on Health

Studies using distributed lag m odels indicate that risk estim ates using zero or one-day

lags may underestimate the magnitude of mortality associations with air quality. Distributed lag

models allow the examination of the combined eff ect of air pollution across a range of prior days

on mortality for one particular day, e.g. today’s mortality with today’s air quality (lag 0),

yesterday’s air quality (lag 1), and day before yest erday’s air quality (lag 2). The lagged effects

of air quality over multiple previous days are co mpared with each day’s mortality throughout the

study period. With 1-in-3 or 1-in-6 day monitors , the relationship with the health measurements

is disordered; the lagged effects of air quality on a single day mu st be compared with mortality

on different days. For example, today’s air qual ity is compared to today’s mortality at lag 0,

with tomorrow’s mortality at lag 1, and with the day after tomorrow’s mortality at lag 2.

Distributed lag models using daily monitors are advantageous because a specific lag structure for

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modeling th e associatio n of a pollutant with health does not ha ve to be selected in advance. This

modeling flexibility will be especially important for the study of PM components, which may

have differing lags between exposure and health outcome.

S UMMARY

The purpose of the preceding discussion has b een to highlight th e importance of timeseries studies using air quality data obtained from EPA’s Air Quality System to identify health

risks associated with ambient PM mass con centration and the limitations of the national

monitoring networks for similar studies of fine particle components as in dicators of PM sources.

This issue was raised by the health research community at the HEI/EPA workshop in Boston

November, 2006 and in subsequent discussions. The lack of da ily speciation monitoring for

PM 2.5 

# components is an important research need identified by the epidemiology community.

This issue has been highlighted because the number of PM 2.5 

# speciation monitors per location is

much smaller and variability (tem poral and spatial) for many fine particle components is much

greater than for PM 2.5 

# mass. Obtaining daily PM 2.5 

# speciation monitoring in a set of key

locations will enhance our understand ing of the health effects associ ated with fine particles by:

 providing improved statistical power for ep idemiologic studies of PM components

within a reasonable time period,

 providing analytical flexibility to examine distributed lags, and

 reducing exposure misclassification to improve the validity and precision of health effect

estimates.

In addition, targeted studies in some metr opolitan areas will help to characterize the

spatial variability of PM 2.5 

# components and quantitative impact on risk estimates.

POTENTIAL OPTIONS FOR OBTAINING DAILY PM 2.5 

# SPECIATION

MEASUREMENTS

A: Retrospectively fill in the missing data

Ac tions could be taken to construct a dataset containing daily values for PM 2.5 

# mass,

metals, elements, sulfate, nitrat e, and carbon for previous years. Options could include analyzing

archived daily PM 2.5 

# mass (Teflon) filters collected at CSN or nearby sites, using data collected

at nearby continuous (hourly) monitors. These ef forts most likely could be done at most at a

limited number of sites due to reso urce constraints and the limited hi storical use of the relevant

samplers.

1. Analyze archived filters to obt ain daily measurements of metals and elements (XRF)

The 54 STN monitors operate on a 1-in-3 day sampling schedule. Some non-STN

monitors in the CSN network may also operate on this schedule. There are some things that

could be done to achieve daily measures at some of these sites retrospectively (back to 1999) for

PM 2.5 

# and some components that ar e key source indicators. XRF an alysis of archived daily PM 2.5 

# mass (Teflon) filters collected from an adequate number of locations of daily FRM monitors

(primarily ones co-located with some of the 1-in-3 day CSN monitors) would provide critical

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inform ation about daily concentrations of metals and elements. There are alternative methods to

measure particle mass, EC, and XRF-elements th at may address the data needs for epidemiology

studies and be cost-effective. For example, Joel Schwartz and George Thurston recommended

using reflectance, a measure of black carbon, at the CSN sites to obtain estimates of daily EC

(where daily samples for PM 2.5 

# mass are available). Reflectance or other optical analyses of the

same filters may provide an indicator of EC. It mu st be noted that the existence of all historical,

Teflon filters of interest remains to be determined and gaining access to those filters that have

been archived will require a collaborativ e effort with State and local agencies.

2. Evaluate continuous measurement data to obt ain daily organic carbon (OC)/elemental

carbon (EC) at TRENDS sites.

Continuous (hourly) data for sulfate, nitrate, EC, and OC are available in some cities

including, Chicago, IL, Indiana polis, IN, Davenport, IA, Bar Ha rbor, ME, Cedar Rapids, IA,

Raleigh, NC, New York City, Seven Oaks, SC, Greenville, SC, Rockwell, NC, Seattle, WA, and

Detroit, MI. However, all components are not measur ed at all cities. Daily measures for sulfate,

nitrate, EC, and OC could be obtained over mu ltiple years for Chicago (2002-2007), Bar Harbor

(2004-2007 for sulfate, 2004 –? for OC, EC, & TC ), New York City (2001 – 2007 for sulfate &

nitrate, 2005 - 2007 for OC & EC), and Ralei gh (2003 – 2006 for OC, 2003 - ? for sulfate, 2003

– 2007 for nitrate, and 2003 – 2006 for total carbon) . These data could be used to construct a

data set containing daily concentrat ions. Of these sites, STN monitors are located in the vicinity

of the continuous monitors at Chicago, Ne w York City, and Raleigh. OAQPS notes that

continuous speciation monitors have their own measurement uncertainties, which may include

systematic biases that are not well characterized; data from them cannot simply be merged with

CSN data to fill in missing days. However, the continuous data could be used on a site-by-site

basis if a relationship between the continuous analyzer and the filter-based monitor was

established.

B: Expand current monitoring schedules at se lected locations in order to conduct daily

speciation measures in sele cted metropolitan areas.

1

. Locations

P opulation size and the number of health events that occur ea ch day are location

attributes that contribu te the greatest amount to the power of a time-series study to detect an

association with exposure to an air pollutant if one exists. The top 22 PMSAs or MSAs with the

highest weight were selected from Table 1 a nd are listed in Table 2 along with any CSN

monitors currently operating in that location. It should be noted that there are three PMSAs

(highlighted in red) in this group where there is no CSN monitor located. All of the other

locations, except for Los Angeles, have an STN monitoring site . In addition to population size

and mortality and the opportunity to take adva ntage of an existing CSN monitor, there are a

number of factors that are importa nt to consider for site selec tion for daily speciation monitoring.

Important information might include:

 What are the major sources in an area? – Are components of interest present in

measureable concentrations?

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 Regional representation of study locations under consideration

 Area characteristics – top ography, which influences spatial variability

 Existing d ata collection at a location -

 Are data available on a daily timescale for co mponents of interest retrospectively?

 A re multiple speciation monitors operating in the location?

 Are special studies (government or grant- supported) being conducted in the location?

Participants at the April 2008 workshop will be asked to provide feedback about the

importance of daily monitoring for fine partic le components for advancing our understanding of

the impacts of air pollutant expos ures on public health and criteria to consider for prioritizing

locations for daily PM 2.5 

# speciation monitoring. For discussi on purposes, three columns have

been added to Table 2 indicating significant ar ea characteristics, notes on predominant PM

components, and any special studies known to be conducted in the location that may contribute

information on temporal or spatial variability.

2. Components

For what PM species would it be beneficial to have daily ambient measurements? For

discussion purposes, Ito (HEI/EPA workshop, 2006) suggested the following components: OC,

EC, nitrate, sulfate, Se, As, Si, Fe, Mn, Cr , Zn, Pb, V, Ni based upon information from

toxicology and source apportionment studies. So me of these components may have more

homogenous distributions in certain regions but others are likely to have a high degree of spatial

variability. CSN and IMPROVE currently analyze for these components and EPA plans

are to continue to do so.

3. Costs

The estimated annual cost for shippi ng and lab analysis to add daily PM 2.5 

# mass and

speciation monitoring at one CSN site that is currently operating on a 1-in-3 day sampling

schedule would be $100,000 based on current EPA c ontracts. The State/local monitoring agency

would incur additional labor a nd equipment costs to operate the monitors as well.

OTHER MONITORING ISSUES

Two additional issues should be mentioned in this discussion of the use of air quality

monitoring data in time-series studies.

A: Spatial Variability: Set up additional mo nitoring sites within certain cities to

increase understanding of spatial variability of specific components.

Several components of research interest will be associated with a high degree of spatial

variability across a location. A small number of monitors (4 – 6) di stributed to capture

concentrations throughout an ar ea could give enough information to conclude whether or not a

specified component has a uniform distribution in that area. If the distri bution appeared uniform

for a certain component, multi-site time-series an alyses could be conducted using data from one

or more centrally located monito rs per location. If not, a more de tailed exposure analysis would

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be necessary in certain locations to obtain a finer spatial resolution and develop exposure

models. Such a detailed, nonroutine study could pote ntially involve a research grant. Based on

current EPA contracts, the estima ted annual cost to establish a CS N-like site operating on a daily

schedule in a new location but probably wher e other monitors ar e located is $150,000 for

shipping and lab analysis.

B. Alternative Measurement Methodologies

There are alternative methods to measure part icle mass, EC, and XRF-elements that may

address the data needs for epidemiology studies and be cost-effective. For example, Joel

Schwartz and George Thurston recommended using reflectance, a measure of black carbon, at

the CSN sites to obtain estimates of daily EC. In addition, the use of a rotating drum sampler

which measures various size classes of PM mass and PM components with a finer time

resolution (six hours) coul d be considered. At a meeting w ith State/local monitoring managers,

reservations were expressed about whether this sampler has demonstrated adequate

repeatabililty.

BE NEFITS OF OBTAINING DAILY PM 2.5 

# SPECIATION DATA

If

resources can be secured or re-programmed to support daily PM 2.5 

# monitoring at a well

prioritized set of monitoring sites of most value in health studies, the following benefits would be

obtained:

1. Time-series studies will have enough statisti cal power to determine which particles are

more toxic than others without having to wait ten or more years for results.

2. We will develop more accurate estimates of he alth effects that fully address lag issues

due to the availability of daily health and monitoring data. Studies have shown that the

use of distributed lag models evaluating seve ral consecutive days pr ior to the occurrence

of death result in a higher estimated relativ e risk. Studies of PM components need more

flexibility in choice of lag m odels because not all component s are predicted to have the

same lag structure for effects. This has obvious implications for RIA, accountability

studies, and basis for NAAQS decisions.

3. With multiple daily speciation monitoring sites in some of the larger cities, especially

those with more complicated geologic featur es, it would become possible to improve our

understanding of the impact of spatial variability on exposure estimates for PM

components. Studies of within-city spatial va riability will allow assessment of whether

the “noise” in exposure estimates is so large for some components that no excess risk is

observed.

4. Researchers could base thei r analyses on actual data, rather than using creative

approaches to get around the fundamental issue of missing data. These methods are

helpful, but introduce more uncertainty into the exposure estimate s by increasing the colinearity with co-pollutants.

5. The primary recommendation in the final NRC report was the need for EPA to

systematically examine which PM components and sources are most important for public

health. Since PM components may exert th eir adverse influences over different lags

between exposure and outcome, the ability to correctly evaluate lagged effects may be

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crucial to the correct assessm ent of the relative toxicity of PM components. The

availability of daily air quality informati on would enable the differential assessment of

PM components and PM sources, and elimin ate a potential bias in favor of the

assessment of those components with very immediate effects.

6. EPA is investing heavily in studies of ke y components and sources of PM (e.g., Hopkins

PM Center studies, HEI’s NPACT study, r ecent STAR RFAs). The return on this

investment would be increased significantly if daily PM 2.5 

# data are available to increase

confidence in the findings and reduce uncertainti es in the estimates as explained above.

7. Accountability: Assessing the hea lth improvements attributable to reduced air pollution is

already a difficult challenge. Without dail y data, such research will be even more

difficult and take many years to demonstrate benefits.

REFERENCES

Burnett RT, Brook J, Dan T, Celocla C, Philips O, Cakmak S, Vincent R, Goldberg MS, Krewski

D. 2000. Association between particulate- and ga s-phase components of urban air pollution and

daily mortality in eight Canadian citi es. Inhalation Toxicol 12 (Suppl4):15-39.

Burnett RT and MS Goldberg. 2003. Size-fractiona ted particulate mass and daily mortality in

eight Canadian cities. In: Revise d Analyses of Time-Series Studi es of Air Pollution and Health.

Special Report. Health Eff ects Institute, Boston, MA.

Dominici F, McDermott A, Daniels M, Zeger SL, Samet JM. 2003. Mortality among residents of

90 cities. In: Revised Analyses of Time-Serie s Studies of Air Polluti on and Health. Special

Report. Health Effects Institute, Boston, MA.

Ito K, Kinney PL, and Thurston GD. 1995. Variati ons in PM-10 concentrations within two

metropolitan areas and their implications for h ealth effects analyses. Inhalation Toxicol 7:735-

745.

National Research Council (NRC). 2004. Research Priorities for Airbourne Particulate Matter

IV: Continuing Research Progress. The National Academies Press, Washington D.C.

Samet JM, Zeger SL, Dominici F, Curriero F, C oursac I, Dockery DW, Schwartz J, Zanobetti A.

2000. The National Morbidity, Mortality, and Ai r Pollution Study, Part II: Morbidity and

Mortality from Air Pollution in the United Stat es. Research Report 94. Health Effects Institute,

Cambridge MA.

Schwartz J, Zanobetti A, Bateson T. 2003. Morbid ity and Mortality Among Elderly Residents of

Cities with Daily PM Measurements. In: Revised Analyses of Time-Series Studies of Air

Pollution and Health. Special Report. Health Effects Institute, Boston, MA.

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D-14 Figure 1. Implication of every-6th-day and every-3 rd-day data: Statistical power for timeseries studies.

Slide provided by Dr. Kazuhito Ito, presented at HEI/EPA Workshop on Air Quality Data,

Newton, MA, November 2006. Adapted sli ghtly for this discussion paper.



# number of monitorin g da y s A B

C 

# 80%DRAFT 3/27/08 - FOR DISCUSSION PURPOSES ONLY - DO NOT QUOTE OR CITETable 2. Twenty-two MSAs with largest population and associated speciation monitors.#2000 PopWgt34MSALocal Site NameCity NameStateSiteIDSample CollectionCounty NameSTN?Area characteristicsComponentsSpecialStudies19,314,23516.0New York, NY PMSA; New York--Northern NewJersey--Long Island, NY--NJ--CT--PA CMSALarge urban incrementplus NE backgroundHigh sulfate andorganics, lownitratesNYDOC,MESA-AIR,SupersiteIS 52New YorkNY0110Met One SASS TeflonBronxSTNDIVISIONSTREETNewYorkNY0134Met One SASS TeflonNew YorkQUEENS COLLEGE 2New YorkNY0124R&P MDL2300 PM2.5SEQ SPECQueens29,519,33816.1Los Angeles--Long Beach, CA PMSA; LosAngeles--Riverside--Orange County, CA CMSAComplex coastal andmountain topography,extreme traffic, ozone.and sunExtremely highnitrate andorganics, lowsulfateCARB, PMCenter, CHS,MESA-Air,SupersiteNULLLos AngelesCA1103Met One SASS TeflonLos Angeles38,272,76815.1Chicago, IL PMSA; Chicago--Gary--Kenosha, IL--IN--WI CMSAIndustrial center with lakeinfluences, windyHigh sulfate andorganics, lownitratesSPRINGFIELD PUMP STATIONChicagoIL0057Met One SASS TeflonCookMESA-AirCOM ED MAINTENANCEBLDGChicagoIL0076Met One SASS TeflonCookSTNNORTHBROOK WATER PLANTNorthbrookIL4201Met One SASS TeflonCookCITY HALLNapervilleIL4002Met One SASS TeflonDuPage45,100,93111.8Philadelphia, PA--NJ PMSA; Philadelphia--Wilmington--Atlantic City, PA--NJ--DE--MD CMSAIndustry plus NEbackgroundHigh sulfate andorganics, lownitratesCAMDEN LABCamdenNJ0003Met One SASS TeflonCamdenAMS LaboratoryPhiladelphiaPA0004Met One SASS TeflonPhiladelphiaSTNON AMTRAK RIGHT OF WAY -NEAR AIRPORT HI SPEED LINE(ELECTRIFIED)PhiladelphiaPA0136Met One SASS TeflonPhiladelphiaA420450002LAT/LON POINT ISOF CORNER OF TRAILERChesterPA0002Met One SASS TeflonDelaware34Weights (Wgt) are proportional to expected inverse-variance regression weights: sqrt((population * 0.01) / 365)D-15DRAFT 3/27/08 - FOR DISCUSSION PURPOSES ONLY - DO NOT QUOTE OR CITE#2000 PopWgtMSALocal Site NameCity NameStateSiteIDSample CollectionCounty NameSTN?Area characteristicsComponentsSpecialStudiesCHESTER COUNTYTRANSPORT SITE INTOPHILADELPHIANot in a cityPA0100Met One SASS TeflonChesterCORNER OF MLK BLVD ANDJUSTISON ST, NO TRAFFICDATA AVAILABLEWilmingtonDE2004Met One SASS TeflonNew Castle54,923,15311.6Washington, DC--MD--VA--WV PMSA; Washington--Baltimore, DC--MD--VA--WV CMSANE background plustrafficHigh sulfate andorganics, lownitratesSupersiteMCMILLAN PAMSWashingtonDC0043Andersen RAAS TeflonDistrict of ColumbiaSTNHOWARD UNIVERSITYBeltsvilleMD0030Andersen RAAS TeflonPrince George's64,441,55111.0Detroit, MI PMSA; Detroit--Ann Arbor--Flint, MI CMSAIndustry and high trafficHigh sulfate andorganics, lownitratesEPANULLAllen ParkMI0001Met One SASS TeflonWayneSTNPROPERTY OWNED BYDEARBORN PUBLIC SCHOOLSDearbornMI0033Met One SASS TeflonWayneDEAN ROAD DEAD-ENDS ATSITE, 200 FT WESTLuna PierMI0005Met One SASS TeflonMonroe74,177,64610.7Houston, TX PMSA; Houston--Galveston--Brazoria, TX CMSAExtreme chemicalindustry and ozone,coastal sunnyMedium (ifinteresting)organics, sulfate?SOUTH OF DETERMINED &ALDINE MAIL RDINTERSECTIONNot in a cityTX0024R & P Model 2025 PM2.5 Sequential AirSampler w/VSCCHarrisNW OF W. LAMBUTH &DURANT INTERSECTIONDeer ParkTX1039URG MASS400 TeflonWINSHarrisSTN84,112,19810.6Atlanta, GA MSAExtreme biogenics, hightraffic, sunnyHigh sulfate andorganics, lownitratesEPRI,Supersite2390-B WILDCAT ROAD,DECATUR, GADecaturGA0002Met One SASSTeflonDeKalbSTN93,519,1769.8Dallas, TX PMSA; Dallas--Fort Worth, TX CMSATraffic and cattle, sunnyhigh ammonia?WEST OF S. AKARD &CANTON STREETSINTERSECTIONDallasTX0050R & P Model 2025 PM2.5 Sequential AirSampler w/VSCCDallasD-16DRAFT 3/27/08 - FOR DISCUSSION PURPOSES ONLY - DO NOT QUOTE OR CITE#2000 PopWgtMSALocal Site NameCity NameStateSiteIDSample CollectionCounty NameSTN?Area characteristicsComponentsSpecialStudiesDALLAS HINTONDallasTX0069URG MASS400 TeflonWINSDallasSTNTHIS SITE WILL MONITORTHE SAME AREA AS SITE1390015MidlothianTX0016R & P Model 2025 PM2.5 Sequential AirSampler w/VSCCEllis103,406,8299.7Boston, MA--NH PMSA; Boston--Worcester--Lawrence, MA--NH--ME--CT CMSANE background plustrafficHigh sulfate andorganics, lownitratesHarvardDUDLEY SQUARE ROXBURYBostonMA0042Met One SASS TeflonSuffolkSTN113,254,8219.4Riverside--San Bernardino, CA PMSA; LosAngeles--Riverside--Orange County, CA CMSAComplex coastal andmountain topography,extreme traffic, ozone.and sunExtremely highnitrate andorganics, lowsulfateMESA-AirNULLRubidoux(WestRiverside)CA8001Met One SASS TeflonRiversideSTN123,251,8769.4Phoenix--Mesa, AZ MSAExtreme traffic, ozone.and sunHigh nitrate andorganics, lowsulfatePHOENIX SUPERSITEPhoenixAZ9997Met One SASS TeflonMaricopaSTN132,968,8069.0Minneapolis--St. Paul, MN--WI MSAContinental urbanMediumMESA-AirANDERSON SCHOOL -PHILLIPS NEIGHBORHOODMinneapolisMN0963Met One SASS TeflonHennepinSTN142,846,2898.8Orange County, CA PMSA; Los Angeles--Riverside--Orange County, CA CMSANo speciation monitors?Complex coastal andmountain topography,traffic, ozone. and sunHigh nitrate andorganics, lowsulfate152,813,8338.8San Diego, CA MSAComplex coastal andmountain topography,traffic, ozone. and sunMedium nitrate andorganics, lowsulfateNULLEl CajonCA0003Met OneSASS TeflonSan DiegoSTNNULLEscondidoCa1002Met One SASS TeflonSan Diego162,753,9138.7Nassau--Suffolk, NY PMSA; New York--Northern New Jersey--Long Island, NY--NJ--CT--PA CMSANo speciation monitors?Large urban incrementplus NE backgroundHigh sulfate andorganics, lownitrates172,603,6078.4St. Louis, MO--IL MSAIndustry and trafficHigh sulfate andorganics, lownitratesSupersiteD-17DRAFT 3/27/08 - FOR DISCUSSION PURPOSES ONLY - DO NOT QUOTE OR CITED-18#2000 PopWgtMSALocal Site NameCity NameStateSiteIDSample CollectionCounty NameSTN?AreacharacteristicsComponentsSpecialStudiesSIU DENTAL CLINICAltonIL2009Met One SASS TeflonMadisonNULLNot in a cityMO0012Met One SASS TeflonJeffersonBLAIR STREET CATEGORY ACORE SLAM PM2.5.St. LouisMO0085Met One SASS TeflonSt. Louis CitySTN182,552,9948.4Baltimore, MD PMSA; Washington--Baltimore, DC--MD--VA--WV CMSANE background plustrafficHigh sulfate andorganics, low nitratesMESA-Air,SupersiteESSEXEssexMD3001Met One SASS TeflonBaltimoreSTN192,414,6168.1Seattle--Bellevue--Everett, WA PMSA; Seattle--Tacoma--Bremerton, WA CMSACoastal urban, highwood burningMedium organics?,nitrate?, low sulfate?SEATTLE DUWAMISHSeattleWA0057Andersen RAAS TeflonKingBEACON HILLSeattleWA0080Met One SASS TeflonKingSTNOLIVE STREETSeattleWA0048Met One SASS TeflonKing202,395,9978.1Tampa--St. Petersburg--Clearwater, FL MSACoastal with some SEand power plantinfluenceMedium sulfate andorganicsSYDNEYPlant CityFL3002Met One SASS TeflonHillsboroughSTNNULLPinellas ParkFL0026MetOne SASS TeflonPinellas212,392,5578.1Oakland, CA PMSA; San Francisco--Oakland--San Jose, CA CMSANo speciation monitors?Coastal urban, highwood burningMedium organics?,nitrate?, low sulfate?222,358,6958.0Pittsburgh, PA MSAIndustry & traffic pluseastern backgroundHigh sulfate &organics, low nitratesNULLPittsburghPA0008Met One SASSTeflonAlleghenySTNSupersiteNULLNot in a cityPA5001Met One SASS TeflonWashingtonS ALLEGHENY HS DOWNWIND FROM USS CLAIRTONCOKE WORKSLibertyPA0064Met One SASS TeflonAlleghenyLAT/LON POINT IS TRAILERGreensburgPA0008Met One SASS TeflonWestmoreland

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# Appendix E: Session V: Ambient Ai r Monitoring Realities – EPA/State/Local

Perspectives - Ambient Air Monitoring Network: Network Design and Site

Selection Approval

Questions on this draft white paper should be directed to Tim Hanley, EPA/OAQPS,

hanley.tim@epa.gov ; (919) 541-4417.

Introduction

The purpose of this white paper is to briefl y describe the process for designing major

ambient air monitoring networks including:

 the roles of EPA and State, local, and Tr ibal monitoring agencies in selecting and

approving monitoring stations;

 the ways that health and other resear chers can provide i nput currently to

State/local/Tribal monitoring agencies a nd EPA on the usefulness and approval of

monitoring stations; and

 suggestions to improve facilitation of soliciting input on monitoring station

selection from health and other researchers.

B ackground

T he measurement of ambient air pollution in the United States is provided through a

number of ambient air monitoring networks opera ted almost exclusively by State, local, and

Tribal air monitoring programs. The EPA identifies key parameters to measure such as criteria

pollutants 35 

# , pollutant precursors, chemi cal composition of particles, and air toxics. Ambient air

monitoring networks are implemented through a combination of Federal requirements and

voluntary programs. 36 

# EPA provides required siting criter ia and network deployment strategies

for measurement of pollutants as one of severa l key components to implementing air monitoring

networks. Monitors are categorized as State and local Air Monitoring Stations (SLAMS) when

they are approved as part of the long-term operating network or Special Purpose Monitors

(SPMs) when they are being used for short-term investigations (i.e., less than two years). Air

toxic monitoring stations are not required by regulation, and do not carry the SLAMS distinction.

Additional, Federally run netw orks provide monitoring covera ge in primarily rural areas

to meet specialized objectives. The Interagenc y Monitoring of Protected Visual Environments

(IMPROVE) network, a cooperative measuremen t effort guided by a steering committee

composed of representatives from Federal and regional-state organizatio ns, provides important

data for implementing both regional haze and PM 2.5 

# attainment programs. The Clean Air Status

and Trends Network (CASTNET), managed by EPA’s Clean Air Mark ets Division, provides

atmospheric data on the dry deposition component of total acid depos ition, ground-level ozone

and other forms of atmospheric pollution. The National Atmospheric Deposition Program

(NADP), another cooperative program involvi ng several governmental agencies, provides

measurements of pollutants in precipitation, including sulf ate, nitrate and ammonium.

35 

# The Clean Air Act requires EPA to set National Ambient Air Quality Standards (NAAQS) for six common air

pollutants. They are particle pollution (often referred to as particulate matter), gr ound-level ozone, carbon

monoxide, sulfur oxides, nitrogen oxides, and lead.

36 

# All Tribal monitoring programs are provided for cooper atively as compliance with Federal rules cannot be

required of Tribes.



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EPA designs and im plements ambient air monitoring networks to meet several

monitoring objectives:

 Determining compliance with health- and we lfare-based standards (i.e., the NAAQS);

 Providing air pollution data to the ge neral public on a timely basis; and

 Supporting the development and tracking of emission control programs.

In addition to the monitoring objectives above, EPA recognizes important additional

objectives that need to be f actored into designing ambient monitoring networks such as:

 Supporting health and welfare effect s and exposure research studies

 Providing air pollution data for human hea lth risk/exposure assessments and NAAQS

reviews;

 Providing air pollution data for we lfare effects assessments; and

 Supporting atmospheric research studies.

EPA recently made changes to the NAAQS-rela ted monitoring regulations. Specifically,

the general monitoring network design requirements for the minimum number of ambient air

monitors were modified to focus more on popul ated areas with air quality problems and to

significantly reduce the requirements for criteria pollutant monitors that have measured ambient

air concentrations well below th e applicable NAAQS. A number of the changes related to the

monitoring of PM 2.5 

# include revisions to th e requirements for refere nce and equivalent method

determinations (including specifications and test procedures). These re gulations also added a

requirement for a new multi-pollutant monitori ng network called National Core (NCore) and

revised certain provisions regard ing monitoring network descripti ons and periodic assessments,

quality assurance, and data certif ications (71 FR 61236, October 17, 2006) 37



# .

De sign criteria for required ambient air mon itoring networks are provided in Appendix D

to 40 CFR Part 58. Network design criter ia include monitoring objectives, scale of

representation, and specifi cations for locating monitors (e.g., a requirement to be in the area of

expected maximum concentration). In many cases , there are multiple monitoring objectives for a

site with the highest concentra tion of a pollutant. For instance , a neighborhood scale site in the

area of maximum fine particle e xposure could be thought of as a central monitoring station.

These central monitoring stations might have several PM measurement samplers such as a PM 2.5 

# FRM for comparison to the NAAQS, a PM 2.5 

# continuous mass monitor for reporting the Air

Quality Index (AQI), and a fine particle specia tion sampler to develop and track emission control

strategies. All of these data could be useful in health st udies depending on the purpose and

availability of health endpoint data. Requirements for the mi nimum number of monitors to

operate are identified for PM, ozone, Photoche mical Air Monitoring Stations (PAMS), and

NCore (which include several measurements); ho wever, monitoring agencies are encouraged to

operate additional stations to ade quately characterize pollutants. Siting criteria are provided in

Appendix E to Part 58. Siting criteria include the specifications for probe and inlet height,

distance from obstructions, and traffic.

37 

# See also http://www.epa.gov/ttn/amtic/ for more information on the Ambient Monitoring Technology Information

Center (AMTIC) operated by EPA's Ambient Air Monitoring Group (AAMG). AMTIC contains information and

files on ambient air quality monitoring programs, details on monitoring methods, relevant documents and articles,

information on air quality trends and nonattainment areas, and Federal regulations related to ambient air quality

monitoring.



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Ro les of EPA and Monitoring Agencies in sel ecting and approving changes to a monitoring

netw ork:

Th e EPA requires each State monitoring ag ency to develop and submit an Annual

Monitoring Network Plan to the applicable EPA Regional Office by July 1 of each year. States

may delegate portions of the Annual Monitoring Ne twork Plan to applicable local agencies (e.g.,

in California there are several plans, while in Ne w York there is one plan for the whole State).

The annual monitoring network plan must be made available for public insp ection for at least 30

days prior to submission to EPA. Any annua l monitoring network plan that proposes SLAMS

network modifications including ne w monitoring sites is subject to the approval of the EPA

Regional Administrator. Air Toxic monitoring stations are encourag ed to be included in annual

monitoring network plans, but are not formally required. Modifications to PAMS, the Speciation

Trends Network (STN), and the NCore network are to be approved by EPA’s Office of Air

Quality Planning and Standards. The EPA Re gional Office will provide an opportunity for

public comment and approve or disapprove the pl an and schedule within 120 days of submission.

If the State or local agency has already provided a public comm ent opportunity on its plan and

has made no changes subsequent to that comm ent opportunity, the Regiona l Administrator is not

required to provide a separa te opportunity for comment.

Th e annual monitoring network plan must contain the following information for each

existing and proposed site:

1. The AQS site identification number.

2. The location, including street addr ess and geographical coordinates.

3. The sampling and analysis method(s) for each measured parameter.

4. The operating schedules for each monitor.

5. Any proposals to remove or move a monito ring station within a period of 18 months

following plan submittal.

6. The monitoring objective and spatial scale of representation for each monitor as defined

in appendix D to this part.

7. The identification of any sites that are suit able and sites that are not suitable for

comparison against the annual PM 2.5 

# NAAQS as described in §58.30.

8

. The metropolitan area (e.g., MSA, CBSA, CSA) or other area represented by the monitor.

The annual monitoring network plan must document how State and local agencies

provide for the review of changes to a PM 2.5 

# monitoring network that impact the location of a

violating PM 2.5 

# monitor or the creation/change to a co mmunity monitoring zone. The affected

State or local agency must document the proc ess for obtaining public comment and include any

comments received through the public notificatio n process within their submitted plan.

What factors are critical in decisions to change the location of a monitoring station?

I n most cases, monitoring stations are located for many years in the same location;

however, from time to time a monito ring station is moved or shut down due to either planned or

unforeseen reasons. The following list provide s a summary of the most common reasons why

monitoring stations are moved or shut down:

L ogistical reasons:

 The lease for the land or bu ilding where the monitoring st ation is located cannot be

extended due to redevelopment or other reasons.

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 Constructio n adjacent to a monitoring station renders the site inappr opriate to use during

construction and in some cases unable to meet siting criteria after construction is

complete.

F ailure to meet probe and siting criteria:

 Growth of trees around a monitori ng station renders the site no longer able to meet siting

criteria and the owner of the trees is unw illing to have them cut or trimmed.

 Increases in motor vehicles tr affic, including the addition of new traffic lanes lead to recategorizing the scale of representation or failure to meet set-back requirements; which

no longer meets the network design criteria.

 Site inspections reveal that some aspect of the siting criteria is no longer acceptable (e.g.,

a new HVAC system or emission source is located too close to an inlet).

Changes in responses to emission and/or ambient monitoring trends:

 Changes to existing point, area, or mobile source emission inventories (e.g.,

establishment of new beltways, shut-down of manufacturing facilities) that alter the

original premise for site placement.

 Long-term trends analysis demonstrates m onitor’s objective has b een fulfilled (taking

into account future alterations of the NAAQS). For example, steep declines in ambient

carbon monoxide levels at micro-scale complia nce sites led to discontinuation of a large

number of CO monitors.

 Network assessment indicates that monitoring re sources should be devoted to other issues

(e.g., air toxics measurement) or conserved to preserve high priority objectives (e.g.,

ozone, PM 2.5 

# )

W hat feeds into the decision-making process for moving or shutting down a monitoring

station?

With any number of reasons why a monitori ng station may need to be moved or shut

down, monitoring agencies must plan for networ k changes. For situations where it may be

possible to stay at the existing si te, if barriers can be overcome, an agency would likely make the

necessary efforts to maintain the site if th e monitoring objective were critical and no other

suitable location were available. Knowing that data from a monitoring station were being used

in an important health or epidemiological study would provide a persuasive argument to keep the

station in the same place if the agency knew the data were being used. For example, an agency

may be willing to petition a land owner to trim a tree or move an obstruction given the more

compelling use of the data in a health research study.

If a monitoring station has to be moved, how is a new location picked and approved?

Although usually not possi ble, the best way to handle m oving a monitoring station is to

identify a new site location within the same general area such that:

 the scale of representation and impacts fr om emission sources is the same as the

original site (so long as this is what is intended to be measured at the monitor);

 the old and new monitoring stations can be both operated simultaneously for one

year or, at minimum, during the season(s) of maximum expected concentrations;

and

 the statistical analyses of the data from the old and new monitoring stations are

deemed to be sufficiently comparable.

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I n m any cases, the decision to move a monitoring station does not allow enough time to

provide for simultaneous operation, so careful selecti on of the new station and analysis of its data

can only be compared to historical levels and other operating monitors. Use of emission

inventories, traffic counts, pict ures, and satellite imagery can he lp document site characteristics

for comparability of old and new sites.

M onitoring station removals or relocations that are antici pated for the next 18 months

must be identified in the annual m onitoring network plan that is re quired to be made available for

public inspection and is due to the EPA Regiona l Office by July 1 of each year. Although not

required, ideally the applicable EPA Regional Offi ce will visit and perform a site inspection to

assure the new station meets siti ng criteria and is acceptable. In recognition of uncontrollable

circumstances (e.g., a natural disaster such as Hurricane Katrina), the EPA provides for moving

an air monitoring station outsi de the window of an annual mo nitoring plan by review and

approval of the applicable EPA Regional Office.

I n what ways can communication with th e health research community be improved

concerning possible changes in the ambient air monitoring networks?

Improved outreach concerning currently available tools:

 EPA has developed a web site that provides a link to each available State and local agency

annual monitoring network plan (see: http://www.epa.gov/ttn/amtic/plans.html ).

 EPA will continue to update the website as plan s are revised. EPA is seeking input regarding

recommendations for how often a reminder s hould goes out when plans are updated.

o State/local/Tribal monitoring agencies can be encouraged to summarize their

anticipated monitoring netw ork changes in one place wi thin the annual monitoring

network plans, or in a companion summary document, that could be easily scanned

by interested parties without wa ding through an extensive plan.

o Although not currently available, there is recognition that a mechanism allowing for

quick review of all anticipated network ch anges across the nation in one place would

be beneficial to the health research comm unity. Note: this is not available as all

network plans are currently summarized by the appropriate State, lo cal, and/or Tribal

agency.

 EPA has developed a web site dedicated to docu menting the site characteristics, including

photos, and links to satellite imagery of candidate NCore monitoring stations

( http://www.epa.gov/ttn/amtic/ncore/ ). At the bottom of each individual NCore station web

page, there is an opportunity to provide commen ts on the candidate station. EPA encourages

health researchers to offer comments on th e usefulness of candidate NCore stations.

 EPA maintains a relatively easy to use public web s ite that can be used to generate maps and

lists of active ambient air monitors ( http://www.epa.gov/air/data/ ).

o An agency contact list is maintained as part of this web site so that data users can

reach State and local contacts c oncerning monitors of interest

( http://www.epa.gov/air/data/contsl.html ).

o A contact list for EPA Regional Office monitoring staff is available at:

http://www.epa.gov/ttn/amtic/namscon.html

.

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E-6  EPA’s Office of Air Quality Planning and Stan dards (OAQPS) has recently developed a list

serve that is used as a communication tool fo r ambient air monitoring and health researchers

can be added to our distribution list. Sign-up instructions are available at:

http://www.epa.gov/tt n/am tic/airlist.html

.

Increased participation in health-focused gatherings:

 Monitoring experts from OAQPS can participate in key, annual national health research

conferences to present information on ambient air monitoring networks and plans for method

improvements or changes. This would also im prove monitoring experts’ knowledge of health

research needs, improve communication, and build a bridge between these two communities.

o OAQPS can also work with key State and lo cal agency monitoring and network leads

by inviting them to participate in annual national health research conferences to

present information on ambient air mon itoring networks for which they are

responsible.

 EPA will continue to engage CASAC’ s Ambient Air Monitoring and Methods

Subcommittee, and in doing so can specifically engage or address health research interests.

Communication initiatives:

 Health researchers are encouraged to co mmunicate with the am bient air monitoring

community on the key monitoring s ites that provide data to thei r research. Communications

should be at multiple levels to ensure an understanding of the importance of the work;

however, the most important communication needs to be directly with the State and/or local

air monitoring agency responsible for ope rating ambient air monitoring stations.

 EPA will facilitate and encourage the particip ation of health researchers at national air

monitoring conferences to provide presentations on how their rese arch is using ambient data.

This will serve to educate and sensitize monitori ng staff to the importance of the ambient air

monitoring program to health rese archers especially if the issu e of relocation or termination

of long-term monitoring s ites is being considered.

 Health researchers and EPA should work collect ively to establish the requirements for a

website or other publicly available forum to serve as an inventory of all on-going and

planned health studies utilizing ambient air monitoring data, the monitoring sites and key

ambient monitoring data being used, and the time period of the study. This would be

extremely beneficial so that monitoring agenci es can make contacts with researchers who are

using the information from their networks.

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# Appendix F: Session V: Ambient Ai r Monitoring Realities – EPA/State/Local

Perspectives - Ambient Air Monitoring Method Implementation

Questions on this draft white paper shou ld be directed to Joann Rice, EPA/OAQPS,

rice.joann@epa.gov , (919) 541-3372.

Introduction

The purpose of this draft white paper is to describe the current process and

communication strategy used by the EPA to implement monitoring methods and method

improvements in support of National Ambi ent Air Quality Standards (NAAQS) criteria

pollutants, criteria pollutant precursors, and ai r toxics and to encourage discussion on how to

improve communications with the health research community.

Background

The Office of Air Quality Planning and Standa rds (OAQPS) is responsible for identifying

ambient monitoring needs based on the NAAQS re view process and othe r air quality data

requirements. OAQPS implements the nation’s ambi ent air monitoring networks to ensure that

they meet critical air program needs by leadi ng and collaborati ng on the development of data

quality objectives (DQOs), monitoring methods, and a quality assurance (QA) program for

achievement of monitoring objectives. The best appr oach is utilized to optimize the value of the

monitoring networks to meet multiple program objectives and regularly assesses the network’s

effectiveness in continuing to m eet those objectives. This is done in collaboration with other key

partners, including EPA Headquarters and Regi onal Offices, the Office of Research and

Development (ORD), other Federal agencies, the Ambient Air Monitoring Steering Committee

(AAMSC), State/local/Tribal agencies, the Na tional Association of Clean Air Agencies

(NACAA), Multi-State Organizations, the National Academy of Sciences (NAS), the Clean Air

Scientific Advisory Committee (CASAC), and privat e entities such as instrument manufacturers.

T he EPA requires approved methods for meas uring criteria pollutants. The monitoring

staff participates in the NAAQS review process to help identify monitori ng network issues and

new monitoring technology needs. Once these needs are identifi ed and articulated, the staff

works with ORD to develop new monitoring technologies and Federa l Reference Methods

(FRMs) to support these needs. EPA also engages the CASAC, and their subcommittee on

ambient air monitoring and methods, in review of the methods developed. Once EPA develops

and specifies the FRM requirements, the instru ment manufacturers are involved to develop

candidate FRM and Federal Equivalent Methods (FEMs). ORD is responsible for testing and

approval of equivalent and re ference methods. A method has several components: sample

collection, analysis, handling, archival, and data processing and reporting, etc. Once FRM/FEMs

are approved, they are implemented in the natio nal ambient air monitoring network to support

the NAAQS. As the NAAQS review cycle repeats, EPA reviews the monitoring networks and

monitoring method needs in consultation with monito ring agencies at the St ate, Local and Tribal

level. If adjustments to the FRM/FEMs are ne eded, the AAMG works with ORD to develop new

methods, or make adjustments or improvements to methods to meet the data needs in support of

the NAAQS. Then the method development, review , consultation, approval, and implementation

cycles repeat as described above.

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I n the case o f criteria po llutant precursors, like PM 2.5 

# chemical species or air toxics, there

are no requirements for FRM development and appr oval. EPA rules or method plans may specify

the species or components and methods needed. In this case, OAQPS works with ORD to

identify the best methods and t echnologies available to meet th e data use objectives. Once these

methods/technologies are iden tified, OAQPS/ORD consults with Regional Offices,

State/local/Tribal agencies, Mult i-State Organizations, and CASAC to obtain feedback on the

appropriateness of the methods chosen. On ce recommendations are provided on the

method/technological approach, th e monitoring methods are implem ented with the help of the

Regions and State/local agencies. Method plan s are documented in the monitoring agency’s

quality assurance project plan (QAPP). States and local agencies often adopt the methods

employed in the national monitoring programs for additional monitoring in their networks. As

EPA regularly reviews and assesses the monitoring ne tworks to confirm that they are meeting the

data quality objectives and data use needs, revisions to the monitoring methods may be

recommended or warranted.

What factors are critical in decisions to change – why make changes or improvements?

Changes to the FRM/FEM are done in suppor t of the NAAQS review process and any

resulting changes in the form or level of the standards, as well as to address needed operational

efficiencies. Changes for non-criter ia pollutants or precursor species are largely made to improve

consistency and data usability across our m onitoring networks, and to support multiple

monitoring objectives such as:

 Supporting the development of modeling t ools and the application of source

apportionment modeling for control strate gy development in support of the NAAQS;

 Assessing the effectiveness of emission reducti ons strategies through the characterization

of air quality trends;

 Supporting health effects and e xposure research studies; and

 Supporting programs aimed at improving enviro nmental welfare (e.g., the regional haze

program).

W hat feeds into the decision-making process?

S ome changes are intentionally made and ot hers inadvertently or unknowingly happen as

a result of changes at the sample collection or an alysis stages (e.g., change s in field or laboratory

instrument operation). In the cas e of intentional plans for chan ge, EPA may invoke special field

or monitoring studies and data analysis efforts to assess the need for, a nd the impact of change.

Plans for change are then vetted within EP A, and the monitoring, expert, and academic

community (disciplines covered include monitori ng, modeling and data anal ysis researchers, as

well as health scientists) in a va riety of ways and forums to obt ain feedback from key partners.

These forums include participation in and presen tation or communication of plans for change at

conferences, meetings, workshops, and Regional/ State/Local and NACAA conference calls. In

addition, OAQPS holds a tri-annual m onitoring conference specific to monitoring issues (the last

one was held November 2006). OAQPS may also issue letters, memorandums, program

Newsletters, and other forms of written communi cation through our list serve (link to sign up

instructions provided below). The list serve send s an email notification to all parties on the

distribution about posting of information on our Ambient Monitoring Technology Information

Center (AMTIC) website. In addition, special co nsultation w ith the AAMSC and CASAC is held

if appropriate.

How do we communicate plans for change?

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G-3 S everal opportunities exist along the way for interested parties and key partners to

provide feedback. EPA begins to consider possi ble changes well in advance of implementation.

It takes several months if not y ears to perform any special studies, analyze the data, consult with

ORD, the academic and expert community and ot her groups before change can occur. The EPA

has (and continually develops) a variety of mechanisms to communicate plans for method

improvements and changes. These mechanisms have already been mentioned above (e.g.,

participation in conferences, meetings and confer ence calls, newsletters, consultations, etc.).

I n what new ways can we engage health researchers and improve communication?

Communications between OAQPS and the health research community can be improved

by the following:

 OAQPS can participate in key, annual national health research conf erences to present

information on ambient air monitoring networks and plans for method improvements or

changes. This would also improve OAQPS’ s knowledge of health research needs,

improve communication, and build a bri dge between these two communities.

o Important conferences and dates need to be identified.

 EPA will continue to engage CASAC, and in doing so can specifically engage or address

health research interests.

o If the monitoring subcommittee is restore d, make sure “right” health person(s)

involved

 OAQPS has recently developed a list serve that is used as a communication tool and

health researchers can be adde d to our distribution list. Sign- up instructions are available

at: http://www.epa.gov/ttn/amtic/airlist.html

.

o NCER can help OAQPS focus what health re searchers need to pay attention to or

focus the distribution versus “mass mailing” (see below).

 EPA can improve internal communications by instituting regular forms of

communication between ORD and OAQPS’ divisions.

o Need regular process of communicati on across EPA on changes/plans, etc.

o Need to “institutional” process to formalize communications between OAQPS

and health researchers through NCER.

o Build additional relationships and channels for communication.

 OAQPS is involved in ORD’s air research implementation planning process where

OAQPS research needs are iden tified and conveyed across ORD laboratories. This forum

can also be used to communicate plans for change across ORD.

o OAQPS can communicate plans to ORD and ORD can help to convey messages

and information across ORD labs and centers.

 ORD can participate in the AAMSC to impr ove communication with health researchers

regarding monitoring method issues and to monitoring agencies regarding ongoing and

planned research efforts.

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# Appendix G: Preliminary Survey of Am bient Air Monitoring Sites Currently

Being Considered in EPA-funded Epidemiology Studies Feb 2008

G-1Preliminary Survey of Ambient Air Monitoring Sites Currently Being Considered in EPA-funded Epidemiology Studies Feb 2008for more information, contact Sascha Lodge, lodge.sascha@epa.gov; (202) 343-9769PLEASE NOTE: Colors signify that a given monitor is being used by multiple researchers.There is no distinction between blue and orange. For example, four researchers are usingthe Bakersfield (CA) monitor, three researchers are using the El Cajon (CA) monitor, andonly one researcher is using the Phoenix (AZ) monitor.StateCityCountySite NameStateCodeCountyCodeSiteIDPriorityAddressMonObjective1MonObjective2LatitudeLongitudeParametersMeasuredResearcherNameOrganization/AffiliationDuration of StudySTN SitesAlabamaBirminghamJeffersonNULL01730023Medium33.553056-86.815000Kaz ItoNYUArizonaPhoenixMaricopaPHOENIXSUPERSITE040139997High33.503643-112.095001Kaz ItoNYUCaliforniaBakersfieldKernFLAT TERRAIN,OILREFINERY 1.3 MINNW,TRAIN 1.4 MIN,FREEWAY 1.3 MIE060290014Medium5558CaliforniaAve;BakersfieldPopulationExposure35.356111-119.040278if availableNO2 OZ PM10PM25PM25speciesBart OstroCA OEHHAFor time-series andcase-crossover, thelonger into the future,the better the analyses.CaliforniaBakersfieldKernFLAT TERRAIN,OILREFINERY 1.3 MINNW,TRAIN 1.4 MIN,FREEWAY 1.3 MIE060290014High35.356111-119.040278AntonellaZanobettiHarvardUniversity2000-2003CaliforniaBakersfieldKernFLAT TERRAIN,OILREFINERY 1.3 MINNW,TRAIN 1.4 MIN,FREEWAY 1.3 MIE060290014High35.356111-119.040278Kaz ItoNYUCaliforniaBakersfieldKernFLAT TERRAIN,OILREFINERY 1.3 MINNW,TRAIN 1.4 MIN,FREEWAY 1.3 MIE060290014High35.356111-119.040278Kaz ItoNYUCaliforniaEl CajonSan DiegoNULL060730003Medium1155RedwoodAve.; ElCajonPopulationExposure32.791389-116.941667if availableNO2 OZ PM10PM25PM25speciesBart OstroCA OEHHAFor time-series andcase-crossover, thelonger into the future,the better the analyses.CaliforniaEl CajonSan DiegoNULL060730003High32.791389-116.941667AntonellaZanobettiHarvardUniversity2000-2003CaliforniaEl CajonSan DiegoNULL060730003High32.791389-116.941667Kaz ItoNYUCaliforniaRiversideRiversideMira Loma060658005High5130PoinsettiaPlaceOther33.995638-117.493304PM2.5, PM10JoelKaufmanUniv. oWash.MESAAirprojectf8/1/2004 - 7/31/2014CaliforniaRubidoux(WestRiverside)RiversideNULL060658001Medium5888 MissionBlvd.;RubidouxPopulationExposure33.999580-117.416010if availableNO2 OZ PM10PM25PM25speciesBart OstroCA OEHHAFor time-series andcase-crossover, thelonger into the future,the better the analyses.CaliforniaRubidoux(WestRiverside)RiversideRiverside-Rubidoux060658001High5888 MissionBlvd.,RubidouxPopulationExposure(RiversideSanBernardino,CA)33.99958-117.41601PM2.5, PM10,SO2, NO2, Oz,COJoelKaufmanUniv. oWash.MESAAirprojectf8/1/2004 - 7/31/2014CaliforniaRubidoux(WestRiverside)RiversideNULL060658001High33.999580-117.416010AntonellaZanobettiHarvardUniversity2000-2003CaliforniaRubidoux(WestRiverside)RiversideNULL060658001High33.999580-117.416010Kaz ItoNYUCaliforniaRubidoux(WestRiverside)RiversideNULL060658001High33.999580-117.416010Kaz ItoNYUCaliforniaSacramentoSacramentoNULL060670006MediumDel Paso2701 AvalonDr;SacramentoPopulationExposure38.614167-121.366944if availableNO2 OZ PM10PM25PM25speciesBart OstroCA OEHHAFor time-series andcase-crossover, thelonger into the future,the better the analyses.CaliforniaSacramentoSacramentoNULL060670006High38.614167-121.366944AntonellaZanobettiHarvardUniversity2000-2003CaliforniaSacramentoSacramentoNULL060670006High38.614167-121.366944Kaz ItoNYUffSTATIONCaliforniaSan JoseSanta ClaraSAN JOSEJACKSON ST060850005Medium156BJacksonStreet; SanJosePopulationExposure37.348500-121.895000if availableNO2 OZ PM10PM25PM25speciesBart OstroCA OEHHAFor time-series andcase-crossover, thelonger into the future,the better the analyses.CaliforniaSan JoseSanta ClaraSAN JOSEJACKSON ST060850005High37.348500-121.895000Kaz ItoNYUCaliforniaSimi ValleyVenturaNULL061112002High34.277500-118.684722Kaz ItoNYUColoradoCommerceCityAdamsALSUPELEMENTARYSCHOOLCOMMERCE CITY080010006High39.825739-104.936987Kaz ItoNYUConnecticuNew HavenNew HavenNULL090090027High41.301111-72.902778Kaz ItoNYUtDistrict OColumbiaWashingtonDistrict oColumbiaMCMILLAN PAMS110010043High38.918889-77.012500Kaz ItoNYUFloridaDavieBrowardNULL120111002High26.082778-80.237778Kaz ItoNYUFloridaPlant CityHillsborougSYDNEY120573002High27.965650-82.230400Kaz ItoNYUGeorgiaDecaturhDeKalb2390-B WILDCATROAD, DECATUR,130890002High33.688007-84.290325Kaz ItoNYUIdahoMeridianAdaGANULL160010010Medium43.607568-116.348434Kaz ItoNYUIllinoisChicagoCookLawndale Comm-Ed170310076High7801LawndalePopulationExposure(Chicago, ILNorthwestern Indiana)41.751369-87.713745PM2.5, SO2,NO2, OzJoelKaufmanUniv. oWash.MESAAirprojectf8/1/2004 - 7/31/2014IllinoisChicagoCookCOM EDMAINTENANCE170310076High41.751369-87.713745Kaz ItoNYUIllinoisChicagoCookBLDGCOM EDMAINTENANCE170310076High41.751369-87.713745AntonellaZanobettiHarvardUniversity2000-2003IndianaIndianapolisMarionBLDGIN PARKING LOTNEXT TO POLICE180970078High39.811097-86.114469Kaz ItoNYUKansasKansas CityWyandotteJFK202090021Medium39.117500-94.635556Kaz ItoNYUKansasKansas CityWyandotteJFK202090021High39.117500-94.635556AntonellaZanobettiHarvardUniversity2000-2003LouisianaBatonRougeEast BatonRougeNULL220330009Medium30.461111-91.176944Kaz ItoNYUMarylandEssexBaltimoreEssex240053001HighWoodwardAnd FranklinRoadsEssexPopulationExposure(Baltimore,MD)39.310833-76.474444PM2.5, SO2,NO2, Oz, COJoelKaufmanUniv. oWash.MESAAirprojectf8/1/2004 - 7/31/2014MarylandEssexBaltimoreESSEX240053001High39.310833-76.474444Kaz ItoNYUMassachusettsBostonSuffolkDUDLEY SQUAREROXBURY250250042High42.329444-71.082778Kaz ItoNYUMassachusettsBostonSuffolkDUDLEY SQUAREROXBURY250250042High42.329444-71.082778AntonellaZanobettiHarvardUniversity2000-2003MassachusChicopeeHampdenNULL250130008High42.194460-72.555711Kaz ItoNYUettsMichiganMichiganAllen ParkDetroitWayne NULLWayne262616316300010001HighHigh42.22861142.228333-83.208333-83.209167Kaz ItoAntonellaZanobettiNYUHarvardUniversity2000-2003MinnesotaMinneapolisHennepinPhillips270530963High2727 10th St.MinneapolisPopulationExposure(Minneapolis-St. Paul,MN)44.955396-93.25827PM2.5JoelKaufmanUniv. oWash.MESAAirprojectf8/1/2004 - 7/31/2014MinnesotaMinneapolisHennepinANDERSONSCHOOL - PHILLIPSNEIGHBORHOOD270530963High44.955396-93.258270Kaz ItoNYUMinnesotaMinneapolisHennepinANDERSONSCHOOL - PHILLIPSNEIGHBORHOOD270530963High44.955396-93.258270AntonellaZanobettiHarvardUniversity2000-2003fMississippiGulfportHarrisonBEHIND HARRISONCOUNTY YOUTHCOURT280470008High30.390139-89.049722Kaz ItoNYUMissouriSt. LouisSt Louis(City)BLAIR STREETCATEGORY ACORE SLAM PM2.5.295100085High38.656300-90.198100AntonellaZanobettiHarvardUniversity2000-2003MissouriSt. LouisSt. LouisCityBLAIR STREETCATEGORY ACORE SLAM PM2.5.295100085High38.656300-90.198100Kaz ItoNYUMontanaMissoulaMissoulaNULL300630031Medium46.874912-113.995253Kaz ItoNYUNebraskaOmahaDouglasNULL310550019High41.247222-95.975556Kaz ItoNYUNevadaRenoWashoeNULL320310016Medium39.525083-119.807717Kaz ItoNYUNewElizabethUnionELIZABETH LAB340390004High40.641440-74.208360Kaz ItoNYUJerseyNewJerseyNorthBrunswick(TownshipMiddlesexNEW BRUNSWICK340230006High40.472790-74.422510Kaz ItoNYUNew Yorkof)New YorkBronxI.S. 52360050110HighE 156th StBet DawsonAnd KellyPopulationExposure(New York,NYNortheastern NewJersey)40.81616-73.90207PM2.5, SO2,NO2, OzJoelKaufmanUniv. oWash.MESAAirproject8/1/2004 - 7/31/2014New YorkNew YorkBronxIS 52360050110High40.816160-73.902070Kaz ItoNYUNorthCarolinaCharlotteMecklenburgGaringer High School371190041High35.240278-80.785556NO2 OZ PM10COAdel HannaUniversityOf Noth01/01/06 - 12/21/2008NorthCharlotteMecklenburGaringer High School371190041High35.240278-80.785556Kaz ItoCarolinaNYUCarolinaNorthFargogCassFARGO NW380171004High46.933754-96.855350Kaz ItoNYUDakotaOhioClevelandCuyahogaGT CRAIG390350060High41.493955-81.678542Kaz ItoNYUOhioClevelandCuyahogaGT CRAIG390350060High41.493955-81.678542AntonellaZanobettiHarvardUniversity2000-2003OklahomaTulsaTulsaNORTH TULSA -FIRE STATION#24AT 36TH ANDPEORIANR401431127High36.204902-95.976537Kaz ItoNYUOregonPortlandMultnomahNULL410510080High45.496667-122.602222Kaz ItoNYUPennsylvaPhiladelphiaPhiladelphiAMS Laboratory421010004High40.008889-75.097778Kaz ItoNYUniaPennsylvaniaPhiladelphiaaPhiladelphiaAMS Laboratory421010004High40.008889-75.097778AntonellaZanobettiHarvardUniversity2000-2003PennsylvaPittsburghAlleghenyNULL420030008High40.465556-79.961111Kaz ItoNYUniaPennsylvaniaPittsburghAlleghenyNULL420030008High40.465556-79.961111AntonellaZanobettiHarvardUniversity2000-2003RhodeProvidenceProvidenceBUILDING440070022High41.807949-71.415000Kaz ItoNYUIslandSouthCharlestonCharlestonROOFTOPCHARLESTON450190049High32.790984-79.958694Kaz ItoNYUCarolinaTennesseeKnoxvilleKnoxPUBLIC WORKSNULL470931020Medium36.019440-83.873610Kaz ItoNYUTexasTexasDallasDallasDallasDallasDALLAS HINTONDALLAS HINTON484811311300690069HighHigh32.81995232.819952-96.860082-96.860082Kaz ItoAntonellaZanobettiNYUHarvardUniversity2000-2003TexasDeer ParkHarrisNW OF W.LAMBUTH &DURANT482011039High29.670046-95.128485Kaz ItoNYUTexasDeer ParkHarrisINTERSECTIONNW OF W.LAMBUTH &DURANT482011039High29.670046-95.128485AntonellaZanobettiHarvardUniversity2000-2003INTERSECTIONTexasTexasEl PasoEl PasoEl PasoEl PasoCHAMIZALCHAMIZAL484814114100440044HighHigh31.76567331.765673-106.455225-106.455225Kaz ItoAntonellaZanobettiNYUHarvardUniversity2000-2003fSITEUtahSalt LakeCitySalt LakeUTMCOORDINATES =PROBE LOCATION490353006High40.736389-111.872222Kaz ItoNYUVermontBurlingtonChittendenZAMPIERI STATEOFFICE BUILDING,CORNER OFCHERRY STREET500070012Medium44.480278-73.214444Kaz ItoNYUVirginiaNot in a cityHenricoNULL510870014High37.558333-77.400278Kaz ItoNYUWashingtoSeattleKingBEACON HILL530330080High47.570273-122.308596Kaz ItoNYUnWashingtonSeattleKingBEACON HILL530330080High47.570273-122.308596AntonellaZanobettiHarvardUniversity2000-2003WashingtonSeattleKingBeacon Hill530330080High4103 BeaconAve. S.PopulationExposure(SeattleTacomaBellevue,WA)47.570273-122.308596PM2.5, SO2,NO2, Oz, COTim LarsonUniv. oWash.7/1/2008 - 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