Integrated Earth

Observations: Application

to Air Quality and

Human Health 

R E S E A R C H A N D D E V E L O P M E N T
EPA/600/R-07/007 

February 2007 

www.epa.gov 

Integrated Earth

Observations: Application

to Air Quality and

Human Health 

Organizing Committee 

Sally Tinkle1, Mary Gant1, Michael Humble1, 

Gary Foley2

, Valerie Garcia2, and Andy Bond2 

1

National Institute of Environmental Health Sciences 

Research Triangle Park, NC 27709 

2

U.S. Environmental Protection Agency 

Office of Research and Development 

National Exposure Research Laboratory 

Environmental Sciences Division 

Las Vegas, NV 89119 

Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official 

Agency policy. Mention of trade names and commercial products does not constitute endorsement or 

recommendation for use. 

U.S. Environmental Protection Agency 

Office of Research and Development 

Washington, DC 20460 171nerl07 
Integrated Earth Observations: Application to 

Air Quality and Human Health 

On 1-2 August 2005, the National Institute of Environmental Health Sciences and the Environmental 

Protection Agency sponsored a workshop, “Integrated Earth Observations: Application to Air Quality and 

Human Health”. The goal of the workshop was to identify the data user requirements and products that 

would enable air quality and climatological data derived from the international Global Earth Observation 

System of Systems (GEOSS) and from the U.S. Integrated Earth Observation System (IEOS) to be used 

effectively in public health research, planning, policy, and management of disease. The workshop brought 

together data producers, data organizers, and data users in a multi-disciplinary, interactive format to 

identify user requirements and research gaps and needs in the respiratory, cardiovascular and 

developmental abnormalities/birth defects fields. The workshop was limited to forty experts in data 

production, organization, and health applications. 

The enthusiasm generated by discussions between data producers and data users, as well as the 

identification of available remotely sensed data sets and potential demonstration projects fulfilled the 

goals of the workshop. The organizing committee thanks the sponsors, speakers, and participants and 

looks forward to the success of their research projects emanating from this workshop. Additionally, we 

thank Charles W. Schmidt for preparing the draft workshop report and the workshop participants who 

reviewed the final draft. 

Sincerely, 

Organizing Committee 

NIEHS: Sally Tinkle 

Mary Gant 

Michael Humble 

EPA: Gary Foley 

Valerie Garcia 

Andy Bond 
ABSTRACT 

In February 2005, ministers from 60 countries and the European Commission met in Brussels, 

Belgium to endorse the 10-year plan for a Global Earth Observation System of Systems 

(GEOSS) prepared by the Group on Earth Observations (GEO), a partnership of nations and 

international organizations. This multinational project integrates surface-based, airborne, and 

space-based remote sensing and in-situ networks to improve knowledge of the environmental 

factors that affect human health and well-being. Shortly thereafter, in April 2005, the US 

Government released its Strategic Plan for the US Integrated Earth Observation System (IEOS), 

which provides a framework for US contributions to the GEOSS, and also strives to meet 

requirements for high-quality data on the state of the Earth as a basis for policy and decisionmaking and to provide more accurate exposure assessments for the health and environment 

research communities. The plan was drafted by the US Group on Earth Observations (USGEO), 

an interagency subcommittee that reports to the National Science and Technology Council’s 

Committee on Environment and Natural Resources. 

Both the GEOSS and the IEOS emphasize consideration of user needs in the development of 

Earth observation data architectures. Toward this end, the National Institute of Environmental 

Health Sciences (NIEHS) and the Environmental Protection Agency (EPA) co-sponsored a 

workshop that united 40 health and Earth observation scientists in a dialogue over data-user 

requirements. The results of the workshop titled Integrated Earth Observations: Application to 

Air Quality and Human Health, which was held at NIEHS on 1-2 August 2005, are described in 

this report. Experts in meteorology, atmospheric chemistry, satellite engineering, and groundbased air measurements represented the Earth observation sciences. Health scientists provided 

expertise in epidemiology, exposure assessment, biostatistics, spatial statistics, clinical research, 

toxicology, informatics, and modeling. 

Participants were tasked with two key objectives: 1) To determine whether integrated Earth 

observations could provide useful public health tools for research, policy decisions, and 

environmental and health planning; and 2) To identify opportunities for improving user access 

to Earth observation data generated by producers, including the National Oceanic and 

Atmospheric Administration (NOAA), the National Aeronautics and Space Administration 

(NASA), and the Environmental Protection Agency (EPA). 

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The focus on air quality derives from substantial evidence that ozone and respirable particulates 

produce a spectrum of health effects. Long implicated as respiratory toxicants, these pollutants 

have more recently been linked to cardiovascular disease, in addition to developmental problems 

and birth defects. Remote sensing will augment ground-based air quality sampling and help fill 

pervasive data gaps that impede efforts to study air pollution and protect public health. 

Expanded Earth observations could support detailed inquiry into environment-disease 

interactions, and help create predictive exposure models that support science-based 

environmental and health decision-making. 

NOTICE: The information in this document has been funded by the United States 

Environmental Protection Agency. It has been subjected to Agency's peer and administrative 

review and has been approved for publication as an EPA document. 

OPENING REMARKS 

Gary Foley, Director, National Exposure Research Laboratory, EPA 

Welcome and Overview of the GEOSS 

In his opening remarks, Dr. Foley underscored the challenge of transforming Earth observation 

data into useful information. The motivating goal, he said, is to use the data to enhance 

interconnected decision-making that promotes health and environmental sustainability. But to 

achieve this goal, better ways are needed to deliver the data to users in research, management, 

and environmental forecasting. 

Foley emphasized that the GEO started with a vision to improve sustainability and then went on 

to identify nine areas that could benefit from expanded Earth observation technologies: Weather 

forecasting, disaster reduction, ocean resources, climate, sustainable agriculture, human health 

and well-being, ecological forecasting, water resources, and energy. 

Now, the GEO is exploring the needs of the user community, Foley said. The current workshop, 

he said, provides an opportunity for health scientists to describe what they do, and in this way, 

contribute to data architectures that suit their requirements and efforts to create better decision 

tools. The challenge, Foley concluded is for specialists to learn each other’s language, jargon, 

2
and research requirements. Foley pointed to existing relationships in this area among the Centers 

for Disease Control and Prevention (CDC), EPA, NASA, NOAA, and the National Weather 

Service, adding that multidisciplinary partnerships are essential to the overall effort. 

PLENARY SESSION I: Data Production (What can be measured) 

The first plenary session featured data producers from NOAA, EPA, and NASA. The goal was 

to provide a summary of remote sensing platforms for analysis and prediction of regional air 

quality. 

S.T Rao, Director, Atmospheric Sciences Modeling Division, EPA/NOAA 

Integrating Air Quality Data to Inform Human Health Decisions 

Dr. Rao addressed data production by NOAA’s Atmospheric Sciences Modeling Division 

(ASMD), which develops modeling and decision support systems for air quality forecasting and 

management. Ground-based monitors deployed by states and federal agencies are limited with 

respect to spatial coverage, Dr. Rao said. Monitoring stations are rare in rural areas and temporal 

air quality estimates for ozone and particulates can vary on an hourly to weekly basis. 

Meanwhile, public health concerns compel efforts to broaden spatial coverage and measures of 

pollutant characteristics and concentrations. 

The ASMD works with the National Weather Service to forecast air quality in areas where 

ground-based monitors are inadequate or absent. Forecasts are derived with the community 

multi-scale air quality (CMAQ) model, which was developed by EPA’S Office of Research and 

Development in partnership with NOAA. The CMAQ model links meteorological information 

to pollutant emissions data derived from local traffic patterns and industrial inventories. By 

simulating chemical reactions and pollution transport and removal processes, the model 

generates air quality forecasts for local advisories. 

Dr. Rao said the ASMD currently investigates methods to merge ground-based air quality 

monitoring data with CMAQ model outputs. The goal is to produce spatial maps that describe 

air quality at a specified grid resolution, for instance, every 12 kilometers. Two methods are 

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applied to these efforts: One of these—Bayesian statistics—provides spatial descriptions of 

predicted air quality along with defined levels of uncertainty. Another method known as 

Bayesian kriging also produces statistically unbiased estimates of spatial variation, but this 

method is much more computationally intensive. 

Additional research efforts, Dr. Rao said, will link satellite data with CMAQ model outputs. Rao 

emphasized a strong correlation between a satellite parameter known as aerosol optical depth 

(AOD), which describes the mass of aerosols in an atmospheric column, and PM2.5 

concentrations at the ground, particularly in summer when vertical columns in the atmosphere 

are more integrated. The incorporation of satellite data into CMAQ modeling will allow ASMD 

researchers to better characterize the spatial and temporal variability of ground-level pollutants. 

Richard Kleidman, NASA/Goddard Space Flight Center (GSFC) and Science 

Systems and Applications, Inc. 

Viewing Atmospheric Aerosols from the MODIS Satellite Sensor 

The Moderate Resolution Imaging Spectroradiometer (MODIS) resides aboard NASA’s Terra 

and Aqua satellites. Dr. Kleidman’s talk addressed two MODIS data products: Aerosol Optical 

Depth (AOD) and Fine-Mode Fraction. 

As noted previously, AOD is a quantitative measure of total column aerosol, which is the mass 

of aerosols within a measured column extending from Earth to the top of the atmosphere. The 

fine-mode fraction corresponds to particles within the AOD with a radius of 0.6 micrometers or 

less. Dr. Kleidman stated that the fine-mode fraction correlates best with anthropogenic 

emissions while AOD is more representative of natural aerosols, such as dusts and sea salts. 

Both values are provided daily and also as monthly averages in a MODIS data product known as 

Level 3. MODIS products are validated by AERONET (Aerosol Robotic Network), which is a 

global system of approximately 100 ground-based sun-photometers. 

MODIS uses different algorithms to turn land- and sea-based measurements into data products. 

Ocean measurements of AOD and fine-mode fraction—in part because they are made over the 

homogenous surface of the sea—have less associated uncertainty. Ocean fine-mode fraction 

measurements are used quantitatively, while land-based measures of the same parameter can 

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only be used as a qualitative indicator of whether AOD values are dominated by natural or 

anthropogenic emissions. 

Today, AOD data products are used in conjunction with EPA ground-based measurements for 

operational PM2.5 air quality forecasting. AOD generally correlates well with PM2.5 

measurements. However, AOD does not specify the location of aerosols within a column, and 

likely overestimates actual concentrations at the ground level, Dr. Kleidman said. Ground and 

spaced-based Light Detection and Ranging instruments (LIDARs) that use lasers to augment 

sunbased photonic measurements in addition to space-based instruments that measure polarized 

light should dramatically enhance the capacity of remote sensors to forecast PM2.5 over land. 

Dr. Kleidman concluded with a description of four pipelines that deliver MODIS data to the 

user: 

• The Goddard Distributed Active Archive Center provides MODIS data in Hierarchical 

Data Format (HDF) within 24 hours. 

• Direct broadcast systems operated collaboratively by NOAA, NASA, and the University 

of Wisconsin provide MODIS data as it comes over the horizon, typically within several 

hours. 

• MODIS Aerosol and Associated Parameters Subset Statistics produce monthly or daily 

data. Frequently associated with co-located AERONET sites. Data can be downloaded 

and used in spreadsheets. See http://modis-atmos.gsfc.nasa.gov/MAPSS 

• The MODIS Online Visualization and Access System (MOVAS) offers an interactive 

tool to graph and plot monthly mean data delivered in American Standard Code for 

Information Interchange (ASCII) format. See http://g0dup05u.ecs.nasa.gov/Giovanni/ 

Shobha Kondragunta, Research Physical Scientist and Air Quality Team Lead, 

NOAA/NESDIS Office of Research and Applications 

Availability and Uses of Operational Satellite Data 

The NOAA/NESDIS Office of Research and Applications (ORA) develops algorithms for 

retrieving geophysical parameters from satellite data. Dr. Kondragunta described NOAA’s 

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satellite program and its application to studies of infectious disease and predicted assessments of 

air quality. 

NOAA’s Earth observations program encompasses both polar-orbiting satellites (which travel 

over both poles on a daily basis) and geostationary satellites (which remain in a fixed position in 

sync with the Earth’s rotation, allowing them to make continuous measurements over a 

particular location). Combined, these satellites generate atmospheric and land-based measures of 

cloud cover, aerosols, ozone, ocean surface temperature, ice and snow cover, wind, and other 

parameters. 

Dr. Kondragunta described a NOAA study showing that malaria epidemics correlate with a 

parameter called the vegetation health index (VHI); a unitless value derived from satellite 

measurements of surface temperature and precipitation. The VHI is derived with the Advanced 

Very High Resolution Radiometer (AVHRR), a remote sensor developed by NOAA to 

characterize surface temperatures and cloud cover. 

The ORA also collaborates with the National Weather Service to improve air quality 

forecasting, which is limited by source data for pollutant emissions. To illustrate, Dr. 

Kondragunta described an occasion during which CMAQ predictions had underestimated 

pollution levels in the continental US by failing to incorporate long-range transport of smoke 

from Canadian and Alaskan forest fires. In this particular case, the fires were located beyond the 

CMAQ model’s geographic domain. NOAA’s geostationary satellites measured particle 

emissions from these sources and thus provided more accurate assessments of air quality than 

those predicted by the CMAQ model. Dr. Kondragunta said she is currently developing 

algorithms that will incorporate real-time emissions from burning biomass into CMAQ models 

to improve forecast accuracy. 

Dr. Kondragunta also described a collaborative effort with the European Organization for the 

Exploitation of Meteorological Satellites (EUMETSAT) to develop algorithms for use in nextgeneration Global Ozone Monitoring Experiment 2 (GOME 2) instrument, which will be 

launched on the MetOP satellite in 2006. These algorithms will produce near real-time 

troposphere measurements of many air pollutants, including nitrogen dioxide, sulfur dioxide, 

carbon monoxide and ozone, among others. 

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Richard Scheffe, Office of Air Quality Planning and Standards, USEPA 

Ambient Air Observation Systems: Infrastructure for Air Pollution and Health Effects 

Associations 

Ground-based air quality monitoring networks deployed throughout the United States routinely 

measure pollutants that include PM2.5, PM10, ozone, NOx, NO2, CO, lead, ozone precursors, 

sulfur, and nitrogen. Most of these data are generated by states and local air quality monitoring 

stations. The EPA’s primary role is to apply the data towards program goals in a number of 

areas, such as identifying non-attainment areas under the Clean Air Act, developing emission 

control strategies, tracking progress on pollution control, and supporting basic research, among 

others. 

The most robust air quality networks are devoted to ozone and PM2.5, the latter accounting for 

up to 70% of the nation’s regulatory air quality monitoring budget. PM2.5 sampling occurs at 

roughly 1,000 sites throughout the country. Routine speciation, whereby the levels of sulfate, 

nitrogen, and carbon in PM2.5 aerosols are quantified, occurs at approximately 400 sites 

nationally. 

Dr. Scheffe raised a number of concerns with the current monitoring system. Spatial coverage 

for PM2.5 and ozone are adequate, however sampling for multiple pollutants is rare, and 

monitoring locations are designated by convenience rather than design. Critics of the current 

approach recommend a more integrated, multi-pollutant strategy with real time reporting 

capability. 

In response to these recommendations, EPA will soon propose the National Core Network 

(NCore), which revises current sampling strategies in a number of ways. The overall goal is to 

de-emphasize regulatory compliance in favor of a suite of broader objectives, including better 

assessment of human pollutant exposures and health effects. 

NCore measurements comprise three levels: Level 1 measurements will take place at 3- 10 

master sites. The goal is to generate multi-pollutant data that advance method development and 

technology transfer. 

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Level 2 measurements will generate core data at 75 sites for numerous pollutants including NO, 

NOx, SO2, CO, PM2.5, PM10, ozone, and ozone precursors. Level 3 measurements will be made 

for single pollutants—mainly PM2.5 and ozone) at roughly 500 sites. Ideally, the NCore data 

infrastructure will accommodate data from additional sources, including space-based remote 

sensing. 

PLENARY SESSION II. Data Integration (Translating data to information) 

Brenda Smith, Geospatial Information Officer, USEPA 

Integrating and Accessing Spatial Data: Challenges and Successes 

Ms. Smith began her presentation by defining terms used in Earth observations. Two such terms 

are Geographic Information Systems (GIS), which refer to technologies that organize and 

display geo-referenced data for solving complex resource planning and management problems; 

and remote sensing, which refers to technologies that monitor atmospheric and ground-based 

features from a distance. Smith pointed out that remote sensing can detect features from farspace, near-space, airborne, and terrestrial vantage points. 

Ms. Smith then described several GIS data formats. One of these, known as vector data, 

connects X, Y, and Z coordinates in ways that form points, lines, and polygons. This format is 

best suited to data structures that represent features, such as well locations, rivers, and lakes. 

Another format, known as raster data, places data values within squares distributed on an evenly 

spaced grid. Raster formats are well suited to pictures and images of land cover, elevation and 

slope. In addition, metadata allows users to inquire about the origins, history, and quality of a 

particular dataset used in GIS modeling. 

Ms. Smith emphasized that GIS systems allow many questions to be answered simultaneously. 

However, implementation challenges remain, she said, particularly with regards to identifying 

and fulfilling user needs. A key problem, Smith stated, emerges when new technologies are 

developed without sufficient, up-front evaluation of user requirements. In these cases, the 

technologies are adapted to purposes for which they may not be well suited. 

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Ray Hoff, Professor, Department of Physics, University of Maryland, Baltimore County 

(UMBC) and Director, Joint Center for Earth Systems Technology 

Integrating Spatial Data to Address Air Quality 

Dr. Hoff contrasted the strengths and weaknesses of ground-based and satellite approaches for 

measuring air quality. Ground measures, he explained, provide continuous pollutant measures at 

discrete locations. Thus, they offer optimal temporal resolution but their spatial coverage is 

poor. Satellites, on the other hand, offer tremendous spatial coverage, but have drawbacks that 

limit their use for health research. This is in part due to the distances and atmospheric changes 

through which photons must travel before reaching remote sensors in space, Hoff said. With few 

exceptions, satellite-based spatial resolution ranges from one to 10 square kilometers, which 

may be inadequate for health studies. In addition, most satellites quantify column airborne 

aerosol levels without specific reference to concentrations on the ground. The best air quality 

assessments, Dr. Hoff concluded, emerge from integrated datasets that include both satellite and 

ground-based measures. 

Dr. Hoff went on to discuss LIDAR systems, which deploy lasers from space or Earth to 

augment passive solar detectors found on most satellites today. LIDAR systems allow scientists 

to add a vertical component to column measurements. Thus, they offer three-dimensional views 

of atmospheric columns (that also include two horizontal planes: north and east) that allow for 

assessments of ground level air quality. 

NASA’s new CALIPSO satellite, for instance—developed cooperatively with the French 

government and launched on October 26, 2005—uses LIDAR to measure discrete vertical 

columns at a resolution of 37 meters. NASA’s GLAS (Geoscience Laser Altimeter System) 

satellite, launched in 2003, achieves a vertical resolution of 75 meters. 

Dr. Hoff also discussed a new 3D air quality system (3D-AQS) being developed by UMBC with 

assistance from NOAA, NASA, Battelle Memorial Institute, and other organizations. The 3DAQS will use LIDAR to integrate vertical dimensions at a scale of 7.5 meters into the EPA’s air 

quality forecasting efforts. 

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Finally, Dr. Hoff described new research from his students showing that AOD measurements 

made in eastern regions of the United States correlate highly with hourly PM2.5 measurements. 

PLENARY SESSION III. DATA USE (Application of information to human health) 

Doug Dockery, Harvard School of Public Health (HSPH) 

Spatial-Temporal Analysis in Air Pollution Epidemiology 

Dr. Dockery began with a discussion of the NIEHS-funded “Harvard Six-Cities Study,” which 

ranks among the most influential, long-running investigations of air pollution and human health. 

Launched in 1973, the Six Cities Study—conducted in Watertown, Massachusetts; Portage, 

Wisconsin; Topeka, Kansas; Kingston/Harriman, Tennessee; St. Louis, Missouri; and 

Steubenville, Ohio—showed that increased mortality correlates with elevated levels of airborne 

particulates. Additional Harvard investigations using data from the American Cancer Society’s 

Cancer (ACS) Prevention Study found similar associations, Dockery said. 

More recent investigations show that air pollution variability within cities correlates with 

differential health outcomes. For example, reanalysis of the ACS data show mortality rates 

within Los Angeles vary among high and low air pollution areas designated by zip code. Based 

in part on these findings, Dr. Dockery emphasized the need for air pollution monitoring data that 

resolves spatially on a scale of city blocks. This need, he said, offers a clear opportunity for 

satellite data. (At this point, Dr. Hoff mentioned that ground-based LIDAR systems now used 

for national security could enable finer-scale spatial resolution for health research). 

Dr. Dockery described new Harvard research that suggests a need for greater temporal satellite 

resolution. These investigations study the relationship between air pollution and cardiac events 

measured by implanted defibrillators. Preliminary data show increased risk of ventricular 

arrhythmia with increasing particle levels. These findings, Dockery said, point to the need for air 

pollution monitoring at extremely fine time scales, on the order of minutes to hours. Ideally, 

technology enhancements will drive improvements in both spatial and temporal resolution that 

facilitate in-depth assessments of air pollution and human health. 

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Marie Lynn Miranda, Professor, Children’s Environmental Health Initiative (CEHI), 

Nicholas School of Environment and Earth Sciences, Duke University 

Spatial Analysis of Mercury Policy Options 

The CEHI is a research, education, and outreach program committed to fostering environments 

where children can prosper. Dr. Miranda described a CEHI effort to compare mercury emissions 

reductions in North Carolina resulting from two distinct policy options: 1) Maximum 

Achievable Control Technology with 90% reduction standard (MACT90); and 2) a national cap 

and trade program with caps set at 26 and 15 tons in 2010 and 2018 respectively (NCT2615). 

Mercury emissions data were obtained from the EPA’s Toxics Release Inventory for 2002 and 

also from the North Carolina Department of Environment and Natural Resources’ Division of 

Air Quality. The CALPUFF, a multi-layer, multi-species non-steady-state puff dispersion model 

that simulates the effects of time- and space-varying meteorological conditions on pollution 

transport, transformation and removal, was used to predict air concentrations, in addition to wet 

and dry deposition rates, among 5200+ census block groups located in North Carolina. 

The key findings are: 

• Preliminary analyses suggest that MACT90 achieves greater reductions than 

NCT2615; however, North Carolina’s mercury emissions reporting programs leave 

out important sources. Moreover, new cap designations proposed under the EPA’s 

new Clean Air Mercury Rule were higher than those used in the analysis. 

• Both programs produce the greatest benefits in areas of the state where the population 

is more affluent and more likely to be Caucasian. 

Dr. Miranda proposed a variety of additional data that could improve modeling efforts: These 

include: 1) comprehensive inventory of mercury emissions across space and time; 2) emissions 

fingerprints off stacks; 3) event-based wet deposition sampling; and 4) high-altitude sampling. 

The characterization of these parameters provides an opportunity for remote sensing. 

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Judith Qualters, Chief, Environmental Tracking Branch, National Center for 

Environmental Health, Centers for Disease Control and Prevention (CDC) 

Integrating Earth Observations and Health Data for Public Health Surveillance 

The Environmental Tracking Branch bears responsibility for implementing the CDC’s National 

Environmental Public Health Tracking (EPHT) Program, which was initiated at the request of 

Congress in 2002. The EHPT Program goals are twofold: to integrate information about 

environmental hazards, human exposures, and disease; and to deliver this information to state 

and local agencies working to protect public health. 

Two specific EPHT projects were discussed in detail. The first, known as the Public Health Air 

Surveillance Evaluation Project (PHASE), critiques methods to generate surrogate measures of 

ozone and PM2.5 that can be linked to health effects data corresponding to asthma and acute 

cardiac events. This effort is a collaboration of CDC, EPA, and scientists from health 

departments in three states: Maine, New York, and Wisconsin. Four methods for characterizing 

air quality are currently being investigated: 1) proximity-based assessments derived with local 

ground monitoring stations; 2) statistical interpolation of ambient air monitoring data using 

kriging techniques that extrapolate continuous surface estimates from a known set of sample 

points; 3) CMAQ modeling; and 4) Bayesian methods that combine monitoring and CMAQ 

data. Results of this comparison are ongoing and conclusive results are not yet available. 

Dr. Qualters then described another multi-agency EPHT project called Health and Environment 

Linked for Information Exchange, Atlanta (HELIX-Atlanta). This project seeks to build an 

EPHT network in five Atlanta counties: Clayton, Cobb, DeKalb, Fulton, and Gwinnett. As part 

of these efforts, EPHT scientists combine MODIS AOD measures generated by the Terra and 

Aqua satellites with ground-based PM2.5 monitoring to estimate population exposure. The goal is 

to enhance spatial and temporal coverage with remote sensing data. Qualters stated that AOD 

measures correlate best with ground-based monitoring in the summer, likely because of stronger 

boundary layer mixing during the warmer months. Thus, as it currently stands, the Helix-Atlanta 

respiratory health and birth defects projects will add AOD simulations into exposure 

assessments only in summer until technical details are resolved. 

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PLENARY SESSION IV 

Guy Duchossois, Work Plan Manager, GEO Secretariat, Geneva Switzerland 

Overview of the GEO Work Plan 

Dr. Duchossois first listed numerous European initiatives in Earth observations by entities that 

include the European Union, the European Space Agency (ESA), and the European Center for 

Medium-Range weather forecasts. He then shifted his talk to a discussion of the GEO and its 

development of a ten-year plan for a Global Earth Observation System of Systems (GEOSS). 

[N.B. At the time of the workshop GEO membership included 58 member nations, the European 

Commission, and 43 international organizations; an additional eight nations joined by October 

2006.] 

The GEO Work Plan is divided among two, six, and 10 year targets. The initial focus is on 107 

two-year targets, of which 14 focus specifically on health. Among these, three were highlighted: 

1) advocate new high-resolution Earth observations relevant to health needs; 2) facilitate 

mechanisms to translate data user needs into requirements that data generators can address; 3) 

facilitate development of data products and systems that integrate Earth science databases with 

health and epidemiological information. 

To advance these aims, the GEO is now strengthening links with the World Health Organization 

and participating in workshops planned by the European Commission, the US EPA, and the 

ESA. In addition, GEO is sponsoring with WHO a workshop on human health, the environment 

and Earth observations. The draft GEO 2006 Work Plan is being prepared for submission to the 

GEO Executive Committee, with comments expected back in late October. It will be submitted 

with a report on 2005 achievements for approval by the GEO at its meeting in December 2005. 

Dr. Duchossois emphasized that health is a top GEO priority in its plan for the GEOSS and that 

Earth observations— despite gaps in coverage—have the capacity to advance health studies in 

many parts of the world, including developing nations. He reported that representatives of the 

G8 nations expressed strong political support for the GEO at their Summit in Gleneagles, 

Scotland in July 2005. They welcomed the adoption of the ten-year plan for the development of 

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the GEOSS and made a commitment to move forward in implementing it in their member states 

and to support efforts to help developing countries obtain full benefit from GEOSS. 

Meredith Golden, Center for International Earth Science Information Network, 

The Earth Institute, Columbia University 

Confidentiality Issues and Policies Related to the Use of Geospatial Data 

Ms. Golden pointed out that data gaps in Earth observations derive from sampling shortages and 

also from confidentiality mechanisms that restrict data access. To define confidentiality, Golden 

quoted Mark Rothstein, Professor of Law at the University of Louisville: “The right of an 

individual to prevent the redisclosure of certain sensitive information that was disclosed 

originally in the confines of a confidential relationship.” 

Ms. Golden cited three reasons to protect confidentiality: 1) Confidentiality preservation is 

regarded as an ethical statistical practice; 2) confidentiality preservation may be required by law 

or regulation or by organization policy; 3) it is believed that respondents would not divulge 

confidential information truthfully or completely without assurance of confidentiality 

preservation. 

Spatial data pose unique threats to confidentiality, Golden stressed, because they are often 

publicly available and displayed as maps. Relational databases could conceivably link a 

subjects’ personal information with visual imagery of their residential locations. Ms. Golden 

pointed out that the QuickBird satellite’s fine spatial resolution is sufficient to visualize and 

identify individual households. Thus, researchers must consider how data gathered during Earth 

observations research are used, to ensure that privacy and confidentiality are protected. 

WORKING GROUP REPORTS 

Working groups were organized and asked to consider: (1) Types of data collected versus 

needed; (2) Areas of application for remotely sensed measurements; (3) Strategies for data 

integration and application; (4) Knowledge Gaps; and (5) Impediments of remote sensing data to 

cardiovascular health. 

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1. Cardiovascular Working Group 

Types of data collected versus data needed 

Existing sources of remote sensing data were listed for ground-level particulates and groundlevel gases (namely, carbon monoxide and ozone). 

Particulate data sources include ground-based monitors, MODIS, NOAA’s Geostationary 

Environmental Satellites (GOES), NOAA’s Advanced Resolution Very High Radiometer 

(AVHRR), and the Automated Weather Observing System (ASOS), which is a suite of groundbased meteorology sensors deployed jointly by the National Weather Service, the Federal 

Aviation Administration, and the Department of Defense. For gases, the key source was said to 

be Differential Optical Absorption Spectroscopy (DOAS), which is an emerging technique for 

trace gases measurement. Emerging and future sources of remote sensing data cited by working 

group participants include LIDAR spatial maps and the CALIPSO satellite, which will be 

launched in 2006 to provide the next generation of climate observations, including an advanced 

study of clouds and aerosols, drastically improving our ability to predict climate change and to 

study air pollution and transport. 

In terms of data needs, the working group identified greater quality assurance and data 

documentation mechanisms, historical GIS information, and spatially distributed data for 

cardiac risk factors, such as housing characteristics, traffic emissions, point-source pollution 

emissions, and residential locations for susceptible populations, such as the elderly and underserved minorities. 

Areas of Application within cardiovascular research for remotely sensed data 

Application areas that might be served by remote sensing data were classified as clinical and 

sub-clinical cardiovascular outcomes that might be linked to acute or chronic exposures on 

individual or population-based levels. Among the clinical outcomes are myocardial infarction, 

arrhythmias, heart failure, hypertension and stroke. Hospital admissions or emergency room 

visits for these outcomes could be evaluated in population-level as well as individual-based 

studies. Sub-clinical outcomes include heart rate variability, blood pressure, changes in the STsegment that represents the period of ventricular muscle contraction before repolarization, 

15
brachial artery diameter, flow-mediated dilation, systemic inflammation, and measures of 

atherosclerosis. 

Opportunities for data integration and application 

The working group participants identified opportunities for pilot studies evaluating the potential 

for data integration and application. Ground level central site and personal measurements might 

be supplemented by data from remote sources: (1) to estimate exposure during times and days 

when there were no ground level measurements; and (2) to get better spatial resolution of certain 

pollutants measured only at central ground sites. However, a more specific understanding is 

needed of the temporal and spatial resolution of exposure measurements that could be 

specifically linked to past or ongoing measurements of health outcomes, and the comparability 

of exposures estimated from global Earth observations to ground level observations. If feasible, 

a combination of MODIS measures and ground-level PM2.5 might be incorporated into several 

ongoing studies, including the Harvard’s Nurses Health Study and the American Cancer 

Society’s Cancer Prevention Study, to assess chronic cardiac effects of ambient pollutants. 

Moreover, MODIS measures of aerosol optical depth could be applied to acute health studies, 

such as the Harvard investigation of air pollution and its effect on ventricular arrhythmias or 

paroxysmal atrial tachycardia detected by cardiac defibrillators. However, pollution data applied 

to these acute studies must be resolved at a scale of 24-hours or less to be useful. 

Opportunities and challenges for data integration and application 

Remote sensors used for particulates and gases were said to have a number of drawbacks. Those 

used for particle detection, for instance, were described as limited with respect to both spatial 

resolution and their capacity to identify chemical composition. Moreover, remote sensors are 

unable to measure ultra-fine particles with a diameter of less than 2.5 micrometers that are now 

implicated in a range of cardiac health effects. The detection of ground-level ozone gas was also 

said to be problematic, chiefly because of the need to subtract out stratospheric ozone, which 

filters ultra-violet solar rays. Efforts to improve spatial resolution may be complicated by higher 

noise-to-signal ratios, which could limit precision. Participants also speculated that privacy and 

national security concerns could limit the availability of remote sensing data and thus its 

application to human health research. 

16
Knowledge gaps: data measurement 

Quality assurance mechanisms are potentially not as robust for remote sensing data as they are 

for conventional regulatory measurements. In addition, cloud cover, snow reflectivity, and 

diminished vertical mixing all reduce the accuracy of ground-level pollutant levels measured in 

winter. 

Knowledge gaps: data application 

Participants noted that polar orbiting satellites have higher spatial resolution but less temporal 

detail owing to Earth’s rotation beneath them. Geostationary satellites, on the other hand, have 

greater temporal resolution (on the order of four measurements per hour) but lower spatial 

resolution. U.S. investigators need to become more familiar with measurements being conducted 

by colleagues from Europe, Asia and other areas outside of North America, participants said. 

Impediments to application of remotely sensed data to cardiovascular health 

Privacy concerns articulated by the Health Insurance Portability and Accountability Act 

(HIPAA) must be considered in studies that link addresses and geocodes to exposure 

measurements. HIPAA regulations designed to protect patient privacy could limit access to 

hospital data. Homeland security concerns may also limit access to satellite data. 

Challenges of and barriers to multidisciplinary problem solving between biological and 

physical scientists 

Limited knowledge of data availability and the lack of resources to translate raw data into 

useable formats were cited as barriers to multidisciplinary research in this area. In addition, the 

use of technical jargon and the lack of avenues for effective communication can inhibit 

collaborations necessary for multidisciplinary research. 

Demonstration Project 

Several demonstration projects were proposed. Researchers could compare cardiovascular 

associations with particle exposures estimated from ground versus satellite measurements. A 

combination of MODIS measurements with ground-level measurements for PM2.5 might be 

incorporated into both the Harvard’s Nurses Health Study and the American Cancer Society’s 

(ACS) Cancer Prevention Study to assess chronic cardiac effects of ambient pollutants. 

Moreover, MODIS measurements of aerosol optical depth could be applied to acute health 

17
studies, such as the Harvard investigation of air pollution and its effect on ventricular 

arrhythmias or paroxysmal atrial tachycardia detected by cardiac defibrillators. Participants 

emphasized repeatedly that remote sensing data must be matched appropriately with the 

applications under investigation. Along these lines, spatial and temporal limits may not impede 

research on chronic applications. However, acute studies--for instance those that address 

myocardial infarction, stroke, or pollution-related factors that trigger implanted defibrillators--

do require highly resolved temporal data. 

2. Respiratory Working Group 

Types of data collected versus data needed 

The respiratory working group identified several data needs that apply to remote sensing and 

studies of respiratory health. These include additional mechanisms for data quality assurance 

and control, and access to long-term data for retrospective research. Participants suggested 

remote sensing could help fill gaps in existing data, and singled out inadequate air quality 

assessments downwind of urban areas as a key opportunity, but greater use of remote sensing 

must be accompanied by validation studies to confirm that remote sensing and ground-based 

measurements are comparable. 

Areas of application within respiratory research for remotely sensed data 

Participants proposed that remote sensing might differentiate anthropogenic and natural sources 

of dust, particularly pollen grains, which can—in the opinion of some health scientists—pose 

health risks equal to or greater than those posed by criteria pollutants. EPA does not currently 

measure pollen levels, so this presents an opportunity for remote sensing, the participants 

concluded. Remote sensors can detect bioaerosols from space, but the associated methods have 

not yet been standardized. Thus, an alternate approach was proposed—namely to construct 

predictive models for pollen release based on seasonal information and geophysical parameters 

such as temperature, sunlight, humidity, and vegetation health. 

Participants also suggested that remote sensing could advance knowledge of large-scale 

respiratory health events, such as the dramatic rise in asthma cases typically observed in 

Baltimore, MD, during the month of September. 

18
Strategies for data integration and application 

Remote sensing could be integrated with data from the EPA’s Supersites program, which uses 

ambient monitoring to address the scientific uncertainties associated with fine particulates. 

However, in order for remote sensing to function in this context, methods for data reduction and 

uncertainty analysis must also be developed. 

Knowledge gaps: data measurement and application 

Knowledge gaps were categorized by relevance to either Earth or health sciences. In terms of 

the latter, knowledge gaps include inadequate measures of coarse versus fine particles; inability 

to distinguish chemical species; and insufficient vertical modeling for ground-level 

contaminants. Health science knowledge gaps include limited population-based surveillance 

systems; insufficient sample sizes; poor characterization of residential and activity-based 

mobility patterns; and inadequate awareness of individual susceptibilities and risk factors. 

Knowledge gaps: data integration 

Scientists should confirm temporal and spatial concordance of remote sensing data, focusing in 

particular on optimal data resolution for specific health outcomes and affected populations. 

International collaboration and data exchange was suggested as a mechanism for enhancing data 

integration. 

Challenges of and barriers to multidisciplinary problem solving between biological and 

physical scientists. 

The main barriers to multidisciplinary collaboration were said to be the lack of effective 

communication among data users and producers and support for multidisciplinary, multiproject 

research. Continued dialogue among specialists and cross-disciplinary education were proposed 

as solutions. 

Demonstration Project 

Participants suggested a study of asthma. Such a study would layer remote sensing data for 

meteorology, fine particulates, and bioallergens over geo-referenced datasets for asthma 

prevalence and exacerbation. Geo-referenced data would be obtained from health maintenance 

organizations, hospitals, and large-scale surveys such as the CDC’s National Health and 

19
Nutrition Examination Survey (NHANES). The effort would build on existing studies and use 

remote sensing to fill gaps in exposure data. 

3. Reproductive Working Group 

Types of data collected versus data needed 

Participants emphasized that studies linking remote sensing to reproductive health effects must 

delineate specific outcomes, such as fetal death, stillbirth, post-infant mortality, and subclinical 

events such as neurological and immune dysfunction. Integration of satellite-based exposure 

data must consider windows of reproductive vulnerability (for instance, early pregnancy), which 

remain poorly understood. Database needs were cited in the area of reproductive outcomes and 

residential history for study subjects. 

Areas of application within reproductive health research for remotely sensed data 

Participants questioned whether remote sensing could provide better air quality data than that 

provided by EPA’s current monitoring programs in metropolitan areas. Niche applications might 

be found in areas where current ground-based networks do not currently exist. Several 

application areas for these locations were identified. Among them is the need to identify 

windows of vulnerability before, during, and following parturition; the need to identify acute 

versus chronic pollutant exposures and their differential reproductive effects; and efforts to 

assess pollutant interactions with maternal and fetal genetic susceptibilities. Participants focused 

their discussions on low-birth-weight and pre-term birth, which are currently the bestunderstood outcomes. 

Strategies for data integration and application 

Existing and on-going birth outcome and child development studies that allow for incorporation 

of air pollution data should be identified and compiled. The CDC’s National Birth Defects 

Prevention Study, which is among the largest case-control studies ever on the causes of birth 

defects, was proposed as a possible candidate. Participants emphasized that if remote sensing is 

to comprise the source of air pollution data, then it must be resolved appropriately, with a 

minimum sampling frequency of once per day, and a minimum spatial resolution of one square 

mile. 

20
Knowledge gaps: data measurement 

Measurement gaps were identified in three key areas: time-activity data for pregnant women and 

children that overlay with pollutant exposure and outcome data; uncertainty estimates for 

measures of air pollution derived with remote sensing, and data corresponding to non-criteria 

pollutants, such as ultrafine particles. 

Knowledge gaps: data integration and application 

Participants recommended the creation of lists that correlate health outcomes with exposure to 

criteria and/or toxic air pollutants. Similarly, participants suggested that air pollutants that can 

be monitored with remote sensing be listed, with accompanying assessments of how remote 

sensing measures of these pollutants compares with ground- based measurements in undersampled areas, such as rural locations. 

Impediments to application of remote sensing data to reproductive health outcomes 

Several key impediments to the use of remote sensing in reproductive health studies were 

identified. These include inconsistent temporal and spatial matching with health outcomes of 

interest; problems extrapolating ground-level concentrations from column AOD measurements; 

insufficient spatial resolution; and remote sensing’s inability to identify air toxics, such as 

metals and ultrafine particles. 

Challenges of and barriers to multidisciplinary problem solving between biological and 

physical scientists 

The main barriers to multidisciplinary collaborations were said to be the absence of personal 

relationships among biological and physical scientists; and difficulties with integrating data 

needs for population-based human studies with those of in-depth, cellular and molecular studies 

of individuals. The first study type requires long-term, population-level exposure data and 

additional measures that account for confounding and risk modification. The second type of 

study incorporates biomarkers and other in-depth exposure characterizations that are not feasible 

in population studies. 

Demonstration project 

Projects were proposed on both neighborhood and regional scales. On a neighborhood scale, 

reproductive outcomes data could be linked with remote sensing data archives, such as those 

21
produced by Canada's Measurements of Pollution in the Troposphere (MOPITT) instrument 

which measures atmospheric carbon monoxide. On a regional scale, existing satellite data could 

be linked to epidemiological data, in an effort to match pollutant levels with adverse 

reproductive outcomes. Participants emphasized the need for preliminary studies that compare 

results obtained with remote sensing-based exposures with results obtained from ground-level 

monitoring-based exposures. Should remote sensing provide comparable results then greater use 

of the technology for reproductive and developmental effects studies is warranted. 

CONCLUSIONS 

The workshop successfully fostered a vigorous exchange of information between scientists from 

the Earth observation and health research communities. It established additional communication 

links between the producers of air quality measurements and health researchers and practitioners 

who use those data to understand the effects of air pollution on human health and make 

decisions regarding public health. The workshop has launched what will ideally become far 

more robust and sustainable collaborations between these data producers and data users than 

exists at the present time. 

In addition to a discussion on data architecture (the way data are organized, stored, and made 

available to users), health scientists raised feasibility issues. These issues focused on several key 

areas, including quality assurance and control for remote sensing data; correlations with groundbased measurements; limits on temporal and spatial resolution; the capacity to assess chemical 

speciation from space; extrapolation of ground-level pollutant levels from measures of aerosol 

optical depth (AOD); and data limitations imposed by national security concerns. On the other 

hand, health scientists were also optimistic that technology issues can be resolved and that 

remote sensing will increasingly complement ground-based measures in studies of air pollution 

and health. Emerging LIDAR systems, for instance, which provide vertical resolution for AOD, 

can be used to quantify pollutant levels on the ground. Moreover, studies increasingly show that 

column AOD measures correlate with PM2.5. Health scientists from CDC, EPA, and other 

federal and state agencies described growing uses for remote sensing, which provides a valuable 

supplement to ground-based air measures and opportunities for predictive modeling. 

22
1
DATA PRODUCTION (what can be measured) 

Chair: Ms. Valerie Garcia, EPA 

9:00 – 9:20 AM Setting the Stage: Strengths and Limitations of Spatial Data 

Dr. S T Rao, NOAA 

9:20 – 9:40 AM New Discoveries and Future Directions of Satellite Research 

Dr. Richard Kleidman, NASA 

9:40 – 10:10 AM Availability and Uses of Operational Satellite Data 

Dr. Shobha Kondragunta, NOAA 

10:10 – 10:30 AM Land-Based Networks 

Dr. Richard Scheffe, EPA 

10:30 – 10:45 AM Break 

Integrated Earth Observations: Application to 

Air Quality and Human Health

National Institute of Environmental Health Sciences 

Research Triangle Park, NC 

MONDAY, AUGUST 1, 2005 

8:00 – 8:30 AM Registration 

8:30 – 8:40 AM Welcome and Introductions 

Dr. Sally Tinkle, Meeting Organizer, NIEHS 

Dr. Anne Sassaman, Director, Division of Extramural Research and 

Training, NIEHS 

8:40 – 9:00 AM Welcome and Overview of the Global Earth Observation System of Systems 

(GEOSS) 

Dr. Gary Foley, Director, National Exposure Research Laboratory, EPA 

Plenary Sessions 

1
DATA INTEGRATION (translating data to information) 

Chair: Ms. Valerie Garcia, EPA 

10:45 – 11:05 AM Integrating and Accessing Spatial Data: Challenges and Successes 

Ms. Brenda Smith, EPA 

11:05 – 11:25 AM Integrating Spatial Data to Address Air Quality 

Dr. Ray Hoff, UMBC 

DATA USE (application of information to human health) 

Chair: Ms. Mary Gant, NIEHS 

11:25 – 11:45 AM Spatial-Temporal Analyses in Air Pollution Epidemiology 

Dr. Doug Dockery, Harvard School of Public Health 

11:45 – 12:05 AM Spatial analysis of mercury policy options 

Dr. Marie Lynn Miranda, Duke University 

12:05 – 12:25 PM Integrating Earth Observation and Health Data for Public Health Surveillance 

Dr. Judy Qualters, Centers for Disease Control and Prevention 

12:25 – 12:30 PM CHARGE TO WORKING GROUPS 

Dr. Sally Tinkle, NIEHS 

12:30 – 1:30 PM Lunch 

Working Group Sessions 

1:30 – 2:45 PM WORKING GROUPS 

Conference Room A: Respiratory 

Conference Room B: Cardiovascular 

Conference Room C: Developmental/Birth Defects 

2:45 – 3:00 PM Break 

3:00 – 5:00 PM WORKING GROUPS (continued) 

5:00 PM Shuttles back to hotel 

6:00 – 7:30 PM DINNER 

Radisson 

8:00 PM WORKING GROUP LEADER AND RAPPORTEUR MEETING 

Radisson 

Chair: Dr. Sally Tinkle, NIEHS 

2
TUESDAY, AUGUST 2, 2005 

8:30 – 8:40 AM Announcements and introduction to plenary session 

Chair: Ms. Mary Gant, NIEHS 

Professor and Chair 

Plenary Sessions 

8:40 – 9:00 AM Overview of the GEOSS Work Plan 

Dr. Guy Duchossois, GEOSS Work Plan Manager 

9:00 – 9:20 AM Confidentiality Issues and Policies Related to the Use of Geospatial Data 

Ms. Meredith Golden, Columbia University 

Working Group Sessions 

WORKING GROUP REPORTS 

Co-Chairs: Dr. Sally Tinkle, NIEHS 

Ms. Valerie Garcia, EPA 

9:20 – 9:50 AM Respiratory Working Group 

Dr. Peggy Reynolds, California Dept. of Health Services 

9:50 – 10:20 AM Cardiovascular Working Group 

Dr. Diane Gold, Harvard School of Public Health 

10:20 – 10:35 AM Break 

10:35 – 11:05 AM Developmental/Birth Defects Working Group 

Dr. Beate Ritz, UCLA 

11:05 – 11:45 AM SUMMARY OF FINDINGS AND NEXT STEPS 

Dr. Sally Tinkle, NIEHS 

11:45 – 12:00 AM CLOSING REMARKS 

Dr. Gary Foley, EPA 

12:00 – 1:00 PM Lunch and/or departure for airport 

3
John Bachmann 

U.S. Environmental Protection Agency 

Office of Air and Radiation 

Office of Air Quality and Planning 

Standards 

Mail Drop: C404-04 

Research Triangle Park, NC 27711 

bachmann.johnd@epa.gov 

Eric Betterton 

Department of Atmospheric Sciences 

University of Arizona 

Tucson, AZ 85721-0081 

betterton@atmo.arizona.edu 

520-621-2050 

Andy Bond 

SEE 

U.S. Environmental Protection Agency 

D305-01 

National Exposure Research Laboratory 

Research Triangle Park, NC 27711 

bond.andy@epamail.epa.gov 

919-541-4529 

Rebecca Calderon 

Director 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects 

Research Laboratory 

Mail Drop: 58A 

Research Triangle Park, NC 27711 

Calderon.Rebecca@epamail.epa.gov 

919-966-0617 

Dan Costa 

National Program Director for Air Research 

U.S. Environmental Protection Agency 

Office of Research and Development 

Mail Drop: B143-01 

Research Triangle Park, NC 27711 

Costa.Dan@epamail.epa.gov 

919-541-2532 

Doug Dockery 

Department of Environmental Health 

HSPH Landmark Center 

Suite 415 

401 Park Dive West 

Boston, MA 02115 

ddockery@hsph.harvard.edu 

617-384-8741 

Guy Duchossois 

GEOSS Work Plan Manager 

GEO Secretariat 

Geneva, Switzerland 

GDuchossois@geosec.org 

41-22-730-8484 

Peyton A. Eggleston 

Department of Pediatrics - Immunology 

School of Medicine 

Johns Hopkins University, East Baltimore 

Campus 

CMSC 1102, Pediatrics 

600 North Wolfe Street 

Baltimore, MD 21287 

pegglest@jhmi.edu 

410-955-5883 

Global Earth Observations: Application to Air Quality and Human Health 

August 1-2, 2005

Participant List 

1
Richard H. Finnell 

Institute of Biosciences and Technology 

Texas A & M University 

2121 W. Holcombe Blvd. 

Houston, TX 77030 

rfinnell@ibt.tamu.edu 

713-677-7777 

Gary Foley 

Director 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Exposure Research Laboratory 

Mail Drop: D305-01 

Research Triangle Park, NC 27711 

Foley.Gary@epamail.epa.gov 

919-541-2106 

Mary Gant 

Office of Science, Policy and Planning 

National Institute of Environmental Health 

Sciences 

31 Center Drive 

Bethesda, MD 20892-2256 

gant@niehs.nih.gov 

301-496-2919 

Valerie Garcia 

Assistant Lab Director 

National Exposure Research Laboratory 

MD-D301-01 

Office of Research and Development 

Environmental Protection Agency 

Research Triangle Park, NC 27711 

garcia.val@epa.gov 

919-541-2649 

Diane R. Gold 

Department of Environmental Health 

Harvard School of Public Health 

Building I, 14th Floor 

665 Huntington Avenue 

Boston, MA 02115 

diane.gold@channing.harvard.edu 

617-432-1270 

Meredith Golden 

CIESIN at Columbia University 

200 Geosciences 

P.O. Box 1000, 61 Route 9W 

Palisades, NY 10964-8000 

mgolden@ciesin.columbia.edu 

845-365-8968 

Kimberly Gray 

Susceptibility and Population Health Branch 

Division of Extramural Research and 

Training 

National Institute of Environmental Health 

Sciences 

P.O. Box 12233 MD EC-21 

111 T.W. Alexander Drive 

Research Triangle Park, NC 27709 

gray6@niehs.nih.gov 

919-541-0293 

John A. Haynes 

Program Manager, Aviation Program 

Element 

Program Manager, Public Health Program 

Element 

Applied Sciences Program 

Science Mission Directorate, Earth-Sun 

System Division 

NASA 

300 E Street, SW 

Mail Suite 5L79 

Washington, DC 20546-0001 

jhaynes@nasa.gov 

202-358-4665 

2
Raymond Hoff 

Professor: Physics Department 

Director: Joint Center for Earth Systems 

Technology 

University of Maryland Baltimore County 

1000 Hilltop Circle 

Baltimore, MD 21250 

hoff@umbc.edu 

410-455-1610 

Michael Humble 

Organs, Systems Pathobiology Branch 

Div of Extramural Research and Training 

NIEHS 

111 T.W. Alexander Drive 

PO 12233, Mail Drop EC-23 

Research Triangle Park, NC 27709 

humble@niehs.nih.gov 

919-316-4621 

Geoffrey M. Jacquez 

President, BioMedware 

516 North State Street 

Ann Arbor, MI 48104-1236 

Jacquez@BioMedware.com 

734-913-1098 ext 6 

Richard Kleidman 

SSAI 

code 613.2 

NASA/Goddard Space Flight Center 

Greenbelt MD 20771 

kleidman@climate.gsfc.nasa.gov 

301-614-6196 

Shobha Kondragunta 

Research Physical Scientist and Air Quality 

Team Lead 

NOAA/NESDIS Office of Research and 

Applications 

5200 Auth Road 

Camp Springs, MD 20746 

Shobha.Kondragunta@noaa.gov 

301-763-8136 X 151 

Dennis Lang 

Deputy Director 

Division of Extramural Research and 

Training 

National Institute of Environmental 

Health Sciences, NIH 

P.O. Box 12233, MD EC20 

Research Triangle Park, NC 27709 

DL73v@nih.gov 

919-541-7729 

Duanping Liao 

Department of Health Evaluation Sciences 

Penn State Medical College 

H173 

Hershey, PA 17033 

Dliao@hes.hmc.psu.edu 

717-531-7178 

Danelle T. Lobdell 

US Environmental Protection Agency 

Epidemiology and Biomarkers Branch 

Human Studies Division 

MD58A 

Research Triangle Park, NC 27711 

Lobdell.danelle@epa.gov 

919-843-4434 

John G. Lyon 

Director 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Exposure Research Laboratory 

Environmental Sciences Division 

944 East Harmon Avenue 

Las Vegas, NV 89193 

lyon.johng@epa.gov 

702-798-2525 

3
Gregory A. Mandt 

Director, Office of Science and Technology 

NOAA/National Weather Service 

1325 East-West Highway, 

SSMC2--Rm. 15146, W/OST 

Silver Spring, MD 20910 

Greg.Mandt@noaa.gov 

301-713-1746 

J. Patrick Mastin 

Chief, Cellular, Organs, and Systems 

Pathobiology Branch 

Division of Extramural Research and 

Training 

NIEHS 

111 T.W. Alexander Drive 

PO 12233, Mail Drop EC-23 

Research Triangle Park, NC 27709 

mastin@niehs.nih.gov 

919-541-3289 

Marie Lynn Miranda 

Nicholas School of the Environment and 

Earth Sciences 

Duke University 

A134 LSRC 

Box 90328 

Durham, NC 27708 

mmiranda@duke.edu 

919-613-8023 

Gunter Oberdorster 

Department of Environmental Medicine 

University of Rochester 

575 Elmwood Avenue, MRBx Bldg., Box 

Rochester, NY 14642 

Gunter_Oberdorster@urmc.rochester.edu 

585-275-3804 

David M. Ozonoff 

Department of Environmental Health 

Boston University 

Talbot Building, 2East 

715 Albany Street 

Boston, MA 02118 

dozonoff@bu.edu 

617-638-4620 

Linda W. Pickle 

Division of Cancer Control and Population 

Science 

National Cancer Institute, NIH 

Executive Plaza North, Suite 4103 MSC 

7359 

6130 Executive Blvd., Bethesda, MD 

30852-7359 

pickle@mail.nih.gov 

301-435-7739 

Judith R. Qualters 

Environmental Public Health Tracking 

Branch 

Centers for Disease Control and Prevention 

1600 Clifton Road, NE, E19 

Atlanta, GA 30329 

judith.qualters@cdc.hhs.gov 

404-498-1815 

Tonse N. K. Raju 

Medical Officer/Program Scientist 

Pregnancy and Perinatology Branch 

CDBPM/NICHD; National Institutes of 

Health 

6100 Executive Blvd, Room 4B03 

Bethesda, MD, 20952. 

(For Fed Ex: Rockville, MD, 20852) 

rajut@mail.nih.gov 

301-402-1872 

4

850 
S. Trivikrama (S.T.) Rao 

NOAA National Exposure Research 

Laboratory/ASMD 

Mail Drop: E243-02 

Research Triangle Park, NC 27711 

Rao.ST@epamail.epa.gov 

919-541-4542 

Peggy Reynolds 

Environmental Health Investigations Branch 

CA Dept Health Services 

1515 Clay Street, Suite 1700 

Oakland, CA 94612 

preynold@dhs.ca.gov 

510-622-4417 

Beate R. Ritz 

Department of Epidemiology and 

Environmental Health 

University of California at Los Angeles 

Box 951772, 73-320A CHS 

Los Angeles, CA 90095-1772 

britz@ucla.edu 

310-206-7458 

Anne Sassaman 

Director 

Division of Extramural Research and 

Training 

National Institute of Environmental 

Health Sciences 

National Institutes of Health 

P.O. Box 12233 

Research Triangle Park, NC. 27709 

Email: sassaman@niehs.nih.gov 

919-541-7723 

Richard Scheffe 

USEPA 

Office of Air Quality Planning and 

Standards 

Mail Drop: C304-01 

Research Triangle Park, NC 27711 

scheffe.rich@epamail.epa.gov 

919-541-4650 

Charles Schmidt 

Science Writer 

111 Commercial Street 

5th Floor 

Portland, ME 04101 

charlie@schmidtwriting.com 

207-347-5237 

Linda Sheldon 

Acting Director 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Exposure Research Laboratory 

Human Exposure & Atmospheric Sciences 

Division 

Mail Drop: E205-01 

Research Triangle Park, NC 27711 

Sheldon.Linda@epamail.epa.gov 

919-541-2205 

Brenda J. Smith 

US Environmental Protection Agency 

Ariel Rios Building 

1200 Pennsylvania Avenue, N.W. 

Mail Code: 2810A 

Washington, DC 20460 

smith.brenda@epa.gov 

202-564-2034 

5
William A. Sprigg 

Department of Atmospheric Sciences 

University of Arizona 

1118 E. 4th Street 

Tucson, AZ 85721 

wsprigg@u.arizona.edu 

520-626-8945 

Shobha Srinivasan 

Susceptibility and Population Health Branch 

Division of Extramural Research and 

Training 

National Institute of Environmental 

Health Sciences 

P.O. Box 12233 MD EC-21 

111 T.W. Alexander Drive 

Research Triangle Park, NC 27709 

sriniva2@niehs.nih.gov 

919-541-2506 

Matthew Strickland 

Health Research Scientist (Battelle) 

National Center on Birth Defects and 

Developmental Disabilities, CDC 

Centers for Disease Control & 

Prevention 

Mailstop E-86 

Atlanta, GA 30333 

cro6@cdc.gov 

404-421-3183 

George D. Thurston 

Department of Environmental Medicine 

NYU, School of Medicine 

Sterling Forest 2 270 

57 Old Forge Road 

Tuxedo, NY 10987 

George.thurston@med.nyu.edu 

845-731-3564 

Sally Tinkle 

Organs, Systems Pathobiology Branch 

Division of Extramural Research and 

Training 

NIEHS 

111 T.W. Alexander Drive 

PO 12233, Mail Drop EC-23 

Research Triangle Park, NC 27709 

stinkle@niehs.nih.gov 

919-541-5327 

Lance Waller 

Department of Biostatistics 

Emory University 

1518 Clifton Road, NE Room 326 

Atlanta, GA 30322 

lwaller@sph.emory.edu 

404-727-1057 

Eric A. Whitsel 

Department of Epidemiology 

University of North Carolina 

Cardiovascular Disease Program 

Bank of America Center, Suite 306 

137 East Franklin Street 

Chapel Hill, NC 27514 

ewhitsel@email.unc.edu 

919-966-3168 

Mark L. Witten 

Southwest Environmental Health Sciences 

Center 

Department of Pediatrics 

Arizona Health Sciences Center, 3301 

1501 North Campbell Ave 

Tucson, AZ 85724-5073 

mwitten@peds.arizona.edu 

520-626-657 

6
Judith T. Zelikoff 

Department of Environmental Medicine 

NYU Medical Center 

SLF 2 235A 

57 Old Forge Road 

Tuxedo, NY 10987 

judyz@env.med.nyu.edu 

845-885-5230 

7 
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