&EPA
United States
Environmental Protection
Agency
Integrated Earth
Observations: Application
to Air Quality and
Human Health
RESEARCH AND DEVELOPMENT
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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
2U.S. Environmental Protection Agency
Office of Research and Development
National Exposure Research Laboratory
Environmental Sciences Division
Las Vegas, NV89119
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 i7merio7
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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
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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 decision-
making 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 ground-
based 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,
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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 PM25 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://gOdup05u.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 next-
generation 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, PMi0, 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 far-
space, 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 3D-
AQS 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 Quakers, 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 PM25that 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 5monitoring 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 ground-
level 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 ground-
based 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 under-
served 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 ST-
segment that represents the period of ventricular muscle contraction before repolarization,
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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.
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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
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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.
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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
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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 best-
understood 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.
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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 under-
sampled 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
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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 ground-
based 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 PM2s. 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.
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THE SECRETARY OF HEALTH, AND HUMAN SERVICES
WA5HINGTQII. B.C. 30201
1 Dear Participants:
Welcome to the "Integrated Earth Observations: Application to Air Quality and Human
i Health," workshop co-sponsored by the Environmental Protection Agency and the National
Institute of Environmental Health Sciences.
Through your participation in this workshop, you join a growing .list of national and
international experts who are focusing their research efforts on linking remote sensing and
ground-based earth observations techniques designed to improve the management of our
environment and improve human health. Geographical and cliniatological data obtained through
the Integrated Earth Observation System (TJEOS) will support more complex and detailed
• inquiries into environment-health interactions and lead to the development of more
comprehensive predictive exposure-health models. These models will support the development
of disease management plans specific to an individual's exposure environment and provide
indicators for disease prevention in large populations. The use of geospatial data in IEOS will
help us improve the urban environment, preserve the rural environment, plan for city growth, and
create healthy cities. The vision for IEOS is one integrated, interoperable system that spans the
globe and protects the health of the planet and of humankind.
The task before you in this workshop may seem daunting, however, you may be assured that
your colleagues who are serving within the U.S. Global Earth Observations committee have
proposed a comprehensive IEOS initiative that recognizes the importance of data users in the
development of an architecture that will translate data to information. You are being challenged
1 to continue the dialogue that will result in a better understanding of the types of remote sensing
and ground-based data that are being acquired, or that are needed, and to ask the important
questions about how these data would apply to human health research, clinical management,
policy decisions, and environmental and health planning. Your conclusions will help shape that
architecture and provide significant insights into the challenges facing the research community.
Again, welcome to the workshop and thank you for your time, energy and talent.
Sincerely,
Michal 0. Leavitt
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Integrated Earth Observations: Application to
Air Quality and Human Health
National Institute of Environmental Health Sciences
Research Triangle Park, NC
8:00 - 8:30 AM
8:30 -8:40 AM
8:40 - 9:00 AM
MONDAY, AUGUST 1, 2005
Registration
Welcome and Introductions
Dr. Sally Tinkle, Meeting Organizer, NIEHS
Dr. Anne Sassaman, Director, Division of Extramural Research and
Training, NIEHS
Welcome and Overview of the Global Earth Observation System of Systems
(GEOSS)
Dr. Gary Foley, Director, National Exposure Research Laboratory, EPA
Plenary Sessions
9:00-9:20 AM
9:20-9:40 AM
9:40-10:10AM
10:10-10:30 AM
DATA PRODUCTION (what can be measured)
Chair: Ms. Valerie Garcia, EPA
Setting the Stage: Strengths and Limitations of Spatial Data
Dr. S T Rao, NOAA
New Discoveries and Future Directions of Satellite Research
Dr. Richard Kleidman, NASA
Availability and Uses of Operational Satellite Data
Dr. Shobha Kondragunta, NOAA
Land-Based Networks
Dr. Richard Scheffe, EPA
10:30- 10:45 AM
Break
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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
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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
9:00-9:20 AM
Overview of the GEOSS Work Plan
Dr. Guy Duchossois, GEOSS Work Plan Manager
Confidentiality Issues and Policies Related to the Use of Geospatial Data
Ms. Meredith Golden, Columbia University
Working Group Sessions
9:20-9:50 AM
9:50-10:20 AM
WORKING GROUP REPORTS
Co-Chairs: Dr. Sally Tinkle, NIEHS
Ms. Valerie Garcia, EPA
Respiratory Working Group
Dr. Peggy Reynolds, California Dept. of Health Services
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
11:45-12:00 AM
12:00 - 1:00 PM
SUMMARY OF FINDINGS AND NEXT STEPS
Dr. Sally Tinkle, NIEHS
CLOSING REMARKS
Dr. Gary Foley, EPA
Lunch and/or departure for airport
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Global Earth Observations: Application to Air Quality and Human Health
August 1-2, 2005
Participant List
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.iohnd@epa.gov
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
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
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
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Richard H. Finnell
Institute of Biosciences and Technology
Texas A & M University
2121 W.Holcombe Blvd.
Houston, TX 77030
rfmnell@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
Kim her ly Gray
Susceptibility and Population Health Branch
Division of Extramural Research and
Training
National Institute of Environmental Health
Sciences
P.O. Box 12233 MDEC-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
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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@B i oMedware. com
734-913-1098 ext 6
Richard Kleidnian
SSAI
code 613.2
NASA/Goddard Space Flight Center
GreenbeltMD 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
301-763-8136X151
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.j ohng@epa.gov
702-798-2525
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Gregory A. Mandt
Director, Office of Science and Technology
NO A A/National Weather Service
1325 East-West Highway,
SSMC2-Rm. 15146, W/OST
Silver Spring, MD 20910
Greg .Mandt@noaa. gov
301-713-1746
David M. Ozonoff
Department of Environmental Health
Boston University
Talbot Building, 2East
715 Albany Street
Boston, MA 02118
dozonoff@bu.edu
617-638-4620
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
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
Marie Lynn Miranda
Nicholas School of the Environment and
Earth Sciences
Duke University
A134LSRC
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
850
Rochester, NY 14642
Gunter_Oberdorster@urmc.rochester.edu
585-275-3804
Judith R. Quakers
Environmental Public Health Tracking
Branch
Centers for Disease Control and Prevention
1600 Clifton Road, NE, El9
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
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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
Richard Scheffe
USEPA
Office of Air Quality Planning and
Standards
Mail Drop :C3 04-01
Research Triangle Park, NC 27711
scheffe.rich@epamail.epa.gov
919-541-4650
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
Charles Schmidt
Science Writer
111 Commercial Street
5th Floor
Portland, ME 04101
charlie@schmidtwriting.com
207-347-5237
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
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
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William A. Sprigg
Department of Atmospheric Sciences
University of Arizona
1118E. 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 MDEC-21
111 T.W. Alexander Drive
Research Triangle Park, NC 27709
sriniva2@niehs.nih.gov
919-541-2506
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
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
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
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Judith T. Zelikoff
Department of Environmental Medicine
NYU Medical Center
SLF2235A
57 Old Forge Road
Tuxedo, NY 10987
judyz@env.med.nyu.edu
845-885-5230
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&EPA
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February 2007
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