Tiger Teams

HAQAST Members and Collaborators: Carl Malings (Morgan State University), Arlene Fiore (Massachusetts Institute of Technology), Tracey Holloway (University of Wisconsin-Madison), Jenny Bratburd (University of Wisconsin-Madison), Amber Soja (NASA LaRC), EmilyGargulinski (National Institute of Aerospace), Junhyeon Seo (Morgan State University/GSFC), Daniel Anderson (University of Maryland Baltimore County), Doyeon Ahn (Morgan State University)

While many capacity-strengthening resources exist, there is no centralized database of resources to help users grow their use of Earth observations. This Tiger Team will work with health and air quality stakeholders across HAQAST activities and networks to assess how well existing training resources meet their needs. Building on the HAQAST Flowchart of Resources and Data Products, which guides users to specific products meeting their needs, this project will design the HAQAST Resource Atlas, a searchable database of resources to guide users, from novice to advanced and technical to managerial, toward relevant data products and training resources.

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Partners: Angela Dickens and Zac Adelman (Lake Michigan Air Directors Consortium (LADCO)), Alexandra Karambelas (Northeast States for Coordinated Air Use Management

(NESCAUM)), Eladio Knipping, Electric Power Research Institute (EPRI), and Kelly Thompson, Illinois Environmental Regulatory Group (IERG)

HAQAST Members and Collaborators: Talat Odman (Georgia Tech), Arlene Fiore (MIT), and Jingqiu Mao (U. Alaska)  Daniel Anderson (University of Maryland Baltimore County), Aaron Naeger (NASA MSFC), and R. Bradley Pierce (University of Wisconsin – Madison)

Accurately quantifying nitrogen oxide (NOx) and volatile organic compound (VOC) emissions and their impacts on ozone formation is crucial for air quality management. This project aims to establish best practices for using TEMPO formaldehyde (HCHO) observations in air quality management, with focus on source attribution and ozone production regime assessment.

Using three case studies (Chicago, New York City, and St. Louis) to serve as a basis for transferable methodology, this team will:

(1) Characterize the relationship between anthropogenic VOC sources and HCHO observations, (2) Map near-source ozone production sensitivities (NOx- vs. VOC-limited regimes) using TEMPO HCHO and NO2

(3) Develop practical tools and guidance documents that enable air quality managers to incorporate TEMPO HCHO observations into existing workflows.

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Partners: Air quality managers across all US state, local, tribal and multi-jurisdictional organizations (including Sara Strachan, Idaho DEQ and Nico Schulte, South Coast Air Quality Management District); the AIR4US governance board (John Haynes (NASA), Emma Knowland (NASA), Laura Judd (NASA), Shobha Kondragunta (NOAA), Gregory Frost (NOAA), Monika Kopacz (NOAA), Alison Eyth (EPA), Corey Mocka (EPA), Barron Henderson (EPA)

HAQAST Investigators and Collaborators: Pawan Gupta (NASA GSFC), Jeff Pierce (Colorado State University, CSU), Dan Anderson (University of Maryland, Baltimore County, UMBC), Travis Toth (NASA LRC), Tracey Holloway (University of Wisconsin-Madison), Xi Chen (University of Iowa), Randall Martin (Washington University St. Louis), Aaron Naeger (NASA MSFC), Amber Soja (NASA LARC), Jennifer Kaiser (Georgia Tech), Jingqiu Mao (University of Alaska Fairbanks), Jeanne le Roux (NASA MSFC), Nathan Pavlovic (Spheros Environmental), Junhyeon Seo (Morgan State University), Salman Khan (Earth Resources Technology, Inc.), Jenny Bratburd (University of Wisconsin-Madison.), Emily Gargulinski (National Institute of Aerospace), Chi Li (Washington University St. Louis), Yu Yan (Washington University St. Louis), Doyeon Ahn (MSU), Haihui Zhu (CSU), Kevin Fuell (University of Alabama Huntsville)

The Air-quality Information Resource for the United States (AIR4US) is a new multi-agency (NASA, NOAA, EPA) platform for integrating air quality information from in-situ monitors, remote sensing, and model outputs. Designed to serve air quality managers at the state and local levels, AIR4US will integrate existing datasets and introduce new capabilities, e.g., aligning datasets to common grids to facilitate comparisons, fusing information sources to produce exposure estimates and proxies, and exploration of “what-if” scenarios through multi-model integration. The AIR4US Tiger Team will synthesize knowledge and experience of HAQAST, broaden stakeholder engagement for feedback and testing, and prioritize functionalities and datasets for AIR4US, building on 15 years’ of HAQAST experience connecting Earth observations with the needs of the US air quality management community.

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Partners: Eben Cross (QuantAQ), Andrew White (PurpleAir), Shobha Kondragunta (NOAA), Barron Henderson (EPA), Andrea Clements (EPA), Lydia Johnson (Alaska Department of Environmental Conservation), Brandon Feenstra (South Coast AQMD / AQ-SPEC), Wilton Mui (South Coast AQMD / AQ-SPEC), Byeong Kim (Georgia Environmental Protection Division), Joel Dreessen (Maryland Department of the Environment), Sean Wihera (Clarity Movement), Levi Stanton (Clarity Movement)

HAQAST Participants: Jeff Pierce (Colorado State University), Jun Wang (University of Iowa), Carl Malings (Morgan State University), Pawan Gupta (GSFC), Arlene Fiore (MIT), Amber Soja (NASA LaRC), Daniel King (Spheros Environmental),  Leiqiu Hu (University of Alabama Huntsville), Daniel Bellamy (University of Alaska Fairbanks), Tianlang Zhao (University of Alaska Fairbanks)

Air quality managers increasingly rely on both low-cost sensor networks and satellite-derived products but lack clear, consistent guidance on their appropriate use, limitations, and integration. This HAQAST Tiger Team will evaluate and demonstrate best practices for integrating hourly and daily satellite-derived surface PM2.5 products with both regulatory networks and low-cost sensor networks, with a focus on exceptional events. The project focus is on wildfire smoke and dust events, which pose significant challenges for both sensor interpretation and satellite retrievals.

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Partners: Dan Welsh (Colorado Department of Public Health and Environment), Ryan Lueck (Minnesota Pollution Control Agency), Joel Dreessen (Maryland Department of the Environment), Sara Strachan (Idaho Department of Environmental Quality (DEQ)), Byeong Kim (Georgia Department of Natural Resources), Ron Pope (Maricopa County Air Quality Department), Mark Sghiatti (Utah DEQ), Amanda Fritz (Connecticut Department of Energy & Environmental Protection), Emily Yang (California Air Resources Board (CARB)), Matthew Densberger (CARB), Barkley Sive (National Park Service (NPS)), Lisa Devore (NPS), Mary Uhl (Western States Air Resources Council), Eladio Knipping (Electric Power Research Institute)

HAQAST Members and Collaborators: Andrew White (University of Alabama in Huntsville), Kevin Fuell (University of Alabama in Huntsville), Arlene Fiore (Massachusetts Institute of Technology), Jingqiu Mao (University of Alaska Fairbanks), Alqamah Sayeed (University of Alabama in Huntsville), Dan Anderson (University of Maryland Baltimore County, NASA GSFC), Carl Malings (Morgan State University, GFSC), Amber Soja (NASA LaRC), Emily Gargulinski (National Institute of Aerospace), Tracey Holloway (University of Wisconsin-Madison), Junsung Park (Smithsonian Astrophysical Observatory), Nathan Pavlovic (Spheros Environmental), Shantanu Jathar, Sheryl Magzamen, Jeffrey Pierce (Colorado State University), and Christopher Uejio (Florida State University)

State, local, and tribal air agencies have long been interested in the use of a satellite ozone (O3) profile product for enhancing air quality management. The new TEMPO O3 profile data has the potential to be a game-changing product by significantly improving our capabilities to track and monitor tropospheric O3. The goal of this Tiger Team is to provide analyses, value-added products, use cases, and tailored user guides for the TEMPO O3 profile product to facilitate effective, accurate, and routine use of the product at air agencies across the U.S. This team will conduct a detailed evaluation and analysis of the TEMPO O3 profile product, with the overarching goal of ensuring more rapid and effective use of the product at air agencies.

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Partners: Laura Myers (Kaiser Permanente); Anny Huang and Eric Rowell (California Air Resources Board); James Bolyan and Byeong Kim (Georgia Department of Natural Resources); Ambarish Vaidyanathan (CDC); Pete Lahm (US Forest Service); Amanda Fritz (Connecticut Department of Energy and Environmental Protection); James Beidler (EPA)

HAQAST Members and Collaborators: Yongtao Hu and Jennifer Kaiser (Georgia Tech); Amber Soja and Emily Gargulinski (NASA Langley), Youhua Tang, Siqi Ma and Daniel Tong (George Mason University), Yang Liu and Lei Li (Emory University), and Monica Harkey (University of Wisconsin); Jeffrey Pierce and Haihui Zhu (Colorado State); Aaron Naeger (NASA Marshall Space Flight Center), and Andrew White and Jonathan Case (NASA Short-term Prediction Research and Transition Center); Arlene Fiore and Adam Schlosser (MIT); Christopher Uejio (Florida State) and Xiuling Zhao; Carl Malings (Morgan State) and Nathan Pavlovic (Sonoma Tech); Travis Toth (NASA Langley Research Center); Xi Chen, Meng Zhou, and Huanxin Zhang (University of Iowa)

Unprecedented levels of smoke exposure are seen in the United States in recent years due to wildfires and prescribed fires. This project aims to build a nationwide dataset of exposures to these different fire types to better understand their distinct impacts on air quality and health. Wildfires are a critical concern, especially those in the wildland urban interface which threaten structures and vehicles. Prescribed burns, used for ecosystem management and fuel reduction to prevent wildfires. Both types of fire produce smoke that can be transported hundreds of miles, impacting communities in downwind regions. Because the fuel types and burning conditions are different, the smoke composition may have differences in toxicity. Using satellite dataset (including MODIS, VIIRS, GOES, TEMPO), other pertinent fire datasets and chemical modeling, this project will tackle three main objectives: 1) differentiate fire type, and 2) evaluate pollutant concentrations from wildland fires using satellite data, and 3) calculate exposures to wildfire and prescribed fire smoke. This effort will allow for differentiation of fire types and emissions estimations, crucial for both state and federal agencies and health organizations seeking to understand the long-term health trade-offs of fire management strategies and far-reaching effects of smoke across state and international borders.

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Partners: Byeong Kim (Georgia Environmental Protection Division), Mary Uhl (WESTAR), Leticia Nogueira (American Cancer Society), James Beidler (Environmental Protection Agency, EPA) [Air Quality (AQ), National Emissions Inventory (NEI); Wildland Fire Emissions Inventory (WLFEI)], Marc Carreras Sospedra (South Coast Air Quality Management District); Air quality modelers and managers across all US state, local, tribal and multi-jurisdictional organizations

HAQAST Members and Collaborators: Emily Gargulinski (National Institute of Aerospace, NIA), Nathan Pavlovic (Spheros Environmental), Carl Malings (Morgan State University, MSU), Jeff Pierce (Colorado State University), Travis Toth (NASA LaRC), Arlene Fiore (MIT), Tracey Holloway (University of Wisconsin-Madison), Jenny Bratburd (University of Wisconsin-Madison.), Chris Uejio (Florida State University), Jun Wang (University of Iowa), Meng Zhou (University of Iowa), Aaron Naeger (NASA MSFC); Xi Chen (University of Iowa), Randall Martin (Washington University)

Numerous organizations use satellite data to accomplish daily-to-annual tasks including emissions estimates, inventories, retrospective assessments, scientific analyses, and statistical analysis of change over time; however, satellite data have changed over time, e.g., the number of satellites orbiting, instrument resolution, and the time satellites are overhead, thus confounding statistics. The goal of this Tiger Team is to work with partner and stakeholder communities to define and enable the seamless transition of data products that evolved with enhanced satellite capabilities.

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Partners: Scott Epstein and team (South Coast Air Quality Management District), (Jeanne Ruff and team) (New Mexico Department of Health), Ron Pope, Kristi Beck, and team (Maricopa County Air Quality Department), and Daniel Tong (George Mason University; World Meteorological Organization)

HAQAST Members and Collaborators: Xi Chen (University of Iowa), Jeffrey Pierce (Colorado State University), Tracey Holloway (University of Wisconsin-Madison), Carl Malings (Morgan State University), Jingqiu Mao (University of Alaska Fairbanks), Daniel Bellamy (University of Alaska Fairbanks), Pawan Gupta (NASA GSFC), Randall Martin (Washington University in St. Louis), Adam Schlosser (Massachusetts Institute of Technology), Daniel King (Spheros Environmental)

Millions of people in rural, arid, undermonitored regions of the southwestern U.S. are impacted by particulate matter pollution from dust events, with coarse particulate matter (PM10) levels being a recent increasing area of concern. This Tiger Team will use NASA datasets to characterize the transport of dust plumes and its impact on AQ and health applications, addressing stakeholder needs including (1) regulatory exceptional dust event demonstrations, (2) dust occurrence below and above the boundary layer, relevant for modeling, (3) analysis of when/where dust is present in the atmospheric column (including how close to the surface), (4) understanding how dust plumes rise, and transport influence on surface PM2.5 and PM10, (5) understanding of dust transport patterns (including source regions), and (6) historical record and climatology of dust to enable further trend studies relevant to dust (e.g., health, meteorology, climate) and increase understanding of how climate change and meteorological conditions influence the frequency, severity, and spatial extent of dust plumes.

Analysis to support air quality and health TEMPO applications for surface ozone

Team Lead: HAQAST Investigator Arlene Fiore

Partners: Angela Dickens (LADCO), Joel Dreessen (MDE), Paul English (Tracking California, Public Health Institute), Michael Geigert (CT DEEP), Barron Henderson (US EPA), Rachel Licker (Union of Concerned Scientists), Vijay Limaye (NRDC), Ruby Tian (NYS DEC), Luke Valin (US EPA), Allison Patton and Pallavi Pant (HEI), Graham MacDonald (Urban Institute), Byeong Kim (GA EPD), Amy Christiansen (University of Missouri – Kansas City), Hazem Mahmoud (NASA LaRC), Jerrold Acdan (UW Madison), Lynsey Parker (Ramboll), Kristen Okorn (NASA ARC)

HAQAST Members and Collaborators: Daniel Goldberg (GW),Tracey Holloway (UW Madison), Jen Kaiser (Georgia Tech), Jingqiu Mao (U AK Fairbanks), Talat Odman (Georgia Tech), Randall Martin (WUSTL), Ted Russell (Georgia Tech), Daniel Tong (GMU), Chris Uejio (FSU), Jun Wang (U Iowa), Madankui Tao (Columbia University), Sara Runkel (GW), Chi Li (WUSTL), Deepangsu Chatterjee (WUSTL), Yanshun Li (WUSTL), Yongtao Hu (Georgia Tech), Tianlang Zhao (U AK Fairbanks), Zhendong Lu (U Iowa)

With the aim of facilitating the transition of prior ozone-focused satellite applications to TEMPO, this team works to evaluate expected new TEMPO retrievals of NO2, HCHO, as well as lower tropospheric ozone over the U.S.A., alongside current satellite products (OMI and TROPOMI NO2 and HCHO) with ground-based observing networks: Pandonia Global Network (PGN), Tropospheric Ozone Lidar Network (TOLNet), ozone sondes, NCore, and state, local and tribal networks. By contrasting high-ozone versus other days, we aim to identify the impacts from ozone precursors on the days that matter most for attaining standards and protecting public health. A joint examination of ozone and heat events can inform understanding of health impacts from co-exposure to multiple stressors and shed light on influences from climate change on air pollution and health. You can find quick guides and tutorials from the team here.

 

Applications of GOES-R aerosol data in operational air quality management and public health decision support systems

Team Lead: HAQAST Investigator Yang Liu

Partners: Phil Dickerson and Barron Henderson (USEPA), Kazuhiko Ito (New York City Department of Health and Mental Hygiene)

HAQAST Members and Collaborators: Pawan Gupta (NASA), Jingqiu Mao (University of Alaska), Randall Martin (Washington University)

Satellite-driven fine particulate matter (PM2.5) concentration estimates with comprehensive spatial and temporal coverage are valuable to air quality (AQ) management and public health agencies in order to identify air pollution hot spots, develop effective emissions control policies, estimate the PM2.5 disease burden, and promote awareness and solutions to community-level air pollution concerns. This project aims to integrate GOES-R aerosol optical depth (AOD) data into operational air quality monitoring data systems such as EPA’s AirNow, and operational public health decision support systems such as NYC’s asthma syndromic surveillance system. Our expected deliverables include (1) an automated near-real-time daily PM2.5 model system designed for NYC and associated documentation, and (2) a machine learning algorithm to generate hourly PM2.5 concentrations based on GOES-R AOD for AirNow and associated documentation. 

 

Mitigating Uncertainties in Lateral Boundary Conditions used for Regional Air Quality Assessment Modeling

Team Lead: HAQAST Co-Investigator Bradley Pierce

Partners: Barron Henderson (US–EPA), Emma Knowland (NASA–GMAO), Zac Adelman (Executive Director, LADCO), Mary Uhl (Executive Director, WESTAR), Paul Miller (Executive Director, NESCAUM), Marc Cone (Executive Director, MARAMA), Jeremy Avise (Chief, Modeling & Meteorology Branch, CARB), Donna Huff (Deputy Director, Air Quality Division, TCEQ), Margaret LaFarr (Assistant Director, Division of Air Resources, NYSDEC

HAQAST Members and Collaborators: HAQAST Investigator Daniel Tong (GMU) and HAQAST Investigator Arlene Fiore (MIT)

Many stakeholders use regional-scale chemistry-transport models in support of state implementation plans (SIPs) to establish emission control strategies to comply with National Ambient Air Quality Standards and the Regional Haze Rule. However, it can be challenging to find, access, and process high quality data for lateral boundary conditions. The proposed Tiger Team project will address the need for more realistic lateral boundary conditions by enabling modelers for regional and state air quality planning agencies to access state of the art global model analyses, forecasts, and tools developed by the air quality research community. This Tiger Team is conducting a collaborative assessment of the impact of chemical boundary conditions using contemporary regional air quality models and global chemical analysis and Chemical Transport Model (CTM) simulations. This has the potential to produce an improved modeling platform for supporting the regulatory decisions of state and local air planning agencies.

 

 

Satellite Observations Supporting Assessment of Unconventional Oil and Gas Emissions and Exposures

Team Lead: HAQAST Investigator Ted Russell

Partners: Donna Voorhees (HEI), Tom Moore (Colorado Dept. of Public Health), Emily Hall (Texas DSHS), Maria Harris (EDF), WRAP/WESTAR, Eric Choi & Jason McKeever (GHGSat)

HAQAST Members  and Collaborators: Jeff Pierce (CSU), Qian Xiao (UT Health), Cici Bauer (UT Health), Susan Anenberg (GWU), Dan Goldberg (GWU), Tracey Holloway (UW Madison), Ana Prados (UMBC), Jennifer Kaiser (GIT), Pawan Gupta (NASA)

Unconventional oil and gas development (UOGD) is a source of criteria pollutants, air toxics, and greenhouse gases. This HAQAST Tiger Team can provide spatial and temporal coverage of air pollutants, including methane, with the potential for identifying hot spots that have been missed by ground measurements. We aim to meet stakeholder needs by 1) mapping HCHO, CH4, NO2 and ozone (O3) levels for use in identifying large fugitive emission sources of CH4 and other air toxics of higher than expected strength, 2) assessing the spatial footprint of UOGD-X operation impacts on air quality; 3) Understanding the potential usefulness of satellite data for air quality monitoring in UOGD-X areas by relating satellite observations to ground-level concentrations and 4) assessing the products of atmospheric transformations (e.g., formation of air toxics like HCHO, criteria pollutants such as O3, as well as secondary aerosols).

 

Enabling Stakeholder Access and Utilization of Data Products for Health and AQ Applications (First Steps)

Team Lead: HAQAST co-investigator Kevin Cromar

Partners: United Nations Environment Programme (UNEP), World Bank, World Health Organization (WHO), United Nations United Children’s Emergency Fund (UNICEF), CDC, United States Department of Agriculture (USDA), NASA Socioeconomic Data and Applications Center (SEDAC), California Department of Public Health, Georgia Environmental Protection Division, University of British Columbia, Health Effects Institute (HEI), American Thoracic Society

HAQAST Members and Collaborators: Bryan Duncan, Ana Prados, C. Keller, Pawan Gupta, Qian Xiao, Christopher Ueijo, Susan Anenberg, Dan Goldberg, Randall Martin, Daniel Tong, Tracey Holloway also contribute to this team.

This project initiated a collaboration between HAQAST members and stakeholders to identify ways to “scale up” the potential impact of satellite data with data products that are mapped onto uniform latitude/longitude grid or with other geophysical variables to all interested stakeholders. Meeting this need will dramatically increase the use of NASA air quality data products, particularly for most potential stakeholders that do not have the financial resources or technical expertise to derive their own products.

This project delivered: 1) thorough documentation of products (e.g., how it was derived, strengths and weaknesses for various applications), 2) case studies to highlight data for health and AQ applications, and 3) a “homepage” prototype (initially here) that serves as a one-stop shop for all these resources.

Communicating the uncertainties of satellite-based NOx emissions for urban planning

Team Lead: HAQAST co-investigator Dan Goldberg

Partners: United States Environmental Protection Agency (EPA), Health Effects Institute (HEI), Ramboll, NASA Applied Remote Sensing Training Program (ARSET), Ramboll, Pacific Northwest National Laboratory (PNNL), Institute for Health Metrics and Evaluation (IHME), Lake Michigan Air Directors Consortium, International Council on Clean Transportation

HAQAST Members and Collaborators: Susan Anenberg, Arlene Fiore, Tracey Holloway, Ted Russell, and Daniel Tong also contribute to this team

Anthropogenic NOx emissions estimates from global cities remain a relatively uncertain quantity despite a recent large effort by the scientific community to reconcile these differences. New satellite instruments (e.g., TROPOMI, TEMPO) and algorithms (NASA OMI NO2 SP v4, TROPOMI NO2 v2) can provide insight on this topic with an improved accuracy. This project provided a better communication of the uncertainty bounds associated with satellite-based urban NOx emission estimates.

This project used two methods: (1) comparing satellite data to high resolution (<12 km2) model simulations and (2) comparing bottom-up emission inventory estimates to satellite-derived estimates from urban areas and power plants. Isolating satellite-model comparisons by land use type – airport, seaport, railyard, agriculture, marine, etc. – may identify a sector of emissions that may be disproportionately erroneous. Rather than restating the typical qualitative responses that accompany most answers to satellite-based uncertainty questions (e.g., magnitude of satellite-based emissions are more uncertain than the trends), this team quantified uncertainties using sensitivity analyses (e.g., top-down NOx emissions have a XX% magnitude uncertainty, but only YY% trend uncertainty). This analysis will allow stakeholders to better interpret satellite-based NOx emissions estimates. The project engaged stakeholders to help researchers prioritize aspects of estimating NOx emissions that are the most impactful for decision-making. You can find a tutorial on how to download and use TROPOMI data here, and TROPOMI NO2 filtered for quality assurance and re-gridded here and a presentation on all the team’s activities here.

Enabling USEPA to ingest high-frequency satellite air quality data into the AirNow system

Team Lead: HAQAST investigator Pawan Gupta

Partners: Phil Dickerson and Barron Henderson with the US Environmental Protection Agency (EPA), and Shobha Kondragunta with the National Oceanic and Atmospheric Administration (NOAA)

HAQAST Members and Collaborators: Jingqiu Mao, Yang Liu, Kel Markert, Robert Levy, Randall Martin, Amber J. Soja, Martin Stuefer, Jenny Bratburd, Emily Gargulinksi, Yanshun Li, and Daniel Tong also contribute to this team.

The EPA, in partnership with other federal and state agencies, operates the AirNow program (airnow.gov). The AirNow system is EPA’s one-stop resource for accessing air quality (AQ) information. The major gap in the AirNow system is limited spatial coverage from ground monitors, limited information on smoke and dust transport, and regional AQ view. NASA, NOAA, and other U.S. agencies have been building on satellite capabilities for AQ monitoring for almost two decades using low earth-orbiting satellites and, more recently, with geostationary satellites. This project initiated a new collaboration between HAQAST members, NOAA, and USEPA to develop a value added hourly and daily PM2.5 dataset covering CONUS region and integrate it into the AirNow system.

The new data layers at high temporal and spatial resolutions in the USEPA’s AirNow system will address significant monitoring gaps in many areas around the country, provide special health advisory during smoke and dust events and generate a framework for ingesting data from future NASA/NOAA missions (i.e., TEMPO, MAIA, ATMOS, GEO-XO) into a regulatory agency’s monitoring system. Thus, the project is an excellent opportunity for NASA and NOAA to incorporate Earth observations into environmental monitoring by federal agencies within the United States. You can read more about this team’s efforts here.

Fused earth observations to quantify health impacts from agricultural fires

Team Lead: HAQAST investigators Sheryl Magzamen and Amber Soja

Partners: Sierra Club Kansas, ProPublica/Palm Beach Post, CDC, Center for Health, Work and Environment and Mountain and Plains Educational Research Center, High Plains Intermountain Center for Agricultural Health and Safety

HAQAST Members and Collaborators: Kellin Slater, Jeff Pierce, Emily Fischer, Bonne Ford, Jun Wang, Christopher Uejio, Emily Gargulinski, Susana Adamo, Randall Martin, Susan Anenberg, Pawan Gupta, Arlene Fiore, Jingqiu Mao also contribute to this team.

Agricultural burning is an extensive and recurring annual event in several regions of the United States. Emissions from agricultural fires can have a demonstrable impact on atmospheric composition and air quality on local to regional scales. Across the U.S., smoke from agricultural burns disproportionately impacts Black communities compared to non-Hispanic White communities. The Fused Earth Observations to Quantify Health Impacts from Agricultural Fires team leveraged expertise among HAQAST investigators in remote sensing technology, novel technology in low-cost monitoring, and high-resolution satellite data to quantify fire and smoke from small fires burning in the southeastern U.S. with two study sites: western Palm Beach County, Florida and the Flint Hills region of Kansas. The project concluded earlier this year.

To estimate the burden of disease due to smoke exposure on downwind communities, this project conducted a health impact assessment (HIA) based on existing concentration response functions for PM2.5. This project sought to serve as a best practice for conducting exposure assessment using a fusion approach for other agricultural burning practices across the United States. You can learn more about this project from Amber Soja’s presentation at HAQAST Wisconsin.

1. Using Satellite Remote Sensing to Derive Global Climate and Air Pollution Indicators

Team Lead: HAQAST investigator Susan Anenberg

Partners: Lancet Commission on Pollution and Health, University College London/Lancet Countdown, and the Health Effects Institute/State of Global Air

HAQAST Members and Collaborators: Jeremy Hess, Bryan Duncan, Arlene Fiore, Daven Henze, Patrick Kinney, Lok Lamsal, Yang Liu, Daniel Tong, and Jason West also contribute to this team

This project initiates a new collaboration between HAQAST members and LCPH, Lancet Countdown, and SoGA projects with the aim of developing satellite-derived air pollution and climate indicators at the global scale. Specifically, this team will use satellite remote sensing to:

1. Transfer knowledge and global-scale datasets tracking indicators for ozone and NO₂ concentration, PM_2.5 and ozone disease burden in cities, and wildfire occurrence
2. Scope the potential for using satellite remote sensing to track global airborne dust storms and pollen season start date and duration. The project draws from a variety of satellite remote sensing products. HAQAST team members will work collaboratively across indicators to share information and work towards achieving consistency among years, metrics, and outputs.

This project will provide quantitative estimates of ozone and NO₂concentrations, ozone and PM_2.5 disease burdens in megacities, and wildfire occurrence globally. This team will develop a methods scoping document for using satellite remote sensing to track dust storms and pollen season start date globally. In addition, they will also help develop a comprehensive set of global pollution and climate indicators for a Global Pollution Observatory that will collect and periodically report on pollution-related data, expected to be established in the near future by the LCPH. Over the long term, results may also be used to generate estimates of the global burden of disease from wildfires, dust, and pollen, and to examine historical trends as well as future climate impacts.

For more information, you can find results from this project published this paper, “Using Satellites to Track Indicators of Global Air Pollution and Climate Change Impacts: Lessons Learned From a NASA-Supported Science-Stakeholder Collaborative.”

2. Supporting the Use of Satellite Data in Regional Haze Planning

Team Lead: HAQAST member Arlene Fiore

Partners: U.S. EPA OAQPS, MARAMA, NESCAUM, TCEQ, ME DEP, and CT DEEP

HAQAST Members and Collaborators: Bryan Duncan, Daven Henze, Patrick Kinney, Talat Odman, Ted Russell, Daniel Tong, Jason West and Mark Zondlo also contribute to this team

This team proposes to work with stakeholders to address three applications of satellite data of direct relevance to regional haze SIPs. The team will develop technical guidance documents that describe their approaches to using satellite data for regional haze applications. They anticipate that the guidance developed under this project will also be relevant to health agencies seeking to assess health burdens due to natural events (e.g., dust, wildfires) associated with severe health effects. In addition, they’ll aid air quality managers in the use of satellite data in the Regional Haze SIP process, provide tangible examples of the value of satellite data for addressing air quality and related health applications, to aid stakeholders who wish to conduct their own analyses, and lower the barrier for new health and air quality stakeholder agencies to apply satellite data.

You can find more information, including a series of technical guidance documents, aimed at regional air-quality managers, available here.

3. Satellite-Evaluated and Satellite-Informed O3 Distributions for Estimating U.S. Background O3

Team Lead: HAQAST member Jessica Neu

Partners: BAAQMD, the South Coast Air Quality Management District, the California Air Resources Board, CT DEEP,New Hampshire Air Resources Division, New York State Department of Air Quality, the Texas Commission on Environmental Quality, WESTAR & WRAP, US EPA, and OAQPS

HAQAST Members and Collaborators: Arlene Fiore, Daven Henze, Brad Pierce, Ted Russell, Jason West, and Anne Thompson also contribute to this team

This team will provide a coordinated set of boundary conditions for O₃, background O₃ (no U.S. anthropogenic emissions), and natural O₃ (no global anthropogenic emissions) for 2016 from multiple global models, many of which are informed by satellite data (e.g., assimilating satellite products). Their goal is to improve the quantification of background O₃ in SIPs, a critical component of the development of our stakeholders’ attainment plans. This team will also establish ‘best practices’ for evaluating models with satellite O₃ measurements, and for evaluating satellite-informed simulations with independent datasets such as those from surface stations and ozonesondes (lightweight, balloon-borne instruments that are paired with conventional meteorological radiosonde).

This project resulted in the delivery of a variety of O3 boundary conditions, in the most popular file formats identified by air-quality stakeholders, for use in modelling O3 transport from other countries into the U.S.

4. Air Quality and Health Burden of 2017 California Wildfires

Team Lead: HAQAST member Susan O’Neill

Partners: BAAQMD, NOAA, the USFS Fire & Aviation Management Program, EPA, Sonoma Technology Inc., the National Park Service, Princeton University, the University of Washington, and the University of California, Davis

HAQAST Members and Collaborators: Daniel Tong, Talat Odman, Minghui Diao, Jason West, Pat Kinney, Brad Pierce, Jessica Neu, and Sim Larkin also contribute to this team

On October 8-9, 2017, a series of wildfires started in the northern San Francisco Bay Area, spread quickly over nine counties and became major fires in the region. Because of the smoke and prevailing weather conditions, PM_2.5 concentrations reached the highest levels ever recorded in the region. All 13 air monitoring stations in the Bay Area captured at least one exceedance of the US EPA’s 24-hr average PM_2.5 standard. Thus, virtually all of the 7.2 million people living in the Bay Area were exposed to unhealthy air during the wildfire period.

This team will assess the effects of wildfire smoke on the air quality and human health burden resulting from October 2017 California wildfires using a combination of satellite data, air quality modeling, health risk information and hospital incidence rates. They will prepare a detailed wildfire emissions inventory, estimate the air quality impacts of wildfire emissions, use satellite and ground-based observations to evaluate model results and iteratively refine wildfire emission estimates to improve the CMAQ model predictions, and utilize short-term exposure-response relationships already established between PM_2.5and public health to assess health impacts of wildfire-induced pollutant exposure.

Wildfire smoke impacts will recur in the future in California and elsewhere, and having a system that can accurately estimate those impacts, not only in terms of PM_2.5, but in terms of short-term exposure-response relationships is critical to future planning of emergency responders to protect public health. End users such as the BAAQMD envision using this project information as a basis for an emergency response manual to help inform emergency responders regarding expected levels of ambient PM based on the nature of wildfire and the number of people who may need medical attention.

Learn more at the team’s website.

1. Demonstration of the Efficacy of Environmental Regulations in the Eastern U.S.

Team Leads: HAQAST members Bryan Duncan and Jason West

Partners: Mid-Atlantic Regional Air Quality Management Association, the Maryland Department of the Environment, the EPA, the Centers for Disease Control/National Center for Environmental Health, the Northeast States for Coordinated Air Use Management, and the Connecticut Department of Energy & Environmental Protection

HAQAST Members and Collaborators: Mark Zondlo, Ted Russell, Yang Liu, Arlene Fiore, Lok Lamsal, Daniel Tong, and Daven Henze also contribute to this team

Between 1990 and 2015, the U.S. average concentration of PM_2.5 decreased by 37%, while O₃ decreased by 22%. Many observers expect such reductions to have brought substantial benefits for public health in the U.S., but assessing the health benefit requires an understanding of where air quality has improved relative to where people live. This team will demonstrate the efficacy of air quality regulations by analyzing the time trends for levels of ozone (O₃), nitrogen dioxide (NO₂—an O₃ precursor), particulate matter (PM), and PM precursors, including NO₂, sulfur dioxide (SO₂), and ammonia (NH₃) in the northeastern U.S., to determine how they affect population health during the same period. ​

For more information, PIs Duncan and West’s team have populated their website with forecasts, impacts, and detailed information on O₃, PM_2.5, and other pollutants. 

Read a brief overview here.

2. Supporting the Use of Satellite Data in State Implementation Plans (SIPs)

Team Lead: HAQAST member Arlene Fiore

Partners: California’s South Coast Air Quality Management District, the Connecticut Department of Energy & Environmental Protection, the Mid-Atlantic Regional Air Quality Management Association, Northeast States for Coordinated Air Use Management, Georgia Environmental Protection Division, the Texas Commission on Environmental Quality, the Bay Area Air Quality Management District, and the EPA

HAQAST Members and Collaborators: Bryan Duncan, Jessica Neu, Daven Henze, Talat Odman, Ted Russell, Patrick Kinney, Daniel Tong, Mark Zondlo, Jonathan Patz, and Tracey Holloway also contribute to this team

Under the U.S. National Ambient Air Quality Standards (NAAQS), states in non-attainment of criteria pollutants, such as ozone and PM_2.5, must submit State Implementation Plans (SIPs) to demonstrate their approach to achieving NAAQS compliance. Satellite data may be included in SIPs as part of a weight-of-evidence approach to show that a particular strategy is anticipated to succeed in attainment, or to show that transported pollution is confounding attainment efforts. Yet, questions often arise as to the accuracy of satellite data, the specific meteorological conditions and spatial or temporal averaging scales over which the product is most reliable, and whether a particular satellite product can be used for a desired application.

This team will work closely with at least three air agencies that are already incorporating satellite data into the SIP process and identify at least three different applications of satellite data to be showcased in a user-friendly, technical-guidance document. Each document will include frequently asked questions (FAQs) and will be “beta-tested” by at least one other air agency. The team will disseminate these case studies widely, including via the NASA Air Quality from Space website, with the goal of enabling other current and future users of satellite data in the SIP process to learn from “early-adopter” air quality managers.​

For more information, this team has developed a suite of easy-to-follow technical guidance documents that support state and local air quality agencies that want to bring the power of NASA’s satellites to bear on the documentation of exceptional events.

Read a brief overview here.

3. High Resolution Particulate Matter Data for Improved Satellite-Based Assessments of Community Health

Team Lead: HAQAST investigator Patrick Kinney

Partners: New York City Department of Health and Mental Hygiene, the California Department of Public Health, the City of Boston Environment Department, the South Coast Air Quality Management District, and the California Air Resources Board.

HAQAST Members and Collaborators: Frank Freedman, Yang Liu, Matt Strickland, Daven Henze, Arlene Fiore, Susan Anenberg, Mohammed Al-Hamda, Akula Venkatram, Mark Zondlo, Susan O’Neill, and Daniel Tong are also members of this team

Health departments and urban planners have growing needs for high-resolution data on urban-air-pollution concentrations to quantify existing health burdens at the neighborhood scale, to identify and prioritize exposure-reduction strategies for pollution hot spots, to track progress in achieving air-quality-related health-improvement goals, and to assess health co-benefits of longer-term carbon-mitigation strategies. To date, however, few data exist to inform these high-priority urban-health objectives. Newly available 1×1 km aerosol optical depth retrievals from NASA MODIS remote sensing provide opportunities to construct higher-resolution PM_2.5 spatial fields for intra-urban public-health assessments. The retrievals also can serve as a launching pad for further downscaling using emerging low-cost sensors in conjunction with land use regression and dispersion models.

The overall objective of this Tiger Team project is to construct gridded PM_2.5 spatial fields on 1-km MAIAC satellite-based aerosol optical depth retrievals, and to explore methods by which these can be downscaled using hi-density urban networks of low-cost sensors and dispersion modeling. The goal is to provide new tools for assessing air-pollution-related health burdens and mitigation strategies in community settings. This work will be carried out across four communities: New York City, Boston, Los Angeles, and California’s Imperial Valley.​

In September, 2018, Kinney led a webinar on Assessing the Health Impact of Air Quality at the Community Scale. You can watch the webinar here:

For more information, PI Kinney and his team have developed a website to profile their research and research team. 

Read a brief overview here.

4. Improved National Emissions Inventory NOx emissions using OMI Tropospheric NO2 retrievals and Potential Impacts on Air Quality Strategy Development

Team Lead: HAQAST investigator R. Bradley Pierce and member Daniel Tong

Partners: NOAA/Air Resources laboratory, NOAA/National Weather Service, EPA/Office of Air Quality Planning and Standards, the Centers for Disease Control, Lake Michigan Air Directors Consortium, and NOAA/Earth System Research Laboratory.

HAQAST Members and Collaborators: Ted Russell, Tracey Holloway, Susan O’Neill, and Daven Henze are also members of this team.The overall goal of this HAQAST Tiger Team effort is to improve estimates of National Emissions Inventory (NEI) area and point source NOx emissions using NO2 retrievals from the NASA Ozone Monitoring Instrument (OMI) and the NASA Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO).

Recent studies suggest that NO_x emissions are overestimated in the NEI. These overestimates can affect model predictions of ozone and nitrate aerosol concentrations, leading to systematic biases in forecasts of surface ozone and nitrate aerosols. Improving constraints on anthropogenic area and non-EGU point source emissions (including wild and prescribed fires) within NEI can lead to improved forecasts thereby improving NWS air quality forecasting, EPA/CDC exposure assessments, and state SIP modeling.

For more information, visit PI Pierce and Tong’s Improved NOx Emissions Using OMI news page.

Read a brief overview here.