What is a Tiger Team?
A Tiger Team is a short-term, high-impact collaborative effort between HAQAST members and public stakeholders to identify and solve an immediate problem using NASA data and products. Each Tiger Team draws on the expertise of multiple HAQAST PIs to find the best, multifaceted solutions to pressing health and air quality issues.
- Satellite data for environmental justice (SD4EJ)
Team Lead: HAQAST investigators Susan Anenberg and Qian Xiao
Partners: Centers for Disease Control and Prevention (CDC), Texas Department of State Health Services, Environmental Defense Fund (EDF), White House Council on Environmental Quality, University of Maryland, Baltimore County, Consortium for the Valuation of Applications Benefits Linked with Earth Science (VALUABLES), National Oceanic and Atmospheric Administration (NOAA), Center for Applied Environmental Law and Policy (CAELP), DC Department of Energy & Environment, United States Environmental Protection Agency (EPA) Office of Environmental Justice
HAQAST Members and Collaborators: Gaige Kerr, Cici Bauer, Bryan Duncan, Mariana Figueiro, Arlene Fiore, Emily Fischer, Emily Gargulinski, Dan Goldberg, Pawan Gupta, Tracey Holloway, Yang Liu, Jeff Pierce, Ted Russell, Amber Soja, Cascade Tuholske, Susana Adamo, Christopher Uejio, Daniel Tong, Jun Wang, and Randall Martin also contribute to this team.
This project will enhance the ability for stakeholders to map environmental justice (EJ) for various environmental exposures and produce new understanding of which communities may experience benefits from governmental initiatives. Specifically, this project will identify communities disproportionately affected by environmental health risks and estimate the benefits of governmental investments in environmental improvements for disproportionately burdened communities. We will also build capacity among the EJ community for using and interpreting satellite datasets
The project will build relationships among scientists and stakeholders and generate future partnerships to address EJ using satellite and other Earth observing data. We plan to develop a central warehouse for long-term satellite data on multiple environmental exposures. We will also develop algorithms for data mapping and easy linkage with health outcomes and ethnoracial and socioeconomic characteristics at various geographic scales. As environmental injustice extends across multiple environmental risk factors and a range of applied research approaches (e.g. exposure assessment, health risk and impact assessment, geospatial mapping, epidemiology), this project brings together a broad set of HAQAST teams with complementary expertise using many satellite products. Learn more and get involved here!
- 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 initiates 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 will deliver: 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 at https://airquality.gsfc.nasa.gov) that will serve 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 will provide a better communication of the uncertainty bounds associated with satellite-based urban NOx emission estimates.
This project will use 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), we will quantify uncertainties using sensitivity analyses (e.g., top-down NOx emissions have a XX% magnitude uncertainty, but only YY% trend uncertainty). This will allow stakeholders to better interpret satellite-based NOx emissions estimates. The project will engage stakeholders to help researchers prioritize aspects of estimating NOx emissions that are the most impactful for decision-making.
- 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 US 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 initiates 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.
- 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. This project will leverage expertise among HAQAST investigators in remote sensing technology, novel technology in low-cost monitoring, and high-resolution fire-detection and Aerosol Optical Depth products from MODIS, VIIRS, and GOES-16 to quantify smoke from sugarcane residue burning in the southeastern U.S. with two study sites: western Palm Beach County, Florida and the Flint Hills region of Kansas.
To estimate the burden of disease due to smoke exposure on downwind communities, this project will conduct a health impact assessment (HIA) based on existing concentration response functions for PM2.5. This project will serve as a best practice for conducting exposure assessment using a fusion approach for other agricultural burning practices across the United States.
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:
- Transfer knowledge and global-scale datasets tracking indicators for ozone and NO2 concentration, PM2.5 and ozone disease burden in cities, and wildfire occurrence
- 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 PM2.5 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.
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, PM2.5 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 PM2.5 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 PM2.5and 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 PM2.5, 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.
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 PM2.5 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, PM2.5, and other pollutants.
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 PM2.5, 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.
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 PM2.5 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 PM2.5 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.
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 NOx 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.