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.
HAQAST 2018 Tiger Teams
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, please visit the team’s website.
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.
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).
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.
HAQAST 2017 Tiger Teams
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.
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.