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Research

We research the interrelationships between air quality, climate change, public health, and environmental policy. We use multi-disciplinary methods, drawing from epidemiology, exposure science, remote sensing, atmospheric chemistry and meteorology, numerical modeling, and economics.

Current projects:

Research and Engagement for Action on Climate and Health (REACH) Center

  • PI: Susan Anenberg, Daniel Tong (George Mason University), Bob Orttung (GW), Sarah Vogel (Environmental Defense Fund)
  • Sponsor: NIEHS P20
  • Objective: Bridge big data to climate solutions that advance health and environmental justice

Maryland EJSCREEN 4.0: Integration of Cumulative Impacts, Structural Racism and Discrimination, and Air Quality to Better Visualize and Assess Environmental Health Disparities

  • PI: Sacoby Wilson (University of Maryland)
  • Sponsor: NIEHS
  • Objective: Improve Maryland EJSCREEN by including additional EJ indicators to better capture and quantify the overall burden and cumulative impact of environmental injustices.

Application of satellite observations in estimating NO2 concentrations, mortality burdens, and inequities

  • PI: Susan Anenberg; FI: Soo-Yeon Kim
  • Sponsor: NASA
  • Objective: estimate surface-level NO2 concentrations, attributable mortality burdens, and inequities in the continental US, leveraging satellite NO2 observations with high spatiotemporal resolutions


Assessing environmental justice, air quality, and health co-benefits of transport interventions in U.S. urban areas

  • PI: Gaige Kerr
  • Sponsor: NASA
  • Objective: Use a community-engaged research approach to model air quality, environmental justice, and health benefits resulting from emission reductions in major metropolitan areas of the U.S. Emission reductions will be achieved by reductions in traffic activity and/or emissions, specifically by targeting different types of vehicles (light versus heavy-duty) and different spatial scales (citywide versus targeted at local overburdened communities).

Pushing the boundaries of fine-scale NOx emission quantification from remote sensing instruments

  • PI: Dan Goldberg
  • Sponsor: NASA
  • Objective: Combine aircraft and satellite observations with high resolution models to evaluate the capabilities of current and future remote sensing instruments to quantify urban NOx emissions

Climate, Economics and Health: Adding air quality impacts into social cost of carbon estimates

  • PI: Kevin Cromar (NYU)
  • Sponsor: Wellcome Trust (subaward from NYU)
  • Objective: Incorporate changes in air quality, and its associated health impacts, into estimates of the social cost of greenhouse used by federal policymakers in the US and Germany

Source-sector NOx emissions analysis with sub-kilometer airborne observations in Houston during TRACER-AQ

  • PI: Dan Goldberg
  • Sponsor: Texas Air Quality Research Program (AQRP)
  • Objective: Use sub-kilometer observations from the NASA GCAS airborne spectrometer jointly with a high-spatial resolution (~500 m) chemical transport model to better understand the NOx emission rates in the Houston metropolitan area

Value of GeoXO atmospheric composition data for estimating air pollution-related health impacts

  • PI: Susan Anenberg
  • Sponsor: NOAA
  • Objective: evaluate the influence of remote sensing capabilities for assessing air pollution-related health impacts that may be possible with GeoXO.

Using satellite NO2 observations for public health surveillance and environmental policy planning at global, national, and urban scales

  • PI: Susan Anenberg
  • Sponsor: NASA Health and Air Quality Applied Sciences Team
  • Objective: Meet stakeholder needs for tracking NO2 concentrations and disease burdens and NOx emissions at multiple spatial scales: global, national, and urban

Data-driven forecasts of hazardous air quality events over North America

  • PI: Daniel Tong (George Mason University)
  • Sponsor: NASA Health and Air Quality Applied Sciences Team
  • Objective: Improve our collective predictability of dust, wildfire, and other hazardous air quality events through emission data assimilation and multi-model ensemble forecasting, in order to mitigate harmful effects on human health and the economy.