Use of Remote Sensing Data to Improve Air Quality Decision Support Systems Used to Protect Public Health

The proposed activity here addresses the Health and Air Quality Application Area. The project anticipates improving the accuracy of the Decision Support Tools (DSTs) used by health and air quality managers to meet the health effect standards set by the Clean Air Act (CAA). The CAA is the comprehensive federal law that authorizes EPA to establish National Ambient Air Quality Standards (NAAQS) to protect public health and public welfare. The states are responsible to meet these standards through the use of the DST to develop and evaluate emissions control strategies under State Implementation Plan (SIP). SIPs are at the nexus of health effects and economics. Since the economic costs of such decisions can amount to billions of dollars nationally, the accuracy of the DST is critical to determining efficient, cost effective strategies for attaining NAAQS.

For this project, the target Decision Support Tool is the Weather Research and Forecasting (WRF) and the Community Multiscale Air Quality (CMAQ) modeling systems. CMAQ is an EPA-developed photochemical modeling system typical of the modeling systems now used by many regulatory agencies. The modeling system is also being used for operational air quality forecasting by NOAA.

The objective of the proposed project is to utilize Earth observations and NASA science in the DST to improve key physical factors such as soil moisture and heat capacity, boundary layer development, and clouds that are critical in air quality photochemical simulations. A critical area in the DSS that will be targeted for improvement is in improving model location and timing of clouds. Clouds have a profound role in photolysis activity, boundary-layer development and deep vertical mixing of pollutants and precursors. Also, a new technique for near-realtime estimation of lightning generated NOx (LNOx) will be tested in the NASA Lightning NO production Model (LNOM). The technique introduces a methodology for directly estimating LNOx, on a flash-by-flash basis, from the observed cloud-top lightning optical energy detected from satellite lightning imagers. This will be a new capability made possible by geostationary observations of lightning events. The satellite products include surface skin temperature, insolation, and albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) on-board AQUA and TERRA satellites and Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite. In addition, we will be using Geostationary Operational Environmental Satellite (GOES) observations under NASA legacy science to complement polar orbiting observations obtained from VIIRS and MODIS. The project will take advantage of GOES-16 observations that offer a broad suite of observations relevant to this project at much higher temporal and spatial resolution. This will require retooling several NASA science products that are critical for our partner organizations. The applied partners in this project are EPA􀁋s Atmospheric Modeling Division (AMD) at the National Environmental Research Laboratory (NERL), the Lake Michigan Air Directors Consortium (LADCO), the California Air Resources Board (CARB), the Texas Commission on Environmental Quality (TCEQ), and the Georgia Environmental Protection Division (GAEPD). Note that this includes some of the largest most active state air pollution agencies in the country.