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Using remote sensing and Earth system models to improve air quality and public health in megacities

The primary goal of this project is to use NASA retrievals of boundary-layer concentrations of ammonia (NH3) from the Crosstrack Infrared Spectrometer (CrIS) aboard the Suomi National Polar-orbiting Partnership satellite to provide improved emission inventories of NH3 to air quality managers, forecasters, and other stakeholders who need to determine the human health impacts of PM2.5 precursors like NH3. Air quality managers have increasingly focused on controlling the growing emissions of NH3 as a potential strategy to reduce these health impacts. For example, the latest EPA regulatory guidance on assessing the impacts of new sources of PM2.5 precursors requires that emissions of NH3 be addressed. However, current NH3 emission inventories are too uncertain to provide credible estimates of the associated health impacts. Our project team has demonstrated that a finite-difference mass-balance approach can use CrIS NH3 observations to constrain NH3 emissions at the resolutions typical of regional air quality modeling. In this project, we will use these NASA Earth observations to produce improved, model-ready emission files for NH3 (covering the current and future CrIS data record) for the main US and Canadian regional air quality models (CMAQ, CAMx, and GEM-MACH). Given our successful proof-of-concept test, our proposed application is currently at Application Readiness Level (ARL) 3. In this project, we will:

(1) Integrate the NASA CrIS NH3 retrieved product and our CMAQ-based inversion methodology into a prototype application system on the Amazon cloud (ARL 4)

(2) Develop model-ready updated NH3 emission files for CMAQ, CAMx, and GEM-MACH and beta-test them in the end-user applications (ARL 5)

(3) Demonstrate that the prototype application improves the simulation of NH3 and inorganic PM2.5 in end-user modeling and leads to better decision making (ARL 6)

(4) Fully integrate the prototype application into end-user decision-making (ARL 7).