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Developing a Method for Resolving NOx Emission Inventory Biases Using Discrete Kalman Filter Inversion, Direct Sensitivities, and Satellite-Based Columns
Citation:
NAPELENOK, S., R. W. PINDER, A. GILLILAND, AND R. V. Marin. Developing a Method for Resolving NOx Emission Inventory Biases Using Discrete Kalman Filter Inversion, Direct Sensitivities, and Satellite-Based Columns. Chapter 3, Carlos Borrego, Ana Isabel Miranda (ed.), Air Pollution Modeling and its Application XIX. Springer, New York, NY, , 322-330, (2008).
Impact/Purpose:
National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling Division (AMD) conducts research in support of EPA′s mission to protect human health and the environment. AMD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
An inverse method was developed to integrate satellite observations of atmospheric pollutant column concentrations and direct sensitivities predicted by a regional air quality model in order to discern biases in the emissions of the pollutant precursors.