Author: Malings, C.; Knowland, K. E.; Keller, C. A.; Cohn, S. E.
                    Title: Subâ€City Scale Hourly Air Quality Forecasting by Combining Models, Satellite Observations, and Ground Measurements  Cord-id: 13d8q013  Document date: 2021_7_2
                    ID: 13d8q013
                    
                    Snippet: While multiple information sources exist concerning surfaceâ€level air pollution, no individual source simultaneously provides largeâ€scale spatial coverage, fine spatial and temporal resolution, and high accuracy. It is, therefore, necessary to integrate multiple data sources, using the strengths of each source to compensate for the weaknesses of others. In this study, we propose a method incorporating outputs of NASA’s GEOS Composition Forecasting model system with satellite information fr
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: While multiple information sources exist concerning surfaceâ€level air pollution, no individual source simultaneously provides largeâ€scale spatial coverage, fine spatial and temporal resolution, and high accuracy. It is, therefore, necessary to integrate multiple data sources, using the strengths of each source to compensate for the weaknesses of others. In this study, we propose a method incorporating outputs of NASA’s GEOS Composition Forecasting model system with satellite information from the TROPOMI instrument and ground measurement data on surface concentrations. Although we use ground monitoring data from the Environmental Protection Agency network in the continental United States, the model and satellite data sources used have the potential to allow for global application. This method is demonstrated using surface measurements of nitrogen dioxide as a test case in regions surrounding five major US cities. The proposed method is assessed through crossâ€validation against withheld ground monitoring sites. In these assessments, the proposed method demonstrates major improvements over two baseline approaches which use groundâ€based measurements only. Results also indicate the potential for nearâ€term updating of forecasts based on recent ground measurements.
 
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