Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India

This paper discusses the newly developed Decision Support System version 1.0 (DSS v1.0) for air quality management activities in Delhi, India. In addition to standard air quality forecasts, DSS provides the contribution of Delhi, its surrounding districts, and stubble-burning fires in the neighboring states of Punjab and Haryana to the PM_2.5 load in Delhi. DSS also quantifies the effects of local and neighborhood emission-source-level interventions on the pollution load in Delhi. The DSS-simulated Air Quality Index for the post-monsoon and winter seasons of 2021-2022 shows high accuracy (up to 80ĝ€¯%) and a very low false alarm ratio (~20%) from day 1 to day 5 of the forecasts, especially when the ambient air quality index (AQI) is >300. During the post-monsoon season (winter season), emissions from Delhi, the rest of the National Capital Region (NCR)'s districts, biomass-burning activities, and all other remaining regions on average contribute 34.4% (33.4%), 31% (40.2%), 7.3% (0.1%), and 27.3% (26.4%), respectively, to the PM_2.5 load in Delhi. During peak pollution events (stubble-burning periods or wintertime), however, the contribution from the main sources (farm fires in Punjab-Haryana or local sources within Delhi) could reach 65%-69%. According to DSS, a 20% (40%) reduction in anthropogenic emissions across all NCR districts would result in a 12% (24%) reduction in PM_2.5 in Delhi on a seasonal mean basis. DSS is a critical tool for policymakers because it provides such information daily through a single simulation with a plethora of emission reduction scenarios.