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

Govardhan, G and Ghude, SD and Kumar, R and Sharma, S and Gunwani, P and Jena, C and Yadav, P and Ingle, S and Debnath, S and Pawar, P and Acharja, P and Jat, R and Kalita, G and Ambulkar, R and Kulkarni, S and Kaginalkar, A and Soni, VK and Nanjundiah, RS and Rajeevan, M (2024) Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India. In: Geoscientific Model Development, 17 (7). pp. 2617-2640.

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Abstract

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 PM2.5 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 80��¯) 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 PM2.5 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 PM2.5 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. © 2024 Copernicus Publications. All rights reserved.

Item Type:	Journal Article
Publication:	Geoscientific Model Development
Publisher:	Copernicus Publications
Additional Information:	The copyright for this article belongs to Copernicus Publications.
Keywords:	air quality; decision support system; particulate matter; policy making; pollutant source; spatiotemporal analysis, Delhi; Delhi; India; New Delhi
Department/Centre:	Division of Mechanical Sciences > Divecha Centre for Climate Change Division of Mechanical Sciences > Centre for Atmospheric & Oceanic Sciences
Date Deposited:	10 Jul 2024 07:32
Last Modified:	10 Jul 2024 07:32
URI:	http://eprints.iisc.ac.in/id/eprint/84785

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