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 neighborin...

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Published in:Geoscientific Model Development 2024-04, Vol.17 (7), p.2617-2640
Main Authors: Govardhan, Gaurav, Ghude, Sachin D., Kumar, Rajesh, Sharma, Sumit, Gunwani, Preeti, Jena, Chinmay, Yadav, Prafull, Ingle, Shubhangi, Debnath, Sreyashi, Pawar, Pooja, Acharja, Prodip, Jat, Rajmal, Kalita, Gayatry, Ambulkar, Rupal, Kulkarni, Santosh, Kaginalkar, Akshara, Soni, Vijay K., Nanjundiah, Ravi S., Rajeevan, Madhavan
Format: Article
Language:English
Subjects:
Air
Air pollution
Air quality
Air quality forecasting
Air quality management
Air quality standards
Anthropogenic factors
Apportionment
Biomass burning
Burning
Decision making
Decision support systems
Emission standards
Emissions
Emissions control
False alarms
Fires
Industrial plant emissions
Monsoons
Outdoor air quality
Particulate matter
Peak load
Pollutant load
Pollutants
Pollution
Pollution load
Quality management
Reduction
Seasons
Stubble
Wind
Winter
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Summary: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.
ISSN:1991-9603
1991-962X
1991-959X
1991-9603
1991-962X
DOI:10.5194/gmd-17-2617-2024