Air Quality Warning and Integrated Decision Support System for Emissions (AIRWISE): Enhancing Air Quality Management in Megacities

Abstract Air pollution poses a significant environmental risk to large cities worldwide, including New Delhi, India’s capital. The occurrence of frequent episodes of elevated levels of air pollution during October–March in Delhi and National Capital Territory (Delhi–NCT) chokes its ∼32 million residents every year. Current air quality models lack the ability to accurately predict severe air pollution events in Delhi–NCT, rendering decision-makers helpless in their efforts to safeguard public health. To address this, a new initiative introduced a high-resolution Air Quality Early Warning System (AQEWS) in 2018, followed by the integration of a decision support system (DSS) in 2021. This enhancement enables dynamic source attribution data and diverse emission reduction scenarios within a single model forecast. The newly developed system, Air Quality Warning and Integrated Decision Support System for Emissions (AIRWISE), assimilates near-real-time satellite aerosol optical depth (AOD) retrievals, satellite-based fire information, surface data from 320 air quality monitoring stations, and high-resolution emissions, resulting in an extensive modeling framework. This framework demonstrates exceptional prediction capabilities, accurately forecasting very poor air quality episodes up to 3 days in advance with a remarkable 83% accuracy, even at a street-level resolution of 400 m. The AQEWS is the world’s first operational air quality forecasting system operating at a high resolution and incorporating chemical data assimilation. The Commission for Air Quality Management (CAQM) relies on forecast data to enforce the Graded Response Action Plan (GRAP) in Delhi–NCT, which imposes restrictions on pollution sources. This paper outlines the AQEWS and DSS, summarizes modeling experiments, verifies forecasts, and discusses challenges in accurately predicting extreme pollution episodes. Significance Statement The rapid growth in Delhi and its surroundings has intensified air pollution, driven by increased energy demand, industrialization, and population, compounded by crop residue burning and unfavorable winter conditions. To combat this, the Indian government has implemented temporary emission control policies. To improve air quality prediction and management, the Air Quality Early Warning System (AQEWS) was developed followed by the integration of a decision support system (DSS). AQEWS employs a high-resolution model and real-time data assimilation for accurate PM 2.5 forecasts, while DSS offers detailed pollution source information and reduction scenarios for policymakers. This study introduces the Air Quality Warning and Integrated Decision Support System for Emissions (AIRWISE) and assesses the performance of AQEWS and DSS, discussing policy implications and future improvements.