Data · dataset · 2026
Air Quality Warning and Integrated Decision Support System for Emissions (AIRWISE): Enhancing air quality management in megacities
Listed in National Center for Atmospheric Research
Air pollution poses a significant environmental risk to large cities worldwide, including New Delhi, India’s capital.
Description
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.
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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.
Links
Get the data
- Publisher page n2t.net/ark:/85065/d7nc65gf ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/air-quality-warning-and-integrated-decision-support-sy… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=0d99e74f-331d-4ab4-b990-b98c7149d… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Atmospheric sciences 73%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 0d99e74f-331d-4ab4-b990-b98c7149df05 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3701 | enrichment · data ucar edu | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |