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<p>Severe particulate pollution in Delhi arises from the interaction of local emissions and regional transport, yet their relative contributions under different meteorological regimes remains insufficiently quantified for policy use. This study applies the WRF‑Chem model to three representative episodes—a pre‑monsoon dust storm, a post‑monsoon crop residue burning (CRB), and a winter pollution event—to estimate background concentrations and separate local from regional contributions using emission zero‑out experiments. WRF-Chem reproduces the observed magnitude and temporal evolution of PM₂.₅ reasonably well, though peak timing and wind fields show notable uncertainties. The analysis shows that Delhi’s event severity is highly season-dependent: regional inflow dominates during dust-storm and post-monsoon burning conditions, whereas winter peaks are comparatively more controlled by local accumulation under unfavourable dispersion. These results underscore that while local emission controls are vital for wintertime improvements, mitigation strategies for summer and post-monsoon episodes require a coordinated, cross-regional airshed management framework. The results are subject to limitations associated with global anthropogenic emission inventories, wind speed biases, and the short simulation periods, which should be addressed in future work through refined local inventories, data assimilation, and longer multi‑year simulations.</p>

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Assessment of the contribution of regional transport on severe air pollution episodes in the Delhi-NCT region using WRF-Chem model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月13日

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  • Rahul Chaurasia,
  • Manju Mohan

摘要

Severe particulate pollution in Delhi arises from the interaction of local emissions and regional transport, yet their relative contributions under different meteorological regimes remains insufficiently quantified for policy use. This study applies the WRF‑Chem model to three representative episodes—a pre‑monsoon dust storm, a post‑monsoon crop residue burning (CRB), and a winter pollution event—to estimate background concentrations and separate local from regional contributions using emission zero‑out experiments. WRF-Chem reproduces the observed magnitude and temporal evolution of PM₂.₅ reasonably well, though peak timing and wind fields show notable uncertainties. The analysis shows that Delhi’s event severity is highly season-dependent: regional inflow dominates during dust-storm and post-monsoon burning conditions, whereas winter peaks are comparatively more controlled by local accumulation under unfavourable dispersion. These results underscore that while local emission controls are vital for wintertime improvements, mitigation strategies for summer and post-monsoon episodes require a coordinated, cross-regional airshed management framework. The results are subject to limitations associated with global anthropogenic emission inventories, wind speed biases, and the short simulation periods, which should be addressed in future work through refined local inventories, data assimilation, and longer multi‑year simulations.