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标题：Performance of high resolution (400 m) PM2.5 forecast over Delhi
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作者：Chinmay Jena ; Sachin D. Ghude ; Rajesh Kumar 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2021
卷号：11
期号：1
页码：4104
DOI：10.1038/s41598-021-83467-8
出版社：Springer Nature
摘要：This study reports a very high-resolution (400 m grid-spacing) operational air quality forecasting system developed to alert residents of Delhi and the National Capital Region (NCR) about forthcoming acute air pollution episodes. Such a high-resolution system has been developed for the first time and is evaluated during October 2019-February 2020. The system assimilates near real-time aerosol observations from in situ and space-borne platform in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to produce a 72-h forecast daily in a dynamical downscaling framework. The assimilation of aerosol optical depth and surface PM 2.5 observations improves the initial condition for surface PM 2.5 by about 45 µg/m 3 (about 50%).The accuracy of the forecast degrades slightly with lead time as mean bias increase from 2.5 µg/m 3 on the first day to - 17 µg/m 3 on the third day of forecast. Our forecast is found to be very skillful both for PM 2.5 concentration and unhealthy/ very unhealthy air quality index categories, and has been helping the decision-makers in Delhi make informed decisions.
其他摘要：Abstract This study reports a very high-resolution (400 m grid-spacing) operational air quality forecasting system developed to alert residents of Delhi and the National Capital Region (NCR) about forthcoming acute air pollution episodes. Such a high-resolution system has been developed for the first time and is evaluated during October 2019-February 2020. The system assimilates near real-time aerosol observations from in situ and space-borne platform in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to produce a 72-h forecast daily in a dynamical downscaling framework. The assimilation of aerosol optical depth and surface PM 2.5 observations improves the initial condition for surface PM 2.5 by about 45 µg/m 3 (about 50%).The accuracy of the forecast degrades slightly with lead time as mean bias increase from 2.5 µg/m 3 on the first day to − 17 µg/m 3 on the third day of forecast. Our forecast is found to be very skillful both for PM 2.5 concentration and unhealthy/ very unhealthy air quality index categories, and has been helping the decision-makers in Delhi make informed decisions.