Performance of high resolution (400 m) PM2.5 forecast over Delhi

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 PM2.5 observations improves the initial condition for surface PM2.5 by about 45 µg/m3 (about 50%).The accuracy of the forecast degrades slightly with lead time as mean bias increase from + 2.5 µg/m3 on the first day to − 17 µg/m3 on the third day of forecast. Our forecast is found to be very skillful both for PM2.5 concentration and unhealthy/ very unhealthy air quality index categories, and has been helping the decision-makers in Delhi make informed decisions.

Characteristics of VOC Composition at Urban and Suburban Sites of New Delhi, India in Winter

“…These biases have been suggested to be due to uncertainties in the input emissions and model resolutions, besides the treatment of atmospheric chemistry in different mechanisms. Recent studies have shown substantial improvements in the forecasts through the assimilation of observational datasets in the model (Jena et al., 2021; Kumar et al., 2020). In view of this scenario, in situ measurements in different environments are needed to characterize the sensitivity of O 3 to its precursors and improve the performances of regional and global models.…”

Systematizing the approach to air quality measurement and analysis in low and middle income countries

“…Forecasting methods are increasingly combining satellite data with chemical transport models and reanalysis data to produce air quality forecasts at regional and global scales [13,14]. Countries, cities, or in some cases, researchers, are also investing in their own fit-for-purpose air quality forecasting and modeling tools [15,16], or adapting global models for local use [17][18][19]. Data from such systems, coupled with strategic communications, can also provide citizens usable and timely information, enabling them to limit their exposure to ambient air pollution [20].…”

Chemical Weather and Chemical Climate

“…Prototype chemical weather models have also been developed in universities or research centers. Examples among several others are the air quality models developed at the National Center for Atmospheric Research (NCAR) in Boulder, CO (Lamarque et al., 2012; Pfister et al., 2020), at the Institute for Atmospheric Physics (IAP) in Beijing (Wang et al., 2006; Wei et al., 2019) or at the Indian Institute for Tropical Meteorology (IITM) in Pune, India (Beig et al., 2012; Jena et al., 2021). See also Baklanov and Zhang (2020).…”