Abstract
Accurate meteorological fields are imperative for correct air quality modeling through their influence on the various chemical species in the atmosphere. In this study, the simulations from the Community Multiscale Air Quality (CMAQ) model were conducted with meteorological fields generated by the Weather Research and Forecasting (WRF) using the original and observation nudging approaches to investigate if the better model performances for PM2.5, O3, and their related precursors in China were produced from the latter. Two pollution episodes (one for PM2.5 and another for O3) in 2018 were selected on the basis of the observations at the monitoring supersites in Xianghe and Taizhou cities. The results showed that the Nudging cases had better model performances on all meteorological parameters with higher values of index of agreement (IOA) and lower values of mean bias (MB). It was found that the Nudging case improved model performances for PM2.5 and its chemical components at the Xianghe site with lower values of normalized mean bias (NMB) and higher values of correlation coefficient (R) than the base case. The results for the regional PM2.5 over China indicated that the Nudging case reproduced the spatial patterns of mean PM2.5 concentrations in the 367 cities with the NMB value of –31%, much better than –42.0% in the base case. During the O3 pollution episode, the Nudging case improved the model performances for O3, CO, NO2, and VOCs with lower NMB values and higher R values than the base case. The results of regional O3 over China revealed that the Nudging case reproduced the spatial patterns of observed mean O3 concentrations in the 367 cities very well with the NMB value of 0.97%, much lower than –5.67% in the base case. The results of this study have great implications for better simulations of meteorology and air quality.
Highlights
Since the implementation of the “Air Pollution Prevention and Control Action Plan” in 2013, China has released a series of relatively strict pollutant emission standards and pollution controlAerosol and Air Quality Research | https://aaqr.org measures (Zhang et al, 2021)
The simulations from the Community Multiscale Air Quality (CMAQ) model were conducted with meteorological fields generated by the Weather Research and Forecasting (WRF) using the original and observation nudging approaches to investigate if the better model performances for PM2.5, O3, and their related precursors in China were produced from the latter
The results showed that the nudging cases (Nudging) cases had better model performances on all meteorological parameters with higher values of index of agreement (IOA) and lower values of mean bias (MB)
Summary
Since the implementation of the “Air Pollution Prevention and Control Action Plan” in 2013, China has released a series of relatively strict pollutant emission standards and pollution controlAerosol and Air Quality Research | https://aaqr.org measures (Zhang et al, 2021). The complex pollution of PM2.5 and O3 has become a tricky problem restricting the improvement of air quality in China (Li et al, 2019; Chen et al, 2019; Zhao et al, 2020). Chemical transport models (CTMs), such as Community Multiscale Air Quality (CMAQ), integrate information from emission inventories, meteorological conditions, and chemical mechanisms to estimate the temporal and spatial distributions of pollutant concentrations. The uncertainties of emission inventories and meteorological conditions, as well as the errors of the model itself, cause that the simulation results cannot fully reproduce the actual transformations and reaction processes of air pollutants (Croft et al, 2012; Gilliam et al, 2015; Zheng et al, 2017). In order to achieve better simulation results, it is feasible to improve the accuracies of meteorological conditions
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