Abstract

As an important issue in atmospheric environment, the contributions of anthropogenic emissions and meteorological conditions to air pollution have been few assessed over the receptor region in regional transport of air pollutants. In this study on observations of environment and meteorology over 2015–2019, the Kolmogorov–Zurbenko (KZ) filter was performed to decompose the PM2.5 variations into multi-time scale components over the Twain-Hu Basin (THB), a receptor region in regional transport of air pollutants in central China, where the short-term, seasonal and long-term components accounted for respectively 47.5 %, 41.4 % and 3.7 % to daily PM2.5 changes. The short-term and seasonal components dominated the day-to-day PM2.5 variations with long-term component determining the change trend of PM2.5 concentrations over recent years. The emission- and meteorology-related long-term PM2.5 components over the THB were identified. The meteorological contribution to PM2.5 declining trend presented the distinct spatial pattern over the THB with northern positive rates up to 61.92 % and southern negative rates down to −24.93 %. The opposite effects of meteorology on PM2.5 pollution could accelerate and offset the effects of emission reductions in the northern and southern THB, which is attributed to the upwind diffusion and downward accumulation of air pollutants over the receptor region in regional PM2.5 transport. It is noteworthy that the increasing conversion efficiencies of SO2 and NO2 to sulfate and nitrate for secondary PM2.5 could offset the effects of PM2.5 emission reduction on air pollution in the THB during recent years, revealing the enhancing contribution of gaseous precursor emissions to PM2.5 concentrations with controlling anthropogenic emissions of PM2.5 and the gaseous precursors over the receptor region in regional transport of air pollutants.

Highlights

  • Haze pollution with high levels of PM2.5 has been a serious problem in atmospheric environment (Peng et al, 2016; Wang et al, 2016) with adverse influences on air quality and human health (Cao et al, 2012; Crouse et al, 2012)

  • It is noteworthy that the increasing conversion efficiencies of SO2 and NO2 to sulfate and nitrate for secondary PM2.5 could offset the effects of PM2.5 emission reduction on air pollution in the Twain-Hu Basin (THB) during recent years, revealing the enhancing contribution of gaseous precursor emissions to PM2.5 concentrations with controlling anthropogenic emissions of PM2.5 and the gaseous precursors over the receptor region in regional transport of air pollutants. 30 1

  • Based on the PM2.5 decomposition results of KZ filter, the short-term, seasonal and long-term components respectively accounted for 34.8%–53.8%, 29.2%–56.3% and 0.2%–9.8% of the total variances of daily PM2.5 changes in the THB over recent years (Figs. 2b, 2c and 2d), reflecting the different patterns of multi-time scale variations of PM2.5 over this region in central China with diverse effects of emissions and meteorology

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Summary

Introduction

Haze pollution with high levels of PM2.5 (fine particulate matters with aerodynamic diameters equal to or less than 2.5 μm) has been a serious problem in atmospheric environment (Peng et al, 2016; Wang et al, 2016) with adverse influences on air quality and human health (Cao et al, 2012; Crouse et al, 2012). The contributions of air pollutant emissions and meteorological conditions to air quality change over this air pollution region in central China need to be assessed with the long-term observations over recent years. In this observational study, we investigated the multi-scale changes of PM2.5 concentrations over the THB from 2015 to 75 2019 by establishing the statistic model with Kolmogorov–Zurbenko (KZ) filter, and evaluated the contributions of anthropogenic emissions and meteorological changes to the declining trends in PM2.5 concentrations in this receptor region in regional PM2.5 transport over CEC during the past 5-year emission control. The analysis of THB’s multi-scale air quality changes can improve the understanding of the effects of emission mitigation and meteorological changes on environmental change with regional transport of air pollutants. 80

Data and methods
Multiple linear regression of air pollutant changes with meteorological variables
Results and discussion
Conclusions
345 References
Full Text
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