Break point identification and spatiotemporal dynamic evolution of air pollutants: An empirical study from Anhui province, east China - Wang, Huajie; Gui, Herong; Wang, Houfeng; Liu, Guijian (Frontiers in Environmental Science, 2022)
The new modality of inter-regional joint prevention and control is increasingly important to the integrated process of collaborative governance of air pollutants. Therefore, it has become necessary to analyze the degree of interaction among air pollutants within and between cities, master the dynamics of their spatiotemporal distribution and its influencing factors, and diagnose the primary obstacle factors. Long-term data on the concentrations of six air pollutants among 16 cities of Anhui province from 2015 to 2020 were analyzed using harmonic regression, the coupling coordination degree model, the obstacle degree model, the logarithmic mean Divisia index (LMDI), and exploratory spatial data analysis (ESDA). Over all, the annual mean concentrations of five of these pollutants (NO2, SO2, CO, PM10, and PM2.5) decreased to a certain extent over time, whereas O3 concentrations increased. The biggest decrease was observed in BZ city, where SO2 decreased by 80.60% (halving time: −2.03 ± 0.02 years), and the biggest increase was observed in CZ city, where O3 increased by 113.85% (doubling time: 1.74 ± 0.01 years). The O3 concentrations in most cities reached their break points starting in 2018, but the break points of other air pollutants appeared earlier than that of O3, mostly before 2018. With the exception of NO2 and O3, the halving times of other air pollutants were basically shorter than the doubling times. The high degree of interaction among air pollutants within and between cities contrasted sharply with the low degree of coordination. An analysis of hotspot evolution revealed that particulate matter (PM10 and PM2.5) migrated to northern Anhui, NO2 and O3 agglomerated to central Anhui, and CO eventually gathered in the Wanjiang City Belt. The primary obstacle factors of air pollutants in Anhui were particulate matter, SO2 and NO2. The seasonal differences in primary obstacle factors were most evident in 2020: NO2 dominated in winter (in 10 cities), SO2 dominated in southern Anhui, and particulate matter dominated in northern and central Anhui in spring. Other seasons were almost entirely dominated by particulate matter. Industrial structure was found to be more effective in reducing industrial carbon emissions, and technological improvement was found to be more advantageous in reducing industrial particulate matter, NOx and SO2. Finally, the policy implications of these results and suggestions for strengthening the inter-city joint prevention and control of air pollutants are discussed.