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Analysis of Spatio-Temporal Variation Characteristics of Air Pollutants in Zaozhuang China from 2018 to 2022

X. Xia,Shangpeng Sun

Published 2025 in Atmosphere

ABSTRACT

Based on the air-quality monitoring data of Zaozhuang City from 2018 to 2022, this study systematically analyzed the spatio-temporal variation characteristics of multiple pollutants by comprehensively applying Kriging interpolation, time-series decomposition, wavelet transform, and DBSCAN spatial clustering methods. The key findings include: (1) Overall, air pollutant concentrations in Zaozhuang decrease from 2018 to 2022, with NO2, SO2, PM2.5, and PM10 concentrations declining by 17.3%, 52.2%, 28.9%, and 33.6%, respectively. However, O3 concentration increases by 2.5% in 2022 compared to 2018. Seasonally, SO2, PM2.5, and PM10 concentrations are the highest in winter and lowest in summer, while CO, NO2, and O3 follow a winter > autumn > spring > summer pattern. Weekly variations show that daily average concentrations of CO, NO2, SO2, PM2.5, and PM10 peak on Mondays, with concentrations slightly higher on weekdays than weekends. (2) Spatially, CO, NO2, PM2.5, and PM10 concentrations are higher in the southern region, while O3 and SO2 concentrations are elevated in Shizhong District, Xuecheng District, and Tengzhou City. (3) Correlation analysis reveals that meteorological parameters, such as precipitation, significantly influence pollutant concentrations, with precipitation playing a role in reducing pollutant levels. This study highlights the effectiveness of the Kriging method in analyzing the complex spatio-temporal dynamics of air pollutants, offering valuable insights for environmental policy and urban planning.

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