ZHAN Qing, ZHANG Yun-jiang, CHEN Hong, et al. Trend Analysis of Atmospheric Particulate Matter over the Beijing-Tianjin-Hebei Region During 2015-2021 Using the KZ Filtering Approach[J]. Journal of Ecology and Rural Environment, 2023, 39(9): 1133-1143. DOI: 10.19741/j.issn.1673-4831.2022.0875
    Citation: ZHAN Qing, ZHANG Yun-jiang, CHEN Hong, et al. Trend Analysis of Atmospheric Particulate Matter over the Beijing-Tianjin-Hebei Region During 2015-2021 Using the KZ Filtering Approach[J]. Journal of Ecology and Rural Environment, 2023, 39(9): 1133-1143. DOI: 10.19741/j.issn.1673-4831.2022.0875

    Trend Analysis of Atmospheric Particulate Matter over the Beijing-Tianjin-Hebei Region During 2015-2021 Using the KZ Filtering Approach

    • The Beijing-Tianjin-Hebei Region has become a key focus area for addressing atmospheric particulate matter pollution in recent years in China. In this study, Kolmogorov-Zurbenko (KZ) filtering analysis was applied to analyze the time series of fine particulate matter (PM2.5), inhalable particulate matter (PM10), and coarse particulate matter (PM2.5-10) in 13 cities in the Beijing-Tianjin-Hebei Region from 2015 to 2021. The results show that the annual average concentrations of PM2.5 and PM10 had generally decreased, with a decline rate of 5.07 and 8.10 μg·m-3·a-1, respectively. The KZ filtering analysis also revealed that the short-term, seasonal, and long-term components of PM2.5, PM10, and PM2.5-10 are independent of each other. The highest contribution to the fluctuations in the original time series was found to be from the short-term component (over 50%), followed by the seasonal component, indicating that the fluctuations are mainly influenced by short-term and seasonal variations in pollutant emissions and meteorological conditions. Using the KZ-filtered concentration series, a stepwise multiple regression linear model was established to quantitatively evaluate the contributions of meteorological factors and emission reduction measures to the trends observed. The city-by-city analysis results show that the impact of meteorological conditions on PM2.5 concentrations was highest in Qinhuangdao (14.86%), while emission reduction measures had the greatest impact on PM2.5 concentrations in Hengshui (96.77%). The impact of meteorological conditions on PM10 concentrations was highest in Qinhuangdao (13.69%), while emission reduction measures had the greatest impact on PM10 concentrations in Langfang (93.96%). The impact of meteorological conditions on PM2.5-10 concentrations was highest in Cangzhou (26.23%), while emission reduction measures had the greatest impact on PM2.5-10 concentrations in Langfang (91.80%). Overall, the analysis results suggest that emission reduction measures plays a crucial role in improving particulate matter pollution in the Beijing-Tianjin-Hebei Region from 2015 to 2021.
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