2016~2020年太原市城区PM_2.5时空分布特征及其影响因素分析

Analysis of the Spatiotemporal Distribution Characteristics of PM_2.5 in Urban Areas of Taiyuan from 2016 to 2020 and Its Influencing Factors

摘要: 本文采用太原市城区2016~2020年PM_2.5空气质量数据，通过Excel统计、普通克里金插值法、Pearson相关系数法等方法来探究其时空变化特征及其影响因素。结果表明：在2016~2020年期间，太原市城区的PM_2.5浓度呈现出明显的季节性变化，即冬季高和夏季低，这与冬季大气稳定性增强和供暖季节排放增加有关，夏季则受有利气象条件和工业排放减少影响。在过去的5年中，PM_2.5浓度呈下降趋势，环境治理和产业结构调整发挥了作用。在空间上，同一季节内PM_2.5浓度差异小，但冬季南部稍高，年际尺度上南部和东部浓度较高。地形和土地利用差异也影响PM_2.5浓度空间分布，工业结构、扬尘污染和环保政策在空气质量变化中至关重要。总体而言，太原市城区PM_2.5浓度的下降反映了综合治理措施的有效实施和环境保护工作的加强。

Abstract: In this paper, PM_2.5 air quality data from 2016 to 2020 in urban areas of Taiyuan were used to explore its spatio-temporal variation characteristics and its influencing factors by Excel statistics, ordinary Kriging interpolation, and Pearson correlation coefficient method. The results show that during 2016~2020, PM_2.5 concentrations in urban areas of Taiyuan city show obvious seasonal variations, i.e., high in winter and low in summer, which are related to the enhanced atmospheric stability and increased emissions during the heating season in winter, and influenced by favorable meteorological conditions and reduced industrial emissions in summer. In the past five years, PM_2.5 concentrations showed a decreasing trend, with environmental management and industrial restructuring playing a role. Spatially, there were small differences in PM_2.5 concentrations within the same season, but they were slightly higher in the south in winter and higher in the south and east on the interannual scale. Topography and land use differences also influence the spatial distribution of PM_2.5 concentrations, and industrial structure, dust pollution, and environmental policies are crucial in air quality changes. Overall, the decline in PM_2.5 concentrations in the urban area of Taiyuan reflects the effective implementation of comprehensive management measures and the strengthening of environmental protection.