成都市城市化与PM_2.5浓度时空演变关系

Relationship between Urbanization and the Spatial-Temporal Evolution of PM_2.5 Concentration in Chengdu

摘要: 本文对成都市2013~2022年近10年的PM_2.5数据进行分析，应用Microsoft Excel软件分析PM_2.5浓度的时间变化特征，应用ArcGIS软件分析PM_2.5浓度的空间变化特征，应用SPSS软件通过主成分分析和耦合协调度分析了城市化与PM_2.5浓度的关系。研究结果表明PM_2.5的月变化特征每年表现出相似的变化模式，呈现出先降低后上升的趋势，1~8月呈下降趋势，9~12月呈上升趋势。季节变化特征冬季PM_2.5浓度最高，夏季PM_2.5浓度最低，春季和秋季PM_2.5浓度相似，基本上是冬季 > 春季 > 秋季 > 夏季。年变化特征整体上呈现下降趋势，从2013年的86.17 μg/m³逐步下降到2022年的31.21 μg/m³。空间变化特征表明PM_2.5浓度在中心区域数值偏高，向四周扩散时则逐渐降低，从西北部向东南部PM_2.5浓度逐渐递增。

Abstract: This paper analyzes the PM_2.5 data of chengdu in the nearly 10 years from 2013 to 2022. The temporal variation characteristics of PM_2.5 concentration are analyzed by using Microsoft Excel software, and the spatial variation characteristics of PM_2.5 concentration are analyzed by using ArcGIS software. The relationship between urbanization and PM_2.5 concentration are analyzed by principal component analysis and coupling coordination relationship using SPSS software. The results indicate that the monthly variation of PM_2.5 shows a similar pattern every year, with a downward trend from January to August and an upward trend from September to December, displaying a pattern of first decreasing and then increasing. PM_2.5 concentrations are highest in winter and lowest in summer, while levels in spring and autumn are relatively comparable, resulting in a general seasonal pattern of winter > spring > autumn > summer. The annual variation characteristics showed a overall downward trend, progressively descending from 86.17 μg/m³ in 2013 to 31.21 μg/m³ in 2022. The spatial variation characteristics indicate that the concentration of PM_2.5 is relatively high in the central area and gradually decreases when diffusing to the periphery, while the concentration increases gradually from the northwest to the southeast.