%0 Journal Article %T 长江中游城市群PM2.5污染驱动因素的地理探测
Geographic Detection of PM2.5 Pollution Drivers in Urban Agglomerations in the Middle Reaches of the Yangtze River %A 谢珍 %J Statistics and Applications %P 2607-2615 %@ 2325-226X %D 2024 %I Hans Publishing %R 10.12677/sa.2024.136251 %X 随着经济的快速发展，大气污染问题不断加重，而PM2.5作为大气污染中重要污染物之一，探究PM2.5污染的时空演变特征与驱动因素对区域大气联动治理意义重大。本文通过地理探测器模型，并结合了空间相关性分析，探究了2006~2022年长江中游城市群PM2.5污染的时空演变特征与其驱动因素。研究结果表明：长江中游城市群PM2.5浓度呈现一个先上升后下降的变化趋势，在空间上呈现显著的空间聚集和空间依赖性；其次，自然条件中的降水量、平均温度、风速均为影响PM2.5浓度的主导因子，在2022年社会经济因素中的建成区绿化覆盖率和第二产业占比的驱动力值上升。且因子交互作用q值远大于单一因子，2006年、2013年、2022年的主导交互因子分别为TEM∩URB、2 PRE∩URB、IND∩GFC。
With the rapid development of the economy, the problem of air pollution is increasing, and PM2.5 is one of the important pollutants in air pollution, so it is of great significance to explore the temporal and spatial evolution characteristics and driving factors of PM2.5 pollution for regional atmospheric linkage control. In this paper, we explored the temporal and spatial evolution characteristics and driving factors of PM2.5 pollution in the urban agglomeration of the middle reaches of the Yangtze River from 2006 to 2022 through a geographic detector model combined with spatial correlation analysis. The results show that the PM2.5 concentration in the urban agglomeration in the middle reaches of the Yangtze River shows a trend of first increasing and then decreasing, showing significant spatial aggregation and spatial dependence in space, and secondly, precipitation, average temperature and wind speed are the dominant factors affecting PM2.5 concentration under natural conditions, and the driving force values of green coverage rate and the proportion of secondary industry in built-up areas increase in 2022. The q-value of factor interaction was much larger than that of a single factor, and the dominant interaction factors in 2006, 2013, and 2022 were TEM∩URB, 2 PRE∩URB, IND∩GFC, respectively. %K PM2.5浓度， %K 驱动因素， %K 空间聚集， %K 地理探测
PM2.5 Concentration %K Driving Factors %K Spatial Aggregation %K Geographic Detection %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=103979