基于空间数据模型的空气质量影响因素分析
Analysis of Influencing Factors of Air Quality Based on Spatial Data Model
摘要: 为了分析空气质量的影响因素，基于空间数据模型，以2025年我国31个省级行政区六种污染物的年平均浓度数据为研究对象，利用熵权Topsis法得出六种污染物指标的权重以及空气质量得分情况，发现衡量空气质量的各项污染物的权重存在较大的差异；根据全域空间自相关法，计算莫兰指数，判断空气质量指数具有明显的地理差异性，空间依赖性；最后，利用空间滞后模型分析影响空气质量的八个因素，发现人均地区生产总值和地区森林覆盖率是促进省域空气质量提高的主要因素；地区社会用电量、地区公路年度客运量和地区年平均气温是制约空气质量提高的主要因素。
Abstract: In order to analyze the influencing factors of air quality, based on the spatial data model, 31 provinces (municipalities directly under the Central Government) in China in 2019 were selected The annual average concentration data of six kinds of pollutants in Autonomous Region were used as the research object, and the weight of six kinds of pollutants and the air quality score were obtained by using entropy weight Topsis method, and it was found that there were great differences in the weight of each kind of pollutants to measure the air quality. According to the global spatial autocorrelation method, the Moran index was calculated and the air quality index was judged to have obvious geographical difference and spatial dependence. Finally, eight factors affecting air quality were analyzed by using spatial lag model, and it was found that GDP per capita and forest coverage rate were the main factors promoting air quality at provincial level. Annual highway passenger volume and annual average temperature are the main factors restricting the improvement of air quality.
文章引用：陈芳. 基于空间数据模型的空气质量影响因素分析[J]. 世界生态学, 2026, 15(3): 532-540. https://doi.org/10.12677/ije.2026.153058

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