生态环境学报2026，Vol.35Issue(2)：256-266,11.DOI:10.16258/j.cnki.1674-5906.2026.02.009
基于生态系统服务供需的城市PM2.5污染风险时间变化特征与影响因素分析
Temporal Dynamics and Influencing Factors of Urban PM2.5 Pollution Risk Based on Ecosystem Service Supply and Demand
摘要
Abstract
With the accelerated urbanization and industrialization in China,the risk of PM2.5 pollution in cities has become increasingly prominent.The spatiotemporal pattern characteristics and influencing mechanisms of PM2.5 pollution risk have become a focus of academic research.Taking the area within the Fifth Ring Road of Beijing(AWFRRB)as a case study,this study constructed a PM2.5 pollution risk characterization method based on ecosystem service supply and demand,quantitatively assessed the PM2.5 pollution risk in this area from 2008 to 2021.Moreover,this study analyzed the interannual and intra-annual temporal variation characteristics of PM2.5 pollution risk using the temporal clustering method based on k-means,and applied the XGBoost machine learning method to analyze the meteorological factors influencing the supply and demand of PM2.5 removal services and the pollution risk.The results show that the PM2.5 pollution risk in the AWFRRB exhibited a changing pattern of first increasing and then decreasing from 2008 to 2021.The risk levels within a year in the four evaluated years were generally stable.The period exhibiting an intersection of high-risk and low-risk clusters generally prevailed from autumn through winter to spring,with a consistent period of low-risk cluster and non-risk occurring during the summer.The primary meteorological influencing factors of PM2.5 removal service supply were specific humidity and wind speed,while the primary influencing factor of service demand was surface shortwave radiation.Precipitation,specific humidity,and surface shortwave radiation were the main influencing factors of PM2.5 pollution risk in 2012 and 2016.Long-wave radiation was the main influencing factor of pollution risk in summer and 2021.Although the influence of wind speed and temperature was relatively weak on a season scale,they had a significant negative correlation with the pollution risk.This study provides a new perspective for understanding the temporal pattern characteristics of urban PM2.5 pollution risk and offers a new method for quantitatively analyzing the meteorological influencing factors of pollution risk.关键词
生态系统服务供需/PM2.5污染风险/影响因素/时间序列分析/XGBoost模型Key words
ecosystem service demand and supply/PM2.5 pollution risk/influencing factors/temporal sequence analysis/XGBoost model分类
资源环境引用本文复制引用
慕浩枫,宋喆禄,高镇,侯鹰,陈卫平..基于生态系统服务供需的城市PM2.5污染风险时间变化特征与影响因素分析[J].生态环境学报,2026,35(2):256-266,11.基金项目
国家自然科学基金项目(42471313) （42471313）
