摘要
长三角地区是继京津冀地区之后雾霾最严重的地区,PM_(2.5)作为雾霾的主要成分,探究其质量浓度变化趋势及驱动因素,对大气污染治理具有重要意义。研究基于2017—2022年长三角城市群监测站点和统计年鉴数据,采用空间自相关和时空地理加权等方法深入分析了长三角城市群PM_(2.5)时空异质性及其驱动因素。结果显示:(1)6 a间长三角城市群PM_(2.5)年均质量浓度整体呈现下降趋势,优良空气质量天数逐渐增加。(2)PM_(2.5)空间变化呈现显著的空间异质性,空间上大致呈现“西高东低,北高南低”的污染格局,西部地区PM_(2.5)质量浓度大多超过30μg/m^(3),且呈现连片污染态势。PM_(2.5)质量浓度的季均值和年均值在空间分布上表现出相似特征,质量浓度通常在冬季最高,夏季最低,而春秋季节则呈现过渡状态,月变化出现明显的“U”形曲线。(3)在2017—2020年,空间聚集性逐渐增强,在2021—2022年,聚集性减弱,PM_(2.5)质量浓度区域间差异降低。(4)社会因子中对PM_(2.5)影响最大的是公共交通载客量,自然因子中影响最大的是风速。疫情期间各社会因子出现明显省际差异,且人均GDP和工业用电量呈现“U”形变化趋势,二产占比、公共交通载客量、工业二氧化硫则呈现倒“U”形变化趋势。
The Yangtze River Delta(YRD)is the second most severe haze region in China,following the Beijing-Tianjin-Hebei area.Given that PM_(2.5) is a primary contributor to haze,understanding its concentration trends and driving factors is crucial for effective air pollution management.Utilizing data from monitoring stations and statistical yearbooks of the YRD urban agglomeration from 2017 to 2022,this study employs spatial autocorrelation and spatiotemporal geographic weighting to conduct a comprehensive analysis of the spatiotemporal heterogeneity of PM_(2.5) and its influencing factors within the YRD urban agglomeration.The study reveals that:(1)The annual average PM_(2.5) mass concentrations in the YRD urban agglomeration exhibited an overall decreasing trend over the six-year period,accompanied by a gradual increase in the number of days with good air quality.(2)The spatial distribution of PM_(2.5) demonstrates significant heterogeneity,characterized by a pollution pattern that is generally"higher in the west and lower in the east,and higher in the north and lower in the south."In the western regions,PM_(2.5) mass concentrations predominantly exceed 30μg/m^(3),displaying a contiguous pollution trend.Both seasonal and annual averages of PM_(2.5) mass concentrations exhibit similar spatial distributions,with the highest levels recorded in winter and the lowest in summer.Transitional concentrations are observed in spring and autumn,characterized by a distinct“U”shape in monthly variations.The seasonal mean and annual mean concentrations share comparable spatial distribution characteristics.(3)The spatial aggregation of PM_(2.5) mass concentrations gradually increased from 2017 to 2020,followed by a decrease from 2021 to 2022,alongside a reduction in regional differences.(4)Among social factors,public transportation ridership has the most significant impact on PM_(2.5) levels,while wind speed is the most influential natural factor.During the pandemic,notable inter-provincial disparities emerged among social factors,with per capita GDP and industrial electricity consumption displaying a"U"shape trend.In contrast,the proportion of the secondary industry,public transportation ridership,and industrial sulfur dioxide levels exhibited an inverted“U”shape trend.
作者
陈优良
李芊芊
范琴
王兆茹
CHEN Youliang;LI Qianqian;FAN Qin;WANG Zhaoru(School of Civil and Surveying Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi,China;School of Resources and Environmental Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi,China)
出处
《安全与环境学报》
北大核心
2025年第8期3252-3264,共13页
Journal of Safety and Environment
基金
国家自然科学基金项目(42261072)。
关键词
环境工程学
PM_(2.5)
时空异质性
驱动因素
时空地理加权回归
environmental engineering
PM 2.5
spatial-temporal heterogeneity
driving factors
geographically and temporally weighted regression
