2015—2020年中国PM_(2.5)污染时空演化及其与ENSO的关系研究  

Analysis of the spatial and temporal evolution of PM_(2.5) and the relationship of ENSO and PM_(2.5) concentrations in China from 2015 to 2020

作　　者：秦靖蒿 王晓红[1] 杨艺科 陆庆恒 李晓艺 于乐江[2] QIN Jinghao;WANG Xiaohong;YANG Yike;LU Qingheng;LI Xiaoyi;YU Lejiang(College of Environment and Safety Engineering,Qingdao University of Science and Technology,Qingdao 266042;SOA Key Laboratory for Polar Science,Polar Research Institute of China,Shanghai 200136)

机构地区：[1]青岛科技大学环境与安全工程学院,青岛266042 [2]中国极地研究中心,自然资源部极地科学重点实验室,上海200136

出　　处：《环境科学学报》2023年第3期315-332,共18页Acta Scientiae Circumstantiae

基　　金：山东自然科学基金项目(No.ZR2020MD016)。

摘　　要：根据2015—2020年中国近1500个监测站点PM_(2.5)小时浓度数据,利用空间自相关分析、回归分析及小波分析方法,探索了中国PM_(2.5)浓度与异常的时空演化及其与ENSO(El Niño-Southern Oscillation,厄尔尼诺-南方涛动)之间的关系.结果表明,PM_(2.5)污染具有显著空间自相关性,空间上存在明显集聚特征.PM_(2.5)浓度较高的站点通常位于华北地区,其次是华中、华东北部,而PM_(2.5)浓度较低的站点通常位于青藏、华南南部和西南南部地区,特别是华南沿海区域.两个ENSO期间,夏季,全国各区域厄尔尼诺年(2015年和2018年)PM_(2.5)平均浓度高于拉尼娜年(2017年和2020年);冬季,北方大部分区域,除ENSO II内蒙古和青藏地区以外,厄尔尼诺年PM_(2.5)平均浓度也高于拉尼娜年,但华南和西南地区的结果相反,表明ENSO对我国冬季南北方PM_(2.5)污染的影响可能相反.回归分析表明,华北、华东、华中北部及东北地区PM_(2.5)月均浓度正异常与ENSO正相(厄尔尼诺)相关,华中南部、华东南部、华南及西南地区PM_(2.5)月均浓度正异常与ENSO呈负相(拉尼娜)相关.这些PM_(2.5)浓度异常可以部分解释为与ENSO相关的气象因素异常的影响,我国北方(除ENSO II青藏以外),特别是东北的PM_(2.5)污染正(负)异常同时受ENSO正相厄尔尼诺(负相拉尼娜)期间的异常高(低)温和降水负(正)异常的共同影响,而中国东南沿海地区PM_(2.5)污染正(负)异常主要与ENSO负相拉尼娜(正相厄尔尼诺)导致的负(正)降水异常和异常东北(西南)风相关.This study used spatial autocorrelation analysis,regression analysis and wavelet analysis to investigate the spatiotemporal evolution of PM_(2.5) pollution and the anomalies,and to examine the relationship between ENSO and PM_(2.5) pollution in China's Mainland based on the hourly PM_(2.5) concentration data of nearly 1500 monitoring stations from 2015 to 2020.The results showed that PM_(2.5) pollution was highly spatially autocorrelated and aggregated.Higher PM_(2.5) concentration stations were usually found in North China,followed by Central China and northern parts of East China,while lower PM_(2.5) concentration stations were in Qinghai-Tibet Plateau,southern parts of South China and Southwest China,especially in the coastal regions of South China.During the two ENSO events,the average PM_(2.5) concentrations in summer were greater in El Nino years(2015 and 2018)than in La Nina years(2017 and 2020)in all the regions;in winter,in most northern regions,except Inner Mongolia and Qinghai Tibet Plateau in ENSOII,the average PM_(2.5) concentrations were higher in El Nino years than in La Nina years too,but the results in South China and Southwest China were opposite,indicating that ENSO might have opposite impacts on PM_(2.5) pollution in Southern and Northern China in winter.According to the results of the regression analysis,the majority of the PM_(2.5) concentration anomalies in North China,East China,Northeast China and northern parts of Central China were positively correlated with the positive phase of ENSO(El Niño);while the majority of the anomalies in South China,Southwest China,southern parts of Central China and East China were negatively correlated with the negative phase of ENSO(La Niña).These PM_(2.5) anomalies could be partially explained by the effects of natural factor anomalies associated with ENSO.The positive(negative)PM_(2.5) pollution anomalies in northern China(except Qinghai-Tibet plateau during ENSO II),especially in Northeast China,were simultaneously influenced by the combination of the

关 键 词：厄尔尼诺-南方涛动(ENSO) PM_(2.5) 时空演化 小波分析 空间自相关 中国 

分 类 号：X51[环境科学与工程—环境工程] X16