摘要
基于2015年9月1日至2016年8月25日杭州城区观测点PM1、PM2.5、PM10小时浓度数据进行分析,利用HYSPLIT模型、潜在源贡献因子(PSCF)方法和浓度权重轨迹(CWT)方法,探讨了杭州城区PM1、PM2.5、PM10时间分布特征和PM2.5潜在来源。结果表明:研究期间PM1季节平均浓度表现为冬季>秋季、春季>夏季,PM1~2.5、PM2.5~10浓度则表现为冬季>春季>秋季>夏季;PM1浓度日变化呈现明显的双峰现象,而PM1~2.5和PM2.5~10在同一时段均无明显浓度峰值;杭州城区PM2.5受外源输送污染具有明显的季节性变化特征,夏季、秋季杭州城区PM2.5的潜在源区主要是浙江北部、安徽东南部等,春季PM2.5的潜在源区主要是浙江中部、江苏南部等,冬季PM2.5的潜在源区主要是山东南部、江苏西南部、浙江北部、安徽南部、江西中部等地区。
In this study,air mass concentration data from September 1,2015 to August 25,2016 were used to analyze temporal characteristics of PM1,PM2.5 and PM10 in Hangzhou.The HYSPLIT model was used to analyze the 48-hour backward trajectories.And the potential source contribution function and concentration-weighted trajectory analysis were applied to evaluate the transport pathways and sources of PM2.5 in Hangzhou.The results showed the order of the seasonal mean concentrations of PM1 was winter>autumn,spring>summer.The order of the seasonal mean concentrations of PM1-2.5 and PM2.5-10 was winter>spring>autumn>summer.The significant diurnal variation of PM1 displayed a bimodal pattern,while PM1-2.5 and PM2.5-10 have no obvious concentration peaks at the same time.The main potential sources of PM2.5 in Hangzhou during and autumn summer are located in northern Zhejiang and southeastern Anhui.The main potental sources of PM2.5 during spring are Located in the central Zhejiang and southern Jiangsu.The main potential sources of PM2.5 during winter are located in the south of Shandong,southwestern Jiangsu,northern Zhejiang,southern Anhui,and central Jiangxi.
作者
蒋琦清
陈文聪
徐冰烨
王琼真
吴建
JIANG Qiqing;CHEN Wencong;XU Bingye;WANG Qiongzhen;WU Jian(Environmental Science Research&Design Institute of Zhejiang Province,Hangzhou 310007,China;The Affiliated School of the College of Education Zhejiang University,Hangzhou 310051,China;Zhejiang Province Environmental Monitoring Centre,Hangzhou 310012,China)
出处
《中国环境监测》
CAS
CSCD
北大核心
2020年第5期88-95,共8页
Environmental Monitoring in China
基金
国家重点研发计划项目(2018YFC0213806)
浙江省环保科研项目(2017A013)。
关键词
大气颗粒物
污染特征
潜在源贡献因子
浓度权重轨迹
杭州
atmospheric particulates
temporal characteristics
potential source contribution function(PSCF)
concentrationweighted trajectory(CWT)
Hangzhou