基于Model-3/CMAQ和CAMx模式的台州市PM_(2.5)数值模拟研究

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英文篇名：Numerical study of PM_(2.5) pollution in Taizhou based on Model-3/CMAQ and CAMx 作者：汪辉 ; 刘强 ; 王昱 ; 李颖 ; 张定定 ; 朱赟洁 ; 洪盼盼 英文作者：WANG Hui;LIU Qiang;WANG Yu;LI Ying;ZHANG Dingding;ZHU Yunjie;HONG Panpan;The Engineering Technology Center of Pollution Control in Taizhou;Nanjing CLIMBLUE Technology Co.,LTD; 关键词：台州 ; PM_(2.5) ; CMAQ ; CAMx ; 污染特征 ; 区域传输 英文关键词：Taizhou;;PM_(2.5);;CMAQ;;CAMx;;pollution characteristics;;regional transport 中文刊名：环境与可持续发展 英文刊名：Environment and Sustainable Development 机构：台州市污染防治工程技术中心;南京创蓝科技有限公司; 出版日期：2019-06-16 出版单位：环境与可持续发展 年：2019 期：03 基金：台州市环保局重大项目(HK-2017-0078) 语种：中文; 页：95-98 页数：4 CN：11-5337/X ISSN：1673-288X 分类号：X513

摘要

为探究沿海城市大气细颗粒物污染特征,应用气象模式WRF耦合空气质量模式CMAQ和CAMx对台州市2016年PM_(2.5)空间分布特征及区域污染贡献情况进行分析。结果表明,2016年PM_(2.5)模拟值与监测值变化趋势基本一致,模拟效果较好。PM_(2.5)平均浓度从高到低依次为冬季>春季>秋季>夏季,空间分布呈现"两边低中间高"态势,与地形分布特征相似,高值区出现在人口稠密的城区附近。PM_(2.5)具有明显的区域污染传输特征,2016年台州本地贡献率为34.7%,外来源贡献率为65.3%。另外,PM_(2.5)还具有明显的季节性变化特征,本地贡献最小的时间段是春季,贡献最大的时间段是秋季。
        To investigate the pollution characteristics of fine particulate matter in the coastal city,the research adopted Weather Research and Forecasting Model(WRF) in combination with Congestion Mitigation and Air Quality Model(CMAQ) and CAMx to analyze the spatial distribution characteristics,contribution of regional pollution of PM_(2.5) in Taizhou City for the year 2016.According to the result,the simulation value and the monitoring value change trend were basically consistent.PM_(2.5) concentration in winter was obviously higher than that in spring,autumn and summer.The spatial distribution of PM_(2.5) in central area was higher than that in west area and east area,and was similar to the features of topographic distribution.The high concentration of PM_(2.5) occured in densely populated urban areas.The results indicated significant contribution of regional transport to ambient PM_(2.5) pollution.Taizhou's local contribution rate was 34.7% in 2016,and the external source contribution rate was 65.3%.In addition,PM_(2.5) air pollution in Taizhou City illustrated obvious seasonal variation.The period for lowest and highest contribution rate was spring and autumn in Taizhou.

引文

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