研究报告
王文丁,陈焕盛,吴其重,韦莲芳,王自发,李成,陈多宏,蒋争明,吴文威.珠三角冬季PM2.5重污染区域输送特征数值模拟研究[J].环境科学学报,2016,36(8):2741-2751
珠三角冬季PM2.5重污染区域输送特征数值模拟研究
- Numerical study of PM2.5 regional transport over Pearl River Delta during a winter heavy haze event
- 基金项目：国家科技支撑计划项目（No.2014BAC21B02）；国家自然科学基金（No.41405119）；环保公益性行业科研专项（No.201509014）；中国科学院战略性先导项目（No.XDB05030200,XDB05030101）
- 作者
- 单位
- 王文丁
- 1. 中国科学院大气物理研究所, 大气边界层物理和大气化学国家重点实验室, 北京 100029;2. 中国科学院大学, 北京 100049
- 陈焕盛
- 中国科学院大气物理研究所, 大气边界层物理和大气化学国家重点实验室, 北京 100029
- 吴其重
- 北京师范大学, 北京 100875
- 韦莲芳
- 1. 中国科学院大气物理研究所, 大气边界层物理和大气化学国家重点实验室, 北京 100029;2. 中国科学院大学, 北京 100049
- 王自发
- 中国科学院大气物理研究所, 大气边界层物理和大气化学国家重点实验室, 北京 100029
- 李成
- 华南理工大学, 广州 510006
- 陈多宏
- 广东省环境监测站, 广州 510308
- 蒋争明
- 中山市环境监测站, 中山 528400
- 吴文威
- 中山市环境监测站, 中山 528400
- 摘要：利用嵌套网格空气质量模式系统（NAQPMS）及其耦合的污染来源追踪模块，针对2013年1月珠三角区域的PM2.5重污染过程输送特征进行了数值模拟研究.结果表明，污染气团首先形成于广州、佛山地区，并在弱偏北风的作用下南移加强，影响整个珠三角区域.重污染期间，广州（64.9%）、佛山（58.9%）的PM2.5主要来自本地贡献，是区域输送最主要的来源地区；中山（51.9%）、珠海（66.2%）的PM2.5主要来自外来贡献，是区域输送主要的受体地区.重污染期间，广州和佛山对中山的PM2.5日均贡献率之和总体保持在25%以上，污染最重时达到40%.交通（26%）、工业（24%）、扬尘（16%）、火力发电（15%）和生物质燃烧（8%）是对中山贡献最大的5类源：工业源中山本地与外来输送贡献率基本相当；交通和扬尘源以中山本地贡献为主，贡献率分别为55%和67%；火力发电和生物质燃烧源以外来输送为主，贡献率分别为56%和62%.各类排放源的外来输送中，以广州、佛山所占的比例最大.
- Abstract：The Nested Air Quality Prediction Model System (NAQPMS) was employed with an online source-tagging module to simulate a heavy haze episode over the Pearl River Delta (PRD) in January 2013 and to quantify the intercity transport of PM2.5. The results showed that the polluted air mass was initially generated over Guangzhou and Foshan, and then transported southward by weak northerly winds to affect the whole PRD. During the haze episode, PM2.5 in Guangzhou and Foshan was mainly from local emissions, accounting for 64.9% and 58.9%, respectively, and these cities were the major sources for regional transport. PM2.5 in Zhongshan and Zhuhai was mainly from surrounding areas, accounting for 51.9% and 66.2%, respectively, and these cities were major receptors of regional transport. During this pollution episode, Guangzhou and Foshan contributed to more than 25% of daily PM2.5 concentrations in Zhongshan, and more than 40% on the most polluted days. Transportation, industry, fugitive dust, power plants and biomass burning were the five major emission categories affecting PM2.5 concentrations in Zhongshan, accounting for 26%, 24%, 16%, 15% and 8%, respectively. The contributions from local and regional industry were similar. Emissions from transportation and fugitive dust were mainly local, accounting for 55% and 67%, respectively. The contributions of power plants and biomass burning were mainly regional, accounting for 56% and 62%, respectively. For all five major emission categories, Guangzhou and Foshan were the main contributors to PM2.5 transported to Zhongshan.
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