| 长三角地区一次区域污染过程中细颗粒物的来源解析及其光学特性 |
| 摘要点击 3033 全文点击 813 投稿时间：2020-06-08 修订日期：2020-08-13 |
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| 中文关键词 长三角 细颗粒物 气象要素 消光系数 来源解析 |
| 英文关键词 Yangtze River Delta fine particle meteorological elements light extinction coefficient source apportionment |
| 作者 | 单位 | E-mail | | 夏丽 | 南京信息工程大学气象灾害教育部重点实验室, 气候与环境变化国际合作联合实验室, 气象灾害预报预警与评估协同创新中心, 中国气象局气溶胶与云降水重点开发实验室, 南京 210044
南京信息工程大学大气与环境实验教学中心, 国家综合气象观测专项试验外场, 南京 210044 | xialixf@163.com | | 朱彬 | 南京信息工程大学气象灾害教育部重点实验室, 气候与环境变化国际合作联合实验室, 气象灾害预报预警与评估协同创新中心, 中国气象局气溶胶与云降水重点开发实验室, 南京 210044
南京信息工程大学大气与环境实验教学中心, 国家综合气象观测专项试验外场, 南京 210044 | binzhu@nuist.edu.cn | | 王红磊 | 南京信息工程大学气象灾害教育部重点实验室, 气候与环境变化国际合作联合实验室, 气象灾害预报预警与评估协同创新中心, 中国气象局气溶胶与云降水重点开发实验室, 南京 210044 | | | 康汉青 | 南京信息工程大学气象灾害教育部重点实验室, 气候与环境变化国际合作联合实验室, 气象灾害预报预警与评估协同创新中心, 中国气象局气溶胶与云降水重点开发实验室, 南京 210044 | |
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| 中文摘要 |
| 为研究长三角地区细颗粒物污染的分布特征及其光学特性，选择在城市（苏州）、郊区（南京）和区域背景站（临安）同时进行PM2.5采集并进行化学分析.这次污染过程中，苏州、南京和临安的PM2.5平均浓度分别达到（169.8±56.5）、（169.9±51.2）和（154.0±54.9）μg·m-3.散度系数分析显示3个站点气象要素和PM2.5化学成分的差异较小，PM2.5污染呈现同步性和区域化特征.利用化学成分法估算的消光系数在苏州、南京和临安分别是（561±223）、（655±340）和（679±349） Mm-1，与能见度法估算的消光系数之间相关度较高（r为0.73~0.80）.利用PMF模型解析PM2.5的污染来源，二次硝酸（32%）和二次硫酸（25%）的占比最大，其次是生物质燃烧（16%）、不完全燃烧源（7%）、燃料燃烧（7%）、土壤地壳源（8%）和海洋源（5%）.对PM2.5消光系数的主要贡献源是二次生成的硝酸硫酸源、不完全燃烧和生物质燃烧源.与质量浓度的源贡献相比，二次硝酸硫酸源的占比降低了约4%，不完全燃烧源的贡献增加了5%，说明PM2.5的各类源对其质量浓度和消光系数的贡献效率存在差别. |
| 英文摘要 |
| In order to study the distribution and optical characteristics of fine particulate matter pollution in the Yangtze River Delta, PM2.5 samples were collected and analyzed from city (Suzhou), suburb (Nanjing), and regional background monitoring stations (Lin'an). The average concentrations of PM2.5 in Suzhou, Nanjing, and Lin'an were (169.8±56.5), (169.9±51.2), and (154.0±54.9) μg·m-3, respectively. There was little difference in meteorological conditions and the chemical composition of PM2.5 among the three sites, and PM2.5 pollution showed significant synchronization and regionalization characteristics. The extinction coefficients estimated using a chemical component method for Suzhou, Nanjing, and Lin'an are (561±223), (655±340), and (679±349) Mm-1, respectively. There is strong correlation between the extinction coefficients estimated by the chemical component method and those estimated by a visibility-based method (r 0.73-0.80). Using a PMF model to analyze the PM2.5 sources, secondary nitrate sources (32%) and secondary sulfate sources (25%) accounted for the largest proportions followed by biomass combustion (16%), incomplete combustion (7%), fuel combustion (7%), soil crusts (8%), and marine sources (5%). The primary sources of the extinction coefficients of PM2.5 are secondary nitrate and sulfate sources, incomplete combustion, and biomass combustion. Compared with the source contribution of mass concentrations, the proportion of secondary nitrate and sulfate sources decreased by approximately 4% and the proportion of the incomplete combustion source increased by 5%. These results show that there are differences in the contributions of various PM2.5 source according to mass concentrations and extinction coefficients. |
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