| 厦门市冬季PM2.5污染情境识别及其与气象条件的关系 |
| |
| 引用本文： | 王一楷,张明锋,陈志彪,林广发,蒋冬升.厦门市冬季PM2.5污染情境识别及其与气象条件的关系[J].环境科学研究,2020,33(8):1758-1765. |
| |
| 作者姓名： | 王一楷 张明锋 陈志彪 林广发 蒋冬升 |
| |
| 作者单位： | 1.福建师范大学, 湿润亚热带生态地理过程教育部重点实验室, 福建 福州 350007 |
| |
| 基金项目： | 国家重点研发计划项目（No.2016YFC0502905） |
| |
| 摘 要： | 为研究厦门市冬季不同PM2.5污染情境与气象条件和气团轨迹路径特征的关系，结合PM2.5观测数据，使用AGAGE（Advanced Global Atmospheric Gases Experiment）统计方法识别2014—2018年冬季厦门市PM2.5观测值、基线值和污染值情境，通过气象数据统计和气团后向轨迹聚类对不同PM2.5污染情境下气象条件和气团轨迹路径特征进行探究.结果表明:①厦门市冬季不同PM2.5污染情境下，ρ（PM2.5）及PM2.5污染值情境时长占比均呈波动中下降的趋势，具体表现为冬季PM2.5观测值、污染值和基线值情境下，ρ（PM2.5）平均值分别从2014年的42.2、90.7、16.4 μg/m3降至2018年的26.3、56.9、8.8 μg/m3，冬季PM2.5污染值情境时长占比从2014年的10.2%降至2018年的3.0%.②冬季PM2.5污染值情境下气象要素呈低风速、低气压、高温度、高相对湿度的特征.③冬季到达厦门市的气团轨迹路径中，局地路径由于大气条件稳定易累积形成PM2.5污染；偏北路径和西北路径易从临近省份携带污染物输入导致PM2.5污染，属于重要的外源污染输入路径；沿海路径和偏西路径均属于清洁路径，但沿海路径易在福建省北部与偏北路径重合形成污染输入，加强了偏北路径的污染物输送能力.研究显示，近年来厦门市冬季PM2.5污染有明显减弱趋势，但不利的气象条件和外来污染输入仍会造成PM2.5污染的发生.
|
| 关 键 词： | 颗粒物 污染情境识别 气象条件 气团后向轨迹 |
| 收稿时间： | 2019/7/27 0:00:00 |
| 修稿时间： | 2020/1/17 0:00:00 |
Identification of PM2.5 Pollution Scenario and Its Relationship with Meteorological Conditions in Winter of Xiamen City |
| |
| WANG Yikai,ZHANG Mingfeng,CHEN Zhibiao,LIN Guangfa,JIANG Dongsheng.Identification of PM2.5 Pollution Scenario and Its Relationship with Meteorological Conditions in Winter of Xiamen City[J].Research of Environmental Sciences,2020,33(8):1758-1765. |
| |
| Authors: | WANG Yikai ZHANG Mingfeng CHEN Zhibiao LIN Guangfa JIANG Dongsheng |
| |
| Affiliation: | 1.Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou 350007, China2.School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China3.Environmental Monitoring Central Station of Fujian Province, Fuzhou 350003, China |
| |
| Abstract: | In order to investigate the different pollution scenarios of fine particulates with diameter < 2.5 μm (PM2.5) and their relationship with meteorological factors and air mass transmission pathways in the winter of 2014-2018 in Xiamen City, combined with the PM2.5 observation data, the Advanced Global Atmospheric Gases Experiment (AGAGE) statistical method was used to identify the observed baseline and pollution values of PM2.5. The characteristics of meteorological factors and air mass pathways under different pollution scenarios were explored through meteorological data statistics and air mass backward trajectory clustering. The results showed that: (1) The concentration of PM2.5 and proportion of pollution duration in Xiamen City in winter showed a downward trend in fluctuation under different pollution scenarios in winter, which was manifested by decrease of PM2.5 mean concentration from 42.2, 90.7, 16.4 μg/m3 in 2014 to 26.3, 56.9, 8.8 μg/m3 in 2018 in the scenario of observed, polluted and baseline values, respectively, and the proportion of pollution duration in winter fell from 10.2% to 3.0% from 2014 to 2018. (2) The meteorological elements of PM2.5 pollution value in winter were characterized by low wind speed, low air pressure, high temperature and high relative humidity. (3) PM2.5 pollution was easily accumulated in the local pathway due to stable atmospheric conditions, and PM2.5 pollution was easily caused by pollutants transported from adjacent provinces by northward and northwest pathway. Coastal and westward pathways were clean pathways, but coastal pathway was easy to coincide with northward pathway in northern Fujian Province, which strengthen the pollutant transport capacity of the northerly route. The research suggested that the impact of PM2.5 pollution was obviously weakened Xiamen City in recent winters, but unfavourable meteorological conditions and external pollution input still caused PM2.5 pollution. |
| |
| Keywords: | particulate matter identification for pollution scenario meteorological conditions air mass backward trajectories |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《环境科学研究》浏览原始摘要信息 |
|
点击此处可从《环境科学研究》下载全文 |
|
