引用本文:孟丽红,蔡子颖,李英华,等.天津市PM2.5浓度时空分布特征及重污染过程来源模拟分析[J].环境科学研究,2020,(1):9-17.
MENG Lihong,CAI Ziying,LI Yinghua,et al.Spatial and Temporal Distributions and Source Simulation during Heavy Pollution of PM2.5 in Tianjin City[J].Research of Environmental Sciences,2020,(1):9-17.]
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天津市PM2.5浓度时空分布特征及重污染过程来源模拟分析
孟丽红1, 蔡子颖2, 李英华1, 郝囝1, 王雪莲1
1. 天津市气象科学研究所, 天津 300074;2. 天津市环境气象中心, 天津 300074
摘要:
天津市多发生以PM2.5为首要污染物的重污染事件,明确ρ(PM2.5)时空分布特征及重污染过程来源对PM2.5的综合治理意义深远.利用天津市2014-2017年环境资料和2016年气象资料,结合WRF-Chem模式研究了天津市ρ(PM2.5)时空分布特征及重污染过程来源.结果表明:①自2014年以来,天津市ρ(PM2.5)呈逐年下降趋势.②ρ(PM2.5)月变化曲线呈"U"型分布,呈冬春季高、夏秋季低的季节性特征;ρ(PM2.5)日变化呈双峰型分布,主峰值出现在08:00-09:00,次峰值出现在21:00-翌日00:00.③各季节天津市ρ(PM2.5)空间分布不同,春季、夏季、秋季和冬季高值中心分别位于天津市西南部的静海区、中心城区北部的北辰区、西部的武清区及北部的蓟州区.④WRF-Chem模式模拟的天津市秋冬季污染物来源结果表明,本地源贡献率为56%,外来源输送贡献率为44%,其中以河北省和山东省的输送为主.2016年12月16-22日天津市一次重污染过程的模拟结果表明,天津市本地源贡献率为49.6%,河北省、北京市和山东省的外来源输送贡献率分别为32.2%、7.0%和2.2%.污染前期,不利气象条件和外来源输送造成天津市ρ(PM2.5)聚集并形成重度污染;污染持续过程中,本地源贡献率逐渐增大并占主导地位.研究显示,近年来天津市ρ(PM2.5)呈下降趋势,并有明显的空间分布特征.
关键词:  PM2.5  时空分布  区域输送  天津市
DOI:10.13198/j.issn.1001-6929.2019.08.14
分类号:X513
基金项目:天津市自然科学基金项目(No.17JCQNJC08200,16JCYBJC21500);天津市气象局项目(No.201718ybxm12)
Spatial and Temporal Distributions and Source Simulation during Heavy Pollution of PM2.5 in Tianjin City
MENG Lihong1, CAI Ziying2, LI Yinghua1, HAO Jian1, WANG Xuelian1
1. Tianjin Institute of Meteorological Science, Tianjin 300074, China;2. Tianjin Environmental Meteorological Centre, Tianjin 300074, China
Abstract:
Heavy pollution of primary pollutant PM2.5 occurs in Tianjin City many times every year. Therefore, to control PM2.5 comprehensively, we must clarify the spatial and temporal distributions and source characteristics of PM2.5. Based on the PM2.5 concentration data at all monitoring sites in Tianjin City from 2014 to 2017 and the meteorological data in 2016, the spatial and temporal distributions of PM2.5 were analyzed. Meanwhile, the PM2.5 source during the heavy pollution were simulated by using the WRF-Chem model. The results showed that the PM2.5 concentration in Tianjin City decreased year by year since 2014. The PM2.5 concentration varied monthly in a U-shaped curve, and the value was higher in winter and spring, lower in autumn and summer respectively. The PM2.5 concentration varied daily in a doublet curve, and the peak value occurred in 08:00-09:00 and 21:00-24:00, respectively. The spatial distribution of PM2.5 concentration in Tianjin City was different in different seasons. The peak value of PM2.5 concentration occurred in Jinghai District in spring, Beichen District in summer, Wuqing District in autumn, and Jizhou District in winter, respectively. The WRF-Chem model was used to simulate the sources of PM2.5. The results showed that the contribution of local and external sources was 56% and 44%, respectively. The main transport contributions were from Hebei Province and Shandong Province. During a heavy pollution process from December 16th to 22nd, 2016, the regional transportation was obvious. Before the beginning of heavy pollution, the static weather situation and the transportation from outlet region caused the accumulation of pollutants. With the pollution continuously, the contribution of external sources decreased, while the contribution of local pollution sources gradually dominated. Regional transport had a very important impact on PM2.5 concentration in Tianjin City. This study showed that the concentration of PM2.5 in Tianjin City decreased gradually and had obviously spatial and temporal distributions. The combined air pollution control measures in Beijing-Tianjin-Hebei Region are more effective to prevent and control the pollution in Tianjin City.
Key words:  PM2.5  spatial and temporal distribution  regional transportation  Tianjin City