2013—2017年天津市大气自净能力与大气颗粒物质量浓度特征分析

doi:10.3969/j.issn.1673-503X.2019.06.008

Abstract

Abstract: Based on the empirical formula,the spatial and temporal characteristics of atmospheric self-purification capability (APC) and concentrations of PM_2.5 and PM₁₀ were analyzed in this paper.Meanwhile,the relationship between APC and particulate concentrations were also analyzed to well understand the impact of the atmospheric environment on the pollutant concentrations.Results reveal that the highest value of the APC appears from 13:00 to 14:00 and the lowest one appears at night during a day.During the year,the APC is relatively lower during the building heating seasons from October to March than that during the non-heating seasons.Conversely,the particulate concentrations are higher during the building heating season than those during the non-heating seasons.Compared with 2013,the annual APC increased 5%,and the concentrations of PM_2.5 and PM₁₀ decreased 34% and 47%,respectively,in 2017.The APC value in the coastal area is higher than that in the inland area,and that in the urban area is lower than that in the surrounding areas.The high value of the particulate concentrations concentrates on the south-central area,especially in urban region.The spatial distributions of APC have a good relationship with that of particulate concentrations.There is a negative correlation between the daily averaged values of the APC and PM_2.5 concentration.The correlation coefficient is about -0.34,and it increases during the heating season.The heavy pollution incidents mostly happen during the low APC periods.

Key words: Atmospheric self-purification capability, PM_2.5, Ventilation coefficient

CLC Number:

X513

TANG Ying-xiao, HAN Su-qin, CAI Zi-ying, YANG Xu, FENG Jin. Feature analysis of atmospheric self-purification capability and atmospheric particulate concentration in Tianjin during 2013-2017[J]. Journal of Meteorology and Environment, 2019, 35(6): 55-66.

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Feature analysis of atmospheric self-purification capability and atmospheric particulate concentration in Tianjin during 2013-2017

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