基于卫星遥感与CMB模型的济南市冬季重污染过程PM2.5溯源分析

doi:10.16258/j.cnki.1674-5906.2022.06.013

生态环境学报 ›› 2022, Vol. 31 ›› Issue (6): 1175-1183.DOI: 10.16258/j.cnki.1674-5906.2022.06.013

基于卫星遥感与CMB模型的济南市冬季重污染过程PM_2.5溯源分析

魏小锋¹(), 韩红¹, 闫学军², 王在峰², 李圣增², 田勇², 梁第¹, 马明亮¹, 张桂芹¹^,³^,^*()

1.山东建筑大学市政与环境工程学院,山东济南 250101
2.山东省济南生态环境监测中心,山东济南 250101
3.山东建筑大学资源与环境创新研究院,山东济南 250101

收稿日期:2021-09-23 出版日期:2022-06-18 发布日期:2022-07-29
通讯作者: *张桂芹,女,教授,博士,主要研究方向为大气污染控制理论与技术。E-mail: zhangguiqin320@163.com
作者简介:魏小锋（1982年生）,女,讲师,博士,主要研究方向为大气环境化学。E-mail: weixf@sdjzu.edu.cn
基金资助:
济南市政府招标项目(402015202000023001);山东建筑大学博士基金项目(XNBS1310)

Source Apportionment of PM_2.5 during Heavy Pollution Process in Ji'nan Based on Satellite Remote Sensing and CMB Model

WEI Xiaofeng¹(), HAN Hong¹, YAN Xuejun², WANG Zaifeng², LI Shengzeng², TIAN Yong², LIANG Di¹, MA Mingliang¹, ZHANG Guiqin¹^,³^,^*()

1. School of Municipal and Environmental Engineering, Shandong Jianzhu University, Ji'nan 250101, P. R. China
2. Shandong Provincial Environmental Monitoring Center, Ji'nan 250101, P. R. China
3. Research Institute of Resources and Environment Innovation, Shandong Jianzhu University, Ji'nan 250101, P. R. China

Received:2021-09-23 Online:2022-06-18 Published:2022-07-29

摘要/Abstract

摘要：

济南市作为京津冀大气污染传输通道“2+26”城市之一,冬季易出现以PM_2.5为首要污染物的重污染天气。为探究济南市冬季PM_2.5重污染过程的污染成因和主要来源,以济南市冬季一次重污染过程（2020年1月1日—6日）为研究对象,基于卫星遥感、化学质量平衡（CMB）模型、潜在源贡献因子分析（PSCF）和浓度权重轨迹分析（CWT）,同时结合气态污染物和PM_2.5组分小时数据以及各项气象要素等资料,全面和综合地对济南市冬季重污染过程污染特征、本地来源、区域传输和时空演变过程进行了分析。结果表明,济南市本次重污染过程以PM_2.5为首要污染物,随着湿度升高和大气边界层高度（PBL）的降低,PM_2.5日均质量浓度达到最高211 μg∙m^-3,其中PM_2.5小时质量浓度最高达到333 μg∙m^-3;NO₃^-、SO₄^2-、NH₄⁺和有机物（OM）在PM_2.5中占比分别为30.7%、11.4%、13.9%和13.7%;重污染时段硫氧化率（SOR）和氮氧化率（NOR）平均值分别达到0.6和0.5,说明此次重污染过程主要来自于气态前体物的二次转化。CMB来源解析结果表明,二次源（硝酸盐、硫酸盐、二次有机碳）和机动车源是济南市冬季PM_2.5重污染过程的主要来源;与清洁天相比,硝酸盐的分担率和质量浓度均显著升高,分担率是清洁天的2.2倍,质量浓度是清洁天的10.5倍。本次重污染过程除济南本地污染源以外,还受山东省内德州东部、滨州西部以及济南市的商河县和济阳区等地污染气团近距离传输,以及来自西南方向的河南省东北部和安徽省西部地区的跨省输送的污染气团,途径济南市南部、泰安和济宁地区以及济南市的长清区和平阴县等地的共同影响。

关键词: 重污染过程, PM_2.5, 溯源分析, 化学质量平衡模型, 卫星遥感, 潜在源贡献因子分析, 浓度权重轨迹分析

Abstract:

Ji'nan, as the economic, political and cultural center of Shandong Province, is one of the “2+26” cities in the Beijing-Tianjin-Hebei air pollution transmission channel. Heavy pollution with PM_2.5as the primary pollutant is prone to occur in winter. To investigate the main sources of PM_2.5 during the heavy pollution process in winter in Jinan, the pollutant data were collected during a winter heavy pollution process (January 1-6 in 2020) and analyzed with satellite interpretation, Chemical Mass Balance (CMB) model, Potential Source Contribution Factor analysis (PSCF), and Concentration-weighted trajectory (CWT). Based on the hourly data of gaseous pollutants, PM_2.5 and meteorological record, the pollution characteristics, local sources, regional transmission, and spatio-temporal evolution of the heavy pollution process in Jinan city were comprehensively analyzed. The results showed that PM_2.5 was the primary pollutant during the heavy pollution process. With the increase of humidity and the decrease of Planetary Boundary Layer (PBL), the average daily concentration of PM_2.5 reached the highest as 211 μg∙m^-3, and the highest hour concentration of PM_2.5 was 333 μg∙m^-3. NO₃^-, SO₄^2-, NH₄⁺ and OM, accounting for 30.7%, 11.4%, 13.9% and 13.7% of PM_2.5, respectively. The average values of SOR and NOR reached 0.6 and 0.5, respectively, indicating that the heavy pollution process mainly came from the secondary transformation of gaseous precursors. The CMB analytical results showed that the secondary source (nitrate, sulfate, secondary organic carbon) and vehicle emission were the main sources of Ji'nan's heavy PM_2.5 pollution process during the winter. The nitrate sharing rate and concentration contribution value were 2.2 and 10.5 times the values on the non-pollutant days. Compared with the local pollution sources in Ji'nan, the heavy pollution process was also affected by the adjacent transmission of air pollution masses in eastern Dezhou, western Binzhou, Shanghe County, and Jiyang District of Ji'nan, as well as the trans-provincial transport of air pollution masses from northeast Henan province and western Anhui Province from the southwest which influenced the south of Ji'nan, Tai'an, Jining area and Ji'nan Changqing district, Pingyin county and other places.

Key words: Heavy pollution process, PM_2.5, source apportionment, Chemical Mass Balance model, Satellite remote sensing, Potential Source Contribution Factor, Concentration-weighed trajectory analysis

中图分类号:

魏小锋, 韩红, 闫学军, 王在峰, 李圣增, 田勇, 梁第, 马明亮, 张桂芹. 基于卫星遥感与CMB模型的济南市冬季重污染过程PM_2.5溯源分析[J]. 生态环境学报, 2022, 31(6): 1175-1183.

WEI Xiaofeng, HAN Hong, YAN Xuejun, WANG Zaifeng, LI Shengzeng, TIAN Yong, LIANG Di, MA Mingliang, ZHANG Guiqin. Source Apportionment of PM_2.5 during Heavy Pollution Process in Ji'nan Based on Satellite Remote Sensing and CMB Model[J]. Ecology and Environment, 2022, 31(6): 1175-1183.

图/表 6

图1 2020年1月1—6日济南市AQI、PM2.5质量浓度、湿度及PBL

Figure 1 AQI, PM2.5 concentration, RH and PBL in Ji'nan from January 1 to 6, 2020

图2 2020年1月1—6日济南市重污染过程SOR和NOR与PM2.5组分质量浓度及气象因素变化

Figure 2 Changes of SOR, NOR and PM2.5 component concentration and meteorological factors during heavy pollution in Ji'nan from January 1 to 6, 2020

图3 重污染天和清洁天各污染源浓度和分担率

Figure 3 PM2.5 concentration and share rate of pollution sources on polluted day and clean day

图4 济南市1月4日PM2.5、NO3-、NH4+和SO42-的WPSCF分布

Figure 4 Distribution of WPSCF of PM2.5, NO3-, NH4+ and SO42- in Ji'nan on January 4

图5 济南市1月4日PM2.5、NO3-、NH4+和SO42-的WCWT分布

Figure 5 Distribution of WCWT of PM2.5, NO3-, NH4+ and SO42- in Ji'nan on January 4

图6 2020年1月1—6日华北平原地区AOD分布红色框及编号为AOD高值区域

Figure 6 AOD distribution in North China Plain from January 1 to 6, 2020 The red boxes and numbers represent areas of high AOD value

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基于卫星遥感与CMB模型的济南市冬季重污染过程PM_2.5溯源分析

Source Apportionment of PM_2.5 during Heavy Pollution Process in Ji'nan Based on Satellite Remote Sensing and CMB Model

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基于卫星遥感与CMB模型的济南市冬季重污染过程PM2.5溯源分析

Source Apportionment of PM2.5 during Heavy Pollution Process in Ji'nan Based on Satellite Remote Sensing and CMB Model

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基于卫星遥感与CMB模型的济南市冬季重污染过程PM_2.5溯源分析

Source Apportionment of PM_2.5 during Heavy Pollution Process in Ji'nan Based on Satellite Remote Sensing and CMB Model