Pollution Characteristics and Sources of Carbonaceous Components in PM2.5 during Winter in Chengdu

doi:10.16258/j.cnki.1674-5906.2021.07.011

Ecology and Environment ›› 2021, Vol. 30 ›› Issue (7): 1420-1427.DOI: 10.16258/j.cnki.1674-5906.2021.07.011

• Research Articles • Previous Articles Next Articles

Pollution Characteristics and Sources of Carbonaceous Components in PM_2.5 during Winter in Chengdu

SHI Huibin¹(), HUANG Yi²^,^*(), CHENG Xin², LI Ting¹, HE Min¹, WANG Jinjin¹

1. College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China
2. College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China

Received:2021-04-28 Online:2021-07-18 Published:2021-10-09
Contact: HUANG Yi

成都市冬季PM_2.5中碳组分污染特征及来源解析

石慧斌¹(), 黄艺²^,^*(), 程馨², 李婷¹, 何敏¹, 王进进¹

1.成都理工大学地球科学学院,四川成都 610059
2.成都理工大学生态环境学院,四川成都 610059

通讯作者: 黄艺
作者简介:石慧斌（1998年生）,男,硕士研究生,主要研究方向为环境地球化学。E-mail: 1482003163@qq.com
基金资助:
国家重点研发计划项目(2018YFC0214001);四川省科技支撑计划项目(21CXTD0015)

Abstract

Abstract:

The characteristics and sources of carbonaceous components in PM_2.5 were studied in Chengdu area during a winter haze period. Samples of PM_2.5 were collected from December 7, 2019 to December 28, 2019 in Chengdu, and mass concentrations of organic carbon (OC), elemental carbon (EC) and isotopic compositions of carbon were determined using a thermal/optical carbon analyzer and elemental analyzer-isotopic mass spectrometer. The average mass concentrations of PM_2.5, OC and EC were 98.23, 14.50, 2.19 μg∙m^-3. OC was strongly correlated with EC in Chengdu (correlation coefficient=0.80), which indicated that OC and EC had either similar sources or a high mixing degree. The OC/EC ratio exceeded 2.0, which further indicated the formation of secondary organic carbon (SOC), yielding a SOC value of 34.48% of total organic carbon. Principal component analysis (PCA) of carbonaceous components in PM_2.5 indicated two overall sources. A mixed source derived from biomass combustion, coal burning and gasoline vehicle exhaust dust was the major source, contributing 59.68% overall in Chengdu area. Diesel vehicle exhaust dust was the minor source, contributing 22.40%. The results of carbon isotope composition showed that the source of carbon components in PM_2.5 was mostly related to the exhaust dust of gasoline vehicles, followed by C3 plant combustion during winter in Chengdu. Results from modeling software IsoSource, showed the following component relations: exhaust dust of gasoline vehicles>C3 plant combustion>diesel vehicle exhaust dust>Coal burning>C4 plant combustion>natural geological sources. Compared to low PM_2.5 clean periods, the exhaust dust of gasoline vehicles and C3 plant combustion accounted for a larger proportion during the haze period. These research results will help to develop effective air pollution control measures in Chengdu.

Key words: organic carbon (OC), elemental carbon (EC), secondary organic carbon (SOC), source analysis, carbon isotope

摘要：

为研究成都市冬季PM_2.5中碳组分的污染特征和来源,于2019年12月7—28日在成都市进行PM_2.5的采集,并利用热光碳分析仪和元素分析仪-同位素质谱仪分别测定了样品中有机碳（OC）和元素碳（EC）的质量浓度以及碳同位素的组成特征。结果表明,成都市PM_2.5、OC和EC的平均质量浓度分别为98.23、14.50、2.19 μg∙m^-3;OC和EC的相关性较高（相关系数为0.80）,表明OC和EC可能具有一致的来源,也有可能是具有较高的混合程度;OC/EC比值大于2.0,表明成都市冬季有二次有机碳（SOC）的形成,且SOC/OC的比值为34.48%;主成分分析结果显示,生物质燃烧、燃煤和汽油车尾气尘混合源是成都市冬季PM_2.5碳组分的主要来源,贡献率为59.68%;其次是柴油车尾气尘,贡献率为22.40%;碳同位素组成结果显示,成都市冬季PM_2.5碳组分的来源与汽油车尾气排放相关性最强,其次为C3植物燃烧;通过IsoSource模型软件进行计算,可知不同时期各污染源的贡献比例均呈现出汽油车尾气排放>C3植物燃烧>柴油车尾气排放>燃煤>C4植物燃烧>地质源（农业土壤、扬尘）的规律,但相较于清洁期来说,污染期的汽油车尾气排放和C3植物燃烧污染源所占比例增大。研究结果可为成都市大气污染治理提供理论指导。

关键词: 有机碳, 元素碳, 二次有机碳, 来源解析, 碳同位素

CLC Number:

X131.1

SHI Huibin, HUANG Yi, CHENG Xin, LI Ting, HE Min, WANG Jinjin. Pollution Characteristics and Sources of Carbonaceous Components in PM_2.5 during Winter in Chengdu[J]. Ecology and Environment, 2021, 30(7): 1420-1427.

石慧斌, 黄艺, 程馨, 李婷, 何敏, 王进进. 成都市冬季PM_2.5中碳组分污染特征及来源解析[J]. 生态环境学报, 2021, 30(7): 1420-1427.

Figures/Tables 7

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采样点 Site	采样时间 Date	ρ_(OC)/(μg∙m^-3)	ρ_(EC)/(μg∙m^-3)	ρ_(OC)/ρ_(EC)	ρ_(SOC)/ρ_(OC)/%	参考文献 Reference
成都 Chengdu	2019冬 2019 winter	14.50	2.19	6.62	34.48	This research
成都 Chengdu	2013冬 2013 winter	20.7	7.5	3.1	-	史芳天等, 2020 (Shi et al., 2020)
北京 Beijing	2017冬 2017 winter	23.98	5.02	4.39	48.09	张俊峰等, 2020 (Zhang et al., 2020)
石家庄 Shijiazhuang	2017冬 2017 winter	35.75	9.22	3.85	44.98	张俊峰等, 2020 (Zhang et al., 2020)
天津 Tianjin	2013冬 2013 winter	19.3	4.5	4.7	35.75	史国良等, 2016 (Shi et al., 2016)
上海 Shanghai	2010冬 2010 winter	11.8	3.0	3.94	39.40	张懿华等, 2014 (Zhang et al., 2014)
广州 Guangzhou	2001冬 2001 winter	22.6	8.3	2.7	49.60	Cao et al., 2003
深圳 Shenzhen		13.2	6.1	2.2	40.70
珠海 Zhuhai		12.2	5.0	2.5	48.30
兰州 Lanzhou	2012冬 2012 winter	35.39	13.80	2.58	22.46	李英红, 2015 (Li, 2015)
西安 Xian	2012冬 2012 winter	47.8	8.5	5.8	21.60	田鹏山等, 2016 (Tian et al., 2016)

采样点 Site	采样时间 Date	ρ_(OC)/(μg∙m^-3)	ρ_(EC)/(μg∙m^-3)	ρ_(OC)/ρ_(EC)	ρ_(SOC)/ρ_(OC)/%	参考文献 Reference
成都 Chengdu	2019冬 2019 winter	14.50	2.19	6.62	34.48	This research
成都 Chengdu	2013冬 2013 winter	20.7	7.5	3.1	-	史芳天等, 2020 (Shi et al., 2020)
北京 Beijing	2017冬 2017 winter	23.98	5.02	4.39	48.09	张俊峰等, 2020 (Zhang et al., 2020)
石家庄 Shijiazhuang	2017冬 2017 winter	35.75	9.22	3.85	44.98	张俊峰等, 2020 (Zhang et al., 2020)
天津 Tianjin	2013冬 2013 winter	19.3	4.5	4.7	35.75	史国良等, 2016 (Shi et al., 2016)
上海 Shanghai	2010冬 2010 winter	11.8	3.0	3.94	39.40	张懿华等, 2014 (Zhang et al., 2014)
广州 Guangzhou	2001冬 2001 winter	22.6	8.3	2.7	49.60	Cao et al., 2003
深圳 Shenzhen		13.2	6.1	2.2	40.70
珠海 Zhuhai		12.2	5.0	2.5	48.30
兰州 Lanzhou	2012冬 2012 winter	35.39	13.80	2.58	22.46	李英红, 2015 (Li, 2015)
西安 Xian	2012冬 2012 winter	47.8	8.5	5.8	21.60	田鹏山等, 2016 (Tian et al., 2016)

组分变量 Variables	因子1 Factor 1	因子2 Factor 2
OC1	0.976	0.181
OC2	0.964	0.215
OC3	0.902	0.330
OC4	0.469	0.583
EC1^a	0.897	0.278
EC2	-0.062	0.805
EC3	0.405	0.733
OPC	0.940	0.043
特征值 Characteristic value	4.77	1.79
方差贡献 Contribution rate of Variance	59.68%	22.40%
累积方差 Contribution rate of accumulated Variance	59.68%	82.08%

组分变量 Variables	因子1 Factor 1	因子2 Factor 2
OC1	0.976	0.181
OC2	0.964	0.215
OC3	0.902	0.330
OC4	0.469	0.583
EC1^a	0.897	0.278
EC2	-0.062	0.805
EC3	0.405	0.733
OPC	0.940	0.043
特征值 Characteristic value	4.77	1.79
方差贡献 Contribution rate of Variance	59.68%	22.40%
累积方差 Contribution rate of accumulated Variance	59.68%	82.08%

来源 Sources	δ13C_TC/‰	参考文献 Reference
柴油车尾气 The exhaust of diesel vehicles	-25.23±0.35	陈颖军等, 2012 (Chen et al., 2012)
汽油车尾气 The exhaust of gasoline vehicles	-27.0±0.92	张建强等, 2012 (Zhang et al., 2012)
地质源（农业土壤、扬尘） The geological sources (Agricultural soil, ground dust)	-20.7±1.5	Lόpez-Veneroni, 2009
C4植物 The C4 plant combustion	-20.9±0.8	Martinelli et al., 2002
C3植物 The C3 plants combustion	-26.99±1.11	陈颖军等, 2012 (Chen et al., 2012)
燃煤 The coal burning	-23.63±0.44	陈颖军等, 2012 (Chen et al., 2012)