京津冀地区典型城市大气细颗粒物碳质组分污染特征及来源

张俊峰; 韩力慧; 程水源; 王晓琦; 张晗宇

doi:10.13198/j.issn.1001-6929.2020.02.12

京津冀地区典型城市大气细颗粒物碳质组分污染特征及来源

doi: 10.13198/j.issn.1001-6929.2020.02.12

北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124

基金项目:

国家重点研发计划重点专项 2018YFC0213206

北京市科技计划项目 Z181100005418017

详细信息

作者简介:
张俊峰(1992-), 男, 安徽安庆人, zjf16@emails.bjut.edu.cn

通讯作者:
程水源(1958-), 男, 北京人, 教授, 博士, 博导, 主要从事区域大气环境规划与管理研究, chengsy@bjut.edu.cn

中图分类号: X513
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出版历程
- 收稿日期: 2019-08-19
- 修回日期: 2020-01-17
- 刊出日期: 2020-08-25

Characteristics and Sources of Carbon Pollution of Fine Particulate Matter in Typical Cities in Beijing-Tianjin-Hebei Region

Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China

Funds:

National Key Research and Development Program of China 2018YFC0213206

Science and Technology of Beijing, China Z181100005418017

摘要

摘要: 为研究京津冀地区典型城市大气细颗粒物及其碳质组分的时空变化特征及来源，于2016年12月28日—2017年1月22日及2017年7月1—26日，对北京市与石家庄市PM_2.5（细颗粒物）及PM₁（亚微米颗粒物）进行采集，使用DRI（热光碳分析仪）检测PM_2.5与PM₁中ρ（OC）与ρ（EC），并对其碳质组分来源进行分析.结果表明：①采样期间，冬、夏两季PM_2.5与PM₁中ρ（OC）均为石家庄市采样点远高于北京市采样点；冬季PM_2.5与PM₁中ρ（EC）均为石家庄市采样点高于北京市采样点，夏季则略有不同.②冬季污染日，北京市采样点ρ（PM_2.5）与ρ（PM₁）均为石家庄市采样点的1.08倍，PM_2.5与PM₁中的ρ（OC）分别为石家庄市采样点的1.14和1.12倍，石家庄市采样点PM_2.5与PM₁中ρ（EC）分别为北京市采样点的1.15和1.28倍；冬季重污染日，北京市采样点的ρ（PM_2.5）与ρ（PM₁）分别为石家庄市采样点的1.03和1.04倍，PM_2.5和PM₁中的ρ（OC）分别为石家庄市采样点的1.23和1.22倍，石家庄市采样点PM_2.5和PM₁中的ρ（EC）分别为北京市采样点的1.03和1.16倍.夏季污染日，石家庄市采样点ρ（PM_2.5）与ρ（PM₁）分别为北京市采样点的1.16和1.30倍，PM_2.5与PM₁中ρ（OC）分别为北京市采样点的1.64和2.71倍，两个采样点ρ（EC）相近.③冬、夏两季PM_2.5与PM₁中ρ（SOC）/ρ（OC）均较高，冬季北京市采样点分别为48.09%和54.29%，石家庄市采样点分别为44.98%和48.09%，夏季北京市采样点分别为48.47%和61.50%，石家庄市采样点分别为61.52%和63.55%，表明SOC更易富集于亚微米粒子中.④冬季北京市和石家庄市两个采样点PM_2.5与PM₁中碳质组分均主要来源于生物质燃烧、燃煤和机动车尾气；夏季北京市采样点PM_2.5与PM₁中碳质组分主要来源于机动车尾气，石家庄市采样点PM_2.5与PM₁中碳质组分主要来源于燃煤和机动车尾气.研究显示，北京市和石家庄市两个采样点大气细颗粒物及其碳质组分浓度存在时空分布和污染来源差异.
- 京津冀地区 /
- 碳质组分 /
- PM_2.5 /
- PM₁ /
- OC /
- EC /
- 来源分析
Abstract: In order to investigate the spatial-temporal distribution and sources of fine particulate matter and its carbonaceous components in typical cities of Beijing-Tianjin-Hebei Region, daily samples of PM_2.5 (fine particles) and PM₁ (submicron particles) were collected and analyzed from December 26^th, 2016 to January 22^nd, 2017 and from July 1^st, 2017 to July 26^th, 2017 in Beijing and Shijiazhuang. ρ(OC) and ρ(EC) were measured by DRI (thermo-optic carbon analyzer). The results indicated that the ρ(OC) of PM_2.5 and PM₁ in Shijiazhuang was higher than that in Beijing in both seasons. As for ρ(EC), the winter value of Shijiazhuang was greater than that of Beijing, while the summer value was different. On polluted winter days, the ρ(PM_2.5) and ρ(PM₁) in Beijing were 1.08 times higher than those in Shijiazhuang. The ρ(OC) of PM_2.5 and PM₁ in Beijing was 1.14 and 1.12 times of Shijiazhuang. The ρ(EC) of Shijiazhuang was 1.15 and 1.28 times of Beijing. On heavy polluted days, the ρ(PM_2.5) and ρ(PM₁) of Beijing was 1.03 and 1.04 times of Shijiazhuang. The ρ(OC) of Beijing was 1.23 and 1.22 times of Shijiazhuang, while the ρ(EC) of Shijiazhuang was 1.03 and 1.16 times of Beijing. In summer, ρ(PM_2.5) and ρ(PM₁) on polluted days of Shijiazhuang was 1.16 and 1.30 times of Beijing, ρ(OC) was 1.64 and 2.71 times, while the ρ(EC) was similar to Beijing. The ratios of ρ(SOC) to ρ(OC) in PM_2.5 and PM₁ during winter were 48.09% and 54.29% in Beijing, respectively, while the ratios were 44.98% and 48.09% in Shijiazhuang. In summer, they were 48.47% and 61.50% in Beijing, while 61.52% and 63.55% in Shijiazhuang, which indicated the SOC was more easily enriched in submicron particles. Biomass burning, coal consumption, vehicles exhaust and diesel emissions were the four main sources of carbonaceous in PM_2.5 and PM₁ in the two cities in winter. In the summer of Beijing, vehicles exhaust was the main source of emissions. As for Shijiazhuang, coal consumption and vehicle exhaust were the biggest contributors. The results showed that the particulate matter and its carbon component concentrations were significantly different in the two cities.
- Beijing-Tianjin-Hebei Region /
- carbon components /
- PM_2.5 /
- PM₁ /
- OC /
- EC /
- source analysis

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图 1 北京市与石家庄市采样点不同季节ρ(PM_2.5)与ρ(PM₁)的分布情况

Figure 1. Concentration and distribution of PM_2.5 and PM₁ at sampling points in Beijing and Shijiazhuang in different seasons

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图 2 采样期间北京市和石家庄市采样点各气象要素的变化特征

Figure 2. Variation characteristics of meteorological elements at sampling points in Beijing and Shijiazhuang during sampling period

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图 3 采样期间PM_2.5与PM₁中ρ(OC)、ρ(EC)及OC/EC

注：采样期间因天气原因或仪器故障导致个别数据缺失.

Figure 3. The mass concentration and ratio of OC and EC in PM_2.5 and PM₁ in sampling period

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表 1 京津冀地区PM_2.5中ρ(OC)与ρ(EC)汇总

Table 1. Concentrations of OC and EC in PM_2.5 in the Beijing-Tianjin-Hebei Region

城市	采样点	时间	ρ(OC)/(μg/m³)	ρ(EC)/(μg/m³)	ρ(PM_2.5)/(μg/m³)	数据来源
北京市	北京师范大学	2017年冬季	23.98	5.02	116.96	该研究
北京市	北京师范大学	2017年夏季	6.22	3.26	50.62	该研究
石家庄市	石家庄市环境监测中心	2017年冬季	35.75	9.22	220.41	该研究
石家庄市	石家庄市环境监测中心	2017年夏季	7.31	2.54	76.91	该研究
北京市	北京市西三环交通带附近	2016年冬季	22.70±5.87	9.01±3.73	130.45±20.78	文献[22]
北京市	北京市西三环交通带附近	2015年夏季	6.22±3.46	2.13±0.58	78.78±12.00	文献[22]
石家庄市	市区	2013年冬季	41.2	8.59	193.4	文献[23]
北京市	市区	2010年冬季	26.8	7.1	126.5	文献[24]
北京市	市区	2009年夏季	10.1	5.9	115.8	文献[24]
石家庄市	市区	2010年冬季	46.5±29.1	12.1±7.1	227.2±148.7	文献[24]
石家庄市	市区	2009年夏季	9.1±2.5	7.6±2.1	145.7±48.5	文献[24]
承德市	市区	2010年冬季	33.6±24.1	13.1±3.9	123.3±63.5	文献[24]
承德市	市区	2009年夏季	10.5±1.8	4.5±0.8	67.8±35.2	文献[24]
北京市	北京市环境保护监测中心	2013年冬季	24.8	2.5		文献[25]
		2013年夏季	14.8	1.8
		2014年冬季	24.1	3.5
		2014年夏季	11.6	1.6
北京市	北京师范大学	2012年夏季	7.0±2.2	3.0±1.4	76.2±38.5	文献[26]
唐山市	唐山市环境监测中心站	2012年夏季	11.7±6.3	7.0±5.0	97.7±38.8	文献[26]
天津市	天津市大气边界层	2010年冬季	24.85±18.45	6.99±3.64	116.70±93.40	文献[27]
天津市	气象观测站	2009年夏季	12.70±3.29	5.90±1.59	160.45±60.34	文献[27]

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表 2 不同污染程度下PM_2.5与PM₁中SOC质量浓度及占比

Table 2. Mass concentration and proportion of SOC in PM_2.5 and PM₁ under different pollution levels

项目			PM_2.5中			PM₁中
项目			ρ(SOC)/(μg/m³)	(SOC/OC)/%	(SOC/PM_2.5)/%	ρ(SOC)/(μg/m³)	(SOC/OC)/%	(SOC/PM₁)/%
北京市采样点	冬季	清洁日	3.69	52.76	13.32	3.55	57.01	17.11
		污染日	18.15	43.90	8.15	16.22	52.17	9.09
		重污染日	20.55	42.20	7.76	18.12	50.59	8.49
		平均值	10.90	48.09	10.97	8.25	54.29	13.21
	夏季	清洁日	3.45	48.47	12.44	2.36	61.46	11.29
		污染日	6.29	48.50	8.07	2.74	61.65	11.69
		平均值	4.64	48.47	11.60	2.42	61.50	11.36
石家庄市采样点	冬季	污染日	10.53	40.86	10.14	10.35	45.77	10.99
		重污染日	18.56	46.53	7.31	14.01	50.21	7.61
		平均值	16.37	44.98	8.09	13.01	48.09	7.81
	夏季	清洁日	4.72	59.96	8.41	3.23	66.59	9.66
		污染日	6.10	42.77	6.23	3.51	56.39	7.93
		平均值	5.50	61.52	7.20	3.26	63.55	9.06

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表 3 不同季节碳质组分主成分分析

Table 3. Principal component analysis of carbon in different seasons

项目	组分	冬季				夏季
		PM_2.5		PM₁		PM_2.5			PM₁
		因子1	因子2	因子1	因子2	因子1	因子2	因子3	因子1	因子2	因子3
北京市采样点	OC1	0.968	-0.230	0.981	-0.141	0.217	0.743	0.489	0.661	0.820	-0.391
	OC2	0.975	-0.204	0.983	-0.144	0.946	-0.089	-0.163	0.914	-0.093	-0.100
	OC3	0.965	-0.194	0.979	-0.164	0.818	0.152	-0.226	0.515	0.582	-0.249
	OC4	0.618	0.679	0.700	-0.357	0.917	0.228	0.125	0.448	-0.662	-0.278
	OP	0.905	-0.406	0.960	-0.075	0.581	-0.394	0.162	0.454	0.417	0.416
	EC1	0.936	-0.342	0.971	-0.097	0.857	0.160	-0.377	0.829	0.037	0.007
	EC2	0.826	0.510	0.789	0.564	0.492	-0.382	0.718	0.652	-0.625	0.073
	EC3	0.720	0.631	0.73	0.564	-0.169	0.775	0.034	0.480	-0.017	0.750
	解释变量/%	76.21	19.17	79.98	10.58	47.42	19.54	12.72	41.10	19.09	13.03
石家庄市采样点	OC1	0.773	-0.558	0.938	-0.208	0.387	0.840	-0.042	0.190	0.942	0.104
	OC2	0.866	-0.457	0.981	-0.140	-0.354	0.287	0.693	0.419	-0.295	0.738
	OC3	0.833	-0.463	0.858	0.004	0.944	0.019	0.184	0.911	-0.072	-0.221
	OC4	0.650	-0.411	0.157	0.821	0.625	0.534	0.008	0.758	0.264	-0.487
	OP	0.760	0.515	0.911	-0.139	0.895	0.166	-0.088	0.906	0.182	0.037
	EC1	0.739	0.525	0.944	-0.110	0.556	0.672	0.178	0.863	-0.323	-0.002
	EC2	0.475	0.756	0.400	0.687	0.696	-0.578	0.301	0.125	0.874	0.369
	EC3	0.611	0.559	0.207	0.752	-0.210	-0.259	-0.619	-0.560	0.332	-0.291
	解释变量/%	52.34	29.09	56.58	22.56	45.81	19.24	12.87	43.88	25.76	13.28

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