Pollution characteristics and sources analysis of carbon components in PM<sub>2.5</sub> in winter at typical coastal cities of China

YU Tao; LIU Yani; REN Lihong; YANG Xiaoyang; GAO Yuanguan; LI Gang; ZHANG Jiahao; CHEN Zhuojiong

doi:10.7524/j.issn.0254-6108.2020091503

2022 Volume 41 Issue 1

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YU Tao, LIU Yani, REN Lihong, YANG Xiaoyang, GAO Yuanguan, LI Gang, ZHANG Jiahao, CHEN Zhuojiong. Pollution characteristics and sources analysis of carbon components in PM2.5 in winter at typical coastal cities of China[J]. Environmental Chemistry, 2022, 41(1): 113-124. doi: 10.7524/j.issn.0254-6108.2020091503

Citation:

YU Tao, LIU Yani, REN Lihong, YANG Xiaoyang, GAO Yuanguan, LI Gang, ZHANG Jiahao, CHEN Zhuojiong. Pollution characteristics and sources analysis of carbon components in PM_2.5 in winter at typical coastal cities of China[J]. Environmental Chemistry, 2022, 41(1): 113-124. doi: 10.7524/j.issn.0254-6108.2020091503

Pollution characteristics and sources analysis of carbon components in PM_2.5 in winter at typical coastal cities of China

1.
Lanzhou University of Technology, Lanzhou, 730050, China
2.
Chinese Academy of Environmental Sciences, Beijing, 100012, China

Corresponding author: REN Lihong, renlh@craes.org.cn ;
Received Date: 15/09/2020
Available Online: 27/01/2022

Fund Project: Basic Scientific Research Funds in Nation Nonprofit Institutes of the Chinese Research Academy of Environmental Sciences (2019YSKY-025, JY-41375133) and National Natural Science Foundation of China (41705136)

Abstract

To investigate the pollution characteristics and sources of carbonaceous species in PM_2.5, samples were collected at three sites simultaneously from Dec.5, 2018 to Jan.30, 2019 in Tianjin (TJ), Shanghai(SH) and Qingdao(QD). The result showed that the average mass concentrations of PM_2.5 were （116.96± 66.93）, （31.21±25.62）μg·m⁻³ and （74.93 ±54.60 ）μg·m⁻³. The spatial distribution of OC and EC shows the order of TJ (18.69 ±7.65）μg·m⁻³, （4.98 ±2.08 ）μg·m⁻³) > QD (16.45 ±8.94）μg·m⁻³, （2.01 ±1.04） μg·m⁻³)> SH (7.28 ±3.11）μg·m⁻³, （1.05 ±1.25） μg·m⁻³). The good correlation between OC and EC indicated the similar OC and EC sources. The OC/EC ratios were 2.37—7.53, 5.47—46.41 and 4.77—13.36 at TJ, SH and QD, respectively, showing that SOC exists at all sampling sites. The SOC concentration was estimated by MRS (minimum r squared method). The average mass concentrations of SOC at three sampling sites were （5.09±4.68）, （3.90±1.65） and （4.21±4.31） μg·m⁻³, accounting for 27.2%, 55.8% and 19.5% of the OC, respectively. Among them, the secondary carbonaceous pollution in SH is the most serious, and which is caused by severe pollution emissions and favorable meteorological conditions benefitting the secondary organic carbon formation, while carbon components in TJ and QD mainly comes from the primary emission. PCA analysis shows that the carbon components of PM_2.5 at TJ are mainly from coal combustion, biomass combustion and motor vehicle exhaust, while at SH they are mainly from biomass combustion, road dust and motor vehicle exhaust. The carbon components at QD mainly come from road dust, motor vehicle exhaust and diesel vehicle exhaust. The backward trajectory analysis shows that the air mass from the northwest has a great influence on TJ, and the concentrations of PM_2.5 and carbon components are the largest, while for the sties at SH and QD, the concentrations of carbon components and PM_2.5 originating from the air mass in the middle of Hebei Province are the highest, indicating that the two cities are more affected by the transport of the surrounding areas.
- typical cities,
- PM_2.5,
- carbon component,
- minimum R² squared method (MRS),
- source analysis

References

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Pollution characteristics and sources analysis of carbon components in PM_2.5 in winter at typical coastal cities of China

Corresponding author: REN Lihong, renlh@craes.org.cn ;

Received Date: 15/09/2020

Available Online: 27/01/2022

Fund Project: Basic Scientific Research Funds in Nation Nonprofit Institutes of the Chinese Research Academy of Environmental Sciences (2019YSKY-025, JY-41375133) and National Natural Science Foundation of China (41705136)

Key words:

Abstract: To investigate the pollution characteristics and sources of carbonaceous species in PM_2.5, samples were collected at three sites simultaneously from Dec.5, 2018 to Jan.30, 2019 in Tianjin (TJ), Shanghai(SH) and Qingdao(QD). The result showed that the average mass concentrations of PM_2.5 were （116.96± 66.93）, （31.21±25.62）μg·m⁻³ and （74.93 ±54.60 ）μg·m⁻³. The spatial distribution of OC and EC shows the order of TJ (18.69 ±7.65）μg·m⁻³, （4.98 ±2.08 ）μg·m⁻³) > QD (16.45 ±8.94）μg·m⁻³, （2.01 ±1.04） μg·m⁻³)> SH (7.28 ±3.11）μg·m⁻³, （1.05 ±1.25） μg·m⁻³). The good correlation between OC and EC indicated the similar OC and EC sources. The OC/EC ratios were 2.37—7.53, 5.47—46.41 and 4.77—13.36 at TJ, SH and QD, respectively, showing that SOC exists at all sampling sites. The SOC concentration was estimated by MRS (minimum r squared method). The average mass concentrations of SOC at three sampling sites were （5.09±4.68）, （3.90±1.65） and （4.21±4.31） μg·m⁻³, accounting for 27.2%, 55.8% and 19.5% of the OC, respectively. Among them, the secondary carbonaceous pollution in SH is the most serious, and which is caused by severe pollution emissions and favorable meteorological conditions benefitting the secondary organic carbon formation, while carbon components in TJ and QD mainly comes from the primary emission. PCA analysis shows that the carbon components of PM_2.5 at TJ are mainly from coal combustion, biomass combustion and motor vehicle exhaust, while at SH they are mainly from biomass combustion, road dust and motor vehicle exhaust. The carbon components at QD mainly come from road dust, motor vehicle exhaust and diesel vehicle exhaust. The backward trajectory analysis shows that the air mass from the northwest has a great influence on TJ, and the concentrations of PM_2.5 and carbon components are the largest, while for the sties at SH and QD, the concentrations of carbon components and PM_2.5 originating from the air mass in the middle of Hebei Province are the highest, indicating that the two cities are more affected by the transport of the surrounding areas.

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大气细颗粒物（PM_2.5）对全球空气质量和人类健康都有重要的作用。碳组分是PM_2.5的主要组成成分之一^[1] ，主要包括有机碳（OC）和元素碳（EC）及少量的碳酸盐酸（CC），其中 CC 含量不超过总碳（TC）的5%，故不考虑^[2-3]。一般认为EC为惰性污染物，主要来自燃料的不完全燃烧，由污染源直接排放，环境中的EC主要分为焦炭(Char-EC)和烟炱(Soot-EC) 2个部分^[4-5]，Char-EC定义为燃料燃烧后固体残渣中的EC，Soot-EC定义为燃烧后气相挥发物质再凝结形成的EC。OC包括一次有机碳（POC）和二次有机碳（SOC）^[6-8]。有研究表明，大气中85%的EC和82%的OC均富集于PM_2.5中^[9]。OC和EC对大气消光和人体健康等都产生重要影响^[10-12]。其中EC具有石墨样的结构，是光吸收的主要贡献者^[13]；OC可以散射光，并与EC一起对云的性质产生影响，从而对辐射强迫产生影响^[14]，因此对碳组分的研究一直是国内外研究热点^[15]。李立伟等^[16]研究了京津冀区域PM_2.5中碳组分污染特征，发现京津冀区域有显著的SOC生成。徐少才等^[17]对青岛市PM_2.5化学组分特征研究发现PM_2.5中占比较高的是碳组分且存在SOC污染。张懿华等^[18]对上海城区PM_2.5中OC和EC进行了研究，发现生物质燃烧、燃煤排放以及道路尘是上海城区PM_2.5中碳组分的主要来源。Ryou等^[19]对韩国PM₁₀和PM_2.5的来源研究发现机动车和二次气溶胶是韩国PM_2.5影响最大的来源。Park等^[20]对北京、首尔和长崎PM_2.5及其化学成分特征研究发现要在东亚地区实施有效的PM_2.5减排计划，应同时考虑PM_2.5的长距离输送来源和本地来源。

由于人类在沿海地区进行如海上运输、港口作业和建筑活动等频繁活动，许多关于PM_2.5组成和来源的研究已在沿海城市进行^[21]。天津不仅是华北地区的超大城市之一，也是重要的港口城市，近些年天津作为“京津冀一体化”大气污染联防联控的重要一环，大气污染状况一直是关注的热点^[22];而位于长江三角洲入海口的上海既是中国南方特大商业和工业城市，也是世界上最大的港口之一^[23]。青岛是东部沿海地区重要的度假旅游城市，虽然主城区的PM_2.5颗粒物研究时间较早^[24]。但总体而言，目前，对中国沿海地区的研究均只集中在其中某一区域（如京津冀、长三角和珠三角），或只是单纯的针对某一个城市的浓度、来源解析以及对人体健康影响等方面的研究^[25-26]，对北方和南方城市进行多点位同步观测研究十分有限^[27-29]，不能完全反映PM_2.5中碳组分整体污染特征，对碳组分来源及形成机制的认识还不够充分。本次研究的3个典型沿海城市分别为北方的天津和青岛以及南方的上海，天津和青岛是我国北方重要的工业城市，近年来随着城市经济和交通运输快速发展，大气环境压力增大。上海是一个人口稠密且经济发达的超大型城市，其环境空气质量的变化与人们的生活密切相关，备受关注。

本研究于2018年12月5日—2019年1月30日，对中国典型沿海城市（天津、上海和青岛）3个站点PM_2.5滤膜样品同步进行采集和分析，对比研究PM_2.5中OC、EC的浓度水平及污染特征、结合SOC的污染特征，同时利用PCA、后向轨迹对碳组分的来源及传输路径进行分析。研究结果将有助于全面地了解中国典型沿海城市PM_2.5中碳组分的演变特征，对大气污染防治工作提供参考依据。

1. 材料与方法 (Materials and methods)

1.1. 采样时间和地点

本研究于2018年12月5日—2019年1月30日，在中国3个典型沿海城市天津、上海和青岛城市的3个采样点对PM_2.5同步开展滤膜采样，采样时段为每日10:00—次日 09:00，每日各采集1个样品，共采集有效 PM_2.5 样品113个，其中天津33个、上海30个和青岛50个。各采样点的详细描述见表1。

1.2. 采样仪器与方法

采样仪器选用国产武汉天虹TH16-A型四通道采样器进行采样，采样流量为每个通道16.7 L·min⁻¹。在每个受体采样点位放置1台采样器采样，一台采样器有4个通道，同时采集2个PM_2.5和2个PM₁₀样品，其中两张特氟龙膜（P膜）采集PM_2.5和PM₁₀的无机元素，两张石英滤膜（Q膜）采集PM_2.5和PM₁₀的碳组分和水溶性离子。采样前将Q膜以 800 ℃在马弗炉中烘焙2 h，冷却至室温后放入恒温恒湿箱中平衡72 h。采样前后滤膜的称重使用精度为十万分之一（10 μg）的电子天平进行称量，且天平室温度应维持在15—35 ℃之间，相对湿度<40%。滤膜称量前须经过静电消除器去除静电，并做到快速称重滤膜，称量1次后，再次放入干燥器内，隔24 h进行第2次称重，每次称重滤膜至衡重，结果精确至0.1 mg并保证2次称量之差不大于0.5 mg即为衡重。样品采集完毕后将采完样品的滤膜先放置玻璃干燥器中，当需称重时重复空白滤膜的称重程序，计算两次的称重差，做浓度的计算。

碳组分分析使用热/光碳气溶胶分析仪（Sunset Laboratory Inc，美国），采用热光透射法（Thermal-optical transmission，TOT），遵循美国EPA推荐的NIOSH 4050分析方法^[30-31]，分别得到OC的4个组分（OC1、OC2、OC3、OC4）和EC的3个组分（EC1、EC2、EC3），其中OC被定义为 OC1+OC2+OC3+OC4+OPC, EC 定义为 EC1+EC2+EC3-OPC^[32-33]。Han等^[34]的研究，将EC分为Char-EC和Soot-EC，Char-EC 定义为 EC1-OPC，Soot-EC定义为EC2+EC3。

1.3. 质量保证与质量控制

（1）样品分析前后，采用 CH₄/CO₂标准气体对仪器进行校正；

（2）每15个样品中随机抽出 1个进行平行分析，每周进行2次标准样品的测量，标准样品的回收率为98%—102%；

（3）每周测量仪器的系统空白以及实验室空白。

3. 结论（Conclusion）

（1）采样期间中国3个典型沿海城市PM_2.5浓度的空间分布差异明显，天津、上海和青岛PM_2.5的平均质量浓度为（116.96± 66.93）、（31.21 ± 25.62）、（74.93 ±54.60 ）μg·m⁻³， PM_2.5的日均浓度超标率分别为66.7%、6. 7%和34.0%，这表明中国典型城市整体大气污染较为严重。3个站点OC的质量浓度分别为（18.69±7.95）、（7.28±3.11）、（16.45±8.94） μg·m⁻³，EC的质量浓度分别为（4.98±2.08）、（1.05±1.25）、（2.01±1.04）μg·m⁻³，OC和EC的空间分布均为天津>青岛>上海。Char-EC与EC浓度变化趋势一致，而Soot-EC浓度日变化较小。天津、上海和青岛等3个城市总碳的占比分别为24.8%、22.1%和31.3%, 表明碳组分是PM_2.5的重要组成部分。

（2）相关性分析表明，3个采样点冬季PM_2.5中OC和EC二者相关性均较强，说明OC和EC的来源一致。中国典型沿海城市3个站点OC/EC比值范围在2.37—7.53，5.47—46.41和4.77—13.36之间，可初步证明各采样点均存在SOC；采用最小R²法对各站点的SOC进行估算，天津、上海和青岛的3个采样点SOC的平均质量浓度为（5.09±4.68）、（3.90 ±1.65）、（4.21 ±4.31） μg·m⁻³，分别占OC总量的27.2%、55.8%和19.5%。天津和青岛的SOC在OC中的占比较小，表明这两个城市的碳组分主要来自污染源的直接排放，而上海的SOC在OC中的占比最大，高达56.2%，表明本地区的二次污染严重。

（3）PCA分析结果表明，天津PM_2.5中碳组分主要来源于道路尘、生物质燃烧和机动车尾气，上海PM_2.5中碳组分主要来源于生物质燃烧、道路扬尘和机动车尾气。青岛PM_2.5中碳组分主要来源于道路扬尘和机动车尾气。

（4）后向轨迹聚类结果表明，来自西北方向的远距离传输对天津的影响较大，PM_2.5浓度和碳组分的浓度最大；而对上海而言，主要受北方气溶胶经过海面又传输回上海的气团的影响；青岛站点主要受华北地区污染物和本地排放源的影响。

Figure (5) Table (4) Reference (55)

Pollution characteristics and sources analysis of carbon components in PM_2.5 in winter at typical coastal cities of China