IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i6p2340-d1355496.html
   My bibliography  Save this article

Characteristics of PM 2.5 Chemical Species in 23 Chinese Cities Identified Using a Vehicular Platform

Author

Listed:
  • Hui Chen

    (Key Laboratory of Organic Compound Pollution Control Engineering, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China)

  • Jingjing Liu

    (Key Laboratory of Organic Compound Pollution Control Engineering, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China)

  • Peizhi Wang

    (Key Laboratory of Organic Compound Pollution Control Engineering, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China)

  • Xiao Lin

    (Key Laboratory of Organic Compound Pollution Control Engineering, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China)

  • Jingjin Ma

    (Ecological Environment Internet of Things and Big Data Application Technology National Engineering Research Center, Shijiazhuang 050035, China
    Hebei Advanced Environmental Protection Industry Innovation Center Co., Ltd., Shijiazhuang 050035, China)

  • Chunying Wang

    (Ecological Environment Internet of Things and Big Data Application Technology National Engineering Research Center, Shijiazhuang 050035, China
    Hebei Advanced Environmental Protection Industry Innovation Center Co., Ltd., Shijiazhuang 050035, China)

Abstract

PM 2.5 pollution remains a significant concern in China due to its adverse environmental and health implications. This study aims to explore in depth the differences in the causes of PM 2.5 pollution between some regions in China based on high temporal resolution PM 2.5 component information. We used a particulate matter chemical composition vehicle (PMCCV) as a mobile monitoring platform which travelled among 23 cities in China from March 2018 to December 2019 to collect PM 2.5 concentrations and chemical composition data. Observations revealed that PM 2.5 concentrations were notably higher in northern cities compared than their southern counterparts. Seasonal variation was evident, with peak concentrations during winter and troughs during summer. In regions experiencing severe winter pollution, such as Hebei and Shanxi (HB/SX), organic matter (OM) emerged as the dominant contributor (47.3%), escalating with increasing PM 2.5 concentrations. OM significantly impacted PM 2.5 levels during autumn in Jiangxi and Anhui (AH/JX) and across the monitoring period in Liuzhou, Guangxi (GX), with the former related to vehicle emissions and the latter related to bagasse reuse and biomass burning emissions. Conversely, nitrate (NO 3 − ) made the highest contribution to PM 2.5 during winter in the AH/JX region (34.4%), which was attributed to reduced SO 2 levels and favorable low-temperature conditions conducive to nitrate condensation. Notably, nitrate contribution to HB/SX rose notably in heavily polluted winter conditions and during light–moderate pollution episodes in the autumn. Sulfate (SO 4 2− ) was dominant among PM 2.5 components during summer in the study regions (29.9% in HB/SX, 36.1% in HN/SD, and 49.7% in AH/JX). Additionally, pollution incidents in Chuzhou, Anhui Province, and Baoding, Hebei Province, underscored nitrates and organic matter, respectively, as the primary causes of sharp PM 2.5 increases. These incidents highlighted the influence of large emissions of primary aerosols, gaseous precursors, and stagnant meteorological conditions as pivotal factors driving haze pollution in the HB/SX region.

Suggested Citation

  • Hui Chen & Jingjing Liu & Peizhi Wang & Xiao Lin & Jingjin Ma & Chunying Wang, 2024. "Characteristics of PM 2.5 Chemical Species in 23 Chinese Cities Identified Using a Vehicular Platform," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2340-:d:1355496
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/6/2340/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/6/2340/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiannan Wu & Pan Zhang & Hongtao Yi & Zhao Qin, 2016. "What Causes Haze Pollution? An Empirical Study of PM 2.5 Concentrations in Chinese Cities," Sustainability, MDPI, vol. 8(2), pages 1-14, January.
    2. Ru-Jin Huang & Yanlin Zhang & Carlo Bozzetti & Kin-Fai Ho & Jun-Ji Cao & Yongming Han & Kaspar R. Daellenbach & Jay G. Slowik & Stephen M. Platt & Francesco Canonaco & Peter Zotter & Robert Wolf & Sim, 2014. "High secondary aerosol contribution to particulate pollution during haze events in China," Nature, Nature, vol. 514(7521), pages 218-222, October.
    3. Jie Yang & Xinran Fu & Liping Qiao & Lan Yao & Fei Zhang & Weiyue Li, 2023. "Characteristics of Atmospheric Pollution in a Chinese Megacity: Insights from Three Different Functional Areas," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huan Wang & Zhenyu Chen & Pan Zhang, 2022. "Spatial Autocorrelation and Temporal Convergence of PM 2.5 Concentrations in Chinese Cities," IJERPH, MDPI, vol. 19(21), pages 1-11, October.
    2. Shi, Wenxiao & Lin, Chen & Chen, Wei & Hong, Jinglan & Chang, Jingcai & Dong, Yong & Zhang, Yanlu, 2017. "Environmental effect of current desulfurization technology on fly dust emission in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1-9.
    3. Yi Yang & Jie Li & Guobin Zhu & Qiangqiang Yuan, 2019. "Spatio–Temporal Relationship and Evolvement of Socioeconomic Factors and PM 2.5 in China During 1998–2016," IJERPH, MDPI, vol. 16(7), pages 1-24, March.
    4. Lili Guo & Yuting Song & Mengqian Tang & Jinyang Tang & Bright Senyo Dogbe & Mengying Su & Houjian Li, 2022. "Assessing the Relationship among Land Transfer, Fertilizer Usage, and PM 2.5 Pollution: Evidence from Rural China," IJERPH, MDPI, vol. 19(14), pages 1-18, July.
    5. Yu Zhang & Jiayu Wu & Chunyao Zhou & Qingyu Zhang, 2019. "Installation Planning in Regional Thermal Power Industry for Emissions Reduction Based on an Emissions Inventory," IJERPH, MDPI, vol. 16(6), pages 1-13, March.
    6. Jingchao, Zhang & Kotani, Koji & Saijo, Tatsuyoshi, 2018. "Public acceptance of environmentally friendly heating in Beijing: A case of a low temperature air source heat pump," Energy Policy, Elsevier, vol. 117(C), pages 75-85.
    7. Ruiqing Ma & Yeyue Zhang & Yini Zhang & Xi Li & Zheng Ji, 2023. "The Relationship between the Transmission of Different SARS-CoV-2 Strains and Air Quality: A Case Study in China," IJERPH, MDPI, vol. 20(3), pages 1-17, January.
    8. Zeng, Jingjing & Liu, Ting & Feiock, Richard & Li, Fei, 2019. "The impacts of China's provincial energy policies on major air pollutants: A spatial econometric analysis," Energy Policy, Elsevier, vol. 132(C), pages 392-403.
    9. Zhang, Pan, 2019. "Do energy intensity targets matter for wind energy development? Identifying their heterogeneous effects in Chinese provinces with different wind resources," Renewable Energy, Elsevier, vol. 139(C), pages 968-975.
    10. Jie Yang & Pengfei Liu & Hongquan Song & Changhong Miao & Feng Wang & Yu Xing & Wenjie Wang & Xinyu Liu & Mengxin Zhao, 2021. "Effects of Anthropogenic Emissions from Different Sectors on PM 2.5 Concentrations in Chinese Cities," IJERPH, MDPI, vol. 18(20), pages 1-13, October.
    11. Kun Liu & Xuemin Liu & Zihao Wu, 2024. "Nexus between Corporate Digital Transformation and Green Technological Innovation Performance: The Mediating Role of Optimizing Resource Allocation," Sustainability, MDPI, vol. 16(3), pages 1-21, February.
    12. Diyi Liu & Kun Cheng & Kevin Huang & Hui Ding & Tiantong Xu & Zhenni Chen & Yanqi Sun, 2022. "Visualization and Analysis of Air Pollution and Human Health Based on Cluster Analysis: A Bibliometric Review from 2001 to 2021," IJERPH, MDPI, vol. 19(19), pages 1-15, October.
    13. Deguang Li & Zhicheng Ding & Jianghuan Liu & Qiurui He & Hamad Naeem, 2022. "Exploring Spatiotemporal Dynamics of PM 2.5 Emission Based on Nighttime Light in China from 2012 to 2018," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    14. Aboubakar Gasirabo & Chen Xi & Baligira R. Hamad & Umwali Dufatanye Edovia, 2023. "A CA–Markov-Based Simulation and Prediction of LULC Changes over the Nyabarongo River Basin, Rwanda," Land, MDPI, vol. 12(9), pages 1-20, September.
    15. Wenbo Chen & Fuqing Zhang & Saiwei Luo & Taojie Lu & Jiao Zheng & Lei He, 2022. "Three-Dimensional Landscape Pattern Characteristics of Land Function Zones and Their Influence on PM 2.5 Based on LUR Model in the Central Urban Area of Nanchang City, China," IJERPH, MDPI, vol. 19(18), pages 1-18, September.
    16. Xuan Sun & Wenting Yang & Tao Sun & Ya Ping Wang, 2018. "Negative Emotion under Haze: An Investigation Based on the Microblog and Weather Records of Tianjin, China," IJERPH, MDPI, vol. 16(1), pages 1-15, December.
    17. Guangzhi Qi & Zhibao Wang & Zhixiu Wang & Lijie Wei, 2022. "Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    18. Mao Mao & Xiaolin Zhang & Yan Yin, 2018. "Particulate Matter and Gaseous Pollutions in Three Metropolises along the Chinese Yangtze River: Situation and Implications," IJERPH, MDPI, vol. 15(6), pages 1-29, May.
    19. Yucong Miao & Shuhua Liu & Li Sheng & Shunxiang Huang & Jian Li, 2019. "Influence of Boundary Layer Structure and Low-Level Jet on PM 2.5 Pollution in Beijing: A Case Study," IJERPH, MDPI, vol. 16(4), pages 1-14, February.
    20. Yu Song & Bingrui Liu & Xiaohong Chen & Jia Liu, 2020. "Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-Based Weighted Co-Word Analysis," IJERPH, MDPI, vol. 17(3), pages 1-16, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2340-:d:1355496. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.