IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i12p7201-d837012.html
   My bibliography  Save this article

Multivariate Statistical Analysis for the Detection of Air Pollution Episodes in Chemical Industry Parks

Author

Listed:
  • Xiangyu Zhao

    (College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
    Institute of Zhejiang University-Quzhou, Quzhou 324000, China)

  • Kuang Cheng

    (College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
    Institute of Zhejiang University-Quzhou, Quzhou 324000, China)

  • Wang Zhou

    (College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
    Institute of Zhejiang University-Quzhou, Quzhou 324000, China)

  • Yi Cao

    (College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
    Institute of Zhejiang University-Quzhou, Quzhou 324000, China)

  • Shuang-Hua Yang

    (College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
    Institute of Zhejiang University-Quzhou, Quzhou 324000, China)

Abstract

Air pollution episodes (APEs) caused by excessive emissions from chemical industry parks (CIPs) have resulted in severe environmental damage in recent years. Therefore, it is of great importance to detect APEs timely and effectively using contaminant measurements from the air quality monitoring network (AQMN) in the CIP. Traditionally, APE can be detected by determining whether the contaminant concentration at any ambient monitoring station exceeds the national environmental standard. However, the environmental standards used are unified in various ambient monitoring stations, which ignores the source–receptor relationship in the CIP and challenges the effective detection of excessive emissions in some scenarios. In this paper, an approach based on a multivariate statistical analysis (MSA) method is proposed to detect the APEs caused by excessive emissions from CIPs. Using principal component analysis (PCA), the spatial relationships hidden among the historical environmental monitoring data are extracted, and the high-dimensional data are projected into only two subspaces. Then, two monitoring indices, T 2 and Q , which represent the variability in these subspaces, are utilized to monitor the pollution status and detect the potential APEs in the CIP. In addition, the concept of APE detectability is also defined, and the condition for APE detectability is derived, which explains when the APEs can be detectable. A simulated case for a CIP in Zhejiang province of China is studied to evaluate the performance of this approach. The study indicates that the method can have an almost 100% APE detection rate. The real-world measurements of Total Volatile Organic Compounds (TVOC) at a 10-min time interval from 3 December 2020∼12 December 2020 are also analyzed, and 64 APEs caused by excessive TVOC emissions are detected in a total of 1440 time points.

Suggested Citation

  • Xiangyu Zhao & Kuang Cheng & Wang Zhou & Yi Cao & Shuang-Hua Yang, 2022. "Multivariate Statistical Analysis for the Detection of Air Pollution Episodes in Chemical Industry Parks," IJERPH, MDPI, vol. 19(12), pages 1-21, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7201-:d:837012
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/12/7201/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/12/7201/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jie Zeng & Guilin Han & Qixin Wu & Yang Tang, 2019. "Heavy Metals in Suspended Particulate Matter of the Zhujiang River, Southwest China: Contents, Sources, and Health Risks," IJERPH, MDPI, vol. 16(10), pages 1-16, May.
    2. Zhengqiu Zhu & Bin Chen & Genserik Reniers & Laobing Zhang & Sihang Qiu & Xiaogang Qiu, 2017. "Playing Chemical Plant Environmental Protection Games with Historical Monitoring Data," IJERPH, MDPI, vol. 14(10), pages 1-23, September.
    3. Zhengqiu Zhu & Bin Chen & Sihang Qiu & Rongxiao Wang & Feiran Chen & Yiping Wang & Xiaogang Qiu, 2018. "An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries," IJERPH, MDPI, vol. 15(4), pages 1-20, March.
    4. Tavoos Hassan Bhat & Guo Jiawen & Hooman Farzaneh, 2021. "Air Pollution Health Risk Assessment (AP-HRA), Principles and Applications," IJERPH, MDPI, vol. 18(4), pages 1-22, February.
    5. Chaofeng Shao & Juan Yang & Xiaogang Tian & Meiting Ju & Lei Huang, 2013. "Integrated Environmental Risk Assessment and Whole-Process Management System in Chemical Industry Parks," IJERPH, MDPI, vol. 10(4), pages 1-22, April.
    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. Bin Chen & Zhengqiu Zhu & Feiran Chen & Yong Zhao & Xiaogang Qiu, 2019. "Strategically Patrolling in a Chemical Cluster Addressing Gas Pollutants’ Releases through a Game-Theoretic Model," IJERPH, MDPI, vol. 16(4), pages 1-18, February.
    2. Zhengqiu Zhu & Bin Chen & Sihang Qiu & Rongxiao Wang & Feiran Chen & Yiping Wang & Xiaogang Qiu, 2018. "An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries," IJERPH, MDPI, vol. 15(4), pages 1-20, March.
    3. Yanzhuo Liu & Shanshan Song & Chunjuan Bi & Junli Zhao & Di Xi & Ziqi Su, 2019. "Occurrence, Distribution and Risk Assessment of Mercury in Multimedia of Soil-Dust-Plants in Shanghai, China," IJERPH, MDPI, vol. 16(17), pages 1-19, August.
    4. Wenxiang Zhou & Guilin Han & Man Liu & Chao Song & Xiaoqiang Li & Fairda Malem, 2020. "Vertical Distribution and Controlling Factors Exploration of Sc, V, Co, Ni, Mo and Ba in Six Soil Profiles of The Mun River Basin, Northeast Thailand," IJERPH, MDPI, vol. 17(5), pages 1-14, March.
    5. Hooman Farzaneh & Mehrnoosh Dashti & Eric Zusman & So-Young Lee & Damdin Dagvadorj & Zifei Nie, 2022. "Assessing the Environmental-Health-Economic Co-Benefits from Solar Electricity and Thermal Heating in Ulaanbaatar, Mongolia," IJERPH, MDPI, vol. 19(11), pages 1-19, June.
    6. Zhengqiu Zhu & Bin Chen & Genserik Reniers & Laobing Zhang & Sihang Qiu & Xiaogang Qiu, 2017. "Playing Chemical Plant Environmental Protection Games with Historical Monitoring Data," IJERPH, MDPI, vol. 14(10), pages 1-23, September.
    7. Jie Zeng & Guilin Han & Shitong Zhang & Qian Zhang, 2022. "Suspended Sediments Quality Assessment in a Coastal River: Identification of Potentially Toxic Elements," IJERPH, MDPI, vol. 19(7), pages 1-14, April.
    8. Nurulkamal Masseran, 2022. "Multifractal Characteristics on Temporal Maximum of Air Pollution Series," Mathematics, MDPI, vol. 10(20), pages 1-15, October.
    9. Xiao-Wen Qi & Jun-Ling Zhang & Shu-Ping Zhao & Chang-Yong Liang, 2017. "Tackling Complex Emergency Response Solutions Evaluation Problems in Sustainable Development by Fuzzy Group Decision Making Approaches with Considering Decision Hesitancy and Prioritization among Asse," IJERPH, MDPI, vol. 14(10), pages 1-35, October.
    10. Akmaral Agibayeva & Rustem Khalikhan & Mert Guney & Ferhat Karaca & Aisulu Torezhan & Egemen Avcu, 2022. "An Air Quality Modeling and Disability-Adjusted Life Years (DALY) Risk Assessment Case Study: Comparing Statistical and Machine Learning Approaches for PM 2.5 Forecasting," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    11. Xia Liu & Yejun Xu & Yao Ge & Weike Zhang & Francisco Herrera, 2019. "A Group Decision Making Approach Considering Self-Confidence Behaviors and Its Application in Environmental Pollution Emergency Management," IJERPH, MDPI, vol. 16(3), pages 1-15, January.
    12. Qianru Man & Lijuan Xu & Mingfang Li, 2022. "Source Identification and Health Risk Assessment of Heavy Metals in Soil: A Case Study of Lintancang Plain, Northeast China," IJERPH, MDPI, vol. 19(16), pages 1-17, August.

    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:jijerp:v:19:y:2022:i:12:p:7201-:d:837012. 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.