IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i16p2820-d255599.html
   My bibliography  Save this article

Understanding the Spatial-Temporal Patterns and Influential Factors on Air Quality Index: The Case of North China

Author

Listed:
  • Wenxuan Xu

    (School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
    Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China)

  • Yongzhong Tian

    (School of Geographical Sciences, Southwest University, Chongqing 400715, China)

  • Yongxue Liu

    (School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)

  • Bingxue Zhao

    (School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)

  • Yongchao Liu

    (School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
    Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China)

  • Xueqian Zhang

    (School of Geographical Sciences, Southwest University, Chongqing 400715, China)

Abstract

North China has become one of the worst air quality regions in China and the world. Based on the daily air quality index (AQI) monitoring data in 96 cities from 2014–2016, the spatiotemporal patterns of AQI in North China were investigated, then the influence of meteorological and socio-economic factors on AQI was discussed by statistical analysis and ESDA-GWR (exploratory spatial data analysis-geographically weighted regression) model. The principal results are as follows: (1) The average annual AQI from 2014–2016 exceeded or were close to the Grade II standard of Chinese Ambient Air Quality (CAAQ), although the area experiencing heavy pollution decreased. Meanwhile, the positive spatial autocorrelation of AQI was enhanced in the sample period. (2) The occurrence of a distinct seasonal cycle in air pollution which exhibit a sinusoidal pattern of fluctuations and can be described as “heavy winter and light summer.” Although the AQI generally decreased in other seasons, the air pollution intensity increased in winter with the rapid expansion of higher AQI value in the southern of Hebei and Shanxi. (3) The correlation analysis of daily meteorological factors and AQI shows that air quality can be significantly improved when daily precipitation exceeds 10 mm. In addition, except for O 3 , wind speed has a negative correlation with AQI and major pollutants, which was most significant in winter. Meanwhile, pollutants are transmitted dynamically under the influence of the prevailing wind direction, which can result in the relocation of AQI. (4) According to ESDA-GWR analysis, on an annual scale, car ownership and industrial production are positively correlated with air pollution; whereas increase of wind speed, per capita gross domestic product (GDP), and forest coverage are conducive to reducing pollution. Local coefficients show spatial differences in the effects of different factors on the AQI. Empirical results of this study are helpful for the government departments to formulate regionally differentiated governance policies regarding air pollution.

Suggested Citation

  • Wenxuan Xu & Yongzhong Tian & Yongxue Liu & Bingxue Zhao & Yongchao Liu & Xueqian Zhang, 2019. "Understanding the Spatial-Temporal Patterns and Influential Factors on Air Quality Index: The Case of North China," IJERPH, MDPI, vol. 16(16), pages 1-23, August.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:16:p:2820-:d:255599
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/16/2820/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/16/2820/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuxia Ma & Bingshuang Xiao & Chang Liu & Yuxin Zhao & Xiaodong Zheng, 2016. "Association between Ambient Air Pollution and Emergency Room Visits for Respiratory Diseases in Spring Dust Storm Season in Lanzhou, China," IJERPH, MDPI, vol. 13(6), pages 1-14, June.
    2. Long, Ruyin & Shao, Tianxiang & Chen, Hong, 2016. "Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors," Applied Energy, Elsevier, vol. 166(C), pages 210-219.
    3. Muhammad Usman & Zhiqiang Ma & Muhammad Wasif Zafar & Abdul Haseeb & Rana Umair Ashraf, 2019. "Are Air Pollution, Economic and Non-Economic Factors Associated with Per Capita Health Expenditures? Evidence from Emerging Economies," IJERPH, MDPI, vol. 16(11), pages 1-22, June.
    4. Giardullo, Paolo & Sergi, Vittorio & Carton, Wim & Kenis, Anneleen & Kesteloot, Chris & Kazepov, Yuri & Kobus, Dominik & Maione, Michela & Skotak, Krzysztof & Fuzzi, Sandro & Pollini, Francesca, 2016. "Air quality from a social perspective in four European metropolitan areas: Research hypothesis and evidence from the SEFIRA project," Environmental Science & Policy, Elsevier, vol. 65(C), pages 58-64.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhixiong Tan & Haili Wu & Qingyang Chen & Jiejun Huang, 2024. "Spatiotemporal Analysis of Air Quality and Its Driving Factors in Beijing’s Main Urban Area," Sustainability, MDPI, vol. 16(14), pages 1-18, July.
    2. Wei Xue & Qingming Zhan & Qi Zhang & Zhonghua Wu, 2019. "Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China," IJERPH, MDPI, vol. 17(1), pages 1-23, December.
    3. Chao Hu & Jin Fan & Jian Chen, 2022. "Spatial and Temporal Characteristics and Drivers of Agricultural Carbon Emissions in Jiangsu Province, China," IJERPH, MDPI, vol. 19(19), pages 1-21, September.
    4. Ruyin Long & Qin Zhang & Hong Chen & Meifen Wu & Qianwen Li, 2020. "Measurement of the Energy Intensity of Human Well-Being and Spatial Econometric Analysis of Its Influencing Factors," IJERPH, MDPI, vol. 17(1), pages 1-21, January.

    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. Chen, Huadun & Du, Qianxi & Huo, Tengfei & Liu, Peiran & Cai, Weiguang & Liu, Bingsheng, 2023. "Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector," Energy, Elsevier, vol. 263(PE).
    2. Kangjuan Lv & Yu Cheng & Yousen Wang, 2021. "Does regional innovation system efficiency facilitate energy-related carbon dioxide intensity reduction in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 789-813, January.
    3. Sahar Amidi & Rezgar Feizi & Thais Nunez Rocha & Isabelle Rabaud, 2022. "Carbon Tax and Emissions Transfer: a Spatial Analysis," Working Papers hal-04638880, HAL.
    4. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    5. Yiwei Wang & Shuwang Yang & Canmian Liu & Shiying Li, 2018. "How Would Economic Development Influence Carbon Productivity? A Case from Hubei in China," IJERPH, MDPI, vol. 15(8), pages 1-13, August.
    6. Min Lu & Xing Wang & Yuquan Cang, 2018. "Carbon Productivity: Findings from Industry Case Studies in Beijing," Energies, MDPI, vol. 11(10), pages 1-19, October.
    7. Zhongye Sun & Xin Zhang & Yifei Gao, 2023. "The Impact of Financial Development on Renewable Energy Consumption: A Multidimensional Analysis Based on Global Panel Data," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    8. Yu, Yantuan & Chen, Xudong & Zhang, Ning, 2022. "Innovation and energy productivity: An empirical study of the innovative city pilot policy in China✰," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    9. Adaku Jane Echendu & Henry Favour Okafor & Olayinka Iyiola, 2022. "Air Pollution, Climate Change and Ecosystem Health in the Niger Delta," Social Sciences, MDPI, vol. 11(11), pages 1-17, November.
    10. Fujii, Hidemichi & Cao, Jing & Managi, Shunsuke, 2016. "Firm-level environmentally sensitive productivity and innovation in China," Applied Energy, Elsevier, vol. 184(C), pages 915-925.
    11. Beidi Diao & Lei Ding & Qiong Zhang & Junli Na & Jinhua Cheng, 2020. "Impact of Urbanization on PM 2.5 -Related Health and Economic Loss in China 338 Cities," IJERPH, MDPI, vol. 17(3), pages 1-18, February.
    12. Xiongfeng Pan & Sai Yuan & Malin Song & Mengna Li & Yuqing Wang, 2024. "Decomposition of the growth drivers and its spatial distribution characteristics of responsible innovation: A study of Chinese industrial enterprises," Asia Pacific Journal of Management, Springer, vol. 41(3), pages 1061-1084, September.
    13. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
    14. Wenwen Li & Wenping Wang & Yu Wang & Yingbo Qin, 2017. "Industrial structure, technological progress and CO2 emissions in China: Analysis based on the STIRPAT framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1545-1564, September.
    15. Pragyan Monalisa Sahoo & Himanshu Sekhar Rout & Mihajlo Jakovljevic, 2023. "Dynamics of Health Financing among the BRICS: A Literature Review," Sustainability, MDPI, vol. 15(16), pages 1-21, August.
    16. Li, Jinying & Li, Sisi, 2020. "Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model," Energy Policy, Elsevier, vol. 140(C).
    17. Li, Hao & Zhao, Yuhuan & Qiao, Xiaoyong & Liu, Ya & Cao, Ye & Li, Yue & Wang, Song & Zhang, Zhonghua & Zhang, Yongfeng & Weng, Jianfeng, 2017. "Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models," Energy Economics, Elsevier, vol. 68(C), pages 522-538.
    18. Liu, Biao & Wang, Jinman & Feng, Yu & Yang, Man & Mu, Jiayin, 2024. "Mitigating the disparities in carbon emission efficiency enhancement in China's coal resource-based cities," Energy, Elsevier, vol. 307(C).
    19. Caroline Orset, 2024. "Air, land, and water pollutants and public health expenditures: Empirical data from selected EU countries in the transport sector [Polluants atmosphériques, terrestres et aquatiques et dépenses de ," Post-Print hal-04521160, HAL.
    20. Samia Nasreen & Aviral Kumar Tiwari & Mehr‐un Nisa & Faryal Ishtiaq, 2024. "Evaluating the Role of GDP Per Capita, Air Pollution and Non‐Economic Factors in Determining Health Expenditure: Evidence from Asian Region Using Instrumental Variables Techniques," Economic Papers, The Economic Society of Australia, vol. 43(1), pages 63-90, March.

    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:16:y:2019:i:16:p:2820-:d:255599. 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.