IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i17p7554-d1468567.html
   My bibliography  Save this article

Analysis of Synergistic Drivers of CO 2 and NO X Emissions from Thermal Power Generating Units in Beijing–Tianjin–Hebei Region, 2010–2020

Author

Listed:
  • Yaolin Wang

    (College of Chemistry, Zhengzhou University, Zhengzhou 450001, China)

  • Zilin Yuan

    (Research Center for Emission Trading and Reduction, Chinese Academy of Environmental Planning, Beijing 100012, China)

  • Jun Yan

    (Zhejiang Ecological Environment Low-Carbon Development Center, Hangzhou 310007, China)

  • Haixu Zhang

    (Research Center for Emission Trading and Reduction, Chinese Academy of Environmental Planning, Beijing 100012, China)

  • Qinge Guan

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Sheng Rao

    (Research Center for Emission Trading and Reduction, Chinese Academy of Environmental Planning, Beijing 100012, China)

  • Chunlai Jiang

    (Research Center for Emission Trading and Reduction, Chinese Academy of Environmental Planning, Beijing 100012, China)

  • Zhiguo Duan

    (Eco-Environment Low Carbon Development Center of Inner Mongolia, Hohhot 010011, China)

Abstract

Synergistic control of the emissions of air pollutants and CO 2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO 2 and NO X emission characteristics of these units, and identifies and quantifies the synergistic drivers affecting these emission trends. The inventory data show that, between 2010 and 2020, NO X emissions were reduced by 86.1%, while CO 2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NO X emissions through measures such as end-of-pipe treatment, controlling CO 2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO 2 and NO X emission growth, energy intensity reduction is the main driver of CO 2 emission reduction, and end-of-pipe treatment is the main driver of NO X emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing–Tianjin–Hebei region, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NO X emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, this high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Suggested Citation

  • Yaolin Wang & Zilin Yuan & Jun Yan & Haixu Zhang & Qinge Guan & Sheng Rao & Chunlai Jiang & Zhiguo Duan, 2024. "Analysis of Synergistic Drivers of CO 2 and NO X Emissions from Thermal Power Generating Units in Beijing–Tianjin–Hebei Region, 2010–2020," Sustainability, MDPI, vol. 16(17), pages 1-17, August.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7554-:d:1468567
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/17/7554/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/17/7554/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Miao, Yuang & Lu, Huixia & Cui, Shizhang & Zhang, Xu & Zhang, Yusheng & Song, Xinwang & Cheng, Haiying, 2024. "CO2 emissions change in Tianjin: The driving factors and the role of CCS," Applied Energy, Elsevier, vol. 353(PA).
    2. Wang, H. & Ang, B.W., 2018. "Assessing the role of international trade in global CO2 emissions: An index decomposition analysis approach," Applied Energy, Elsevier, vol. 218(C), pages 146-158.
    3. Huanbi Yue & Chunyang He & Qingxu Huang & Dan Yin & Brett A. Bryan, 2020. "Stronger policy required to substantially reduce deaths from PM2.5 pollution in China," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    4. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    5. Wang, Zhaohua & Yin, Fangchao & Zhang, Yixiang & Zhang, Xian, 2012. "An empirical research on the influencing factors of regional CO2 emissions: Evidence from Beijing city, China," Applied Energy, Elsevier, vol. 100(C), pages 277-284.
    6. Pu Wang & Cheng-Kuan Lin & Yi Wang & Dachuan Liu & Dunjiang Song & Tong Wu, 2021. "Location-specific co-benefits of carbon emissions reduction from coal-fired power plants in China," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    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. Jialing Zou & Zhipeng Tang & Shuang Wu, 2019. "Divergent Leading Factors in Energy-Related CO 2 Emissions Change among Subregions of the Beijing–Tianjin–Hebei Area from 2006 to 2016: An Extended LMDI Analysis," Sustainability, MDPI, vol. 11(18), pages 1-17, September.
    2. Miao, Yuang & Lu, Huixia & Cui, Shizhang & Zhang, Xu & Zhang, Yusheng & Song, Xinwang & Cheng, Haiying, 2024. "CO2 emissions change in Tianjin: The driving factors and the role of CCS," Applied Energy, Elsevier, vol. 353(PA).
    3. Jiancheng Qin & Hui Tao & Chinhsien Cheng & Karthikeyan Brindha & Minjin Zhan & Jianli Ding & Guijin Mu, 2020. "Analysis of Factors Influencing Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China," Sustainability, MDPI, vol. 12(3), pages 1-15, February.
    4. Haitao Zheng & Jie Hu & Rong Guan & Shanshan Wang, 2016. "Examining Determinants of CO 2 Emissions in 73 Cities in China," Sustainability, MDPI, vol. 8(12), pages 1-17, December.
    5. Gangfei Luo & Tomas Baležentis & Shouzhen Zeng & JiaShun Pan, 2023. "Creating a decarbonized economy: Decoupling effects and driving factors of CO2 emission of 28 industries in China," Energy & Environment, , vol. 34(7), pages 2413-2431, November.
    6. Yang, Lin & Yang, Yuantao & Zhang, Xian & Tang, Kai, 2018. "Whether China's industrial sectors make efforts to reduce CO2 emissions from production? - A decomposed decoupling analysis," Energy, Elsevier, vol. 160(C), pages 796-809.
    7. Zhang, Yan & Wu, Qiong & Fath, Brian D., 2018. "Review of spatial analysis of urban carbon metabolism," Ecological Modelling, Elsevier, vol. 371(C), pages 18-24.
    8. Wei Li & Shuang Sun & Hao Li, 2015. "Decomposing the decoupling relationship between energy-related CO 2 emissions and economic growth in China," 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. 79(2), pages 977-997, November.
    9. Jiang, Xueting, 2023. "Rapid decarbonization in the Chinese electric power sector and air pollution reduction Co-benefits in the Post-COP26 Era," Resources Policy, Elsevier, vol. 82(C).
    10. Wang, Zhaojing & Jiang, Qingzhe & Dong, Kangyin & Mubarik, Muhammad Shujaat & Dong, Xiucheng, 2020. "Decomposition of the US CO2 emissions and its mitigation potential: An aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 147(C).
    11. Li, Guo & Zakari, Abdulrasheed & Tawiah, Vincent, 2020. "Energy resource melioration and CO2 emissions in China and Nigeria: Efficiency and trade perspectives," Resources Policy, Elsevier, vol. 68(C).
    12. Dong, Kangyin & Hochman, Gal & Timilsina, Govinda R., 2020. "Do drivers of CO2 emission growth alter overtime and by the stage of economic development?," Energy Policy, Elsevier, vol. 140(C).
    13. Shang, Wen-Long & Ling, Yantao & Ochieng, Washington & Yang, Linchuan & Gao, Xing & Ren, Qingzhong & Chen, Yilin & Cao, Mengqiu, 2024. "Driving forces of CO2 emissions from the transport, storage and postal sectors: A pathway to achieving carbon neutrality," Applied Energy, Elsevier, vol. 365(C).
    14. Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.
    15. Isik, Mine & Sarica, Kemal & Ari, Izzet, 2020. "Driving forces of Turkey's transportation sector CO2 emissions: An LMDI approach," Transport Policy, Elsevier, vol. 97(C), pages 210-219.
    16. 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).
    17. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    18. Zhang, Shulin & Su, Xiaoling & Singh, Vijay P & Ayantobo, Olusola Olaitan & Xie, Juan, 2018. "Logarithmic Mean Divisia Index (LMDI) decomposition analysis of changes in agricultural water use: a case study of the middle reaches of the Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 208(C), pages 422-430.
    19. Tsai, Bi-Huei & Chang, Chih-Jen & Chang, Chun-Hsien, 2016. "Elucidating the consumption and CO2 emissions of fossil fuels and low-carbon energy in the United States using Lotka–Volterra models," Energy, Elsevier, vol. 100(C), pages 416-424.
    20. Lei Gao & Taowu Pei & Jingran Zhang & Yu Tian, 2022. "The “Pollution Halo” Effect of FDI: Evidence from the Chinese Sichuan–Chongqing Urban Agglomeration," IJERPH, MDPI, vol. 19(19), pages 1-17, September.

    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:17:p:7554-:d:1468567. 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.