IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i9p3155-d167624.html
   My bibliography  Save this article

Exploring City Development Modes under the Dual Control of Water Resources and Energy-Related CO 2 Emissions: The Case of Beijing, China

Author

Listed:
  • Yan Wang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Weihua Xiao

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Yicheng Wang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Baodeng Hou

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Heng Yang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Xuelei Zhang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Mingzhi Yang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Lishan Zhu

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

Abstract

Water and energy are basic resources for urban development. It is of extreme importance to balance economic development, water and energy security, and environmental sustainability at the city level. Although many studies have focused on energy-related CO 2 emissions or water resources, individually, in relation to socioeconomic development, few studies have considered water and energy-related CO 2 emissions as synchronous limiting factors. Here, taking Beijing as an example, a partial least squares STIRPAT model—a method that combines partial least squares with the STIRPAT (stochastic impacts by regression on population, affluence, and technology) model—was used to determine the main driving factors of water use and energy-related CO 2 emissions at the regional scale from 1996 to 2016. The empirical results showed that the population, per capita gross domestic product (GDP), urbanization level, technology level, and service level, are all important factors that influence the total water use and energy-related CO 2 emissions. Additionally, eight scenarios were established to explore suitable development modes for future years. Consequently, a medium growth rate in socioeconomic status and population, and a high growth rate in the technology and service level, were found to be the most appropriate development modes. This scenario would result in a total water use of 4432.13 million m 3 and energy-related CO 2 emissions of 173.64 million tons in 2030. The results provide a new perspective for decision makers to explore suitable measures for simultaneously conserving water resources and reducing energy-related CO 2 emissions in the context of urban development.

Suggested Citation

  • Yan Wang & Weihua Xiao & Yicheng Wang & Baodeng Hou & Heng Yang & Xuelei Zhang & Mingzhi Yang & Lishan Zhu, 2018. "Exploring City Development Modes under the Dual Control of Water Resources and Energy-Related CO 2 Emissions: The Case of Beijing, China," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3155-:d:167624
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/9/3155/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/9/3155/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.
    2. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    3. Xunzhang, Pan & Wenying, Chen & Clarke, Leon E. & Lining, Wang & Guannan, Liu, 2017. "China's energy system transformation towards the 2°C goal: Implications of different effort-sharing principles," Energy Policy, Elsevier, vol. 103(C), pages 116-126.
    4. Lv, You & Liu, Jizhen & Yang, Tingting & Zeng, Deliang, 2013. "A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 319-329.
    5. Pao, Hsiao-Tien & Tsai, Chung-Ming, 2011. "Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil," Energy, Elsevier, vol. 36(5), pages 2450-2458.
    6. Meng, Ming & Niu, Dongxiao & Shang, Wei, 2014. "A small-sample hybrid model for forecasting energy-related CO2 emissions," Energy, Elsevier, vol. 64(C), pages 673-677.
    7. Liddle, Brantley, 2015. "What Are the Carbon Emissions Elasticities for Income and Population? Bridging STIRPAT and EKC via robust heterogeneous panel estimates," MPRA Paper 61304, University Library of Munich, Germany.
    8. Gu, Alun & Teng, Fei & Lv, Zhiqiang, 2016. "Exploring the nexus between water saving and energy conservation: Insights from industry sector during the 12th Five-Year Plan period in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 28-38.
    9. Dhakal, Shobhakar, 2009. "Urban energy use and carbon emissions from cities in China and policy implications," Energy Policy, Elsevier, vol. 37(11), pages 4208-4219, November.
    10. Xiangmei Li & Ying Wang & Jiangfeng Li & Bin Lei, 2016. "Physical and Socioeconomic Driving Forces of Land-Use and Land-Cover Changes: A Case Study of Wuhan City, China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-11, April.
    11. Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
    12. Shili Yang & Changxin Liu & Wenjie Dong & Jieming Chou & Di Tian & Ting Wei & Yuan Tian, 2018. "Quantifying the Climate Impact of the US Policy Choices Using an Economic and Earth System Model," Sustainability, MDPI, vol. 10(6), pages 1-11, June.
    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. Li, Jia Shuo & Zhou, H.W. & Meng, Jing & Yang, Q. & Chen, B. & Zhang, Y.Y., 2018. "Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city," Applied Energy, Elsevier, vol. 226(C), pages 1076-1086.
    2. Xinlin Zhang & Yuan Zhao & Qi Sun & Changjian Wang, 2017. "Decomposition and Attribution Analysis of Industrial Carbon Intensity Changes in Xinjiang, China," Sustainability, MDPI, vol. 9(3), pages 1-16, March.
    3. Weidong Chen & Ruoyu Yang, 2018. "Evolving Temporal–Spatial Trends, Spatial Association, and Influencing Factors of Carbon Emissions in Mainland China: Empirical Analysis Based on Provincial Panel Data from 2006 to 2015," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    4. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
    5. Ma, Xuejiao & Jiang, Ping & Jiang, Qichuan, 2020. "Research and application of association rule algorithm and an optimized grey model in carbon emissions forecasting," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    6. Ma, Xuejiao & Wang, Yong & Wang, Chen, 2017. "Low-carbon development of China's thermal power industry based on an international comparison: Review, analysis and forecast," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 942-970.
    7. Shiqing Zhang & Jianwei Wang & Wenlong Zheng, 2018. "Decomposition Analysis of Energy-Related CO 2 Emissions and Decoupling Status in China’s Logistics Industry," Sustainability, MDPI, vol. 10(5), pages 1-21, April.
    8. Li, Li & Shan, Yuli & Lei, Yalin & Wu, Sanmang & Yu, Xiang & Lin, Xiyan & Chen, Yupei, 2019. "Decoupling of economic growth and emissions in China’s cities: A case study of the Central Plains urban agglomeration," Applied Energy, Elsevier, vol. 244(C), pages 36-45.
    9. Junbo Wang & Liu Chen & Lu Chen & Xiaohui Zhao & Minxi Wang & Yiyi Ju & Li Xin, 2019. "City-Level Features of Energy Footprints and Carbon Dioxide Emissions in Sichuan Province of China," Energies, MDPI, vol. 12(10), pages 1-14, May.
    10. Tang, Miaohan & Hong, Jingke & Liu, Guiwen & Shen, Geoffrey Qiping, 2019. "Exploring energy flows embodied in China's economy from the regional and sectoral perspectives via combination of multi-regional input–output analysis and a complex network approach," Energy, Elsevier, vol. 170(C), pages 1191-1201.
    11. Zhang, Hong & Jin, Gui & Zhang, Zhengyu, 2021. "Coupling system of carbon emission and social economy: A review," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    12. Zhou, Dequn & Zhou, Xiaoyong & Xu, Qing & Wu, Fei & Wang, Qunwei & Zha, Donglan, 2018. "Regional embodied carbon emissions and their transfer characteristics in China," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 180-193.
    13. Huo, Tengfei & Du, Qianxi & Xu, Linbo & Shi, Qingwei & Cong, Xiaobo & Cai, Weiguang, 2023. "Timetable and roadmap for achieving carbon peak and carbon neutrality of China's building sector," Energy, Elsevier, vol. 274(C).
    14. Huo, Tengfei & Ma, Yuling & Xu, Linbo & Feng, Wei & Cai, Weiguang, 2022. "Carbon emissions in China's urban residential building sector through 2060: A dynamic scenario simulation," Energy, Elsevier, vol. 254(PA).
    15. Zhao, Mengxue & Yuan, Zhihang & Chan, Hon S., 2023. "Housing wealth and household carbon emissions: The role of homeownership in China," Ecological Economics, Elsevier, vol. 212(C).
    16. Li, Yonglin & Zuo, Zhili & Cheng, Yue & Cheng, Jinhua & Xu, Deyi, 2023. "Towards a decoupling between regional economic growth and CO2 emissions in China's mining industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 80(C).
    17. Qi Wang & Jiejun Huang & Han Zhou & Jiaqi Sun & Mingkun Yao, 2022. "Carbon Emission Inversion Model from Provincial to Municipal Scale Based on Nighttime Light Remote Sensing and Improved STIRPAT," Sustainability, MDPI, vol. 14(11), pages 1-17, June.
    18. Shijie Yang & Yunjia Wang & Rongqing Han & Yong Chang & Xihua Sun, 2021. "Spatial Heterogeneity of Factors Influencing CO 2 Emissions in China’s High-Energy-Intensive Industries," Sustainability, MDPI, vol. 13(15), pages 1-24, July.
    19. Shahbaz, Muhammad & Hye, Qazi Muhammad Adnan & Tiwari, Aviral Kumar & Leitão, Nuno Carlos, 2013. "Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 109-121.
    20. Guo, Xuepeng & Pang, Jun, 2023. "Analysis of provincial CO2 emission peaking in China: Insights from production and consumption," Applied Energy, Elsevier, vol. 331(C).

    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:10:y:2018:i:9:p:3155-:d:167624. 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.