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Dynamic simulation of China’s carbon emission reduction potential by 2020

Author

Listed:
  • Feng Xu
  • Nan Xiang
  • Jingjing Yan
  • Lujun Chen
  • Peter Nijkamp
  • Yoshiro Higano

Abstract

Along with the rapid economic development of China, carbon dioxide (CO $$_{2}$$ 2 ) emissions will inevitable rise in the future. This will happen even though the Chinese government has made a series of attempts to constrain the CO $$_{2}$$ 2 -emissions, and is committed to reduce its CO $$_{2}$$ 2 -emissions per unit of gross domestic product (GDP) by 40–45 % (1,045–1,140 tons/million dollars) by 2020 from 2005 levels. However, according to estimates the total amount of CO $$_{2}$$ 2 -emissions will grow to more than 13 billion tons, and the carbon intensity will be twice of the world average. In order to improve this situation, this research study will construct a comprehensive dynamic simulation model to forecast China’s CO $$_{2}$$ 2 -emissions and GDP development under different energy structure adjustment plans and carbon intensity constraints from 2008 to 2020. In addition, find out the trade-off between Chinese carbon intensity reduction and economic development. The comprehensive model we constructed includes a CO $$_{2}$$ 2 -emissions model, an energy balance model, and a socio-economic model. Through a dynamic simulation analysis established by LINGO programming, this study provides the proper carbon intensity that China can achieve under the current situation, lie 1,040 tons/million dollars in 2020 (a 45 % reduction compared with the situation in 2005), while the CO $$_{2}$$ 2 -emissions will be 12.51 billion tons, the proportion of non-fossil energy 15 %, and the average annual increase in GDP 9 %. This research provides an effective method to estimate the interaction between economic growth and CO $$_{2}$$ 2 -emissions reduction, with alternative energy utilization in the future. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Feng Xu & Nan Xiang & Jingjing Yan & Lujun Chen & Peter Nijkamp & Yoshiro Higano, 2015. "Dynamic simulation of China’s carbon emission reduction potential by 2020," Letters in Spatial and Resource Sciences, Springer, vol. 8(1), pages 15-27, March.
  • Handle: RePEc:spr:lsprsc:v:8:y:2015:i:1:p:15-27
    DOI: 10.1007/s12076-014-0120-4
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    Cited by:

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    2. Qian Zhou & Helmut Yabar & Takeshi Mizunoya & Yoshiro Higano, 2017. "Evaluation of Integrated Air Pollution and Climate Change Policies: Case Study in the Thermal Power Sector in Chongqing City, China," Sustainability, MDPI, vol. 9(10), pages 1-17, September.
    3. Abbasi, Kashif Raza & Hussain, Khadim & Haddad, Akram Masoud & Salman, Asma & Ozturk, Ilhan, 2022. "The role of Financial Development and Technological Innovation towards Sustainable Development in Pakistan: Fresh insights from consumption and territory-based emissions," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    4. Cui, Xuezhu & Li, Shaoying & Gao, Feng, 2020. "Examining spatial carbon metabolism: Features, future simulation, and land-based mitigation," Ecological Modelling, Elsevier, vol. 438(C).
    5. Xinhai Lu & Bing Kuang & Jing Li & Jing Han & Zuo Zhang, 2018. "Dynamic Evolution of Regional Discrepancies in Carbon Emissions from Agricultural Land Utilization: Evidence from Chinese Provincial Data," Sustainability, MDPI, vol. 10(2), pages 1-13, February.

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    More about this item

    Keywords

    Dynamic simulation; CO $$_{2}$$ 2 -emissions; Carbon intensity; China; C61; O21; Q54;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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