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Four system boundaries for carbon accounts

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  • Liu, Zhu
  • Feng, Kuishuang
  • Hubacek, Klaus
  • Liang, Sai
  • Anadon, Laura Diaz
  • Zhang, Chao
  • Guan, Dabo

Abstract

Knowing the carbon emission baseline of a region is a precondition for any mitigation effort, but the baselines are highly dependent on the system boundaries for which they are calculated. On the basis of sectoral energy statistics and a nested provincial and global multi-regional input–output model, we calculate and compare four different system boundaries for China's 30 provinces and major cities. The results demonstrate significant differences in the level of emissions for the different system boundaries. Moreover, the associated emissions with each system boundary varies with the regional development level, i.e. richer areas outsource more emissions to other areas, or in other words boundary 4 emissions are higher than boundary 1 emissions for rich areas and vice versa for poor areas. Given these significant differences it is important to be aware of the implications the choice of an accounting system might have on outcomes.

Suggested Citation

  • Liu, Zhu & Feng, Kuishuang & Hubacek, Klaus & Liang, Sai & Anadon, Laura Diaz & Zhang, Chao & Guan, Dabo, 2015. "Four system boundaries for carbon accounts," Ecological Modelling, Elsevier, vol. 318(C), pages 118-125.
    • Handle: RePEc:eee:ecomod:v:318:y:2015:i:c:p:118-125
    DOI: 10.1016/j.ecolmodel.2015.02.001
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    2. Jingwei Han & Zhixiong Tan & Maozhi Chen & Liang Zhao & Ling Yang & Siying Chen, 2022. "Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis," IJERPH, MDPI, vol. 19(18), pages 1-23, September.
    3. Guangfang Luo & Jianjun Zhang & Yongheng Rao & Xiaolei Zhu & Yiqiang Guo, 2017. "Coal Supply Chains: A Whole-Process-Based Measurement of Carbon Emissions in a Mining City of China," Energies, MDPI, vol. 10(11), pages 1-18, November.
    4. Changjian Wang & Fei Wang & Gengzhi Huang & Yang Wang & Xinlin Zhang & Yuyao Ye & Xiaojie Lin & Zhongwu Zhang, 2021. "Examining the Dynamics and Determinants of Energy Consumption in China’s Megacity Based on Industrial and Residential Perspectives," Sustainability, MDPI, vol. 13(2), pages 1-21, January.
    5. Chen, Shaoqing & Zhu, Feiyao, 2019. "Unveiling key drivers of urban embodied and controlled carbon footprints," Applied Energy, Elsevier, vol. 235(C), pages 835-845.
    6. Wang, Saige & Chen, Bin, 2018. "Three-Tier carbon accounting model for cities," Applied Energy, Elsevier, vol. 229(C), pages 163-175.
    7. Shan, Yuli & Liu, Zhu & Guan, Dabo, 2016. "CO2 emissions from China’s lime industry," Applied Energy, Elsevier, vol. 166(C), pages 245-252.
    8. Chen, Shaoqing & Long, Huihui & Chen, Bin & Feng, Kuishuang & Hubacek, Klaus, 2020. "Urban carbon footprints across scale: Important considerations for choosing system boundaries," Applied Energy, Elsevier, vol. 259(C).
    9. Babatunde, Kazeem Alasinrin & Begum, Rawshan Ara & Said, Fathin Faizah, 2017. "Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 61-71.
    10. Qian Zhang & Jun Nakatani & Yuichi Moriguchi, 2015. "Compilation of an Embodied CO 2 Emission Inventory for China Using 135-Sector Input-Output Tables," Sustainability, MDPI, vol. 7(7), pages 1-17, June.
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    12. Zhang, Zhonghua & Zhao, Yuhuan & Su, Bin & Zhang, Yongfeng & Wang, Song & Liu, Ya & Li, Hao, 2017. "Embodied carbon in China’s foreign trade: An online SCI-E and SSCI based literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 492-510.
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