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Reducing global CO2 emissions with the technologies we have

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  • Ward, Hauke
  • Radebach, Alexander
  • Vierhaus, Ingmar
  • Fügenschuh, Armin
  • Steckel, Jan Christoph

Abstract

The energy intensities of the various industrial sectors differ considerably across countries. This suggests a potential for emissions reductions through improved accessibility to efficient technologies. This paper estimates an upper-bound CO2 emission mitigation potential that could theoretically be achieved by improved access to efficient technologies in industrial sectors. We develop a linear optimization framework that facilitates the exchange of sectoral production technologies based on the World Input-Output Database (WIOD), assuming perfect substitutability of technologies and homogeneity within economic sectors, while ignoring barriers to technological adoption and price driven adjustments. We consider the full global supply chain network and multiple upstream production inputs in addition to energy demand. In contrast to existing literature our framework allows to consider supply chain effects of technology replacements. We use our model to calculate emission reduction potentials for varying levels of access to technology. If best practice technologies were made available globally, CO2 emissions could theoretically be reduced by more than 10 gigatons (Gt). In fact, even second-tier production technologies would create significant global reduction potentials. We decompose sectoral emission reductions to identify contributions by changes in energy intensity, supply chain effects and changes in carbon intensities. Excluding the latter, we find that considering supply chain effects increases total mitigation potentials by 14%. The largest CO2 emission reduction potentials are found for a small set of developing countries.

Suggested Citation

  • Ward, Hauke & Radebach, Alexander & Vierhaus, Ingmar & Fügenschuh, Armin & Steckel, Jan Christoph, 2017. "Reducing global CO2 emissions with the technologies we have," Resource and Energy Economics, Elsevier, vol. 49(C), pages 201-217.
  • Handle: RePEc:eee:resene:v:49:y:2017:i:c:p:201-217
    DOI: 10.1016/j.reseneeco.2017.05.001
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    2. Avetisyan, Misak, 2018. "Impacts of global carbon pricing on international trade, modal choice and emissions from international transport," Energy Economics, Elsevier, vol. 76(C), pages 532-548.
    3. Srikant Gupta & Armin Fügenschuh & Irfan Ali, 2018. "A Multi-Criteria Goal Programming Model to Analyze the Sustainable Goals of India," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    4. Forin, Silvia & Radebach, Alexander & Steckel, Jan Christoph & Ward, Hauke, 2018. "The effect of industry delocalization on global energy use: A global sectoral perspective," Energy Economics, Elsevier, vol. 70(C), pages 233-243.
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    6. Wang, Juan & Hu, Mingming & Tukker, Arnold & Rodrigues, João F.D., 2019. "The impact of regional convergence in energy-intensive industries on China's CO2 emissions and emission goals," Energy Economics, Elsevier, vol. 80(C), pages 512-523.
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    8. Ming-Chieh Wang & Chang-Sheng Wang, 2018. "Tourism, the environment, and energy policies," Tourism Economics, , vol. 24(7), pages 821-838, November.
    9. Ward, Hauke & Steckel, Jan Christoph & Jakob, Michael, 2019. "How global climate policy could affect competitiveness," Energy Economics, Elsevier, vol. 84(S1).
    10. H. Wang & Chen Pan & P. Zhou, 2019. "Assessing the Role of Domestic Value Chains in China’s CO2 Emission Intensity: A Multi-Region Structural Decomposition Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 865-890, October.
    11. Fetter, T. Robert, 2022. "Energy transitions and technology change: “Leapfrogging” reconsidered," Resource and Energy Economics, Elsevier, vol. 70(C).
    12. Wei Zhen & Quande Qin & Lei Jiang, 2022. "Heterogeneous Domestic Intermediate Input-Related Carbon Emissions in China’s Exports," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 453-479, March.
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    More about this item

    Keywords

    GHG mitigation potential; Sectoral energy intensities; Technology transfer; Multi-regional input output data; Optimization; Multiple production inputs; Supply chain effects;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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