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Greenhouse Gas Emissions Quantification and Reduction Efforts in a Rural Municipality

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Listed:
  • Andreas Froemelt
  • Manuela Mauchle
  • Bernhard Steubing
  • Stefanie Hellweg

Abstract

The present article aims to determine the current carbon footprint (CF) of Zernez, a Swiss mountain village, and to identify reduction potentials of greenhouse gas (GHG) emissions. For this purpose, material and energy flows were assessed mainly based on detailed household surveys, interviews, and energy bills, but also by means of other information sources, for example, national statistics, traffic censuses, and literature values. To set up the GHG balance, special attention was paid to the consistent definition of system boundaries by adopting two fundamentally different perspectives: purely geographical accounting (PGA) and the consumption†based footprint (CBF) method. Each of these two perspectives total approximately 10 tonnes of carbon dioxide equivalents per capita per year. The PGA revealed that 70% of the direct emissions in Zernez are caused by agricultural activities, whereas no consumption area dominated the consumption†induced CF. For the identification of targeted measures, both perspectives were considered in a complementary manner. The building stock and its underlying energy supply system showed a GHG reduction potential of 80%. The building sector was thus detected as a reasonable first step for the municipality to adopt GHG mitigation strategies. In the case of Zernez, building†stock†related measures are predicted to decrease the current CF by 13% (CBF) and 17% (PGA), respectively.

Suggested Citation

  • Andreas Froemelt & Manuela Mauchle & Bernhard Steubing & Stefanie Hellweg, 2018. "Greenhouse Gas Emissions Quantification and Reduction Efforts in a Rural Municipality," Journal of Industrial Ecology, Yale University, vol. 22(1), pages 92-105, February.
  • Handle: RePEc:bla:inecol:v:22:y:2018:i:1:p:92-105
    DOI: 10.1111/jiec.12534
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    Cited by:

    1. Christian Gelleri, 2022. "Creating Monetary Collaborative Spaces for Social and Ecological Transformation," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
    2. Andreas Froemelt & René Buffat & Stefanie Hellweg, 2020. "Machine learning based modeling of households: A regionalized bottom‐up approach to investigate consumption‐induced environmental impacts," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 639-652, June.

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