Evaluation of sector-specific AWARE characterization factors for water scarcity footprint of electricity generation

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2021

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  • handle:  10670/1.huts24
  • Karimpour, Shooka; Boulay, Anne-Marie et Bulle, Cecile (2021). « Evaluation of sector-specific AWARE characterization factors for water scarcity footprint of electricity generation ». Science of The Total Environment, 753, p. 142063.
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http://archipel.uqam.ca/16048/

Ce document est lié à :
http://dx.doi.org/10.1016/j.scitotenv

Ce document est lié à :
doi:10.1016/j.scitotenv.2020.142063

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Shooka Karimpour et al., « Evaluation of sector-specific AWARE characterization factors for water scarcity footprint of electricity generation », UQAM Archipel : articles scientifiques, ID : 10670/1.huts24


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Life Cycle Impact Assessment (LCIA) links the emissions and resource abstractions of a product system or process to potential impacts on the environment through characterization factors (CF). For regionalized impact categories like water-use, the regional CFs can vary over several orders of magnitude within the same country. The aggregated country-level CF, often used in LCIA, represents an average of local CF weighted by the local water consumption of all (or most) human water use including water use by all (or most) economic sectors. There is, however, great variability in spatio-temporal distribution of human water consumption across different industries. This study provides industry-specific water-use CFs for the electricity sector across the US. Our analysis shows that for electricity generation, the use of all-sector aggregated water-use CF would lead to an underestimation of impact scores compared to industry-specific CFs, by two folds. Even within the electricity sector, for two of the major subsectors, electricity based on natural gas and hydroelectricity, the country-level CFs can be significantly different due to the geographic distribution of powerplants. Our findings signify that the use of industry-specific CF can have a high influence in LCIA, especially for impact categories, such as water-use, with great spatio-temporal heterogeneity.

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