The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Water use of electricity technologies: A global meta-analysis
Open accessAbstract
Understanding the water use of power production is an important step to both a sustainable energy transition and an improved understanding of water conservation measures. However, there are large differences across the literature that currently present barriers to decision making. Here, the compiled inventory of the blue water use of power production from existing studies allowed to uncover the characteristics of water use and to investigate current uncertainties. The results show that photovoltaics, wind power, and run-of-the-river hydropower consume relatively little water, whereas reservoir hydropower and woody and herbaceous biomass can have an extremely large water footprint. The water consumption of power production can differ greatly across countries due to different geographic conditions. Only a few studies provided the values for the influencing factors of water use, such as the capacity factor. Values that are reported came mainly from assumptions and other literature rather than direct measurement. Omitting a life cycle stage may lead to significant underestimations. Water scarcity is attracting more attention, but the few existing results are not useable for a regional comparison due to data gaps and inconsistent measurements. In the future, a clear and detailed definition of the water footprint and system boundary of power production is essential to improving comparisons and energy systems modelling.
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PRISMA-P Group, Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015) · Systematic Reviews · doi:10.1186/2046-4053-4-1 · Cited by 26,223
Opportunities and challenges for a sustainable energy future
Chu, S., & Majumdar, A. (2012) · Nature · doi:10.1038/nature11475 · Cited by 12,550
Recent developments in life cycle assessment
Finnveden, G., Hauschild, M. Z., Ekvall, T., Guinée, J., Heijungs, R., Hellweg, S., Koehler, A., Pennington, D., & Suh, S. (2009) · Journal of Environmental Management · doi:10.1016/j.jenvman.2009.06.018 · Cited by 3,444
Biophysical and economic limits to negative CO2 emissions
Smith, P., Davis, S. J., Creutzig, F., Fuss, S., Minx, J., Gabrielle, B., Kato, E., Jackson, R. B., Cowie, A., Kriegler, E., et al. (2016) · Nature Climate Change · doi:10.1038/nclimate2870 · Cited by 1,440
Boulay, A.-M., Bare, J., Benini, L., Berger, M., Lathuillière, M. J., Manzardo, A., Margni, M., Motoshita, M., Núñez, M., Pastor, A. V., et al. (2018) · The International Journal of Life Cycle Assessment · doi:10.1007/s11367-017-1333-8 · Cited by 849
The consumptive water footprint of electricity and heat: a global assessment
Mekonnen, M. M., Gerbens-Leenes, P. W., & Hoekstra, A. Y. (2015) · Environmental Science: Water Research & Technology · doi:10.1039/c5ew00026b · Cited by 308
Hejazi, M. I., Voisin, N., Liu, L., Bramer, L. M., Fortin, D. C., Hathaway, J. E., Huang, M., Kyle, P., Leung, L. R., Li, H.-Y., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1421675112 · Cited by 166
Cited by
Tawalbeh, M., Al-Othman, A., Kafiah, F., Abdelsalam, E., Almomani, F., & Alkasrawi, M. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.143528 · Cited by 659
Emerging materials and technologies for electrocatalytic seawater splitting
Jin, H., Xu, J., Liu, H., Shen, H., Yu, H., Jaroniec, M., Zheng, Y., & Qiao, S.-Z. (2023) · Science Advances · doi:10.1126/sciadv.adi7755 · Cited by 417
Rabaia, M. K. H., Shehata, N., Olabi, V., Abdelkareem, M. A., Semeraro, C., Chae, K.-J., & Sayed, E. T. (2024) · Sustainable Horizons · doi:10.1016/j.horiz.2024.100106 · Cited by 20
Metadata
- Authors
- Jin, Y., Behrens, P., Tukker, A., & Scherer, L.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 115
- Pages
- 109391
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2974697259
- Cited by
- 201
- References
- 7
- FWCI
- 5.63
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Jin, Y., Behrens, P., Tukker, A., & Scherer, L. (2019). Water use of electricity technologies: A global meta-analysis. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2019.109391
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.