Reducing greenhouse gas emissions of Amazon hydropower with strategic dam planning
Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity)....
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Published in | Nature communications Vol. 10; no. 1; pp. 4281 - 9 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
19.09.2019
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Abstract | Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO
2
eq MWh
−1
, 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO
2
eq MWh
−1
) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated.
Some dams produce large amounts of GHGs and it is important to see whether future dams will satisfy sustainable energy goals. Here the authors estimate the range of GHG emission intensities expected for 351 proposed and 158 existing Amazon dams and find that existing Amazon hydropower reservoirs collectively emit 14 Tg CO
2
eq per year, and that if all proposed Amazon dams are built, annual emissions would increase 5-fold. |
---|---|
AbstractList | Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO
2
eq MWh
−1
, 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO
2
eq MWh
−1
) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated.
Some dams produce large amounts of GHGs and it is important to see whether future dams will satisfy sustainable energy goals. Here the authors estimate the range of GHG emission intensities expected for 351 proposed and 158 existing Amazon dams and find that existing Amazon hydropower reservoirs collectively emit 14 Tg CO
2
eq per year, and that if all proposed Amazon dams are built, annual emissions would increase 5-fold. Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO 2 eq MWh −1 , 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO 2 eq MWh −1 ) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated. Hundreds of dams have been proposed throughout the Amazon basin, one of the world's largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO2eq MWh-1, 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO2eq MWh-1) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated.Hundreds of dams have been proposed throughout the Amazon basin, one of the world's largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO2eq MWh-1, 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO2eq MWh-1) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated. Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO2eq MWh−1, 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO2eq MWh−1) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated. Hundreds of dams have been proposed throughout the Amazon basin, one of the world's largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO eq MWh , 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO eq MWh ) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated. Some dams produce large amounts of GHGs and it is important to see whether future dams will satisfy sustainable energy goals. Here the authors estimate the range of GHG emission intensities expected for 351 proposed and 158 existing Amazon dams and find that existing Amazon hydropower reservoirs collectively emit 14 Tg CO2eq per year, and that if all proposed Amazon dams are built, annual emissions would increase 5-fold. |
ArticleNumber | 4281 |
Author | Montoya, Mariana Sethi, Suresh A. Gomes-Selman, Jonathan M. García-Villacorta, Roosevelt Wu, Xiaojian Xue, Yexiang Melack, John M. Almeida, Rafael M. Hamilton, Stephen K. Flecker, Alexander S. Barros, Nathan Angarita, Hector Forsberg, Bruce R. Gomes, Carla P. Shi, Qinru Perez, Guillaume |
Author_xml | – sequence: 1 givenname: Rafael M. orcidid: 0000-0001-5398-7054 surname: Almeida fullname: Almeida, Rafael M. email: rafaelmalmeida2@gmail.com organization: Department of Ecology and Evolutionary Biology, Cornell University – sequence: 2 givenname: Qinru surname: Shi fullname: Shi, Qinru organization: Cornell University, Institute for Computational Sustainability – sequence: 3 givenname: Jonathan M. surname: Gomes-Selman fullname: Gomes-Selman, Jonathan M. organization: Department of Computer Science, Stanford University – sequence: 4 givenname: Xiaojian orcidid: 0000-0001-8656-3741 surname: Wu fullname: Wu, Xiaojian organization: Cornell University, Institute for Computational Sustainability, Microsoft AI & Research – sequence: 5 givenname: Yexiang surname: Xue fullname: Xue, Yexiang organization: Cornell University, Institute for Computational Sustainability, Department of Computer Science, Purdue University – sequence: 6 givenname: Hector orcidid: 0000-0001-7089-2014 surname: Angarita fullname: Angarita, Hector organization: Stockholm Environment Institute Latin America – sequence: 7 givenname: Nathan surname: Barros fullname: Barros, Nathan organization: Department of Biology, Federal University of Juiz de Fora – sequence: 8 givenname: Bruce R. surname: Forsberg fullname: Forsberg, Bruce R. organization: National Institute of Amazonian Research (INPA) – sequence: 9 givenname: Roosevelt surname: García-Villacorta fullname: García-Villacorta, Roosevelt organization: Department of Ecology and Evolutionary Biology, Cornell University – sequence: 10 givenname: Stephen K. surname: Hamilton fullname: Hamilton, Stephen K. organization: W.K. Kellogg Biological Station and Department of Integrative Biology, Michigan State University, Cary Institute of Ecosystem Studies – sequence: 11 givenname: John M. surname: Melack fullname: Melack, John M. organization: Bren School of Environmental Science and Management, University of California at Santa Barbara – sequence: 12 givenname: Mariana surname: Montoya fullname: Montoya, Mariana organization: Wildlife Conservation Society Peru – sequence: 13 givenname: Guillaume surname: Perez fullname: Perez, Guillaume organization: Cornell University, Institute for Computational Sustainability – sequence: 14 givenname: Suresh A. surname: Sethi fullname: Sethi, Suresh A. organization: USGS New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources, Cornell University – sequence: 15 givenname: Carla P. surname: Gomes fullname: Gomes, Carla P. email: gomes@cs.cornell.edu organization: Cornell University, Institute for Computational Sustainability – sequence: 16 givenname: Alexander S. surname: Flecker fullname: Flecker, Alexander S. email: asf3@cornell.edu organization: Department of Ecology and Evolutionary Biology, Cornell University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31537792$$D View this record in MEDLINE/PubMed |
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Copyright | The Author(s) 2019 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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Snippet | Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially... Hundreds of dams have been proposed throughout the Amazon basin, one of the world's largest untapped hydropower frontiers. While hydropower is a potentially... Some dams produce large amounts of GHGs and it is important to see whether future dams will satisfy sustainable energy goals. Here the authors estimate the... |
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SubjectTerms | 704/172/4081 704/47/4113 706/4066/4076 Carbon Clean energy Dams Electric power generation Emissions Emissions control Fossil fuels Greenhouse effect Greenhouse gases Humanities and Social Sciences Hydroelectric power Industrial plant emissions multidisciplinary Multiple objective analysis Optimization Power plants Renewable energy sources River basins Science Science (multidisciplinary) Solar energy Sustainable development Sustainable energy Wind power |
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Title | Reducing greenhouse gas emissions of Amazon hydropower with strategic dam planning |
URI | https://link.springer.com/article/10.1038/s41467-019-12179-5 https://www.ncbi.nlm.nih.gov/pubmed/31537792 https://www.proquest.com/docview/2293842528 https://www.proquest.com/docview/2295465294 https://pubmed.ncbi.nlm.nih.gov/PMC6753097 https://doaj.org/article/0e9eefbae2f24c0b8f5c63ff9a2faa3f |
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