Modeling Future Life-Cycle Greenhouse Gas Emissions and Environmental Impacts of Electricity Supplies in Brazil

Energies

Alexander T. Dale³  André Frossard Pereira de Lucena¹  Joe Marriott³  Bruno Soares Moreira Cesar Borba²  Roberto Schaeffer¹ 

[1] Programa de Planejamento Energético, Universidade Federal do Rio de Janeiro, Centro de Tecnologia, Bloco C, Sala 211, Cidade Universitária, Ilha do Fundão, Rio de Janeiro 21941-972, Brazil; E-Mails:;Departamento de Engenharia Elétrica, Universidade Federal Fluminense, Rua Passo da Pátria, Bloco D, Sala 509, São Domingos, Niteroi 24210-240, Brazil; E-Mail:;Civil and Environmental Engineering, University of Pittsburgh, 3700 O’Hara St., Pittsburgh, PA 15260, USA; E-Mails:

关键词: life-cycle assessment (LCA);    scenarios;    Brazil;    energy;    climate change;    Monte-Carlo analysis (MCA);   

DOI  :  10.3390/en6073182

来源: mdpi

【 摘 要 】

Brazil’s status as a rapidly developing country is visible in its need for more energy, including electricity. While the current electricity generation mix is primarily hydropower based, high-quality dam sites are diminishing and diversification to other sources is likely. We combined life-cycle data for electricity production with scenarios developed using the IAEA’s MESSAGE model to examine environmental impacts of future electricity generation under a baseline case and four side cases, using a Monte-Carlo approach to incorporate uncertainty in power plant performance and LCA impacts. Our results show that, under the cost-optimal base case scenario, Brazil’s GHGs from electricity (excluding hydroelectric reservoir emissions) rise 370% by 2040 relative to 2010, with the carbon intensity per MWh rising 100%. This rise would make Brazil’s carbon emissions targets difficult to meet without demand-side programs. Our results show a future electricity mix dominated by environmental tradeoffs in the use of large-scale renewables, questioning the use tropical hydropower and highlighting the need for additional work to assess and include ecosystem and social impacts, where information is currently sparse.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.