Estimating greenhouse gas emissions from future Amazonian hydroelectric reservoirs

被引:71
作者
de Faria, Felipe A. M. [1 ]
Jaramillo, Paulina [1 ]
Sawakuchi, Henrique O. [2 ]
Richey, Jeffrey E. [3 ]
Barros, Nathan [4 ]
机构
[1] Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA
[2] Univ Sao Paulo, Ctr Nucl Energy Agr, Environm Anal & Geoproc Lab, BR-13400970 Piracicaba, SP, Brazil
[3] Univ Washington, Sch Oceanog, Seattle, WA 98195 USA
[4] Univ Fed Juiz de Fora, BR-36036330 Juiz De Fora, MG, Brazil
来源
ENVIRONMENTAL RESEARCH LETTERS | 2015年 / 10卷 / 12期
基金
美国国家科学基金会; 瑞典研究理事会; 巴西圣保罗研究基金会; 美国安德鲁·梅隆基金会;
关键词
hydropower; greenhouse gas emissions; emission factor; Amazon; TROPICAL HYDROPOWER; CARBON-DIOXIDE; METHANE; BALANCE; RIVERS; DAM;
D O I
10.1088/1748-9326/10/12/124019
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Brazil plans to meet the majority of its growing electricity demand with new hydropower plants located in the Amazon basin. However, large hydropower plants located in tropical forested regions may lead to significant carbon dioxide and methane emission. Currently, no predictive models exist to estimate the greenhouse gas emissions before the reservoir is built. This paper presents two different approaches to investigate the future carbon balance of eighteen new reservoirs in the Amazon. The first approach is based on a degradation model of flooded carbon stock, while the second approach is based on flux data measured in Amazonian rivers and reservoirs. The models rely on a Monte Carlo simulation framework to represent the balance of the greenhouse gases into the atmosphere that results when land and river are converted into a reservoir. Further, we investigate the role of the residence time/stratification in the carbon emissions estimate. Our results imply that two factors contribute to reducing overall emissions from these reservoirs: high energy densities reservoirs, i.e., the ratio between the installed capacity and flooded area, and vegetation clearing. While the models' uncertainties are high, we show that a robust treatment of uncertainty can effectively indicate whether a reservoir in the Amazon will result in larger greenhouse gas emissions when compared to other electricity sources.
引用
收藏
页数:13
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