Bi-objective optimization of biochar-based carbon management networks

被引:28
作者
Belmonte, Beatriz A. [1 ,2 ]
Benjamin, Michael Francis D. [2 ,3 ]
Tan, Raymond R. [1 ]
机构
[1] De La Salle Univ, Chem Engn Dept, 2401 Taft Ave, Manila 0922, Philippines
[2] Univ Santo Tomas, Chem Engn Dept, Espana Blvd, Manila 1015, Philippines
[3] Univ Santo Tomas, Res Ctr Nat & Appl Sci, Espana Blvd, Manila 1015, Philippines
关键词
Biochar; Negative emissions technology; Bi-objective optimization; Carbon management network; Source-sink model; Mixed-integer linear programming; NEGATIVE EMISSIONS TECHNOLOGIES; MITIGATION STRATEGIES; SEQUESTRATION; SOIL; SYSTEMS;
D O I
10.1016/j.jclepro.2018.04.023
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Biochar is the carbon-rich solid product derived from thermochemical processing of biomass. Its application to soil can sequester atmospheric carbon, leading to negative net emissions, while also improving agricultural yield. Biochar-based carbon management networks thus have the potential for scalable contributions to climate change mitigation efforts. However, it is necessary to allocate biochar of suitable quality to appropriate sinks, based on contaminant tolerance limits of soil. In this work, the network is modelled as a bi-objective mixed integer linear programming model, with profit and carbon sequestration as the objective functions. The model calculates the optimum allocation of biochar such that their prescribed limits for the contaminants are met. A Philippine case study is solved under different scenarios to illustrate the practical use of the developed model. The results provide useful insights for the rational decision-maker to arrive at the most preferred solution among the Pareto optimal choices. Comparison of the two scenarios substantiate the significance of unique sequestration factor as an additional parameter in the model to account for the interactions between the soils and biochars so that the maximum sustainable potential of biochar in climate change mitigation can be properly assessed. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:911 / 920
页数:10
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