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An Optimization Model of Carbon Sinks in CDM Forestry Projects Based on Interval Linear Programming
College of Environment and Resources, Jilin University, Changchun 130012, China
Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing 102206, China
* Author to whom correspondence should be addressed.
Received: 9 April 2012; in revised form: 5 June 2012 / Accepted: 5 June 2012 / Published: 13 June 2012
Abstract: This study describes the first general optimization model for complex systems with uncertain parameters and decision variables represented as intervals in CDM forestry projects. We work through a specific example of the optimization method developed for a Clean Development Mechanism (CDM) forestry project in Inner Mongolia, China. This model is designed to optimize the carbon sink capacity of the new forests, and can deal with uncertainties in the carbon sink capacity, average annual rainfall, ecological parameters, and biological characteristics of tree species. The uncertain inputs are presented in the form of intervals, as are several of the optimized output variables. Compared with the project’s originally recommended scheme, the optimized model will absorb and fix between 1,142 and 885,762 tonnes of extra carbon dioxide. Moreover, the ecological and environmental benefits of the project are also raised to various extents.
Keywords: carbon sink; optimization model; uncertainty; interval; Clean Development Mechanism forestry project
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MDPI and ACS Style
Li, D.; Zhang, Y.; Wang, X.; Li, Y.; Zhao, W. An Optimization Model of Carbon Sinks in CDM Forestry Projects Based on Interval Linear Programming. Energies 2012, 5, 1766-1781.
Li D, Zhang Y, Wang X, Li Y, Zhao W. An Optimization Model of Carbon Sinks in CDM Forestry Projects Based on Interval Linear Programming. Energies. 2012; 5(6):1766-1781.
Li, Dufeng; Zhang, Yang; Wang, Xianen; Li, Yu; Zhao, Wenjin. 2012. "An Optimization Model of Carbon Sinks in CDM Forestry Projects Based on Interval Linear Programming." Energies 5, no. 6: 1766-1781.