MOE Key Laboratory of Regional Energy Systems Optimization, S&C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206, China.
J Hazard Mater. 2011 Oct 15;193:112-9. doi: 10.1016/j.jhazmat.2011.07.036. Epub 2011 Jul 20.
Recent studies indicated that municipal solid waste (MSW) is a major contributor to global warming due to extensive emissions of greenhouse gases (GHGs). However, most of them focused on investigating impacts of MSW on GHG emission amounts. This study presents two mixed integer bilevel decision-making models for integrated municipal solid waste management and GHG emissions control: MGU-MCL and MCU-MGL. The MGU-MCL model represents a top-down decision process, with the environmental sectors at the national level dominating the upper-level objective and the waste management sectors at the municipal level providing the lower-level objective. The MCU-MGL model implies a bottom-up decision process where municipality plays a leading role. Results from the models indicate that: the top-down decisions would reduce metric tonne carbon emissions (MTCEs) by about 59% yet increase about 8% of the total management cost; the bottom-up decisions would reduce MTCE emissions by about 13% but increase the total management cost very slightly; on-site monitoring and downscaled laboratory experiments are still required for reducing uncertainty in GHG emission rate from the landfill facility.
最近的研究表明,由于温室气体(GHG)的大量排放,城市固体废物(MSW)是导致全球变暖的一个主要因素。然而,大多数研究都集中在调查 MSW 对 GHG 排放总量的影响上。本研究提出了两个用于综合城市固体废物管理和 GHG 排放控制的混合整数双层决策模型:MGU-MCL 和 MCU-MGL。MGU-MCL 模型代表自上而下的决策过程,国家层面的环境部门主导上层目标,市级的废物管理部门提供下层目标。MCU-MGL 模型意味着自下而上的决策过程,其中市政府发挥主导作用。模型的结果表明:自上而下的决策将减少约 59%的吨碳排放量(MTCE),但会增加约 8%的总管理成本;自下而上的决策将减少 MTCE 排放量约 13%,但会略微增加总管理成本;仍需要进行现场监测和小规模实验室实验,以减少垃圾填埋场 GHG 排放率的不确定性。