《How organizational and global factors condition the effects of energy efficiency on CO2 emission rebounds among the world's power plants》

  • 来源专题:广州能源研究所信息监测
  • 编译者: giecinfo
  • 发布时间:2016-04-14
  • The United Nations Intergovernmental Panel on Climate Change (IPCC), the International Energy Agency (IEA), and several nations suggest that energy efficiency is an effective strategy for reducing energy consumption and associated greenhouse gas emissions. Skeptics contend that because efficiency lowers the price of energy and energy services, it may actually increase demand for them, causing total emissions to rise. While both sides of this debate have researched the magnitude of these so-called rebound effects among end-use consumers, researchers have paid less attention to the conditions under which direct rebounds cause CO2 emissions to rise among industrial producers. In particular, researchers have yet to explore how organizational and global factors might condition the effects of efficiency on emissions among power plants, the world's most concentrated sources of anthropogenic greenhouse gases. Here we use a unique dataset containing nearly every fossil-fuel power plant in the world to determine whether the impact of efficiency on emissions varies by plants' age, size, and location in global economic and normative systems. Findings reveal that each of these factors has a significant interaction with efficiency and thus shapes environmentally destructive rebound effects.

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  • 《How organizational and global factors condition the effects of energy efficiency on CO2 emission rebounds among the world's power plants》

    • 来源专题:能源战略信息监测
    • 编译者:giecinfo
    • 发布时间:2016-04-14
    • The United Nations Intergovernmental Panel on Climate Change (IPCC), the International Energy Agency (IEA), and several nations suggest that energy efficiency is an effective strategy for reducing energy consumption and associated greenhouse gas emissions. Skeptics contend that because efficiency lowers the price of energy and energy services, it may actually increase demand for them, causing total emissions to rise. While both sides of this debate have researched the magnitude of these so-called rebound effects among end-use consumers, researchers have paid less attention to the conditions under which direct rebounds cause CO2 emissions to rise among industrial producers. In particular, researchers have yet to explore how organizational and global factors might condition the effects of efficiency on emissions among power plants, the world's most concentrated sources of anthropogenic greenhouse gases. Here we use a unique dataset containing nearly every fossil-fuel power plant in the world to determine whether the impact of efficiency on emissions varies by plants' age, size, and location in global economic and normative systems. Findings reveal that each of these factors has a significant interaction with efficiency and thus shapes environmentally destructive rebound effects.
  • 《Life cycle energy and CO2 emission optimization for biofuel supply chain planning under uncertainties》

    • 来源专题:广州能源研究所信息监测
    • 编译者:giecinfo
    • 发布时间:2016-03-24
    • The purpose of this paper is to develop a model for the decision-makers/stakeholders to design biofuel supply chain under uncertainties. Life cycle energy and CO2 emission of biofuel supply chain are employed as the objective functions, multiple feedstocks, multiple transportation modes, multiple sites for building biofuel plants, multiple technologies for biofuel production, and multiple markets for biofuel distribution are considered, and the amount of feedstocks in agricultural system, transportation capacities, yields of crops, and market demands are considered as uncertainty variables in this study. A bi-objective interval mix integer programming model has been developed for biofuel supply chain design under uncertainties, and the bio-objective interval programming method has been developed to solve this model. An illustrative case of a multiple-feedstock-bioethanol system has been studied by the proposed method, and the results show that the proposed model can help decision-makers/stakeholders plan and design the biofuel supply chain by proposing feasible solutions to them.