中文摘要：

To reduce carbon intensity, an improved management method balancing the reduction in costs and greenhouse gas(GHG)emissions is required for Tianjin’s waste management system. Firstly, six objective functions, namely, cost minimization, GHG minimization, eco-efficiency minimization, cost maximization, GHG maximization and eco-efficiency maximization, are built and subjected to the same constraints with each objective function corresponding to one scenario. Secondly, GHG emissions and costs are derived from the waste flow of each scenario. Thirdly, the range of GHG emissions and costs of other potential scenarios are obtained and plotted through adjusting waste flow with infinitely possible step sizes according to the correlation among the above six scenarios. And the optimal scenario is determined based on this range. The results suggest the following conclusions. 1) The scenarios located on the border between scenario cost minimization and GHG minimization create an optimum curve, and scenario GHG minimization has the smallest eco-efficiency on the curve; 2) Simple pursuit of eco-efficiency minimization using fractional programming may be unreasonable; 3) Balancing GHG emissions from incineration and landfills benefits Tianjin’s waste management system as it reduces GHG emissions and costs.

英文摘要：

To reduce carbon intensity, an improved management method balancing the reduction in costs and greenhouse gas（GHG）emissions is required for Tianjin＇s waste management system. Firstly, six objective functions, namely, cost minimization, GHG minimization, eco-efficiency minimization, cost maximization, GHG maximization and eco-efficiency maximization, are built and subjected to the same constraints with each objective function corresponding to one scenario. Secondly, GHG emissions and costs are derived from the waste flow of each scenario. Thirdly, the range of GHG emissions and costs of other potential scenarios are obtained and plotted through adjusting waste flow with infinitely possible step sizes according to the correlation among the above six scenarios. And the optimal scenario is determined based on this range. The results suggest the following conclusions. 1） The scenarios located on the border between scenario cost minimization and GHG minimization create an optimum curve, and scenario GHG minimization has the smallest eco-efficiency on the curve; 2） Simple pursuit of eco-efficiency minimization using fractional programming may be unreasonable; 3） Balancing GHG emissions from incineration and landfills benefits Tianjin＇s waste management system as it reduces GHG emissions and costs.