Emission path planning based on dynamic abatement cost curve
本文改进了传统的边际减排成本曲线，引入即时单位边际减排成本概念，并考虑双因素学习曲线，将问题转化为非线性规划求解，为不同减排目标下的路径规划提供依据。
Global climate change is one of the most serious environmental problems that has attracted an unprecedented global attention. The scientific community has recognized that human activity is mostly responsible for global climate warming. Therefore, states participating in the United Nations Framework Convention on Climate Change (UNFCCC) have initiated a series of negotiations on how to develop their own emission reduction targets. However, the realization of these targets is at the expense of economic development to a great extent. Therefore, an abatement plan is necessary to decide how and when to implement emission reduction targets. A marginal abatement cost curve (MACC), often used as an important quantitative tool to estimate abatement burden or evaluate abatement performance, should be considered carefully. In this paper, we enrich the traditional MACC by introducing the concept of an “immediate unit marginal abatement cost” to describe its intrinsic incremental abatement difficulty. This cost is proved to be agreed with the actual situation in many ways, and is therefore very suitable for practical use. Two-factor learning curve are considered in the model, which can go some way in improving the performance of the revised MACC. Using a parameterization method, the original problem can be converted into a tractable nonlinear programming problem. We use an algorithm to search for the approximate global optimal solution. The effectiveness and the efficiency of the algorithm are discussed respectively. In the results, we find that the abatement path distinguishes largely under different abatement targets. Some plausible reasons and policy advices are given.