A bi-objective programming model for carbon emission quota allocation: Evidence from the Pearl River Delta region
A bi-objective programming model for carbon emission quota allocation: Evidence from the Pearl River Delta region
复制标题
碳排放配额分配的双目标规划模型：来自珠三角地区的证据
DOI：
10.1016/j.jclepro.2018.09.069
复制
发表时间：
2018
影响因子：
11.1
通讯作者：
Tan Kim Hua
中科院分区：
文献类型：
--
作者：
Li Lixu;Ye Fei;Li Yina;Tan Kim Hua
作为排放权交易机制（ETS）的核心组成部分，碳配额的初始分配极为重要。目前，大多数分配方法主要集中在实现单一的绩效目标，这将导致不同层次的参与者之间的冲突。为了克服这一局限性，提出了一个双目标规划模型（BPM）的减排成本和碳资产的两个子目标函数。同时，成本导向模型（CM）和资产导向模型（AM）作为比较方法，分别代表区域减排成本最小化和个人利益最大化。珠江三角洲地区的实证结果表明，BPM是最有效的和可行的方法在一定程度上。更准确地说，BPM可以在优化减排成本的同时激发所有参与者的积极性。随着区域总量的增加，BPM的优势越来越突出。本文的贡献在于提出了一种新的碳排放配额分配方法，填补了现有文献中的差距。此外，所提出的方法，可以部署在其他类似地区的政策制定者制定有效的减排政策，并在更好地了解经济，能源和环境的目标。
As a core component of the emission trading scheme (ETS), the initial allocation of carbon quotas is extremely important. Currently, most allocation methods mainly focus on the realization of a single performance goal, which will result in conflicts between different levels of participants. To overcome this limitation, a bi-objective programming model (BPM) with two sub-objective functions of abatement costs and carbon assets is proposed. Meanwhile, cost-oriented model (CM) and asset-oriented model (AM) are implemented as comparison approaches that represent the minimization of regional abatement costs and the maximization of individual interests, respectively. The empirical results of the Pearl River Delta (PRD) region reveal that BPM is the most efficient and feasible approach to some extent. More precisely, BPM can motivate the enthusiasm of all participants while optimizing abatement costs. With the increase of regional total quotas, the advantage of BPM becomes more and more prominent. The contribution of this paper is to present a novel method for carbon emission quota allocation, which fills the gap in the existing literature. Furthermore, the proposed method that can be deployed in other similar regions assists policymakers in enacting an effective emission reduction policy and in better understanding the objectives of economy, energy and environment.