TY - JOUR A2 - Nourinejad, Mehdi AU - Li, Xiao AU - Gao, Li AU - Liu, Jintao PY - 2020 DA - 2020/12/23 TI -道路交通碳排放配额的方法:碳交易是道路交通减少能源消耗和碳排放的有效措施。碳排放配额是确保碳交易效率的首要问题。然而，现有的研究大多集中在不同地区，即不同国家和省份的碳排放配额上。鲜有文献模拟道路运输中的碳配额分配。在数据包络分析(DEA)模型的基础上，从汽车碳排放强度的角度提出了一种新的方法。与其他研究不同的是，引入了基线激励分配的思想，并将强度作为基线包含在模型中。首先，采用德尔菲法对输入输出指标进行选择。其次，碳排放强度由累积分布函数(CDF)决定。并利用我国30个省份的道路交通碳排放配额对模型进行了验证。 The results show that (1) the carbon emission intensity of commercial trucks and buses in China’s road transport industry is 75.04 g/t·km and 13.12 g/p·km, respectively; (2) the provinces of Shanghai, Guangdong, and Xinjiang have the greatest carbon reduction potential and Henan, Hunan, and Anhui have the largest increase in emission quotas; (3) compared with traditional “history responsibility” and “baseline” methods, the proposed approach increases allocation efficiency by 19% and 14%, respectively; and (4) the approach can make the carbon emission quotas play the role of incentive while taking fairness into account and can more effectively promote the implementation of carbon trading system in road transportation. SN - 0197-6729 UR - https://doi.org/10.1155/2020/8819694 DO - 10.1155/2020/8819694 JF - Journal of Advanced Transportation PB - Hindawi KW - ER -