长江经济带交通碳排放测度及其效率格局(1985~2016年)

采用"自上而下"的方法测度了长江经济带1985~2016年交通碳排放量并分析其空间格局和时序演化特征;在考虑非期望产出的基础上,剔除外部环境变量和随机误差的影响,构建了三阶段DEA模型进行长江经济带交通碳排放效率值的评价与比较.结果发现：①长江经济带交通碳排放总量呈不断上升趋势,其中石油类能源消费产生的排放量占比最大,四川、两湖地区和苏浙沪地区分别是长江上、中、下游交通碳排放的高值区.②从东西方向看,交通碳排放重心总体上呈现先东移、后西移的变动轨迹;从南北方向看,在空间上突出表现为越来越向长江沿岸集中分布的特征.③不同省份的交通碳排放效率值存在显的空间分异现象;2007~2016年东部地区的效率值始终最高,但中部地区的效率值由高于西部地区演变为低于西部地区.④外部环境因素对交通碳排放效率具有显著性影响,其中产业结构优化始终有利于交通碳排放效率提升,而政府干预的影响则由"创新补偿"效应转变为"遵循成本"效应.

Measurement of Traffic Carbon Emissions and Pattern of Efficiency in the Yangtze River Economic Belt (1985-2016)

The "top-down" method was used to measure the traffic carbon emissions from 1985 to 2016 in the Yangtze River Economic Belt and analyze its spatial pattern and temporal evolution characteristics. Considering the unexpected output, a three-stage DEA model was constructed to evaluate and compare the traffic carbon emission efficiency of the Yangtze River Economic Belt, excluding the influence of external environment variables and random errors. The study found that first, the total traffic carbon emissions in the Yangtze River Economic Belt showed a rising trend, among which the carbon emissions from petroleum energy consumption accounted for the largest proportion. Sichuan, Hubei, and Hunan and the Su-Zhe-Hu Region were the high-value areas of traffic carbon emissions in the upper, middle, and lower reaches of the Yangtze River, respectively. Second, from the east to west, the center of traffic carbon emissions generally showed a changing track of moving east first and then west; from the north to south, it highlighted the characteristics of increasing concentrated distribution along the Yangtze River in space. Third, there was an obvious spatial differentiation in the traffic carbon emission efficiency values of different provinces; from 2007 to 2016, the efficiency value of the eastern region was the highest, but the value of the central region changed from higher than that in the western region to lower than that in the western region. Finally, external environmental factors had a significant impact on the efficiency of traffic carbon emissions, in which the optimization of industrial structure was found to be conducive to the improvement of traffic carbon emission efficiency, while the influence of government intervention was changed from "innovation compensation" effect to "compliance cost" effect.