“双碳”目标下交通运输业碳排放脱钩效应与峰值预测

Decoupling effect and peak prediction of carbon emission in transportation industry under dual-carbon target

为助力交通运输业实现碳达峰、碳中和的战略发展目标,从历史验证和未来预测2个角度分析了中国交通运输业的碳排放变动趋势和影响因素,利用对数平均迪氏分解(LMDI)模型分解了2000至2020年中国交通运输业CO_(2)排放量变化的影响因素,结合Tapio脱钩模型分析了行业碳排放与经济发展的脱钩状态及脱钩的驱动因素;以影响因素分解结果作为情景分析法指标选择的依据,设定不同情景下的预测指标变动量,利用岭回归构建了STIRPAT预测模型。分析结果表明:研究期内CO_(2)排放总量呈现逐年增长的趋势,2000至2020年间累计增加了约6.94亿吨,运输强度的降低是碳排放增加的主要抑制因素,累计效应约为-6.26亿吨;人均GDP的增长是碳排放增加的最主要促进因素,累计效应约为12.94亿吨;能源消耗仍然以化石燃料为主,能源结构并未得到显著优化;行业碳排放的脱钩指数处于稳定的下降阶段,脱钩状态有所改善,主要表现为扩张负脱钩、增长连接和弱脱钩3种状态,能源结构的优化是助力脱钩最有潜力的因素;未来中国交通运输业碳排放变化趋势呈现先快速增长,在峰值附近增速减缓,达到峰值后有短期的平台,最后转入下降阶段;基准情景、悲观情景和乐观情景下中国交通运输业CO_(2)排放量峰值分别出现在2040、2045和2035年,峰值分别约为12.10亿吨、12.63亿吨和11.30亿吨。

To help the transportation industry achieve the strategic development goals of carbon peaking and carbon neutrality,the change trend and influencing factors of carbon emission in China's transportation industry were analyzed from two perspectives of historical verification and future prediction.The logarithmic mean Divisia index(LMDI)model was used to decompose the influencing factors of CO_(2)emission change in China's transportation industry from 2000 to 2020.The decoupling state of carbon emission and economic development in the industry and the driving factors of decoupling were analyzed by combining the Tapio decoupling model.The decomposition results of influencing factors were used as the basis for the selection of the indicators in the scenario analysis method,and the variations of prediction indicators under different scenarios were set.A prediction model of stochastic impacts by regression on population,affluence,and technology(STIRPAT)was constructed by using ridge regression.Analysis results show that the total CO_(2)emission exhibits an increasing trend year by year during the study period,with a cumulative increase of 694 million tons from 2000 to 2020.The decrease in transportation intensity is the main inhibiting factor for the increase in carbon emission,with a cumulative effect of-626 million tons.The growth of per capita GDP is the most important factor promoting the increase in carbon emission,and the cumulative effect is 1294 million tons.The energy consumption is still dominated by fossil fuels,and the energy structure is not significantly optimized.The decoupling index of industrial carbon emission is in a stable decline stage,and the decoupling state improves,mainly manifesting in three states,such as the expansion negative decoupling,growth connection,and weak decoupling.The optimization of energy structure is the most potential factor to help the decoupling.In the future,the carbon emission in China's transportation industry will rapidly grow at first,slow down near the peak,reach a plateau for a short period after the peak,and finally decline.In the baseline,pessimistic,and optimistic scenarios,the peak CO_(2)emission in China's transportation industry will occur in 2040,2045,and 2035,respectively,with peaks of about 1.210 billion,1.263 billion,and 1.130 billion tons,respectively.