我国纺织服装行业碳排放影响因素及达峰预测

Influencing Factors and Peak Prediction of Carbon Emission in China’s Textile and Garment Industry

为推动我国纺织服装业的低碳发展,助力“碳达峰”与“碳中和”目标的实现,运用碳排放系数法对我国纺织服装行业2000—2019年的碳排放量和碳排放强度进行测算,运用拓展的STIRPAT模型对影响我国纺织服装行业碳排放的因素进行筛选,并使用岭回归法建立预测模型,最后对我国纺织服装行业2020—2050年9种情境下的碳达峰情况进行预测。结果表明:经济水平、人口规模、城市化率、产业结构、开放程度和碳排放强度会对我国纺织服装行业碳排放产生正向显著影响;促进排放模式1、促进排放模式2与激进排放模式较不理想,达峰时间晚于2030年;中和排放模式1与基准模式是较为理想的发展模式;低碳模式、抑制排放模式1与抑制排放模式2虽理想但不现实。此外,积极因素的控制只需酌情即可,并非越低越好。

In order to promote the low-carbon development of China textile and garment industry and achieve the goals of “carbon peaking” and “carbon neutrality”, firstly the carbon emission coefficient method was used to calculate the carbon emissions and carbon emission intensity of China’s textile and garment industry from 2000 to 2019. Then, the extended STIRPAT model was used to screen the influencing factors of carbon emissions in China’s textile and garment industry, and a prediction model was established by the ridge regression method. Finally, the carbon peaking situation of China’s textile and garment industry under 9 scenarios from 2020 to 2050 was predicted. The results show that economic level, population size, urbanization rate, industrial structure, degree of openness and carbon emission intensity have a positive and significant impact on carbon emissions in China’s textile and garment industry. The effects of promoting emission model 1 and model 2 and radical emission model are unsatisfactory, and the peak time will be later than 2030;the neutral promoting emission model 1 and the benchmark model are more ideal development models;the low-carbon model, the emission suppression model 1 and the emission suppression model 2 are ideal but unrealistic. In addition, the control of positive factors should be adjusted according to the circumstances, rather than the lower the better.