福建省减污降碳协同效应及驱动因子研究

Synergistic effects and driving factors of pollutant and carbon reduction in Fujian Province

选取福建省CO_(2)和主要污染物排放指标构建减污降碳耦合协调模型,通过随机森林(RF)和时空地理加权回归(GTWR)模型评估能源消费、产业升级、人均国内生产总值(GDP)、常住人口、用地结构等驱动因子对减污降碳协同工作的重要性,以及驱动因子与减污降碳耦合协调度相关性的时空变化。结果表明:相比2015年,2020年福建省主要污染物当量平均减排44.3%,温室气体排放当量平均升高22.5%;2015—2020年,泉州市和福州市减污降碳耦合协调度排名位于全省前二,莆田市和宁德市协调度提升最为显著;能源消费结构和能源消费强度与福建省减污降碳耦合协调度相关性的时空差异较大,但“十四五”期间仍可允许一定的煤炭消费增长;逐步提高人均GDP和推进产业升级,将为福建省减污降碳协同工作提供正面助力。

This study selected the emission indicators of CO 2 and major pollutants in Fujian Province to construct a coupling coordination model for pollutant and carbon reduction,and evaluated the effects of energy consumption,industrial upgrading,per capita gross domestic product(GDP),permanent population,land use structure on pollutant and carbon reduction through random forest(RF)and spatio-temporal geographically weighted regression(GTWR)models.The results showed that compared with 2015,the average reduction ratio of major pollutants in Fujian Province was 44.3%in 2020,and the average increase in greenhouse gas emissions was 22.5%.From 2015 to 2020,the cities with the highest degree of coupling coordination between pollutant reduction and carbon reduction in Fujian Province were Quanzhou and Fuzhou,and the cities with the most significant improvement in coupling coordination degree were Putian and Ningde.There were significant differences in the correlation between energy consumption structure and energy consumption intensity and the coupling coordination degree for pollutant and carbon reduction.However,during the“14th Five-Year Plan”period,a certain amount of coal consumption growth could still be permitted.Gradually increasing per capita GDP and promoting industrial upgrading would provide positive assistance for the coordinated reduction of pollutant and carbon in Fujian Province.