北京市能源消费碳足迹影响因素分析

为了量化人口、城市化和技术等因素对城市碳排放的影响,以北京市为研究对象,引入修正的碳足迹方法计算1990~2011年城市能源消费碳足迹,采用STIRPAT模型和偏小二乘模型对城市能源消费碳足迹的影响因素进行评估.结果显示,城市化、人均收入、人口是碳排放最主要的正向驱动因素,而能源消费强度、产业结构和研发投入比重等因素导致碳排放降低.北京市二氧化碳排放不存在环境库兹涅茨曲线,城市碳排放总量虽然整体状况还在增加,但增长速度在逐步放缓,经济发展与环境保护尚未实现协同.根据模拟结果,降低碳排放和建设低碳城市的建议是发展集中型和紧凑型的城镇功能组团,控制人口过快增长,合理引导居民绿色消费,依靠科技创新和技术进步.

Examining the impact factors of energy consumption related carbon footprints using the STIRPAT model and PLS model in Beijing

To explore the effects of population, urbanization, and technology on metropolitan’s CO2 emissions, we examine Beijing city’s carbon footprints of energy consumption during 1990-2011 using the revised footprint method. In particular, the influence factors of the carbon footprint of urban energy consumption are evaluated by STIRPAT model and PLS model. The results show that: urbanization, affluence, and population are the most important positive driving factors of Beijing city’s CO2 emissions, while the impacts of energy consumption intensity, industrial structure and R&D proportion in GDP are negative; the inverted U-shaped relationship between carbon footprints and affluence is not strongly supported by the estimation. The city’s carbon footprints still increase, but the growing speed begins to slow down, which shows that the economic development and environment improvement have not achieved a coordinated effect.; simulation result further suggests that applied measures of integrated and compact urban function units, controlling excessive growth population, reasonable consumption for city dwellers, and technology innovation can help to reduce carbon dioxide emissions and develop the low-carbon city in Beijing.