基于STIRPAT模型的长三角区域四省市碳排放预测

Prediction of carbon emissions of four provinces in the Yangtze River delta region based on STIRPAT model

  • 摘要: 基于STIRPAT模型,通过岭回归方法分别定量分析长三角区域四省市(安徽、江苏、上海和浙江)的人口规模、人均GDP、城市化率、能源消耗强度、能源结构、第二产业增加值占比与碳排放量的关系,设置3种情景预测模式,预测长三角区域四省市的碳排放量发展趋势。结果表明:安徽省碳排放量影响最显著的变量是能源强度,能源强度每增加1%,碳排放量将下降0.524%,其余三省市碳排放量影响最显著的自变量均为人均GDP,人均GDP每增加1%,江苏、上海和浙江三省碳排放量分别增加1.734%、1.434%和1.355%。长三角区域在基准情景、低碳情景和强化低碳情景下分别于2035年、2030年和2025年达到碳排放峰值。人口增长速度、经济发展水平和能源强度是影响未来长三角四省市碳排放量增长的主要因素。建议长三角区域四省市制定分阶段、分地区差异化的碳达峰目标,对于煤炭依赖程度较高的安徽省,要努力构建多元化的低碳能源体系,利用长三角东部地区丰富的自然资源承接劳动密集型产业;上海、江苏、浙江三省市在加大科技创新助力产业转型升级的同时,也要合理控制人口数量,增强公民环保意识。

     

    Abstract: The relationship between population, per capita gross domestic product, urbanization level, energy consumption intensity, energy structure, the proportion of added value of secondary industry, and carbon emission of four provinces in the Yangtze River delta region were quantitatively analyzed by using the ridge regression method based on STIRPAT model, respectively. Three scenarios were set to analyze the development trend of carbon emissions of the four provinces. The results showed that the variable with the most significant impact on carbon emissions in Anhui Province was energy intensity. For every increase of 1%, carbon emissions would decrease by 0.524%. The independent variable with the most significant impact on carbon emissions in the other three provinces was per capita GDP. For every increase of 1%, the carbon emissions would increase by 1.734%, 1.434% and 1.355% in Jiangsu Province, Shanghai Municipality and Zhejiang Province, respectively. The four provinces would reach their CO2 peaks in 2035, 2030 and 2025 under the baseline, low-carbon and enhanced low-carbon scenarios, respectively. Population growth rate, economic development level and energy intensity would be the main factors affecting the future carbon emissions in the four regions of the Yangtze River Delta. It was suggested that the four provinces in the Yangtze River Delta region formulate phased and regionally differentiated carbon peak targets. Anhui Province, highly dependent on coal, should build a diversified low-carbon energy system and take advantage of the abundant natural resources in the eastern part of the Yangtze River Delta region to undertake labor-intensive industries. Shanghai Municipality, Jiangsu Province and Zhejiang Province should increase scientific and technological innovation to help industrial transformation and upgrading, control the population reasonably, and enhance the citizens' awareness of environmental protection.

     

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