基于改进的主成分回归模型的碳排放预测研究 (Carbon emission forecast using improved Principal Component Regression (PCR) model)

This brief is submitted in the Chinese language. The full brief could be accessed through the below link. Your comments could be in either English or Chinese.

摘 要
为分析影响碳排放的主要因素,本文引入主成分分析理论,多元线性回归模型来考察影响碳排放的人文、经济、能源等 因素与碳排放之间的相互关系,进一步对其影响因素进行主成分多元回归建模,并就未来的碳排放及其强度展开预测。结果表明:在 所考察因素中,能源消费总量与碳排放的关系最为紧密;其次是 GDP 和人口总量。在结构指标中,工业化率和化石燃料比重,这两个 因素对碳排放的影响远高于城市化率、城镇居民消费水平。对上述结果分析后,本文提出了合理控制能源消费总量和经济增速,提高 经济发展质量和服务业比重,促进新能源产业发展等政策建议。最后,基于情景设置,本文运用主成分回归方程对我国 2020 年碳排 放总量及其强度进行预测。

https://sustainabledevelopment.un.org/content/documents/6110GSDR%20Brief%2037CN.pdf

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