预测摩洛哥的二氧化碳排放:通过数据预处理和特征影响分析探索回归的使用
Yassine Dani1, Naoual Belouaggadia2, Mustapha Jammoukh2
1Laboratory of Modeling and Simulation of Intelligent Industrial Systems, Higher Normal School of Technical Education, Hassan II University of Casablanca, Mohammedia, Morocco. yassinedani98@gmail.com.
Environmental science and pollution research international
|November 6, 2025
概括
回归准确地预测了摩洛哥的二氧化碳排放量,这是由石油消费驱动的. 增加可再生能源的部署为缓解气候变化提供了重大潜力.
科学领域:
- 环境科学 环境科学
- 计量经济学 计量经济学 计量经济学
- 气候建模气候模型
背景情况:
- 摩洛哥面临着能源,经济和人口因素影响的二氧化碳排放管理方面的挑战.
- 准确预测二氧化碳 (CO2) 排放对于有效的气候变化减缓战略至关重要.
研究的目的:
- 应用和评估回归 (RR) 来预测摩洛哥的二氧化碳排放.
- 将RR的性能与LASSO,ElasticNet和线性回归模型进行比较.
- 确定二氧化碳排放的主要驱动因素,并评估可再生能源政策的影响.
主要方法:
- 使用了1965-2021年摩洛哥的时间序列数据,包括十个变量.
- 应用回归 (RR),LASSO回归,弹性网回归和线性回归.
- 对可再生能源目标进行特征重要性分析和政策场景测试.
主要成果:
- RR模型实现了最高的预测准确性 (R2 = 0.994),优于其他方法.
- 石油消费被确定为二氧化碳排放的主要驱动因素 (标准化效应为129%),其次是煤炭 (9%).
- 可再生能源和水力发电与排放有负相关性,这表明有缓解效应.
结论:
- 回归是环境建模和二氧化碳排放预测的可靠工具.
- 实现摩洛哥2030年可再生能源目标可以减少每年约0.67万的排放量.
- 扩大可再生能源的部署对于摩洛哥减缓气候变化的努力来说,从战略上来说至关重要.
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