基于GAMLSS模型的二氧化碳排放驱动因素分析
Analysis of Driving Factors of Carbon Dioxide Emission Based on GAMLSS Model
DOI: 10.12677/AAM.2020.98137, PDF,  被引量   
作者: 李秋萍, 陈兴荣*, 朱燚丹：中国地质大学(武汉)数学与物理学院，湖北 武汉
关键词: 二氧化碳排放；GAMLSS模型；非参数回归；Carbon Dioxide Emissions； GAMLSS Model； Non-Parametric Regression
摘要: 全球变暖与二氧化碳减排是各国关注的重要议题。综合研究碳排放影响因素，有效减少碳排放是亟待解决的重要任务。本文收集了我国2005~2017年30个省市的相关数据，构建GAMLSS模型进行非参数回归分析，探讨人口规模、经济水平、城市化水平和能源强度对二氧化碳排放的影响机制。分析结果显示，各因素从长期来看对二氧化碳排放具有线性正向效应，且人口规模、经济水平和城市化水平在一定范围内对二氧化碳排放呈现倒“U”型的非线性影响模式。基于研究结论，结合我国国情提出了关于二氧化碳减排的一些建议。
Abstract: Global warming and carbon dioxide reduction are important issues of concern to all countries. It is an important task to comprehensively study the factors affecting carbon emissions and effectively reduce carbon emissions. This paper collects relevant data from 30 provinces and cities in China from 2005 to 2017, constructs a GAMLSS model for non-parametric regression analysis, and explores the impact of population size, economic level, urbanization level, and energy intensity on carbon dioxide emissions. The analysis results show that all factors have a linear positive effect on carbon dioxide emissions in the long run, and that the population size, economic level, and urbanization level have an inverted “U”-shaped non-linear impact mode on carbon dioxide emissions within a certain range. Based on the conclusions of the study, combined with China’s national conditions, this paper puts forward some suggestions on carbon dioxide emission reduction.
文章引用：李秋萍, 陈兴荣, 朱燚丹. 基于GAMLSS模型的二氧化碳排放驱动因素分析[J]. 应用数学进展, 2020, 9(8): 1177-1186. https://doi.org/10.12677/AAM.2020.98137

参考文献

[1] Panayotou, T. (1993) Empirical Tests and Policy Analysis of Environmental Degradation at Different Stages of Economic Development. International Labour Organization, Geneva.
[2] Ang, B.W. and Choi, K.H. (1997) Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method. Energy Journal, 18, 59-73. [Google Scholar] [CrossRef] 
[3] Mousavi, B., Lopez, N.S., Biona, J.B., et al. (2017) Driving Forces of Iran’s CO2 Emissions from Energy Consumption: An LMDI Decomposition Approach. Applied Energy, 206, 804-814. [Google Scholar] [CrossRef] 
[4] Yang, J., Cai, W., Ma, M., et al. (2020) Driving Forces of China’s CO2 Emissions from Energy Consumption Based on Kaya-LMDI Methods. Science of the Total Environment, 711, Article ID: 134569. [Google Scholar] [CrossRef] [PubMed]
[5] Wen, L. and Li, Z. (2020) Provincial-Level Industrial CO2 Emission Drivers and Emission Reduction Strategies in China: Combining Two-Layer LMDI Method with Spectral Clustering. Science of the Total Environment, 700, Article ID: 134374. [Google Scholar] [CrossRef] [PubMed]
[6] Dietz, T. and Rosa, E.A. (1997) Effects of Population and Affluence on CO2 Emissions. Proceedings of the National Academy of Sciences, 94, 175-179. [Google Scholar] [CrossRef] [PubMed]
[7] Zhang, H., Zhang, Z. and Sheng, K. (2018) Effects of Global Value Chain Position on the Carbon Emissions of Manufacturing Industry in China: An Empirical Study Based on the STIRPAT Model. Meteorological and Environmental Research, 9, 52-57.
[8] 渠慎宁, 郭朝先. 基于STIRPAT模型的中国碳排放峰值预测研究[J]. 中国人口·资源与环境, 2010, 20(12): 10-15.
[9] Hastie, T. and Tibshirani, R. (1986) Generalized Additive Models. Statistical Science, 1, 297-318. [Google Scholar] [CrossRef] 
[10] Wen, L. and Shao, H. (2019) Influencing Factors of the Carbon Dioxide Emissions in China’s Commercial Department: A Non-Parametric Additive Regression Model. Science of the Total Environment, 668, 1-12. [Google Scholar] [CrossRef] [PubMed]
[11] Rigby, R.A. and Stasinopoulos, D. (2005) Generalized Additive Models for Location, Scale and Shape. Journal of The Royal Statistical Society Series C Applied Statistics, 54, 507-554. [Google Scholar] [CrossRef] 
[12] Ehrlich, P.R. and Holdren, J.P. (1971) Impact of Population Growth. Science, 171, 1212-1217. [Google Scholar] [CrossRef] [PubMed]
[13] Hoesly, R., Matthews, H.S., Hendrickson, C., et al. (2015) Energy and Emissions from U.S. Population Shifts and Implications for Regional GHG Mitigation Planning. Environmental Science & Technology, 49, 12670-12678. [Google Scholar] [CrossRef] [PubMed]
[14] Kim, K. and Kim, Y. (2012) International Comparison of Industrial CO2 Emission Trends and the Energy Efficiency Paradox Utilizing Production-Based Decomposition. Energy Economics, 34, 1724-1741. [Google Scholar] [CrossRef] 
[15] Zhang, Y., Zhang, Q. and Pan, B. (2019) Impact of Affluence and Fossil Energy on China Carbon Emissions Using STIRPAT Model. Environmental Science and Pollution Research, 26, 18814-18824. [Google Scholar] [CrossRef] [PubMed]
[16] Li, S. and Wang, S. (2019) Examining the Effects of Socioeconomic Development on China’s Carbon Productivity: A Panel Data Analysis. Science of the Total Environment, 659, 681-690. [Google Scholar] [CrossRef] [PubMed]
[17] 刘希雅, 王宇飞, 宋祺佼, 等. 城镇化过程中的碳排放来源[J]. 中国人口·资源与环境, 2015, 25(1): 61-66.
[18] 李国志, 李宗植. 人口、经济和技术对二氧化碳排放的影响分析——基于动态面板模型[J]. 人口研究, 2010, 34(3): 32-39.
[19] Poumanyvong, P. and Kaneko, S. (2010) Does Urbanization Lead to Less Energy Use and Lower CO2 Emissions? A Cross-Country Analysis. Ecological Economics, 70, 434-444. [Google Scholar] [CrossRef] 
[20] 张腾飞, 杨俊, 盛鹏飞. 城镇化对中国碳排放的影响及作用渠道[J]. 中国人口·资源与环境, 2016, 26(2): 47-57.
[21] Panayotou, T. (1993) Empirical Tests and Policy Analysis of Environmental Degradation at Different Stages of Economic Development. International Labour Organization, Geneva.
[22] Ang, B.W. and Choi, K.H. (1997) Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method. Energy Journal, 18, 59-73. [Google Scholar] [CrossRef] 
[23] Mousavi, B., Lopez, N.S., Biona, J.B., et al. (2017) Driving Forces of Iran’s CO2 Emissions from Energy Consumption: An LMDI Decomposition Approach. Applied Energy, 206, 804-814. [Google Scholar] [CrossRef] 
[24] Yang, J., Cai, W., Ma, M., et al. (2020) Driving Forces of China’s CO2 Emissions from Energy Consumption Based on Kaya-LMDI Methods. Science of the Total Environment, 711, Article ID: 134569. [Google Scholar] [CrossRef] [PubMed]
[25] Wen, L. and Li, Z. (2020) Provincial-Level Industrial CO2 Emission Drivers and Emission Reduction Strategies in China: Combining Two-Layer LMDI Method with Spectral Clustering. Science of the Total Environment, 700, Article ID: 134374. [Google Scholar] [CrossRef] [PubMed]
[26] Dietz, T. and Rosa, E.A. (1997) Effects of Population and Affluence on CO2 Emissions. Proceedings of the National Academy of Sciences, 94, 175-179. [Google Scholar] [CrossRef] [PubMed]
[27] Zhang, H., Zhang, Z. and Sheng, K. (2018) Effects of Global Value Chain Position on the Carbon Emissions of Manufacturing Industry in China: An Empirical Study Based on the STIRPAT Model. Meteorological and Environmental Research, 9, 52-57.
[28] 渠慎宁, 郭朝先. 基于STIRPAT模型的中国碳排放峰值预测研究[J]. 中国人口·资源与环境, 2010, 20(12): 10-15.
[29] Hastie, T. and Tibshirani, R. (1986) Generalized Additive Models. Statistical Science, 1, 297-318. [Google Scholar] [CrossRef] 
[30] Wen, L. and Shao, H. (2019) Influencing Factors of the Carbon Dioxide Emissions in China’s Commercial Department: A Non-Parametric Additive Regression Model. Science of the Total Environment, 668, 1-12. [Google Scholar] [CrossRef] [PubMed]
[31] Rigby, R.A. and Stasinopoulos, D. (2005) Generalized Additive Models for Location, Scale and Shape. Journal of The Royal Statistical Society Series C Applied Statistics, 54, 507-554. [Google Scholar] [CrossRef] 
[32] Ehrlich, P.R. and Holdren, J.P. (1971) Impact of Population Growth. Science, 171, 1212-1217. [Google Scholar] [CrossRef] [PubMed]
[33] Hoesly, R., Matthews, H.S., Hendrickson, C., et al. (2015) Energy and Emissions from U.S. Population Shifts and Implications for Regional GHG Mitigation Planning. Environmental Science & Technology, 49, 12670-12678. [Google Scholar] [CrossRef] [PubMed]
[34] Kim, K. and Kim, Y. (2012) International Comparison of Industrial CO2 Emission Trends and the Energy Efficiency Paradox Utilizing Production-Based Decomposition. Energy Economics, 34, 1724-1741. [Google Scholar] [CrossRef] 
[35] Zhang, Y., Zhang, Q. and Pan, B. (2019) Impact of Affluence and Fossil Energy on China Carbon Emissions Using STIRPAT Model. Environmental Science and Pollution Research, 26, 18814-18824. [Google Scholar] [CrossRef] [PubMed]
[36] Li, S. and Wang, S. (2019) Examining the Effects of Socioeconomic Development on China’s Carbon Productivity: A Panel Data Analysis. Science of the Total Environment, 659, 681-690. [Google Scholar] [CrossRef] [PubMed]
[37] 刘希雅, 王宇飞, 宋祺佼, 等. 城镇化过程中的碳排放来源[J]. 中国人口·资源与环境, 2015, 25(1): 61-66.
[38] 李国志, 李宗植. 人口、经济和技术对二氧化碳排放的影响分析——基于动态面板模型[J]. 人口研究, 2010, 34(3): 32-39.
[39] Poumanyvong, P. and Kaneko, S. (2010) Does Urbanization Lead to Less Energy Use and Lower CO2 Emissions? A Cross-Country Analysis. Ecological Economics, 70, 434-444. [Google Scholar] [CrossRef] 
[40] 张腾飞, 杨俊, 盛鹏飞. 城镇化对中国碳排放的影响及作用渠道[J]. 中国人口·资源与环境, 2016, 26(2): 47-57.

为你推荐