Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also ...Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.展开更多
针对协方差分析描述函数法(Covariance Analysis Describing Function Technique,CADET)在分析存在内部参数摄动的不确定系统时精度不高的问题,提出了一种分析存在内部参数摄动的导弹姿态控制系统新型精度分析方法。结合传统的CADET方法...针对协方差分析描述函数法(Covariance Analysis Describing Function Technique,CADET)在分析存在内部参数摄动的不确定系统时精度不高的问题,提出了一种分析存在内部参数摄动的导弹姿态控制系统新型精度分析方法。结合传统的CADET方法,对含有参数摄动的广义非线性项进行统计线性化,得到状态均值和协方差的增广传播方程,采用改进的CADET方法对某型号导弹的姿态控制系统进行了数学仿真。仿真结果表明了改进的CADET方法可快速、有效分析存在外部干扰和内部参数摄动系统的精度。展开更多
基金financially supported by the National Natural Science Foundation of China(41771535)the National Social Science Foundation Major Project(20&ZD092)。
文摘Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.
文摘针对协方差分析描述函数法(Covariance Analysis Describing Function Technique,CADET)在分析存在内部参数摄动的不确定系统时精度不高的问题,提出了一种分析存在内部参数摄动的导弹姿态控制系统新型精度分析方法。结合传统的CADET方法,对含有参数摄动的广义非线性项进行统计线性化,得到状态均值和协方差的增广传播方程,采用改进的CADET方法对某型号导弹的姿态控制系统进行了数学仿真。仿真结果表明了改进的CADET方法可快速、有效分析存在外部干扰和内部参数摄动系统的精度。
