利用STL(Seasonal-Trend decomposition using Loess,时间序列分解算法)模型对工业园区运行阶段的建筑碳排放进行预测分析,介绍电碳模型构建技术路线、模型构建的STL和线性回归,给出某高新园区2021年到2022年碳排放量的预测结果。可为...利用STL(Seasonal-Trend decomposition using Loess,时间序列分解算法)模型对工业园区运行阶段的建筑碳排放进行预测分析,介绍电碳模型构建技术路线、模型构建的STL和线性回归,给出某高新园区2021年到2022年碳排放量的预测结果。可为园区规划双碳路径、制定减排计划、开展节能减排手段提供数据支撑,辅助园区实现绿色低碳发展目标。展开更多
Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study...Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study uses the IPCC calculation method to calculate the industrial carbon emissions in Shaanxi Province.The prediction model for industrial carbon emissions in Shaanxi Province was constructed based on the STIRPAT model from three aspects:population,economy,and technology.By setting three scenario models,the industrial carbon emissions from 2021 to 2035 and the time to achieve peak carbon neutrality were then predicted.The results show that the industry in Shaanxi Province cannot achieve a carbon peak under the baseline scenario,although it can achieve carbon peaking in 2030 under a low-carbon scenario or in 2025 under an enhanced low-carbon scenario.The predicted carbon peak values are 209.11 million t and 188.36 million t,respectively.Based on the results of this study,four policy recommendations are proposed:(1)strengthen publicity and education efforts to increase public participation in energy conservation and emission reduction;(2)promote the green transformation of industry and develop a green economy,including the active development of energy-saving and emission reduction technologies;(3)accelerate the implementation of industrial carbon reduction;and(4)promote the development and utilization of clean energy and increase efforts to adjust the energy structure.展开更多
文摘利用STL(Seasonal-Trend decomposition using Loess,时间序列分解算法)模型对工业园区运行阶段的建筑碳排放进行预测分析,介绍电碳模型构建技术路线、模型构建的STL和线性回归,给出某高新园区2021年到2022年碳排放量的预测结果。可为园区规划双碳路径、制定减排计划、开展节能减排手段提供数据支撑,辅助园区实现绿色低碳发展目标。
基金The Shaanxi Social Science Federation Foundation Project(2021HZ1118)The Shaanxi Normal University Graduate Student InnovationTeam Project(TD2020006Y).
文摘Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study uses the IPCC calculation method to calculate the industrial carbon emissions in Shaanxi Province.The prediction model for industrial carbon emissions in Shaanxi Province was constructed based on the STIRPAT model from three aspects:population,economy,and technology.By setting three scenario models,the industrial carbon emissions from 2021 to 2035 and the time to achieve peak carbon neutrality were then predicted.The results show that the industry in Shaanxi Province cannot achieve a carbon peak under the baseline scenario,although it can achieve carbon peaking in 2030 under a low-carbon scenario or in 2025 under an enhanced low-carbon scenario.The predicted carbon peak values are 209.11 million t and 188.36 million t,respectively.Based on the results of this study,four policy recommendations are proposed:(1)strengthen publicity and education efforts to increase public participation in energy conservation and emission reduction;(2)promote the green transformation of industry and develop a green economy,including the active development of energy-saving and emission reduction technologies;(3)accelerate the implementation of industrial carbon reduction;and(4)promote the development and utilization of clean energy and increase efforts to adjust the energy structure.
