河北省碳排放预测及不确定性分析

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关键词：碳排放预测；GM-BP组合模型；灰色关联分析；蒙特卡洛模拟；不确定性分析中图分类号：X24 文献标识码：A 文章编号：1008-9500(2026)03-0162-05DOI: 10.3969/j.issn.1008-9500.2026.03.049

Carbon Emission Prediction and Uncertainty Analysis in Hebei Province

LIJiawen,ZHANGJingxiu,ZHUiyi (College of Science,North China University of Scienceand Technology,TangshanO630oo,China)

Abstract:For the issue of carbon emission prediction in Hebei province,acombined forecasting model(GM-BP) integrating greysystem theory[GM(1,1)model],Back Propagation (BP)neural network,and Monte Carlo simulation uncertaintyanalysis isproposed.Throughgreyrelationalanalysis,coalconsumption,GrossDomesticProduct(GDP),and industrialoutputarescreenedaskeydrivingfactors.TheGM(1,1)modelisfirstusedforinitialtrendprediction,andthen theBP neural network isusedtooptimizenonlinearfiting,whichcansignificantlyimprovepredictionaccuracy(relative error controlled within ±1% ).Monte Carlo simulation results show that the model is robust under perturbation of input variables,and the 95% confidence interval of carbon emission predictions is relatively concentrated.Sensitivity analysis indicatesthatcoalconsumptionhasthemostsignificant impactoncarbonemissons.Accordingly,itisrecommendedthat Hebei provinceshouldaccelerate energy structure transformation,promote green industrialupgrading,andestablish a dynamic carbon emission early warning mechanism,providing ascientific basis for achieving thecarbon peak and carbon neutrality goals.

Keywords:carbon emision prediction;GM-BPcombined model;grey relational analysis; Monte Carlo simulation; uncertainty analysis

随着全球气候变化问题日益严峻，应对碳排放成为世界各国的重要议题。（剩余8976字）