Forecasting and reduction pathways for CO2 emissions in the power industry:a case study of Xuzhou city
Utilizing data from the Xuzhou Statistical Yearbook from 1996 to 2022,this study analyzes CO2 emission characteristics of the power industry in Xuzhou city.The CO2 emissions have been computed using the method ac-cording to Bin chanjia et al.,and the BP neural network model served to predict and assess the power industry's CO2 emissions.The findings indicate that CO2 emissions in Xuzhou's power sector ranged from 10.026 84 to 44.620 32 million tons between 1995 and 2021.The CO2 emission coefficient per unit of coal consumption surged from 1.027 t/MWh in 1995 to 1.043 t/MWh in 1998,subsequently declining to 0.820 t/MWh by 2021.Independ-ent sample t test comparing predicted and actual CO2 emission figures under different scenarios validate the BP neu-ral network model's predictive capability for the power industry's emissions.Projections indicate that by 2030,CO2 emissions will reach 53.823 58 million tons under a baseline scenario,44.815 23 million tons under a low-carbon scenario,and 40.771 67 million tons under an enhanced low-carbon scenario for Xuzhou's power sector.The study proposes that Xuzhou's power industry can undertake carbon emission reduction measures at the generation,grid,and consumption sectors.
Xuzhou citypower industryCO2 emissionsBP neural network model
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