期刊文献+

基于BP神经网络模型的水泥行业碳排放量预测及达峰路径研究——以徐州市为例

Research on Carbon Emission Prediction and Peak Path of Cement Industry Based on BP Neural Network Model:A Case Study of Xuzhou
下载PDF
导出
摘要 为开展水泥行业碳达峰碳中和路径研究,采用碳排放因子法计算了1995—2021年徐州市水泥行业CO_(2)排放量,运用BP神经网络模型对水泥行业CO_(2)排放量进行了评估,基于不同情景对2022—2030年CO_(2)排放量进行了预测。结果表明:1995—2021年徐州市水泥行业CO_(2)排放量为736.78~2732.27万t。水泥行业CO_(2)排放整体呈先升高后降低的趋势。2010年碳排放量达到峰值2732.27万t后,逐渐波动下降到2021年的812.81万t。BP神经网络模型预测水泥行业CO_(2)排放量是可行的。根据基准情景、低碳情景、强化低碳情景,通过BP神经网络模型对2022—2030年徐州市水泥行业碳排放量预测:基准情景下,2030年徐州市水泥行业CO_(2)排放量为2484.75万t,相比于2021年,年均增长率约为22.86%。低碳情景下,2030年CO_(2)排放量为1979.80万t,年均增长率约为15.95%。强化低碳情景下,2030年CO_(2)排放量为1502.43万t,年均增长率约为9.43%。建议从政策和技术升级等方面实施CO_(2)减排,助力徐州市水泥行业碳达峰碳中和的实现。 To study the pathway for carbon neutrality and peak carbon emissions in the cement industry,the CO_(2) emissions of the cement industry in Xuzhou City from 1995 to 2021 were calculated with the carbon emission factor method.The BP neural network model was used to evaluate the CO_(2) emissions of the cement industry,and the CO_(2) emissions from 2022 to 2030 on different scenarios were predicted based.The results indicate that from 1995 to 2021,the CO_(2) emissions from the cement industry in Xuzhou City ranged from 7.3678 million tons to 27.3227 million tons.The overall CO_(2) emissions in the cement industry show a trend of first increasing and then decreasing.After reaching a peak of 27.3227 million tons in 2010,carbon emissions gradually fluctuated and decreased to 8.1281 million tons in 2021.The BP neural network model is feasible for predicting CO_(2) emissions in the cement industry.Based on the baseline scenario,low-carbon scenario,and enhanced low-carbon scenario,the BP neural network model is used to predict the carbon emissions of the cement industry in Xuzhou City from 2022 to 2030.It is found that under the baseline scenario,the CO_(2) emissions of the cement industry in Xuzhou City in 2030 are 24.8475 million tons,with an average annual growth rate of about 22.86%compared to 2021.Under the low-carbon scenario,the CO_(2) emissions in 2030 are 19.798 million tons,with an average annual growth rate of about 15.95%.Under the strengthened low-carbon scenario,the CO_(2) emissions in 2030 will be 15.0243 million tons,with an average annual growth rate of about 9.43%.It is recommended to implement CO_(2) emission reduction from various aspects such as policy and technological upgrading,to help the cement industry in Xuzhou achieve carbon peak and carbon neutrality.
作者 万亚丽 徐辉 朱燕 陈孚尧 张远远 曹泊 吴蒙 赵欣 WAN Yali;XU Hui;ZHU Yan;CHEN Fuyao;ZHANG Yuanyuan;CAO Bo;WU Meng;ZHAO Xin(Jiangsu Mineral Resources and Geological Design and Research Institute(Testing Center of China National Administration of Coal Geology),Xuzhou,Jiangsu 221006;Jiangsu Province Greenhouse Gas Emission Accounting and Monitoring Technology Public Service Platform,Xuzhou,Jiangsu 221006;School of Earth Sciences,Chengdu University of technology,Chengdu,Sichuan 610059;General Survey and Research Institute of China Coal Geology Administration,Beijing 100039)
出处 《中国煤炭地质》 2024年第6期63-67,共5页 Coal Geology of China
基金 徐州市政策引导类计划(创新引领示范专项)“徐州市可持续发展碳排放综合管控技术研究及应用示范”(KC23381) 中国煤炭地质总局科技创新项目“碳排放核算与监测技术研究”(ZMKJ-2023-JBGS-07-01) 江苏省碳达峰碳中和科技创新基金专项“面向可持续发展目标的徐州市减排降碳关键技术研究及重大科技示范”(BE2023855)。
关键词 BP神经网络模型 碳排放量预测 碳达峰路径 BP neural network model carbon emission prediction carbon peak path
  • 相关文献

参考文献16

二级参考文献196

共引文献221

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部