预测哈萨克斯坦共和国工业生产中的温室气体排放

A. Zaidulla
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引用次数: 0

摘要

过量的温室气体(GHG)排放是一个环境问题。为确定减少温室气体排放的经济有效方法而进行的研究表明,需要对二氧化碳、一氧化二氮、甲烷和其他气体的排放动态进行建模。在这项研究中,计算了哈萨克斯坦共和国境内工业过程和生产的二氧化碳当量排放量。在预测时,使用了联合国气候变化框架公约提供的数据。为了预测工业生产的二氧化碳排放,使用了时间序列分析和预测工具:Prophet方法、k-means时间序列聚类分析、现代版本的ARIMA算法、指数平滑方法和线性回归。本研究提出了在2045年之前不采取任何行动的基线情景的比较模拟结果。本研究比较了四种模型,提出了一种有效的未来二氧化碳排放预测模型。使用各种误差度量进行精度比较,选择平均绝对百分比误差(MAPE)作为比较度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FORECASTING GREENHOUSE GAS EMISSIONS IN THE INDUSTRIAL PRODUCTION OF THE REPUBLIC OF KAZAKHSTAN
Excessive greenhouse gas (GHG) emissions are an environmental problem. Studies to determine cost-effective ways to reduce GHG emissions have revealed the need to model the dynamics of emissions of carbon dioxide, nitrous oxide, methane, and other gases. In this study, the calculation of CO2 equivalent emissions from industrial processes and production in the territory of the Republic of Kazakhstan was carried out. When forecasting, the data provided by the UN Framework Convention on Climate Change were used. To predict CO2 emissions from industrial production, tools for analysis and forecasting of time series were used: Prophet method, Cluster analysis of k-means time series, modern versions of ARIMA algorithms, exponential smoothing methods, and linear regression. This study presents comparative simulation results based on a baseline scenario with no action until 2045.This study compares four models to suggest an effective one for future CO2 emission forecasting. The accuracy comparison is conducted using various error measures, with the mean absolute percentage error (MAPE) chosen as the metric for comparison. 
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