The forecast of CO₂ emissions is very crucial, especially for Pakistan as it is one of the top victims of climate change. A univariate model, (ARIMA) autoregressive integrated moving average (ARIMA), was used to forecast CO₂ emissions for Pakistan. The CO₂ emissions scenarios were developed for Pakistan till 2020, forecasting them further to 2030. The scenarios developed include China–Pakistan Economic Corridor (CPEC) scenario, where CO₂ emissions from high‐priority energy projects under the CPEC were considered. The scenarios attempt to estimate the impactful emission reduction percentage, which the country needs to adopt along with other necessary changes in the existing policies of the country. The forecast results clearly indicate that the emissions are bound to increase under business as usual and CPEC scenarios and the country would fail to meet the Nationally Determined Contributions pledged at COP21. In other scenarios, where we assumed the country has adopted mitigatory strategies to curb the emissions, the forecast shows decreased CO₂ emissions for Pakistan. The mean absolute percentage error for all the forecasts was found to be less than 10%, making the forecast highly accurate. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

中文翻译：

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在不同情况下预测巴基斯坦能源消耗产生的二氧化碳排放量：中巴经济走廊

对CO ₂排放的预测非常关键，特别是对于巴基斯坦而言，因为它是气候变化的最大受害者之一。使用单变量模型（ARIMA）自回归综合移动平均值（ARIMA）预测巴基斯坦的CO ₂排放量。巴基斯坦一直到2020年都制定了CO ₂排放情景，并预测了到2030年的排放。情景包括中巴经济走廊（CPEC）情景，其中CO ₂考虑了CPEC的高优先级能源项目的排放。这些方案试图估算有影响的减排百分比，该国需要采用该百分比以及该国现有政策中的其他必要变化。预测结果清楚地表明，在照常营业和CPEC情景下，排放量必将增加，而该国将无法满足COP21承诺的国家自主贡献。在其他情况下，如果我们假设该国已采取减排策略来抑制排放，则该预测表明CO ₂减少了。排放量。发现所有预测的平均绝对百分比误差均小于10％，从而使预测高度准确。©2020年化学工业协会和John Wiley＆Sons，Ltd.