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Forecasting CO 2 emissions from energy consumption in Pakistan under different scenarios: The China–Pakistan Economic Corridor
Author(s) -
Malik Aysha,
Hussain Ejaz,
Baig Sofia,
Khokhar Muhammad Fahim
Publication year - 2020
Publication title -
greenhouse gases: science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.45
H-Index - 32
ISSN - 2152-3878
DOI - 10.1002/ghg.1968
Subject(s) - autoregressive integrated moving average , china , univariate , environmental science , greenhouse gas , natural resource economics , energy consumption , consumption (sociology) , climate change , economics , agricultural economics , time series , geography , engineering , mathematics , statistics , ecology , social science , archaeology , multivariate statistics , sociology , electrical engineering , biology
The forecast of CO 2 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 CO 2 emissions for Pakistan. The CO 2 emissions scenarios were developed for Pakistan till 2020, forecasting them further to 2030. The scenarios developed include China–Pakistan Economic Corridor (CPEC) scenario, where CO 2 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 CO 2 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.