A comparative analysis to forecast carbon dioxide emissions

Faruque, Md. Omer; Rabby, Md. Afser Jani; Ma, Hossain; Islam, Md. Rashidul; Rashid, M. Mushfiqur; Muyeen, S. M.

doi:10.1016/j.egyr.2022.06.025

Cited by 40 publications

(14 citation statements)

References 54 publications

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“…This depicts a rapid increase in CO 2 emissions from previous years. These results are in line with those of Aftab et al [ 2 ] and Faruque et al [ 3 ].…”

Section: Resultssupporting

confidence: 93%

“…Based on the forecasted value of the NNAR (1, 1) model, Pakistan's CO 2 emissions will be 1.048 metric tons per capita by 2028. These results are in line with those of Aftab et al [ 2 ] and Faruque et al [ 3 ]. To achieve the targeted goal in the fight of reducing CO 2 emissions, in order to accomplish the Paris Agreement of the UNFCCC, we propose that the Pakistan government should adapt the following: We should charge US$ 1000 per ton of CO 2 emitted by companies and entities in every quarter of the year [ 61 , 62 ].…”

Section: Discussionsupporting

confidence: 93%

“…Agriculture is the principal dominant area in Pakistan's economic growth irrespective of the growing industrial sector. However, this industrial drive, coupled with high population growth, has caused massive deforestation, resulting in less absorption of CO 2 by plants, leading to a higher CO 2 concentration in the atmosphere [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…The critical factor of Pakistan's commercial revolution is reworking its economy from organic economies based totally on human and animal energy to inorganic economies, which are completely dependent on fossil fuels. Interestingly, the by-product of fossil fuels is CO 2 , thereby contributing to the concentration of CO 2 in the environment [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…The growth in population means expanding cities by destroying green vegetation, which absorbs most of the CO 2 in the atmosphere. The growing population also means increasing cars with carbon emissions being used in the country [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Pakistan CO2 Emission Modelling and Forecasting: A Linear and Nonlinear Time Series Approach

Tawiah

Daniyal

Qureshi

2023

Journal of Environmental and Public Health

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Pakistan is considered among the top five countries with the highest CO2 emissions globally. This calls for pragmatic policy implementation by all stakeholders to bring finality to this alarming situation since it contributes greatly to global warming, thereby leading to climate change. This study is an attempt to make a comparative analysis of the linear time series models with nonlinear time series models to study CO2 emission data in Pakistan. These linear and nonlinear time series models were used to model and forecast future values of CO2 emissions for a short period. To assess and select the best model among these linear and nonlinear time series models, we used the root mean square error (RMSE) and the mean absolute error (MAE) as performance indicators. The outputs showed that the nonlinear machine learning models are the best among all other models, having the lowest RMSE and MAE values. Based on the forecasted value of the nonlinear machine learning neural network autoregressive model, Pakistan’s CO2 emissions will be 1.048 metric tons per capita by 2028. The increasing trend in emissions is a frightening and clear warning, suggesting that innovative policies must be initiated to reduce the trend. We encourage the Pakistan government to price CO2 emissions by companies and entities per ton, adapt electricity production from hydro, wind, and different sources with no emissions of CO2, initiate rigorous planting of more trees in the populated areas of Pakistan as forest covers, provide incentives to companies, organisations, institutions, and households to come out with clean technologies or use technologies with no CO2 emissions or those with lower ones, and fund more studies to develop clean and innovative technologies with less or no CO2 emissions.

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“…This depicts a rapid increase in CO 2 emissions from previous years. These results are in line with those of Aftab et al [ 2 ] and Faruque et al [ 3 ].…”

Section: Resultssupporting

confidence: 93%

Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Pakistan CO2 Emission Modelling and Forecasting: A Linear and Nonlinear Time Series Approach

Tawiah

Daniyal

Qureshi

2023

Journal of Environmental and Public Health

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Prediction method of regional carbon dioxide emissions in China under the target of peaking carbon dioxide emissions: A case study of Zhejiang

Xu,

Lv,

et al. 2024

Meteorological Applications

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All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently.

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Forecasting carbon dioxide emissions in Chongming: a novel hybrid forecasting model coupling gray correlation analysis and deep learning method

Wang,

Zhao,

Zhu

et al. 2024

Environ Monit Assess

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A comparative analysis to forecast carbon dioxide emissions

Cited by 40 publications

References 54 publications

Pakistan CO2 Emission Modelling and Forecasting: A Linear and Nonlinear Time Series Approach

Pakistan CO2 Emission Modelling and Forecasting: A Linear and Nonlinear Time Series Approach

Prediction method of regional carbon dioxide emissions in China under the target of peaking carbon dioxide emissions: A case study of Zhejiang

Forecasting carbon dioxide emissions in Chongming: a novel hybrid forecasting model coupling gray correlation analysis and deep learning method

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