Interaction Between Decomposed Energy Utilization and Environmental Health in Canada: A Cointegration and Counterfactual Analysis Approach

Despite the substantial impact of various energy consumption parameters on the generation of nitrous oxide and methane emissions, which contribute to environmental degradation, most prior research has primarily concentrated on carbon emissions and ecological footprint metrics. This study seeks to address this void by examining the intricate link between total energy usage and its disaggregated components, including natural gas, oil, coal, renewable, and nuclear energy sources, and their role in four critical aspects of the environment in Canada. Incorporating time series data spanning from 1990 to 2022, we employ the dynamic autoregressive distributed lag (DARDL) approach, which reveals that total energy consumption, particularly from nonrenewable sources, such as coal, natural gas, and oil, contributes to environmental degradation by accelerating ecological footprint, carbon, nitrous oxide, and methane emissions. Conversely, renewable and nuclear energy sources have the opposite effect, reducing environmental decay. Additionally, counterfactual analysis examines the effects of (±) 1% and (±) 5% shocks from the predictors to predicted variables. Moreover, the study evaluates the robustness of the findings derived from the DARDL estimation technique by employing the Kernel‐based Regularized Least Squares (KRLSs) machine learning algorithm. While the environmental impacts of various energy sources are well‐documented, this study offers a novel contribution by analyzing the differentiated effects of both renewable and nonrenewable energy consumption on CO 2 , CH 4 , and N 2 O emissions in a single framework, with a specific focus on the Canadian context. Unlike previous studies, this research integrates economic policy uncertainty and technological innovation as vibrant variables, revealing their distinct roles in amplifying or mitigating environmental degradation. Finally, important policy implications are discussed.

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Publication Details

Journal
International Journal of Energy Research
Published
2025-01-01
DOI
https://doi.org/10.1155/er/1173970
Citations
2
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
6.26

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article

Interaction Between Decomposed Energy Utilization and Environmental Health in Canada: A Cointegration and Counterfactual Analysis Approach

Brian Ceh, Md. Idris Ali, Md. Monirul Islam
2 citations
International Journal of Energy Research
Energy, Environment, Economic Growth
6.26
article

Interaction Between Decomposed Energy Utilization and Environmental Health in Canada: A Cointegration and Counterfactual Analysis Approach

Brian Ceh, Md. Idris Ali, Md. Monirul Islam
article en
2 citations

Abstract

Despite the substantial impact of various energy consumption parameters on the generation of nitrous oxide and methane emissions, which contribute to environmental degradation, most prior research has primarily concentrated on carbon emissions and ecological footprint metrics. This study seeks to address this void by examining the intricate link between total energy usage and its disaggregated components, including natural gas, oil, coal, renewable, and nuclear energy sources, and their role in four critical aspects of the environment in Canada. Incorporating time series data spanning from 1990 to 2022, we employ the dynamic autoregressive distributed lag (DARDL) approach, which reveals that total energy consumption, particularly from nonrenewable sources, such as coal, natural gas, and oil, contributes to environmental degradation by accelerating ecological footprint, carbon, nitrous oxide, and methane emissions. Conversely, renewable and nuclear energy sources have the opposite effect, reducing environmental decay. Additionally, counterfactual analysis examines the effects of (±) 1% and (±) 5% shocks from the predictors to predicted variables. Moreover, the study evaluates the robustness of the findings derived from the DARDL estimation technique by employing the Kernel‐based Regularized Least Squares (KRLSs) machine learning algorithm. While the environmental impacts of various energy sources are well‐documented, this study offers a novel contribution by analyzing the differentiated effects of both renewable and nonrenewable energy consumption on CO 2 , CH 4 , and N 2 O emissions in a single framework, with a specific focus on the Canadian context. Unlike previous studies, this research integrates economic policy uncertainty and technological innovation as vibrant variables, revealing their distinct roles in amplifying or mitigating environmental degradation. Finally, important policy implications are discussed.

International Journal of Energy ResearchVol. 2025(1)
Ural Federal University (RU), University of Dhaka (BD), Green University of Bangladesh (BD), Toronto Metropolitan University (CA)
Russian Science Foundation
Openalex Percentile: Top 4%
Energy, Environment, Economic Growth
6.26
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