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Energy intensity, renewable energy, and air quality: fresh evidence from BIMSTEC countries through method of moments quantile model

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Abstract

In the wake of the Kyoto Protocols, Sustainable Development Goals, and COP26, the urgency to reduce Greenhouse Gas emissions has gained attention among policymakers and academicians. Against this backdrop, the existing literature employed various theoretical frameworks to explore the linkage between air quality and economic growth. In this study, we used annual data from the BIMSTEC member countries and rigorously applied the quantile regression methodology, as Machado and Silva (J Econ 213:145–173, 2019. https://doi.org/10.1016/j.jeconom.2019.04.009) outlined in their seminal work. Quantile-based analysis showed that the N-shaped Environmental Kuznets Curve holds for the BIMSTEC region. Also, the result shows that energy intensity use has an adverse effect on air quality at median and above quantiles. Contrarily, renewable energy use has a mitigating impact on air quality, which is significant at all quantile levels. In addition, urbanization increases pollution levels significantly across the conditional distribution of quantiles. The region’s decarbonization strategy should concentrate on improving energy-efficient technology to mitigate energy intensity and increase energy efficiency. Sustainable development policies should also support and invest in renewable energy generation.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ECG:

Economic growth

END:

Environmental degradation

REN:

Renewable energy

ENC:

Energy consumption

GDP:

Gross domestic product

ENI:

Energy intensity

COE:

Carbon dioxide emissions

URB:

Urbanization

CD:

Cross-sectional dependence

SDG:

Sustainable development goals

UN:

United Nations

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Correspondence to Ashar Awan.

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Bilgili, F., Rahut, D.B. & Awan, A. Energy intensity, renewable energy, and air quality: fresh evidence from BIMSTEC countries through method of moments quantile model. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04490-z

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  • DOI: https://doi.org/10.1007/s10668-024-04490-z

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