Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network

Maintaining public health and environmental safety in the Nordic nations calls for a strict plan to define exact benchmarks on air quality and energy efficiency. This study investigates the complicated interaction of decentralized energy production (DEP) with energy efficiency, and air quality index in the Nordic nations from 1990 to 2022 using System GMM and Artificial Neural Network (ANN) approach. Our research explored positive role of decentralized energy production and technological advancement to propel notable increases in energy efficiency, hence lowering pollution expressed as PM2.5 level. Our research indicates, however, that although international trade, GDP and urbanization assist to enhance energy efficiency, they also contribute to pollution by raising PM2.5 Level by higher energy usage. Furthermore damaging to environmental quality is the persistent link shown by economic disparity and the energy price index with increased degrees of pollution and less energy efficiency. Policy frameworks must devised sustainable development policy (decentralized energy production) to significantly improve energy efficiency and lower the amount of pollution. This calls for proper urban planning and a close observation of the possible drawbacks of growing GDP, trade, economic disparity, and energy expenses.

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Publication Details

Journal
Frontiers in Public Health
Published
2024-11-05
DOI
https://doi.org/10.3389/fpubh.2024.1429058
Citations
2
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
2.26

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article

Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network

Faheem Ur Rehman, Mehran Ullah, Irfanullah Khan, Abul Ala Noman
2 citations
Frontiers in Public Health
Energy, Environment, Economic Growth
2.26
article

Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network

Faheem Ur Rehman, Mehran Ullah, Irfanullah Khan, Abul Ala Noman
article en
2 citations

Abstract

Maintaining public health and environmental safety in the Nordic nations calls for a strict plan to define exact benchmarks on air quality and energy efficiency. This study investigates the complicated interaction of decentralized energy production (DEP) with energy efficiency, and air quality index in the Nordic nations from 1990 to 2022 using System GMM and Artificial Neural Network (ANN) approach. Our research explored positive role of decentralized energy production and technological advancement to propel notable increases in energy efficiency, hence lowering pollution expressed as PM2.5 level. Our research indicates, however, that although international trade, GDP and urbanization assist to enhance energy efficiency, they also contribute to pollution by raising PM2.5 Level by higher energy usage. Furthermore damaging to environmental quality is the persistent link shown by economic disparity and the energy price index with increased degrees of pollution and less energy efficiency. Policy frameworks must devised sustainable development policy (decentralized energy production) to significantly improve energy efficiency and lower the amount of pollution. This calls for proper urban planning and a close observation of the possible drawbacks of growing GDP, trade, economic disparity, and energy expenses.

Frontiers in Public HealthVol. 12
King Fahd University of Petroleum and Minerals (SA), University of the West of Scotland (GB), Ruhr University Bochum (DE), Middle East University (JO)
King Fahd University of Petroleum and Minerals
Affordable and clean energy
Openalex Percentile: Top 8%
Energy, Environment, Economic Growth
2.26
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Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network — Faheem Ur Rehman, Mehran Ullah, et al. · Frontiers in Public Health (2024) | TGRS Research Map | TGRS