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ORIGINAL RESEARCH article

Front. Public Health
Sec. Environmental Health and Exposome
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1429058

Nordic Environmental Resilience: Balancing Air Quality and Energy Efficiency by Applying Artificial Neural Network

Provisionally accepted
Abul Ala Noman Abul Ala Noman 1Faheem Ur Rehman Faheem Ur Rehman 2*Irfanullah Khan Irfanullah Khan 2Mehran Ullah Mehran Ullah 3
  • 1 Ruhr University Bochum, Bochum, North Rhine-Westphalia, Germany
  • 2 King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
  • 3 School of Business and Creative Industries, University of the West of Scotland, Paisley, Scotland, United Kingdom

The final, formatted version of the article will be published soon.

    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 Artificical Neural Network (ANN) apporach. 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.

    Keywords: Environmental Management, Air Quality, energy efficiency, artificial neural network, Nordic countries

    Received: 07 May 2024; Accepted: 07 Oct 2024.

    Copyright: © 2024 Noman, Rehman, Khan and Ullah. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Faheem Ur Rehman, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.