JOURNAL ARTICLE
Sustainable energy generation – Scenario development for Pakistan in the context of WWF's 2050 vision.
Published In: Environmental Progress & Sustainable Energy, 2023, v. 42, n. 6. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Shah, Salman; Aized, Tauseef; Sumair, Muhammad; Rehman, Syed Muhammad Sohail 3 of 3
Abstract
Pakistan is fighting a long‐standing energy crisis with an unbalanced, fossil‐fuel dominated energy mix mired with climatic catastrophes. World Wide Fund for Nature (WWF), in its fight against climate change, has proposed a global energy model that illustrates a shift to renewable energy completely by the year 2050. In this study, we have scaled down that energy model for Pakistan to demonstrate country level implementation of WWF's vision. Scenario‐based energy model of Pakistan is developed in this research using LEAP Software. Four scenarios namely, Business‐As‐Usual (BAU), Alternative and Renewable Energy (ARE), Green Energy (GE) and Advanced Sustainable Energy (ASE) are developed. The BAU scenario is based on government's existing policies and plans, and ASE scenario shows the crux of WWF's Global vision on Pakistan's scale. ARE and GE are intermediate scenarios reflecting a transition from BAU to ASE. Simulation results demonstrated the demand in ASE is halved as compared to BAU and its energy mix is homogeneous and completely renewable. In conclusion, ASE gave country‐level insights into WWF's vision towards the ways to contend climate change. This work inspires country‐scale modeling of WWF's vision for other countries as well. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Environmental Progress & Sustainable Energy. 2023/11, Vol. 42, Issue 6, p1
- Document Type:Article
- Subject Area:Diplomacy and International Relations
- Publication Date:2023
- ISSN:19447442
- DOI:10.1002/ep.14176
- Accession Number:173369294
- Copyright Statement:Copyright of Environmental Progress & Sustainable Energy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.