JOURNAL ARTICLE

Reducing air pollution through smart energy management in industrial clusters of India.

  • Published In: Environmental Progress & Sustainable Energy, 2023, v. 42, n. 4. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Dube, Sanjay 3 of 3

Abstract

Smart energy management, along with clean technologies and advanced pollution control measures has proven to be an effective strategy for reducing air pollution in both developed and transitioning economies and holds significant potential to reduce emissions from industries and power plants—two of the major sources of air pollution in many of India's urban areas. This manuscript presents the results from a project and provides a critical proof of concept to show that developing country cities can achieve significant, measurable reductions in air pollution, Volatile Organic Compound emissions and greenhouse gas emissions through investing in smart energy management and advance control technologies. Achieving this goal, however, requires addressing two key challenges: (1) lack of a demonstrated link between smart energy management and air quality improvements in India; and (2) the need to scale up development, financing, and implementation of smart energy solutions, including energy efficiency and clean technology measures that can help address air pollution in industrialized urban areas, critically polluted areas by offsetting fossil fuel use for diesel‐ and coal‐fired electricity generation. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Environmental Progress & Sustainable Energy. 2023/07, Vol. 42, Issue 4, p1
  • Document Type:Article
  • Subject Area:Mining and Mineral Resources
  • Publication Date:2023
  • ISSN:19447442
  • DOI:10.1002/ep.14169
  • Accession Number:164960765
  • 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.)

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