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Cleaner Engineering and Technology
Article . 2021 . Peer-reviewed
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Cleaner Engineering and Technology
Article
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Energy and water consumption pattern in seafood processing industries and its optimization methodologies

Authors: S. Murali; V. Soumya Krishnan; P.R. Amulya; P.V. Alfiya; D.S. Aniesrani Delfiya; Manoj P. Samuel;

Energy and water consumption pattern in seafood processing industries and its optimization methodologies

Abstract

The study aims to comprehensively assess the energy and water consumption pattern in the seafood industries and suggest measures for the sustainable development of the sector. The unscrupulous usage of water and higher consumption of energy resulted in an uncontrolled generation of wastewater and enormous usage of fossil fuels. In the seafood industry, energy is primarily used for machinery and equipment handling processes such as freezing, refrigeration, heating, cooling, and drying. Similarly, a huge amount of clean water is used for cleaning machinery and plant, and for operations like washing of raw material, de-icing, defrosting, and salt splashing. As a consequence, in the energy-water nexus, additional energy is required for drawing fresh water and further processing of wastewater demands energy that results in air pollution and greenhouse gas emissions and incurring additional costs to the plant. Hence, this review mainly focuses on the significance of energy and water use optimization in the seafood industry, the existing trend of energy and water use pattern and management practices, optimization strategies, and the seafood-energy-water nexus and its environmental implications.

Keywords

TJ807-830, Environmental engineering, Fossil fuel, Wastewater treatment, TA170-171, Greenhouse gas, Carbon footprint, Renewable energy sources, Refrigeration

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Average
Top 10%
gold