Classification of industrial sectors based on their profiles of greenhouse gas emissions and policy implications
Abstract
Purpose: This article reports on a study of greenhouse gases emitted by industrial manufacturing sectors and gives insights into the appropriate orientation of emission reduction public programmes for better efficiency.
Design/methodology/approach: For this study, a classification of industrial manufacturing sectors based on their greenhouse gas emissions profiles was performed. Using economic data on the consumption of energy sources and a conversion process to obtain an estimation of greenhouse gas emissions, a profile of the direct/indirect emissions, concentration of emissions, total emissions and electrification level of each sector was developed. Finally, the sectors were segmented into four groups.
Findings: The emissions profile of each of the identified sector segments features specific characteristics; therefore, public programmes promoting greenhouse gas reduction should be specific to each segment. Special attention should be given to the segment that features a large amount of emissions concentrated in a relatively low number of firms and a low level of electrification but appears to use public funds disproportionate to their emissions.
Research limitations/implications: Due to the lack of data, some big emitter sectors, such as extractive industries and petroleum refining industries, are not included in the study.
Practical implications: Public programmes should consider different approaches to reducing greenhouse gas emissions based on sectoral segmentation. General projects are proposed for each of the identified segments.
Social implications: Improved public programmes should foster the reduction of greenhouse gas emissions and the United Nation’s Sustainable Development Goals 7 and 12.
Originality/value: The methodology proposed in this paper allows research to go beyond consideration of the local emissions of an industry to measure its direct and indirect emissions and focus on the firms that should invest in reducing them.
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PDFDOI: https://doi.org/10.3926/jiem.5375
This work is licensed under a Creative Commons Attribution 4.0 International License
Journal of Industrial Engineering and Management, 2008-2024
Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008
Publisher: OmniaScience