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Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis
Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom”...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516983/ https://www.ncbi.nlm.nih.gov/pubmed/36141618 http://dx.doi.org/10.3390/ijerph191811343 |
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author | Han, Jingwei Tan, Zhixiong Chen, Maozhi Zhao, Liang Yang, Ling Chen, Siying |
author_facet | Han, Jingwei Tan, Zhixiong Chen, Maozhi Zhao, Liang Yang, Ling Chen, Siying |
author_sort | Han, Jingwei |
collection | PubMed |
description | Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom” method, input–output analysis (IOA) has become a universally applicable CF assessment tool for tracing the carbon footprint embodied in economic activities. A wide range of CF studies from the perspective of the IOA model have been presented and have made great progress. It is crucial to have a better understanding of what the relevant research focuses on in this field, yet so far a systematic synopsis of the literature is missing. The purpose of this paper is to explore the knowledge structure and frontier trends in respect of the IOA model applied to CF research using scientometric visualization analysis. The main findings of this paper are as follows. (1) Published articles show a two-stage increase in the period 2008 to 2021, and present a complex academic network of countries, authors, and institutions in this important domain. (2) The classic studies are mainly divided into three categories: literature reviews, database application introduction, and CF accounting in different scales. (3) The research hotspots and trends show that the research scales tend to be more microscopic and applications of models tend to be more detailed. In addition, supply-chain analysis and driver-factor analysis will probably become the main research directions in the future. |
format | Online Article Text |
id | pubmed-9516983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95169832022-09-29 Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis Han, Jingwei Tan, Zhixiong Chen, Maozhi Zhao, Liang Yang, Ling Chen, Siying Int J Environ Res Public Health Review Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom” method, input–output analysis (IOA) has become a universally applicable CF assessment tool for tracing the carbon footprint embodied in economic activities. A wide range of CF studies from the perspective of the IOA model have been presented and have made great progress. It is crucial to have a better understanding of what the relevant research focuses on in this field, yet so far a systematic synopsis of the literature is missing. The purpose of this paper is to explore the knowledge structure and frontier trends in respect of the IOA model applied to CF research using scientometric visualization analysis. The main findings of this paper are as follows. (1) Published articles show a two-stage increase in the period 2008 to 2021, and present a complex academic network of countries, authors, and institutions in this important domain. (2) The classic studies are mainly divided into three categories: literature reviews, database application introduction, and CF accounting in different scales. (3) The research hotspots and trends show that the research scales tend to be more microscopic and applications of models tend to be more detailed. In addition, supply-chain analysis and driver-factor analysis will probably become the main research directions in the future. MDPI 2022-09-09 /pmc/articles/PMC9516983/ /pubmed/36141618 http://dx.doi.org/10.3390/ijerph191811343 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Han, Jingwei Tan, Zhixiong Chen, Maozhi Zhao, Liang Yang, Ling Chen, Siying Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis |
title | Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis |
title_full | Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis |
title_fullStr | Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis |
title_full_unstemmed | Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis |
title_short | Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis |
title_sort | carbon footprint research based on input–output model—a global scientometric visualization analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516983/ https://www.ncbi.nlm.nih.gov/pubmed/36141618 http://dx.doi.org/10.3390/ijerph191811343 |
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