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Analysis of the Impact of Livestock Structure on Carbon Emissions of Animal Husbandry: A Sustainable Way to Improving Public Health and Green Environment
Carbon emissions of animal husbandry have been gaining increasing attention due to their high share in global carbon emissions. In this regard, it is essential to assess the regional differences, dynamic evolution patterns, convergence characteristics, and the impact of livestock structure on carbon...
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Published in: | Frontiers in public health 2022-02, Vol.10, p.835210-835210 |
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description | Carbon emissions of animal husbandry have been gaining increasing attention due to their high share in global carbon emissions. In this regard, it is essential to assess the regional differences, dynamic evolution patterns, convergence characteristics, and the impact of livestock structure on carbon emissions of animal husbandry. Using data from 30 provincial administrative regions from 2000 to 2018 in China, this study employs the Thiel index method, kernel density analysis, and convergence analysis to quantify the impact of livestock structure on carbon emissions of animal husbandry. The statistical results reveal that carbon emissions of animal husbandry exhibit a rising and declining trend. Specifically, the carbon emissions of animal husbandry are highest in agricultural areas (with a declining trend), followed by agro-pastoral areas (with a declining trend), and the pastoral areas (with a rising trend). It is further revealed that there are no δ convergence and β convergence of carbon emissions of animal husbandry. Finally, essential and useful policy recommendations are put forward to inhibit carbon emissions of animal husbandry. |
doi_str_mv | 10.3389/fpubh.2022.835210 |
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In this regard, it is essential to assess the regional differences, dynamic evolution patterns, convergence characteristics, and the impact of livestock structure on carbon emissions of animal husbandry. Using data from 30 provincial administrative regions from 2000 to 2018 in China, this study employs the Thiel index method, kernel density analysis, and convergence analysis to quantify the impact of livestock structure on carbon emissions of animal husbandry. The statistical results reveal that carbon emissions of animal husbandry exhibit a rising and declining trend. Specifically, the carbon emissions of animal husbandry are highest in agricultural areas (with a declining trend), followed by agro-pastoral areas (with a declining trend), and the pastoral areas (with a rising trend). It is further revealed that there are no δ convergence and β convergence of carbon emissions of animal husbandry. Finally, essential and useful policy recommendations are put forward to inhibit carbon emissions of animal husbandry.</description><subject>animal husbandry</subject><subject>Animal Husbandry - methods</subject><subject>Animals</subject><subject>Carbon - analysis</subject><subject>carbon emission</subject><subject>China</subject><subject>geographical heterogeneity</subject><subject>Livestock</subject><subject>livestock breeding</subject><subject>livestock structure</subject><subject>Public Health</subject><issn>2296-2565</issn><issn>2296-2565</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkstuEzEUhkcIRKvSB2CDvGST4Pt4WCBFUWkiRSpSQSwtj-dM4jKxg-2JlEfhbXGStmpXvp3_Oxf_VfWR4CljqvnS78Z2M6WY0qlighL8prqktJETKqR4-2J_UV2n9IAxJphxTMn76qLEU1ZzeVn9m3kzHJJLKPQobwAttztj8_G0cntIOdg_6D7H0eYxAgoezU1sy3KzdSm54E_CmXdbM6DFmFrju3j4imbofkzZOG_aAdBvc0A5HNkx7J1fox9jOziLFmCGvEFFg24jQKH6vYvBb8HnD9W73gwJrh_Xq-rX95uf88VkdXe7nM9WE8ulyBOuAIjoJOlox1nbgSCY4lY1VDVSUGGh7zmhjTFtI2prBe46wWuGlQFQuGFX1fLM7YJ50LtYOokHHYzTp4sQ19rE7OwAminJsG2EbCTmvCamLyXUBENvOmmpLKxvZ1b5my10trQRzfAK-vrFu41eh71WqmaiVgXw-REQw9-xjF-XMVsYBuMhjEmXHLw01WBeQsk51MaQUoT-OQ3B-ugQfXKIPjpEnx1SNJ9e1vesePID-w-YVLmo</recordid><startdate>20220211</startdate><enddate>20220211</enddate><creator>Shi, Rubiao</creator><creator>Irfan, Muhammad</creator><creator>Liu, Guangliang</creator><creator>Yang, Xiaodong</creator><creator>Su, Xufeng</creator><general>Frontiers Media S.A</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20220211</creationdate><title>Analysis of the Impact of Livestock Structure on Carbon Emissions of Animal Husbandry: A Sustainable Way to Improving Public Health and Green Environment</title><author>Shi, Rubiao ; Irfan, Muhammad ; Liu, Guangliang ; Yang, Xiaodong ; Su, Xufeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c465t-48ee15d61d2d43bde51020b892896525ceff4129aab957cc50dd547308aee8093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>animal husbandry</topic><topic>Animal Husbandry - methods</topic><topic>Animals</topic><topic>Carbon - analysis</topic><topic>carbon emission</topic><topic>China</topic><topic>geographical heterogeneity</topic><topic>Livestock</topic><topic>livestock breeding</topic><topic>livestock structure</topic><topic>Public Health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shi, Rubiao</creatorcontrib><creatorcontrib>Irfan, Muhammad</creatorcontrib><creatorcontrib>Liu, Guangliang</creatorcontrib><creatorcontrib>Yang, Xiaodong</creatorcontrib><creatorcontrib>Su, Xufeng</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shi, Rubiao</au><au>Irfan, Muhammad</au><au>Liu, Guangliang</au><au>Yang, Xiaodong</au><au>Su, Xufeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analysis of the Impact of Livestock Structure on Carbon Emissions of Animal Husbandry: A Sustainable Way to Improving Public Health and Green Environment</atitle><jtitle>Frontiers in public health</jtitle><addtitle>Front Public Health</addtitle><date>2022-02-11</date><risdate>2022</risdate><volume>10</volume><spage>835210</spage><epage>835210</epage><pages>835210-835210</pages><issn>2296-2565</issn><eissn>2296-2565</eissn><abstract>Carbon emissions of animal husbandry have been gaining increasing attention due to their high share in global carbon emissions. In this regard, it is essential to assess the regional differences, dynamic evolution patterns, convergence characteristics, and the impact of livestock structure on carbon emissions of animal husbandry. Using data from 30 provincial administrative regions from 2000 to 2018 in China, this study employs the Thiel index method, kernel density analysis, and convergence analysis to quantify the impact of livestock structure on carbon emissions of animal husbandry. The statistical results reveal that carbon emissions of animal husbandry exhibit a rising and declining trend. Specifically, the carbon emissions of animal husbandry are highest in agricultural areas (with a declining trend), followed by agro-pastoral areas (with a declining trend), and the pastoral areas (with a rising trend). It is further revealed that there are no δ convergence and β convergence of carbon emissions of animal husbandry. 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subjects | animal husbandry Animal Husbandry - methods Animals Carbon - analysis carbon emission China geographical heterogeneity Livestock livestock breeding livestock structure Public Health |
title | Analysis of the Impact of Livestock Structure on Carbon Emissions of Animal Husbandry: A Sustainable Way to Improving Public Health and Green Environment |
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