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Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model
Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we appl...
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Published in: | Land (Basel) 2024-05, Vol.13 (5), p.585 |
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description | Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude. |
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An Analysis Based on Decoupling Theory and Spatial EKC Model</title><source>Publicly Available Content Database</source><creator>Wu, Haoyue ; Ding, Bangwen ; Liu, Lu ; Zhou, Lei ; Meng, Yue ; Zheng, Xiangjiang</creator><creatorcontrib>Wu, Haoyue ; Ding, Bangwen ; Liu, Lu ; Zhou, Lei ; Meng, Yue ; Zheng, Xiangjiang</creatorcontrib><description>Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude.</description><identifier>ISSN: 2073-445X</identifier><identifier>EISSN: 2073-445X</identifier><identifier>DOI: 10.3390/land13050585</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agricultural industry ; Agricultural land ; agricultural land-use carbon emissions ; Agricultural production ; Agriculture ; Analysis ; Carbon dioxide ; China ; Climate change ; Crops ; Cultivation ; Decoupling ; Diesel fuels ; Economic development ; emission peak ; Emissions ; Emissions (Pollution) ; Energy consumption ; Environmental Kuznets curve ; Global warming ; Grain cultivation ; greenhouse gas emissions ; Greenhouse gases ; Land use ; Livestock ; Livestock breeding ; Pesticides ; Rice ; Soil management ; spatial Durbin model ; Tapio decoupling index</subject><ispartof>Land (Basel), 2024-05, Vol.13 (5), p.585</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. 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/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c363t-6a71ed74906e5c8a0a7233655aa3400969c1046b01e1d1829dfd5d3db160de653</cites><orcidid>0000-0002-9296-4303</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3059592592/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3059592592?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Wu, Haoyue</creatorcontrib><creatorcontrib>Ding, Bangwen</creatorcontrib><creatorcontrib>Liu, Lu</creatorcontrib><creatorcontrib>Zhou, Lei</creatorcontrib><creatorcontrib>Meng, Yue</creatorcontrib><creatorcontrib>Zheng, Xiangjiang</creatorcontrib><title>Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model</title><title>Land (Basel)</title><description>Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. 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An Analysis Based on Decoupling Theory and Spatial EKC Model</atitle><jtitle>Land (Basel)</jtitle><date>2024-05-01</date><risdate>2024</risdate><volume>13</volume><issue>5</issue><spage>585</spage><pages>585-</pages><issn>2073-445X</issn><eissn>2073-445X</eissn><abstract>Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/land13050585</doi><orcidid>https://orcid.org/0000-0002-9296-4303</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural industry Agricultural land agricultural land-use carbon emissions Agricultural production Agriculture Analysis Carbon dioxide China Climate change Crops Cultivation Decoupling Diesel fuels Economic development emission peak Emissions Emissions (Pollution) Energy consumption Environmental Kuznets curve Global warming Grain cultivation greenhouse gas emissions Greenhouse gases Land use Livestock Livestock breeding Pesticides Rice Soil management spatial Durbin model Tapio decoupling index |
title | Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model |
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