Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors

As one of the major sources of carbon emissions, the significant spatial disparities in agricultural carbon emissions (ACE) pose a serious challenge to coordinated regional carbon reduction efforts. In order to precisely identify the sources of these ACE differences, this study estimates the ACE of...

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Main Authors: Jie Huang, Hongyang Lu, Minzhe Du
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/14/4/682
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author Jie Huang
Hongyang Lu
Minzhe Du
author_facet Jie Huang
Hongyang Lu
Minzhe Du
author_sort Jie Huang
collection DOAJ
description As one of the major sources of carbon emissions, the significant spatial disparities in agricultural carbon emissions (ACE) pose a serious challenge to coordinated regional carbon reduction efforts. In order to precisely identify the sources of these ACE differences, this study estimates the ACE of China from 2005 to 2020 across four main emission sources and applies the bidimensional decomposition method of the Gini coefficient to measure and decompose their spatial disparities. Finally, the key factors driving ACE disparities are analyzed using the Quadratic Assignment Procedure (QAP). The results show that China’s total ACE initially declined, followed by an upward trend over the study period. Spatially, emissions were higher in eastern regions compared to western regions, and higher in southern regions compared to northern regions. The differences in paddy field emissions between the central and western regions were identified as the primary contributor to east–west disparities, while differences in agricultural materials emissions between northern and southern regions were the dominant source of north–south disparities. Furthermore, regional differences in agricultural development levels and mechanization capacity were found to be the strongest drivers of spatial ACE disparities. This study provides empirical evidence for formulating region-specific and source-targeted carbon reduction policies. Our findings highlight the importance of addressing regional imbalances, particularly in paddy field management and agricultural material usage, to promote more coordinated and sustainable agricultural carbon reduction across China.
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spelling doaj-art-5d9b8fda960e41748bd77a81c8430e7c2025-08-20T03:13:47ZengMDPI AGLand2073-445X2025-03-0114468210.3390/land14040682Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing FactorsJie Huang0Hongyang Lu1Minzhe Du2Business School, Xinyang Normal University, Xinyang 464000, ChinaBusiness School, Xinyang Normal University, Xinyang 464000, ChinaSchool of Economics and Management, South China Normal University, Guangzhou 510006, ChinaAs one of the major sources of carbon emissions, the significant spatial disparities in agricultural carbon emissions (ACE) pose a serious challenge to coordinated regional carbon reduction efforts. In order to precisely identify the sources of these ACE differences, this study estimates the ACE of China from 2005 to 2020 across four main emission sources and applies the bidimensional decomposition method of the Gini coefficient to measure and decompose their spatial disparities. Finally, the key factors driving ACE disparities are analyzed using the Quadratic Assignment Procedure (QAP). The results show that China’s total ACE initially declined, followed by an upward trend over the study period. Spatially, emissions were higher in eastern regions compared to western regions, and higher in southern regions compared to northern regions. The differences in paddy field emissions between the central and western regions were identified as the primary contributor to east–west disparities, while differences in agricultural materials emissions between northern and southern regions were the dominant source of north–south disparities. Furthermore, regional differences in agricultural development levels and mechanization capacity were found to be the strongest drivers of spatial ACE disparities. This study provides empirical evidence for formulating region-specific and source-targeted carbon reduction policies. Our findings highlight the importance of addressing regional imbalances, particularly in paddy field management and agricultural material usage, to promote more coordinated and sustainable agricultural carbon reduction across China.https://www.mdpi.com/2073-445X/14/4/682agricultural carbon emissionGini coefficient bidimensional decompositionregional differencequadratic assignment procedure analysis
spellingShingle Jie Huang
Hongyang Lu
Minzhe Du
Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors
Land
agricultural carbon emission
Gini coefficient bidimensional decomposition
regional difference
quadratic assignment procedure analysis
title Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors
title_full Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors
title_fullStr Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors
title_full_unstemmed Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors
title_short Regional Differences in Agricultural Carbon Emissions in China: Measurement, Decomposition, and Influencing Factors
title_sort regional differences in agricultural carbon emissions in china measurement decomposition and influencing factors
topic agricultural carbon emission
Gini coefficient bidimensional decomposition
regional difference
quadratic assignment procedure analysis
url https://www.mdpi.com/2073-445X/14/4/682
work_keys_str_mv AT jiehuang regionaldifferencesinagriculturalcarbonemissionsinchinameasurementdecompositionandinfluencingfactors
AT hongyanglu regionaldifferencesinagriculturalcarbonemissionsinchinameasurementdecompositionandinfluencingfactors
AT minzhedu regionaldifferencesinagriculturalcarbonemissionsinchinameasurementdecompositionandinfluencingfactors