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Introduction: The agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets. Methods: Agricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model. Results: The analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts. Conclusion: The findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions. [ABSTRACT FROM AUTHOR]

Agricultural activities constitute the second-largest contributor to greenhouse gas emissions. Proactively mitigating agricultural carbon emissions is crucial for safeguarding the ecological en-vironment, improving agricultural productivity, and fostering long-term ecological sustainability. This paper employs bibliometric analysis to examine the research status, hot topics, and development trends of agricultural carbon emissions in China over the past 2 decades. Based on Citespace software, the study primarily conducts visual analysis on 660 academic articles on ag-ricultural carbon emissions collected from the China National Knowledge Infrastructure (CNKI) between 2001 and May 2023, including publications indexed in Peking University Chinese Core Journals (PKU Core), Chinese Social Sciences Citation Index and Chinese Science Citation Database. The analysis covers publication quantity, author cooperation, institution cooperation, keyword co-occurrence, keyword clustering, keyword burst, keyword timeline, and keyword timezone. Research results indicate: (1) From the annual publication volume changes perspective, research on China's agricultural carbon emissions demonstrates a rapid upward trend in the new era, with increasing research interest. (2) The core net-work of research authors has been established, primarily concentrated in agricultural and forestry universities, and the core network of institutions in this field is gradually forming. However, collaboration networks between authors and research institutions are relatively dispersed, necessitating strengthened collaboration among institutions. (3) Current research on agricultural carbon emissions predominantly focuses on the challenges of reducing agricultural carbon emissions in China under the "dual carbon" goals, measures, and pathways to achieve agricultural carbon emission reductions; performance evaluation of agricultural carbon emissions, factors affecting these emissions, and their reduction potential; as well as the relationship between agricultural carbon emissions and agricultural economic growth. Future research should delve deeper into the precise accounting of agricultural carbon emissions under the "dual carbon" goals, their underlying mechanisms, and issues related to precise and differentiated agricultural carbon reduction strategies. (4) The development trajectory of domestic agricultural carbon emissions research shows a period of germination from 2001 to 2009, a development stage from 2010 to 2015, and a deepening stage from 2016 to 2023, with a notable increase in publications in 2021, signifying a new upward phase in research output. [ABSTRACT FROM AUTHOR]

Mitigating agricultural carbon emissions is pivotal for attaining the objectives of carbon peak and carbon neutrality. Utilizing a time-varying parametric Cobb-Douglas (C-D) production function, this study employs an enhanced Logarithmic Mean Divisia Index (LMDI) decomposition approach, the Tapio decoupling model, and Monte Carlo simulations to investigate the determinants and decoupling dynamics of agricultural carbon emissions within Sichuan Province from 2010 to 2020. The findings reveal that: (1) Factors such as carbon emission intensity, agricultural structure, labor inputs, and capital stock played a significant role in suppressing agricultural carbon emissions, collectively contributing to a reduction of 484.12 million tonnes. (2) The unstable decoupling of agricultural carbon emissions from economic development in Sichuan Province. Capital stock, alongside carbon emission intensity and agricultural structure, significantly contributed to this decoupling. To harmonize agricultural economic growth with carbon emission reduction, emphasis should be placed on manure management and resource utilization in livestock and poultry farming. Furthermore, leveraging technological advancements to enhance resource efficiency is crucial for reducing carbon emissions. Simultaneously, strategic management of fixed asset growth, focused on energy conservation, can catalyze the synergistic effects of economic development and technological spillovers. [ABSTRACT FROM AUTHOR]

Comprehensive accounting of carbon emissions and carbon sinks in the agricultural sector is crucial for China to achieve its carbon neutrality goal as early as possible. This paper develops a comprehensive and scientific accounting system to recalculate China's agriculture sector's carbon emissions and sinks from 1995 to 2020, taking into account both resource inputs and productive activities. Subsequently, the STIRPAT model is employed to predict alterations in carbon emissions and sinks across different scenarios. The results show that energy consumption, chemical inputs, and farmland soil management have surpassed livestock and poultry breeding as the main contributors to agricultural carbon emissions. Furthermore, this paper classifies 31 provinces in China into five distinct types based on the variations in agricultural carbon emissions and carbon sinks. These types include carbon sink-dominated regions, paddy planting-dominated regions, livestock farming-dominated regions, resource inputs-dominated regions, and composite factor-dominated regions. In addition, the extent of agricultural technology and the magnitude of agricultural development are the key factors impacting China's agricultural carbon emissions and carbon sinks, respectively. Prior to 2045, agricultural carbon emissions must be directly reduced as much as possible, and their source must be controlled; following that year, the role of carbon sequestration will become more prominent, and the active development of agricultural carbon sinks will be more beneficial in achieving agricultural carbon neutrality. [ABSTRACT FROM AUTHOR]

The effects of land transfer on agricultural carbon emissions and their underlying mechanisms must be investigated if we are to achieve sustainable development and environmentally friendly high-quality agricultural development. This research experimentally investigated the spatial impacts of land transfer on agricultural carbon emissions and their underlying causes using multiple econometric models based on provincial panel data covering the years 2010 to 2022. The results allow us to draw the following conclusions: (1) Land transfer significantly inhibits agricultural carbon emissions. This conclusion remained valid after various robustness checks, including a reduction in sample size, change model type, and adjustment of geographical regions. (2) Agricultural socialized services play a positive moderating role in the process of land transfer to curb agricultural carbon emissions. (3) Land transfer has a substantial spillover effect on agricultural carbon emissions, resulting in significantly reduced emissions in the immediate area and nearby regions. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Within the "dual carbon" framework, sustainable agriculture is pivotal for climate change mitigation and long-term agricultural health. To explore the environmental effects of agricultural trade, this study assesses the carbon emissions from agriculture using information from 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan due to a lack of available data) from 2001 to 2021. Then, we analyzed the impact of agricultural trade on agricultural carbon emissions and tested for the possible existence of mechanisms. Finally, we validate the synergistic effects of agricultural trade on pollution and carbon abatement. The findings were as follows: (1) Agricultural trade significantly suppresses agricultural carbon emissions. (2) Agricultural technological progress and the rationalization of the structure of the agricultural industry are the two influencing mechanisms. (3) The inhibitory effect of agricultural trade on agricultural carbon emissions is more pronounced in southern regions and regions with lower degree of topographic relief and higher agricultural industrial agglomeration. (4) Agricultural trade fosters the collaborative advancement of mitigating agricultural pollution and reducing carbon emissions. As a result, this study confirms that agricultural trade has a role in reducing carbon emissions and that giving full play to the environmental effects of trade in agricultural products contributes to the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

The process of urbanization leads to the reallocation and adjustment of agricultural production factors, which has a significant impact on agricultural carbon emissions (ACEs). Based on the panel data of 30 provinces in China from 2007 to 2019, this study explores the mechanism of how urbanization affects ACEs and conducts empirical tests. The results show that there is an “inverted U-shaped” relationship between urbanization and ACEs, with ACEs first increasing and then decreasing as the urbanization rate increases. From the perspective of intermediate mechanisms, urbanization mainly influences ACEs through the scale of farmland operations, the structure of crops, and the intensity of agricultural mechanization. Agricultural land management scale and crop structure have an inhibitory effect on ACEs, but the increasing intensity of agricultural mechanization exacerbates ACEs. In terms of regional heterogeneity, due to differences in physical geography and agricultural policies, the impact of urbanization on ACEs occurs in northern areas and non-major grain-producing areas. The spatial analysis indicates that urbanization has a spatial spillover effect on ACEs in the neighboring provinces. This study contributes to the existing ACEs’ literature by integrating urbanization, agricultural land use, and ACEs into the same theoretical analytical framework, exploring the underlying mechanisms, spillover effects, and regional heterogeneity. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, the low-carbon transition in agriculture is crucial to achieving carbon mitigation through clean production. The provision of agricultural productive services (APS) is pivotal for modernizing farming practices in China. However, the impact of this on the low-carbon transformation has received limited attention. This research examined the non-linear relationship between agricultural productive services and low-carbon development, including verifying a threshold effect with APS as the threshold variable, employing panel data for 31 provinces in China from 2010 to 2021. The results of the study suggested that the effect of services associated with agricultural productivity on the transition of the agricultural sector to low-carbon practices varied across threshold ranges. Specifically, when the APS exceeded the threshold of 2.4396, a significant suppressive effect was observed on carbon emission intensity. Further analysis revealed that APS indirectly influenced the farmland scale and agricultural technological advancements, thereby promoting the low-carbon transition of China's agriculture. Based on these results, it is recommended to intensify the development of APS in key cereal-producing regions, while emphasizing the harmonious progress of these services in conjunction with large-scale farmland management. [ABSTRACT FROM AUTHOR]

There is significant interest among policymakers and academics about whether green agricultural subsidy policy (GASP) has achieved its intended effect of reducing agricultural carbon emissions (ACEs) in China. Based on the panel data of 172 prefecture-level cities from 2010 to 2021, this study evaluates the impact and mechanisms of GASP on ACEs' reduction effect by employing the DID model. The results demonstrate that GASP does significantly reduce carbon emissions. Mechanism tests illustrate that GASP promotes carbon reduction via two mechanisms: enhancing agricultural technology progress efficiency and increasing scale management efficiency. Further heterogeneity analyses reveal that the carbon reduction effects of GASP are particularly prominent in the main grain-producing regions and in cities with higher levels of carbon emissions. The empirical tests and mechanism analyses in this paper can better clarify the function of GASP, enrich and deepen the existing literature, and provide some useful references for carbon reduction. [ABSTRACT FROM AUTHOR]

The digital economy, closely linked to agricultural progress, plays a key role in reducing agricultural carbon emissions. By utilizing panel data between 2011 and 2021 from 30 Chinese provincial-level regions, the present work empirically assesses the direct impact and nonlinear spatial spillover effects of the digital economy on agricultural carbon emissions, where methodologies including fixed effects, threshold models, and spatial econometrics are employed. The results were as follows: (1) The digital economy led to remarkable inhibition of agricultural carbon emissions, which was consistent across various robustness checks. (2) The carbon reduction efficiency of the digital economy presented obvious spatial variation, which had a greater negative effect in eastern regions and major grain-producing regions. (3) The digital economy had a nonlinear impact on agricultural carbon emissions, and technological innovation played a threshold effect, showing an "inverted U-shaped" characteristic of increasing first and then decreasing overall. (4) This emission abatement effect also showed a significant spatial spillover aspect, meaning that the digital economy development in one area prominently abates agricultural carbon emissions in adjacent provinces. Our findings might provide a theoretical and empirical foundation for comprehending and addressing agricultural carbon emissions abatement in China from the digital economy perspective. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

AbstractReducing agricultural carbon emissions (ACEs) is essential to China’s overall carbon-emission-reduction target and agricultural sustainable development. This paper analyzes the impact of agricultural technology progress (ATP) and financial support for agriculture on ACEs from a theoretical level, and empirically tests the effect of ATP on ACEs by spatial econometric model, using China’s provincial data from 2001 to 2019. The regulatory effect model is used to examine the moderating effect of financial support policies on ATP and ACEs. The sample was divided according to natural geographical environment, economic development level and agricultural production structure to study the regional heterogeneity from the spatial perspective. The main conclusions are as follows: Overall, ATP has an inhibitory effect on ACEs, and this effect has a spatial spillover effect. In terms of regulation effect, fiscal support for agriculture policy has an enhanced regulatory effect in the impact of ATP on reducing ACEs. In addition, there is obvious regional heterogeneity in the carbon emission reduction effect of ATP in the west or east of the Hu Huanyong line, western or non-western, major or non-major grain-producing regions. This paper draws the following policy implications: First, increase agricultural technology research and development and expand technology spillover channels; second, establish regional collaborative emissions reduction mechanisms and strengthen regional technical cooperation; third, improve the financial support system for agriculture; Fourth, implement regional heterogeneous agricultural policies in accordance with local conditions.

Carbon emissions from agriculture should not be underestimated. With the aim for carbon peaking and carbon neutralization and the help of digital inclusive finance, the effective reduction in carbon emissions in agriculture and animal husbandry production is crucial to achieving China's carbon emission reduction goals. We used the balanced panel data of 31 provinces in China from 2011 to 2021 to study this issue. We empirically tested the impact, mechanism, and heterogeneity of digital inclusive finance on agricultural carbon emissions based on the systematic measurement of agricultural carbon emissions. The results revealed that (1) the development of digital inclusive finance has a significant inhibitory effect on agricultural carbon emissions, and it is an important path to reduce agricultural carbon emissions. (2) Through the intermediary effects' analysis, it was found that capital deepening is an important transmission mechanism for the promotion of agricultural carbon emission reduction through digital inclusive finance. (3) Further analysis using the quantile regression model reveals that the impact of digital inclusive finance on agricultural carbon emissions is significantly negative at different quantiles. (4) Through the spatial Durbin model, digital inclusive finance has a space carbon enhancement effect. Finally, we put forward suggestions to promote the development of low-carbon agriculture by paying attention to the technical effect of digital inclusive finance, strengthening the connection and cooperation between various regions and promoting the carbon emission reduction role of capital deepening. [ABSTRACT FROM AUTHOR]

Introduction: Reducing carbon emissions from agriculture is essential to ensuring food security and human prosperity. As a country with approximately 20% of the global population, China has begun actively practicing the lowcarbon agricultural development conception. Against the backdrop of disruptive technologies that continue to be integrated into various industries, the massive application of agricultural robots has opened the way to intelligent agriculture. This paper tries to answer whether there is some non-linear nexus between the application of agricultural robots and agricultural carbon emissions in China. As an essential tool for carbon emission reduction in China, does environmental regulation moderate the nexus between agricultural robot applications and agricultural carbon emissions? If so, how does this effect manifest itself? Methods: This work takes China as an example by collecting macro-regional panel data from 30 provinces from 2006 to 2019. The environmental Kuznets curve theory is extended to agricultural carbon emissions, and we carried out empirical tests utilizing the panel fixed effects model and the moderating effects model. Results: This study verifies the inverted U-shaped nexus between agricultural robotics applications and agricultural carbon emissions in Chinese provinces, i.e., the agricultural carbon emissions (ACE)-Kuznets curve holds. The higher the level of formal environmental regulation, the larger the peak of the ACE-Kuznets curve and the more the inflection point is pushed back. The higher the level of informal environmental regulation, the lower the peak of the ACE-Kuznets curve and the later the inflection point. Discussion: The findings in this paper represent the first exploration of the environmental Kuznets curve in agricultural carbon emissions. It is noteworthy that the moderating effect of formal environmental regulation does not lower the peak of the curve as we expect. This appearance is attributed to the reality that China is still in a phase of rising agricultural carbon emissions, which is exacerbated by the overlapping positive effects of agricultural robotics applications and formal environmental regulations. Informal environmental regulation is more effective than formal environmental regulation in reducing agricultural carbon emissions at this stage. [ABSTRACT FROM AUTHOR]

【Objective】By analyzing the total amount of carbon emissions from agriculture in Gansu Province during 2000 to 2020 and its development and evolution characteristics,and the decoupling effect as a reference for the development of green and low-carbon agriculture in Gansu Province.【Methods】The agricultural carbon emissions in Gansu Province between 2000 to 2020 were measured based on the IPCC carbon emission coefficient method using agricultural inputs as the carbon source,and using the grey prediction model GM（1,1）,the agricultural carbon emissions of different years were selected as samples to predict the agricultural carbon emissions in Gansu Province from 2025 to 2030,and the prediction results were compared and analyzed. The Tapio decoupling model was used to study and analyse the relationship between agricultural carbon emissions and economic development.【Results】Agricultural carbon emissions in Gansu Province from 2000 to 2020 show a trend of increasing and then decreasing.The source of carbon emissions were mainly chemical fertilizers and agricultural films,chemical fertilizer carbon emissions accounted for 31.27% to 43.22% of agricultural carbon emissions,always at the highest level during the 20-year period;agricultural carbon emissions reached a maximum of 2.825 138 million tons in 2015. After 2015,it began to decline gradually,and the agricultural carbon emissions in 2020 were 2.288 601 million tons. The decoupling relationship of agricultural carbon emissions from 2000 to 2020 mostly showed strong decoupling or weak decoupling. Using the data of the last 10 years and the data of the last 5 years as the samples to predict the agricultural carbon emissions as a whole all showed a clear downward trend.The model′s prediction accuracy was the highest when using the data of the last 5 years as the sample for prediction. The agricultural carbon emissions in Gansu Province have reached the peak before 2025,agricultural carbon emissions projected for a sample of the last 5 years of data will be 17.08% lower in 2025 compared to 2020,the rate of reduction will reach 30.36% in 2030,and the average annual reduction rate will be 0.139 million tons.【Conclusion】Gansu Province′s agricultural carbon emissions continue to decline,the agricultural economy shows stable growth,and agricultural carbon emissions will peak before 2025,indicating that Gansu Province has made some progress in green low-carbon agriculture in recent years. Measures should be taken according to the actual local situation in order to achieve the goal of continuously promoting the development of green agriculture,reducing high-carbon emission activities,increasing agricultural carbon sinks,and realizing agricultural carbon emission reduction in Gansu Province. [ABSTRACT FROM AUTHOR]

To obtain a scientific understanding of the spatial and temporal patterns of agricultural eco-efficiency (AEE) as well as its influencing factors in Fujian Province, effective recommendations were provided to promote agricultural green development. The Super-SBM model with undesired output was employed to assess AEE, and the GTWR model was used to analyze the main factors influencing AEE based on data from nine prefecture-level cities in Fujian Province spanning from 2000 to 2020. There are three conclusions to be drawn: Firstly, the AEE of Fujian Province has increased from 0.340 in 2000 to 0.971 in 2020, but it has not yet reached the efficiency frontier due to excessive input of agricultural factors and carbon emissions. The development of AEE across regions is unbalanced with a wide gap between them. Secondly, from a spatial correlation perspective, global correlation of AEE in Fujian Province showed random distribution while local agglomeration existed to varying degrees. Thirdly, AEE in Fujian Province was influenced by various driving factors that changed significantly over different periods and exhibited obvious regional differences. In summary, the AEE of Fujian Province has shown overall improvement; however, its effectiveness remains limited. The disparities among cities are evident, necessitating the formulation of differentiated strategies for agricultural ecological development to enhance regional synergistic driving forces and improve regional AEE. [ABSTRACT FROM AUTHOR]

Agriculture is a significant source of carbon emissions, which have a substantial environmental impact. The digital economy plays a vital role in mitigating these emissions through innovative digital solutions. As a leading agricultural nation, China faces substantial pressure to reduce its agricultural carbon emissions(ACE). This paper aims to thoroughly examine the relationship between the growth of the rural digital economy and ACE. To achieve this, we utilize an extensive panel dataset covering China's provinces from 2011 to 2020, analyzing the dynamic and spatial effects of digital economy development on ACE. The key findings of this research are as follows: (1) The rapid expansion of the digital economy significantly reduces ACE. (2) The impact of digital economic development on lowering ACE varies spatially, with a clear progression from eastern to western regions. (3) The digital economy helps reduce ACE through three specific channels: fostering technological innovation, enhancing scale efficiency management, and providing agricultural financial incentives. Based on these findings, this study proposes policy recommendations to improve digital infrastructure, promote balanced regional development in the digital economy, and optimize the management of agricultural science and technology. These policy insights aim to transform agriculture and achieve the goal of reducing ACE, thereby contributing to broader environmental sustainability.

Comprehensive accounting of carbon emissions and carbon sinks in the agricultural sector is crucial for China to achieve its carbon neutrality goal as early as possible. This paper develops a comprehensive and scientific accounting system to recalculate China’s agriculture sector’s carbon emissions and sinks from 1995 to 2020, taking into account both resource inputs and productive activities. Subsequently, the STIRPAT model is employed to predict alterations in carbon emissions and sinks across different scenarios. The results show that energy consumption, chemical inputs, and farmland soil management have surpassed livestock and poultry breeding as the main contributors to agricultural carbon emissions. Furthermore, this paper classifies 31 provinces in China into five distinct types based on the variations in agricultural carbon emissions and carbon sinks. These types include carbon sink-dominated regions, paddy planting-dominated regions, livestock farming-dominated regions, resource inputs-dominated regions, and composite factor-dominated regions. In addition, the extent of agricultural technology and the magnitude of agricultural development are the key factors impacting China’s agricultural carbon emissions and carbon sinks, respectively. Prior to 2045, agricultural carbon emissions must be directly reduced as much as possible, and their source must be controlled; following that year, the role of carbon sequestration will become more prominent, and the active development of agricultural carbon sinks will be more beneficial in achieving agricultural carbon neutrality.

China’s Rural Multifunctional Community (RMC) construction is an effective means to achieve economic growth and environmental sustainability in agriculture. Therefore, we measure the agricultural green total factor productivity (AGTFP) in China considering carbon emissions and non-point source pollution and examine the impact of China’s pilot RMC policy on AGTFP using the difference-in-difference (DID) model based on panel data for 30 of China’s provincial-level regions during 2010–2020. Further, we analyze the regional heterogeneity and internal transmission channel. The main findings are as follows. First, the implementation of China’s pilot RMC policy significantly increases AGTFP. Second, the effects have a downward trend from eastern to western China which may be caused by the different levels in the economy, infrastructure, environmental resources, labor size and quality, transportation, innovation capability, etc. Finally, China’s pilot RMC policy can improve AGTFP through the channels of rural industrial convergence, agricultural green technology innovation and urban-rural income gap reduction. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ecology & Rural Environment is the property of Journal of Ecology & Rural Environment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] Analyze the total amount, intensity and decoupling effect of agricultural carbon emissions in Henan Province, to provide references for the high-quality development of agriculture and formulation of emission reduction policies in Henan Province. [Methods] Taking Henan Province as the research object and generalized agriculture as the research perspective, the carbon emission coefficient method, intensity calculation formula and Tapio decoupling model were used to calculate the total agricultural carbon emissions, intensity and decoupling elasticity coefficient of Henan Province from 2011 to 2020, and the corresponding temporal-spatial characteristics were analyzed. [Results] The primary sources of agricultural carbon emissions in Henan Province were mainly consists of CH4, N2O and chemical fertilizer. The total agricultural carbon emissions in Henan Province can be divided into three temporal stages: steady growth period, rapid decline period, and volatility trend decline period and six types of spatial regions: "high-steady" "high-volatility" "medium-steady" "medium-volatility" "low-steady" and "low-volatility". The agricultural carbon emission intensity in Henan Province, can be divided into two temporal stages; accelerated decline period and fluctuating decline period, as well as three types of spatial regions: convergent decline type, accelerated decline type and back-end rise type. The decoupling effect of agricultural carbon emissions can be classified into three temporal stages: weak decoupling, strong decoupling, and repeated conversion, and three spatial types: economic development and ecological environment good relationship region, stable relationship region and poor relationship region. [Conclusion] Henan Province has made outstanding achievements in agricultural emission reductions. The relationship between agricultural development and ecological environment gradually improved, but lacking stability. The carbon emission characteristics of livestock and poultry industry was strong correlated with agricultural carbon emission characteristics in Henan Province. And there were regional differences in the total amount, intensity and decoupling effect of agricultural carbon emissions. Based on the above analysis, following suggestions were proposed: enriching the carbon emission reduction policy system of livestock and poultry industry, formulating regionally targeted agricultural carbon emission reduction policies, and institutional reform and technological innovation going hand in hand. [ABSTRACT FROM AUTHOR]

Carbon emissions represent an important cause of climate change. Agriculture is affected by climate change as well as a major source of carbon emissions. In this study, the PVAR and Han-Phillips GMM dynamic SDM models as well as urban panel data of Northeast China from 2007 to 2021 were used to explore the response mechanisms and spatial effects in the logical framework of "Regional development -Agricultural industrial upgrading-Carbon emissions", and to analyze the effect of fiscal expenditure on agricultural carbon reduction and climate risk management. The results show that: (1) The long-term regulation effect of fiscal expenditure on agricultural carbon reduction is ineffective, because fiscal agricultural expenditure only stimulates industrial upgrading, whereas fiscal environmental expenditure has a long-term stimulating effect on regional development; (2) Fiscal environmental expenditure has a short-term inhibiting effect on agricultural carbon emissions, which is only significant during the lag 1 period; (3) The spatial correlation of agricultural carbon emissions is mainly due to fiscal agricultural expenditure and industrial upgrading, based on the effects of technological spillovers, industrial linkages, and resource crowding between cities; and (4) Regional development and industrial upgrading contribute to agricultural carbon emissions in the long term; however, agricultural carbon emissions threaten long-term development. The above-mentioned results verify that regional development and agricultural industry upgrading depend on the environment in the sample area and indicate that insufficient attention has been paid to the low-carbon development of agriculture in fiscal expenditure. Currently, agricultural carbon reduction in China faces difficult challenges because of the time and spatial interactions, which must be considered in terms of systematic interventions, cross-regional, and development longevity in the future. This study supports the practice of agriculture carbon reduction and provides a new perspective for detailed analysis of the effect of fiscal expenditure on regional and industrial development. [ABSTRACT FROM AUTHOR]

Digital economy is being closely integrated with agricultural development and tapping into its unique potential to alleviate agriculture’s carbon emissions To explore the mechanism of how digital economy reduce the agricultural carbon emissions, this paper constructs a systematic evaluation method with extend STIRPAT model and panel data drawn from 29 provinces (or municipalities and autonomous regions) in the Chinese mainland from 2013–2020. The results show that the development of the rural digital economy has a significant negative influence on agricultural CEs, and this result is still valid given robustness tests. Second, the alleviation of CEs based on the rural digital economy is more significant in the higher technological investment zones than that in the lower technological investment zones, and the central and eastern regions also have more significant CEs reduction effect. Third, the influence mechanism analysis shows that agricultural green technology change is an effective means to promote the rural digital economy’s CEs reduction effect. This paper not only provide new empirical evidence for understanding nexus between digital economy and agricultural carbon reduction, but also give constructive policy implication to improve agricultural green development.

[Objective] The spatial-temporal characteristics and decoupling effects of agricultural carbon emissions at Xuzhou City, Jiangsu Province were analyzed in order to provide a theoretical basis and data reference for green, high-quality sustainable development of agriculture and the benign growth of the agricultural economy in Xuzhou City, and its surrounding resource-based cities in the future. [Methods] The total amount, intensity, and structure of agricultural carbon emissions at Xuzhou City from 2000 to 2020 were measured using the emission coefficient method, and their decoupling relationship with agricultural economic development was determine based on the Tapio decoupling model. [Results] ① The overall trend of agricultural carbon emissions at Xuzhou City could be described as M-shaped (rapid rise-fluctuating rise-rapid decline) from 1.61×106 t in 2000 to 1.69×106 t in 2020. The contributions of factors affecting agricultural carbon emissions followed the order of arable land use (46.44%), crop cultivation (31.90%) and livestock breeding (21.66%), with chemical fertilizers being the most important carbon source; ② Agricultural carbon emission at Xuzhou City varied significantly among districts (counties and cities) and had undergone a long-term evolutionary process from rising to falling, with a spatial distribution pattern of “higher in the middle and lower in the surrounding areas”, with Pizhou City being the most prominent; ③ Xuzhou City’s agricultural carbon emissions and agricultural economic development have generally undergone a process of “weak decoupling—strong negative decoupling—expansion of negative decoupling—strong decoupling”, and has mainly manifested as strong decoupling since the 13th Five-Year Plan. [Conclusion] Xuzhou City’s agricultural carbon emissions are becoming more and more reasonable as the concept of low-carbon emission reduction continues to deepen. Agricultural economic development has also achieved clear and convincing effects.

The effects of land transfer on agricultural carbon emissions and their underlying mechanisms must be investigated if we are to achieve sustainable development and environmentally friendly high-quality agricultural development. This research experimentally investigated the spatial impacts of land transfer on agricultural carbon emissions and their underlying causes using multiple econometric models based on provincial panel data covering the years 2010 to 2022. The results allow us to draw the following conclusions: (1) Land transfer significantly inhibits agricultural carbon emissions. This conclusion remained valid after various robustness checks, including a reduction in sample size, change model type, and adjustment of geographical regions. (2) Agricultural socialized services play a positive moderating role in the process of land transfer to curb agricultural carbon emissions. (3) Land transfer has a substantial spillover effect on agricultural carbon emissions, resulting in significantly reduced emissions in the immediate area and nearby regions.

Within the “dual carbon” framework, sustainable agriculture is pivotal for climate change mitigation and long-term agricultural health. To explore the environmental effects of agricultural trade, this study assesses the carbon emissions from agriculture using information from 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan due to a lack of available data) from 2001 to 2021. Then, we analyzed the impact of agricultural trade on agricultural carbon emissions and tested for the possible existence of mechanisms. Finally, we validate the synergistic effects of agricultural trade on pollution and carbon abatement. The findings were as follows: (1) Agricultural trade significantly suppresses agricultural carbon emissions. (2) Agricultural technological progress and the rationalization of the structure of the agricultural industry are the two influencing mechanisms. (3) The inhibitory effect of agricultural trade on agricultural carbon emissions is more pronounced in southern regions and regions with lower degree of topographic relief and higher agricultural industrial agglomeration. (4) Agricultural trade fosters the collaborative advancement of mitigating agricultural pollution and reducing carbon emissions. As a result, this study confirms that agricultural trade has a role in reducing carbon emissions and that giving full play to the environmental effects of trade in agricultural products contributes to the high-quality development of agriculture.

In the context of carbon neutrality, the low-carbon transition in agriculture is crucial to achieving carbon mitigation through clean production. The provision of agricultural productive services (APS) is pivotal for modernizing farming practices in China. However, the impact of this on the low-carbon transformation has received limited attention. This research examined the non-linear relationship between agricultural productive services and low-carbon development, including verifying a threshold effect with APS as the threshold variable, employing panel data for 31 provinces in China from 2010 to 2021. The results of the study suggested that the effect of services associated with agricultural productivity on the transition of the agricultural sector to low-carbon practices varied across threshold ranges. Specifically, when the APS exceeded the threshold of 2.4396, a significant suppressive effect was observed on carbon emission intensity. Further analysis revealed that APS indirectly influenced the farmland scale and agricultural technological advancements, thereby promoting the low-carbon transition of China’s agriculture. Based on these results, it is recommended to intensify the development of APS in key cereal-producing regions, while emphasizing the harmonious progress of these services in conjunction with large-scale farmland management.

The digital economy, closely linked to agricultural progress, plays a key role in reducing agricultural carbon emissions. By utilizing panel data between 2011 and 2021 from 30 Chinese provincial-level regions, the present work empirically assesses the direct impact and nonlinear spatial spillover effects of the digital economy on agricultural carbon emissions, where methodologies including fixed effects, threshold models, and spatial econometrics are employed. The results were as follows: (1) The digital economy led to remarkable inhibition of agricultural carbon emissions, which was consistent across various robustness checks. (2) The carbon reduction efficiency of the digital economy presented obvious spatial variation, which had a greater negative effect in eastern regions and major grain-producing regions. (3) The digital economy had a nonlinear impact on agricultural carbon emissions, and technological innovation played a threshold effect, showing an “inverted U-shaped” characteristic of increasing first and then decreasing overall. (4) This emission abatement effect also showed a significant spatial spillover aspect, meaning that the digital economy development in one area prominently abates agricultural carbon emissions in adjacent provinces. Our findings might provide a theoretical and empirical foundation for comprehending and addressing agricultural carbon emissions abatement in China from the digital economy perspective.

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above ‘dual carbon’ target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of ‘dual carbon’ target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the ‘dual carbon’ target.

AbstractAgriculture plays an indispensable role in the economic system of all countries, and the issue of agricultural carbon emissions has become a challenge to the sustainable development of the global economy. Against this backdrop, based on the data of 30 provinces, municipalities directly under the central government and autonomous regions (excluding Hong Kong, Macau and Tibet) in China from 2005 to 2019, this current study comprehensively uses the two-way fixed effect panel model and panel vector autoregressive (PVAR) model to explore the static and dynamic relationships between agricultural mechanization, large-scale operation and agricultural carbon emissions. Analysis show that agricultural mechanization and large-scale operation promote the agricultural carbon emissions, and increasing the level of urbanization will help curb the increase of agricultural carbon emissions. However, in a dynamic perspective, there is a two-way granger causality relationship between agricultural mechanization and agricultural carbon emissions. Agricultural mechanization is an important cause of agricultural carbon emissions and its promoting effect is sustainable, while the short-term effect of large-scale operation on agricultural carbon emissions is positive, and in the long run it helps reduce agricultural carbon emissions. Accordingly, the study recommends that the government should make the following efforts: firstly, speed up the research and development of agricultural machinery driven by clean energy; secondly, guide the effective transfer of land and encourage farmers to reduce the amount of agricultural chemical materials input while improving the use efficiency of pesticide chemical materials; thirdly, uphold the concept of ecological civilization in the process of promoting urbanization.

The existing research covers digital finance's carbon reduction impacts in industrial and urban settings, however, leaving a gap in understanding its effects in agriculture. This study addresses this gap by examining the relationship and mechanism between digital finance and agricultural carbon reduction. Two hypotheses are proposed to guide the study: (1) The development of digital finance could reduce agricultural carbon emissions; (2) The development of digital finance could significantly promote agricultural green innovation, empowering agricultural carbon emission reduction. By employing panel data spanning 31 provinces from 2011 to 2020, we empirically investigate the relationship between digital finance development and a reduction in agricultural carbon emissions. The results indicate that digital financial development significantly reduces agricultural carbon emissions. Mechanism analysis further elucidates the pivotal role of digital finance in facilitating agricultural green innovation, resulting in a decline in agricultural carbon emissions. Additionally, heterogeneity analysis reveals that the impact of digital finance on agricultural carbon emission reduction is particularly pronounced in regions with higher income levels and greater educational attainment. The study offers empirical evidence on the nexus between digital finance and agricultural carbon emissions, from a developing country perspective. It could provide innovative ideas and experiences from China for global agricultural low-carbon development practices. [ABSTRACT FROM AUTHOR]

Identifying the stage of agricultural energy carbon reduction in each province of China is obviously helpful for the construction of targeted strategies and the early achievement of China ’s goals of reaching peak carbon emissions and achieving carbon neutrality. Therefore, based on a comprehensive evaluation of the carbon emission reduction maturity of China's agricultural energy in each province and nationwide, this article explored the dynamic evolution trend using the degree of coordinated development as an indicator. The results showed that: ① From 2005 to 2020, the relative carbon emission reduction maturity of agricultural energy in most provinces showed an upward trend, and a considerable number of provinces achieved a level crossing of one or even two levels. Only Heilongjiang experienced a level drop, with its relative coordination of agricultural energy carbon emission reduction dropping from a higher level to a lower level. ② The overall carbon emission reduction maturity of China ’s agricultural energy during the examination period had some interannual fluctuations, but the overall upward trend was obvious. In terms of the evolution trend, the overall development of agricultural energy carbon emission reduction showed a ‘rising-relatively stable’ characteristic, while both the overall coordination degree and the overall coordination development degree showed a three-stage change characteristic of ‘fluctuating up-continuously decreasing continuously increasing’. ③ The overall level of coordinated development of agricultural energy carbon emission reduction in China in‑ creased significantly, and the inter-provincial gap was narrowing during the examination period. The three types of regions were also in a state of improvement, but the inter-provincial disparity within them showed different characteristics, among which the inter-provincial disparity between production and marketing balanced areas was significantly reduced, while the inter-provincial disparity between the main grain producing areas and the main marketing areas increased, with the latter showing a trend of polarization. Therefore, on the one hand, based on the powerful guidance of government departments and the continuous improvement of relevant systems, the relative development and relative coordination of inter-provincial agricultural energy carbon emission reduction should be promoted; on the other hand, on the basis of necessary experience accumulation and inter-provincial exchanges, each province should explore new emission reduction paths according to local conditions. In addition, we should continue to improve the construction of rural infrastructure and strive to improve the level of agricultural social services, through which agricultural energy carbon emission reduction can be promoted. [ABSTRACT FROM AUTHOR]

Given the huge carbon footprint of agricultural activities, reduction in agricultural carbon emission (ACE) is important to achieve China’s carbon peaking and carbon neutrality goals, but it may affect agricultural food security and economic development. Therefore, it is important for scientific carbon reduction measures to understand the multi-year trends and the influencing factors of ACE, and clarify whether the process of ACE affects food security and economic development. This study analyzed the trends of total ACE and ACE caused by different agricultural carbon sources (ACS) from 2001 to 2020 in Zhejiang Province, then we revealed the main influencing factors of ACE based on the logarithmic mean Divisia index (LMDI) model and dissected the relationship between ACE and food security and economic development. Results show that the total ACE fluctuated from 6.10 Mt in 2001 to 3.93 Mt in 2020, and the process included a decrease in 2001–2003 and 2005–2020 and an increase in 2003–2005. The decrease in ACE, from 2001 to 2014, was mainly due to the decline in rice acreage, which contributed 90.38%; from 2014 to 2020, it was by the reduction in the use of fertilizer, diesel, and pesticide, which contributed 83.9%. As drivers, agricultural economic development effect and total population size effect drove 4.25 and 1.54 Mt of ACE, respectively. As inhibitors, planting structure effect, technology development effect, and population structure effect inhibited 3.12, 2.11, and 2.74 Mt of ACE, respectively. With the reduction of ACE, the agricultural economy continued to grow, but the food security situation was pessimistic, indicating that ACE reduction has achieved synergy with economic development, but not with food security. [ABSTRACT FROM AUTHOR]

Digital technology can be used to adjust the structure of energy production, promote the development of new agricultural production technologies, and reduce carbon emissions. With the increasing integration of digital technology in various fields, rural development is also entering a critical period of digital transformation. Therefore, this paper uses digital technology and agricultural carbon emission intensity as research objects. We use panel data from 2011 to 2019. We first measure and analyse the level of digital technology development in China. This article empirically tests the impact between digital technology and the intensity of agricultural carbon emissions. Digital technology can be used to significantly suppress the intensity of agricultural carbon emissions. The suppressive effect is more significant in the western region of China than in the central and eastern regions. [ABSTRACT FROM AUTHOR]

Controlling agricultural carbon emissions contributes to achieving peak carbon emissions and carbon neutrality. However, as a conservation management practice of farmland, the impact of No-tillage management (NTM) on agricultural carbon emissions needs to be further discussed. The main purpose of this paper is to assess the direct effect and spatial spillover effect of NTM on agricultural carbon emissions, revealing the regulating mechanism of NTM on agricultural carbon emissions and the combined application of NTM. Results indicate that NTM reduces agricultural carbon emissions, which is significant in the central and western regions, along with the primary grain, corn, and rice production areas, as well as the northern regions of the Huai River. Furthermore, the spatial spillover analysis reveals that the implementation of NTM increases agricultural carbon emissions in neighboring regions, but financial support and cross-regional services can negatively regulate the relationship between NTM and space agricultural carbon emissions. This paper also finds that combining straw-returning technology and NTM reduces agricultural carbon emissions. Building a cross-regional coordination mechanism, an incentive mechanism, and innovating the conservation tillage model is essential for promoting the NTM and achieving agricultural carbon reduction. [ABSTRACT FROM AUTHOR]

Accelerating economic globalization is a major driver of the transfer of embodied pollutant emissions from trade. China and the United States are currently the largest importers and exporters of agricultural products, respectively, and are also major producers and consumers of these products. This paper aims to analyze and compare the patterns of embodied agricultural carbon emissions (ACE) in the two countries, which is crucial for understanding how trade influences the transfer of such emissions. In this study, we calculated the embodied ACE of China and the United States from the perspectives of production and consumption for the years 1970, 1980, 1990, 2000, 2010, and 2016 by establishing a multi-regional input–output (MRIO) model. Additionally, we employed the Logarithmic Mean Divisia Index (LMDI) decomposition method to analyze the driving factors behind the changes in embodied ACE over time. The findings indicated that the embodied ACE associated with imports and exports in China and the United States followed a pattern of increase and subsequent decrease during the period 1970–2016, with net imports escalating from −18.79 million tons and −3.62 million tons to 40.35 million tons and 51.22 million tons, respectively. This study identified two main factors contributing to the reduction in embodied ACE in both countries: the declining intensity of embodied ACE per unit of traded products and the diminishing proportion of the primary industry. The growth in GDP per capita, population expansion, and an increase in the proportion of agricultural products in international trade are predicted to promote an increase in embodied ACE imports and exports in both countries. This paper advocates for the reduction of embodied ACE through the continuous promotion of research and application of energy-saving and emission-reduction technologies, an optimized industrial structure, and the implementation of relevant energy-saving and emission-reduction policies. [ABSTRACT FROM AUTHOR]

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China's agricultural subsidy system has increased the investment on the agricultural production factors such as energy and chemistry, which caused an increase of agricultural carbon emissions. Based on the Thousand-Village Survey data from Shanghai University of Finance and Economics in 2013, the focal paper uses ordinary and two-stage least squares (OLS and 2SLS) to systematically investigate the impact and mechanism of agricultural subsidies on agricultural carbon emissions in China. Results show that China's current agricultural subsidy system has a promoting effect on agricultural carbon emissions. Four types of agricultural subsidies, namely, direct grain subsidies, subsidies for improved varieties, comprehensive subsidies for agricultural materials, and agricultural machinery purchase subsidies, impact the agricultural carbon emissions in ascending order. The agricultural subsidies increase the agricultural carbon emissions directly and indirectly. The findings indicate that a new type of agricultural subsidy system should be constructed, which mainly includes subsidies for farmers' out-migrating for work and land transfer, direct subsidies for grain, and subsidies for improved seed varieties. Among them, the direct grain subsidies should be implemented on the size of planting area and subsidies for improved seed varieties on the size of farmland to reduce the agricultural carbon emissions. [ABSTRACT FROM AUTHOR]

The prediction of regional agricultural carbon emissions is of great significance for regional environmental protection and sustainable development of regional agriculture. The article proposes a PLS-SA-AdaBoost prediction model combining partial least squares (PLS), simulated annealing algorithm (SA) and adaptive boosting algorithm (AdaBoost), which overcomes the shortcomings of a single model with insufficient prediction accuracy. Through an empirical study of agricultural carbon emissions in Fujian Province, China, the article validates the effectiveness of this combined forecasting model. The results show that the combined PLS-SA-AdaBoost forecasting model has higher accuracy and better performance than other models. The article predicts the future trend and range of agricultural carbon emissions in Fujian Province under five different scenarios. [ABSTRACT FROM AUTHOR]

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Introduction: Strengthening the early warning of greenhouse gas emissions from agriculture is an important way to achieve Goal 13 of the Sustainable Development Goals. Agricultural carbon emissions are an important part of greenhouse gases, and accelerating the development of green and low-carbon agriculture is of great significance for China to achieve high-quality economic development and the goal of “carbon neutrality in peak carbon dioxide emissions”.Methods: By measuring the total agricultural carbon emissions in China and seven administrative regions from 2000 to 2021, the paper analyzes the influencing factors of agricultural carbon emissions in China by using STIRPAT environmental pressure model, and on this basis, predicts the peak trend of agricultural carbon emissions in China under different development scenarios by using the extreme learning machine model optimized by genetic algorithm.Results: The results showed that the extreme learning machine model improved by the genetic algorithm can overcome the shortcoming that the extreme learning machine model is easy to fall into the local optimal solution, thus obtaining higher prediction accuracy. At the same time, from 2000 to 2021, the total agricultural carbon emissions in China showed a continuous fluctuation trend, and due to the constraints of the agricultural economic level, agricultural industrial structure, and agricultural human capital, the agricultural carbon emissions showed spatial differentiation. It is worth noting that, in the context of green development, the agricultural carbon emissions of the seven regions in China all have the potential to achieve the “peak carbon dioxide emissions” goal in 2030, with only a slight difference at the peak.Discussion: The research results of this paper provide evidence for the government to formulate flexible, accurate, reasonable and appropriate agricultural carbon reduction policies, which is helpful to strengthen the exchanges and cooperation of regional agricultural and rural carbon reduction and fixation, and actively and steadily promote China's agriculture to achieve the goal of “peak carbon dioxide emissions carbon neutrality”.

China’s agricultural and rural greenhouse gas emissions account for about 15% of its total emissions. Studying how to reduce China’s agricultural carbon emissions (ACEs) is of great strategic significance. Based on the panel data of 31 provinces (cities) in China from 2007 to 2020, this paper empirically tests the impact of fiscal environmental protection expenditure (FEPE) on ACEs. The results reveal that: FEPE has significant negative impacts on ACEs; FEPE has a heterogeneous impact on ACEs in different regions, which shows that it has a significant impact on the eastern and central regions and provinces with relatively “high” carbon emissions, while it has no significant impact on the western regions and provinces with relatively “low” carbon emissions; Further the results of mechanism analysis show that the impact of FEPE on ACEs is mainly manifested in its inhibiting effect on agricultural diesel, fertilizer and film use of carbon emissions. In light of these findings, it is imperative for the government to ensure steady and substantial investments in environmental protection. Moreover, implementing region-specific measures is essential to effectively curbing ACEs. The findings of this study offer invaluable insights that can guide the formulation of policies aimed at effectively reducing ACEs.

Taking the data of 30 provinces (excluding Hong Kong, Macao, and Taiwan regions and Tibet) at the provincial level from 2010 to 2019 as the research object, this paper analyzes the current situation and characteristics of China's agricultural modernization and response to carbon emissions. Agricultural modernization is decomposed into production modernization, management modernization, and ecological modernization. This study uses the spatial Dobbin model to demonstrate the impact of agricultural modernization on carbon emissions and analyzes the impact of agricultural modernization on carbon emissions in the East. The direct effect and spatial spillover effect of the three western regions are to different degrees. The results show that agricultural carbon emissions are spatially dependent. The development of agricultural modernization and transportation of neighboring provinces and cities will have an impact on agricultural carbon emissions in this region. Therefore, under the background of rural revitalization and low-carbon agriculture, this paper further analyzes the impact of agricultural modernization on the spatial distribution of carbon emissions in the eastern, central, and western regions. Recommendations are proposed with a view to giving better play to the process of agricultural modernization. [ABSTRACT FROM AUTHOR]

How to control the growth of agricultural carbon emissions while developing tourism has become the primary issue that needs addressing in the development of rural China. This paper explores the impact of tourism on agricultural carbon emissions and further analyses the mediating effect of labor transfer in this relationship. The analysis is evaluated using provincial panel data from 31 provinces in China from 2007 to 2019 with a sequential regression model. The results show that tourism development increases agricultural carbon emissions, which is more pronounced in areas with advanced economies or higher education levels. Second, labor transfer to nonfarming industries suppresses the increase in agricultural carbon emissions caused by tourism. Finally, (i) the impact of tourism on labor transfer in less developed and less educated regions is limited, and (ii) there is the expectation of large‐scale use of agricultural machinery due to labor transfer in economically developed or highly educated areas. The heterogeneity test shows these two reasons lead to a mediating effect of labor transfer on agricultural carbon emissions in different regions. [ABSTRACT FROM AUTHOR]

Agricultural green total factor productivity (AGTFP) is an important indicator to reflect the sustainability level of agriculture. The AGTFP network reflects the spatial correlations of the AGTFP among regions; thus, exploring its network structure and influencing factors can provide targeted policy guidance to the coordinated development of the agriculture sector. This study builds an epsilon-based measurement data envelopment analysis (EBM-DEA) model to calculate 31 provincial AGTFPs in China from 2002 to 2020. Then, social network analysis (SNA) was utilized to explore the characteristics of the AGTFP network, and the quadratic assignment procedure (QAP) was applied to find its external influencing factors. We reached four central conclusions: (1) Overall, there was a gradual upward trend of AGTFP in China during 2002~2020, and the average value rose from 0.75 in 2002 to 0.90 in 2020, but there were some differences among regions. (2) There is a complex and stable network characteristic of AGTFP; the average network density is 0.3753, and the average network efficiency is 0.4714. Meanwhile, some eastern and central areas, such as Henan, Anhui, Hubei, Hebei, Jiangsu, etc., have relatively high centrality and are a bridge in the entire network. (3) The AGTFP network can be divided into eight blocks, including two net beneficial blocks (the central-eastern provinces with high centrality); two net spillover blocks, including the provinces located in the developed urban areas (Beijing, Tianjin, Shanghai, and Jilin), the underdeveloped northwest regions (Ningxia, Qinghai, Xinjiang, and Tibet). The other areas are two-way spillover blocks. (4) Transportation development gap, technological progress gap, and the similarities of the agricultural industry structure are critical factors influencing the AGTFP network. Hence, improving the efficiency of the logistics and transportation industry, promoting technology transfer from developed areas to underdeveloped areas, and developing characteristic agriculture are all conducive to promoting the whole region's AGTFP. Our research provides policy implications for sustainable agricultural development in China and other developing countries. [ABSTRACT FROM AUTHOR]

The study investigated the impact of temperature extremes on carbon emissions (CE) from crop production. (1) Background: Many scholars have studied climate extremes. However, the research on the relationship between temperature extremes and CE is not extensive, which deserves attention. (2) Methods: The study adopted a fixed-effect model to analyze the impact of temperature extremes on CE from crop production, and the moderating effect was tested using total factor productivity (TFP) in agriculture. (3) Results: Temperature extremes in Hebei Province were mainly reflected in a decline in the cold day index (TX10p) and a rise in the warm spell duration index (WSDI) and the number of summer days (SU25). Additionally, TX10p was positively correlated with CE. For every 1% reduction in TX10p, CE dropped by 0.237%. There was no significant correlation between WSDI and CE. Finally, the agricultural TFP had a significant moderating effect on CE, with each 1% increase resulting in a corresponding 0.081% decrease in CE. (4) Conclusions: The results indicated a warming trend in Hebei Province, which resulted in a decrease in the number of winter days, and reduced CE from crop production. The improvement of input efficiency in agricultural production factors helped moderate the CE. [ABSTRACT FROM AUTHOR]

Reducing agricultural carbon emissions (ACE) is important for the sustainable development of agriculture. Agricultural productive services (APS), a novel form of agricultural technology extension, offer new avenues for promoting sustainable and green agriculture. The present study aims to explore the impact of APS on ACE. In line with the aim of the study, the Kernel density, Moran's I index, spatial Durbin model, and threshold regression model are employed. The findings reveal that APS demonstrate a significant inhibitory effect on ACE, reducing ACE not only within the region itself but also exerting a negative spatial spillover effect on other regions. Furthermore, a non-linear relationship between APS and ACE is observed, characterized by an inverted U-shaped curve with the arable land operating area serving as the threshold. Therefore, to fully harness the inhibitory effect of APS on ACE and to promote environmentally friendly and sustainable agricultural development, policymakers should vigorously develop APS, strengthen regional cooperation, and promote land transfer. Our research can help in understanding the impact of APS on ACE and to promote sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Agricultural product trade openness is a crucial factor impacting agricultural carbon emissions. This study analyzes the relationship between trade openness and carbon emissions in China. Using panel data from 2002 to 2020 for 31 provinces, a threshold panel model is employed to examine the non-linear relationship from an environmental regulation perspective. The findings reveal a significant single-threshold effect of environmental regulation. When environmental regulation intensity is low, trade openness is positively associated with agricultural carbon emissions. However, when environmental regulation intensity is high, trade openness significantly reduces carbon emissions. Regional regression analysis indicates that this single-threshold effect holds true in major grain-producing, grain-selling, and grain- producing- selling balance areas, although regional differences exist. This study emphasizes the need to coordinate environmental regulations and trade policies, strengthen environmental control, and leverage the threshold effect of environmental regulation in reducing carbon emissions through agricultural product trade openness. [ABSTRACT FROM AUTHOR]