Robotics, environmental regulation, and agricultural carbon emissions: an examination of the environmental Kuznets curve theory and moderating effects

Modern agriculture contributes significantly to greenhouse gas emissions, and agriculture has become the second biggest source of carbon emissions in China. In this context, it is necessary for China to study the nexus of agricultural economic growth and carbon emissions. Taking Jilin province as an example, this paper applied the environmental Kuznets curve (EKC) hypothesis and a decoupling analysis to examine the relationship between crop production and agricultural carbon emissions during 2000–2018, and it further provided a decomposition analysis of the changes in agricultural carbon emissions using the log mean Divisia index (LMDI) method. The results were as follows: (1) Based on the results of CO2 EKC estimation, an N-shaped EKC was found; in particular, the upward trend in agricultural carbon emissions has not changed recently. (2) According to the results of the decoupling analysis, expansive coupling occurred for 9 years, which was followed by weak decoupling for 5 years, and strong decoupling and strong coupling occurred for 2 years each. There was no stable evolutionary path from coupling to decoupling, and this has remained true recently. (3) We used the LMDI method to decompose the driving factors of agricultural carbon emissions into four factors: the agricultural carbon emission intensity effect, structure effect, economic effect, and labor force effect. From a policymaking perspective, we integrated the results of both the EKC and the decoupling analysis and conducted a detailed decomposition analysis, focusing on several key time points. Agricultural economic growth was found to have played a significant role on many occasions in the increase in agricultural carbon emissions, while agricultural carbon emission intensity was important to the decline in agricultural carbon emissions. Specifically, the four factors’ driving direction in the context of agricultural carbon emissions was not stable. We also found that the change in agricultural carbon emissions was affected more by economic policy than by environmental policy. Finally, we put forward policy suggestions for low-carbon agricultural development in Jilin province.

Digital inclusive finance can help to achieve agricultural carbon reduction through effective resource allocation, financial innovation, and digital networks. This study empirically tested the role of digital inclusive finance in agricultural carbon emissions reduction using a two-way fixed-effects model that was based on panel data of 30 provinces from 2011 to 2019 in China. The data and statistics showed that China's total agricultural carbon emissions were still growing and had not yet reached their peak. This empirical study found that digital inclusive finance had a significant effect on the reduction in agricultural carbon emissions. Specifically, for every one-level increase in the digital financial inclusion development (DFII) level, the province's total agricultural carbon emissions (TACC), agricultural greenhouse gas carbon emissions (ACGC), and agricultural carbon source carbon emissions (ACSC) decreased by 0.31, 0.38, and 0.25%, respectively, but there was no significant decrease in agricultural energy use carbon emissions (ACEC)1. Furthermore, the first- and second-order lagged terms of digital inclusive finance still had significant agricultural carbon reduction effects, reducing TACC by 0.30 and 0.29%, respectively. To better utilize the agricultural carbon emissions reduction effect of digital inclusive finance, we should further support the development of digital inclusive finance; promote education on, and the breadth and depth of digital inclusive finance; encourage cooperation between digital inclusive finance and low-carbon enterprises to reduce the financing constraints of agricultural low-carbon enterprises; and stimulate the R&D and sales of low-carbon technologies.

How does agricultural specialization affect carbon emissions in China?

Reducing agricultural carbon emissions is an important aspect of achieving China’s carbon peak and neutrality goals. Different agricultural centrality result in different agriculture status and role in different regions, affecting agricultural carbon emissions. In this study, agricultural centrality is introduced from the perspective of social network analysis. Spatial autocorrelation analysis, geographically and temporally weighted regression (GTWR) and other methods are used to empirically explore the effect of technological progress and agricultural centrality on the spatiotemporal heterogeneity of agricultural carbon emissions. The moderating effect of agricultural centrality on the relationship between technological progress and agricultural carbon emissions is further explored. The results show that 1) during the research period (2001–2019), the agricultural carbon emissions first increased and then decreased, with remarkable spatial agglomeration characteristics, revealing a significant spatial autocorrelation of carbon emissions among provinces; 2) provinces have distinctly uneven characteristics in the social network of agricultural carbon emissions, while the same province shows relative consistency in terms of location centrality and betweenness centrality. Areas with high centrality are the major grain producing areas, and they invariably play an important role in the spatially linked network of agricultural carbon emissions; 3) technological progress has an inhibitory effect on agricultural carbon emissions, and the regression coefficient decreases from western to eastern regions, demonstrating a spatial gradient distribution. The location centrality has a negative effect on agricultural carbon emissions, with significant spatial heterogeneity. The effect of betweenness centrality on agricultural carbon emissions has increased from positive to negative over time, and the promotion of each province’s intermediary role has inhibited the increase of agricultural carbon emissions; 4) both agricultural location centrality and betweenness centrality have significant positive moderating effects on the relationship between technological progress and agricultural carbon emissions. With the increase of location centrality and betweenness centrality, technological progress has an increasingly strong inhibitory effect on agricultural carbon emissions. We put forward targeted suggestions based on different agricultural centrality in order to reduce agricultural carbon emissions and provide directions for achieving the China’s carbon peak and neutrality goals and the Sustainable Development Goals of the United Nations’ Agenda 2030.

Sensitive zone of global climate change has been formed in China, and it has become a hot topic how can agriculture ensure food security and the supply of important agricultural products while achieving the “Dual Carbon” goal in the country. Based on such background, this paper uses the IPCC carbon emission calculation method, environmental input-output model and economic-water-carbon coefficient method to measure agricultural net carbon emissions, adopts bivariate spatial auto-correlation analysis and SYS-GMM to explore separately the relationship between agricultural net carbon emissions and effective supply of agricultural products, as well as the carbon reduction effect, growth effect and reasonable range of green technology innovation. The results show that: (1) China's agricultural net carbon emissions reveal a spatial distribution of “higher in the east than in the west than in the center” and a temporal characteristic of increasing year by year; China's effective supply of agricultural products shows an increasing trend and a spatial distribution of “higher in the east than in the center than in the west” in 2006–2012 and “higher in the east than in the west than in the center” in 2013–2020. (2) In 2006, 2010, 2015 and 2020, the number of provinces that belong to low-low agglomeration trade-off zone, low-high agglomeration synergy zone, non-significant zone, high-low agglomeration non-trade-off-synergy zone and high-high agglomeration trade-off zone averagely accounted for 12.500 %, 30.000 %, 26.667 %, 9.167 % and 21.667 % of the totality, respectively. (3) The carbon reduction and production growth effects of green technology innovation both show an inverted “U-shape”, and green technology innovation is conducive to both reducing agricultural net carbon emissions and improving supply of agricultural products when it is within a reasonable range of greater than 0.930. (4) Green technology innovation not only has significant spatial and temporal heterogeneity impact, but also exhibits a differential effect on productive agricultural carbon emissions, agricultural trade carbon emissions, agricultural carbon sinks, total output of agricultural products and agricultural net imports in international trade. Therefore, it is proposed that China should establish and improve green technology innovation incubation platforms, guide all participants to ensure the investment and application of green technology products within a reasonable range, formulate and implement regional differential policies and plan in accordance with local conditions, drive ultimately coordinated promotion of agricultural carbon emission reduction and product supply guarantee and lay an important foundation for achieving high-quality economic development and efficient ecological protection.

It is vital to explore the relationship between regional agricultural carbon emissions and economic growth for promoting the research of the agricultural Environmental Kuznets Curve (EKC) in China. Based on this, this research first uses the carbon emissions coefficient method to measure Fujian’s agricultural carbon emissions from 2000 to 2016, and uses the EKC model to explore the evolutionary relationship between regional agricultural carbon emissions and economic growth. Research shows that chemical fertilizers are the main cause of agricultural carbon emissions in Fujian. The agricultural carbon footprints and carbon emission intensity in the research area have not yet met the “inverted U-shape” assumed by EKC. Based on this, the author proposes that Fujian should continue to deepen the adjustment of the agricultural supply-side structure and take the road of green and low-carbon agricultural development. Fujian should implement technology reforms and improve the utilization of fertilizers in agricultural production and other emission reduction measures

The development of low-carbon agriculture systems has been a global consensus to reduce carbon emissions in the agricultural sector for addressing climate change challenges. This fact brings the need to study the agricultural carbon emissions (ACEs). Studies focusing on calculating the spatiotemporal changes of ACEs and analyzing the main factors for ACE changes have been conducted. The agricultural technology inputs (ATIs) as an important factor to influence ACEs have been identified. The traditional linear model was the commonly used method to study the relationship between ATIs and ACEs, whereas the impact of ATIs on ACEs in different areas might be complex and nonlinear due to the differences in trade openness causing different development levels of agricultural technologies. Therefore, this study aims to investigate the effect of trade openness on the relationship between ATIs and ACEs using a panel threshold model and put forward policy implications for the low-carbon agriculture development. The analysis was based on data from a panel of 31 provinces of China during 2003-2018. The results show that ATIs and ACEs increased from 2003 to 2018 and the spatial distribution of ATIs was similar to that of ACEs. The ATIs had a positive effect on ACEs with a significant single-threshold effect from trade openness. When the trade openness was below the threshold (0.1425), the positive effect of ATIs on ACEs was significant (coefficient, 0.117), whereas, when the trade openness was above the threshold (0.1425), the positive effect of ATIs on ACEs significantly decreased (coefficient, 0.062). Furthermore, industrial structure and agricultural economic development were the positive drivers of ACEs, while trade openness, education level of rural workers, R&D funding, and natural disasters had negative relationships with ACEs. The results provide valuable references for understanding ACE drivers and developing low-carbon agriculture with the consideration of ATIs and trade openness.

Ensuring the synergistic advancement of agricultural pollution reduction and carbon emission mitigation, along with sustainable development, is crucial for achieving the ‘dual carbon’ target and modernizing agriculture. To ensure sustainable agricultural development, this study employs a coupling coordination model to explore the synergistic effects of pollution reduction and carbon emission mitigation in Henan Province, considering the agricultural carbon emissions (ACEs), agricultural non-point source pollution (ANP), and the gross value of agricultural output (GVAO) of 18 cities in Henan from 2010 to 2022 as endogenous variables. A panel vector autoregression (PVAR) model is utilized to analyze the interactive responses between agricultural pollution reduction and carbon emission mitigation and agricultural economic development. The results indicate that the degree of synergy between ACE and ANP in Henan Province has shown a trend towards higher values and a diminishing polarization phenomenon between 2010 and 2022, with most regions having degrees of synergy at higher levels. Furthermore, the interactive response relationships between agricultural pollution reduction and carbon emission mitigation and agricultural economic development reveals that the GVAO in Henan Province has a significant positive impact on both ACE and ANP, and that agricultural pollution reduction and carbon emission mitigation are constrained by agricultural economic development, with no significant bidirectional causal relationship observed overall and a lack of positive interaction in the long term. Finally, ACE, ANP, and GVAO in Henan Province exhibit a strong self-reinforcing mechanism, particularly ACE and GVAO, which show a pronounced self-growth trend. Overall, Henan Province should fully utilize the synergistic effects of agricultural pollution reduction and carbon emission mitigation to achieve coordinated progress in agricultural pollution reduction and carbon emission mitigation, as well as green and sustainable development of the agricultural economy.

Clarifying the spatiotemporal characteristics of agricultural carbon emissions and influencing factors in China is crucial. A system for measuring agricultural carbon emissions was established, thus evaluating the level of carbon emissions in China and its provinces. Moreover, the dynamic evolution of agricultural carbon emissions in China and the regions on both sides of the Hu Line was analyzed, then investigated factors affecting agricultural carbon emissions by the LMDI model. The results indicate that the total amount and intensity of agricultural carbon emissions showed an upward and then a downward trend in China from 2001 to 2021. The peaks were 330.72 million tons and 1.98 tons\\ha, respectively. Agricultural carbon intensity in provinces was mostly Low-Low Cluster and the range of High-High Cluster has decreased. Inter-provincial disparities in agricultural carbon emissions were also gradually narrowing. These show that the effect of agricultural carbon emissions reduction was obvious in China. It is important to note that carbon emissions from energy consumption in agriculture and agricultural material inputs were substantial, accounting for about 95% of the total. Agricultural carbon emissions were restricted by the agricultural production efficiency, changes in industrial structure, rural population size, and agricultural industrial structure, but were promoted by the level of economy and urbanization. Therefore, we recommend enhancing inter-provincial synergistic collaboration to create agricultural carbon emissions reduction pathways with unique features. It is also essential to maximize agricultural production efficiency and grasp the direction of green and low-carbon. We also suggest that the Chinese government should accelerate the in-depth adjustment and transformation and upgrading of the industrial structure, thereby reducing agricultural carbon emissions at source.

Carbon emissions in agricultural production activities have become an important source of accelerating climate warming. At present, low-carbon agriculture is not only an important means to mitigate climate warming, but also a necessary process of transformation from traditional agriculture to modern agriculture. Therefore, to achieve the sustainable development of agriculture in China's Western Taiwan Straits Economic Zone (WTS Economic Zone), the governments should vigorously promote the upgrading and realize the development of low-carbon agriculture. By adopting the latest emission coefficients and the ordered weighted averaging (OWA) aggregation operator, this paper selected agricultural land use, rice paddies, crop production, livestock manure storage and livestock enteric fermentation as the five carbon emission sources, and measured agricultural carbon emissions in the WTS Economic Zone from 2010 to 2017. Thus, from the time perspective, the average agricultural carbon emissions in the WTS Economic Zone showed a fluctuating downward trend, from 762.64 10 3 tonnes in 2010 to 710.02 10 3 tonnes in 2017. From the spatial perspective, total agricultural carbon emissions among regions are quite different. To further clarify the factors affecting agricultural carbon emissions in the WTS Economic Zone, by applying the geographically and temporally weighted regression (GTWR) model, this paper selected the research and development intensity, the added value of agriculture, the proportion of agricultural labour force, the overall level of urbanization, per capita disposable income of rural residents and per capita arable land areas as the influencing factors, and then measured the direction and degree of the influences on agricultural carbon emissions in different temporal-spatial backgrounds. The results showed that the added value of agriculture, the proportion of agricultural labour force and per capita arable land areas had positive influences on agricultural carbon emissions, while the research and development intensity, the overall level of urbanization and per capita disposable income of rural residents had negative impacts. Although agricultural carbon emissions in the WTS Economic Zone have decreased in recent years, further measures can be taken to effectively reduce agricultural carbon emissions, and ultimately promote the development of lowcarbon agriculture according to the results of this study.

The “Village Merger and Resettlement” policy, as an adjustment of rural living arrangements and spatial organization, addresses the rural population outflow against the backdrop of global urbanization and industrialization. It has profound impacts on agricultural resource allocation, technological innovation, and carbon emissions, playing a significant role in achieving green and low-carbon development alongside high-quality agricultural advancement. This paper conducts an empirical analysis based on panel data from 30 provincial regions in China from 2001 to 2022 (excluding Tibet, Hong Kong, Macau, and Taiwan) to examine the impact of the “Village Merger and Resettlement” policy on agricultural carbon emissions. It explores the mediating effects of agricultural informatization and the integration of agricultural industries and analyzes the moderating roles of government environmental regulations and public environmental participation. The findings indicate that the “Village Merger and Resettlement” policy significantly suppresses agricultural carbon emissions, with the effects being more pronounced in major grain-producing areas, regions with flat terrain, convenient transportation, and higher levels of technology and labor, as well as on the east side of the Hu Huanyong Line, where the degree of agricultural industrial restructuring is lower and government policy enforcement is stronger. The mediation analysis reveals that the processes of agricultural informatization and industry integration both play positive transmission roles in the policy’s impact on reducing agricultural carbon emissions. The moderation analysis shows that compulsory government environmental regulations have a negative moderating effect on the policy’s carbon emission suppression, while public environmental participation has a positive moderating effect. Therefore, in implementing the “Village Merger and Resettlement” policy, it is necessary to tailor strategies to local conditions, make full use of agricultural informatization resources, reasonably plan the integration of agricultural industries, and accurately grasp the roles of environmental regulations to promote the positive effects on green, low-carbon, and high-quality agricultural development.

The development of digital rural areas has important theoretical and practical implications for promoting agricultural carbon emission reduction in China. Based on the panel data of 29 provinces， cities， and autonomous regions in China （with data for Hong Kong， Macau， Taiwan， Tibet， and Hainan temporarily unavailable） from 2011 to 2021， the spatial spillover effect of digital rural development on agricultural carbon emission reduction was tested using the Spatial Durbin Model. The study produced several interesting results： ① The process of digital rural development and the changes in agricultural carbon emissions are highly correlated in space. ② Digital rural development has significant spatial spillover characteristics in suppressing agricultural carbon emissions. The development of digital rural areas not only effectively suppresses carbon emissions in the region but also has a positive inhibitory effect on the carbon emissions of nearby regions. ③ Digital rural development can lower the level of agricultural carbon emissions through the pathway of promoting green technology innovation. ④ The heterogeneity test results show that the inhibitory effect of digital rural development on agricultural carbon emissions in the central region is more significant than the effect in the eastern and western regions. ⑤ The spatial spillover effect of digital rural development first increases and then decreases as the geographic distance increases and reaches its maximum value at a distance of 500 km.

Carbon emissions, energy consumption and economic growth: Evidence from the agricultural sector of China's main grain-producing areas

Regional development, agricultural industrial upgrading and carbon emissions: What is the role of fiscal expenditure? —-Evidence from Northeast China

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 devel-opment 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.