Study on the Impact of China's Digital Economy on Agricultural Carbon Emissions

With the rapid development of China’s economy, China has become the world’s largest carbon emitter. China not only has an obvious growth rate of industrial carbon emissions but also the intensity of agricultural carbon emissions is hovering at a high level. The development of China’s agricultural economy has largely come at the expense of high emissions. Currently, under the background of global warming and difficulty in controlling greenhouse gas emissions, the development of low-carbon agriculture is an important way to realize the harmonious development of the ecological environment and economic growth and to promote the sustainable development of agriculture. The agricultural production efficiency is the main factor affecting the intensity of agricultural carbon emissions. Based on provincial panel data of China from 2010 to 2019, this paper establishes an indicator system and uses the super-efficiency SBM model to measure agricultural production efficiency. The regional agricultural carbon emissions were estimated using carbon-emission-related agricultural production activities. In order to study the nonlinear relationship between agricultural production efficiency and agricultural carbon emission intensity in the narrow sense, this paper uses a threshold regression model with agricultural carbon emissions as the threshold variable. Based on the analysis of China’s agricultural production efficiency and agricultural carbon emissions from 2010 to 2019, an empirical test is conducted through a threshold regression model. The results show an “inverted U-shaped” relationship between agricultural production efficiency and agricultural carbon emission intensity. In areas with high agricultural production efficiency, the improvement of production efficiency can suppress the intensity of agricultural carbon emissions; in areas with low agricultural production efficiency, the improvement of production efficiency increases the intensity of agricultural carbon emissions. Finally, based on the research conclusions, this paper provides feasible suggestions and countermeasures for China’s agricultural carbon emission reduction and improvement of agricultural production efficiency.

The development of digital economy not only directly affects agricultural carbon emissions through digital technology input, but also indirectly affects inter-regional agricultural carbon emissions through spatial spillover effect. Based on the panel data of 30 provinces, autonomous regions and municipalities in China from 2012 to 2022 (excluding Tibet, Hong Kong, Macao and Taiwan), this paper uses the entropy method to measure the development level of digital economy, and constructs a spatial econometric model to test the spatial spillover effect and heterogeneity of digital economy on agricultural carbon emissions. The results show that the development of digital economy has a significant inhibitory effect on agricultural carbon emissions. Digital economy has a spatial spillover effect on agricultural carbon emissions. The higher the development level of digital economy in neighboring regions, the less agricultural carbon emissions in the region. In the northeast and central regions, the development level of the digital economy has a significant positive impact on agricultural carbon emissions. In the western region, the impact is significantly negative, while in the eastern region, it is not significant. In addition, there is a spatial spillover effect in the northeast region. This paper puts forward policy suggestions from four aspects: promoting the construction of digital infrastructure, narrowing the development gap among provinces, strengthening the digital literacy of agricultural operators, and promoting financial innovation, so as to further play the role of carbon emission reduction in the digital economy.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-21487-4.

How does agricultural specialization affect carbon emissions in China?

Impact and transmission mechanism of digital economy on agricultural energy carbon emission reduction

As a progressive and systematic initiative that necessitates the collective participation of society, achieving the goals of carbon peaking and carbon neutrality has had a significant and positive impact on the transformation of the energy structure, the development of the new energy industry, the enhancement of economic efficiency and environmental quality, and the deepening of international cooperation across multiple dimensions. This study examines how the digital economy affects carbon reductions in the context of China’s pursuit of carbon peak and carbon neutrality targets. To thoroughly examine how regional digital economy development influences agricultural carbon emissions and uncover its underlying mechanism, this study uses regression analysis models using panel data from 31 Chinese provinces (not including Hong Kong, Macau, and Taiwan) from 2013 to 2022. In the meantime, the study investigates the spatial effects of the digital economy on agricultural carbon emissions. The results show that the rapid development of the digital economy plays a significant role in reducing agricultural carbon emissions. In particular, every 1 unit increase in the level of digital economy development is associated with a 0.125-unit reduction in agricultural carbon emissions. Second, the expansion of the digital economy allows regional labor transfer, which indirectly influences its suppressive effect on agricultural carbon emissions through this channel. Third, the expansion of the digital economy in one area has significant spatial spillover effects, leading to agricultural carbon emissions in other provinces and cities. Fourth, these spatial spillover effects vary depending on the topography and economic production. In particular, flat regions and high-yield agricultural areas see greater carbon reduction spillover effects from the digital economy compared to steep regions and low-yield agricultural areas. Therefore, research on the impact of the digital economy on agricultural carbon emissions can help to reveal the path of the digital-technology-driven green transformation of agriculture and provide a scientific basis for optimizing agricultural carbon-emission-reduction policies and achieving sustainable agricultural development.

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.

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.

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.

With the rapid development of the digital economy and the increasing global attention to the issue of agricultural carbon emissions, the use of the digital economy to promote agricultural carbon emission reduction has become an inevitable path to achieve sustainable agricultural development. Based on China's provincial panel data from 2015 to 2022, this paper constructs a comprehensive digital economy evaluation index system and empirically analyzes the impact of rural digital economy development on agricultural carbon emissions. The results show that the vigorous development of digital economy significantly reduces agricultural carbon emissions, and effectively promotes the green transformation and sustainable development of agriculture through multiple paths such as optimizing industrial structure, promoting technological innovation, and improving service efficiency.

The rapid development of the digital economy has increased attention to its impact on agricultural carbon emissions. Using panel data covering 30 Chinese provinces from 2012 to 2022, this study examines the relationship between the digital economy and agricultural carbon emissions, along with the underlying mechanisms. The results indicate that the digital economy significantly reduces overall agricultural carbon emissions, a finding that remains robust across various tests. Notably, the effect of the digital economy on the intensity of agricultural carbon emissions is heterogeneous, with more pronounced reductions observed in major grain-producing regions. Key intermediary mechanisms for this reduction include agricultural scale, the enhancement of digital financial services, and technological innovation. Based on these findings, we recommend focusing on strengthening digital infrastructure, enhancing the digitally inclusive financial system, promoting the development of digital agricultural talent, and exploring innovative models of digital agricultural development.

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.

This study intends to determine the inter-relationship among carbon emissions and economic development from agriculture in Jharkhand, during 2005-2022, utilizing decoupling and decomposition analysis. The decoupling analysis revealed a weakly decoupled state for 7 years, followed by strongly decoupled and strongly coupled states for 3 years, an expansively coupled state for 2 years, a weakly coupled state for one year, and a recessively decoupled state for one year. This suggests that there was no consistent evolutionary path from the coupled state to the decoupled state. However, the empirical findings of the Log Mean Divisia Index method suggest that the rise in agricultural carbon emissions from 2005 to 2022 is primarily due to the effects of agricultural economics followed by the agricultural labor force. Additionally, factors such as the intensity of agricultural carbon emissions and agricultural structure tend to decrease agricultural carbon emissions, with the intensity of emissions having the largest impact on reducing emissions. Furthermore, the combination of decoupling and decomposition analysis suggests that the environmental pressure declined with a rise in the agricultural economy in 2008, 2009, and 2018. The intensity of agricultural carbon emissions significantly contributed to reducing overall emissions during these years. Overall, efforts to reduce carbon emissions from the agricultural sector in Jharkhand are still ineffective.

Despite achieving remarkable development, China’s agricultural economy has been under severe environmental pressure. Based on previous studies, the present study further considers the sources of agricultural carbon emissions in depth, estimates China’s agricultural carbon emissions from 1997 to 2016, and analyzes the agricultural pollution faced by China and its provinces. The study estimates the amount and intensity of agricultural carbon emissions in China from five carbon sources—agricultural materials, rice planting, soil N2O, livestock and poultry farming, and straw burning—and analyzes their spatial and temporal characteristics. The following results were obtained: (1) between 1997 and 2016, the amount of agricultural carbon emissions in China generally increased, while the intensity of agricultural carbon emissions decreased; (2) in the same period, the amount of carbon emissions from each category of carbon source generally increased, with the exception of rice planting; however, the amount of emissions fluctuated; (3) the amount and intensity of carbon emissions varied greatly among provinces; (4) the emissions from different categories of carbon source showed different concentration trends and agglomeration forms; (5) China’s agricultural carbon emissions showed obvious spatial correlation, which overall was high–high agglomeration; however, its carbon emissions gradually weakened, and the spatial agglomeration of agricultural carbon emissions in each province changed between 1997 and 2016.

Research has found that the transfer of agricultural land in China has to some extent led to agricultural carbon emissions. Therefore, it is urgent to systematically analyze the reasons for carbon emissions caused by agricultural land transfer, find ways to mitigate the increase in agricultural carbon emissions, and achieve low-carbon and sustainable development of agriculture. This article analyzes the relationship between agricultural land transfer, rural human capital, and agricultural carbon emissions in 30 sample provinces in China based on property rights incentives and scale operation theory, using the system GMM model, adjustment model, and threshold model. The results indicate that the transfer of agricultural land has, to some extent, intensified agricultural carbon emissions, with an increase of 0.003 units per unit of agricultural land transfer intensity. Rural human capital has mitigated the carbon emissions resulting from agricultural land transfer and played a corrective role. Under varying levels of rural human capital, there exists a dual threshold effect on the impact of agricultural land transfer on carbon emission intensity, exhibiting a pattern of ‘ineffectiveness-promotion-inhibition’. The analysis of regional heterogeneity reveals significant differences in the relationship between agricultural land transfer and carbon emissions between major grain-producing areas and non-grain-producing areas. It is worth noting that in the northern region, the transfer of agricultural land exacerbates carbon emissions, whereas in the southern region, higher levels of rural human capital effectively curb the growth of carbon emissions. Furthermore, the impact of agricultural land transfer on carbon emissions is not confined to specific regions, indicating that its environmental consequences transcend administrative boundaries and spread geographically, displaying distinct time-dependent characteristics.

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