Impact of Grain Production on Agricultural Carbon Emission in Jharkhand, India: An Empirical Analysis

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.

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.

<p _msthash="770" _msttexthash="18511649104"><span lang="EN-US" style="font-size:12.0pt"><span style="font-family:"Times New Roman",serif">Under the background of China's “double carbon” goal, digital economy has become an important way to reduce carbon emissions in China. This paper utilizes the provincial panel data of China from 2012 to 2022, introduces the perspective of agricultural science and technology innovation, empirically examines the impact mechanism of regional digital economy development on agricultural carbon emission through regression analysis model, and portrays the dynamic effect and spillover effect of digital economy development on agricultural carbon emission from both time and space dimensions. The empirical results show that: digital economic development will have a significant inhibitory effect on the intensity of agricultural carbon emissions, and the inhibitory effect will be indirectly affected through the path of agricultural scientific and technological innovation; the impact of digital economic development on the intensity of agricultural carbon emissions there is a time lag effect, the current stage of the digital economic development will still have a strong inhibitory effect on the intensity of agricultural carbon emissions in the future; Digital economic development has a spatial spillover effect, i.e., the development of the regional digital economy will have an inhibitory effect on the intensity of agricultural carbon emissions in neighboring provinces. Based on this, it is proposed to strengthen the construction of digital infrastructure, promote the coordinated development of the digital economy in the region, and formulate policies to reduce carbon emissions in agriculture.</span></span></p>

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.

Ensuring food security and curbing agricultural carbon emissions are both global policy goals. The evaluation of the relationship between grain production and agricultural carbon emissions is important for carbon emission reduction policymaking. This paper took Heilongjiang province, the largest grain-producing province in China, as a case study, estimated its grain production-induced carbon emissions, and examined the nexus between grain production and agricultural carbon emissions from 2000 to 2018, using decoupling and decomposition analyses. The results of decoupling analysis showed that weak decoupling occurred for half of the study period; however, the decoupling state and coupling state occurred alternately, and there was no definite evolving path from coupling to decoupling. Using the log mean Divisia index (LMDI) method, we decomposed the changes in agricultural carbon emissions into four factors: agricultural economy, agricultural carbon emission intensity, agricultural structure, and agricultural labor force effects. The results showed that the agricultural economic effect was the most significant driving factor for increasing agricultural carbon emissions, while the agricultural carbon emission intensity effect played a key inhibiting role. Further integrating decoupling analysis with decomposition analysis, we found that a low-carbon grain production mode began to take shape in Heilongjiang province after 2008, and the existing environmental policies had strong timeliness and weak persistence, probably due to the lack of long-term incentives for farmers. Finally, we suggested that formulating environmental policy should encourage farmers to adopt environmentally friendly production modes and technologies through taxation, subsidies, and other economic means to achieve low-carbon agricultural goals in China.

Based on the classic IPCC carbon emission calculation theory, this paper calculates the agricultural carbon emissions intensity and efficiency in Zhejiang Province from 2011 to 2020. The LMDI model is further adapted to carry out the influence factors of agricultural carbon emissions. In addition, the grey prediction model GM (1, 1) is used to predict the carbon emissions of Zhejiang Province from 2022 to 2025. The results show that the agricultural carbon emissions and carbon emission intensity in Zhejiang Province have a downward trend. Further, it is concluded that Shaoxing, Hangzhou, Jiaxing, and Huzhou are the cities with low emission and high efficiency, and Wenzhou is the city with high emission and low efficiency. Meanwhile, the improvement of Total Factor Productivity (TFP) results from the joint action of Technical Progress Efficiency (TECH) and Technical Efficiency (EFF). TECH is greater than EFF, and Scale Efficiency (SE) and Pure Technical Efficiency (PTE) contributions change with the years. In general, the contribution of PTE is more significant than that of SE, and its improvement mainly rests on technical progress. Among the factors influencing agricultural carbon emission efficiency, agricultural carbon emission intensity and labor force size have inhibiting effects on agricultural carbon emission efficiency growth. In contrast, agricultural industrial structure, economic development, and urbanization positively affect agricultural carbon emission efficiency. The prediction results show that the overall carbon emissions of Zhejiang Province will get a downward trend. Finally, based on these findings, we offer policy implications.

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

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.

The study of the evolutionary patterns and trends of agricultural carbon emission intensity and agricultural economic development levels plays an important role in promoting the green and low-carbon sustainable development of agriculture. This paper adopts the carbon emission factor method to measure the agricultural carbon emissions in Jiangxi Province from 2001 to 2020, uses the LMDI decomposition method to explore the drivers of carbon emissions, and further analyzes the coupling relationship between agricultural carbon emissions and the agricultural economy using the Tapio decoupling model, based on which a GM (1,1) model is used to forecast the agricultural carbon emissions in Jiangxi Province from 2001 to 2015. According to the research results, agricultural carbon emissions in Jiangxi Province show a trend of “rising and then falling”, with the intensity decreasing; the level of economic development is the main factor that increases carbon emissions, while the efficiency of agricultural production, the size of the labor force, and the structure of agricultural production have positive effects in terms of reducing carbon emissions. How to reduce carbon emissions while promoting agricultural economic development is an issue that remains to be addressed in the future. Further analysis found that the decoupling states of Jiangxi Province from 2001 to 2009 switched between strong decoupling and weak decoupling, with weak decoupling dominating the years 2010–2015 and strong decoupling dominating from 2016 onwards. With the continuous promotion of carbon emission reduction, agricultural carbon emissions in Jiangxi Province will continue to show a decreasing trend over the next five years. Three policy recommendations are put forth in order to advance the effort to reduce agricultural carbon emissions in Jiangxi Province: cultivating high-quality and low-carbon rice varieties, switching to green agricultural production, and coordinating the connection between economic growth and agricultural carbon emissions.

The focus of world governance on climate change has been on the industrial and transport sectors, yet the agricultural sector produces a lot of greenhouse gases, and this has always been ignored. This paper focuses on China, one of the world’s largest agricultural countries, and it investigates its agriculture carbon emission from a new perspective of the internal structure of it, which is relatively under-researched. Carbon metrology, the emission factor method and kernel density estimations are used to analyze China’s agricultural carbon emissions structure and its regional differences and its dynamic evolution characteristics. We find that: (1) China’s total amount of agricultural carbon emissions showed a ladder-like upward trend, but the growth rate of it has gradually slowed down; the inter-provincial heterogeneity of the agricultural carbon emissions was obvious. (2) From the standpoint of the grain functional areas, the annual total amount of agricultural carbon emissions and the amount of carbon emissions of each carbon source in the major grain producing areas were significantly higher than those in the major grain sales areas and the production–sales balance areas, and the carbon emission intensity in the major grain producing areas was the lowest overall. (3) In regard to the internal structure, China’s agricultural carbon emissions mainly came from the livestock and poultry, rice planting and agricultural energy sectors; the proportion of carbon emissions that were caused by the agricultural materials, agricultural energy and soil increased in general, and the inter-provincial differences between them expanded, while the inter-provincial differences between livestock and poultry gradually decreased. The proportion of carbon emissions from the six major agricultural carbon sources showed a convergence trend, and their kernel density had a right tail phenomenon. Our research deepens the understanding of China’s agricultural carbon emission structure, contributes to the rational optimization of the agricultural structure, and helps the agriculture sector and the rural areas to reach the carbon peak.

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.

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.

This study examines the impact of digital economy development on carbon emissions in Chinese agriculture and its underlying mechanisms. Empirical analysis is conducted using panel data from 31 provinces in China for the years 2013 to 2021, employing a fixed-effects model.The study reveals that the development of the digital economy significantly reduces agricultural carbon emissions, with this effect showing a non-linear increasing trend. The impact of digital economy development on agricultural carbon emissions varies with climate types, and the reduction effect is more pronounced in regions with lower rainfall. Furthermore, the development of the digital economy lowers the intensity of agricultural carbon emissions by improving logistics efficiency and promoting industrial upgrading and transformation.This paper provides a theoretical basis and policy recommendations for the nation to reduce agricultural carbon emissions and promote green transformation. It suggests that the government should strengthen support and guidance for the development of the digital economy, actively promote the digitalization of agriculture, including the formulation of differentiated strategies for the development of digital agriculture, improvement of regulations and standards for agricultural product logistics, and enhancement of the application and innovation in smart agriculture.

Greenhouse gas emissions from the agricultural ecosystem account for 7%–20% of the world’s total greenhouse gas emissions, while approximately 17% of China’s carbon emissions are from agriculture. In this study, based on the scientific calculation system of carbon emissions in agriculture, we calculated the carbon emissions of agriculture in the Hotan prefecture between 1999 and 2013 and analyzed their spatial-temporal characteristics; next, we used the LMDI model to study the driving factors of agricultural carbon emissions. The results demonstrated the following: (1) in time series, the agricultural carbon emissions showed three stages of change, i.e., “decline, continued to rise and decline”, during the period of 1999 to 2013 in the Hotan prefecture; (2) In space, the carbon emissions from agricultural land use, paddy fields, enteric fermentation, and manure management were different due to the different sizes of cities and counties. The intensity of agricultural carbon emissions was varied and high, but the agricultural production structure, agricultural carbon emissions structure and other aspects had a high degree of consistency and homogeneity in the cities and counties of the Hotan prefecture; (3) Regarding the driving mechanism, the labor factor, agricultural labor productivity, and planting-animal husbandry carbon intensity are the main factors that increase agricultural carbon emissions in the Hotan prefecture. Compared with 1999, three major factors cumulatively achieved a 199.68% carbon emission increment from 2000 to 2013, of which the labor factor cumulatively increased by 120.04%, the agricultural labor productivity factor cumulatively increased by 54.94% and the planting-animal husbandry carbon intensity factor cumulatively increased by 24.70%. The agricultural production structure factor largely inhibited agricultural carbon emissions of the Hotan prefecture, which cut 99.74% of the carbon emissions from 2000 to 2013. Finally, we proposed policy recommendations, including the acceleration of labor transfer, the innovation and promotion of science and technology, the scientific breeding and rational disposal of livestock waste, and the adjustment and optimization of the agricultural industry structure.

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.