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In the context of carbon peaking and neutrality, effectively controlling agricultural carbon emissions has gained academic attention. As an essential form of agricultural service scale management, this study investigates whether and how trusteeship affects the carbon emission behavior in planting production.

The authors established a theoretical framework to analyze the impact of agricultural production trusteeship on carbon emissions from planting. China's provincial panel data in the 2012–2021 period were selected to test the impact, mechanisms and heterogeneity of agricultural production trusteeship on carbon emissions from planting using the bidirectional fixed effect model and the panel correction standard error regression model.

The findings indicate that agricultural production trusteeship significantly inhibits carbon emissions from planting, especially in the dimensions of fertilizer input, pesticide application, agricultural film use and mechanical fuel. Agricultural production trusteeship primarily affects the intensity of these carbon emissions through contiguous farmland management and planting structure adjustment. Further examinations revealed that the influence of agricultural production trusteeship on carbon emissions from planting was heterogeneous with respect to geographical location, proportion of non-farming income and scale of agricultural production.

This study is the first to systematically evaluate the impact of agricultural production trusteeship on carbon emissions from planting.

Agricultural development still constitutes an integral part of Ghana's drive towards job creation, industrial development and economic growth with various growth policies placing the agricultural sector at the core. While there are likely environmental effects of agricultural activities, evidence in Ghana remains scanty. The study focused on examining, empirically, the effects of the development of the agricultural sector on carbon dioxide (CO₂) emission in Ghana.

The paper employed the Stochastic impacts by regression on population, affluence and technology (STIRPAT) framework to test for the environmental Kuznets curve (EKC) hypothesis for agriculture and carbon dioxide emission as well as the effect that the changing structure of Ghana's agricultural development has on carbon dioxide emission for the 1971–2018 period. Regression analysis, variance decomposition and causality analysis were performed.

The regression results revealed a U-shaped relationship between agricultural development and carbon emission, implying a rejection of the EKC hypothesis between the two variables. In addition, the Structural Adjustment Programme was found to positively moderate the effect agriculture has on carbon emission.

The study recommends the need for policy-makers to facilitate the large-scale adoption and use of modern technology and environmentally friendly agricultural methods.

The study is among the few works to assess the EKC hypothesis between agriculture and carbon dioxide emission in Africa. The direct and indirect effect of structural adjustment programme on carbon emission is estimated.

The purpose of this paper is to estimate shadow prices of agricultural carbon emissions produced by agricultural inputs, rice paddy and burning crop residue, and to explore the impact of cropping pattern on marginal abatement cost (MAC).

The shadow price of agricultural carbon emissions is estimated by applying directional distance function and non-parametric methods.

The estimated shadow price of agricultural carbon emissions ranges from 6.78 to 557.83 yuan/ton, and the average value is 62.50 yuan/ton (or $10.18/ton). The MAC value varies in different provinces and years. The regional difference of MAC shows a decreasing trend during the investigation period. Cropping pattern shows a significant negative impact on agricultural MAC. A 1 percent decrease of rice proportion leads to a 0.31 percent increase in MAC value. This implies that the higher the proportion of rice is, the lower the economic cost to reduce agricultural carbon emissions would be.

It is feasible to draw up appropriate mechanisms for the allocation of emission reduction responsibilities according to conditions in various regions, with emphasis on the local cropping patterns. There is a trade-off between reducing carbon emission and increasing crop yields.

This study calculates agricultural MAC by using the shadow price approach, taking agricultural carbon emissions as undesired environmental output. The study also provides a reference emission right price and provides guidance to make use of cropping structure adjustment and optimization for exploring the emission reduction strategy.

Quality environment is argued to be essential for ensuring food security. The effect of environmental degradation on agriculture has thus gained the attention of researchers. However, the analyses of aggregate and sectoral effect of carbon dioxide emissions on agricultural development are limited in the literature. Consequently, this study examines the effect of aggregate and sectoral carbon emissions on Ghana's agricultural development.

Time-series data from 1971 to 2017 are employed for the study. Regression analysis and a variance decomposition analysis are employed in the study.

The results show that the country's agricultural development is negatively affected by aggregate carbon emission while financial development, labour and capital increases agricultural development. Further, industrial development and emissions from transport sector, industrial sector and other sectors adversely affect Ghana's agriculture development. The contribution of carbon emission together with other explanatory variables to the changes in agricultural development generally increases over the period.

This study analyses the aggregate and sectoral carbon dioxide emission effect on Ghana's agricultural development.

Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

This paper aims to explore the future path of agricultural development in China toward 2060 under the dual carbon goals, so as to inform better policy choices for facilitating agricultural and rural transformation toward the goal of maintaining food security, sustainable income growth and low carbon emission.

This study employs a single-country, multi-sectoral computable general equilibrium model, CHINAGEM model and develops eight illustrative scenarios to simulate the impacts of attaining dual carbon goals on agricultural development in China. Additional two scenarios have also been designed to inform better policy making with the aim to offset the negative impact of the decarbonization schemes through facilitating agricultural technology progress.

Dual carbon goals are projected to impose substantial negative impact on agricultural productions and consumptions in China in the coming four decades. Under the assumption of business as usual, agricultural production will reduce by 0.49–8.94% along with the attainment of carbon neutrality goal by 2060, with the production of cereals and high-value being more severely damaged. To mitigate the adverse impact of the decarbonization schemes, it is believed that fastening technology progress in agriculture is one of the most efficient ways for maintaining domestic food security without harming the dual carbon goals. In particular, if agricultural productivity (particularly, for cereals and high-value products) can be increased by another 1% per year, the production losses caused by carbon emission mitigation will be fully offset. This implies that promoting technology progress is still the best way to facilitate agricultural development and rural transformation in future China.

The paper contributes to the literature in better informing the impact of dual carbon goals on China's agriculture and the effectiveness of technology progress in agriculture on buffering the adverse impact of the decarbonization schemes and promoting agricultural development.

Mitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.

The study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.

Agriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO₂e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.

The Chinese government should consider expanding its national carbon market to cover agricultural sector.

Existing studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.

This study evaluates the impact of carbon emission on life expectancy in Nigeria. The study also investigates the mediating role of agricultural output and foreign direct investment as suggested by the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH), respectively.

The hypotheses and theories were tested using structural equation modeling (SEM). Primary data were collected using cross-sectional survey design. Questionnaires were distributed and responses were used to measure the latent variables of the study. A confirmatory factor analysis (CFA) was used to evaluate the measurement models, while path analysis was used to estimate the coefficients of the structural equations.

Carbon emission was found to have a negative and significant impact on life expectancy. This impact constituted both direct and indirect effects that were mediated by both foreign direct investment and agricultural output. Carbon emission and agricultural output were found to play significant roles that lead to a further negative- and significant-mediated relationship of carbon emission with life expectancy.

Unlike many previous studies on air pollution, this study investigates carbon emission in particular as well as the mediating role of agricultural output and foreign direct investment in the carbon emission and life expectancy relationship. The use of SEM also fills a methodological gap as it computes coefficients of mediation and controls for measurement bias and multicollinearity.

The main objective of the present study is to figure out the effect of agricultural development on environmental pollution in the Indian context over the period 1970 to 2018. The study also tests the applicability of pollution haven hypothesis.

To begin with, the authors test the stationarity of the variables by using the DF-GLS and KPSS tests. To examine the relationship between agricultural development and carbon emissions, the study applies nonlinear autoregressive distributed lag cointegration test developed by Shin et al. (2014). The study also applies Wald test to test the asymmetry between agriculture and environmental pollution.

The findings of this study indicate that agricultural development in India is good for carbon mitigation in the long run whereas energy consumption degrades the environment. The findings document the existence of an asymmetric association between agricultural development and environmental pollution. Furthermore, the results did not find any presence of pollution haven hypothesis for India.

This is the only empirical work that assesses the contribution of agricultural sector to carbon mitigation in the Indian context. The novelty of the study is further ensured by the very nature that it is the first study that examines the effect of agricultural sector on environment in an asymmetric configuration.

Within an effort of European Union (EU) policy to achieve carbon-neutral agriculture, the present study intends to explore the impact of carbon emissions generated by different sources related to agriculture namely energy used in farming, by enteric fermentation and by fertilizers on agricultural income in 25 countries from EU.

In order to evaluate the environmental – economic performance linkage for EU agriculture, we employ a couple of different widely used panel unit root tests explicitly Levin, Li and Chu, Im, Pesaran and Shin, ADF and PP Fisher Chi-square test cointegration test (Pedroni and Kao cointegration tests) and model estimation methodologies namely the FMOLS and DOLS and ARDL – PMG models.

All the cointegration techniques employed namely Pedroni, Kao test and Johansen Pesaran cointegration tests validate the existence of long run relationships. The most significant finding is the model estimation based on three different methodologies namely FMOLS, DOLS and ARDL/PMG models. No convergence in the results was found by different estimation models. For the short term coefficients and more specifically for the case of carbon emissions generated by energy the impact on agricultural income seems to be decreasing with a decreasing trend, a result that validates the little effort made by farmers to limit carbon emissions along with the limited efficacy of the implementing policy. The same findings are valid for the first two estimation models while for the case of the third model the reversed relationship is validated. For the carbon emissions generated by enteric fermentation, the inverted-U pattern is validated with DOLS and ARDL/PMG model while for the case of fertilizers only the third model confirms the validity of inverted-U- pattern.

Based on the obtained empirical results, a list of policy implications is unveiled with multiple impacts on the strategy and practices adopted by farmers in order for the objective of eco efficieny to be achieved.

The conducted research is focusing on the environmental – economic performance linkages for EU agriculture and examines the role of agri – environmental policy in the evolution of the particular relationship for different sources of environmental pollution in agricultural activity.