Does the prevailing Indian agricultural ecosystem cause carbon dioxide emission? A consent towards risk reduction

The ecological impact of agricultural production on CO2 emissions in India: Pathways to sustainable agriculture

This study examines the relationship between CO2 emissions and agricultural production in India from 1990 to 2023, using an Autoregressive Distributed Lag (ARDL) model. Key agricultural indicators analyzed include the Food Production Index (FPI), Cereal Production (CP), Livestock Production Index (LPI), and the value added by Agriculture, Forestry, and Fishing (AFF). The results show that on the long run, a 1 % increase in FPI leads to a 7.86 unit increase in CO2 emissions per capita, while a 1 % increase in livestock production results in a 3.28 unit decrease in CO2 emissions per capita. In the short run, a similar increase in food production and livestock production also influences CO2 emissions, with notable but varying impacts over time. These findings underline the environmental trade-offs between food security and CO2 emissions, emphasizing the need for sustainable agricultural practices. This research contributes to existing literature by utilizing a broad set of agricultural indicators and robust ARDL analysis to examine both short- and long-term effects, providing a more comprehensive understanding of agricultural sustainability. The study was prompted by India's rapid agricultural growth, driven by its growing population and economic expansion, which has raised significant environmental concerns. Unlike prior research that often takes a generalized or global approach, this study offers an India-specific analysis that captures the country's distinct socio-economic and ecological conditions. By focusing on nationally relevant agricultural indicators and sustainability challenges, the research provides context-sensitive insights that can support effective and targeted policy design. The findings highlight the importance of policies that align agricultural productivity with sustainability, supporting the UN Sustainable Development Goals on climate action and food security.

Assessing potential reductions of agricultural GHG in countries with different land productivities: Long-term integrated efficiency in DEA hybrid meta-frontier model

Globally, the agricultural sector is responsible for the emission of ca. 9.3 gigatons of CO2 equivalent annually. A realistic efficiency model orientation, considering agricultural policy objectives in a given region of the world, is a crucial premise for finding the optimal path for achieving global targets of emission reduction. The main objective of this article is to assess agricultural greenhouse gases (GHG) potential reductions in countries with different farming productivity accounting for food security and economic performance of agricultural sector. The analysis focuses on non-radial slack that, theoretically, may be easily reduced by the improvement in available resource management. The DEA-based hybrid super-efficiency meta frontier model with undesirable output was employed, using the efficiency approach integrating three sustainability dimensions. The dataset consisted of data from 99 countries (2005-2018) divided into clusters. Several potential model orientations were tested and discussed with regard to agricultural policy objectives. It was found that by reducing slacks, agricultural emissions can be decreased by 0.74 Gt of CO2eq per year. Hence, removing only management inefficiencies would help achieve up to 80% of the global reduction targets in agriculture without a substantial technological change. However, the efficiency change component turned out to be mainly negative over the period studied; thus, a specific focus on agricultural policy is needed in terms of supporting farmers with a more rational use of their resources.

Pesticide residues: Bridging the gap between environmental exposure and chronic disease through omics

Pesticide residues, resulting from agricultural practices, pose significant health and environmental risks. This review synthesizes the current understanding of pesticide impacts on the immune system, highlighting their role in chronic diseases such as asthma, diabetes, Parkinson's disease (PD) and cancer. We emphasize the significant role of omics technologies in the study of pesticide toxicity mechanisms. The integration of genomics, proteomics, metabolomics, and epigenomics offers a multidimensional strategy for a comprehensive assessment of pesticide effects, facilitating personalized risk management and policy formulation. We advocate for stringent regulatory policies, public education, and global cooperation to enhance food safety and environmental sustainability. By adopting a unified approach, we aim to mitigate the risks of pesticide residues, ensuring human health and ecological balance are preserved.

Fiscal policy, green finance, and low carbon transformation nexus: a novel study unleashing the synergistic effects of carbon reduction and pollution in China

Under the simultaneous demands of combating environmental pollution and decreased carbon emissions, it is critical to investigate the combined effect of agricultural contamination reduction and fiscal policy carbon reduction to support and promote green agriculture and low-carbon transformation. Based on provincial panel data of 2007 to 2020 in China, this paper employs the spatial Dubin model to empirically examine the pollution reduction and carbon reduction effects of fiscal policies supporting agriculture, as well as calculating the synergistic effect of pollution reduction and carbon reduction. Our study's findings reveal that non-point source agricultural pollution and agricultural carbon emissions have a tendency of growing and subsequently reducing, such as increasing from 2007 to 2015 and decreasing from 2016 to 2020. Second, results demonstrate that agricultural carbon emissions and agricultural pollution have a positive geographical dependency in each province, and fiscal policies supporting agriculture have high-high and low-low spatial clustering features. Furthermore, fiscal policies that promote agriculture can lower local agricultural carbon emissions and pollution while also having a considerable beneficial spillover impact on neighboring provinces. According to the study findings, the fiscal policy for supporting agriculture has a negative pollution reduction impact and a positive synergistic effect, resulting in a synergistic effect of agricultural pollution reduction and carbon reduction. The outcomes of this study can serve to promote carbon-reduction measures and provide recommendations for future policy development.

The impact of economic growth, tourism, natural resources, technological innovation on carbon dioxide emission: evidence from BRICS countries

The main objective of this manuscript was to investigate the relationships among economic development, tourism, the use of natural resources, technical advancement, and carbon dioxide emissions in the BRICS group of nations. Data from the panel was gathered from 1995 to 2018. Modern methodology tools including the CS-ARDL tests, Westerlund cointegration tests, and panel data unit root tests have been used in this study. Results of the models show that all the variables were transformed to the first difference to make it stationary. The Westerlund model test results suggest that dependent and independent variables have robust cointegration. Results of the CS-ARDL models reveal that all the variables signed, and significance are aligned with the economic theory. It indicates that except for tourism, the rest of the variables like technical innovation, natural resources, and economic growth have positive and significant effects on carbon dioxide emissions both in the short and long runs. Additionally, a 1% rise in economic growth, technical innovation, and natural resources over the long term would raise carbon dioxide emissions in the BRICS economies by 1.79%, 0.15%, and 0.10%, respectively. However, a 1% increase in tourism would result in a 0.39% decrease in carbon dioxide emissions among the nations in the panel data set. Therefore, the promotion of sustainable tourism and advancement in technological innovation is highly important in these countries, so the high impact of environmental degradation pressure may reduce to some extent. An in-addition comprehensive set of policies should be made on encouraging low-carbon transportation, promoting sustainable tourism certification, boosting local produce, reducing waste management, and provide education and awareness campaigns to tourists.

Analysis of regional differences and spatial spillover effects of agricultural carbon emissions in China

In order to realize "double carbon" target in agriculture and high-quality development of the rural economy in China, it is crucial to study the regional differences and spatial spillover effects of agricultural carbon emissions (ACE). This paper measures ACE using panel data of 31 Chinese provinces from 2005 to 2020, examines the spatio-temporal evolution characteristics，the convergence of agricultural carbon emissions, compares and analyzes regional differences, and investigates the spatial correlation and spatial spillover effects. The study found that: (1) Total agricultural carbon emissions over the research period exhibit a rising and then reducing trend, the spatial distribution of total agricultural carbon emissions is described as high in east-central and low in west. The gap of agricultural carbon emissions is gradually declining in the east, and will eventually reach their respective steady-state levels in the west and northeast. (2) There is a strong spatial interprovincial link of ACE, which has a beneficial knock-on effect on the convergence of adjacent provinces. (3) Agricultural industrial structure, urbanization level, the size of the agricultural labor force, and the intensity of the agricultural machinery input all directly affect ACE in this province and indirectly affect ACE in adjacent provinces, with the exception of the negligible coefficient of economic development level on ACE. Hence, pertinent policy suggestions are put out to serve as a guide for reducing ACE.

Impact of agricultural production outsourcing services on carbon emissions in China

Increasing food output while reducing agricultural carbon emissions (ACE) is a major challenge to achieving green agriculture in China. Previously unexplored research regarding the relationship between agricultural production outsourcing services (APOS) and ACE is investigated using household microsurvey data in China and econometric methods, and the influencing mechanism is also tested empirically. The results reveal that APOS increases the total ACE and reduces ACE per unit area. The mechanism test shows that APOS are beneficial to the expansion of rice planting areas and farmers' adoption of agricultural green production techniques. The increasing effect of rice planting area on ACE was greater than the decreasing effect of green production techniques. In the future, China should accelerate the selection and breeding of rice varieties with low carbon emissions to reduce the increase of ACE caused by large-scale land management in the process of APOS development. Policy support and subsidies should be strengthened for APOS organizations to purchase green production techniques, so as to further drive farmers to adopt green production techniques and reduce ACE. It is also necessary for China to encourage small-scale farmers to outsource their agricultural production activities to APOS organizations. The role of collective action consciousness of agricultural production in increasing the supply capacity of APOS organizations should be enhanced.

Towards a clean production by exploring the nexus between agricultural ecosystem and environmental degradation using novel dynamic ARDL simulations approach

Agriculture, which serves as a lifeline for us, is unequivocally vital for an agriculture-dependent economy like Bangladesh, not only for its food supply but also because of its significant contribution towards achieving Sustainable Development Goals (SDGs) 1 and 2. However, in a third-world nation like Bangladesh, where farming practices largely circumvent the environmental consequences, raised our concern. In this milieu, this study is a novel attempt to explore the association between agricultural ecosystem and environmental degradation in Bangladesh using a long time spanning from 1972 to 2018. We observed a long-run association between the agroecosystem and CO₂ emission. Further, findings from the dynamic autoregressive distributed lag (DARDL) simulation model revealed that the environmental quality of Bangladesh is heavily distorted by total cereal production, total livestock head, enteric methane emissions, N₂O emissions from manure application, and CO₂ equivalent N₂O emissions from synthetic fertilizers in the short and long run, whereas agricultural technology, pesticide use in agriculture, and burned biomass crop residue deteriorated the environmental quality only in the long run. The counterfactual diagram entailed from the DARDL model projected the trend of CO₂ emission in response to positive and negative changes in the analyzed variables. Lastly, this study established a causal relationship between the agroecosystem and environmental degradation using frequency domain causality. Indeed, our study will aid in reshaping agricultural practices in an eco-friendly manner to mitigate environmental degradation and help formulate pragmatic policy actions so that agro-lead nations can thrive in the race of achieving SDGs 1, 2, and 13.

Assessing the Influence of Financial Inclusion on Environmental Degradation in the ASEAN Region through the Panel PMG-ARDL Approach

The rise of financial inclusion in recent years has attracted the attention of environmental economists to assess its role in environmental degradation. Therefore, this study was carried out with the aim of exploring the impact of financial inclusion on environmental degradation in the ASEAN region using balanced panel data for the period 2000–2019. First, panel unit root tests were employed to examine each data series for stationarity. Findings of the panel unit root tests depicted that all data series are stationary at the first difference. Second, Westerlund and Edgerton’s error correction panel cointegration test was employed to handle heterogeneity and cross-sectional dependence. Third, the PMG-ARDL approach was used to explore the long- and short-term effects of financial inclusion on environmental degradation. Findings of the PMG-ARDL found that financial inclusion, energy use, economic growth and urbanization are causing environmental degradation in the ASEAN region. Furthermore, the financial inclusion coefficient is 0.15, which is statistically significant at 5%. In the short run, a 1% increase in financial inclusion results in a 0.15% increase in environmental degradation, ceteris paribus. In the long run, financial inclusion and CO2 have a positive association that is statistically significant at 5% and has a coefficient value of 0.42. This implies that a 1% increase in financial inclusion results in a 0.42% increase in environmental degradation in the long run. Finally, this study recommends that financial inclusion must be incorporated into climate change adaptation efforts at the local, national and regional levels to address the side effects of increased CO2 emissions.

Risk Preference, Health Risk Perception, and Environmental Exposure Nexus: Evidence from Rural Women as Pig Breeders, China

Rural women are an integral part of the agricultural economy. Still, their exposure to environmental pollution, especially in the context of risk preference and health risk perception, has not gained much attention in the existing literature. So to explore this notion, a survey and experimental data of 714 rural Chinese women as pig breeders are taken, we innovatively evaluate the degree of environmental exposure from the pre-exposure, in-exposure, post-exposure intervention of women breeders, and two-stage least squares (2SLS) method is employed to address the endogeneity issue between health risk perception and environmental exposure. The results show that rural women breeders suffer from severe environmental exposure, and the degree of environmental exposure is up to 72.102(Min = 0, Max = 100). Risk preference also emerges as a crucial determinant behind their environmental exposure, but health risk perception significantly deters the degree of environmental exposure. The health risk perception can offset risk preference effects on women breeders' environmental exposure by 15.15%. Moreover, considering the heterogeneity of the breeding scale, it is found that the impact of risk preference and health risk perception on women breeders' environmental exposure is an inverted U-shaped relationship, i.e., the results are at the turning stage when the breeding scale is 31-40 heads. Based on the empirical findings, the study offers guidelines for policymakers to enhance awareness amongst women breeders regarding health and pollution and encourage them to opt for environment-friendly breeding. Moreover, this research also has substantial guiding significance for related research on environmental exposure of rural women in other developing countries.

Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region

The sustainable environment has been a desired situation around the world for the last few decades. Environmental contaminations can be a consequence of various economic activities. Different socio-economic factors influence the environment positively or negatively. Many previous studies have resulted in the efficient allocation of inputs as an environment-friendly component. This paper investigates the effects of energy efficiency on ecological footprint in the ASEAN region using balanced panel data from 2001 to 2019. First, this paper technically derives the energy efficiency, using the stochastic frontier analysis (SFA) of the translog production type of single output and multiple inputs. Findings of the SFA show that the Philippines and Singapore have the highest energy efficiency (94%) and Laos has the lowest energy efficiency (85%) in the ASEAN region. The estimated average efficiency score of the ASEAN region was around 90%, ranging from 85% to 96%, indicating that there is still 10% room for improvement in energy efficiency. Second, this study employed the panel autoregressive distributed lag (ARDL) model to explore the short run and long run impact of technically derived energy efficiency on ecological footprint in the ASEAN region. Results of the panel ARDL model show that energy efficiency is a reducing factor of ecological footprint in the long run. Moreover, energy efficiency plays a significant role to control the environmental contaminations. In addition, results of this study also explored that urbanization is an increasing factor of ecological footprint, and investment in agriculture is also beneficial for the environment. Moreover, to obtain the directional nature of the associations between the ecological footprint and its independent variables, this paper has employed the paired-panel Granger causality test. The results of the paired wise panel Granger causality test also confirm that the energy efficiency, urbanization, and investment in agriculture cause ecological footprint. Finally, this study recommends that efficient utilization of energy resources as well as investment in agriculture are necessary for sustainable environment.