Impact of mineral based social equity on unearthing inequities: A longitudinal analysis of environmental and social equity of mineral exploitation in the global south.

Mineral extraction plays a pivotal role in economic growth and development of the Global South, serving as a cornerstone for numerous industries and contributing significantly to national economies. However, its exploitation often comes with significant environmental and social challenges. This research paper examines the impacts of mineral extraction on environmental sustainability and social equity in the Global South, focusing particularly on China over the past two decades (2002-2022). Utilizing the Dynamic Autoregressive Distributed Lag (DARDL) methodology, we offer a comprehensive empirical analysis of the impact of mineral extraction on environmental and social implications. Our findings provide an in-depth perspective, highlighting the multifaceted nature of this relationship. The study underscores the temporal dynamics and evolving nature of the environmental and social repercussions associated with mineral extraction. It offers critical insights for policymakers, industry stakeholders, and civil society organizations engaged in the Global South.

Exploring the impact of carbon emissions and co-macroeconomic determinants on China's sustainable apple export.

China is the foremost global consumer, producer, and exporter of fresh apples. In 2021, China produced roughly 44 million tons of apples and exported just over 1 million tons, a nearly 2% increase over the previous year. However, the ongoing COVID-19 pandemic has had a detrimental impact on global trade and has led to a decrease in China's agricultural exports. The present study aims to contribute to the existing body of literature by analyzing plausible macroeconomic determinants that might impact China's apple exports. We used novel dynamic autoregressive distributed lag (DYARDL) simulations to model causal relationships among fundamental economic parameters. We made use of annual time series data from 1990 to 2020 from the World Bank and China's national statistical bureau. We found that increases in apple orchard area, apple production, and trade openness had a positive impact on apple exports over both the short and long term. Conversely, decreases in the prices of exported apples, agrochemicals, and carbon emissions in the agricultural sector had a positive impact on the long-term and short-term exportation of apples. Finally, we note that pictographic illustrations from the DYARDL simulations provide corroborative evidence for our findings. Based on the study results, this study proposes that the adoption of technological advancements in apple orchards could potentially enhance apple production while simultaneously upholding environmental sustainability.

The effect of energy resources on economic growth and carbon emissions: A way forward to carbon neutrality in an emerging economy.

Globally, all countries have producing different levels of carbon emissions and also facing both the problems of climate change and global warming due high carbon emissions in the atmosphere. Therefore, it is important to cutting carbon emissions in the atmosphere. This is only possible by switching to cleaner fuels, use of innovation technologies and development of carbon capture storages. These can substantially help the nations to reaching carbon neutrality. Given this background, this paper examines the effect of disaggregated energy consumption, technological innovations, capital on economic output and CO2 emissions in India for the period of 1990-2018. Based on empirical analysis, our long-run elasticities indicate that disaggregated energy consumption and technological innovations have a positive impact on economic growth, while renewable energy consumption and technological innovations have a positive impact on CO2 emissions. It implies that more use of energy consumption producing significant amount of CO2 emissions and by using renewable energy consumption and technological innovations (i.e. carbon capture storages) can significantly lowering CO2 emissions, which is clearly indicating that India has moving towards carbon neutrality. The causality analysis further indicates a unidirectional causal relationship running from disaggregated energy usage to economic growth and carbon emissions. These empirical findings suggest that the increased consumption of renewable power does not lead to rise carbon emissions, which, in turn, ensures sustainable economic growth.

Foreign direct investment, financial development, energy consumption, and air quality: A way for carbon neutrality in China.

Air quality is a social, economical, and health issue for fast-developing countries such as China. Due to the overuse of nonrenewable energy, industrialization, and the population put pressure on air quality, which seriously threatens public health and economic growth. This study focuses on air quality and also aims to investigate the short-and long-run correlation between foreign direct investment, energy consumption, domestic credit, and financial development. The Autoregressive distributed lag model and the Granger non-causality test were carried out over the period from 1985 to 2018. The main findings of this study show a positive and significant long-run impact of energy consumption on air quality. In addition, domestic credit and financial development similarly show a significant positive short-run association with air quality. Moreover, the unidirectional causality correlation running from foreign direct investment and domestic credit to air quality was concluded by the Granger non-causality test. Considering the empirical analysis, this study suggests that domestic financial institutions should offer credit to industries at a low-interest rate in order to help them to switch from non-renewable to renewable energy consumption towards the promotion of sustainable and healthy air quality.

Bioenergy consumption, carbon emissions, and agricultural bioeconomic growth: A systematic approach to carbon neutrality in China.

China is the world's largest fossil fuel consumer and carbon emitter country. In September 2020, China pledged to reduce carbon emissions, and achieve carbon neutrality by 2060. Therefore, this study aimed to contribute to the literature and show the pictorial nexus of bioenergy and fossil fuel consumption, carbon emission, and agricultural bioeconomic growth, a new pathway towards carbon neutrality. For this study, time-series data from 1971 to 2019 were used to analyze the autoregressive distributed lag (ARDL) bound testing and novel dynamic autoregressive distributed lag (DYNARDL) simulation models. Initially, the unit root tests results showed that all variables were stationarity at the level and first difference. The presence of cointegration between selected variables was confirmed by the results from ARDL bound test. In addition, the results of long-run and short-run nexus show an increase in bioenergy consumption that caused an increase in agricultural bioeconomic growth both in the long and short-run nexus. A decrease in fossil fuel consumption was shown to result in increased agricultural bioeconomic growth with respect to both long- and short-term effects. Furthermore, the results of the novel dynamic ARDL simulation model demonstrated that a 10% positive shock from bioenergy consumption caused an increase in agricultural bioeconomic growth, while at the same time, a 10% negative shock in bioenergy consumption led to a decrease. A 10% negative shock from fossil fuels caused an increase in agricultural bioeconomic growth, whereas a 10% positive shock from fossil fuels led to a decrease. Therefore, this study suggests that China needs to switch from fossil fuel and other non-renewable energy consumption to sources of bioenergy and other renewable energy consumption to achieve carbon neutrality by 2060.

The impact of economic growth, energy consumption, trade openness, and financial development on carbon emissions: empirical evidence from Malaysia.

Globally, the rising concentration of anthropogenic greenhouse gases emission in the atmosphere is extremely detrimental to the environment. The high concentration among all greenhouse gases is carbon dioxide emission. Therefore, this study explores the linkages between energy consumption, trade openness, globalization, urbanization, and carbon dioxide emission for Malaysia over the spans from 1978 to 2018. ARDL bound testing model was employed to investigate involvement in the elevation of carbon dioxide emissions in the economy. The study illustrates that a 1% growth in energy consumption, trade openness, and urbanization will deteriorate the environment by 0.18%, 0.03%, and 2.51% respectively. Further, variance decomposition analysis predicts that all the determinants in the study have significantly caused carbon dioxide emission in Malaysia. The paper presents scientific support for further studies and argues for the use of innovation shocks as a policy instrument for a prosperous future by formulating more successful environmental policies.

Revisiting the relationship between carbon emission, renewable energy consumption, forestry, and agricultural financial development for China.

Globally, the use of modern technologies is increasing along with carbon emission due to the consumption of fossil fuels to operate modern technologies. Therefore, in this study, we aimed to investigate the relationship between carbon emission, renewable energy consumption, forestry, and agricultural value added per capita from 1998 to 2018. The auto-regressive distribution lag model was estimated for long-run and short-run correlation analysis. The results of this study revealed that carbon emission decreases owed increases in forest areas in the long and well as short-run nexus. Furthermore, in the short run, carbon emission decreases due to an increase in renewable energy consumption. In addition, the carbon emission was run in an upward direction parallel to agricultural financial development. Furthermore, this study confirmed that the unidirectional causality between variables by estimating the non-Granger causality test. Therefore, this study suggests that to combat carbon emissions with carbon emission, it is necessary to switch from nonrenewable energy to renewable energies and organic fertilizer consumption along with afforestation to make the climate free from carbon.

Dynamic linkage between industrialization, energy consumption, carbon emission, and agricultural products export of Pakistan: an ARDL approach.

This study aims to contribute to the literature and examine the causal relationship between Pakistan's agricultural products export, industrialization, urbanization, transportation, energy consumption, and carbon emissions. For the last four decades, time-series data were used to employ short-run and long-run nexus between the selected variables by analyzing the autoregressive distributed lag model (ARDL). The Granger causality test was analyzed to estimate the causality directions. The unit root test results indicate that all the selected variables are stationary at the level and first difference. The bound test confirmed that all variables are cointegrated at a 1% significance level. Long-run estimates suggest that an increase in energy consumption will increase the export of agricultural products. An increase in urbanization, transportation, and carbon emission resulted in a decrease in agricultural products export in Pakistan. In the short run, an increase in industrialization, transportation, and energy consumption leads to an increase in agricultural products export. Increasing urbanization and carbon emission decrease the agricultural products export of Pakistan. Based on our findings, we recommend sustainable agricultural production, renewable energy consumption, low carbon emission technologies, and a green portfolio for sustainable agricultural products export.

A visualization review analysis of the last two decades for environmental Kuznets curve "EKC" based on co-citation analysis theory and pathfinder network scaling algorithms.

Environmental Kuznets curve (EKC) is a statistical tool to examine the cointegration and causality nexus between economic growth and carbon emissions. The EKC is widely used in energy and environmental economics studies. Although a large number of researchers have analyzed the EKC by applying different statistical models, some review work has been summarized to draw a pictorial view of extending studies in this research field. However, still, the macroscopic overview needs to be considered. Therefore, this study aims to contribute to the literature for finding a new pathway for further research employing, and to facilitate this research, scientometric analysis is carried out by feature in CiteSpace. The dataset was screened and found 2384 records out of 59,225 Web of Science (WoS) references, and the records for the timespan 1999-2019 was used to visualize the knowledge map and outcome of the scientific enterprise. The visualization results reveal the most influencing studies, institutions, authors, countries, keywords, and category cloud, in the research field of EKC. This article reveals that the research on EKC in alignment with green and sustainable technology science requires more attention. Further, this article would help authors and publishers make their decisions for the research of EKC and planning for future perspectives to contribute to academic development and applied methodology.

The Spillover Influence of Household Waste Sorting on Green Consumption Behavior by Mediation of Environmental Concern: Evidence from Rural China.

The spillover effect of environmental behavior has been of wide concern in recent years. The purpose of this paper is to explore the influence of household waste sorting on green consumption (behavioral spillover) and the possible psychological mechanisms involved in such spillover of environmental concern. Though it is important, insufficient attention has been paid to exploring the relationship, and the process of its formation, between waste sorting and green consumption. To narrow this gap, survey data collected in 2018 from 688 rural households from Shaanxi Province in western China were used. The propensity score matching method was employed to measure the effect of waste sorting on rural households' green consumption. The mediating model was employed to investigate the path of influence in the relationship between waste sorting and green consumption. The results showed that waste sorting behavior positively spilled over into green consumption, with a net effect of 0.205. Environmental concern has a mediating effect on the relationship between waste sorting and green consumption behavior, with a mediating effect of 0.3177. In summary, household waste sorting behavior has a spillover effect on green consumption behavior as a result of the mediation effect of environmental concern. The results of this article fill in our knowledge on the spillover effects of waste sorting behavior in developing countries. Policy makers and regulators should vigorously advocate and implement waste sorting behavior, increase farmers' concern for the environment, and promote their participation in green consumption behavior, so as to maximize the spillover effect.

Perceived Value Influencing the Household Waste Sorting Behaviors in Rural China.

Waste sorting is the cardinal measurement to solve the problem of low efficiency of rural environmental governance and to alleviate environmental pollution by reduction, recycling, and harmlessness in rural areas. However, non-excludable and non-rival features of public goods easily cause a wide free-rider problem, which results in a low frequency of participation in the waste sorting of rural people. Based on the theory of the utility maximization of the rational economic man, this paper investigates survey data of 688 farm households in three cities and three counties of Shaanxi Province to explore the effect of the perceived value on the household waste classification behavior based on cost-benefit analysis. The results show that perceived benefit and perceived cost are important perceived value factors affecting farmers' participation in waste sorting. Specifically, the spiritual benefit of the perceived benefit has a significantly positive impact on classification behavior, while the time cost, physical cost, and material cost of the perceived cost have a negative impact on waste classification behavior. Further study of the heterogeneity of income impact shows that time cost only has a significant impact on the high-income group of farmers' classification behavior, while spiritual benefit and learning cost only affect the low-income group of farmers' waste classification behavior. Material cost has different influence directions on high- and low-income groups. In view of the aforementioned findings, this study highlights corresponding policy implications from the perspective of perceived benefit and perceived cost.

Looking back over the past two decades on the nexus between air pollution, energy consumption, and agricultural productivity in China: a qualitative analysis based on the ARDL bounds testing model.

Increasing population and food demand has led to steadily declining resources as a result of over-exploitation and fossil fuel consumption that cause air contamination and reduce soil fertility. Therefore, this study aimed to investigate the correlation between air pollution, energy consumption, and the contribution of agriculture to national GDP. Secondary study data covering two decades were collected from different sources, and an autoregressive distributed lag (ARDL) bounds testing model was employed to determine long-run and short-run correlations. First, the unit root test was used to determine the stationarity of variables, and results showed that variables were integrated at level, ARDL co-integration equation estimation, which rejected the null hypothesis at less than 5% significance level. Further, based on the results of the ARDL bounds testing model, F-statistic values exceeded the upper bound value. This entire model was adjusted at a speed of -2.364 towards long-run equilibrium. In addition, CUSUM test and CUSUMSQ test results confirmed the goodness of fit of this model. In light of the resulting policy implications, the Chinese government may consider measures to improve the agricultural industry to meet the food demand for the fast-growing population while maintaining a healthy environment and safeguarding the available limited resources for future generations.