Environmental consequences of population, affluence and technological progress for European countries: A Malthusian view

Coupling coordination and driving mechanisms of water resources carrying capacity under the dynamic interaction of the water-social-economic-ecological environment system

The water resources carrying capacity (WRCC) is a complex and comprehensive system that is jointly influenced by water resources, society, the economy and the ecological environment. Previous WRCC studies have primarily focused on estimating the overall level of regional WRCC. Few studies have explored the interactions among the various elements in the WRCC system and their influence on the WRCC evolution. Therefore, the purpose of this paper is, on the one hand, to explore the dynamic interactive relationships within the WRCC system from the perspectives of water resources, society, the economy and the ecological environment using a coupling coordination degree model and a panel vector autoregressive (PVAR) model, and on the other hand, to determine the evolutionary driving mechanism of the WRCC using the geographically and temporally weighted regression (GTWR) model to improve the regional WRCC. Taking 21 cities in Guangdong Province as an example, the results show that (1) the coupling coordination degree among the four WRCC subsystems in Guangdong Province shows an overall upward trend from 2009 to 2020, and the coordination between water resources utilization and other subsystems needs to be further strengthened. (2) The economic subsystem is the core of the WRCC system with reinforcing effects on both water resources and social subsystems but significant inhibitory effects on the ecological environment subsystem. Notably, the development of the ecological environment plays a crucial role in promoting social and economic development. (3) From 2009 to 2020, the development of the WRCC in Guangdong Province is initially driven by social and economic development, followed by economic development and ecological environmental protection, and then mainly by ecological environmental protection, which gradually becomes the primary driving force. This study provides a new entry point for studying the regional WRCC and formulating targeted measures for enhancing the regional WRCC.

The adoption of renewable energy towards environmental sustainability: Evidence from Partial Least Square Structural Equation Modelling (PLS-SEM)

The effect of carbon emissions on the environment has made some of the Sustainable Development Goals difficult to achieve. Despite the efforts of international bodies, there is still a need to address the problem since the transition is not complete. Therefore, this study investigates the effect of globalization, economic growth, financial inclusion, renewable energy, and government institutions on carbon emissions from the period of 1998 to 2021. To be able to assess both the direct and indirect effects of the variables, the Partial Least Square Structural Equation Modelling is employed, where renewable energy serves as the mediator, and the Two-Stage Least Squares is employed as the robustness check. The findings of the study reveal that globalization promotes the use of renewable energy, but financial inclusion has a negative effect on renewable energy use. Renewable energy has a direct positive and significant effect on carbon emissions. Financial inclusion has an indirect negative and significant effect on carbon emissions. The results imply that more enlightenment on financial inclusion will help a smooth transition, and globalization should be embraced when all environmental regulations are enforced.

Shaping a greener future: The role of geopolitical risk, renewable energy and financial development on environmental sustainability using the LCC hypothesis

The recent progress report of Sustainable Development Goals (SDG) 2023 highlighted the extreme reactions of environmental degradation. This report also shows that the current efforts for achieving environmental sustainability (SDG 13) are inadequate and a comprehensive policy agenda is needed. However, the present literature has highlighted several determinants of environmental degradation but the influence of geopolitical risk on environmental quality (EQ) is relatively ignored. To fill this research gap and propose a inclusive policy structure for achieving the sustainable development goals. This study is the earliest attempt that delve into the effects o of geopolitical risk (GPR), financial development (FD), and renewable energy consumption (REC) on load capacity factor (LCF) under the framework of load capacity curve (LCC) hypothesis for selected Asian countries during 1990-2020. In this regard, we use several preliminary sensitivity tests to check the features and reliability of the dataset. Similarly, we use panel quantile regression for investigating long-run relationships. The factual results affirm the existence of the LCC hypothesis in selected Asian countries. Our findings also show that geopolitical risk reduces environmental quality whereas financial development and REC increase environmental quality. Drawing from the empirical findings, this study suggests a holistic policy approach for achieving the targets of SDG 13 (climate change).

Do institutions contribute to environmental sustainability? A global analysis using the dynamic spatial Durbin and threshold models

There has been a recent surge in attention to the potential involvement of institutions in enhancing environmental quality. This research contributes to the ongoing debate by analyzing the spillover and nonlinear effects of institutions on the load capacity factor (LCF) in a sample of 100 countries between 2000 and 2019. The spillover effects are analyzed using the dynamic spatial Durbin model (DSDM), while the dynamic threshold model is implemented to estimate the nonlinear impacts of institutions. The Moran's I and Geary's C tests reveal a positive spatial autocorrelation for the LCF. The DSDM indicates the existence of positive direct and indirect (spillover) effects of political stability, control of corruption, and the rule of law on the LCF. Moreover, control of corruption has the highest positive influence on the environment. When conducting the threshold analysis, the locally weighted scatterplot smoothing curve indicates a nonlinear relationship between institutions and LCF, while the threshold test suggests a single threshold and two regimes. The dynamic panel threshold model reveals that government effectiveness and the rule of law positively affect the environment under both regimes. On the contrary, the positive effects of control of corruption, regulatory quality, and political stability are only observed under the upper regime. Furthermore, control of corruption has the highest positive environmental impact, albeit it needs more time to be achieved. The research emphasizes the importance of international collaboration and the design of both short- and long-term strategies to enhance institutional quality and, consequently, safeguard the environment.

Assessing the impact of incentive coordination effect on the equilibrium of agricultural water usage by China's South-to-North Water Diversion Middle Route Project

In recent years, the sustainable development of agricultural water resources has received much attention. The mismatch between agricultural water distribution patterns, land resources, and socioeconomics threatens food production, especially in vast water-scarce plains. Therefore, monitoring agricultural water spatial equilibrium (AWRSE) is necessary. Based on equilibrium theory and information entropy, in this study, the AWRSE evaluation model is constructed from three aspects: agricultural water resources, land resources, and socioeconomics. In addition, the relationship between social factors with cropping pattern as the primary explanatory variable and AWRSE was examined in conjunction with the extended STIRPAT model and applied to the water-receiving area of the Middle Route of South-to-North Water Diversion Project (MR-SNWDP). The results show that compared with the pre-diversion period, the AWRSE of 75% of the water-receiving cities has been significantly improved by the MR-SNWTP water supply. The MK test z value of the overall regional AWRSE has changed from - 0.328 to - 2.65, and the AWRSE development has shifted from not significantly better to significantly better. The cropping pattern shows a positive response to this development, and this effect can be mitigated in the late stage of water transfer; when the proportion of food crop cultivation increases by 1%, the sub-regional AWRSE value will increase by 0.347%. The evaluation model demonstrates a broad range of inclusiveness and application potential; it provides novel insights for examining agroecological, social, and economic stability.

Evaluating urban environmental quality using multi criteria decision making

In the urban environment, the quality refers to the capacity that provides and fulfills the material and spiritual needs of inhabitants. In order to improve the quality of urban life and standard of living for their citizens, planners and managers strive to raise Urban Environmental Quality. The objective of this study is to evaluate the quality of urban environment through the spatial analysis of a multi-criteria decision making (MCDM) method utilizing CRITIC. This research is conducted in district 4 and district 2 of the Tabriz Metropolis Municipality. In order to determine the quality of an urban environment, air pollution, vegetation coverage, land surface temperature, production of waste, population density, noise pollution, health care per capita, green spaces per capita, recreational spaces per capita, and distance from fault lines are used. After evaluating and producing environmental quality maps in two separate districts, 10 indicators were tested for significance and a comparative evaluation of two districts was conducted in order to determine which district was in better condition based on a statistical analysis of the T-test results. In accordance with the CRITIC method, there are significant differences between averages of waste production, population density, noise pollution, distance from fault lines, Land Surface Temperature, Normalized difference vegetation index, and distance from fault lines between the two districts. It appears that recreational space, air pollution, health care per capita, and green space per capita are not meaningfully different on averages. The preparation of environmental quality maps reveals the importance of meaningful indicators at the neighborhood level in two urban districts. In both districts by strengthening the continuity of the landscape through the development of ecological corridors and an increase in per capita can contribute to the improvement of the quality of the urban environment.

Long run renewable energy productivity, carbon capture patents and air quality in Taiwan

This study investigates the connection between nonrenewable energy productivity, renewable energy productivity, and air quality degradation in Taiwan from 2002 to 2019. We specifically emphasize the novel contribution of analyzing the productivity of renewable energy consumption. Robust estimation models, namely Nonlinear Autoregressive Distributed Lag (NARDL) and Robust Standard Estimation, are employed for comprehensive analyses. Our findings reveal a strong correlation between nonrenewable energy productivity and increased air pollutants, highlighting the significant impact of fossil fuels on air quality deterioration. Although renewable energy productivity demonstrates a negative association with air degradation, its effect is not statistically significant. This can be attributed to Taiwan's continued reliance on non-renewable energy sources within the overall energy mix. Hence, reducing dependence on fossil fuels is crucial for improving air quality. Importantly, the identified relationships have long-term implications, underscoring the necessity of persistent policy measures that promote renewable energy transition and emissions reduction over time. Our research emphasizes the urgency of addressing fossil fuel dependency to mitigate air pollution and highlights the potential benefits of enhancing renewable energy efficiency to achieve cleaner and healthier environments.

The responsiveness of renewable energy production to geopolitical risks, oil market instability and economic policy uncertainty: Evidence from United States

This paper aims to investigate the responsiveness of renewable energy production (REP) to fluctuations in geopolitical risks, oil prices and economic policy uncertainty (EPU). It applies a cross-quantilogram framework to examine monthly data of the US economy for the period of 1986-2022. The findings illustrate the asymmetric effect of historical geopolitical risk (GPRH) on REP under long memory. The findings also hold after different subcategories of GPRH, including geopolitical threats and geopolitical acts, are considered. A positive shock in GPRH has the most decisive positive impact on REP when the policies are driven by both energy security and environmental commitments. A positive shock in GPRH can negatively impact REP when policies are driven by energy security causes only. EPU exerts strong negative effects on REP in bearish and bullish states of the market under medium and long memory across different measures of EPU. Dynamic connectedness analysis applying TVP-VAR method between pairwise variables indicates that net REP is a volatility receiver to the changes in GPRH, its subcomponents, oil prices and different measures of EPU.

How does Information and Communication Technology (ICT) industry agglomeration affect carbon emission efficiency? Evidence from China

The Information and Communication Technology (ICT) industry takes on critical significance in promoting economic development and reducing carbon emissions. From the agglomeration perspective, how the ICT industry agglomeration affects carbon emission efficiency (CEE) in 30 provinces in China from 2006 to 2020 is innovatively investigated. We measured CEE using a dynamic directional distance function-based DEA model. Then, based on the research hypotheses, the specific impact and transmission mechanism of ICT industrial agglomeration on CEE are revealed using a spatial Dubin model and a threshold panel model. The results show that: (1) the ICT industry agglomeration exerts a remarkable inverted "U-shaped" effect on CEE. This non-linear effect is significant in the eastern and central regions, but not in the western region. (2) ICT industry agglomeration can affect CEE in neighboring regions. The spatial spillover effect shows an inverted "U-shaped" in the central region, positive in the western region, and insignificant in the eastern region. (3) when green technology innovation exceeds the threshold value (4.948), ICT industry agglomeration positively affects CEE, and when energy structure exceeds the threshold value (0.389), their marginal effects are significantly negative. The threshold effect also shows regional heterogeneity. This research proposes policy recommendations focusing on accelerating the ICT industry transformation, leveraging the spillover and technological advantages of agglomeration, and enhancing regional cooperation.

Assessing the environmental impacts of renewable energy sources: A case study on air pollution and carbon emissions in China

This study investigates the impact of renewable and non-renewable energy sources on carbon emissions in the context of China's 14th Five-Year Plan (2021-2025). The plan emphasises a "Dual-control" strategy of simultaneously setting energy consumption limits and reducing energy intensity for GDP (gross domestic product) in order to meet the targets of the five-year plan. Using a comprehensive dataset of Chinese energy and macroeconomic information spanning from 1990 to 2022, we conduct a Granger causality analysis to explore the relationship between energy sources and the level of air pollution. Our findings reveal a unidirectional link, wherein renewable energy contributes to a reduction in air pollution, while non-renewable energy sources lead to an increase. Despite the government's investment in renewable energy, our results show that China's economy remains heavily reliant on traditional energy sources (e.g., fossil fuels). This research is the first systematic examination of the interplay between energy usage and carbon emissions in the Chinese context. Our findings provide valuable insights for policy and market strategies aimed at promoting carbon neutrality and driving technological advancements in both government and industries.

How to lead on carbon neutrality through sustainable development: A perspective on renewable energy, Information and Communication Technology (ICT), and logistics networks

In the face of intensifying climate change-induced environmental problems, understanding the causal relationship between carbon dioxide (CO2) emissions and socioeconomic factors is crucial for achieving sustainable development. This study investigates how the causal relationships between renewable energy, information and communication technology (ICT), logistics networks, economic growth, industrialization, and energy intensity impact sustainable development using a panel dataset drawn from 104 countries and covering 2006 to 2019. Methodologically, panel unit root, panel co-integration, and Granger causality tests are employed as robust econometric techniques. The results of the panel unit root and co-integration tests confirm the stationarity of the variables and reveal significant long-term relationships among them throughout the empirical analysis period. Notably, the panel FMOLS and DOLS estimates indicate a positive effect of RE and ICT on reducing CO2 emissions, whereas GDP and energy intensity have a negative impact on CO2 emissions reduction. Moreover, the pairwise Granger causality test findings indicate bidirectional causal relationships between RE and CO2, IND and CO2, ICT and RE, IND and RE, GDP and ICT, as well as IND and ICT. The study recommends providing policy support, including for technological development and innovation, towards establishing a system that fosters sustainable development.

Democracy, green energy, trade, and environmental progress in South Asia: Advanced quantile regression perspective

Unquestionably, the industrial revolution of the twenty-first century contributes to global warming. Excessive amounts of carbon emissions into the atmosphere are responsible for global warming. Therefore, this research aims to assess the impact of GDP, green energy consumption, population, trade openness, and democracy on CO2 emissions in four selected South Asian countries from 1990 to 2019. This research also attempts to evaluate the EKC hypothesis in terms of economic growth (GDP2). The unit root of panel data and cointegration tests are executed in this study as a prelude to the regression analysis. Quantile regression for panel data, which (Powell, 2016) devised to deal with the fixed effect problem, is used in this study, and (Powell, 2016) empirical findings are the main focus. The estimated coefficient of GDP is positively significant, demonstrating that economic activity increases the burning of fossil fuels and upsurges atmospheric CO2 emissions. After attaining economic development, the reversed U-shaped EKC theory is valid for four selected South Asian countries. Economic development encourages these countries to use green technology, which helps mitigate CO2 emissions. The research, however, reveals that green energy is to blame for CO2 emissions. Burning biomass releases carbon dioxide that negatively impacts the quality of the environment. The study confirms that human activities are the leading contributor to environmental deterioration. Population growth has a worsening effect on the environment. The association between population and CO2 emissions is positively significant. The estimated coefficient of trade openness is positive, which increases CO2 emissions significantly. The estimated coefficient of democracy is quite negative. Therefore, this study suggests prioritizing democracy to reduce CO2 emissions. Citizens who live in democracies are better informed, more organized, and able to protest, all of which contribute to increased government responsiveness to environmental preservation. The results of the Wald test support the differential effects at various quantiles. The Dumitrescu-Hurlin (2012) panel causality tests are also used in this analysis to check causality between variables. Based on the findings, this research makes many policy suggestions for lowering carbon emissions.

Does environmental quality react asymmetrically to unemployment and inflation rates? African OPEC countries' perspective

Environmental degradation, inflation, and unemployment are unquestionably among the current global issues. However, there has not been an in-depth investigation of how unemployment and inflation rates affect environmental quality, particularly when considering the asymmetric scenario in oil-producing countries. This gap in the literature motivated this study to investigate how the environment (proxied by CO2 emissions) reacts to asymmetric shocks in inflation and unemployment rates using the panel NARDL model methodology. This study also examines whether the environmental Phillips curve (EPC) hypothesis holds true in the context of African OPEC countries over the period 1990 to 2019. The study presents three interesting findings. First, CO2 emissions are adversely associated with unemployment and inflation rates, meaning that protecting a healthy environment would have to come at the expense of two undesirable outcomes: losing employment and a decline in purchasing power. Second, the asymmetry analysis demonstrates that both negative unemployment and positive inflation shocks have a larger effect on CO2 emissions than the opposite scenario. Finally, long-term evidence exists to support the presence of the EPC in these countries.

Energy and air? The impact of energy efficiency improvement on air quality in China

The global economic growth is hindered by resources shortage, energy demand, air pollution and climate. Energy efficiency can reduce some pollutants while potentially increase others. This study refers to sulfur dioxide (SO2), nitrogen oxides (NOx), and dust and smoke (DS) as primary pollutants to distinguish it from secondary ones. The influence of energy efficiency, socioeconomic, and natural climatic factors on air quality is analyzed under the theory of STIRPAT. It is highly coupled between energy efficiency and the spatial distribution of air quality. Increased energy efficiency can improve air quality by reducing SO2 and NOx, but the impact on DS is insignificant. Air pollutants decrease by about 0.531% for every 1% increase in temperature and 0.105% for every 1% increase in precipitation. Consumption will reduce air pollution, and there is an inverted U-shaped relationship between population density, economic scale, urbanization, technology innovation, and air pollution. It is worth mentioning that this work adds temperature and precipitation to the STIRPAT as natural climatic factors, analyzing the impact of energy efficiency on air pollution under the two-factor restrictions of socioeconomic and natural climatic factors. Finally, management suggestions are made to improve air quality.

Do economic development and tourism heterogeneously influence ecological sustainability? Implications for sustainable development

While economic development-driven anthropogenic emissions pose challenges to ecological sustainability, the international travel and tourism sector has appeared as a hot contestant to bring sustainability to the ecological systems across varying development levels. This work investigates the diversified effects of the international travel and tourism sector and economic development on ecological deterioration, in the presence of urban agglomeration and energy use efficiency, across the development levels of China's 30 provincial units from 2002 to 2019. It contributes in two ways. (i) The stochastic estimation of environmental impacts by regression on population, affluence, and technology (STIRPAT) is modified to integrate the variables like international travel and tourism sector, urban agglomeration, and energy use efficiency. (ii) We measured an international travel and tourism sector index (ITTI) and made use of a continuously updated bias correction strategy (CUBCS) and a continuously updated fully modified strategy (CUFMS) for the long-term estimations. Besides, we used the bootstrapping-based causality technique for determining causality directions. The core results are as follows: Firstly, ITTI and economic development produced an inverse U-type association with ecological deterioration for the aggregate panels. Secondly, provinces exhibited a diverse range of links in that ITTI mitigated (boosted) the ecological deterioration in eleven (fourteen) provinces presenting diversified shapes of linkages. Economic development established the environmental Kuznets curve (EKC) theory with ecological deterioration in merely four provinces; however, the non-EKC theory is verified in twenty-four divisions. Thirdly, in China's east zone (high development scale), the ITTI revealed the ecological deterioration reduction (promotion) impact in eight (two) provinces. China's central zone (moderate development scale) exhibited ecological deterioration promotion in half of the provinces, and the other half showed a reduction impact. In China's west zone (low development scale), it promoted ecological deterioration in eight provinces. Economic development promoted (reduced) ecological deterioration in a single (nine) province(s). In China's central zone, it boosted (mitigated) the ecological deterioration in five (three) provinces. In China's west zone, it promoted (reduced) ecological deterioration in eight (two) provinces. Fourthly, urban agglomeration and energy use efficiency deteriorated and improved the environmental quality in aggregated panels, respectively; however, a diverse range of effects are observed for provinces. Finally, a unilateral bootstrap causality, from ITTI (economic development) to ecological deterioration, is revealed in twenty-four (fifteen) provinces. A bilateral causality is established in a single (thirteen) province(s). Based on empirical findings, policies are suggested.

Exploring influential factors of CO2 emissions in China's cities using machine learning techniques

The precise and exhaustive discernment of factors influencing CO₂ emissions underpins the advancement toward sustainable, low-carbon development. Although numerous studies have probed the correlation between predetermined proxy variables and carbon emissions, methodological constraints have often led to an inability to effectively discern carbon emission determinants among numerous potential variables or unravel complex, non-linear relationships, and interaction effects. To redress these research gaps, this research utilized machine learning models to correlate urban CO₂ emissions with socioeconomic indicators. The model outputs were then visualized and interpreted using explainable methods. The findings indicated that the model successfully identified a comprehensive array of dominant influences on urban CO₂ emissions, principally associated with local fiscal policies, land use, energy consumption, industrial development, and urban transportation. The findings further revealed a complex non-linear association between these factors and urban CO₂ emissions; however, the majority of these variables displayed a prevalent propensity to intensify carbon emissions in correspondence with an increase in sample value. Additionally, these factors exhibited a complex interactive influence on urban CO₂ emissions, with distinct pairings producing a suppressive effect exclusively at specific combination of sample values. Consequently, this research posited that a robust correlation between urban socioeconomic development and CO₂ emissions in China remains to be established. Given the varied impacts of these influencing factors across different cities, a differentiated approach to development should be adopted when charting low-carbon trajectories.

Nexus between stock markets, economic strength, R&D and environmental deterioration: new evidence from EU-27 using PNARDL approach

This research investigates the impact of stock market indices, economic strength, and research and development expenditures on environmental deterioration in the EU-27 countries for the period 2000-2020. This study utilized linear and non-linear panel ARDL to estimate the short- and long-run effect. According to the results, the stock market indices have negative effect on environmental deterioration in the symmetric form. However, the asymmetric evidence shows that in the long run the positive shocks of stock market indices contribute positively to the environmental deterioration and negative shocks decrease the environmental deterioration. This effect is reversed in the short run. Linear effect of economic strength on environmental deterioration is positive. For non-linear effect, the long-run shocks show no difference. However, the negative shock of economic strength in the short run causes an increase in the environmental deterioration. Symmetric evidence for research and development increases environmental deterioration. However, asymmetric results show weak evidence. The study has policy implications in context of achieving sustainable development goals.

Spatio-temporal variations, spatial spillover, and driving factors of carbon emission efficiency in RCEP members under the background of carbon neutrality

Improving carbon emission efficiency (CEE) has emerged as a critical way for Regional Comprehensive Economic Partnership (RCEP) members to promote carbon reduction in the context of climate change mitigation and carbon neutrality. The super-efficiency slacks-based measure (SBM) model, which considers non-desired outputs, is adopted to comprehensively assess the current state and trend of CEE in 15 RCEP countries from a spatio-temporal dynamic perspective, and the global Malmquist-Luenberger (GML) index is coupled to quantify the spatial and temporal differences and dynamic changes. Following that, taking into account the spatial characteristics of CEE, the extended STIRPAT model and the spatial Durbin model are combined to further investigate the primary influencing factors of CEE. It is found that (1) the CEE of RCEP members is generally poor and unevenly distributed in temporal and spatial dimensions, with significant room for improvement and an overall positive spatial autocorrelation; (2) CEE varies considerably among RCEP members, with developed countries far outstripping developing countries in terms of both the current status and trend of CEE; (3) on a dynamic level, the GML index exhibits W-shaped fluctuations, with technological progress acting as the dominant force; and (4) in terms of spillover effects, affluence and economic agglomeration inhibit CEE enhancement, whereas technology level and investment capacity facilitate it. The findings will be useful in developing carbon-neutral plans for various countries as well as coordinated sustainable development for RCEP regions.

The role of economic growth, information technologies, and globalization in achieving environmental quality: a novel framework for selected Asian countries

This study examines the impact of information and communication technologies (ICT), GDP growth, population, and globalization on the environmental quality of 31 Asian economies (i.e., categorized as lower middle-income, upper middle-income, and high-income groups Asian economies). This analysis employed the time series data from 1990 to 2018. The robust second-generation econometric technologies are used in this analysis. This study applied the Environmental Kuznets curve (EKC) premises under the extended "STIRPAT model" to add population and GDP (per capita) and information technologies (ICTs) by employing ecological footprint. To estimate, the estimators of this study used the CS-ARDL estimates, and for robustness check, this study used the augmented mean group (AMG) test. The co-integration test found the long-run association between ecological footprint and its main determinants. The results of CS-ARDL have confirmed the imperative role of information technologies in mitigating the ecological footprint in the higher, upper-middle, and lower-middle-income economies of Asian economies. The statistical findings of this study are robust to diagnostic tests and alternative estimation proxies and techniques. Moreover, policymakers need to identify the direction of the information technology-ecological footprint nexus through cooperation in combating climate change with financial assistance in the ICT sector.

Does globalization and energy usage influence carbon emissions in South Asia? An empirical revisit of the debate

The 2030 United Nations Sustainable Development Goal (SDG) 13 agenda hinges on attaining a sustainable environment with the need to "take urgent action to combat climate change and its impacts". Hence, this study empirically revisits the debate on the effect of nonrenewable energy and globalization on carbon emissions within the framework of the Kuznets hypothesis using an unbalanced panel data from seven South Asian countries (Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) covering 1980-2019. The variables of interest are carbon emissions measured in metric tons per capita, energy use measured as kg of oil equivalent per capita, and globalization index. To address five main objectives, we deploy four techniques: panel-corrected standard errors (PCSE), feasible generalized least squares (FGLS), quantile regression (QR), and fully modified ordinary least squares (FMOLS). For the most part, the findings reveal that the (1) inverted U-shaped energy-Kuznets curve holds; (2) U-shaped globalization-Kuznets curve is evident; (3) inverted U-shaped turning points for nonrenewable energy are 496.03 and 640.84, while for globalization are 38.83 and 39.04, respectively; (4) globalization-emission relationship indicates a U-shaped relationship at the median and 75th quantile; and (5) inverted U-shaped energy-Kuznets holds in Pakistan but a U-shaped nexus prevails in Nepal and Sri Lanka; inverted U-shaped globalization-Kuznets holds in Bangladesh and Sri Lanka, but U-shaped nexus is evident in Bhutan, Maldives, and Nepal. Deductively, our results show that South Asia countries (at early stage of development) are faced with the hazardous substance that deteriorates human health. Moreover, the non-linear square term of the nonrenewable energy-emissions relationship is negative, which validates the inverted U-shaped EKC theory. Overall, the effect of energy and globalization on carbon emissions is opposite while the consistency at the 75th quantile result indicates that countries with intense globalization are prone to environmental degradation.

Urbanization and CO2 emissions in Belt and Road Initiative economies: analyzing the mitigating effect of human capital in Asian countries

Balanced and sustainable development is one of the Belt and Road Initiative (BRI) objectives. Therefore, considering the role of urbanization and human capital as critical elements for sustainable development, we analyzed the moderating effect of human capital on the relationship between urbanization and CO₂ emissions in Asian member countries of the Belt and Road Initiative. In doing so, we used the STIRPAT framework and the environmental Kuznets curve (EKC) hypothesis. We also employed the pooled OLS estimator with the Driscoll-Kraay's robust standard errors, the feasible generalized least squares (FGLS), and the two-stage least square (2SLS) estimators in the case of 30 BRI countries for the period 1980-2019. The relationship between urbanization, human capital, and carbon dioxide emissions were examined first by showing a positive correlation between urbanization and carbon dioxide emissions. Secondly, we showed that human capital mitigated the positive effect of urbanization on CO₂ emissions. Next, we demonstrated that human capital had an inverted U-shaped effect on CO₂ emissions. Specifically, a 1% increase in urbanization rose CO₂ emissions by 0.756%, 0.943%, and 0.592% following the Driscoll-Kraay's OLS, the FGLS, and the 2SLS estimators, respectively. A 1% increase in the combination of human capital and urbanization reduced CO₂ by 0.751%, 0.834%, and 0.682%, respectively. Finally, a 1% increase in the square of human capital decreased CO₂ emissions by 1.061%, 1.045%, and 0.878%, respectively. Accordingly, we provide policy implications on the conditional influence of human capital in the urbanization-CO₂ emission nexus for sustainable development in these countries.

A novel EKC perspective: do agricultural production, energy transition, and urban agglomeration achieve ecological sustainability?

We aim to analyze the existence of a novel agricultural production-augmented environmental Kuznets curve (EKC-AP) theory for energy transition, urban agglomeration, and financial depth. To conduct this research, we use a global panel of selected 54 countries belonging to low, medium, and high levels of economic development from 1971 to 2017. Since our data are distributed into three development levels, it is highly likely to face cross-sectional dependence across the countries within and between the development levels, which may provide biased empirical results. To outpace such possibility, we employ advanced econometric strategies, which are robust to cross-sectional dependence and slope heterogeneity issues. We found that agricultural production, energy transition, urban agglomeration, financial depth, and ecological degradation experience a long-term cointegrating equilibrium association. We also confirm that exists an EKC-AP linkage of agricultural production with ecological degradation in highly developed economies, while those at the low and medium levels of development reveal a positive exponential and monotonic impact, respectively, of agricultural production on ecological degradation. The energy transition is found to promote ecological sustainability in developed countries through technique impact, while it deteriorates the ecological quality in countries at the medium development level. Moreover, urban agglomeration adversely impacts the ecological quality in the economies at low and medium development levels, whereas it improves the ecological sustainability in developed economies. Besides, financial depth proves harmful to ecological sustainability, with less subtle effects in developed economies. Based on our findings, for countries at low and medium levels of development, we propose advancing farming techniques using ecologically friendly technologies, promoting green energy transition, expanding the share of the services sector, and providing green financial systems to support green investment projects to achieve the Sustainable Development agenda of the United Nations.

Causal complexity of environmental pollution in China: a province-level fuzzy-set qualitative comparative analysis

Environmental problems are endowed with the causal complexity of multiple factors. Traditional quantitative research on the influencing mechanism of environmental pollution has tended to focus on the marginal effects of specific influencing factors but generally neglected the multiple interaction effects between factors (especially three or more). Based on the panel data of 30 Chinese provinces between 2011 and 2020, this study employs fuzzy set qualitative comparative analysis (fsQCA) - which can provide a fine-grained insight into the causal complexity of environmental issues - to shed light on the influencing mechanism of environmental pollution. The results show that there are several different configurations of pollution drivers which lead to high pollution or low pollution in provinces, confirming the multiple causality, causal asymmetry, and equifinality of environmental pollution. Furthermore, the combination effect of advanced industrial structure, small population size, and technological advance is significant in achieving a state of green environment compared to environmental regulation factors. In addition, spatiotemporal analysis of the configurations indicates that strong path dependencies and spatial agglomeration exist in current local environmental governance patterns. Finally, according to our findings, targeted policy recommendations are provided.

Understanding the Impact of Environmentally Specific Servant Leadership on Employees' Pro-Environmental Behaviors in the Workplace: Based on the Proactive Motivation Model

The increasingly severe environmental situation has brought challenges to the world, and organizations are aware of the importance of environmental management and are committed to changing individuals' environmental behavior patterns. Based on the proactive motivation model, this study constructs a moderated multiple mediation model to explore the impact mechanism and boundary conditions between environmentally specific servant leadership (ESSL) and employees' workplace pro-environmental behaviors (WPB). This study examines 440 Chinese industrial sector employees, and the linear regression method test results show that: (1) ESSL significantly promotes employees' WPB. (2) Green self-efficacy (GSE), green organizational identity (GOI), and environmental passion (EP) act as multiple mediators between ESSL and employees' WPB. (3) Green shared vision (GSV) positively moderates the relationship between ESSL and employees' WPB. This study provides a new theoretical perspective on how ESSL affects employees' WPB, which is analyzed from three aspects: "can do", "reason to", and "energized to". This new mechanism reveals that leaders should transform their leadership style to that of environmental service, and focus on enhancing the employees' GSE, GOI, and EP. Moreover, ESSL should make copious use of green strategy tools, such as GSV, to realize the above mechanism.

Factor market distortion, technological innovation, and environmental pollution

Factor market distortion is a critical factor that affects environmental pollution, and technological innovation is regarded as a new opportunity to alleviate environmental pollution. Based on panel data from 30 Chinese provinces from 2003 to 2019, this study constructs an intermediary effect model to test the influence mechanism of factor market distortion on regional environmental pollution and the intermediary effect of technological innovation, exploring these effects based on spatial differentiation characteristics. This study shows that factor market distortion protects industries with backward production capacity, high resource consumption, serious pollution, and low production efficiency from elimination; hinders the transformation and upgrading of the regional industrial structure; and forms a lock in the sloppy growth mode, which directly affects the improvement of regional environmental quality. This study reveals the influence of factor market distortions on environmental pollution. This provides empirical evidence for giving play to the decisive role of the market in resource allocation and promoting green technology innovation.

Cost-benefit allocation of collaborative carbon emissions reduction considering fairness concerns-A case study of the Yangtze River Delta, China

As the country with the highest carbon emissions, the main focus of China has become carbon reduction. At present, the governance of carbon reduction is mainly based on the division of administrative regions, which leads to the governance inefficiency and high costs because of spatial spillover and regional mobility of carbon emissions. The need for collaborative governance to promote carbon reduction performance has been recognized. However, because of differences in both costs and benefits between developed and less developed regions, a clear cost and benefit allocation mechanism must be established first. Fairness is very important when all members are to actively participate in collaborative carbon emission reduction efforts. In this paper, one of the regions renowned for collaborative governance-the Yangtze River Delta region-is used as example, and a cost-benefit allocation mechanism is constructed that incorporates members' fairness concerns. The carbon emission efficiency, carbon reduction efforts, and total carbon emission amount are compared under two scenarios: a cost-sharing scenario and a centralized decision-making scenario. The results indicate that, compared with the centralized decision-making scenario, the cost-sharing scenario achieved greater regional carbon reduction efforts, a higher carbon emission efficiency, and more total emissions. Furthermore, under the cost-sharing scenario, in less developed regions, fairness concerns increase carbon emission efficiency and total carbon emissions. The fairness concern in developed regions reduces the profit proportion, while the fairness concern in less developed region increases the profit proportion. The impact of fairness concern on carbon reduction is stronger in developed regions.

Assessing environmental concern and its association with carbon trade balances in N11 Do financial development and urban growth matter?

Expanding of complex global supply chains enhances the role of global trade in the deterioration of the environment by production redeployment across nations, which is tightly connected to emission transmission or the carbon trade balance. Although much earlier studies have assessed the link between emissions of carbon dioxide (CO₂) and their influenced variables in the past few years, no substantial attention is available in the literature review concerning the influence of carbon trade balance on the environment in N11 economies. Therefore, via economic progress, renewable/fossil energies consumption, financial development, and urbanization growth as control variables, the influence of the carbon trade balance on emissions of CO₂ in N11 countries is explored from 1990 to 2020. The Co-integration and causality relationships using Panel PMG ARDL and Granger causality techniques are investigated to reach our goal. All of the variables investigated degrade the environment in the long run, whereas renewables alleviate CO₂. As a result, carbon emission countries' regulators should step up their efforts to support green energy subsidies and carbon taxes, as well as, when supply chains outsource emission-intensive production units to partner nations, they should encourage positive externalities of innovative green technologies.

The impact of industrial robots application on air pollution in China: Mechanisms of energy use efficiency and green technological innovation

The battle against air pollution in China persists, and haze remains over cities. Whether industrial robots, as the core technology of intelligent manufacturing, can improve city air quality in the process of production has not been determined. Using the International Federation of Robotics data and Chinese city air pollution data (2013-2018), this study finds that industrial robots significantly reduce city air pollution levels (PM2.5, PM10, and SO2), which remains robust after addressing endogeneity. The mechanism of action lies in the synergistic benefits of industrial robots in reducing city air pollution levels by effectively improving energy use efficiency and promoting green technological innovation. Heterogeneity analysis suggests that industrial robots, as the incarnation of green technology, can be an effective alternative tool to green policies, such as low-carbon piloting, resource planning, and environmental regulation. This study empirically confirms that industrial robots are environment-friendly technologies that can provide new policy ideas to promote air pollution prevention and control in the industrialization process.

Causality analysis of CO2 emissions, foreign direct investment, gross domestic product, and energy consumption: empirical evidence from South Asian Association for Regional Cooperation (SAARC) countries

Over the period 1980-2016, this study looks into the causal relations between carbon dioxide (CO₂) emissions, energy consumption (EC), foreign direct investment (FDI), and gross domestic product (GDP) in five South Asian countries (Bangladesh, India, Nepal, Pakistan, and Sri Lanka). To achieve the research objectives, panel unit root tests, panel co-integration, autoregressive distributed lag model, and Granger causality tests are used. In the long run, GDP has a positive impact on CO₂ emissions, while squared GDP has a negative impact, confirming the framework of the environmental Kuznets curve (EKC) in Pakistan and Sri Lanka. However, in the short run along with these two countries, Bangladesh also confirms the EKC hypothesis. Among these five countries, Bangladesh and Nepal support the pollution haven hypothesis, but India, Pakistan, and Sri Lanka support the FDI halo hypothesis. The EC has a large positive impact on CO₂ emissions across five countries. In the long run, the Granger causality test confirms one-way causation from EC to CO₂ emissions and bidirectional causality of FDI and CO₂. These countries might encourage clean energy technology through FDI without jeopardizing GDP and environmental quality. The findings of the study provide a guideline for these countries to reduce CO₂ emissions, achieve a long-term green GDP, and combat global warming.

The assessment of environmental sustainability: The role of research and development in ASEAN countries

Considering the set targets of the Association of Southeast Asian Nations (ASEAN) to increase research and development (R&D) expenditures, this study probes the long-term and causal association between renewable energy (RE), nonrenewable energy (NRE), economic growth (GDP), and ecological footprints (EFs) in the context of the environmental Kuznets curve (EKC). Empirical evidence is based on the panel data throughout the period 1990-2016 for the selected six ASEAN economies. The Westerlund co-integration test confirms the long-run association between R&D, RE, NRE, GDP, and EF. The results of Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) confirm the presence of EKC and show that R&D expenditures lower EF significantly. A 1% increase in R&D and RE decreases EF by 0.01% and 0.27%, respectively. Moreover, a 1% increase in GDP and NRE increases EF by 5.52% and 0.17%, respectively. This means that investment in R&D will enhance air quality by lowering EF in estimated panel countries. Moreover, NRE consumption and GDP increase EF. The panel causality results confirm the bidirectional association between GDP, RE use, R&D expenditures, and EF. To achieve a desirable goal of a clean environment, R&D expenditures hold a strong position for ASEAN countries. This finding should encourage governments to involve public and private investments in R&D programs for energy efficiency. Integr Environ Assess Manag 2022;18:1313-1320. © 2021 SETAC.

Co-inventions, uncertainties and global food security

This paper examines the effects of international collaborative efforts on climate-friendly agricultural technologies on global food security. In particular, we use patent data on environmental technological innovations for OECD countries and global food prices from the period 1990 to 2016. Also, we investigate the impact of uncertainties in weather conditions in terms of rising global temperature created by climate change using data on global surface temperature from the Energy Information Administration and the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis of the National Aeronautics and Space Administration (NASA). We used both impulse response functions and variance error decomposition from a panel Vector Auto-Regressive (VAR) model to examine both the response of global food prices to shocks on the concerned variables and the decomposition of error variance in global food prices. First, our results show that international collaborative efforts on climate-friendly agricultural technologies reduce global food prices while increasing global surface temperature increases food prices. Regarding the variance decomposition of global food prices, results show that surface temperature followed by international collaborations in climate-friendly innovations and other environment-related technologies are the main drivers of forecast error variance in global food prices. The food price variance share associated with greenhouse gas emissions is less when compared to that of technological innovations.

Transition to renewable energy and environmental technologies: The role of economic policy uncertainty in top five polluted economies

The United Nations' "Sustainable Development Goals" (SDGs) express attention to climate action. Even though a considerable number of papers have targeted this issue, the literature on the top five, "China, India, Japan, Russia, and the United States" economies is uncommon. Therefore, this paper is targeted to examine the influence of renewable energy (RE), environmental technologies (ETs), and economic policy uncertainty (EPU) on carbon emissions. By using the most recent data available from 1992 to 2020, results are estimated with robust econometric techniques, i. e. "cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and augmented mean group (AMG)". Findings reflect the harmful role of EPU. However, RE and ETs have a supportive role in the transition towards a sustainable environment. The findings are also strong in terms of policy implications for the top five polluters.

Do economic policy uncertainty and environment-related technologies help in limiting ecological footprint?

Economic policies related to energy and the environment are found uncertain in developing economies. Renewable energy sources are gradually increasing in energy structure (ES) with the adoption of environment-related technologies (ERT). However, least attention is paid to investigating the nexus of economic policy uncertainty (EPU), ERT, ES, and ecological footprint (EF). Therefore, this study is an effort to examine the EPU, ERT, ES, and interaction of EPU and ERT on EF for BRICS economies under the umbrella of the STIRPAT model. By using the data from 1992 to 2020, findings are estimated through "cross-sectional dependence (CD test); CIPS and CADF unit root test; Westerlund's co-integration; and CS-ARDL, AMG, and CCEMG." Findings unveiled the negative role of EPU on EF. Furthermore, the role of RE and ERT is positive and substantial in decreasing the environmental degradation in BRICS. Therefore, the BRICS economies are suggested to be consistent on economic policies to catch the positive impact of ERT. Findings are robust to the policy implications.

Sustainability challenges in Peru: embossing the role of economic integration and financial development-application of novel dynamic ARDL simulation

Inspired by the commitment to address the environmental challenges in Peru under the UN Sustainable Development Goals 13 (Climate Action) and its implications by 2030, therefore, this study investigates the combined role of economic globalization, financial development, and fossil fuel intensity consumption using a combination of dynamic ARDL counterfactual simulation and kernel-based regularized least squares within the context of Stochastic Impact by Regression on Population, Affluence and Technology over the period 1971-2017. This research output confirms the inverted-U-shaped hypothesis between economic growth and carbon emissions. In contrast, the kernel-based regularized least squares confirms the scale effect and fossil curse hypothesis in the relationship between financial development and carbon emission, and heterogeneous effects in economic integration and carbon emission. We further document that financial development, fossil fuel consumption, urban population, affluence (economic growth), and government final consumption expenditure spur environmental pollution while economic integration reduces it. This study recommends Peru to instill environmental justice through regulations and policies restricting inflows into an exploration of environmentally unsustainable projects within Peruvian metropolises or in the Peruvian Amazon. There is a need to revisit finance and investment laws and increase investment in low-carbon infrastructure within Peru.

Determinants of ecological footprint in OCED countries: do environmental-related technologies reduce environmental degradation?

The world is in a clash between the perspectives of economic expansion and sustainable environment. The high pace of technological progress opens space for fostering economic growth but at the same time, it creates a big dilemma for humans in protecting the environmental quality. The environmentally specific technologies are expected to help human beings to achieve dual objectives of economic prosperity and environmental sustainability. Despite its importance, attention to the role of environmental-related technologies in reducing environmental degradation is limited. This paper, therefore, intends to discover the impact of environmental-related technologies on the ecological footprint for 20 OECD from 1990 to 2015. The results endorse a long-run relationship between ecological footprint and green technologies, renewable energy, international trade, energy intensity, and real income. Environmental-related technologies and renewable energy consumption are found to be impetuous to sustainable development. The study provides relevant implications for policymakers to support the development and adoption of green technologies.

Dynamic link between bilateral FDI, the quality of environment and institutions: evidence from G20 countries

The sustenance of a clean, natural, and relatively less tampered environment is one of the most important apprehensions of contemporary households, firms, and governments in the globalized world. Both developing and developed countries rely heavily on foreign direct investments (FDI) and institutional arrangements for economic prosperity and have feedback repercussions about environmental quality. Thus, the current paper attempts to explore such a triplex integrated linkage among bilateral FDI, institutional quality, and environmental quality proxied by CO₂ emissions intensity on each other for 19 selected G20 countries during 2009-2017. The empirical estimation of this paper takes into account three equations that jointly address the endogeneity problem by employing both static (such as seemingly unrelated regression and three-stage least square) and dynamic simultaneous econometric techniques (such as the system generalized method of moments) with a panel dataset considering host and source countries with 342-panel pairs for the selected sample time. The empirical results confirm that bilateral FDI reduces CO₂ emission intensity and strengthens the institutional quality of G20. It also supports the idea that institutional quality has a favorable and considerable impact on bilateral FDI. This paper confirms a positive and considerable feedback between environmental and institutional quality. Further, this study establishes a triplex relationship between these three factors. This study argues that governments should use incentives like tax cuts and additional subsidies to promote greener FDI in G20 nations. This is because it facilitates the employment of more modern technology and clean energy-efficient technologies to minimize emissions and spur economic growth.

Energy intensity determinants based on structure-oriented cointegration by embedding a knowledge box in a time series model: evidence from Iran

Energy intensity reduction is an exigent issue for Iran, where energy consumption is so high. Therefore, finding effective policies to reduce energy intensity is essential. With this in mind, the impact of financial development, government investment, oil revenues, and trade openness on energy intensity is assessed in this study. We combined structural vector error correction model (SVECM) and directed acyclic graphs (DAG) technique to examine the relationships between study variables. The results of DAG prove that financial development, government investment, oil revenues, and trade openness influence the intensity of energy. Besides, the significant and long-run relationships among variables allowed us to apply SVECM. Impulse response functions and variance decomposition analysis indicate that government investment, oil revenues, and trade openness are negatively associated with the intensity of energy. Also, financial development positively influences energy intensity. Meanwhile, the impact of government investment is more significant than oil revenues, trade openness, and financial development impacts. So, government investment is the most effective policy regarding optimizing the consumption of energy and reducing energy intensity. We also advise policymakers to use oil revenues to increase government investment, enhance trade openness, and tax the private sector to improve the level of energy intensity.

Ensemble system for short term carbon dioxide emissions forecasting based on multi-objective tangent search algorithm

Carbon emissions play a crucial role in inducing global warming and climate change. Accurate and stable carbon emissions forecasting is beneficial for formulating emissions reduction schemes and achieving carbon neutrality as early as possible. Although previous studies have concentrated on employing one or several methods for carbon emissions forecasting, the improvement in forecasting performance is limited because they ignore the importance of objectively selecting the models and the necessity of interval forecasting. In this paper, a novel ensemble prediction system, composed of data decomposition, model selection, phase space reconstruction, ensemble point prediction, and interval prediction, is proposed to conduct both point and interval predictions, which has been proven to be effective in prompting carbon emissions forecasting accuracy and stability. According to the empirical results, the mean MAPE results of our proposed forecasting strategy in point prediction are 1.1102% (in Dataset A) and 1.1382% (in Dataset B), and the mean CWC values in the interval forecasting are 0.3512 and 0.1572, respectively. Thus, the proposed forecasting system improves the forecasting performance relative to other models considerably, which can provide meaningful references for policymakers.

Nexus between fiscal imbalances, green fiscal spending, and green economic growth: empirical findings from E-7 economies

The green economy is viewed as a cost-effective means of achieving sustainability around the globe, and a recent study inferred the nexus between the fiscal imbalances and green economic growth based on E-7 economies data. This paper attempts to answer how green fiscal spending ensures green economic growth and stabilizes fiscal imbalances in E-7 economies. The study findings highlighted the mechanism and viability of green fiscal spending for fiscal imbalances and green economic growth. More specifically, results showed that green fiscal spending extends green economic growth in Brazil with 30%, in China with 44%, in India with 11.8%, in Indonesia with 34%, Russia with 29.7%, and Turkey with 22.4%, respectively. Based on the findings, the following are our recommendations: (i) local governments should rebalance their fiscal budgets and invest more on public goods to assess local sustainable development, and (ii) several development initiatives specific to the local level should be employed to maximize fiscal spending.

Environmental quality and the role of economic policy uncertainty, economic complexity, renewable energy, and energy intensity: the case of G7 countries

This study explores the environmental impacts of economic policy uncertainty, economic complexity, renewable energy, and energy intensity on the countries in the Group of Seven (G7) countries. To this end, the study employs fully modified ordinary least squares and a fixed effects model with Driscoll and Kraay, Rev Econ Stat 80:549-560, (1998) robust standard errors and a panel dataset from 1997 to 2015. The findings demonstrate a long-term relationship between the variables of interest and carbon dioxide emissions and the ecological footprint. Specifically, high energy intensity increases environmental pollution while high economic policy uncertainty and renewable energy reduces environmental degradation. The environmental Kuznet curve of economic complexity and environmental quality holds for G7 countries. Moreover, economic policy uncertainty strongly moderates the environmental effect of renewable energy, economic complexity, and energy intensity. Specifically, although economic policy uncertainty amplifies the beneficial environmental effects of renewable energy and economic complexity, it enlarges the harmful effect of energy intensity on environmental quality. These empirical outcomes allow us to draw useful implications for policy makers to mitigate the environmental degradation.

Population dynamics and environmental quality in Africa

The nexus of population dynamics and environmental degradation has been discussed widely in the extant literature. Most related studies have utilized carbon emission as a proxy of environmental quality. However, carbon emission does not capture the multidimensional nature of environmental degradation. To fill this gap, this study utilized the ecological footprint to capture environmental degradation because it is a more dynamic environmental quality measure. The paper examines the population-environmental degradation hypothesis for five populous African countries (DR Congo, Ethiopia, Nigeria, South Africa and Tanzania) using panel information from 1990 to 2019. The Cross-sectionally Augmented autoregressive distributed lag (CS-ARDL) was employed to assess the relationship among the data - ecological footprint per capita (ECFP), population growth rate (POPG), population density (POPD), urban population growth rate (URBN), age structure of the population (AGES), per capita GDP growth rate (PGDP), energy consumption (ENEC), and trade openness (TRAD). The findings of the study revealed that POPG, POPD, AGES, PGDP, ENEC and TRAD increase environmental degradation. Urbanization (URBN) has no significant influence on environmental degradation in the selected African countries. The study concludes with policy prescriptions geared towards addressing population expansion and improving environmental quality.

Examining the temporal impact of stock market development on carbon intensity: Evidence from South Asian countries

The growing size of stock market in the South Asian countries might have contributed to raising the level of industrial production and energy consumption. This upturned energy usage might have widened the scope for carbon emissions because these nations heavily rely on fossil fuels. In this milieu, therefore, in the present study, we assessed the impacts of stock market development, per capita income, trade expansion, renewable energy solutions, and technological innovations on carbon intensity in the four South Asia countries from 1990 to 2016. The empirical results based on the CS-ARDL approach revealed that stock market development, per capita income, and trade expansion invigorated carbon intensity in the South Asian countries. On the contrary, the increased usage of renewable energy solutions and technological advancement helped in reducing the energy-led carbon intensity. Further, the interaction of stock market with renewable energy, and subsequently with technological advancement delivered insignificant coefficients, which indicates the inefficacy of renewable energy and technological advancement in regulating stock market-led carbon intensity during the study period. Therefore, by considering the need for complementarity between economic growth and environmental targets, we proposed a multipronged policy framework, which may help the selected countries to attain the Sustainable Development Goals, with a special focus on SDG 7, 8, 9, and 13.

How does responsible leadership affect employees' voluntary workplace green behaviors? A multilevel dual process model of voluntary workplace green behaviors

This study aims to explore how to encourage employees to engage in voluntary workplace green behavior. Drawing upon social identity and social information processing theories, we theorized and tested a multilevel model in which responsible leadership triggers employee voluntary workplace green behavior by fostering organizational identification and a green work climate. Additionally, we distinguished these two critical processes by introducing employees' green values as a moderator. A multilevel, multisource study collected from 299 employees and 71 supervisors generally supported our predictions. Specifically, responsible leadership was a significant predictor of voluntary workplace green behavior. Moreover, employees' green values strengthened the organizational identification mechanism and attenuated the green work climate process in the relationship between responsible leadership and voluntary workplace green behavior. The findings and the theoretical underpinning of our study shed a new light on the green work climate, identity, and values in a responsible way shape the voluntary green behaviors among organizational actors and provide practical implications for leaders determined to improve environmental sustainability in organizations.

Towards sustainability path in Argentina: the role of finance, energy mix, and industrial value-added in low or high carbon emission-application of DARDL simulation

The interconnection between environmental protection and sustainable development is at the heart of discussion among all the intergovernmental agencies around the globe. Such discussion is considered highly important considering the role of finance, an abundance of fossil fuel and industrial value-added on economic activities and environmental issues. Meanwhile, few empirical studies in this line of discussions have documented policy options for projecting the path towards sustainable development in Argentina from 1971 to 2018. To contribute to the extant literature in filling this gap, this study examines whether finance can escalate a long-lasting economic shift that will change the path of carbon emission in Argentina using the novel econometric technique, dynamic Autoregressive Distributed Lag simulations. The modelling protocol incorporates the impact of the following economic agents such as population, economic growth, trade openness, and government consumption expenditure. Our result suggests that all the variables are cointegrated under the ARDL-bounds testing framework. The long and short-term estimates from the dynamic ARDL simulation show that finance and industrial value added interestingly offer policy options for CO2 mitigation in Argentina. Fossil fuel, population, economic growth, and government consumption expenditure have increasing an impact on CO2 emissions, exacerbating sustainability challenges in Argentina. In sum, improved finance and industrial restructuring are needed economic acumen that can accelerate a quick transition to a low-carbon development in Argentina, while fossil fuel, population, economic growth, and government consumption expenditure generate environmental challenges. Policy options in consideration of investors' safety in carbonated companies in Argentina, these companies owe shareholders an obligation to invest in a resilient carbon capture and storage technology in a bid to decrease environmental degradation and align with environmental goals set by the Argentine government.

Carbon dioxide emissions and Chinese OFDI: From the perspective of carbon neutrality targets and environmental management of home country

Studies investigating the relationship between foreign direct investment (FDI) and the environment have focused predominantly on the effects of FDI on host country environments with less attention paid to the impact on home countries. This study turns its attention to the effects of outward foreign direct investment (OFDI) on a home country's carbon dioxide emissions. We use three paths through which OFDI can affect the carbon dioxide emissions of a home country, including economic scale, technology level, and industry composition effects. Using a simultaneous equation model and panel data of 30 provinces of China for the period of 2003-2017, this study finds that OFDI is positively related to the carbon dioxide emissions of the home country, though the effects of emissions have weakened dynamically due the technology developments brought about by OFDI. More specifically, we find that both 'pollution haven' and 'pollution halo' effects existing in three different paths. The paths of industry composition and technology level show negative effects on carbon dioxide emissions, whilst the path of economic scale is positive. OFDI is also found to be negatively related to the carbon intensity of the home country.

Searching appropriate system boundary for accounting India's emission inventory for the responsibility to reduce carbon emissions

This paper explores the features of accounting for the national carbon emission inventory under four different system boundaries, including the presently operational territorial production-based accounting (PBA) practised by the UNFCCC. Using a recently published input-output table with the base year for 2013-2014, the study calculates India's 'Nationally Determined Contribution (NDC)' to the mitigation of carbon emissions using production-based, consumption-based, sharing-based and equity-based accounting. The study finds India as a net importer of carbon emissions, especially for its high emission-intensive capital and energy goods import such that the country is bearing the minimum burden of emission reduction responsibility. However, the study intends to analyse this burden of responsibility in terms of the criteria of justice and effectiveness and addresses the future policy priorities for India to become a net exporter of industrial goods. We recommend India for supporting and implementing an alternative system boundary of emission inventory accounting which would be more consistent with the provisions of 'equity' subscribed under the UNFCCC while at the same time, helpful for achieving the climate goals by appropriately trace and track the sources of 'carbon leakage'.

Technology spillovers and sustainable environment: Evidence from time-series analyses with Fourier extension

Globalization and human capital accumulation are the main drivers of technology spillovers and essential for economic growth. At the same time, globalization and human capital are drivers to construct a green growth path that prevents pollution and the overuse of resources, and thus mitigates environmental degradation and achieves sustainable development. This mechanism, known as the 'technique/technology effect', may occur by stimulating technological development and creating environmental awareness and is of utmost importance in developed and developing countries to protect the environment. The aim of this study is to evaluate these outcomes, investigating how the environment reacts to developments in globalization and human capital accumulation by performing time-series analyses augmented with Fourier extensions, for countries in the BRICS group (Brazil, Russia, India, China and South Africa). The study first checks unit root and cointegration relationship by using Fourier unit root and Fourier cointegration approaches. Having confirmed a cointegration relationship, the FMOLS estimator extended with Fourier terms is applied to estimate cointegration parameters. Empirical results show that globalization and human capital are beneficial to protect the environment and to build a sustainable blueprint for the future, which specifically refer to more investment in the educational system and more efforts promoting social and cultural interaction across the globe.

Mirroring risk to investment within the EKC hypothesis in the United States

In reality, economic expansion cannot be paced-up enough. This account for a potential trade-off between income and environmental degradation that is expectedly feasible at a maximum level of income. On this note, the current study looked at the validity of income-environmental degradation (Environmental Kuznets Curve, EKC) hypothesis especially amidst risk to investment in the United States over the period 1984-2017. Considering that the burning of fossil fuels constitutes the largest source of Greenhouse gas (GHG) in the United States, this study employed energy carbon emissions as a proxy for environmental quality and as a dependent variable. While the study employed renewable energy production as additional explanatory variable, it implemented the Autoregressive Distributed Lag (ARDL) technique in addition to a set of cointegration techniques. Importantly, the study found that the EKC hypothesis is valid for the case of the United States but not without a non-significant trade-off of risk to investment. Additionally, renewable energy production exhibits a statistically significant and desirable impact on environmental quality in both the short and long-run. In general, the study posited that while environmental sustainability is achievable at maximum level of income, it is likely attainable at the detriment of risk to investment. Hence, this observation should trigger a potential policy mechanism that minimizes risk to investment in light of the attainment of the country's sustainable development goals (SDGs).

A comparative analysis of the relationship between innovation and transport sector carbon emissions in developed and developing Mediterranean countries

Innovation technologies have been recognized as an efficient solution to alleviate carbon emissions stem from the transport sector. The aim of this study is to investigate the impact of innovation on carbon emissions stemming from the transportation sector in Mediterranean countries. Based on the available data, Albania, Algeria, Bosnia and Herzegovina, Croatia, Egypt, Morocco, Tunisia, and Turkey are selected as the 8 developing countries; and Cyprus, France, Greece, Israel, Italy, and Spain are selected as the 6 developed countries and included in the analysis. Due to data constraints, the analysis period has been determined as 1997-2017 for the developing Mediterranean countries and 2003-2017 for the developed Mediterranean countries. After determining the long-term relationship with the panel co-integration method, we obtained the long-term coefficients with PMG and DFE methods. The empirical test results indicated that the increments in the level of innovation in developing countries have a positive impact on carbon emissions due to transportation if the innovation results from an increase in patents. An increase in the level of innovation in developed countries has a positive impact on carbon emissions due to transportation if the innovation results from an increase in trademark. As a result, innovation level has a positive effect on carbon emissions due to transportation, and this effect is stronger for developed countries.