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The ecological footprint (EF) has become one of the leading indicators for environmental assessments. The EF is an indicator that is at the center of researchers' interest in empirical analysis, as it simultaneously reflects air, water, and soil pollution. Analyzing the six sub-components of the EF is essential for assessing the environmental pressures from forestry, construction, fisheries, agriculture, and livestock, as well as for remediating these pressures. In this context, this study examines the impact of income, globalization, and technological progress (represented by patents) on the EF and its subcomponents for the BRICS countries over the period 1992-2020. The BRICS countries are of critical importance to this study as major countries in the global economic and environmental landscape. The study employs the panel LM cointegration test and the common correlated effects estimator. The results show that economic expansion augments ecological, carbon, and built-up land footprints and that patents have no significant impact on the EF indicators. On the contrary, globalization is a factor that reduces five of the seven EF indicators. A robustness check performed with a half-panel jackknife confirms the analysis findings. These results suggest that BRICS policymakers should harmonize economic development and ecology while making greater use of the environmental benefits of globalization.

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The circular economy practices contribute to sustainable development by maximising efficiency, utilising renewable resources, extending product lifespans, and implementing waste reduction strategies. This study investigates the individual impacts of four sources of the circular economy on the ecological footprint in Germany, a country that is among the pioneers in establishing a comprehensive roadmap for the circular economy. The four sources examined are renewable energy consumption (REC), recycling, reuse, and repair of materials. Using time series data from 1990 to 2021, the study employed the dynamic autoregressive distributed lag (ARDL) simulation technique and also applied kernel-based linear regression (KRLS) to test the robustness of the results. The findings revealed that reuse practices significantly reduce the ecological footprint in both the short and long run. REC and repair also substantially decrease the ecological footprint, as shown by the simulation analysis. Conversely, while recycling is generally considered crucial for minimising environmental impact, in this study, it was found to contribute to environmental degradation. This paradox may be attributed to the nascent state of the recycling industry and data limitations. The results from KRLS confirm the findings of the dynamic ARDL. It is recommended that policymakers develop measures that are appropriate, efficient, and targeted to enhance the role of each source of the circular economy in reducing the ecological footprint in Germany. The major limitation of the study is its reliance on the indirect measures of circular economy attributed to the non-availability of data on direct measures.

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Artificial intelligence (AI) technology serves as a powerful tool to optimize energy efficiency and lessen ecological footprints. Using data from 30 provinces in China over the period from 2018 to 2022, this study investigates how regional AI development affects the per capita ecological footprint and explores the underlying mechanisms. The results show that: (1) Regional AI development can significantly decrease the ecological footprint, and this conclusion remains robust after a series of robustness checks. (2) Mediation effect analysis indicates that AI technology mainly decreases the ecological footprint by improving energy utilization efficiency. (3) The panel threshold model results show that AI's influence on the ecological footprint has a single energy efficiency threshold. Only when regional energy efficiency exceeds a certain threshold can AI fully exert its suppressive effect on the ecological footprint. (4) Regional heterogeneity analysis shows that the reduction effect of AI on the ecological footprint is more pronounced in the central and eastern regions of China. This paper helps clarify the specific impact of AI technology development on the ecological footprint and provides scientific evidence for regional technology development, energy efficiency improvement, and ecological environment policy formulation.

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This study explores how globalization influences the relationship between institutional quality and the ecological footprint in Africa. Utilizing dynamic panel threshold models with data from 49 African countries (2002-2022), we investigate how different types of globalization-economic, social, cultural, and political-affect this relationship. Our findings reveal that the impact of institutional quality on the ecological footprint varies significantly depending on globalization thresholds. Specifically, below certain thresholds, improved institutional quality increases the ecological footprint, whereas above these thresholds, it tends to reduce it. For economic globalization, the threshold is 53.510; for social globalization, 48.332; for cultural globalization, 28.446; and for political globalization, 69.663. These results highlight the need for targeted environmental policies that consider the specific effects of each globalization dimension to effectively manage Africa's ecological footprint. The study contributes to the literature by addressing the complex link between institutional quality and globalization and provides practical insights for policymakers to design more effective sustainability strategies in the African context.

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This study examines the spillover of pollution among the 26 European Union (EU) countries from 1995 to 2020. In order to quantify pollution spillovers among the countries, we estimated the Environmental Kuznets Curve (EKC) using spatial econometric methods. Our research is unique in that it investigates ecological footprint spillovers for EU countries. This study also considers the direct and indirect effects of renewable and fossil energy consumption and globalization on environmental degradation in EU countries. The empirical results favor the validity of the EKC hypothesis. Our results support the presence of positive and significant ecological footprint spillovers among EU countries. Our spatial estimates also reveal the significant spillover impact of explanatory variables on the ecological footprint. The ecological footprint of the local country is declining owing to the consumption of renewable energy in neighboring countries. Furthermore, the fossil energy consumption of the local and neighboring countries has a positive impact on the ecological footprint. Evidence obtained from our spatial estimates provides useful insights to policymakers in developing appropriate environmental policies to combat climate change.

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This study delves into the intricate relationship between economic growth and its ecological repercussions, employing a comprehensive assessment of ecological footprint across 131 nations. The time period considered for the research spans from 2009 to 2019. Utilizing the CS-ARDL methodology, the results indicate a correlation between reducing ecological footprint and bolstering private sector domestic credit. Additionally, a relationship between diminishing private sector domestic credit of banks and augmenting private sector domestic credit within the financial sector has been identified. In conjunction with other indicators of financial advancement, the significance of domestic lending to the private sector has been underscored. The study reveals a notable reduction in human population's adverse impact on the environment. However, increased levels of energy consumption, foreign direct investment and per capita GDP are associated with an improvement in global quality of life. Particularly noteworthy is the validation of the "pollution haven hypothesis" in the global economic context. The implications of this research are substantial; suggesting that global economic dynamics may support efforts towards environmental conservation. However, outcomes may vary across regions or countries, particularly regarding the emphasis placed by the financial sector on environmental preservation. This study comprehensively examines the complex nexus between economic progress and its ecological consequences, keeping in consideration factors such as financial growth, urbanization, energy consumption and Foreign Direct Investment (FDI).

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BACKGROUND: Various factors have been found responsible for the increment in ecological footprint resulting difficulties in maintaining environmental sustainability. This has been noticed through a modeling perspective. Identifying the factors affecting Ecological Footprint helps policymakers to formulate policies regarding sustainability. However, studies conducted based upon systematic reviews on Ecological Footprint through modeling are still limited. OBJECTIVE: This study intends to identify influential factors associated with ecological footprint through a systematic review. METHODS: ProQuest, Science Direct, Scopus, and Web of Science databases were used to search literature systematically. Particular keywords and Boolean operators were applied to dig out relevant studies for the review. Peer-reviewed research articles published in the English language till September 13, 2023, were incorporated for the analysis. Following the guidelines of Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA), 1011 articles were identified from four different databases and only 37 research papers were eligible for this study. These articles were assessed and relevant information was extracted and then amalgamated into the systematic review. RESULTS: Gross domestic product, urbanization, energy consumption, renewable energy, non-renewable energy, natural resources, bio-capacity, human capital, foreign direct investment, trade openness, and financial development were observed as key factors of the ecological footprint. CONCLUSION: Factors known to influence ecological footprint need to be addressed properly for environmental sustainability including widespread use of renewable energy.

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Amidst pressing global environmental challenges, exacerbated by climate change and the imminent threat of global warming, there is a critical need to assess the efficacy of environmental policies. This study centers its attention on the pivotal role of these policies in addressing environmental concerns. Specifically, our research aims to scrutinize the impact of stringent environmental policies on environmental quality under the theoretical underpinnings of environmental Kuznets curve. To achieve this objective, the study collected data from BRICS-T economies over the period of 1990-2020. This study employed the method of moments quantile regression technique for empirical analysis. Our study validates the presence of the Environmental Kuznets curve (EKC hypothesis). Empirical findings reveal the sustained significance of environmental stringency across all quantiles, demonstrating a positive correlation in lower quantiles and a negative correlation in higher quantiles. At lower quantiles, the impact is insignificant initially, but pronounced due to efficiency improvements induced by stringent policies. The effects became negative at middle quantiles, indicating stringent policies might encounter diminishing returns where policy measures start stabilizing ecological impacts. At higher quantiles, the influence of ESI remains significant, reflecting ongoing adaptations in larger economies with higher ecological footprints. This suggests the potential effectiveness of stringent regulatory measures in mitigating environmental impacts and reducing ecological footprints. The identified inverted U-shaped curve signifies that while stringent policies may not inherently enhance environmental health, beyond a certain threshold, they can indeed contribute to its improvement. Our policy recommendation advocates for the widespread adoption and promotion of such stringent measures to safeguard environmental health.

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This comprehensive study addresses the urgent global challenges of climate change and environmental degradation by focusing on the Ecological Footprint (EF). Unlike previous studies, it introduces a novel approach incorporating spatial spillover, temporal effects, and common shocks in panel data analysis. The spatial spillover effect highlights the influence of trade, pollution havens, and competition between neighboring countries on EF. The temporal effects emphasize the significance of historical production patterns and export strategies in shaping the current EF. The study also considers the impact of exogenous common shocks, such as international agreements and global events, on EF. Utilizing a dynamic spatial panel data model with common shocks, the research examines 40 European countries from 1992 to 2020, revealing the significant impact of biocapacity, energy consumption, industrialization, and globalization on EF. Findings indicate that spatial spillover effects contribute to EF transfer, emphasizing the need for collaborative global efforts. The study sheds light on the interconnectedness of environmental impacts and underscores the importance of considering both weak and strong forms of cross-sectional dependence in achieving accurate estimations. The research enriches our understanding of EF determinants and provides nuanced insights for policymakers striving to develop effective strategies for sustainable resource management and environmental conservation.

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The Sub-Saharan African (SSA) region remains the world's largest recipient of remittances. Due to growing concerns over climate change issues, recent studies have examined how these financial flows have affected environmental quality. Sundry variables were controlled in such studies concerning the remittances-environment nexus, including institutional quality. Notwithstanding that remittance and institutional quality are imperative, their combined effect on environmental quality has been overlooked. The present study has inspected how remittances and institutional quality have jointly influenced environmental quality in 44 economies in the SSA region between 2000 and 2022. Using PMG-ARDL analysis, the findings revealed that remittances had a negative long-term impact on environmental quality. Conversely, the study found that institutional quality positively affected the per capita ecological footprints, as measured by the six indicators' average. Furthermore, the results indicated that improvements in institutional quality over time mitigated the adverse impact of remittances on the environment in the sampled SSA countries. Additionally, a threshold level of institutional quality effectively moderates remittances' detrimental effects on environmental quality were identified. Therefore, most regional countries must enhance their institutional quality to mitigate the negative environmental impact of remittances.

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Increasing energy vulnerability can cause environmental pollution by increasing fossil fuel consumption. If it leads to cost-cutting-oriented industry growth, financial development can lead to environmental regulations being ignored, compromising environmental quality. Political globalization and economic growth can increase short-term environmental pressures, straining long-term ecological balance and causing habitat loss and pollution. This study investigates the impact of energy vulnerability, financial development, and political globalization on environmental sustainability in Turkey for the 2000-2019 period using with wavelet quantile-based techniques. According to results, while the negative effect of energy vulnerability on environmental quality is lower in the short term, the size of the effect increases in the medium and long term. In addition, at low quantiles of environmental quality, the negative effect of financial development is low in the short and long term, while the effect becomes evident in the long term. Moreover, the effects of political globalization on environmental quality are positive in all quantiles. Additionally, the harmful effects of economic growth are more evident at lower quantiles of environmental quality. Turkey should increase its clean energy investments by using its geographically advantageous location. Policymakers should also prioritize environmental regulations and promote sustainable practices in industries. Incentives for cleaner production technologies and environmentally friendly initiatives can help steer the financial sector towards more responsible and environmentally friendly practices. Additionally, the study suggests that increasing institutional capacity and aligning national policies with international agreements can accelerate the positive effects of political globalization.

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The escalating phenomenon of environmental degradation is an urgent global concern, imperiling ecosystems and hindering the prospects for sustainable development on a planetary scale. Therefore, this study aims to explore the intricate interplay between renewable energy (RE) and ecological footprint (EF), considering the conditional impact of fiscal capacity (FIC), human development (HDI), institutional quality (IQI), and population density (PDN). Drawing on panel data encompassing 74 developing countries from 2000 to 2022, the study employs a dynamic panel threshold regression method, both with and without an instrumental variable approach. The findings unveil a non-linear nexus between RE and EF, revealing significant threshold values for FIC (1.870), HDI (0.736), and IQI (0.311), above which RE showcases its efficacy in mitigating EF. Conversely, when these predictors dip below the thresholds of FIC (1.391), HDI (0.655), and IQI (0.2545), the impact of RE on FE becomes insignificant. Moreover, the study introduces PDN as an additional threshold variable in the analysis, pinpointing that the effectiveness of RE in reducing EF hinges on PDN being below a threshold value of 263.144; however, above a threshold value of 276.98, the influence of PDN on the RE-FE nexus diminishes. The findings underscore the complexity of policy landscapes in developing countries. They suggest that while promoting renewable energy is pivotal for environmental sustainability, it is equally imperative to bolster existing environmentally friendly fiscal capacity, advance human capital, enhance institutional quality, and craft effective population distribution policies.

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In this paper, the ecological footprint model is used to analyze the ecological carrying capacity of resource-based cities, and the ecological profit and loss state is calculated to evaluate their sustainable development ability. Taking Zigong City of Sichuan Province as an example, Research has shown that the ecological carrying capacity of Zigong City has been increasing year by year from 2006 to 2012 and from 2015 to 2021. There was a sharp decline from 2013 to 2014. The ecological and economic diversity index and the development capacity of the ecological and economic system showed an upward trend from 2006 to 2021. However, from 2006 to 2020, the ecological sustainable development index of Zigong City was below 0.2, indicating a serious unsustainable state. In 2021, it was in a moderately unsustainable state. According to the protection of cultivated land resources, forest resources, grassland resources, water resources, energy utilization and building land involved in Zigong City's sustainable development ability, the corresponding suggestions are put forward.Considering the economic, environmental and social aspects, this paper propose a path for sustainable development ability of resource-based cities.

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Clarifying the spatiotemporal evolution of sustainable water resources utilization (SWU) and its decoupling effects from economic growth (EG) is essential for the effective management of water ecosystems and sustainable development of basins. However, the traditional Ecological Footprint model limits the ability to compare SWU within a basin, and existing studies need to pay more attention to the importance of water renewability in quantifying SWU. Based on the capital flow and capital stock perspectives, this study constructed an evaluation method for SWU and its decoupling effect from EG by combining the three-dimensional Water Ecological Footprint (WEF), sustainable reclassification, and the Tapio model, and explored different types of SWU enhancement strategies. The results indicate that: (1) From 2010 to 2022, the SWU of the Yellow River Basin (YRB) shows a decreasing and then increasing trend and is generally in water ecological deficit, with a lower SWU in the middle and lower reaches. Overall, the per capita WEFsize decreased by 0.73% per year, while the WEFdepth increased by 0.26% per year, the pressure and stress on the SWU of the YRB are still significant. (2) Agricultural freshwater use and domestic greywater discharge dominate the WEF of the basin, and the problem of inversion of the water use structure with the industrial structure is evident. (3) Spatial differentiation within the basin is apparent, and SWU shows a spatial distribution of western strength and eastern weakness, with significant consumption of water capital stock due to insufficient water capital flow as the main reason. (4) Topio decoupling analysis shows that WEF and EG are mainly strongly decoupled, with WEF lagging behind EG; the decoupling relationship between SWU and EG evolves from END-SD-WD, reduces the consumption of water capital stock and increasing water capital flow is a reasonable way to realise its stable strong decoupling. This study is essential for SWU studies of large river basins in arid and semi-arid regions. It provides insights into the sustainable management and rational allocation of water resources in the YRB and other similar basins worldwide.

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The significance of accurate energy production prediction cannot be overstated, especially in the context of achieving carbon neutrality and balancing traditional and clean energy sources. Unlike conventional models with simplified assumptions or limited data inputs hindering energy usage optimization, waste reduction and efficient resource allocation, we introduced a novel structural equation modelling approach to eight manufacturing industries' sustainable waste management practices (SWMPs) in Iraq. This comprehensive analysis, conducted with Smart PLS software on 375 responses aims to enhance energy production predictions' accuracy and support sustainability goals contribute to achieving carbon neutrality goals and promote a balanced energy mix that supports sustainability and environmental stewardship. The findings reveal noteworthy insights: notably, chemical manufacturing companies exhibit a substantial advantage from green accounting practices, witnessing a 78.1 % and 45.8 % improvement in environmental auditing oversight and SWMPs, respectively, compared to other manufacturing sectors. Compared to conventional grey models, our model demonstrates that a 1-unit improvement in CSR enhances environmental auditing oversight effectiveness by 33.4 % and sustainable waste management by 56.9 % across industries. By leveraging these data-driven insights and innovative approaches, we can drive positive change towards a more sustainable and resilient energy future, collectively contributing to a more resilient, efficient, and sustainable energy ecosystem that benefits societies, economies, and the environment. The heightened accuracy of energy production prediction facilitated by our novel model empowers stakeholders at regional and global levels to make informed decisions, mitigate risks, support policy development, achieve sustainability goals, formulate effective policies and foster collaboration.

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Green growth is of great importance in terms of solving environmental problems and achieving sustainable development goals. However, the existing literature has not investigated how green growth affects environmental degradation and environmental sustainability variables. In light of this gap, this study aims to analyse the impact of green growth and institutional quality on CO2 emissions, ecological footprint and inverse load capacity factor in OECD countries by constructing three different models. The results of the analysis indicate that (i) green growth exerts a significant mitigating and differentiating effect on CO2, ecological footprint and inverted load capacity factor in the long run. This is evidenced by a 1% increase in green growth reducing CO2, ecological footprint and inverted load capacity factor by 0.563%, 0.373% and 0.198%, respectively. (i) The impact of green growth on CO2 and inverted load capacity factor in the long run is negative and statistically significant; (ii) the impact of green growth on CO2 and inverted load capacity factor in the short run is negative and statistically significant; (iii) the impact of institutional quality on deterioration is positive and significant in the long run; (iv) the impact of population on deterioration and sustainability is significant and mixed. The findings indicate that decision-makers in OECD countries should review green energy policies when setting the sustainable development goals, as environmental sustainability is more challenging than reducing pollution.

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The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the "Dynamic Autoregressive Distributed Lag (DYNARDL)" simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional "Environmental Kuznets Curve," implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, trade openness can exacerbate environmental degradation due to economic priorities often taking precedence over environmental concerns.

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This study employs Fully Modified Ordinary Least Squares, Common Correlated Effects and Dumitrescu-Hurlin panel causality techniques to investigate the environmental impacts of nuclear energy generation in European Union countries from 1990 to 2022. The ongoing debate within the European Union and the empirical contradictions in the literature, coupled with the overall singular-dimensionality surrounding the impacts of nuclear energy on the environment, necessitate a broader and comprehensive examination of its effects across various environmental dimensions. These dimensions include the presence of CO2 emissions and the ecological footprint generated. The findings reveal that nuclear energy adoption by countries tends to affect CO2 emissions but this relationship goes from CO2 to nuclear energy consumption as per the causality test, while the ecological footprint variable does not exhibit a causal relationship with nuclear energy consumption. We estimated that a higher presence of air pollutants promotes the generation of nuclear energy as an alternative to fossil fuel energy sources. The study highlights that while nuclear energy generation produces no air pollution, it does impose significant land use requirements, potentially leading to ecosystem degradation. Factors such as uranium extraction, nuclear waste management, disposal, and accidents contribute to this impact. Further research is needed to understand the specific mechanisms and factors contributing to the observed environmental degradation associated with nuclear energy generation.

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This paper is the first comprehensive research to examine the effect of circular economy on environment employing two environmental degradation indicators (CO2 emissions, ecological footprint) and one environmental quality indicator (load capacity factor) for 57 Belt and Road Initiative (BRI) countries during 2000-2019. The effect of other variables such as renewable energy, industrialization, and globalization was also controlled. The study applied the cross-sectional autoregressive distributed lag method (CS-ARDL), the augmented mean group (AMG), and common correlated effects mean group (CCEMG) methods as a robustness checks. The empirical findings reveal that circular economy and renewable energy have pro-environmental effects by decreasing carbon emissions and ecological footprint and increasing the load capacity factor in BRI countries. However, industrialization and globalization have detrimental effects on the environment. The result of causality shows a bidirectional causality between renewable energy, circular economy, industrialization, and three environmental indicators, but the relationship of globalization with CO2 emissions and the load capacity factor is unidirectional and with the ecological footprint is bidirectional. All the results are confirmed by the robustness tests. The study suggests policy implications for the BRI government.

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Our world has had difficulty meeting humans' needs in recent years. To ensure that the world can sustain its inhabitability and self-sufficiency in terms of natural resources, it is required to make the total amount of biocapacity areas equal to or higher than the ecological footprint. An analytical study has been carried out to remedy the biocapacity deficit by utilizing this information for Turkey and then these areas are optimized with heuristic optimization techniques. As a result, Artificial Bee Colony provides better objective function results (fewer errors) compared to Particle Swarm Optimization and Global Optimization Method Based on Clustering and Parabolic Approximation in terms of minimum, maximum, average value, and standard deviation. The rates of change according to the current situation of the biocapacity areas in 2016 are 277.97 %, 30.28 %, -29.28 %, 14.97 %, and -44.85 % for cropland, grazing land, forestland, fishing grounds, and built-up land, respectively. Depending on the population growth, these rates should additionally change by 83.24 %, -0.69 %, 3.97 %, 6.22 %, and -14.24 % respectively in 2050. The developed model can be used in industry or within the frame of government development policy and thus the balance between ecological footprint and biocapacity can be kept under control.

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