Capita Ecological Footprint Research Articles

Spatial-temporal evolution and drivers of ecological sustainability of coastal fisheries in China

Marine fisheries are an important source for the survival and economic livelihood of the world's population. With coastal economic development, rapid population growth, and advances in fishing technology, oceans and coastal areas have been placed under greater environmental pressure. Therefore, the sustainability of coastal fisheries must be revisited. This study used the 3D ecological footprint (EF) model and partial least squares (PLS) to analyze the spatial-temporal evolution of the ecological sustainability of coastal fisheries in China, and discuss the direct and indirect impacts of drivers from economic, social, and technological perspectives. Results showed that the gap between per capita EF and per capita biocapacity (BC) of coastal fisheries narrowed until it stabilized from 2010 to 2020. Footprint depth and size wholly showed a fluctuating upward trend. In terms of spatial distribution, footprint depth was high in the north and low in the south, and footprint size was a relatively scattered. Consumption pull had the largest effect on the ecological sustainability of coastal fisheries in China, followed by the economy push, but the effect of technology suppression was not significant. Some policy recommendations for sustainable fisheries governance were proposed in terms of consumption structure transformation, fisheries industry upgrading, and ecosystem-based management. This study indicated that the current development of coastal fisheries in China is sustainable from an ecological supply and demand perspective. The findings provide information on effective coastal fisheries governance and broad coastal and ocean management, and have the potential to provide references for sustainable fisheries governance in other coastal countries with similar contexts.

Does artificial intelligence affect the ecological footprint? –Evidence from 30 provinces in China

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.

Navigating the impact of remittances on environmental quality in Africa: The crucial role of institutional quality

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.

Ecological Footprint Deficit in Brazil: An analysis of reports from The World Wide Fund For Nature

This article aimed to analyze changes in the ecological footprint in Brazil over time, focusing on reports from the World Wide Fund for Nature (WWF) and scientific literature. To do so, the present article is of a documentary, bibliographical, and qualitative nature. Data collection was conducted through systematic searches, employing search terms such as "Ecological Footprint," "Brazil," "World Wide Fund for Nature." The results showed that despite having one of the largest global biocapacities, Brazil faces challenges in effectively translating this advantage into sustainable benefits. The findings highlight the phenomenon of horizontal and vertical scale growth in the Brazilian economic system, pointing to the combination of population growth with increased consumption, especially in urban areas. Regional disparities in per capita Ecological Footprint are evident, indicating distinct consumption patterns in different parts of the country. WWF reports emphasize the importance of strategic interventions to trigger significant transformations. In this point of view, the study highlights the need to rethink consumption models and adopt more sustainable practices. The deficit of the Ecological Footprint in Brazil requires a proactive and collaborative response from policymakers, communities, and economic sectors. Only through strategic interventions and a fundamental shift in the approach to natural resources can one aspire to a future where Brazil's biocapacity is effectively transformed into sustainable benefits, ensuring harmony between economic development and environmental preservation.

Improvement and application of the ecological footprint calculation Method—A case study of a Chinese university

The Ecological Footprint (EF) model is an effective tool for determining the resource consumption demand of human activities and whether natural assets are overutilized. The EF calculation method has certain theoretical and methodological importance for low-carbon campus construction. With the development of science and technology, some parameters in traditional EF calculation methods need to be modified. Based on the definition of fossil energy land and the latest average grain yield, this paper revised the calculation parameters of the EF method in six aspects: absorbed gas, electricity, agricultural products, aquatic products, livestock products, and paper. This paper applied the calculation method before and after improvement to Henan Polytechnic University. The EF of the campus according to calculations was 28,358.41 gha, and the per capita EF was 0.657 gha/person using the improved calculation method. Compared with the unimproved method, the improved method resulted in a substantial decrease in EFs, which can be explained by three reasons. First, the fossil energy land was divided into forestland and pasture land. Second, the average yield was recalculated using the latest statistical database of the United Nations Food and Agriculture Organization. Finally, the utilization of waste pulp in the paper industry was considered. The calculated results were also analyzed and compared with those of other universities, Worldwide Fund for Nature and Enhancing Universities’Sustainability Teaching and Practices through Ecological Footprint. The improved calculation results can better reflect the actual situation of the campus, improve the rationality of EF calculation, and provide a reference for EF at the campus level. Accordingly, the current situation of campus resource consumption can be explained, further providing a basis for proposing an EF reduction scheme for green campus construction.

Evaluation and regulation strategy for ecological security in the Tarim River Basin based on the ecological footprint

Population growth, oasis expansion, and increased consumption of water and fossil energy pose a significant threat to the ecological security of the Tarim River Basin (TRB). However, single-factor assessments and traditional ecological footprint models limit the ability to compare ecological security across prefectures, and existing studies neglected renewable resources in the ecological security regulation strategies. This study constructed TRB's ecological footprint accounts, analyzed the status of the sustainable development of the watershed in combination with the landscape ecological risk index, and explored the strategies and feasibility of watershed ecological security regulation based on multi-objective planning and multi-scenario simulation. The results are as follows: 1) the ecological deficit of the basin has expanded by approximately 1.79 times since the beginning of 21st century, with the eastern part of the basin being at higher ecological risk. Overall, the annual decrease in per capita ecological carrying capacity was 0.85%, while the annual increase in per capita ecological footprint was 32.35%. 2) Fossil energy dominates the inter-annual variation in the ecological footprint of the watershed; its contributions to the total ecological footprint significantly increased from 9.55% to 71%. 3) On the basis of increasing crop yields and optimizing cropping structure, fully utilizing solar energy resources, increasing cultivated land by 15% or reducing fossil energy by 50% will improve the ecological security of the watershed. This study represents an important supplement to ecological security assessments of inland river basins in extreme arid regions, such as the TRB, and provides insights into ecological security regulation and sustainable socioeconomic development in such regions.

Multi-scale analysis on sustainability and driving factors based on three-dimensional ecological footprint: A case study of the Yangtze River Delta region, China

Accurate assessment of the sustainable development level is crucial to providing reasonable and effective management recommendations. However, analysis with a single scale can only reflect the sustainable status at a specific level. In this study, a multi-scale analysis of sustainability was conducted via the three-dimensional Ecological Footprint (EF) model in the Yangtze River Delta (YRD). Moreover, driving factors of sustainability were analyzed using the Multi-scale Geographically Weighted Regression model (MGWR). The conclusions include: (1) the development of YRD showed an unsustainable trend from 2014 to 2021, with per capita EF decreasing from 5.769 ha/cap to 5.283 ha/cap. The provincial sustainability is ranked as follows, from being the most sustainable to the least: Anhui Province > Jiangsu Province > Zhejiang Province > Shanghai City. (2) Based on dual indicators of EF depth and size, 41 cities were categorized into nine groups. The dominant type is always Medium size-Low depth (ML) and High size-Low depth (HL) type cities from 2014 to 2021. From the perspective of city scale, the sustainability of five cities weakened, while seven cities showed improvements. (3) Output value of primary industry (OVPI) and population (POP) were always the dominant factors affecting EF, but showed positive and negative correlations respectively. OVPI changes from north-south symmetric type to central symmetric type, while POP changes from central symmetric type to north-south symmetric type. This paper aims to comprehensively assess the sustainable development status from agglomeration-province-city perspectives, and its findings can provide a reference for similar regions with unbalanced development status between ecology and production.

Spatio-temporal evolution of provincial ecological footprint and its determinants in China: A spatial econometric approach

The increasing demand for ecosystem services in regional development has presented significant challenges to environmental sustainability. To alleviate environmental pressure, it is crucial to employ the provincial ecological footprint to gauge regional ecological pressure and research the determinants that contribute to reducing environmental pressure. This underscores the significance of examining and addressing the intricate relationships between ecological resources and regional development. While prior studies often focus on national data, provincial ecological footprints have been relatively ignored. Moreover, scant research exists on the influence of variables such as resource rents and industrial structures. This study employs the ecological footprint model to assess the per capita ecological footprint of Chinese provinces from 1990 to 2020, intending to gauge escalating ecological pressures and pinpoint their drivers. We use spatial panel data analysis to investigate the association among economic growth, natural resource rents, industrial structures and ecological footprint. Leveraging spatial weight matrices, we detected provincial footprint spatial autocorrelation and further analyzed it using the spatial Durbin model. Results underscore that economic growth profoundly shapes the ecological footprint, but an explicit Environmental Kuznets Curve remains elusive. Both natural resource rents and industrial shifts considerably influence the ecological footprint. Distinguishing from earlier non-spatial studies, our research merges spatial panel data analysis, emphasizing the regulatory role of juxtaposing natural resource rents with industrial structure adjustment can decrease the impact of economic growth on the ecological footprint. Advocating robust policies that favor renewables over non-renewables is pivotal, emphasizing the imperative for rigorous environmental standards in sectors shifting to renewables.

Harnessing the energy transition from total dependence on fossil to renewable energy in the Arabian Gulf region, considering population, climate change impacts, ecological and carbon footprints, and United Nations’ Sustainable Development Goals

The aim of this research is to investigate various issues related to oil consumption and environmental impacts in the Gulf Cooperation Council (GCC) countries, in relation to population, climate change impacts, United Nations Sustainable Development Goals (UN’s SDGs), and ecological and carbon footprints. The GCC countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) are almost entirely dependent on fossil energy sources (oil and natural gas) domestically, industrially, commercially, economically, and transportation-wise. Although the total population of the GCC countries is around 60 million, making up only 0.76% of the world’s population (8 billion), they do consume 5.15 million barrels per day (bbl/d) of oil, forming nearly 5.8% of the world’s daily consumption, which is around 88.4 million bbl/d as of 2021. Moreover, daily per capita consumption of oil in the GCC countries is about 0.09 barrels, while it is about 0.06 barrels in the USA. These figures indicate that the GCC’s countries combined and per capita, although not industrialized and small in population, consume large quantities of oil, compared to other countries of the world that are industrialized and/or densely populated, such as the USA, India, Japan, Russia, and Germany. The high rates of oil consumption in the GCC countries, associated with the highest per capita ecological and carbon footprints worldwide, have led to negative impacts on the environment, climate, and public health. The results of this work show that some of the GCC countries have the highest per capita ecological and carbon footprints. Thus, the GCC countries should effectively reduce their dependence on fossil energy sources and gradually replace them with renewable energy sources, especially photovoltaic (PV) solar energy. Furthermore, the statistics presented in this article and the outcomes reached uncover that the GCC countries lag behind with regard to various indicators of the UN’s SDGs. This implies the GCC countries are not taking adequate actions to encounter environmental problems, in order to fulfill some of the UN’s SDGs by 2030.

Does renewable energy reduce per capita carbon emissions and per capita ecological footprint? New evidence from 130 countries

This study explores whether increasing renewable energy consumption can alleviate environmental pressures (per capita carbon emissions and per capita ecological footprint) and the heterogeneity of the effects of increasing renewable energy consumption on the environmental pressures of countries in different income groups. We analyze 130 countries and three income groups from 1992 to 2019 based on a panel threshold regression estimation approach. The results show that (i) There is a negative relationship between renewable energy consumption and per capita ecological footprint and per capita carbon emissions, indicating that renewable energy consumption alleviates environmental pressure. (ii) When renewable energy consumption increases, the negative effects of renewable energy on per capita ecological footprint and per capita carbon emissions become more significant. This means that the more renewable energy is developed, the more it helps to alleviate environmental pressure. (iii) The inhibitory effect of renewable energy consumption on per capita ecological footprint is more significant in low-income countries than in middle-income countries. This indicates that renewable energy is more effective in reducing environmental pressures in poor countries than in rich countries.

Economic complexity and ecological footprint: The role of energy structure, industrial structure, and labor force

Existing studies show the important influence of economic complexity index (ECI) on environmental quality, but do not consider the mediating effect of other key factors on the relationship between the two, thus ignoring the structural break and nonlinear characteristics of the relationship between ECI and environmental quality. To fill this research gap, this study constructs a decomposition framework and multiple panel threshold regression models based on an extended STIRPAT model using panel data from 36 OECD countries to explore the nonlinear relationship between ECI and ecological footprint (an indicator of environmental quality) in terms of three key mediators: energy consumption structure, industrial structure, and human capital. The results show that a 1% increase in economic complexity is associated with a 0.075% increase in ecological footprint per capita, and an increase in economic complexity is detrimental to environmental improvement. When energy consumption structure is used as the threshold variable, the correlation coefficient between ECI and ecological footprint per capita gradually shifts from positive to negative with an inverted U-shaped curve as the share of renewable energy consumption increases. In particular, when the share of renewable energy consumption is higher than 44.56%, ECI shows a negative correlation with ecological footprint, i.e., ECI promotes the improvement of environmental quality. When the industrial structure is used as the threshold variable, the coefficient change from the below-threshold stage to the above-threshold stage indicates that the reduction of per capita ecological footprint shrinks from 0.161% to 0.102% for each 1% increase in ECI. The increase in the human capital index suppresses the positive effect of ECI on the ecological footprint per capita, i.e., the technology effect mitigates the environmental pressure caused by ECI, and only a country with a human capital index above 2.60 is in the interval where the technology effect comes into play. Finally, targeted policy recommendations from the perspective of the energy structure, industrial structure, and labor force are proposed to mitigate the effects of economic complexity on environmental quality.

A Study on the Influencing Factors of China’s Ecological Footprint Based on EEMD–GeoDetector

Ecological footprint (EF) is used to measure the energy and resources that are consumed by human beings, and it is used to calculate the energy that ecological services can provide to determine the gap between human behavior and what the earth can tolerate so as to ensure that human activities and sustainable development fall within this range. Therefore, it is crucial to research the influencing factors of EF. In this study, the ensemble empirical mode decomposition (EEMD) method was used to decompose China’s per capita ecological footprint from 1961 to 2018 into four intrinsic mode functions (IMFs) and a residual (R) and to conduct factor detection and interaction detection on both each obtained sequence and the original sequence. In order to examine the contributing factors, 15 independent variables representing the economic, social, and environmental pillars of sustainable development were chosen. The outcome under the interaction factor is more logical than the result under the single factor. Under the interaction factor of climate, the short-term changes in the number of doctors per 1000 people, long-term population density, carbon dioxide emissions, and average life expectancy interact with each other and the trend in CO2 emissions to affect the change in ecological footprint.

Does the frequency of stochastic convergence in per capita ecological footprint matter?

Among the environmental economics research issues, the issue of convergence has received quite a lot of attention, which is also known as stationary analysis. In this research strand, whether shocks to the time series variable are permanent or temporary is tested via the unit root tests. In this study, based on the theory and empirical works of stochastic convergence, we evaluate the convergence for the BASIC member countries, including Brazil, South Africa, India, and China. We use a variety of methodologies to see whether the convergence of ecological footprint holds for these countries or not. We first use the wavelet decomposition technique to decompose the series into the short run, middle run, and long run, and then we run several unit root tests to confirm the stationarity property of the series. The methodologies implemented in this study allow us to apply econometric tests to the original series as well as to the decomposed series. The results of panel CIPS test demonstrate that the null hypothesis of unit root could be rejected for the short run but not for the middle and long run, implying that long-lasting impact might prevail due to any shocks to the ecological footprint in the middle and long run. The results for individual countries varied.

Convergence of per capita ecological footprint among BRICS-T countries: evidence from Fourier unit root test

In recent years there has been a great deal of research into environmental pollution using a variety of techniques in response to growing environmental concerns. Convergence analysis, one of these techniques, helps determine whether the developing countries will catch up with the rich countries in pollution using unit root tests. However, the vast majority of the research in the field has generally used conventional unit root tests. Since many economic series contain structural breaks, using unit root tests that account for structural breaks is essential for accurate prediction. More specifically, if the series has a fractional process, conventional unit root tests may erroneously conclude that the departure from linearity is permanent. Moreover, the existing literature mainly uses gas emissions, such as carbon dioxide, which represent pollution weakly. Therefore, we use per capita ecological footprint (EF hereafter) as a more comprehensive pollution indicator of environmental degradation. In this direction, the study aims to determine whether BRICS-T countries' EF converges to the average of the BRICS-T for the 1992–2017 period. Besides the ADF unit root test, we employed the Fourier ADF unit root test, which considers the structural breaks, and the Fractional Frequency Fourier ADF unit root test, which accounts for structural breaks by considering fractional values. Our results showed that EF converges in Russia and Turkey according to the conventional ADF test, in China and Russia according to the Fourier ADF test, and in Brazil and China according to the Fractional Fourier Frequency test.

How economic and geographical indicators affect dietary environmental footprint: Evidence from China

A sustainable diet is widely recognized as an effective way to solve environmental and healthy dilemmas. Due to economy improvement, food consumption is undergoing a dietary transition toward more animal-based products. However, very few studies explored how geographical locations are correlated with dietary environmental footprints. Here, we quantified the per capita ecological footprint (EFP) and Greenhouse gas (GHG) emissions of Chinese people’s food consumption during the 2015 to 2020 period. Our results showed that the southern residents with high per capita disposable income (PCDI) showed the highest EFP (0.596 ha) and GHG emissions (1946 kgCO2eq), and the northern residents with low PCDI showed the lowest EFP (0.368 ha) and GHG emissions (1260 kgCO2eq). The overconsumption of meat is severe in China, and southern high PCDI residents annually consumed 116.7% more than they need. The EFP and GHG emissions were significantly related to geographical locations (i.e., southern and northern areas), direct economic indicators (i.e., PCDI and food expenditure), and indirect economic indicators (i.e., urban and rural status, and East-Central-West areas) (all p < 0.01). We also showed that though not significant, the correlation coefficient between geographical locations and EFP (r = 0.52) exceeded the coefficient between direct economic indicators and EFP (r = 0.44/0.48), while both coefficients mentioned above were significantly higher than the coefficient between indirect economic indicators and EFP (r = 0.32/0.31). These findings suggest that, besides economic indicators, more attention should be paid to the geographical locations and the related dietary cultures to reduce the environmental impacts not only in China but also in other countries with distinct regional differences.

基于改进生态足迹模型的可持续发展评价——以北疆为例

PDF HTML阅读 XML下载 导出引用 引用提醒 基于改进生态足迹模型的可持续发展评价——以北疆为例 DOI: 10.5846/stxb202112203605 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（2020D04003） Sustainable development evaluation based on an improved ecological footprint model: a case study of northern Xinjiang Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:生态足迹评价体系，可以在一定程度上刻画区域社会经济发展对当地生态环境产生的影响，当前可持续发展研究的难点之一，便是如何更加真实的体现这种影响。立足于传统生态足迹模型，采用"一年一区一值"的参数方案计算区域当年均衡因子与产量因子，结合土地利用转移矩阵和建设用地流入量改进建设用地足迹算法，对北疆地区2005年、2010年、2015年、2018年生态足迹及生态承载力进行测度，并结合相关指数对研究区发展的可持续性进行评价。结果表明：①北疆生态足迹增涨3.5倍，且以能源增长为主导，生物生产性足迹贡献率大幅下降；人均生态足迹增长3.4倍，工业型城市生态足迹增长率及人均生态足迹增长率均高于其他类型城市。②研究区生态承载力呈现上升态势，除水域和草地外，其他地类承载力均呈上升态势，昌吉州与阿勒泰地区的总体承载力及人均承载力均呈下降态势。③北疆生态利用效率上涨1.32倍，各行政单元呈现农业及服务业型城市生态利用效率上升、工业型城市生态利用效率降低的态势，表明工业型城市生态足迹增速远高于经济增速。④各行政单元呈现生态赤字状态且不断加剧，总体及人均增速都呈现工业型 > 农业型 > 服务业型城市。整体而言，研究区系统安全性一般，处于协调发展状态，但存在由生态足迹激增引发安全性下降的风险，部分地州呈低协调甚至不协调状态，整体可持续发展性有所降低。 Abstract:Ecological footprint is a biologically productive land that can produce the materials needed to meet the productive needs of human life and absorb the waste generated by humans in the region. Ecological footprint evaluation system can describe the impact of regional social and economic development on local ecological environment to a certain extent, but one of the difficulties in current sustainable development research is how to more truly reflect such impact. Based on traditionally ecological footprint model, this study firstly calculates the equilibrium factor and yield factor by year and by subregion. We improved the construction land footprint algorithm through combining the land use transfer matrix. Finally measured the ecological footprint and ecological carrying capacity of Northern Xinjiang in 2005, 2010, 2015 and 2018, and evaluated the sustainability of development in the study area. The results showed that:(1) the ecological footprint of the Northern Xinjiang increased by 3.5 times, which was dominated by energy footprint, while the contribution of biological productivity footprint decreased significantly. Per capita ecological footprint increased by 3.4 times, and the growth rate of ecological footprint and per capita ecological footprint of industrial cities were both higher than other types of cities. (2) The ecological carrying capacity of the study area showed an upward trend except for water and grassland. The overall and per capita carrying capacity of Changji and Altay were both declining. (3) The ecological efficiency of Northern Xinjiang increased by 1.32 times. The units showed a trend of increasing ecological efficiency in agricultural and service-oriented cities and decreasing in industrial cities, indicated that the growth rate of ecological footprint of industrial cities was higher than the corresponding cities' economy. (4) The ecological deficit of each unit was increased, and the growth rate of overall and per capita showed a trend of industrial cities > agricultural cities > service-oriented cities. Overall, ecosystem security in the study area was at an average level, and the ecological system and economic system were in a coupling state. But there was a risk of security decline caused by the surge of ecological footprint. Some cities were in a low coupling or even decoupling state, and the overall sustainability was reduced. Therefore, in the future development process, government should combine national and regional policy guidance with our own geographic and resource advantages, actively optimize the industrial structure, improve the efficiency of resource utilization, to build a diversified, healthy and sustainable new development system. 参考文献 相似文献 引证文献

Assessing the Ecological Risks Based on the Three-Dimensional Ecological Footprint Model in Gansu Province

It has become a hot topic in sustainable development to determine how to use data series to predict the trajectory of ecological footprints (EFs), precisely map biocapacity (BC), and effectively analyze regional sustainability. The sustainability of the ecological system in Gansu province must be investigated because the province is situated in western China and serves as a significant economic and transportation hub. We used the EF model to compute the per capita EF and BC of Gansu province from 2010 to 2020. We created a three-dimensional ecological footprint (EF3D) model by incorporating the ecological footprint size (EFsize) and ecological footprint depth (EFdepth) into the EF model and the EF3D of Gansu province from 2010 to 2020 was measured. The EF3D value was estimated using the gray GM (1, 1) prediction model in order to determine the sustainability condition of Gansu province during the next ten years. Finally, the risk of ecosystem loss in the province of Gansu was ultimately assessed using an ecological risk model (EVR). The results show that Gansu province’s per capita EF and BC displayed generally rising trends and the province is experiencing unsustainable development. The region’s projected future consumption of natural capital was estimated by the results, and the EF3D of Gansu province is expected to increase significantly in the future. These findings have a certain reference value for adjusting the industrial structure and utilizing resources in Gansu province. Furthermore, these findings will assist Gansu province in achieving sustainable development policy recommendations.

Panel Estimation of the Environmental Kuznets Curve for CO2 Emissions and Ecological Footprint: Environmental Sustainability in Developing Countries

Abstract Research background: The relationship between the economy and the environment is one of the most frequently encountered issues recently. Today the issue of environmental sustainability is one of the problems faced by countries. Purpose: This study, it is aimed at investigating the relationship between economic and environmental variables. Research methodology: The existence of the environmental Kuznets curve theory, in other words, the inverted U-connection between per capita carbon dioxide emissions, per capita ecological footprint, and per capita GDP in the examples of 10 developing countries is examined. We analyzed annual balanced panel data covering the period 1992–2014 for an inverted U-link between carbon dioxide emissions and ecological footprint and per capita GDP. Westerlund’s cointegration test was applied as a cointegration test. The Common Correlated Effects Mean Group (CCEMG) and Augment Mean Group (AMG) estimator methods were applied for long-term parameter estimation. The Dumitrescu and Hurlin causality test was applied to determine the causal connections. Results: As a result of the study, a positive and significant effect of electricity consumption on carbon dioxide emission was determined in the long term in the model where the ecological footprint is the dependent variable. In the environmental Kuznets curve hypothesis, an inverted U-shaped relationship was determined. That is, the results confirming the existence of the environmental Kuznets curve have been determined. Finally, bidirectional causal links between carbon emissions and economic growth, between carbon dioxide emissions and the square of economic growth, and between carbon dioxide emissions and electricity consumption; It is observed between the ecological footprint and economic growth, between the ecological footprint and the square of economic growth, and between the ecological footprint and electricity consumption. It is expected that this article will make a significant contribution to the literature with the important results obtained by using both an ecological footprint and carbon dioxide emission as dependent variables. Novelty: In this study, unlike other studies, two models were created with both CO2 emissions and the ecological footprint data as environmental variables.

Can Renewable Energy and Export Help in Reducing Ecological Footprint of India? Empirical Evidence from Augmented ARDL Co-Integration and Dynamic ARDL Simulations

The objective of this study is to investigate the impact of exports, renewable energy, and industrialization on the ecological footprint (EF) of India over the period spanning from 1970–2017 by employing the newly developed augmented ARDL (A-ARDL) co-integration approach and the novel dynamic ARDL (D-ARDL) technique. The empirical results demonstrate that exports and renewable energy consumption reduce the EF, while industrialization intensifies the EF. More precisely, a 1% increase in export (renewable energy consumption) reduces the EF by 0.05% (0.09%). In addition, the short-run elasticity of the GDP is found to be larger than the long-run elasticity indicating the possibility of the existence of the Environmental Kuznets Curve (EKC) of the EF for India. The study indicates that the income effect and increased policy focus on renewable energy usage can be expected to reduce India’s per capita EF in the long run. Moreover, India’s export sector has been traditionally less energy intensive, which reflects in our findings of export growth leading to a reduction in EF. Based on the empirical findings, this study recommends some policy insights that may assist India to effectively reduce its ecological footprint.

Dynamic change and driving force of natural capital in Qinghai Province based on the three-dimensional ecological footprint, China

Natural capital is a basic condition for human survival, and its utilization evaluation is the core issue of regional sustainable development. Based upon the improved three-dimensional ecological footprint model, this study discusses the dynamic changes in natural capital time series and spatial patterns in Qinghai Province from 2011 to 2020. The driving factors of ecological footprint change were revealed using partial least squares (PLS). The results demonstrate that (1) from 2011 to 2020, the per capita ecological footprint of Qinghai Province will increase from 2.505 hm2/person to 3.125 hm2/person. The per capita ecological capacity is affected by resource endowment and is maintained at 3.982–4.160hm2/person, thus indicating a weak downward trend year by year. (2) During the study period, the per capita EFdepth, of Qinghai exhibited an overall growth trend and increased from 1.299 hm2/person to 1.419 hm2/person. The per capita EFsize was primarily affected by the ecological capacity and reached the highest value of 1.352hm2/person in 2019. The three-dimensional model demonstrates that the per capita EFsize (bottom area) changes slightly during the four periods. (3) Over the past 10 years, the capital flow occupancy rate of Qinghai Province has increased from 26.23 % to 30.90 % with an average annual growth rate of 1.65 %, this indicating a large potential for natural capital utilization. (4) The PLS model revealed that energy consumption, ecological construction, social consumption, population, and economic development are the primary factors affecting the increase in natural capital utilization in Qinghai Province. This study aims to provide a reference for promoting regional sustainable development goals, for achieving coordinated development of resources, the environment, and the social economy, and for accelerating the construction of ecological civilization.