Search Results (394)

The transition to green energy in the transport sector is becoming a priority in the context of global climate challenges and the European Green Deal. This paper investigates the development of alternative fuelling stations, particularly electric vehicle (EV) charging infrastructure and hydrogen stations, across EU countries with a focus on Poland. It combines a policy and technology overview with a quantitative scientific analysis, offering a multidimensional perspective on green infrastructure deployment. A Pearson correlation analysis reveals significant links between charging station density and both GDP per capita and the share of renewable energy. The study introduces an original Infrastructure Accessibility Index (IAI) to compare infrastructure availability across EU member states and models Poland’s EV charging station demand up to 2030 under multiple growth scenarios. Furthermore, the article provides a comprehensive overview of biofuels, including first-, second-, and third-generation technologies, and highlights recent advances in hydrogen and renewable electricity integration. Emphasis is placed on life cycle considerations, energy source sustainability, and economic implications. The findings support policy development toward zero-emission mobility and the decarbonisation of transport systems, offering recommendations for infrastructure expansion and energy diversification strategies. Full article

This article introduces the Index of Distributive and Developmental Outlook (IDDO), a composite indicator designed to jointly assess economic performance and income inequality across EU-27 Member States. While GDP per capita is widely used to evaluate national prosperity, and the Gini coefficient captures income distribution, their separate use often obscures the interaction between growth and equity—an essential dimension of sustainable development. To address this gap, the IDDO integrates normalized values of both indicators using arithmetic and geometric means. The study applies the IDDO to a longitudinal dataset covering the years 2005, 2014, and 2024, allowing for comparative and temporal analysis. Based on IDDO scores, countries are classified into four development types: balanced development, growth with inequality, equity with stagnation, and dual vulnerability. Results show that while some Member States, such as Luxembourg, Czechia, and Slovenia, maintain consistently high IDDO levels, others—including Bulgaria, Romania, and Latvia—exhibit persistent challenges in aligning growth with equitable outcomes. The findings underscore the need for cohesion policies that prioritize not only economic convergence but also distributive fairness. The IDDO provides a practical and adaptable tool for diagnosing development patterns, benchmarking performance, and informing policy design within the EU framework. Full article

The measurement of national well-being has become central to both academic and policy debates, particularly within the framework of sustainable development. In this context, this study investigates the relationship between macroeconomic conditions and subjective well-being in Portugal. Using annual data from 2004 to 2022, we explore the effects of GDP per capita, unemployment, and inflation on the Global Well-Being Index (GWBI). Employing ordinary least squares (OLS) regression, the results indicate a significant positive relationship between GDP per capita and subjective well-being, while inflation is negatively associated. Contrary to expectations, the unemployment rate showed a positive and significant association with the GWBI. This counterintuitive result may reflect institutional buffering effects, such as social safety nets, strong family structures, or lagged responses in perceptions of well-being. Similar patterns were observed in other southern European countries with strong informal social support systems. These findings contribute to a deeper understanding of how economic indicators relate to perceived well-being, particularly in the context of a southern European country. The study offers relevant insights for public policy, including the alignment of macroeconomic management with the Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being) and SDG 8 (Decent Work and Economic Growth). Full article

This article examines how research-and-development (R&D) expenditure—as a share of GDP—both in total and disaggregated by sector (business enterprise and government)—shapes key socioeconomic outcomes in the EU-27. Drawing on Eurostat panel data for 2013–2022, we estimate fixed- and random-effects models with sector-specific lags. Business R&D expenditure is associated with lower female and male unemployment and faster GDP growth. Government R&D expenditure, by contrast, widens the gender pay gap and dampens GDP per capita after two years, although it attracts foreign direct investment in the short and medium term. The diminishing impact of R&D over time underscores the need for policies that sustain innovation benefits. Full article

Happiness is defined as well-being and contentment with life. The growing imperative to evaluate well-being beyond economic growth alone has led to the formulation of holistic indices that better reflect quality of life and sustainable development goals. This has resulted in the emergence of the Happiness Score (HS), which adopts a more holistic and human-centred perspective on development and well-being. The present study takes the Happiness Score as a basis for the identification of some of the main determinants of happiness in an empirical and data-driven perspective. To this end, data from 145 countries was analysed, using statistical methodologies such as Generalised Linear Models (GLM), Principal Component Analysis (PCA), fuzzy set Qualitative Comparison Analysis (fsQCA) and the decision tree machine learning approach. A range of indices were considered to translate the reality of countries in different socio-economic dimensions, the level of development of each country, and the continent to which it belongs. The African continent demonstrates substantial disparities across virtually all variables and is frequently associated with the most unfavourable values for each index. The indicators that exerted the most profound influence on happiness were identified as the freedom to make life choices, literacy rate, and Gross Domestic Product (GDP) per capita. These results inform policy strategies aligned with sustainable development, emphasising that enhancing happiness requires multidimensional action beyond economic indicators—particularly in low- and middle-income countries. Full article

Fine particulate matter (PM_2.5) plays a major role in haze, and studying its spatio-temporal dynamics and influencing factors is crucial for improving air quality. However, previous studies have often obscured the spatio-temporal interactions of PM_2.5 and neglected local spatio-temporal differences in influencing factors. To address these limitations, this research utilized PM_2.5 concentration data derived from satellite remote sensing and employed exploratory spatio-temporal data analysis (ESTDA) methods to investigate the spatio-temporal evolution patterns of PM_2.5 in Chinese cities from 2000 to 2021. Furthermore, the effects of natural environmental and socioeconomic factors on PM_2.5 were analyzed from both global and local perspectives using a spatial econometric model and the geographically and temporally weighted regression (GTWR) model. Key findings include (1) The annual value of PM_2.5 from 2000 to 2021 ranged between 27.4 and 42.6 µg/m³, exhibiting a “bimodal” variation trend and phased evolutionary characteristics. Spatially, higher concentrations were observed in the central and eastern regions, as well as along the northwestern border, while lower concentrations were prevalent in other areas. (2) The spatial–temporal distribution of PM_2.5 was generally stable, demonstrating a strong spatial dependence during its growth process, with significant path dependence characteristics in local spatial clusters of PM_2.5. (3) Precipitation, temperature, wind speed, and the Normalized Difference Vegetation Index (NDVI) significantly reduced PM_2.5 levels, whereas relative humidity, per capita Gross Domestic Product (GDP), industrialization level, and energy consumption exerted positive effects. These factors exhibited distinct local spatio-temporal variations. These findings aim to provide scientific evidence for the implementation of coordinated regional efforts to reduce air pollution across China. Full article

The United Arab Emirates has become increasingly concerned about carbon dioxide emissions due to their impact on climate change and the environment, as it is one of the top ten world oil producers. This reflects its recognition of the need for sustainable development. Therefore, this research aims to study the dynamic impact of economic growth, urbanization, energy consumption, and economic openness on CO₂ emissions, during the period 1975–2022. To capture these effects, a novel dynamic ARDL is employed to separate the impact of each variable separately. The results indicate that the effect of GDP per capita on carbon emissions is negative, as a 1% increase in economic growth leads to a decrease in carbon dioxide emissions by 0.6%. Moreover, the findings confirm that the UAE economy does not apply to the Kuznets curve in developing countries. Furthermore, the impact of energy consumption, urbanization, and trade openness is positive on CO₂ emissions, as a 1% increase in each raises CO₂ by 0.17%, 11.6%, and 1.2%, respectively. These findings are important for decision makers in the environmental field to make decisions to reduce carbon emissions by altering the impact of economic variables and spread awareness towards reducing carbon emissions. Full article

This study explores the relationship between renewable and non-renewable energy consumption, economic growth (EG), and ecological footprint (EF) in Poland’s top 18 energy-importing countries from 2000 to 2022. While the energy-growth-environment nexus is well-studied, limited attention has been paid to how a single major energy-exporting country influences sustainability in its trade partners, a gap this study aims to fill. A panel dataset was constructed using five key variables: real GDP per capita, Poland’s fuel exports, ecological footprint per capita, renewable energy consumption, and primary energy consumption per capita. Methodologically, the study employs panel cointegration techniques, including FMOL and DOLS estimators for long-run analysis, as well as the VECM and Granger causality tests for the short run. The study’s main contribution lies in its novel focus on Poland’s export influence and the application of advanced econometric models to examine long-run and short-run effects. Results indicate a stable long-run cointegration relationship. Specifically, a 1% increase in renewable energy use is associated with a 0.0219% rise in GDP per capita. Additionally, Poland’s fuel exports and ecological footprint positively impact growth, whereas primary energy use is statistically insignificant. These findings offer practical implications for policymakers in Poland and its trading partners aiming to align energy trade with sustainability goals. Full article

This study aims to evaluate environmental performance indicators and eco-controls in the poultry production chain in Goiás, with a focus on forest management, waste generation, water resources, energy use, emissions, and environmental accounting. A mixed-methods approach was used, combining qualitative and quantitative data from 13 agro-industrial companies, 230 farms, and 816 broiler houses. The results highlight the role of environmental management accounting (EMA) in monitoring and improving environmental practices, supporting continuous performance assessment. Econometric analysis revealed a positive link between sustainability practices and economic growth, as measured by GDP per capita. However, productive capacity and energy efficiency showed no significant impact at the 5% level. The study limitations include the focus on a single region and industry, which may limit the generalizability of the findings. Future research should expand to other chains and regions to assess broader applicability and explore the public policy impacts on environmental sustainability, as well as the impact of public policies on environmental sustainability within the sector. Full article

In the face of increasingly complex urban challenges, a critical question arises: can urban ecosystems maintain resilience, vitality, and sustainability when confronted with external threats and pressures? Taking Kunming—a plateau-mountainous city in China—as a case study, this research constructs an urban ecosystem resilience (UER) assessment model based on the DPSIR (Driving forces, Pressures, States, Impacts, and Responses) framework. A total of 25 indicators were selected via questionnaire surveys, covering five dimensions: driving forces such as natural population growth, annual GDP growth, urbanization level, urban population density, and resident consumption price growth; pressures including per capita farmland, per capita urban construction land, land reclamation and cultivation rate, proportion of natural disaster-stricken areas, and unit GDP energy consumption; states measured by Evenness Index (EI), Shannon Diversity Index (SHDI), Aggregation Index (AI), Interspersion and Juxtaposition Index (IJI), Landscape Shape Index (LSI), and Normalized Vegetation Index (NDVI); impacts involving per capita GDP, economic density, per capita disposable income growth, per capita green space area, and per capita water resources; and responses including proportion of natural reserve areas, proportion of environmental protection investment to GDP, overall utilization of industrial solid waste, and afforestation area. Based on remote sensing and other data, indicator values were calculated for 2006, 2011, and 2016. The entire-array polygon indicator method was used to visualize indicator interactions and derive composite resilience index values, all of which remained below 0.25—indicating a persistent low-resilience state, marked by sustained economic growth, frequent natural disasters, and declining ecological self-recovery capacity. Forecasting results suggest that, under current development trajectories, Kunming’s UER will remain low over the next decade. This study is the first to integrate the DPSIR framework, entire-array polygon indicator method, and Grey System Forecasting Model into the evaluation and prediction of urban ecosystem resilience in plateau-mountainous cities. The findings highlight the ecosystem’s inherent capacities for self-organization, adaptation, learning, and innovation and reveal its nested, multi-scalar resilience structure. The DPSIR-based framework not only reflects the complex human–nature interactions in urban systems but also identifies key drivers and enables the prediction of future resilience patterns—providing valuable insights for sustainable urban development. Full article

The aim of this research is to determine the significance of the impact of selected environmental protection indicators, with a focus on waste management, on the sustainability of economic growth in EU countries (21 member states) over the period 2013–2022. To conduct this analysis, four independent variables were selected, belonging to the domains of waste management the (recycling rate of municipal waste and recycling rate of packaging waste by type of packaging) and secondary raw material management (the circular material use rate and trade in recyclable raw materials, imports from outside the EU27). Sustainable economic growth was measured by gross domestic product per capita (GDP per capita), which serves as the dependent variable in this study. The aforementioned independent variables can also be categorized as circular economy (CE) indicators, which have been gaining increasing relevance in the EU context. Using a panel regression analysis, the potential influence of CE indicators on sustainable economic growth was examined both over time and across entities, through the lens of waste management. The statistical analysis was conducted by applying four econometric models: pooled OLS (POLS), fixed effects (FEs), random effects (REs), and mixed effects (MEs). The results of the analysis confirmed several specific hypotheses (depending on the model used), which posit a statistically significant positive impact of CE variables on GDP per capita. Full article

Water plays a critical role in ensuring sustainable food security, particularly in the face of increasing freshwater scarcity and climate variability. This study examines virtual water use and virtual water trade in Ghana’s vegetable production sector over a 30-year period (1994–2023), focusing on four key crops: tomato, pepper, onion, and eggplant. Using secondary data on production volumes, trade flows, and virtual water content, the research quantifies imported and exported virtual water volumes and assesses net virtual water trends. The results reveal a substantial increase in virtual water use for most crops, with the exception of pepper, which experienced a marked decline. Onion and tomato are identified as the dominant contributors to both imports and exports of virtual water, while pepper and eggplant play relatively minor roles. The study finds that Ghana is a net importer of virtual water in vegetable trade, emphasizing the need for integrated water resource management to balance agricultural growth with water sustainability. A gravity model analysis was applied to identify the primary determinants of virtual water trade, revealing that GDP per capita, population size, distance, land availability, virtual water use, and border-sharing significantly influence trade patterns. The findings suggest that enhancing domestic production capacity and promoting efficient water use practices can reduce Ghana’s reliance on imports and improve resilience against water-related risks. This research provides valuable insights for policymakers, researchers, and practitioners aiming to develop sustainable water and food systems in Ghana and similar contexts. Full article

This study examined how green innovation (GIN), environmental governance (EGR), and renewable energy transition (RET) influence trade-adjusted resource footprints (proxied by material footprint, MFP) in the top 15 Sub-Saharan African (SSA) countries from 1970 to 2022. After confirming the cross-sectional dependence and slope heterogeneity in the dataset, second-generation panel econometric techniques, including the cross-sectionally augmented Dickey–Fuller (CADF) unit root test and Kao cointegration test, were employed to establish stationarity and long-run equilibrium relationships. The Method of Moments Quantile Regression (MMQR) revealed heterogeneous effects across quantiles: GIN exhibited a positive impact on MFP, intensifying at higher quantiles (resource-intensive economies), while GDP per capita (GDPC) reduced MFP, with effects strengthening as quantiles raised. Conversely, EGR and RET exacerbated MFP across all quantiles, suggesting that governance and energy policies may inadvertently spur resource exploitation in SSA’s transitional economies. The Dumitrescu–Hurlin (D-H) causality test confirmed a unidirectional relationship from all independent variables to MFP, highlighting the need for integrated policies to decouple growth from material consumption. This suggests that while governance, innovation, and renewable energy transition influence resource footprints, MFP does not, in turn, impact these factors, reinforcing the importance of proactive policy interventions. Full article

It is crucial to clarify the relationship between ecological industry development and ecological civilization construction, as well as their driving forces, to promote high-quality local development. The ecological environment of the karst region is fragile, and it faces a contradiction between ecological preservation and economic advancement. Coordinating the relationship between economic development and ecological protection is crucial for achieving sustainable development in rural karst regions. This study identified karst characteristics in Guizhou province, China, by constructing an index system for ecological industry development and civilization construction. It employed the entropy weight method to calculate a comprehensive score and utilized a coupling coordination model to analyze interactions and symbiotic coordination. Finally, a linear regression analysis model was employed to analyze the impact of ecological industrial development on the construction of ecological civilization. The results indicate the following: (1) The ecological industry and ecological civilization construction levels exhibited a relatively stable growth trajectory across three research areas from 2011 to 2021, with the ecological civilization construction index outperforming the ecological industry development index. (2) The correlation analysis indicated a relationship between the two indices in the research areas, and the divergence trend among the three research areas rose in a uniform direction, indicating a strong positive correlation between the two indices. From the perspective of the coupling degree (C), the degree of coupling between ecological industry and ecological civilization construction in the three research areas exceeded 0.9, indicating a high level of coordination. This suggests that ecological civilization construction and ecological industry in these research areas are effectively coordinated and exist in a state of harmonious co-promotion. There were differences from the coupling coordination degree (D) perspective, but they increased in the three research areas. (3) The regression analysis results indicate that the per capita agricultural output value, per capita forestry output value, per capita forage industry output value, industrial solid waste utilization rate, energy consumption per unit of GDP, tourism income, rocky desertification level, and proportion of the labor force population with a high school education or higher significantly contribute to the development of ecological civilization. The per capita forestry output value greatly advances ecological civilization, significantly enhancing ecological culture and security. The coefficients are 0.0354 and 0.0393, respectively, indicating that a 1% rise in the per capita forestry output value results in increases of 0.0354% and 0.0393% in the ecological culture and security indices. Full article

This study examines the impact of macroeconomic and ESG (Environmental, Social, and Governance) factors on meat consumption in EU countries through a behavioral economics framework. Using panel data from 27 EU countries (2000–2021), the analysis applies Fixed Effects (FE), Random Effects (RE), and Generalized Estimating Equations (GEE) models to identify key drivers of meat consumption. The results reveal that GDP PPP (purchasing power parity) per capita, livestock availability, and methane emissions have a significant positive impact on meat consumption, reflecting the role of economic prosperity and agricultural production in dietary choices. In contrast, unemployment and inflation negatively influence meat consumption, highlighting the importance of economic stability. The GEE model, which corrects for autocorrelation, confirms that methane emissions and GDP PPP per capita remain significant predictors, suggesting that economic growth and environmental impact are critical determinants of dietary behavior. These findings underscore the complex interplay between economic development, sustainability, and consumer behavior, providing valuable insights for policymakers aiming to balance economic growth with environmental goals in the EU. Full article