Search Results (1,658)

The aim of this paper is to analyze the potential of circular economy in the context of increasing the supply of raw materials for modern economy with particular focus on the role of science and business. The article presents an approach consistent with the concept of sustainable development and fitting in with the implementation of four Sustainable Development Goals: Industry, Innovation, and Infrastructure (SDG 9), Responsible Consumption and Production (SDG 2), Climate Action (SDG 13), and Life on Land (SDG 15). An innovative approach to raw material supply sources is also presented. In addition, the potential of urban mining e-waste in meeting the demand for critical metals is emphasized. The paper presents barriers and challenges for using the potential of raw materials deposited in spoil heaps and landfills or in tailings ponds, with emphasis on the role of modern technologies in increasing the competitiveness of Polish industry. The necessity of a systemic approach to the topic of the circular economy was also emphasized, particularly regarding secondary raw materials as essential for securing critical resources. Full article

This study is situated at the critical stage of comprehensive implementation of China’s territorial spatial planning system, addressing the strategic need for planning evaluation and optimization. We innovatively construct a Computable General Equilibrium Model for China’s Territorial Spatial Planning (CTSPM-CHN) that integrates dual factors of construction land costs and energy consumption costs. Through designing two policy scenarios of rigid constraints and structural optimization, we systematically simulate and evaluate the dynamic impacts of different territorial spatial governance strategies on macroeconomic indicators, residents’ welfare, and carbon emissions, revealing the multidimensional effects and operational mechanisms of territorial spatial planning policies. The findings demonstrate the following: First, strict implementation of land use scale control from the National Territorial Planning Outline (2016–2030) could reduce carbon emission growth rate by 12.3% but would decrease annual GDP growth rate by 0.8%, reflecting the trade-off between environmental benefits and economic growth. Second, industrial land structure optimization generates significant synergistic effects, with simulation results showing that by 2035, total GDP under this scenario would increase by 4.8% compared to the rigid constraint scenario, while carbon emission intensity per unit GDP would decrease by 18.6%, confirming the crucial role of structural optimization in promoting high-quality development. Third, manufacturing land adjustment exhibits policy thresholds: moderate reduction could lower carbon emission peak by 9.5% without affecting economic stability, but excessive cuts would lead to a 2.3 percentage point decline in industrial added value. Based on systematic multi-scenario analysis, this study proposes optimized pathways for territorial spatial governance: the planning system should transition from scale control to a structural optimization paradigm, establishing a flexible governance mechanism incorporating anticipatory constraint indicators; simultaneously advance efficiency improvement in key sector land allocation and energy structure decarbonization, constructing a coordinated “space–energy” governance framework. These findings provide quantitative decision-making support for improving territorial spatial governance systems and advancing ecological civilization construction. Full article

Individual actions play a pivotal role in climate change, one of the most urgent global challenges, as daily behaviors generate substantial greenhouse gas emissions. Saudi Arabia, in particular, demonstrates its strong commitment to environmental sustainability through the Saudi Green Initiative and Middle East Green Initiative, aiming for net-zero emissions by 2060 and advancing reforestation, land conservation, and renewable energy under Vision 2030. However, many Saudi individuals remain unaware of the environmental consequences of their choices, including transportation, energy consumption, and lifestyle habits. To address this gap, this study developed GreenKSA, the first Arabic-supported gamified mobile application designed to promote pro-environmental behavior within the Saudi culture. The app integrates gamification elements grounded in Self-Determination Theory (SDT) and Trans-Theoretical Model (TTM) in an attempt to bridge the gap between theory and practice. GreenKSA delivers multimedia content—short videos and infographics—demonstrating sustainable routines in households, workplaces, and mobility. The design and user experience of GreenKSA were evaluated in a pilot study of 10 participants. The results indicated high usability (SUS = 91.25) and a positive overall user experience. By combining theory-driven design with culturally relevant gamification elements, this study contributes to digital sustainability interventions and aligns with the global Sustainable Development Goals SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action. Full article

Microbial lipid production from renewable carbon sources, particularly lignocellulosic hydrolysates, is a promising alternative to plant-derived oils and fats for food applications, as it can minimize the land use by utilizing agricultural wastes and byproducts from food production. In this context, a standard approach to prevent oxygen limitation at reduced air gassing rates during long-term aerobic microbial processes is to operate bioreactors at increased pressure for elevating the gas solubility in the fermentation broth. This study investigates the effect of absolute pressures of up to 2.5 bar on the conversion of the carbon sources (glucose, xylose, and acetate), growth, and lipid biosynthesis by Cutaneotrichosporon oleaginosus converting a synthetic nutrient-rich lignocellulosic hydrolysate at low air gassing rates of 0.1 vessel volume per minute (vvm). Increasing pressure delayed xylose uptake, reduced acetic acid consumption, and reduced biomass formation. Lipid accumulation decreased with increasing pressure, except for fermentations at 1.5 bar, which achieved a maximum lipid content of 83.6% (±1.6, w/w) (weight per weight in %). At an absolute pressure of 1.5 bar, a lipid yield from glucose, xylose, and acetic acid of 38% (w/w) was reached after 6 days of fermentation. The pressure sensitivity of C. oleaginosus may pose challenges on an industrial scale due to the dynamic changes in pressure when the yeast cells pass through the bioreactor. Increasing liquid heights in full-scale bioreactors will result in increased hydrostatic pressures at the bottom, substantially reducing lipid yields, e.g., to only 23% (w/w) at 2.0–2.5 bar, as shown in this study. However, further scale-up studies with dynamic pressure regimes (1–2.5 bar) may help to evaluate scale-up feasibility. Full article

The Citarum River Basin (DAS Citarum) in Indonesia faces significant challenges in waste management, necessitating a circular economy-based approach to reduce land-based pollution, which is critical for achieving the sustainability goals of the blue economy in the basin. This study addresses the complexity and inherent uncertainty in decision-making processes related to this challenge by developing a novel hybrid model, namely the Weighted Fuzzy N-Soft Set combined with the COmbinative Distance-based Assessment (CODAS) method. The model synergistically integrates the weighted 10R strategies in the circular economy, obtained via the Analytical Hierarchy Process (AHP), the capability of Fuzzy N-Soft Sets to represent uncertainty granularly, and the robust ranking mechanism of CODAS. Applied to a case study covering 16 types of waste in the Citarum River Basin, the model effectively processes expert assessments that are ambiguous regarding the 10R criteria. The results indicate that single-use plastics, particularly plastic bags (HDPE), styrofoam, transparent plastic sheets (PP), and plastic cups (PP), are the top priorities for intervention, in line with the high AHP weights for upstream strategies such as Refuse (0.2664) and Rethink (0.2361). Comparative analysis with alternative models, namely Fuzzy N-Soft Set-CODAS, Weighted Fuzzy N-Soft Set with row-column sum ranking, and Weighted Fuzzy N-Soft Set-TOPSIS, confirms the superiority of the proposed hybrid model in producing ecologically rational priorities, free from purely economic value biases. Further sensitivity analysis shows that the model remains highly robust across various weighting scenarios. This study concludes that the WFN-SS-CODAS framework provides a rigorous, data-driven, and reliable decision support tool for translating circular economy principles into actionable waste management priorities, directly supporting the restoration and sustainability goals of the blue economy in river basins. The findings suggest that targeting the high-priority waste types identified by the model addresses the dominant fraction of riverine pollution, indicating the potential for significant waste volume reduction. This research was conducted to directly contribute to achieving multiple targets under SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 14 (Life Below Water). Full article

This study proposes a lightweight framework for transferring pretrained land cover classification architectures without additional training. The system utilizes French IGN imagery and Korean UAV and aerial imagery. It employs FLAIR U-Net models with ResNet34 and MiTB5 backbones, along with the AI-HUB U-Net. The implementation consists of four sequential stages. First, we perform class mapping between heterogeneous schemes and unify coordinate systems. Second, a quadratic polynomial regression equation is constructed. This formula uses multispectral band statistics as hyperparameters and class-wise IoU as the dependent variable. Third, optimal parameters are identified using the stationary point condition of Response Surface Methodology (RSM). Fourth, the final land cover map is generated by fusing class-wise optimal results at the pixel level. Experimental results show that optimization is typically completed within 60 inferences. This procedure achieves IoU improvements of up to 67.86 percentage points compared to the baseline. For automated application, these optimized values from a source domain are successfully transferred to target areas. This includes transfers between high-altitude mountainous and low-lying coastal territories via proportional mapping. This capability demonstrates cross-regional and cross-platform generalization between ResNet34 and MiTB5. Statistical validation confirmed that the performance surface followed a systematic quadratic response. Adjusted R² values ranged from 0.706 to 0.999, with all p-values below 0.001. Consequently, the performance function is universally applicable across diverse geographic zones, spectral distributions, spatial resolutions, sensors, neural networks, and land cover classes. This approach achieves more than a 4000-fold reduction in computational resources compared to full model training, using only 32 to 150 tiles. Furthermore, the proposed technique demonstrates 10–74× superior resource efficiency (resource consumption per unit error reduction) over prior transfer learning schemes. Finally, this study presents a practical solution for inference and performance optimization of land cover semantic segmentation on standard commodity CPUs, while maintaining equivalent or superior IoU. Full article

Commercial smooth-hound sharks of the genus Mustelus are commonly landed and consumed in Mediterranean fisheries, raising concerns about potential human exposure to persistent contaminants. This study investigated the occurrence of organochlorine compounds (OCs), including hexachlorobenzene (HCB), dichlorodiphenyltrichloroethane (DDT) and its metabolites, and polychlorinated biphenyls (PCBs), together with per- and polyfluoroalkyl substances (PFAS), in muscle and liver tissues of Mustelus mustelus and Mustelus punctulatus collected in the waters of the Egadi Archipelago (central Mediterranean Sea). OCs were detected in all analyzed samples, with total PCB concentrations reaching higher values in liver compared to muscle tissues, reflecting tissue-specific accumulation and detoxification processes. PFAS were detected in all analyzed muscle samples (1.10–58.5 ng/g w.w.), with PFOS, PFOA and PFNA generally below current European regulatory thresholds, although isolated exceedances were observed. Stable isotope analysis (δ¹³C and δ¹⁵N) highlighted differences in trophic ecology between the two species and suggested that feeding habitat and trophic position may influence contaminant exposure patterns, particularly in M. punctulatus. The human health risk assessment, conducted as a screening-level evaluation, indicated potential concern associated with PCB concentrations in liver tissue, while risks associated with muscle consumption were generally lower. Overall, the integration of contaminant analysis and stable isotopes provides insights into organismal exposure pathways and supports the use of smooth-hound sharks as sentinels of contaminant presence in Mediterranean coastal ecosystems. Full article

The worldwide transition to renewable energy systems is motivated by diminishing fossil fuel availability and the intensifying consequences of climate change. This study presents a Mixed-Integer Linear Programming (MILP) model for designing and optimising the bio-fuel and electricity supply chain in Colombia, using sugarcane as the main feedstock and integrating microalgae cultivation in vinasse. Six alternative biorefinery configurations and four microalgae conversion pathways were evaluated to inform strategic planning. The optimisation results indicate that microalgae achieve higher energy yields per unit of land than sugarcane. Ethanol production from sugarcane could meet all of Colombia’s gasoline demand, while diesel and sustainable aviation fuel derived from microalgae could supply around 9% and 16%, respectively, of the country’s consumption. Further-more, pelletised bagasse emerges as a viable alternative to replace part of the coal used in thermoelectric plants. From an economic perspective, all scenarios achieve a positive net present value, confirming their profitability. Sensitivity analysis highlights the critical factors influencing the deployment of distilleries as ethanol price, algae productivity, and sugarcane cost. Furthermore, transportation costs play a decisive role in the geographic location of microalgae-based facilities and the distribution of their products. Full article

The behavior of the carbon cycle within the Land-Ocean Aquatic Continuum (LOAC) is shaped not only by aquatic processes but also by chemical interactions occurring at the atmosphere–water interface. In particular, the transport of acid rain precursors such as SO₂ and NO_x to surface waters via deposition can alter the water’s pH balance, thereby affecting Dissolved Inorganic Carbon (DIC) fractions and CO₂ emission potential. In this study, air quality measurements from three monitoring stations (Bosna, Karatay, and Meram) in Konya province of Türkiye, along with precipitation and temperature data from a representative meteorological station for the period 2021–2023, were analyzed using the Mann–Kendall Trend Test. Additionally, seasonal pH values of groundwater were examined, and their trends were compared with those of the other variables. The findings reveal striking differences on a station basis. At the Bosna station, while NO (Z = 10.80), NO₂ (Z = 9.47), and NO_x (Z = 10.04) showed strong increasing trends, O₃ decreased significantly (Z = −15.14). At the Karatay station, significant increasing trends were detected for CO (Z = 10.01), PM₁₀ (Z = 8.59), SO₂ (Z = 5.55), and NO_x (Z = 2.44), whereas O₃ exhibited a negative trend (Z = −6.54). At the Meram station, a significant decrease was observed in CO (Z = −11.63), while NO₂ showed an increasing trend (Z = 3.03). Analysis of meteorological series indicated no significant trend in precipitation (Z = −0.04), but a distinct increase in temperature (Z = 2.90, p < 0.01). These findings suggest that the increasing NO_x load in the Konya atmosphere accelerates O₃ consumption and, combined with rising temperatures, creates a potential for change in the carbon chemistry of aquatic systems. The results demonstrate that atmospheric pollutant trends constitute an indirect but significant pressure factor on the aquatic carbon cycle in semi-arid regions and highlight the necessity of integrating atmospheric processes into carbon budget analyses within the scope of LOAC. Full article

(1) Background: Rubus geoides Sm., a native species of southern Patagonia, faces increasing threats due to climate change and anthropogenic land-use changes. Historically widespread, its distribution has become restricted by overgrazing, urban expansion, extractive industries, and direct harvesting from natural populations driven by interest in its nutraceutical potential since the first European settlements. (2) Methods: To assess its resilience and conservation prospects, we analyzed the morphological variability, genetic diversity, and population structure, complemented by species distribution modeling under past and future climate scenarios. (3) Results: Our findings reveal moderate genetic differentiation and private alleles in specific populations, alongside significant variation in flowering phenology. Paternity analysis indicates a tendency toward self-pollination, although this conclusion is constrained by the limited number of microsatellite markers employed. These results suggest post-glacial dispersal patterns and highlight the species’ potential for expansion under certain climate scenarios. (4) Conclusions: This study provides critical insights for biodiversity conservation and sustainable land management, directly aligned with the UN Sustainable Development Goals SDG 15 (Life on Land). Indirectly, this study contributes to SDG 2 (Zero Hunger) by highlighting the importance of threatened species that hold value for human consumption and food security. Land-use changes, particularly mining and green hydrogen industry settlements, may represent stronger limitations to species expansion than climate change itself. Full article

Urban heat islands (UHIs) have intensified in rapidly urbanizing regions like New York, exacerbating thermal discomfort, public health risks, and energy consumption. While previous research has highlighted various environmental and socioeconomic contributors, most existing studies lack interpretable, fine-scale models capable of quantifying the effects of specific drivers—limiting their utility for targeted planning. To address this challenge, we develop an interpretable machine learning framework using Random Forest and XGBOOST to predict land surface temperature across 1800+ census tracts in the New York metropolitan area, incorporating vegetation indices, water proximity, urban morphology, and socioeconomic factors. Both models performed strongly (mean R² ≈ 0.90), with vegetation coverage and water proximity emerging as the most influential cooling factors, while built form features played supporting roles. Socioeconomic vulnerability indicators showed weak correlations with temperature, suggesting a relatively equitable thermal landscape. Optimization simulations further revealed that increasing vegetation to a threshold level could lower average surface temperatures by up to 6.38 °C, with additional but smaller gains achievable through adjustments to water access and urban form. These findings provide evidence-based guidance for climate-adaptive urban design and green infrastructure planning. More broadly, the study illustrates the potential of explainable machine learning to support data-driven environmental interventions in complex urban systems. Full article

To contribute to the United Nations’ 17 Sustainable Development Goals (SDGs), this study focuses on improving two specific goals—SDG 2 (Zero Hunger) and SDG 12 (Responsible Consumption and Production)—by examining how off-farm employment affects agricultural green total factor productivity (GTFP) in China, a key link between rural socio-economic transformation and agricultural sustainability. The results show that: First, the part-time operation of farmers significantly reduces the green total factor productivity, and the negative impact is more pronounced for off-farm employment households with higher non-agricultural income shares. It mainly stems from the redundant input of land and machinery elements. Second, the effect showed obvious heterogeneous effects at different stages of family development and land management scale. In addition, the scale effect of continuous agricultural production services and the technological synergy effect driven by the deepening of agricultural division of labor are the key to improving green total factor productivity and alleviating the negative effects of part-time operations. In summary, promoting sustainable agricultural practices requires the government to further deepen the reform of the land property rights system and optimize the agricultural socialization service system to ensure both food security and environmental sustainability. Full article

The advent of digital transformation, social learning, and the increasing use of artificial intelligence is driving requisite changes in the development of data centres, which are buildings designed to process and store data. Green innovation is an integral component of the sustainable development of data centre units. Solutions utilising green and blue infrastructure in data centres are being currently introduced with the objective of optimising energy consumption and reducing energy demand. The primary aim of the research is to analyse the utilisation of biomass production and blue–green infrastructure in data centres. The article provides a consolidated set of key performance indicators (KPIs): energy efficiency, water use, waste heat utilisation, renewable energy integration, hourly carbon-free matching, embodied carbon, and land use impacts, that can be used to compare different data centre designs. Traditional PUE-centric evaluations are broadened by added metrics such as biodiversity/green area, intensity, and 24/7 CFE, reflecting the broader, multi-dimensional sustainability challenges highlighted in the current literature. Twelve international case studies described in the literature were compared and the feasibility of the Polish pilot project in Michalowo was assessed to illustrate specific cases related to energy-saving solutions and the use of renewable energy sources in data centres. Full article

The study examines the recent transformation of traditional agricultural landscapes in the transition zone between Sierra de las Nieves and the Western Costa del Sol (Andalusia, Spain), one of the European regions where urban development pressure has reached its peak in replacing agricultural land with residential and tourism uses. Through a diachronic analysis of historical orthophotos (1956–2025), statistical sources (Agricultural Census, SIGPAC), and fieldwork, land-use changes and their impact on ecological functionality and territorial resilience are quantified. Results reveal a widespread loss of agricultural land—exceeding 68% overall—particularly severe in Benahavís, where more than 70% of farmland has disappeared, largely converted to urban areas. In contrast, in Istán and Ojén, the predominant trend is the renaturalization of abandoned agricultural land. These dynamics illustrate a coastal–inland territorial model that epitomizes the Mediterranean “territorial consumption” process, in which tourism-driven urbanization fragments traditional agroforestry mosaics. The study concludes that, despite their regression, traditional agricultural landscapes continue to play a key role in water regulation, soil conservation, and wildfire risk mitigation. Their restoration and maintenance are proposed as a replicable strategy for climate change adaptation and for reconciling territorial sustainability with economic development in other Mediterranean regions under intense urban pressure. Full article

Resource-based cities generally have large carbon-emission, and their carbon balance status is receiving more attention. Land use is a key factor in regulating regional carbon balance. To explore the relationship between land use patterns and carbon balance in resource-based cities, we selected nine cities in Anhui, a major energy province, as the research object. Based on the land use data (2000–2020) and the carbon emission coefficient method, we calculated the carbon emissions, carbon sequestration, and net carbon emissions to show their spatiotemporal evolution. The Logarithmic Mean Divisia Index (LMDI) method was employed to explore the driving factors of carbon emissions. The results indicated the following: (1) Net carbon emissions increased by 149.60%, and the growth rate had slowed down since 2015. Forestland constituted the primary carbon sink, whereas cropland was the dominant carbon source. The spatial distribution of carbon emissions and carbon sequestration was uneven. (2) The economic development level and energy consumption density were the principal factors of emission increases. Conversely, carbon emission intensity and land use economic efficiency served as the key mitigating factors. Full article