Search Results (796)

This study employs k-means clustering to analyze local organizations responsible for land improvement in Greece, identifying four distinct groups with consistent geographic patterns but divergent financial and operational characteristics. By integrating unsupervised machine learning with spatial analysis, the research offers a novel perspective on irrigation water pricing and cost recovery. The findings reveal that organizations located on islands, despite high water costs due to limited rainfall and geographic isolation, tend to achieve relatively strong financial performance, indicating the presence of adaptive mechanisms that could inform broader policy strategies. In contrast, organizations managing extensive irrigable land or large volumes of water frequently show poor cost recovery, challenging assumptions about economies of scale and revealing inefficiencies in pricing or governance structures. The spatial coherence of the clusters underscores the importance of geography in shaping institutional outcomes, reaffirming that environmental and locational factors can offer greater explanatory power than algorithmic models alone. This highlights the need for water management policies that move beyond uniform national strategies and instead reflect regional climatic, infrastructural, and economic variability. The study suggests several policy directions, including targeted infrastructure investment, locally calibrated water pricing models, and performance benchmarking based on successful organizational practices. Although grounded in the Greek context, the methodology and insights are transferable to other European and Mediterranean regions facing similar water governance challenges. Recognizing the limitations of the current analysis—including gaps in data consistency and the exclusion of socio-environmental indicators—the study advocates for future research incorporating broader variables and international comparative approaches. Ultimately, it supports a hybrid policy framework that combines data-driven analysis with spatial intelligence to promote sustainability, equity, and financial viability in agricultural water management. Full article

Given the significant shifts in rural labor mobility patterns and their continuous influence on the transformation of the land factor market, it is crucial to understand the relationship between labor factor prices and land factor prices. This understanding is essential to keep land factor prices within a reasonable range. This study establishes a theoretical framework to investigate how migrant workers’ return shapes land price formation mechanisms. Using 2023 micro-level survey data from eight counties in Jiangsu Province, China, this study empirically examines how migrant workers’ return affects land transfer prices and its underlying mechanisms through OLS regression and instrumental variable approaches. The findings show that under the current pattern of labor mobility, the outflow factor alone is no longer sufficient to exert substantial downward pressure on land transfer prices. Instead, the localized return of labor has emerged as a key driver behind the rise in land transfer prices. This upward mechanism is primarily realized through the following pathways. First, factor substitution effect: this effect lowers labor prices and increases the relative marginal output value of land factors. Second, supply–demand effect: migrant workers’ return simultaneously increases land demand and reduces supply, intensifying market shortages and driving up transfer prices. Lastly, the results demonstrate that enhancing the stability of land tenure security or increasing local non-agricultural employment opportunities can mitigate the effect of rising land transfer prices caused by the migrant workers’ return. According to the study’s findings, stabilizing land factor prices depends on full non-agricultural employment for migrant workers. This underscores the significance of policies that encourage employment for returning rural labor. Full article

Transportation infrastructure is a fundamental driver of economic growth and regional connectivity; and the supply of this infrastructure is often assumed to reduce spatial disparities. This study investigates the impact of transportation accessibility on regional disparities in land prices across South Korea from 2010 to 2019. Using spatial econometric models and geographically weighted regression (GWR), this study evaluates how variations in transportation networks influence land price differentials between regions. The results confirm that transportation accessibility positively affects land prices; but GWR coefficients reveal substantial regional variations in the extent to which accessibility improvements drive land price growth. Furthermore, while the overall distribution of transportation accessibility remained relatively stable, its influence on land price appreciation varied significantly, contributing to a widening gap in land values between regions. These findings underscore the critical role of transportation infrastructure in shaping regional inequalities and highlight the need for more equitable transportation policies to mitigate spatial disparities and promote balanced regional development Full article

Elasmobranch species are considered a global conservation priority due to their susceptibility to fishing pressure. In the Madeira Archipelago, Northeastern Atlantic, most elasmobranch species are caught as bycatch in artisanal drifting longline fishery targeting scabbardfishes. All commercial elasmobranch landings carried out in this archipelago over three decades (1990–2020) were analysed, aiming to provide a reliable overview of Madeira’s elasmobranch fisheries and their evolution. A total of 2316 tonnes of elasmobranchs were landed during the study period, corresponding to approximately EUR 2.1 million in first-sale value. The most representative period occurred from 2003 to 2013, corresponding to 75.21% of the total elasmobranch landings. A general pattern of supply and demand was evident, with mean price values typically showing an inverse trend to landed tonnage. At the species level, Centrophorus squamosus appears as the dominant species, representing about 89% of the total elasmobranch species landed, followed by Prionace glauca, with approximately 3%. The high dominance of C. squamosus in the scabbardfish fishery raises significant ecological and management concerns, as this deep-water shark species is known for its vulnerability to overexploitation. Management measures currently in place need to be updated and ought to be based on studies on the type and size of hooks for each fishery, to ultimately infer about species-specific survival rates, as well as the fishing gears’ soak time. Moreover, studies on the enhancement of food supply through fisheries discards are still missing, even though it is highly likely that this input may alter the dynamics of marine food webs. Full article

This study examines Poland’s agricultural land market between 2009 and 2023 through fixed effects and spatial econometric models, highlighting economic and spatial determinants of land prices. Key results show that GDP per capita strongly increases land values (β = +0.699, p < 0.001), while agricultural gross value added (–2.698, p = 0.009), soil quality (–6.241, p < 0.001), and land turnover (–0.395, p < 0.001) are associated with lower prices. Spatial dependence is confirmed (λ = 0.74), revealing strong regional spillovers. The volume of state-owned WRSP land sales declined from 37.4 thousand hectares in 2015 to 3.1 thousand hectares in 2023, while non-market transfers, such as donations, exceeded 49,000 annually. Although these trends support farmland protection and family farms, they also reduce market mobility and hinder generational renewal. The findings call for more flexible, sustainability-oriented land governance that combines ecological performance, regional equity, and improved access for young farmers. Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article

With over 180 million tons produced annually and a global market exceeding 500 billion dollars, beer is one of the most widely consumed beverages in the world, thanks to its broad variety of styles, traditions, ingredients, and brewing techniques. However, behind this widespread popularity lies a potentially impactful production chain, whose environmental impacts remain underexplored, particularly within the craft segment. This research evaluates the sustainability of a hemp-based craft beer produced in the Lazio region (Italy) using an integrated approach that combines life cycle assessment with environmental impact monetization. The results indicate that the main impacts in beer production are related to global warming potential (0.916 kg CO₂ eq/L), terrestrial ecotoxicity (0.404 kg 1.4-DCB eq/L), land use (0.841 m²a crop eq/L), and fossil resource scarcity (0.211 kg oil eq/L), primarily due to malt production and hop transportation. Packaging analysis revealed that including environmental costs, aluminum cans may add an additional environmental cost of €0.80–1.60 per unit, while glass bottles, despite their weight, incur a lower additional cost. For a beer priced at €3.50, this would translate to a real cost of €4.30–5.10, reflecting a 22–45% increase. Improving sustainability in the brewing sector requires strategic actions, such as careful supplier selection and appropriate packaging choices. Overall, sustainability in brewing emerges as a balance between production needs, distribution impacts, and systemic decisions. Full article

Municipal sewage sludge, a by-product of urban wastewater treatment, is increasingly recognized to be a strategic resource rather than a disposal burden. Traditional management practices, such as landfilling, incineration, and land application, are facing growing limitations due to environmental risks, regulatory pressures, and the underuse of the sludge’s energy and nutrient potential. This review examines the evolution of sludge management, focusing on technologies that enable energy recovery and resource valorization. The transition from linear treatment systems toward integrated biorefineries is underway, combining biological, thermal, and chemical processes. Anaerobic digestion remains the most widely used energy-positive method, but it is significantly improved by processes such as thermal hydrolysis, hydrothermal carbonization, and wet oxidation. Among these, hydrothermal carbonization stands out for its scalability, energy efficiency, and phosphorus-rich hydrochar production, although implementation barriers remain. Economic feasibility is highly context-dependent, being shaped by capital costs, energy prices, product markets, and policy incentives. This review identifies key gaps, including the need for standardized treatment models, decentralized processing hubs, and safe residual management. Supportive regulation and economic instruments will be essential to facilitate widespread adoption. In conclusion, sustainable sludge management depends on modular, integrated systems that recover energy and nutrients while meeting environmental standards. A coordinated approach across technology, policy, and economics is vital to unlock the full value of this critical waste stream. Full article

Water resources have become a critical factor limiting agricultural development and ecological health in arid regions. The ecological efficiency of agricultural water use (EEAWU) serves as an indicator of the sustainable utilization of agricultural water resources, taking into account both economic output and environmental impact. This paper, grounded in the social–ecological system (SES) framework, integrates multidimensional variables related to social behavior, economic decision-making, and ecological constraints to construct an analytical system that examines the impact mechanism of farmers’ part-time employment on the EEAWU. Utilizing survey data from 448 farmers in the western Tarim River Basin, and employing the super-efficiency SBM model alongside Tobit regression for empirical analysis, the study reveals the following findings: (1) the degree of farmers’ part-time employment is significantly negatively correlated with EEAWU (β = −0.041, p < 0.05); (2) as the extent of part-time employment increases, farmers adversely affect EEAWU by altering agricultural labor allocation, adjusting crop structures, and inadequately adopting water-saving measures; (3) farm size plays a negative moderating role in the relationship between farmers’ part-time engagement and the EEAWU, where scale expansion can alleviate the EEAWU losses associated with part-time employment through cost-sharing and factor substitution mechanisms. Based on these findings, it is recommended to enhance the land transfer mechanism, promote agricultural social services, implement tiered water pricing and water-saving subsidy policies, optimize crop structures, and strengthen environmental regulations to improve EEAWU in arid regions. Full article

Urban green spaces (UGSs), including parks, forests, and community gardens, play a critical role in enhancing public health and well-being by providing essential ecosystem services such as improving air quality, reducing surface temperatures, and mitigating harmful substances. As urbanization accelerates, especially in rapidly growing cities like Jinan, China, the demand for UGSs is intensifying, necessitating careful urban planning to balance development and environmental protection. While previous studies have often focused on city-level green coverage, this study shifts the analytical focus from UGS as a whole to urban functional units (UFUs), allowing for a more detailed examination of how green space is distributed across different land use types. We investigate UGS changes in Jinan over the past two decades and assess the influence of socio-economic factors—such as housing prices, land use types, and building age—on UGS distribution within UFUs. Remote sensing technology was employed to analyze the spatiotemporal dynamics of UGS and its correlation with these variables. Our findings reveal a significant shift in UGS distribution, with parks and leisure areas becoming primary drivers of UGS expansion. This study also highlights the growing influence of economic factors, particularly housing prices, on UGS distribution in more affluent UFUs. Additionally, while UGS in Jinan has generally expanded, challenges remain in balancing green space with urban expansion, especially in commercial and residential UFUs. This paper contributes to a more nuanced understanding of UGS distribution by integrating the UFU framework and identifying socio-economic drivers—including housing prices, construction age, and land use type—that shape green space patterns in Jinan. Our findings demonstrate that the spatial pattern of UGS in Jinan mirrors socio-economic and land use disparities observed in other global cities, highlighting both the universality of these patterns and the need for targeted planning in rapidly urbanizing contexts. Full article

Forest carbon sink (FCS) is essential for achieving carbon neutrality and supporting sustainable development in ecologically fragile, resource-based cities such as those on the Loess Plateau. Despite the success of national afforestation programs, economic valuations of FCS at the city level remain limited. This study develops an integrated framework combining carbon stock estimation, regional carbon pricing, and net present value (NPV)-based valuation. Using Shenmu City in Shaanxi Province as a case study, forest carbon stocks from 2010 to 2023 are estimated based on the 2006 IPCC Guidelines. Future stocks (2024–2060) are projected using the GM (1,1) model. A dynamic pricing mechanism with a government-guaranteed floor price is applied under three offset scenarios (5%, 10%, 15%). The results show that Shenmu’s forest carbon stock could reach 20.67 million tonnes of CO₂ by 2060, and under a 15% offset scenario, the peak NPV reaches CNY 4.02 billion. Higher offset ratios increase FCS value by 18–22%, reflecting the growing scarcity of carbon credits. The pricing model improves market stability and investor confidence. This study provides a replicable approach for carbon sink valuation in semi-arid areas and offers policy insights aligned with SDG 13 (Climate Action) and SDG 15 (Life on Land). Full article

Income level is a key indicator of the standard of living and the economic efficiency of undertaken activities. This paper aims to evaluate the earnings of Polish dairy farmers compared to those in other economic sectors between 2005 and 2022. The analysis covered 1688 family-run farms that participated continuously in the FADN system throughout the study period, with particular emphasis on farms that expanded their dairy cow herds. The remuneration for the labour of farmers and their families was estimated ex post by subtracting the opportunity costs of owned land and capital from farm income. The alternative cost of engaging one’s own land was determined on the basis of actual rental prices for farmland occurring in the surveyed farm groups in the years analysed. This information is collected in the FADN system from which the studied group of farms was drawn. The basis for determining the alternative cost of involvement of own capital was the average interest rates on deposits for households, concluded for a period of 6 months to 1 year inclusive, reported by the National Bank of Poland. The analysed population was divided into seven groups based on the number of dairy cows maintained. The analysis focused on two three-year reference periods: 2005–2007 and 2020–2022. The results were compared with average salaries and wages in non-agricultural sectors of the economy. Structural changes in agriculture, increased productivity, and the expansion of production scale in dairy farms indicate a growing professionalisation of the sector. The rise in farm incomes during the analysed period contributed to a significant increase in the remuneration for farmers’ and their families’ labour. The highest growth in remuneration was observed among farms with the greatest production potential and scale. While in 2005–2007 the remuneration for labour in dairy farms was lower than in non-agricultural sectors, this situation changed in 2020–2022. During this latter period, the average remuneration for labour on dairy farms slightly exceeded the average salary and wages in other sectors of the economy. Full article

India’s revised nationally determined contribution at COP26 set a net-zero target for 2070, but the role of carbon dioxide removal (CDR) in achieving this goal remains unclear. This study quantifies the contribution of land-based CDR—bioenergy carbon capture and storage, biochar, and afforestation—in achieving India’s net-zero goal. Additionally, a stylised scenario explores an accelerated net-zero target by 2050 in India`s climate target. The global emission target is modelled to follow India’s climate ambition in both stylised scenarios. The results show that the ambitious 2050 net-zero pathway requires 56 GtCO₂ of cumulative novel CDR across the century, compared to 47 GtCO₂ under the 2070 scenario, with both requiring around 1 GtCO₂/year at net-zero. A higher ambitious pathway leads to increased economic costs, with a mid-century carbon price of USD 938, compared to USD 174 in the 2070 scenario. Without novel CDR methods, the cost of achieving net zero by 2050 quadruple. The accelerated 2050 net-zero pathway also intensifies land and water trade-offs, reducing land for crop production while increasing water demand for electricity and biomass. Despite these challenges, it limits end-of-century warming to 1.46 °C, compared to 1.79 °C under the 2070 scenario. These findings highlight the importance of clearly defined climate targets, scalable CDR strategies, and integrated resource management to balance climate ambition with sustainable development. Full article

As technological progress and population growth continue to drive rising energy demand, renewable energy has emerged as a key focus of the global energy transition due to its environmental sustainability. However, in suitability assessments and site selection for green energy projects such as photovoltaic (PV) power generation, key criteria such as supply–demand balance and land price are often inadequately considered, despite their direct impact on decision outcomes. Moreover, excessive reliance on expert judgment for weighting, along with the neglect of inter-criterion relationships, introduces uncertainty. Combined with the presence of ill-posed problems, these issues limit the practical value of the evaluation results. This study integrates economic cost–benefit analysis into the evaluation criteria system alongside climatic and geographical criteria, constructing a set of 11 spatial indicators, including global horizontal irradiation (GHI), land prices, and regional power demand, to support PV site selection. Furthermore, a comprehensive evaluation framework is proposed that combines geographic information systems (GIS), multi-criteria decision analysis (MCDA), fuzzy comprehensive evaluation (FCE), and machine learning (ML). The framework enables the collaborative optimization of expert-constrained and data-driven criteria weighting. A national suitability zoning map for PV power plants was developed and validated against actual construction cases. The results demonstrate that the proposed methodology outperforms traditional approaches, achieving a 0.1178 improvement in weight determination compared to expert-based methods, producing a photovoltaic suitability map that more accurately reflects actual construction trends, thereby providing better and more effective support for PV site planning. 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