Sustainable Futures最新文献

This study compares the obstacles to the efficient integration of Information Technology into Transportation services. In order to comprehend the significance and connections between the identifying criteria, a hybrid Interpretive Structural Modelling (ISM) and Matrix Impact Cross Multiplication Applied to Classification (MICMAC) analysis was performed. Based on the experts’ opinion, Government factors, financial restrictions, sector restrictions, firm-related restrictions, and a shift in demand are the five factors that emerged. According to the ISM-based study model, the Information Technology - enabled applications in Transportation services operations is driven by governmental restrictions, then financial constraints, construction industry constraints, and firm-related constraints.

This study investigates the effects and transmission mechanisms of research and development (R & D) efficiency and the proportion of state-owned enterprises (SOEs) on carbon intensity using data from 30 Chinese provinces. The findings show that improving R & D efficiency can lower carbon intensity by promoting technological progress. However, more SOEs can increase carbon intensity by inhibiting technological progress. Thus, a higher proportion of SOEs can reduce the positive impact of R & D efficiency on decreasing carbon intensity. Additionally, the proportion of SOEs has a moderating effect that extends beyond provincial boundaries, resulting in spatial spillover due to strong interconnections between provinces. Heterogeneity analysis indicates that this moderating effect is particularly pronounced in the central and western regions, as well as in the electricity sector. This variation is due to differences in economic development levels and government priorities. Given the characteristics of China’s carbon intensity, policymakers should shift from a one size fits all carbon reduction policy to prioritizing enhancing R & D efficiency, boosting the innovation capabilities of SOEs, and considering spatial linkages and regional disparities.

Residential carbon emissions are an important component of anthropogenic carbon emissions. a significant increase in residential carbon emissions has become a reality under the global urbanization process. In this context, this paper built a feature combination value model based on NPP-VIIRS nighttime light remote sensing data, and divided urban-rural areas through breakpoint analysis method and reference comparison method. Then, explored the characteristics and differences of residential carbon emissions and per capita residential carbon emissions in nine different levels of cities in 2019 from the perspective of urban-rural areas. The results indicate that the residential carbon emissions and per capita residential carbon emissions shows the spatial distribution characteristics of first tier cities>second tier cities>third tier cities. Among them, the residential carbon emissions in Beijing, Guangzhou, Nanjing, Taiyuan show a distribution pattern of urban>urban-rural fringe>rural. The residential carbon emissions in Shijiazhuang, Wuxi, Xiangyang, Zunyi, Huai’an show a distribution pattern of rural>urban-rural fringe>urban. The per capita residential carbon emissions of urban areas are relatively low, while the per capita residential carbon emissions of rural areas are relatively high, show a distribution pattern of rural>urban-rural fringe >urban. The results can help the Chinese government balance the needs of urban-rural development in different levels of cities, so as to formulate targeted carbon emission reduction policies and achieve low-carbon goals.

To meet the net zero 2050 target in construction, a net-zero carbon public procurement policy is needed. This paper adopts a systematic review approach to explore the drivers and barriers to adopting net-zero carbon procurement. The top three drivers include developing sustainable public procurement policies, increasing investment in low-carbon procurements, and high demand for green construction projects. The top three barriers include inadequate budget for net-zero procurement implementation, weak capacity in public and private institutions to implement net-zero policies, and low stakeholder involvement. The paper's findings provide insights for stakeholders to effectively adopt net-zero carbon procurement for construction projects.

Studying land use and land cover (LULC) patterns, identifying driving forces, and simulating future scenarios are vital for grasping the complex connection between human actions and the environment. This helps in shaping sustainable land management strategies and preparing for the impacts of climate change. However, there is a necessity for a comprehensive system modeling framework that can accurately capture spatial and temporal changes in LULC, analyze driving mechanisms, and provide an integrated analysis of future simulations. In this paper, a comprehensive IM-RF-Markov-PLUS analysis framework is developed, focusing on the Fuxian Lake Basin (FLB) as a study area. The study aims to achieve accurate prediction of LULC by combining the microscopic LULC change trend and the contribution of macroscopic driving forces. The results show that: (1) The IM-RF-Markov-PLUS framework can explore the change patterns and driving mechanisms of LULC in the FLB, and accurately predict the LULC in the FLB. Compared with the PLUS model, its accuracy is improved by 2 %. (2) IM analysis reveals that LULC transformation in the FLB is both general and specific. Although the area of grassland, buildings, roads and structures converted to desert and bare land is minimal, it shows relatively tendentious and specific change characteristics. (3) Different land types are significantly affected by driving factors, with the expansion of LULCs is constrained by major factors. The distance to the lake has the most significant impact on the distribution of garden land, while the primary road has the greatest impact on the distribution of forestland. (4) Under different scenarios, the spatial heterogeneity of LULC patterns is obvious. In 2035, under baseline and economic development scenarios, cultivated land will decrease, while other LULC types will increase. Under the cultivated land protection scenario, cultivated land is protected, with an increase of 5.85 %. Under the ecological protection scenario, there is an increase in ecological land. The largest increase is in forestland, which increases by a total of 3.46 %. The ecological protection scenario presents a viable approach for ensuring the sustainable development of the FLB. The results of this paper may serve as a reliable foundation for implementing LULC strategies in the FLB and offer guidance for crafting sustainable development regulations at the regional level.

The complexity of a sustainable economy is rooted in its socio-economic and environmental intricacies, particularly in formulating pathways for the harmonious integration of these parameters. This study introduces an extended input-output analysis and a multi-objective optimisation framework designed to discern trajectories for reducing CO₂ emissions while simultaneously maximising GDP and employment. The economic alterations are evaluated through metrics facilitating the examination of both direct and indirect consequences stemming from perturbations within the economy. The focus of this research centres on the French economy, concentrating on pivotal sectors where reducing demand could yield the greatest reduction in CO₂ emissions with minimal socio-economic ramifications. Additionally, a model is outlined for energy substitution, wherein fossil fuels in the French electricity mix are supplanted with clean energies. The ensuing effects of such a model on emission reduction pathways are scrutinised, followed by a comparison with the baseline case study.

This study examines the financial implications of carbon pricing policies within the Knightian uncertainty framework. Employing a dynamic behavioural credit risk model driven by Lévy jump-diffusion, we scrutinise how carbon pricing uncertainty influences default probability and securities value. We explore investors' strategic responses to ambiguity and assess their impact on their investment decisions. Our findings reveal that carbon pricing uncertainty exacerbates the margin of default risk, has a moderating effect on stock value, and makes investors more cautious, thereby altering corporate capital structures. This study contributes to the discourse on carbon credit risk assessment and sustainable finance by addressing policy-driven uncertainties in the financial markets.

The acceleration of global urbanization has intensified land use activities, which threaten the ecological environment and hinder the achievement of sustainable socioeconomic development goals. With the background of continuous land use expansion, the reasonable management of land use and ecological protection has increasingly become an important issue. This study constructs an ecological security (ES) index to evaluate the ES pattern, and employs the Future Land-Use Simulation (FLUS) model for multi-scenario simulation of land use patterns in mountainous areas. The results showed that from 2000 to 2020, cultivated land and grassland showed a sharp decrease, with areas of −128.64 and −228.18 km² respectively, while forest land, urban land, and other construction land increased, with areas of 116.12, 31.21, and 120.69 km² respectively. Over time, the mountainous areas mainly exhibited low and moderate ES patterns. Furthermore, for 2020–2030, under the natural development scenario, cultivated land, forest land, and grassland will show a decrease, while urban and other construction land will show a sharp increase. In contrast, under the ecological protection scenario, ecological land will show significant increase, and the patch expansion of urban construction land will be smaller. These results confirm the positive contribution of ES protection effects to improving the land use development, and support insightful guidance for formulating policies on ecological management in mountainous areas.

This study explores the impact of supply chain integration, management commitment, and sustainable supply chain practices on the performance of non-profit organizations in Afghanistan. Using Structural Equation Modeling (SEM) and Fuzzy-set Qualitative Comparative Analysis (FsQCA) with 169 participants, it finds that supply chain integration enhances sustainable supply chain practices and overall performance. Management commitment improves sustainable supply chain practice, while supply chain challenges significantly affect organizational performance. FsQCA reveals key factors like sustainable supply chain practices and management commitment, highlighting their contribution to positive outcomes. Overcoming supply chain challenges within an integrated framework is crucial for non-profit performance enhancement.

This study evaluates the effects of time resolution on the optimization results of a renewable energy system for an off-grid island. The assessment uses a multi-objective genetic algorithm (MOGA) applied to Tilos Island in Greece. Three objective functions—levelized cost of electricity (LCOE), renewable ratio (RR), and profit—are considered across four distinct scenarios with six variables representing the number of renewable technologies. These cases are implemented using three time resolutions: minute-by-minute, 15-minute, and hourly. A significant difference in results is observed based on the time resolution used. With hourly data optimization, 100 % renewable energy coverage is achievable at Tilos’ current diesel generator cost (0.46 $/kWh). However, using minute-by-minute data, renewable energy coverage ranges from 85.87 % to 95.64 %, depending on the scenario. The primary reason for this discrepancy is the volatile nature of demand and power generation on Tilos Island. The analysis further indicates that the differences between minute-by-minute and hourly optimization diminish as the volatility of the input data to the algorithm decreases.