Search Results (696)

The advancement of sustainable economic development has become a strategic imperative for enterprises aiming to combine financial development with environmental and social responsibility. In this regard, strategic enterprise management (SEM) has a critical role in incorporating the aspects of sustainability into decision making. The present paper suggests a multicriteria decision-making framework that utilizes fuzzy TOPSIS in assessing and ranking sustainability integration aspects in organizations. By considering the intrinsic vagueness of sustainability analysis, the fuzzy TOPSIS model enables the systematic analysis of environmental, social, and governance (ESG) factors by companies for ensuring their alignment to corporate strategic goals. A case study of a major international airport in Greece demonstrates how the proposed methodology assists strategic choice making, balancing economic viability and sustainable value creation. The results show primary trade-offs among human capital investment, environmental footprint reduction, and stakeholder communication, demonstrating how companies can enhance long-term resilience and competitiveness. This research adds to the existing literature by giving an integrated strategic enterprise management framework with the use of decision support instruments to foster sustainability-oriented corporate governance and strategic efficacy. The suggested model is flexible and can be applied in any industry, hence being a benchmark for sustainable business practice. This paper contributes to the literature by integrating fuzzy TOPSIS with balanced scorecard in the context of airport strategic sustainability management, offering both methodological advancement and empirical insights for transport and supply chain enterprises. Full article

The paper explores the pressing issue of energy consumption in machine learning (ML) models and their environmental footprint. As ML technologies, especially large-scale models, continue to surge in popularity, their escalating energy demands and corresponding CO₂ emissions are drawing critical attention. The article dives into innovative strategies to curb energy use in ML applications without compromising—and often even enhancing—model performance. Key techniques, such as model compression, pruning, quantization, and cutting-edge hardware design, take center stage in the discussion. Beyond operational energy use, the paper spotlights a pivotal yet often overlooked factor: the substantial emissions tied to the production of ML hardware. In many cases, these emissions eclipse those from operational activities, underscoring the immense potential of optimizing manufacturing processes to drive meaningful environmental impact. The narrative reinforces the urgency of relentless advancements in energy efficiency across the IT sector, with machine learning and data science leading the charge. Furthermore, deploying ML to streamline energy use in other domains like industry and transportation amplifies these benefits, creating a ripple effect of positive environmental outcomes. The paper culminates in a compelling call to action: adopt a dual-pronged strategy that tackles both operational energy efficiency and the carbon intensity of hardware production. By embracing this holistic approach, the artificial intelligence (AI) sector can play a transformative role in global sustainability efforts, slashing its carbon footprint and driving momentum toward a greener future. Full article

Despite global efforts to address climate change, carbon dioxide (CO₂) emissions are still on the rise. While carbon dioxide is essential for life on Earth, its increasing concentration due to human activities poses severe environmental and health risks. Therefore, accurately and efficiently predicting CO₂ emissions is essential. Hence, this research delves deeply into the prediction of CO₂ emissions by examining various deep learning models utilizing time series data to identify carbon dioxide levels in Oman. First, four important production materials of Oman (oil, gas, cement, and flaring), which have a great impact on CO₂ emissions, were selected. Then, the time series related to the release of CO₂ was collected from 1964 to 2022. After data collection, preprocessing was performed, in which outliers were removed and corrected, and data that had not been measured were completed using interpolation. Then, by dividing the data into two sections, education (1946–2004) and test (2022–2005) and creating scenarios, predictions were made. By creating four scenarios and modeling with two independent GRU and LSTM models and a hybrid LSTM-GRU model, annual carbon was predicted for Oman. The results were evaluated with three criteria: root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation coefficient (r). The evaluations showed that the hybrid LSTM-GRU model with an error of 2.104 tons has the best performance compared to the rest of the models. By identifying key contributors to carbon footprints, these models can guide targeted interventions to reduce emissions. They can highlight the impact of industrial activities on per capita emissions, enabling policymakers to design more effective strategies. Therefore, in order to reduce pollution and increase the productivity of factories, using an advanced hybrid model, it is possible to identify the carbon footprint and make accurate predictions for different countries. Full article

This study provides a comparative analysis of the environmental and economic performance of Oman, Egypt, and Morocco, focusing on the critical interplay between their economic structures, governance frameworks, and energy policies. Morocco stands out as a regional leader in renewable energy, driven by significant investments in solar, wind, and hydroelectric projects, positioning itself as a model for clean energy transition. Egypt, despite its rapid industrialization and urbanization, faces mounting environmental pressures that challenge its economic diversification efforts. Oman, heavily dependent on hydrocarbons, confronts significant sustainability risks due to its reliance on fossil fuels, despite the political stability that could support renewable integration. The research underscores that while these nations share common challenges, including regulatory weaknesses and energy policy inconsistencies, their distinct economic contexts demand tailored approaches. Morocco’s path to energy leadership must focus on integrating renewables across all sectors, enhancing grid infrastructure, and expanding green technology innovations to maintain momentum. Egypt should prioritize scaling up renewable infrastructure, reducing dependency on fossil fuels, and investing in clean technology to address its carbon footprint. For Oman, the strategic diversification of its economy, combined with aggressive renewable energy integration, is critical to reducing CO₂ emissions and mitigating climate impacts. This study contributes novel insights by highlighting the role of political stability, institutional quality, and policy coherence as critical enablers of long-term sustainability. It also identifies the importance of regional cooperation and knowledge sharing to overcome shared challenges like data limitations, geopolitical complexities, and methodological gaps in sustainability assessments. The findings advocate for a multi-method approach, integrating economic modeling, life-cycle analysis, and policy evaluation, to guide future sustainability efforts and foster resilient, low-carbon economies in the MENA region. Full article

This article addresses a topic of critical importance globally, particularly in the context of the ongoing energy crisis, climate change, and efforts to transition towards sustainable energy systems. A growing environmental awareness among consumers, along with changing regulations on energy efficiency, forces companies to adapt their products and services to meet new market demands. Eco-innovations, such as energy-efficient technologies and environmentally friendly materials, can respond to the increasing demand for products with a lower carbon footprint and reduced energy consumption. Using structural equation modelling, our study aimed to evaluate the significance of selected determinants of enterprise activities aimed at innovations that yield environmental benefits. The analysis focused on the scale of the benefits obtained due to these innovations (e.g., reduced material or water use per unit of output, reduced energy use, reduced CO₂ footprint, reduction in pollution, or recycling of waste) and during the consumption or use of goods or services by the end user (e.g., energy savings, facilitated recycling, or extended product life). The empirical data source was a database of anonymised individual data from Statistics Poland. The database comprised 8544 industrial enterprises employing 10 or more people, of which 2714 introduced eco-innovations. To verify the hypothetical relationships between variables, we proposed a structural equation modelling method. The structural model estimates indicated that requirements arising from current and future regulations, pressure from high operational costs and administrative formalities, and reputation and incentives had a positive and statistically significant impact on the scale of benefits obtained due to these eco-innovations. The assessment of the importance of factors determining the introduction of eco-innovations differed slightly between companies of different sizes. For large enterprises, the key determinants were incentives, reputation, and law requirements. For medium-sized enterprises, incentives and reputation were the most influential. For small enterprises, reputation was the primary determinant, followed closely by pressure and incentives at a similar level. Full article

The sustainable development of the Guanzhong Plain Urban Agglomeration (GPUA), which is a pivotal Belt and Road hub, is critical for achieving the UN’s 17 SDGs. Based on the ecological footprint (EF) model, this study innovatively constructs a three-dimensional framework integrating natural and human-made capital, using the Gini coefficient and spatiotemporal analysis to evaluate resource allocation fairness in the GPUA from 2005 to 2022. Key findings include the following: (1) EF and GDP grew continuously at annual rates of 11.43% and 11.87%, while ecological carrying capacity (EC) stabilized, pushing the GPUA toward its ecological threshold under the Environmental Kuznets Curve (EKC). Moreover, the increasing Ecological Pressure Index (EPI) shows that after 2014, the GPUA has trended toward “extremely unsafe” status. (2) The ecological carrying capacity Gini coefficient (G₁, 0.1710–0.6060) fluctuated significantly, while the economic contribution Gini coefficient (G₂, 0.1039–0.3519) showed a narrow upward trend; since 2015, the comprehensive Gini (G < 0.4) indicates that the EF aligns with its EC and economic contribution. (3) The GPUA shows fair resource allocation. Tongchuan, Baoji, and Xianyang are low economic contribution and high ecological contribution; Xi’an and Yangling Demonstration Zone are high economic contribution and low ecological contribution; Weinan is low ecological contribution and low economic contribution. These findings provide critical insights for hub urban agglomerations to achieve the 17 SDGs through fair ecological resource allocation and sustainable development. Full article

Global food systems are contributing to a shift toward unhealthy diets, which is linked to the three components of the global syndemic. This cross-sectional study evaluates how dietary patterns in Brazil are associated with the components of the global syndemic. Anthropometric and food intake data were obtained from the CUME Study—a prospective cohort conducted with a sample of Brazilian university graduates. BMI was used to assess obesity. Insufficient intake of micronutrients was considered undernutrition. Carbon, water, and ecological footprints were used to assess the environmental impact of dietary patterns. Dietary patterns were identified through principal components analysis. Linear regression models were used to evaluate associations between dietary patterns and the components of the global syndemic. The Unhealthy Dietary Pattern was positively associated with BMI and had the highest environmental impact. The Brazilian Dietary Pattern was also positively associated with BMI but had the lowest environmental impact. The Healthy Dietary Pattern was the most protective against micronutrient inadequacy. Diet affected the environment and people’s health in this sample. The dietary patterns identified here as contributing to poor health and environmental damage can help the government develop policies that incorporate the costs of these effects into the prices of food. Full article

The global potato industry has changed dramatically over the past half century—the potato-planting area in Poland decreased from 2,819,200 hectares in 1961 to 188,580 hectares in 2023, representing a 1394.96% relative decrease; South Africa’s potato production increased from 332,000 tons in 1961 to 2.42 million tons in 2023, representing a 627.60% relative increase. This study provides a comprehensive comparison of the potato-processing industries in China and major global producers. The global potato-processing market was valued at USD 40.97 billion in 2023 and is projected to reach USD 60.08 billion by 2031, with significant variations in production and consumption patterns across countries. As the world’s largest potato producer, China processes approximately 15% of its total potato output, whereas India, the second-largest producer, processes only about 7%. In contrast, developed countries such as the United States, Canada, and leading European nations—including Germany, the Netherlands, France, and Belgium—demonstrate significantly higher levels of processing, underpinned by advanced technologies, automation, and efficient quality-control systems. In order to conduct an in-depth analysis of the competitiveness of China’s potato-processing industry, this paper employs the Diamond Model to carry out relevant research. Despite rapid progress, China’s potato-processing industry still lags behind these global leaders in key aspects such as automation, production efficiency, and product quality. Differences remain evident in major processed potato products, including French fries, potato chips, potato flakes, and starch, as well as in raw-material supply chains, environmental sustainability, and market competitiveness. However, China’s role in the global potato-processing industry is evolving. A major milestone was reached in 2022 when China became a net exporter of frozen French fries for the first time, signaling a shift in its position in the international market. This transformation highlights China’s emergence as a key player in global French fry exports and suggests a potential restructuring of the industry. While challenges remain, the growing acceptance of Chinese French fries in international markets reflects improving product quality. Future industry trends point toward increased automation, product innovation, circular economy practices, and greater international market integration. To enhance its competitiveness, China must further modernize its processing industry, adopt cutting-edge technologies, strengthen quality control, and expand its global footprint to secure a stronger position in the evolving international potato-processing landscape. Full article

This study evaluates and compares the environmental and economic implications of desktop and laptop computer systems throughout their life cycles using screening life cycle assessment (LCA) and life cycle costing (LCC) methodologies. The functional unit was defined as the use of one computer system for fundamental home and small-business productivity tasks for over four years. The analysis considered the production, use, and end-of-life phases. The results showed the desktop system had a higher overall carbon footprint (679.1 kg CO_2eq) compared to the laptop (286.1 kg CO_2eq). For both systems, manufacturing contributed the largest share of the emissions, followed by use. Desktops exhibited significantly higher use phase emissions, due to greater energy consumption. Life cycle cost analysis revealed that laptops had slightly lower total costs (EUR 593.88) than desktops (EUR 608.40) over the 4-year period, despite higher initial investment costs. Sensitivity analysis examining different geographical scenarios highlighted the importance of considering regional factors in the LCA. Manufacturer-provided data generally showed lower carbon footprint values than the modeled scenarios. This study emphasizes the need for updated life cycle inventory data and energy efficiency improvements to reduce the environmental impacts of computer systems. Overall, laptops demonstrated environmental and economic advantages over desktops in the defined usage cases. Full article

This study aims to develop a process to calculate the carbon footprint of a company in the textile sector for the automotive industry, thus addressing a research gap identified in this sector. Based on a structured calculation model, the project aspires to innovate by quantifying not only the greenhouse gas emissions at different stages of the company’s operations, including those generated by the consumed electricity and gas, but also the emissions related to external and in-house transportation and solid waste management. The approach includes the design of a specific calculator, capable of integrating variables such as energy consumption, transport and types of waste, analysing them in the light of recognised conversion factors. This tool not only allows for a detailed assessment of emissions but also supports strategic decision-making, guiding the implementation of more sustainable business practices. The results indicate that, considering the use of renewable energy sources, the company’s total emissions amount to approximately 18 thousand tonnes of carbon dioxide equivalent. On the other hand, considering non-renewable energy, purchased electricity accounts for 31 thousand megawatt-hours per year, corresponding to 5 thousand tonnes of carbon dioxide equivalent, with the twisting area being the largest consumer at 89% of total usage, followed by the dipping area. In terms of mobile combustion, raw materials contribute 1373 million tonnes of carbon dioxide equivalent, while finished products generate 1869 million tonnes of carbon dioxide equivalent. Among the most impactful variables, solid waste, and stationary combustion stand out as the main contributors. These findings highlight the need for concrete measures to mitigate climate change, such as transitioning from stationary natural gas combustion to green electric power; identifying companies with more suitable waste treatment solutions, process changes that reduce disposable, and easily substitutable materials; making use of green electricity; exploring alternative transport methods or combining different modes, such as using electric vehicles for short distances; and optimizing transport routes. These initiatives reinforce the company’s commitment to sustainable development goals and the promotion of responsible environmental practices. Full article

The paper presents the design and development of a universal simulation model named SustainSIM, intended for optimizing the carbon footprint in mechanical engineering production. The objective of this model is to enable enterprises to accurately quantify, monitor, and simulate CO₂ emissions generated during various manufacturing processes, thereby identifying and evaluating effective reduction strategies. The paper thoroughly examines methodologies for data collection and processing, determination of emission factors, and categorization of emissions (Scope 1 and Scope 2), utilizing standards such as the GHG Protocol and associated databases. Through a digital simulation environment created in Unity Engine, the model interactively visualizes the impacts of implementing green technologies—such as solar panels, electric vehicles, and heat pumps—on reducing the overall carbon footprint. The practical applicability of the model was validated using a mechanical engineering company as a case study, where simulations confirmed the model’s potential in supporting sustainable decision-making and production process optimization. The findings suggest that the implementation of such a tool can significantly contribute to environmentally responsible management and the reduction of industrial emissions. In comparison to existing methods such as SimaPro/OpenLCA (detailed LCA) and the Corporate Calculator (GHG Protocol), SustainSIM achieves the same accuracy in calculating Scopes 1/2, while reducing the analysis time to less than 15% and decreasing the requirements for expertise. Unlike simulation packages like Energy Plus, users can modify parameters without scripting, and they can see the immediate impact in CO₂e. Full article

Given the relevance of sustainability, this study analyzed the impacts on water consumption in the production chain of ornamental stone pieces (marble and granite) and quartz-based composites. The goal was to compare the water demand throughout the process, from extraction to manufacturing, using 1 m³ blocks as the unit of analysis. This study was conducted in Bahia, a state with significant ornamental stone production, located in a semi-arid region with limited water availability. The methodology included data collection from participating companies, combined with sectorial information and the Ecoinvent version 3.3 database, modeled using the SimaPro 8.0 software. The impact assessment was carried out using the AWaRE (Water Scarcity Footprint) and ReCiPe Endpoint methods, following the guidelines of Life Cycle Assessment (LCA), as per ABNT NBR ISO 14040 standards. The results showed that marble and granite have lower water demand and environmental impact in the categories of particulate matter, human toxicity, ecotoxicity, eutrophication, and acidification when compared to quartz composites. The highest environmental impact occurred during the processing stage, which requires a large amount of water and generates effluents, losses, and particulate matter. The results indicate that marble and granite demand less water and exhibit lower environmental impacts—across categories like particulate matter, human toxicity, ecotoxicity, eutrophication, and acidification—than quartz composites. Notably, the processing stage incurred the highest environmental burden due to its intensive water use and consequent generation of effluents, losses, and particulate matter. These findings highlight the necessity of efficient water management and the adoption of circular economy principles—including water reuse and waste valorization—to promote long-term sustainability in the ornamental stone industry. Full article

The transition to electric public transportation is crucial for reducing the carbon footprint and promoting environmental sustainability. However, successful implementation requires strong public policies, including tax incentives and educational programs, to encourage widespread adoption. This study identifies the optimal electric bus model for Cuenca, Ecuador, using the multicriteria decision-making methods PROMETHEE and TOPSIS. The evaluation considers four key dimensions: technical (autonomy, passenger capacity, charging time, engine power), economic (acquisition, operation, and maintenance costs), social (community acceptance and accessibility), and environmental (reduction of pollutant emissions). The results highlight passenger capacity as the most influential criterion, followed by autonomy and engine power. The selected electric bus model emerges as the most suitable option due to its energy efficiency, low maintenance costs, and long service life, making it a cost-effective long-term investment. Additionally, its adoption would enhance air quality and improve the overall user experience. Beyond its relevance to Cuenca, this study provides a replicable methodology for evaluating electric bus feasibility in other cities with different geographic and socioeconomic contexts. Full article

The rapid pace of urbanization is contributing to ecological degradation and poses a threat to regional ecological security. Addressing these issues requires effective strategies to mitigate existing environmental challenges. Ecological networks, as the spatial foundation for ecosystem services, play a critical role in reducing environmental degradation. By reconfiguring the spatial relationship between human activities and natural ecosystems, anthropogenic pressures on land can be alleviated. However, most current research focuses on administrative boundaries, which limits spatial continuity and regional coordination. Therefore, constructing ecological networks from a cross-regional perspective is essential for integrated ecological management. This study uses the Yangtze River Delta Ecological Green Integration Demonstration Area as a case study. We construct a blue–green ecological network by applying ecological footprint analysis, Morphological Spatial Pattern Analysis (MSPA), landscape connectivity assessments, the Minimum Cumulative Resistance (MCR) model, and gravity modeling. Practical strategies for integrating the ecological network into territorial spatial planning are also explored. The key findings are as follows: (1) The demonstration area contains 33 ecological source areas, including 20 primary sources located near administrative boundaries and central lakeshore wetlands. A total of 333 ecological corridors were identified. First-grade corridors are primarily located in rural areas, traversing agricultural land and water bodies. (2) We recommend corridor widths of 200 m for first-grade corridors, 60 m for second-grade corridors, and 30 m for third-grade corridors. These widths are based on species characteristics and land use types, and are found to be conducive to species migration and habitat connectivity. (3) We propose the development of tourism landscape zones from a cross-regional perspective, leveraging existing ecological and cultural resources. The multifunctionality of corridors is redefined through the integration of ecological and social values, enhancing their spatial implementation. This framework provides a practical reference for constructing cross-regional blue–green ecological networks and informs spatial planning efforts in other multi-jurisdictional areas. Full article

Architects and building designers are pivotal in mitigating climate change by shaping the environmental footprint of buildings from their inception, with life cycle assessment (LCA) serving as a crucial tool for quantifying these impacts. Given that structural systems contribute significantly to embodied carbon, accounting for approximately 24% of a building’s life cycle emissions, this research investigates the relationship between structural span length—a key design factor influencing material choices and construction methods—and overall environmental performance. Through a scenario-based analysis employing building information modeling (BIM) and whole building life cycle assessment (WBLCA) tools, this study evaluates various building configurations to reveal that in long-span scenarios, steel demonstrates a lower environmental impact compared to timber. This finding offers a novel, quantifiable insight for architects and designers to assess and optimize building designs, particularly in the context of emerging architectural trends featuring longer spans, ultimately contributing to more sustainable building practices. Full article