Search Results (274)

This paper proposes an incentive scheme based on a public–private partnership (PPP) to encourage low-carbon travel behavior by inducing the mode choice shift from private cars to public transit. The scheme involves three key entities: travelers, the government, and the private sector. Travelers can choose between private cars and public transit, producing different emissions. As the leader, the government aims to reduce total emission to a certain level with limited budgets. The private sector, as an intermediary, invests subsidies in low-carbon rewards to attract green travelers and benefits from a larger user pool. A two-layer multi-objective optimization model is proposed, which includes travel time, monetary cost, and emission. The objective of the upper level is to maximize the utilities of the private sector and minimize social costs to the government. The lower layer is the user equilibrium of the travelers. The numerical results obtained through heuristic algorithms demonstrate that the proposed scheme can achieve a triple-win situation, where all stakeholders benefit. Moreover, sensitivity analysis finds that prioritizing pollution control strategies will be beneficial to the government only if the unit pollution control cost coefficient is below a low threshold. Contrary to intuition, larger government subsidies do not necessarily lead to better promotion of low-carbon travel. Full article

The building sector remains one of the largest contributors to global energy consumption and CO₂ emissions, yet selecting optimal retrofit strategies is often hindered by inconsistent evaluation practices and limited integration of environmental and social impacts. This review addresses that gap by systematically analyzing how various assessment methods are applied to building retrofits, particularly from a financial and environmental perspective. A structured literature review was conducted across four major scientific databases using predefined keywords, filters, and inclusion/exclusion criteria, resulting in a final sample of 50 studies (green colored citations of this paper). The review focuses on the application of Life Cycle Cost Analysis (LCCA), Cost–Benefit Analysis (CBA), and Life Cycle Assessment (LCA), as well as additional indicators that quantify energy and sustainability performance. Results show that LCCA is the most frequently used method, applied in over 60% of the studies, often in combination with LCA (particularly for long time horizons). CBA appears in fewer than 25% of cases. More than 50% of studies are based in Europe, and over 60% of case studies involve residential buildings. EnergyPlus and DesignBuilder were the most common simulation tools, used in 28% and 16% of the cases, respectively. Risk and uncertainty were typically addressed through Monte Carlo simulations (22%) and sensitivity analysis. Comfort and social impact indicators were underrepresented, with thermal comfort included in only 12% of studies and no formal use of tools like Social-LCA or SROI. The findings highlight the growing sophistication of retrofit assessments post-2020, but also reveal gaps such as geographic imbalance (absence of African case studies), inconsistent treatment of discount rates, and limited integration of social indicators. The study concludes that future research should develop standardized, multidimensional evaluation frameworks that incorporate social equity, stakeholder values, and long-term resilience alongside cost and carbon metrics. Full article

The implementation of a carbon tax in the transportation sector aims to reduce carbon emissions and encourage the transition to sustainable mobility amid increasing urbanization. The transportation sector is one of the largest contributors of carbon emissions in Indonesia, requiring effective policies to reduce its environmental impacts. Therefore, this study aims to find a more optimal carbon tax formula that is in accordance with Indonesia’s socio-economic conditions. The approach used includes analysis of transportation emission data, the economic impact of different carbon tax schemes, and tax revenue allocation strategies to support green infrastructure and sustainable transportation. The results of the study indicate that an adaptive carbon tax formula in the transportation sector is able to balance the economic burden, emission reduction targets, social justice, behavioral changes, and revenue allocation for green infrastructure, thus ensuring a just and sustainable transition. A progressive carbon tax, based on vehicle emission levels and fuel types, can encourage the transition to low-emission vehicles without excessively burdening low-income communities. With this approach, carbon tax policy functions not only as a fiscal instrument but also as a transformative strategy in creating an environmentally friendly and equitable transportation system. Full article

This study explores how carbon pricing and electricity market liberalization jointly contribute to China’s sustainable energy transition. Using a dynamic computable general equilibrium (CGE) model (CEEEA2.0), we simulate three policy scenarios—business as usual, emissions trading scheme (ETS) with regulated electricity prices, and ETS with market-based pricing—under a unified emissions cap. The results demonstrate that electricity market liberalization enhances carbon pricing efficiency by eliminating price distortions, leading to a 0.06% increase in GDP and a 12% reduction in emission abatement costs. However, liberalization also raises electricity and consumer prices, disproportionately affecting rural and low-income households. These findings underscore the need to balance economic efficiency and social equity in sustainability-oriented energy reforms. Our analysis emphasizes the importance of designing inclusive and just transition policies to ensure that carbon mitigation efforts support long-term environmental, economic, and social sustainability goals. Full article

This study provides a bibliometric analysis of life cycle assessments (LCAs) to explore the sustainability potential of mass timber buildings, focusing on glulam. The analysis highlights regional differences in carbon footprint performance within the ISO 14040 and EN 15978 frameworks. LCA results from representative countries across six continents show that wood buildings, compared to traditional materials, have a reduced carbon footprint. The geographical distribution of forest resources significantly influences the carbon footprint of glulam production. Europe and North America demonstrate optimal performance metrics (e.g., carbon sequestration), attributable to advanced technology and investment in long-term sustainable forest management. Our review research shows the lowest glulam carbon footprints (28–70% lower than traditional materials) due to clean energy and sustainable practices. In contrast, Asia and Africa exhibit systemic deficits, driven by resource scarcity, climatic stressors, and land-use pressures. South America and Oceania display transitional dynamics, with heterogeneous outcomes influenced by localized deforestation trends and conservation efficacy. Glulam buildings outperformed concrete and steel across 11–18 environmental categories, with carbon storage offsetting 30–47% of emissions and energy mixes cutting operational impacts by up to 67%. Circular strategies like recycling and prefabrication reduced end-of-life emissions by 12–29% and cut construction time and costs. Social benefits included job creation (e.g., 1 million in the EU) and improved well-being in wooden interiors. To further reduce carbon footprint disparities, this study emphasizes sustainable forest management, longer building lifespans, optimized energy mixes, shorter transport distances, advanced production technologies, and improved recycling systems. Additionally, the circular economy and social benefits of glulam buildings, such as reduced construction costs, value recovery, and job creation, are highlighted. In the future, prioritizing equitable partnerships and enhancing international exchanges of technical expertise will facilitate the adoption of sustainable practices in glulam buildings and advance decarbonization goals in the global building sector. Full article

The adoption of green building materials (GBMs) has become increasingly important in reducing carbon emissions and realizing zero-carbon cities. Although some scholars have investigated the decision-making of GBMs adoption in markets, they mainly focused on the impact factors of GBMs adoption without considering consumers’ multi-channel purchasing behavior. Thus motivated, this paper aims to develop a theoretical game model incorporating consumers’ multi-channel purchasing behavior and study the optimal sales strategies of GBMs manufacturers and retailers in markets for promoting GBMs adoption. To do this, not only the equilibrium outcome on sales strategy is examined, but also the effects of different GBMs sales strategies on urban environments and social welfare are theoretically verified. It is found that (1) the equilibrium sales strategy relies on two core parameters, namely matching rate and online return cost. Only when the matching rate is low and the online return cost is at a medium level can the GBMs manufacturer and retailer achieve a strategic consensus, and the equilibrium sales strategy is S (i.e., selling GBMs through the online channel, offline channel, and store-to-online channel). (2) When pursuing total profits of manufacturers and retailers in GBMs markets, the S sales strategy is 100% superior to the D sales strategy (i.e., selling GBMs only through online and offline channels). This is because the introduction of a store-to-online channel can reduce online return losses by providing consumers with physical experiences. (3) When pursuing social welfare (refers to public benefits including consumer surplus, urban environmental impacts, and others), the D sales strategy is optimal if the matching rate is relatively large and the return cost is low. (4) Under certain conditions, governments should incentivize GBMs manufacturers and retailers to adopt the D sales strategy through regulatory instruments, so as to achieve a balance between economic benefits and social benefits. Full article

Regenerative agriculture has emerged as an innovative approach to food production, offering the potential to achieve reduced or even positive environmental and social outcomes compared to the soil degradation and greenhouse gas emissions of conventional agriculture. Simultaneously, a sophisticated dual-use system combining solar energy generation from photovoltaics with agricultural production, called agrivoltaics, is rapidly expanding. Combining these approaches into regenerative agrivoltaics offers a promising solution to the challenges regarding food in a rapidly warming world. This review theoretically examines the compatibility and mutual benefits of combining agrivoltaics and regenerative agriculture while also identifying the challenges, opportunities, and pathways for implementing this system. A foundation for advancing regenerative agrivoltaics is made by identifying areas for research, which include the following: (1) carbon sequestration, (2) soil health and fertility, (3) soil moisture, (4) soil microbial activity, (5) soil nutrients, (6) crop performance, (7) water-use efficiency, and (8) economics. By addressing the intersection of agriculture, renewable energy, and sustainability, regenerative agrivoltaics emphasizes the transformative potential of integrated systems in reshaping land use and resource management. This evaluation underscores the importance of policy and industry collaboration in facilitating the adoption of regenerative agrivoltaics, advocating for tailored support mechanisms to enable widespread implementation of low-cost, zero-carbon, resilient food systems. Full article

Transportation infrastructure serves a pivotal role in driving regional development. This study proposes a decision-making framework for rural road network planning within the context of China’s common prosperity initiative. An integrated model combining Data Envelopment Analysis (DEA) and the Analytic Hierarchy Process (AHP) is developed, where DEA is employed to identify technically efficient planning alternatives and AHP is used to rank these alternatives based on social and environmental benefits. Applying the model to the case of Yueqing City, Zhejiang Province, the findings reveal that common prosperity-oriented schemes, particularly the Scheme, which emphasizes full industrial coverage and balanced equity, achieve a superior balance among construction costs, industrial coverage, regional equity, and carbon emissions. Theoretically, this research advances transportation planning by incorporating equity-focused metrics, such as the Gini coefficient, into efficiency analyses, thus promoting a socially sustainable approach to infrastructure development. Practically, the proposed method offers a systematic and actionable tool for local governments to optimize rural transportation networks in support of common prosperity and balanced regional growth. The resulting framework not only identifies technically efficient and equitable layouts but also offers planners a transparent tool for balancing cost, social equity, and environmental impact in future rural infrastructure projects. Full article

Quantifying greenhouse gas (GHG) emissions from forest fires is essential for climate change mitigation strategies, yet current methodologies predominantly focus on vegetation combustion, neglecting emissions from firefighting operations. This study presents a comprehensive assessment of GHG emissions from a forest fire in Yajiang County, China, by integrating remote sensing data with ground-based measurements to quantify emissions from both vegetation combustion and emergency response activities. Analysis revealed that the fire, which affected 20,688.67 hectares, generated 63,764.59 tons of GHGs—with vegetation combustion accounting for 83.5% (53,266.29 tons) and emergency response activities contributing 16.5% (10,498.30 tons). Moderate-severity fires in evergreen forests yielded the highest emissions, while aerial operations constituted the primary source of emergency-response-related emissions. Significantly, NO_x emissions from emergency response activities exceeded those from vegetation combustion. This research advances forest fire management by establishing a holistic accounting framework that incorporates previously unquantified emission sources, thereby providing foundational data for developing environmentally optimized fire social rescue activity protocols. 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

Selecting grid loss reduction strategies is crucial for energy-saving transformations, particularly in the context of electricity transmission and distribution pricing reforms. The optimization of strategic selection is not easy due to the vast number of grid devices, which leads to a multitude of possible strategy combinations. This paper presents an optimal model for selecting loss reduction strategies, aiming to minimize the sum of comprehensive investment costs and energy loss costs over the life cycle of the strategies. The energy loss costs include both direct expenses due to energy loss and indirect costs, namely, carbon emission penalties. The constraints include allowable voltage deviations, branch power transmission, the number of loss reduction measures, loss rates, and total investment limits. The model comprehensively considers both economic benefits and the social benefits of reduced carbon emissions. It can help companies better adapt to electricity transmission and distribution pricing reforms, reduce operational costs, and contribute to low-carbon development. Finally, the model is validated using the data provided by one provincial power grid company in China. The results show that the loss reduction reaches 13.9 MW and the reduced carbon emission per hour is 10.425 t. The proposed method is also compared with the enumeration method, which demonstrates its effectiveness and efficiency. Further research will be conducted on establishing functional relationships between electricity sales prices and line losses to incentivize companies to apply loss reduction measures under different pricing functions. Full article

Healthcare organisations in the United Kingdom must comply with national standards for food and drink, including sustainable sourcing and minimisation, mitigation, and management of food waste. Despite this, an estimated one in six plates of food served in hospitals are wasted daily, producing 12% of the UK’s food waste, equating to 6% of carbon dioxide emissions (CO₂e) nationally, and a waste-management cost of GBP 230 m per annum. Within healthcare, there is a move towards the implementation of “plant-based diets by default” to reduce the environmental impact, improve nutritional outcomes, and reduce costs. However, plant-based diets are often perceived as being difficult to prepare by caterers, less enjoyable, and potentially resulting in more food waste. We conducted a scoping review to examine the influence of the social, medical, and physical environment on food intake during inpatient admission to a mental health hospital. Fourteen studies were included. We identified five critical knowledge areas: (i) food and socio-cultural environment, (ii) evidence-based measures and strategies to reduce food waste, (iii) economic food environment, (iv) inevitability of weight gain, and (v) applications of theoretical models for behaviour change. Future research should explore the development of a behaviour-change framework inclusive of training, education, and goal-setting components for staff, patients, and visitors. Full article

Research on clean production in automotive painting processes is a core component of achieving green manufacturing, addressing environmental regulatory challenges, and advancing sustainable development in the automotive industry by reducing volatile organic compound (VOC) emissions, optimizing resource utilization, and minimizing energy consumption. To reduce pollutants generated by automotive painting processes and improve coating efficiency, this study proposes a clean production method for automotive body painting based on an improved whale optimization algorithm from the perspective of “low-carbon consumption and emission-reduced production”. A multi-level, multi-objective decision-making model is developed by integrating three dimensions of clean production: material flow (optimizing material costs), energy flow (minimizing painting energy consumption), and environmental emission flow (reducing carbon emissions and processing time). The whale optimization algorithm is enhanced through three key modifications: the incorporation of nonlinear convergence factors, elite opposition-based learning, and dynamic parameter self-adaptation, which are then applied to optimize the automotive painting model. Experimental validation using the painting processes of TJ Corporation’s New Energy Vehicles (NEVs) demonstrates the superiority of the proposed algorithm over the MHWOA, WOA-RBF, and WOA-VMD. Results show that the method achieves a 42.1% increase in coating production efficiency, over 98% exhaust gas purification rate, 18.2% average energy-saving improvement, and 17.9% reduction in manufacturing costs. This green transformation of low-carbon emission-reduction infrastructure in painting processes delivers significant economic and social benefits, positioning it as a sustainable solution for the automotive industry. Full article

The development of new technologies for the production of renewable energy is fundamental to reducing greenhouse gas emissions. Therefore, the search for new energy generation methods that are environmentally responsible, socially rational, and economically viable is gaining momentum in order to mitigate carbon footprint. The aviation sector is responsible for a significant fraction of greenhouse gas emissions; for this reason, the decarbonisation of this sector must be investigated using biorefinery models. This study presents a mixed-integer linear programming (MILP) model for optimising the design and configuration of the supply chain in different states of Brazil for the production of sustainable aviation fuel (SAF) and green diesel and gasoline, using microalgae cultivated in sugarcane vinasse as the raw material. The technology of hydrothermal liquefaction was assessed in terms of its capacity to convert microalgae without need for the energy-intensive drying step. The MILP model was developed in the LINGO v.20 software using a library of physical and economic process models. We consider the selection of processes based on the object of total minimum cost, with optimal production plant scaling and regional supply chain design, including an assessment of resources and final product distribution. A case study was implemented in Brazil, considering different regions of the country and its local demands for fuels. São Paulo is the most profitable state, with a cash flow of 1071.09 and an IRR of 36.19%, far outperforming the rest. Transport emissions alone represent between 0.6 and 8.6% of emissions generated by the model. The costs of raw materials, mainly hydrogen (57%) and electricity (27%) represent the main costs evaluated in the model. The production cost (MUS$/TJ biofuel) is in the range of 0.009–0.011. Finally, changes in the cost of electricity have the greatest impact on the model. Full article

Energy efficiency potentially reduces global carbon emissions, whereas the need of emerging countries to maintain economic growth and development entails a sharp increase in energy consumption. However, to meet this, current energy systems need to be transformed. Several studies find different conclusions on the short-run and long-run relationship and the direction of causality, and none of the studies have considered energy efficiency in their model. This study investigates the direction of causality between energy efficiency, energy consumption, and economic growth in South Africa. To determine if a long-run relationship between the variables exists, the Johanson cointegration test is used, and the results indicate that there is a long-run relationship between economic growth, energy depletion, energy efficiency, non-renewable energy consumption, renewable energy consumption, and energy security, with trace statistics suggesting that the null hypothesis of no cointegration should be rejected at a 5% level of significance. The Toda and Yamamoto procedure of the Granger causality approach was then applied. This study finds a unidirectional causality between energy efficiency, non-renewable energy consumption, and economic growth and no causality between renewable energy consumption, energy depletion, energy security, and economic growth. The growth hypothesis is supported, while the neutrality hypothesis is only confirmed regarding renewable energy consumption and economic growth. The results further suggest that a unidirectional Granger causality exists between non-renewable consumption and energy efficiency, and economic growth in South Africa. In South Africa, energy efficiency is a significant tool to enhance sustainable growth and attain climate objectives. Also, energy efficiency helps to lower the costs of mitigating carbon emissions and further advance both social and economic development. Full article