The construction industry produces a large amount of carbon emissions, with a significant portion attributed to embodied carbon (EC). Prefabrication has the potential to reduce EC through streamlined workflows and controlled production environments. However, inefficiencies such as rework, material waste, excessive labor input, and quality issues can offset these benefits, necessitating a flexible digital technology approach. This study proposes the integration of mixed reality (MR) into prefabrication workflows to mitigate these issues and reduce EC emissions. A hybrid input-output (I-O) life cycle assessment (LCA) model combined with Monte Carlo (MC) simulation was employed to evaluate EC emission under uncertainty. Four prefabrication scenarios representing increasing levels of MR integration, ranging from conventional methods to high-level digitalization, were analyzed across several life cycle stages. Results emphasize that EC emissions were reduced by 8.5%, 14.9%, and 21.2% in the Lower, Medium, and Higher MR scenarios, respectively, due to significant reductions in rework, rejections, labor hours, and energy use. MC simulation confirmed the robustness of the results, showing decreased variability and tighter confidence intervals with higher levels of MR integration. While the experimental context focuses on precast panel production, the proposed approach is generalizable to broader prefabrication systems with appropriate adaptations to the MR model. This study contributes to the body of knowledge by introducing a novel integration of MR with hybrid I-O LCA for EC accounting in prefabrication and by demonstrating how MC simulation enhances the reliability of environmental impact assessments under uncertainty. The proposed hybrid I-O LCA approach offers a replicable and data-driven method for sustainable decision-making in construction engineering and management.

Introduction Global warming is progressing, and China is under great pressure to reduce carbon dioxide emissions. The three northeastern provinces belong to the country’s powerful industry regions. They not only produce a large amount of carbon emissions but also suffer from city shrinkage. These two facts strongly indicate that China should progress toward low-carbon development. Methods Using data from the province-level cities in the three northeastern provinces in 2005, 2010, 2015, 2020, and 2023, this study explores their city shrinkage and carbon emission intensity spatial and time frames, and further explores how urban shrinkage affects the mechanisms of carbon emission intensity. Results Results show that core cities have little contraction and some are even still growing, while edge cities face stronger contraction. Over time, the overall level of contraction has gradually weakened. From 2005 to 2023, the average carbon emission intensity decreased from 4.54 to 2.87, with the standard deviation narrowing from 3.25 to 1.86. Regions with higher economic development generally showed a downward trend in carbon emission intensity, while resource-based cities showed more fluctuations. The relationship between urban shrinkage and carbon emission intensity in the three northeastern provinces improved each year but differed across regions, presenting a spatial pattern of high coordination in core cities and low coordination in peripheral areas. Among the influencing factors, GDP had a clear positive effect on carbon emission intensity with the highest explanatory power ( q = 0.404). The shares of human capital and per capita road area showed big spatial and temporal differences in their effects on carbon emissions, where the inhibitory effect of human capital gradually diminished and the promoting effect of road area intensified. Discussion This study provides theoretical references and decision-making support for formulating differentiated low-carbon planning strategies and achieving high-quality revitalization in old industrial bases facing urban shrinkage.

The goal of the study is to examine and assess the influence of various water sources, energy inputs, and their effect on carbon emissions. The approach included site visits to the textile production mill and discussions with both the production and commercial procurement teams to collect data from the last three calendar years. The findings and conclusions of this analysis show that Textile manufacturing contributes to a considerable amount of carbon emissions, approximately 3.1 kgCO2e/kg of nylon fabric. Purchasing electricity as an energy source generates the highest carbon emissions 3.03 kgCO2e/kg of nylon fabric, In contrast, the use of LPG fuel and Diesel fuel resulted in notably lower CO2 emissions. Additionally, this study assessed the emissions in the scope 1 and scope 2 categories during the textile processing stage, which contributed to 136535 kg CO2e. Personalization in the application of sizing chemicals using industry 4.0 techniques, such as warping, sizing and weaving can further minimize the consumption of resources, water, and energy. Prioritizing the design of waterless processes should be central to energy optimization efforts. Energy usage, which is directly related to the amount of water needed for the slashing process. Sizing processors are somewhat reluctant to adopt these changes due to the added production costs. Coordinated efforts from all stakeholders in the textile value chain are essential to address the sustainability challenges in textile manufacturing. This case study focuses on five out of the seventeen sustainable development goals (SDGs): 6-Clean water and sanitation, 7-Affordable and clean energy, 12-Responsible production and consumption, 13-Climate action, and 15-Life on land.

When treating wastewater, traditional AOPs mainly break down pollutants into harmless substances completely with radical chain reactions. However, the long-term use of these methods brings problems in sustainable development. They use too much energy and produce large amounts of carbon emissions. Researchers have carried out recent studies on oxidation-polymerization ways. These studies show that polymerization reactions work better than mineralization processes. They can remove organic pollutants effectively. They also cut down energy use greatly and help realize the reuse of resources. This paper summarizes the working principles and newest progress of polymerization reactions. These reactions are started by different active substances. The content includes radical ways like organic and inorganic radicals. It also includes non-radical ways such as high-valent metal oxides, electron transfer processes, complexes and singlet oxygen. Additionally, this paper puts forward methods to improve polymerization reactions. These methods come from two aspects. One is radical ways including concentration synergistic regulation, redox potential and nanoconfinement. The other is non-radical ways including electron regulation, microstructure regulation and composite carrier design. Finally, this paper talks about the difficulties and limits of polymerization ways in removing organic pollutants and lists future research directions in this area. It aims to offer reference and theoretical help for the later use of oxidative polymerization ways in resource recovery.

Thermal insulation materials play a significant role in balancing buildings' total carbon emissions. Balancing involves applying the optimized amount of insulation materials to avoid excessive emissions in either the operational or embodied phases. Due to the wide range of insulation materials and variations of their specifications, it is vital to analyse them individually. The focus of this study is to optimize the amount of insulation materials in the facades of Residential Buildings (RB) to balance the amount of Operational Carbon Emissions (OCE) and Embodied Carbon Emissions (ECE) by applying the Building Information Modelling-Life Cycle Assessment (BIM-LCA) integration method. The Life Cycle Assessment (LCA) stages, from extraction of raw materials, manufacturing, construction, usage, and end-of-life, as well as the impact assessment categories, are based on European standards. 49 building materials are utilized during this research activity, which includes the three insulation materials as alternatives, such as Glass wool, polyurethane (PUR), and Natural Cork from mineral, synthetic, and natural categories, and lightweight concrete blocks made from pumice, and clay brick blocks as other alternatives for the main core of the Facades. The RB under study is a prototype sample located in Milan. After performing the methodology and analyses, the results demonstrate that thermal conductivity and density play an important role. For instance, Natural Cork in higher thickness values performs better, while PUR in lower ones.

The logistics industry is responsible for a significant amount of carbon emissions because it relies heavily on fossil fuels for transportation, uses a lot of energy in warehouses, and has complicated networks for distributing goods. In Saudi Arabia, the economy is growing quickly and there are a lot of new buildings. This has increased the amount of goods being moved around, which has made the environment more polluted. In reply, Saudi Vision 2030 is very focused on being kind to the environment and on reducing the carbon footprint of the economy. This study looks at ways to reduce carbon emissions in the logistics sector of Saudi Arabia. It focuses on using techniques to manage supply chains in a way that is good for the environment. The paper uses a detailed review of academic literature, policy documents, and industry reports to identify important green strategies that can be used in Saudi logistics, such as buying products and services in ways that do not harm the environment, using transportation systems that use less energy, using renewable energy, using digital technologies to make processes more efficient, and managing supply chains in a way that is collaborative. The analysis shows how these practices can reduce greenhouse gas emissions while also improving how well the company works, how it controls its costs, and its ability to compete with other companies. The results show that using green methods in supply chains is good for the environment and also helps Saudi Arabia reach its national logistics strategy and sustainability goals.

This article presents an environmentally sustainable Economic Production Quantity (EPQ) model under the influence of imperfect production and shortages. The defective items are reworked under an asynchronous rework process, where the reworking starts just after the production process stops. In this study, we have proposed two models under shortages, one with shortages satisfied by perfect production, and the other with shortages satisfied by production permitting defective item production which are reworked under asynchronous approach. During the processes of production, transportation and storage of inventory items, significant amount of carbon emissions is generated. In order to minimize these emissions and to reduce the setup costs, this paper proposes the integration of investment in green technology. The primary objective of this paper is to obtain the optimal values of lot size, backordered quantities, setup costs and green investment amounts in order to minimize the total cost of the manufacturer. To find the optimal solution, we have employed a metaheuristic method, Grey Wolf Optimization (GWO). A numerical example is also presented, accompanied with a sensitivity analysis to illustrate and validate the outcomes of the proposed inventory models.

It is of great significance to clarify the evolution trend and key influencing factors of China's rural energy carbon emissions in order to promote the green development of agriculture and rural areas and to realize the goal of "double carbon" on schedule. On the basis of clarifying the current situation of rural energy carbon emission in China and 30 provinces， this study focused on analyzing the evolution trend of rural energy carbon emission and key influencing factors by using the kernel density estimation method and the random forest model. The study showed that： ① China's total rural energy carbon emission was on an upward trend from 2005 to 2022， and their evolution could be broadly categorized into three phases： "fluctuating increase， relatively stable， and continuous increase，" and the carbon intensity increased by more than 160% during the study period. In terms of provinces， the total amount of rural energy carbon emission was greatest in Guangdong， with Shanghai showing the least， and the intensity was greatest in Tianjin， with Guangxi showing the lowest. ② During the investigation period， rural energy carbon emission intensity increased significantly in both the country and the southern and northern regions， and the distribution of provinces in the low-value region decreased significantly. The rural energy carbon emission intensity in both the country and the northern regions still showed some polarization at the end of the investigation period. ③Rural energy carbon emission was influenced by factors at the economic， social， and governmental levels. Among the factors at the economic level， the structure of agricultural industry had an inverted U-shaped effect on rural energy and carbon emissions. Among the factors at the social level， the aging of the rural population， the degree of mechanization of agriculture， and the increase in the level of rural human capital all led to an increase in rural energy and carbon emissions， while the increase in the level of urbanization could play a restraining role. Among the governmental factors， the increase in the level of financial support for agriculture will help to realize the carbon emission reduction of rural energy. The results of the study can provide scientific references for the construction of the optimization path of emission reduction and carbon sequestration in rural areas.

ABSTRACTBACKGROUND:Telemedicine can promote access to specialized care and avoid travel to referral centers.OBJECTIVES:To present the environmental impacts and the positive results for the sustainability of the Brazilian public health system after the implementation of the TeleNordeste Project developed by hospital BP – A Beneficência Portuguesa de São Paulo.DESIGN AND SETTING:A retrospective cohort study was developed in three states in the Brazilian Northeast, Alagoas, Maranhão, and Piauí.METHODS:This study was conducted between August 2022 and December 2023. All patients participating in telemedicine care were selected for this type of care by Primary Health Care (PHC) doctors according to the need for clinical discussion. The variables analyzed were the total distance and time (round trip) saved by telemedicine care, the amount of carbon emissions not released into the environment, gasoline costs, resolution of care through teleconsultation, and evaluation of the Net Promoter Score.RESULTS:In total, 25,194 consultations were conducted via telemedicine, requiring in-person referral in 775 tele-interconsultations, representing a resolution rate of 96.92%. It saved approximately 10,737,287 miles (17,279,988.6 km) and 264,302 hours for patients and the municipal health department, and reduced carbon dioxide (CO2) emissions according to Environmental Protection Agency (EPA) parameters, estimated at 4,294,915 kg, saving US$ 1,660,068.89 (R$ 8,532,754.09) on gasoline.CONCLUSION:To our knowledge, in Brazil, this study is one of the first to present results on the impact of telemedicine on reducing carbon emissions in relation to the movement of patients to reference centers in healthcare networks and the resolution of care provided in health units in the context of the PROADI-SUS TeleNordeste Project developed by BP and promotes reflection on the potential benefits of telemedicine according to current evidence.

In the process of building materials supply chain management, there are problems such as information opacity, low logistics coordination efficiency, difficulty in material quality traceability, and weak trust mechanism among supply chain entities, which lead to rising costs, low efficiency, and waste of resources. In addition, the construction industry has a large amount of carbon emissions, and the impact of supply chain management on carbon emission reduction cannot be ignored. To this end, this paper introduces blockchain technology to improve supply chain transparency, optimize logistics management, enhance material quality traceability, and explore its role in carbon emission reduction. This paper constructs a blockchain-based building materials supply chain management system, using distributed ledgers to ensure data transparency, smart contracts to automate procurement, acceptance and payment, which is a material traceability system to ensure quality control, the Internet of Things combined with blockchain to optimize logistics management, and establish a carbon emission monitoring and optimization mechanism to achieve real-time data recording and low-carbon scheduling. The system built in this study shows significant advantages in multiple key indicators. The overall carbon emissions of the supply chain in the experimental group are 88 tons of CO2, a 12% decrease compared to 100 tons of CO2 in the control group. The average transportation time in the experimental group is 4.5 hours, while that in the control group is 8.2 hours, a 45.1% decrease. The application of blockchain technology has effectively improved the efficiency and transparency of building materials supply chain management, optimized logistics and material quality control, and played a positive role in carbon emission reduction.

Packaging is an indispensable element in all industries, as it can both protect products and attract consumers. However, it has also become one of the main causes of global environmental problems. The widespread use of disposable plastics, non-recyclable materials, and excessive packaging designs has led to a large amount of waste and significant carbon emissions. In response, governments and enterprises around the world are promoting sustainable packaging policies that are in line with the United Nations' Sustainable Development Goals. Walmart is a typical example, demonstrating how Green Supply Chain Management (GSCM) can strike a balance between operational efficiency and environmental responsibility. By collaborating with suppliers, establishing a sustainability index, innovating logistics, and reducing packaging, Walmart has decreased emissions, waste, and costs, while fulfilling its social responsibility through food donation programs. However, small businesses often struggle to adopt similar practices due to budget and structural constraints. This article proposes practical strategies for small businesses, including using appropriately sized recyclable packaging, offering incentives to customers who use reusable containers, and integrating transportation with local partners. These methods show that sustainability is not limited to multinational companies; through targeted practices, small businesses can also reduce their environmental impact, improve efficiency, and attract environmentally conscious consumers.

Amid the swift expansion of the global economy, environmental issues in China have garnered increasing scrutiny. Along with the increase in China’s economic development level, the total amount of carbon emissions in China is also rising. As one of the economically developed cities in northern China, Tianjin will inevitably impact the environment during its development. This paper explores the factors affecting carbon emissions in Tianjin through relevant data from 2002 to 2021, based on the Kaya constant equation and using the LMDI model. It learns that economic development is the main contributing factor to carbon emissions and further compares and analyzes the GDPs of various industries in terms of economic benefits. In order to promote the low-carbon development of Tianjin, it should maintain sustained and stable economic growth, formulate low-carbon policies that are tailored to its actual situation, transform the economic development model, restructure the industry, and promote the ideology of sustainable consumption, among other measures.

The municipal solid waste recycling industry has become a rapidly growing emerging industry. Its carbon emissions account for 1/10 of the urban carbon emissions, which cannot be ignored. It is highly important for cities to achieve the goals of peak carbon and carbon neutrality and to strive for space for economic and social development. Taking Beijing as an example, using the life cycle analysis method, this paper systematically combines the historical changes in the characteristic structure of municipal solid waste. On this basis, the amount and structural characteristics of carbon emissions and their evolution are calculated, the achievements of municipal solid waste treatment in Beijing are comprehensively evaluated, and the space for further emission reduction in the future is estimated. The following conclusions are drawn: (1). Since the implementation of waste classification treatment, carbon emissions in Beijing have decreased by 22.9%. (2). Carbon emissions from plastic and paper waste from municipal solid waste have become the main source of carbon emissions from waste treatment. (3). There is still more than 2.6 × 106 t of carbon emission reduction space for municipal solid waste treatment in Beijing in the future. On the basis of the calculation results, several suggestions are proposed.

Objectives: This study aims to estimate the carbon emissions of scenic spots in rural tourism using digital management technology. Methods: The Dashahe National Wetland Park, located along the old course of the Yellow River in Feng County, Jiangsu Province, was taken as a case for analysis. During the analysis process, the carbon emission, carbon absorption, and net carbon emission amount of the park during 2018-2023 were estimated. The correlation between different types of land area and the carbon absorption amount was analyzed. Findings: The carbon emission of the wetland park increased annually, but the carbon absorption amount also showed a consistent upward trend, resulting in relatively stable net carbon emissions over the study period. Moreover, the area of wetlands, water bodies, and grasslands exhibited a significant positive correlation with the carbon absorption amount, whereas the correlation between the area of cultivated lands and garden lands and the carbon absorption amount was insignificant. Innovation: This research applied digital management technology to precisely collect data related to carbon emissions within the scenic spot, enabling a more reliable estimation of its carbon footprint.

Cutting carbon emissions is one of the most important steps in fighting climate change, and the United Statesbeing one of the largest pollutershas a big responsibility. This study looks at how business and data analytics can help reduce carbon emissions. Analytics tools allow companies and governments to track energy use in real-time, predict future trends, and run operations more efficiently. We used data from 2022 to 2024, including carbon emissions levels, how much analytics was being used in energy systems, and how many smart buildings were in use. Our analysis shows a strong negative link (r = -0.96, p < 0.01) between the use of analytics and the amount of carbon emissions. This means that as more organizations used analytics, carbon emissions went down. These results show that using data and technology can make a real difference in protecting the environment. It also highlights the importance of including analytics in climate policies and sustainability planning (U.S. EPA, 2024; DOE, 2023).

Clarifying the spatiotemporal characteristics of agricultural carbon emissions and influencing factors in China is crucial. A system for measuring agricultural carbon emissions was established, thus evaluating the level of carbon emissions in China and its provinces. Moreover, the dynamic evolution of agricultural carbon emissions in China and the regions on both sides of the Hu Line was analyzed, then investigated factors affecting agricultural carbon emissions by the LMDI model. The results indicate that the total amount and intensity of agricultural carbon emissions showed an upward and then a downward trend in China from 2001 to 2021. The peaks were 330.72 million tons and 1.98 tons\\ha, respectively. Agricultural carbon intensity in provinces was mostly Low-Low Cluster and the range of High-High Cluster has decreased. Inter-provincial disparities in agricultural carbon emissions were also gradually narrowing. These show that the effect of agricultural carbon emissions reduction was obvious in China. It is important to note that carbon emissions from energy consumption in agriculture and agricultural material inputs were substantial, accounting for about 95% of the total. Agricultural carbon emissions were restricted by the agricultural production efficiency, changes in industrial structure, rural population size, and agricultural industrial structure, but were promoted by the level of economy and urbanization. Therefore, we recommend enhancing inter-provincial synergistic collaboration to create agricultural carbon emissions reduction pathways with unique features. It is also essential to maximize agricultural production efficiency and grasp the direction of green and low-carbon. We also suggest that the Chinese government should accelerate the in-depth adjustment and transformation and upgrading of the industrial structure, thereby reducing agricultural carbon emissions at source.

Construction steel is responsible for considerable amounts of carbon emissions in building sectors, and promoting the low-carbon design of steel components is conducive to the sustainable development of the industry. As one of the most typical components, I/H-beams are widely used in steel structures. In this paper, a new comprehensive index named carbon-capacity ratio (CCR) was proposed considering both mechanical properties and carbon emissions of I/H-beams, based on which the geometry coefficient and material coefficient were derived. Quantitative investigation was then conducted on the geometry coefficient to figure out the effects of different geometry variables, and the geometry criteria for low-carbon design of steel beams were concluded considering different load conditions. Results show that for double-symmetric cross-sections bearing flexural loads, larger flange width and beam height are suggested, while for single-symmetric cross-sections bearing flexural loads, increasing beam height as well as flange width and thickness can all contribute to sustainable beam designs, but adopting large beam height is the most effective. For cross-sections bearing shear loads, increasing beam height and web thickness would be beneficial. The feasible design domain (FDD) for geometry variables was proposed to be predicted with either linear or hyperbolic criteria depending on different loads and cross-sections. Additionally, a qualitative discussion was also given on the material coefficient, and steel with higher strength or that produced from recycled scrap using energy-saving technologies, as well as new prototyping techniques with lower energy and material loss, are recommended for beam fabrication. This study is expected to serve as a preliminary supplement to the blank in current codes or standards for low-carbon design of construction steel.

BackgroundWater and land resources are important for maintaining the sustainable development of society. However, with the utilization of water and land resources, a large amount of carbon emissions will be generated. Therefore, studying carbon emissions under the water-land-carbon connection is of great significance for achieving “dual carbon goals”. This paper first calculated the land use carbon emissions and the total carbon emissions in Shandong Province. Secondly, the carbon emission economic contribution coefficient (EC), carbon water coefficient (CWC), carbon emission intensity (CI), and coefficient of variation (CV) were constructed. The center of gravity-standard deviation ellipse was used to determine the spatio-temporal distribution characteristics of carbon emissions. Finally, the Kaya-LMDI model was used to investigate the factors that influence carbon emissions.Results(1) The land use and total carbon emissions of the Provincial Capital Economic Circle (PEC) are more than those of the Jiaodong Economic Circle (JEC) and those of Lunan Economic Circle (LEC). For EC, PEC is greater than LEC is greater than JEC. For CWC, JEC is greater than PEC is greater than LEC. For CI, LEC is greater than PEC is greater than JEC. (2) The CV of carbon emissions in the province is at a low level, indicating a small fluctuation in carbon emissions. The spatial–temporal distribution of the land use carbon emissions is generally from northeast to southwest, and the center of gravity migration track is from northwest to northeast to southwest. The distribution of the total carbon emissions changes from northeast-southwest to southeast-northwest, and the shifting track is east-southwest. (3) Carbon emission efficiency effect, land economy effect, and population effect promote carbon emission; water use intensity effect and per capita land use effect inhibit carbon emission.ConclusionsPEC gives priority to promoting the adjustment of industrial structure and the development of renewable energy; JEC strengthens the application of water-saving and recycling technologies; LEC optimizes land efficiency, develops low-carbon agriculture and strictly controls high energy-consuming projects. This result provides a new perspective and practical basis for urban collaborative carbon reduction.

Analyzing the driving mechanisms behind provincial carbon emissions is crucial to formulating appropriate carbon reduction policies， which is vital for achieving China's "carbon peaking and carbon neutrality" goals. This study employed the LMDI method to examine the influences of six key factors （population size， economic development， industrial structure， energy intensity， energy structure， and carbon emission coefficient） on carbon emissions across 30 regions in China from 2010 to 2021. By using the contribution rate of each driving factor to changes in carbon emissions as the clustering variable， the K-means clustering method was used to categorize the 30 regions into five groups. This facilitated identifying the similarities and differences in carbon emission driving mechanisms across various regions. The results of the study follow： ① For most regions， economic development and population growth are the primary drivers of carbon emission increases， while energy intensity and industrial structure are important factors in carbon emission reductions. ②The driving factors of carbon emissions vary significantly between the Twelfth and Thirteenth Five-Year Plan periods， with the growth in both the amount and rate of carbon emissions being notably lower in the former period. ③ Importantly， the driving mechanisms of carbon emissions differ greatly across the five region types identified. The first and fifth types of regions face greater challenges in achieving carbon emission peak goals， whereas the second and third types are better positioned to attain these objectives. Based on the characteristics of the different region types and representative provinces and cities， targeted carbon reduction policies are proposed.

Achieving carbon emission reduction synergy is vital for green economic transformation. This study examines whether environmental governance pressure promotes such synergy, simultaneously driving carbon reduction and pollution control. Leveraging the 2012 Ambient Air Quality Standard as a quasi-natural experiment, we employ a continuous difference-in-differences (DID) method on 250 prefecture-level cities from 2009 to 2022. Our findings reveal that increased environmental governance pressure significantly reduces both the total amount and intensity of carbon emissions, demonstrating a clear synergistic effect. This synergy is positively correlated with reductions in major air pollutants (e.g., SO2 and NOx), indicating that pressure curbs both the total amount and intensity of carbon emissions. Mechanistic analysis shows that this pressure primarily curtails carbon emissions by fostering green innovation and accelerating cleaner energy transitions, with no ‘green paradox’. It also promotes low-carbon industrial restructuring while reducing reliance on end-of-pipe pollution management. Heterogeneity analysis indicates stronger synergistic effects in regions with lower emission reduction costs (e.g., western China, less developed industrial bases). We recommend robust central government environmental regulation policies to amplify local governance pressure, strengthen carbon reduction synergy, and facilitate continuous green development.