Carbon Footprint Research Articles

Optimization of Bio-based Polymer Composites Using Grey Relational Analysis (GRA) Method

Bio-based polymer composites comprise polymers sourced from renewable biological origins like plants, algae, or bacteria, combined with reinforcing agents such as natural fibers or nanoparticles. They serve as eco-friendly substitutes for traditional petroleum-based plastics, lessening environmental concerns and lessening dependence on finite fossil resources. Employing bio-based polymers diminishes carbon footprint and decreases reliance on non-renewable materials, fostering a more circular and sustainable economy. Natural fibers like hemp, flax, or kenaf are commonly integrated as reinforcements due to their robustness and biodegradability. These composites are widely applicable across industries like automotive, construction, packaging, and consumer goods. They're utilized in automotive interiors to reduce weight and bolster fuel efficiency, in construction for insulation, panels, and structural elements, and in packaging as biodegradable alternatives to conventional plastics, thus lowering environmental impact. Despite their environmental merits, challenges persist, including optimizing mechanical properties, scaling up production, and managing end-of-life disposal. Ongoing research and innovation endeavor to overcome these hurdles, making bio-based polymer composites more competitive and sustainable on a global scale. Research significance: Bio-based polymer composites research is crucial for tackling environmental issues and pushing forward sustainable materials technology. These composites combine renewable resources with polymer matrices, resulting in less reliance on fossil fuels, decreased carbon footprints, and improved biodegradability compared to traditional options. They offer eco-friendly alternatives in packaging, automotive, construction, and biomedical fields. Delving into their characteristics, manufacturing techniques, and effectiveness allows for the creation of novel materials that lessen environmental harm while meeting diverse needs, thus aiding in building a more sustainable and robust future. Methodology: Grey Relational Analysis (GRA) is a technique employed to examine the correlation among numerous variables, especially in scenarios where data might be scant or uncertain. It gauges the extent of linkage between variables by evaluating their likeness or disparity patterns. GRA empowers decision-makers to pinpoint influential elements, rank actions, and refine procedures in intricate systems like engineering, finance, and management. Through the conversion of qualitative and quantitative data into grey numbers, GRA addresses uncertainties and offers valuable insights for problem-solving, decision-making, and performance improvement across various domains, facilitating more knowledgeable and efficient decision-making strategies. Alternative: PLA (Polylactic Acid) Composites, Hemp Fiber Reinforced Composites, Kenaf Fiber Reinforced Composites, Soy Protein-based Composites, Cellulose Nanocrystal Composites, Bamboo Fiber Reinforced Composites, Corn Starch-based Composites, Algae-based Composites. Evaluation preference: Mechanical Strength, Environmental Impact, Biodegradability, Renewable Resource, Cost-effectiveness. Results: From the result it is seen that Cellulose Nanocrystal Composites is got the first rank whereas is the Corn Starch-based Composites is having the lowest rank

The cost of implant waste in trauma orthopaedic surgery and sustainability considerations: an observational study.

Implant wastage in trauma and orthopaedic (T&O) surgery remains an under-reported yet significant issue, contributing to rising healthcare costs and environmental concerns. With increasing surgical demand driven by an ageing population and the growing prevalence of conditions like osteoporosis, this study aimed to quantify implant wastage in T&O procedures at a Level 1 Major Trauma Centre in London, assessing both its frequency and financial impact. A retrospective cohort study was conducted on all weekday T&O procedures performed between 1st December 2023 and 31st January 2024. Two of the authors identified wasted implants using intraoperative implant logbooks, and cross-referencing implant stickers with post-operative radiographs. Data pertaining to patient demographics, procedure types, surgical sites, and implant usage were collected. Cost analysis was performed using procurement data to determine the financial impact of implant wastage. Among 184 procedures analysed, 131 (71.2%) used implants, with wastage observed in 108 (82.4%) cases. A total of 141 implants were wasted, with screws accounting for 92.9% (n = 131) of wasted implants. Locking screws were the most frequently discarded (n = 65; 46.1%). Across ORIF and intramedullary nailing procedures, an overall screw wastage rate of 20% (17-31%) was observed with 2.4 screws wasted per trauma procedure. The financial cost of implant wastage over the 44-day study period amounted to approximately £335 per day and £136 per case. This study highlights the substantial economic burden associated with implant wastage in T&O surgery, with screws, particularly locking screws, being the primary contributors. Targeted interventions, including improved preoperative planning, precision-based implant selection, and enhanced intraoperative decision-making, are essential to reducing waste and improving cost-efficiency and sustainability in surgical practices. Further research should explore the broader economic and environmental impact of implant wastage, incorporating factors such as operative time and carbon footprint to develop comprehensive waste-reduction strategies. IV.

A Comparative Analysis of Life Cycle Costs and Emissions in Mae Sariang’s Microgrid Energy Scenarios

This study evaluates the life cycle costs, net present value (NPV), and greenhouse gas (GHG) emissions of three energy scenarios for the Mae Sariang microgrid system to assess the economic and environmental impacts of different energy sources. The reliance on renewable energy has become increasingly vital in addressing energy sustainability and reducing carbon footprints. The analysis reveals that Scenario I, primarily utilizing solar energy, achieved the lowest life cycle cost per kilowatt-hour (kWh) at 6.18 and the highest NPV of 226,583,036 baht, while also producing the fewest GHG emissions at 21,239 kgCO₂e/year. In contrast, Scenario II, dependent on grid electricity, incurred the highest costs and emissions at 25,180 kgCO₂e/year, reflecting its reliance on higher-carbon sources. Scenario III, which incorporates diesel generation, demonstrated moderate emissions at 22,240 kgCO₂e/year but resulted in a negative NPV of -2,690,330 baht due to high fuel expenses. The findings highlight that prioritizing renewable energy sources not only enhances financial viability but also minimizes environmental impact. Therefore, the study concludes that adopting a renewable-focused approach in microgrid systems offers substantial economic and ecological benefits. Policy recommendations include incentivizing renewable energy integration, promoting energy efficiency measures, and developing supportive frameworks to reduce reliance on high-carbon electricity, ultimately enhancing the feasibility and sustainability of energy systems.

Performance and Environmental Impact of a 45 kWp Rooftop Grid-connected Solar PV System in a Semi-arid Academic Campus: A Case Study from Western India

Aims: This study aimed to evaluate the technical performance and environmental impact of a 45 kWp rooftop grid-connected solar photovoltaic (PV) system installed at the College of Agricultural Engineering and Technology (CAET), Junagadh Agricultural University, Gujarat. Methodology: The system was monitored over five months (August–December 2018). Real-time data on energy output, meteorological parameters, and system efficiencies were recorded. Performance metrics such as array yield, final yield, module and system efficiencies, performance ratio (PR), and CO₂ emission reduction were analyzed using IEC 61724 guidelines. Results: The system generated 22,205 kWh of DC energy and exported 20,829.26 kWh of AC energy to the grid. It achieved an average final yield of 3.37 kWh/kWp/day and a performance ratio of 71%. The average module, inverter, and system efficiencies were 11.26%, 93.84%, and 10.56% respectively. A total of 20,494 kg of CO₂ emissions were avoided. Conclusion: The solar PV system showed reliable performance and high efficiency across seasonal conditions. It proved effective for reducing institutional carbon footprint and demonstrated the feasibility of rooftop solar adoption in semi-arid academic environments.

Engineering a Novel Ceramic Composite for High‐Temperature Thermal Insulation

Thermal insulations play a pivotal role in energy conservation and carbon footprint reduction by mitigating energy losses at elevated temperatures. The thermal insulation of large energy systems faces challenges of in situ application and rise in thermal conductivity of the insulation with the increasing application surface temperature. This work develops, characterizes, and investigates a high‐temperature ceramic composite (HTCC) insulation to address these challenges for high‐temperature (≥300 °C) applications. Ceramic wool fiber, hollow ceramic microspheres, and silica form a multiscale porous structure in the HTCC that minimizes heat loss at high temperatures due to the infinite hot plate effect and phonon scattering phenomena. The rise in thermal conductivity for HTCC is 38%, whereas for conventional insulation, ceramic fiber (CF) it is 56%, when the application temperature increases from 300 to 500 °C. Moreover, the thermal diffusivity of the developed composite is 58% lower than CF. The efficacy of the HTCC is investigated experimentally using a model of thermal energy storage. The HTCC insulation, at 55% less thickness, reduces the heat loss by 37%, saving around 4780 kWh m−2 yearly compared to conventional insulation. Significant energy savings are expected when HTCC is applied to large‐scale industrial energy systems.

The Carbon Footprint of Diets with Different Exclusions of Animal-Derived Products: Exploratory Polish Study

Background/Objectives: Analyzing the carbon footprint of diets in various populations is important as it can help identify more sustainable food choices that reduce the overall impact of human activities on ongoing warming of the global climate. This pilot exploratory study analyzed the carbon footprint (measured in kg of CO2 equivalent, eq.) using food diaries collected from Polish individuals with varying levels of animal-derived product exclusion in their diets. Methods: The study employed a food diary method, where participants from four dietary groups (vegan, vegetarian, fish-eater, and meat-eater) recorded all meals and beverages consumed over a 7-day period, including portion sizes and packaging details. These diaries were then analyzed to assess dietary adherence and calculate carbon footprints, utilizing standardized CO2 equivalent emission data from publicly available databases. Results: The analysis revealed a decreasing trend in the carbon footprint corresponding to the degree of elimination of animal-derived products from the diet (R2 = 0.96, p = 0.0217). The mean daily footprint in the vegan group was 1.38 kg CO2 eq., which was significantly lower than in the vegetarian (2.45), fish-eater (2.72), and meat-eater groups (3.62). For each 1000 kcal, the meat-eater diet generated 39.7, 58.3, and 93.9% more CO2 eq. than in the case of fish-eaters, vegetarians, and vegans, respectively. Over a week, a group of 10 vegans had a total carbon footprint lower than vegetarians, fish-eaters, and meat-eaters by 42.9, 52.2, and 61.8%, respectively. Hard and mozzarella cheese had the highest contribution to the carbon footprint in vegetarians, fish, and seafood in fish-eaters, and poultry, pork, and beef had the highest contribution in meat-eaters. Conclusions: Dietary carbon footprints vary considerably by dietary pattern, with lower consumption of animal-derived products associated with lower emissions. Additionally, identifying specific high-impact food items within each diet may inform strategies for reducing environmental impact across various eating patterns.

Enhanced Heat-Powered Batteryless IIoT Architecture with NB-IoT for Predictive Maintenance in the Oil and Gas Industry

The carbon footprint associated with human activity, particularly from energy-intensive industries such as iron and steel, aluminium, cement, oil and gas, and petrochemicals, contributes significantly to global warming. These industries face unique challenges in achieving Industry 4.0 goals due to the widespread adoption of industrial Internet of Things (IIoT) technologies, which require reliable and efficient power solutions. Conventional wireless devices powered by lithium batteries have limitations, including a reduced lifespan in high-temperature environments, incompatibility with explosive atmospheres, and high maintenance costs. This paper proposes a novel approach to address these challenges by leveraging residual heat to power IIoT devices, eliminating the need for batteries and enabling autonomous operation. Based on the Seebeck effect, thermoelectric energy harvesters transduce waste heat from industrial surfaces, such as pipes or chimneys, into sufficient electrical energy to power IoT nodes for applications like the condition monitoring and predictive maintenance of rotating machinery. The methodology presented standardises the modelling and simulation of Waste Heat Recovery Systems (IoT-WHRSs), demonstrating their feasibility through statistical analysis of IoT-WHRS architectures. Furthermore, this technology has been successfully implemented in a petroleum refinery, where it benefits from the NB-IoT standard for long-range, robust, and secure communications, ensuring reliable data transmission in harsh industrial environments. The results highlight the potential of this solution to reduce costs, improve safety, and enhance efficiency in demanding industrial applications, making it a valuable tool for the energy transition.

Simulation-Guided Design of Solar Steam Generator Arrays for Efficient All-Cold Evaporation under Natural Sunlight.

Solar-powered interfacial evaporation has emerged as a promising, sustainable technology for clean water production with its minimal carbon footprint. Currently, extensive research efforts focus on enhancing solar evaporation rates and broadening the applicability of three-dimensional (3D) interfacial steam generators (SGs). For large-scale water production, individual 3D SGs must be integrated into system-level SG arrays for deployment in portable devices or solar distillation plants. Therefore, the SG array's configuration plays an even more critical role in boosting solar evaporation. From a methodological perspective, the development of numerical simulation and evaluation methods to predict the solar evaporation of SG arrays is an emerging research frontier. Nonetheless, the complex energy-water-solute interactions within SG arrays remain largely underexplored. Herein, 3D SGs and their integrated SG arrays are developed. The temperature, relative humidity, airflow, and air particle distributions throughout individual SGs and SG arrays are simulated, guiding the optimization of SG structures and the arrangement of SG arrays. By promoting cold evaporation, 8-Fin SG achieves the highest water evaporation rate of over 2.3 kg m-2 h-1 under 1 sun, with a further increase to 4.8 kg m-2 h-1 under a moderate airflow, positioning it among the best-performing solar-powered SGs. The circular array configuration of nine 8-Fin SGs (12 cm spacing) enables sustained "all-cold evaporation" in each unit, where continuous energy harvesting from both ambient air and bulk water drives an exceptional evaporation rate of 5.9 kg m-2 h-1 of the SG array under natural sunlight. We present an integrated approach combining numerical simulation with experimental studies of SG and their arrays, inspiring a new paradigm for advancing SG arrays toward system-level applications.

Carbon footprint of private dental laboratories in Egypt: A cross-sectional study

BackgroundClimate change poses a serious threat to the planet, mainly driven by greenhouse gas (GHG) emissions. Dental laboratories contribute to GHG emissions through staff travel, waste, energy and water consumption, and procurement. Carbon footprinting is the process of quantifying the direct and indirect GHG emissions associated with a service. This study aimed to assess the Carbon Footprint (CFP) of private dental laboratories in Egypt.Materials and methodsData were collected from private dental laboratories in Cairo, Alexandria, and Elbeheira, Egypt in August 2024 through interview questionnaires. A CFP calculator was used to estimate carbon emissions from staff travel, waste, energy and water consumption, and procurement. The data of all laboratories was summed and divided to determine the average CFP per laboratory and per prothesis/appliance, both with and without the depreciation of dental equipment.ResultsData from 21 dental laboratories were collected. An average private dental laboratory in Egypt worked 309 days with a staff of around 7 persons and makes around 7119 prostheses/appliance per year. The CFP of dental laboratories was around 20,820 kg CO2e, equal to 2.9 kg CO2e per prosthesis/appliance. The largest contributor to the CFP was staff travel (43.6%), followed by procurement (27.8%), energy consumption (25%), waste (3.3%), and water consumption (0.1%). After including the depreciation of dental equipment, the CFP increased by 7.7%.ConclusionPrivate dental laboratories in Egypt produce a significant amount of carbon emissions. Staff travel was the major contributor to the carbon emission because each laboratory hired several couriers to deliver the prostheses/appliances and impressions. The CFP of electricity consumption was significant, likely because the air conditioning ran throughout the year to cool the machines down. Future studies are needed to develop customized country-specific CFP calculators to accurately measure the carbon emissions of dental laboratories in various settings. Preventing oral diseases, educating technicians on sustainable dental practices, optimizing public transportation, using bulk delivery services, shifting to renewable energy, and adopting circular economy are essential to mitigate the carbon emissions of dental laboratories.

Factors affecting the carbon footprint of reinforced concrete structures

With the need to decarbonise global cement and concrete production, much emphasis has been placed on the use of supplementary cementitious materials, such as ground granulated blast furnace slag. However, while such blends can significantly reduce the carbon footprint of cements, other options are also available to decarbonise concrete structures. For example, changing the dimensions of structural elements or concrete strengths can affect both the volume of structural concrete and its carbon footprint. This study has examined the effects of changing concrete strength, span and binder type on the carbon footprint of a hypothetical two-storey concrete structure. Furthermore, durability requirements can impose additional demands, such as higher-grade concrete or greater cover depths, affecting the structure’s carbon footprint. Thus, these structures were designed to resist a non-aggressive (XC1) and a mildly aggressive (XS1) environment. Higher-strength concrete, despite allowing dematerialisation, increased the carbon footprint of the structures, as did longer beam spans. The use of a 50% GGBS CEM III/A-S cement offered significant carbon reduction potential, with greater carbon reduction in a mildly aggressive environment. GGBS is a limited resource, so while it can always reduce concrete’s carbon footprint, its use should be focused where it can also offer durability benefits.

Toward a cleaner road: Environmental transformation in Hungary’s automotive sector

A transition toward sustainable logistics is crucial for Hungary’s automotive industry, which remains a main contributor to environmental degradation through its reliance on carbon-based supply chains. This study aims to examine how green technology, policy regulation, and infrastructure availability influence sustainability outcomes for the industry, with a focus on reducing carbon emissions and improving operational efficiency. Partial least squares structural equation modeling with 2015–2023 empirical data was employed. The model examined direct and moderate effects of such factors on lowering carbon footprint and sustainability performance, as well as on implementation cost, firm size, and demand.The results suggest a significant impact on carbon footprint reduction (path coefficient = 0.32) and sustainability performance (0.38) through the adoption of green technology. Availability of regulatory frameworks (0.29 for reduction of carbon footprint; 0.25 for sustainability performance) and infrastructure (0.35 and 0.40, respectively) also have a significant impact. High implementation costs (–0.22 and –0.18) and the complexity of the supply chain (–0.15 and –0.17) have a negative impact, particularly for small and medium-sized enterprises. Moderation analysis shows that firm size (0.22) and strong demand (0.26) enhance the benefits of adopting green technology.The indications are toward enhancing regulatory enforcement, raising financial aid schemes, and upgrading logistics infrastructure as a solution for Hungary’s accelerating adoption of sustainable logistics practices. Public-private partnerships are put forward as a strategic solution for bridging infrastructure and investment gaps and enabling long-term economic and environmental advantages for the automotive logistics industry.

Decomposition and Decoupling Analysis of the Driving Factors of the “Water–Carbon–Ecological” Footprint in the Eleven Provinces and Municipalities of the Yangtze River Economic Belt

Studying the spatio-temporal evolution characteristics of the “water–carbon–ecological” footprint and the decoupling status of its main driving factors is of paramount importance for achieving sustainable development in society. Based on quantifying the footprint family, this study constructs an integrated driving factor analysis model of “Kaya–LMDI–Tapio”, screens the main driving factors influencing the footprint family, and conducts decoupling analysis. The research results indicate that: (1) The water, carbon, and ecological footprints of the Yangtze River Economic Belt from 2002 to 2017 were 1534.265 billion cubic meters, 61,672.89 million hectares, and 45,528.76 million hectares, respectively. (2) The main driving factors for water, carbon, and ecological footprints were economic effect factors, agricultural production scale factors, and economic effect factors. (3) During the research period, the decoupling trends between the water, carbon, and ecological footprints and their main driving factors presented a transformation from a weak decoupling state to a strong decoupling state, the decoupling index value decreased initially and then increased, and the decoupling index value showed a downward trend. These findings provide a quantitative basis for the formulation of differentiated basin management policies, indicating that, through the collaborative promotion of technological innovation and institutional innovation, the leap from relative decoupling to absolute decoupling can be achieved, which has important reference value for the sustainable development governance of global river basins.

Sustainable biodiesel production with ZnO catalysts: A carbon footprint and fuel property analysis

Sustainable biodiesel production with ZnO catalysts: A carbon footprint and fuel property analysis

Advancements in Electric Vehicles: Hybrid Powertrain in Scooters

The transition to electric vehicles (EVs) is a crucial step toward sustainable transportation, with hybrid powertrain scooters emerging as a viable bridge between traditional internal combustion engine (ICE) vehicles and fully electric models. This research paper explores the advancements, challenges, and methodologies associated with hybrid powertrain scooters. It examines their impact on urban mobility, fuel efficiency, emissions reduction, and infrastructure requirements. The study also highlights existing gaps and challenges in the adoption of hybrid scooters, along with an analysis of consumer preferences and market potential. Experimental evaluations, surveys, and real-world observations provide comprehensive insights into the effectiveness of hybrid technology in two-wheelers. The findings indicate that hybrid scooters can play a pivotal role in reducing carbon footprints while maintaining cost-effectiveness and efficiency for users. Further technological innovations and policy support are essential to accelerating the adoption of hybrid scooters in India and globally.

Minimizing Energy Demand in the Conversion of Levulinic Acid to γ‑Valerolactone via Photothermal Catalysis Using Raney Ni.

The valorization of lignocellulosic wastes emerges as a prime strategy to mitigate the global carbon footprint. Among the multiple biomass derivatives, γ-valerolactone is particularly attractive as precursor of high-value chemicals, biofuel, green solvent or perfumery. γ-Valerolactone can be synthesized through a hydrogenation reaction from levulinic acid, obtained from cellulose. However, the high energy requirements of this synthetic pathway have hindered its industrial viability. To drastically reduce the reaction energy requirements, here a novel synthetic strategy, based on solvothermal-photothermal processes using cost-effective Raney-Ni as photothermal catalyst, is proposed. First, the use of hydrogen gas is avoided by selecting isopropanol as a safer and greener H-source. Second, a photothermocatalytic process is used to minimize the reaction temperature and time with respect to conventional reactions. This approach exploits the broadband optical absorption of the Raney®-Ni, due to its highly damped plasmonic behavior, to achieve fast and efficient catalyst heating inside the reactor. The photothermal reaction required less than 2h and just 132°C to reach over 95% conversion, thereby drastically reducing the reaction time and energy consumption compared to conventional reactions. Importantly, these conditions granted high catalyst reusability. This solvothermal-photothermal approach could offer a sustainable alternative for the industrial production of γ-valerolactone.

Carbon footprint Assessment of Open Snail-Farm Systems in Central and Northern Greece

This study examines the environmental sustainability of open-field snail farming systems in Greece, focusing on their carbon footprint (CF) as a representative environmental impact metric. Eleven snail farms across Central and Northern Greece were analyzed using the Life Cycle Assessment (LCA) methodology, assessing inputs, outputs, and processes from farm construction to the point of sale. The results demonstrated significant variability in CF values, ranging from 0.048 to 7.65 kg CO₂eq per kilogram of live snails. The primary contributors to CF were identified as the use of metal materials, electricity consumption for irrigation and drilling, and plowing. Farms with lower productivity exhibited disproportionately higher CF values, emphasizing the need for improved management practices. A comparative analysis with conventional livestock production highlighted snail farming as a more environmentally sustainable protein source, with significantly lower CF values, than cattle, pig, and poultry farming. Additionally, this study evaluates the environmental performance of heliciculture in Greece and proposes actionable strategies for enhancing sustainability in small-scale farming systems. Notably, transitioning from conventional electricity to renewable energy sources was shown to reduce the CF by up to 85%. These findings contribute to the broader discourse on sustainable protein production, offering valuable insights for both researchers and practitioners in agricultural sustainability.

Green, Sustainable Nephrology: State of the Art Needs for Education and Implementation.

Green nephrology, also often called sustainable nephrology, has become a field of interest in our discipline in recent years. While several reviews have been published, comparatively few original papers have appeared, witnessing interest but also lack of original data. Greater awareness of the impact nephrology has on the planet, including, but not limited to its carbon footprint, is needed to promote education and research on these issues. Increasing awareness entails increasing knowledge at various levels and it is for this reason that we are presenting this review focusing on educational activities that have been and could further be undertaken to spread knowledge of these topics. We start from a description of the various approaches to green nephrology: technical, mainly focused on dialysis, clinical, encompassing medical and non-medical treatments in all chronic kidney disease (CKD) phases, and comprehensive, embedding kidney care in the society. We further summarize what is known and the fundamental needs and problems we presently face in reducing dialysis carbon-print, optimizing the pathways of care, avoiding futility in clinical work and research, implementing lifestyle interventions and education. We further acknowledge the lack of data on lifecycle of items and procedures, including commonly used drugs, and identify research needs at various levels. We finally discuss some examples of educational programs on green nephrology that are already available at various levels, from medical schools (an educational game), to medical meetings (healthy eating, reduction of plastic and paper waste), and daily clinical practice, in which teaching passes also through examples (personalizing dialysis, adapting schedules to each patient). Finally, we identify some barriers educational approaches may offers ways to overcome, to promote effective, targeted interventions that will make us advance on the road to reduce nephrology's carbon footprint.

Stochastic carbon footprint tracing for power systems with uncertainty

AbstractThe increasing penetration of distributed energy resources (DERs) and renewable energy sources (RESs) requires more granular analysis for accurate carbon footprint tracing. Traditional tracing methodologies primarily utilized deterministic steady‐state analyses, which inadequately addressed the significant uncertainties inherent in RESs. To address this gap, this study introduces two stochastic carbon footprint‐tracing approaches that incorporate RES uncertainties into load‐side carbon footprint assessments. The first method embeds a probabilistic analysis within the carbon emissions flow (CEF) framework, providing a comprehensive reference for the spatial distribution of carbon intensity across power system components. Recognizing that the CEF network complexity increases with higher DER penetration, the second method extends the initial approach to enhance computational efficiency while maintaining accuracy, thus ensuring scalability for large‐scale power system topologies. The proposed models were validated and benchmarked using a synthetic 1004‐bus test system in a case study, demonstrating their enhanced performance and advancements over conventional deterministic methods. The results underscore the effectiveness of the stochastic approaches in delivering more precise and reliable carbon footprint tracing, thereby contributing to the sustainable management of decarbonized power systems.

From Carbon Footprints to Competitive Edges: Analyzing Environmental Efficiency in Aviation

Purpose: This study conducts a comprehensive analysis of environmental efficiency in the aviation industry, focusing on 19 global airline companies employing diverse business models. Methodology: Utilizing Data Envelopment Analysis for 2017 to 2022, the research quantifies efficiency levels based on input and output variables, including Fuel Consumption, Revenue Passenger Kilometers, Greenhouse Gas Emissions, and Total Income. Findings: Noteworthy findings reveal that Alaska Airlines (VRS=1), Lufthansa (VRS=1), Spirit Airlines (VRS=1), and Delta Air Lines (VRS=1) consistently operated at the environmental efficiency frontier, showcasing a proportional relationship between input and output values. Originality: The dynamic nature of the aviation industry, coupled with the economic implications of environmental initiatives, necessitates a nuanced understanding of airlines' sustainability efforts. Policymakers are urged to consider measures such as the effective introduction of Sustainable Aviation Fuels and large-scale strategies to reduce aviation-related greenhouse gas emissions.

Low-Carbon Slag Concrete Design Optimization Method Considering the Coupled Effects of Formwork Stripping, Strength Progress, and Carbonation Durability

Partially substituting cement with slag is an efficient approach to lowering the carbon footprint of concrete. Earlier research on low-carbon slag concrete has primarily concentrated on the optimization of material strength without considering the coupled effects of formwork stripping time, strength progress, and carbonation durability, which may lead to the risk of steel reinforcement corrosion. To address this limitation, this study introduces an optimized design approach for low-carbon slag concrete that simultaneously accounts for the formwork stripping time and carbonation durability. First, based on strength test results, a strength prediction equation which incorporates the curing age, water-to-(cement+slag) mass ratio, and slag-to-(cement+slag) mass ratio is developed. As such, the coefficients of the equation have clear physical meanings. Both the cement and slag strength coefficients increase with curing age, with the slag strength coefficient exhibiting a greater growth rate than that of cement. Second, an evaluation of concrete’s carbon emissions per 1 MPa increase in strength reveals that, for a given curing age, adopting a low water-to-(cement+slag) mass ratio and a high slag-to-(cement+slag) mass ratio effectively reduces these emissions. Parameter analysis of the carbonation model reveals that increasing the curing time before the onset of carbonation reduces the carbonation depth. Furthermore, four design scenarios are considered in this study: scenario C1 does not consider carbonation durability, with a specified strength of 30 MPa at 28 days; scenario C2 considers carbonation durability, with the same specified strength of 30 MPa at 28 days; scenario C3 does not consider carbonation durability but requires formwork stripping at 7 days; and scenario C4 considers carbonation durability and also requires formwork stripping at 7 days. Through the formulation of constraints for optimization using a genetic algorithm, the appropriate mix proportions for each design scenario are obtained. Finally, the optimization results reveal that, when transitioning from C1 to C2, the actual 28-day concrete compressive strength rises from 30 MPa to 65.139 MPa; when transitioning from C1 to C3, the actual 28-day concrete compressive strength slightly rises from 30 MPa to 30.122 MPa; and when transitioning from C3 to C4, the actual 28-day concrete compressive strength significantly rises from 30.122 MPa to 80.890 MPa. In summary, this study introduces a new approach to the material design of low-carbon slag concrete. In particular, prolonging the curing period plays a crucial role in optimizing low-carbon slag concrete mixtures.