Search Results (515)

This study provides a comprehensive quantitative assessment of the carbon footprint of a four-star hotel in Istanbul, Türkiye, spanning the period from 2022 to 2024, to identify critical operational emission drivers. Methodologically grounded in ISO 14064-1 and the Greenhouse Gas Protocol, the research integrates direct (Scope 1), indirect energy (Scope 2), and selected value-chain (Scope 3) emissions. The operational data underwent rigorous uncertainty and sensitivity analyses, alongside multi-tier benchmarking against global, climatic, and regional datasets. Findings reveal that total emissions increased from 1444.93 tCO₂e in 2022 to 1592.61 tCO₂e in 2024, predominantly driven by grid-connected electricity, which accounted for approximately 47.1% of the total footprint in 2024. Key operational hotspots include the continuous baseload energy demands of mechanical rooms and lifts, fugitive R-404A refrigerant leakage, and Scope 3 impacts from red meat procurement and organic waste. Furthermore, sensitivity analyses confirmed the footprint’s high elasticity to the national grid’s carbon intensity. Despite the facility outperforming benchmarked peers in overall eco-efficiency, the study concludes with actionable, stratified recommendations for facility engineers, hotel operators, and tourism policymakers to overcome technical, supply-chain, and grid-level barriers to decarbonization. Full article

The use of recycled aggregate concrete (RAC) enables the valorization of construction waste and supports carbon-reduction strategies. However, long-term service-induced deterioration means that recycled aggregates and their interfacial transition zones inevitably contain defects, which severely restrict the safe application of RAC in load-bearing structures. Notably, although RAC reduces embodied carbon by recycling construction waste, steel tube manufacturing introduces an additional carbon footprint; such carbon trade-offs can be well compensated by the improved structural efficiency and extended service life of steel-confined concrete, achieving superior whole-life carbon benefits. In the present study, a steel-tube-confined recycled aggregate concrete (STCRC) composite system is proposed. Through designed external confinement, the stress state of the internal concrete is altered from uniaxial compression to triaxial compression, thereby enhancing its axial load-bearing capacity. Axial compression tests were performed on 36 short column specimens of steel-tube-confined concrete (STCC) composed of C30 aggregate concrete and Q235 steel tubes with three wall thicknesses (4.5 mm, 6 mm, 8 mm). Further parametric finite element analyses with 16 calculation cases were conducted to quantify the effects of higher concrete strength grades (C40 and C50) and of steel tube strength grades. The evolutionary characteristics of the load-displacement response, the axial stress–lateral strain relation, and the lateral strain–longitudinal strain were systematically investigated across various parameters. Test outcomes indicate that steel tube confinement significantly restrains lateral dilation of RAC and enhances its ductility and ultimate bearing capacity, with higher confinement efficiency observed for RAC than for natural aggregate concrete (NAC). Numerical results further identify the differing sensitivities of NAC and RAC to variations in tube wall thickness, steel yield strength, and concrete strength grade. Using combined experimental and numerical datasets, a peak stress modification factor is proposed, and a tailored stress–strain constitutive model for STCRC is developed and validated. The research findings provide theoretical guidance for the design of axially compressed short columns made of prefabricated recycled concrete. Full article

The dual reliance on surface-mount technology (SMT) and pin-through-hole (PTH) assembly lines in high-volume printed circuit board (PCB) manufacturing induces logistical bottlenecks, excessive operational costs, and elevated thermal stress on components. This study presents the optimization of a wireless detector terminal production line by integrating Pin-in-Paste (PiP) technology within a Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) framework. By accurately calculating the required solder volume ($V_{req}$) and stencil aperture dimensions based on pin and pad geometries, the wave soldering process was eliminated without altering existing thermal profiles. The integration consolidated the assembly into a single heat cycle, ensuring IPC-A-610 Class 2 compliance for barrel fill ratios. The results demonstrate a 97% reduction in average assembly costs, yielding annual savings of USD 92,513 while eliminating USD 44,025 in work-in-progress (WIP) inventory. Furthermore, the single-reflow approach mitigated component thermal degradation and reduced the facility’s carbon footprint by an estimated 13.32–17.76 metric tons of CO₂ equivalent annually. This research validates a comprehensive methodology for transitioning to PiP technology, offering a sustainable, cost-effective framework for operational excellence in the electronics’ manufacturing industry. Full article

The assimilation capacity of the biosphere and the sustainability of the living resources are enhanced by the efficient and continued contribution of the vegetation from all ecoregions of the Earth. The urban greenery fulfills many regulatory ecosystem services (RES) as well. In this regard, the importance of urban green spaces (UGS) in helping to reduce the adverse impacts of overcrowding and changing climate is of pertinence. Lack of quantitative information from urban settings in different climatic regions seriously constrains the recognition of the important role UGS play in carbon storage and sequestration. To assess how the UGS is aiding the retention of carbon, which is photosynthetically assimilated into biomass and/or sequestered, relevant field parameters were collected from 4010 trees belonging to 34 different species, different hedge plants, and groundcover grasses spread in 24,991 m² area in three parks of Panaji city, India. Standard methods were followed to derive carbon stock and sequestration rates by trees, hedge plants, and groundcover. Notwithstanding wide differences between tree species, the weighted mean of CO₂ sequestered per tree averaged 55 kg y⁻¹ (ca. 78.82 tons ha⁻¹) in Panaji city. Accordingly, the CO₂ sequestration potential of trees, in the UGS of Panaji (by 76,751 trees) and Tumkur (with an estimated 38,152 trees) cities, respectively, was 4221.31 tons y⁻¹ ha⁻¹ and 2098 tons ha⁻¹ y⁻¹ @ 55 kg tree⁻¹ y⁻¹. It is apparent from this first-time study that calculated tree carbon biomass and species-wise yearly carbon sequestration rates (CSRs) of 78.82 tons ha⁻¹ y⁻¹ and that of carbon production rates of 31.77 tons ha⁻¹ y⁻¹ are far higher than the previously reported CSR estimates variously from 1 to 8 tons ha⁻¹ y⁻¹ and carbon production rates 3.23 to 6.55 tons ha⁻¹ y⁻¹. The hedge row carbon biomass averaged 13.18 tons ha⁻¹ and sequestration of 48.38 tons ha⁻¹ y⁻¹ CO₂. Similarly, occupying over 42% of the UGS, the groundcover carbon biomass averaged 14.69 tons ha⁻¹ with sequestration of 53.92 tons CO₂ ha⁻¹ y⁻¹. Combined CSP of existing trees, groundcover, and hedge plants in Panaji and Tumkur city UGS apparently neutralize carbon footprint of over 4550 and 2200 Indians at an annual per capita emission of 1.94-ton. It is thus undeniable that in our global fight against climate change, the addition of inputs and data from studies like these can aid in planning mitigation measure as well as in fulfilling local/regional sustainability plans and needs. Full article

The metalworking industry faces growing regulatory pressure to quantify and verify its product carbon footprint (PCF), driven by frameworks such as the European Union’s Carbon Border Adjustment Mechanism (CBAM) and emissions trading schemes (ETS). Traditional static accounting methods, based on generic emission factors and annual averages, are insufficient given the dynamic, multi-stakeholder nature of the sector’s supply chains. This study presents a systematic review conducted under the PRISMA 2020 protocol to identify, classify and critically evaluate the digital tools and technologies used to calculate, manage and verify PCF in this sector. From 495 records screened, 53 thematically relevant studies were analyzed and 5 sector-specific cases examined in depth. The results indicate that the Internet of Things (IoT) and smart sensor networks constitute the primary data-capture layer, while Machine Learning, Big Data and Digital Twins are the predominant processing technologies. Blockchain and verifiable digital credentials emerge as governance mechanisms that ensure the transparency, auditability and immutability of emissions inventories, enabling compliance through Digital Product Passports (DPPs). We conclude that digital decarbonization requires interoperable architectures integrating real-time capture, distributed traceability and common semantic standards; viability in small and medium-sized enterprises (SMEs) and interoperability across heterogeneous platforms remain the main research gaps. Full article

This study presents a theoretical justification and simulation analysis of a flat wagon with increased load capacity for the needs of intermodal transport. A modification is proposed by replacing the middle two-axle bogie with a prototype three-axle bogie. Preliminary calculations using mechanics of materials demonstrate the possibility of increasing the payload by 14 tonnes per wagon, thereby improving economic efficiency and reducing the carbon footprint. To assess the safety against derailment and the running behavior, a computational multibody model was developed in the Universal Mechanism software (Version 10.0.7). The simulation results are evaluated in accordance with the requirements of the European standard EN 14363, confirming the operational reliability of the proposed innovative design. Full article

This pilot study presents a surrogate modeling framework for estimating carbon emissions for 35 data centers in the New York City metropolitan area. Using publicly available facility data (square footage, operator type, location), we calculated the annual CO₂e emissions based on standard industry assumptions. These calculated values, which represent modeled emissions rather than measured data, served as the target variable for surrogate model development. A Random Forest regression model was implemented. The model achieved strong performance in producing the calculated emissions with the test set with cross-validated performance (CV R² = 0.960 ± 0.022 and CV MAE = 2431 ± 739 MT CO₂e). Analysis indicated that data center size was the major predictor, accounting for 79.7% of the total feature importance, while location and operator type contributed 13.6% and 6.6%, respectively. As a localized, preliminary feasibility study, this case study demonstrates that surrogate modeling using only publicly available facility data can provide modeled carbon footprint estimates for infrastructure planning and grid decarbonization efforts. The reproducible methodology can be applied to other metropolitan regions, though generalizability requires further validation with larger datasets. Full article

Surface congestion and taxiing delays at high-density airports increasingly constrain aviation sustainability, as ground-phase fuel consumption and emissions constitute a significant share of total airport emissions. Existing studies typically decouple air traffic flow management from ground resource scheduling, hindering coordinated optimization of punctuality, environmental benefits, and resource utilization. This paper proposes a multi-objective optimization method for runway-taxiway systems oriented toward air–ground collaborative decision-making, integrating Calculated Take-Off Time (CTOT) compliance constraints. A tri-objective mixed-integer programming model is formulated to minimize CTOT deviation, total taxiing time, and runway workload imbalance. A hybrid intelligent algorithm, SSA-SCA-NSGA-II, is designed with a bidirectional elite feedback mechanism to address this NP-hard problem. Validation uses real operational data of 58 departure flights during a peak period at Beijing Daxing International Airport. The results demonstrate that the proposed method achieves effective trade-offs on the Pareto front: CTOT compliance rate increased from 77.6% to 89.7–96.6%; total taxiing time decreased from 692 min to 551–635 min; and dual-runway utilization imbalance declined from 5.2% to 1.7–3.8%. These improvements translate into quantifiable sustainability gains: fuel consumption is reduced by 1425–3525 kg and CO₂ emissions by 4503–11,139 kg per peak hour, alongside a 19-percentage point improvement in punctuality that lowers passenger delay costs and reduces controller coordination workload. By simultaneously advancing environmental sustainability (carbon footprint reduction), economic sustainability (fuel and operational cost savings), and social sustainability (service punctuality and labor efficiency), the framework provides a measurable, monitorable, and policy-relevant decision-support tool for green airport surface operations aligned with sustainable development goals (SDGs). Full article

Microalgal lipid extraction, particularly the subsequent solvent recovery phase, constitutes the primary energy bottleneck in algal-based biodiesel biorefineries. Recently, switchable polarity solvents (SPS), such as the tertiary amine N,N-dimethylcyclohexylamine (DMCHA), have emerged as promising ‘green’ alternatives capable of extracting lipids directly from wet biomass, theoretically bypassing energy-intensive drying and solvent recovery distillation stages. This study presents a rigorous techno-energetic and thermodynamic evaluation combined with supporting experiments for qualitative conclusions to scrutinize the actual viability of DMCHA-mediated extraction against conventional hexane benchmarks, across three process configurations using different biomass types: algal liquor, wet paste, and dried biomass. Contrary to widespread assumptions in the literature, fundamental thermodynamic calculations reveal that the energy required for amine regeneration via protonation/deprotonation mechanisms equals or exceeds that of conventional distillation. Furthermore, mitigating biomass drying inadvertently escalates overall downstream energy and economic penalties due to the excessive solvent volumes demanded by dilute aqueous matrices. Direct extraction from algal liquor displays a cost and energy consumption countably higher than the other scenario; precisely, a cost of 232 €/kg of lipids and energy consumption of 454 kWh/kg of lipids. Extraction from wet paste exhibits, indeed, a slightly lower energy consumption compared to the hexane process (respectively 51 kWh/h versus 72 kWh/kg), but, due to the CO₂ requirements, the cost is double (19 €/kg of lipids versus 8 €/kg of lipids). Ultimately, while switchable polarity chemistry offers a marginal reduction in process water footprints, it introduces substantial operational complexity, elevated carbon dioxide payloads, and severe solvent degradation risks, challenging its current readiness for industrial upscaling. Full article

This study evaluates the economic and carbon footprint impact of using calcium lignosulfonate (CLS) in stabilizing highway subgrade on road pavement. Specifically, the effect of stabilized soil strength on layer thickness, costs, and carbon emissions during the initial construction phase was investigated. Two different soil types (clayey and sandy) were used with varying CLS concentrations. Furthermore, the performance of CLS was evaluated using sodium hydroxide-based alkaline activation (AAS). Standard proctor, unconfined compressive strength (UCS), and California bearing ratio tests were applied to the prepared samples. The experimental results showed that CLS significantly increased the CBR and UCS values of the soil samples. Additionally, it was calculated that the initial construction costs of flexible and rigid road pavements designed on stabilized clayey soil decreased by 14.34% and 25.24%, respectively, while on sandy soils, the decreases were 8.10% and 14.95%, respectively. Meanwhile, it has been determined that CO₂ emissions were reduced by up to 10.76% in flexible pavement designs and by up to 17.88% in rigid pavement designs. Consequently, these findings show that the use of CLS in soil stabilization enables both a reduction in the layer thickness of road pavement designs and a reduction in environmental impacts. Full article

Background: The research question explored in this study revolves around the quantitative evaluation of the carbon footprint of cranioplasty surgery, a neurosurgical intervention meant to reconstruct skull defects. Methods: Following a calculation of the emissions pertaining to Scope 1 to 3 of the Greenhouse Gas (GHG) Protocol, the authors engaged with various stakeholders to identify possible interventions meant to drive the carbon efficiency of a cranioplasty pathway. The service improvement project (SIP) that ensued was aimed at reducing the volume and weight of the packaging materials for cranioplasty shipping boxes, and decreasing the paper consumption relative to the preparation of user manuals without compromising patients’ safety. Results: Our analysis indicates a cumulative carbon footprint of 104.35 kg CO₂e for a single unilateral cranioplasty operation, where packaging corresponds to 6.4% of Scope 3 emissions and 1.41% of its total emissions. Of note, our SIP led to an overall 76.53% decrease in the number of emissions generated by the packaging equivalent required for a unilateral titanium implant. Conclusions: This study demonstrates the effectiveness of a partnership between public institutions and medtech companies in driving carbon net efficiency of a cranioplasty pathway, and we suggest that such approach is scalable to other surgical specialties. Full article

This paper presents an exploratory operational assessment of the carbon footprint of an LNG tanker using real operational data collected by a continuous emission monitoring system over a ten-month period of vessel operation. The analysis included carbon dioxide (CO₂) and methane (CH₄) emissions from the main engines and diesel generators, the calculation of CO₂-equivalent using the GWP₁₀₀ and GWP₂₀ global warming potential factors, and a comparison with a hypothetical heavy fuel oil (HFO) operating scenario. The methodology is based on a Tier III approach, that is, on real operational data, which allows a more realistic assessment of emissions than approaches based on standard emission factors. The results show that CO₂ emissions make up the largest share of total emissions, but including methane emissions significantly increases the ship’s overall climate impact. Total methane slip was 3.62%, with diesel generators exhibiting higher slip than the main engines. When GWP₂₀ was applied, total emissions expressed as CO₂-equivalent were, in some periods, comparable to or higher than those estimated for the HFO scenario, despite lower direct CO₂ emissions. The emission distribution indicated that the main engines dominated CO₂ emissions, while methane emissions were more evenly distributed between the main engines and the auxiliary generators, with generators making a significant contribution to total CO₂-equivalent emissions due to their higher methane slip. The results confirm that any assessment of the climate performance of LNG-fueled operation must include methane emissions and should be based on real operational data; otherwise, the overall climate impact may be underestimated. Full article

Background/Objectives: Animal-source protein consumption in Saudi Arabia has increased substantially over the last two decades, raising concerns regarding its environmental impact in a country with among the highest per capita carbon emissions globally. Despite growing interest in sustainable diets, empirical evidence on dietary carbon footprint (CF) in Gulf Cooperation Council countries remains limited. This study aimed to quantify the CF associated with the consumption of animal- and plant-based protein foods among Saudi adults and to identify sociodemographic and lifestyle predictors of dietary CF, with attention to sex differences. Methods: A cross-sectional study was conducted among 1624 Saudi adults (47.1% males; 52.9% females). A newly developed, expert-reviewed, and pilot-tested food frequency questionnaire covering 21 protein-containing food items (13 animal-based; 8 plant-based) was used to estimate daily intake. CF values were calculated using Life Cycle Assessment-derived greenhouse gas emission factors (kgCO₂e/kg food) obtained from peer-reviewed sources. Sex-stratified multiple linear regression models and a pooled sex × animal-source protein food interaction model was used to identify independent predictors of daily CF. Results: Animal-source protein foods contributed 45,641.8 kgCO₂e/week to cumulative CF—a 64-fold excess over plant-based sources (708.33 kgCO₂e/week). Mean individual protein-food CF was 4.07 kgCO₂e/day, of which 98.5% derived from animal sources. Lamb and beef carried the highest emission intensities; nuts the lowest. Animal-source intake was the strongest independent predictor of CF in both sexes, with a significantly stronger association in males than females. High consumers substantially exceeded EAT–Lancet red meat targets across all consumption strata. Conclusions: Red meat dominates protein-food-related GHG emissions among Saudi adults. Even a partial dietary shift toward plant-based proteins, embedded within a coordinated food-system transformation framework, could substantially reduce per capita emissions in alignment with Saudi Vision 2030 and One Health targets. Full article

The application of urea in agricultural practices leads to carbon dioxide (CO₂) emissions through hydrolysis. Urea, when applied to soil, reacts with water and undergoes hydrolysis, releasing ammonia (NH₃) and CO₂. This reaction is facilitated by soil enzymes such as urease. The released NH₃ can further undergo nitrification, producing nitrate (NO₃⁻) and nitrous oxide (N₂O). While CO₂ from urea hydrolysis is relatively small compared to other sources, cumulative emissions from agricultural activities contribute significantly to climate change and agriculture’s carbon footprint. A straightforward calculation model (CO₂ = A × 0.73) was employed to approximate CO₂ emissions in various countries based on annual urea usage. In this model, China led emissions with 40,483 Gg yr⁻¹, followed by India (26,031 Gg yr⁻¹) and the USA (12,032 Gg yr⁻¹). Out of total annual emissions (94,763 Gg), China contributed 43%, India 27%, the USA 13%, the EU 8%, Pakistan 5%, and Indonesia 4%. China’s CO₂ emissions from urea were 16% higher than India, 30% higher than the USA, 35% higher than the EU, 38% higher than Pakistan, and 39% higher than Indonesia. As expected from the deterministic IPCC formula (CO₂ = Urea × 0.73), the relationship between urea consumption and CO₂ emissions is linear with a slope of 0.73. Linear regression shows that for every 1000-ton increase in urea consumption, CO₂ emissions increase by 730 tons (0.73 Gg) (R² = 0.99, p < 0.001). Pakistan’s urea consumption grew at an average annual rate of 2.2% from 2015 to 2023, with corresponding CO₂ emissions increasing from 4015 to 4788 Gg yr⁻¹ (total increase of 20% over eight years). Optimizing fertilizer application rates, timing, and methods to enhance nutrient uptake efficiency, along with sustainable agricultural practices (organic matter management, conservation tillage, and precision agriculture), can help mitigate environmental impacts. This study emphasizes implementing sustainable agricultural practices and integrated nutrient management to minimize CO₂ emissions from urea application, enabling agricultural systems to contribute to climate change mitigation and reduced carbon footprints. Full article

Against the backdrop of global climate change and the “dual carbon” goals, the issue of agricultural greenhouse gas emissions has garnered increasing attention. As a major grain and oilseed crop in China, carbon emissions from soybean production have a significant impact on the green and low-carbon development of agriculture. Although research on agricultural carbon footprints has grown in recent years, existing studies have largely focused on single regions or specific stages of crop production, and analyses of the carbon footprint of production systems in China’s major soybean-producing regions remain relatively limited. This study employs the Life Cycle Assessment (LCA) methodology to calculate and analyze the carbon footprint of soybean production systems across China’s 10 major soybean-producing provinces, utilizing agricultural input data from 2014 to 2023. The study establishes a carbon footprint accounting system based on two key aspects: carbon emissions from agricultural inputs and soil N₂O emissions. It further analyzes the temporal trends, regional variations, and contribution characteristics of each component within the carbon footprint. The results indicate that the average carbon footprint of soybean production in China is approximately 528 kg CO₂eq/ha (ranging from 273 to 855) and 0.25 CO₂eq/kg of soybean (ranging from 0.13 to 0.46). Specifically, the carbon footprint per unit of area and yield declined simultaneously, indicating a continuous improvement in the low-carbon efficiency of soybean production. Spatially, there are significant regional differences in the carbon footprint of soybean production. Henan, Anhui, and Inner Mongolia have relatively low carbon footprints, while Shaanxi and Shanxi have relatively high levels. In terms of composition, chemical fertilizer inputs and soil N₂O emissions are the primary sources of the carbon footprint in soybean production, with chemical fertilizer inputs being the largest source, accounting for approximately 40–60%, and soil N₂O emissions being the second major source. Overall, differences among regions in natural conditions, agricultural input structures, and production methods result in distinct regional characteristics in the carbon footprint composition. The findings of this study provide a scientific basis for the low-carbon transition of China’s soybean production system and serve as a reference for the formulation of policies related to green agricultural development. Full article