Estimation Of Carbon Footprint Research Articles

LCA comparativo en distintos escenarios del edificio NZEB El Salvador, estimación de CO2 para el desempeño térmico

The recent IPCC 2023 report reiterates that humansare responsible for global warming over the past 200 years, causing a rise temperature of 1.1°C above pre-industrial levels, as well as an increase in energy demand, which can be avoided with mitigation options, reducing its use in all sectors, especially in the building sector. One of the options is the design based on the NZEB concept, as it has been the case of the laboratory built on the UCA campus, using passive and active energy efficiency strategies, studying the interaction between construction systems and energy savings. One of the NZEB El Salvador project research objectives, was to study the thermal performance of different construction scenarios, therefore, the present work presents the results of the Life-cycle assessment(LCA) in three proposals for popular construction systems in El Salvador, regulated by the national regulatory framework, comparing them with the baseline of its current operation, through 3 iterative calculation tools: structural, thermal and carbon footprint estimation, managing to find importantfindings on how vernacular systems meet the NZEB standard. ILIA: Investigaciones Latinoamericanas en Ingeniería y Arquitectura, No. 01, 2024: 160-166.

Estimated Carbon Savings from Changing Surgical Trends in Primary Elective Total Hip Arthroplasty in England: A Retrospective Observational Study.

The National Health Service (NHS) in England has set a target to be net zero for carbon emissions by 2045. The aim of this study was to investigate how changes in key aspects of clinical practice over the last 8 years have contributed towards reducing the per-patient carbon footprint of elective total hip arthroplasty (THA). This was a retrospective analysis of administrative data. Data were extracted from the Hospital Episode Statistics database for all adult (≥ 17 years), primary, elective THA procedures conducted in England from 1 April, 2014 to 31 March, 2022. The estimated carbon footprint for key elements of the surgical pathway were calculated based on data from Greener NHS and the Sustainable Healthcare Coalition. Data were available for 537,441 THA procedures conducted during the study period. The per-patient carbon footprint associated with the primary THA (index) procedure fell by around 25% from 2014/15 to 2021/22. Length of stay was by far the largest contributor to this decline, falling from 169.1 kgCO2e to 117.6 kgCO2e per patient from 2014/15 to 2021/22. Absolute declines in the carbon footprint associated with emergency readmissions, revisions and outpatient attendances were more modest. If all patients in all years had the 2021/22 average carbon footprint, then carbon equivalent to powering 19,976 UK homes for 1year would have been saved. Improving per-patient efficiency of surgery is likely to contribute towards meeting the NHS's net-zero target whilst also helping to improve patient outcomes, reduce costs and cut waiting lists.

FP8.2 - Sustainability Within the Abscess Pathway

Abstract Background Global warming and the current climate crisis remain a threat to global health. It is estimated that 5% of the total carbon footprint of an acute NHS organisation was attributable to general anaesthetic (GA) gases, which contributes to ongoing ozone depletion. Aims To review current practices in managing abscesses and improve sustainability within the abscess pathway in our trust. Methods Retrospective data on all patients who underwent incision and drainages (I&D) between January – July 2022 were collected and analysed. A new abscess pathway was introduced in June 2023 and departmental teaching provided to junior doctors on incision and drainage of abscesses under local anaesthetic (LA). Data on patients who underwent I&D between June – September 2023 were collected and analysed to assess the impact of the new abscess pathway. Results In the first-cycle audit, 162 patients underwent I&D, of which 119 (92%) were done under GA. Of these, 71 (60%) were suitable for LA I&Ds, 91% were admitted for their procedures. The estimated carbon footprint was 4525kg CO2e/year. In the second-cycle audit, 68 patients underwent I&D, of which 37 (76%) were done under GA. Of these, 31 (46%) were suitable for LA I&Ds, 41% were admitted for their procedures. The estimated carbon footprint was 3735kg CO2e/year. Conclusions Following implementation of the new abscess pathway, we reduced the number of patients having general anaesthetic procedures and inpatient admission. This not only improves the sustainability of our practice, but makes treatment and recovery quicker for patients, and has a lower financial burden.

Determinant factor of environmental quality based on carbon footprint levels in Asia using regression model and Jacobian optimization method

Abstract The rapid economic growth in Asia has resulted in significant carbon emissions, leading to global climate change and environmental degradation. The situation is closely linked to increased industrial activities, population growth, and high energy consumption. Thus, this research is focused on analyzing whether the growth domestic product per capita, foreign direct investment per capita, energy use per capita, and forestland emissions per capita are associated with carbon footprint records in Asia. The attempt is conducted by employing parameter estimation of carbon footprint using a regression model and Jacobian Optimization procedure. The model incorporates data from FAOSTAT, Global Footprint Network, and the World Bank in 2021. The result suggested that if GDP per capita increases by 1,000 units, then the estimated average of carbon footprint per capita will also increase by 0.2, holding other variables remain constant. The finding contributes to formulating effective strategies for carbon footprint reduction and sustainable development in the region. The optimized parameter estimation provides valuable insights into the factors affecting the carbon footprint in Asia.

Reducing single-use plastics in dental practice: a quality improvement project.

Introduction Climate change is a major issue facing the global population. Healthcare services, including dentistry, have an obligation to examine current practice and reduce the carbon footprint of their services. Single-use plastics, for example, those used to cover dental equipment, are not necessarily essential for cross-infection purposes.Materials and methods This quality improvement project was carried out in 2023 across 12 dental practices in the North London dental foundation training scheme. Baseline financial and environmental costs were estimated for the weekly single-use barrier plastics used in each practice. This was communicated to each practice. Practices using single-use plastics were contacted three months later to see if they had made any changes.Results In total, 10 out of 12 practices were using one or more of the single-use plastics at baseline, with an estimated carbon footprint ranging from 0.07-27.02 kg carbon dioxide equivalent (CO2e) per week. Three practices reduced or eliminated their single-use plastics as a result of this quality improvement project, which resulted in an equivalent saving of 46.87 kg CO2e per week.Discussion and conclusion The use of single-use plastic barriers varies widely between dental practices and is associated with a financial and environmental cost. Infection control guidelines are unclear with their recommendations. The authors urge dental services to reduce their single-use plastic barriers and would encourage infection control guidelines to consider the environmental impact when making recommendations.

Correction: Kurian et al. Estimation of Carbon Footprint of Residential Building in Warm Humid Climate of India through BIM. Energies 2021, 14, 4237

There was an error in the original publication [...]

Carbon footprint of the predominant mechanized timber harvesting methods in the Northeastern US

Estimating carbon footprint of forest operations is essential to budget the environmental impacts of the industry. The study objectives were to a) assess the carbon footprint of whole-tree (WT), cut-to-length (CTL), and hybrid cut-to-length (Hyb CTL) harvesting methods in the Northeastern US; b) assess global warming potential of various processes involved in timber harvesting for different harvest methods; and c) evaluate variation in the carbon footprint for the summer and winter harvest. SimaPro 9.3.0.3 software and allied databases (USLCI and US-EI 2.2) adhering to ISO 14,040 and 14,044 standards were used for cradle-to-gate life cycle assessment (LCA) with a functional unit of 1 tonne of green roundwood. Tool for reduction and assessment of chemicals and other environmental impacts (TRACI v 2.1) was used for impact assessment. The input variables were quantity of fuel (liter tonne-1) and lubricants (kg tonne-1) for respective harvesting operations. The results of LCA showed that carbon footprint was highest for WT (11.57 kg CO2 eq), followed by Hyb CTL (11.09 kg CO2 eq) and CTL (9.91 kg CO2 eq) methods. Secondary transportation (trucking) had highest global warming potential among the processes. Winter harvest had a higher carbon footprint than summer by 2 and 3 percent, respectively, for CTL and Hyb CTL methods. The extra time needed to warm up engine resulted in a higher carbon footprint for winter harvest. Higher carbon footprint for WT method can be attributed to greater number of equipment involved for WT resulting in more fuel consumption, compared to other methods. Among the stump-to-landing processes, skidding contributed foremost in WT, whereas felling and processing in CTL, and processing in Hyb CTL, respectively. These results could be used in the upstream process for future LCA of different wood products manufactured in the region.

Changing carbon footprints and the consequent impacts of carbon taxes and cash transfers on poverty and inequality across years: A Peruvian case study

Carbon taxes are key policies to achieve climate goals. Yet, they increase prices especially in the short term, and can affect households’ income depending on their carbon footprints. Cash transfer programs can be used to address adverse social impacts and protect the poorest. However, because carbon footprints, and the consequent tax impacts, may change over time it is important to understand how to design and adapt such cash transfer programs accordingly. As the existing studies focus on single years, we address the gap in the literature in two steps. First, we estimate changes in carbon footprints and their drivers over time; second, we simulate the effects of a carbon tax in combination with cash transfers on poverty and inequality for the years 2004, 2007 and 2011 in Peru. We combine a bottom-up household carbon footprint estimation, and multiple scenarios simulation. We show that, in a context of rapid economic growth, footprints increase over time, particularly for lower deciles. Most importantly, the distributional impacts of a reform combining carbon tax and cash transfers change by year. The paper concludes that, to maximize poverty and inequality reduction, the design of cash transfer programs and tax levels need to be adapted over time.

A retrospective audit with subsequent cost and environmental analysis of a denosumab self-injection program.

The Metabolic Bone Health Department, Cardiff and Vale University Health Board, serves a local population of approximately 445 000 people. A retrospective audit of attendance data regarding the denosumab treatment clinic (the traditional treatment pathway) and the denosumab Self-Injection Program (SIP) was conducted to determine whether the SIP is both cost-effective and environmentally beneficial, compared to the traditional treatment pathway. Cost analysis was then conducted by the Finance Department. The audit was conducted over 3years following the implementation of the service development; 233 patients had enrolled in the program at the time of the audit and 69 had completed 3years of self-injected treatment. A control group of 497 patients were identified by the service. This group remained on the historical pathway and had consistent attendance activity over the 3-yr period from 2017 to 2019. Pre- and post-period activity of all patients on the program was compared, together with the activity for the independent control group. The SIP resulted in a reduction in clinical contacts, with financial analysis showing a total opportunity cost saving per patient of £420 per annum. There were obvious benefits to the patient of a reduced number of visits to a clinical site, which also resulted in an estimated carbon footprint reduction of 59 kg CO2 per patient per annum. The cost analysis is based on our organization's 2022 charges. The SIP demonstrates that by focusing on care "closer to home", it is possible to maximize resources, improve the patient experience through reduced travel, and reduce the environmental impact of healthcare.

Towards Carbon Footprint Management in Hybrid Multicloud

Enterprises today aspire to optimize the operating costs and carbon footprint (CFP) of their IT operations jointly without compromising their business imperatives. This has given rise to a hybrid approach in which enterprises retain the dynamic choice to leverage private data centers and one or more public clouds in conjunction. While cloud service providers (CSPs) have long provided APIs for estimating, reconciling, and optimizing operating costs, they have only recently started exposing APIs related to CFP. Indeed, this is a step in the right direction. Nevertheless, our analyses of these APIs reveals many gaps that need to be addressed to facilitate sizing and placement decisions that can factor in carbon. First, there is a lack of standardized, transparent methodology for CFP quantification across different CSPs. Second, the coarse granularity of the CFP data provided today can help with post-facto reporting but is not suitable for proactive fine-grained optimization. Last, enterprises themselves are unable to independently compute the current CFP or estimate potential CFP savings since CSPs do not share the required power usage data. To address these gaps, enterprises have started developing their own carbon assessment methodologies and tools to estimate the CFP of workloads running on public clouds using the available user-facing APIs. These systems hold the promise for an independent and unbiased evaluation and estimation of relative savings between different deployment options by cloud users. We describe and analyze the details of CSP-native carbon-reporting tools and their quantification methodology, and the "outside-of-the-cloud" estimation approaches. Finally, we present opportunities for future research in the direction of trustworthy, fine-grained, public cloud workload CFP estimation, which is a prerequisite for meaningful realization of carbon optimization.

Estimation of carbon footprint of Indian households in Kalyani subdivision of district Nadia, West Bengal, India

The present study aims to assess the contribution of Indian households to the increase in carbon footprint. Hence, this cross-sectional study was conducted in the Kalyani subdivision of Nadia district, West Bengal, India. Data were collected from 610 households, comprising 299 rural and 311 urban households, to analyse energy consumption patterns for various purposes. To summarize the dependent and continuous data, descriptive statistics were employed, while for inferences, independent sample t-test, Pearson correlation and regression were used. A significant difference was observed in total annual household carbon footprint between the urban and rural households due to varied energy consumption (t = 15.60, p < 0.05). The urban households were emitting twice (2325.20 kgCO2e) as much as the rural ones (1125.77 kgCO2e). It can also be inferred that emission was determined by the increase in household size, income, and improvement in the standard of living. Thus, in addition to several determinants, a complex cultural system, social practices, and awareness of green consumerism should also be incorporated and studied through an interdisciplinary approach to reduce the overall household carbon footprint.

Artificial Intelligence and Digital Tools for Assisting Low-Carbon Architectural Design: Merging the Use of Machine Learning, Large Language Models, and Building Information Modeling for Life Cycle Assessment Tool Development

The construction sector is a significant contributor to global carbon emissions and a major consumer of non-renewable resources. Architectural design decisions play a critical role in a building’s carbon footprint, making it essential to incorporate environmental analyses at various design stages. Integrating artificial intelligence (AI) and building information modeling (BIM) can support designers in achieving low-carbon architectural design. The proposed solution involves the development of a Life Cycle Assessment (LCA) tool. This study presents a novel approach to optimizing the environmental impact of architectural projects. It combines machine learning (ML), large language models (LLMs), and building information modeling (BIM) technologies. The first case studies present specific examples of tools developed for this purpose. The first case study details a machine learning-assisted tool used for estimating carbon footprints during the design phase and shows numerical carbon footprint optimization results. The second case study explores the use of LLMs, specifically ChatGPT, as virtual assistants to suggest optimizations in architectural design and shows tests on the suggestions made by the LLM. The third case study discusses integrating BIM in the form of an IFC file, carbon footprint analysis, and AI into a comprehensive 3D application, emphasizing the importance of AI in enhancing decision-making processes in architectural design.

Life cycle assessment in net zero energy building scenarios in a tropical country

The recent IPCC 2023 report reiterates that humans are responsible for global warming over the past 200 years, causing a rise in temperature of 1.1 °C above pre-industrial levels, urging the implementation of mitigation options, especially in the building energy sector. One strong mitigation strategy is designing and building net zero energy buildings (NZEB), although their implementation faces challenges such as opposition to change, especially in tropical countries with traditional and conservative design and construction practices. This paper uses data from a pilot NZEB Laboratory building at UCA, El Salvador, and details its results by comparing different construction system scenarios. The present work presents the results of the Life-cycle assessment (LCA) in three popular construction systems in El Salvador, comparing them with the baseline of its current operation, through 3 iterative calculation tools: structural, thermal and carbon footprint estimation, managing to visualize important findings on how vernacular systems could meet the NZEB performance with added insulation in the structural walls. In addition, a triple-axis sustainability analysis (environmental, economic and social) is conducted using the weighted criteria matrix, which provides nuanced results, such as the proportional share of embodied carbon between the proposals, there is not much difference between the results of the proposed systems, but compared to the baseline, the proposals represent a significant increase of more than 50%. Our results show that in this context, the scalability of NZEB buildings is feasible for different construction systems, paving the way for a progressive and incremental.

The carbon footprint of livestock farms under conventional management and silvopastoral systems in Jalisco, Chiapas, and Campeche (Mexico)

Livestock production is one of the most important agricultural sources of greenhouses gasses (GHG). Transforming the livestock sector is a critical task to mitigate the effects of climate change, and the implementation of silvopastoral systems (SPS) may be a way to do so. Carbon footprint (CF) estimation was carried out for 131 conventional livestock farms (CONF) and SPS farms (SPSF) selected in the states of Jalisco, Chiapas and Campeche (Mexico). GHG emissions were estimated based on interviews with the farmers and farm monitoring to collect information about management, milk production and the live weight gain (LWG) of calves (for meat production) using national emission factors. Emissions from animals, fossil fuels, electricity and nitrogen fertilizers were estimated using Tier I and II criteria. Land use distribution was recorded for each farm, and their carbon fixation in total biomass and soils was estimated using studies from tropical Latin America. CF was estimated for area and for production of milk and the LWG of calves. SPSF had lower GHG emissions, higher carbon fixation rates and a better CF than CONF (5.7 vs. 8.0 t CO2e/ha/year; 6.9 vs. 5.5 t C/ha/year and − 5.0 vs. −2.9 t CO2e/ha/year, respectively). The CF of milk production and calf LWG were − 68.6 to −4.6 kg CO2e/kg and − 3.2 to −0.1 t CO2e/kg, respectively. Our results highlight the importance of implementing SPS to mitigate climate change in livestock production, given its contribution to GHG emissions and the importance of capturing atmospheric carbon in biomass and soils. National and regional policies should focus on promoting implementing SPS as an active and effective strategy for improving CF in livestock farms.

Revealing the ecological footprint of Argan (Argania spinosa) derivatives: A comprehensive analysis of the carbon impact of Argan oil

Argania spinosa, commonly known as the Argan tree, assumes a crucial role in bolstering environmental sustainability by augmenting carbon storage in both biomass and soil. Despite its significant environmental contributions, there exists a conspicuous gap in scientific research and data pertaining to the carbon dynamics associated with Moroccan Argan forest ecosystems and their prized products, particularly Argan oil. To address this research gap, our study meticulously investigates the intricate details of the carbon footprint linked to Argan oil production within the "Argan Biosphere Reserve" in southern Morocco.This innovative research aims to deliver a comprehensive assessment of the carbon footprint within the Argan oil industry, conducting a thorough examination of 10 companies and 16 cooperatives actively involved in production. The foundation of this investigation rests on on-site interviews with leaders of production units, systematically gathering essential data for rigorous analysis.Employing the "Bilan Carbone" tool, we intricately calculated emissions, categorizing them into three scopes. The resulting carbon footprint outcomes were meticulously delineated across three distinct scenarios, shedding light on the nuanced dynamics of greenhouse gas emissions.In the first scenario, encompassing all scopes, including export-related emissions, companies displayed an average carbon footprint of approximately 10.17 kg CO2 eq.l−1, while cooperatives recorded 8.68 kg CO2 eq.l−1. The second scenario, excluding export-related emissions, unveiled companies with an average carbon footprint of 3.71 kg CO2-eq.l−1 and cooperatives with 6.32 kg CO2-eq.l−1. The third Scenario, concentrating solely on scopes 1 and 2, indicated companies with an average estimated carbon footprint of 1.31 kg CO2 eq.l−1, and cooperatives with approximately 3.01 kg CO2 eq.l−1.Delving deeper into the intricacies of emissions by scenario and oil-producing organizations, our findings underscore the substantial impact of electricity consumption on the overall carbon footprint of Argan oil. For companies, electricity consumption contributed between 10.84% (first scenario) and 66.97% (third scenario), while for cooperatives, the range was 26.97% (first scenario) to 75.57% (third scenario).To optimize the carbon footprint, our study recommends strategic interventions such as reducing electricity and butane consumption. Moreover, adopting sustainable practices, including leveraging photovoltaic electricity and synthetic gas from the pyrolysis of Argan byproducts, can significantly curtail the average carbon footprint of companies and cooperatives, charting a trajectory toward environmental sustainability. Specifically, a reduction of 37.05% and 40.75% (second scenario) and an impressive 71.66% and 77.01% (third scenario) for companies and cooperatives, respectively, could be achieved after a 30-year amortization period of photovoltaic panels.These findings not only contribute valuable insights into the environmental impact of Argan oil production but also pave the way for future in-depth studies and the formulation of sustainable pathways to optimize the carbon footprint of this critical industry.

47 Application of a ‘high’ or ‘low’ energy matrix to a nutrient-reduced diet supplemented with a novel phytase maintained growth performance and conferred production and sustainability benefit

Abstract This study assessed the capacity of a novel consensus bacterial 6-phytase variant (PhyG) to maintain growth performance of weaned pigs when added to a nutrient-reduced mixed cereal diet with two levels of dietary net energy (NE) reduction applied. A total of 360 newly weaned pigs [Greater York × Norsvin Landrace; initial body weight (BW) 8.4 ± 0.78 kg] were assigned to 60 floor-pens and 5 dietary treatments in a randomized complete block design. There were 2 blocks (weaning group), 6 replicate pens per block, and 6 pigs/pen (3 male, 3 female), in total of 12 replications per treatment. Diets were based on wheat, corn, barley, and soybean meal and were offered to pigs in 2 phases in pelleted form (0–14 and 14–35 d post-weaning). Treatments comprised a nutritionally adequate positive control (PC) and 4 negative control (NC) diets supplemented with PhyG. The NC diets were reduced in digestible P, Ca, Na, and digestible amino acids vs. PC, according to the expected contribution of PhyG added at 1,000 phytase units (FTU)/kg (NC1) or 2,000 FTU/kg (NC2), respectively. Each NC1 and NC2 was formulated at two NE reduction levels, designated ‘low’ and ‘high’ (‘low’: -53 to -65 kcal/kg and ‘high’: -73 to -86 kcal/kg, vs. PC at 1,000 and 2,000 FTU/kg PhyG, respectively). Data were analyzed by ANOVA. Means separation was by Tukey’s HSD test. During both phases and overall (0–35 d), average BW, average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR) in all PhyG-supplemented, nutrient- and NE-reduced treatments, were either not different or were improved compared with the PC. Overall ADG, ADFI, and final BW (d 35) were greater in NC2+PhyG 2,000 FTU/kg ‘low’ vs. PC (466 vs. 424 g, 9.9%, 622 vs. 567 g, 9.7%, and 24.7 vs. 23.1 kg, 6.9%, respectively; P < 0.05). Total feed costs (ingredients price, February 2023) and estimated carbon footprint (CFP; FeedPrint, WUR, The Netherland) per kilogram of BW gain (BWG) were reduced in all PhyG-supplemented, nutrient- and NE-reduced treatments vs. PC. Feed costs saving per kg BWG were greater with ‘high’ than ‘low’ NE reduction applied (-0.013 vs. -0.007 €, respectively, vs. PC) with PhyG at 1,000 FTU/kg, and it was greatest in NC2+PhyG 2,000 FTU/kg with ‘low’ NE reduction (-0.036 € vs. PC). Similarly, the CFP was reduced from 2,068 to 1,840 g CO2 eq/kg BWG (-11 %) by NC2+PhyG 2,000 FTU/kg with ‘low’ NE reduction vs. PC. In conclusion, the application of a full nutrient matrix with ‘high’ or ‘low’ NE reduction combined with supplementation of PhyG maintained growth performance of weaned pigs and reduced the total feed costs and carbon footprint per kg BW gain, lead to production and sustainability benefits.

All's eco‐friendly that ends eco‐friendly: Short‐term memory effects in carbon footprint estimates of temporal item sequences

AbstractWhen people estimate the summative carbon footprint of a sequence of events, how are the individual events integrated? In three experiments, we found that summative carbon footprint judgments of item sequences are disproportionately influenced by items at the end of the sequence in comparison with those at the beginning—a recency effect. When, for example, sequences ended with a low carbon footprint item, they were assigned a lower carbon footprint than corresponding sequences with an identical content but different item order. The results also revealed that a green peak (presenting many low carbon footprint items at once) had a relatively large effect on estimates when the peak was contextually distinct from other items in terms of its valence. The results are consistent with an account within which distinctiveness of representations within short‐term memory differentially influences decision‐making and suggest that memory processes bias the perceived environmental footprint of temporally separated instances.

Average total weight of surgical waste and CO2 carbon footprint of orthopedic surgery in France, estimated on the basis of a representative panel

BackgroundReduction of waste and carbon footprint can be optimized. Awareness of carbon sources and quantification of the waste are two key parameters. To our knowledge, there is no study in France on waste production by the surgical team during the operation in orthopedic surgery, in a global scope. Therefore, we performed an observational investigation aiming to: (1) quantify and characterize the weight of the wastes generated after a panel of orthopedic procedures, (2) calculate the CO2 footprint generated by these wastes and extrapolate the figure at the national scale. HypothesisWaste production is highly variable according to the types of procedures and infectious clinical waste is still a predominant source of waste and CO2 emission. Materials and methodsIt is a comparative and prospective study in which a total of 14 procedures were selected as a representative panel: arthroplasties (hip, knee), spine fusions, arthroscopic procedures (shoulder, knee), nerve release, forefoot osteotomies, trauma procedures. The main outcome was the average total weight of waste for each of the fourteen categories (280 measurements: 140 times 2, at the end of each procedure), expressed in kilograms (kg), and the proportions of infectious clinical waste (ICW) and household wastes (HW), expressed in percentages. Ten measures were prospectively recorded for each type of procedure in a single teaching hospital from January to September 2022. The theoretical carbon footprint generated by the treatment of the wastes was estimated in kilograms of CO2 equivalent (KgEqCO2). The national extrapolation of the carbon footprint was performed by collecting the total number of procedures in France in 2021 using the VisuChir tool. ResultsA total of 937kg of waste were produced for the 140 procedures, amongst which 514kg of ICW (54.8%) and 423kg of HW (45.2%). The overall median waste weight was 5.9kg (Q1: 4.4, Q3: 8.1), ranging from 1.8kg to 18.3kg. The overall median waste weight for HW was 2.8kg (Q1: 2.5, Q3: 3.4), ranging from 1.8kg to 17.8kg. The overall median waste weight for ICW was 3.8kg (Q1: 2.7, Q3: 4.8), ranging from 0.8kg to 7.2kg. The knee surgeries were responsible for the heaviest waste weight; the least waste-productive procedures were the foot and the carpal tunnel release. The median proportions of ICW varied from 39% for the total knee replacements to 72% for the femoral nails. There was a significant inverse correlation between the total waste weight and the proportion of ICW: r=−0.47, p<10−4. The total median estimated carbon footprint was 4.3KgCO2Eq (Q1: 3.1, Q3: 5.8), ranging from 1.59KgCO2Eq (Q1: 1.5, Q3: 1.8) and 7.07KgCO2Eq (Q1: 6.7, Q3: 8.17). The total median estimated carbon footprint was 3.5KgCO2Eq for ICW (Q1: 2.5, Q3: 4.5) and 0.76KgCO2Eq (Q1: 0.54, Q3: 1.3) for HW. The national median estimated carbon footprint was 10.1 million KgEqCO2 in 2021 for orthopedic surgery. ConclusionOur study revealed that in most cases more than half of the wastes were ICW. The total estimated national carbon footprint for orthopedic procedures was 10 million kilograms. The reduction of the ICW constitutes a cornerstone, as they are responsible for more carbon emissions. Level of evidenceIII; prospective comparative observational in vivo study.

The computational and energy cost of simulation and storage for climate science: lessons from CMIP6

Abstract. The Coupled Model Intercomparison Project (CMIP) is one of the biggest international efforts aimed at better understanding the past, present, and future of climate changes in a multi-model context. A total of 21 model intercomparison projects (MIPs) were endorsed in its sixth phase (CMIP6), which included 190 different experiments that were used to simulate 40 000 years and produced around 40 PB of data in total. This paper presents the main findings obtained from the CPMIP (the Computational Performance Model Intercomparison Project), a collection of a common set of metrics, specifically designed for assessing climate model performance. These metrics were exclusively collected from the production runs of experiments used in CMIP6 and primarily from institutions within the IS-ENES3 consortium. The document presents the full set of CPMIP metrics per institution and experiment, including a detailed analysis and discussion of each of the measurements. During the analysis, we found a positive correlation between the core hours needed, the complexity of the models, and the resolution used. Likewise, we show that between 5 %–15 % of the execution cost is spent in the coupling between independent components, and it only gets worse by increasing the number of resources. From the data, it is clear that queue times have a great impact on the actual speed achieved and have a huge variability across different institutions, ranging from none to up to 78 % execution overhead. Furthermore, our evaluation shows that the estimated carbon footprint of running such big simulations within the IS-ENES3 consortium is 1692 t of CO2 equivalent. As a result of the collection, we contribute to the creation of a comprehensive database for future community reference, establishing a benchmark for evaluation and facilitating the multi-model, multi-platform comparisons crucial for understanding climate modelling performance. Given the diverse range of applications, configurations, and hardware utilised, further work is required for the standardisation and formulation of general rules. The paper concludes with recommendations for future exercises aimed at addressing the encountered challenges which will facilitate more collections of a similar nature.

Impacts of Behavioral, Organizational, and Spatial Factors on the Carbon Footprint of Traditional Retail and E-commerce in the Paris Region.

Carbon footprint assessment of retail is necessary to optimize procurement strategies and adopt sustainable shopping habits. However, estimating carbon footprints is a complex task, given the diversity of existing distribution channels. Average values for carbon emissions of "conventional" retail (i.e., purchasing and receiving the product directly at the physical point of sale) found in most studies mask a heterogeneous reality: different retail strategies entail diverse shopping behavior for consumers, as well as varied procurement processes for outlets. In this paper, we propose a methodology to assess greenhouse gas (GHG) impacts of different distribution systems related to the consumption of goods in the Paris Region by coupling traditional transport modeling with a life-cycle assessment (LCA) approach. We model and compare six distribution systems, including five traditional retail formats (hypermarkets, supermarkets, small generalist retail, small food retail, and small nonfood retail) and E-commerce home deliveries. Our model includes warehouse activity, shop and home delivery, shop energy consumption, consumer mobility, and goods packaging. Overall, we conclude that E-commerce emits fewer GHG emissions than retail outlets per kilogram of product purchased. This result is in line with the existing literature on the topic. However, the carbon footprint varies greatly within the case study depending on the characteristics of the logistics procurement processes of outlets, the behavior of shoppers, and spatial characteristics.