Search Results (444)

Electricity is a significant factor in the life cycle of many products, so the reliability of greenhouse gas (GHG) emissions data is crucial. The article presents publicly available sources of emission factors representative of Poland. The aim of the study is to assess their strengths and weaknesses in the context of the calculation requirements of carbon footprint analysis in accordance with the GHG Protocol. The article presents the results of carbon footprint calculations for different ranges of emissions in the life cycle of 1 kWh of electricity delivered to a hypothetical organization. Next, a discussion on the quality of the emissions factors has been provided, taking account of data quality indicators. It was concluded that two of the emissions factors that are compared—those based on the national consumption mix and the residual mix for Poland—have been recognized as suitable for use in carbon footprint calculations. Beyond the calculation results, the research highlights the significance of the impact of the selection of emissions factors on the reliability of environmental analysis. The article identifies methodological challenges, including the risk of double counting, limited transparency, methodological inconsistency, and low correlation of data with specific locations and technologies. The insights presented contribute to improving the robustness of carbon footprint calculations. Full article

Analyses of student mobility are typically conducted in an urban environment and are informed by socio-demographic or trip attributes. The prevailing focus is on individual modes of transport, different groups of commuters travelling to campus, students’ behavioural perceptions, and the totality of student trips. This paper starts with the identification of the determinants of student mobility that have received insufficient research attention. Utilising surveys, the study captures the mobility patterns of a sample of 1014 students and calculates their carbon footprint (CF; in kg/academic year) to assess whether the factors neglected in previous studies influence differences in the actual environmental load of student commuting. A regression analysis is employed to ascertain the significance of these factors as predictors of sustainable student mobility. This study exclusively focuses on the group of student commuters to campus and analyses the trips associated with compulsory activities at a suburban campus that is distant from the university centre and student facilities, which changes the mobility context in terms of commuting options. The under-researched factors identified in this research have not yet been quantified as CF. The findings confirm that only some of the factors neglected in previous research are statistically significant predictors of the local environmental load of student mobility. Specifically, variables such as student employment, frequency of class attendance, and propensity for ride-sharing could be utilised to forecast and regulate students’ mobility towards more sustainable patterns. However, all of the under-researched factors (including household size, region of origin (i.e., past experiences), residing at term-time accommodation while studying, and the availability of a family car) have an influence on the differences in CF magnitude in the studied campus. Full article

Personal lifestyle choices contribute up to 75% of national emissions and yet the greenhouse gas (GHG) inventories included in the National Inventory Report (NIR) of Canada provide limited insight on these choices. Better insight can be found using carbon footprint calculators that estimate individual emissions; however, they vary in regard to their input parameters, output data, and calculation methods. This study assessed five calculators, which are popular with the public, or compatibility with the Canadian NIR. A quantitative scoring matrix was developed to assess the output depth, academic proficiency, and effectiveness of the calculators to inform lifestyle changes, alongside NIR alignment. The results showed that the calculator with the overall highest cumulative score across all the comparative criteria was the one offered by Carbon Footprint Ltd. The other calculators that scored highly include CoolClimate Calculator and Carbon Independent. The potential of the calculators in regard to informing low-carbon lifestyles can be improved through the incorporation of more depth in terms of capturing the purchase information of goods and services and providing detailed secondary information to users, including mitigation strategies and carbon offset options. The main driver of incompatibility between the calculator tools and the NIR was the different approaches taken to the emissions inventory, with the NIR using a territorial framework and the calculators being consumption driven. The outcomes of this study demonstrate a global need for the evolution of NIR structuring to increase its relatability with citizens and for the improved standardization of publicly available tools. Full article

Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. In this study, VR-N technology was applied to durum wheat in two small-scale commercial fields (3–4 ha each) located in distinct agro-climatic zones of Thessaly, central Greece. A real-time VR-N application algorithm was used to calculate N rates based on easily obtainable near-real-time data from unmanned aerial vehicle (UAV) imagery, tailored to the crop’s actual needs. VR-N implementation was carried out using conventional fertilizer spreaders equipped to read prescription maps. Results showed that VR-N reduced N input by up to 49.6% compared to the conventional uniform-rate N (UR-N) application, with no significant impact on wheat yield or grain quality. In one of the fields, the improved gain of VR-N when compared to UR-N was 7.2%, corresponding to an economic gain of EUR 163.8 ha⁻¹, while in the second field—where growing conditions were less favorable—no considerable VR-N economic gain was observed. Environmental benefits were also notable. The carbon footprint (CF) of the wheat crop was reduced by 6.4% to 22.0%, and residual soil nitrate (NO₃⁻) levels at harvest were 13.6% to 36.1% lower in VR-N zones compared to UR-N zones. These findings suggest a decreased risk of NO₃⁻ leaching and ground water contamination. Overall, the study supports the viability of VR-N as a practical and scalable approach to improve N use efficiency (NUE) and reduce the environmental impact of wheat cultivation which could be readily adopted by farmers. Full article

Amidst the global strategic transition towards low-carbon energy systems, electric vehicles (EVs) are pivotal for achieving deep decarbonization within the transportation sector. Consequently, enhancing the scientific rigor and precision of their life-cycle carbon footprint assessments is of paramount importance. Addressing the limitations of existing research, notably ambiguous assessment boundaries and the omission of dynamic coupling characteristics, this study develops a dynamic regional-level life-cycle carbon footprint assessment model for EVs that incorporates time-variant carbon emission factors. The methodology first delineates system boundaries based on established life-cycle assessment (LCA) principles, establishing a comprehensive analytical framework encompassing power battery production, vehicle manufacturing, operational use, and end-of-life recycling. Subsequently, inventory analysis is employed to model carbon emissions during the production and recycling phases. Crucially, for the operational phase, we introduce a novel source–load synergistic optimization approach integrating dynamic carbon intensity tracking. This is achieved by formulating a low-carbon dispatch model that accounts for power grid security constraints and the spatiotemporal distribution of EVs, thereby enabling the calculation of dynamic nodal carbon intensities and consequential EV emissions. Finally, data from these distinct stages are integrated to construct a holistic life-cycle carbon accounting system. Our results, based on a typical regional grid scenario, reveal that indirect carbon emissions during the operational phase contribute 75.1% of the total life-cycle emissions, substantially outweighing contributions from production (23.4%) and recycling (1.5%). This underscores the significant carbon mitigation leverage of the use phase and validates the efficacy of our dynamic carbon intensity model in improving the accuracy of regional-level EV carbon accounting. Full article

Livestock contributes to global warming through greenhouse gas (GHG) emissions. Reducing these emissions is an ongoing challenge for the small ruminant sector. Despite its significant role in national economies, limited studies on the carbon footprint (CF) of dairy small ruminants in Mediterranean countries exist. The study aimed to achieve the following: (a) estimate the GHG emissions of eleven semi-extensive sheep and goat farms in a mountainous region of southern Greece, using the Tier 1 and Tier 2 methodologies; (b) compare the outcomes of both methods; and (c) calculate farms’ CF, as a means of their environmental impact evaluation. All on-farm activities (except machinery or medicine use) related to sheep or goat production were considered to estimate GHG emissions. The results show differences between Tier 1 and Tier 2 estimates, reflecting the simplified computational approach of Tier 1. The average CF values estimated via Tier 1 for goat and sheep farms were 2.12 and 2.87 kg CO₂-eq./kg FPCM, respectively. Using Tier 2, these values increased to 2.73 and 3.99 kg CO₂-eq./kg FPCM. To mitigate environmental impact, farms could enhance productivity by improving herd management and feeding strategies. Full article

The imperative for building managers, in the face of high-density urban environments, is to drive existing chiller plants to greater operational efficiency through the application of advanced technological interventions. The case for applying Supervisory Control (SC) and a Building Automation System (SC+BAS) for optimizing chiller plants is the subject of investigation here, through the lens of a typical commercial shopping mall in the high-density infrastructure of Hong Kong. The application of SC+BAS falls into the realm of advanced Trim/Respond algorithms coupled with sophisticated sequencing algorithms that allow for refined optimization of the chiller operations in response to the dynamic demands of urban infrastructure. The SC+BAS features an array of optimizations specifically for the chiller plant. Incentive parameters such as cooling capacity, energy usage, and Coefficient of Performance (COP) were thoroughly studied through 12 months’ worth of data, before and after the implementation of the SC+BAS. Empirical observations indicate a statistically significant 17.6% energy usage decrease, coupled with a 15.3% decrease in the related energy expenditure costs. Furthermore, the environmental impact is calculated, with an estimated 61.1 tons reduction in the amount of CO₂ emissions, hence emphasizing the capacity for SC+BAS in offsetting the carbon footprint for commercial buildings. These data prove convincingly that the implementation of SC+BAS can increase the energy efficiency in chiller plants in commercial buildings, supporting the overall sustainability of the urban infrastructure. In turn, the authors suggest other areas for optimization through the advanced sequencing of chillers and demand-based cooling strategies. This highlights the ability of SC+BAS in creating more economical and green building operations regarding urban microclimates, occupant behavior patterns, and interactivity with the power grid, leading ultimately to the holistic optimization of chiller plant performance within the urban framework. Full article

Rapid urbanization, excessive motorization, and the imperative to reduce carbon footprints are driving the search for sustainable urban space solutions. One promising approach involves the effective design of small-scale architecture, such as parking shelters, optimized for structural material consumption and resilience to vehicle impacts. This research employed a novel approach during the initial design phase. Genetic algorithms and optimization techniques were utilized to define the optimal geometries of steel structures, focusing on the height of the conoidal roof and the shape and arrangement of columns. The subsequent analysis included static and strength calculations, dimensioning, and evaluating structural responses to exceptional loading, incorporating novel impact scenarios. The analysis yielded several key insights into the structural efficiency, dynamic behavior, and design optimization of the shelters. The research revealed that both roof geometry and column shape and arrangement significantly influenced material consumption and design effectiveness. The findings indicated that shelters with four straight, vertical, non-corner columns exhibited the most favorable dynamic behavior and highest impact resistance. These shelters also facilitated easy parking for both single-module and double-module roof types. The research findings provide a foundation for the parametric design of functional and structurally resilient parking shelters that cater to urban transportation needs and ecological objectives. Full article

Background: Severe asthma is a respiratory condition, involving treatments (i.e., inhaled steroids, systemic steroids, hospitalization) capable of increasing significant carbon footprint, raising concerns about environmental sustainability in healthcare. Sustainable healthcare policies and use of environmentally friendly treatment options are crucial in balancing effective asthma management with climate responsibility. Objectives: With this manuscript, we want to assess the impact, in terms of CO₂ production, of patients suffering from severe asthma and treated with biological drugs, to show the reduction in carbon footprint after the use of these drugs compared to the time when they were not prescribed. We analyzed data from three studies, all conducted in real life in Italy, of patients treated with mepolizumab, benralizumab and dupilumab, for the control of severe asthma. Methods: Data on number of exacerbations and hospitalizations, systemic corticosteroids (CS) cycles and their dose, were collected by three already published real-life trials, on the above-mentioned biologics, and used to calculate carbon footprint impact before and after biological therapy. For the mepolizumab study, the data collected referred to patients who started the drug between June 2017 and January 2019; for dupilumab, there were no age limits with patients enrolled between December 2019 and July 2020, whereas in the benralizumab study, all patients had to be over 18 years old. The statistical analysis was performed with Shapiro–Wilk test, t test and Cohen’s test. Results: The use of biologic drugs showed a significant reduction in CO₂ production after the introduction of these therapies, mainly secondary to a reduction in exacerbations, hospitalizations and CS use. In numerical terms, an average reduction of 75% in CO₂ production, per patient, is shown. Conclusions: Disease control, clinical remission of disease, in patients with severe asthma is certainly a determining factor in assessing the effectiveness of a treatment. Provided these goals are achieved, biological drug therapy has also proved to be particularly virtuous from the fundamental environmental point of view, allowing a significant reduction in CO₂ production for the management of these patients. Full article

Rubberized concrete is a more environmentally friendly material than natural concrete as it helps to reduce rubber disposal issues and has superior impact resistance. Geopolymer concrete, on the other hand, is an economical concrete with higher mechanical properties than nominal concrete that uses fly ash and slag, among other industrial solid wastes, to lower carbon footprints. Rubberized geopolymer concrete (RuGPC) combines the advantages of both concrete types, and a thorough grasp of its dynamic compressive characteristics is necessary for its use in components linked to impact resistance. Despite the advantages of RuGPC, predicting its mechanical characteristics is sometimes difficult because of variations in binder type and combination. This research investigated the combined effect of ground granulated blast furnace slag (GGBFS) and fly ash (FA) on the workability, compressive strength, and stress–strain characteristics of RuGPC with rubber at 0%, 10%, and 20% fine aggregate replacement. Thereafter, energy absorption and ductile characteristics were evaluated through the concrete toughness and ductility index. Numerical models were proposed for the cube compressive strength, modulus of elasticity, and peak strain of RuGPC at different percentages of crumb rubber. It was found that RuGPC made with GGBFS/FA had similar stress–strain characteristics to FA- and MK-based RuGPC. At 20% of crumb rubber aggregate replacement, the workability, compressive strength, modulus of elasticity, and peak stress of RuGPC reduced by 8.33%, 34.67%, 43.42%, and 44.97%, while Poisson’s ratio, peak, and ultimate strain increased by 30.34%, 8.56%, and 55.84%, respectively. The concrete toughness and ductility index increased by 22.4% and 156.67%. The proposed model’s calculated results, with R² values of 0.9508, 0.9935, and 0.9762, show high consistency with the experimental data. RuGPC demonstrates high energy absorption capacity, making it a suitable construction material for structures requiring high-impact resistance. Full article

This research aims to calculate the Carbon Footprint for Organization of a plant manufacturing frozen processed seafood and propose strategies to reduce greenhouse gas (GHG) emissions following the Net-Zero Pathway, using 2024 as the baseline year. The findings indicate that Scope 1 emissions amounted to 12,685 tons of CO₂ eq, Scope 2 emissions totaled 15,403 tons of CO₂eq, and Scope 3 emissions reached 31,564 tons of CO₂eq, leading to a combined total of 59,652 tons of CO₂eq across all scopes, with an additional 34,027 tons of CO₂eq from other GHG sources. To achieve net-zero emissions by 2050, annual reductions of 3.46% per category are required. The short-term target for 2028f aims to reduce emissions to 10,929 tons of CO₂eq for Scope 1, 13,270 tons of CO₂eq for Scope 2, and 27,194 tons of CO₂eq for Scope 3, resulting in total emissions of 51,392 tons of CO₂eq. The proposed reduction strategies include optimizing Scope 1 emissions by preventing leaks in R507 refrigerant systems, replacing corroded pipelines, installing shut-off valves, and switching to low-GHG refrigerants. For Scope 2, measures focus on reducing electricity consumption through energy conservation initiatives, carrying out regular machinery maintenance, installing Variable Speed Drives (VSDs), upgrading to high-efficiency motors, and integrating renewable energy sources such as solar power. For Scope 3, emissions from raw material procurement can be minimized by sourcing from certified suppliers with established product carbon footprints, prioritizing carbon reduction labeling, and selecting nearby suppliers to reduce transportation-related emissions. These strategies will support the organization in achieving carbon neutrality and progressing toward the net-zero goal. Full article

As the population increases, the growing demand for residential housing escalates construction activities, significantly impacting global warming by contributing 42% of primary energy use and 39% of global greenhouse gas (GHG) emissions. This study addresses a gap in research on lifecycle assessment (LCA) for Indian residential buildings by evaluating the full cradle-to-grave carbon footprint of a typical single-family house in Northern India. A BIM-based LCA framework was applied to a 110 m² single-family dwelling over a 60-year life span. Operational use performance and climate analysis was evaluated via cove tool. The total carbon footprint over a 60-year lifespan was approximately 5884 kg CO₂e, with operational energy use accounting for about 87% and embodied carbon approximately 11%. Additional impacts came from maintenance and replacements. Energy usage was calculated as 71.76 kWh/m²/year and water usage as 232.2 m³/year. Energy consumption was the biggest driver of emissions, but substantial impacts also stemmed from material production. Cement-based components and steel were the largest embodied carbon contributors. Under the business-as-usual (BAU) scenario, the operational emissions reach approximately 668,000 kg CO₂e with HVAC and 482,000 kg CO₂e without HVAC. The findings highlight the necessity of integrating embodied carbon considerations alongside operational energy efficiency in India’s building codes, emphasizing reductions in energy consumption and the adoption of low-carbon materials to mitigate the environmental impact of residential buildings. Future work should focus on the dynamic modeling of electricity decarbonization, improved regional datasets, and scenario-based LCA to better support India’s transition to net-zero emissions by 2070. Full article

This study examines the emissions generated by a tall ship of 81.36 m length under various operating conditions, focusing particularly on carbon dioxide emissions at different navigation speeds. The main purpose of the paper is to establish theoretical and practical methods for calculating and measuring the level of CO₂ emitted by the ship engines. Additionally, this article compares the results of carbon dioxide emission calculations based on theoretical methods with the results of real measurements. The paper verifies and assesses the carbon dioxide emission calculation methods compared to the emissions measured in real conditions for diesel engines. A comparative analysis of several methods for determining CO₂ emissions leads to much more accurate and conclusive results close to reality. The results obtained through empirical and theoretical methods for determining CO₂ emissions from the main engine demonstrate that the difference between these values is more accurate at lower engine loads but shows discrepancies at higher loads due to real-world inefficiencies, combustion variations, and model simplifications. The measured CO₂ emission values for auxiliary engines at 60% load demonstrate consistency and closely reflect real operating conditions, while analytical calculations tend to be higher due to theoretical losses and model assumptions. Stoichiometric values fall in between, assuming ideal combustion but lacking adjustments for real variables. This highlights the efficiency of the diesel generator and the importance of empirical data in capturing actual emissions more accurately. The investigation aims to provide a detailed understanding of CO₂ emission variations based on the ship’s operating parameters, including the study of these emissions at the level of the main diesel propulsion engine as well as the auxiliary engines. By analyzing these methods for determining engine emissions, conclusions can be reached about aspects such as the following: engine wear condition, efficiency losses, or incomplete combustion. This analysis has the potential to guide the implementation of new policies and technologies aimed at minimizing the carbon footprint of a reference ship, considering the importance of sustainable resource management and environmental protection in a viable long-term manner. Full article

Forested areas are defined as wooded regions characterized by dense vegetation, largely preserved natural ecosystem features, and availability for recreational use. These areas play a critical role in maintaining ecological balance and are increasingly utilized as preferred sites for various outdoor activities. However, the growing intensity of recreational activities in such sensitive ecosystems contributes to increased waste generation and poses significant threats to environmental sustainability. The objective of this study is to calculate the carbon footprint resulting from waste produced during recreational activities in forested areas of Lithuania, Turkey, and Morocco, and to identify innovative waste management strategies aimed at achieving clean and safe forest ecosystems. This study includes a comparison of Turkey, Lithuania, and Morocco. Quantitative data and carbon footprint calculations were conducted, while quantitative methods were also employed through semi-structured interviews with experts. Firstly, carbon footprint calculations were carried out based on the types and amounts of waste generated by participants. Subsequently, semi-structured interviews were conducted with experts and participants from all three countries to identify issues related to waste management and innovative waste management strategies. The carbon footprint resulting from waste generation was estimated to be 1517.26 kg in Turkey, 613.25 kg in Lithuania, and 735.68 kg in Morocco. Experts from Turkey, Lithuania, and Morocco have proposed innovative solutions for improving waste management systems in their respective countries. In Turkey, the predominant view emphasizes the need for increased use of digital tools, stricter enforcement measures, a rise in the number of personnel and waste bins, as well as the expansion of volunteer-based initiatives. In Lithuania, priority is given to educational and awareness-raising activities, updates to legal regulations, the placement of recycling bins, the development of infrastructure, and the promotion of environmentally friendly projects. In Morocco, it is highlighted that there is a need for stronger enforcement mechanisms, updated legal frameworks, increased staffing, more frequent waste collection, and the implementation of educational programs. Full article

Climate change is one of our most critical challenges, requiring urgent and comprehensive action across all levels of society. Individual actions and their roles in mitigating and adapting to climate change remain underexplored, despite global efforts. Under this context, this study was conducted to evaluate the ecological footprint of individuals for climate change mitigation. A structured online survey was designed and distributed through email lists, social media platforms, and community organisations to over 200 potential participants in the northwest of the UK. Due to the anonymous nature of the survey, only 83 individuals from diverse demographics completed the questionnaire. A carbon footprint calculator using conversion factors has been employed, based on energy consumption, travel, and material goods use. Participants are categorised into four groups based on their annual CO₂ emissions, ranging from less than 2 tonnes to over 10 tonnes. Personalised recommendations provided by the calculator focus on practical strategies, including adopting renewable energy, minimising unnecessary consumption, and opting for sustainable transportation. Results showed that only 5.5% of participants who employed advanced technologies and smart home technologies, 1.8% were implementing water-saving practices and 65.4% preferred to use their own car over other modes of transportation. In addition, the study found that 67.3% of participants had no or only a very limited knowledge of renewable energy technologies, indicating a need for education and awareness campaigns. The findings also highlight the importance of addressing demographic differences in ecological footprints, as these variations can provide insights into tailored policy interventions. Overall, despite the study’s limited sample size, this research contributes to the growing body of evidence on the importance of individual action in combating climate change and provides actionable insights for policymakers and educators aiming to foster a more sustainable lifestyle. Future studies with larger samples are recommended to validate and expand upon these findings. Full article