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Keywords = commuting carbon emissions

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24 pages, 2295 KiB  
Article
Multi-Objective Coordinated Control Model for Paths Considering Left-Turn Speed Guidance
by Jiao Yao, Xiaoxiao Zhu and Chengyi Yang
Systems 2025, 13(7), 516; https://doi.org/10.3390/systems13070516 - 26 Jun 2025
Viewed by 237
Abstract
Urban traffic signal coordination often prioritizes straight-through traffic, causing inefficiencies at intersections with high left-turn volumes. This study addresses left-turn traffic in path coordination control. First, using an enhanced FVD car-following model with acceleration decay and a minimum-jerk turning trajectory model, speed guidance [...] Read more.
Urban traffic signal coordination often prioritizes straight-through traffic, causing inefficiencies at intersections with high left-turn volumes. This study addresses left-turn traffic in path coordination control. First, using an enhanced FVD car-following model with acceleration decay and a minimum-jerk turning trajectory model, speed guidance is provided at intersections. For paths where left turns dominate, the traditional AM-BAND model is modified to maximize the green wave bandwidth for turning traffic and minimize carbon emissions, forming a multi-objective coordination control model with speed guidance. A case study was conducted on a typical path in Shanghai’s Jinqiao area. The results show that the left-turn-optimized model increases the green wave bandwidth by 16.67% over the traditional model, with an additional 9.52% improvement when speed guidance is included. For carbon emissions, the left-turn model reduces emissions by 12.99%, with a further 6.47% reduction under speed guidance. This approach effectively enhances efficiency and sustainability for left-turn-dominated paths, meeting urban commuter demands. Full article
(This article belongs to the Section Systems Practice in Social Science)
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31 pages, 14297 KiB  
Article
The Road to 2030: Combining Life Cycle Assessment and Multi-Criteria Decision Analysis to Evaluate Commuting Alternatives in a University Context
by Denner Deda, Jônatas Augusto Manzolli, Margarida J. Quina and Helena Gervasio
Sustainability 2025, 17(13), 5839; https://doi.org/10.3390/su17135839 - 25 Jun 2025
Viewed by 505
Abstract
Institutions are increasingly being challenged to reduce the environmental impacts of daily commuting, while balancing complex and often conflicting sustainability goals. This study addressed the limitations of carbon-centric assessments by proposing a framework that integrated life cycle assessment (LCA) with multi-criteria decision analysis [...] Read more.
Institutions are increasingly being challenged to reduce the environmental impacts of daily commuting, while balancing complex and often conflicting sustainability goals. This study addressed the limitations of carbon-centric assessments by proposing a framework that integrated life cycle assessment (LCA) with multi-criteria decision analysis (MCDA) to evaluate seven prospective commuting alternatives for 2030, using a Portuguese university as a case study. Utilizing the PROMETHEE method across 16 environmental criteria, the analysis revealed that active mobility offered the most balanced and sustainable outcomes, consistently performing the best across all impact categories. In contrast, the electrification of private vehicles, although it reduced greenhouse gas emissions, was identified as the least favorable option, due to significant trade-offs in areas such as resource depletion and water use, as well as other environmental burdens. Public transport scenarios, particularly those involving electric bus systems, showed intermediate performance. In this context, the proposed LCA–MCDA framework provides policymakers and institutions with a comprehensive decision-support tool to navigate environmental trade-offs, promote low-impact mobility strategies, and meet evolving sustainability reporting requirements. Full article
(This article belongs to the Collection Advances in Transportation Planning and Management)
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19 pages, 2602 KiB  
Article
Dynamic Optimization of Tramp Ship Routes for Carbon Intensity Compliance and Operational Efficiency
by Dequan Zhou, Yuhan Yang and Rui Cai
Sustainability 2025, 17(5), 2280; https://doi.org/10.3390/su17052280 - 5 Mar 2025
Cited by 1 | Viewed by 1171
Abstract
To address the challenges of carbon emission reduction in the global shipping industry and the requirements of the International Maritime Organization (IMO)’s Carbon Intensity Indicator (CII) rating, this paper takes China’s commuter ships as an example to study the dynamic optimization of ship [...] Read more.
To address the challenges of carbon emission reduction in the global shipping industry and the requirements of the International Maritime Organization (IMO)’s Carbon Intensity Indicator (CII) rating, this paper takes China’s commuter ships as an example to study the dynamic optimization of ship routes based on CII implementation requirements. In response to the existing research gap in the collaborative optimization of routes and carbon emissions under CII constraints, this paper constructs a mixed-integer programming model that comprehensively considers CII limits, port throughput capacity, channel capacity, and the stochastic demand for spot cargo. The objective is to minimize the operating costs of shipping companies, and an adaptive genetic algorithm is designed to solve the dynamic route scheduling problem. Numerical experiments demonstrate that the model can reasonably plan routes under different sequences of spot cargo arrivals, ensuring compliance with CII ratings while reducing total costs and carbon emissions. The results indicate that the proposed method provides efficient decision-making support for dynamic ship scheduling under CII constraints, contributing to the green transformation of the shipping industry. Future work will extend the model to scenarios involving multiple ship types and complex maritime conditions, further enhancing its applicability. Full article
(This article belongs to the Topic Carbon-Energy-Water Nexus in Global Energy Transition)
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20 pages, 16826 KiB  
Article
Leveraging a Cooler, Healthier, and Decarbonized School Commute: City-Scale Estimation and Implications for Nanjing, China
by Lifei Wang, Ziqun Lin, Zhen Xu and Lingyun Han
ISPRS Int. J. Geo-Inf. 2025, 14(3), 114; https://doi.org/10.3390/ijgi14030114 - 5 Mar 2025
Viewed by 1015
Abstract
An important aspect of a well-designed urban form is supporting active school travel by adolescents, as it has positive effects on physical activity, healthy lifestyles, and reducing vehicle-related carbon emissions. To achieve this, it is necessary to provide sufficient shading and fewer detours [...] Read more.
An important aspect of a well-designed urban form is supporting active school travel by adolescents, as it has positive effects on physical activity, healthy lifestyles, and reducing vehicle-related carbon emissions. To achieve this, it is necessary to provide sufficient shading and fewer detours on home–school routes, especially in an era of frequent heatwaves. Analyzing the school travel environment at the city scale is essential for identifying practical solutions and informing comprehensive urban policy-making. This study proposes a framework for investigating, assessing, and intervening in home–school routes in Nanjing, China, emphasizing a dual assessment of commuting routes based on the pedestrian detour ratio and shading ratio. This work reveals that approximately 34% of middle school households in Nanjing face challenges in walking to and from school, with only 24.18% of walking routes offering fewer detours and sufficient shade. We advocate reengineering urban forms by reducing barriers to facilitate shortcuts, thereby providing school-age students with better access to cooler and healthier environments, aiming to promote walking and reduce car dependence. The findings may encourage more families to engage in active commuting and serve as a lever to drive school decarbonization and combat climate warming. Our work, with transferability to other cities, can assist urban designers in piloting urban (re)form incrementally and pragmatically to promote sustainable urban agendas. Full article
(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T)
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22 pages, 4374 KiB  
Article
Energy Efficiency and Decarbonization Resulting from the Transition to Virtual Space
by Viktoria Mannheim, Zsuzsa Szalay, Renáta Bodnárné Sándor, Anita Terjék, Judit Lovasné Avató, Péter Sasvári, Zsolt István, Artúr Szilágyi, Orsolya Szalainé Kaczkó and Klára Tóthné Szita
Energies 2025, 18(5), 1206; https://doi.org/10.3390/en18051206 - 28 Feb 2025
Viewed by 933
Abstract
It is a serious challenge for humanity to find an appropriate response to stop the accelerating rise in global temperature caused by atmospheric carbon dioxide emissions. After a methodological review of the literature, online and in-person modelling of education, work, and conferences, and [...] Read more.
It is a serious challenge for humanity to find an appropriate response to stop the accelerating rise in global temperature caused by atmospheric carbon dioxide emissions. After a methodological review of the literature, online and in-person modelling of education, work, and conferences, and relying on the results of life-cycle studies, we sought the answer to what reasonable solutions are available for decarbonization and energy reduction. During the research, the organizational carbon footprint of a selected office, educational institution and conference, and then the carbon footprint created by a person in 1 h, were examined. The two-day online education significantly reduced the daily commute load in transport by 402 tons of CO2 equivalent per year. Still, the energy demand of home learning subtracts 136 tons from this, so the real benefit was 266 tons above in an institution educating nearly 3500 students. In a workplace of 180 people, where 52% of employees commute, 90% teleworking saved 222 tons of carbon dioxide emissions in one month, taking into account the carbon footprint of working from home. In the case of conferences, the online solution reduces the carbon footprint due to the absence of travel and catering. Comparing the three areas, for the in-person case, the conference’s carbon footprint per person per hour was the highest (11.91 kg CO2 eq.). This value for education was 1.15 kg CO2 eq.; for work, it was the lowest with a value of 0.90 kg CO2 eq. Moving to an online space resulted in the most significant savings for the conference (11.55 kg CO2 eq.), followed by working (0.54 kg CO2 eq.), and minor savings were achieved in hybrid education (0.13 kg CO2 eq.). The sensitivity analysis highlighted the impact of transport on carbon footprint in all three cases. However, the life cycle cost analysis showed that moving to a virtual space reduces the life cycle cost of de-carbonization by 42%. Full article
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29 pages, 5068 KiB  
Article
Two-Stage Locating and Capacity Optimization Model for the Ultra-High-Voltage DC Receiving End Considering Carbon Emission Trading and Renewable Energy Time-Series Output Reconstruction
by Lang Zhao, Zhidong Wang, Hao Sheng, Yizheng Li, Tianqi Zhang, Yao Wang and Haifeng Yu
Energies 2024, 17(21), 5508; https://doi.org/10.3390/en17215508 - 4 Nov 2024
Viewed by 1073
Abstract
With the load center’s continuous expansion and development of the AC power grid’s scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking due to the high strength of AC-DC coupling [...] Read more.
With the load center’s continuous expansion and development of the AC power grid’s scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking due to the high strength of AC-DC coupling and the low level of system inertia, which brings many complexities and uncertainties to economic scheduling. In addition, the large-scale grid integration of wind power, photovoltaic, and other intermittent energy sources makes the ultra-high-voltage (UHV) DC channel operation state randomized. The deterministic scenario-based timing power simulation is no longer suitable for the current complex and changeable grid operation state. In this paper, we first start with the description and analysis of the uncertainty in renewable energy (RE) sources, such as wind and solar, and reconstruct the time-sequence power model by using the stochastic differential equation model. Then, a carbon emission trading cost (CET) model is constructed based on the CET mechanism, and the two-stage locating and capacity optimization model for the UHV DC receiving end is proposed under the constraint of dispatch safety and stability. Among them, the first stage starts with the objective of maximizing the carrying capacity of the UHV DC receiving end grid; the second stage checks its dynamic safety under the basic and fault modes according to the results of the first stage and corrects the drop point and capacity of the UHV DC line with the objective of achieving safe and stable UHV DC operation at the lowest economic investment. In addition, the two-stage model innovatively proposes UHV DC relative inertia constraints, peak adjustment margin constraints, transient voltage support constraints under commutation failure conditions, and frequency support constraints under a DC blocking state. In addition, to address the problem that the probabilistic constraints of the scheduling model are difficult to solve, the discrete step-size transformation and convolution sequence operation methods are proposed to transform the chance-constrained planning into mixed-integer linear planning for solving. Finally, the proposed model is validated with a UHV DC channel in 2023, and the results confirm the feasibility and effectiveness of the model. Full article
(This article belongs to the Section F6: High Voltage)
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23 pages, 2744 KiB  
Article
Exploring Psychological Factors Influencing the Adoption of Sustainable Public Transit Considering Preference Heterogeneity
by Gyeongjae Lee, Sujae Kim, Jahun Koo and Sangho Choo
Sustainability 2024, 16(18), 7924; https://doi.org/10.3390/su16187924 - 11 Sep 2024
Cited by 1 | Viewed by 2275
Abstract
Carbon emission reduction strategies are being implemented in the transportation sector by encouraging the adoption of eco-friendly vehicles and introducing demand management policies such as Mobility as a Service (MaaS). Nevertheless, the efficacy of MaaS in reducing carbon emissions remains uncertain. This study [...] Read more.
Carbon emission reduction strategies are being implemented in the transportation sector by encouraging the adoption of eco-friendly vehicles and introducing demand management policies such as Mobility as a Service (MaaS). Nevertheless, the efficacy of MaaS in reducing carbon emissions remains uncertain. This study introduces Sustainable Public Transit (SPT) as a public transit alternative consisting of only green modes to promote sustainability. We explore the preferences of SPT in a commuting context, incorporating individual preference heterogeneity in a discrete choice model. We systematically identify the relationship between choice behaviors and individual heterogeneity in alternative attributes and psychological factors stemming from socio-demographic characteristics. The integrated choice and latent variable (ICLV) model with a mixed logit form is adopted, and the key findings can be summarized as follows: Preference heterogeneity is observed in the travel cost variable, which can be explained by characteristics such as the presence of a preschooler, household size, and income. CO2 emissions do not have a statistically significant impact on choices. Furthermore, psychological factors are also explained through socio-demographic characteristics, and it is found that low-carbon knowledge positively influences low-carbon habits. Psychological factors significantly affect choices. Respondents who dislike transfers and prioritize punctuality are less likely to choose SPT, while those who have positive low-carbon attitudes are more likely to do so. Finally, scenario analysis is conducted to forecast mode share based on improvements in SPT alternative attributes and variations in attribute levels. Policy implications are then provided to enhance the acceptability of SPT. Full article
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17 pages, 7988 KiB  
Article
Spatial Heterogeneity Analysis of Factors on Commuting Carbon Emissions: Evidence from the Shenzhen Metropolitan Area in China
by Xin Li, Jiayue Zhang, Wenna Zhang and Yue Tan
Sustainability 2024, 16(11), 4397; https://doi.org/10.3390/su16114397 - 23 May 2024
Cited by 1 | Viewed by 1499
Abstract
As an essential part of daily life, commuting produces considerable carbon emissions and is currently receiving increased amounts of attention. Comprehensive explorations of carbon emissions and the spatial distribution of their effects based on previous studies are lacking. First, we adopt stepwise regression [...] Read more.
As an essential part of daily life, commuting produces considerable carbon emissions and is currently receiving increased amounts of attention. Comprehensive explorations of carbon emissions and the spatial distribution of their effects based on previous studies are lacking. First, we adopt stepwise regression and geographically weighted regression (GWR) to explore the diverse impacts of carbon emissions on the different layers of metropolitan areas, employing factors from the perspectives of socioeconomics, transportation services, and road networks. Our findings show that optimizing the road network structure could be an effective approach to reducing carbon emissions from commuting, especially in the periphery of metropolitan areas. In addition, the mixed use of land contributes to reducing carbon emissions from commuting, especially in the central areas. Thus, the coverage of public transport should be improved, especially in peripheral regions. Policymakers should monitor the spatial heterogeneity of variables and develop suitable policies to adapt to the conditions of the different layers of metropolitan areas. Full article
(This article belongs to the Section Sustainable Transportation)
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17 pages, 4397 KiB  
Article
New Energy Commuting Optimization under Low-Carbon Orientation: A Case Study of Xi’an Metropolitan Area
by Xin Dai, Tianshan Ma and Enyi Zhou
Energies 2023, 16(23), 7916; https://doi.org/10.3390/en16237916 - 4 Dec 2023
Cited by 2 | Viewed by 1608
Abstract
Low-carbon travel is an important part of low-carbon cities and low-carbon transportation, and low-carbon transportation is an inevitable choice to slow down the growth of carbon emissions in China. All countries in the world are actively promoting new energy vehicles and attach great [...] Read more.
Low-carbon travel is an important part of low-carbon cities and low-carbon transportation, and low-carbon transportation is an inevitable choice to slow down the growth of carbon emissions in China. All countries in the world are actively promoting new energy vehicles and attach great importance to the application of the new energy industry in urban transportation. Commuting is an important part of urban life, and the choice of travel behavior has an important impact on traffic and environmental protection. Taking the Xi’an metropolitan area as an example, this paper expounds on the integrated development path of the industrial chain of new energy + travel in the metropolitan area and clarifies the energy transformation model of the integrated development of low-carbon transportation and energy. From the perspective of green and low-carbon, 1000 commuters were interviewed using a questionnaire survey, and the cumulative prospect model was used to verify the internal mechanism affecting commuters in metropolitan areas to choose new energy commuting. The results of the study show that new energy transportation modes play an important role in the low-carbon economy, and under different scenarios and assumptions, there are significant differences in the cumulative prospect values of the subway, new energy buses and fuel private cars, and corresponding optimization measures are proposed to increase the proportion of new energy commuting trips. The results will help further promote the development of a low-carbon economy and energy integration in the field of transportation and provide a reference for the sustainable development of public transportation. Full article
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18 pages, 1490 KiB  
Article
Low-Carbon Travel Behavior in Daily Residence and Tourism Destination: Based on TPB-ABC Integrated Model
by Liying Wang, Junya Wang, Pengxia Shen, Shangqing Liu and Shuwei Zhang
Sustainability 2023, 15(19), 14349; https://doi.org/10.3390/su151914349 - 28 Sep 2023
Cited by 13 | Viewed by 3651
Abstract
Low-carbon travel is considered as one of the most important strategies to reduce transportation carbon emissions, and its success is decided by the active participation of residents. Based on the theory of planned behavior (TPB) and Attitude-Behavior-Context theory (ABC), this study explores the [...] Read more.
Low-carbon travel is considered as one of the most important strategies to reduce transportation carbon emissions, and its success is decided by the active participation of residents. Based on the theory of planned behavior (TPB) and Attitude-Behavior-Context theory (ABC), this study explores the influencing factors and formation paths of individual low-carbon travel behavior, and analyzes low-carbon travel behavior regarding both daily commuting from residence and tourism destinations. This study collects a sample of 506 respondents and uses Mplus 8.0 to examine the hypotheses. Empirical research results indicate that: (1) A certain gap exists in the individuals’ low-carbon travel behavior between daily residence and tourism destination. Differences exist in direct effects, mediating effects and moderating effects. (2) Low-carbon travel behavioral intention plays a significant mediating role in both daily residence and tourism destination, especially the former. Regarding daily residence, individuals’ attitude, subjective norms and perceived behavioral control have a positive effect on behavior through behavioral intention. Regarding tourism destination, only the attitude-low-carbon travel behavioral intention-behavior path is significant. (3) Situational factors play a significant positive moderating effect on the relationship between low-carbon travel behavioral intention and behavior, especially in tourism destination. This study reveals the internal mechanism of individuals’ low-carbon travel behavior and the differences between travel in daily life and tourism, helping to deepen understanding of individuals’ low-carbon travel behavior and providing guidance for promoting individuals’ low-carbon travel. Full article
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11 pages, 269 KiB  
Brief Report
Advances in Hydrogen-Powered Trains: A Brief Report
by Andile Nqodi, Thapelo C. Mosetlhe and Adedayo A. Yusuff
Energies 2023, 16(18), 6715; https://doi.org/10.3390/en16186715 - 20 Sep 2023
Cited by 13 | Viewed by 6685
Abstract
The majority of rail vehicles worldwide use diesel as a primary fuel source. Diesel engine carbon emissions harm the environment and human health. Although railway electrification can reduce emissions, it is not always the most economical option, especially on routes with low vehicle [...] Read more.
The majority of rail vehicles worldwide use diesel as a primary fuel source. Diesel engine carbon emissions harm the environment and human health. Although railway electrification can reduce emissions, it is not always the most economical option, especially on routes with low vehicle demand. As a result, interest in hydrogen-powered trains as a way to reduce greenhouse gas (GHG) emissions has steadily grown in recent years. In this paper, we discuss advancements made in hydrogen-powered freight and commuter trains, as well as the technology used in some aspects of hydrogen-powered vehicles. It was observed that hydrogen-powered trains are already in use in Europe and Asia, unlike most developing countries in Africa. Commuter trains have received most of the research and development (R&D) attention, but interest in hydrogen-powered freight trains has recently picked up momentum. Despite the availability and use of gray and blue hydrogen, green hydrogen is still the preferred fuel for decarbonizing the rail transport sector. Full article
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21 pages, 9520 KiB  
Article
Research on the Rapid Recognition Method of Electric Bicycles in Elevators Based on Machine Vision
by Zhike Zhao, Songying Li, Caizhang Wu and Xiaobing Wei
Sustainability 2023, 15(18), 13550; https://doi.org/10.3390/su151813550 - 11 Sep 2023
Cited by 6 | Viewed by 1910
Abstract
People are gradually coming around to the idea of living a low-carbon lifestyle and using green transportation, and given the severe urban traffic congestion, electric bicycle commuting has taken over as the preferred mode of short-distance transportation for many. Since batteries are used [...] Read more.
People are gradually coming around to the idea of living a low-carbon lifestyle and using green transportation, and given the severe urban traffic congestion, electric bicycle commuting has taken over as the preferred mode of short-distance transportation for many. Since batteries are used to power electric bicycles, there are no greenhouse gas emissions while they are in use, which is more in line with the requirement for sustainable development around the world. The public has been increasingly concerned about the safety issues brought on by electric bicycles as a result of the industry’s quick development and the rapid increase in the number of electric bicycles worldwide. The unsafe operation of the elevator and the safety of the building have been seriously compromised by the unauthorized admission of electric bicycles into the elevator. To meet the need for fast detection and identification of electric bicycles in elevators, we designed a modified YOLOv5-based identification approach in this study. We propose the use of the EIoU loss function to address the occlusion problem in electric bicycle recognition. By considering the interaction ratio and overlap loss of the target frames, we are able to enhance localization accuracy and reduce the missed detection rate of occluded targets. Additionally, we introduce the CBAM attention mechanism in both the backbone and head of YOLOv5 to improve the expressive power of feature maps. This allows the model to prioritize important regions of the target object, leading to improved detection accuracy. Furthermore, we utilize the CARAFE operator during upsampling instead of the nearest operator in the original model. This enables our model to recover details and side information more accurately, resulting in finer sampling results. The experimental results demonstrate that our improved model achieves an mAP of 86.35 percent, a recall of 81.8 percent, and an accuracy of 88.0 percent. When compared to the original model under the same conditions, our improved YOLOv5 model shows an average detection accuracy increase of 3.49 percent, a recall increase of 5.6 percent, and an accuracy increase of 3.5 percent. Tests in application scenarios demonstrate that after putting the model on the hardware platform Jeston TX2 NX, stable and effective identification of electric bicycles can be accomplished. Full article
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12 pages, 856 KiB  
Article
Evaluating the Impact of COVID-19 on the Carbon Footprint of Two Research Projects: A Comparative Analysis
by Sofia Papadogiannaki, Natalia Liora, Daphne Parliari, Stavros Cheristanidis, Anastasia Poupkou, Ioannis Sebos, Athena Progiou and Dimitrios Melas
Atmosphere 2023, 14(9), 1365; https://doi.org/10.3390/atmos14091365 - 30 Aug 2023
Cited by 21 | Viewed by 2785
Abstract
The objective of this study is to investigate the impact of the COVID-19 pandemic on the carbon footprint (CF) of two research projects. These projects were initiated prior to the onset of the pandemic and subsequently concluded afterward, serving as the Base Case [...] Read more.
The objective of this study is to investigate the impact of the COVID-19 pandemic on the carbon footprint (CF) of two research projects. These projects were initiated prior to the onset of the pandemic and subsequently concluded afterward, serving as the Base Case (BC) for analysis. Furthermore, the study seeks to explore the potential applicability of measures implemented during the period of lockdown for future mitigation of CF. The applied methodology, which adheres to the guidelines provided by the GHG Protocol and the Department for Environment Food & Rural Affairs (DEFRA) emission factors, is utilized to examine the CF of the projects under two different scenarios. The first scenario assumes that the projects were implemented without the pandemic, while the second scenario considers that the projects were conducted entirely during the pandemic. Among the two projects under review, one emphasizes innovation and entails a collaboration between academia and business. This project is supported by a limited number of employees, exclusively from domestic partners. The other project is more oriented toward policy-making and involves a larger group of partners from Greece and Italy. Its main priority is dissemination. Carbon dioxide (CO2) emissions associated with project activities mainly stem from electricity use, material consumption, project-hosted events, project participation in events, employees commuting, and equipment. Results show that in the first scenario, the projects exhibit a more than 40% increase in CO2 emissions compared to the BC, while in the second scenario, the implementation of measures such as teleworking, virtual participation in events, and digitization of bureaucratic processes lead to a reduction in emissions by at least 20%. The study suggests that adopting such measures after the COVID-19 pandemic could significantly decrease greenhouse gas emissions. Full article
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6 pages, 434 KiB  
Proceeding Paper
Assessing the Carbon Footprint of Teleworking: A Case Study of Two Research Projects before and after the COVID-19 Pandemic
by Sofia Papadogiannaki, Natalia Liora, Daphne Parliari, Stavros Cheristanidis, Anastasia Poupkou and Dimitrios Melas
Environ. Sci. Proc. 2023, 26(1), 101; https://doi.org/10.3390/environsciproc2023026101 - 28 Aug 2023
Viewed by 1036
Abstract
The objective of this study is to assess the carbon footprint (CF) of electricity use and transportation, with a focus on teleworking, through the implementation of two research projects that were initiated before and completed after the COVID-19 pandemic. The study applies an [...] Read more.
The objective of this study is to assess the carbon footprint (CF) of electricity use and transportation, with a focus on teleworking, through the implementation of two research projects that were initiated before and completed after the COVID-19 pandemic. The study applies an integrated methodology based on the GHG Protocol guidance and DEFRA emission factors to investigate the CF of the projects, both during the pre-pandemic and teleworking period, as well as during the pandemic period with 50% teleworking. The results indicate that telecommuting contributed to a reduction in CO2 emissions of 49–55%. Furthermore, a 20% reduction in car usage for commuting to and from work resulted in reductions of approximately 30% in transportation. These findings suggest that implementing such measures post-COVID-19 could have a significant impact on reducing greenhouse gas emissions. Full article
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18 pages, 986 KiB  
Article
GHG Emission Accounting and Reduction Strategies in the Academic Sector: A Case Study in Mexico
by Leslie Cardoza Cedillo, Michelle Montoya, Mónica Jaldón and Ma Guadalupe Paredes
Sustainability 2023, 15(12), 9745; https://doi.org/10.3390/su15129745 - 19 Jun 2023
Cited by 2 | Viewed by 2822
Abstract
The carbon footprint (CF) quantifies the greenhouse gas (GHG) emissions generated by human activities, expressed in carbon dioxide equivalent (CO2e) units. It is an instrument for monitoring and mitigating the effects of climate change, which particularly affects low- and middle-income countries [...] Read more.
The carbon footprint (CF) quantifies the greenhouse gas (GHG) emissions generated by human activities, expressed in carbon dioxide equivalent (CO2e) units. It is an instrument for monitoring and mitigating the effects of climate change, which particularly affects low- and middle-income countries such as Mexico. The Mexican government has established a goal of reducing GHG emissions by 22% from the levels in 2000 by 2030. Although most efforts to reduce GHG emissions have been focused on the energy and agriculture sectors, the academic sector is also important since it can advise changes in public policy. In this study, the 2019 CF of the Centro Roberto Garza Sada (CRGS), a design school at the Universidad de Monterrey, was estimated in an effort to develop measures for reducing GHG emissions. The GHG Protocol was employed to calculate the total CF of the CRGS and identify the greatest contributors, including commuting (50.2%), energy purchase (28.5%), business travel (19.6%), and energy generation, use of paper, refrigerants, and shipments (1.7%). Three progressive mitigation scenarios were developed to reduce the GHG emissions from commuting, energy consumption, collaborators and student mobility, and material resources. These strategies could reduce the GHG emissions of the CRGS by 63.5% of the baseline assessed. Full article
(This article belongs to the Section Air, Climate Change and Sustainability)
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