Search Results (32)

Electric vehicles (EVs) play a critical role in the transition to transportation electrification and are important for achieving carbon neutrality in this sector. China currently leads the world in EV ownership; however, the energy regulation potential of in-use batteries remains largely untapped in the context of an increasingly saturated EV stock. This study systematically evaluates the long-term benefits of vehicle-to-everything (V2X) applications based on EV sales projections and advancements in battery technology. The results indicate that, without compromising daily travel requirements, V2X applications could enable 109.50–422.37 TWh of annual electricity dispatch by 2030, achieving an estimated economic benefit of 198.92–767.25 billion CNY, and reducing carbon dioxide (CO₂) emissions by 45.01–173.60 Mt. By 2060, these figures are projected to increase significantly, with annual dispatchable electricity reaching 4217.39–21,689.43 TWh, generating an economic value of 10.82–55.66 trillion CNY, and reducing CO₂ emissions by 118.09–607.30 Mt. Furthermore, V2X applications could substantially contribute to achieving the emission reduction targets outlined in China’s Nationally Determined Contributions (NDCs). These findings highlight that V2X applications, as a transformative solution that promotes deep integration between the transportation and power sectors, enhance cross-sectoral emission reduction synergies and support the realization of carbon neutrality goals. Full article

The role of public housing in improving wellbeing for tenants and society is an important public policy issue. Public housing tenants in Aotearoa New Zealand have constrained incomes and their mode of transport has implications for their budgets, their wellbeing, and carbon emissions. Tenants’ daily life choices and wellbeing are influenced by the set of transport options available to them and the constraints and opportunities these options entail. What is important for wellbeing is also dependent on culture. Little is known, however, about the specific influences of transport on the wellbeing of public housing tenants and how that is mediated by the culture of particular groups, particularly Māori and Pacific people, who make up the majority of people in public housing in Aotearoa. In this article we review the literature on public housing, transport, and wellbeing, to establish what is known about how transport, and the access it affords, influence the wellbeing of public housing tenants. We searched Scopus and Web of Science for academic journal articles, published in English and available online, about public housing tenant wellbeing with regard to the transportation and location characteristics of public housing. We found that creating highly accessible public housing developments with options of various modes of travel is important for the wellbeing of tenants. We also found that understanding the specific needs and preferences of tenants, ensuring tenants have agency over how they travel, and engaging with tenants during transport decision-making are particularly important and often under-recognised for people in public housing. Finally, we identified substantial gaps in the literature around understanding transport needs and experiences from Māori and Pacific perspectives, emphasising the importance of including indigenous and ethnic minority views in future research. Full article

Urban rail transit, a crucial component of urban public transportation, often experiences increased operational costs and carbon emissions due to low-load operations being conducted during off-peak passenger flow periods. This study aims to develop an optimization method for the daily scheduling of rail train operations with the goal of carbon emission reduction, while comprehensively considering the built environment and travel demand. Firstly, the influence of the urban built environment on residents’ travel demand is analyzed using an XGBoost model. Secondly, a time convolutional travel demand prediction model, Built Environment-Weighted Temporal Convolutional Network (BE-TCN), weighted by built environment factors, is constructed. Finally, an optimization method for rail train operation schedules based on the built environment and travel demand is proposed, with the objective of carbon emission reduction. A case study is conducted using the Hangzhou urban rail transit system as an example. The results indicate that the optimization method proposed in this study can achieve monthly carbon emission reductions of 1524.58 tons, 1181.94 tons, and 520.84 tons for Lines 1, 2, and 4 of the Hangzhou urban rail transit system, respectively. The research findings contribute to enhancing the economic efficiency and environmental sustainability of urban rail transit systems. Full article

This study explores the driving factors of household energy consumption in high-density residential areas of Beijing and proposes targeted energy-saving strategies. Data were collected through field surveys, questionnaires, and interviews, covering 16 influencing factors across household, building, environment, and transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined with genetic algorithm tuning performing best. SHAP analysis revealed that key factors varied by season but included floor level, daily travel distance, building age, greening rate, water bodies, and household age. The findings inform strategies such as optimizing workplace–residence layout, improving building insulation, increasing green spaces, and promoting community energy-saving programs. This study provides refined data support for energy management in high-density residential areas, enhances the application of energy-saving technologies, and encourages low-carbon lifestyles. By effectively reducing energy consumption and carbon emissions during the operational phase of residential areas, it contributes to urban green development and China’s “dual carbon” goals. Full article

Aviation is one of the most important industries in the current global scenario, but it has a significant impact on climate change due to the large quantities of carbon dioxide emitted daily from the use of fossil kerosene-based fuels (jet fuels). Although technological advancements in aircraft design have enhanced efficiency and reduced emissions over the years, the rapid growth of the aviation industry presents challenges in meeting the environmental targets outlined in the “Flightpath 2050” report. This highlights the urgent need for effective decarbonisation strategies. Hydrogen propulsion, via fuel cells or combustion, offers a promising solution, with the combustion route currently being more practical for a wider range of aircraft due to the limited power density of fuel cells. In this context, this paper designs and models a nitrogen–hydrogen heat exchanger architecture for use in an innovative hydrogen-propelled aircraft fuel system, where the layout was recently proposed by the same authors to advance sustainable aviation. This system stores hydrogen in liquid form and injects it into the combustion chamber as a gas, making the cryogenic heat exchanger essential for its operation. In particular, the heat exchanger enables the vaporisation and superheating of liquid hydrogen by recovering heat from turbine exhaust gases and utilising nitrogen as a carrier fluid. A pipe-in-pipe design is employed for this purpose, which, to the authors’ knowledge, is not yet available on the market. Specifically, the paper first introduces the proposed heat exchanger architecture, then evaluates its feasibility with a detailed thermodynamic model, and finally presents the calculation results. By addressing challenges in hydrogen storage and usage, this work contributes to advancing sustainable aviation technologies and reducing the environmental footprint of air travel. Full article

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

Climate change is a major global issue because transportation is a major source of pollutants and greenhouse gases that affect human health and air quality. However, to effectively prioritize and fund mitigating actions, decision-makers lack scientific rigor and diagnoses with sufficient spatial resolution. Based on the Origin-Destination Matrix (ODM), this study suggests a methodology to measure and identify mobility emissions (CO₂, Nox, PM) at the neighborhood level with high spatial resolution. Testing of the methodology was performed in Valencia, Spain. Even though many studies calculate carbon footprint, few make use of precise geographic information and openly accessible data, and they frequently concentrate on entire cities rather than smaller areas. To determine all potential routes for each Origin-Destination (OD) trip, the process uses geostatistics to estimate daily trip activity data (kilometers traveled). The COPERT calculator methodology from the European Union is used to analyze these routes to calculate the total emissions and the distance traveled per neighborhood. Based on road infrastructure, the methodology determines which neighborhoods receive emissions and creates measures of equitable environmental responsibility. It also identifies short trips that might be replaced by cycling or walking, as well as possible improvements to public transportation. Full article

In order to improve the operational efficiency of a shared electric vehicle (SEV) system, this paper conducts integrated planning research from the aspects of locating and sizing SEV outlets, locating and sizing charging facilities, and operation scheduling by considering the carbon emission reduction and its benefits. Firstly, a multi-objective locating model was constructed with the optimization objectives of minimum outlet construction cost and user travel time cost and minimum carbon emissions from outlet construction and vehicle routing. Secondly, a charging demand simulation predictive model framework was designed. Finally, an SEV scheduling model with maximal operating income and minimal scheduling costs as optimization objectives was constructed considering the benefits of carbon emission reduction. By applying these models to the Chicago Sketch network and using a genetic algorithm to solve the models, it is concluded that the optimal outlet location solution considering carbon emission reduction will increase the outlet construction cost and user travel time cost. When the user loss rate is 40%, the initial number of vehicles in each outlet can make the operator’s daily income reach the maximum. The number of charging piles in each outlet is optimally configured according to 55% of the highest charging demand. Scheduling can make the distribution of charging demand more uniform and reduces the maximum charging demand by about 36.8% and the total number of charging piles by about 24.0%, at the same time, increases the average time utilization rate of charging piles at all outlets by about 15.6% and the user satisfaction rate by about 8.6%. Although scheduling increases the scheduling cost by about 3.8%, it can increase the total daily revenue of operators by 6.5%. Carbon reduction benefits can increase the total daily revenue of operators by 0.7%. Full article

Carbon emissions from transportation account for an increasing proportion of total carbon emissions, and daily travel carbon emissions are an essential part of carbon emissions from transportation. Urban form influences the transportation network layout, so the degree of influence of urban transportation development on daily travel carbon emissions varies according to urban form. This paper uses panel data from 254 prefecture-level cities in China from 2006 to 2019 to explore the impact of urban transportation development on daily travel carbon emissions based on the moderating effect of urban form. The results show that urban transportation development plays a pivotal role in significantly reducing daily travel carbon emissions. The urban form further amplifies the impact of carbon emission reductions. Specifically, polycentric urban structures enable residents to meet their daily travel needs through short-distance trips, thereby alleviating traffic congestion. The impact of urban transportation development on daily travel carbon emission intensity exhibits heterogeneity. In both low-carbon pilot cities and large cities, urban transportation development markedly decreases daily travel carbon emission intensity. Additionally, it is observed that cities with lower economic development levels exhibit more pronounced effects in carbon emission reduction compared to their more economically developed counterparts. This paper provides empirical support for rational planning of urban transportation systems and low-carbon development of daily travel. Full article

In-home activities are inevitably important parts of individuals’ daily schedules, as people spend more time working and doing various other activities (e.g., online shopping or banking) at home. However, conventional activity-based travel demand models (ABMs) only consider travel and travel-related out-of-home activities, ignoring the interaction between in-home and out-of-home activities. To fill in this gap and increase the understanding of what people do at home and how in-home and out-of-home activities affect each other, a new method is proposed in this study. The approach predicts the types and durations of in-home activities of daily schedules generated by ABMs. In model building, statistical methods such as multinomial logit, log-linear regression, and activity sequential information are utilized, while in calibration, the Simultaneous Perturbation Stochastic Approximation (SPSA) method is employed. The proposed method was tested using training data and by applying the approach to the schedules of 6.3 million people in the Flemish region of Belgium generated by a representative ABM. Based on the statistical methods, the mean absolute errors were 0.36 and 0.21 for predicting the number and sum of the durations of in-home activities (over all types) per schedule, respectively. The prediction obtained a 10% and 8% improvement using sequential information. After calibration, an additional 60% and 68% were gained regarding activity participation rates and time spent per day. The experimental results demonstrate the potential and practical ability of the proposed method for the incorporation of in-home activities in activity–travel schedules, contributing towards the extension of ABMs to a wide range of applications that are associated with individuals’ in-home activities (e.g., the appropriate evaluation of energy consumption and carbon emission estimation as well as sustainable policy designs for telecommuting). Full article

With the advancement of urban modernization, more and more residents are flocking to large cities, leading to problems such as severe traffic congestion, uneven distribution of spatial resources, and deterioration of the urban environment. These challenges pose a serious threat to the coordinated development of cities. In order to better understand the travel behavior of metropolitan residents and provide valuable insights for urban planning, this study utilizes taxi trajectory data from the central areas of Beijing, Shanghai, Shenzhen, and Wuhan. First, the relationship between daytime taxi drop-off points and urban amenities is explored using Ordinary Least Squares (OLS). Subsequently, Geographically Weighted Regression (GWR) techniques were applied to identify spatial differences in these urban drivers. The results show that commonalities emerge across the four cities in the interaction between external transport stops and commercial areas. In addition, the average daily travel patterns of residents in these four cities show a trend of “three peaks and three valleys”, indicating the commonality of travel behavior. In summary, this study explores the travel characteristics of urban residents, which can help urban planners understand travel patterns more effectively. This is crucial for the strategic allocation of transport resources across regions, the promotion of sustainable urban transport, and the reduction in carbon emissions. Full article

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

The citizen’s carbon footprint is affected by various factors, but mostly by electricity consumption, daily transportation, travelling habits, as well as municipal solid waste management, a critical factor that is not frequently incorporated in carbon footprint estimations. This paper proposes a new carbon footprint calculator, the Carbon Footprint Simulation Dashboard—COMPAIR’s CO₂ calculator. The CO₂ calculator employs Citizen Science (CS) information in order to assist citizens in understanding and comparing how future carbon emissions will be modified in accordance with changes in their daily routines. The calculator offers several statistics, e.g., the country’s average carbon footprint and comparisons between EU members with respect to sectors that shape it, along with several recommendations for those domains where carbon footprint is significantly higher than the desired limits. The novelty of this tool is the integration of waste management strategies as a dimension of the total CO₂ calculation. In this framework, the study presents the development of the Carbon Footprint Simulation Dashboard while two different waste management scenarios are applied with different citizen behaviours on recycling and composting. The applications highlighted the consumption in buildings that account for almost 50% of the total CO₂ emissions, while the crucial role of transportation is also a key parameter. The different waste management scenarios showed a correlation between the CO₂ footprint and the overall consumption/disposal habits of citizens. In the case of advanced recycling and composting, waste management accounted for up to 7% of the CO₂ emissions, and this highlights the significance of behavioural choices. Full article

Our paper focuses on the transformation of the concept of sustainable business leadership (especially regarding the Sustainable Development Goals (SDGs)) and corporate social responsibility (CSR) in the post-COVID-19 era. The COVID-19 pandemic is without question posing a generation-defining challenge for public health and the global economy. Moreover, the pandemic has revived some old and introduced many new threats that today’s business leaders will have to face in the years to come. Despite the fact that the COVID-19 crisis was a humanitarian tragedy that continues to ravage millions of lives, it can also be viewed as an excellent opportunity to restart sustainable economic development as well as to help our business and economy to shift towards real business corporate social responsibility and ethical decision-making (thanks to the reduction in carbon emissions as a result of reduced economic activity and travel, increasing investments into healthcare and education, or finding the new ways for working and learning, such as remote work and online education). Our paper examines the effect of small entrepreneurs’ perceptions of CSR on their daily business under the conditions of the COVID-19 pandemic. The paper features an empirical model that assesses the implementation of CSR practices and principles (social responsibility, environmental sustainability, or ecological governance) after the COVID-19 pandemic. The model investigates whether the factors internal to the company might influence the enhancement of the CSR principles. The model is based on our own data obtained from the 450 online questionnaire surveys conducted with managers of small and medium enterprises (SMEs) in the Czech Republic and the Russian Federation. The two countries in question have been selected due to their similarities and, at the same time, differences regarding their geopolitical orientation, pathways of economic transformation, and attitudes to sustainable development policies and embracing SDGs. Our results demonstrate that the business type, as well as the ownership structure, positively impacts the introduction of CSR and sustainable development principles in SMEs in question, while the company’s age has a negative impact. Our results might be of special importance for the stakeholders and business owners wishing to enhance CSR practices and promote sustainable economic development in their enterprises in the post-COVID era. Full article

Urban travel is a major component of urban transport, and the total carbon emissions of urban transport can be effectively reduced if the carbon emissions of residents’ travel can be reasonably controlled. Based on the questionnaire data of many different types of residential areas in Guangzhou, the daily travel behaviour of residents was analysed and their travel carbon emissions were calculated. The differences in travel characteristics and travel carbon emissions of residents in different types of residential areas were compared. The influencing factors of residents’ travel carbon emissions were divided into three categories: individual socio-economic factors, built environment, and residents’ travel behaviour. On this basis, a structural equation model is established to study the impact mechanism of residents’ travel carbon emissions. The path relationship between endogenous variables and endogenous variables, as well as the path relationship between exogenous variables and endogenous variables were investigated. The interactions between various influencing factors of residents’ travel carbon emissions were examined. The results show that: (1) there are significant differences in residents’ travel carbon emissions in different types of municipalities. Residents’ travel carbon emissions in Guangzhou are closer to the 60/20 distribution; (2) compared with individual socio-economic factors, the impact of the built environment on travel carbon emissions is more obvious; (3) travel distance and travel mode are the factors that directly affect residents’ travel carbon emissions. Proposals have been made to reduce the carbon emissions of residents travelling. Full article