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Life cycle carbon dioxide emissions of bike sharing in China: Production, operation, and recycling
Abstract
Recent global environmental initiatives designed to achieve a more sustainable society include the United Nations’ sustainable development goals (SDGs) and the Paris Agreement. While the shared economic model has long been linked to the creation of the sustainable use of resources, one problem encountered by the bike sharing is whether the current management model can maintain the focus on sustainability in China. Based on the amount of resources consumed during bike production, operation, and recycling, this paper aims to use life cycle carbon emission assessment to calculate an emission reduction threshold for bike-sharing industry. The research obtained energy consumption data from the OFO Curve bike, which is the most commonly used type of bike sharing in China. Calculating the average distance traveled and number of times each bike was used per day via the Baidu Map Application Program Interface, we found that the average number of times each bike was used per day was 4.552, and the average riding distance was 0.356 km. Additionally, the overall utilization of shared bikes averages about 50%. Further results show that the whole life cycle carbon footprint of one bike is 34.56 kg CO2. The power generation by incineration produces 1.9916 kg CO2 in less than a landfill. If a bike is deposited directly in a landfill, it will take 31 years to degrade. The final calculations show that based on the current number of bikes, each used at least 686 days to achieve a net positive reduction in emissions. This paper provides a basis for capacity management and operation management of shared bikes from the perspective of pro-environment and provides a new angle for the research on environmental impact of sharing economy.
... The report claims that the short-lived booming sharing bikes will be produced extra carbon emissions and waste a lot of materials during sharing bikes production [9] . By contrast, due to the advance of competitiveness and rise in output, bike sharing brings more advantages for Ireland under different development backgrounds and got more competitive than other cities [10] . ...
... As the researchers note "PPE is productive process emission which used to count carbon emissions, while EC represents the energy consumption of producing bikes, and EF is the carbon emission factor of producing bikes". It is worth noticing that Chen provides an in-depth analysis of the equation in the operation and dispatch stage to get exact results [9] . ...
... The highest proportion in the production stage of carbon emission was 87% and the energy consumption ratio of raw materials account for 93%. The raw materials production process is the main part of energy consumption [9] . Figure 5 illustrate that solar panel, steel components, and bicycle frame components occupy more than 95% of the whole life production process which affect our environment [17] . ...
Bike sharing always been regarded as one of green transportation to reduce carbon emissions all over the world. It was a sustainable development method supported by governments. While the emergence of bike sharing provides convenient transportation for humans, the current situation of bike sharing is facing several challenges in our cities. Intensive carbon emissions might be produced from continuous production of sharing bikes under the oversupply problem which has a negative effect on the urban environment. This literature review proposed to reconsider the relationship between bike sharing system and carbon emissions to recognize the real meaning of bike sharing. The article overviews the development of bike sharing system, summarize from the history of bike sharing and design the measurement of bike sharing system with study cases in recent years. Collecting carbon emissions computational formula calculates life cycle carbon dioxide emissions of bike sharing to evaluate energy consumption. However, some studies remain narrow in focus dealing with the design method of bike sharing system or carbon emissions estimate. These findings signal the need for additional studies to investigate more about the adverse impact of bike sharing and try to keep the balance supply with demand to protect our cities' environment.
... Luo et al. (2019) [44] compared the GHG emissions of DBS systems and station-based bike systems in the U.S from the perspective of an LCA. Chen et al. (2020) [45] used an LCA to measure CO 2 emissions thresholds during the production, operation, and recycling of shared bikes. They also calculated the minimum time needed using bike sharing to offset the above ISPRS Int. ...
... Luo et al. (2019) [44] compared the GHG emissions of DBS systems and station-based bike systems in the U.S from the perspective of an LCA. Chen et al. (2020) [45] used an LCA to measure CO 2 emissions thresholds during the production, operation, and recycling of shared bikes. They also calculated the minimum time needed using bike sharing to offset the above ISPRS Int. ...
... Third, this study only evaluated the nonlinear associations between the influencing factors and the potential GHG emission reduction of bike-sharing operations. However, bike sharing still has environmental impacts from the other phases of its life cycle (e.g., bike manufacturing and bike rebalancing) [12,44,45]. We encourage researchers in related fields to comprehensively analyze and compare the life cycle GHG emission characteristics and influencing factors of bike-sharing systems. ...
Existing studies have limited evidence about the complex nonlinear impact mechanism of road network topology and built environment on bike-sharing systems’ greenhouse gas (GHG) emission reduction benefits. To fill this gap, we examine the nonlinear effects of road network topological attributes and built environment elements on the potential GHG emission reduction of dockless bike-sharing (DBS) trips in Shenzhen, China. Various methods are employed in the research framework of this study, including a GHG emission reduction estimation model, spatial design network analysis (sDNA), gradient boosting decision tree (GBDT), and partial dependence plots (PDPs). Results show that road network topological variables have the leading role in determining the potential GHG emission reduction of DBS trips, followed by land use variables and transit-related variables. Moreover, the nonlinear impacts of road network topological variables and built environment variables show certain threshold intervals for the potential GHG emission reduction of DBS trips. Furthermore, the impact of built environment on the potential GHG emission reduction of DBS trips is moderated by road network topological indicators (closeness and betweenness). Compared with betweenness, closeness has a greater moderating effect on built environment variables. These findings provide empirical evidence for guiding bike-sharing system planning, bike-sharing rebalancing strategy optimization, and low-carbon travel policy formulation.
... Bike-sharing systems have grown rapidly in recent years and are considered important in reducing CO 2 emissions [1]. Bike-sharing is considered to play a role in encouraging people to participate in energy saving and emission reduction [2]. It promotes green transportation and contributes significantly to carbon neutrality [3]. ...
... Kou et al. found that the bike-sharing system in the United States could only reduce less than 0.1% of the greenhouse gas (GHG) emissions from the transportation sector through their assessment [69]. Chen et al. analyzed the full life cycle emissions of the dockless bike-sharing system of China's ofo dockless bike-sharing company and found that the main contribution of carbon emissions from shared bicycles is in the production stage [2]. Mao et al. similarly assessed the full life cycle of shared bicycles in China and found that the production stage brings the greatest environmental impact, and its average contribution to the environmental impact is as high as 81.18% [13]. ...
... This function converts the weights to [1,2]. Ultimately, the improved method is given below ...
In this paper, we investigate the sustainability of docked bike-sharing in Nanjing in terms of environmental benefits and financial operations by comparing the data of March 2017 and March 2023 in Nanjing. We modify a community detection method, give and prove dynamic boundary conditions for the objective function of the heuristic algorithm, and realize the estimation of the rebalancing coefficients for this mega-system, thus obtaining more accurate emission factors. We find that there are significant differences in the results obtained from environmental benefit assessments over time. Further, there are also significant differences at the national level. This may signify that the assessment data of one country’s system cannot give a direct reference for another country’s system. Second, we considered the economic basis required for the environmental benefits of docked bike-sharing systems. We have calculated the sustainability of the system’s financial operations by considering its revenues over the next nine years, including the cost of facility inputs, facility upgrades, dispatching costs, labor costs, maintenance costs, and the time value of money. The results show a 4.6-fold difference in emission factors between 2017 and 2023; comparing 2017 to 2023 (when demand loss has been severe), the investment in 2017 will be recouped 2 years later than in 2023. Switching distribution vehicles from fuel vehicles to electric trikes would severely deteriorate the operator’s key financial metrics while only reducing the emission factor value by 8.64 gCO2 eq/km, leading to an unsustainable system. This signals the potential for the financial unsustainability, or even bankruptcy, of operators if the requirements for sustained emissions reductions from the bike-sharing system are divorced from the form of the economy on which it is sustainably operated. Finally, we consider the geographical patterns between environmental benefits and financial operations. We find that financial sustainability varies across geographic locations. Under financial sustainability, we gave emission factors under the mix distribution vehicle scenario.
... The rapid development of bike sharing in China has effectively met the "last mile" travel needs of local residents, not only bringing economic benefits to individuals and collectives [1], but also playing an important role in net zero [2]. However, in the process of the development of the bike-sharing industry, there are also problems that need to be regulated (commonly known as the "bike-sharing siege"), such as abandoned bikes being discarded at will, bikes being parked indiscriminately, operation and maintenance not being in place, disorderly competition among companies, and the main responsibility of companies not being implemented. ...
... However, in the process of the development of the bike-sharing industry, there are also problems that need to be regulated (commonly known as the "bike-sharing siege"), such as abandoned bikes being discarded at will, bikes being parked indiscriminately, operation and maintenance not being in place, disorderly competition among companies, and the main responsibility of companies not being implemented. As solid waste, abandoned bikes not only crowd public roads, but they also produce large amounts of harmful gases (CO 2 , SO 2 , NO X , etc.) [2] and heavy metals [3]. Abandoned bikes are difficult to dismantle, difficult to repair, have a low recycling price, are widespread, and produce heavy pollution, which bring new challenges to urban environmental management. ...
... (1) How do the recycling subsidy amount and resident satisfaction affect stakeholder decisions? (2) In order to implement the EPR system nationwide, what subsidy policy should local governments adopt: the fixed-amount recycling subsidy policy or regressive recycling subsidy policy? (3) Under the policy of regressive recycling subsidies, how can local governments influence stakeholders' decisions to promote the EPR system? ...
The launch of large-scale bike sharing in China has effectively met the demand for low-carbon short-distance travel, but it has also led to the emergence of a large number of abandoned bikes, which is called the “bike-sharing siege”. In order to achieve the sustainable development of the bike-sharing industry, this paper discusses how to encourage bike-sharing companies to recycle and reuse abandoned bikes and improve the efficiency of local government financial resources based on the promotion of the EPR system. We apply the evolutionary game to investigate the interaction mechanism of complex behaviors between local governments and bike-sharing companies under two subsidy policies: a fixed recycling subsidy and regressive recycling subsidy. The results show that both recycling subsidy policies have diminishing marginal effects. In addition to incentives, local governments need to unify bike-sharing parking, establish bike-sharing monitoring platforms, and reasonably allocate bike parking spaces to ensure the quality of the urban environment. Under effective regulation, by implementing a regressive recycling subsidy policy and setting a rational amount for the recycling subsidy, local governments can effectively promote the EPR system, strengthen the environmental responsibility of companies, and avoid the “free-rider phenomenon”. Based on the current situation in China, this research provides references for each local government to formulate management policies from the perspective of subsidy policy.
... For this purpose, some measurement models of environmental benefits from public bikes have been developed, for which there are two main approaches. The first is to undertake a life cycle assessment considering carbon emissions generated and reduced over the entire life cycle of public bikes [1,[22][23][24]. The second is to estimate the capability of reducing carbon emissions by reducing demand as travel is shifted to bikeshare [25][26][27][28]. ...
... There is a large number of studies on carbon emission reductions from bikeshares. Some studies analyze the policy and system of the carbon emissions trading market and their impact on bike transportation [30]; some studies estimate the amount of carbon emissions from bikeshares [1,[22][23][24]; others analyze the theory of the mechanism of carbon emission reductions from bikeshares [26]; and yet other studies analyze the carbon emission reduction effect of the e-bike [27,28]. ...
... The results showed that the bike sharing in Shanghai saved 8358 tonnes of petrol and decreased CO 2 and NO x emissions by 25,240 and 64 tonnes in 2016. Chen Jingrui et al. used a life cycle carbon emission assessment to calculate an emission reduction threshold for the bikesharing industry [22]. The results showed that the whole life cycle carbon footprint is 34.56 kg CO 2 /bike, and if a bike is deposited directly in a landfill, it will take 31 years to degrade. ...
The reduction of carbon emissions has become a heated background topic in the context of climate change. This paper estimates the potential for carbon reduction from the use of public bikes, on the basis of a travel mode choice model and a carbon emission calculation model. A probability model for the travel mode choice is built to predict travel demands of different modes, and is based on the Logit-based stochastic user equilibrium model. According to this, the generalized travel cost of choosing to walk increases with distance, but the cost of choosing a taxi decreases with distance. When the trip distance is 1.4 km, the walk cost equals to that of the taxi, while if the trip distance is smaller than 1.4 km, the probability of the walk is larger than of a taxi, and vice versa. The case of Ningbo is analyzed. Based on the monthly travel data, the travel characteristics of the public bikes are first analyzed; these indicate that the medium travel distance is 1.44 km, and that the number of trips less than 1.6 km accounts for 70% of all trips. This reveals that the public bike trips are mainly short-distance and in workday rush hour. The related carbon emission reductions of Ningbo on average are 1.97 kg/person and 1.98 kg/km², and the reductions are positively linearly related to the average hourly total turnover rate, which means the turnover rate is a great parameter to reflect the capability of carbon emission reductions.
... Currently, there are two main directions of research on the environmental impact of contributing bicycles. The first one is the study of the life cycle of bicycle-sharing, in which the threshold of zero carbon emissions is found by exploring the carbon emissions generated during the life cycle of bicyclesharing [15][16][17]. Through the analysis of the carbon emission of bicycle-sharing, D' Almeida et al. took Edinburgh, UK, as a case study, and then obtained the carbon emissions of bicycle-sharing [18]. ...
... Among the current studies on the substitution effect of bicycle-sharing, Shaheen et al. obtained the substitution effect of bicycle-sharing in North America by analyzing the effect of bicycle-sharing on other travel mode preferences [23]. Fishman et al. studied the substitution effect generated by bicycle-sharing in the United States, the United Kingdom, and Australia, respectively [24,25], and Chen et al. obtained the combined emission reduction factor by investigating the substitution effect of bicycle-sharing in China on car and cabs, and the substitution effect of private cars and walking [15]. However, it can be seen that all the substitution effects for bicycle-sharing are static, i.e., the current studies are based on data studies over a certain period while they have not analyzed the impact of the development of electric vehicles on the combined emission reduction factor. ...
... Further, the promotion of electric vehicle development is an important way to reduce emissions and realize the future carbon neutrality goals in China [29][30][31]. In addition, the current research on electric vehicles consists of analysis of the life cycle models of electric vehicles [15,32], the emission reduction options for renewable energy and electric vehicles [33], and the impact of substitution effects on different vehicle materials [34]. ...
Bicycle-sharing plays an important role in solving the “last mile” problem of Chinese people and promoting the construction of an environment-friendly society. This study assesses the carbon emissions generated in the life cycle of bicycle-sharing, examines the substitution effect of bicycle-sharing, and quantifies the depletion rate of bicycle-sharing in combination with the current rate of electric vehicles in China. The depletion rate of shared bicycles in China is high, roughly 5–15% per year. In addition, we discuss scenarios where the annual growth rate of electric vehicles is 40%, 50%, and 60%. Results show that when electric vehicles’ depletion rate is 5% and the annual growth rate of electric vehicles is 40%, the largest net emission reduction in 2025 is 1.96 million tons. Additionally, when electric vehicles’ depletion rate is 5% and the annual growth rate of electric vehicles is 60%, the smallest net emission reduction totals 1.7 million tons.
... 2 Literature review 2.1 Behavior and travel pattern of shared bike users Behavior patterns of bike-sharing users have raised considerable concerns worldwide. Studies have mainly focused on users' personal characteristics (Chen et al., 2020a;Zamir et al., 2019) and usage patterns (Link et al., 2020;Wei et al., 2021), including the travel speed and time, usage types, and spatial structure of bike-sharing trips (Link et al., 2020;Zhang et al., 2017). In addition, some studies have discussed factors affecting users' behaviors (Shen et al., 2018), as well as the benefits of and problems caused by bike-sharing (Tao and Zhou, 2021). ...
... There are different methods to measure the carbon reduction emission effects of DLBS. Chen et al. calculated the whole life cycle carbon footprint of one bike as 34.56 kg CO 2 according to the Life Cycle Analysis (LCA) theory (Chen et al., 2020a); Li et al. calculated that one bike-sharing trip could reduce approximately 80.77 g CO 2 -eq per distance travelled in greenhouse gas emissions , and Sun et al. compared the quantity of reduced carbon emissions due to DLBS between railway stations in Beijing . However, the conclusions of the studies on environmental benefits produced by DLBS differ substantially and are difficult to compare. ...
Introduction
Dockless bike-sharing systems have become popular in urban China. However, how dockless bike-sharing influence users’ daily travel choices has rarely been investigated.
Methods
Drawing upon travel-related data collected by the day reconstruction method in Fuzhou, this study explores whether and how the mode shift caused by dockless bike-sharing reduces the carbon emission effect in different scenarios.
Results
The results show that the mode proportion varied before and after the introduction of dockless bike-sharing and affected by travel distance. The carbon emission reduction effect of shared bikes shows an inverted U-shape with the increase of distance, with the carbon emission reduction gain from the medium-distance travel group of 3-5 km being the largest. The unit carbon emission reduction coefficient presents an inverted U-shape rather than a linear rise with distance. The annual personal carbon emission reduction of dockless bike-sharing users is 4,312.42 g and the total in Fuzhou is 33.03 Mt per year.
Discussion
These findings indicate that a improve of the city’s fast cycling lane system can promote the travel mobility and efficiency in the central downtown area.
... The recycling of shared bikes has also gradually been paid attention to by the academic community. Most literature on recycling shared bikes examines the routes for recycling from the perspective of actual operation, such as Chang et al. [32], Chen et al. [35], Wang and Szeto [36] and Lu et al. [37]. Du et al. [23] and Zhang et al. [38,39] also studied the routes for recycling and rebalancing. ...
... (1) Few studies have considered the combination of the BRP and recycling broken bikes. It is more in line with the current development of the urban shared bike industry [35]. This paper introduces a novel variation of the BRP that fills this gap and has theoretical significance. ...
Bike-sharing system has become an indispensable element of sustainable urban transportation, effectively resolving the "last mile" transportation challenge for city dwellers. A major daily operational task in these systems is planning a fleet to rebalance the bikes over time, ensuring the optimal availability of bikes and docks to users. Recycling is also a daily work with the an increase in the number of broken bikes. However, rebalancing or recycling operation is always regarded as an independent tasks. They are separately studied in existing papers. Thus, this paper develops an operational strategy for recycling broken bikes during the rebalancing process, and studies the combination of the station inventory and vehicle routing problems. First, an inventory routing model is constructed with the aim of minimizing the total costs including procurement, expected user loss, inventory and transportation costs. Then, a two-stage iterative algorithm is developed with both exact and heuristic algorithms. We use real-world data from Capital Bikeshare to test our proposed model and approach, which shows the two-stage iterative algorithm is efficient and outperforms existing solutions in reducing total costs. Finally, the sensitivity analysis is performed on key parameters such as the vehicle’s capacity, unit penalty costs for customer dissatisfaction events, unit inventory holding costs and the observation period of rebalancing. It shows that enterprises can reduce the total cost by altering vehicle’s capacity, reducing the unit inventory holding costs or changing the observation period of rebalancing.
... If a bicycle is directly landfilled, it takes 31 years to decompose. Furthermore, for a genuine net positive emissions reduction to be achieved, a user would need to ride the bicycle for 686 days (Chen et al., 2020). Wang (2021) conducted a life cycle analysis on shared bicycles in schools and found that the highest carbon emissions occurred during the raw material acquisition and maintenance stages (35%), followed by the recycling phase (15%), and the manufacturing stage (10%) ( Table 1). ...
... In addition, bicycles also generate a certain amount of carbon emissions during the maintenance and recycling stages. If a bicycle is directly disposed of in a landfill, it takes 31 years to degrade, and it would take us over 600 days of using a bicycle to achieve true net-zero emissions (Chen & Chen, 2018;Chen et al., 2020). Therefore, finding alternative technologies, as well as applying and optimizing recycling and reuse methods, are crucial pathways to maximize the carbon reduction benefits of bicycle products. ...
Under the trend of environmental protection and carbon reduction, bicycles have become an important component of green urban transportation, and therefore, the net-zero emissions in the manufacturing process of the bicycle industry have become even more important. This study focuses on the green transformation of the bicycle industry in Taiwan and explores the carbon distribution of bicycles through the product life cycle. In order to understand the status of the industry, we invite four senior industry experts and three green design scholars. It conducts research and analysis on green design and carbon reduction in the bicycle industry through expert interviews and grounded theory. In the face of development challenges, we believe that the Taiwan bicycle industry should adopt a systematic approach, carry out phased carbon reduction tasks, and implement product life cycle carbon footprint verification in order to achieve a balance between business models and sustainable operations. In the present study, we formulate preliminary carbon reduction strategies for different-scale enterprises into four stages based on the current status of the industry: (1) product plan, (2) design and development, (3) manufacturing, and (4) collaborative carbon reduction. These strategies can be applied to different production stages of the manufacturer. In addition, we plan a green design carbon reduction flowchart for the bicycle industry from the perspective of life cycle, which allows them to think more comprehensively about product carbon reduction plans. In order to alleviate the international and internal pressure faced by the industry, we have also formulated three countermeasures: (1) risk reduction and increased implementation willingness, (2) transformation of product–service models, and (3) implementation of carbon footprint verification throughout the life cycle. Furthermore, the assembly of bicycle products depends on raw materials and parts from different countries. Therefore, carbon reduction in the bicycle industry is not a goal that can be achieved by single manufacturer or single stakeholder’s efforts. Although this study focuses on the bicycle industry in Taiwan, when facing changes in the international market, it is crucial for enterprises to seize the opportunity to transition timely. The research findings can still provide reference for other countries facing similar challenges. Subsequent studies can also test the methods and strategies proposed in this research in actual industry settings, thereby providing more practical implementation suggestions and promoting green design and carbon reduction in the industry.
... This shift can reduce road congestion, making urban travel more efficient [8]. Furthermore, Chen et al. (2020) leveraged OFO Curve bike data to estimate the life-cycle carbon footprint of shared bikes, demonstrating their potential to replace short-distance car trips and improve first-and last-mile connectivity to public transit, thereby enhancing the overall use of public transport [9,10]. ...
With increasing concerns over climate change and air pollution, sustainable transportation has become a critical component of modern city planning. Bike-sharing systems have emerged as an eco-friendly alternative to motorized transport, contributing to energy conservation and emission reduction. To elaborate on bike-sharing’s contribution to urban sustainable development, this study conducts a quantitative analysis of its environmental benefits through a case study of the Bluebikes program in the Boston area, using a longitudinal dataset of 20.07 million bike trips from January 2015 to December 2024, with data between January 2020 and December 2021 excluded. A combination of Scheiner’s model and Multinomial Logit model was adopted to evaluate the substitution of Bluebikes trips, an optimized Seasonal Autoregressive Integrated Moving Average (SARIMA) model was employed to predict future usage, while energy savings were calculated by estimating reductions in gasoline and diesel consumption. The findings reveal that during the analyzed period, Bluebikes trips saved 2616.44 tons of oil equivalent and reduced CO2 and NOX emissions by 7614.96 and 16.43 tons, respectively. Furthermore, based on the historical trends, it is forecasted that the Bluebikes program will annually save an average of 723.66 tons of oil equivalent and decrease CO2 and NOX emissions by 2422.65 and 4.52 tons between 2025 and 2027. The results highlight the substantial environmental impact of Bluebikes and support policies that encourage their usage.
... On the one hand, new mobility solutions bring promising advantages, such as lower fuel consumption [7], reduced greenhouse gases emissions (J. [10]), and decreased traffic congestion [18]. On the other hand, the wide range of transport modes can be challenging for users as each service has its own mobile applications [32]. ...
The penetration of shared mobility services is spreading worldwide, leading to the restructuring of the existing transportation system. Mobility as a Service (MaaS) is presumed to answer the challenge of utilizing several transport modes including emerging services, where travel planning, booking options, payment methods, and ticketing solutions are integrated into one single application. MaaS promises several benefits, but studies on motivational mechanism behind the technology adoption are still lacking and usually rely on structural equation modelling approach. In this study, we apply latent class cluster analysis using attitudinal variables as indicators to examine the motivational factors in adopting MaaS, revealing the heterogeneity in preferences among college students. Based on the results, five clusters are identified, namely MaaS neutral, MaaS enthusiast, MaaS opponent, MaaS avoider, MaaS lover. College students with high environmental consciousness and seeking variety are more enthusiastic about MaaS, while others coming from higher-income households are likely to adopt MaaS. The negative precautions regarding MaaS should be decreased by respecting data privacy and providing easy-to-use MaaS applications, while the perceived safety risks should be eliminated by providing emergency features. Finally, some policy recommendations are drawn based on the identified clusters of university students.
... Taking shared bicycles as an example, they reduce energy consumption and environmental pollution. Moreover, through route optimization and intelligent scheduling technologies, they decrease ENI (Chen et al., 2020). ...
The digital economy exerts both positive and negative influences on urban sustainable development, yet there is a notable gap in the existing research concerning its impact on energy intensity and the underlying mechanisms. this study pioneers the investigation of a nonlinear relationship between the digital economy and energy intensity, revealing a significant inverted U-shaped relationship. Specifically, we observe a noteworthy reduction in energy intensity when the digital economy index surpasses 0.286. Our empirical findings indicate that the digital economy not only directly influences energy intensity but also exerts an indirect impact through initiatives such as the promotion of green innovation and the agglomeration of high-tech industries. Importantly, the promotional effects of the digital economy exhibit heterogeneity with respect to geographical location, resource endowment, and urban scale. This paper contributes to the theoretical understanding of information technology in urban green development by analyzing the mechanisms of the digital economy at the urban level and its intricate impact on energy intensity.
... La Economía Colaborativa (EC) proporcionó una base para la gestión de la capacidad y la gestión operativa del modelo económico compartido, desde una perspectiva ambiental estudiando el impacto de la economía colaborativa [1]- [2]. Además, las plataformas de EC han revolucionado el sector del alojamiento turístico generando discusión en las implicaciones gerenciales para la sostenibilidad (SO), la gestión del comportamiento del consumidor y los campos de marketing [3]. ...
El presente estudio tiene como objetivo realizar una revisión sistemática de la investigación en economía colaborativa desde un enfoque de sostenibilidad como modelo de negocio. El trabajo y servicios compartidos en busca del bienestar social permiten que las empresas operan con modelos de negocios novedosos bajo actividades de sostenibilidad. Siendo así, se han realizado varios enfoques bibliométricos que buscan priorizar la relaciòn de la EC con sectores de movilidad, alojamiento y turismo. Se realizó una consulta en WoS y se clasificaron los más importantes en la plataforma ToS. Por último se identificaron las perspectivas con base en la analogía del árbol, con esto se demostró la motivación de los consumidores en el uso de servicios compartidos, el alojamiento fuente principal del consumo compartido y el modelo de negocio de EC hacia la sostenibilidad.
... In terms of carbon emissions, most studies concerning the carbon emissions of BSS concentrated on carbon emissions during the life cycle of BSS and the carbon reduction from BSS as a substitute travel mode (Chen et al. 2020;D'Almeida et al. 2021;Wang and Sun 2022). The life cycle of BSS includes bike production, operation, and disposal. ...
This study explored spatiotemporal patterns of e-bike usage. The carbon emissions of electric bike-sharing systems in Chicago were estimated, and their spatial distribution was characterized. Customers preferred e-bikes as a transportation mode for trips that took less than 20 min, indicating that the use of e-bikes for short trips could reduce traffic congestion. This finding has an important implication for urban planning studies. It would be more reasonable to calculate the potential reduction of carbon emissions from substituting e-bike rides for short trips by car or other transportation modes rather than for all trips. This study also identified hotspots and corresponding peak periods. Recommendations were made for strategically dispatching e-bikes around the central business district to meet customer needs during weekday peak commuting hours. E-bike trips produced the least amount of carbon in January. Emissions gradually climbed until April, when they almost tripled the January emissions. Throughout these 4 months, e-bike trips generated 1624.4 kg of carbon emissions, with weekday emissions accounting for the majority. The spatial patterns of carbon emissions were visualized based on street networks. The method used in this study for exploring carbon emissions can be applied to future research after adjusting the model parameters to fit particular scenarios.
... In overcoming this problem, big cities are competing to find the right way to develop a sustainable transportation system. For example, the Beijing Government China, proposed implementing eco-friendly travel in large cities by development in the form of bike sharing to reduce carbon emissions (Chen, Zhou, Zhao, Wu, Wu, & 2020). The Copenhagen government also supports including bicycle transportation in the city's development planning system by dividing the percentage of bicycle trips by 50 % from 75 % of nonmotorized vehicle trips (Braun et al., 2016). ...
... According to statistics, the daily cycling volume of shared bikes in Shenzhen is about 1.38 million. We also know that cycling can replace driving a car for 100km, thus reducing carbon dioxide emissions by about 20.1kg (Chen et al., 2020). Assuming that you only drive once a day, the increased distance is used to replace the distance travelled by car, which means a reduction of 554.8 tons of carbon emissions per day. ...
Extending cycling distances is crucial for sustainable urban transport development and plays a role in encouraging the shift from motorized vehicles to public transport. However, there is a lack of research examining the combined impacts of both objective and perceived aspects of the cycling environment on cycling distance, and the existence of threshold effects remains unclear. This study uses 2019 cycling data from Shenzhen, China, employing the XGBoost algorithm to uncover the relative importance and thresholds of objective and perceived factors in the cycling environment. The results indicate that population density (24.8%), road network density (15.2%), the proportion of recreational facilities (9.1%), perceived accessibility (8.0%), and comfort (8.6%) hold high relative importance in predicting cycling distance. Also, maintaining road network density between 3 to 6 km/km2 and increasing the population density to exceed 22,000 people/km2 proves effective in extending cycling distances. Land use demonstrates a threshold effect, with cycling distances increasing when the recreational facilities share exceeds 8%, transport facilities share remains below 25%, and commercial facilities share stays below 30%. Perceived metrics exhibit a clear threshold effect. The study identifies that perceived safety indicates a psychological bottleneck in increasing cycling distance. Perceived accessibility is positively correlated with cycling distance when accessibility is at a low level, while comfort shows a positive correlation with cycling distance when comfort is at a high level. These findings can contribute to refining land planning and prioritizing resource allocation for organizations aiming to promote non-motorized travel and design bicycle-friendly environments.
... Bike-sharing is considered a more environmentally friendly mode, especially in terms of reducing energy consumption if suitable strategies are incorporated (Li et al., 2020). Bike-sharing is also claimed to have positive impacts on the environment since it reduces greenhouse gas emissions (Chen et al., 2020;Fan & Harper, 2022;Y. Zhang & Mi, 2018). ...
Mobility as a Service (MaaS) is becoming popular for solving transportation issues since it supports the integration of several shared transport modes through a single application. Even though this mobility solution is claimed to decrease the use of private cars, car users show less interest in using MaaS. Moreover, they are most interested in using car-sharing in MaaS packages instead of other more environmentally friendly transport modes such as shared micro-mobility services. Therefore, this review paper aims to examine the potential effects of transport modes that are often included in MaaS packages should be investigated. A total of 14 articles investigating the mobility packages are discussed, and information related to the included transport modes is extracted. Based on the findings, several transport modes are assessed regarding their impacts on transport externalities. Based on the findings, ride-hailing has some traffic issues, such as traffic density and the increase in total vehicle-kilometers travelled. The indirect effect of this issue is environmental problems such as CO2 emissions and energy consumption. In general, other transport modes have positive impacts on transport externalities. Finally, future studies could explore the effects of MaaS on transport externalities by using real implementation data.
... In the context of city carbon peaking and neutrality, bike sharing has been widely recognized as a green, convenient, and economical travel mode (Ma et al., 2020). It offers several advantages such as alleviating traffic congestion (Fan & Zheng, 2020), reducing carbon emissions from transportation (Chen, Zhou, et al., 2020;Chen, Zhang, et al., 2022), promoting personal health (Bullock et al., 2017;Clockston & Rojas-Rueda, 2021), and improving travel experience (Chen, van Lierop, et al., 2020). Additionally, with dockless bike-sharing (DBS) systems, it can effectively extend the service range of urban metro by solving the first-and last-mile travel problems Li et al., 2020). ...
The influence of the built environment on dockless bike-sharing (DBS) trips connecting to urban metro stations has always been a significant problem for planners. However, the evidence for correlations between microscale built-environment factors and DBS-metro transfer trips remains inconclusive. To address this, a framework, augmented by big data, is formulated to analyze the correlation of built environment with DBS–metro transfer trips from the macroscopic and microscopic views, considering Beijing as a case study. The trip density and cycling speed are calculated based on 11,120,676 pieces of DBS data and then used to represent the characteristic of DBS-metro transfer trips in a multiple linear regression model. Furthermore, a novel method is proposed to determine the built-environment sampling area around a station by its corresponding DBS travel distances. Accordingly, 6 microscale built-environment factors are extracted from street-view images using deep learning and integrated into the analysis model, together with 14 macroscale built-environment factors and 8 potential influencing factors of socioeconomic attributes and metro station attributes. The results reveal the significant positive influence of greenery and presence of barriers on trip density and cycling speed. Additionally, presence of streetlights is found to be negatively correlated with both trip density and cycling speed. Presence of signals is also found to have an influence on DBS-metro transfer trips, but it only negatively impacts trip density.
... A comparative LCA of station-based and dock-less bike sharing system in the United States was conduted by Luo et al. (2019), exposing the sustainability of both systems in the condition of well design and operation. D' Almeida et al. (2021) and Chen et al. (2020) executed the emission assessment of shared bicycles in Edinburgh and China from the life cycle perspective, demonstrating the emissions of one bicycle were 87 g CO 2 e/km in Edinburgh and 34.56 kg CO 2 in China, respectively. These LCA studies only focused on the shared bicycle itself, however, the substitution effects from transportation modes transit are obviously significant. ...
The emergence of Bicycle-Sharing Systems (BSSs) has brought about changes in traffic systems and generated economic, environmental, and human health effects. This study took Beijing as the research object, and aimed to examine the economic, environmental, and human health effects of BSSs and the key drivers affecting the environmental performance of shared bicycles. Questionnaire surveys were carried out to provide an overview of BSSs in Beijing by referring to the original data in the impact assessment, and the identification of key drivers. Based on the relationship between leisure-time and economic growth, the economic effects resulted in a statistically significant increase of 79.3 US dollars (612.3 RMB) and 44.4 US dollars (342.7 RMB) per capita GDP per day in the baseline of the United States and Denmark, respectively. The environmental and human health effects were evaluated using the life cycle assessment method to study the substitution of different transport modes during the entire life cycle of bicycle-sharing. The results revealed that reduced adverse environmental effects were proved to be significant and positive on all impact categories and the reduction in human health damage were positive, approximately equal to 500,000 DALYs. The sensitivity analysis demonstrated that the increase of usage rate in sharing bicycle will bring more environment benefits and human health damage reduction. The identification of key drivers was determined by the binary logistic model, and included the following: gender, monthly income, the low cost of BSSs, the location of BSSs in relation to bus stations, metro stations, and residential areas; perceptions of a higher frequency of bicycle-sharing; damaged bicycles as a development barrier, and optimism about the future of BSSs. This study provides empirical evidence for BSS management and policy making by the administrative department.
... The dynamic development of urban infrastructure, combined with pro-ecological trends, has made bicycles become increasingly popular means of transport. This phenomenon became ever more evident during the SARS-CoV-2 pandemic [1][2][3][4]. The more frequent selection of a bicycle as means of transport increasingly more often translates to limited air pollution emissions [5][6][7] and improved quality and level of life [8][9][10][11][12]. ...
The work presents the methods of collecting and processing data with the use of devices used in individual measurement methods. Based on the collected video materials, the number of vehicles was determined, which at both measuring points actually exceeded each of the tested cross-sections of the bicycle path. More precise determination of the means of transport was divided into three categories: bicycles, electric scooters, and PT (personal transporters). The data collected with the use of each of the devices was properly processed and aggregated into a form that allows for their mutual comparison (they can be used to manage the energy of electric vehicles). Their greatest advantages and disadvantages were indicated, and external factors that had an impact on the size of the measurement error were identified. The cost of carrying out the traffic volume survey was also assessed, broken down into the measurement methods used. The purpose of this paper is to analyse and evaluate the methods used to measure bicycle traffic volume. Four different measurement methods were used to perform the practical part, which included such devices as a video recorder, microwave radar, perpendicular radar, and a meter connected to an induction loop embedded in the asphalt. The results made it possible to select a rational method for measuring the volume of bicycle traffic. The measurements carried out allow optimization of bicycle routes, especially for electric bicycles. The results indicate the method of physical counting of vehicles from video footage, thanks to which it is possible to achieve a level of measurement accuracy equal to 100%.
... We found two studies providing CO 2 emission factors of free-floating BSSs in the literature. The first one is Luo et al. (2019), which found that the rebalancing CO 2 emission factor is 86 g/km based on the dockless BSS in the U.S. The second one is Chen et al. (2020), which studied the life cycle CO 2 emissions of the BSS in China and set the rebalance-induced CO 2 emission factor as 87 g/km. The CO 2 emission factor for the BSS provided by the two studies is quite close, and we adopt 87 g/km in our study. ...
This paper presents a quantitative analysis of the mode substitution and usage-phase carbon emission impacts of the electric bike-sharing system (EBSS) on urban transportation using self-administrated survey data and EBSS operating data. The substitution probabilities of a given EBSS trip for different transport modes is determined using the Bayesian inference method. Emission impact is measured by comparing the current emissions to those generated by other transport modes without the EBSS. Remarkably, the partial-trip substitution impact of the EBSS on car travel is investigated, where the EBSS serves as a connection to public transit. The results show that the EBSS barely generates new trips; most short-distance EBSS trips were transferred from walking and conventional bike-sharing, and most long-distance trips were shifted from cars, buses, and the subway. Around 5% of EBSS trips less than 2 km were transferred from the car by integrating with public transit while accounting for over half of the emission reduction. Based on our method, the CO2 emissions per km of EBSS are 19.47 g, with 6.91 g generated by e-bikes due to electricity consumption and 12.56 g by trucks for battery swapping and bike relocation. The studied EBSS has saved 75.52% of CO2 emissions that other transport modes could have generated.
... They confirm that in predicting the levels of emissions from electricity, the population and per capita electricity are very vital. Efforts are made to optimize carbon emissions reduction in China [62] while evaluating its national technological effects (Huang, et al., 2020a), international technology spillover effects [22], energy efficiency [67], political decision effects [42], trade effects [68], production, operation, & recycling effects [13,44], stock market effects [66], foreign direct investment effects [40], and household carbon emission effects [57]. Similar analyses have been evaluated for other economies and regions, for instance, the effects of innovation on carbon emission in the G20 countries [19], country risk effects on the G7 countries [12], trade & economic growth effects on the E7 economies [53], Austrian sustainability option effects [65], multinational enterprises effects in the EU [49], etc. ...
Renewable and clean energies foster carbon abatement. This makes the prospects of emission mitigation through Biofuels vital in Africa’s energy transitioning agenda. As such, the role of Biofuel energies in abating Africa’s emissions is worthy of investigation. This study goes a step further, from existing studies, to analyse the carbon abatement prospects of biofuel in Africa’s energy transitioning journey. To this end, the top five leading African economies are sampled. These economies account for over 77% of Africa’s carbon emissions and over 60% of Africa’s output. Firstly, the carbon emission levels of these top 5 economies, from 1990 to 2019, are decomposed using the Index Decomposition Analysis (IDA). Then, based on these decompositions, the carbon mitigation intensities are derived and analyzed due to Biofuels consumption. Finally, three different scenarios are designed as a forward-looking measure toward reducing carbon emissions in Africa up to 2030. The findings support that Biofuel energy consumption substantially increases carbon abatement levels and intensities in Africa. As a policy implication from these findings; the cultivation, processing, and production of biofuels and their sources should be encouraged in all African economies.
This study presents a comparative lifecycle assessment framework to quantify the personal and societal costs of internal combustion engine vehicles (ICEVs), battery electric vehicles (BEVs), and public transit, focusing on the heterogeneous impacts as megacities shift toward greener transportation. Using one-month data from nearly 160,000 BEV travelers in Shanghai, we found that switching from ICEVs to BEVs reduces personal costs by 19%, with only a modest 4% reduction in societal costs from a lifecycle cost perspective. In contrast, switching to transit offers much larger personal (48%) and societal (59%) benefits, reducing over 34,000 tons of GHG emissions monthly. This underscores BEVs’ limitations in achieving zero-emission goals. Additionally, our analysis reveals that the heterogenous responses of traveler subgroups based on travel behavior variably to five demand management strategies (bus priority, transit discount, carbon subsidy, BEV subsidy reduction, and congestion pricing), highlighting the need for targeted interventions to address diverse travel behaviors.
The use of bicycles is promoted to reduce the environmental impacts of road transport. Nevertheless, the bicycles manufacturing and transportation to the customer generate impacts related to the materials and energy used. To assess how the environmental performances of bicycles production are influenced by the local framework, the study analysed the European and Chinese production of bicycles sold in Europe. The life cycle assessment (LCA) of the production of one bicycle (set as functional unit) included the manufacturing of components, the final assembly, and the transportation to Europe when performed. Muscular propulsion bicycles (bikes) and electric bicycles (e-bikes) and two time horizons (2020 and 2030) were considered. Three geographical scenarios were evaluated: (i) bicycles manufactured in Europe together with their components; (ii) bicycles manufactured in China and shipped to Europe; (iii) bicycles manufactured in Europe with components produced both in China and in Europe. The results showed that producing bicycles in Europe allows for substantial benefits compared to producing them in China, for every type of bicycle and time horizon evaluated, with significant reductions for most of the impact categories, including climate change. The impact of producing one bike in Europe resulted between 61 and 80 kgCO2eq (107–162 kgCO2eq for an e-bike), with the lowest values observed for 2030. For the Chinese manufacturing, the impact increases to 141–166 kgCO2eq/bike (209–287 kgCO2eq/e-bike). Moreover, the study highlighted the benefits allowed by the use of renewable energy and of recycled aluminium in the components production.
Understanding the CO2 emissions and influencing factors of travelers' multiple modes can provide direction for energy conservation and emission reduction, which is of great significance for developing sustainable cities. Previous studies focused on the CO2 emissions of the transportation sector or individual modes. Which has overlooked the variations of emissions within the transport system. Hence, this study focuses on multiple modes (i.e., car, subway, bus, and bike) in the township in the Guangdong-Hong Kong-Macao Greater Bay Area. This study proposes a framework for exploring the spatial autocorrelation of urban transport emission structure based on ratios (i.e., CO2 emissions from each mode divided by total emissions) and key factors by combining spatial econometric model (i.e., Moran's I index and Spatial Error Model) and machine learning model (i.e., Random Forest and SHAP model). In addition, the spatial autocorrelation of ratios at different spatial scales is investigated. The results indicate the high spatial dependence in the ratios from each transport mode and Moran's I indices for four ratios are 0.883, 0.886, 0.706, and 0.776, respectively. In addition, subway and car ratios exhibit a negative spatial correlation (−0.798), and subway and bike show a positive correlation (0.570). Population density, road length, and land use diversity are the key drivers of CO2 emission ratios and have different effects on various transport modes. Furthermore, as the spatial scales expand from townships to distinct and city, the spatial autocorrelation of the ratios decreases. This study could provide policy implications for optimizing urban transport strategies and reducing CO2 emissions.
Shared micro-mobility systems (SMMS) have the potential to reduce CO 2 emissions of urban transportation. However, the reduction varies with fleet sizes (i.e., the number of different types of bikes in the market) and layouts. The excessive commercialization of SMMS has resulted in a decline in carbon benefits. In this study, we propose an agent-based model integrated with a lifecycle assessment (LCA) approach to evaluating the carbon benefits of unknown shared bike scale scenarios by establishing a brand-new SMMS. The proportion of satisfied actual trip demand and bike utilization rates also be analyzed for exploring the inherent mechanisms of SMMS. Take San Francisco, California, as an example, the evaluation of free-floating shared electric bikes and station-based shared-bikes analyzes five different layouts, each consisting of 121 different combinations. The results indicate that, for an area of approximately 100 km 2 with a daily travel demand of over ten thousand, a fleet size of 4500-7500 bikes is suggested, potentially leading to a weekly carbon reduction of 10,000-11,000 kg CO 2-eq. This study will provide insights for launch plan and scale management of SMMS from a sustainable perspective.
Transportation significantly contributes to carbon emissions, prompting the need for effective mitigation policies. This study addresses the knowledge gaps in assessing the effectiveness of transport carbon policies and offers the lack of a holistic comparative overview. The study used a model composed of a mixed-effects meta-regression and carbon elasticity to investigate policies, like shared bikes, mobility hubs, low emission zones, congestion pricing, electric vehicles, and hydrogen vehicles. This model included seven control variables: year, GDP, implementation costs, geographic scale, environmental benefits, and transport share of energy consumption and carbon emissions. Mobility hubs and electric vehicles ranked are top effective policies with carbon elasticities of 3.73 and 3.72, effect sizes of 127.47 and 86.73, and confidence intervals of [65.55, 107.93] and [106.17, 148.78], respectively. Followed by the low emission zone of 16.3 carbon elasticity, proving its cost-effectiveness, effect size of 10.16, and a confidence interval of [−2.48, 22.80]. Congestion pricing, despite having the highest effect size of 873.39, its confidence interval [−354.01, 2100.80] is wide, indicating the uncertainty of this effect. Shared bikes and hydrogen vehicles ranked lowest, suggesting a need for deeper life cycle-based analysis. Although this model displayed high accuracy , the findings' interpretation should consider the inherent data limitations. ARTICLE HISTORY
Bicycle-Sharing-Systems offer a modal alternative for urban mobility, allowing individuals to use bicycles without the burden of ownership while reducing carbon emissions. Previous research has emphasized the importance of considering the perceived values of those interested and involved in BSS. Thus, the objective of this study was to understand the benefits and sacrifices perceived by users of a specific system, namely Bike PE-Brazil System. Using a qualitative approach, this article collected data through direct observations and semi-structured interviews. The collected data was analyzed using Social-hermeneutic Discourse Analysis. Several dimensions were identified that shape BSS users' perception of value. These dimensions were categorized into the core benefit of value, which is access to bicycle usage, and motivators and inhibitors that influence users' perception and their continued engagement with the BSS. The findings led to the development of a theoretical model of value for BSS, encompassing motivators in economic, social, environmental, and cultural spheres, as well as inhibitors related to emotional, physical, time, research, and additional monetary costs, along with functional and physical risks. This theoretical model provides a structural perspective that expands the existing literature on sharing practices, emphasizing the role of value in ensuring the continued use of BSS.
In the coming four-decade, China will face serious challenge while shifting to carbon neutral. Photovoltaic (PV) power, as one of the most promising clean energies, is seen as an important focus for decarbonization of the power sector in China. The novelty of this s study is to use life cycle assessment (LCA) methods to analyze the CO2 emission reduction of the PV generation industry before 2060 base on the amount of energy and resources consumed and PV generation's CO2 reduction benefits during the whole industrial chain. This paper aims to examine CO2 emission reduction contribution, we firstly compute the historical emissions and predict future PV waste and new power capacity from 2010 to 2060. Then, considering the change of industrial structure and technological evolution, the yearly life cycle CO2 emission from producing stage to recycling stage is calculated. The key results show that the unit CO2 emission of PV system producing will reduce 88.07% from 2010 to 2060. PV generation industry's total CO2 emission has reached its neutrality between 2014 and 2015, and will reduce 33.03 Giga tons CO2-eq till 2060. The findings can offer relevant insights to low-carbon development of China's PV industry and will provide suggestions for policy-making.
Following the bike-sharing system, the shared electric bicycle (SEB) is experiencing explosive growth in China as an emerging shared transportation mode. While shared transportation has long been linked to energy conservation and reducing emissions, a major problem facing SEB is whether it can reach the goal of greenhouse gas (GHG) reduction. This paper aims to evaluate GHG emissions at each stage of production, operation, and disposal of the SEB using life cycle assessment of GHG emissions. We also compared the differences in GHG emissions between the recycling incineration scenario (H1) and the recycling degradation scenario (H2) in the disposal stage. The GHG emissions of SEB in the production and operation stages were found to be 379.6173 kg CO2-eq and 183.4663 kg CO2-eq, respectively. However, the GHG emission reduction in the use stage was 1049.8374 kg CO2-eq. Thus, the net GHG reduction in the life cycle of the SEB was 487.3923 kg CO2-eq. (H1) and 433.9215 kg CO2-eq. (H2), respectively, indicating that SEB had a green effect. Non-recyclable parts of SEB will take 48 years to degrade in landfills in the H2 scenario. The GHG emission thresholds for SEB were further discussed. When the average daily turnover rate of SEB was less than 4 and its operation day was less than 479, SEB would not be able to achieve the goal of GHG reduction in the whole life cycle, with the riding statistics remaining unchanged. Finally, some advice for practical issues of electric bicycle sharing in energy conservation and GHG reduction were presented in response to the results.
Autonomous bicycles have recently been proposed as a new and more efficient approach to bicycle-sharing systems (BSS), but their environmental impacts remain unresearched. Conducting environmental impact assessments at an early technological stage is critical to influencing the design and, ultimately, environmental impacts of a system. Consequently, this paper aims to assess the environmental impact of autonomous shared bikes compared with current station-based and dockless systems under different sets of modeling hypotheses and mode-shift scenarios. The results indicate that autonomy could reduce the environmental impact per passenger kilometer traveled of current station-based and dockless BSS by 33.1 % and 58.0 %. The sensitivity analysis shows that the environmental impact of autonomous shared bicycles will mainly depend on vehicle usage rates and the need for infrastructure. Finally, this study highlights the importance of targeting the mode replacement from more polluting modes, especially as traditional mobility modes decarbonize and become more efficient.
The transit-oriented development (TOD) is an effective planning strategy for achieving the Sustainable Development Goals (SDGs) in transportation by incentivizing active transport. As an active transport with high flexibility and affordability, the use of dockless bike-sharing (DBS) services was affected by many identified factors. However, few studies have examined this effect from a temporally heterogeneous perspective. Here, this study aims to test if there are heterogeneous effects of station-level land-use on the use of DBS across time and to explore how and to what extent station-level land-use affects the use of DBS dynamically. Taking Beijing as a case study, this study developed the Global Linear Regression models and the Time-Varying Coefficients panel data models to estimate the heterogeneity. The results prove the existence of heterogeneity on both working days and non-working days. The daily DBS trips were significantly correlated to the density, diversity, and most types of land-use; the effect of density maintained a high level and varies with hours, and the effect of diversity showed an insignificant effect on hourly DBS trips. Besides, public management and service facilities were critical in influencing DBS usage during the daily off-peak hours, while residences always significantly and positively correlated to the use of DBS before morning peak hours and after evening peak hours. Further, the study suggests an active transfer of DBS facilities in the businesses and commercial areas to surrounding areas during non-working days. The findings guide the improvement of the service efficiency of DBS systems, and integrate DBS management strategies into TOD practice toward SDGs.
Bike-sharing (BS) as one of the sustainable travel modes, has become increasingly popular in cities around the world. However, the comprehensive benefit (CB) derived from multiple impacts in terms of environmental, time, convenience, and payment perspectives has not been well investigated. The study proposes an Environment-Time-Convenience-Payment (ETCP) model is to quantitatively evaluate the CB of different clusters of BS users. More than 340,000 BS users in Beijing are clustered into 6 groups through a two-stage clustering algorithm, which are low-frequency travel users, subway-dependent users, less subway-dependent users, long-distance travel users, work purpose users, and BS preferred users. On this basis, 8 alternative scenarios of BS are suggested to address the mode substitution uncertainty. The study monetizes the CO2 emission and the travel-related time, so that various benefits can be quantified and estimated uniformly. The results show that long-distance travel users can bring positive CBs under all scenarios, with an average CB of 1.01 to 6.47 RMB per day for each user. Although BS usage could increase CO2 emissions under most scenarios, it would correspond to travel time or/and hassle time savings at the same time. This study also investigates the beneficial differences between dock-based and dock-less BSs existing in different cities. The dock-based system in Chicago could provide the best environmental benefit, while the dock-less one in Beijing is relatively lower due to its flexibility with more short-distance trips.
Technology-enabled bike-sharing services are increasingly being regarded as effective means of reducing air pollution. However, their actual impact on urban air pollution, especially the factors that might amplify these environmental benefits, is still not well understood. Taking advantage of Ofo and Mobike's staggered entry into 98 major Chinese cities as a quasi-natural experiment, this study empirically examines the impact of technology-enabled dockless bike-sharing services on air pollution and its heterogeneity using a difference-in-differences approach. The results show that there is significant heterogeneity in the impact of the entry of bike-sharing services on urban air pollution, while the overall effect is not significant. Specifically, the reduction effect of dockless bike-sharing service entry on air pollution is greater in cities with larger urban populations, longer average commute times, and higher public transit use, and the increase in traffic congestion further amplifies such effects. This study serves as the first empirical analysis of the impact of bike-sharing services on air pollution, providing important and valuable references for policymakers to better utilize these services to improve air quality and develop sustainable urban transport systems.
The rising population, developing technology, growing industry, urbanization, and improvement of living standards all over the world are related to the increase in household waste being hard to recycle, and resulting in concerns about the management of waste. Considering limited natural resources and seeking new ways to utilize energy more efficiently, it is vital to recycle, recover, and reuse. This means the materials are transformed into a new product with economic value. This paper reports on some household materials (batteries, styrofoam, plastic films, textile, mattresses, LED lams, and bicycles) which are difficult to recycle, giving reasons and suggestions. There are a lot of barriers to recycling these products. In the paper, some of the obstacles (economic viability of the process, complicated chemical and physical components of the products, non-availability of the materials, light weight/accumulation of the materials, transportation, technological limitations, and lack of information) to recycling are presented based on specific products. The materials that are hard to recycle generally end up in landfills and remain for a long time since they are non-biodegradable. Consequently, they lead to detrimental impacts on environment (contamination of water, soil, and air), and energy conservation. Therefore, in addition to recycling, minimizing the utilization of the household products, reuse or manufacturing them from biodegradable materials, which are capable of fully being decomposed by microorganisms to carbon dioxide, water, methane, mineral, compost, and biomass, without any bad impact on environment, are some good alternatives.
As a green travel mode, public bikes have positive implications in terms of reducing emissions. Based on the life cycle theory, we calculate the carbon emissions generated and reduced over the entire life cycle of public bikes.The calculation shows that when the average daily turnover rate of public bikes is 1.874 times/ bike, the average daily travel distance is 2.150 km, and the damage rate increases by 2.5% per month, each public bike needs approximately 7 months to reach the carbon balance. After the carbon emission balance is reached, the use of public bikes causes a net reduction in carbon emissions. However, the carbon emissions once again exceed the emission reductions after approximately 29 months of using public bikes. Furthermore, the carbon balance of the 186 stations used in Wenling City is studied.Based on the conclusions obtained, some policy recommendations are made to help public bikes achieve real emissions reduction.
As an innovative and convenient micro-mobility service, dockless bicycle-sharing systems (DBSSs) are essential to achieving green recovery of the transportation sector in post-COVID-19 world. DBSS green externalities on climate change have attracted the attention of scholars and have revealed different roles in carbon mitigation in different studies. In this study, Shanghai is employed as a case city to analyze DBSS green externalities. The direct carbon emissions reduced by DBSS cycling are calculated and the indirect carbon mitigation by a DBSS in promoting use of low-carbon public transport is estimated. The carbon consumption of DBSS from the perspective of life-cycle assessment is also valued. The results show that DBSSs have much greater carbon mitigation potential in promoting the use of low-carbon public transport than do cycling routes. The production, maintenance, and rebalance of DBSSs may produce a large number of carbon emissions and even offset their green benefits. The application of (electric) e-bikes and the integration of DBSSs and public transportation should be the key issue for policy makers to promote the green recovery of the transport sector. This study calls for further studies to demonstrate the green externality of DBSSs based on the detailed operation dataset.
The accumulation of private automobiles in urban transportation networks has become a serious challenge in many developing countries. However, introduction of a competitive mode could dissuade the passengers from commuting by car and hence alleviate traffic congestion and its consequent environmental impacts. In the present study, we address this issue by proposing an innovative mathematical model that maximizes the competitiveness of Bike-and-ride (B&R) services in inter-zonal trips, where a stand-alone Bicycle Sharing System (BSS) is uncompetitive against the car. Considering both access and egress ends of trips for the first time in the literature, the model optimally lays out the B&R network elements (a hierarchical set of BSS stations referred to as hubs, and their linking bicycle lanes) under budget constraints. Having selected the city of Isfahan as a case to implement our model on, we conduct experimental and sensitivity analyses to gain further insights into how different parameter settings affect the objective value. Results indicate significant modal shifts (from private automobiles toward B&R) occur in solution networks yielded with limited budgets available. This confirms that unlike the existing BSSs ¬that are shown to mainly substitute public transportation, if designed as a feeder mode with the objective of cutting private car trips, a BSS could be significantly effective in boosting public transportation ridership through attracting demand from private cars to B&R. With value of time taken as an indicator of the passengers’ income, it is found that affluent societies will be less likely to substitute their car for the B&R mode if the latter is the slower mode overall, and that the model fares best for developing countries. It is worth mentioning that these findings are based on the assumption of temporal and monetary expenses being the only determining factor in mode-choice.
To better understand the characteristics of a bike-sharing system, we applied complex network methods to analyze the relationship between stations within the bike-sharing system. Firstly, using Gephi software, we constructed the public bicycle networks of different urban areas based on the real-time data of the Nanjing public bicycle system. Secondly, we analyzed and compared degree, strength, radiation distance, and community structure of the networks to understand the internal relations of the public bicycle system. The results showed that there were many stations with low usage of public bicycles. Furthermore, there was a geographical division between high-demand and low-demand areas for public bicycles. The usage of public bicycles at a station was not only related to land use but also related to the usage of bicycles at stations nearby. Moreover, the average service coverage of the public bicycle system was consistent with the original intention of “the first and last mile”, and public bicycles could meet different travel needs.
The emerging bike share systems provide convenient mobility to short-distance travelers for both leisure and commuting purposes. Many cities are rolling out bike share programs. However, few studies have evaluated how bike share systems (BSS) are used to quantify their sustainability impacts. This study proposes a Bike Share Emission Reduction Estimation Model (BS-EREM) to quantify the environmental benefits from bike share trips and compare the greenhouse gas (GHG) emission reductions from BSS in eight cities in the United States, including New York, Chicago, Boston, Philadelphia, Washington D.C., Los Angeles, San Francisco, and Seattle. The BS-EREM model stochastically estimates the transportation modes substituted by bike share trips, considering factors such as trip distance, trip purpose, trip start time, the accessibility of public transits, and historical distributions of transportation mode choices. Based on average life cycle emission factors of different transportation modes, our analysis reveals that the annual GHG emission reductions contributed by the eight BSSs in year 2016 range from 41 tons of CO2-eq (Seattle) to 5417 tons of CO2-eq (New York City), while the emission reductions per trip range from 283 to 581 g CO2-eq. The total annual emission reduction is linearly correlated to the number of trips, bikes, and docks. The bike share stations located in the center of a city contributed to more total GHG emission reductions due to the high trip volumes, while the stations that are further away have higher emission reductions on a per trip basis due to longer trips and higher car substitution rate.
As a representation of smart and sustainable city development, bicycle-sharing system is one of the hottest topics in the domains of transportation, public health, urban planning, and so on. In this paper, a model is proposed for analyzing the potential reduction in emissions associated with the adoption of a bicycle-sharing system. Methods are proposed for extracting human travel modes from mobile phone GPS trajectories, together with a geometry-based probability model, to support particle swarm optimization. A comparison study is implemented to analyze the model's computational efficiency. Based on the resulting optimal layout for the network of bicycle docking stations, and considering demand uncertainty, a multi-scenario integer linear programming model is proposed to optimize rebalancing procedures (i.e., moving bicycles between docking stations according to demand), to determine the detailed design-scale information required. Mobile phone GPS trajectories from approximately 3.7 million local mobilities are used to construct a case study for Setagaya Ward, Tokyo. The results show that, compared with the previous methods, the optimal layout solved by the proposed method could reduce emissions by a further 6.4% and 4.4%. With an increase from 30 to 90 bicycle stations, the adoption of bicycle-sharing can reduce CO 2 emissions by approximately 3.1–3.8 thousand tonnes. However, emission reduction will maximally decrease by 21.26% after offset by bicycles production and rebalancing-generated emission.
With the rapid development of rail transit, a vast amount of electric power is consumed each year. However, the generation of electricity, and especially coal power generation, is an important source of greenhouse gases. Therefore, it is very important to analyze the potential of carbon emission reduction of urban rail transit based on specific electricity consumption structures. In this study, 18 cities in China were taken as the research object, and backward analysis was used to analyze the proportion limit of coal power consumption for rail transit in each city under three scenarios from 2015 to 2017. By comparing the limit value with the actual coal power consumed by urban rail transit, we analyzed the potential carbon emission reduction of rail transit relative to other traffic modes. The study results supported several conclusions. First, the traffic demand is in direct proportion to the carbon emission reduction potential in rail transit. Second, for cities with high coal power consumption, the development of ground bus transit is more conducive to achieving carbon reduction targets compared with rail transit. Finally, promoting the development of rail transit technology and lowering the energy consumption per capita unit travel distance are the fundamental ways to increase the emission reduction potential of rail transit. Therefore, as a modern transportation tool, rail transit is not an absolute emission reduction advantage for all cities. A city needs to analyze its own resource structure and travel demand together, set up suitable traffic modes to realize green growth and sustainable development.
The transport sector produced numerous global greenhouse gas emissions in China. It is important to promote low carbon commuting in China. This paper aims to investigate the determinants of intention and behavior of low-carbon commuting through bicycle-sharing (LCB) in China. Theoretical model and hypotheses are put forward by integrating the theory of planning behavior and theories of value and residual effects. Through structural equation model (SEM), the empirical analysis revealed that residual effect has the largest positive impact on intention of LCB for both males and females. Subjective norms positively affected intention of LCB for males. Attitude towards bicycle-sharing, perceived behavioral control positively affected intention of LCB for females. Intention has higher positive effect on females' behavior of LCB than males’. It is better for government to increase financial subsidies for bicycle-sharing users and producers.
Globally, crop straw is a rich resource and further establishment of its use as an energy source is an important aspect in developing the circular economy. Projects in this vein can bring benefits such as improving energy access and living conditions as well as boosting the local economy and employment opportunities in rural communities. This paper presents a detailed case study on the production of bio-natural gas (BNG) from corn straw in China, using Life Cycle Analysis (LCA) to assess energy consumption and greenhouse gas (GHG) emissions, conducting economic analysis, and analyzing operation management models. The "Nongbaomu" business model (whereby professional personnel assist farmers in the management of straw collection, bundling, storage and transportation) and the "Mutual Offsetting in Kind" business model (whereby farmers can buy a quota of the project's BNG products at a lower price in return for selling straw to the project) can ensure the acquisition of straw by the BNG project at stable prices and high quality. Because the main product (BNG) replaces refined oil products used by automobiles and the byproduct (organic fertilizer) replaces traditional fertilizer (produced using coal), the project offers the potential for significant decreases (up to 80%) in life cycle GHG emissions and fossil fuel use. Benefited from the relatively high natural gas prices in the project location and applicable government subsidies, our studied case was found to be economically viable. The findings in this study are also likely to be relevant to other countries where governments should develop industrial policies that support the development of rural distributed energy, and introduce and implement appropriate subsidies to allow BNG to compete in the traditional natural gas market. Although, enterprises are responsible for selecting an effective business models and the most appropriate technological pathway, governments should also identify the ways in which they can support businesses to make these choices.
Plant-integrated methane (CH4) and nitrous oxide (N2O) emission quantifications were performed at five Scandinavian wastewater treatment plants, using a ground-based remote sensing approach that combines a controlled release of tracer gas from the plant with downwind concentration measurements. CH4 emission factors were between 1 and 21% of CH4 production, and between 0.2 and 3.2% of COD influent. The main CH4 emitting sources at the five plants were sludge treatment and energy production units. The lowest CH4 emission factors were obtained at plants with enclosed sludge treatment and storage units. N2O emission factors ranged from < 0.1 to 5.2% of TN influent, and from < 0.1 to 5.9% of TN removed. In general, measurement-based, site-specific CH4 and N2O emission factors for the five studied plants were in the upper range of the literature values and default emission factors applied in international guidelines. This study showed that measured CH4 and N2O emission rates from wastewater treatment plants were plant-specific and that emission rates estimated using models in current guidelines, mainly meant for reporting emissions on the country scale, were unsuitable for Scandinavian plant-specific emission reporting.
Smart bikes as public transportation for the 21st century is presented. The problem of theft gave rise to a third generation of public-use bicycle programs. The high-tech solution involving intelligent transportation systems allowed public-use bicycles to be smartened and better tracked. It was suggested that Smart Bike programs should be implemented in conjunction with a hostnof bicycle facility improvement measures to make bicycling comfortable for Smart Bike users.
In this paper, measures such as planting urban greenery and using high-albedo paint to mitigate the urban heat-island effect, conserve energy, and reduce CO2 emissions were assessed. As a typical energy-saving method for buildings, reducing the internal heat sources and increasing the insulation are also assessed. We used a coupled urban canopy and building energy model to predict the heat loads of buildings in city districts, the effects of air-conditioning on energy consumption, and air temperature changes. In this model, a vertical one-dimensional local atmospheric model is coupled with an air-conditioning load calculation model for buildings, making it possible to assess the interaction between anthropogenic heat release due to air-conditioning usage and the outside thermal environment. In this study, we selected a target study region in the city of Kawasaki, Japan. When typical city districts were assessed, planting greenery or increasing albedo achieved temperature reductions of 0.6–1.0 °C and 0.1–0.5 °C, respectively, and energy savings of 40–80 and 70–90 kJ/m2/day (per unit floor area) on a typical summer day. The results from the large-scale assessment show that urban greening or albedo increases achieved the highest energy savings, of up to 400 t-CO2/day, in the entire target study region.
The methods for estimating major gaseous state pollutants emissions due to fossil fuels consumption by thermal power were introduced. The life cycle emission inventory of the Me cycle total emission amount and the unit electricity use due to the fuel consumption was calculated. The life cycle emissions amounts of unit electricity use of CO2, SO2, NOx, CO, CH4, non-methane volatile organic compound (NMVOC), dust, As, Cd, Cr, Hg, Ni, Pb, V and Zn related to the fuel consumption of thermal power in China in 2002 were 1.07, 9.93 × 10-3, 6.46 × 10-3, 1.55 × 1O-3, 2.60 × 10-3 4.87 × 10-4, 2.02 × 10-2, 2.00 × 10-6, 1.27 × 10-8, 1.69 × 10-7, 8.78 × 10-8, 2.50 × 10-7, 1.76 × 10-6, 2.88 × 10-6 and 2.40 × 10-6 kg/(kW·h) respectively. The direct emissions of fossil fuels combustion was the main source of the life cycle emission of As, Zn, Pb, Hg, dust, Cr, V, SO2, CO2, CO, Ni, NO, and NMVOC. The Cd direct emission and indirect emission was matched basically; while the life cycle emission of CH4 was mainly due to the stages of fossil fuels production and transportation.
With life cycle assessment (LCA) methodology, a life cycle model of coal-based dimethyl ether (CBDME) as a vehicle fuel is established for China. Its life cycle from well to wheel are divided into three phases. They are feedstock extraction, fuel production and fuel consumption in vehicle. The primary energy consumption (PEC) and global warming potential (GWP) of CBDME pathway are analyzed and compared with coal-based diesel (CBD) as a latent rival to replace conventional petroleum-based diesel (CPBD).This study demonstrates that the LCA methodology is very suitable and effective for the choice of vehicle fuels. One result is that the greenhouse gases (GHGs) emission of coal-based vehicle fuel pathways is usually concentrated on fuel production stage. The percentages of CBDME and CBD pathways both exceed 60%. The application of carbon capture and storage (CCS) is helpful for coal-based vehicle fuel pathways to improve their global warming effect dramatically. Compared with CBD pathway, CBDME pathway consumes less PEC and emits less GHGs emission as well. Even though the CCS and CH4-fired generation are used, the advantages of CBDME are still kept. For saving petroleum energy and reducing global warming effect, CBDME has greater potential than CBD to substitute CPBD under current fuel synthesis technologies.If the hurdles such as the maturity of engine and vehicle technologies, corresponding regulations and standards and infrastructures are reliably solved, CBDME will have better prospect in China.
Unraveling the modal impacts of bikesharing
- Shaheen
Carbon emission accounting and assessment in the life cycle of large public buildings
- Li
The bicycle: an environmental hero
- Aenews
Is the shared bike really green? A probe into the impact of shared bikes on resources and environment from the perspective of full life cycle
- Chen
Life cycle carbon emission accounting and energy saving and emission reduction benefit analysis of green buildings: a case study of an office building in Tianjin
- Zheng