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Cycling, climate change and air pollution
Abstract
Cycling is considered a healthy and sustainable form of getting from A to B. The net effects of the various forms of cycling and e-biking on mobility-related air pollutant emissions are complex. This chapter synthesizes research on the potential of cycling and e-biking to reduce (and contribute) to air pollutant emissions from mode shift away from motorized transport. Life cycle analysis of greenhouse gas emissions from production, use and end-of-life of active and motorized vehicles is used to compare the most common urban transport modes and determine whether cycling and e-biking reduce overall emissions or not. By doing so the Chapter provides a summary of research on cycling as a low carbon and clean mobility option in context of the climate emergency and the air quality crisis in cities.
... In recent years, commuting by bike has attained significant attention from the transportation, environmental, and health sectors. Cycling increases physical activity levels, leading to a multitude of health benefits [1,2], while also mitigating air pollution, carbon emissions, congestion, noise, and other detrimental impacts associated with car use [3][4][5][6]. Consequently, cycling and walking are recognized as sustainable transportation modes. ...
... (www.preprints.org) | NOT PEER-REVIEWED | Posted: 6 March 2024 doi:10.20944/preprints202403.0374.v16 ...
The benefits of cycling as a sustainable transportation mode are widely recognized. Cycling to work offers numerous advantages for individuals, employers, the environment, and society, ranging from improved physical health, wellbeing, and productivity to enhanced public health and reduced carbon emissions. Many governments around the world have implemented various policy measures, interventions, and initiatives to promote cycling. Some cities and towns have encouraged workplaces to provide bike-friendly amenities, such as secure bike parking/storage and shower and changing facility (referred to as end-of-trip facilities), to accommodate cyclists and motivate more employees to embrace sustainable transportation options. However, the presence or absence of such amenities has been found to both positively influence cycling behavior or deter some individuals from cycling to work. Despite the desirability of these amenities, the number of office buildings equipped with bike storage and shower/changing facility remains small, and their economic value is not well understood. In this paper, we aim to investigate whether the presence of cycling-supportive facilities could add value to office buildings. Specifically, we conduct a study using data from office buildings across England as of the end of 2021. We employ hedonic techniques to examine whether office buildings with bike storage and/or shower facility command a rent premium and whether the existence of a rent premium for bike storage and/or shower facility vary by location and across regions in England, independently from any premium associated with BREEM certification. We find that the buildings with bike storage and shower facility secure rent premiums respectively. The level of rent premiums varies with location and regions. The variations of premium are driven by the shortage of the supply of these facilities.
... Also, shared schemes can have carbon implications, e.g. around the short lifespan of vehicles and their re-distribution [27]. Environmental benefits of EMM go beyond reductions in carbon emissions to include lower occupation of public space [1,27]. ...
... around the short lifespan of vehicles and their re-distribution [27]. Environmental benefits of EMM go beyond reductions in carbon emissions to include lower occupation of public space [1,27]. Despite these complexities, overall, compared to car ownership and use (both electric and conventional), EMM has significant benefits [28]. ...
Physical inactivity is a leading risk factor for non-communicable diseases. Climate change is now regarded as the biggest threat to global public health. Electric micromobility (e-micromobility, including e-bikes e-cargo bikes and e-scooters) has the potential to simultaneously increase people’s overall physical activity while decreasing greenhouse gas emissions where it substitutes for motorised transport. The ELEVATE study aims to understand the impacts of e-micromobility, including identifying the people, places and circumstances where they will be most beneficial in terms of improving people’s health while also reducing mobility-related energy demand and carbon emissions. A complex mixed methods design collected detailed quantitative and qualitative data from multiple UK cities. First, a nationally representative (n=2000), city-wide (n = 1200) and targeted study area surveys have collected data on travel behaviour, levels of physical activity, vehicle ownership and use as well as attitudes towards e-micromobility. Then, to provide insights on an understudied type of e-micromobility, 49 households have been recruited to take part in e-cargo bike one-month trials. Self-reported data from participants are validated with objective data using methods such as GPS trackers and smartwatches recording of routes and activities. CO2 impacts of e-micromobility use are also calculated. Participant interviews provided detailed information on preferences, expectations, experiences, barriers and enablers of e-micromobility.
... In designing the living environment for human beings, more and more attention is paid to the quality of human life [11][12][13][14] . Personal vehicles can contribute to an increase in interest in pro-ecological and health-promoting means of transport [15][16][17] . A human being generally needs some physical effort to maintain health. ...
The aim of the study was to optimize the seat for a personal vehicle equipped with a crankset mechanism, meant for everyday use. The inclination of the seat backrest was selected on the basis of theoretical considerations. Then dynamic tests were carried out on a group of young, healthy men in order to verify the ergonomic aspects of the seat position in relation to the crankset and determine the efficiency of the human-mechanism system with a load of 50 W. The data obtained from the dynamic tests were subject to statistical analysis. Research has shown that higher seat positions result in statistically higher efficiencies. In addition, a holistic analysis of the personal vehicle design problem shows that the upper position of the seat is also the best. The results of the research can be used to optimize personal vehicles using human force as a drive.
This review highlights the significant impact of air quality, specifically particulate matter (PM), on cognitive decline and age-related diseases in the elderly. Despite established links to other pathologies, such as respiratory and cardiovascular illnesses, there is a pressing need for increased attention to the association between air pollution and cognitive aging, given the rising prevalence of neurocognitive disorders. PM sources are from diverse origins, including industrial activities and combustion engines, categorized into PM10, PM2.5, and ultrafine PM (UFPM), and emphasized health risks from both outdoor and indoor exposure. Long-term PM exposure, notably PM2.5, has correlated with declines in cognitive function, with a specific vulnerability observed in women. Recently, extracellular vesicles (EVs) have been explored due to the interplay between them, PM exposure, and human aging, highlighting the crucial role of EVs, especially exosomes, in mediating the complex relationship between PM exposure and chronic diseases, particularly neurological disorders. To sum up, we have compiled the pieces of evidence that show the potential contribution of PM exposure to cognitive aging and the role of EVs in mediating PM-induced cognitive impairment, which presents a promising avenue for future research and development of therapeutic strategies. Finally, this review emphasizes the need for policy changes and increased public awareness to mitigate air pollution, especially among vulnerable populations such as the elderly.
Active travel is cheaper, healthier, better for the environment, and no slower on congested urban streets. So how much carbon can it save on a daily basis? And what is its role in reducing emissions from transport overall?
In new research, colleagues and I reveal that people who walk or cycle have lower carbon footprints from daily travel, including in cities where lots of people are already doing this. Despite the fact that some walking and cycling happens on top of motorised journeys instead of replacing them, more people switching to active travel would equate to lower carbon emissions from transport on a daily and trip-by-trip basis.
In low-cycling countries like Aotearoa New Zealand, women are much less likely to cycle. Previous research has identified improvements to cycling infrastructure and increasing gender equality as key ways to open up cycling to women. The electric bicycle (or e-bike) may be another tool that could be used to lift women’s cycling rates. In this paper we explored findings from the Electric City research project in Auckland, Aotearoa New Zealand that touched on aspects of gender and e-cycling experience. We used data from interviews with three groups, e-cyclists, e-bike retailers, and cycling planners and policy-makers, to gain insights into the gendered dimensions of the e-cycling assemblage (rider, bike, environment). The results showed that e-bikes act as a cycling enabler for women in ways that both reinforce as well as challenge aspects of traditional gender socialisation: E-bikes enable women to meet traditional care responsibilities, and achieve traditional feminine expectations of presentation on a bike. However, they also increase women’s cycling confidence and assertiveness, provide less fit women with more empowering physical activity experiences, improve the quality of bikes available to women, and can create more inclusive bike retail environments. We concluded that these benefits are less likely to be available to lower-income women, due to the high cost of e-bikes.
Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobility-related CO2 emissions are complex and under-researched. Here we collected travel activity data in seven European cities and derived life cycle CO2 emissions across modes and purposes. Daily mobility-related life cycle CO2 emissions were 3.2 kgCO2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO2 emissions than non-cyclists. Life cycle CO2 emissions decreased by −14% per additional cycling trip and decreased by −62% for each avoided car trip. An average person who ‘shifted travel modes’ from car to bike decreased life cycle CO2 emissions by 3.2 kgCO2/day. Promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life.
Active travel (walking or cycling for transport) is considered the most sustainable and low carbon form of getting from A to B. Yet the net effects of changes in active travel on changes in mobility-related CO2 emissions are complex and under-researched. Here we collected longitudinal data on daily travel behavior, journey purpose, as well as personal and geospatial characteristics in seven European cities and derived mobility-related lifecycle CO2 emissions over time and space. Statistical modelling of longitudinal panel (n = 1849) data was performed to assess how changes in active travel, the ‘main mode’ of daily travel, and cycling frequency influenced changes in mobility-related lifecycle CO2 emissions.
We found that changes in active travel have significant lifecycle carbon emissions benefits, even in European urban contexts with already high walking and cycling shares. An increase in cycling or walking consistently and independently decreased mobility-related lifecycle CO2 emissions, suggesting that active travel substituted for motorized travel – i.e. the increase was not just additional (induced) travel over and above motorized travel. To illustrate this, an average person cycling 1 trip/day more and driving 1 trip/day less for 200 days a year would decrease mobility-related lifecycle CO2 emissions by about 0.5 tonnes over a year, representing a substantial share of average per capita CO2 emissions from transport. The largest benefits from shifts from car to active travel were for business purposes, followed by social and recreational trips, and commuting to work or place of education. Changes to commuting emissions were more pronounced for those who were younger, lived closer to work and further to a public transport station.
Even if not all car trips could be substituted by active travel the potential for decreasing emissions is considerable and significant. The study gives policy and practice the empirical evidence needed to assess climate change mitigation impacts of urban transport measures and interventions aimed at mode shift to more sustainable modes of transport. Investing in and promoting active travel whilst ‘demoting’ private car ownership and use should be a cornerstone of strategies to meet ‘net zero’ carbon targets, particularly in urban areas, while also reducing inequalities and improving public health and quality of urban life in a post-COVID-19 world.
The socio-economic impacts on cities during the COVID-19 pandemic have been brutal, leading to increasing inequalities and record numbers of unemployment around the world. While cities endure lockdowns in order to ensure decent levels of health, the challenges linked to the unfolding of the pandemic have led to the need for a radical re-think of the city, leading to the re-emergence of a concept, initially proposed in 2016 by Carlos Moreno: the “15-Minute City”. The concept, offering a novel perspective of “chrono-urbanism”, adds to existing thematic of Smart Cities and the rhetoric of building more humane urban fabrics, outlined by Christopher Alexander, and that of building safer, more resilient, sustainable and inclusive cities, as depicted in the Sustainable Development Goal 11 of the United Nations. With the concept gaining ground in popular media and its subsequent adoption at policy level in a number of cities of varying scale and geographies, the present paper sets forth to introduce the concept, its origins, intent and future directions.
As sales of e-bikes increase, so does the need for reliable evaluations of which means of transport the e-bike replaces, what we call the substitution effect. A randomised controlled trial with GPS data from 98 frequent drivers in Sweden was conducted to investigate the effect of the e-bike on modal choice, the number of trips, distance, as well as perceptions of the e-bike as a substitute for the car. The results demonstrate that the treatment group increased cycling on average with 1 trip and 6.5 km per day and person, which led to a 25% increase in total cycling. The whole increase was at the expense of car use, which on average decreased by 1 trip and 14 km per person and day, a decrease in car mileage of 37%. Implications for policy and further research are discussed.
New, shared mobility modes, including dockless e-scooters and e-bikes, were recently introduced to many cities around the world. The aim of this article is to determine the differences between the users of e-bike sharing, and e-scooter sharing systems, and the characteristics of their travel behaviour. This study is based on the survey of the citizens of Tricity in northern Poland. We find that e-bicycles are predominantly used as first and last mile transport and to commute directly to various places of interest, whereas e-scooters are more often used for leisure rides. Survey respondents that adopted shared micromobility are generally young, and e-scooter users are on average younger than e-bike users. Although all shared vehicles in Tricity are electrically assisted, this did not allow for the elimination of the gender gap, or help retired and disabled people in the adoption of shared micromobility services. We have also identified factors discouraging people from the usage of e-bike and e-scooter sharing and found them to be different for both types of services. Finally, we investigated the issue of using shared e-bikes for urban logistics.
The World Health Organization’s Health Economic Assessment Tool (HEAT) for walking and cycling is a user-friendly web-based tool to assess the health impacts of active travel. HEAT, developed over 10 years ago, has been used by researchers, planners and policymakers alike in appraisals of walking and cycling policies at both national and more local scales. HEAT has undergone regular upgrades adopting the latest scientific evidence. This article presents the most recent upgrades of the tool. The health impacts of walking and/or cycling in a specified population are quantified in terms of premature deaths avoided (or caused). In addition to the calculation of benefits derived from physical activity, HEAT was recently expanded to include assessments of the burden associated with air pollution exposure and crash risks while walking or cycling. Further, the impacts on carbon emissions from mode shifts to active travel modes can now be assessed. The monetization of impacts using Value of Statistical Life and Social Costs of Carbon now uses country-specific values. As active travel inherently results in often substantial health benefits as well as not always negligible risks, assessments of active travel behavior or policies are incomplete without considering health implications. The recent developments of HEAT make it easier than ever to obtain ballpark estimates of health impacts and carbon emissions related to walking and cycling.
Previous research shows that e-bike owners use private cars less than other transport user groups, and also report to have changed from motorised to non-motorised transport. A challenge with many studies is that they are either retrospective or cross-sectional, thus giving little control over confounding factors.
We followed up a short term trial where quite large mode change had been observed among participants. In the present study we conducted a before after-study with a customer group who bought an e-bike (N = 39) and a comparison group wanting to buy one (N = 142) using a survey with a travel diary to capture changes in travel behaviour. We also used a broader comparison group (N = 767) to test the robustness of the results from a policy perspective. The measurement period lasted up to six months.
We found that people who purchased an e-bike increased their bicycle use from 2.1 to 9.2 km per day on average, representing a change in bike as share of all transport from 17 to 49 percent. The comparison group had negligible changes in cycling during the same time period, and the choice of comparison group had a very marginal effect on the results. The results show that the large change in cycling we previously found of a trial scheme with e-bikes is replicated with actual customers. The change in cycling share is somewhat larger than it was for the short-term users, showing that mode change from e-bikes is not just a novelty effect.
Reducing motorized transport and increasing active transport (i.e. transport by walking, cycling and other active modes) may reduce greenhouse gas (GHG) emissions and improve health. But, active modes of transport are not zero emitters. We aimed to quantify GHG emissions from food production required to fuel extra physical activity for walking and cycling. We estimate the emissions (in kgCO2e) per kilometre travelled for walking and cycling from energy intake required to compensate for increased energy expenditure, and data on food-related GHG emissions. We assume that persons who shift from passive modes of transport (e.g. driving) have increased energy expenditure that may be compensated with increased food consumption. The GHG emissions associated with food intake required to fuel a kilometre of walking range between 0.05 kgCO2e/km in the least economically developed countries to 0.26 kgCO2e/km in the most economically developed countries. Emissions for cycling are approximately half those of walking. Emissions from food required for walking and cycling are not negligible in economically developed countries which have high dietary-related emissions. There is high uncertainty about the actual emissions associated with walking and cycling, and high variability based on country economic development. Our study highlights the need to consider emissions from other sectors when estimating net-emissions impacts from transport interventions.
Recent data on conventional bike and/or electric bike (e-bike) sharing systems reveal that more than 2900 systems are operating in cities worldwide, indicating the increased adoption of this alternative mode of transportation. Addressing the existing gap in the literature regarding the deployment of e-bike sharing systems (e-BSSs) in particular, this paper reviews their spatio-temporal characteristics, and attempts to (a) map the worldwide distribution of e-BSSs, (b) identify temporal trends in terms of annual growth/expansion of e-BSS deployment worldwide and (c) explore the spatial characteristics of the recorded growth, in terms of adoption on a country scale, population coverage and type of system/initial fleet sizes. To that end, it examines the patterns identified from the global to the country level, based on data collected from an online source of BSS information worldwide. A comparative analysis is performed with a focus on Europe, North America and Asia, providing insights on the growth rate of the specific bikesharing market segment. Although the dockless e-BSS has been only within three years of competition with station-based implementations, it shows a rapid integration to the overall technology diffusion trend, while it is more established in Asia and North America in comparison with Europe and launches with larger fleet sizes.
Soft travel interventions are generally regarded as effective measures for reducing personal car use. However, doubts about the validity of such claims are raised, primarily fueled by the low methodological quality of evaluation studies upon which such conclusions are based and by the fact that the literature is, for the most part, narratively synthesized. The present systematic review addresses these critiques by investigating the effect of soft interventions on car use through a meta-analysis, which includes only experimental and well-controlled quasi-experimental studies. Results revealed that interventions (k = 41) lead to a significant reduction of 7% in car modal split share (Hedges' g = 0.163). Moderators of interventions' effectiveness were investigated in a meta-regression. Effectiveness was moderated by the type of intervention and by the main psychological variable targeted by the interventions, whereas the other studied moderators (i.e. residential relocation of participants, study design, percentage of females in the study, the presence of incentives, passed time to follow-up, interventions' measurement instrument, city size in which interventions were applied and the setting where they were conducted) were non-significant. Limitations of the present findings, together with implications for policy and practice are discussed.
Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders were closed and populations were confined to their homes, which reduced transport and changed consumption patterns. Here we compile government policies and activity data to estimate the decrease in CO2 emissions during forced confinements. Daily global CO2 emissions decreased by –17% (–11 to –25% for ±1σ) by early April 2020 compared with the mean 2019 levels, just under half from changes in surface transport. At their peak, emissions in individual countries decreased by –26% on average. The impact on 2020 annual emissions depends on the duration of the confinement, with a low estimate of –4% (–2 to –7%) if prepandemic conditions return by mid-June, and a high estimate of –7% (–3 to –13%) if some restrictions remain worldwide until the end of 2020. Government actions and economic incentives postcrisis will likely influence the global CO2 emissions path for decades. COVID-19 pandemic lockdowns have altered global energy demands. Using government confinement policies and activity data, daily CO2 emissions have decreased by ~17% to early April 2020 against 2019 levels; annual emissions could be down by 7% (4%) if normality returns by year end (mid-June).
Within climate–energy–transport scholarship and professions there is a growing consensus that electric vehicles (EVs), which include personal cars, sport utility vehicles (SUVs), vans, and pickup trucks, are essential for decarbonizing mobility. This article urges caution and pause before an EV lock-in and calls on geographers and other scholars, professionals, and sustainability advocates to consider the multiscale environmental and social problems associated with EVs. The article begins by reviewing the mainstream assumptions about mass EV uptake, with particular emphasis on projections forecasting more, not fewer, cars in the future. Using a mobility justice framework, I ask who is making these assumptions and why and discuss the influence of liberal economic theory on future projections of EVs. I next consider assumptions about the environmental efficacy and decarbonization potential of mass EV uptake and review how EV production and consumption might escalate rather than reduce global resource and energy demand. I also scale down to cities and describe how EVs will lay claim to many of the same spaces designated for green mobility, such as cycle tracks, bus lanes, and compact, walkable spaces. The conclusion proposes research questions to consider with regard to EVs, future transportation, future geographies, and future carbon emissions.
Introduction
Active travel (walking and cycling) is increasingly being recognised as a potentially effective means of increasing physical activity levels and thereby contribute to physical and mental health. To date, however, much of the empirical evidence related to the health benefits of active travel is based on cross-sectional data. As such, the direction of causation remains uncertain, i.e. does active travel lead to improved health or vice-versa, are healthier individuals more inclined to participate in active travel? This study aims to systematically assess the bidirectional relationships between active travel, on the one hand, and two relevant health outcomes on the other, namely body-mass index (BMI) and mental health.
Method
To this end, random-intercept cross-lagged panel models are estimated using data from 10 waves (years) of the Longitudinal Internet Studies for the Social sciences panel, a panel that is representative for the Dutch population. Active travel was assessed using a measure of walking frequency and mental health was measured using the 5-item mental health inventory (MHI-5).
Results
The results indicate that active travel does not affect later BMI levels, but, vice versa, BMI does negatively influence later levels of active travel, a pattern that is in line with earlier research related to general physical activity and BMI. Regarding mental health, the pattern is exactly opposite. In this case, the effect of active travel on mental health is significant, while the reverse effect is not (at the 5% level of statistical significance).
Conclusion
Overall, the results underline the notion that cross-sectional estimates of the effects between active travel and health outcomes should be interpreted with care, as they can be the result of effects in either direction. In addition, the results suggest that the uptake of active travel may be increased by decreasing BMI levels in the population, e.g. via dietary programs.
The phasing out of conventional fossil fuel road vehicles is one of a number of potentially disruptive transport and energy policies. The implied technical substitution alone may be too slow to contribute meaningfully to meeting ‘net zero’ carbon reduction targets. This paper uses established modelling techniques and prospective scenario analyses in a UK case study to investigate what the impacts might be if we were more ambitious, how much disruption is needed to meet climate goals, the role of lifestyle and social change, and the potential implications for key actors in transport energy systems. Existing policies may neither hit carbon reduction targets nor make the early gains needed for a Paris-compliant trajectory. Deeper and earlier reductions in carbon and air quality emissions can be achieved by more ambitious but largely non-disruptive change of a 2030 phase out that includes (plug-in) hybrids. The earlier phase outs combined with lower demand for mobility and car ownership would make significant contributions to an emissions pathway that is both Paris compliant and meets urban air quality goals. Some disruption for technology providers, business and government can be expected in the more ambitious cases. The paper concludes by discussing key policy implications and recommendations.
To ensure long-term availability of mobility and to keep the effects of humanity on global climate limited, politics, research, and industry currently search for ways to reduce greenhouse gas (GHG) emissions caused by it. A potential reduction could be achieved by transitioning towards more efficient transport modes, optimally powered by renewable energy. Based on mobility (commutes), population, and weather data from Switzerland, we present a model to compute energy savings due to a (hypothetical) widespread deployment of electric bicycles. In different scenarios, we analyze the dependence of the commuting energy demand on users’ preferences about when to take the bike, such as an aversion to biking on cold and rainy days. Our study shows that GHG emission reductions of up to approx. 10% of the total emissions from diesel and gasoline are possible. In combination with a widespread deployment of electric vehicles, further savings of up to 17.5% could be achieved. In particular, the willingness to drive longer commutes by e-bike influences the potential GHG emission reductions, followed by the willingness to use the bicycle at temperatures below 10°C. Using these results, we identify the spatial energy and greenhouse gas savings potential and thus regions that are particularly suited for e-bike use. The identification of regions with high saving potentials allows for targeted marketing, transition-supporting incentives, or infrastructural changes to maximize the reduction of emissions.
Physical activity has been widely associated with beneficial health effects. The use of electric-assist bicycles (e-bikes) can lead to increased or decreased physical activity, depending on the transport mode substituted.
This study aimed to compare physical activity levels of e-bikers and conventional bicycle users (cyclists) as well as across e-bike user groups based on the transport mode substituted by e-bike. Physical activity, transport and user related parameters were analysed. Data from the longitudinal on-line survey of the PASTA project were used. The survey recruited over 10,000 participants in seven European cities.
Physical activity levels, measured in Metabolic Equivalent Task minutes per week (MET min/wk), were similar among e-bikers and cyclists (4463 vs. 4085). E-bikers reported significantly longer trip distances for both e-bike (9.4 km) and bicycle trips (8.4 km) compared to cyclists for bicycle trips (4.8 km), as well as longer daily travel distances for e-bike than cyclists for bicycle (8.0 vs. 5.3 km per person, per day, respectively). Travel-related activities of e-bikers who switched from cycling decreased by around 200 MET min/wk., while those switching from private motorized vehicle and public transport gained around 550 and 800 MET min/wk. respectively.
Therefore, this data suggests that e-bike use leads to substantial increases in physical activity in e-bikers switching from private motorized vehicle and public transport, while net losses in physical activity in e-bikers switching from cycling were much less due to increases in overall travel distance.
Poor air quality is a pressing policy issue that spans public health and environmental portfolios, and governments worldwide are investing in a wide array of measures to address it. This paper is a rapid review of the evidence behind air quality strategies and technologies. It was conducted according to the principles of a systematic review, and includes both academic and “grey” literature sources. It focuses on road transport in urban areas, because air pollution tends to be worse in cities, and the main source is fossil fuel vehicles. It draws on the environmental science and policy literature to provide interdisciplinary insight into the most effective air quality policy measures. The most promising initiatives include active travel infrastructure, roadside barriers, low emission zones, and low speed limits. Technologies which remove pollution from the air largely remain unproven, especially at the scale needed to make a significant impact. The combinations of policies from three cities which rank highly for air quality are reviewed; one important finding is that policies are most effective when they are a part of a mutually reinforcing suite of measures. Policies consistent across the cities studied are good public transport coverage, a good cycle network, and financial incentives for electric vehicle purchase.
The real-world impacts of the Trump administration's effort to roll back the Corporate Average Fuel Economy (CAFE) standards for new light-duty vehicles are not obvious, because new vehicles are highly durable and remain in the on-road fleet for many years. We demonstrate that freezing CAFE between 2020-2026, one of the proposals circulated by the Trump administration, will increase fleet fuel consumption and greenhouse gas emissions until 2040 and beyond, because relatively less-efficient vehicles sold during this time would remain in use for potentially decades. We argue for stringent fuel-economy standards for new vehicles, and for placing greater emphasis on the retirement and disposal of the oldest and most inefficient vehicles on our roads. These steps will help to build a fleet that is efficient, low-emission, and adaptable as the automotive industry enters a period of unprecedented technological change.
Background
The Propensity to Cycle Tool (PCT) is a freely available, interactive tool help prioritise cycling initially launched in England in 2017 and based on adult commuting data. This paper applies the method to travel to school data, and assesses health and carbon benefits based on nationwide scenarios of cycling uptake.
Methods
The 2011 National School Census provides origin-destination data for all state-funded schools in England (N = 7,442,532 children aged 2–18 in 21,443 schools). Using this dataset, we modelled propensity to cycle as a function of route distance and hilliness between home and school. We generated scenarios, including ‘Go Dutch’ – in which English children were as likely to cycle as Dutch children, accounting for trip distance and hilliness. We estimated changes in the level of cycling, walking, and driving, and associated impacts on physical activity and carbon emissions.
Results
In 2011, 1.8% of children cycled to school (1.0% in primary school, 2.7% in secondary school). If Dutch levels of cycling were reached, under the Go Dutch scenario, this would rise to 41.0%, a 22-fold increase. This is larger than the 6-fold increase in Go Dutch for adult commuting. This would increase physical activity from school travel among pupils by 57%, and reduce transport-related carbon emissions by 81 kilotonnes/year. These impacts would be substantially larger in secondary schools than primary schools (a 96% vs. 9% increase in physical activity, respectively).
Conclusion
Cycling to school is uncommon in England compared with other Northern European countries. Trip distances and hilliness alone cannot explain the difference, suggesting substantial unmet potential. We show that policies resulting in substantial uptake of cycling to school would have important health and environmental benefits. At the level of road networks, the results can inform local investment in safe routes to school to help realise these potential benefits.
There is a growing recognition of the role that walking and cycling can make in reducing greenhouse gas (GHG) emissions by substituting motorized travel, particularly on short trips. However, there is a lack of evidence at the micro level on the realistic, empirically derived potential of walking and cycling to displace motorized travel and thus reduce GHG emissions. The aim of this study was to investigate the potential for GHG emissions savings from replacing short car trips with walking and cycling and the extent to which high quality infrastructure for walking and cycling may influence day-to-day travel decisions, change the spatial and temporal nature of local journeys and impact on overall GHG emissions from motorised travel.
To achieve this aim this study conducted an in-depth observational study of a purposively selected cohort of 50 residents in Cardiff, Wales. Using a mixed-method approach detailed quantitative and qualitative data were collected for each participant using personal Global Position System (GPS) devices, 7-day travel diaries and contextual interviews over two seasonally matching 7-day time periods in 2011 and 2012. GHG emissions for motorized travel modes were derived using journey distance, vehicle technology details and average speeds obtained from the GPS data. The spatial and contextual data provided new insights into the complexities of walking behaviour and factors influencing cycling for everyday travel or recreation, including route choice decisions, activity destinations and the role of the new infrastructure to enable change.
We found significant potential of active travel to substitute short car trips, with sizeable impacts on carbon emissions from personal travel. Half of all car trips were less than 3 miles long. Taking into account individual travel patterns and constraints, walking or cycling could realistically substitute for 41% of short car trips, saving nearly 5% of CO2e emissions from car travel. This was on top of 5% of ‘avoided’ emissions from cars due to existing walking and cycling. The evolving high quality walking and cycling infrastructure in the case study area was unlikely to promote a significant reduction in carbon emissions from (displaced) car journeys on its own.
The study contributes to the debate on how to achieve stringent low carbon targets in urban transport. The combination of methods for data collection developed and employed in this study also helps to inform future research on the wider environmental impacts of active travel, including ‘co-benefits’ of improved air quality, reduced noise and reduced fossil fuel use.
Background
A modal shift to cycling has the potential to reduce greenhouse gas emissions and provide health co-benefits. Methods, models, and tools are needed to estimate the potential for cycling uptake and communicate to policy makers the range of impacts this would have.
Methods and findings
The Impacts of Cycling Tool (ICT) is an open source model with a web interface for visualising travel patterns and comparing the impacts of different scenarios of cycling uptake. It is currently applied to England. The ICT allows users to visualise individual and trip-level data from the English National Travel Survey (NTS), 2004–2014 sample, 132,000 adults. It models scenarios in which there is an increase in the proportion of the population who cycle regularly, using a distance-based propensity approach to model which trips would be cycled. From this, the model estimates likely impact on travel patterns, health, and greenhouse gas emissions. Estimates of nonoccupational physical activity are generated by fusing the NTS with the English Active People Survey (APS, 2013–2014, 559,515 adults) to create a synthetic population. Under ‘equity’ scenarios, we investigate what would happen if cycling levels increased equally among all age and gender categories, as opposed to in proportion to the profile of current cyclists. Under electric assist bike (pedelecs or ‘e-bike’) scenarios, the probability of cycling longer trips increases, based on the e-bike data from the Netherlands, 2013–2014 Dutch Travel Survey (50,868 adults).Outcomes are presented across domains including transport (trip duration and trips by mode), health (physical activity levels, years of life lost), and car transport–related CO2 emissions. Results can be visualised for the whole population and various subpopulations (region, age, gender, and ethnicity). The tool is available at www.pct.bike/ict. If the proportion of the English population who cycle regularly increased from 4.8% to 25%, then there would be notable reductions in car miles and passenger related CO2 emissions (2.2%) and health benefits (2.1% reduction in years of life lost due to premature mortality). If the new cyclists had access to e-bikes, then mortality reductions would be similar, while the reduction in car miles and CO2 emissions would be larger (2.7%). If take-up of cycling occurred equally by gender and age (under 80 years), then health benefits would be marginally greater (2.2%) but reduction in CO2 slightly smaller (1.8%). The study is limited by the quality and comparability of the input data (including reliance on self-report behaviours). As with all modelling studies, many assumptions are required and potentially important pathways excluded (e.g. injury, air pollution, and noise pollution).
Conclusion
This study demonstrates a generalisable approach for using travel survey data to model scenarios of cycling uptake that can be applied to a wide range of settings. The use of individual-level data allows investigation of a wide range of outcomes, and variation across subgroups. Future work should investigate the sensitivity of results to assumptions and omissions, and if this varies across setting.
In advance of this year’s Clean Air Day on 21 June we have produced new research - “The health costs of air pollution from cars and vans”.
We found that the health damage associated with diesel vehicle emissions are around 20 times greater than electric vehicles and at least 5 times greater than those associated with petrol vehicles.
The total health cost to the UK from cars and vans is £6 billion each year, with almost 90% of this coming from diesel vehicles.
Using the data from the academic report, we have imagined three alternative transport scenarios and the impact that they could have:
- If every new car in 2019 were electric it would save more than £325 million in health costs in the first year
- Swapping 1 in 4 car journeys in urban areas for walking or cycling could save over £1.1 billion in health damage costs per year
- Switching 1 million cars from diesel to electric would save more than £360 million per year in health costs from local air pollution
The report was disseminated widely, appearing in over 300 papers (print and online), and on national radio and TV.
It provided supporting evidence to the Mayor of London's announcement in June 2018 to widen and bring forward London's Ultra Low Emissions Zone. https://www.london.gov.uk/press-releases/mayoral/ultra-low-emission-zone-to-expand
Background:
Climate change poses a dangerous and immediate threat to the health of populations in the UK and worldwide. We aimed to model different scenarios to assess the health co-benefits that result from mitigation actions.
Methods:
In this modelling study, we combined a detailed techno-economic energy systems model (UK TIMES), air pollutant emission inventories, a sophisticated air pollution model (Community Multi-scale Air Quality), and previously published associations between concentrations and health outcomes. We used four scenarios and focused on the air pollution implications from fine particulate matter (PM2·5), nitrogen dioxide (NO2) and ozone. The four scenarios were baseline, which assumed no further climate actions beyond those already achieved and did not meet the UK's Climate Change Act (at least an 80% reduction in carbon dioxide equivalent emissions by 2050 compared with 1990) target; nuclear power, which met the Climate Change Act target with a limited increase in nuclear power; low-greenhouse gas, which met the Climate Change Act target without any policy constraint on nuclear build; and a constant scenario that held 2011 air pollutant concentrations constant until 2050. We predicted the health and economic impacts from air pollution for the scenarios until 2050, and the inequalities in exposure across different socioeconomic groups.
Findings:
NO2 concentrations declined leading to 4 892 000 life-years saved for the nuclear power scenario and 7 178 000 life-years saved for the low-greenhouse gas scenario from 2011 to 2154. However, the associations that we used might overestimate the effects of NO2 itself. PM2·5 concentrations in Great Britain are predicted to decrease between 42% and 44% by 2050 compared with 2011 in the scenarios that met the Climate Change Act targets, especially those from road traffic and off-road machinery. These reductions in PM2·5 are tempered by a 2035 peak (and subsequent decline) in biomass (wood burning), and by a large, projected increase in future demand for transport leading to potential increases in non-exhaust particulate matter emissions. The potential use of biomass in poorly controlled technologies to meet the Climate Change Act commitments would represent an important missed opportunity (resulting in 472 000 more life-years lost from PM2·5 in the low-greenhouse gas scenario and 1 122 000 more life-years lost in the nuclear power scenario from PM2·5 than the baseline scenario). Although substantial overall improvements in absolute amounts of exposure are seen compared with 2011, these outcomes mask the fact that health inequalities seen (in which socioeconomically disadvantaged populations are among the most exposed) are projected to be maintained up to 2050.
Interpretation:
The modelling infrastructure created will help future researchers explore a wider range of climate policy scenarios, including local, European, and global scenarios. The need to strengthen the links between climate change policy objectives and public health imperatives, and the benefits to societal wellbeing that might result is urgent.
Funding:
National Institute for Health Research.
Purpose of review:
This paper reviews the use of conceptual frameworks in research on active travel, such as walking and cycling. Generic framework features and a wide range of contents are identified and synthesized into a comprehensive framework of active travel behavior, as part of the Physical Activity through Sustainable Transport Approaches project (PASTA). PASTA is a European multinational, interdisciplinary research project on active travel and health.
Recent findings:
Along with an exponential growth in active travel research, a growing number of conceptual frameworks has been published since the early 2000s. Earlier frameworks are simpler and emphasize the distinction of environmental vs. individual factors, while more recently several studies have integrated travel behavior theories more thoroughly. Based on the reviewed frameworks and various behavioral theories, we propose the comprehensive PASTA conceptual framework of active travel behavior. We discuss how it can guide future research, such as data collection, data analysis, and modeling of active travel behavior, and present some examples from the PASTA project.
This paper reports on a review of the European literature about the impacts of having an electrically-assisted bike available to use, together with results from a trial in the UK city of Brighton, where 80 employees were loaned an electrically-assisted bike for a 6–8 week period. In the Brighton trial, three-quarters of those who were loaned an e-bike used them at least once a week. Across the sample as a whole, average usage was in the order of 15–20 miles per week, and was accompanied by an overall reduction in car mileage of 20%. At the end of the trial, 38% participants expected to cycle more in the future, and at least 70% said that they would like to have an e-bike available for use in the future, and would cycle more if this was the case. This is consistent with the results of the European literature which shows that when e-bikes are made available, they get used; that a proportion of e-bike trips typically substitutes for car use; and that many people who take part in trials become interested in future e-bike use, or cycling more generally.
Objective
To quantify changes in mortality, greenhouse gas (GHG) emissions and consumer costs for physical activity and diet scenarios.
Design
For the physical activity scenarios, all car trips from <1 to <8 miles long were progressively replaced with cycling. For the diet scenarios, the study population was assumed to increase fruit and vegetable (F&V) consumption by 1–5 portions of F&V per day, or to eat at least 5 portions per day. Health effects were modelled with the comparative risk assessment method. Consumer costs were based on fuel cost savings and average costs of F&V, and GHG emissions to fuel usage and F&V production.
Setting
Working age population for England.
Participants
Data from the Health Survey for England, National Travel Survey and National Diet and Nutrition Survey.
Primary outcomes measured
Changes in premature deaths, consumer costs and GHG emissions stratified by age, gender and socioeconomic status (SES).
Results
Premature deaths were reduced by between 75 and 7648 cases per year for the physical activity scenarios, and 3255 and 6187 cases per year for the diet scenarios. Mortality reductions were greater among people of medium and high SES in the physical activity scenarios, whereas people with lower SES benefited more in the diet scenarios. Similarly, transport fuel costs fell more for people of high SES, whereas diet costs increased most for the lowest SES group. Net GHG emissions decreased by between 0.2 and 10.6 million tons of carbon dioxide equivalent (MtCO2e) per year for the physical activity scenarios and increased by between 1.3 and 6.3 MtCO2e/year for the diet scenarios.
Conclusions
Increasing F&V consumption offers the potential for large health benefits and reduces health inequalities. Replacing short car trips with cycling offers the potential for net benefits for health, GHG emissions and consumer costs.
In Norway, as in many countries, there is a political goal to increase bicycle use. The electric bicycle (e-bike) is a promising tool for achieving this goal, given the hilliness of the country. However, little is yet known about the deterrents of cycling in Norway in general, and in particular how the purchase of an e-bike could be stimulated.
In the current study, 5500 respondents from a convenience sample among car owners were asked about their perceptions of bicycling in general, and of e-bikes in particular as well as their willingness to pay for an e-bike. Randomly selected participants (N = 66) were given access to an e-bike for a limited time (2 or 4 weeks). A second questionnaire captured the same perceptions and willingness to pay post-intervention. Results were compared with a control group (N = 214).
The results showed that those who cycle the least were most interested in buying an e-bike and that prior knowledge of the e-bike corresponded with a higher desire to buy one. Pro-environmental values did not predict interest in e-bikes, neither did norms and attitudes towards cycling. The willingness to pay for an e-bike increased after having experienced the benefits for those who used an e-bike compared to those who did not. Price reduction of the e-bike (e.g. VAT exemption), spread of knowledge among the wider population, and actions to offer an e-bike experience may therefore be effective strategies for further expansion of the e-bike in the transport system and thereby to increase bicycle use in Norway.
Objective: To quantify changes in mortality, greenhouse gas (GHG) emissions, and consumer costs for physical activity and diet scenarios. Design: For the physical activity scenarios all car trips from less than 1 to less than 8 miles long were progressively replaced with cycling. For the diet scenarios the study population was assumed to increase fruit and vegetable (F&V) consumption by 1 to 5 portions of F&V per day, or to eat at least 5 portions per day. Health effects were modelled with comparative risk assessment method. Consumer costs were based on fuel cost savings and average costs of F&V, and GHG emissions to fuel usage and F&V production. Setting: Adult population for England. Participants: Data from Health Survey for England, National Travel Survey and National Diet and Nutrition Survey. Primary outcomes measured: Changes in premature deaths, consumer costs, and GHG emissions stratified by age, gender and socio-economic status (SES). Results: Premature deaths were reduced by between 75 and 7648 cases per year for the physical activity scenarios, and 3255 and 6187 cases per year for the diet scenarios. Morality reductions were greater amongst people of medium and high SES in the physical activity scenarios, whereas people with lower SES benefited more in the diet scenarios. Similarly, transport fuel costs fell more for people of high SES, whereas diet costs increased most for the lowest SES group. Net GHG emissions decreased by between 0.2 and 10.6 Million tons of carbon dioxide equivalent (MtCO2e) per year for the physical activity scenarios and increased 1.3 and 6.3 MtCO2e/year for the diet scenarios. Conclusions: Increasing F&V consumption offers the potential for large health benefits and reduce health inequalities. Replacing short car trips with cycling offers the potential for net benefits for health, GHG emissions and consumer costs.
We estimate the maximum capability to reduce CO2 by substituting private car travel for e-bike. We use spatial microsimulation (population-synthesis) to stimulate the adult population within every small area in England, taking account of area type and geodemographic circumstances of the population. By estimating for individuals the distance they are capable of travelling by e-bike and the extent to which they are capable of replacing private car travel, we find the upper limit on the capability to reduce CO2 by substituting car travel for e-bike use is 24.4 MTCO2 p.a. (per annum) in England. CO2 saving capability per person and per small area are highest (over 750 kg CO2 per person p.a.) for residents of rural areas and the rural urban fringe. e-bikes offer major conurbations more modest CO2 saving capability per person. We identify areas which are vulnerable to car related economic stress and also have high capability to replace car km with e-bikes, which if supported appropriately could contribute to equitable carbon reduction. Though capable of a very significant contribution to transport carbon reduction, other changes in technology and reduction in demand would also be necessary to reach zero emissions.
Our results are directly relevant to policy actors internationally who require evidence on place-based decarbonisation capability, particularly where car dependence is high. The results highlight how context is important in any attempt to design policy for equitable carbon reduction both to influence discussion on what is possible, as well as practical identification of areas for targeted intervention. Digital indicators covering all zones in a country's geography such as this are also useful because of the rapid digitalisation of policy making. We provide code so that others can produce similar analyses in other countries (https://github.com/DrIanPhilips/e-bikeCarbonReductionCapability).
The environmental performance of shared micromobility services compared to private alternatives has never been assessed using an integrated modal Life Cycle Assessment (LCA) relying on field data. Such an LCA is conducted on three shared micromobility services in Paris – bikes, second-generation e-scooters, and e-mopeds - and their private alternatives. Global warming potential, primary energy consumption, and the three endpoint damages are calculated. Sensitivity analyses on vehicle lifespan, shipping, servicing distance, and electricity mix are conducted. Electric micromobility ranks between active modes and personal ICE modes. Its impacts are globally driven by the vehicle manufacturing. Ownership does not affect directly the environmental performance: the vehicle lifetime mileage does. Assessing the sole carbon footprint leads to biased environmental decision-making, as it is not correlated to the three damages: multicriteria LCA is mandatory to preserve the planet. Finally, a major change of paradigm is needed to eco-design modern transportation policies.
Electric bicycles (e-bikes) have been found to offer a promising solution to reduce the greenhouse gas (GHG) impact of a region’s passenger transportation system. Using data from a North American survey of e-bike owners, a mode replacement model was adapted and augmented to consider the case of Portland, OR for various levels of e-bike person miles traveled (PMT) mode share penetration. It was estimated that for a 15% e-bike PMT mode share, car trip mode share could be reduced from 84.7% to 74.8%. Total car PMT per day could be reduced from 28.9 million to 25.5 million. Furthermore, carbon dioxide (CO2) emissions from passenger transportation could be reduced by 12% after accounting for e-bike emissions from electricity generation and induced e-bike trips. An individual e-bike could provide an average reduction of 225 kg CO2 per year. These estimates show that e-bikes have the potential to help cities and regions achieve their climate goals. Additionally, this research can be used to support policies and programs necessary to facilitate the growth of this emerging mode to realize carbon reduction impacts.
This chapter examines possible low-speed urban futures. It reiterates the importance of ‘slow cities’ in creating a healthy and sustainable future, and asks whether our obsession with increasing speeds might at least partly explain the inadequate responses to the global challenges facing humanity. Conquering our societal addiction to fast travel in the city represents an enormous challenge, and to help meet this we examine the positive vision of child-friendly cities. A focus on children and their well-being can help build consensus, lifting debates beyond narrow self-interest and encouraging more collective and long-term responses. We show how child-friendly cities must be slower cities, and slower cities are child-friendly cities, and both are healthier for us all. There follows discussion of three opportunities for change in the future: the re-imagining of goals, attitudes and outcomes. Ten key ideas from this book are then presented as the basis for a ‘Manifesto for 21st Century Slow Cities’. The chapter concludes with a message from the future written by a 30-year-old in the year 2050, thanking her parents’ generation for their efforts in creating slower, healthier, sustainable and child-friendly cities.
The key to understanding the impacts of electric bicycles (e-bikes) on congestion, the environment, and public health is to what extent they displace travel by other (particularly motorized) modes of transportation. This study investigates the mode substitution effects of e-bikes, based on a meta-analysis of 38 observations of mode substitution patterns reported in 24 published studies from around the world. Median mode substitution reported in the literature is highest for public transit (33%), followed by conventional bicycle (27%), automobile (24%), and walking (10%), but varies widely with interquartile ranges of 31% for auto and 44% for public transit. Weighted mixed logit model results indicate a trade-off in substitution of motorized modes, with significantly greater displacement of public transit in China and greater displacement of auto travel elsewhere (Europe, North America, and Australia). Newer studies report greater displacement of driving and walking and less displacement of conventional bicycle trips, which indicates a positive trend. Results also suggest that e-bike adoption may be part of a transition away from conventional bicycle use, while displacing auto and transit travel after adoption. Further studies are needed in the context of evolving forms of micromobility, particularly outside of northern Europe and China.
This paper investigates the modal shift patterns of e-bike users in the Dutch context. We focus on the change in e-bikers’ travel behavior to assess whether this change benefits sustainability. Our study provides direct ecologically valid evidence on modal shift by using a longitudinal dataset from the Netherlands Mobility Panel survey. We examine e-bikers’ modal shift patterns before and after acquiring an e-bike. The findings indicate that after e-bike adoptions, conventional bike use reduces significantly, while car use reduces less strongly. Nonetheless, the share of car kilometers is much larger than that of conventional bikes at the baseline. Besides, the emission rate per passenger kilometer of an e-bike is several times lower than that of a car. These imply a net environmental gain after e-bike adoptions. The present study also sheds light on modal shifts at a disaggregated level by investigating those e-bikers who are more likely to drive less after e-bike adoption. The findings suggest that e-bikers younger than 50 and those around retirement age (60–69) seem more likely to step out of their cars. Additionally, people living in rural areas tend to be more likely to reduce their car use than their counterparts in highly urbanized areas. Based on our findings, we present policy recommendations for achieving a greener shift in mobility systems.
Mobility is a service that demands energy. Energy, in turn, is fraught with complexity in terms of its forms, availability, infrastructure, ownership, extraction, conversion and combustion, and the sociopolitical implications of all of these factors. It is also complex in that the fundamental laws of thermodynamics render it simultaneously extremely productive and profligately wasteful. This has led to a science and policy of energy conservation which is a testing mix of calls to use energy resources more sparingly while applying an engineering focus on maximising work and minimising waste.
Bike sharing system (BSS) is growing worldwide. Although bike sharing is viewed as a sustainable transportation mode, it still has environmental footprints from its operation (e.g., bike rebalancing using automobiles) and upstream impacts (e.g., bike manufacturing). Thus, evaluating the environmental impacts of BSS from the life cycle perspective is vital to inform decision making for the system design and operation. In this study, we conducted a comparative life cycle assessment (LCA) of station-based and dock-less BSS in the U.S. The results show that dock-less BSS has a greenhouse gas (GHG) emissions factor of 118 g CO2-eq/bike-km in the base scenario, which is 82% higher than the station-based system. Bike rebalancing is the main source of GHG emissions, accounting for 36% and 73% of the station-based and dock-less systems, respectively. However, station-based BSS has 54% higher total normalized environmental impacts (TNEI), compared to dock-less BSS. The dock manufacturing dominants the TNEI (61%) of station-based BSS and the bike manufacturing contributes 52% of TNEI in dock-less BSS. BSS can also bring environmental benefits through substituting different transportation modes. Car trip replacement rate is the most important factor. The results suggest four key approaches to improve BSS environmental performance: 1) optimizing the bike distribution and rebalancing route or repositioning bikes using more sustainable approaches, 2) incentivizing more private car users to switch to using BSSs, 3) prolonging lifespans of docking infrastructure to significantly reduce the TNEI of station-based systems, and 4) increasing the bike utilization efficiency to improve the environmental performance of dock-less systems.
Electric bicycles (e-bikes) are a new addition to bicycle-sharing and may improve its competitiveness. E-bikes allow for higher speeds at a higher level of comfort than conventional bicycles and, compared with traditional bicycle-sharing, e-bike-sharing is better positioned to complement or compete with existing public transportation, or to even challenge established taxi services. In this paper, eight months of transaction data from a free-floating e-bike-sharing system in Zürich, Switzerland, were used to study the market position of e-bike sharing and drivers of demand. The results of the analysis indicate that a large proportion of the trips are commuting, and that the distance range of e-bike-sharing trips overlaps with the distance ranges of traditional public transportation and taxi services. Intensity of use is sensitive to precipitation. Spatial regression modeling indicates that economic and social activity, public transportation service quality, and the availability of bicycle infrastructure are key drivers of demand for free-floating e-bike-sharing. Given the substantial differences in the service compared with traditional bicycle-sharing, a new fifth generation of bicycle-sharing schemes is proposed.
Policies promoting active transport, such as walking and cycling, can reduce transport-related carbon emissions. However, there are few studies that examine the carbon emission outcomes of such policies. This paper presents a case study of an intervention carried out in New Zealand that involved the construction of urban cycling and walking infrastructure in parallel with programmes to encourage such active travel.
Using vehicle licensing data in the context of a quasi-experimental study design, we evaluated transport carbon dioxide emissions saved. Vehicle distance travelled within the study area was derived from odometer readings that are recorded on the New Zealand licensed vehicle administration system. Using a representative sample of households in the intervention and control areas, we also estimated changes in the number of vehicles licensed per household.
Consistent with increases found previously in walking and cycling trips, there was a decline of 1.6% in average distance travelled per passenger vehicle by the third year of the intervention. Averaged across the intervention period, there was a 1% reduction in distance travelled per vehicle and associated carbon dioxide emissions. It is possible that this estimate is conservative as there was indicative evidence from travel survey data that the number of vehicles per household also fell.
This is the first study we know of to have shown, using independent and objectively measured data, that the establishment of cycling and walking infrastructure is associated with reduced transport carbon dioxide emissions within a short space of time, even though the reductions found were modest.
The predominance of automobile dependency in North America is associated with a host of negative health and environmental impacts and has sparked the promotion of low-carbon and active modes of transportation. Encompassing both priorities, electric-bicycles have become a popular mode of transportation in some parts of the world. While multiple studies have suggested older adult populations may be most likely to benefit from e-bike technology, few studies have exclusively focused on this demographic to identify the factors that may promote or inhibit e-bike adoption amongst this group. This study explores the potential for e-bikes to support independent mobility and active aging among the older adult population in Canada's auto-dependent context. Guided by a conceptual framework for older adult mobility, this study used qualitative methods to gather perceptual and experiential data from 17 community stakeholders and 37 older adults in the Region of Waterloo, Ontario. The findings highlight the importance of cycling life histories, social connection and physical limitations to adopting cycling later in life. Specific individual and structural factors were discussed in relation to e-bike adoption including facilitators such as increased convenience, reduced physical exertion, reduced reliance on a vehicle and fun. Barriers included cycling infrastructure and road safety, regulation, and stigmatization barriers. E-bikes as a more convenient and supportive mode of transit for older adults is discussed alongside the importance of e-bikes as a replacement for traditional bicycles in a subset of this population.
Transport contributed 26% of New Zealand's direct greenhouse gas (GHG) emissions in 2014 (MFE, 2017). In the same year private car journeys made up 79% of trips nationally and 71% of trips in the capital city Wellington (MOT, 2016b). Electric bicycles (E-bikes) present an opportunity to reduce those emissions. A life cycle assessment approach was used to estimate the environmental impacts of a greater uptake of E-bikes that would displace the use of family size cars powered by petrol or diesel engines. The potential life cycle impacts for the E-bike were found to be favourable compared to the car for most impact categories, including GHG emissions. This was largely due to the approximately 80% share of renewable electricity generation in New Zealand. This electricity mix also meant that the E-bike's environmental impacts during use were small compared with those related to its production and disposal. The environmental impacts were evaluated for recharging the battery at for four different times of day, representing different average electricity generation mixes. This was found to have very little influence on the environmental performance of the E-bike. The environmental impacts of people switching from other transport modes to E-bikes were calculated for four different user groups in Wellington, New Zealand. These four groups had different transport preferences that were defined with respect to their barriers to cycling: Safe Cyclists, Likely Cyclists, Recreational Cyclists, and Hesitant Cyclists. The groups provided the basis for developing scenarios representing city-wide mode switches from car, bus, train and walking—to use of E-bikes. The Safe Cyclists scenario performed best for 9 of the 15 impact categories. This suggests the desirability of focusing on specific user-groups and their needs in order to change transport behaviours. In particular, in this case it implies a need to prioritise cyclist safety in transport planning (such as providing separate infrastructure for E-bikes).
Background:
In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health.
Methods:
Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively.
Results:
Cross-sectionally, BMI was 0.027 kg/m2 (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m2 (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m2, 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m2, 95%CI 0.033 to 0.802).
Conclusions:
Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility.
Our study focuses on the carbon emission and mitigation potential in the domain of daily travel in Beijing. Using a sample with the focus on working class, the average individual carbon emissions from daily travel are computed as 1.46 kg/day•person and 2.40 kg/day•person for weekday and weekend. Except for residents who need to conduct more long-distance trips, the main contributor to the emissions of the rest high emitters are not the need of longer daily travel distances or the need to conduct more long distance trips, but the need to use cars more intensively for trips with similar distances compared with low emitters. High emitters are associated with the characteristics of being male, having higher income, owning cars, and being in the age between 30s and 40s. On the other hand, living within fifth ring and having good accessibility to public transport are associated with lower emissions. We innovatively use trip-based information to obtain a more relevant and realistic assessment of mitigation potential through mode shift under the current transport system. The mitigation percentage can be as high as 20%–25% if only travel time is considered, but will be substantially constrained by practical barriers. Therefore mitigation policy for daily transport should not only focus on improving travel time of low emission modes to comparable levels with cars but also tackle practical barriers for car drivers to use low emission modes.
After Asian countries, the e-bike is now also on the rise in many Western countries. Related to this development, an important question posed by scholars is to what extent the adoption of the e-bike will lead to environmental and health benefits. These will be present if the e-bike replaces travel by motorized modes. Surveying the literature addressing this issue, empirical studies conducted to date do indeed reach the conclusion that the e-bike is substituting travel by car. However, a general shortcoming of empirical studies is that substitution is assessed by asking direct questions to e-bike owners. The aim of the present study is to address this limitation and statistically assess the effect of e-bike ownership on various indicators of travel behavior. To this end, a conceptual model is developed, which is specified as a structural equation model and estimated using data from the last three national mobility surveys in the Netherlands (2013, 2014 and 2015). The results show that e-bike ownership strongly reduces the use of the conventional bicycle, but also, to a lesser extent, car and public transport use. Secondly, e-bike owners reduce their car and public transport use more than conventional bicycle owners. And thirdly, on the level of vehicle ownership, the e-bike acts as a substitute for the conventional bicycle and does not act as a substitute for the car. Overall, the results shed some light on the health and environmental benefits of the uptake of e-bikes in the Netherlands.
There is a strong political desire to reduce the use of fossil fuels in road transport. In this paper, the use of e-bikes (of the pedelec type) in Sweden is analysed by focusing on changes in travel behaviour and their corresponding effects on CO2 emissions. The aim is to analyse the effect on CO2 emissions due to the use of e-bikes. The analysis is carried out on the possible differences in changed travel behaviour between areas dominated by either urban or rural environments. It is based on a combination of responses to a questionnaire distributed to e-bike users and a survey of local transport planners in Swedish municipalities. The results indicate that there are large gains to be made from e-bike usage in terms of decreased CO2 emissions through a reduction in car mileage. Furthermore, the results indicate that the potential for e-bikes to replace car trips is as great in rural areas as it is in urban areas. At the same time, the results indicate that the Swedish municipalities carrying out e-bike campaigns target trips in both urban and rural areas, therefore representing an effective promotion strategy to achieve the full CO2 emissions reducing potential of e-bike use. This study also shows that, depending on the type of errand being carried out, more respondents living in urban areas than in rural areas replace their conventional bicycle trips with e-bike trips. Thus, the use of e-bikes produces some less than desirable effects, such as reduced physical activity.
Background:
Many cities across the world are beginning to shift their mobility solution away from the private cars and towards more environmentally friendly and citizen-focused means. Hamburg, Oslo, Helsinki, and Madrid have recently announced their plans to become (partly) private car free cities. Other cities like Paris, Milan, Chengdu, Masdar, Dublin, Brussels, Copenhagen, Bogota, and Hyderabad have measures that aim at reducing motorized traffic including implementing car free days, investing in cycling infrastructure and pedestrianization, restricting parking spaces and considerable increases in public transport provision. Such plans and measures are particularly implemented with the declared aim of reducing greenhouse gas emissions. These reductions are also likely to benefit public health.
Aims:
We aimed to describe the plans for private car free cities and its likely effects on public health.
Methods:
We reviewed the grey and scientific literature on plans for private car free cities, restricted car use, related exposures and health.
Results:
An increasing number of cities are planning to become (partly) private car free. They mainly focus on the reduction of private car use in city centers. The likely effects of such policies are significant reductions in traffic-related air pollution, noise, and temperature in city centers. For example, up to a 40% reduction in NO2 levels has been reported on car free days. These reductions are likely to lead to a reduction in premature mortality and morbidity. Furthermore the reduction in the number of cars, and therefore a reduction in the need for parking places and road space, provides opportunities to increase green space and green networks in cities, which in turn can lead to many beneficial health effects. All these measures are likely to lead to higher levels of active mobility and physical activity which may improve public health the most and also provide more opportunities for people to interact with each other in public space. Furthermore, such initiatives, if undertaken at a sufficiently large scale can result in positive distal effects and climate change mitigation through CO2 reductions. The potential negative effects which may arise due to motorized traffic detouring around car free zone into their destinations also need further evaluation and the areas in which car free zones are introduced need to be given sufficient attention so as not to become an additional way to exacerbate socioeconomic divides. The extent and magnitude of all the above effects is still unclear and needs further research, including full chain health impact assessment modeling to quantify the potential health benefits of such schemes, and exposure and epidemiological studies to measure any changes when such interventions take place.
Conclusions:
The introduction of private car free cities is likely to have direct and indirect health benefits, but the exact magnitude and potential conflicting effects are as yet unclear. This paper has overviewed the expected health impacts, which can be useful to underpin policies to reduce car use in cities.
The sale of electrically assisted bicycles (‘e-bikes’) is growing at a rapid rate across Europe. Whereas market data is available describing sales trends, there is limited understanding of the experience of early adopters of e-bike technology. This paper investigates the motives for e-bike purchase, rider experience and perceived impact on mobility, health and wellbeing through in-depth interviews with e-bike owners in the Netherlands and the UK.
Findings revealed that the motive for purchasing e-bikes was often to allow maintenance of cycling against a backdrop of changing individual or household circumstances. E-bikes also provided new opportunities for people who would not otherwise consider conventional cycling. Perceptions of travel behaviour change revealed that e-biking was replacing conventional cycling but was also replacing journeys that would have been made by car. There was also a perception that e-biking has increased, or at least allowed participants to maintain, some form of physical activity and had benefitted personal wellbeing. Technological, social and environmental barriers to e-biking were identified. These included weight of bicycle, battery life, purchase price, social stigma and limitations of cycle infrastructure provision.
Additional research is necessary to quantify actual levels of mode substitution and new journey generation among new e-bike owners and the impact of e-biking on promoting physical health and mental wellbeing.