Active travel (walking or cycling for transport) is considered the most sustainable form of getting from A to B. Yet the net effects of active travel on mobility-related CO2 emissions are complex and underresearched. Here we collected travel activity data in seven European cities and derived lifecycle CO2 emissions from daily travel activity. Daily mobility-related lifecycle CO2 emissions were 3.2 kgCO2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower lifecycle CO2 emissions from all daily travel than non-cyclists. Lifecycle CO2 emissions decreased by -14% (95%CI -12% to -16%) per additional cycling trip and decreased by -62% (95%CI -61% to -63%) for each avoided car trip. An average person who ‘shifted travel modes’ from car to bike decreased lifecycle CO2 emissions by 3.2 (95%CI 2.0 to 5.2) kgCO2/day, and using a bike as the ‘main method of travel’ gave 7.1 (95%CI 4.8 to 10.4) kgCO2/day lower lifecycle CO2 emissions than mainly using a car or van. Investing in and 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.
This paper compares the environmental performance of three different last mile scenarios. The first one operates within a traditional truck-based delivery. The second one consists of having trucks serving as mobile depots while the final delivery is performed by motorized tricycles. Based on second scenario a hypothetical third scenario was created by using electric assisted cargo bikes replacing the motorized tricycles. Data was collected in Rio de Janeiro city and a Monte Carlo simulation was used to assess the environmental performance of these three delivery setups. The analysis suggests that, despite of having similar operational characteristics and service levels, the multimodal delivery scenarios yield substantial reductions in term of CO2 emissions when compared with the traditional operation and that the electric assisted cargo bike scenario performs better for all the air pollutant and greenhouse gas emissions when compared with the similar scenario that uses motorized tricycles.
This chapter begins with the discussion of climate change, greenhouse gas (GHG) emissions and the contribution of the transportation sector to GHG emissions. The chapter then introduces three key mechanisms through which active transportation can be beneficial to the environment: (1) it requires less space; (2) it produces fewer emissions per passenger kilometre; and (3) it creates fewer wastes and has lower life cycle costs. Next, we extend the discussion to a broader environmental impact by exploring various environmental dimensions related to active transportation, including land consumption, GHG emissions, air pollution, life cycle and ecological impacts, and urban run-off and soil contamination. The chapter is followed by a brief discussion about the risk trade-off between physical activity and air pollution exposure for pedestrians and cyclists. By summarizing the most recent literature, we provide a current consensus that active transportation far outweighs the risks associated with air pollution exposure. The chapter concludes with recommendations for maximizing the environmental benefits of active transportation, which can foster environmental stewardship in schools and at home.
Sales rates of electric bicycles (e-bikes) have grown rapidly over the last ten years, not only in Germany but all over Europe. Thus, the strongest movement towards electric mobility on German roads is yet dominantly pushed by e-bikes, whereas electric cars need to catch up. So far, there are hardly any reliable investigations about everyday use patterns, modal shift effects and potentials to reduce climate impact. An assessment of the significance of e-bikes for achieving climate and energy policy guidelines from the "German Federal Government’s National Energy Concept" from 2010 has not been possible so far. The project "Pedelection" analysed these questions by conducting a field test focused on people who purchased their e-bike only recently. The main finding from the field test is that e-bikes have the potential to substitute a considerable amount of car mileage. Since the climate balance of distance travelled by e-bikes is by factor 10 better, additional induced traffic or shifting from bicycle/walking is negligible to a certain degree. Bicycles – with or without electric assistance – are serious means of transport and a genuine alternative to passenger cars on short and medium distances up to 15 km.
This paper investigates the evolution of urban cycling in Montreal, Canada and its link to both built environment indicators and bicycle infrastructure accessibility. The effect of new cycling infrastructure on transport-related greenhouse gas (GHG) emissions is then explored. More specifically, we aim at investigating how commuting cycling modal share has evolved across neighborhood built-environment typologies and over time in Montreal, Canada. For this purpose, automobile and bicycle trip information from origin–destination surveys for the years 1998, 2003 and 2008 are used. Neighborhood typologies are generated from different built environment indicators (population and employment density, land use diversity, etc.). Furthermore, to represent the commuter mode choice (bicycle vs automobile), a standard binary logit and simultaneous equation modeling approach are adopted to represent the mode choice and the household location. Among other things, we observe an important increase in the likelihood to cycle across built environment types and over time in the study region. In particular, urban and urban-suburb neighborhoods have experienced an important growth over the 10 years, going from a modal split of 2.8–5.3% and 1.4–3.0%, respectively. After controlling for other factors, the model regression analysis also confirms the important increase across years as well as the significant differences of bicycle ridership across neighborhoods. A statistically significant association is also found between the index of bicycle infrastructure accessibility and bike mode choice – an increase of 10% in the accessibility index results in a 3.7% increase in the ridership. Based on the estimated models and in combination with a GHG inventory at the trip level, the potential impact of planned cycling infrastructure is explored using a basic scenario. A reduction of close to 2% in GHG emissions is observed for an increase of 7% in the length of the bicycle network. Results show the important benefits of bicycle infrastructure to reduce commuting automobile usage and GHG emissions.