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Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobilityrelated CO 2 emissions are complex and under-researched. Here we collected travel activity data in seven European cities and derived life cycle CO 2 emissions across modes and purposes. Daily mobility-related life cycle CO 2 emissions were 3.2 kgCO 2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO 2 emissions than non-cyclists. Life cycle CO 2 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 CO 2 emissions by 3.2 kgCO 2 /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 generally good for health, the environment and the economy. Yet the net effects of changes in active travel on changes in mobility-related CO 2 emissions are complex and under-researched. Here we collected longitudinal data on daily travel behavior, mode choice, as well as personal and geospatial characteristics in seven European cities and derived mobility-related lifecycle CO 2 emissions from daily travel activity over time and space. Fixed-and mixed-effects modelling of longitudinal panel data (n=1849) was performed to assess the associations between changes in lifecycle CO 2 emissions and changes in transport mode use (primary exposure), main mode of travel, and cycling frequency (secondary exposures). Daily mobility-related lifecycle CO 2 emissions were 2.8 kgCO 2 per person at baseline, with car travel contributing 69% and cycling 1%. At follow-up, mobility-related lifecycle CO 2 emissions were-0.52 (95%CI-0.82 to-0.21) kgCO 2 /day lower per additional cycling trip,-0.41 (95%CI-0.69 to-0.12) kgCO 2 /day lower per additional walking trip, and-2.11 (95%CI-1.78 to-2.43) kgCO 2 /day lower per 'avoided' car trip. An average person cycling 1 trip/day more and driving 1 trip/day less for 200 days a year would decrease mobility-related lifecycle CO 2 emissions by about 0.5 tonnes over a year. Those who changed from 'not cycling' to 'cycling' decreased daily CO 2 emissions by-2.54 (95%CI-3.90 to-1.17) kgCO 2 /day. Mobilityrelated CO 2 emissions decreased by-9.28 (95%CI-11.46 to-7.11) kg/day for those who changed their 'main mode' from car, van or motorbike to active travel. Extensive sensitivity analyses by city, journey purpose and key personal characteristics largely con rmed our results. Active travel is shown to substitute for motorized travel, with signi cant climate change mitigation effects. Even if not all car trips could be substituted by active travel the potential for decreasing emissions is considerable and signi cant. Investing in and promoting active travel should therefore 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. 'objective' built environment characteristics included here were (see Gascon et al., 2019 for how these

Similarity of findings across cities suggested that active transport, especially bicycle use, should be encouraged to improve population health and social outcomes.

Background Sufficient sample size and minimal sample bias are core requirements for empirical data analyses. Combining opportunistic recruitment with a Web-based survey and data-collection platform yields new benefits over traditional recruitment approaches. Objective This paper aims to report the success of different recruitment methods and obtain data on participants’ characteristics, participation behavior, recruitment rates, and representativeness of the sample. Methods A longitudinal, Web-based survey was implemented as part of the European PASTA (Physical Activity through Sustainable Transport Approaches) project, between November 2014 and December 2016. During this period, participants were recruited from 7 European cities on a rolling basis. A standardized guide on recruitment strategy was developed for all cities, to reach a sufficient number of adult participants. To make use of the strengths and minimize weakness, a combination of different opportunistic recruitment methods was applied. In addition, the random sampling approach was applied in the city of Örebro. To reduce the attrition rate and improve real-time monitoring, the Web-based platform featured a participant’s and a researchers’ user interface and dashboard. Results Overall, 10,691 participants were recruited; most people found out about the survey through their workplace or employer (2300/10691, 21.51%), outreach promotion (2219/10691, 20.76%), and social media (1859/10691, 17.39%). The average number of questionnaires filled in per participant varied significantly between the cities ( P <.001), with the highest number in Zurich (11.0, SE 0.33) and the lowest in Örebro (4.8, SE 0.17). Collaboration with local organizations, the use of Facebook and mailing lists, and direct street recruitment were the most effective approaches in reaching a high share of participants ( P <.001). Considering the invested working hours, Facebook was one of the most time-efficient methods. Compared with the cities’ census data, the composition of study participants was broadly representative in terms of gender distribution; however, the study included younger and better-educated participants. Conclusions We observed that offering a mixed recruitment approach was highly effective in achieving a high participation rate. The highest attrition rate and the lowest average number of questionnaires filled in per participant were observed in Örebro, which also recruited participants through random sampling. These findings suggest that people who are more interested in the topic are more willing to participate and stay in a survey than those who are selected randomly and may not have a strong connection to the research topic. Although direct face-to-face contacts were very effective with respect to the number of recruited participants, recruiting people through social media was not only...

We found that lung function improved with physical activity at low black carbon levels. This beneficial effect decreased in higher air pollution concentrations. Our results suggest a greater need to reduce air pollution exposures during physical activity.

Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility.

Physical activity and ventilation rates have an effect on an individual's dose and may be important to consider in exposure-response relationships; however, these factors are often ignored in environmental epidemiology studies. The aim of this study was to evaluate methods to estimate the inhaled dose of air pollution and understand variability, in the absence of a true gold standard metric. Five types of methods were identified: (1) methods using (physical) activity types; (2) methods based on energy expenditure, METs (metabolic equivalents of task) and oxygen consumption; (3) methods based on heart rate or (4) breathing rate; and (5) methods that combine heart and breathing rate. Methods were compared using a real-life dataset of 122 adults who wore devices to track movement, black carbon air pollution and physiological health markers for three weeks in three European cities. Different methods to estimate minute ventilation performed well in relative terms with high correlations among different methods. But in absolute terms, ignoring increased ventilation during day to day activities could lead to an underestimation of daily dose by a factor 0.08 to 1.78. There is no single best method and a multitude of methods are currently being used to approximate dose.The choice of a suitable method to determine dose in future studies will depend both on the size and the objectives of the study.