Cyclists' exposure to air pollution, noise, and greenery: a population-level spatial analysis approach.

Urban travel exposes people to a range of environmental qualities with significant health and wellbeing impacts. Nevertheless, the understanding of travel-related environmental exposure has remained limited. Here, we present a novel approach for population-level assessment of multiple environmental exposure for active travel. It enables analyses of (1) urban scale exposure variation, (2) alternative routes' potential to improve exposure levels per exposure type, and (3) by combining multiple exposures. We demonstrate the approach's feasibility by analysing cyclists' air pollution, noise, and greenery exposure in Helsinki, Finland. We apply an in-house developed route-planning and exposure assessment software and integrate to the analysis 3.1 million cycling trips from the local bike-sharing system. We show that especially noise exposure from cycling exceeds healthy thresholds, but that cyclists can influence their exposure by route choice. The proposed approach enables planners and individual citizens to identify (un)healthy travel environments from the exposure perspective, and to compare areas in respect to how well their environmental quality supports active travel. Transferable open tools and data further support the implementation of the approach in other cities.

In search of sustainable and inclusive mobility solutions for rural areas.

Background: Despite emerging research on novel mobility solutions in urban areas, there have been few attempts to explore the relevance and sustainability of these solutions in rural contexts. Furthermore, existing research addressing rural mobility solutions typically focuses on a specific user group, such as local residents, second-home owners, or tourists. In this paper, we study the social inclusivity, economic viability, and environmental impacts of novel mobility solutions in rural contexts based on published scholarly literature. When doing so, we bring both permanent and temporary residents of rural areas under one research framework. Methods: We used grey literature to identify and categorise novel mobility solutions, which have been applied in European rural areas and are suitable for travelling longer distances. By using six service flexibility variables, we reached four categories of novel mobility solutions: semi-flexible demand-responsive transport, flexible door-to-door demand-responsive transport, car-sharing, and ride-sharing. We analysed the social inclusivity, economic viability, and environmental impacts of those categories based on criteria and evidence identified from scholarly literature by including the perspectives of both permanent and temporary residents of rural areas. Results: Our findings revealed that while single novel mobility solutions are seldom applicable for all rural travellers, strong spatial and temporal synergies exist when combining different solutions. The need for a connected and flexible set of mobility solutions sensitive to the temporal and spatial patterns of mobility needs is inevitable. Accessible and easily understandable information on routing, booking, and ticketing systems, as well as cooperation, shared values, and trust between various parties, are key success factors for sustainable rural mobility. Conclusion: Integration of the needs of various user groups is essential when aiming to achieve the provision of environmentally, socially, and economically sustainable mobility solutions in rural areas. Supplementary Information: The online version contains supplementary material available at 10.1186/s12544-022-00536-3.

Environmental exposure during travel: A research review and suggestions forward.

Daily travel through the urban fabric exposes urban dwellers to a range of environmental conditions that may have an impact on their health and wellbeing. Knowledge about exposures during travel, their associations with travel behavior, and their social and health outcomes are still limited. In our review, we aim to explain how the current environmental exposure research addresses the interactions between human and environmental systems during travel through their spatial, temporal and contextual dimensions. Based on the 104 selected studies, we identify significant recent advances in addressing the spatiotemporal dynamics of exposure during travel. However, the conceptual and methodological framework for understanding the role of multiple environmental exposures in travel environments is still in an early phase, and the health and wellbeing impacts at individual or population level are not well known. Further research with greater geographical balance is needed to fill the gaps in the empirical evidence, and linking environmental exposures during travel with the causal health and wellbeing outcomes. These advancements can enable evidence-based urban and transport planning to take the next step in advancing urban livability.

COVID-19 is spatial: Ensuring that mobile Big Data is used for social good.

The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understanding the broad implications of the pandemic. The avalanche of mobile Big Data makes it possible to study the spatial effects of the crisis with spatiotemporal detail at the national and global scales. However, the current crisis also highlights serious limitations in the readiness to take the advantage of mobile Big Data for social good, both within and beyond the interests of health sector. We propose two strategical pathways for the future use of mobile Big Data for societal impact assessment, addressing access to both raw mobile Big Data as well as aggregated data products. Both pathways require careful considerations of privacy issues, harmonized and transparent methodologies, and attention to the representativeness, reliability and continuity of data. The goal is to be better prepared to use mobile Big Data in future crises.