Since the first release of modern electric vehicles, researchers and policy makers have shown interest in the deployment and utilization of charging infrastructure. Despite the sheer volume of literature, limited attention has been paid to the characteristics and variance of charging behavior of EV users. In this research, we answer the question: which scientific approaches can help us to understand the dynamics of charging behavior in charging infrastructures, in order to provide recommendations regarding a more effective deployment and utilization of these infrastructures. To do so, we propose a conceptual model for charging infrastructure as a social supply–demand system and apply complex system properties. Using this conceptual model, we estimate the rate complexity, using three developed ratios that relate to the (1) necessity of sharing resources, (2) probabilities of queuing, and (3) cascading impact of transactions on others. Based on a qualitative assessment of these ratios, we propose that public charging infrastructure can be characterized as a complex system. Based on our findings, we provide four recommendations to policy makers for taking efforts to reduce complexity during deployment and measure interactions between EV users using systemic metrics. We further point researchers and policy makers to agent-based simulation models that capture interactions between EV users and the use complex network analysis to reveal weak spots in charging networks or compare the charging infrastructure layouts of across cities worldwide.
Western cities are rapidly densifying, and new building typologies are beinginvented to mitigate high-rise and balance residential, commercial andrecreational functions. This vertical urbanization requires rethinking thetraditional design of public space to promote citizens’ well-being. While the scarce studies on high-rise environments indicate several risks, including social fragmentation and privatization of public functions (Henderson-Wilson 2008; Love et al., 2014), mental stress and undermining attention restoration (Mazumder et al., 2020; Lindal & Hartig 2013), evidence on the potential salutary and mitigating effects of architectural design qualities is limited (Suurenbroek & Spanjar 2023).The Building for Well-being research project combines biometric and socialdata-collection techniques to address this gap. It builds on studies investigatinghow built environments allow user engagement (Mallgrave 2013; Simpson2018) and afford important activities (Gibson 1966). This case study focuseson the experiences of predominant users of the NDSM Wharf in Amsterdamas it is transformed from a post-industrial site into a high-density, mixeduseneighborhood. Using eye-tracking, field and laboratory-based surveys, itexplores how residents, passers-by and visitors visually experience, appreciateand perceive the restorative value of the wharf’s recently developed urbanspaces.Thirty-six university students were randomly recruited as test subjects for thelaboratory test and assigned to one of the three user groups. The residentand passer-by groups were primed for familiarity. Each group was assigneda distinct walking mode and participants were told to imagine they werestrolling (residents), rushing (passers-by) or exploring (visitors). The exposuretime to visual stimuli of participants was five seconds per image. Afterwards,they reported on the perceived restorative quality of ten urban spaces,focusing on: (1) sense of being away, (2) level of complexity-compatibilityand (3) fascination, based on an adapted Restorative Components Scale (RCS,Yin et al. 2022; Laumann et al. 2001). Self-reported appreciation per scenewas measured on a 10-point Likert scale and subjects indicated elements inthe ten urban spaces they liked or disliked (see Figure 1). A semi-structuredon-site survey was also carried out to investigate user experiences furtherand for triangulation. Thirty-one users, consisting of residents, passers-byand visitors to the NDSM Wharf, rated their appreciation of the site and itsperceived restorative and design qualities (following Ewing & Clemente, 2013)on a 10-point Likert scale.The meta-data analysis of RCS statistics, appreciation values, eye-trackingmetrics and heatmaps reveals distinct visual patterns among user groups. Thispoints to the influence of environmental tasks and roles (see Figure 2). Strollingand exploring resulted in a comprehensive visual exploration of scenes with ahigher mean total fixation count and shorter mean total fixation duration thangoal-oriented walking. It suggests that walking mode determines the level ofopenness to the environment and that architectural attributes can also steervisual exploration. Scenes with the highest appreciation scores correlatedwith the RCS outcomes. They displayed coherence and opportunities forsocial engagement, contrasting with scenes with inconsistent industrial andcontemporary features. These findings provide spatial designers with insightsinto the subliminal experiences of predominant user groups to promote wellbeing in urban transformation.
The main objective of the study is to determine if non-specific physical symptoms (NSPS) in people with self-declared sensitivity to radiofrequency electromagnetic fields (RF EMF) can be explained (across subjects) by exposure to RF EMF. Furthermore, we pioneered whether analysis at the individual level or at the group level may lead to different conclusions. By our knowledge, this is the first longitudinal study exploring the data at the individual level. A group of 57 participants was equipped with a measurement set for five consecutive days. The measurement set consisted of a body worn exposimeter measuring the radiofrequency electromagnetic field in twelve frequency bands used for communication, a GPS logger, and an electronic diary giving cues at random intervals within a two to three hour interval. At every cue, a questionnaire on the most important health complaint and nine NSPS had to be filled out. We analysed the (time-lagged) associations between RF-EMF exposure in the included frequency bands and the total number of NSPS and self-rated severity of the most important health complaint. The manifestation of NSPS was studied during two different time lags - 0–1 h, and 1–4 h - after exposure and for different exposure metrics of RF EMF. The exposure was characterised by exposure metrics describing the central tendency and the intermittency of the signal, i.e. the time-weighted average exposure, the time above an exposure level or the rate of change metric. At group level, there was no statistically significant and relevant (fixed effect) association between the measured personal exposure to RF EMF and NSPS. At individual level, after correction for multiple testing and confounding, we found significant within-person associations between WiFi (the self-declared most important source) exposure metrics and the total NSPS score and severity of the most important complaint in one participant. However, it cannot be ruled out that this association is explained by residual confounding due to imperfect control for location or activities. Therefore, the outcomes have to be regarded very prudently. The significant associations were found for the short and the long time lag, but not always concurrently, so both provide complementary information. We also conclude that analyses at the individual level can lead to different findings when compared to an analysis at group level. https://doi.org/10.1016/j.envint.2019.104948 LinkedIn: https://www.linkedin.com/in/john-bolte-0856134/
MULTIFILE
07/05/2019
