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The joint use of hourly resolution sampling and analyses with accelerated ion beams such as Particle Induced X-ray Emission (PIXE) technique has allowed the measurement of hourly temporal patterns of particulate matter (PM) composition at many sites in different parts of the world. The demand within the scientific community for this type of analysis has been continuously increasing in recent years, but hourly resolution samplers suitable for PIXE analysis are now discontinued and/or suffer from some technical limitations. In this framework, a new hourly sampler, STRAS (Size and Time Resolved Aerosol Sampler), was developed for the collection of PM10, PM2.5 or PM1. It allows automatic sequential sampling of up to 168 hourly samples (1 week), it is mechanically robust, compact, and easily transportable. To increase PIXE sensitivity, each sample is concentrated on a small surface area on a polycarbonate membrane. The comparison between the elemental concentrations retrieved by STRAS samples and samples collected using a standard sequential sampler operated in parallel shows a very good agreement; indeed, if both the samplers use the same kind of membrane, the concentrations of all detected elements are in agreement within 10 %. [ABSTRACT FROM AUTHOR]

Background: COVID-19 containment measures curb viral spread but may hamper walking mobility. As a low daily step count is associated with increased noncommunicable diseases and mortality, assessing the relationship between pandemic responses and walking mobility can help trade-off public health measures. We investigated the association between containment stringency and walking mobility across 60 countries in the period between January 21, 2020 and January 21, 2022 and modeled how this could impact mortality hazard. Methods: Walking mobility was measured through the Apple Mobility Trends, containment measures stringency index through the Oxford COVID-19 response tracker (which considers local policies on closures, healthcare, and economy), and meteorological data by National Oceanic and Atmospheric Administration weather stations. Walking mobility was regressed over stringency in a mixed-effect model with weather variables as covariates. The impact of stringency on all-cause mortality due to reduced mobility was modeled based on regression results, prepandemic walking mobility, and the association between step count and all-cause mortality hazard. Results: Across the 60 countries, the average stringency was 55 (9) (mean [SD]) out of 100. Stringency was negatively associated with walking mobility; a log-linear model fitted data better than a linear one, with a regression coefficient for stringency on ln (walking mobility) (95% confidence interval) of −1.201 × 10−2 (−1.221 × 10−2 to −1.183 × 10−2). Increasing stringency, thus decreasing walking mobility, nonlinearly incremented the modeled all-cause mortality hazard by up to ∼40%. Conclusions: In this study, walking mobility was negatively associated with containment measures stringency; the relationship between stringency, mobility, and the subsequent impact on health outcomes may be nonlinear. These findings can help in balancing pandemic containment policies. [ABSTRACT FROM AUTHOR]