Redox-activity and in vitro effects of regional atmospheric aerosol pollution: Seasonal differences and correlation between oxidative potential and in vitro toxicity of PM1.

Particulate Matter (PM) is a complex and heterogeneous mixture of atmospheric particles recognized as a threat to human health. Oxidative Potential (OP) measurement is a promising and integrative method for estimating PM-induced health impacts since it is recognized as more closely associated with adverse health effects than ordinarily used PM mass concentrations. OP measurements could be introduced in the air quality monitoring, along with the parameters currently evaluated. PM deposition in the lungs induces oxidative stress, inflammation, and DNA damage. The study aimed to compare the OP measurements with toxicological effects on BEAS-2B and THP-1 cells of winter and summer PM1 collected in the Po Valley (Italy) during 2021. PM1 was extracted in deionized water by mechanical agitation and tested for OP and, in parallel, used to treat cells. Cytotoxicity, genotoxicity, oxidative stress, and inflammatory responses were assessed by MTT test, DCFH-DA assay, micronucleus, γ-H2AX, comet assay modified with endonucleases, ELISA, and Real-Time PCR. The evaluation of OP was performed by applying three different assays: dithiothreitol (OPDTT), ascorbic acid (OPAA), and 2',7'-dichlorofluorescein (OPDCFH), in addition, the reducing potential was also analysed (RPDPPH). Seasonal differences were detected in all the parameters investigated. The amount of DNA damage detected with the Comet assay and ROS formation highlights the presence of oxidative damage both in winter and in summer samples, while DNA damage (micronucleus) and genes regulation were mainly detected in winter samples. A positive correlation with OPDCFH (Spearman's analysis, p < 0.05) was detected for IL-8 secretion and γ-H2AX. These results provide a biological support to the implementation in air quality monitoring of OP measurements as a useful proxy to estimate PM-induced cellular toxicological responses. In addition, these results provide new insights for the assessment of the ability of secondary aerosol in the background atmosphere to induce oxidative stress and health effects.

Insights on the combination of off-line and on-line measurement approaches for source apportionment studies.

This paper presents a source apportionment study performed on a dataset collected at a trafficked site in Coimbra (Portugal) during the period December 2018-June 2019. The novelty of this work consists in the methodological approach used and the sensitivity study carried out to give hints to potential future applications. Indeed, a multi-time resolution and multi-parameter study was performed joining together aerosol data from 24-h chemically characterized samples and high-time resolution multi-wavelength absorption coefficients retrieved by an Aethalometer. A detailed sensitivity study on the most suitable combination of time resolution and uncertainties was carried out to obtain reliable physical and stable solutions over all analyses. In parallel, a regular EPA-PMF source apportionment study using chemical and optical variables averaged on 24 h is presented and discussed in comparison to the more complex multi-time and multi-parameter approach. Apart from results pertaining to the identification and relevance of different sources in Coimbra, the methodological results shown here can give guidance for readers who want to implement optical variables jointly with chemical ones in the same model run.

COVID-19 Containment Measures-a Step Back for Walking Mobility? A 2-Year, 60-Country Analysis of the Apple Mobility Data.

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.