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Ambient particulate matter (PM) is a major contributor to air pollution, leading to adverse health effects on the human population. It has been suggested that the oxidative potential (OP, as a tracer of oxidative stress) of PM is a possible determinant of its health impact. In this study, samples of PM10, PM2.5, and PM1 were collected roughly every four days from January 2018 until March 2019 at a Barcelona urban background site and Montseny rural background site in northeastern Spain. We determined the chemical composition of samples, allowing us to perform source apportionment using positive matrix factorization. The OP of PM was determined by measuring reactive oxygen species using dithiothreitol and ascorbic acid assays. Finally, to link the sources with the measured OP, both a Pearson's correlation and a multiple linear regression model were applied to the dataset. The results showed that in Barcelona, the OP of PM10 was much higher than those of PM2.5 and PM1, whereas in Montseny results for all PM sizes were in the same range, but significantly lower than in Barcelona. In Barcelona, several anthropogenic sources were the main drivers of OP in PM10 (Combustion + Road Dust + Heavy Oil + OC-rich) and PM2.5 (Road Dust + Combustion). In contrast, PM1 -associated OP was driven by Industry, with a much lower contribution to PM10 and PM2.5 mass. Meanwhile, Montseny exhibited no clear drivers for OP evolution, likely explaining the lack of a significant difference in OP between PM10, PM2.5, and PM1. Overall, this study indicates that size fraction matters for OP, as a function of the environment typology. In an urban context, OP is driven by the PM10 and PM1 size fractions, whereas only the PM1 fraction is involved in rural environments., The present work was supported by the European Union's Horizon 2020 research and innovation program under grant agreement 101036245 (RI-URBANS); the “Agencia Estatal de Investigación” from the Spanish Ministry of Science and Innovation, and FEDER funds under the projects CAIAC (PID2019-108990RB-I00); and the Generalitat de Catalunya (AGAUR 2017 SGR41) and the Direcció General de Territori.

Air pollution is one of the most important problems the world is facing nowadays, adversely affecting public health and causing millions of deaths every year. Particulate matter is a criteria pollutant that has been linked to increased morbidity, as well as all-cause and cause-specific mortality. However, this association remains under-investigated in smaller-size cities in the Eastern Mediterranean, which are also frequently affected by heat waves and dust storms. This study explores the impact of particulate matter with an aerodynamic diameter ≤ 10 μm (PM10) and ≤ 2.5 μm (PM2.5) on mortality (all-cause, cardiovascular, respiratory) in two coastal cities in the Eastern Mediterranean; Thessaloniki, Greece and Limassol, Cyprus. Generalized additive Poisson models were used to explore overall and gender-specific associations, controlling for long- and short-term patterns, day of week and the effect of weather variables. Moreover, the effect of different lags, season, co-pollutants and dust storms on primary associations was investigated. A 10 μg/m3 increase in PM2.5 resulted in 1.10 % (95 % CI: -0.13, 2.34) increase in cardiovascular mortality in Thessaloniki, and in 3.07 % (95 % CI: -0.90, 7.20) increase in all-cause mortality in Limassol on the same day. Additionally, significant positive associations were observed between PM2.5 as well as PM10 and mortality at different lags up to seven days. Interestingly, an association with dust storms was observed only in Thessaloniki, having a protective effect, while the gender-specific analysis revealed significant associations only for the males in both cities. The outcome of this study highlights the need of city- or county-specific public health interventions to address the impact of climate, population lifestyle behaviour and other socioeconomic factors that affect the exposure to air pollution and other synergistic effects that alter the effect of PM on population health.

In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People’s Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM2.5 was a major contributor to COVID-19 cases in England, as an increase of 1 m3 in the long-term average of PM2.5 was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic., Graphical abstract Image 1, Highlights • Regional levels of NO2, NO and O3 correlate with number of COVID-19 deaths. • Sub-regional NOx levels are associated with increased COVID-19 deaths and cases. • Levels of PM and NOx map increased number of COVID-19 infections in the UK Biobank.

There is evidence of adverse health impacts from human exposure to particulate air pollution, including increased rates of respiratory and cardiovascular illness, hospitalizations, and pre-mature mortality. Most recent hypotheses assign an important role to ultrafine particles (UFP) ( We performed experimental measurements during both morning and evening traffic peak hours throughout the winter season (December 2013–March 2014), for a total of 98 trips. Our results suggest that the lowest UFP exposures are experienced by underground train commuters, with an average number concentration of 14 134 cm −3 , and are largely a reflection of the routes being at greater distance from vehicular traffic. Motorcyclists experienced significantly higher average concentrations (73 168 cm −3 ) than all other exposure classes, and this is most likely a result of the presence of high-concentration and short-duration peaks which do not occur when the same routes are traveled by car. UFP concentrations in subway train environments were found to be comparable to urban background levels. Still, in underground trains we found the highest values of PM 10 mass concentration with a maximum value of 422 μg/m 3 . PM 10 concentration in trains was found to be four and two times higher than what was measured in car and motorbike trips, respectively. Transport mode contribution to total integrated UFP daily exposure was found to be 16.3%–20.9% while travelling by car, 28.7% for motorbike trips, and 8.7% for subway trips. Due to lower exposure times, commuting by car and motorbike is comparable to other daily activities in terms of exposure. Our data can provide relevant information for transport decision-making and increase environmental awareness in the hope that the information about inhaled pollutants can translate into a more rational approach to urban travelling.

Plants and phyllosphere microorganisms may effectively contribute to reducing air pollution in cities through the adsorption and biodegradation of pollutants onto leaves. In this work, during all seasons, we sampled atmospheric particulate matter (PM10) and leaves of southern magnolia Magnolia grandiflora and deodar cedar Cedrus deodara, two evergreen plant species widespread in the urban area of Milan where the study was carried out. We then quantified Polycyclic Aromatic Hydrocarbons (PAHs) both in PM10 and on leaves and used sequencing of 16S rRNA gene, shotgun metagenomics and qPCR analyses to investigate the microbial communities hosted by the sampled leaves. Taxonomic and functional profiles of epiphytic bacterial communities differed between host plant species and seasons and the microbial communities on leaves harboured genes involved in the degradation of hydrocarbons. Evidence collected in this work also suggested that the abundance of hydrocarbon-degrading microorganisms on evergreen leaves increased with the concentration of hydrocarbons when atmospheric pollutants were deposited at high concentration on leaves, and that the biodegradation on the phyllosphere can contribute to the removal of PAHs from the urban air.

Aims Urbanisation has been linked with an increased risk of developing diabetes mellitus, dramatically worsening the healthcare system's financial burden. Environmental influences are emerging among the causing factors of the urban diabetes epidemic. We evaluated the relationship between air pollution and the prevalence of diabetes in the Municipalities of the Metropolitan City of Milan, comprising more than 3,4 million citizens. Methods The prevalence of diabetes in the resident population and the mean annual air concentrations of PM10 and NO2 were retrieved from the municipal Agency for Health Protection and the regional Agency for Ambient Protection datasets. Two linear regression models were estimated to inspect the relationships between the (logit-based transformed) diabetes prevalence and air pollution concentrations, namely: (i) PM10, and (ii) NO2. Both models were adjusted for five control variables, including the qualitative variable year (2011–2018). Results Both models highlight a statistically significant positive relationship between air pollutants and diabetes prevalence. An increase of one PM10 or NO2 concentrations' unit translates into a rise of 0.81% or 0.41% in diabetes prevalence, respectively. Conclusion Our results contribute to the ongoing research regarding health outcomes of urbanisation dynamics and should be considered in city planning policies.

Author(s): Wong, Jason YY; Margolis, Helene G; Machiela, Mitchell; Zhou, Weiyin; Odden, Michelle C; Psaty, Bruce M; Robbins, John; Jones, Rena R; Rotter, Jerome I; Chanock, Stephen J; Rothman, Nathaniel; Lan, Qing; Lee, Jennifer S | Abstract: BackgroundMosaic loss of chromosome Y (mLOY) can occur in a fraction of cells as men age, which is potentially linked to increased mortality risk. Smoking is related to mLOY; however, the contribution of air pollution is unclear.ObjectiveWe investigated whether exposure to outdoor air pollution, age, and smoking were associated with mLOY.MethodsWe analyzed baseline (1989-1993) blood samples from 933 men ≥65 years of age from the prospective Cardiovascular Health Study. Particulate matter ≤10 μm (PM10), carbon monoxide, nitrogen dioxide, sulfur dioxide, and ozone data were obtained from the U.S. EPA Aerometric Information Retrieval System for the year prior to baseline. Inverse-distance weighted air monitor data were used to estimate each participants' monthly residential exposure. mLOY was detected with standard methods using signal intensity (median log-R ratio (mLRR)) of the male-specific chromosome Y regions from Illumina array data. Linear regression models were used to evaluate relations between mean exposure in the prior year, age, smoking and continuous mLRR.ResultsIncreased PM10 was associated with mLOY, namely decreased mLRR (p-trend = 0.03). Compared with the lowest tertile (≤28.5 μg/m3), the middle (28.5-31.0 μg/m3; β = -0.0044, p = 0.09) and highest (≥31 μg/m3; β = -0.0054, p = 0.04) tertiles had decreased mLRR, adjusted for age, clinic, race/cohort, smoking status and pack-years. Additionally, increasing age (β = -0.00035, p = 0.06) and smoking pack-years (β = -0.00011, p = 1.4E-3) were associated with decreased mLRR, adjusted for each other and race/cohort. No significant associations were found for other pollutants.ConclusionsPM10 may increase leukocyte mLOY, a marker of genomic instability. The sample size was modest and replication is warranted.

We established air pollution modelling to study particle (PM10) exposures during pregnancy and infancy (1990–1993) through childhood and adolescence up to age ~15 years (1991–2008) for the Avon Longitudinal Study of Parents And Children (ALSPAC) birth cohort. For pregnancy trimesters and infancy (birth to 6 months; 7 to 12 months) we used local (ADMS-Urban) and regional/long-range (NAME-III) air pollution models, with a model constant for local, non-anthropogenic sources. For longer exposure periods (annually and the average of birth to age ~8 and to age ~15 years to coincide with relevant follow-up clinics) we assessed spatial contrasts in local sources of PM10 with a yearly-varying concentration for all background sources. We modelled PM10 (μg/m3) for 36,986 address locations over 19 years and then accounted for changes in address in calculating exposures for different periods: trimesters/infancy (n = 11,929); each year of life to age ~15 (n = 10,383). Intra-subject exposure contrasts were largest between pregnancy trimesters (5th to 95th centile: 24.4–37.3 μg/m3) and mostly related to temporal variability in regional/long-range PM10. PM10 exposures fell on average by 11.6 μg/m3 from first year of life (mean concentration = 31.2 μg/m3) to age ~15 (mean = 19.6 μg/m3), and 5.4 μg/m3 between follow-up clinics (age ~8 to age ~15). Spatial contrasts in 8-year average PM10 exposures (5th to 95th centile) were relatively low: 25.4–30.0 μg/m3 to age ~8 years and 20.7–23.9 μg/m3 from age ~8 to age ~15 years. The contribution of local sources to total PM10 was 18.5%–19.5% during pregnancy and infancy, and 14.4%–17.0% for periods leading up to follow-up clinics. Main roads within the study area contributed on average ~3.0% to total PM10 exposures in all periods; 9.5% of address locations were within 50 m of a main road. Exposure estimates will be used in a number of planned epidemiological studies.

Made available in DSpace on 2013-08-12T18:05:29Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-01-01 Made available in DSpace on 2013-09-30T19:14:47Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T15:31:32Z No. of bitstreams: 0 Made available in DSpace on 2014-05-20T15:31:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Fundação para o Desenvolvimento da UNESP (FUNDUNESP) Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB) British Council in Brazil RCUK academic fellowship Industrial emissions are a notorious source of atmospheric pollution in the Cubatao industrial park of Southern Brazil, where dispersion is restricted by surrounding mountain ranges. It is shown here that road transport is also a large source of gases and aerosols, which can dominate pollutant concentrations at ground level, depending on meteorological conditions. SO(2) was released mainly by industry, while road transport was a major source of NO(x). Rapid removal of NO(2) and SO(2) was attributed to fast gas phase and heterogeneous reactions, respectively. Average PM(10) concentrations increased by an order of magnitude during sea breeze fumigation, and high particulate pollution events were associated with vehicular activity. It is demonstrated that fast-response portable instrumentation can provide a useful alternative to measurements at fixed network sites for spatial (horizontal and vertical) mapping of atmospheric pollutants. Univ Estadual Paulista, Inst Quim, BR-14800900 Araraquara, SP, Brazil Univ Sheffield, Dept Geog, Sheffield S10 2TN, S Yorkshire, England Univ Lancaster, Dept Environm Sci, Lancaster LA1 4YQ, England Universidade Federal da Bahia (UFBA), Ctr Interdisciplinar Energia & Ambiente, BR-40110040 Salvador, BA, Brazil Universidade Federal da Bahia (UFBA), Inst Quim, BR-40170029 Salvador, BA, Brazil Univ Estadual Paulista, Inst Quim, BR-14800900 Araraquara, SP, Brazil