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Fine particulate air pollution (PM2.5; particulate matter 2.5 μm or less in diameter) is thought to contribute to acute respiratory morbidity in part through oxidative stress. To examine the association between PM2.5 oxidative burden and emergency room visits for respiratory illnesses. We conducted a case-crossover study in Ontario, Canada between 2004 and 2011, including 127,836 cases of asthma, 298,751 cases of chronic obstructive pulmonary disease, and more than 1.1 million cases of all respiratory illnesses. Daily air pollution data were collected from ground monitors, and city-level PM2.5 oxidative potential was measured on the basis of a synthetic respiratory tract lining fluid containing the antioxidants glutathione and ascorbate. Conditional logistic regression was used to estimate associations between air pollution concentrations and emergency room visits, adjusting for time-varying covariates. Three-day mean PM2.5 concentrations were consistently associated with emergency room visits for all respiratory illnesses. Among children (<9 yr), each interquartile change (5.92 μg/m(3)) in 3-day mean PM2.5 was associated with a 7.2% (95% confidence interval, 4.2-10) increased risk of emergency room visits for asthma. Glutathione-related oxidative potential modified the impact of PM2.5 on emergency room visits for respiratory illnesses (P = 0.001) but only at low concentrations (≤10 μg/m(3)). Between-city differences in ascorbate-related oxidative potential did not modify the impact of PM2.5 on respiratory outcomes. Between-city differences in glutathione-related oxidative potential may modify the impact of PM2.5 on acute respiratory illnesses at low PM2.5 concentrations. This may explain in part how small changes in ambient PM2.5 mass concentrations can contribute to acute respiratory morbidity in low-pollution environments.

ObjectivesAccumulated evidence implies that night shift work may trigger liver dysfunction. Non-alcoholic fatty liver (NAFL) is suggested to be a necessary mediator in this process. This study aimed to examine the relationship between night shift work and elevated level of alanine transaminase (e-ALT) of workers and investigate the potential mediation effect of NAFL.MethodsThis study included all male workers from the baseline survey of a cohort of night shift workers. Information on demographics, lifestyle and lifetime working schedule was collected by face-to-face interview. Liver sonography was used to identify NAFL cases. Serum ALT level was detected by an automatic biochemical analyser. e-ALT was defined as ALT >40 U/L. Logistic regression models were used to evaluate ORs, and mediation analysis was employed to examine the mediation effect.ResultsAmong 4740 male workers, 39.5% were night shift workers. Night shift workers had an increased risk of e-ALT (OR, 1.19, 95% CI 1.00 to 1.42). With the increase in night shift years, the OR of e-ALT increased from 1.03 (95% CI 0.77 to 1.36) to 1.60 (95% CI 1.08 to 2.39) among workers without NAFL. A similar trend was not found among workers with NAFL. In addition, no significant mediation effect of NAFL in the association between night shift work and e-ALT was found.ConclusionsNight shift work is positively associated with abnormal liver function, in particular among workers without NAFL. Shift work involving circadian disruption is likely to exert a direct effect on liver dysfunction rather than rely on the mediation effect of NAFL.

Biomass burning organic aerosol (BBOA) can be emitted from natural forest fires and human activities such as agricultural burning and domestic energy generation. BBOA is strongly associated with atmospheric brown carbon (BrC) that absorbs near-ultraviolet and visible light, resulting in significant impacts on regional visibility degradation and radiative forcing. The mixing state of BBOA can play a critical role in the prediction of aerosol optical properties. In this work, single-particle measurements from a Soot-Particle Aerosol Mass Spectrometer coupled with a light scattering module (LS-SP-AMS) were performed to examine the mixing state of BBOA, refractory black carbon (rBC), and potassium (K, a tracer for biomass burning aerosol) in an air mass influenced by wildfire emissions transported from northern Québec to Toronto, representing aged biomass burning plumes. Cluster analysis of single-particle measurements identified five BBOA-related particle types. rBC accounted for 3–14 wt % of these particle types on average. Only one particle type exhibited a strong ion signal for K+, with mass spectra characterized by low molecular weight organic species. The remaining four particle types were classified based on the apparent molecular weight of the BBOA constituents. Two particle types were associated with low potassium content and significant amounts of high molecular weight (HMW) organic compounds. Our observations indicate non-uniform mixing of particles within a biomass burning plume in terms of molecular weight and illustrate that HMW BBOA can be a key contributor to low-volatility BrC observed in BBOA particles. The average mass absorption efficiency of low-volatility BBOA is about 0.8–1.1 m2 g−1 based on a theoretical closure calculation. Our estimates indicate that low-volatility BBOA contributes ∼ 33–44 % of thermo-processed particle absorption at 405 nm; and almost all of the BBOA absorption was associated with low-volatility organics.

Rapidly rising temperatures and loss of snow and ice cover have demonstrated the unique vulnerability of the high Arctic to climate change. There are major uncertainties in modelling the chemical depositional and scavenging processes of Arctic snow. To that end, fresh snow samples collected on average every 4 days at Alert, Nunavut, from September 2014 to June 2015 were analyzed for black carbon, major ions, and metals, and their concentrations and fluxes were reported. Comparison with simultaneous measurements of atmospheric aerosol mass loadings yields effective deposition velocities that encompass all processes by which the atmospheric species are transferred to the snow. It is inferred from these values that dry deposition is the dominant removal mechanism for several compounds over the winter while wet deposition increased in importance in the fall and spring, possibly due to enhanced scavenging by mixed-phase clouds. Black carbon aerosol was the least efficiently deposited species to the snow.

BackgroundAmbient air pollution is thought to contribute to increased risk of COVID-19, but the evidence is controversial.ObjectiveTo evaluate the associations between short-term variations in outdoor concentrations of ambient air pollution and COVID-19 emergency department (ED) visits.MethodsWe conducted a case-crossover study of 78 255 COVID-19 ED visits in Alberta and Ontario, Canada between 1 March 2020 and 31 March 2021. Daily air pollution data (ie, fine particulate matter with diameter less than 2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone were assigned to individual case of COVID-19 in 10 km × 10 km grid resolution. Conditional logistic regression was used to estimate associations between air pollution and ED visits for COVID-19.ResultsCumulative ambient exposure over 0–3 days to PM2.5 (OR 1.010; 95% CI 1.004 to 1.015, per 6.2 µg/m3) and NO2 (OR 1.021; 95% CI 1.015 to 1.028, per 7.7 ppb) concentrations were associated with ED visits for COVID-19. We found that the association between PM2.5 and COVID-19 ED visits was stronger among those hospitalised following an ED visit, as a measure of disease severity, (OR 1.023; 95% CI 1.015 to 1.031) compared with those not hospitalised (OR 0.992; 95% CI 0.980 to 1.004) (p value for effect modification=0.04).ConclusionsWe found associations between short-term exposure to ambient air pollutants and COVID-19 ED visits. Exposure to air pollution may also lead to more severe COVID-19 disease.

Prenatal exposure to fine particulate matter air pollution with aerodynamic diameter ≤2.5 μm (PM ) has been associated with preterm delivery and low birth weight (LBW), but few studies have examined possible effect modification by oxidative potential. The aim of this study was to evaluate if regional differences in the oxidative potential of PM modify the relationship between PM and adverse birth outcomes. A retrospective cohort study was conducted using 196,171 singleton births that occurred in 31 cities in the province of Ontario, Canada, from 2006 to 2012. Daily air pollution data were collected from ground monitors, and city-level PM oxidative potential was measured. We used random-effects meta-analysis to combine the estimates of effect from regression models across cities on preterm birth, term LBW, and term birth weight and used meta-regression to evaluate the modifying effect of PM oxidative potential. An interquartile increase (2.6 μg/m ) in first-trimester PM was positively associated with term LBW among women in the highest quartile of glutathione (GSH)-related oxidative potential [odds ratio (OR)=1.28; 95% confidence interval (CI): 1.10, 1.48], but not the lowest quartile (OR=0.99; 95% CI: 0.87, 1.14; -interaction=0.03). PM on the day of delivery also was associated with preterm birth among women in the highest quartile of GSH-related oxidative potential [hazard ratio (HR)=1.02; 95% CI: 1.01, 1.04], but not the lowest quartile [HR=0.97; 95% CI: 0.95, 1.00; -interaction=0.04]. Between-city differences in ascorbate (AA)-related oxidative potential did not significantly modify associations with PM . Between-city differences in GSH-related oxidative potential may modify the impact of PM on the risk of term LBW and preterm birth. https://doi.org/10.1289/EHP2535.

AbstractBackgroundExposure to traffic-related air pollution (TRAP) is associated with increased incidence of several cardiopulmonary diseases. The elevated TRAP exposures of commuting environments can result in significant contributions to daily exposures.ObjectivesTo assess the personal TRAP exposures (UFPs, BC, PM2.5, and PM10) of the bus transit systems of Toronto, Ottawa, and Vancouver, Canada. Personal exposure models estimated the contribution of bus commuting to daily TRAP exposures. Associations between bus type and riding exposures and bus stop/station type and waiting exposures were estimated.ResultsBus commuting (4.6% of the day) contributed ~59%(SD = 15%), 60%(SD = 20%), and 57%(SD = 18%) of daily PM2.5-Ba and 70%(SD = 19%), 64%(SD = 15%), and 70%(SD = 15%) of daily PM2.5-Fe, in Toronto, Ottawa, and Vancouver, respectively. Enclosed bus stations were found to be hotspots of PM2.5 and BC. Buses with diesel particulate filters (DPFs) and hybrid diesel/electric propulsion were found to have significantly lower in-bus PM2.5, UFP, and BC relative to 1983–2003 diesel buses in each city with the exception of UFP in Vancouver.SignificancePersonal exposures for traffic-related air pollutants were assessed for three Canadian bus transit systems. In each system, bus commuting was estimated to contribute significantly toward daily exposures of fine-fraction Ba and Fe as well as BC. Exposures while riding were associated with bus type for several pollutants in each city. These associations suggest the use of hybrid diesel/electric buses equipped with diesel particulate filters have improved air quality for riders.

To accurately study the characteristics of an air pollution emitter, it is necessary to isolate the contribution of that emitter to total measured pollution concentrations. A variety of published methods exist to complete this task, like placing measurements upwind the emitter, employing a distant background measurement station, or algorithmic methods that extract a background from the time series of measured concentrations (e.g. wavelet decomposition). In this study, we measured nitrogen oxides (NOx), carbon monoxide (CO), carbon dioxide (CO2), and fine particulate matter (PM2.5) at four sites spanning Toronto, Ontario, Canada. We first characterized the spatial variability of background concentrations across the city and then tested the accuracy of seven different algorithmic methods of estimating true measured upwind-of-emitter backgrounds near Toronto's Highway 401 by using the data collected at a downwind site. These methods included time-series and regression methods, including machine learning (XGBoost). We observed background concentrations had notable spatial variability, except for PM2.5. When predicting backgrounds upwind the highway, we found a distant measurement station provided an accurate background only during some times of day and was least accurate during rush hours. When testing algorithmic predictions of upwind-of-highway backgrounds, we found that regression models surpassed the performance of time-series methods, with best predictions having R2 exceeding 0.8 for all four pollutants. Despite the better performance of regression models, time-series methods still provided reasonable estimates. We also found that emitter-specific covariates (e.g. traffic counts, on-site dispersion modelling) did not play an important role in regressions, suggesting backgrounds can be well characterized by time of day, meteorology, and distant measurement stations. Based on our results, we provide ranked recommendations for choosing background estimation methods. We suggest future air pollution research characterizing individual emitters includes careful consideration of how background concentrations are estimated.

Adverse health outcomes related to exposure to air pollution have gained much attention in recent years, with a particular emphasis on traffic-related pollutants near roadways, where concentrations tend to be most severe. As such, many projects around the world are being initiated to routinely monitor pollution near major roads. Understanding the extent to which local on-road traffic directly affects these measurements, however, is a challenging problem, and a more thorough comprehension of it is necessary to properly assess its impact on near-road air quality. In this study, a set of commonly measured air pollutants (black carbon; carbon dioxide; carbon monoxide; fine particulate matter, PM2.5; nitrogen oxides; ozone; and ultrafine particle concentrations) were monitored continuously between 1 June 2015 and 31 March 2017 at six stations in Canada: two near-road and two urban background stations in Toronto, Ontario, and one near-road and one urban background station in Vancouver, British Columbia. Three methods of differentiating between local and background concentrations at near-road locations were tested: (1) differences in average pollutant concentrations between near-road and urban background station pairs, (2) differences in downwind and upwind pollutant averages, and (3) interpolation of rolling minima to infer background concentrations. The last two methods use near-road data only, and were compared with method 1, where an explicit difference was measured, to assess accuracy and robustness. It was found that method 2 produced average local concentrations that were biased high by a factor of between 1.4 and 1.7 when compared with method 1 and was not universally feasible, whereas method 3 produced concentrations that were in good agreement with method 1 for all pollutants except ozone and PM2.5, which are generally secondary and regional in nature. The results of this comparison are intended to aid researchers in the analysis of data procured in future near-road monitoring studies. Lastly, upon determining these local pollutant concentrations as a function of time, their variability with respect to wind speed (WS) and wind direction (WD) was assessed relative to the mean values measured at the specific sites. This normalization allowed generalization across the pollutants and made the values from different sites more comparable. With the exception of ozone and PM2.5, local pollutant concentrations at these near-road locations were enhanced by a factor of 2 relative to their mean in the case of stagnant winds and were shown to be proportional to WS−0.6. Downwind conditions enhanced local concentrations by a factor of ∼2 relative to their mean, while upwind conditions suppressed them by a factor of ∼4. Site-specific factors such as distance from roadway and local meteorology should be taken into consideration when generalizing these factors. The methods used to determine these local concentrations, however, have been shown to be applicable across pollutants and different near-road monitoring environments.

Alkylamines are associated with both natural and anthropogenic sources and have been detected in ambient aerosol in a variety of environments. However, little is known about the ubiquity or relative abundance of these species in Europe. In this work, ambient single-particle mass spectra collected at five sampling sites across Europe have been analysed for their alkylamine content. The aerosol time-of-flight mass spectrometer (ATOFMS) data used were collected in Ireland (Cork), France (Paris, Dunkirk and Corsica) and Switzerland (Zurich) between 2008 and 2013. Each dataset was queried for mass spectral marker ions associated with the following ambient alkylamines: dimethylamine (DMA), trimethylamine (TMA), diethylamine (DEA), triethylamine (TEA), dipropylamine (DPA) and tripropylamine (TPA). The fraction of ambient particles that contained detectable alkylamines ranged from 1 to 17 % depending on location, with the highest fractions observed in Paris and Zurich in the winter months. The lowest fractions were observed at coastal sites, where the influence of animal husbandry-related alkylamine emissions is also expected to be lowest. TMA was the most ubiquitous particle phase alkylamine detected and was observed at all locations. Alkylamines were found to be internally mixed with both sulphate and nitrate for each dataset, suggesting that aminium salt formation may be important at all sites investigated. Interestingly, in Corsica, all alkylamine particles detected were also found to be internally mixed with methanesulphonic acid (MSA), indicating that aminium methanesulphonate salts may represent a component of marine ambient aerosol in the summer months. Internal mixing of alkylamines with sea salt was not observed, however. Alkylamine-containing particle composition was found to be reasonably homogeneous at each location, with the exception of the Corsica and Dunkirk sites, where two and four distinct mixing states were observed, respectively.