Potential health impact of ultrafine particles under clean and polluted urban atmospheric conditions: a model-based study

Prediction of Short-Term Ultrafine Particle Exposures Using Real-Time Street-Level Images Paired with Air Quality Measurements

Within-city ultrafine particle (UFP) concentrations vary sharply since they are influenced by various factors. We developed prediction models for short-term UFP exposures using street-level images collected by a camera installed on a vehicle rooftop, paired with air quality measurements conducted during a large-scale mobile monitoring campaign in Toronto, Canada. Convolutional neural network models were trained to extract traffic and built environment features from images. These features, along with regional air quality and meteorology data were used to predict short-term UFP concentration as a continuous and categorical variable. A gradient boost model for UFP as a continuous variable achieved R² = 0.66 and RMSE = 9391.8#/cm³ (mean values for 10-fold cross-validation). The model predicting categorical UFP achieved accuracies for "Low" and "High" UFP of 77 and 70%, respectively. The presence of trucks and other traffic parameters were associated with higher UFPs, and the spatial distribution of elevated short-term UFP followed the distribution of single-unit trucks. This study demonstrates that pictures captured on urban streets, associated with regional air quality and meteorology, can adequately predict short-term UFP exposure. Capturing the spatial distribution of high-frequency short-term UFP spikes in urban areas provides crucial information for the management of near-road air pollution hot spots.

Analysis of ways to reduce potential health risk from ultrafine and fine particles emitted from 3D printers in the makerspace

Due to the growing maker culture, maker spaces using multiple fused deposition modeling (FDM)-3D printers have spread around the world. However, the 3D printing process is known to cause the release of ultrafine and fine particles, which may have adverse health effects on occupants. Therefore, this experiment-based study was conducted on FDM-3D printers placed in an actual makerspace by the following three scenarios: the number of operating FDM-3D printers, ventilation, and measurement location to compare the concentrations of ultrafine and fine particles. In addition, the deposited dose in alveolar region for ultrafine and fine particles was predicted using a respiratory deposition model to analyze the potential health risk on occupants. As a result, the scenario-based comparison revealed that if the number of operating 3D printers is reduced by less than half, the potential health risk can be decreased by 34.1%, proper ventilation can reduce potential health risk by 55.5%, and working away from the 3D printer can also reduce potential health risk by up to 27.5%. This study analyzed the potential health risk of multiple FDM-3D printers on users in an actual makerspace, and proposed various improvement measures to reduce the potential health risk of ultrafine and fine particles.

A gradient boost approach for predicting near-road ultrafine particle concentrations using detailed traffic characterization

This study investigates the influence of meteorology, land use, built environment, and traffic characteristics on near-road ultrafine particle (UFP) concentrations. To achieve this objective, minute-level UFP concentrations were measured at various locations along a major arterial road in the Greater Toronto Area (GTA) between February and May 2019. Each location was visited five times, at least once in the morning, mid-day, and afternoon. Each visit lasted for 30 min, resulting in 2.5 h of minute-level data collected at each location. Local traffic information, including vehicle class and turning movements, were processed using computer vision techniques. The number of fast-food restaurants, cafes, trees, traffic signals, and building footprint, were found to have positive impacts on the mean UFP, while distance to the closest major road was negatively associated with UFP. We employed the Extreme Gradient Boosting (XGBoost) method to develop prediction models for UFP concentrations. The Shapley additive explanation (SHAP) measures were used to capture the influence of each feature on model output. The model results demonstrated that minute-level counts of local traffic from different directions had significant impacts on near-road UFP concentrations, model performance was robust under random cross-validation as coefficients of determination (R²) ranged from 0.63 to 0.69, but it revealed weaknesses when data at specific locations were eliminated from the training dataset. This result indicates that proper cross-validation techniques should be developed to better evaluate machine learning models for air quality predictions.

Immune-pineal axis protects rat lungs exposed to polluted air

Environmental pollution in the form of particulate matter <2.5 μm (PM_2.5 ) is a major risk factor for diseases such as lung cancer, chronic respiratory infections, and major cardiovascular diseases. Our goal was to show that PM_2.5 eliciting a proinflammatory response activates the immune-pineal axis, reducing the pineal synthesis and increasing the extrapineal synthesis of melatonin. Herein, we report that the exposure of rats to polluted air for 6 hours reduced nocturnal plasma melatonin levels and increased lung melatonin levels. Melatonin synthesis in the lung reduced lipid peroxidation and increased PM_2.5 engulfment and cell viability by activating high-affinity melatonin receptors. Diesel exhaust particles (DEPs) promoted the synthesis of melatonin in a cultured cell line (RAW 264.7 cells) and rat alveolar macrophages via the expression of the gene encoding for AANAT through a mechanism dependent on activation of the NFκB pathway. Expression of the genes encoding AANAT, MT1, and MT2 was negatively correlated with cellular necroptosis, as disclosed by analysis of Gene Expression Omnibus (GEO) microarray data from the human alveolar macrophages of nonsmoking subjects. The enrichment score for antioxidant genes obtained from lung gene expression data (GTEx) was significantly correlated with the levels of AANAT and MT1 but not the MT2 melatonin receptor. Collectively, these data provide a systemic and mechanistic rationale for coordination of the pineal and extrapineal synthesis of melatonin by a standard damage-associated stimulus, which activates the immune-pineal axis and provides a new framework for understanding the effects of air pollution on lung diseases.

Exposure to Secondhand Tobacco Smoke at Airport Terminals

Background

Airports may represent significant sources of secondhand smoke (SHS) exposure for both travelers and employees. While previously common smoking rooms have largely disappeared from US airports, smoking continues to occur outdoors at terminal entrances. SHS may be especially high at arrival areas, since they oftentimes are partially enclosed by overhead departures, creating stagnant microenvironments. This study assessed particulate matter <2.5 microns in diameter (PM2.5), a common surrogate for SHS, at airport terminal locations to evaluate both outdoor exposure risk and possible indoor drift of SHS from outdoor sources.

Methods

A convenience sample of nine airport terminal arrival areas in the US state of Florida was surveyed between February and July 2018. PM2.5 levels were assessed outdoors and indoors at terminal entrances and at control areas far into terminal interiors. We also examined the impact of smoking location on SHS exposure by correlating cigarette and passing vehicle counts with PM2.5 levels at terminals with contrasting proximity of designated smoking locations to terminal entrances.

Results

Although outdoor PM2.5 levels (mean 17.9, SD 6.1 µg/m³) were significantly higher than indoors (p < 0.001), there was no difference between indoor areas directly inside terminal entrances and areas much further interior (mean 8.8, SD 2.6 vs mean 8.5, SD 3.0 µg/m³, p=0.49). However, when smoking areas were in close proximity to terminal entrances, the number of lit cigarettes and vehicular traffic per minute predicted 70% of the variance of PM2.5 levels (p < 0.001), which was attributable mostly to the cigarette number (β = 0.83; 95% CI (0.55 to 1.11); p < 0.001). This effect was not observed at smoking areas further away.

Conclusion

PM2.5 data did not suggest indoor drift from outside smoking. Nevertheless, absolute exposure outdoors was high and correlated with the location of designated smoking areas. Further studies are needed to examine the effect of microclimate formation on exposure risk.

Genotoxic and epigenotoxic effects in mice exposed to concentrated ambient fine particulate matter (PM2.5) from São Paulo city, Brazil

BACKGROUND

The Metropolitan Area of São Paulo has a unique composition of atmospheric pollutants, and positive correlations between exposure and the risk of diseases and mortality have been observed. Here we assessed the effects of ambient fine particulate matter (PM2.5) on genotoxic and global DNA methylation and hydroxymethylation changes, as well as the activities of antioxidant enzymes, in tissues of AJ mice exposed whole body to ambient air enriched in PM2.5, which was concentrated in a chamber near an avenue of intense traffic in São Paulo City, Brazil.

RESULTS

Mice exposed to concentrated ambient PM2.5 (1 h daily, 3 months) were compared to in situ ambient air exposed mice as the study control. The concentrated PM2.5 exposed group presented increased levels of the oxidized nucleoside 8-oxo-7,8-dihydro-2'-deoxyguanosine in lung and kidney DNA and increased levels of the etheno adducts 1,N6-etheno-2'-deoxyadenosine and 1,N2-etheno-2'-deoxyguanosine in kidney and liver DNA, respectively. Apart from the genotoxic effects, the exposure to PM2.5 led to decreased levels of the epigenetic mark 5-hydroxymethylcytosine (5-hmC) in lung and liver DNA. Changes in lung, liver, and erythrocyte antioxidant enzyme activities were also observed. Decreased glutathione reductase and increased superoxide dismutase (SOD) activities were observed in the lungs, while the liver presented increased glutathione S-transferase and decreased SOD activities. An increase in SOD activity was also observed in erythrocytes. These changes are consistent with the induction of local and systemic oxidative stress.

CONCLUSIONS

Mice exposed daily to PM2.5 at a concentration that mimics 24-h exposure to the mean concentration found in ambient air presented, after 3 months, increased levels of DNA lesions related to the occurrence of oxidative stress in the lungs, liver, and kidney, in parallel to decreased global levels of 5-hmC in lung and liver DNA. Genetic and epigenetic alterations induced by pollutants may affect the genes committed to cell cycle control, apoptosis, and cell differentiation, increasing the chance of cancer development, which merits further investigation.

Heavy truck restrictions and air quality implications in São Paulo, Brazil

This study quantified the effects of traffic restrictions on diesel fuel heavy vehicles (HVs) on the air quality of the Bandeirantes corridor using hourly data obtained by continuous monitoring of traffic and air quality at sites located on this avenue. The study addressed the air quality of a city impacted by vehicular emissions and that PM₁₀ and NO_X concentrations are mainly due to diesel burning. Data collection was split into two time periods, a period of no traffic constraint on HVs (Nov 2008 and 2009) and a period of constraint (Nov 2010, 2011 and 2012). We found that pollutants on this corridor, mainly PM₁₀ and NO_X, decreased significantly during the period from 2008 to 2012 (28 and 43%, 15.8 and 86.9 ppb) as a direct consequence of HV traffic restrictions (a 72% reduction). Rebound effects in the form of increased traffic of light vehicles (LVs) during this time had impacts on the concentration levels, explaining the differences between rates of reduction in HV traffic and pollutants. Reductions in the number of trucks resulted in longer travel times and increased traffic congestion as a consequence of the modal shift towards LVs. We found that a 51% decrease in PM₁₀ (28.8 μg m^-3) was due to a reduction in HV traffic (vehicle emissions were estimated to be 71% of total sources, 40.1 μg m^-3). This percentage was partially offset by 10% more PM₁₀ emissions related to an increase in LV traffic, while other causes, such as climatic conditions, contributed to a 13% increase in PM₁₀ concentrations. The relationships analyzed in this research served to highlight the need to apply urban transport policies aimed at decreasing pollutant concentrations in São Paulo, especially in heavily congested urban corridors on working days.

Cognitive Effects of Air Pollution Exposures and Potential Mechanistic Underpinnings

PURPOSE OF REVIEW

This review sought to address the potential for air pollutants to impair cognition and mechanisms by which that might occur.

RECENT FINDINGS

Air pollution has been associated with deficits in cognitive functions across a wide range of epidemiological studies, both with developmental and adult exposures. Studies in animal models are significantly more limited in number, with somewhat inconsistent findings to date for measures of learning, but show more consistent impairments for short-term memory. Potential contributory mechanisms include oxidative stress/inflammation, altered levels of dopamine and/or glutamate, and changes in synaptic plasticity/structure. Epidemiological studies are consistent with adverse effects of air pollutants on cognition, but additional studies and better phenotypic characterization are needed for animal models, including more precise delineation of specific components of cognition that are affected, as well as definitions of critical exposure periods for such effects and the components of air pollution responsible. This would permit development of more circumscribed hypotheses as to potential behavioral and neurobiological mechanisms.

Association between size-segregated particles in ambient air and acute respiratory inflammation

The health effects of particulate matter (PM) in ambient air are well documented. However, whether PM size plays a critical role in these effects is unclear in the population studies. This study investigated the association between the ambient concentrations of PM with varies sizes (5.6-560nm) and a biomarker of acute respiratory inflammation, the fraction of exhaled nitric oxide (FENO), in a panel of 55 elderly people in Shanghai, China. Linear mixed-effect model was fitted to estimate the association between FENO and moving average concentrations of PM, adjusting for temperature, relative humidity, day of the week, and age. Results showed that among the measured particles size range, Aitken-mode (20-100nm) particles had the strongest positive association with increased FENO when using moving average concentration of PM up to 24h prior to visits. The estimates were robust to the adjustment for gender, condition of chronic disease and use of medication, and to the sensitive analysis using different times of visits. The authors concluded that the association between acute respiratory inflammation and PM concentration of fine particulates depended on particle size, and suggested Aitken-mode particles may be the most responsible for this adverse health association.

Near roadway air pollution across a spatially extensive road and cycling network

This study investigates the variability in near-road concentrations of ultra-fine particles (UFP). Our results are based on a mobile data collection campaign conducted in 2012 in Montreal, Canada using instrumented bicycles and covering approximately 475 km of unique roadways. The spatial extent of the data collected included a diverse array of roads and land use patterns. Average concentrations of UFP per roadway segment varied greatly across the study area (1411-192,340 particles/cm(3)) as well as across the different visits to the same segment. Mixed effects linear regression models were estimated for UFP (R(2) = 43.80%), incorporating a wide range of predictors including land-use, built environment, road characteristics, and meteorology. Temperature and wind speed had a large negative effect on near-road concentrations of UFP. Both the day of the week and time of day had a significant effect with Tuesdays and afternoon periods positively associated with UFP. Since UFP are largely associated with traffic emissions and considering the wide spatial extent of our data collection campaign, it was impossible to collect traffic volume data. For this purpose, we used simulated data for traffic volumes and speeds across the region and observed a positive effect for volumes and negative effect for speed. Finally, proximity to truck routes was also associated with higher UFP concentrations.

Temporal distribution of air quality related to meteorology and road traffic in Madrid

The impact of climatology--air temperature, precipitation and wind speed--and road traffic--volume, vehicle speed and percentage of heavy-duty vehicles (HDVs)--on air quality in Madrid was studied by estimating the effect for each explanatory variable using generalized linear regression models controlling for monthly variations, days of week and parameter levels. Every 1 m/s increase in wind speed produced a decrease in PM10 concentrations by 10.3% (95% CI 12.6-8.6) for all weekdays and by 12.4% (95% CI 14.9-9.8) for working days (up to the cut-off of 2.4 m/s). Increases of PM10 concentrations due to air temperature (7.2% (95% CI 6.2-8.3)) and traffic volume (3.3% (95% CI 2.9-3.8)) were observed at every 10 °C and 1 million vehicle-km increases for all weekdays; oppositely, slight decreases of PM10 concentrations due to percentage of HDVs (3.2% (95% CI 2.7-3.7)) and vehicle speed (0.7% (95% CI 0.6-0.8)) were observed at every 1% and 1 km/h increases. Stronger effects of climatology on air quality than traffic parameters were found.

Characterization and estimation of human airway deposition of size-resolved particulate-bound trace elements during a recent haze episode in Southeast Asia

Toxic elements present in airborne particulate matter (PM) are associated with human health effects; however, their toxic characteristics depend on the source of their origins and their concentrations in ambient air. Twenty four elements (Al, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, K, Li, Mg, Mn, Na, Ni, Pb, Se, Sr, Te, Tl, and Zn) in 12 different size fractions of PM ranging from 10 nm to 10 μm were characterized in Singapore during two different atmospheric conditions (smoke haze and non-haze periods) in 2012 for the first time. In addition, their possible sources were identified based on backward air trajectory analysis and principal component analysis (PCA). The health implications of inhalable particles were assessed using a human airway deposition model, the Multiple-Path Particle Dosimetry model (MPPD). The results concerning particle-bound trace elements are interpreted in terms of coarse (PM2.5-10), fine (PM2.5), ultrafine (PM0.01-0.1, 0.01 μm < Dp < 0.10 μm), and nano (PM0.01-0.056, 0.01 μm < Dp < 0.056 μm) particles. The ratios of elemental concentrations measured between the smoke haze episode and the non-haze period in coarse, fine, ultrafine, and nano particles varied from 1.2 (Bi) to 6.6 (Co). Both the PCA and backward trajectory analysis revealed that trans-boundary biomass-burning emissions from Indonesia were primarily responsible for enhanced concentrations of particulate-bound elements during the smoke haze episode. The particle depositions in the respiratory system were higher during the smoke haze episode compared to the non-haze period. The study finds that ultrafine and nano particles present in the atmosphere have higher tendencies to be deposited into the deeper parts of the respiratory system, compared to coarse and fine particles.

Particle emission from heavy-duty engine fuelled with blended diesel and biodiesel

In this study, particulate matter (PM) were characterized from a place impacted by heavy-duty vehicles (Bus Station) fuelled with diesel/biodiesel fuel blend (B3) in the city of Londrina, Brazil. Sixteen priority polycyclic aromatic hydrocarbons (PAH) concentrations were analyzed in the samples by their association with atmospheric PM, mass size distributions and major ions (fluorite, chloride, bromide, nitrate, phosphate, sulfate, nitrite, oxalate; fumarate, formate, succinate and acetate; lithium, sodium, potassium, magnesium, calcium and ammonium). Results indicate that major ions represented 21.2% particulate matter mass. Nitrate, sulfate, and ammonium, respectively, presented the highest concentration levels, indicating that biodiesel may also be a significant source for these ions, especially nitrate. Dibenzo[a,h]anthracene and indeno[1,2,3,-cd]pyrene were the main PAH found, and a higher fraction of PAH particles was found in diameters lower than 0.25 μm in Londrina bus station. The fine and ultrafine particles were dominant among the PM evaluated, suggesting that biodiesel decreases the total PAH emission. However, it does also increase the fraction of fine and ultrafine particles when compared to diesel.