Incomplete combustion processes in diesel engines produce particulate matter (PM) that significantly contributes to air pollution. Currently, there remains a knowledge gap in relation to the physical and chemical characteristics and also the biological reactivity of the PM emitted from old- and new-generation diesel vehicles. In this study, the emissions from a Euro 3 diesel vehicle were compared to those from a Euro 6 car during the regeneration of a diesel particulate filter (DPF). Different driving cycles were used to collect two types of diesel exhaust particles (DEPs). The particle size distribution was monitored using an engine exhaust particle sizer spectrometer and an electrical low-pressure impactor. Although the Euro 6 vehicle emitted particulates only during DPF regeneration that primarily occurs for a few minutes at high speeds, such emissions are characterized by a higher number of ultrafine particles (<0.1 μm) compared to those from the Euro 3 diesel vehicle. The emitted particles possess different characteristics. For example, Euro 6 DEPs exhibit a lower PAH content than do Euro 3 samples; however, they are enriched in metals that were poorly detected or undetected in Euro 3 emissions. The biological effects of the two DEPs were investigated in human bronchial BEAS-2B cells exposed to 50 μg/mL of PM (corresponding to 5.2 μg/cm²), and the results revealed that Euro 3 DEPs activated the typical inflammatory and pro-carcinogenic pathways induced by combustion-derived particles, while Euro 6 DEPs were less effective in regard to activating such biological responses. Although further investigations are required, it is evident that the different in vitro effects elicited by Euro 3 and Euro 6 DEPs can be correlated with the variable chemical compositions (metals and PAHs) of the emitted particles that play a pivotal role in the inflammatory and carcinogenic potential of airborne PM.

Emerging evidence witnesses the association of air pollution exposure with sleep disorders or the risk of obstructive sleep apnea (OSA); however, the results are not consistent. OSA patients with or without a low arousal threshold (LAT) have different pathology and therapeutic schemes. No study has evaluated the potential diverse effects of air pollution on the phenotypes of OSA. The current study aimed to evaluate the associations of short-term and long-term exposure to air pollution with sleep-disordered measures and OSA phenotypes. This cross-sectional study consisted of 4634 participants from a sleep center in Taipei from January 2015 to April 2019. The personal exposure to ambient PM₂.₅ and NO₂ was assessed by a spatial-temporal model. Overnight polysomnography was used to measure the sleep parameters. According to a developed clinical tool, we defined the low arousal threshold (LAT) and identified the OSA patients with or without LAT. We applied a generalized linear model and multinomial logistic regression model to estimate the change of sleep measures and risk of the OSA phenotypes, respectively, associated with an interquartile range (IQR) increment of personal pollution exposure after adjusting for the essential confounders. In the single-pollutant model, we observed the associations of NO₂ with sleep-disordered measures by decreasing the total sleep time, sleep efficiency, extending the time of wake after sleep onset, and the association of NO₂ with the increased risk of LAT OSA by around 15%. The two-pollutant model with both long-term and short-term exposures confirmed the most robust associations of long-term NO₂ exposure with sleep measures. An IQR increment of NO₂ averaged over the past year (6.0 ppb) decreased 3.32 min of total sleep time and 0.85% of sleep efficiency. Mitigating exposure to air pollution may improve sleep quality and reduce the risk of LAT OSA.

The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NOX, NO₂, O₃, PM₁₀, PM₂.₅, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM₂.₅, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM₂.₅, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.

Numerous epidemiological studies have shown a close relationship between outdoor air pollution and increased risks for cancer, infection, and cardiopulmonary diseases. However, very few studies have investigated the potential health effects of coexposure to airborne particulate matter (PM) and bioaerosols through the transmission of infectious agents, particularly under the current circumstances of the coronavirus disease 2019 pandemic. In this study, we aimed to identify urinary metabolite biomarkers that might serve as clinically predictive or diagnostic standards for relevant diseases in a real-time manner. We performed an unbiased gas/liquid chromatography-mass spectroscopy (GC/LC-MS) approach to detect urinary metabolites in 92 samples from young healthy individuals collected at three different time points after exposure to clean air, polluted ambient, or purified air, as well as two additional time points after air repollution or repurification. Subsequently, we compared the metabolomic profiles between the two time points using an integrated analysis, along with Kyoto Encyclopedia of Genes and Genomes-enriched pathway and time-series analysis. We identified 33 and 155 differential metabolites (DMs) associated with PM and bioaerosol exposure using GC/LC-MS and follow-up analyses, respectively. Our findings suggest that 16-dehydroprogesterone and 4-hydroxyphenylethanol in urine samples may serve as potential biomarkers to predict or diagnose PM- or bioaerosol-related diseases, respectively. The results indicated apparent differences between PM- and bioaerosol-associated DMs at five different time points and revealed dynamic alterations in the urinary metabolic profiles of young healthy humans with cyclic exposure to clean and polluted air environments. Our findings will help in investigating the detrimental health effects of short-term coexposure to airborne PM and bioaerosols in a real-time manner and improve clinically predictive or diagnostic strategies for preventing air pollution-related diseases.

Lichens serve as important bioindicators of air pollution in cities. Here, we studied the diversity of epiphytic lichens in the urban area of Munich, Bavaria, southern Germany, to determine which factors influence species composition and diversity. Lichen diversity was quantified in altogether 18 plots and within each, five deciduous trees were investigated belonging to on average three tree species (range 1–5). Of the 18 plots, two were sampled in control areas in remote areas of southern Germany. For each lichen species, frequency of occurrence was determined in 10 quadrats of 100 cm² on the tree trunk. Moreover, the cover percentage of bryophytes was determined and used as a variable to represent potential biotic competition. We related our diversity data (species richness, Shannon index, evenness, abundance) to various environmental variables including tree traits, i.e. bark pH levels and species affiliation and air pollution data, i.e. NO₂ and SO₂ concentrations measured in the study plots. The SO₂ levels measured in our study were generally very low, while NO₂ levels were rather high in some plots. We found that the species composition of the epiphytic lichen communities was driven mainly by NO₂ pollution levels and all of the most common species in our study were nitrophilous lichens. Low NO₂ but high SO₂ values were associated with high lichen evenness. Tree-level lichen diversity and abundance were mainly determined by tree traits, not air pollution. These results confirm that ongoing NO₂ air pollution within cities is a major threat to lichen diversity, with non-nitrophilous lichens likely experiencing the greatest risk of local extinctions in urban areas in the future. Our study moreover highlights the importance of large urban green spaces for species diversity. City planners need to include large green spaces when designing urban areas, both to improve biodiversity and to promote human health and wellbeing.

Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM₂.₅, PM₁₀, NO₂, SO₂, O₃ and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O₃ had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O₃-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O₃ in the future.

Unplanned urbanization and heavy automobile use by the rapidly growing population contribute to a variety of environmental issues. Roadside plants can mitigate air pollution by modifying their enzymatic activity, physiological and anatomical traits. Plant enzymes, physiological and anatomical traits play an important role in adaptation and mitigation mechanisms against vehicular emissions. There is a significant gap in understanding of how plant enzymes and anatomical traits respond or how they participate in modulating the effect of vehicular emissions/air pollution. Modulation of leaf anatomical traits is also useful in regulating plant physiological behavior. Hence, the present study was conducted to evaluate the effects of vehicular pollution on the enzymatic activity, physiological, and anatomical traits of plant species that grow in forests (S1) and alongside roads (S2-1 km away from the S1 site) during different seasons. The present study examines four commonly found roadside tree species i.e. Grevillea robusta, Cassia fistula, Quercus leucotrichophora and Cornus oblonga. The study found that the activities of catalase and phenylalanine ammonium enzymes were higher in G. robusta species of roadside than control site (S1). Non-enzymatic antioxidants such as flavonoid and phenol were also found in higher concentrations in roadside tree species during the summer season. However, the measured values of physiological traits were higher in Q. leucotrichophora tree species of S1 during the summer season. When compared to the other species along the roadside, Q. leucotrichophora had the highest number of stomata and epidermal cells during the summer season. Hence, we found that tree species grown along the roadside adapted towards vehicular emissions by modulating their enzymatic, physiological, and anatomical traits to mitigate the effect of air pollution.

Several studies have reported an association between residential surrounding particulate matter with an aerodynamic diameter ≤2.5 μm (PM₂.₅) and coronary heart disease (CHD). However, the underlying biological mechanism remains unclear. To fill this research gap, this study enrolled a residentially stable sample of 942 patients with CHD and 1723 controls. PM₂.₅ concentration was obtained from satellite-based annual global PM₂.₅ estimates for the period 1998–2019. MicroRNA microarray and pathway analysis of target genes was performed to elucidate the potential biological mechanism by which PM₂.₅ increases CHD risk. The results showed that individuals exposed to high PM₂.₅ concentrations had higher risks of CHD than those exposed to low PM₂.₅ concentrations (odds ratio = 1.22, 95% confidence interval: 1.00, 1.47 per 10 μg/m³ increase in PM₂.₅). Systolic blood pressure mediated 6.6% of the association between PM₂.₅ and CHD. PM₂.₅ and miR-4726-5p had an interaction effect on CHD development. Bioinformatic analysis demonstrated that miR-4726-5p may affect the occurrence of CHD by regulating the function of RhoA. Therefore, individuals in areas with high PM₂.₅ exposure and relative miR-4726-5p expression have a higher risk of CHD than their counterparts because of the interaction effect of PM₂.₅ and miR-4726-5p on blood pressure.

Air pollution exposure is a public health emergency, which attributes globally to an estimated seven million deaths on a yearly basis We are all exposed to air pollutants, varying from ambient air pollution hanging over cities to dust inside the home. It is a mixture of airborne particulate matter and gases that can be subdivided into three categories based on particle diameter. The smallest category called PM₀.₁ is the most abundant. A fraction of the particles included in this category might enter the blood stream spreading to other parts of the body. As air pollutants can enter the body via the lungs and gut, growing evidence links its exposure to gastrointestinal and respiratory impairments and diseases, like asthma, rhinitis, respiratory tract infections, Crohn's disease, ulcerative colitis, and abdominal pain. It has become evident that there exists a crosstalk between the respiratory and gastrointestinal tracts, commonly referred to as the gut-lung axis. Via microbial secretions, metabolites, immune mediators and lipid profiles, these two separate organ systems can influence each other. Well-known immunomodulators and gut health stimulators are probiotics, prebiotics, together called synbiotics. They might combat air pollution-induced systemic inflammation and oxidative stress by optimizing the microbiota composition and microbial metabolites, thereby stimulating anti-inflammatory pathways and strengthening mucosal and epithelial barriers. Although clinical studies investigating the role of probiotics, prebiotics, and synbiotics in an air pollution setting are lacking, these interventions show promising health promoting effects by affecting the gastrointestinal- and respiratory tract. This review summarizes the current data on how air pollution can affect the gut-lung axis and might impact gut and lung health. It will further elaborate on the potential role of probiotics, prebiotics and synbiotics on the gut-lung axis, and gut and lung health.

The influences of weather and air pollutants on chronic obstructive pulmonary disease (COPD) have been well-studied. However, the heterogeneous effects of different influenza viral infections, air pollution and weather on COPD admissions and re-admissions have not been thoroughly examined. In this study, we aimed to elucidate the relationships between meteorological variables, air pollutants, seasonal influenza, and hospital admissions and re-admissions due to COPD in Hong Kong, a non-industrial influenza epicenter. A total number of 507703 hospital admissions (i.e., index admissions) and 301728 re-admission episodes (i.e., episodes within 30 days after the previous discharge) for COPD over 14 years (1998–2011) were obtained from all public hospitals. The aggregated weekly numbers were matched with meteorological records and outdoor air pollutant concentrations. Type-specific and all-type influenza-like illness positive (ILI+) rates were used as proxies for influenza activity. Generalized additive models were used in conjunction with distributed-lag non-linear models to estimate the associations of interest. According to the results, high concentrations of fine particulate matter, oxidant gases, and cold weather were strong independent risk factors of COPD outcomes. The cumulative adjusted relative risks exhibited a monotone increasing trend except for ILI+ B, and the numbers were statistically significant over the entire observed range of ILI+ total and ILI+ A/H3N2 when the reference rate was zero. COPD hospitalization risk from influenza infection was higher in the elderly than that in the general population. In conclusion, our results suggest that health administrators should impose clean air policies, such as strengthening emissions control on petrol vehicles, to reduce pollution from oxidant gases and particulates. An extension of the influenza vaccination program for patients with COPD may need to be encouraged: for example, vaccination may be included in hospital discharge planning, particularly before the winter epidemic.