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.

Air pollution is well recognized as a central player in cardiovascular disease. Exhaust particulate from diesel engines (DEP) is rich in nanoparticles and may contribute to the health effects of particulate matter in the environment. Moreover, diesel soot emitted by modern engines denotes defective surfaces alongside chemically-reactive sites increasing soot cytotoxicity. We recently demonstrated that engineered nanoparticles can cross the air/blood barrier and are capable to reach the heart. We hypothesize that DEP nanoparticles are pro-arrhythmogenic by direct interaction with cardiac cells. We evaluated the internalization kinetics and the effects of DEP, collected from Euro III (DEPe3, in the absence of Diesel Particulate Filter, DPF) and Euro IV (DEPe4, in the presence of DPF) engines, on alveolar and cardiac cell lines and on in situ rat hearts following DEP tracheal instillation. We observed significant differences in DEP size, metal and organic compositions derived from both engines. DEPe4 comprised ultrafine particles (<100 nm) and denoted a more pronounced toxicological outcome compared to DEPe3. In cardiomyocytes, particle internalization is fastened for DEPe4 compared to DEPe3. The in-vivo epicardial recording shows significant alteration of EGs parameters in both groups. However, the DEPe4-instilled group showed, compared to DEPe3, a significant increment of the effective refractory period, cardiac conduction velocity, and likelihood of arrhythmic events, with a significant increment of membrane lipid peroxidation but no increment in inflammation biomarkers. Our data suggest that DEPe4, possibly due to ultrafine nanoparticles, is rapidly internalized by cardiomyocytes resulting in an acute susceptibility to cardiac electrical disorder and arrhythmias that could accrue from cellular toxicity. Since the postulated transfer of nanoparticles from the lung to myocardial cells has not been investigated it remains open whether the effects on the cardiovascular function are the result of lung inflammatory reactions or due to particles that have reached the heart.

NO₂ oxidation of soot exhausted from engines is more efficient than O₂ under low-temperature conditions, and is crucial for diesel particulate filter to control soot pollution. To explore the principle behind accelerating soot oxidation by NO₂, this paper uses density functional theory to reveal soot oxidation process by NO₂. This study contributes to understanding rules of soot oxidation by NO₂ and perfecting soot oxidation models to develop soot emission control technologies. Results show that NO₂ oxidation of pyrene radical involves three steps. Firstly, NO₂ attacks the C∗ atom to form –C (NO₂) with reaction energy of 306.3 kJ/mol, which decomposes to produce a –C (O) compound. Secondly, another NO₂ molecule climbs over an energy barrier of 8.8 kJ/mol, and changes into a –C (ONO₂) intermediate on –C (O). Finally, the N or O atom of NO₂ attacks –C (O) for a second time to help open aromatic ring for releasing CO or CO₂. Further decomposition of –C (NO₂) and –C (ONO₂) requires activation energies of 81.6 kJ/mol, 75.7 kJ/mol, and 53.5 kJ/mol, respectively, on preferential pathways. Calculations prove that attacks of O atom from NO₂ on C∗ help open the aromatic ring more efficiently than N atom.

Addressing the presence of rutile nanoparticles (NPs) in the air is a work in progress, and the development of methodologies for the identification of NPs in atmospheric dust is essential for the assessment of its toxicological effects. To address this issue, we selected the fast growing desertic city of Hermosillo in northern Mexico. Road dust (n = 266) and soils (n = 10) were sampled and bulk Ti-contents were tested by portable X-ray fluorescence. NPs were extracted from atmospheric dust by PM₁.₀-PTFE filters and further characterized by Confocal Raman Microscopy, Energy-dispersive X-ray spectroscopy (EDS) coupled to Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM). Results showed (i) the average concentration of Ti in road dust (3447 mg kg⁻¹) was similar to natural values and worldwide urban dusts; (ii) the bulk geochemistry was not satisfactory for Ti-NPs identification; (iii) 76% of the total extracted PM₁.₀ sample corresponded to NPs; (iv) mono-microaggregates of rutile NPs were identified; (v) ubiquitous polycyclic aromatic hydrocarbons (PAHs) were linked to NPs. The genotoxicity of rutile and PAHs, in connection with NPs content, make us aware of a crucial emerging environmental issue of significant health concern, justifying further research in this field.

Microfibres are one of the most ubiquitous particulate pollutants, occurring in all environmental compartments. They are often assumed to be microplastics, but include natural as well as synthetic textile fibres and are perhaps best treated as a separate class of pollutants given the challenges they pose in terms of identification and contamination. Microfibres have been largely ignored by traditional methods used to sample floating microplastics at sea, which use 300–500 μm mesh nets that are too coarse to sample most textile fibres. There is thus a need for a consistent set of methods for sampling microfibres in seawater. We processed bulk water samples through 0.7–63 μm filters to collect microfibres in three ocean basins. Fibre density increased as mesh size decreased: 20 μm mesh sampled 41% more fibres than 63 μm, and 0.7 μm filters sampled 44% more fibres than 25 μm mesh, but mesh size (20–63 μm) had little effect on the size of fibres retained. Fibre density decreased with sample volume when processed through larger mesh filters, presumably because more fibres were flushed through the filters. Microfibres averaged 2.5 times more abundant at the sea surface than in water sampled 5 m sub-surface. However, the data were noisy; counts of replicate 10-L samples had low repeatability (0.15–0.36; CV = 56%), suggesting that single samples provide only a rough estimate of microfibre abundance. We propose that sampling for microfibres should use a combination of <1 μm and 20–25 μm filters and process multiple samples to offset high within-site variability in microfibre densities.

This study assessed the sources, magnitudes, and chemical compositions of household air pollution (HAP) and personal exposure in traditional Tibetan households. We measured 24-h personal exposures to PM₂.₅ and kitchen area black carbon (BC) concentrations, using MicroPEMs and microAeths, respectively. Particulate polycyclic aromatic hydrocarbon (PAH) and inorganic element concentrations were quantified via post analyses of a subset of MicroPEM sample filters. Household surveys regarding participant demographics, cookstove usage, household fuel, cooking behaviors, and lifestyles were collected. The results reaffirm that burning firewood and yak dung, mainly for cooking, leads to high PM₂.₅ and BC exposures. The geometric mean concentration (95% confidence interval, CI) was 74.3 (53.6, 103) μg/m³ for PM₂.₅ and the arithmetic mean ± standard deviation (SD) concentration was 4.90 ± 5.01 μg/m³ for BC and 292 ± 364 ng/m³ for 15 identified PAHs, respectively. The arithmetic mean ± SD of mass concentrations of 24 detected elements ranged from 0.76 ± 0.91 ng/m³ (Co) to 1.31 ± 1.35 μg/m³ (Si). Our statistical analyses further illustrated that the high concentrations of PM₂.₅, BC, and most PAHs and metals, are significantly associated with nomadic village, poorer stove/chimney conditions and yak dung burning. The results from this study show that substantial HAP exposure is prevalent in Tibetan households and requires immediate actions to mitigate potential negative environmental health impacts. The observational data also revealed the possibility of other important sources (e.g. traffic and garbage burning) that have contributed to personal exposures. These findings improve our understanding of HAP exposure and potential health risks in Tibetan communities and will help inform strategies for reducing HAP in Tibetan households and beyond.

Emissions of major reactive nitrogen compounds, including nitric oxide (NO), nitrogen dioxide (NO₂) and ammonia (NH₃), from heavy-duty diesel vehicles (HDDVs) place substantial pressure on air quality for many large cities in China. To control nitrogen oxide (NOX) emissions from HDDVs, selective catalytic reduction (SCR) systems have been widely used since the China IV standards. To investigate the impacts of aftertreatment technologies and driving conditions on real-world emissions of reactive nitrogen compounds, a portable emissions measurement system was employed to test eighteen heavy-duty diesel trucks in China. The results showed that the China IV and China V HDDVs with appropriate SCR functionality could reduce NOX emissions by 36% and 53%, respectively, compared to the China III results, although their real-world emissions were still higher than the corresponding emission limits for regulatory engine tests. For these HDDVs, five samples were tested with NH₃ emissions, ranging from 1.67 ppm to 51.49 ppm. The NH₃ emission rates tended to significantly increase under high-speed driving conditions. The results indicate that the current SCR technology may have certain risks in exceeding the future China VI NH₃ limit. However, five China IV/V HDDVs were found to have SCR temperature sensors that were intentionally tampered with, resulting in comparable or even higher NOX emissions and zero NH₃ emissions. Increased NO₂ emissions due to the adoption of diesel oxidation catalysts and diesel particulate filters were also found from our experiments. This study highlights the importance of enhancing in-use compliance requirements and eliminating aftertreatment tampering for China IV and China V HDDVs.

The occurrence and concentrations of a wide range of organic phosphates (OPEs) in vehicle's exhaust (VPM), ambient air particulate matter (APM), and soil of various urban environments were researched. VPM comes from passenger cars, commercial vehicles, marine and bus engines emitted in New European Driving Cycle tests whereas APM was sampled in several sites of the Upper Silesia region (Poland). APM and VPM collected on filters and soil from the same locations as APM sampling sites were extracted with dichloromethane and extracts analyzed by gas chromatography-mass spectrometry. The OPEs found include aryl phosphates such as triphenyl phosphate (TPhP) and tricresyl phosphate (TCP), alkyl phosphates - triethyl phosphate (TEP), tripropyl phosphate (TPP), tributyl phosphate (TBP) and tri(butoxyethyl)phosphate (TBEP), and alkylchlorinated phosphates including tris-(2-chloroisopropyl) phosphate (TCiPP) and tris(2-chloroethyl) phosphate (TCEP). Occurrence and concentrations of these compounds in the PM investigated are highly variable. It was found that total concentrations in APM are directly related to traffic density in particular sites of the urban environment and a style of a vehicle driving. The highest emission of OPEs was found at a crossroad and city center sites where traffic is the densest and vehicles stops and starts are frequent. Village and residential areas were less exposed to OPEs emission. Since OPEs concentrations show exponential correlations to each other also human exposure to these compounds increases exponentially with increasing traffic density. High TEP and TBP level is tentatively proposed as an indicator of emission from petrol-fueled cars. Concentrations of OPEs in some soil are related to their emission to the air and resistance to degradation of a particular compound since only the most resistant TCiPP and TPhP were identified in soil extracts.

Microplastic pollution within the marine environment is of pressing concern globally. Accordingly, spatial monitoring of microplastic concentrations, composition and size distribution may help to identify sources and entry pathways, and hence allow initiating focused mitigation. Spatial distribution patterns of microplastics were investigated in two compartments of the southern North Sea by collecting sublittoral sediment and surface water samples from 24 stations. Large microplastics (500−5000 μm) were detected visually and identified using attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy. The remaining sample was digested enzymatically, concentrated onto filters and analyzed for small microplastics (11−500 μm) using Focal Plane Array (FPA) FTIR imaging. Microplastics were detected in all samples with concentrations ranging between 2.8 and 1188.8 particles kg−1 for sediments and 0.1–245.4 particles m−3 for surface waters. On average 98% of microplastics were <100 μm in sediments and 86% in surface waters. The most prevalent polymer types in both compartments were polypropylene, acrylates/polyurethane/varnish, and polyamide. However, polymer composition differed significantly between sediment and surface water samples as well as between the Frisian Islands and the English Channel sites. These results show that microplastics are not evenly distributed, in neither location nor size, which is illuminating regarding the development of monitoring protocols.

Ambient concentrations of fine particulate matter (PM₂.₅) concentration is often used as an exposure surrogate to estimate PM₂.₅ health effects in epidemiological studies. Ignoring the potential variations in the amount of outdoor PM₂.₅ infiltrating into indoor environments will cause exposure misclassification, especially when people spend most of their time indoors. As it is not feasible to measure the PM₂.₅ infiltration factor (Fᵢₙf) for each individual residence, we aimed to build models for residential PM₂.₅Fᵢₙf prediction and to evaluate seasonal Fᵢₙf variations among residences. We repeated collected paired indoor and outdoor PM₂.₅ filter samples for 7 continuous days in each of the three seasons (hot, cold and transitional seasons) from 48 typical homes of Shanghai, China. PM₂.₅-bound sulfur on the filters was measured by X-ray fluorescence for PM₂.₅Fᵢₙf calculation. We then used stepwise-multiple linear regression to construct season-specific models with climatic variables and questionnaire-based predictors. All models were evaluated by the coefficient of determination (R²) and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV). The 7-day mean (±SD) of PM₂.₅Fᵢₙf across all observations was 0.83 (±0.18). Fᵢₙf was found higher and more varied in transitional season (12–25 °C) than hot (>25 °C) and cold (<12 °C) seasons. Air conditioning use and meteorological factors were the most important predictors during hot and cold seasons; Floor of residence and building age were the best transitional season predictors. The models predicted 60.0%–68.4% of the variance in 7-day averages of Fᵢₙf, The LOOCV analysis showed an R² of 0.52 and an RMSE of 0.11. Our finding of large variation in residential PM₂.₅Fᵢₙf between seasons and across residences within season indicated the important source of outdoor-generated PM₂.₅ exposure heterogeneity in epidemiologic studies. Our models based on readily available data may potentially improve the accuracy of estimates of the health effects of PM₂.₅ exposure.