The present investigation examined the impact of highways on the global dispersion patterns of metallic elements present in dust and snow. A total of 18 mixed snow samples were collected from both sides of the Moscow-Tambo-Astrakhan Caspian Highway by the end of the winter season. The analysis of the samples indicated the presence of 35 distinct chemical elements, where Al, Ba, Ca, Fe, K, Mg, Na, and Zn were identified as the primary contaminants. The primary area of pollution on the windward side originating from the road spans a distance of 20-40 meters, while on the leeward side, it extends to 10 meters. The data presented suggests that the metals found in highways exhibited variability in terms of their solubility in water and concentration. Our findings demonstrate that the predominant wind directions affect the dispersion of pollutants. Furthermore, it was observed that the region with a higher concentration of metal on the side of the road facing the wind had a thickness that was 2-3 times less than that of the opposite side. It is advisable to conduct a subsequent inquiry within the ensuing five years to obtain dependable data regarding the extent of metal pollution.

PM₂.₅ (fine particulate matter with aerodynamics diameter <2.5 μm) is the most important component of air pollutants, and has a significant impact on the atmospheric environment and human health. Using satellite remote sensing aerosol optical depth (AOD) to explore the hourly ground PM₂.₅ distribution is very helpful for PM₂.₅ pollution control. In this study, Himawari-8 AOD, meteorological factors, geographic information, and a new deep forest model were used to construct an AOD-PM₂.₅ estimation model in China. Hourly cross-validation results indicated that estimated PM₂.₅ values were consistent with the site observation values, with an R² range of 0.82–0.91 and root mean square error (RMSE) of 8.79–14.72 μg/m³, among which the model performance reached the optimum value between 13:00 and 15:00 Beijing time (R² > 0.9). Analysis of the correlation coefficient between important features and PM₂.₅ showed that the model performance was related to AOD and affected by meteorological factors, particularly the boundary layer height. Deep forest can detect diurnal variations in pollutant concentrations, which were higher in the morning, peaked at 10:00–11:00, and then began to decline. High-resolution PM₂.₅ concentrations derived from the deep forest model revealed that some cities in China are seriously polluted, such as Xi ‘an, Wuhan, and Chengdu. Our model can also capture the direction of PM₂.₅, which conforms to the wind field. The results indicated that due to the combined effect of wind and mountains, some areas in China experience PM₂.₅ pollution accumulation during spring and winter. We need to be vigilant because these areas with high PM₂.₅ concentrations typically occur near cities.

While the health impacts of larger particulate matter, such as PM₁₀ and PM₂.₅, have been studied extensively, research regarding ultrafine particles (UFPs or PM₀.₁) and particle surface area concentration (PSC) is lacking. This case-crossover study assessed the associations between exposure to PSC and UFP number concentration (UFPnc) and hospital admissions for cardiovascular diseases (CVDs) in New York State (NYS), 2013–2018. We used a time-stratified case-crossover design to compare the PSC and UFPnc levels between hospitalization days and control days (similar days without admissions) for each CVD case. We utilized NYS hospital discharge data to identify all CVD cases who resided in NYS. UFP simulation data from GEOS-Chem-APM, a state-of-the-art chemical transport model, was used to define PSC and UFPnc. Using a multi-pollutant model and conditional logistic regression, we assessed excess risk (ER)% per inter-quartile change of PSC and UFPnc after controlling for meteorological factors, co-pollutants, and time-varying variables. We found immediate and lasting associations between PSC and overall CVDs (lag0–lag0-6: ERs% (95% CI%) ranges: 0.4 (0.1,0.7) - 0.9 (0.7–1.2), and delayed and prolonged ERs%: 0.1–0.3 (95% CIs: 0.1–0.5) between UFPnc and CVDs (lag0-3–lag0-6). Exposure to larger PSC was associated with immediate ER increases in stroke, hypertension, and ischemic heart diseases (1.1%, 0.7%, 0.8%, respectively, all p < 0.05). The adverse effects of PSC on CVDs were highest among children (5–17 years old), in the fall and winter, and during cold temperatures. In conclusion, we found an immediate, lasting effects of PSC on overall CVDs and a delayed, prolonged impact of UFPnc. PSC was a more sensitive indicator than UFPnc. The PSC effects were higher among certain CVD subtypes, in children, in certain seasons, and during cold days. Further studies are needed to validate our findings and evaluate the long-term effects.

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.

The health effects of potentially toxic elements (PTEs) in airborne particulate matter (PM) are strongly dependent on their size distribution and dissolution. This study examined PTEs within nine distinct sizes of PM in a Chinese megacity, with a focus on their deposited and dissolved bioaccessibility in the human pulmonary region. A Multiple Path Particle Dosimetry (MPPD) model was used to estimate the deposited bioaccessibility, and an in-vitro experiment with simulated lung fluid was conducted for dissolved bioaccessibility. During the non-heating season, the dissolved bioaccessible fraction (DBF) of As, Cd, Co, Cr, Mn, Pb and V were greater in fine PM (aerodynamics less than 2.1 μm) than in coarse PM (aerodynamics between 2.1 and 10 μm), and vice versa for Ni. With the increased demand of heating, the DBF of Pb and As decreased in fine particle sizes, probably due to the presence of oxide/silicate compounds from coal combustion. Inhalation health risks based on the bioaccessible concentrations of PTEs displayed the peaks in <0.43 μm and 2.1–3.3 μm particulate sizes. The non-cancer risk was at an acceptable level (95th percentiles of hazard index (HI) was 0.49), but the cancer risk exceeded the threshold value (95th percentiles of total incremental lifetime cancer risk (TCR) was 8.91 × 10⁻⁵). Based on the results of uncertainty analysis, except for the exposure frequency, the total concentrations and DBF of As and Cr in <0.43 μm particle size segment have a greater influence on the uncertainty of probabilistic risk.

Construction workers on highway rehabilitation projects can be exposed to a combination of traffic- and construction-related emissions. To assess the personal exposure a worker experiences, a portable battery-operated Air Quality Device (AQD) was utilised to measure emissions during normal construction operations of a major road rehabilitation project. Emissions measured were nitrogen dioxide (NO₂), Total Volatile Organic Compounds (TVOCs) and Particulate Matter (PM₁₀, PM₂.₅, and PM₁). The objective of the paper is to document the hazardous emissions that construction workers may be exposed to and allow for a basis of informed decision making to mitigate the risks of a road construction project. Most critically, this article is designed to raise awareness of the potential impact to a worker's wellbeing as well as highlight the need for further research. Through statistical analysis, asphalt paving was identified as the most hazardous activity in terms of exposure relative to other activities. This activity was further assessed using discrete-time Markov chain Monte Carlo simulations with results indicating a high probability that workers may be exposed to greater hazardous emission concentrations than measured. Limiting the distance to the source of emissions, large-scale use of warm-mix asphalt and reducing the idling times of construction vehicles were identified as practical mitigation measures to reduce exposure and aid in achieving zero-harm objectives. Finally, it is found that males are more susceptible to long-term implications of hazardous emission inhalation and should be more aware if the scenarios they might work in expose them to this.

The inherent oxidation potential (OP) of atmospheric particulate matter has been shown to be an important metric in assessing the biological activity of inhaled particulate matter and is associated with the composition of PM₂.₅. The current study examined the chemical composition of 388 personal PM₂.₅ samples collected from students and guards living in urban and suburban areas of Beijing, and assessed the ability to predict OP from the calculated metrics of carcinogenic risk, represented by ELCR (excess lifetime cancer risk), non-carcinogenic risk represented by HI (hazard index), and the composition and sources of the particulate matter using multiple linear regression methods. The correlations between calculated ELCR and HI and the measured OP were 0.37 and 0.7, respectively. HI was a better predictor of OP than ELCR. The prediction models based on pollutants (Model_1) and pollution sources (Model_2) were constructed by multiple linear regression method, and Pearson correlation coefficients between the predicted results of Model_1 and Model_2 with the measured volume normalized OP are 0.81 and 0.80, showing good prediction ability. Previous investigations in Europe and North America have developed location-specific relationships between the chemical composition of particulate matter and OP using regression methods. We also examined the ability of relationships between OP and composition, sources, developed in Europe and North America, to predict the OP of particulate matter in Beijing from the composition and sources determined in Beijing. The relationships developed in Europe and North America provided good predictive ability in Beijing and it suggests that these relationships can be used to predict OP from the chemical composition measured in other regions of the world.

Particulate-filtering respirators (PFRs) have been recommended as a practical personal-level intervention to protect individuals from the health effects of particulate matter exposure. However, the cardiovascular benefits of PFRs including improvements in key surrogate endpoints remain unclear. We performed a systematic review and meta-analysis of randomized studies (wearing versus not wearing PFRs) reporting the effects on blood pressure (BP) and heart rate variability (HRV). The search was performed on January 3, 2022 to identify published papers until this date. We queried three English databases, including PubMed, Web of Science Core Collection and Scopus. Of 527 articles identified, eight trials enrolling 312 participants (mean age ± standard deviation: 36 ± 19.8; 132 female) met our inclusion criteria for analyses. Study participants wore PFRs from 2 to 48 h during intervention periods. Wearing PFRs was associated with a non-significant pooled mean difference of −0.78 mmHg (95% confidence interval [CI]: −2.06, 0.50) and −0.49 mmHg (95%CI: −1.37, 0.38) in systolic and diastolic BP (SBP and DBP). There was a marginally significant reduction of mean arterial pressure (MAP) by nearly 1.1 mmHg (95%CI: −2.13, 0.01). The use of PFRs was associated with a significant increase of 38.92 ms² (95%CI: 1.07, 76.77) in pooled mean high frequency (power in the high frequency band (0.15–0.4 Hz)) and a reduction in the low (power in the low frequency band (0.04–0.15Hz))-to-high frequency ratio [−0.14 (95%CI: −0.27, 0.00)]. Other HRV indices were not significantly changed. Our meta-analysis demonstrates modest or non-significant improvements in BP and many HRV parameters from wearing PFRs over brief periods. However, these findings are limited by the small number of trials as well as variations in experimental designs and durations. Given the mounting global public health threat posed by air pollution, larger-scale trials are warranted to elucidate more conclusively the potential health benefits of PFRs.

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.

The short-term alteration of peripheral cytokines may be an early adverse health effect of PM₂.₅ exposure and may be further associated with cardiovascular disease. We conducted a randomized, double-blind crossover trial using true or sham air filtration among 54 healthy college students in Beijing to investigate the potential benefits of short-term indoor air filtration and the adverse health effects of time-weighted personal PM₂.₅ exposure through inflammatory cytokines. The participants randomly received true or sham air filtration intervention for a week, and the treatment was changed after a two-week washout period. Peripheral blood samples were collected after each intervention period to measure 38 inflammatory cytokines. A linear mixed-effects model was applied to estimate the impacts of air purification or a 10 μg/m³ PM₂.₅ exposure increase on cytokines. Lag effects of PM₂.₅ exposure were analyzed using single-day and moving average lag models. Air filtration reduced indoor and time-weighted average personal PM₂.₅ concentrations by 69.0% (from 33.6 to 10.4 μg/m³) and 40.3% (from 40.6 to 24.3 μg/m³), respectively. We observed a significant association of PM₂.₅ exposure with growth-regulated alpha protein (GRO-α) of −11.3% (95%CI: 17.0%, −5.4%). In the lag models, significant associations between personal PM₂.₅ exposure and interleukin-1 receptor antagonist (IL-1Ra), monocyte chemotactic protein (MCP-1), and eotaxin were obtained at lag0, while associations with cytokines including vascular endothelial growth factor (VEGF), epidermal growth factor (EGF), fibroblast growth factor-2 (FGF-2), granulocyte colony-stimulating factor (G-CSF), macrophage inflammatory protein-1β (MIP-1β), IL-4, tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ) were noted at relatively long lagged exposure windows (lag5-lag6). No significant alteration in cytokines was observed under true air filtration intervention. Our study indicates the effectiveness of air filtration on indoor PM₂.₅ reduction. PM₂.₅ exposure may decrease GRO-α levels and change different cytokine levels time-varyingly. Further study is still needed to explore the mechanisms of PM₂.₅ exposure on the inflammatory response.