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.

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.

Fine particulate matter (PM₂.₅) has been associated with risk of oral and respiratory diseases. However, the biological mechanisms of adverse oral and respiratory health response to PM₂.₅ fluctuation have not been well characterized. This study aims to explore the relationships of PM₂.₅ with airway inflammation, salivary biomarkers and buccal mucosa microbiota. We performed a panel study among 40 college students involving 4 follow-ups from August to October 2021 in Hefei, Anhui Province, China. Health outcomes included fractional exhaled nitric oxide (FeNO), salivary biomarkers [C-reactive protein (CRP), cortisol, lysozyme and alpha-amylase] and buccal mucosa microbial diversity. Linear mixed-effect models were applied to explore the cumulative impacts of PM₂.₅ on health indicators. PM₂.₅ was positively correlated with FeNO, CRP, cortisol and alpha-amylase, while negatively with lysozyme. Per 10-μg/m³ increase in PM₂.₅ was linked to maximum increments in FeNO of 10.71% (95%CI: 2.01%, 19.41%) at lag 0–24 h, in CRP of 7.10% (95%CI: 5.39%, 8.81%) at lag 0–24 h, in cortisol of 1.25% (95%CI: 0.44%, 2.07%) at lag 0–48 h, and in alpha-amylase of 2.12% (95%CI: 0.53%, 3.71%) at lag 0–24 h, while associated with maximum decrement in lysozyme of 0.53% (95%CI: 0.12%, 0.95%) at lag 0–72 h. Increased PM₂.₅ was linked to reduction in the richness and evenness of buccal microbe and o_Bacillales and o_Bacteroidales were identified as differential microbes after PM₂.₅ inhalation. Bio-information analysis indicated that immunity system pathway was the most important enriched abundant process altered by PM₂.₅ exposure. In summary, short-term PM₂.₅ exposure may impair oral and respiratory health by inducing inflammatory and stress responses, weakening immune function and altering buccal mucosa microbial diversity.

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.

To elucidate the molecular composition and sources of organic aerosols in Central Asia, carbonaceous compounds, major ions, and 15 organic molecular tracers of total suspended particulates (TSP) were analyzed from September 2018 to August 2019 in Dushanbe, Tajikistan. Extremely high TSP concentrations (annual mean ± std: 211 ± 131 μg m⁻³) were observed, particularly during summer (seasonal mean ± std: 333 ± 183 μg m⁻³). Organic carbon (OC: 11.9 ± 7.0 μg m⁻³) and elemental carbon (EC: 5.1 ± 2.2 μg m⁻³) exhibited distinct seasonal variations from TSP, with the highest values occurring in winter. A high concentration of Ca²⁺ was observed (11.9 ± 9.2 μg m⁻³), accounting for 50.8% of the total ions and reflecting the considerable influence of dust on aerosols. Among the measured organic molecular tracers, levoglucosan was the predominant compound (632 ± 770 ng m⁻³), and its concentration correlated significantly with OC and EC during the study period. These findings highlight biomass burning (BB) as an important contributor to the particulate air pollution in Dushanbe. High ratios of levoglucosan to mannosan, and syringic acid to vanillic acid suggest that mixed hardwood and herbaceous plants were the main burning materials in the area, with softwood being a minor one. According to the diagnostic tracer ratio, OC derived from BB constituted a large fraction of the primary OC (POC) in ambient aerosols, accounting for an annual mean of nearly 30% and reaching 63% in winter. The annual contribution of fungal spores to POC was 10%, with a maximum of 16% in spring. Measurements of plant debris, accounting for 3% of POC, divulged that these have the same variation as fungal spores.

Inhalation exposure to fine particulate matter (PM₂.₅) represents a global concern due to the adverse effects in human health. In the last years, scientific community has been adopted the assessment of the PM₂.₅-bound pollutant fraction that could be released (bioaccessible fraction) in simulated lung fluids (SLFs) to achieve a better understanding of PM risk assessment and toxicological studies. Thus, bioaccessibility of 49 organic pollutants, including 18 polycyclic aromatic hydrocarbons (PAHs), 12 phthalate esters (PAEs), 11 organophosphorus flame retardants (OPFRs), 6 synthetic musk compounds (SMCs) and 2 bisphenols in PM₂.₅ samples was evaluated. The proposed method consists of a physiologically based extraction test (PBET) by using artificial lysosomal fluid (ALF) to obtain bioaccessible fractions, followed by a vortex-assisted liquid-liquid microextraction (VALLME) and a final analysis by programmed temperature vaporization-gas chromatography-tandem mass spectrometry (PTV-GC-MS/MS). The highest inhalation bioaccessibility ratio was found for bisphenol A (BPA) with an average of 83%, followed by OPFRs, PAEs and PAHs (with average bioaccessibilities of 68%, 41% and 34%, respectively). Correlations between PM₂.₅ composition (major ions, trace metals, equivalent black carbon (eBC) and UV-absorbing particulate matter (UVPM)) and bioaccessibility ratios were also assessed. Principal Component Analysis (PCA) suggested that PAHs, PAES and OPFRs bioaccessibility ratios could be positively correlated with PM₂.₅ carbonaceous content. Furthermore, both inverse and positive correlations on PAHs, PAEs and OPFRs bioaccessibilites could be accounted for some major ions and metal (oid)s associated to PM₂.₅, whereas no correlations comprising considered PM₂.₅ major ions and metal (oid)s contents and BPA bioaccessibility was observed. In addition, health risk assessment of target PM₂.₅-associated PAHs via inhalation was assessed in the study area considering both total and bioaccessible concentrations, being averaged human health risks within the safe carcinogenic and non-carcinogenic levels.

Fine particulate matter 2.5 (PM2.5) exposure leads to the progress of pulmonary disease. It has been reported that N6-methyladenosine (m6A) modification was involved in various biological processes and diseases. However, the critical role of m6A modification in pulmonary disease during PM2.5 exposure remains elusive. Here, we revealed that lung inflammation and mucus production caused by PM2.5 were associated with m6A modification. Both in vivo and in vitro assays demonstrated that PM2.5 exposure elevated the total level of m6A modification as well as the methyltransferase like 3 (METTL3) expression. Integration analysis of m6A RNA immunoprecipitation-seq (meRIP-seq) and RNA-seq discovered that METTL3 up-regulated the expression level and the m6A modification of Interleukin 24 (IL24). Importantly, we explored that the stability of IL24 mRNA was enhanced due to the increased m6A modification. Moreover, the data from qRT-PCR showed that PM2.5 also increased YTH N6-Methyladenosine RNA Binding Protein 1 (YTHDF1) expression, and the up-regulated YTHDF1 augmented IL24 mRNA translation efficiency. Down-regulation of Mettl3 reduced Il24 expression and ameliorated the pulmonary inflammation and mucus secretion in mice exposed to PM2.5. Taken together, our finding provided a comprehensive insight for revealing the significant role of m6A regulators in the lung injury via METTL3/YTHDF1-coupled epitranscriptomal regulation of IL24.

Individual-level studies with adjustment for important COVID-19 risk factors suggest positive associations of long-term air pollution exposure (particulate matter and nitrogen dioxide) with COVID-19 infection, hospitalisations and mortality. The evidence, however, remains limited and mechanisms unclear. We aimed to investigate these associations within UK Biobank, and to examine the role of underlying chronic disease as a potential mechanism. UK Biobank COVID-19 positive laboratory test results were ascertained via Public Health England and general practitioner record linkage, COVID-19 hospitalisations via Hospital Episode Statistics, and COVID-19 mortality via Office for National Statistics mortality records from March–December 2020. We used annual average outdoor air pollution modelled at 2010 residential addresses of UK Biobank participants who resided in England (n = 424,721). We obtained important COVID-19 risk factors from baseline UK Biobank questionnaire responses (2006–2010) and general practitioner record linkage. We used logistic regression models to assess associations of air pollution with COVID-19 outcomes, adjusted for relevant confounders, and conducted sensitivity analyses. We found positive associations of fine particulate matter (PM₂.₅) and nitrogen dioxide (NO₂) with COVID-19 positive test result after adjustment for confounders and COVID-19 risk factors, with odds ratios of 1.05 (95% confidence intervals (CI) = 1.02, 1.08), and 1.05 (95% CI = 1.01, 1.08), respectively. PM 2.5 and NO 2 were positively associated with COVID-19 hospitalisations and deaths in minimally adjusted models, but not in fully adjusted models. No associations for PM₁₀ were found. In analyses with additional adjustment for pre-existing chronic disease, effect estimates were not substantially attenuated, indicating that underlying chronic disease may not fully explain associations. We found some evidence that long-term exposure to PM₂.₅ and NO₂ was associated with a COVID-19 positive test result in UK Biobank, though not with COVID-19 hospitalisations or deaths.

Considerable investigations have been carried out to address the relationship between ambient fine particulate matter (PM₂.₅) and blood pressure (BP) in patients with hypertension. However, few studies have explored the influence of PM₂.₅ and its constituents on Trimethylamine N-oxide (TMAO), an established risk factor for hypertension and cardiovascular disease (CVD), particularly in severely air-polluted areas. To explore the potential impact of PM₂.₅ constituents on BP, plasma hormones, and TMAO, a panel study was conducted to investigate changes in BP, plasma hormones, and TMAO in response to ambient air pollution exposure in stage 1 hypertensive young adults. Linear mixed effect models were used to estimate the cumulative effects of fine particulate matters (PM₂.₅) and its constituents on BP, plasma hormones and TMAO. We found that one interquartile range (IQR) (35 μg/m³) increase in 0–1 day moving-average PM₂.₅ concentrations was statistically significantly associated with elevated systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) with estimated values of 0.13 (95% confidence interval (CI): 0.03 to 0.23) mmHg, 0.18 (95% CI: 0.08 to 0.28) mmHg, and 0.17 (95% CI: 0.09 to 0.26) mmHg, respectively. Hormone disturbance in the renin-angiotensin-aldosterone system was also associated with PM₂.₅ exposure. Elevated TMAO levels with an IQR increase for 0–4, 0–5, 0–6 moving-average concentrations of PM₂.₅ were found, and the increased values ranged from 26.28 (95% CI: 2.92 to 49.64) to 60.78 (31.95–89.61) ng/ml. More importantly, the PM₂.₅-bound metal constituents, such as manganese (Mn), titanium (Ti), and selenium (Se) showed robust associations with elevated BP and plasma TMAO levels. This study demonstrates associations between PM₂.₅ metal constituents and increased BP, changes in plasma hormones and TMAO, in stage 1 hypertensive young adults. Source control, aiming to reduce the emission of PM₂.₅-bound metals should be implemented to reduce the risk of hypertension and CVD.

India struggles with frequent exceedances of the ambient air quality standard for particulate matter and benzene. In the past two decades, India has made considerable progress in tackling indoor air pollution, by phasing out kerosene lamps, and pushing biofuel using households towards Liquefied Petroleum Gas (LPG) usage. In this study, we use updated emission inventories and trends in residential fuel consumption, to explore changes in the contribution of different sectors towards India's largest air pollution problem. We find that residential fuel usage is still the largest air pollution source, and that the <10% households using cow dung as cooking fuel contribute ∼50% of the residential PM₂.₅ emissions. However, if current trends persist, residential biofuel usage in India is likely to be phased out by 2035. India's renewable energy policies are likely to reduce emissions in the heat and electricity sector, and manufacturing industries, in the mid-term. PM₂.₅ emissions from open waste burning, on the other hand, hardly changed in the decade from 2010 to 2020. We conclude that without strong policies to promote recycling and upcycling of non-biodegradable waste, and the conversion of biodegradable waste to biogas, open waste burning is likely to become India's largest source of air pollution by 2035. While our study is limited to India, our findings are of relevance for other countries in the global South suffering from similar waste management challenges.