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.

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.

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.

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 consequence of the lockdowns implemented to address the COVID-19 pandemic on human health damage due to air pollution and other environmental issues must be better understood. This paper analyses the effect of reducing energy demand on the evolution of environmental impacts during the occurrence of 2020-lockdown periods in Italy, with a specific focus on life expectancy. An energy metabolism analysis is conducted based on the life cycle assessment (LCA) of all monthly energy consumptions, by sector, category and province area in Italy between January 2015 to December 2020. Results show a general decrease (by ∼5% on average) of the LCA midpoint impact categories (global warming, stratospheric ozone depletion, fine particulate matter formation, etc.) over the entire year 2020 when compared to past years. These avoided impacts, mainly due to reductions in fossil energy consumptions, are meaningful during the first lockdown phase between March and May 2020 (by ∼21% on average). Regarding the LCA endpoint damage on human health, ∼66 Disability Adjusted Life Years (DALYs) per 100,000 inhabitants are estimated to be saved. The analysis shows that the magnitude of the officially recorded casualties is substantially larger than the estimated gains in human lives due to the environmental impact reductions. Future research could therefore investigate the complex cause-effect relationships between the deaths occurred in 2020 imputed to COVID-19 disease and co-factors other than the SARS-CoV-2 virus.

Rapid economic growth, industrialization, and urbanization have caused frequent air pollution events in East Asia over the last few decades. Recently, aerosol data from geostationary satellite sensors have been used to monitor ground-level particulate matter (PM) concentrations hourly. However, many studies have focused on using historical datasets to develop PM estimation models, often decreasing their predictability for unseen data in new days. To mitigate this problem, this study proposes a novel real-time learning (RTL) approach to estimate PM with aerodynamic diameters of <10 μm (PM₁₀) and <2.5 μm (PM₂.₅) using hourly aerosol data from the Geostationary Ocean Color Imager (GOCI) and numerical model outputs for daytime conditions over Northeast Asia. Three schemes with different weighting strategies were evaluated using 10-fold cross-validation (CV). The RTL models, which considered both concentration and time as weighting factors (i.e., Scheme 3) yielded consistent improvement for 10-fold CV performance on both hourly and monthly scales. The real-time calibration results for PM₁₀ and PM₂.₅ were R² = 0.97 and 0.96, and relative root mean square error (rRMSE) = 12.1% and 12.0%, respectively, and the 10-fold CV results for PM₁₀ and PM₂.₅ were R² = 0.73 and 0.69 and rRMSE = 41.8% and 39.6%, respectively. These results were superior to results from the offline models in previous studies, which were based on historical data on an hourly scale. Moreover, we estimated PM concentrations in the ocean without using land-based variables, and clearly demonstrated the PM transport over time. Because the proposed models are based on the RTL approach, the density of in-situ monitoring sites could be a major uncertainty factor. This study identified that a high error occurred in low-density areas, whereas a low error occurred in high-density areas. The proposed approach can be operated to monitor ground-level PM concentrations in real-time with uncertainty analysis to ensure optimal results.

We investigated the biological response of soluble organic fraction (SOF) and water-soluble fraction (WSF) extracted from particulate matter (PM) emitted by an automotive diesel engine operating in a representative urban driving condition. The engine was fueled with ultra-low sulfur diesel (ULSD), and its binary blends by volume with 13% of butanol (Bu13), and with hydrotreated vegetable oil (HVO) at 13% (HVO13) and 20% (HVO20). Cytotoxicity, genotoxicity, oxidative DNA damage and ecotoxicity tests were carried out, and 16 polycyclic aromatic hydrocarbons (PAH) expressed as tbenzo(a)pyrene total toxicity equivalent (BaP-TEQ) were also analyzed. The Hepatocarcinoma epithelial cell line (HepG2) was exposed to SOF for 24 h and analyzed using comet assay, with the inclusion of formamidopyrimidine DNA glycosylase (FPG) and endonuclease III (Endo III) to recognize oxidized DNA bases. The WSF was evaluated through acute ecotoxicity tests with the aquatic microcrustacean Daphnia pulex (D. Pulex). Results showed that there was no cytotoxic activity for all tested SOF concentrations. Genotoxic responses by all the SOF samples were at same level, except for the HVO13 which was weaker in the absence of the enzymes. The addition of the FPG and Endo III enzymes resulted in a significant increase in the comet tail, indicating that the DNA damage from SOF for all tested fuel blends involves oxidative damage including a higher level of oxidized purines for ULSD and Bu13 in comparison with HVO blends, but the oxidized pyrimidines for HVO blends were slightly higher compared to Bu13. The WSF did not show acute ecotoxicity for any of the fuels. Unlike other samples, Bu13-derived particles significantly increase the BaP-TEQ. The contribution to the genotoxic activity and oxidative DNA from SOF was not correlated to BaP-TEQ, which means that the biological activity of PM might be affected also by other toxic compounds present in particulate phase.

Engine start-stop (S&S) technology has been substantially incorporated into modern vehicles to save fuel during idling in congested urban areas because fuel economy regulations have become more stringent. However, the potential for increasing particle emissions after engine restarts, especially in cold environments, is of great concern. To investigate the effects of S&S systems on fuel consumption and tailpipe emissions, a chassis dynamometer was employed to measure the fuel consumption, particulate matter (PM), solid particle number (PN), particle number size distribution and black carbon (BC) for a typical gasoline direct injection vehicle when the S&S was on (S&S-on) and when the S&S was off (S&S-off) according to the worldwide harmonized light-duty test cycle in both hot (28 °C) and cold (5 °C) environments. S&S operation resulted in 3.1–4.3% fuel-savings at 28 °C but had a tendency to increase particulate emissions, especially of BC (21.8–31.8%) and PM (19.2–32.8%). Although PN emissions with S&S-on over the entire cycle were slightly lower than those with S&S-off, more particles were emitted during the engine restart moments. In a cold environment, the fuel-savings advantage of the S&S system was weakened, and the negative impacts on the particle emissions during the restart moment worsened. The S&S system resulted in higher abundances of accumulation mode particles, especially under cold ambient conditions. The relationship between the PN reduction rates and idling segments was determining to be exponential. Our results indicate that the S&S system, which may increase particle emissions during restarts, does save fuel, and that a comprehensive evaluation of the system in cold environments is needed to determine the serviceability of new engine technologies and after-treatments.

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.