Particulate Research Articles

Assessment of impacts of air pollution on people living in Ezza North close to quarry operation sites in Ebonyi State, Nigeria

Quarrying activities have become lucrative work for low income people in low income countries most found in Africa. This study aimed assess the impacts of air pollution on people living in Ezza North close to quarry operation sites in Ebonyi State, Nigeria. A descriptive cross sectional study was used and pollution level was determined with the use of calibrated Handheld GPS, Amex multiple gas meter, Sound meter and interview of participants with a questionnaire on the health status. The collected data were entered into the Statistical Package for Social Sciences (SPSS) software (version 21). The one sample T-test was used to test the hypotheses at 95% confidence interval and 0.05 level of significance. The results showed that 31–40 years had 19(5.37%) males and 20(5.65%) females as highest quarrying workers. The concentration of carbon monoxide was highest at 193ppm, Sulphur dioxide at 568ppm, nitrogen dioxide at 1.9ppm, Suspended particulate Matter (SPM) at 1982ppm and sound level at 82.9dB. The concentrations of these pollutants were found to be significantly higher (P<0.05) than normal levels apart from sound level without significant impact at P = 0.285. The 93.3% of the participants reported blasting of rocks produced highest air pollution, 87.5% that reported crushing, conveying, sieving produce a lot of dust. Also, 80% of participants reported high level of noise came from machinery blasting rocks, processing and haulage trucks. In all, 35% reported they had fair health condition when asked about the health status since they started quarrying work. In conclusion, the concentrations of carbon monoxide, carbon dioxide, sulphur dioxide, particulate matter and nitrogen oxides were all higher than normal. It was observed air pollutants had association with respiratory system. Therefore, the air pollution at quarrying site can be mitigated through dust suppression techniques and treating quarry pit with water before discharging.

Research on an adaptive prediction method for restaurant air quality based on occupancy detection

This study evaluates the impact of personnel on air quality in air-conditioned restaurant environments during winter, summer, and transitional seasons, characterized by the peculiarities of personnel movement, high concentration of personnel in a short period of time, poor ventilation and high personnel density, leading to the accumulation of pollutants that can severely damage personnel health. This study examines carbon dioxide (CO2) and particulate matter (PM) concentrations and proposes an online adaptive model for their prediction.Environmental influence factors are analyzed through correlations of measured data, and appropriate input parameters (time-lagged cumulative number of people) are selected. The Auto-Regressive with Exogenous Inputs (ARX) model is used to predict the change of air quality with the movement and number of people, compared with classical models (LR, DT, SVM, ENS, GPR, NN, VARX). Results show that the ARX model performs excellently in predicting restaurant environments; the effect of different environmental factors on the predictive effectiveness of the model was also explored. When combined with real-time sensor data and AIC-based adaptive optimization, the prediction accuracy is further improved by more than 25 %. The R2 of the ARX model is 0.9549, the MAE is 0.8352 μg/m3 and the MAPE is 3.17 %. The adaptively optimized model can be adapted to different environments, overcoming the problem of poor adaptability of such models. Our results enable effective environmental control strategies in public spaces, contributing to Sustainable Development Goal (SDG) 3: Good Health and Well-being by reducing health risks associated with indoor air pollution.

ANALYSIS AND ASSESSMENT OF AIR QUALITY IN ASTANA: COMPARISON OF POLLUTANT LEVELS AND THEIR IMPACT ON HEALTH

This study presents an in-depth analysis of air quality in Astana, Kazakhstan, utilizing both mobile and stationary air monitoring systems over a two-year period. The research focuses on tracking key air pollutants, namely carbon monoxide (CO), nitrogen dioxide (NO₂), particulate matter (PM2.5 and PM10), and sulfur dioxide (SO₂), providing a comparative assessment of seasonal trends and the sources of pollution, which include transportation, industrial emissions, and domestic heating during the cold season. The study emphasizes the significance of monitoring systems in urban environments to understand better the impact of air pollution on public health and the effectiveness of sustainable interventions. One of the major insights from this research is the comparison between seasonal variations in pollutant levels and the city's transition toward sustainable energy practices, such as increased gasification and the use of electric transportation, which has already demonstrated a positive impact on reducing emissions during peak heating periods. The results show that while Astana has improved air quality, air pollution remains a concern, especially in winter due to the increased use of solid fuel. This paper emphasizes the importance of real-time data from mobile sensors and suggests their wider use to complement stationary sensors for better monitoring. In addition to pollutant tracking, the study delves into the health implications of prolonged exposure to air pollutants, particularly in urban areas. The study concludes by advocating for expanded use of mobile monitoring systems and advanced data analytics to provide actionable insights for policymakers, urban planners, and public health officials.

Association of residential air pollution and green space with all-cause and cause-specific mortality in individuals with diabetes: an 11-year prospective cohort study

To assess the long-term impact of residential air pollution and green space exposure on cause-specific mortality in individuals with type 2 diabetes mellitus (T2DM). This study includes 174,063 participants newly diagnosed with T2DM from a prospective cohort in Shanghai, China, enrolled between 2011 and 2013. Residential annual levels of air pollutants, including fine (PM2.5) and coarse (PM2.5-10) particulate matter, nitrogen dioxide (NO2), along with the normalized difference vegetation index (NDVI), were derived from satellite-based exposure models. During a median follow-up of 7.9 years (equivalent to 1,333,343 person-years), this study recorded 22,205 deaths. Higher exposure to PM2.5 was significantly associated with increased risks for all mortality outcomes, whilst PM2.5-10 showed no significant impacts. The strongest associations of PM2.5 were observed for diabetes with peripheral vascular diseases [hazard ratio (HR): 2.70; per 10μg/m3 increase] and gastrointestinal cancer (2.44). Effects of NO2 became significant at concentrations exceeding approximately 45μg/m³, with the highest associations for lung cancer (1.20) and gastrointestinal cancer (1.19). Conversely, each interquartile range increase in NDVI (0.10) was linked to reduced mortality risks across different causes, with HRs ranging from 0.76 to 1.00. The association between greenness and mortality was partly and significantly mediated by reduced PM2.5 (23.80%) and NO2 (26.60%). There was a significant and negative interaction between NO2 and greenness, but no interaction was found between PM2.5 and greenness. Our findings highlight the vulnerability of individuals with T2DM to the adverse health effects of air pollution and emphasise the potential protective effects of greenness infrastructure. The 6th Three-year Action Program of Shanghai Municipality for Strengthening the Construction of Public Health System (GWVI-11.1-22), the National Key Research and Development Program (2022YFC3702701), and the National Natural Science Foundation of China (82030103, 82373532).

Non-repeatability of the WLTP vehicle test results

The paper presents results of considerations on the repeatability of the passenger car test results obtained in the WLTP procedure on a chassis dynamometer. The research concerned the aspects of exhaust emissions and fuel consumption. Measurements were carried out in the WLTC test with a cold engine start and then in four WLTC (Worldwide harmonized Light vehicles Test Cycle) tests with a hot engine start. The following values were measured: average specific distance emissions of hydrocarbons, non-methane hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter and carbon dioxide, specific distance particulate number, and operational fuel consumption. Thus, it was possible to assess the impact of the engine's thermal state at start-up on the test results and the nature of test results repeatability with the start-up of a hot engine. The repeatability of the test results was assessed based on the coefficient of variation obtained in the individual tests and the relationship of the maximum difference between measurement results values in the individual tests for a hot engine start. The obtained test results turned out to be very diverse for the considered parameters and indicated low repeatability. Values of carbon dioxide emissions and operational fuel consumption were definitely the least varied in individual hot engine start tests. The exhaust emission of particulate matter varied the most in individual test iterations. However, the specific distance particulate number was relatively similar between individual tests, less so than the exhaust emission of other pollutants. In the case of different engine thermal state at start-up, the emitted particulate number varied the most in the test results, while the emission of carbon dioxide and operational fuel consumption varied the least. The repeatability of executing the velocity process in WLTC tests at hot engine and cold engine start-up was also examined as processes determining exhaust emissions and fuel consumption. These tests were much more repeatable than the exhaust emission and fuel consumption.

Concurrent Particulate Matter and Heat Exposure in Working and Non-Working Women in Rural Guatemala

High temperatures and air pollution exposure are individually known risks to human health, with amplifying adverse health effects during periods of co-exposure. This study compared co-occurring individual-level exposures to particulate matter (PM5, aerodynamic diameter of ≤5 μm) and heat among women in residential and agricultural settings in Guatemala. We measured personal and ambient exposure to PM5, temperature, and humidity among 21 female sugarcane workers in the fields and on their off days. We measured similar exposures among a group of 30 community members not involved in sugarcane work. We collected 171 personal PM5 measurements across 18 sampling days. The median workday personal PM5 concentration was 271 µg/m3, which was 3.6-fold higher than ambient area levels in the fields. The median personal PM5 concentration was 95.8 µg/m3 for off-work days and 83.5 µg/m3 for community days. The average workday individual-level temperature and humidity were 39.4 °C and 82.4%, respectively, with significantly lower temperatures on off-work and community days. The women workers and community members were exposed to high levels of PM5 and heat in both occupational and residential settings. Research needs to consider individual-level exposures at both work and home to help tailor more effective comprehensive prevention efforts to reduce risks.

Development of diesel combustion with low cooling loss and high dispersion spray using two-dimensional optical measurements

In this study, a novel, high-efficiency, and clean combustion concept utilizing low cooling loss and high dispersion spray is proposed. The research aims to validate the objectives of this concept through spatiotemporal analysis of phenomena when key variables such as combustion chamber shape, spray parameters, and swirl are modified. This new combustion approach focuses on achieving low heat loss by using smaller nozzle diameters, multi-hole nozzles, and reduced swirl compared to conventional combustion. The combustion chamber is designed with an increased cavity diameter and an expanded taper diameter to enhance upward spray dispersion, thereby reducing fuel spray penetration into the cavity and decreasing cooling loss. This configuration reduces the fuel spray penetration in cavity, achieving a reduction in cooling heat loss. Furthermore, to increase the volume in the lower part of the combustion chamber, a corner-bottom shape is employed. Additionally, by causing spray impingement through the corner bottom shape, the strategy aimed to prevent the return of the mail injections to the central part of the combustion chamber. These parameters were evaluated using two-dimensional optical measurements, which calculated thermal flux, temperature, velocity, and KL value distributions. The impact of cavity diameter on internal cooling loss is significant, and preventing flame stagnation from a smoke perspective is crucial. An increase in taper diameter reduces squish velocity, achieving heat losses reduction, while necessitating spray dispersion into the squish area. The influence of swirl ratio on heat losses is more pronounced in the squish and taper areas than inside the cavity, necessitating consideration of flame temperature reduction within the cavity when reducing swirl ratios. The implementation of double after injection influences low heat losses and avoids flame stagnation, enabling soot reduction. The corner bottom shape combustion chamber proved effective in reducing heat losses and particulate matter (PM) at medium and high loads.

THE RELATIONSHIP BETWEEN AIR POLLUTION AND CORONARY ARTERY DISEASE: A SYSTEMATIC REVIEW

Several previous research studies have shown that air pollution has broad impacts on human health, particularly in the cardiovascular field. Exposure to air pollution entering the respiratory system can trigger inflammatory responses and increase the risk of cardiovascular diseases such as coronary artery disease. This systematic review aim to determine the relationship between air pollution and the occurrence of Coronary Artery Disease (CAD). Journal searches were conducted on five electronic databases, namely Pubmed, Science Direct, Europe PMC, Wiley Online Library, and Cochrane, following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) method. The search results get six original articles that meet the inclusion and exclusion criteria for analysis. Based on the results of the analysis shows that there is a significant relationship between air pollution in the form of gas components or particulate matter with the incidence of coronary artery disease. High levels of air pollution in an area can also increase the risk of CAD higher than areas with lower levels of air pollution.

A Novel Piezoelectric Nonwoven Fabric for Recoverable High-Efficiency Filters.

Serious haze pollution, mainly caused by fine and ultrafine particulate matters (PMs) and aerosols, poses a significant threat to the public health, especially when the aerodynamic diameter is less than 2.5 μm. Electrostatic capture techniques, such as polymer electret filters and kinetic plasma processes, are widely used instead of mechanical filtration with high removal efficiency and low wind resistance (pressure drop). However, the inability to recharge, coupled with the generation of ozone byproducts, makes it challenging to meet the requirements for both recoverability and highly efficient filtration. Here, we propose an electrostatic filter as an alternative to conventional polymer electrets, aiming to achieve an ultrahigh removal efficiency, long-term performance stability, and reusability. Piezoelectric LiNbO3 (LN) particles are integrated into the polypropylene (PP) matrix through the melt-blown strategy to fabricate the LN/PP nonwoven fabric. Benefiting from the employment of piezoelectric LN particles, the LN/PP nonwovens exhibit an ultrahigh removal efficiency of 99.9% for PM0.3 to PM10. The airflow facilitates the sustained regeneration of piezoelectric charges on the surface of LN/PP nonwovens, thereby maintaining a removal efficiency of approximately 95% for continuous filtration over 11 days. Even after eight cycles of washing, the removal efficiency of the LN/PP nonwovens remains at nearly 90%, demonstrating the excellent reusability. Our proposed strategy offers an ingenious combination of high-efficiency and recoverability for filters, holding great promise for reducing plastic pollution.

Mobile laboratory measurements of air pollutants in Baltimore, MD elucidate issues of environmental justice

ABSTRACT The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations – near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5th to 95th percentiles] = 2.08 [2.0–10.9] μg m−3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 – 1.8] μg m−3). Other species, including criteria pollutants ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles. Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source – diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems. Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.

Air Cleaning Plants

Air quality, both outdoor and indoor, is the most critical element that we must protect for the entire environment. While the deterioration of air quality primarily causes respiratory diseases in living things, it also causes corrosive effects on nonliving things, such as corrosion caused by acid rain, which results from air pollution. Therefore, it is necessary to monitor and prevent air pollution by various methods. WHO plays an active role in protecting air quality through its mission. Plants are indispensable beings for the environment and life. They balance the CO2 concentration, temperature, and humidity in the air. Plants use CO2, light, and water during photosynthesis, which is necessary for their growth and development. They reduce the CO2 concentration in the environment. In addition, plants, depending on their leaf characteristics, can trap particulate matter in the atmosphere. Many studies have proven that plants positively affect indoor and outdoor air quality. In this review, we aim to summarize the results of some selected studies, provide information about the air purification capacities of the researched plants, and emphasize the topic's importance.

Effects of Wildfire Smoke on Volatile Organic Compound (VOC) and PM2.5 Composition in a United States Intermountain Western Valley and Estimation of Human Health Risk

With a warmer and drier climate, there has been an increase in wildfire events in the Northwest US, posing a potential health risk to downwind communities. The Lewis–Clark Valley (LCV), a small metropolitan area on the Washington/Idaho border in the United States Intermountain West region, was studied over the time period of 2017–2018. The main objective was to determine the community’s exposure to particulate matter (PM2.5) and volatile organic compounds (VOCs) during wildfire smoke events and to estimate the associated health risk. VOCs were analyzed previously in the LCV using sorbent tube sampling and thermal-desorption gas-chromatography mass-spectrometry (TD-GC-MS) during several local smoke events in the 2017–2018 fire seasons. PM2.5 measurements were obtained from nearby agency monitors. PM2.5 reached up to 200 µg/m3 in 2017 and over 100 µg/m3 in 2018 in the LCV, and has been observed to be increasing at a rate of 0.10 µg m−3/yr over the past two decades. Benzene, a carcinogen and air toxic, was measured with concentrations up to 11 µg/m3, over ten times the normal level in some instances, in the LCV. The health risk in the LCV from benzene was calculated at seven extra cancers per million for lifetime exposure and thirteen extra cancers per million considering all air toxics measured. The other cities monitored showed similar lifetime cancer risk, due to benzene of about 6–7 extra cancers per million. This work is important, as it measures ground-level exposures of VOCs and demonstrates decreases in PM2.5 air quality over time in the region.

Impact of Wildfire Smoke on PM2.5, CO, NO2, and SO2 Levels

Air pollution can negatively impact public and individual health, as well as the environment. This paper investigates the impact of wildfires on levels of different air pollutants in order to determine whether focusing on reducing wildfires can be an efficient way to reduce specific pollutants. By plotting the number of acres burning in wildfires along with the overall concentration of particulate matter less than 2.5 microns in diameter (PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) during a period of time in California, this paper estimates the contribution of wildfire smoke to the level of each pollutant. The results show that PM2.5 levels were the most heavily impacted by wildfires out of the four pollutants studied, and therefore actions to reduce the size and quantity of wildfires can be helpful to reduce the damage done by PM2.5 pollution. However, CO, NO2, and SO2 levels, while they may be correlated with fire size, are likely more strongly influenced by other factors. To minimize the harmful effects of these three pollutants, it may be more effective to focus on investigating other sources of CO, NO2, and SO2, such as the burning of fossil fuels in industrial machinery and motor vehicles.

Modeling of PM10 Particulate Matter in Ahvaz City Using Remote Sensing and Meteorological Parameters

Introduction: In recent years, remote sensing (RS) products have emerged as effective tools for monitoring air pollution. This study aims to predict the concentrations of particulate matter with a diameter smaller than 10μm (PM10) using a multivariate linear regression (MLR) model, incorporating both Aerosol Optical Depth (AOD) products and meteorological parameters. Material and Methods: In this study, data on PM10 concentrations, Aerosol Optical Depth (AOD), and meteorological parameters (wind speed, temperature, humidity, and horizontal visibility) were used. The study focused on the time 15:00 each day, as this time was identified as having significant data relevance. The methodology section also consisted of three steps: 1) pairwise correlation analysis: The relationship between meteorological parameters, AOD, and PM10 was assessed using the pairwise correlation method. 2) Model development: A MLR model was developed to predict PM10 concentrations. 3) Validation: The model was validated using a separate dataset, ensuring that 70% of the data was used for training, and 30% for testing and validation. Results: The pairwise correlation analysis revealed a strong correlation (0.86) between AOD remote sensing index and PM10. The highest correlation (0.9) was observed during the spring season. The five developed equations to estimate the PM10 index yielded correlation coefficients ranging from 0.86 to 0.90. Notably, the highest correlation was achieved when AOD data and all the meteorological parameters were u tilized simultaneously. These results highlighted the utility of remote sensing products and meteorological data in air quality monitoring and prediction. Conclusion: This study demonstrates that a MLR model incorporating AOD and meteorological parameters can effectively predict PM10 concentrations in Ahvaz City, particularly during dust storms in hot seasons. These findings can aid policymakers and public health officials in developing strategies to mitigate the adverse effects of dust storms on air quality and public health.

Impact of ENVI-met-Based Road Greening Design on Thermal Comfort and PM2.5 Concentration in Hot–Humid Areas

Road greening markedly impacts road thermal comfort and air quality. However, previous studies have primarily focused on thermal comfort or PM2.5 individually, with relatively few addressing both aspects comprehensively, particularly in humid regions. This study combined field measurements and simulations. It employed physiological equivalent temperature (PET) and quantified the horizontal distribution of particulate matter 2.5 (PM2.5). The research examines the effects of planting spacing, tree species, and tree–shrub combinations on pedestrian walkways in humid climates during both summer and winter. Using measured tree data and road PM2.5, a plant model was established and pollution emission parameters were set to validate the effectiveness of the ENVI-met through fitting simulations under various scenarios. The results indicated that (1) plant spacing for trees influenced both the road thermal environment and PM2.5 levels. Smaller spacing improved thermal conditions but increased PM2.5. (2) trees with large canopies and high leaf area indices (LAIs) notably enhanced thermal comfort, while those with smaller canopies and dense understories facilitated PM2.5 dispersion. The 3 m spacing resulted in a maximum absolute PM2.5 concentration difference (C) of 5.05 μg/m3 in summer and a maximum mean absolute PM2.5 concentration difference (M) in the downwind region of 2.13 μg/m3 in winter. (3) Combining trees with shrubs moderately improved pedestrian thermal comfort. However, taller shrubs elevated PM2.5 concentrations on walkways; heights ranging from 1.5 m to 2 m in summer showed higher C values of 5.38 μg/m3 and 5.37 μg/m3. This study provides references and new perspectives for the optimization of roadway greening design in humid areas in China.

Exploring the association between knee osteoarthritis outpatient visits and Asian dust storms: a time-series analysis

Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases in Taiwan, posing a significant public health challenge. In recent years, outdoor air pollution has become an increasingly critical global health issue. Asian Dust Storms (ADS) are known to exacerbate various health conditions due to elevated levels of particulate matter and other pollutants. However, the relationship between ADS and knee OA remains insufficiently explored. This study investigates the association between ADS occurrences and knee OA outpatient visits from January 2006 to December 2012, aiming to understand the potential health impacts of dust storms on OA patients. Using data from the National Health Insurance Research Database (NHIRD), the Taiwan Environmental Protection Agency (TEPA), and the Taiwan Central Weather Bureau, we conducted a time-series analysis employing the autoregressive moving average with exogenous variables (ARMAX) model. This approach accounted for daily outpatient visits related to knee OA, ADS events, and various environmental and meteorological factors. The results revealed a significant increase in knee OA outpatient visits on days immediately following ADS events, with peaks observed one to two days after the event. This increase was most pronounced among females, individuals aged 61 and above, and residents in the western regions. The study demonstrates an association between ADS and increased knee OA outpatient visits, highlighting the need for public health strategies to mitigate the health impacts of dust storms.

Airborne antibiotic resistome from sludge dewatering systems: Mobility, pathogen accessibility, cross-media migration propensity, impacting factors, and risks

Bioaerosol contamination was considered as a potential health threat in sludge dewatering systems (SDSs), while emission and risk of airborne antibiotic resistome remain largely unclear. Herein, seasonal investigations of fine particulate matter (PM2.5) were conducted using metagenomics-based methods within and around different SDSs, together with an analysis of sewage sludge. Featured with evident seasonality, antibiotic resistance genes (ARGs) in SDS-PM2.5 also possessed greater accumulation, transfer, and pathogen accessibility than those in ambient air PM2.5. Mobile ARGs in SDS-PM2.5 mainly encoded resistance to tetracycline, and most were flanked by integrase. Some pathogenic antibiotic resistant bacteria (PARB), including Enterobacter asburiae, Escherichia coli, Enterococcus faecium, and Staphylococcus aureus, also carried mobile genetic elements in SDS-PM2.5. Dewatering behavior actuated > 50.56% of ARG subtypes and > 42.86% of PARB in sewage sludge to aerosolize into air. Relative humidity, temperature, and PM2.5 concentration collectively drove the evolution of bacterial community and indirectly promoted the antibiotic resistance of SDS-PM2.5. SDS-PM2.5 posed more serious resistome risks than sewage sludge and ambient air PM2.5, and the highest levels were discovered in winter. These findings underline the role of dewatering behavior in facilitating resistome's aerosolization, and the need to mitigate this potential air pollution.

Diesel exhaust particle inhalation in conjunction with high-fat diet consumption alters the expression of pulmonary SARS-COV-2 infection pathways, which is mitigated by probiotic treatment in C57BL/6 male mice

BackgroundBoth exposure to air pollutants and obesity are associated with increased incidence and severity of COVID-19 infection; however, the mechanistic pathways involved are not well-characterized. After being primed by the transmembrane protease serine 2 (TMPRSS2) or furin protease, SARS-CoV-2 uses the angiotensin-converting enzyme (ACE)-2 receptor to enter respiratory epithelial cells. The androgen receptor (AR) is known to regulate both TMPRSS2 and ACE2 expression, and neuropilin-1 (NRP1) is a proposed coreceptor for SARS-CoV-2; thus, altered expression of these factors may promote susceptibility to infection. As such, this study investigated the hypothesis that inhalational exposure to traffic-generated particulate matter (diesel exhaust particulate; DEP) increases the expression of those pathways that mediate SARS-CoV-2 infection and susceptibility, which is exacerbated by the consumption of a high-fat (HF) diet.MethodsFour- to six-week-old male C57BL/6 mice fed either regular chow or a HF diet (HF, 45% kcal from fat) were randomly assigned to be exposed via oropharyngeal aspiration to 35 µg DEP suspended in 35 µl 0.9% sterile saline or sterile saline only (control) twice a week for 30 days. Furthermore, as previous studies have shown that probiotic treatment can protect against exposure-related inflammatory outcomes in the lungs, a subset of study animals fed a HF diet were concurrently treated with 0.3 g/day Winclove Ecologic® Barrier probiotics in their drinking water throughout the study.ResultsOur results revealed that the expression of ACE2 protein increased with DEP exposure and that TMPRSS2, AR, NRP1, and furin protein expression increased with DEP exposure in conjunction with a HF diet. These DEP ± HF diet-mediated increases in expression were mitigated with probiotic treatment.ConclusionThese findings suggest that inhalational exposure to air pollutants in conjunction with the consumption of a HF diet contributes to a more susceptible lung environment to SARS-CoV-2 infection and that probiotic treatment could be beneficial as a preventative measure.

On the dose-response association of fine and ultrafine particles in an urban atmosphere: toxicological outcomes on bronchial cells at realistic doses of exposure at the Air Liquid Interface

Air pollution and particulate matter (PM) are the leading environmental cause of death worldwide. Exposure limits have lowered to increase the protection of human health; accordingly, it becomes increasingly important to understand the toxicological mechanisms on cellular models at low airborne PM concentrations which are relevant for actual human exposure. The use of air liquid interface (ALI) models, which mimic the interaction between airborne pollutants and lung epithelia, is also gaining importance in inhalation toxicological studies. This study reports the effects of ALI direct exposure of bronchial epithelial cells BEAS-2B to ambient PM1 (i.e. particles with aerodynamic diameter lower than 1 μm). Gene expression (HMOX, Cxcl-8, ATM, Gadd45-a and NQO1), interleukin (IL)-8 release, and DNA damage (Comet assay) were evaluated after 24 h of exposure. We report the dose-response curves of the selected toxicological outcomes, together with the concentration-response association and we show that the two curves differ for specific responses highlighting that concentration-response association may be not relevant for understanding toxicological outcomes. Noteworthy, we show that pro-oxidant effects may be driven by the deposition of freshly emitted particles, regardless of the airborne PM1 mass concentration. Furthermore, we show that reference airborne PM1 metrics, namely airborne mass concentration, may not always reflect the toxicological process triggered by the aerosol.These findings underscore the importance of considering different aerosol metrics to assess the toxicological potency of fine and ultrafine particles. To better protect human health additional metrics should be defined, than account for the properties of the entire aerosol mixture including specific as particle size (i.e. particles with aerodynamic diameter lower than 20 nm), the relevant aerosol sources (e.g., traffic combustion, secondary organic aerosol …) as well as their atmospheric processing (freshly emitted vs aged ones).

The mediating effect of TyG-related indicators between long-term exposure to particulate matter and cardiovascular disease: evidence from a national longitudinal cohort study

BackgroundAmbient particulate matter (PM) exposure is recognized as a risk factor for cardiovascular disease (CVD). However, the extent to which PM exposure is associated with CVD via triglyceride glucose (TyG)-related indicators remains unknown. This study examines the relationship between long-term PM exposure and CVD events, further assessing whether TyG-related indicators mediate this association.MethodsThis cohort study involved 7,532 individuals aged at least 45 years who were not diagnosed with CVD in 2011 from the China Longitudinal Study of Health and Retirement (CHARLS) and were followed up for the occurrence of CVD until 2020. The annual PM concentration data at the city level, with aerodynamic diameters ≤ 1 μm (PM1), ≤ 2.5 μm (PM2.5), and ≤ 10 μm (PM10), were obtained from the ChinaHighAirPollutants (CHAP). The average concentration of PM in the 3 years before the baseline survey in 2011 was defined as the long-term exposure level of the individual. The relationship between PM exposure and CVD incidence was examined via Cox proportional hazards models, with a focus on probing the role of TyG-related indicators through mediation analysis.ResultsA total of 1,865 individuals with CVD were diagnosed over the span of a 7.4-year follow-up period. The 3-year average concentrations before baseline were 31.29 µg/m³ for PM1, 56.03 µg/m³ for PM2.5, and 95.73 µg/m³ for PM10. In fully adjusted model, the Cox proportional hazards models revealed that an increase of 10 µg/m³ in the PM1, PM2.5, and PM10 exposure concentrations corresponded to elevated CVD risk, with HRs (95% CI) of 1.135 (1.078–1.195), 1.092 (1.062–1.123), and 1.075 (1.059–1.090), respectively. Mediation analyses further suggested that the correlation between PM exposure and CVD could be partly mediated via TyG-BMI, TyG-WC, and TyG-WHtR, with mediation proportions varying from 5.54 to 15.30%.ConclusionA significant correlation was observed between long-term PM exposure and increased CVD risk, with TyG-related indicators, such as TyG-BMI, TyG-WC, and TyG-WHtR, partially mediating this relationship.