Determinants of personal exposure to some carcinogenic substances and nitrogen dioxide among the general population in five Swedish cities

Personal exposure monitoring of fine and coarse particulate matter using exposure assessment models for elderly residents in Hong Kong

This study investigated the determinants of personal exposures (PE) to coarse (PM2.5-10) and fine particulate matter (PM2.5) for elderly communities in Hong Kong. The mean PE PM2.5 and PM2.5-10 were 23.6 ± 10.8 and 13.5 ± 22.1 μg/m3, respectively during the sampling period. Approximately 76% of study subjects presented statistically significant differences between PE and ambient origin for PM2.5 compared to approximately 56% for PM2.5-10, possibly due to the coarse-size particles being more influenced by similar sources (road dust and construction dust emissions) compared to the PM2.5 particles. Individual PE to ambient (P/A) ratios for PM2.5 all exceeded unity (≥1), suggesting the dominant influences of non-ambient particles contributed towards total PE values. There were about 80% individual P/A ratios (≤1) for PM2.5-10, implying possible effective infiltration prevention of larger size particulate matter particles leading to dominant influences from the outdoor sources. The higher concentration of NO3- and SO42- in PM2.5-10 compared to PM2.5 suggests possible heterogeneous reactions of alkaline minerals leading to the formation of NO3- and SO42- in PM2.5-10 particles. The PE and ambient OC/EC ratios in PM2.5 (8.8 ± 3.3 and 10.4 ± 22.4, respectively) and in PM2.5-10 (6.0 ± 1.9 and 3.0 ± 1.1, respectively) suggest possible secondary formed OC from surrounding rural areas. Heterogeneous distributions (COD >0.2) between the PE and ambient concentrations were found for both the PM2.5 and PM2.5-10 samples. The calibration coefficient as the association between personal and surrogate exposure measure of PE to PM2.5 (0.84) was higher than PM2.5-10 (0.52). The findings further confirm that local sources were the dominant contributor to the coarse particles and these coefficients can potentially be used to estimate different PE to PM2.5 and PM2.5-10 conditions. A comprehensive understanding of the PE to determinants in coarse particles is essential to further reduce potential exposure misclassification.

SARS-CoV-2 infection and smoking: What is the association? A brief review

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The link between smoking and the expression of SARS-CoV-2 key entry genes is discussed.

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Smoking-related cardiac and respiratory diseases are risk factors for COVID-19.

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The impact of smoking on ACE-2 and TMPRSS2 receptors expression is controversial.

Susceptibility to severe illness from COVID-19 is anticipated to be associated with cigarette smoking as it aggravates the risk of cardiovascular and respiratory illness, including infections. This is particularly important with the advent of a new strain of coronaviruses, the severe acute respiratory syndrome coronavirus (SARS-CoV-2) that has led to the present pandemic, coronavirus disease 2019 (COVID-19). Although, the effects of smoking on COVID-19 are less described and controversial, we presume a link between smoking and COVID-19. Smoking has been shown to enhance the expression of the angiotensin-converting enzyme-2 (ACE-2) and transmembrane serine protease 2 (TMPRSS2) key entry genes utilized by SARS-CoV-2 to infect cells and induce a ‘cytokine storm’, which further increases the severity of COVID-19 clinical course. Nevertheless, the impact of smoking on ACE-2 and TMPRSS2 receptors expression remains paradoxical. Thus, further research is necessary to unravel the association between smoking and COVID-19 and to pursue the development of potential novel therapies that are able to constrain the morbidity and mortality provoked by this infectious disease. Herein we present a brief overview of the current knowledge on the correlation between smoking and the expression of SARS-CoV-2 key entry genes, clinical manifestations, and disease progression.

Exposures to Fumigants and Residual Chemicals in Workers Handling Cargo from Shipping Containers and Export Logs in New Zealand

OBJECTIVES

Previous studies have reported high concentrations of airborne fumigants and other chemicals inside unopened shipping containers, but it is unclear whether this is reflective of worker exposures.

METHODS

We collected personal 8-h air samples using a whole-air sampling method. Samples were analysed for 1,2-dibromoethane, chloropicrin, ethylene oxide, hydrogen cyanide, hydrogen phosphide, methyl bromide, 1,2-dichloroethane, C2-alkylbenzenes, acetaldehyde, ammonia, benzene, formaldehyde, methanol, styrene, and toluene. Additive Mixture Values (AMVs) were calculated using the New Zealand Workplace Exposure standard (WES) and American Conference of Governmental Industrial Hygienists (ACGIH) Threshold Limit Values (TLVs) of the 8-h, time-weighted average exposure limit. Linear regression was conducted to assess associations with work characteristics.

RESULTS

We included 133 workers handling shipping containers, 15 retail workers unpacking container goods, 40 workers loading fumigated and non-fumigated export logs, and 5 fumigators. A total of 193 personal 8-h air measurements were collected. Exposures were generally low, with >50% below the limit of detection for most chemicals, and none exceeding the NZ WES, although formaldehyde exceeded the TLV in 26.2% of all measurements. The AMV-TLV threshold of 1 was exceeded in 29.0% of the measurements. Levels and detection frequencies of most chemicals varied little between occupational groups, although exposure to methyl bromide was highest in the fumigators (median 43 ppb) without exceeding the TLV of 1000 ppb. Duration spent inside the container was associated with significantly higher levels of ethylene oxide, C2-alkylbenzenes, and acetaldehyde, but levels were well below the TLV/WES. Exposure levels did not differ between workers handling fumigated and non-fumigated containers.

CONCLUSIONS

Personal exposures of workers handling container cargo in New Zealand were mainly below current exposure standards, with formaldehyde the main contributor to overall exposure. However, as it is not clear whether working conditions of participants included in this study were representative of this industry as a whole, and not all relevant exposures were measured, we cannot exclude the possibility that high exposures may occur in some workers.

Two important controversial risk factors in SARS-CoV-2 infection: Obesity and smoking

The effects of obesity and smoking in the coronavirus disease 2019 (COVID-19) pandemic remain controversial. Angiotensin converting enzyme 2 (ACE2), a component of the renin-angiotensin system (RAS), is the human cell receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. ACE2 expression increases on lung alveolar epithelial cells and adipose tissue due to obesity, smoking and air pollution. A significant relationship exists between air pollution and SARS-CoV-2 infection, as more severe COVID-19 symptoms occur in smokers; comorbid conditions due to obesity or excess ectopic fat accumulation as underlying risk factors for severe COVID-19 strongly encourage the virus/ACE2 receptor-ligand interaction concept. Indeed, obesity, air pollution and smoking associated risk factors share underlying pathophysiologies that are related to the Renin-Angiotensin-System in SARS-CoV-2 infection. The aim of this review is to emphasize the mechanism of receptor-ligand interaction and its impact on the enhanced risk of death due to SARS-CoV-2 infection.

Exposure to Air Pollution inside Electric and Diesel-Powered Passenger Trains

Diesel-powered trains are used worldwide for passenger transport. The present study aimed to assess air pollution concentrations in passenger cars from diesel and electric trains. Personal exposure monitoring (6-7 h per day) was carried out for 49 days on diesel and 22 days on electric trains. Diesel trains had higher concentrations of all the assessed air pollution components. Average increases (and fold differences) in passenger cars of diesel trains compared with electric trains were for ultrafine particles 212 000 particles/cm³ (35-fold), black carbon 8.3 μg/m³ (6-fold), NO _x 316 μg/m³ (8-fold), NO₂ 38 μg/m³ (3-fold), PM_2.5 34 μg/m³ (2-fold), and benzo( a)pyrene 0.14 ng/m³ (6-fold). From time-series data, the pull and push movement modes, the engine in use, and the distance to the locomotive influenced the concentrations inside the diesel trains. In conclusion, concentrations of all air pollutants were significantly elevated in passenger cars in diesel trains compared to electric trains.

Human cancer risk estimation for 1,3-butadiene: An assessment of personal exposure and different microenvironments

This study estimated the lifetime cancer risk (LCR) attributable to 1,3-butadiene (BD) personal exposure and to other microenvironments, including residential home, outdoor, in-office, in-vehicle, and dining. Detailed life expectancy by country (WHO), inhalation rate and body weight by gender reported by USEPA were used for the calculation, focusing on adult population (25≤Age<65). LCR estimation of the adult population due to personal exposure exceeded the USEPA benchmark of 1×10^-6 in many cities. For outdoor BD exposure, LCR estimations in 45 out of 175 cities/sites (sharing 26%) exceeded the USEPA benchmark. Out of the top 20 cities having high LCR estimations, developing countries contributed 19 cities, including 14, 3, 1, 1 cities in China, India, Chile, and Pakistan. One city in the United States was in the list due to the nearby industrial facilities. The LCR calculations for BD levels found in residential home, in-vehicle and dining microenvironments also exceeded 1×10^-6 in some cities, while LCR caused by in-office BD levels had the smallest risk. Four cities/regions were used for investigating source distributions to total LCR results because of their sufficient BD data. Home exposure contributed significantly to total LCR value (ranging 56% to 86%), followed by in-vehicle (4% to 38%) and dining (4 to 7%). Outdoor microenvironment shared highly in Tianjin with 6%, whereas in-office contributed from 2-3% for all cities. High LCR estimations found in developing countries highlighted the greater cancer risk caused by BD in other cities without available measurement data.