Toxicological effects of personal exposure to fine particles in adult residents of Hong Kong

Year-long and seasonal differences of PM2.5 chemical characteristics and their role in the viability of human lung epithelial cells (A549)

Fine particulate matters-PM2.5 in the air can have considerable negative effects on human health and the environment. Various human cell-based studies examined the effect of PM2.5 on human health in different cities of the world using various chemical parameters. Unfortunately, limited information is available regarding the relationship between toxicity and chemical characteristics of PM2.5 collected in Istanbul, Türkiye, located in one of the most populated cities in the world. To investigate the chemical characteristics and cytotoxicity of PM2.5 in Istanbul, samples were collected for 12 months, then potentially toxic metals, oxidative potential, and particle indicators (e.g., functional groups and elements) were determined, and the cytotoxicity of PM2.5 on human A549 lung alveolar epithelial cells was examined. The mean PM2.5 mass concentration was 24.0 ± 17.4 µg m-3 and higher in cold months compared to other seasons. Moreover, the results of the metals, elemental, and functional groups indicated that seasonal and monthly characteristics were influenced by the regional anthropogenic sources and photochemistry input. The cytotoxicity results also showed that the viability of A549 cells was reduced with the exposure of PM2.5 (30-53%) and higher cytotoxicity was obtained in summer compared to the other seasons due to the impact of the metals, elements, and oxidative characteristics of PM2.5.

Statistical estimation of noise induced hearing loss among the drivers in one of the most polluted cities of India

In the present study, an attempt has been made to assess the impact of vehicular noise upon the 3-wheeler tempo drivers and to know whether there is any relationship between hearing loss and cumulative noise exposure. For this purpose, 3-wheeler tempo drivers (Exposed group) and non-commercial light motor vehicle car drivers (Unexposed group) were chosen as study subjects. Three traffic routes were selected to assess the noise level during waiting and running time in the exposed and unexposed groups. Among all three routes, the highest mean noise level (Leq) was observed on the Chowk to Dubagga route for waiting and en-route noise measurement. It was measured as 84.13 dB(A) and 86.36 dB(A) for waiting and en-route periods of 7.68 ± 3.46 and 31.05 ± 6.6 min, respectively. Cumulative noise exposure was found to be significantly different (p < 0.001) in all age groups of exposed and unexposed drivers. Audiometric tests have been performed over both exposed and unexposed groups. The regression analysis has been done keeping hearing loss among tempo drivers as the dependent variable and age (years) and Energy (Pa2 Hrs) as the independent variable using three different criteria of hearing loss definitions, i.e., World Health Organization, National Institute for Occupational Safety and Health (NIOSH), Occupational Safety and Health Administration criteria. Among these three criteria, the NIOSH criterion of hearing loss best explained the independent variables. It could explain the total variation in dependent variable by independent variable quite well, i.e., 68.1%. The finding showed a linear relationship between cumulative noise exposures (Pa2 Hrs) and the exposed group's hearing loss (dB), i.e., hearing loss increases with increasing noise dose. Based on the findings, two model equations were developed to identify the safe and unsafe noise levels with exposure time.

Impact of Beijing's "Coal to Electricity" program on ambient PM2.5 and the associated reactive oxygen species (ROS)

The Beijing "Coal to Electricity" program provides a unique opportunity to explore air quality impacts by replacing residential coal burning with electrical appliances. In this study, the atmospheric ROS (Gas-phase ROS and Particle-phase ROS, abbreviated to G-ROS and P-ROS) were measured by an online instrument in parallel with concurrent PM_2.5 sample collections analyzed for chemical composition and cellular ROS in a baseline year (Coal Use Year-CUY) and the first year following implementation of the "Coal to Electricity" program (Coal Ban Year-CBY). The results showed PM_2.5 concentrations had no significant difference between the two sampling periods, but the activities of G-ROS, P-ROS, and cellular ROS in CBY were 8.72 nmol H₂O₂/m³, 9.82 nmol H₂O₂/m³, and 2045.75 µg UD /mg PM higher than in CUY. Six sources were identified by factor-analysis from the chemical components of PM_2.5. Secondary sources (SECs) were the dominant source of PM_2.5 in the two periods, with 15.90% higher contribution in CBY than in CUY. Industrial Emission & Coal Combustion sources (Ind. & CCs), mainly from regional transport, also increased significantly in CBY. The contributions of Aged Sea Salt & Residential Burning sources to PM_2.5 decreased 5.31% from CUY to CBY. The correlation results illustrated that Ind. & CCs had significant positive correlations with atmospheric ROS, and SECs significantly associated with cellular ROS, especially nitrates (r = 0.626, p = 0.000). Therefore, the implementation of the "Coal to Electricity" program reduced PM_2.5 contributions from coal and biomass combustion, but had little effect on the improvement of atmospheric and cellular ROS.

Investigating PM2.5 toxicity in highly polluted urban and industrial areas in the Middle East: human health risk assessment and spatial distribution

Exposure to particulate matter (PM) can be considered as a factor affecting human health. The aim of this study was to investigate the concentration of PM2.5 and heavy metals and their influence on survival of A549 human lung cells in exposure to PM2.5 breathing air of Ahvaz city. In order to assess the levels of PM2.5 and heavy metals, air samples were collected from 14 sampling stations positioned across Ahvaz city during both winter and summer seasons. The concentration of heavy metals was determined using ICP OES. Next, the MTT assay [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] was employed to ascertain the survival rate of A549 cells. The findings from this research demonstrated that average PM2.5 of the study period was (149.5 μg/m3). Also, the average concentration of PM2.5 in the urban area in winter and summer was (153.3- and 106.9 μg/m3) and in the industrial area this parameter was (191.6 and 158.3 μg/m3). The average concentration of metals (ng/m3) of urban areas against industrial, Al (493 vs. 485), Fe (536 vs. 612), Cu (198 vs. 212), Ni (128 vs. 129), Cr (48.5 vs. 54), Cd (118 vs. 124), Mn (120 vs. 119), As (51 vs. 67), Hg (37 vs. 50), Zn (302 vs. 332) and Pb (266 vs. 351) were obtained. The results of the MTT assay showed that the highest percentage of cell survival according to the exposure concentration was 25 > 50 > 100 > 200. Also, the lowest percentage of survival (58.8%) was observed in the winter season and in industrial areas with a concentration of 200 μg/ml. The carcinogenic risk assessment of heavy metals indicated that except for Cr, whose carcinogenicity was 1.32E-03, other metals were in the safe range (10-4-10-6) for human health. The high concentration of PM2.5 and heavy metals can increase respiratory and cardiovascular diseases and reduce the public health level of Ahvaz citizens.

Concomitant exposure to air pollution, green space, and noise and risk of stroke: a cohort study from Denmark

Background

Air pollution, road traffic noise, and green space are correlated factors, associated with risk of stroke. We investigated their independent relationship with stroke in multi-exposure analyses and estimated their cumulative stroke burden.

Methods

For all persons, ≥50 years of age and living in Denmark from 2005 to 2017, we established complete address histories and estimated running 5-year mean exposure to fine particles (PM_2.5), ultrafine particles, elemental carbon, nitrogen dioxide (NO₂), and road traffic noise at the most, and least exposed façade. For air pollutants, we estimated total, and non-traffic contributions. Green space around the residence was estimated from land use maps. Hazard ratios (HR) and 95% confidence limits (CL) were estimated with Cox proportional hazards models and used to calculate cumulative risk indices (CRI). We adjusted for the individual and sociodemographic covariates available in our dataset (which did not include information about individual life styles and medical conditions).

Findings

The cohort accumulated 18,344,976 years of follow-up and 94,256 cases of stroke. All exposures were associated with risk of stroke in single pollutant models. In multi-pollutant analyses, only PM_2.5 (HR: 1.058, 95% CI: 1.040-1.075) and noise at most exposed façade (HR: 1.033, 95% CI: 1.024-1.042) were independently associated with a higher risk of stroke. Both noise and air pollution contributed substantially to the CRI (1.103, 95% CI: 1.092-1.114) in the model with noise, green space, and total PM_2.5 concentrations.

Interpretation

Environmental exposure to air pollution and noise were both independently associated with risk of stroke.

Funding

Health Effects Institute (HEI) (Assistance Award No. R-82811201).

Personal exposure to PM2.5 oxidative potential and its association to birth outcomes

BACKGROUND

Prenatal exposure to fine particulate matter (PM2.5) assessed through its mass concentration has been associated with foetal growth restriction in studies based on outdoor levels. Oxidative potential of PM2.5 (OP) is an emerging metric a priori relevant to mechanisms of action of PM on health, with very limited evidence to indicate its role on birth outcomes.

OBJECTIVES

We investigated the association of OP with birth outcomes and compared it with that of PM2.5 mass concentration.

METHODS

405 pregnant women from SEPAGES cohort (Grenoble area) carried PM2.5 personal dosimeters for one or two one-week periods. OP was measured using dithiothreitol (DTT) and ascorbic acid (AA) assays from the collected filters. Associations of each exposure metric with offspring weight, height, and head circumference at birth were estimated adjusting for potential confounders.

RESULTS

The correlation between PM2.5 mass concentration and [Formula: see text] was 0.7. An interquartile range increase in .. was associated with reduced weight (adjusted change, -64 g, -166 to -11, p = 0.02) and height (-4 mm, -6 to -1, p = 0.01) at birth. PM2.5 mass concentration showed similar associations with weight (-53 g, -99 to -8, p = 0.02) and height (-2 mm, -5 to 0, p = 0.05). In birth height models mutually adjusted for the two exposure metrics, the association with [Formula: see text] was less attenuated than that with mass concentration, while for weight both effect sizes attenuated similarly. There was no clear evidence of associations with head circumference for any metric, nor for [Formula: see text] with any growth parameter.

IMPACT

PM2.5 pregnancy exposure assessed from personal dosimeters was associated with altered foetal growth. Personal OP exposure was associated with foetal growth restrictions, specifically decreased weight and height at birth, possibly to a larger extent than PM2.5 mass concentration alone. These results support OP assessed from DTT as being a health-relevant metric. Larger scale cohort studies are recommended to support our findings.

Air pollution, road traffic noise and lack of greenness and risk of type 2 diabetes: A multi-exposure prospective study covering Denmark

OBJECTIVE

Air pollution, road traffic noise and lack of greenness coexist in urban environments and have all been associated with type 2 diabetes. We aimed to investigate how these co-exposures were associated with type 2 diabetes in a multi-exposure perspective.

METHODS

We estimated 5-year residential mean exposure to fine particles (PM_2.5), ultrafine particles (UFP), elemental carbon (EC), nitrogen dioxide (NO₂) and road traffic noise at the most (LdenMax) and least (LdenMin) exposed facade for all persons aged > 50 years living in Denmark in 2005 to 2017. For each air pollutant, we estimated total concentrations and traffic contributions. Based on land use maps, we estimated proportion of green and non-green space within 150 and 1000 m of all residences. In total, 1.9 million persons were included and 128,358 developed type 2 diabetes during follow-up. We performed analyses using Cox proportional hazards models, with adjustment for individual and neighborhood-level sociodemographic co-variates.

RESULTS

In single-pollutant models, all air pollutants, noise and lack of green space were associated with higher risk of diabetes. In two-, three- and four-pollutant analyses of the air pollutants, only UFP and NO₂ remained associated with higher diabetes risk in all models. LdenMax, LdenMin and the two proxies of green space remained associated with diabetes in two-pollutant models of, respectively, noise and green space. In a multi-pollutant analysis, we found hazard ratios (95 % confidence intervals) per interquartile range of 1.021 (1.005; 1.038) for UFP, 1.012 (0.996; 1.028) for NO₂, 1.022 (1.012; 1.033) for LdenMin, 1.013 (1.004; 1.022) for LdenMax, and 1.038 (1.031; 1.044) and 1.018 (1.010; 1.025) for lack of green space within, respectively, 150 m and 1000 m, and a cumulative risk index of 1.131 (1.113; 1.149).

CONCLUSIONS

Air pollution, road traffic noise and lack of green space were independently associated with higher risk of type 2 diabetes.

Contribution of heavy metals in PM2.5 to cardiovascular disease mortality risk, a case study in Guangzhou, China

Heavy metals play an important role in inducing fine particulate matter (PM_2.5) related cardiovascular disease (CVD). However, most of the past researches concerned the associations between CVD mortality and the PM_2.5 mass, which may not reveal the CVD mortality risk contributed by heavy metals in PM_2.5. This study explored the correlations between individual heavy metals in PM_2.5 and CVD mortality, identified the heavy metals that significantly contribute to PM_2.5-related CVD, heart disease (HD), and cerebrovascular disease (CEV) mortality, and attempted to establish corresponding source control measures. Over a 2-year study period, PM_2.5 was sampled daily in Guangzhou, China and analyzed for heavy metals. The airborne pollution and weather data, along with CVD, HD, and CEV mortality, were obtained at the same time. The excess risk (ER) of mortality was linked to the individual heavy metals using a distributed lag non-linear model. PM_2.5 and most heavy metals showed significant correlations with the CVD, HD, and CEV mortality; the largest cumulative ER (LCER) values of CVD mortality associated with an interquartile range increase in the levels of lead, cadmium, arsenic, selenium, antimony, nickel, thallium, aluminum, iron, and PM_2.5 were 2.43%, 2.23%, 1.66%, 2.39%, 1.19%, 1.21%, 2.69%, 3.29%, 1.74%, and 2.40%, respectively. Most heavy metals showed comparable LCER values of HD and CEV mortality. Heavy metals with the addition of PM_2.5 were divided into three groups following their LCER values; lead, cadmium, arsenic, antimony, thallium, zinc, aluminum, and iron, whose contributions were greater than or equal to the average effect of the PM_2.5 components, should be limited on a priority basis. These findings indicated that heavy metals play roles in the CVD, HD, and CEV mortality risk of PM_2.5, and specific control measures which aimed at the emission sources should be taken to reduce the CVD mortality risk of PM_2.5.

Characteristics, Source Contributions, and Source-Specific Health Risks of PM2.5-Bound Polycyclic Aromatic Hydrocarbons for Senior Citizens during the Heating Season in Tianjin, China

Polycyclic aromatic hydrocarbons (PAHs) have carcinogenic impacts on human health. However, limited studies are available on the characteristics, sources, and source-specific health risks of PM2.5-bound PAHs based on personal exposure data, and comparisons of the contributions of indoor and outdoor sources are also lacking. We recruited 101 senior citizens in the winter of 2011 for personal PM2.5 sample collection. Fourteen PAHs were analyzed, potential sources were apportioned using positive matrix factorization (PMF), and inhalational carcinogenic risks of each source were estimated. Six emission sources were identified, including coal combustion, gasoline emission, diesel emission, biomass burning, cooking, and environmental tobacco smoking (ETS). The contribution to carcinogenic risk of each source occurred in the following sequence: biomass burning > diesel emission > gasoline emission > ETS > coal combustion > cooking. Moreover, the contributions of biomass burning, diesel emission, ETS, and indoor sources (sum of cooking and ETS) to PAH-induced carcinogenic risk were higher than those to the PAH mass concentration, suggesting severe carcinogenic risk per unit contribution. This study revealed the contribution of indoor and outdoor sources to mass concentration and carcinogenic risk of PM2.5-bound PAHs, which could act as a guide to mitigate the exposure level and risk of PM2.5-bound PAHs.

Exposure to source-specific air pollution and risk for type 2 diabetes: a nationwide study covering Denmark

BACKGROUND

Only few epidemiological studies have investigated whether chronic exposure to air pollution from different sources have different impacts on risk of diabetes. We aimed to investigate associations between air pollution from traffic versus non-traffic sources and risk of type 2 diabetes in the Danish population.

METHODS

We estimated long-term exposure to traffic and non-traffic contributions of particulate matter with a diameter <2.5 µg (PM2.5), elemental carbon (EC), ultrafine particles (UFP) and nitrogen dioxide (NO2) for all persons living in Denmark for the period 2005-17. In total, 2.6 million persons aged >35 years were included, of whom 148 020 developed type 2 diabetes during follow-up. We applied Cox proportional hazards models for analyses, using 5-year time-weighted running means of air pollution and adjustment for individual- and area-level demographic and socioeconomic covariates.

RESULTS

We found that 5-year exposure to all particle measures (PM2.5, UFP and EC) and NO2 were associated with higher type 2 diabetes risk. We observed that for UFP, EC and potentially PM2.5, the pollution originating from traffic was associated with higher risks than the non-traffic contributions, whereas for NO2 similar hazard ratios (HR) were observed. For example, in two-source models, hazard ratios (HRs) per interquartile change in traffic UFP, EC and PM2.5 were 1.025, 1.045 and 1.036, respectively, whereas for non-traffic UFP, EC and PM2.5, the HRs were 1.013, 1.018 and 1.001, respectively.

CONCLUSIONS

Our finding of stronger associations with particulate matter from traffic compared with non-traffic sources implies that prevention strategies should focus on limiting traffic-related particulate matter air pollution.