Airborne particulate matter in Tehran's ambient air

Investigation of the spatial variation of ambient air VOCs and their effects on the health risk caused by long-term exposure in urban area

Long-term exposure to Volatile Organic Compounds (VOCs) is a health risk for citizens. In this study, the cumulative health risk of exposure to VOCs in Tehran was assessed by investigating the concentration of these pollutants in ambient air in a five-year period. Health risk assessment was calculated by the quantitative method and the carcinogenic risk level was determined using the lifetime carcinogenic risk (LCR) method. The average concentration of benzene, toluene, ortho-xylene, and ethylbenzene was 1.4-1.8, 4.8-5.4, 5-6.5, and 3.6-4 ppb, respectively. Although HQ was not greater than 1, but it was very close in the case of benzene, ortho-xylene, meta-xylene, and para-xylene. Benzene and ethylbenzene had the largest effect in the assessed health risk. So the long-term exposure of Tehran citizens to VOCs has serious health consequences for them, which could be different according to the exposure time and spatial variations.

Assessment of carcinogenic risk from indoor radon exposure influenced by geological structures in the mountains of southern Caspian Sea

Indoor radon exposure is the main form of radon exposure that causes health consequences including lung cancer. The aim of this study was to investigate indoor radon concentration affected by different geological characteristics in a mountainous area. For this purpose, three areas close to each other in the mountains of northern Iran, which were different in terms of the presence of hot springs, were studied. Sampling and analysis of indoor radon concentration was done in twelve buildings in summer and winter. The results showed that the average concentration of radon in the studied buildings was 124.5 Bq m-3, which was higher than the reference dose suggested by World Health Organization (WHO) (100 Bq m-3) and lower than reference dose suggested by U.S. Environmental Protection Agency (EPA) (150 Bq m-3). The average indoor radon concentration in areas with many hot springs, few hot springs, and no hot springs were 144.9 Bq m-3, 130.45 Bq m-3, and 98.06 Bq m-3, respectively. The average Excess Lifetime Cancer Risk in the studied area was 9.700E-03, but Excess Lifetime Cancer Risk was 16.4% and 4.7% higher than the average in the areas that had many hot springs and few hot springs, respectively. High indoor radon concentration in hot spring areas and the carcinogenic risk caused by exposure to it should be controlled by concentration reduction techniques such as vent pipes and adequate ventilation, regular monitoring, and radon-resistant materials.

Predictive modeling of air quality in the Tehran megacity via deep learning techniques

Air pollution is a significant challenge in metropolitan areas, where increasing amounts of air pollutants threaten public health and environmental safety. The present study aims to forecast the concentrations of various air pollutants, including CO, O3, NO2, SO2, PM10, and PM2.5, from 2013 to 2023 in the Tehran megacity, Iran, via deep learning (DL) models and evaluate their effectiveness over conventional machine learning (ML) methods. Key driving variables, including temperature, relative humidity, dew point, wind speed, and air pressure, were considered. R-squared (R2), root-mean-square error (RMSE), mean absolute error (MAE), and mean-square error (MSE) were used to assess and compare the models. This research demonstrated that DL models typically outperform ML models in forecasting air pollution. Gated recurrent units (GRUs), fully connected neural networks (FCNNs), and convolutional neural networks (CNNs) recorded R2 and MSE values of 0.5971 and 42.11 for CO, 0.7873 and 171.40 for O3, and 0.4954 and 25.17 for SO2, respectively. Consequently, the FCNN and GRU presented remarkable performance in predicting NO2 (R2 = 0.6476 and MSE = 75.16), PM10 (R2 = 0.8712 and MSE = 45.11), and PM2.5 (R2 = 0.9276 and MSE = 58.12) concentrations. In terms of operational speed, the FCNN model exhibited the most efficiency, with a minimum and maximum runtime of 13 and 28 s, respectively. The feature importance analysis suggested that CO, O3 and NO2, SO2 and PM10, and PM2.5 are most affected by temperature, humidity, PM2.5, and PM10, respectively. Thus, temperature and humidity were the primary factors affecting the variability in pollutant concentrations. The conclusions confirm that the DL models achieve significant accuracy and serve as essential instruments for managing air pollution, providing practical insights for decision-makers to adopt efficient air quality control strategies.

A study of indoor air pollution caused by disinfection equipment as a consequence of infectious waste management

Infectious waste disinfection is an essential process in medical waste management that may cause release of some pollutants. In this study, the PAHs concentration at the disinfection was investigated. The change in the release rate of PAHs in two including infectious waste reduction and increasing the segregation ratio was estimated. The results showed that the PAHs concentration was 1172 - 2066 ng/m3. The specific concentration of PAHs was 852 ng/ton of infectious waste in average. The annual emission of the PAHs resulting from infectious waste disinfection is estimated to be 612.6 kg. Reduction of infectious waste caused by redefining infectious waste and increasing the segregation ratio leads to reduction of PAHs concentration by 50%. Increasing the ratio of segregation and redefinition of infectious waste that led to reduced waste loading volume are essential measures that reduce the emissions of pollutants as by-products of disinfection.

Risk control of heavy metal in waste incinerator ash by available solidification scenarios in cement production based on waste flow analysis

Incineration is a common method in municipal solid waste management, which has several advantages such as reducing the volume of waste, but with concerns about exhaust gas and ash management. In this study, heavy metals in bottom ash, secondary furnace ash and fly ash of two waste incinerators in Tehran and Nowshahr were analyzed and its control in cement production was investigated. For this purpose, twelve monthly samples of three types of incinerator ash were analyzed. By combining the studied ashes in the raw materials, the quantity of metals in the cement was analyzed. Finally, by investigating four scenarios based on quantitative variations in the routes of municipal solid waste, ash quantity and the related risk caused by its heavy metals were studied. The results showed that the concentration of heavy metals in the three ash samples of the studied incinerators was 19,513-23,972 µg/g and the composition of the metals included Hg (less than 0.01%), Pb (2.93%), Cd (0.59%), Cu (21.51%), Zn (58.7%), As (less than 0.01%), Cr (15.88%), and Ni (0.91%). The best quality of produced cement included 20% ash and 10% zeolite, which was the basis of the next calculations. It was estimated that the reduction of the release of metals into the environment includes 37 gr/day in best scenario equal to 10.6 tons/year. Ash solidification can be considered as a complementary solution in waste incinerator management.

Analysis of the Temporal Distribution Characteristics of PM2.5 Concentration and Risk Evaluation of Its Inhalation Exposure

PM_2.5 poses a threat to human health. It is important to evaluate the potential risk of PM_2.5 inhalation exposure when people are located in different spatiotemporal activity locations. In this study, the PM_2.5 concentration was detected by the atmospheric cruise monitoring system (ACMS), a new detection technology used for city-wide PM_2.5 concentration monitoring. People were divided into eight categories of five typical activity patterns, including rest (R), sedentary behavior (SB), light physical activity (LPA), moderate physical activity (MPA), and vigorous physical activity (VPA). The PM_2.5 inhalation exposure risk was then estimated for these typical activities. The research results showed that the time sequence data of the ACMS had a similar tendency to change as those of the traditional air quality monitoring stations (AQMS). Although both passed the stationarity test, the relative error (RE) of the monthly average PM_2.5 concentration between the ACMS and AQMS was 7.5-14%. RE was usually lower when the individual air quality index (IAQI) of PM_2.5 was higher. Otherwise, RE was higher. The research results also showed that PM_2.5 exposure was positively correlated with PM_2.5 concentration, respiration rate, and human activity patterns. Because adults had a higher monthly average potential exposure (MAPE) than minors and that males had a higher MAPE than females. The potential exposure generated by LPA and MPA reached 50.76% of the total potential exposure (TPE). VPA brought about a 14.7% increase in the TPE. The research findings are helpful to understand the temporal distribution characteristics of PM_2.5 concentrations and guide the potential risk evaluation of PM_2.5 inhalation exposure.

The effect of PM2.5-related hazards on biomarkers of bronchial epithelial cells (A549) inflammation in Karaj and Fardis cities

Fine particles (especially PM2.5 particles) in ambient air can cause irreversible effects on human health. In the present study, seasonal variations in toxicity PM2.5 (cell viability and release of pro-inflammatory cytokines) were exposed human lung cells (A549) to concentrations of PM2.5 samples in summer (sPM2.5) and winter (wPM2.5) seasons. Cells were separately exposed to three concentrations of PM2.5 (25, 50, and 100 μg/mL) and three times (12 h, 1 and 2 days). We evaluated cell viability by MTT assay [3- (4, 5-dimethylthiazol-2-yl) -2, 5-diphenyltetrazolium bromide] and liberation of pro-inflammatory cytokines (interleukin-6 and interleukin-8) by the ELISA method. The toxicological results of this study showed that increasing the concentration of PM2.5 particulates and contact time with it reduces cell viability and increases inflammatory responses. Seasonal cytotoxicity of PM2.5 particles in high-traffic areas at summer season compared to winter season was lower. The lowest percent of viability at 2 days of exposure and 100 μg/mL exposure in the winter sample was observed. Also, PM2.5 particles were influential in the amount of interleukins 8 and 6. The average release level of IL-6 and IL-8 in the cold season (winter) and the enormous exposure time and concentrations (2 days-100 μg/mL) was much higher than in the hot season (summer). These values were twice as high for winter PM2.5 samples as for summer samples. The compounds in PM2.5 at different seasons can cause some biological effects. The samples' chemical characteristics in two seasons displayed that the PMs were diverse in chemical properties. In general, heavy metals and polycyclic aromatic hydrocarbons were more in the winter samples. However, the samples of wPM2.5 had a lower mass quota of metals such as aluminum, iron, copper, zinc, and magnesium. Concentrations of chromium, cadmium, arsenic, mercury, nickel, and lead were more significant in the sample of wPM2.5.

Potential cytotoxicity of PM2.5-bound PAHs and toxic metals collected from areas with different traffic densities on human lung epithelial cells (A549)

Laboratory and epidemiological researches have indicated that ambient air particulate matter have a plays critical role in causing diseases. The current research evaluated the chemical attributes of PM2.5 in the ambient air of the cities of Karaj and Fardis and determined its toxicological effects on human lung epithelial cells (A549). In the study city, 16 points were selected from the two high-traffic and low-traffic points for sampling. A sampling of ambient air was carried out in spring, summer, autumn, and winter 2018-19. Air sampling was performed for 24 h according to the EPA-TO/13A guidelines. To analyze of toxic metals and polycyclic aromatic hydrocarbons (PAHs), ICP-OES and GC-MS were used, respectively, and for cell toxicity analysis, an ELISA reader was used. Then from SPSS, Excel and R software were used for statistical analysis. The results of the current study indicated that the concentration of PAHs carcinogenic in the autumn season in high-traffic stations was the highest and equal to 9.3 ng/m3, and in the spring season in the low-traffic stations, it was the lowest and equal to 5.82 ng/m3. In general, during the period of study, Heavy metals including Zn, Fe, Pb, Cu, and Al had the highest concentration compared to other metals. However, Hg, Cr, As, Pb, Cu, Cd, and Zn were higher concentration in the winter and autumn seasons than in the spring and summer seasons. Cell viability measurements by using MTT showed that low-traffic and high-traffic stations had the highest toxicity in autumn season compared to other seasons. (p < 0.05). In general, high-traffic stations had the highest toxicity than low-traffic stations. The general conclusion of the present study was that PM2.5-bound PAHs and toxic metals, due to their high concentration, were toxic pollutants in air for residents of Karaj and Fardis. Also, the high concentration of PM2.5 caused the mitochondrial activity of A549 cells to stop and this stop was more significant in cold seasons and high-traffic areas.

Contamination of obsterics and gynecology hospital air by bacterial and fungal aerosols associated with nosocomial infections

Bacterial and fungal bioaerosols are a global concern due to nosocomial infections, especially in developing countries. Our study aimed to detect fungal and bacterial bioaerosols in different wards of an obstetrics and gynecology hospital air samples. 240 bioaerosol samples were collected by performing impaction method from different wards of a hospital in the central part of Iran, during two seasons. Fungi genera and bacteria species are recognized by cultivation. Concentrations of bacteria and fungi were ranged from 44 to 75 CFU/m3 and 8 to 22 CFU/m3, respectively. Labor Delivery and Recovery (LDR) and Emergency room had first and second most contaminated air among all the hospital wards. No significant difference between microbial load of wards which used natural ventilation and heating, ventilating, and air conditioning (HVAC) system was observed. The microbial load was not affected significantly by temperature, working shift, and Inpatient Bed Occupancy Rate (IBOR). Fungal load related significantly with relative humidity. Staphylococcus aureus (detected in 48.3% of samples) and Penicillium (27%) were the most predominant isolated bacteria and fungi, respectively. The results revealed that the level of bacteria and fungi responsible for nosocomial infections in the air of this hospital is very low. Although levels of microbial contamination are relatively low, it is important to investigate the effect of bioaerosols on nosocomial infections, especially in neonates.

Health risk assessment and source apportionment of heavy metals in atmospheric dustfall in a city of Khuzestan Province, Iran

The heavy metals in the atmospheric particulate matters are now considered a risk for humans and the environment. The purpose of this study was to assess the concentration, source apportionment, and health risk of heavy metals in atmospheric dustfall in Dezful City of Khuzestan Province, Iran. The dustfall samples were collected from five locations every month for one year (2018-2019). The heavy metals ( lead (Pb), cadmium (Cd), chromium (Cr), iron (Fe), and nickel (Ni)) contents of dustfall samples were determined by ICP-OES. The monthly mean of dustfall for five sampling locations was 22.81 ± 21.9 ton.km- 2.month- 1. The mean concentrations of the examined heavy metals were assessed as Fe > Cr > Ni > Pb > Cd. The highest enrichment level belonged to Cd (59.35 ± 128.18) and all heavy metals had enrichment levels beyond 10. The HI (Hazard Index) values were less than one and there was no significant non-carcinogenic risk due to these heavy metals. For children, Ni showed the most HI with a value of 0.205. The calculations demonstrate that the obtained values of cancer risk in both groups are less than the acceptable range (10- 6 to 10- 4). The PMF (Positive Matrix Factorization) results indicated four main sources of pollutants, namely, vehicular exhaust, industrial, road dust, and nonferrous smelting. The results of the study revealed that industrial activities and traffic play crucial roles in increasing the heavy metals contamination of dustfall in Dezful City.