Journal of Air Pollution and Health
Volume:6 Issue: 4, Autumn 2021

Adverse effects of air pollution on human health has been identified as a major concern worldwide. We conducted this study to investigate the association between prenatal exposure to ambient air pollution and Low Birth Weight (LBW) and preterm among newborns in the megacity of Tehran.

This cross-sectional study was carried out on 1605 newborns. Data on the residential locations of mothers were collected from birth certificates. To estimate the prenatal exposure to air pollutants, data of 21 air quality monitoring stations in Tehran were used. The Man-Whitney test was used to estimate the association between exposure to ambient air pollution and LBW and preterm.

The mean birth weight in our analyses was 3117 g. A significant association was found between maternal exposure to particulate matter less than 2.5 µm (PM2.5) in the first trimester and incidence of preterm (p=0.011) and LBW (p=0.003) in newborns. Also, a close association was observed between exposure to Carbon Monoxide (CO) in the first and second trimesters and LBW (p=0.002, p=0.015). There were no statistically significant associations in LBW in the case of Particulate Matter less than 10 µm (PM10), Sulfur Dioxide (SO2), and Ozone (O3).

The results revealed that the higher risk for LBW was related to ambient PM2.5 and CO. Since many factors may affect LBW, and the pathogenic mechanisms of the effect of air pollution on LBW have not been completely elucidated, the findings should be interpreted with caution and further studies need to be conducted on this issue considering the large sample size

Inadequate air quality is one of the environmental hazards factors imposing a significant number of deaths and complications of diseases on society. Therefore, it is highly important to determine the extent of its effects on health in communities. This study sought to assessment the concentration and additional short- and long-term mortality attributed to Particulate Matter less than 2.5 µm (PM2.5), Nitrogen Dioxide (NO2) and Ozone (O3) were observed in Ahwaz from 2012 to 2018 using AirQ+.

Daily and hourly concentrations of PM2.5, ozone and NO2 were obtained from Department of Environment in Ahvaz. Then, the mean concentration of 2.5 PM2.5 for 24 h, the mean concentration of NO2 for 1 h and the maximum concentration of O3 for 8 h daily were calculated using Excel 2010. Finally, to calculate the annual sum of maximum daily 8-h ozone means over 35 ppb (SOMO35) index, concentrations above 35 were collected and entered into the software.

The mean seven-year concentrations of PM2.5, NO2 and O3 were 68.21 (±135.86%), 24.46 (±22.79%) µg/m3 and 24.48 (±13.77%) ppb, respectively. The death rates of Ischemic Heart Disease (IHD), Chronic Obstructive Pulmonary Disease (COPD), lung cancer and Acute Lower Respiratory tract Infections (ALRI) and stroke related to PM2.5 were 2023, 128, 110, 23, 802, respectively. The number of respiratory deaths attributed
to ozone was 68.

The results show a high number of deaths due to bad weather in Ahvaz. It can be concluded that by designing and implementing appropriate and correct solutions and decisions, both health and economic losses are prevented.

Noise exposure is a common phenomenon in all personal life activities. Due to the prevalence of exposure to noise, many people are exposed to noise. Some of the harmful effects of noise on human health
have been proven so far. The purpose of this study was to experiment histopathological effects caused by exposure to white noise.

Four New Zealand white rabbits were exposed to 85±2 dB white noise for five consequent days. Heart, kidney, liver, and lung tissues were studied by the Hematoxylin and Eosin staining (H&E) method. The independent t-test was used for comparing the mean weight of tissues.

This study showed that exposure to 85±2 dB white noise did not significantly change heart and lungs tissues. Nevertheless, this study indicated that exposure to noise induced different pathological changes  in kidney and liver tissues. Exposure to noise made congestion, unclear brush border, and tubular cell vacuolization in kidney tissue. Moreover, eosinophilic cytoplasm was made by noise exposure in liver tissue. Furthermore, no statistically significant difference was detected in the mean tissue weight/mean body weight in rabbits.

This study showed that exposure to noise might be a risk factor for different renal and hepatic diseases. Nevertheless, more studies need to complete these results.

In the present study, the emission of Volatile Organic Compounds (VOCs) from gas stations located in the city of Khorramabad and its impact on the environment was investigated based on the AERMOD  dispersion model and the preparation of maps in Geographic Information System (GIS).

7 gas stations were randomly selected and the values of VOCs emission in two seasons of the year (winter and summer) were examined. The Phochek 5000 direct reading device was used to  measure VOC concentrations. R 3.6.3 was used for the data analysis.

The results showed that there was no significant difference among the gas stations in terms of VOCs emission (P>0.05). The highest mean concentration observed at gas station No. 6 with 7.7± 6.48 mg/m3 while  the lowest concentration was at gas station number 3 with a concentration of 0.52±0.18 mg/m3. The results from the anova revealed that there was a significant difference between the seasons in terms of the VOCs emission (P<0.05). The mean concentration of the VOCs was 3.58±2.77 mg/m3 in the summer and 2.53±2.4 mg/m3 in the winter.

Based on the results, the highest estimated concentration in the summer was recorded in the vicinity of gas station No. 6, which is located below Imam Hossein square. Due to the proximity of gas station No. 5 to gas station No. 6 as well as being in the direction of the prevailing wind, the concentrations of VOC emitted by these two gas stations will increase the estimated concentration around Imam Hossein square.

Studies in different parts of the world have shown that exposure to air pollutants has a negative effect on human health.

For statistical analysis between the dependent variable Particulate Matter less than 2.5 µm (PM2.5) concentration and independent variables (wind speed, precipitation, humidity, and temperature) R version 3.6.2 was used. Spearman correlation coefficient was used to determine the correlation between the parameters with the dependent variable. In addition, the multiple linear regression model was used to investigate the relationship and prediction between the independent variables and the dependent variable. In the present study, the effect of meteorological parameters on PM2.5 concentration in different seasons in Tehran in 2018 was studied using Pearson correlation and linear regression statistical analyzes.

Based on the results, it was found that PM2.5 had no significant relationship with meteorological parameters. Only in summer, there was a significant relationship between the dependent variable and the independent variable (wind speed) (p-value=0.01) and there was also an inverse relationship between these variables (r=-0.65). Multiple linear regression was also used to investigate the significant effect of independent variables on the dependent variable.

According to the coefficients of determination in this model, 47, 16, 45, and 20% of the dependent variable change in autumn, winter, spring, and summer, respectively, can be explained by meteorological parameters (independent). Due to the fact that the concentration of PM2.5 in Tehran is higher than the national standard, more attention of officials is necessary to improve air quality in Tehran.

Medical waste incinerator is a matter of concern for the environment and public health due to secondary pollutants. The present work aims to evaluate the toxic emissions from medical waste incineration, such as Polychlorinated Dibenzo-Dioxin/Furan (PCDD/Fs), Polycyclic Aromatic Hydrocarbons (PAHs), and the inorganic components in ambient air and ash. Hence, this study discusses several strategies to reduce emissions. For this purpose, searches were done in Scopus, Web of Science, and PubMed databases from 2000 to 2020. After the search, screening was done according to the predefined criteria, 96 papers were finally selected for this study. The results show that the emissions levels depend on many factors like the composition of the feeding, waste type, waste classification, segregation practice, types of incinerators, operation conditions (designed temperature, retention time, and excess oxygen), and air pollution control devices. For instance, emissions of Medical Waste Incinerators (MWIs) rise sharply with a decrease in temperature, increase in oxygen levels and chlorine content in waste, and the absence or weak function of air pollution control systems. This review prepared a comprehensive detailed for decision-makers to help them to understand the environmental consequences of using incinerators. However, there is a gap in finding efficient methods to reduce emissions of incinerators.