The impact of meteorological parameters on PM10 and visibility during the Middle Eastern dust storms.

Air pollution is one of the most pressing issues in populated Middle Eastern cities, in particular for the city of Ahvaz, Iran, imposing deleterious effects on the environment, public health, economy, culture, and other sectors. In this study, we investigate the relationship between meteorological parameters, PM10, AOD, air mass source origin, and visibility during severe desert dust storms (Average3h PM10 > 3200 µg m-3) between 2009 and 2012. Six of seven such events occurred between February and March. Interestingly, for the seven cases there was always an alarming PM10 mass concentration peak (137-553 µg m-3) between 12:00-18:00 (local time) that was 18-24 h before the dominant peak of the storm (3279-4899 µg m-3). The maximum wind speed over the multi-day periods examined for the dust storms is usually observed 6 h before the alarming PM10 peak. The minimum relative humidity, dew point temperature and air pressure occurred ± 3 h around the time of the alarming PM10 peak. Wind speed was the meteorological parameter that was consistently higher around the time of the first peak as compared to the second peak, with the reverse being true for sea level pressure. Based on four years of daily data in Ahvaz, PM10 was positively correlated with wind speed and air temperature and inversely correlated with sea level pressure and RH. An empirically-derived equation with R2 = 0.95 is reported to estimate the maximum PM10 concentration for severe desert dust events in the study region based on meteorological parameters. Finally, AOD is shown to correlate strongly (R2 = 0.86) with PM10 during periods with severe desert dust storms in the region.

Temporal profiles of ambient air pollutants and associated health outcomes in two polluted cities of the Middle East.

Dust storms and particulate matters had been increased due to climate change in the Middle East. On the other hand, urbanization and industrialization raised levels of gaseous air pollutants in all big cities. In the current study, air pollution information collected from Environmental Protection Agency of Khuzestan and Tehran containing hourly O3, NO2, CO, SO2, PM10 and PM2.5 concentrations between 2014 and 2015. This study evaluated the air quality of these two cities by Air Quality Index (AQI). As a result, mean concentrations of O3, NO2, PM10 and PM2.5 were higher in Ahvaz than Tehran while Tehran was more pollutant in terms of CO and SO2. Diurnal variations of O3 in weekend were the only trend located above weekday variations along the daytimes. Hourly variations of all pollutants changed with a wider range of concentrations in Ahvaz. Diurnal peaks of all pollutants showed their highest level on Monday as the busiest day in mega city, Tehran with the exception of SO2. PM2.5 was the worst and limiting pollutant for both cities. Accordingly, winter was the most polluted season by 77 and 33 µg m-3 in Ahvaz and Tehran, respectively. Number of clean days was significantly lower in Ahvaz (no-day) than mega city, Tehran (<17 days). The number of unhealthy days was also presented significantly higher in Ahvaz (>186 days). Although, annual PM2.5 concentrations were more in Ahvaz, the higher at-risk population in Tehran caused more health endpoints in the capital of Iran. Consequently, both cities should have their own especial pattern to control air pollution and attributed health damages.

Effect of Total Suspended Particulate Matter in the Air on Inflammation Factors and Apoptotic Markers in Diabetic Rats: The Protective Effect of Insulin and Crocin.

BACKGROUND: The effect of total suspended particulate matter (TSP) was investigated on the expression of inflammatory and apoptotic factors in diabetic rats, and the effect of crocin and insulin was examined on these factors. METHODS: Fifty-four adult male wistar rats were divided into nine experimental groups: control group, crocin group (received crocin, 50 mg/kg), diabetic group (received a single dose of alloxan at 120 mg/kg, IP), TSP group (5 mg/kg TSP instilled intratracheally), diabetic-crocin group (received crocin at 50 mg/kg after the induction of diabetes by alloxan (120 mg/kg)), diabetic-insulin group (received regular insulin (5 U/kg), crocin-TSP group (received crocin at 50 mg/kg, IP, and then 5 mg/kg TSP was instilled intratracheally), diabetic-TSP-insulin group (after receiving alloxan (120 mg/kg) and instilling TSP (5 mg/kg, intratracheally), a single dose (5 U/kg) of regular insulin), and diabetic-TSP-crocin group (after receiving alloxan (120 mg/kg) and instilling TSP (5 mg/kg, intratracheally), a single dose of crocin (50 mg/kg, IP)). Quantitative real-time PCR was performed to measure the expression of the mRNAs of apoptotic (Bax and Bcl2) and inflammatory mediators (TNFα, COX2, iNOS/eNOS) in Wistar rats. RESULTS: In diabetic and TSP groups the inflammatory factors and BAX/Bcl2 ratio significantly increased compared to the control group. In diabetic-TSP-insulin and diabetic-TSP-crocin, a significant decrease was observed in the rate of inflammatory factors and BAX/Bcl2 ratio. CONCLUSION: The results suggested that diabetes and exposure to TSP increase the rate of apoptosis and inflammation, and also demonstrated the anti-apoptotic and anti-inflammation role of insulin and crocin.

Contrasting Iran's air quality improvement during COVID-19 with other global cities.

BACKGROUND AND PURPOSE: In late 2019, a novel infectious disease (COVID-19) was identified in Wuhan China, which turned into a global pandemic. Countries all over the world have implemented some sort of lockdown to slow down its infection and mitigate it. This study investigated the impact of the COVID-19 pandemic on air quality during 1st January to 30th April 2020 compared to the same period in 2016-2019 in ten Iranian cities and four major cities in the world. METHODS: In this study, the required data were collected from reliable sites. Then, using SPSS and Excel software, the data were analyzed in two intervals before and after the corona pandemic outbreak. The results are provided within tables and charts. RESULTS: The current study showed the COVID-19 lockdown positively affected Iran's air quality. During the COVID-19 pandemic, the four-month mean air quality index (AQI) values in Tehran, Wuhan, Paris, and Rome were 76, 125, 55, and 60, respectively, which are 8 %, 22 %, 21 %, and 2 % lower than those during the corresponding period (83, 160, 70, and 61) from 2016 to 2019. CONCLUSIONS: Although the outbreak of coronavirus has imposed devastating impacts on economy and health, it can have positive effects on air quality, according to the results.

Temporal fluctuations of PM2.5 and PM10, population exposure, and their health impacts in Dezful city, Iran.

Morbidity and mortality impacts of particulate matter (PM) are globally important health critical parameters. In this ecological-descriptive study, the health impact of PM10 and PM2.5 associated with there temporal variations in Dezful city were assessed from 2013 to 2015. AirQ+ software handles the PM air pollutants by addressing impact evaluation and life table evaluation. We used a new method to analysis fine particles feature by using regular daily observations of PM10. In this method, relationship between PM2.5 and PM10 mass concentrations were analyzed and calculated. The annual average concentrations of PM10 were 147.1, 114.3 and 158.8 µg/m3, and the annual average concentration of PM2.5 were 57.8, 50.7 and 58.2 µg/m3 in 2013, 2014 and 2015, respectively. PM10 also had obvious diurnal variations with highest hourly concentrations in 13:00 and 22:00 but the lowest concentrations often occurred in 05:00 and 16:00. Unexpectedly, in weekends the concentration of PM pollutants appeared to have increased from 18:00 to midnight. The daily based analysis showed that there are 147 dusty days in the study period during which the most severe dusty day occurred in 2014. Over the study period, mean levels of PM10 and PM2.5 in both conditions were higher in 2015 compare to 2013 and 2014, which probably is due to higher frequency of dust storms in 2015. Hence, during 2015 and 2013 they're were higher morbidity and mortality compare to 2014 due to exposure to higher polluted air with PMs in all cases except lung cancer (LC).

Exposure to ambient dusty particulate matter impairs spatial memory and hippocampal LTP by increasing brain inflammation and oxidative stress in rats.

OBJECTIVES: Exposure of healthy subjects to ambient airborne dusty particulate matter (PM) causes brain dysfunction. This study aimed to investigate the effect of sub-chronic inhalation of ambient PM in a designed special chamber to create factual dust storm (DS) conditions on spatial cognition, hippocampal long-term potentiation (LTP), inflammatory cytokines, and oxidative stress in the brain tissue. METHODS: Adult male Wistar rats (250-300 g) were randomly divided into four groups: Sham (clean air, the concentration of dusty PM was <150 µg/m3), DS1 (200-500 µg/m3), DS2 (500-2000 µg/m3) and DS3 (2000-8000 µg/m3). Experimental rats were exposed to clean air or different sizes and concentrations of dust PM storm for four consecutive weeks (exposure was during 1-4, 8-11, 15-16 and 20-23 days, 30 min, twice daily) in a real-ambient dust exposure chamber. Subsequently, cognitive performance, hippocampal LTP, blood-brain barrier (BBB) permeability and brain edema of the animals evaluated. As well as, inflammatory cytokines and oxidative stress indexes in the brain tissue measured using ELISA assays. RESULTS: Exposing to dust PM impaired spatial memory (p < 0.001), hippocampal LTP (p < 0.001). These disturbances were in line with the severe damage to respiratory system followed by disruption of BBB integrity (p < 0.001), increased brain edema (p < 0.001), inflammatory cytokines (p < 0.001) excretion and oxidative stress (p < 0.001) in brain tissue. CONCLUSIONS: Our study showed that exposure to ambient dust PM increased brain edema and BBB permeability, induced memory impairment and hippocampal LTP deficiency by increasing the inflammatory responses and oxidative stress in the brain of the rats.

Air pollution prediction by using an artificial neural network model.

Air pollutants impact public health, socioeconomics, politics, agriculture, and the environment. The objective of this study was to evaluate the ability of an artificial neural network (ANN) algorithm to predict hourly criteria air pollutant concentrations and two air quality indices, air quality index (AQI) and air quality health index (AQHI), for Ahvaz, Iran, over one full year (August 2009-August 2010). Ahvaz is known to be one of the most polluted cities in the world, mainly owing to dust storms. The applied algorithm involved nine factors in the input stage (five meteorological parameters, pollutant concentrations 3 and 6 h in advance, time, and date), 30 neurons in the hidden phase, and finally one output in last level. When comparing performance between using 5% and 10% of data for validation and testing, the more reliable results were from using 5% of data for these two stages. For all six criteria pollutants examined (O3, NO2, PM10, PM2.5, SO2, and CO) across four sites, the correlation coefficient (R) and root-mean square error (RMSE) values when comparing predictions and measurements were 0.87 and 59.9, respectively. When comparing modeled and measured AQI and AQHI, R 2 was significant for three sites through AQHI, while AQI was significant only at one site. This study demonstrates that ANN has applicability to cities such as Ahvaz to forecast air quality with the purpose of preventing health effects. We conclude that authorities of urban air quality, practitioners, and decision makers can apply ANN to estimate spatial-temporal profile of pollutants and air quality indices. Further research is recommended to compare the efficiency and potency of ANN with numerical, computational, and statistical models to enable managers to select an appropriate toolkit for better decision making in field of urban air quality.

On the chemical nature of precipitation in a populated Middle Eastern Region (Ahvaz, Iran) with diverse sources.

This study reports on the chemical composition of rainwater collected at three ground sites with varying degrees of pollution in Ahvaz, Iran, between January 2014 and February 2015. A total of 24 rainwater samples were analyzed for pH and concentrations of trace elements (Fe, Al, Pb, and Cd) and major ions (Na+, NH4+, Ca2+, Mg2+, HCO3-, NO3-, Cl- and SO42-). Principle Component Analysis (PCA) was used to identify sources of the measured species. The equivalent concentration of the components followed the order of Ca2+ > SO42- > HCO3- > NH4+ > Cl- > Na+ > NO3- > Mg2+. The average pH of the rainwater samples was 6, and only three events exhibited acidic conditions below a pH of 5.6. The lowest and the highest average pH values were observed in the high traffic area (5.96) and industrial area (6.54), respectively. The highest and lowest Ca2+ levels were observed in the industrial and high traffic areas, respectively. Na+, Mg2+, and SO42- exhibited their highest and lowest concentrations in the industrial and high traffic areas, respectively. 70.36% of the total variance was due to anthropogenic species (Ca2+, SO42-, Mg2+, NO3-, Cl-), soil particles (Cl-, Na+, and HCO3-), and biomass burning (NH4+, pH). The results of this study show that local anthropogenic sources and Middle Eastern Dust (MED) storms affect the rainwater chemistry strongly, which the latter stems from the Arabian Peninsula, Kuwait, Iraq, and some parts of Iran.

Comparison of normal and dusty day impacts on fractional exhaled nitric oxide and lung function in healthy children in Ahvaz, Iran.

Children are the vulnerable group at risk of adverse health effects related to air pollution due to dust storm in Ahvaz. The purpose of this study was to compare the values of fractional exhaled nitric oxide (FENO) and lung functions as parameters of adverse health effects of particulate matter (PM) in dusty and normal (non-dusty) days in elementary schoolchildren. The study was conducted among elementary school students in Ahvaz. The healthy elementary schoolchildren (N = 105) were selected from different districts for FENO and lung function sampling during the dusty and normal days. The values of PM10 and PM2.5 during dusty days were higher than during normal days. Mean values of FENO during the normal and dusty days were 14.23 and 20.3 ppb, respectively, and the difference between these values was statistically significant (p < 0.05). Lung function results showed a statistically significant difference between the mean values of forced vital capacity during the dusty and normal days (p < 0.05). The results revealed a significant difference both in the values of inflammatory biomarker and in the lung function tests in dusty and normal days. Based on our results, fractional exhaled nitric oxide could be a useful short-term biomarker of particulate pollution effect coupled with spirometry.

Temporal profile of PM10 and associated health effects in one of the most polluted cities of the world (Ahvaz, Iran) between 2009 and 2014.

Ahvaz, Iran ranks as the most polluted city of the world in terms of PM10 concentrations that lead to deleterious effects on its inhabitants. This study examines diurnal, weekly, monthly and annual fluctuations of PM10 between 2009 and 2014 in Ahvaz. Health effects of PM10 levels are also assessed using the World Health Organization AirQ software. Over the study period, the mean PM10 level in Ahvaz was 249.5 µg m-3, with maximum and minimum values in July (420.5 µg m-3) and January (154.6 µg m-3), respectively. The cumulative diurnal PM10 profile exhibits a dominant peak between 08:00-11:00 (local time) with the lowest levels in the afternoon hours. While weekend PM10 levels are not significantly reduced as compared to weekdays, an anthropogenic signature is instead observed diurnally on weekdays, which exhibit higher PM10 levels between 07:00-17:00 by an average amount of 14.2 µg m-3 as compared to weekend days. PM10 has shown a steady mean-annual decline between 2009 (315.2 µg m-3) and 2014 (143.5 µg m-3). The AirQ model predicts that mortality was a health outcome for a total of 3777 individuals between 2009 and 2014 (i.e., 630 per year). The results of this study motivate more aggressive strategies in Ahvaz and similarly polluted desert cities to reduce the health effects of the enormous ambient aerosol concentrations.