The presence of microbes in airborne aerosol particles, especially dust, is a major public health concern in desert regions. This study is the first of its kind to examine the effect of dust storms ...on indoor and outdoor microbial air quality at a hospital on the western side of Iran (city of Ahvaz), which is notorious for being highly vulnerable to dust emissions. Air samples were collected inside and outside of the hospital environment for six months, with the unique advantage of this study being that the region and duration of measurements allow for a clear comparison between dusty and normal days. On normal days, the average concentrations (outdoor/indoor) of bacteria and fungi were 423/329 cfu m−3 and 596/386 cfu m−3, respectively, which increased to 1257/406 cfu m−3 and 1116/550 cfu m−3 on dust event days. Indoor/Outdoor ratios for bacteria and fungi are lower on dust event days (0.26–0.60) versus normal days (0.44–0.95). Bacillus spp., Micrococcus spp., Streptomyces spp., and Staphylococcus spp. were the dominant bacteria both indoors and outdoors on normal and dust event days. Gram positive bacteria exhibited higher concentrations than Gram negative bacteria in both outdoor and indoor air samples as well as during both normal and dust event days. The data suggest that Gram positive bacteria are more resistant to undesirable outdoor conditions (e.g., high incident solar radiation) as compared to Gram negative ones. These results have implications for other populated arid regions where more stringent control of indoor air quality can greatly benefit public health.
•Bioaerosol composition measurements in and outside of a hospital in Ahvaz, Iran.•Outdoor bioaerosol are shown to impact indoor hospital air quality.•Bacteria and fungi concentrations higher on dusty days in and out of hospital.•Indoor:outdoor ratios of bioaerosol lower on dusty days (≤0.60) versus normal days.•Gram positive bacteria exhibit higher concentrations than Gram negative bacteria.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Particulate matter (PM) represents a criteria air pollutant (CAP) influencing health, climate, cloud properties, economy, agriculture, and the environment. Numerous studies on this subject have ...classified dust events based on wind speed, visibility, and PM
10
levels. The purpose of this study was to evaluate PM
10
with a wider range of meteorological parameters and CAPs during different dust storms. Moreover, spatiotemporal and geometrical properties of dust storms were analyzed over the city of Ahvaz between 2012 and 2015. Meteorological parameters included those obtained from the Iran Meteorological Organization (IMO) as well as CAPs from the Ahvaz Environmental Protection Organization (AEPO). During the study period, 68 dust storms were investigated, with sources identified by the AEPO. The highest levels of PM
10
were 2877.2, 1327, 2146, 2094, and 1218 µg m
−3
during local storms (LS), dusts from Iraq (DI), dust from both sources (DBS), and 1 and 2-peak dust events, respectively. The criteria levels of wind speed, relative humidity, and air temperature also shifted 3 h forward when the severity of dust storms decreased and their durations increased. Strong correlation coefficients (R
2
) were observed between PM
2.5
and PM
10
ranging from 0.88 to 0.95 for dust storms falling within each of the five classifications. The highest ascending and the lowest descending slopes belonged to dusts from DBS (600.3 µg m
−3
h
−1
) and DI (73 µg m
−3
h
−1
), respectively. These results have relevance to planning and mitigation strategies for combating different types of dust storms in Ahvaz.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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 (O
3
, NO
2
, PM
10
, PM
2.5
, SO
2
, 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.
Graphical abstract
Ahvaz, Iran ranks as the most polluted city of the world in terms of PM
10
concentrations that lead to deleterious effects on its inhabitants. This study examines diurnal, weekly, monthly and annual ...fluctuations of PM
10
between 2009 and 2014 in Ahvaz. Health effects of PM
10
levels are also assessed using the World Health Organization AirQ software. Over the study period, the mean PM
10
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 PM
10
profile exhibits a dominant peak between 08:00–11:00 (local time) with the lowest levels in the afternoon hours. While weekend PM
10
levels are not significantly reduced as compared to weekdays, an anthropogenic signature is instead observed diurnally on weekdays, which exhibit higher PM
10
levels between 07:00–17:00 by an average amount of 14.2 µg m
−3
as compared to weekend days. PM
10
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.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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.
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.
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.
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.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Air pollution is considered as one of the major causes of environmental health problems. Young children and infants are more susceptible than adults due to age and higher sensitivity to environmental ...hazards. The aim of the present study was to an investigation of indoor/outdoor, regional and seasonal variations of airborne bacteria and PM concentrations of six randomly selected child day-care centers (DCCs) in greater Ahvaz. bio-aerosol sampling, PM measurement, and meteorological parameters data capture were performed monthly in DCCs of industrial, high traffic and residential regions during autumn, winter, and spring. The results revealed that the highest and the lowest of indoor and outdoor of mean concentrations of airborne bacteria were observed in the DCCs in the high traffic regions and residential area, respectively. The monthly highest and the lowest mean of culturable bacteria was determined in February (812 CFU/m3) and November (188 CFU/m3), respectively. There is a positive correlation between concentrations of PM and airborne bacteria in the DCCs during the study. The highest mean concentrations of airborne bacteria in indoor air samples were measured in winter season in high traffic and residential regions with 789 CFU/m3 and 646 CFU/m3, respectively, this value for outdoor samples was determined in spring and winter seasons at industrial and residential regions with 335.41 CFU/m3 and 306.34 CFU/m3, respectively. The highest and the lowest indoor/outdoor (I/O) ratio of mean concentrations of bacteria were determined in the autumn and spring at the industrial region with I/O ratio of 23.17 and 1.37, respectively. In the indoor and outdoor conditions of all DCCs, the Gram-positive bacteria were the dominant species which shows higher concentration than Gram-negative bacteria. The dominant bacterial genera were Bacillus spp. and Staphylococcus spp. in air samples. The results of the present study suggest strongly that instead of natural ventilation using windows, use of artificial ventilation and air conditioning systems could improve indoor air quality (IAQ) in the DCCs. Facial air filters and air treatment devices are recommended particularly at the time of dust event days in cities like Ahvaz.
•Bacteria communities of daycare centers in different region/season were examined.•The I/O ratio for PM and bacteria in different region/season was calculated.•The dust storm was a major driver for increasing PM and bacteria concentration.•The predominant bacteria of identified isolates were attributed to Gram positive bacteria.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The sudden occurrence of dust storms results in significant economic damage, with additional negative impacts on public health and welfare. This study investigates one of the most vulnerable areas of ...the world to dust storms (Ahvaz, Iran) to determine whether there are any meteorological parameters with predictive skill through which weather forecasters can confidently warn the public about the likelihood of an impending dust storm the following day. To this end, this study focuses on data including meteorological parameters, visibility and particulate matter mass concentrations for both dust event days and preceding days for the period between 2008 and 2016. Data were obtained for four monitoring stations (Naderi, Havashenasi, Edareh Kol and Behdasht) from the Iran Meteorological Administration and Khuzestan Environmental Protection Organization. Pearson correlation coefficients were used to identify influential parameters for dust storm prediction, and an artificial neural network (ANN) approach was applied to predict the maximum dust concentration. Minimum dew point temperature 1 day prior to dust occurrences showed a significant correlation (
p
-value < 0.01) with the maximum 3-h mean PM
10
concentration during dusty days. A less significant relationship (
p
-value = 0.045) was found when using the minimum dew point temperature from 2 days before dust occurrences. Using the minimum dew point temperature from 1 day before dust events with ANN resulted in strong forecasting skill for the maximum 3-h mean PM
10
concentration during dusty days (
R
2
= 0.71). Therefore, dew point temperature may provide predictive skill for the next day’s dust events.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This study aimed to survey the concentration of PM10 and heavy metals (cadmium, chromium, cobalt, nickel, lead, and zinc) on normal and dusty days in Ahvaz, Iran. Concentrations of PM10 in a ...high-traffic area of the city were measured from October 2012 to September 2013 using a high-volume sampler (HVS). Extracted heavy metals were speciated and quantified using Inductivity Coupled Plasma Optical Emission Spectrometry (ICP-OES). The results of this study showed that the average concentration of PM10 in the autumn (October, November, and December), winter (January, February, and March), spring (April, May, and June), and summer (July, August, and September) was 131, 189, 145, and 127 µg/m3 on normal days, respectively. The corresponding values on dusty days were 410, 742, 300, and 278 µg/m3, respectively. The concentrations of the heavy metals during dusty days were higher than those on normal days. The ratio of the overall mean concentration of the heavy metals on dust storm days relative to normal days (D/N ratio) ranged from 1.21 to 2.53. Due to the importance and impacts of PM10 and associated heavy metals on human health, further studies should be conducted to evaluate the concentrations, impacts, and the associated diseases during pollution periods to establish and implement strategies to minimize harmful effects of PM inhalation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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.
•Characterization of the chemical composition of rainwater in the most polluted city of the world was carried out.•The pH of the rainwater was higher than that of expected due to neutralization by alkaline dust particles.•Sources contributions of the ions in the rainwater were identified.•Anthropogenic inputs and crustal sources were the primary contributors to the rainwater chemistry.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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 O
3
, NO
2
, CO, SO
2
, PM
10
and PM
2.5
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 O
3
, NO
2
, PM
10
and PM
2.5
were higher in Ahvaz than Tehran while Tehran was more pollutant in terms of CO and SO
2
. Diurnal variations of O
3
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 SO
2
. PM
2.5
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 PM
2.5
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.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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