Publications by authors named "Heidar Maleki"

6 Publications

  • Page 1 of 1

Temporal fluctuations of PM and PM, population exposure, and their health impacts in Dezful city, Iran.

J Environ Health Sci Eng 2020 Dec 18;18(2):723-731. Epub 2020 Jun 18.

Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Morbidity and mortality impacts of particulate matter (PM) are globally important health critical parameters. In this ecological-descriptive study, the health impact of PM and PM 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 PM. In this method, relationship between PM and PM mass concentrations were analyzed and calculated. The annual average concentrations of PM were 147.1, 114.3 and 158.8 μg/m, and the annual average concentration of PM were 57.8, 50.7 and 58.2 μg/m in 2013, 2014 and 2015, respectively. PM 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 PM and PM 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).
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http://dx.doi.org/10.1007/s40201-020-00498-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721840PMC
December 2020

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

Life Sci 2020 Feb 23;242:117210. Epub 2019 Dec 23.

Physiology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Iran National Science Foundation (INSF), Science Deputy of Presidency, Islamic Republic of Iran, Iran; Department of Physiology, Medicine Faculty, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Medicinal Plant Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. Electronic address:

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/m), DS1 (200-500 μg/m), DS2 (500-2000 μg/m) and DS3 (2000-8000 μg/m). 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.
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http://dx.doi.org/10.1016/j.lfs.2019.117210DOI Listing
February 2020

Air pollution prediction by using an artificial neural network model.

Clean Technol Environ Policy 2019 Aug 28;21(6):1341-1352. Epub 2019 May 28.

Environmental Engineering, School of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

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, NO, PM, PM, SO, and CO) across four sites, the correlation coefficient () 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, 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.
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http://dx.doi.org/10.1007/s10098-019-01709-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075317PMC
August 2019

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

Ecotoxicol Environ Saf 2018 Nov 1;163:558-566. Epub 2018 Aug 1.

Health and Environment Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

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, NH, Ca, Mg, HCO, NO, Cl and SO). Principle Component Analysis (PCA) was used to identify sources of the measured species. The equivalent concentration of the components followed the order of Ca > SO > HCO > NH > Cl > Na > NO > Mg. 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 Ca levels were observed in the industrial and high traffic areas, respectively. Na, Mg, and SO 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 (Ca, SO, Mg, NO, Cl), soil particles (Cl, Na, and HCO), and biomass burning (NH, 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.
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http://dx.doi.org/10.1016/j.ecoenv.2018.07.103DOI Listing
November 2018

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

Aeolian Res 2016 Sep 20;22:135-140. Epub 2016 Aug 20.

Social Determinants of Health Research Center, Yasuj University of Medical Science, Yasuj, Iran.

Ahvaz, Iran ranks as the most polluted city of the world in terms of PM concentrations that lead to deleterious effects on its inhabitants. This study examines diurnal, weekly, monthly and annual fluctuations of PM between 2009 and 2014 in Ahvaz. Health effects of PM levels are also assessed using the World Health Organization AirQ software. Over the study period, the mean PM level in Ahvaz was 249.5 µg m, with maximum and minimum values in July (420.5 µg m) and January (154.6 µg m), respectively. The cumulative diurnal PM profile exhibits a dominant peak between 08:00-11:00 (local time) with the lowest levels in the afternoon hours. While weekend PM levels are not significantly reduced as compared to weekdays, an anthropogenic signature is instead observed diurnally on weekdays, which exhibit higher PM levels between 07:00-17:00 by an average amount of 14.2 µg m as compared to weekend days. PM has shown a steady mean-annual decline between 2009 (315.2 µg m) and 2014 (143.5 µg m). 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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http://dx.doi.org/10.1016/j.aeolia.2016.08.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422000PMC
September 2016

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

Environ Sci Pollut Res Int 2017 May 29;24(13):12360-12371. Epub 2017 Mar 29.

Master of Environmental Engineering, School of Science Water Engineering, Shahid Chamran University of Ahvaz, 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 PM and PM 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.
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http://dx.doi.org/10.1007/s11356-017-8853-4DOI Listing
May 2017