Ramin Nabizadeh Nodehi, Ph.D.
Vol 2 No 2 (2017): Spring 2017
Introduction: Among air pollutants, particles are the primary and major pollutant. Particulate matters in closed environments like underground subway stations have many severe effects on human health. The aim of this study was to evaluate the concentration of PM in various parts of indoor and outdoor air line 1 of Tehran subway stations.
Materials and methods: Surveys were conducted during peak- hours of working days in January 2016 using a portable photometric aerocet 531 sampler. Samples were taken from indoor and outdoor air at each station from platform.
Results: The highest PM concentration was observed at Darvazeh Dowlat Station ( PM2.5, PM10 and TSP were 48, 108 and 140 μg/m3 ). The highest PM concentration is related to the evening, beginning of the platforms and the lowest PM concentration is related to the before noon. As can be seen, PM2.5 / PM10 ratio ranges from 0.45 to 0.50 and PM10 / TSP ratio from 0.55 to 0.65.
Conclusions: The results of this study indicate that the average concentration of PM2.5 in Tehran metro stations was higher than EPA and there was a strong correlation between PM concentrations at platform station and outdoor air. Also air quality in metro stations was inappropriate.
Introduction: Understanding public attitudes for planning policies and actions to control air pollution is important. Attitude is partially socially constructed and thus must be studied in each area separately, rather than inferred from other settings. This study was aimed to evaluate the knowledge and attitudes of university students about the air pollution sources and solutions in Tehran.
Material and methods: 200 students of Shahid Beheshti University of Medical Sciences (SBMU) during 2015 - 2016 years were selected by random sampling. The questionnaires were used to collect data consisted of four parts: demographic information, knowledge, attitude, and solutions for reducing air pollution.
Results: Most of the participants were 18 - 22 years old, male, single, studying in bachelor degree, and from Tehran. Significant correlations were found between attitude on one side and age, gender, marital status, and education level on the other side. The most approved solutions for air pollution by students were improvement of the quality of fuel (84.7%) and vehicles (79.7%), and development of green space (76.2%).
Conclusions: Educational programs must be designed to raise the level of public attitude about air pollution. Citizens should be a part of any solution for environmental problems.
Introduction: The increase in noise pollution is a common problem in most countries, raising public health concerns in the workplace. This paper presents the results of a noise survey in different care units of Tabriz Children’s Hospital, Iran.
Materials and methods: The present cross- sectional observational research was conducted to assess 24 h noise levels in 5 pediatric care wards (neonatal, infectious, internal, NICU, and emergency) using two TES - 1358 sound level meters in the autumn of 2016. Noise level was measured as maximum level (Lmax), minimum level (Lmin), and equalizing level (Leq).
Results: Mean 24 h sound level was the highest in the emergency ward (69.65 ± 1.68). The highest mean sound level in morning, afternoon, and night shifts also belonged to the emergency ward (69.53 ± 0.27, 69.30 ± 0.39, and 69.85 ± 0.43, respectively). There was no significant difference (Pvalue > 0.05) in mean sound level in the emergency ward among different work shifts. The highest and most fluctuating noise values were related to the day time, between 10:00 and 17:00 (i.e. including morning and afternoon) in all the wards, except for the emergency ward.
Conclusions: The results of this study demonstrate a noise problem in Tabriz children’s hospital. The sound levels measured in all locations and at all times were higher than the recommended levels. This can have an adverse effect on the health of staff and patients, decreasing the professional performance of the personnel in various hospital units. Therefore, the sound level in different units of the hospital should be reduced to the suggested values by implementing effective noise control and prevention measures.
Introduction: Predicting PM10 concentration as a significant risk factor for anumber of pollution related diseases has been recently inevitable task for areas with high population density particularly for areas with no updating monitoring systems. This study aims to illustrate how PM10 concentration level can be predicted by the prior information of the air pollutants and the meteorologicalfactors in urban areas.
Materials and methods: The data we used are measured from four monitoringstations in the city of Tehran between January 2012 and December 2014. We use the Auto-regressive group method of data handling (AR - GMDH) neuralnetwork approach which employees the prior stationary time series data setting.
Results: Our results demonstrate that PM10 concentration level for a specific dayis more likely to be predictable by sulfur dioxide (SO2) and nitrogen dioxide (NO2) than the carbon monoxide (CO) concentrations, and also show thatPM10 concentration is positively associated with precipitation and wind speedand with high temperature. The accuracy of the predicted values of the PM10 concentration is evaluated by inspecting the coefficient of determination, meansquared error, the square root of mean squared error, mean absolute deviation, and index of agreement.
Conclusions: The AR - GMDH algorithm can be proposedin comparison with the chemical and physical approaches due to its accuracyand simplicity, and its cost efficiency.
Introduction: Large amount of CO2 emissions from combustion of fossil fuels will lead to environmental crisis. One method for removing CO2 is adsorption by modified adsorbents. In this study, mesoporous silica, MCM- 41, modified by mono- ethanolamine, was used for CO2 removal from exhaust gases of methane combustion.
Materials and methods: MCM- 41 was synthesized by using tetraethyl orthosilicate (TEOS) as silica source, according to classic method. MCM- 41 was modified with different amounts (25, 50 and 75 %) of monoethanol amine (MEA) by impregnation method. Amine modified MCM- 41 were used in filters and adsorption experiments were conducted to determine adsorption capacity by passing CO2 in different concentrations (2000 -5000 ppm), different flow rates (100 – 400 ml/min), and different temperatures (25, 55 and 90 °C) individually. CO2 was analyzed by ND IR CO2 analyzer.
Results: Time to reach adsorption equilibrium of carbon dioxide on to examined adsorbents was about 10 h. Maximum carbon dioxide adsorption capacity for MCM- 41 was determined 5.0 mg/g. Maximum adsorption rate was due to MCM41- MEA 50 % with adsorption capacity of 50 mg/g for CO2 concentration of 5000 ppm. By increasing temperature from 25 to 90 °C, adsorption capacity was increased only about 10 %. Maximum CO2 adsorption capacity was achieved at gas flow rate of 100 mL/min, and by increasing flow rate, capacity was decreased. By increasing amine loaded on MCM, CO2 adsorption capacity was decreased.
Conclusions: Modification of MCM- 41 using monoethanol amine by simple impregnation method will result in the production of adsorbents with a higher absorption capacity for carbon dioxide removal. By using amine modified MCM- 41, it is possible to remove carbon dioxide from exhaust gases of methane combustion.
Introduction: UV index is a precaution index that shows level of exposure to sunlight UV. UV index can be calculated by the related formula according to solar spectral irradiance (Eλ). But this formula and others like this are mostly used when sky is clear. The aim of this investigation is determination of effect of PM2.5 and NO2 concentration on UV index.
Material and methods: Two points with the same altitude were chosen and the PM2.5 and NO2 concentrations, and UV index were measured 4 h every day from 11am to 3 pm, in these points during one month from 15 October till 15 November 2016.
Results: Simple and interaction regression models showed significant reverse relationship between contaminants concentration and UVI (Pvalue ≤ 0.05), although the effect of PM2.5 concentration was more significant than NO2 (Pvalue ≤ 0.001), in both point.
Conclusions: There is a strong correlation between PM2.5 concentration and decrease in UV index. Also a significant correlation between NO2 concentration and UV index was found and any significant correlation between UV index and interaction effect of NO2 - PM2.5 was not appeared. Results of this study showed that air pollutants concentration can reduce UV index, thus it can change the risk of skin eczema and skin cancer.