Tehran Megacity Research Articles

Modeling relationships between the network distance and travel time dynamics for assessing equity of accessibility to urban parks

ABSTRACT Static models of accessibility are usually based on the fixed distance or Average Travel Time (ATT) models. Because of ignoring the traffic as a dynamic process affecting the accessibility through the change of Travel Time (TT), these models lead to unperceived temporal inequities. In contrast to the consideration of the temporal Variation of TT (VTT) in the previous studies, the variation of traffic-related TT and its relations with network distance has not been considered. In this study, relations between VTT and network distance to access urban parks in Tehran megacity has been modeled. Traffic maps at five times of day are used to produce TT maps of Traffic Analysis Zones (TAZs) to their 3-closest parks. Comparison of the Gini coefficients of accessibility show significant inequities of accessibility at different times of day. Relations between the distance, ATT, and TT max are modeled by statistical analysis. Results show both TT and TT max have significant positive relations with distance and traffic and reach their maximum at 6 p.m. Observation of significant relations between distance, ATT, TT max, and VTT provides interesting knowledge for the conversion of temporal measures of equity (TT) to a physical measure of equity (distance). A simple application of these findings for effective management of the spatiotemporal inequities is the definition of critical distances from public services. As an example, to decrease the TT max of TAZs to less than 12 min, their maximum distance to the closest parks should be less than 4 km. The developed approach can be adopted for the accessibility evaluation of the other public services, particularly the health and education centers.

Aliphatic hydrocarbons in urban runoff sediments: a case study from the megacity of Tehran, Iran.

Urban runoff is known as an important contributor to diffuse a wide range of pollutants to receiving environments. Hydrocarbons are common contaminants in runoff mainly transported coupled to suspended particles and sediments. The aim of the study was to investigate the distribution and sources of Aliphatics in the sediments of Tehran's runoff drainage network. Thirty surface sediment samples were collected along with three main sub-catchments of Tehran during April 2017. The concentrations of n-Alkanes (nC-11-nC-35) and isoprenoids were determined by GC-MS, and their possible emission sources were evaluated using the biomarkers and the diagnostic ratios. Total aliphatic hydrocarbon (n-alkanes + isoprenoids) concentrations were found in the range of 2.94 to114.7mg.kg-1 dw with the total mean of 25.4mg.kg-1 dw in the whole catchment. The significant concentrations of n-alkanes between n-C20 and n-C24 indicate the predominance of petrogenic origins at all stations. The CPI values range from 0.7 to 3, except the station C1S28 (CPI = 4.2). The CPI values were less than 1.6 at 70% of the stations which indicate the petrogenic nature of the aliphatic origins. Pr/Ph and LMW/HMW ratios ranged from 0.3 to 2.5 and 0.3 to 5.6 confirmed the petrogenic sources as the major origin of Aliphatics in urban runoff sediments. The ratios of n-C17/Pr and n-C18/Ph vary from 0.4 to 2.1 and 0.2 to 2.1, respectively which showed that petroleum contamination is mainly due to the degraded oil products with a lesser extent of fresh oil. Results revealed that the aliphatic hydrocarbons in the sediment samples were derived mainly from petrogenic sources such as leakage and spillage of fuels and petroleum derivatives with a relatively low contribution of biogenic sources. Vascular plants' waxes and microbial activities are identified as the most important biogenic sources of the samples. The mean concentrations of total organic carbon were 13.3,12 and14.7mg.g-1 dw in the sub-catchments 1, 2, and 3, respectively. Pearson correlation test demonstrated a weak correlation between the concentrations of n-alkanes and TOC (P > 0.05) with a correlation coefficient of less than 0.54 for all the sub-catchments.

Earthquake Risk Assessment for Tehran, Iran

The megacity of Tehran, the capital of Iran, is subjected to a high earthquake risk. Located at the central part of the Alpine–Himalayan seismic belt, Tehran is surrounded by several active faults that show some M7+ historical earthquake records. The high seismic hazard in combination with a dense population distribution and several vulnerability factors mean Tehran is one of the top 20 worldwide megacities at a high earthquake risk. This article aims to prepare an assessment of the present-day earthquake risk in Tehran. First, the earthquake risk components including hazard, exposure, and vulnerability are evaluated based on some accessible GIS-based datasets (e.g., seismicity, geology, active faults, population distribution, land use, urban fabric, buildings’ height and occupancy, structure types, and ages, as well as the vicinity to some critical infrastructures). Then, earthquake hazard maps in terms of PGA are prepared using a probabilistic approach as well as a surface rupture width map. Exposure and vulnerability maps are also provided deterministically in terms of population density and hybrid physical vulnerability, respectively. Finally, all these components are combined in a spatial framework and an earthquake risk map is provided for Tehran.

The Psychometric Properties of the Persian Version of Childhood Experience of Care and Abuse Questionnaire (CECA).

Background: The present study aimed to determine the psychometric properties of the Persian version of the Childhood Experience of Care and Abuse Questionnaire (CECA.Q), a tool based on a retrospective interview with the child. Materials and Methods: To this aim, 251 adolescents from four regions of Tehran megacity completed the questionnaire. The reliability of the questionnaire was examined, along with the face and content validity. In addition, the construct validity was evaluated by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results: EFA and CFA supported a 4-factor solution including mother’s role scale items, father’s role scale items, maternal behavior scale items, and paternal behavior scale items. The total variance extracted in EFA ranged from 33.9 to 60.7. The internal consistency for mother’s role, father’s role, maternal behavior, and paternal behavior was 0.61, 0.65, 0.86, and 0.9 respectively. Thus, the questionnaire had a suitable fit, as well as reasonable reliability and validity. Conclusion: The Persian version of the CECA.Q had adequate reliability and validity as a self-report measurement for childhood experience of care and abuse.

The Psychometric Properties of the Persian Version of Childhood Experience of Care and Abuse Questionnaire (CECA)

Background: The present study aimed to determine the psychometric properties of the Persian version of the Childhood Experience of Care and Abuse Questionnaire (CECA.Q), a tool based on a retrospective interview with the child. Materials and Methods: To this aim, 251 adolescents from four regions of Tehran megacity completed the questionnaire. The reliability of the questionnaire was examined, along with the face and content validity. In addition, the construct validity was evaluated by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results: EFA and CFA supported a 4-factor solution including mother’s role scale items, father’s role scale items, maternal behavior scale items, and paternal behavior scale items. The total variance extracted in EFA ranged from 33.9 to 60.7. The internal consistency for mother’s role, father’s role, maternal behavior, and paternal behavior was 0.61, 0.65, 0.86, and 0.9 respectively. Thus, the questionnaire had a suitable fit, as well as reasonable reliability and validity. Conclusion: The Persian version of the CECA.Q had adequate reliability and validity as a self-report measurement for childhood experience of care and abuse. [GMJ.2020;9:e1663]

Characterizing Multiple Air Pollutant Indices Based on Their Effects on the Mortality in Tehran, Iran during 2012–2017

The current limitations of Air Quality Indices (AQIs) have intrigued the attention on capturing the combined health effects of multiple air pollutants. Although previous studies have proposed the Aggregate Air Quality Index (AAQI) as the model of multiple air pollutants, there is no study evaluated the validity of the model considering the health effects related to air pollution. In this study, the three AAQI indices were proposed based on the variable parameter (ρ = 2, 2.5 and 3) and the Air Quality Index (AQI) was compared with AAQI to clarify which model predicts the mortality more effectively in the mega-city of Tehran. Time-series analysis was conducted to estimate the associations between air quality indices and cause - specific mortality at different lags in Tehran, Iran, and the fitted models were compared based on Akaike Information Criterion (AIC). Strongest associations were observed between deaths caused by Cardiovascular Diseases (CVD) and Respiratory Diseases (RPD) with AAQI ( = 2) by 2.01 % (95 % CI: 1.27–2.75) and 1.82 % (95 % CI: 1.10–2.54) per interquartile range (IQR) increase in the AAQI, respectively at moving average lags of 0–2 and 0–3. Finally, evaluation of the indices showed that AAQI (ρ = 2), AAQI (ρ = 2.5), AAQI (ρ = 3), and AQI, respectively were better in predicting the health outcomes of air pollution in the majority of lag times although, these differences were not statistically significant.

Numerical assessment of the urban green space scenarios on urban heat island and thermal comfort level in Tehran Metropolis

The growing rate of urbanization and alterations in natural land-use/land-cover properties cause many worldwide environmental issues such as Urban Heat Island (UHI), low Thermal Comfort Level (TCL) and air pollution in megacities. Development of urban green spaces is one of the most proposed measures for mitigation of UHI and improvement of thermal comfort satisfaction which causes lower cooling energy consumption and indirectly improves the urban air quality. Therefore, the efficiency of realistic and executable green scenarios in both surface and roof levels (surface vegetation, green roof, surface vegetation + green roof) on early summertime UHI and TCL are evaluated and compared in Tehran Metropolis, using coupled Weather Research and Forecasting model with Single Layer Urban Canopy Model (WRF/SLUCM). Model predefined urban parameters (the urban density and vegetation fraction) are modified before the main simulations by data of remote-sensing methods which let us define surface green spaces developmental scenarios without any change in the basic urban morphology. Results are presented for three areas with different urban morphologies (Low and High-Intensity Residential (LR and HR) and Commercial and Industrial (C/I)). Three indexes (THI, ETI and RSI) are calculated for assessing TCL variations. Generally, results show that environmental operations of selected scenarios are different over selected areas. In LR area, diurnal cooling (up to −0.86 °C in green roof approach) and improvement in thermal comfort condition are observed in all scenarios. On the other hand, in HR and C/I areas, the daytime cooling (nighttime warming) effect up to −0.85 °C (up to +0.63 °C) in the third scenario are simulated. TCL alterations show similar deteriorating nightly effects in all scenarios in selected regions. Averaged diurnal decrease in wind speed is another undesirable impact of green development scenarios due to the enhanced surface roughness that can reduce urban natural heat and pollution ventilations. Current results clarify that the adoption of efficient urban green spaces programs needs to consider different environmental concerns. By comparison between roof level and surface greenery, it can be concluded that the green roof approach with the least undesirable nightly effects is a more efficient approach than surface vegetation development in high-density Tehran megacity.

The Psychometric Properties of the Drug Abuse Screening Test.

BackgroundSubstance abuse is a critical problem in most countries, especially in developing ones. Early detection is the pre-requisite of early control, for which reliable and valid tools are required. In the present study, we aimed at measuring the psychometric properties of the 10-item Drug Abuse Screening Test (DAST-10) in Iranian individuals.MethodsAfter translation and back-translation of the questionnaire, 244 adults were recruited from Tehran Megacity, Iran, and completed the questionnaires. Participants were recruited by a multistage randomized cluster sampling method. Reliability was determined by Cronbach’s alpha. Also, construct validity was evaluated using confirmatory factor analysis (CFA) and exploratory factor analysis (EFA).FindingsThe internal consistency using Cronbach's alpha coefficients for the total score of the Persian version of DAST-10 was 0.93. EFA evoked only one factor for DAST-10. The CFA for 1-factor models for DAST-10 indicated an acceptable fit for the proposed models.ConclusionThe results prove desirable reliability and validity of the Persian version of the DAST which can be utilized as a screening instrument for drug abuse among Iranian adults.

Underlying pathway of factors leading to mental health in Iranian young adolescents: A structural equation modeling.

Background:The present study aimed to provide a field-tested model of constituting factors affecting mental health in young Iranian adolescents.Materials and Methods:In this cross-sectional study, a conceptual model was proposed based on an extensive literature review. A total of 254 young adolescents aged 11–14 years were recruited from north, south, east, and west regions of Tehran megacity by a random cluster sampling procedure, of whom 244 adolescents participated. The adolescents and their mothers altogether completed eight questionnaires pertaining to the proposed conceptual model: (1) Strengths and Difficulties Questionnaire (SDQ), (2) Childhood Experience of Care and Abuse Questionnaire, (3) Child Exposure to Domestic Violence Scale, (4) Drug Abuse Screening Test-10, (5) Baumrind Parenting Style Questionnaire, (6) Conflict Behavior Questionnaire, (7) General Health Questionnaire-28, and (8) Garmaroodi Socioeconomic Status Questionnaire. The statistical analysis was performed using structural equation modeling.Results:This study demonstrated that parent mental health (b = −0.111), experience of father's care (b = −1.112), conflict with mother (b = 0.309), conflict with father (b = 0.135), and exposure to domestic violence (b = 0.217), as well as age (b = 0.93) and gender (b = 0.139), had direct effect on adolescent mental health (all P < 0.05). Further, the results showed that exposure to domestic violence and conflict with mother had the greatest direct impact on adolescent mental health among all other family-related factors, followed by conflict with father and parent mental health. Conflict with mother and conflict with father also affected adolescent mental health indirectly through experience of domestic violence and had a mediating effect for the influence of several other factors on adolescent mental health, thus playing an important role in the pathway leading to young adolescent mental health status in the Iranian population.Conclusion:Overall, the final model proved to be fit and the factors constituting the final model were able to predict 88% of the variations in the mental health of Iranian adolescents. This model can guide clinical psychologists, psychiatrists, and other mental health workers in a more realistic and effective prevention or treatment planning for their young clients. Moreover, it may help in arriving at a comprehensive preventive policymaking for mental health policymakers.

Concurrent spatiotemporal daily land use regression modeling and missing data imputation of fine particulate matter using distributed space-time expectation maximization

In this study, a spatiotemporal land use regression (LUR) model using distributed space-time expectation maximization (D-STEM) software was developed. We trained the model using daily mean ambient particulate matter ≤2.5 μm (PM2.5) data measured hourly in 2015 at 30 regulatory monitoring network stations within the megacity of Tehran, Iran. Since a substantial amount of measured data were missing (48% of the total number of daily PM2.5 observations), we used the D-STEM to impute missing data and compared the missing imputation performance between different fitted models and the mean substitution method. We used h-block cross-validation (h-block CV) method in order to account for spatial autocorrelation in the model building and validation. In the imputation of missing data, the D-STEM LUR model had a mean absolute percentage error (MAPE) of 25.3%, outperforming the mean substitution method, which resulted in MAPE of 28.3%. The spatiotemporal R-squared was 0.73 and the average CV R-squared of 2-block and 5-block cross-validations was 0.60. These values were 0.68 and 0.47 when the spatial aspect of the LUR model was assessed, and 0.995 and 0.992 when the temporal aspect of the LUR model was assessed. This study demonstrated the competence of D-STEM software in spatiotemporal modeling, missing data imputation, and mapping of daily ambient PM2.5 at a very high spatial resolution (20 m × 20 m). These estimations are available for future research, especially for epidemiological studies on short- and/or long-term health effects of ambient PM2.5. Generally, we found D-STEM as a promising tool for spatiotemporal LUR modeling of ambient air pollution, especially for those models that rely on regulatory network monitoring stations with a considerable amount of missing data.

On the environmental effectiveness analysis of energy policies: A case study of air pollution in the megacity of Tehran

The present study compared different approaches to assessing the environmental cost-effectiveness of energy policy scenarios. As a case study, the megacity of Tehran in Iran was studied. A key policy challenge in this city is to curb high concentrations of PM2.5 and mitigate the associated adverse impacts. The results demonstrated that in the business as usual case, the spatially averaged primary and secondary PM2.5 concentration in Tehran will increase by 30% in the 2010–2030 period. Adopting certain planned policy scenarios and the corresponding pollutant concentration reductions in Tehran shows that although most of the emission comes from industrial activities around the city, the distribution of the transportation emission sources may play the most effective role in decreasing pollution levels in transport-related energy policies. Next, based on environmental damage costs and abatement costs in different pollution mitigation scenarios, the best (most environmentally cost-effective) scenarios were evaluated. The eco-efficiencies of the energy policies were assessed based on two proxies of environmental impacts: the reduced damage cost as a function of the reduced emission rates of the pollutants and the decreased number of polluted days in the year. In a sample area in which the simulated concentrations were verified by local measurements, the most efficient mitigation scenario would decrease the average concentration of PM2.5 by 35% in 2030 and the number of polluted days by 20%. These findings indicate how far the linear functionality of the damage cost from emission levels may mislead environmental impact assessments. This is due to neglecting the source distribution effects and geographical conditions of the environment.

PMU72 ATTRIBUTES OF DISSATISFACTION OF HEALTH INSURANCE COVERAGE IN PATIENTS VISITED PUBLIC AND PRIVATE DENTAL HEALTHCARE CENTERS

Patients‘ satisfaction is one of the five indicators of quality evaluation in healthcare services This study aimed to identify the determinants of dissatisfaction of insurance coverage among patients visited dental healthcare centers from October 2018 to January 2019 in Tehran-Iran. This is a qualitative study. Using deprivation index and taking socio-economic indicators into account, we identified six private and public dental healthcare centers in three districts in the mega city of Tehran- Iran. We conducted 54 in-depth face-to-face interviews with the head of households or their spouses that visited selected dental centers. Data gathering continued until saturation point. Using a hybrid inductive/deductive approach, we used thematic analysis for data analysis. MAXQDA12 software was used to help data management. We extracted 17 subthemes. Fiscal and non-fiscal determinants were identified as two main dissatisfaction determinants of basic and complementary health insurance. High premium and inappropriate benefit package created the greatest dissatisfaction among users of both basic and complementary insurance services. In addition, the interviewees with basic insurance expressed high dissatisfaction with quality of health services, while those with complementary coverage were mostly dissatisfied with insurance reimbursement system Our study indicates to improve patients’ satisfaction with healthcare insurance coverage, policy makers need to consider the affordability of insurance coverage as well as the quality of healthcare services covered by insurers simultaneously.

Short-term associations between daily mortality and ambient particulate matter, nitrogen dioxide, and the air quality index in a Middle Eastern megacity

There is limited evidence for short-term association between mortality and ambient air pollution in the Middle East and no study has evaluated exposure windows of about a month prior to death. We investigated all-cause non-accidental daily mortality and its association with fine particulate matter (PM2.5), nitrogen dioxide (NO2), and the Air Quality Index (AQI) from March 2011 through March 2014 in the megacity of Tehran, Iran. Generalized additive quasi-Poisson models were used within a distributed lag linear modeling framework to estimate the cumulative effects of PM2.5, NO2, and the AQI up to a lag of 45 days. We further conducted multi-pollutant models and also stratified the analyses by sex, age group, and season. The relative risk (95% confidence interval (CI)) for all seasons, both sexes and all ages at lag 0 for PM2.5, NO2, and AQI were 1.004 (1.001, 1.007), 1.003 (0.999, 1.007), and 1.004 (1.001, 1.007), respectively, per inter-quartile range (IQR) increment (18.8 μg/m3 for PM2.5, 12.6 ppb for NO2, and 31.5 for AQI). In multi-pollutant models, the PM2.5 associations were almost independent from NO2. However, the RRs for NO2 were slightly attenuated after adjustment for PM2.5 but they were still largely independent from PM2.5. The cumulative relative risks (95% CI) per IQR increment reached maximum during the cooler months, including: 1.13 (1.06, 1.20) for PM2.5 at lag 0–31 (for females, all ages); 1.17 (1.10, 1.25) for NO2 at lag 0–45 (for males, all ages); and 1.13 (1.07, 1.20) for the AQI at lag 0–30 (for females, all ages). Generally, the RRs were slightly larger for NO2 than PM2.5 and AQI. We found somewhat larger RRs in females, age group >65 years of age, and in cooler months. In summary, positive associations were found in most models. This is the first study to report short-term associations between all-cause non-accidental mortality and ambient PM2.5 and NO2 in Iran.

Global DNA methylation changes in rock pigeon (Columba livia) as a sentinel species due to polycyclic aromatic hydrocarbons exposure in Tehran (Iran) as a megacity.

Global DNA methylation, as an epigenetic modifications, can be a promising genomic marker for monitoring the contaminants and predicting their adverse health effects. The study aims to assess the effects of 16 PAH concentration on the altered DNA methylation levels in the kidney and liver of rock pigeon (Columba livia), as a sentinel species, from Tehran megacity as well as 40days benzo(a)pyrene in vitro exposure: (0.1, 2.5, 5, 7.5, and 10mgkg-1 bw). Data indicated that the total LMW-PAH (low molecular weight PAHs) group (120.22, 121.34, 103.69, and 128.79ngg-1 dw in liver, kidney, skin, and muscle, respectively) in the Tehran samples have higher levels than the other PAHs groups. In addition, the DNA methylation level had negative relation with the total amount of PAHs in liver and kidney. A comparatively higher global DNA hypomethylation (by 8.65% in liver and 3.76% in kidney) was observed in birds exposed to B(a)P. Our results lead us to suggest that DNA hypomethylation in liver and kidney associated with the B(a)P may be useful biomarker discovery (more than the amount of PAH concentration in different tissues of C. livia) in urban areas. In conclusion, based on the overall results assessed, DNA methylation changes in pigeon may show a new target pathway for evaluation of environmental health.

Improving spatial accuracy of urban growth simulation models using ensemble forecasting approaches

This paper aims to improve the spatial accuracy of urban growth simulation models and clarify any associated uncertainties. Artificial Neural Networks (ANNs), Random Forest (RF), and Logistic Regression (LR) were implemented to simulate urban growth in the megacity of Tehran, Iran, as a case study. Model calibration was performed using data between 1985 and 1999 whereas the data between 1999 and 2014 was used for model validation. First of all, Transition Index Maps (TIMs) were computed by means of each model to assess the potential of urban growth for each cell. Using the standard deviation, consensus between the TIMs was evaluated. Because the TIMs of the individual models manifested discrepancies, they were combined using a number of ensemble forecasting approaches including median, mathematical average, principle component analysis, and weighted area under the total operating characteristic. The individual and combined TIMs were then put into Cellular Automata (CA) to simulate the future pattern of urban growth in Tehran. The results were evaluated in two stages. At first, the TIMs were evaluated by means of Total Operating Characteristics (TOC), and then a set of statistical indices was used to evaluate the spatial accuracy of the simulated urban growth maps. The best result was obtained by median ensemble forecasting, whereas the LR model showed the lowest level of accuracy. In similar studies, it is recommended to implement and compare different ensemble methods when integrating individual models.

Risk-adjusted design basis earthquake: a case study of Tehran megacity

The basic goal of earthquake resistant building design codes is to provide life safety in the event of extreme earthquake loading and to reduce the seismic risk in the long run. In the most building codes including Iranian building code (Standard No. 2800), design basis earthquake is defined as an earthquake with 10% probability of exceedance (PE) in 50 years. Such an approach leads to buildings with unknown reliability, meaning that the probability of exceedance from the specified limit states in the service lifetime is not known. Furthermore, the regions with the same mapped peak ground acceleration (PGADBE) and different hazard curves, may have different seismic risks. Therefore, life safety is not uniformly provided across the entire region. Here, an attempt is made to estimate PGADBEs based on the uniform collapse risk approach for Tehran megacity. The building capacity and PGA hazard curve for 354 grids in Tehran are computed. Then, the risk-adjusted design PGA at different grid points are calculated by optimizing risk integral using the acceptance criteria of 1% in 50 years for ordinary usage buildings (risk category II). The computed risk-adjusted design PGAs vary from 0.33 g in the east to about 0.45 g toward west, south, and north. Meanwhile, the proposed mapped PGADBE in standard 2800 is a constant value of 0.35 g for the whole region. To preserve a uniform collapse risk, risk-adjustment factors to modify the mapped PGADBE are introduced. Furthermore, the maximum considered earthquake (MCE) required to evaluate the acceptance criteria is found to be in the range of 1.5% to 2.5% PE in 50 years. The PGAs with 2% PE in 50 years provide nearly uniform acceptable probability of collapse for buildings classified in risk category II. In addition, it is found that the buildings’ seismic importance factor (I) also needs to be revised from 1.2 to 1.3 for seismic risk category III, and from 1.4 to 1.6 for seismic risk category IV to preserve the 0.5% and 0.25% collapse risk in 50 years, respectively. The outcomes also revealed that the sensitivity analysis with regard to the uncertainty of buildings’ collapse fragility curve can be ignored for buildings in risk categories I and II, while it needs to be performed for buildings in risk categories III, and especially IV. Finally, the estimated PGA hazard curves of the Tehran megacity are approximated by the cubic functions to expedite the future risk assessment studies in Tehran megacity.

Temporal variations of atmospheric benzene and its health effects in Tehran megacity (2010-2013).

The main aims of the present research were (1) investigation of the temporal trends of atmospheric benzene concentrations in Tehran city during the period 2010 to 2013 and (2) assessment of carcinogenic and non-carcinogenic health risks of inhalation exposure to benzene. For the first objective, the data of ambient air benzene concentrations were derived from 15 air quality monitoring stations (AQMSs) in Tehran during the years 2010 to 2013 and they were temporally investigated after data cleaning and missing data imputation. The excess lifetime cancer risk (ELCR) and hazard quotient (HQ) were estimated to reveal the carcinogenic and non-carcinogenic health effects of exposure to ambient benzene. Our findings indicated that over 2010-2013, annual mean concentrations of benzene were in the range of 1.84 to 2.57 μg m-3, and the highest annual mean concentration was observed in 2011 with a mean of 2.57 μg m-3. The four-year average concentration of benzene during the period from 2010 to 2013 was 2.14 μg m-3. Furthermore, the HQ for inhalation exposure to ambient benzene was lower than the acceptable risk level (HQ < 1) over the study time period which indicated that the non-carcinogenic effects are very unlikely to happen. In addition, health risk assessment for ELCR showed that the potential cancer risk for inhalation exposure to benzene was 1.67 × 10-5 over the study period, which is significantly higher than the limits recommended by the U.S. EPA (1 × 10-6). Our study clearly proves that the ambient benzene concentration in Tehran has substantially higher carcinogenic effects on the population. Appropriate sustainable control measures should be taken to reduce air benzene concentration and protect public health.

Survey of knowledge and attitude of people about air pollution in Tehran, Iran

Introduction: The importance of air quality and paying attention to what we breathe have been valuable always. So that air pollution is one of the key environmental issues in urban communities. Several studies show that the potential effects of air pollution on human health include increased mortality and changes in cardiovascular and respiratory functions. Materials and methods: The population of this study was people in 22 dis-tricts of Tehran megacity. The questionnaires were placed at the municipality centers of 22 districts and randomly completed by people who came to the center. Questions included the importance of air pollution, the comparison of air quality with last year, the main sources of air pollution, the problems created by air pollution, the quality of informing system, as well as questions about their satisfaction about government’s actions on air pollution control plans. Data analysis was performed using SPSS 24. Results: 84.14 % of the participants stated that air pollution is important to them and has a negative influence on their lives. Also, most of them were not satisfied with the measures taken and expected that actions would be better to reduce air pollution. 91.10 % of the participants considered cars as the main causes of air pollution. Also, 68.22 % of people believed that air pollution had a significant negative impact on their quality of life. Conclusion: Most people are willing to live at a higher cost but a less pol-luted environment, while more of them are not well aware of their role in reducing air pollution. Moreover further education should be provided on the role of people in reducing air pollution. Additionally, the government must deal with air pollutants and take serious measures.

On the nature and health impacts of BTEX in a populated middle eastern city: Tehran, Iran

This study describes a spatio-temporal characterization of concentrations of BTEX in ambient air of four hot spots (bus terminals) in the megacity of Tehran. Monte Carlo simulations were performed to evaluate cancer risk and non-cancer risk owing to BTEX exposure in three age groups (<6, 6 to <21 and 21 to <81 years). The average toluene to benzene ratios for the four intercity bus terminals were 2.63 (summer) and 2.88 (winter). Furthermore, the mean xylenes to benzene and ethylbenzene to benzene ratios in the two seasons for all stations ranged from 3.33 to 4.40 (summer) and 2.13–2.80 (winter), respectively. There was insignificant difference in BTEX levels between working and non-working days owing to the lack of change in vehicular traffic during the full week. Factors promoting BTEX formation in the study region were fuel evaporation, gas stations, diesel bus emissions, and a lack of hydroxyl radicals (OH) for reacting with the target compounds. Calculations suggested that cancer risk for benzene and ethylbenzene in three age groups at the four bus terminals exceeded values recommended by U. S. EPA. In addition, the hazard quotient for BTEX in both seasons for different age groups ranged between 1.23 × 10−5 and 3.58 × 10−1, values of which were lower than reference levels. Carcinogenic emissions such as with benzene and ethylbenzene discharged by bus terminals impact the growing population in the study region, which requires additional action to reduce health effects.

Prediction of driving behavior based on emotional intelligence &amp; driving risk perception

Background: The aim of this study was to predict driving behavior based on emotional intelligence & driving risk perception. Methods: This research was descriptive & correlational. The sample size consisted of 400 drivers from 5 taxi terminals of different areas of Tehran megacity by convenience sampling. The tools which used in this study were as follows: Manchester driving behavior questionnaire, Ulleberg & Rundmo driving risk perception questionnaire, Shrink emotional intelligence questionnaire. Data analysis was based on Pearson correlation & multiple simultaneous regression. Results: Analysis revealed that the relationship between driving behavior & driving risk perception was significant & negative (r = -0/34) (ɑ = 0/01). The relationship between driving behavior & emotional intelligence was significant & negative (r = -0/28) (ɑ = 0/01). Conclusion: Emotional intelligence & driving risk perception could predict 16% of driving behavior. That means by increasing emotional intelligence & promote driving risk perception among taxi drivers, the risky driving behavior could be decreased. In the other words drivers who do risky driving behavior and commit driving offenses, their emotional intelligence is less than other drivers.