Annual and seasonal spatial models for nitrogen oxides in Tehran, Iran

Ambient air pollutants and breast cancer stage in Tehran, Iran

This study aimed to examine the impacts of single and multiple air pollutants (AP) on the severity of breast cancer (BC). Data of 1148 diagnosed BC cases (2008-2016) were obtained from the Cancer Research Center and private oncologist offices in Tehran, Iran. Ambient PM10, SO2, NO, NO2, NOX, benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene, and BTEX data were obtained from previously developed land use regression models. Associations between pollutants and stage of BC were assessed by multinomial logistic regression models. An increase of 10 μg/m3 in ethylbenzene, o-xylene, m-xylene, and 10 ppb of NO corresponded to 10.41 (95% CI 1.32-82.41), 4.07 (1.46-11.33), 2.89 (1.08-7.73) and 1.08 (1.00-1.15) increase in the odds of stage I versus non-invasive BC, respectively. Benzene (OR, odds ratio = 1.16, 95% CI 1.01-1.33) and o-xylene (OR = 1.18, 1.02-1.38) were associated with increased odds of incidence of BC stages III & IV versus non-invasive stages. BC stage I and stage III&IV in women living in low SES areas was associated with significantly higher levels of benzene, ethylbenzene, o-xylene, and m-xylene. The highest multiple-air-pollutants quartile was associated with a higher odds of stage I BC (OR = 3.16) in patients under 50 years old. This study provides evidence that exposure to AP is associated with increased BC stage at diagnosis, especially under premenopause age.

Climatic comparison of surface urban heat island using satellite remote sensing in Tehran and suburbs

In this study, we aim to compare the climatic conditions of Surface Urban Heat Island (SUHI) in Tehran and its suburbs using day/night time data from three satellites. A high-resolution Land Surface Temperature (LST) data from MODIS Aqua, Sentinel-3, and Landsat 8 were selected to facilitate this study. The highest values of LST/UHI are observed in downtown Tehran and suburban areas at night. The temperature difference also shows an increase at night in Tehran and the western suburbs, while it decreases during the day. When comparing LST/UHI with altitude in different directions, it is found that urban areas and the south, southeast, southwest, and west suburban areas experience higher temperatures at night. MODIS LST products are more appropriate for checking nighttime SUHI in Tehran's Great area in comparison to other products. Moran's I indicates that the highest positive values occur during seasonal and annual periods at night. The Getis index demonstrates a consistent pattern across all seasons, and this trend persists throughout the year. The seasonal and annual UHI difference between Tehran and its suburbs is 5 °C. The LST diagram reveals that higher temperatures occur during warm months. The temporal NDVI distribution indicates lower NDVI values from June to February and summer to winter. The spatial distribution shows that due to the lack of NDVI index in urban areas, LST/UHI values are higher at night in Tehran compared to the suburbs. UHI is not limited to urban areas but has also spread beyond the city borders. As a result, the highest UHI values are found in downtown Tehran and its southeast, south, southwest, and west suburbs.

Development of Spatio-Temporal Land Use Regression Models for Fine Particulate Matter and Wood-Burning Tracers in Temuco, Chile

Biomass burning is common in much of the world, and in some areas, residential wood-burning has increased. However, air pollution resulting from biomass burning is an important public health problem. A sampling campaign was carried out between May 2017 and July 2018 in over 64 sites in four sessions, to develop a spatio-temporal land use regression (LUR) model for fine particulate matter (PM) and wood-burning tracers levoglucosan and soluble potassium (Ksol) in a city heavily impacted by wood-burning. The mean (sd) was 46.5 (37.4) μg m-3 for PM2.5, 0.607 (0.538) μg m-3 for levoglucosan, and 0.635 (0.489) μg m-3 for Ksol. LUR models for PM2.5, levoglucosan, and Ksol had a satisfactory performance (LOSOCV R2), explaining 88.8%, 87.4%, and 87.3% of the total variance, respectively. All models included sociodemographic predictors consistent with the pattern of use of wood-burning in homes. The models were applied to predict concentrations surfaces and to estimate exposures for an epidemiological study.

Long-term exposure to air pollution and anti-mullerian hormone rate of decline: a population-based cohort study in Tehran, Iran

Anti-mullerian hormone (AMH) concentration is a marker of ovarian reserve that decreases with age. However, a decrease in AMH may occur more rapidly under the influence of environmental factors. The present study investigated the association between long-term exposure to ambient air pollutants with serum concentrations of AMH and the AMH rate of decline. This study included 806 women with median age of 43 years (interquartile range: 38-48) participating in the Tehran Lipid and Glucose Study (TLGS) that were followed from 2005 to 2017. The AMH concentration and the demographic, anthropometric, and personal health parameters of the study participants were obtained from the TLGS cohort database. Air pollutant data were collected from the monitoring stations and the individual exposures were estimated by previously developed land use regression (LUR) models. Multiple linear regression analysis was used to estimate linear relationships between the air pollutant exposures and serum concentration of AMH and with the AMH declination rate. The results show no statistically significant associations between exposures to any of the air pollutants (including PM10, PM2.5, SO2, NO, NO2, NOX, and benzene, toluene, ethylbenzene, p-xylene, m-xylene, o-xylene (BTEX), and total BTEX) with serum concentration of AMH. Compared to the first tertile, no statistically significant associations were observed between the second or third tertiles of air pollutants, with the AMH rate of decline. In this study, we did not find significant association between air pollution and AMH in middle age women in Tehran, Iran. Future work may study such associations in younger women.

Functional Kriging for Spatiotemporal Modeling of Nitrogen Dioxide in a Middle Eastern Megacity

Long-term hour-specific air pollution exposure estimates have rarely been of interest in epidemiological research. However, this can be relevant for studies that aim to estimate the residential exposure for the hours that subjects mostly spend time there, or for those hours that they may work in another location. Here, we developed a model by spatially predicting the long-term diurnal curves of nitrogen dioxide (NO2) in Tehran, Iran, one of the most polluted and populated megacities in the Middle East. We used the statistical framework of functional data analysis (FDA) including ordinary kriging for functional data (OKFD) and functional analysis of variance (fANOVA) for modeling. The long-term NO2 diurnal curves had two distinct maxima and minima. The absolute minimum value of the city average was 40.6 ppb (around 4:00 p.m.) and the absolute maximum value was 52.0 ppb (around 10:00 p.m.). The OKFD showed the concentrations, the diurnal maximum/minimum values, and their corresponding occurring times varied across the city. The fANOVA highlighted that the effect of population density on the NO2 concentrations is not constant and depends on time within the diurnal period. The provided estimation of long-term hour-specific maps can inform future epidemiological studies to use the long-term mean for specific hour(s) of the day. Moreover, the demonstrated FDA framework can be used as a set of flexible statistical methods.

Temporal variations, regional contribution, and cluster analyses of ozone and NOx in a middle eastern megacity during summertime over 2017-2019

Particulate matter is usually regarded as the dominant pollutant in Tehran megacity in Iran. However, the number of ozone exceedance days significantly increased in recent years. This study analyzes simultaneous measurements of O3 and NOx (NO+NO2) concentrations to improve our understanding of ozone evolution during the summers of 2017 to 2019. The k-means clustering technique was used to select five representative air quality monitoring sites in Tehran to capture O3 and NOx concentrations' variability. The findings show that all of the investigated sites failed to meet the ozone non-attainment criterion. The ozone weekend effect is seen in the study of weekday/weekend differences in 2017 and 2018, but not in 2019, which can be due to the shift in the ozone production regime. The summer mean variation analysis can also be used to deduce this regime change. In 2017, the O3 and NO2 summer mean variations suggest a holdback in the NO2 upward trend and a reversal in the O3 downward trend that had been in place since 2012. Air mass back trajectory clustering reveals that east and north-east air mass clusters have the most significant impact on Tehran's O3 pollution and the highest regional contribution to OX. The study of OX against NOx shows that the regional contribution to OX increased from 2017 to 2018 and then decreased in 2019; however, the local contribution is the opposite. The diurnal analysis of the regional and local contributions to OX indicated that OX in Tehran might be primarily affected by pollutants from a short distance. The findings reveal critical changes in the behavior of O3 in recent years, indicating that decision-makers in Tehran should reconsider air pollution control measures.

Study on the Mechanism of SO2 Poisoning of MnOx/PG for Lower Temperature SCR by Simple Washing Regeneration

Manganese oxide-supported palygorskite (MnOx/PG) catalysts are considered highly efficient for low-temperature SCR of NOx. However, the MnOx/PG catalyst tends to be poisoned by SO2. The effect of SO2 on activity of the SO2-pretreated poisoning catalysts under ammonia-free conditions was explored. It was determined that the MnOx/PG catalyst tends to be considerably deactivated by SO2 in the absence of ammonia and that water-washed regeneration can completely recover activity of the deactivated catalyst. Based on these results and characterizations of the catalysts, a reasonable mechanism for the deactivation of MnOx/PG catalyst by SO2 was proposed in this study. SO2 easily oxidized to SO3 on the surface of the catalyst, leading to the formation of polysulfuric acid, wrapping of the active component and blocking the micropores. The deactivation of the MnOx/PG catalyst is initially caused by the formation of polysulfuric rather than the deposition of ammonia sulfate, which occurs later.

Multiple air pollutant exposure and lung cancer in Tehran, Iran

Lung cancer is the most rapidly increasing malignancy worldwide with an estimated 2.1 million cancer cases in the latest, 2018 World Health Organization (WHO) report. The objective of this study was to investigate the association of air pollution and lung cancer, in Tehran, Iran. Residential area information of the latest registered lung cancer cases that were diagnosed between 2014 and 2016 (N = 1,850) were inquired from the population-based cancer registry of Tehran. Long-term average exposure to PM₁₀, SO₂, NO, NO₂, NO_X, benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene (BTEX), and BTEX in 22 districts of Tehran were estimated using land use regression models. Latent profile analysis (LPA) was used to generate multi-pollutant exposure profiles. Negative binomial regression analysis was used to examine the association between air pollutants and lung cancer incidence. The districts with higher concentrations for all pollutants were mostly in downtown and around the railway station. Districts with a higher concentration for NOx (IRR = 1.05, for each 10 unit increase in air pollutant), benzene (IRR = 3.86), toluene (IRR = 1.50), ethylbenzene (IRR = 5.16), p-xylene (IRR = 9.41), o-xylene (IRR = 7.93), m-xylene (IRR = 2.63) and TBTEX (IRR = 1.21) were significantly associated with higher lung cancer incidence. Districts with a higher multiple air-pollution profile were also associated with more lung cancer incidence (IRR = 1.01). Our study shows a positive association between air pollution and lung cancer incidence. This association was stronger for, respectively, p-xylene, o-xylene, ethylbenzene, benzene, m-xylene and toluene.

Multiple sclerosis in Iran: An epidemiological update with focus on air pollution debate

BACKGROUND

Multiple sclerosis (MS), as the most common neurologic disorder of the central nervous system, with growing incidence and prevalence worldwide and in the Middle East. This article aimed to find out the potential relationship between MS and air pollution in Iran.

METHODS

By assessing the published articles on MS and air pollution in Iran, the situation of MS as well as air/soil pollution in Iran was clarified. Then, studies on air pollution and its potential effect on Iranian MS patients were checked until 2020.

RESULTS

The MS prevalence is distributed across Iran Provinces with highest rates in Isfahan, located in the center of Iran. The higher rates of MS in Isfahan and Tehran (the Metropolitan) might be due to industrial pollution of these cities, but this hypothesis is not true for non-industrial provinces. Based on the published atlas of MS in Iran, it seems that there is a high-risk "belt" from northwest to southeast.

CONCLUSION

There are many risk factors of MS in Iran including age, gender, Vitamin D deficiency, smoking, and air pollution. The potential main risk factor of MS might be air pollution considering Isfahan and Tehran provinces. However, Chahar Mahal and Bakhtiary Province, with non-industrial nature, has the second highest MS rates which does not follow this hypothesis.

RELEVANCE FOR PATIENTS

By finding the air pollution as the main potential risk factor of MS in big provinces including Isfahan and Tehran, its effect of this factor can also be considered during diagnosis and treatment.

RNA delivery by extracellular vesicles in mammalian cells and its applications

The term 'extracellular vesicles' refers to a heterogeneous population of vesicular bodies of cellular origin that derive either from the endosomal compartment (exosomes) or as a result of shedding from the plasma membrane (microvesicles, oncosomes and apoptotic bodies). Extracellular vesicles carry a variety of cargo, including RNAs, proteins, lipids and DNA, which can be taken up by other cells, both in the direct vicinity of the source cell and at distant sites in the body via biofluids, and elicit a variety of phenotypic responses. Owing to their unique biology and roles in cell-cell communication, extracellular vesicles have attracted strong interest, which is further enhanced by their potential clinical utility. Because extracellular vesicles derive their cargo from the contents of the cells that produce them, they are attractive sources of biomarkers for a variety of diseases. Furthermore, studies demonstrating phenotypic effects of specific extracellular vesicle-associated cargo on target cells have stoked interest in extracellular vesicles as therapeutic vehicles. There is particularly strong evidence that the RNA cargo of extracellular vesicles can alter recipient cell gene expression and function. During the past decade, extracellular vesicles and their RNA cargo have become better defined, but many aspects of extracellular vesicle biology remain to be elucidated. These include selective cargo loading resulting in substantial differences between the composition of extracellular vesicles and source cells; heterogeneity in extracellular vesicle size and composition; and undefined mechanisms for the uptake of extracellular vesicles into recipient cells and the fates of their cargo. Further progress in unravelling the basic mechanisms of extracellular vesicle biogenesis, transport, and cargo delivery and function is needed for successful clinical implementation. This Review focuses on the current state of knowledge pertaining to packaging, transport and function of RNAs in extracellular vesicles and outlines the progress made thus far towards their clinical applications.

A hybrid kriging/land-use regression model with Asian culture-specific sources to assess NO2 spatial-temporal variations

Kriging interpolation and land use regression (LUR) have characterized the spatial variability of long-term nitrogen dioxide (NO₂), but there has been little research on combining these two methods to capture small-scale spatial variation. Furthermore, studies predicting NO₂ exposure are almost exclusively based on traffic-related variables, which may not be transferable to Taiwan, a typical Asian country with diverse local emission sources, where densely distributed temples and restaurants may be important for NO₂ levels. To advance the exposure estimates in Taiwan, a hybrid kriging/LUR model incorporates culture-specific sources as potential predictors. Based on 14-year NO₂ observations from 73 monitoring stations across Taiwan, a set of interpolated NO₂ values were generated through a leave-one-out ordinary kriging algorithm, and this was included as an explanatory variable in the stepwise LUR procedures. Kriging interpolated NO₂ and culture-specific predictors were entered in the final models, which captured 90% and 87% of NO₂ variation in annual and monthly resolution, respectively. Results from 10-fold cross-validation and external data verification demonstrate robust performance of the developed models. This study demonstrates the value of incorporating the kriging-interpolated estimates and culture-specific emission sources into the traditional LUR model structure for predicting NO₂, which can be particularly useful for Asian countries.

National and sub-national exposure to ambient fine particulate matter (PM2.5) and its attributable burden of disease in Iran from 1990 to 2016

Ambient particulate matter is a public health concern. We aimed (1) to estimate national and provincial long-term exposure of Iranians to ambient particulate matter (PM) < 2.5 μm (PM_2.5) from 1990 to 2016, and (2) to estimate the national and provincial burden of disease attributable to PM_2.5 in Iran. We used all available ground measurements of PM < 10 μm (PM₁₀) (used to estimate PM_2.5) from 91 monitoring stations. We estimated the annual mean exposure to PM_2.5 for all Iranian population from 1990 to 2016 through a multi-stage modeling process. By applying comparative risk assessment methodology and using life table for years of life lost (YLL), we estimated the mortality and YLL attributable to PM_2.5 for five outcomes. The predicted provincial annual mean PM_2.5 concentrations range was between 21.7 μg/m³ (UI: 19.03-24.9) and 35.4 μg/m³ (UI: 31.4-39.4) from 1990 to 2016. We estimated in 2016, about 41,000 deaths (95% uncertainty interval [UI] 35634, 47014) and about 3,000,000 YLL (95% UI: 2632101, 3389342) attributable to the long-term exposure to PM_2.5 in Iran. Ischemic heart disease was the leading cause of mortality by 31,363 deaths (95% UI: 27520, 35258), followed by stroke (7012 (5999, 8062) deaths), lower respiratory infection (1210 (912, 1519) deaths), chronic obstructive pulmonary disease (1019 (715, 1328) deaths), and lung cancer (668 (489, 848) deaths). In 2016, about 43% of all PM_2.5 related mortality in Iran was, respectively, in the following provinces: Tehran (12.6%), Isfahan (9.3%), Khorasan Razavi (8.0%), Fars (6.5%), and Khozestan (6.4%). In summary, we found that the majority of Iranians were exposed to the levels of ambient particulate matter exceeding the WHO guidelines from 1990 to 2016. Further, we found that there was an increasing trend of total mortality attributed to PM_2.5 in Iran from 1990 to 2016 where the slope was higher in western provinces.

Maternal exposure to air pollutants and birth weight in Tehran, Iran

BACKGROUND

Air pollution can cause various health outcomes, especially in susceptible groups including pregnant women. Low birth weight (LBW) is among the adverse birth outcomes and is one of the main causes of infant mortality. The aim of this study was to assess the association between air pollutants and LBW in Tehran, Iran.

METHODS

In this case-control study, 2144 babies born in three hospitals of Tehran (Iran) during 2011 to 2012 whose mothers were the residents of this city in last 5 years were considered. Of these, 468 infants with birth weight < 2500 g and 1676 with birth weight ≥ 2500 g were regarded as case and control groups, respectively. Gestational age was also considered for definition of cases (small for gestational age (SGA)) and controls (appropriate for gestational age). Land use regression models were used to assess exposure to particulate matter ≤10 μm in aerodynamic diameter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and volatile organic compounds (benzene, toluene, ethylbenzene, o-xylene, m-xylene, p-xylene (BTEX), and total BTEX) during pregnancy. Logistic regression model was applied to assess the association between air pollutants and LBW.

RESULTS

The concentrations of air pollutants were very high but similar in cases and controls. After adjustment for potential confounding variables, no statistically significant association was observed between air pollutants and LBW. The adjusted odds ratios (95% confidence interval) for PM₁₀, SO₂, and benzene were 0.999 (0.994-1.005), 0.998 (0.993-1.003), and 0.980 (0.901-1.067), respectively.

CONCLUSIONS

No association was found between LBW and air pollutants. Further studies with more rigorous designs and access to more comprehensive information are suggested to assess the effect of other air pollutants, such as CO, O₃, PM_2.5, ultrafine particles, and oxidative potential of particles on birth outcomes.

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 (PM_2.5), 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 PM_2.5, 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 PM_2.5, 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 PM_2.5, 12.6 ppb for NO₂, and 31.5 for AQI). In multi-pollutant models, the PM_2.5 associations were almost independent from NO₂. However, the RRs for NO₂ were slightly attenuated after adjustment for PM_2.5 but they were still largely independent from PM_2.5. The cumulative relative risks (95% CI) per IQR increment reached maximum during the cooler months, including: 1.13 (1.06, 1.20) for PM_2.5 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 PM_2.5 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 PM_2.5 and NO₂ in Iran.

Environmental determinants of polycyclic aromatic hydrocarbons exposure at home, at kindergartens and during a commute

The aim of this study was to assess the potential health risk of exposure to polycyclic aromatic hydrocarbons (PAHs) at home and kindergarten for pre-school children. The urine samples were taken from 200 pre-school children aged 5-7 years and analyzed for 1-OHP as a biomarker of PAHs. Mixed effect models were applied to investigate the association between effective environmental parameters (mode of transport, distance to major roads, traffic density, greenness, tobacco exposure, home ventilation, and grill foods) and urinary 1-OHP levels. A Monte-Carlo simulation technique was applied to calculate the risk of exposure to PAHs and to check the uncertainty of input variables and the sensitivity of the estimated risk. The median and inter quartile range (IQR) of 1-OHP was 257 (188.5) ng L^-1. There was a positive significant association between distance from the kindergartens to the green space with surface area ≥5000 m² and 1-OHP concentration (β = 0.844, 95% CI: 0.223, 1.46, P-value = 0.009). Also, urinary 1-OHP was found to be inversely associated with the time the window was open at the home (β = -12.56, 95% CI: -23.52, -1.596, P-value = 0.025) and normalized difference vegetation index (NDVI) in a 100 m buffer around the homes. The mean (9.76 E-3) and 95th percentile (3.28 E-2) of the hazard quotient (HQ) indicated that the concentration of urinary 1-OHP is at a safe level for the target population (HQ < 1). According to the sensitivity analysis results, the concentration of 1-OHP is the most influential variable in the estimated risk. Our findings indicated that the proximity of homes and kindergartens to green space areas and their remoteness from the main streets and heavy traffic areas are associated with reduced exposure to PAHs.

Development of a microscale land use regression model for predicting NO2 concentrations at a heavy trafficked suburban area in Auckland, NZ

Land use regression (LUR) analysis has become a key method to explain air pollutant concentrations at unmeasured sites at city or country scales, but little is known about the applicability of LUR at microscales. We present a microscale LUR model developed for a heavy trafficked section of road in Auckland, New Zealand. We also test the within-city transferability of LUR models developed at different spatial scales (local scale and city scale). Nitrogen dioxide (NO₂) was measured during summer at 40 sites and a LUR model was developed based on standard criteria. The results showed that LUR models are able to capture the microscale variability with the model explaining 66% of the variability in NO₂ concentrations. Predictor variables identified at this scale were street width, distance to major road, presence of awnings and number of bus stops, with the latter three also being important determinants at the local scale. This highlights the importance of street and building configurations for individual exposure at the street level. However, within-city transferability was limited with the number of bus stops being the only significant predictor variable at all spatial scales and locations tested, indicating the strong influence of diesel emissions related to bus traffic. These findings show that air quality monitoring is necessary at a high spatial density within cities in capturing small-scale variability in NO₂ concentrations at the street level and assessing individual exposure to traffic related air pollutants.

Land Use Regression Models for Alkylbenzenes in a Middle Eastern Megacity: Tehran Study of Exposure Prediction for Environmental Health Research (Tehran SEPEHR)

Land use regression (LUR) has not been applied thus far to ambient alkylbenzenes in highly polluted megacities. We advanced LUR models for benzene, toluene, ethylbenzene, p-xylene, m-xylene, o-xylene (BTEX), and total BTEX using measurement based estimates of annual means at 179 sites in Tehran megacity, Iran. Overall, 520 predictors were evaluated, such as The Weather Research and Forecasting Model meteorology predictions, emission inventory, and several new others. The final models with R² values ranging from 0.64 for p-xylene to 0.70 for benzene were mainly driven by traffic-related variables but the proximity to sewage treatment plants was present in all models indicating a major local source of alkylbenzenes not used in any previous study. We further found that large buffers are needed to explain annual mean concentrations of alkylbenzenes in complex situations of a megacity. About 83% of Tehran's surface had benzene concentrations above air quality standard of 5 μg/m³ set by European Union and Iranian Government. Toluene was the predominant alkylbenzene, and the most polluted area was the city center. Our analyses on differences between wealthier and poorer areas also showed somewhat higher concentrations for the latter. This is the largest LUR study to predict all BTEX species in a megacity.

Spatiotemporal description of BTEX volatile organic compounds in a Middle Eastern megacity: Tehran Study of Exposure Prediction for Environmental Health Research (Tehran SEPEHR)

The spatiotemporal variability of ambient volatile organic compounds (VOCs) in Tehran, Iran, is not well understood. Here we present the design, methods, and results of the Tehran Study of Exposure Prediction for Environmental Health Research (Tehran SEPEHR) on ambient concentrations of benzene, toluene, ethylbenzene, p-xylene, m-xylene, o-xylene (BTEX), and total BTEX. To date, this is the largest study of its kind in a low- and middle-income country and one of the largest globally. We measured BTEX concentrations at five reference sites and 174 distributed sites identified by a cluster analytic method. Samples were taken over 25 consecutive 2-weeks at five reference sites (to be used for temporal adjustments) and over three 2-week campaigns in summer, winter, and spring at 174 distributed sites. The annual median (25^th-75^th percentile) for benzene, the most carcinogenic of the BTEX species, was 7.8 (6.3-9.9) μg/m³, and was higher than the national and European Union air quality standard of 5 μg/m³ at approximately 90% of the measured sites. The estimated annual mean concentrations of BTEX were spatially highly correlated for all pollutants (Spearman rank coefficient 0.81-0.98). In general, concentrations and spatial variability were highest during the summer months, most likely due to fuel evaporation in hot weather. The annual median of benzene and total BTEX across the 35 sites in the Tehran regulatory monitoring network (7.7 and 56.8 μg/m³, respectively) did a reasonable job of approximating the additional 144 city-wide sites (7.9 and 58.7 μg/m³, respectively). The annual median concentrations of benzene and total BTEX within 300 m of gas stations were 9.1 and 67.3 μg/m³, respectively, and were higher than sites outside this buffer. We further found that airport did not affect annual BTEX concentrations of sites within 1 km. Overall, the observed ambient concentrations of toxic VOCs are a public health concern in Tehran.

A review of Mn-containing oxide catalysts for low temperature selective catalytic reduction of NOx with NH3: reaction mechanism and catalyst deactivation

The reactions over Mn-containing selective catalytic reduction (SCR) catalysts.