Evaluating near highway air pollutant levels and estimating emission factors: Case study of Tehran, Iran

Investigating the Effects of Air Pollution on Plant Species Resistance in Urban Areas

Context: Air pollution is a serious concern for environmental and human health, especially due to increasing the risk of respiratory and cardiovascular diseases. The purpose of this study was to investigate the effects of air pollution on plant species resistance in urban areas. Evidence Acquisition: This narrative review was conducted by searching the databases of Web of Science, Science Direct, Scopus, PubMed, Google Scholar, and Springer. Sixty-five articles were screened by reading their abstracts and full texts. In the end, 12 relevant papers published from 1993 to 2021 were finally selected. Results: The literature review showed that the green spaces created by municipalities in different areas of the city included a set of trees and shrubs compatible by the climate, grass, soil, and water of the region, leading to a significant improvement in air quality. Based on the results, urban green space has the ability to reduce the amount of artificially produced pollutants, and the use of natural potential of trees can improve the quality of the environment depending on various factors such as the climatic condition of the region and the density and amount of vegetation cover. Conclusions: The most effective ways to reduce health and economic costs include reducing the emission of pollutants from cars and industries, extending urban green space, educating citizens, and organizational planning and cooperation. The findings of this study may have important implications for selecting plant species for vegetation traffic barriers.

Airborne particulate matter in Tehran's ambient air

In recent decades, particulate matter (PM) concentrations in Tehran have exceeded the World Health Organization's (WHO) guideline on most days. In this study, a search protocol was defined by identifying the keywords, to carry out a systematic review of the concentrations and composition of PM in Tehran's ambient air. For this purpose, searches were done in Scopus, PubMed, and Web of Science in 2019. Among the founded articles (197 in Scopus, 61 in PubMed, and 153 in Web of Science). The results show that in Tehran, the annual average PM₁₀ exceeded the WHO guidelines and for more than 50.0% of the days, the PM_2.5 concentration was more than WHO 24-h guidance value. The PM concentration in Tehran has two seasonal peaks due to poorer dispersion and suspension from dry land, respectively. Tehran has two daily PM peaks due to traffic and changes in boundary-layer heights; one just after midnight and the other during morning rush hour. Indoor concentrations of PM10 and PM2.5 in Tehran were 10.6 and 21.8 times higher than the corresponding values in ambient air. Tehran represents a unique case of problems of controlling PM because of its geographical setting, emission sources, and land use. This review provided a comprehensive assessment for decision makers to assist them in making appropriate policy decisions to improve the air quality. Considering factors such as diversity of resources, temporal and spatial variations, and urban location is essential in developing control plans. Also future studies should focus more on PM reduction plans.

Anthropogenic noise is associated with telomere length and carotenoid-based coloration in free-living nestling songbirds

Growing evidence suggests that anthropogenic noise has deleterious effects on the behavior and physiology of free-living animals. These effects may be particularly pronounced early in life, when developmental trajectories are sensitive to stressors, yet studies investigating developmental effects of noise exposure in free-living populations remain scarce. To elucidate the effects of noise exposure during development, we examined whether noise exposure is associated with shorter telomeres, duller carotenoid-based coloration and reduced body mass in nestlings of a common urban bird, the great tit (Parus major). We also assessed how the noise environment is related to reproductive success. We obtained long-term measurements of the noise environment, over a ∼24-h period, and characterized both the amplitude (measured by LA_eq, LA_90, LA₁₀, LA_max) and variance in noise levels, since more stochastic, as well as louder, noise regimes might be more likely to induce stress. In our urban population, noise levels varied substantially, with louder, but less variable, noise characteristic of areas adjacent to a highway. Noise levels were also highly repeatable, suggesting that individuals experience consistent differences in noise exposure. The amplitude of noise near nest boxes was associated with shorter telomeres among smaller, but not larger, brood members. In addition, carotenoid chroma and hue were positively associated with variance in average and maximum noise levels, and average reflectance was negatively associated with variance in background noise. Independent of noise, hue was positively related to telomere length. Nestling mass and reproductive success were unaffected by noise exposure. Results indicate that multiple dimensions of the noise environment, or factors associated with the noise environment, could affect the phenotype of developing organisms, that noise exposure, or correlated variables, might have the strongest effects on sensitive groups of individuals, and that carotenoid hue could serve as a signal of early-life telomere length.

Estimation of real-world traffic emissions for CO, SO2, and NO2 through measurements in urban tunnels in Tehran, Iran

Mobile sources are considered to be one of the most important sources of air pollution among which are motor vehicles, recognized as the major contributor of air pollutants in urban areas. To determine the emissions for CO, SO₂, and NO₂ from motor vehicles as part of the attempt to realize the extent of traffic air pollution, measurements were carried out in two heavily traversed traffic tunnels in Tehran metropolitan area. The concentrations of pollutants and metrological and traffic data were collected through intensive measurements from September 27 to October 17, 2016. Resalat Tunnel fleet was composed of about 10% diesel-fueled vehicles and 90% non-diesel-fueled vehicles while throughout the entire duration of our campaign, only non-diesel-fueled vehicles traversed Niayesh Tunnel. Under an average traffic speed of 43 km h^-1, emission factors from Resalat Tunnel campaign were measured to be (6.59 ± 2.69)E+3, (1.42 ± 0.84)E+2, and 6.80 ± 4.99 mg km^-1 for CO, SO₂, and NO₂, respectively. These values were respectively 11% higher, 22% lower, and 40% higher than those from Niayesh Tunnel measurements which were recorded at a traffic speed of 30 km h^-1. Current results indicate that the vehicular emissions in certain countries, especially the developing ones and in this case, Iran, are quite different from those measured in developed countries and that the high emission levels of SO₂ in Iran are associated with the high sulfur content of the gasoline.

An Exposure Appraisal of Outdoor Air Pollution on the Respiratory Well-being of a Developing City Population

Zaria is the educational hub of northern Nigeria. It is a developing city with a pollution level high enough to be ranked amongst the World Health Organization’s (WHO) most polluted cities. The study appraised the influence of outdoor air pollution on the respiratory well-being of a population in a limited resource environment. With the approved ethics, the techniques utilized were: portable pollutant monitors, respiratory health records, WHO AirQ+ software, and the American Thoracic Society (ATS) questionnaire. They were utilized to acquire day-time weighted outdoor pollution levels, health respiratory cases, assumed baseline incidence (BI), and exposure respiratory symptoms among selected study participants respectively. The study revealed an average respiratory illness incidence rate of 607 per 100,000 cases. Findings showed that an average of 2648 cases could have been avoided if the theoretical WHO threshold limit for the particulate matter with diameter of <2.5/10 micron (PM_2.5/PM₁₀) were adhered to. Using the questionnaire survey, phlegm was identified as the predominant respiratory symptom. A regression analysis showed that the criteria pollutant PM_2.5, was the most predominant cause of respiratory symptoms among interviewed respondents. The study logistics revealed that outdoor pollution is significantly associated with respiratory well-being of the study population in Zaria, Nigeria.

Developing air exchange rate models by evaluating vehicle in-cabin air pollutant exposures in a highway and tunnel setting: case study of Tehran, Iran

The passengers inside vehicles could be exposed to high levels of air pollutants particularly while driving on highly polluted and congested traffic roadways. In order to study such exposure levels and its relation to the cabin ventilation condition, a monitoring campaign was conducted to measure the levels inside the three most common types of vehicles in Tehran, Iran (a highly air polluted megacity). In this regard, carbon monoxide (CO) and particulate matter (PM) were measured for various ventilation settings, window positions, and vehicle speeds while driving on the Resalat Highway and through the Resalat Tunnel. Results showed on average in-cabin exposure to particle number and PM₁₀ for the open windows condition was seven times greater when compared to closed windows and air conditioning on. When the vehicle was passing through the tunnel, in-cabin CO and particle number increased 100 and 30%, respectively, compared to driving on highway. Air exchange rate (AER) is a significant factor when evaluating in-cabin air pollutants level. AER was measured and simulated by a model developed through a Monte Carlo analysis of uncertainty and considering two main affecting variables, vehicle speed and fan speed. The lowest AER was 7 h^-1 for the closed window and AC on conditions, whereas the highest AER was measured 70 h^-1 for an open window condition and speed of 90 km h^-1. The results of our study can assist policy makers in controlling in-cabin pollutant exposure and in planning effective strategies for the protection of public health.

A general method for evaluating the effects of air pollutants on lung cancer prevalence

It is widely accepted that some air pollutants are related to lung cancer prevalence. An effective method is proposed to quantitatively evaluate the effects of air pollutants and the interactions between them. The method consisted of three parts: data decomposition, comparable data generation and relationship inference. Firstly, very limited monitoring data published by Geographic Information System were applied to calculate the inhalable air pollution of relatively massive patient samples. Then the investigated area was partitioned into a number of districts, and the comparable data containing air pollutant concentrations and lung cancer prevalence in all districts were generated. Finally, the relationships between pollutants and lung cancer prevalence were concluded by an information fusion tool: Choquet integral. As an example, the proposed method was applied in the investigation of air pollution in Tianjin, China. Overall, SO₂, O₃ and PM_2.5 were the top three factors for lung cancer. And there was obvious positive interaction between O₃ and PM_2.5 and negative interaction among SO₂, O₃ and PM₁₀. The effect of SO₂ on men was larger than on women. O₃ and SO₂ were the most important factors for the adenocarcinoma and squamous cell carcinoma, respectively. The effect of SO₂ or NO₂ on squamous cell carcinoma is obviously larger than that on adenocarcinoma, while the effect of O₃ or PM_2.5 on adenocarcinoma is obviously larger than that on squamous cell carcinoma. The results provide important suggestions for management of pollutants and improvement of environmental quality. The proposed method without any parameter is general and easily realized, and it sets the foundation for further researches in other cities/countries. Implications: For total lung cancer prevalence, male and female lung cancer prevalence, and adenocarcinoma and squamous cell carcinoma prevalence, the proposed method not only quantify the effect of single pollutant (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) but also reveals the correlations between different pollutants such as positive interaction or negative interaction. The proposed method without any geographic predictor and parameter is much easier to realize, and it sets the foundation for further research in other cities/countries. The study results provide important suggestions for the targeted management of different pollutants and the improvement of human lung health.

Thermal evaluation of urbanization using a hybrid approach

Urban development increases runoff temperatures from buildings and pavement, which can be harmful to aquatic life. However, our ability to predict runoff temperature as a function of land use is limited. This paper explores available tools for simulating runoff temperature with respect to brook trout (Salvelinus sp.), a sensitive species. The Minnesota Urban Heat Export Tool (MINUHET) and the Storm Water Management Model (SWMM) were applied to a 14.1 km² portion of the Stroubles Creek watershed near Blacksburg, Virginia for two summers. Streamflow, water temperature, and weather data were acquired from the Virginia Tech StREAM Lab (Stream Research, Education, and Management) monitoring stations. SWMM and MINUHET were calibrated and validated for streamflow, and stream temperature, respectively. The models were sensitive to imperviousness (SWMM-predicted streamflow) and dew point temperature (MINUHET-predicted water temperature). While the models output time-step was 15 min, the model performance in simulating streamflow was evaluated using Nash-Sutcliffe Efficiency (NSE) on hourly time-steps. NSE values were 0.67 and 0.65 for SWMM and 0.62 and 0.57 for MINUHET during the calibration and validation periods, respectively, indicating that SWMM performed better than MINUHET in streamflow simulation. Stream temperatures were simulated using MINUHET with NSE value of 0.58 for the validation period, demonstrating a satisfactory simulation of water temperature. Since SWMM is not capable of stream temperature simulation beyond simple mixing. Hydrologic and thermal outputs from SWMM and MINUHET were combined in a hybrid approach that emphasized the strength of each respective model, i.e. SWMM for runoff and streamflow and MINUHET for water temperature. Heat loads were simulated using the MINUHET and the Hybrid models; the Hybrid model (0.56) had a greater NSE than MINUHET (0.45) alone. MINUHET predictions indicated water temperatures would exceed the trout toxicity threshold of 21 °C during 39% and 38% of calibration and validation periods, respectively. Since the observed temperature exceeded the toxicity threshold 59% and 53% of the time for the calibration and validation periods, respectively, MINUHET was not a conservative predictor of the duration of temperatures exceeding the toxicity threshold value.

Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS

Transportation infrastructures play a significant role in the economy as they provide accessibility services to people. Infrastructures such as highways, road networks, and toll plazas are rapidly growing based on changes in transportation modes, which consequently create congestions near toll plaza areas and intersections. These congestions exert negative impacts on human health and the environment because vehicular emissions are considered as the main source of air pollution in urban areas and can cause respiratory and cardiovascular diseases and cancer. In this study, we developed a hybrid model based on the integration of three models, correlation-based feature selection (CFS), support vector regression (SVR), and GIS, to predict vehicular emissions at specific times and locations on roads at microscale levels in an urban areas of Kuala Lumpur, Malaysia. The proposed model comprises three simulation steps: first, the selection of the best predictors based on CFS; second, the prediction of vehicular carbon monoxide (CO) emissions using SVR; and third, the spatial simulation based on maps by using GIS. The proposed model was developed with seven road traffic CO predictors selected via CFS (sum of vehicles, sum of heavy vehicles, heavy vehicle ratio, sum of motorbikes, temperature, wind speed, and elevation). Spatial prediction was conducted based on GIS modelling. The vehicular CO emissions were measured continuously at 15 min intervals (recording 15 min averages) during weekends and weekdays twice per day (daytime, evening-time). The model’s results achieved a validation accuracy of 80.6%, correlation coefficient of 0.9734, mean absolute error of 1.3172 ppm and root mean square error of 2.156 ppm. In addition, the most appropriate parameters of the prediction model were selected based on the CFS model. Overall, the proposed model is a promising tool for traffic CO assessment on roads.

Seasonal trends in the composition and sources of PM2.5 and carbonaceous aerosol in Tehran, Iran

Currently PM_2.5 is a major air pollution concern in Tehran, Iran due to frequent high levels and possible adverse impacts. In this study, which is the first of its kind to take place in Tehran, composition and sources of PM_2.5 and carbonaceous aerosol were determined, and their seasonal trends were studied. In this regard, fine PM samples were collected every six days at a residential station for one year and the chemical constituents including organic marker species, metals, and ions were analyzed by chemical analysis. The source apportionment was performed using organic molecular marker-based CMB receptor modeling. Carbonaceous compounds were the major contributors to fine particulate mass in Tehran, as OC and EC together comprised on average 29% of PM_2.5 mass. Major portions of OC in Tehran were water insoluble and are mainly attributed to primary sources. Higher levels of several PAHs, which are organic tracers of incomplete combustion, and hopanes and steranes as organic tracers of mobile sources were obtained in cold months and compared to the warm months. The major contributing source to particulate OC was identified as vehicles, which contributed about 72% of measured OC. Among mobile sources, gasoline-fueled vehicles had the highest impact with a mean contribution of 48% to the measured OC. Mobile sources also were the largest contributor to total PM_2.5 (40%), followed by dust (24%) and sulfate (11%). In addition to primary emissions, mobile sources also directly and indirectly played an important role in another 27% of fine particulate mass (secondary organics and ions), which highlights the impact of vehicles in Tehran. Our results highlighted and quantified the role of motor vehicles in fine PM production, particularly during winter time. The results of this study could be used to set more effective regulations and control strategies particularly upon mobile sources.

Traffic-Related Air Pollution and All-Cause Mortality during Tuberculosis Treatment in California

BACKGROUND

Ambient air pollution and tuberculosis (TB) have an impact on public health worldwide, yet associations between the two remain uncertain.

OBJECTIVE

We determined the impact of residential traffic on mortality during treatment of active TB.

METHODS

From 2000-2012, we enrolled 32,875 patients in California with active TB and followed them throughout treatment. We obtained patient data from the California Tuberculosis Registry and calculated traffic volumes and traffic densities in 100- to 400-m radius buffers around residential addresses. We used Cox models to determine mortality hazard ratios, controlling for demographic, socioeconomic, and clinical potential confounders. We categorized traffic exposures as quintiles and determined trends using Wald tests.

RESULTS

Participants contributed 22,576 person-years at risk. There were 2,305 deaths during treatment for a crude mortality rate of 1,021 deaths per 10,000 person-years. Traffic volumes and traffic densities in all buffers around patient residences were associated with increased mortality during TB treatment, although the findings were not statistically significant in all buffers. As the buffer size decreased, fifth-quintile mortality hazards increased, and trends across quintiles of traffic exposure became more statistically significant. Increasing quintiles of nearest-road traffic volumes in the 100-m buffer were associated with 3%, 14%, 19%, and 28% increased risk of death during TB treatment [first quintile, referent; second quintile hazard ratio (HR)=1.03 [95% confidence interval (CI): 0.86, 1.25]; third quintile HR=1.14 (95% CI: 0.95, 1.37); fourth quintile HR=1.19 (95% CI: 0.99, 1.43); fifth quintile HR=1.28 (95% CI: 1.07, 1.53), respectively; p-trend=0.002].

CONCLUSIONS

Residential proximity to road traffic volumes and traffic density were associated with increased all-cause mortality in patients undergoing treatment for active tuberculosis even after adjusting for multiple demographic, socioeconomic, and clinical factors, suggesting that TB patients are susceptible to the adverse health effects of traffic-related air pollution. https://doi.org/10.1289/EHP1699.

An Assessment of Spatial Pattern Characterization of Air Pollution: A Case Study of CO and PM2.5 in Tehran, Iran

Statistically clustering air pollution can provide evidence of underlying spatial processes responsible for intensifying the concentration of contaminants. It may also lead to the identification of hotspots. The patterns can then be targeted to manage the concentration level of pollutants. In this regard, employing spatial autocorrelation indices as important tools is inevitable. In this study, general and local indices of Moran’s I and Getis-Ord statistics were assessed in their representation of the structural characteristics of carbon monoxide (CO) and fine particulate matter (PM2.5) polluted areas in Tehran, Iran, which is one of the most polluted cities in the world. For this purpose, a grid (200 m × 200 m) was applied across the city, and the inverse distance weighted (IDW) interpolation method was used to allocate a value to each pixel. To compare the methods of detecting clusters meaningfully and quantitatively, the pollution cleanliness index (PCI) was established. The results ascertained a high clustering level of the pollutants in the study area (with 99% confidence level). PM2.5 clusters separated the city into northern and southern parts, as most of the cold spots were situated in the north half and the hotspots were in the south. However, the CO hotspots also covered an area from the northeast to southwest of the city and the cold spots were spread over the rest of the city. The Getis-Ord’s PCI suggested a more polluted air quality than the Moran’s I PCI. The study provides a feasible methodology for urban planners and decision makers to effectively investigate and govern contaminated sites with the aim of reducing the harmful effects of air pollution on public health and the environment.

The effects of vegetation barriers on near-road ultrafine particle number and carbon monoxide concentrations

Numerous studies have shown that people living in near-roadway communities (within 100 m of the road) are exposed to high ultrafine particle (UFP) number concentrations, which may be associated with adverse health effects. Vegetation barriers have been shown to affect pollutant transport via particle deposition to leaves and altering the dispersion of emission plumes, which in turn would modify the exposure of near-roadway communities to traffic-related UFPs. In this study, both stationary (equipped with a Scanning Mobility Particle Sizer, SMPS) and mobile (equipped with Fast Mobility Particle Sizer, FMPS) measurements were conducted to investigate the effects of vegetation barriers on downwind UFP (particle diameters ranging from 14 to 102 nm) concentrations at two sites in North Carolina, USA. One site had mainly deciduous vegetation while the other was primarily coniferous; both sites have a nearby open field without the vegetation barriers along the same stretch of limited access road, which served as a reference. During downwind conditions (traffic emissions transported towards the vegetation barrier) and when the wind speed was above or equal to 0.5m/s, field measurements indicated that vegetation barriers with full foliage reduced UFP and CO concentrations by 37.7-63.6% and 23.6-56.1%, respectively. When the test was repeated at the same sites during winter periods when deciduous foliage was reduced, the deciduous barrier during winter showed no significant change in UFP concentration before and after the barrier. Results from the stationary (using SMPS) and mobile (using FMPS) measurements for UFP total number concentrations generally agreed to within 20%.