Seasonal variation in ambient PM mass and number concentrations (case study: Tehran, Iran)

The relative contributions of traffic and non-traffic sources in ultrafine particle formations in Tehran mega city

Emissions of ultrafine particles (UFPs; diameter < 100 nm) are strongly associated with traffic-related emissions and are a growing global concern in urban environments. The aim of this study was to investigate the variations of particle number concentration (PNC) with a diameter > 10 nm at nine stations and understand the major sources of UFPs (primary vs. secondary) in Tehran megacity. The study was carried out in Tehran in 2020. NOx and PNC were reported from a total of nine urban site locations in Tehran and BC concentrations were examined at two monitoring stations. Data from all stations showed diurnal changes with peak morning and evening rush hours. The hourly PNC was correlated with NOx. PNCs in Tehran were higher compared to those of many cities reported in the literature. The highest concentrations were at District 19 station (traffic) and the lowest was at Punak station (residential) such that the average PNC varied from 8.4 × 103 to 5.7 × 104 cm-3. In Ray and Sharif stations, the average contributions of primary and secondary sources of PNC were 67 and 33%, respectively. Overall, we conclude that a decrease in primary emission leads to a decrease in the total concentration of aerosols, despite an increase in the formation of new particles by photo nucleation.

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.

Characteristics, toxicity, source identification and seasonal variation of atmospheric polycyclic aromatic hydrocarbons over East India

Atmospheric PM_2.5-bound polycyclic aromatic hydrocarbons (PAHs) were analyzed over urban and rural sites during January to December 2018. Total annual average concentration of PM_2.5 was 74.41 ± 24.96 μg/m³ over urban and 52.03 ± 13.11 μg/m³ over rural site during study time. The annual average concentration of PM_2.5 over urban and rural atmospheres were found approximately twice in urban and found also higher over rural site, with respect to National Ambient Air Quality (NAAQ) standard of 40 μg/m³ for PM_2.5 concentration. The annual concentration of PAHs was 750.80 ± 19.49 ng/m³ over urban, and, over rural, it was 559.59 ± 17.56 ng/m³. The seasonal variation of concentration of PAHs was in order of winter > post-monsoon > summer > monsoon. The most predominant PAHs were IcP (17.21%), B(ghi) P(15.22%), BkF (11.60%), DBahA (11.34%) and BbF (10.91%) to the total PAH concentration over urban site; over rural site, most predominant PAHs were IcP (16.02%), B(ghi)P, (15.63%), BkF (11.46%), DBahA (11.12%) and BbF (8.99%) of total PAHs. DBahA concentration was contributed approximately 46% carcinogenicity over both urban and rural sites, and BaP contributes 33.56% carcinogenicity over urban site and 34.62% carcinogenicity over rural site of total PAH samples. The Excess Life Time Cancer Risk (ELCR) values over urban were found at acceptable limit 10^-6-10^-4 given by the United States Environmental Protection Agency. Over rural site, the ELCR value was found near about acceptable limit. Diagnostic ratio analysis demonstrated that major sources of PAHs were pyrogenic sources and vehicular emission over study. Air parcel through trajectories over study site also contributed in PAH concentration.

Ultrafine particles and PM2.5 in the air of cities around the world: Are they representative of each other?

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM_2.5 (mass concentration of particles with aerodynamic diameter < 2.5 μm) and factors that influence their concentrations. Hourly average PNC and PM_2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 10³ to 19.5 × 10³ particles·cm^-3 and from 7.0 to 65.8 μg·m^-3 for PNC and PM_2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM_2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM_2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM_2.5 demonstrated that a high PNC level does not lead to a high PM_2.5, and vice versa. The particle number-to-mass ratio (in units of 10⁹ particles·μg^-1) ranged from 0.14 to 2.2, >1 for roadside sites and <1 for urban background sites with lower values for more polluted cities. The Pearson's r ranged from 0.09 to 0.64 for the log-transformed data, indicating generally poor linear correlation between PNC and PM_2.5. Therefore, PNC and PM_2.5 measurements are not representative of each other; and regulating PM_2.5 does little to reduce PNC. This highlights the need to establish regulatory approaches and control measures to address the impacts of elevated UFP concentrations, especially in urban areas, considering their potential health risks.

Discrimination of aerosol types over the Tehran city using 5 years (2011-2015) of MODIS collection 6 aerosol products

PURPOSE

Tehran, Iran, is an interesting location for aerosol studies because it is affected by anthropogenic pollution and desert dust aerosols. The aim of this study was to discriminate the aerosol types using satellite data over the city.

METHOD

The study was performed using Level-2 daily Aerosol Optical Depth (AOD) and Ångström Exponent (AE) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites for the years 2011 to 2015. As the Deep Blue (DB) AE retrievals are more reliable than the Dark Target (DT) AE retrievals, the study was performed using DB data.

RESULTS

The number of granules with successful retrievals (at least in two pixels with AODs >0.2 over Tehran with high quality assurance) was 200, which indicates that aerosols could be observed in 5.47% (200 from 3652 of Terra and Aqua granules) of the overpasses during the study period. The maximum and minimum values of AOD occurred during May (0.32 ± 0.27) and August (0.18 ± 0.07), respectively. Based on the AOD vs. AE data, aerosols were classified into three different categories: urban/industry (UI), Desert Dust (DD) and Mixed (Mix). To improve the accuracy of the aerosol classification, the analysis was limited to retrievals with AOD values larger than 0.2. The DD, UI and Mix types had 48.5%, 30.5% and 21% contribution in the aerosol days, respectively.

CONCLUSIONS

The maximum DD frequency was observed in the spring and summer seasons, while the UI type had its maximum during the cold season. The AOD of the DD type (over Tehran) correlated well with the AOD observations done at the Aerosol Robotic Network (AERONET) site in Zanjan (300 km northwest from Tehran). For the UI type, no relationship with the AERONET AOD was detected. This gives confidence in our aerosol typing as the contribution of dust in the aerosol load is mainly from long-range transport, whereas the urban aerosols originate from local sources. Back trajectories ending in Tehran show that the northeast and west trajectories are two main transport routes for the dust to the study area.

Tracking atmospheric boundary layer in tehran using combined lidar remote sensing and ground base measurements

The vertical structure of the atmospheric boundary layer (ABL) has been studied by use of a depolarized LiDAR over Tehran, Iran. The boundary layer height (BLH) remains under 1km, and its retrieval from LiDAR have been compared with sonding measurements and meteorological model outputs. It is also shown that the wind speed and direction as well as topography lead to the persistence of air pollution in Tehran. The situation aggravate in fall and winter due to temperature inversion.

Speciation of atmospheric polycyclic aromatic hydrocarbons (PAHs) present during fog time collected submicron particles

Airborne submicron particles (PM1) were collected using PM1 sampler during the fog-dominated days (December 2013-January 2014). PM1 values varied between 58.12 μg/m(3) and 198.75 μg/m(3), and average mass concentration was 162.33 ± 38.25 μg/m(3) while total average concentration of particle-associated polycyclic aromatic hydrocarbon (PAHs) determined was 616.31 ± 30.31 ng/m(3). This is a signal for an alarming high pollution level at this site situated in the Indo-Gangetic Plain (IGP). PAHs were extracted from filters using toluene and acetonitrile. Quantitative measurements of polycyclic aromatic hydrocarbons (PAHs) were carried out using the high performance liquid chromatography (HPLC) technique. The extracts were analyzed for 16 target polycyclic aromatic hydrocarbons (PAHs) including carcinogenic compound benzo(a)pyrene (19.86 ± 38.98 ng/m(3)). Fluoranthene, benzo(a)anthracene, anthracene, and fluorene were the predominant compounds found in the samples collected during foggy days. Based on number of rings, four-ring PAH compounds had maximum contribution (43%) in this fog time collected submicron particles followed by three-ring (21%), five-ring (20%), six-ring (13%), and two-ring (3%), respectively. In winter and foggy days, wood and coal combustion and biomass burning also significantly contribute to the PAH levels. However, diagnostic ratio suggests diesel emissions as the prime source of PAHs at this sampling site.

Fine particulate phase PAHs in ambient atmosphere of Chennai metropolitan city, India

BACKGROUND

Airborne fine particulates (PM 2.5) and its associated polycyclic aromatic hydrocarbons (PAHs) are reportedly hazardous in urban environment due to the presence of multiple emission sources.

METHODS

In this study, fine particulates collected from fourth largest metropolitan city of India, Chennai, were extracted and analyzed for 11 PAHs by high-performance liquid chromatography equipped with a fluorescence detector.

RESULTS

PM 2.5 values varied between 27.2 and 190.2 μg/m(3), while average concentration of particle-associated PAHs determined was in the range from 325.7 to 790.8 ng/m(3), which signaled an alarming pollution level in Chennai.

CONCLUSIONS

Factor analysis suggested vehicular emissions inclusive of petrol- and diesel-driven engines as probable sources.