Investigation of the chemical nature of precipitation and source apportionment of its constituents in Tehran metropolis, Iran

Precipitation is a key process for purifying the atmosphere of pollutants. However, precipitation chemistry is also a significant environmental catastrophe on a global scale. Tehran Metropolitan Area, Iran's capital, is one of the world's most polluted cities. Nonetheless, little effort has been paid to determining the chemical composition of precipitation in this polluted metropolis. The chemical components and likely sources of trace metals and water-soluble ions in precipitation samples collected from 2021 to 2022 at an urban location in Tehran, Iran, were investigated in this study. The pH of the rainwater samples varied from 6.330 to 7.940 (mean 7.313, volume weighted mean (VWM) 7.523). The following is the order of the VWM concentration of main ions: Ca²⁺ > HCO₃^- > Na⁺ >SO₄^2- > NH₄⁺ > Cl^- > NO₃^- > Mg²⁺> K⁺> F^-. Furthermore, we discovered that VWM concentrations for trace elements are modest, with the exception of Sr (39.104 eq L^-1). The primary neutralizing species for precipitation acidity were Ca²⁺ and NH₄⁺. Vertical feature mask (VFM) diagrams derived from cloud-aerosol lidar and infrared pathfinder satellite observation (CALIPSO) track data indicated that polluted dust was the most common pollutant in the Tehran sky that might contribute significantly to the neutralization of precipitation. A study of species concentration ratios in seawater and the earth's crust indicated that virtually all Se, Sr, Zn, Mg²⁺, NO₃^-, and SO₄^2- were anthropogenic. While Cl^- was largely obtained from sea salt, K⁺ was obtained from both the earth's crust and the sea, with the earth's crust playing a larger role in K⁺. The earth's crust, aged sea salt, industry, and combustion processes were all verified as sources of trace metals and water-soluble ions by positive matrix factorization analysis.

Statistical classification of synoptic weather patterns associated with Tehran air pollution

Introduction: Poor air quality in the heavily polluted cities like Tehran is often the main city problem that influences people health and comfort. The main goals of this study are summarized as: 1) Seasonal pollutants mean variations during 2005, meteorological conditions effects on pollutant concentration; 2) Meteorological conditions case study and pollution spatial distribution for three determining synoptic patterns (MET1, MET4, MET5); 3) Further analysis of the episode from 30th November to 13th December 2005 (MET4); 4) Episode analysis from 30th November to 13th December 2005 (MET4) and 5) Episode analysis from 12th-22th of September 2005 (MET5). These are systematic weather patterns that usually affect the air pollution levels in Tehran. Materials and methods: Concentration changes of CO, PM10, SO2 and O3, as the relationship between the air pollution extreme events and atmospheric conditions in Tehran have been investigated. The hourly air pollution data from 11 representative monitoring sites were used. To understand the relationship between local meteorological synoptic patterns and air pollution, the principal component analysis (PCA) method has been applied to meteorological data. Then for minimizing the data complication the varimax rotations (VR) was used and five synoptic perspectives weather patterns have resulted for highly polluted periods. Results: Pollutants correlation investigation of the five patterns showed that air quality was highly dependent on middle tropospheric high geopotential ridge development, local southerly wind with strong static stability. Conclusion: The most polluted periods were associated with a weak pressure gradient, a weak wind, severe air descent, and radiation inversion.

Characterization of aerosol optical properties using multiple clustering techniques over Zanjan, Iran, during 2010-2013

Discrimination of aerosol types is very important, because different aerosols are created from diverse sources having different chemical, physical, and optical properties. In the present study, we have analyzed the seasonal classification of aerosol types by multiple clustering techniques, using AERosol Robotic NETwork (AERONET) data during 2010-2013 over Zanjan, Iran. We found that aerosol optical depth (AOD) showed pronounced seasonal variations of a summer high and winter low. Conversely, the values of the Angstrom exponent (AE) in winter and fall were higher than in spring and summer, which confirmed the presence of fine particles, while the low value of AE in the summer and spring represented the existence of coarse particles. Single Scattering Albedo (SSA) variations revealed the presence of scattering aerosols like dust in spring, summer, and fall while the dominance of absorbing-type aerosols in winter were also observed. The influence of local anthropogenic activities has caused a higher concentration of fine aerosols, and a higher fine mode fraction (FMF) of AOD in winter was recorded. Classification of aerosol types was carried out by analyzing different aerosol properties such as AOD versus AE, extinction Angstrom exponent (EAE) versus SSA, EAE versus absorption Angstrom exponent (AAE), FMF AOD versus EAE, and SSA versus FMF AOD. The analysis revealed the presence of dust and polluted dust in spring, summer, and fall in the atmosphere of Zanjan. Urban/industrial aerosols were available in all seasons, especially in fall and winter. The mixed aerosols existed in all seasons over the study location; however, no biomass burning aerosols were found. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol subtype profiles showed the dominance of dust and polluted dust in spring and summer. However, the presence of polluted dust and industrial smoke during fall and winter were also noted over the study site.