Source Identification of the elements in PM10 Aerosols, Case Study: Kermanshah City

Document Type : Full length article


1 MSc in Environmental Engineering, Faculty of Agricultural and Natural Resources, University of Tehran

2 Professor of Agricultural and Natural Resources, University of Tehran


Particulate matters are particles that have placed as dispersed particles, in solid or liquid, in gaseous intermediators. Recently, aerosols as one of the air pollutants, from natural or anthropogenic sources, have received the attention of many researchers due to the roles they play in global climate change and the environmental and health problems. They can scatter or absorb solar radiation and thermal radiation emitted from the earth surface. The aerosols as condensation nuclei of cloud droplets can also affect cloud formation and precipitation. Numerical studies have performed particulate matter (PM10) and their source identification.
Source identification of trace elements in PM2.5 in Mira Loma, in southern California, was performed using factor analysis, the backward air mass trajectory analysis, enrichment factor calculation and the Al/Zn ratio. Al is a major constituent in the earth crust but it is not in vehicle emissions. This study suggests that the Al/Zn ratio can be used to understand the dominance of soil-related sources. The low Al/Zn ratio shows that dominant sources are vehicle emissions.
The purpose of this research is source identification of the main and trace elements of PM10 aerosols and also, investigation of effective areas in production of the aerosols (PM10) using satellite images in Kermanshah. In this research, the exploratory factor analysis has been used to identify natural and anthropogenic sources of the elements in PM10 aerosols.
Materials and Methods  
In this research, sampling of aerosols has been performed by aerosol sampler. Then, the concentrations of the eleven elements (K,Al, Na, Ca, Cu, Ni, Pb, Mn, Fe, Mg, V) have been detected by ICP-OES. 
In this study, the exploratory factor analysis has been used to identify potential sources of major and trace elements in aerosols. In this method, variables are placed in the factors so that the percentage of variance decreases from first factor to next factors. Hence, the variables in the first factor are most effective.
In this study, the days that particulate matter concentration was higher than permissible level, we have determined daily information of particulate matter concentration at Air Quality Monitoring Station in Kermanshah. Then, effective areas in production of aerosols (PM10) have been investigated using satellite images during February to July 2010.  
Results and discussion  
In the factor analysis, the variables (elements) with the factor-loading less than 0.5 are not listed in the table. The total number of factors has been selected so that the cumulative percentage of the variance explained by all the selected factors was more than 77%. Only the factors are selected that had an eigenvalue greater than one. The last column shows the values of the communalities which explains the amount of common variance for each of the variables (elements) with the four factors.
Table 3.  Factor- Loading for trace and main elements in the Kermanshah atmosphere


Component 1(soil-related emissions)

Component 2(vehicle-related emissions)

Component 3(vehicle exhaust)

Component  4(industry-oil burning emissions)










































































% variance






Cumulative % variance






Factor analysis identified four possible sources: soil-related emissions, vehicle-related emissions, vehicle exhaust, oil combustion and industry (table 3). These four factors account for an average of 77.047% of the total variance. According to this table, the first factor is heavily loaded (factor loading >0.50) for element of K, Ca, Fe, Mg, Na, Mn and Al which are soil-related elements. This factor may be related to the sources such as crust material (mineral dust), paved and unpaved roads, construction, and etc. This factor accounts for the largest part of the total variance (36.1%). This means that sources of soil-related emissions are likely the major contributors to the trace and main elements in PM10 in Kermanshah. The second factor (consisting of Cu and Pb) is likely associated with brake pads. According to the San Francisco Bay Study, the brake pads are the largest source of discharge of Cu to the Bay.
Copper is the most abundant element (up to 20%) in composition of brake pads, followed by zinc (up to 18%) and lead (up to 12%). Thus, the second factor is likely associated with vehicle-related emissions. The third factor is highly loaded for element of Fe and V which are typical of vehicle exhausts. Besides, Zn and Fe are as a possible indicator of vehicle exhaust. Fe is usually emitted from the wearing of steel parts of vehicles such as cylinders. In summary, the second factor and third factor are likely related to vehicle-related emissions. The fourth factor consists of nickel and vanadium which are mainly derived from industry and oil. Based on 33 scientific researches in Europe, source of iron, zinc, copper and lead are traffic and vehicle exhaust. The trend of their variations is dependent on the volume of the traffic emissions. Also, according to 24 scientific studies, aluminum, calcium, potassium and iron are derived from mineral dust. Based on 21 studies, the sources of vanadium and nickel have been expressed by the industry and oil burning. Obtained results of investigation of source identification of dusts using satellite images indicated that the most frequent dust (particulate matter) is in the northwestern regions between the northwest and northeast Iraq, then the east of Syria and northwest Saudi Arabia.
The crustal elements were the major contributor to the main and trace elements in PM10 in the Kermanshah atmosphere. According to the satellite images, it can be stated that Iraq and its neighboring regions have played important role in production of aerosols (PM10). 


Main Subjects

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Volume 49, Issue 4
January 2018
Pages 557-569
  • Receive Date: 09 June 2016
  • Revise Date: 08 May 2017
  • Accept Date: 21 May 2017
  • First Publish Date: 22 December 2017