seasonal variation of selected metals in particulate

Aerosol and Air Quality Research, 16: 990–999, 2016 Copyright © Taiwan Association for Aerosol Research ISSN: 1680-8584 print / 2071-1409 online doi: 10.4209/aaqr.2015.02.0074

Seasonal Variation of Selected Metals in Particulate Matter at an Industrial City Kota, India Manju Meena1, Bharat Singh Meena1, Uttra Chandrawat1, Ashu Rani2* 1 Department of Chemistry, Government College, Kota-324001, Rajasthan, India 2 Department of Pure and Applied Chemistry, University of Kota, Kota-324005, Rajasthan, India

ABSTRACT

This study investigates seasonal variation in concentration of some heavy metals in suspended and respirable particulate matter (SPM and RPM) collected from five different zones situated in Kota city during both summer (March, April, May and October) and winter (January, February, November and December) seasons of 2011–2012. Mean concentrations of anthropogenic origin metals (Pb, Zn, Cu and Cd) were higher in winter and lower in summer with their relative abundance in order: Zn > Pb > Cu > Cd while reverse trend was observed for crustal origin metals (Ca, Mg and Fe) at all zones. Meteorological conditions such as temperature, relative humidity, wind velocity and wind direction during winter and summer were found affecting the metals concentration trends in different seasons. Wind roses indicate that the zones lying in predominant North-east wind direction from point source (KSTPS) in winter (25.74%) and summer (15.31%) faced higher metal burden following zone 1, which is suffering most owing to its closest location to the source. Statistical analysis by Pearson’s correlations, enrichment factor and principal component analysis indicates that coal based Thermal Power Plant is the major source of heavy metals besides other industrial activities in the study area. It is to be noted that because of higher residence time, significant concentration of Pb is found at all the zones in the city which, probably, has its origin in earlier vehicular exhaust as well. Keywords: Seasonal variation; Suspended and respirable particulate matter; Pearson’s correlations; Enrichment factor; Principal component analysis. INTRODUCTION

Particulate matter (PM) in the atmosphere is a complex mixture of elemental and organic carbon, mineral dust, trace elements and water (Lim et al., 2010). It originates from both the natural sources such as wind erosion, crushing, abrasion of surfaces, suspension and re-suspension of soil minerals, volcanic eruptions, dust storms and anthropogenic sources namely industrial processes, traffic sources, coal combustion etc. (Florence et al., 2012). Particulate matter has serious environmental impacts on climate, biogeochemical cycling in ecosystems, outside visibility and the health of living things (Colette et al., 2008; Chen et al., 2010).

Size, concentration, composition and toxicity of PM are important factors which can greatly affect the possible human health problems associated with their exposure (Hu et al., 2014; Kim et al., 2015). It is, particularly, the fine and ultra-fine PM that harbours the capacity to outsmart * Corresponding author.

Tel.: +919352619059; Fax: +91-744-2411742 E-mail address: [email protected]

the natural defence functions within our respiratory system (Samara et al., 2003; Quiterio et al., 2004; Shah et al., 2006b; Pérez et al., 2008; Begum et al., 2010). The particle size appears to have a carrier capacity for associated chemicals. The fine and ultra-fine particles with their potential of entering the blood stream, carry along with them their constituents enabling them to cause all sorts of systemic effects. Among those constituents, metals such as iron, zinc, copper, cadmium and lead etc. have toxicological and carcinogenic effects (Gilmour et al., 1996; Moja and Mnisi, 2013).

Over the last few decades, intensive monitoring programs of heavy metals in atmospheric precipitations have been carried out worldwide, which are mainly focused on the chemical characteristics and long-term temporal trends (Halstead et al., 2000; Wong et al., 2003; Gabrielli et al., 2008; Garcia et al., 2009; Kyllonen et al., 2009). According to these studies, the loadings and sources of heavy metals in precipitation have great spatial variability over different locations, which is mainly caused by different meteorological conditions (prevailing wind directions and type, frequency, temperature, relative humidity and amount of precipitation) and the emission patterns of pollutants (emission sources, distance from emission sources and the sampling sites).

City Kota is having coal based Kota Super Thermal

Meena et al., Aerosol and Air Quality Research, 16: 990–999, 2016 991

Power Station (KSTPS), where huge amount i.e., approximate 3000 metric tonne per day of fly ash (homogeneous mixture of several metal oxides viz. SiO2, Al2O3, Fe2O3, CaO, MgO, CuO, CdO, MnO2, NiO, ZnO, PbO etc.) is produced and released in the atmosphere. Several small and large scale industries including DCM Shriram Consolidated Limited (DSCL), Multimetals Limited, Samtel Glass Limited, Chambal Fertilizers and Chemicals Limited (CFCL), Shriram Fertilizers and Metal India, Shriram Rayons and a number of Kota stone cutting polishing units further enhance the heavy metal burden of the city environment. In the past, cases of asthmatic and respiratory disorders in residents of the zones characterized by these industrial activities have been presented in local newspapers in the form of internal reports, however, research studies relating to atmospheric pollution caused by fine particulate matter associated with fly ash emission from KSTPS are scanty.

Kota has three distinct seasons; summer, rainy and winter. We have selected only two seasons (winter and summer) for particulate matter analysis because during rainy season, relatively high amount of rainfall and humidity is experienced causing very less amount of particulate matter so we did not consider the rainy season. Therefore, the present study has been conducted during both summer (March, April, May and October) and winter (January, February, November and December) seasons of 2011–2012 with the main objectives: i) to determine the composition of suspended and respirable particulate matter in terms of crustal (Fe, Ca and Mg) and anthropogenic (Cu, Cd, Zn and Pb) metals at various sampling sites located in five different zones covering entire Kota city area; ii) to identify possible sources of heavy metals associated with SPM and RPM using statistics namely enrichment factor, Pearson’s correlation coefficient and principal component analysis; iii) to study the effect of climate on the concentration levels of heavy metals as a function of sampling sites, distance from KSTPS, seasons and meteorological parameters such as temperature, relative humidity, wind speed and wind direction. BACKGROUND OF THE STUDY AREA

Kota is one of the major industrial city of Rajasthan state in India. It is situated at 25°11 N and 75°51 E on the eastern bank of river Chambal in the southern part of Rajasthan with an elevation of 271 meters (889 feet) above sea level on the South-east of Aravali ranges. The total geographical area of the district is 5,21,133 hectares as per land. Kota has a semi arid climate with temperature varying from minimum of 6°C in winter (January) to maximum 47°C in summer (June) and an average annual rainfall of about 885.6 mm. The monsoon season follows with comparatively lower temperature with higher humidity and frequent torrential downpours. It is concluded from the wind rose analysis that the prevailing wind directions in the city during this study are North-east in winter (25.74%) and summer (15.31%). Many large and small scale industries are present due to availability of river water and power supply. A popular cost effective building stone i.e., Kota stone is being excavated, cut to various sizes and polished

in more than 200 units generating huge amount of slurry waste containing mainly CaO, MgO and SiO2. In addition, Kota district is a major power production centre of the country having coal based KSTPS identified as point source for heavy metal pollution in the present study. MATERIALS AND METHODS Sampling Sites

The sampling sites for atmospheric precipitation were chosen with the help of cartographic charts, field job and GPS (Global Positioning System). The choice of the sampling sites followed some criteria laid by ASTM D 5111 Standards (ASTM, 1996a). These criteria were: i) distance from point source (approximately a radius of 12 km from KSTPS); ii) predominant wind direction; iii) the distance from obstacles that could interfere in sampling (twice the height of obstacles); and iv) logistics (security, access, electric power supply). The entire city area was divided into five zones (Fig. 1). The location of the zones with respect to the point source KSTPS and other possible source of heavy metal in the study area are presented in Table 1.

Sampling Methods

A high volume sampler with respirable dust sampler attachment was used for the measurement of suspended particulate matter (PM10–100) and respirable particulate matter (< PM10). A total of 626 samples of both matter i.e., SPM (313 samples) and RPM (313 samples) were collected using above mentioned high volume air sampler model IPM 165 (Fig. 2) placed at about 6 meter height from the ground level at various sampling sites on 8 hourly basis and afterwards taking their average for 24 hour data (twice a week) during both summer (March, April, May and October) and winter (January, February, November and December) seasons of 2011–2012 on the clear day without wet precipitation activities.

The IPM 165 sampler first separates the coarser particles (larger than 10 microns) from the air stream before filtering it on the 0.5 micron pore size filter allowing the measurement of both suspended particulate matter and respirable fraction of this total suspended particulate matter (TSP). Ambient air, laden with suspended particulates, enters the system through the inlet pipe where coarse and non-respirable particulate matter is separated from the air stream by centrifugal forces acting on the solid particles. These separated particulates fall through a cyclone’s conical Hooper and collected in the sampling pan placed at its bottom. The fine dust forming the respirable fraction of the TSP, is carried by the air stream to the pre-weighed filter paper of size 20 cm × 25.4 cm (with rough surface upwards) clamped between the top cover and filter adaptor assembly, to be retained by this filter paper. Afterwards, the carrier air is exhausted from the system through the blower. The folded filter paper is transferred to a clean petri dish and kept in the hot air oven for about 30 minutes followed by transfer to a dessicator for cooling. SPM samples (from pan) and the filter papers (re- weighed with RPM samples up to 4 decimals) were analyzed for their total metal content after digestion.


Fig. 1. Kota city map.

Chemical Analysis For analysis of heavy metal content in SPM, 1 gm of

sample was allowed to remain over night at ambient temperature in a covered beaker (to avoid the loss of Cd and Pb) containing a mixture of high purity HNO3 (5 mL). After slow evaporation to dryness, 2 mL of HNO3 was added and the solution was extracted with 0.1 N HCl. It is then filtered through pre-washed Whatman filter paper no. 42 and diluted with 1% HNO3 in a 50 mL polyethylene bottle (Rashed, 2008).

Each filter disc (containing RPM) was extracted using digestion reagents; hydrogen peroxide 35%, hydrochloric acid 37% and nitric acid 65% (Merck, Germany) following similar open acid digestion procedures as reported in literature (Loyola et al., 2009; Gharaibeh et al., 2010). Each filter paper was divided into four equal pieces using a clean paper

cutter. One portion of the divided paper was further torn into small pieces and transferred to beaker to which 30 mL of HCl (1+1) and 5 ml of H2O2 were added. The beaker was covered with a watch glass and heated on a hot plate at 120°C for 1 hour. After cooling, the solution was separated using a filter paper (Whatman 42). Another 20 mL of HCl (1+1) was added to the residue in the beaker and heated for 15 minutes for complete metal extraction. The beaker content was filtered again and the filtrate was added to the previously collected filtrate. This solution was concentrated on a hot plate till small amount of liquid left in the beaker. Then, HNO3 (2+98) mixture was added to the beaker. The prepared sample was transferred to a 25 mL volumetric flask and filled up to the mark with HNO3 mixture. After transfer to polyethylene bottle the digested samples were analyzed for their metal content.


Table 1. Location and characteristics of different zones of Kota city for present study.

Zone No. Location with reference to point source (KSTPS) Characteristics

Zone-1 Within 2 km. radii surrounding point source

(KSTPS)

Coal dust (as raw material for coal based KSTPS); Fly ash (emitted from KSTPS); Soil dust; High population

density; High traffic load

Zone-2 2–10 km. towards North-east direction from

point source (KSTPS)

Fly ash (emitted from KSTPS favoured by north-east wind blow mainly during the study period); Soil dust; Traffic dust owing to location of several public transport centres

Zone-3 2–7 km. towards East direction from point source

(KSTPS)

Fly ash (emitted from KSTPS); Soil dust; High traffic dust; Commercial activities (Multimetals Limited, Samtel

Glass Limited); High population density

Zone-4 2–12 km. towards East-south direction from

point source (KSTPS)

Fly ash (emitted from KSTPS); Soil dust; High traffic dust; Establishment of industrial complex (DCM Shriram Consolidated Limited, Shriram Fertilizers and Metal India,

Shriram Rayons); High population density

Zone-5 2–8 km. towards South direction from point

source (KSTPS) Fly ash (emitted from KSTPS); Soil dust; Residential area;

Stone mining activities

Fig. 2. Respirable dust sampler (IPM 165).

After digestion, the concentrations of 6 metals (Fe, Zn, Cu, Cd, Mg and Pb) were measured by Direct Air – Acetylene Flame method (Atomic Absorption Spectrophotometer - Shimadzu-6300). The Ca metal concentration was determined using Flame Photometer (Systronics -128) method. Certified standard solutions (CertiPUR* - MERCK) were used for calibrating the instruments. Blanks, quality control standards and standard reference materials were inserted during the analytical measurement to detect contamination and drift. The elemental concentrations of the blanks were lower than 1% of the mean analyte concentration for all metals and the

precision (RSD) of the control standards and replicates were generally lower than 5%. Statistical Analysis

The meteorological data during the measurement period [summer (March, April, May and October) and winter (January, February, November and December) seasons of 2011–2012] were collected from the Automated Weather Station (model number: DCPAWS02) mounted at the Kota Aerodrome, India. With the help of above meteorological data, monthly wind roses of study period were drawn using


enviroware wind rose software. The results were summarized into a multielemental database using MS – Excel 2007. Analysis of principal components was performed with SPSS version 16 software. RESULT AND DISCUSSION Metal Analysis

Concentrations of crustal and anthropogenic metals in suspended (SPM) and respirable particulate matter (RPM) at five zones in Kota city were shown in Fig. 3. For both SPM and RPM, the concentration levels of crustal metals (Ca, Mg and Fe) were observed highest in Z5 and lowest in Z1 in the observed seasons. The activities related with the

erosion and disturbance of upper layer of earth crust in zone 5 might be responsible for causing their higher concentrations while these activities were lower in Z1 resulting in their reduced levels.

These metals (Ca, Mg and Fe), originating mainly from local soil, undergo a process of resuspension or mobilization and finally become incorporated in the local area. It is to be noted here that higher Ca metal concentration originates from carbonates generated from alkaline sources such as soil dust and earth crust whereas elevated levels of Mg metal can be the result of lime stone and mining activities carried out in the study area. Fe content is present in atmospheric particulate matter in the form of various oxides such as goethite, hematite, magnetite etc. indicating its origin from

Fig. 3. Seasonal average concentrations of Ca, Mg, Fe, Pb, Zn, Cu and Cd measured at the five zones in SPM and RPM.

100200300400500600

Z1 Z2 Z3 Z4 Z5Con

cent

rati

on

(mg

L–1

)

Zones

Ca

RPM WinterSPM WinterRPM SummerSPM Summer

02468

1012

Z1 Z2 Z3 Z4 Z5

Con

cent

rati

on(m

g L

–1)

Zones

Mg


5101520253035

Z1 Z2 Z3 Z4 Z5

Con

cent

rati

on(m

g L

–1)

Zones

Fe

RPM WinterSPM WinterRPM Summer

0

1

2

3

Z1 Z2 Z3 Z4 Z5

Con

cent

rati

on(m

g L

–1)

Zones

Pb


02468

10

Z1 Z2 Z3 Z4 Z5Con

cent

rati

on(m

g L

–1)

Zones

Zn

RPM WinterSPM WinterRPM SummerSPM Summer 0

0.6

1.2

1.8

Z1 Z2 Z3 Z4 Z5

Con

cent

rati

on(m

g L

–1)

Zones

Cu


00.020.040.060.080.1

Z1 Z2 Z3 Z4 Z5Con

cent

rati

on(m

g L

–1)

Zones

Cd



earth crust. These findings of our study are in accordance with the results reported in earlier studies (Yusuf and Rashid, 1995; Banerjee, 2008; Teixeira et al., 2008).

The influence of fly ash emission (from KSTPS) and Kota stone factories could be seen from the higher values of crustal elements in comparison to anthropogenic elements at all zones. Furthermore, they could be original components from earth and dust (particulate matter) resulting in their elevated levels in the ambient atmosphere.

On viewing the results of anthropogenic origin metals associated with both SPM and RPM, among all the studied zones, zone 1 was found to have highest average arithmetic mean concentrations of heavy metals i.e., Cu, Cd, Zn and Pb in both the seasons (winter and summer) due to its closer vicinity to coal based Thermal Power Plant while zone 5, which is a residential area mainly with lesser number of industrial sources, was found to have lowest concentrations of all the measured metal species in both the seasons. As evident from wind roses shown in Fig. 4, North-east direction of wind blow from KSTPS encourages their worrying level in other zones (after zone 1) of study region.

The relative abundance of these heavy metals in SPM and RPM samples followed the order Zn > Pb > Cu > Cd in all zones. As volatile metals with low melting point are emitted more from the Thermal Power Station (KSTPS in the present work), Zn and Pb were quite readily transported in air owing to their lower melting point (Krolak, 2000). Besides, particulate Zn may also get suspended in air due to vehicular activities, source of which may be tyre wear or lubricants and fuel additives. In our study, Zn was found in highest concentration followed by Pb, Cu and Cd respectively which is similar to the reports of earlier research work (Banerjee, 2003; Fang et al., 2005; Wang et al., 2005). Despite the use of lead free petrol, high concentration of Pb could be due to Pb particles in street dust accumulated from earlier vehicular exhaust for a long time due to their higher residence time in environment (Kulshrestha et al., 2009).

Seasonal variation of the average arithmetic mean concentrations of all the analysed metals were, generally, consistent from site to site but were different depending on the metal species and then meteorological conditions. In all the zones, concentrations of heavy metal species viz. Cu, Cd, Zn and Pb were higher in winter and lower in summer while a reverse trend was observed for crustal metal species viz. Ca, Mg and Fe. The difference of concentration levels between the two seasons i.e., winter and summer could be explained by difference in meteorological conditions. During the sampling period in winter, Kota city had witnessed low average temperature, higher relative humidity and low wind speed leading to higher levels of anthropogenic metal species in ambient air while summers had high average temperature, low relative humidity and high average wind speed causing their decreased concentrations (Table 2). On looking at the results of crustal metals, high wind strength during summer is responsible for their deflation or entrainment and transport resulting in their higher levels whereas wind strength available to transport these metals drops significantly in the winter causing their reduced levels.

In summer, the frequent precipitation processes are effective for the removal of particulate matter from ambient air. In addition, influenced by the high pressure system and strong solar radiation, the higher wind speeds and temperatures favour the diffusion of SPM and RPM in summer, thereby reducing anthropogenic metal concentration. In winter, the atmospheric conditions are stable and prone to thermal inversion, breezes and calm winds inhibit the diffusion and dilution, resulting in an exponential increase of pollutants near the ground (Yang et al., 2005).

Enrichment Factor

Calculation of enrichment factor (EF) helps to determine whether a certain element has an additional or anthropogenic source other than its major or natural source. Calcium (Ca) has been used as a reference element for an EF evaluation, assuming that the contribution from its anthropogenic

(a) (b)

Fig. 4. Wind roses of Kota city during (a) winter and (b) summer sampling periods.


Table 2. Meteorological conditions of Kota city during sampling periods.

Meteorological parameter Winter Summer Temperature (°C) 19.7 ± 3.7 30.7 ± 4.1

Humidity (RH) (%) 42.2 ± 5.4 20.0 ± 8.6 Wind speed (km h–1) 2.0 ± 0.8 5.5 ± 3.1

Rain fall (mm) 10.0 10.0

sourcesto the atmosphere is negligible (Yaroshevsky et al., 2006). This study used the EF calculation formula (1) as follows:

X/C precipitation

X/C reference meteEF

rial (1)

where x is the concentration of the metal of interest and c is the concentration of the reference metal. If the EF value approaches unity, then crustal sources are predominant while EF > 5 indicates that a large fraction of the element can be attributed to non- crustal or anthropogenic sources (Wu et al., 2007).

Figs. 5 and 6 showed the seasonal mean enrichment factors based on average seasonal metal concentration of heavy metals measured in SPM and RPM collected from the five zones in winter and summer seasons.

For both Fe and Mg, the mean EF value was approximate 1.0 which indicates its origin from soil dust. These metals were mainly introduced into the atmospheric aqueous phase by influence of particulate resuspension of soil particles besides being emitted from lime stone mining activities carried out at study area.

The higher EF values suggest a substantial point source input for Cu, Cd, Pb and Zn as all these metals were components of fly ash generated at KSTPS. Pb is still persistent in road dust from earlier vehicular emission before ban of leaded gasoline because of its long residence time in the environment besides emission from coal burning power plant.

Seasonal EF values of Cu, Cd, Zn and Pb metal species showed similar trends in both the seasons. The higher EF values of metals (Cu, Cd, Zn and Pb) during winter season than summer may be attributed to transport of fly ash from coal combustion activity from point source KSTPS under the influence of stable and calm meteorological conditions in winter.

On comparing the EF values of SPM and RPM, every metal shows different characteristics. The EF values of Cu, Cd, Zn and Pb, suggesting their origin from mainly anthropogenic source such as coal based Thermal Power Plant, were higher in RPM than in SPM. This indicates that Kota city is more exposed to these toxic metals associated with fine particles than those associated with coarse particles causing more adverse health effects. This finding is supported by earlier reports (Zhu et al., 2002a; Vogt et al., 2003; Maynard, 2004).

Correlation Analysis

The Pearson’s correlation coefficient (r) was calculated

from the elemental concentration in order to predict the possibility of a common source of SPM (Table 3) and RPM (Table 4).

In SPM, significant positive correlations were found between Mg and Ca (r = 0.846 and 0.887); Mg and Fe (r = 0.709 and 0.777); Ca and Fe (r = 0.812 and 0.819) in both winter and summer seasons, respectively. These significant positive correlations indicate that these metals have a common source, possibly natural soil. Similarly, significant positive correlation were found between Cu and Cd (r = 0.890 and 0.881); Cu and Zn (r = 0.837 and 0.825); Cu and Pb (r = 0.854 and 0.853); Cd and Zn (r = 0.743 and 0.838); Cd and Pb (r = 0.840 and 0.818); Zn and Pb (r = 0.826 and 0.845) in both winter and summer seasons, respectively.

In RPM, significant positive correlations were found between Mg and Ca (r = 0.855 and 0.828); Mg and Fe (r = 0.779 and 0.791); Ca and Fe (r = 0.802 and 0.813) in both winter and summer seasons respectively. These significant positive correlations indicate these metals have a common source, possibly earth crust. Similarly, significant positive correlation values were found between Cu and Cd (r = 0.799 and 0.771); Cu and Zn (r = 0.822 and 0.732); Cu and Pb (r = 0.754 and 0.767); Cd and Zn (r = 0.783 and 0.774); Cd and Pb (r = 0.820 and 0.798); Zn and Pb (r = 0.756 and 0.814) in both winter and summer seasons respectively.

These significant positive correlations indicate these metals have a common anthropogenic origin i.e., fly-ash emission from point source KSTPS along with earlier vehicular emission and other industrial activities.

Principal Component Analysis

Principal component analysis (PCA) is a numerical approach to account for statistical variance by deriving the least number of major factors. It is useful in reducing the dimensionality of the large data sets and in clarifying the relationship between the variables and thus can effectively be used in interpretation of SPM and RPM composition data (Zhang et al., 1992; Shukla and Sharma, 2010).

To further identify pollution sources of SPM and RPM in the present study, PCA was carried out with varimax rotation. The results of principal component analysis (PCA) showed that only two eigenvalues were >1 which explains over 66.49% and 68.03% of variance in SPM and 64.67% and 65.05% of variance in RPM in both winter and summer season respectively. The results in rotated component matrix (Table 5) showed that all the analyzed seven metal species are explained by two factors (varimax factors 1 and 2).

The first factor (VF 1), which explained over 37.12% and 36.89% in SPM and 35.90% and 33.43% in RPM in winter and summer seasons of variance, showed high loading of the heavy metals such as Pb, Zn, Cu and Cd


(a) (b)

Fig. 5. Enrichment factor of analyzed metals in SPM at five zones in Kota city in (a) winter and (b) summer seasons.

(a) (b)

Fig. 6. Enrichment factor of analyzed metals in RPM at five zones in Kota city in (a) winter and (b) summer seasons.

Table 3. Correlation coefficients between the concentration values of analyzed metals in SPM at Kota city during 2011–2012 (*significant at 5% level).

Metal Mg Ca Fe Cu Cd Zn Pb Mg 1.000 0.887* 0.777* –0.685 –0.663 –0.751 –0.562 Ca 0.846* 1.000 0.819* –0.630 –0.609 –0.699 –0.553 Fe 0.709* 0.812* 1.000 –0.659 –0.595 –0.624 –0.699 Cu –0.705 –0.801 –0.636 1.000 0.881* 0.825* 0.853*

Cd –0.672 –0.793 –0.679 0.890* 1.000 0.838* 0.818*

Zn –0.783 –0.790 –0.531 0.837* 0.743* 1.000 0.845*

Pb –0.768 –0.869 –0.737 0.854* 0.840* 0.826* 1.000 Winter, n = 157; Summer, n = 156.

Table 4. Correlation coefficients between the concentration values of analyzed metals in RPM at Kota city during 2011–2012 (*significant at 5% level).

Metal Mg Ca Fe Cu Cd Zn Pb Mg 1.000 0.828* 0.791* –0.614 –0.628 –0.656 –0.573 Ca 0.855* 1.000 0.813* –0.559 –0.616 –0.612 –0.656 Fe 0.779* 0.802* 1.000 –0.658 –0.532 –0.549 –0.545 Cu –0.699 –0.601 –0.636 1.000 0.771* 0.732* 0.767*

Cd –0.688 –0.593 –0.579 0.799* 1.000 0.774* 0.798*

Zn –0.731 –0.590 –0.531 0.822* 0.783* 1.000 0.814*

Pb –0.702 –0.669 –0.637 0.754* 0.820* 0.756* 1.000 Winter, n = 157; Summer, n = 156.

indicating the influence of anthropogenic activities mainly coal combustion at KSTPS. VF 2 that accounted for 29.37% and 31.14% in SPM and 28.77% and 31.62% in

RPM in winter and summer seasons of the layout variance showed high loading of Ca, Fe and Mg indicating the influence of crustal aerosols.

0

20

40

60

80

100

120

Mg Fe Cu Cd Zn Pb

Enr

ichm

ent

Fac

tor

Metal

Zone-1

Zone-2

Zone-3

Zone-4

Zone-5

0

20

40

60

80

100

Mg Fe Cu Cd Zn Pb

Enr

ichm

ent

Fac

tor

Metal

Zone-1

Zone-2

Zone-3

Zone-4

Zone-5

0

50

100

150

200

250

Mg Fe Cu Cd Zn Pb

Enr

ichm

ent

Fac

tor

Metal

Zone-1

Zone-2

Zone-3

Zone-4

Zone-50

50

100

150

200

Mg Fe Cu Cd Zn Pb

Enr

ichm

ent

Fac

tor

Metal

Zone-1

Zone-2

Zone-3

Zone-4

Zone-5


Table 5. Varimax rotation of PCA results showing loading of seven variables with 2 independents varimax factors (VF) in SPM and RPM in winter and summer seasons during 2011–2012 and 2012–2013.

Variables Component (SPM) Component of (RPM)

Winter season Summer season Winter season Summer season VF 1 VF 2 VF 1 VF 2 VF 1 VF 2 VF 1 VF 2

Ca –0.266 0.847 –0.214 0.912 –0.302 0.787 –0.271 0.831 Mg –0.118 0.851 –0.189 0.895 –0.441 0.864 –0.305 0.815 Fe –0.169 0.792 –0.178 0.819 –0.278 0.672 –0.214 0.738 Pb 0.855 –0.178 0.859 –0.168 0.819 –0.318 0.726 –0.232 Zn 0.770 –0.211 0.714 –0.249 0.876 –0.332 0.802 –0.244 Cu 0.921 –0.195 0.720 –0.218 0.721 –0.241 0.651 –0.261 Cd 0.758 –0.108 0.845 –0.139 0.707 –0.152 0.678 –0.176

% of variance 37.12 29.37 36.89 31.14 35.90 28.77 33.43 31.62 Cumulative (%) 37.12 66.49 36.89 68.03 35.90 64.67 33.43 65.05

CONCLUSION

The monitoring of particulate matter levels in atmosphere is important as finer particles are related to stronger health effects hence it is necessary to quantify the metal content adsorbed onto these particles and identify their main sources.

Based on the seasonal measurement of concentrations of seven metal species in SPM and RPM samples at various sampling sites situated in five different zones in and around Kota city during 2011–2012, it was concluded that in both the winter and summer seasons, the zone which is in close vicinity of point source KSTPS has highest concentrations of all the anthropogenic metal species (Cu, Cd, Zn and Pb). Less metal burden was found in distant zones lying in opposite direction of wind blow as well as having comparatively low traffic load. Thus, anthropogenic activities, mainly the coal combustion at KSTPS and prevailing winds during that time, are the major contributors for the metal pollutants in SPM and RPM in the entire study region.

The seasonal differences of particulate matter concentrations were significant for both metals originated from natural and anthropogenic sources. Controlled by meteorological factors, concentrations of anthropogenic elements in particulate matter (SPM and RPM) were higher in winter and lower in summer, while those of crustal elements were higher in summer and lower in winter.

Enrichment factor (EF), Pearson’s correlation and principal component analysis (PCA) showed that the dominant pollution source of heavy metal is mainly coal based thermal power plant along with other industrial activities. Pb has its origin from both fly ash and earlier vehicular emission. The predominant pollution sources for crustal metals are resuspended soil dust and mining activities.

Heavy metals in finer particles are more affected by anthropogenic sources, which is evident from their higher concentrations in RPM than those of coarse particles in SPM. This study indicates that particulate matter pollution may possess serious health risks to the residents in this rapidly developing city. ACKNOWLEDGEMENTS

The authors are thankful to A. Mukhopadhyay and DST,

New Delhi for instrumental support provided through DST – FIST project sanctioned to Govt. College, Kota and University Grants Commission, New Delhi for Minor Research Project sanctioned to Mrs. Manju Meena for this work. REFERENCES ASTM (1996a). Standard Guide for Choosing Locations

and Sampling Methods to Monitor Atmospheric Deposition at Non – Urban Locations: D 5111, West Conshohocken, PA.

Banerjee, A.D.K. (2003). Heavy Metal Levels and Solid Phase Speciation in Street Dusts of Delhi, India. Environ. Pollut. 123: 95–105.

Banerjee, D. (2008). Study of Precipitation Chemistry over an Industrial City. Int. J. Environ. Sci. Technol. 5: 331–338.

Begum, B.A., Biswas, S.K., Markwitz, A. and Hopke, P.K. (2010). Identification of Sources of Fine and Coarse Particulate Matter in Dhaka, Bangladesh. Aerosol Air Qual. Res. 10: 345–353.

Chen, Y., Zhao, D., Chai, F., Liang, G., Xue, Z., Wang, B., Liang, Y., Chen, Y. and Zhang, M. (2010). Correlation between the Atmospheric Visibility and Aerosol Fine Particle Concentrations in Guangzhou and Beijing. China Environ. Sci. 30: 967–971.

Colette, A., Menut, L., Haeffelin, M. and Morille, Y. (2008). Impact of the Transport of Aerosols from the Free Troposphere towards the Boundary layer on the Air Quality in the Paris Area. Atmos. Environ. 42: 390–402.

Fang, G.C., Wu, Y.S., Huang, S.H. and Rau, J.Y. (2005). Review of Atmospheric Metallic Elements in Asia during 2000-2004. Atmos. Environ. 39: 3003–3013.

Florence, G., Peter, S., Volke, D. and Reto, G. (2012). Chemical and Isotopic Properties and Origin of Coarse Airborne Particles Collected by Passive Samplers in Industrial, Urban, and Rural Environments. Atmos. Environ. 62: 631–645.

Gabrielli, P., Cozzi, G., Torcini, S., Cescon P. and Barbante, C. (2008). Trace Elements in Winter Snow of the Dolomites (Italy): A Statistical Study of Natural and Anthropogenic Contributions. Chemosphere 72: 1504–


1509. Garcia, R., Belmont, R., Padilla, H., Torres, M.C. and Baez,

A. (2009). Trace Metals and Inorganic Ion Measurements in Rain from Mexico City and a Nearby Rural Area. Chem. Ecol. 25: 71–86.

Gharaibeh, A.A., El-Rjoob, A.O. and Harb, M.K. (2010). Determination of Selected Heavy Metals in Air Samples from the Northern Part of Jordan. Environ. Monit. Assess. 160: 425–429.

Gilmour, P.S., Brown, D.M., Lindsay, T.G., Beswick, P.W., MacNee, W. and Donaldson, K. (1996). Adverse Health Effects of PM10 Particles: Involvement of Iron in Generation of Hydroxyl Radical. Occup. Environ. Med. 53: 817–823.

Halstead, M.J.R., Cunninghame, R.G. and Hunter, K.A. (2000). Wet Deposition of Trace Metals to a Remote Site in Fiordland, New Zealand. Atmos. Environ. 34: 665–676.

Hu, Z., Jun, W., Yuanyuan, C., Zhenlou, C. and Shiyuan, X. (2014). Concentration and Source Apportionment of Particulate Matter in Different Functional Areas of Shanghai, China. Atmos. Pollut. Res. 5: 138–144.

Kim, K.H., Kabir, E. and Kabir, S. (2015). A Review on the Human Health Impact of Airborne Particulate Matter. Environ. Int. 74: 136–143.

Krolak, E. (2000). Heavy Metals in Falling Dust in Eastern Mazowieckie Province. Polish J. Environ. Stud. 9: 517–522.

Kulshrestha, A., Satsangi, G., Masih J. and Taneja, A. (2009). Metal Concentration of PM2.5 and PM10 Particles and Seasonal Variations in Urban and Rural Environment of Agra, India. Sci. Total Environ. 407: 6196–6204.

Kyllonen, K., Karlsson, V. and Ruoho-airola, T. (2009). Trace Element Deposition and Trends during a Ten Year Period in Finland. Sci. Total Environ. 407: 2260–2269.

Lim, J.M., Lee, J.H., Moon, J.H., Chung, Y.S. and Kim, K.H. (2010). Source Apportionment of PM10 at a Small Industrial Area Using Positive Matrix Factorization. Atmos. Res. 95: 88–100.

Loyola, J., Arbilla, G., Quiterio, S.L., Escaleira, V. and Bellido, A.V. (2009). Concentration of Airborne Trace Metals in a Bus Station with a High Heavy-Duty Diesel Fraction. J. Braz. Chem. Soc. 20: 1343–1350.

Maynard, R. (2004). Key Airborne Pollutants – The Impact on Health. Sci. Total Environ. 334: 9–13.

Moja, S.J. and Mnisi, J.S. (2013). Seasonal Variations in Airborne Heavy Metals in Vanderbijlpark South Africa. J. Environ. Chem. Ecotoxicol. 5: 227–233.

Pérez, N., Pey, J., Querol, X., Alastuey, A., López, J.M. and Viana, M. (2008). Partitioning of Major and Trace Components in PM10–PM2.5–PM1 at an Urban Site in Southern Europe. Atmos. Environ. 42: 1677–1691.

Quiterio, S.L., Sousa da Silva, S.C.R., Arbilla, G. and Escaleira, V. (2004). Metals in Airborne Particulate Matter in the Industrial District of Santa Cruz, Rio de Janeiro, in an Annual Period. Atmos. Environ. 38: 321–331.

Rashed, M.N. (2008). Total and Extractable Heavy Metals

in Indoor, Outdoor and Street Dust from Aswan City, Egypt. Clean J. 36: 850–857.

Samara, C., Kouimtzis, T.H., Tsitouridou, R., Kanias, G. and Simeonov, V. (2003). Chemical Mass Balance Source Apportionment of PM10 in an Industrialized Urban Area of Northern Greece. Atmos. Environ. 37: 41–54.

Shah, M.H., Shaheen, N., Jaffar, M., Khalique, A., Tariq, S.R. and Manzoor, S. (2006b). Spatial Variations in Selected Metal Contents and Particle Size Distribution in an Urban and Rural Atmosphere of Islamabad, Pakistan. J. Environ. Manage. 78: 128–137.

Shukla, S.P. and Sharma, M. (2010). Neutralization of Rainwater Acidity at Kanpur, India. Tellus Ser. B 62: 172–180.

Teixeira, E.C., Migliavacca, D., Filho, S.P., Machado, A.C.M. and Dallarasa, J.B. (2008). Study of Wet Precipitation and its Chemical Composition in South of Brazil. An Acad. Bras. Cienc.80: 381–395.

Vogt, R., Scheer, V., Casati, R. and Benter, T., (2003). On-Road Measurement of Particle Emission in the Exhaust Plume of a Diesel Passenger Car. Environ. Sci. Technol. 37: 4070–4076.

Wang, X., Sato, T., Xing, B., Tamamura, S. and Tao, S. (2005). Source Identification, Size Distribution and Indicator Screening of Airborne Trace Metals in Kanazawa, Japan. J. Aerosol Sci. 36: 197–210.

Wong, C.S.C., Li, X.D., Zhang, Q.I.S.H. and Peng, X.Z. (2003). Atmospheric Deposition of Heavy Metals in the Pearl River Delta, China. Atmos. Environ. 37: 767–776.

Wu, Y.S., Fang, G.C., Lee, W.J., Lee, J.F., Chang C.C. and Lee, C.Z. (2007). A Review of Atmospheric Fine Particulate Matter and its Associated Trace Metal Pollutants in Asian Countries during the Period 1995-2005. J. Hazard. Mater. 143: 511–515.

Yang, S.S., Shao, L.Y., Xiao, Z.H., Li, J.J. and Li, W.J. (2005). The Analysis of Air Quality and the Relationship between Particulate Mass Concentrations and Meteorology Condition of the Typical Cities in China, 2004. J. Zhongyuan Inst. Technol. 5: 5–9.

Yaroshevsky, A. (2006). Abundances of Chemical Elements in the Earth’s Crust. Geochem. Int. 44: 48–55.

Yusuf, S.I. and Rashid, M. (1995). Analysis of Wet Acidic Deposition in Petaling Jaya, SOMCE 95 Conference, 18–19 June 1995, Kuala Terengganu, Malaysia.

Zhang, P., Dudley, N., Ure, A.M., and Littlejohn, D. (1992). Application of Principal Component Analysis to the Interpretation of Rainwater Compositional Data. Anal. Chim. Acta 258: 1–10.

Zhu, Y.F., Hinds, W.C., Kim, S., Shen, S. and Sioutas, C. (2002a). Study of Ultrafine Particles near a Major Highway with Heavy-Duty Diesel Traffic. Atmos. Environ. 36: 4323–4335.

Received for review, February 18, 2015 Revised, May 28, 2015

Accepted, August 27, 2015

seasonal variation of selected metals in particulate

Documents