Source Characterization of Metals in Rainwater: Case Study of Akure, Ondo State, Nigeria

Abstract

One source of water is rainwater. It is a pure solvent if not polluted. It has diverse functions in humans, animals and other materials. For rainwater not to be polluted, it means the values of cations, anions and particulate matter should be below water permissible limits. In this paper, we have characterized metals in rainwater harvested in Akure, Ondo State, Nigeria using standard methods of analyses. The physico-chemical parameters and metals were below WHO water guidelines. The variation of the metals was as follows: Ca>K>Na>Mg>Zn>Fe>Cu>Pb>Cr. Cd was absent and the Pb content was low. Principal Component Analysis showed that factors 1, 2 and 3 showed high loadings for Cr and Zn; Pb and Ca; and Cu, Mn and Mg respectively. Sources of these metals were due to anthropogenic activities.

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Copyright © 2016 by Modern Scientific Press Company, Florida, USA
International Journal of Environment and Bioenergy, 2016, 11(2): 65-77
International Journal of Environment and Bioenergy
Journal homepage:www.ModernScientificPress.com/Journals/IJEE.aspx
ISSN: 2165-8951
Florida, USA
Article
Source Characterization of Metals in Rainwater: Case Study of
Akure, Ondo State, Nigeria
Francis Olawale Abulude1 and Akinyinka Akinnusotu2
1Science and Education Development Institute, Akure, Ondo State
2Central Analytical Laboratory, Science Laboratory Technology Department, Rufus Giwa Polytechnic,
Owo, Ondo State, Nigeria
* Author to whom correspondence should be addressed; E-Mail:waleabul@yahoo.com
Article history: Received 6 June 2016, Received in revised form 20 July 2016, Accepted 25 July 2016,
Published 30 July 2016.
Abstract: One source of water is rainwater. It is a pure solvent if not polluted. It has diverse
functions in humans, animals and other materials. For rainwater not to be polluted, it means
the values of cations, anions and particulate matter should be below water permissible limits.
In this paper, we have characterized metals in rainwater harvested in Akure, Ondo State,
Nigeria using standard methods of analyses. The physico-chemical parameters and metals
were below WHO water guidelines. The variation of the metals was as follows:
Ca>K>Na>Mg>Zn>Fe>Cu>Pb>Cr. Cd was absent and the Pb content was low. Principal
Component Analysis showed that factors 1, 2 and 3 showed high loadings for Cr and Zn; Pb
and Ca; and Cu, Mn and Mg respectively. Sources of these metals were due to anthropogenic
activities.
Keywords: Rainwater, harvest, trace metals, permissible limits, PCA, anthropogenic sources.
1. Introduction
Water has diverse functions in humans, animals, plants and other substances. Without water it is
impossible for life to thrive. One of the sources of water is rainwater. It is highly pure if not contaminated
by pollutants (Mehta, 2011). According to Cerqueira et al., (2014) the chemical component of water is
depicted by the environment where it falls. This statement was confirmed by Akoto et al., (2011).

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66
Trace metals are abound in the environment so also rainwater, According to WHO report of 2002,
almost 1.1 billion consumers drink unsafe water and this has resulted into different ailments (WHO,
2002). When water (rainwater) has values below permissible limit of trace metals the water is considered
safe. However, it is always advisable to constantly monitor. Thus, it calls for appropriate interventions
by stakeholders to constantly put up awareness programmes and improve all existing infrastructures. If
all these are put in place, there is the possibility of reducing the potential health risk of the consumers
(Yasin et al., 2015).
Akure is the capital of Ondo State, Nigeria it is a fast growing city. The population, housing,
transportation and industries are on the increase. No doubt the possibility of environmental pollutants
would be on the increase too. Researches on water samples have been on going in Akure (Akinnusotu et
al., 2015) most of the results dealt with the physico-chemical parameters and trace metals, but none dealt
with finding the sources of the pollutants in the area (source apportionment).
In this present work, we studied the physico-chemical properties, metal concentrations, identified
and apportioned the emission sources.
2. Materials and Methods
2.1. The Study Area
2.1.1. Ondo State
Ondo State, the sunshine state is one of the states in Nigeria created in February 1976. According
to 2006 census a total of 1, 745, 057 and 1,715,820 were recorded for men and women respectively. The
state has a land size of 15,195.177 km2 and 18 Local Government Areas (NPC, 2010). The state is
Located in the South West Geo-Political Zone of the country. The mineral resources the state is endowed
with are large deposit of bitumen and other mineral resources such as marble gold, gemstone, clay, diorite
and lignite. Some of the tourist attractions in the state include the Idanre Hills, Owo Museum, Olumirin
Water Falls, Ebomi Lake and Oke Marie Hills. The people of Ondo State are lovers of traditional arts
and crafts especially ivory carvings and bronze works (NPC, 2010).
2.1.2. Akure
Akure is regarded as the largest city in Ondo State and it is the capital of the state. It is situated
in south-western part of Nigeria. The city has a population of 421,100. The people are of the Yoruba
ethnic group. The geographical coordinates of Akure, Ondo, Nigeria are 7° 15' 0" North, 5° 12' 0" East
at an elevation/altitude of meters. The average elevation of Akure, Nigeria is 353 meters. The time zone
for Akure is Africa/Lagos (GeoNames Geographical Database, 2012). Tradition has it that Akure was

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67
founded by Omoremi Omoluabi, a grandson of the Emperor Oduduwa. The title of Akure king is known
as the Deji of Akure and is supported by six (6) high chiefs (Iwarefa) in his or her domain. The city of
Akure is fast growing. According to the National population census, it has a total of 421,000 people
(NPC, 2010). This town is the trade center of cash crops, has radio and television stations, federal and
state primary, secondary and tertiary institutions, shopping activities, two stadia and other recreational
and tourist attractions. The Christianity, Islam and Traditional or Totemistic worshipers live in peace
with one accord.
2.2. Research Design
A number of different analytical approaches have been applied in air quality management in order
to establish the overall levels of pollution in the air. To achieve the research objectives, these
methodologies were used.
2.3. Sampling Area
The area is Akure, Ondo State, Nigeria (Fig 1). The sites were divided into eleven (11) locations
comprising of forty (40) sites (Table 1).These sites represented different industrial, urban and rural
settings. Samples were collected for a period of one month (August, 2015). At the end of the sampling
period 40 samples were collected. The location (Longitude and Latitude) of the sampling sites were
determined using GPS Map 76CSX (Garmin Ltd, Taiwan).
Fig. 1: Sampling locations

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68
Table 1: Sample locations
2.4. Sample Collection
The rain water samples were collected once a month, using appropriate sampler (Fig 2). A simple
system made with a high-density polyethylene (HDPE) bottle (5L) connected to a HDPE funnel. The
Sites Location No of Samples Description of Sites
No in each location
1 - 3 Oba Ile Estate 3 Residential
4 - 9 Expressway Area 7 Mountain Top, Residential, Traffic, Farm
Settlement, Mechanic
Workshop, Abattoir,
Industry, Quarry.
11 – 12 Owode Area 2 Sawmill, Traffic, Residential.
13 – 18, 40 Oba Ile Area 6 Residential, Market, Traffic, Welding,
Mechanic Workshop,
Construction of Road,
Petrol Station, Block
Industry.
19 Federal College of Agriculture 1 Residential, Traffic, Road Construction,
Farming Activities
20 – 23, 10 Federal University of
Technology Area 4 Residential, Industry, MTN
Mast, Traffic, Petrol
Station, School of Science
(Laboratories), School of
Environmental
Technology.
24 – 26 Idanre Road Area 3 Residential, Traffic
27 - 31 Ondo Road Area 5 Sawmill, Traffic, Incinerator,
Residential, College
Compound, Mechanic
Workshop
32 – 34 Igoba Road Area 3 Residential, Traffic
35 - 37 Igbatoro Road Area 3 Incinerator, Waste Dump, Traffic,
Residential
38 - 39 Oda Road Area 2 Residential, Traffic

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container was placed on sampling stand at a height above 1.5 m ground in order to prevent lichen forming
during the sampling period. After rainwater samples were collected, they were filtered using Whatman
ashless filter paper (11.0cm, Cat. No. 14442 110).
The prepared samples were subjected to appropriate determinations using standard methods of
analyses.
Fig. 2: Sampler for the rainwater samples
2.5. Analyses
2.5.1. Physico-chemical properties
Total Dissolved Solids (TDS), temperature and Electrical Conductivity (EC) were determined in
the samples using a 3 in 1 tester (EZ – 1 TDS & EC, China). pH was measured with a pen type pH meter
(pH – 009 (1) CE, ROHS, China). All these parameters were taken at the sampling sites using
manufacturers’ specifications and methods. The free CO2 was determined using the methods of Limgis
(2001). The determination was done immediately on arrival to the laboratory. All chemical evaluations
were performed within 12 hours after sampling.
2.5.2. Metals
The samples were subjected to wet ashing using concentrated acid (APHA, 1998). Standard
methods of analyses were employed. The instrumentation were done with AAS Buck Scientific 210 VGP
(Cd, Pb, Cr, Ni, Cu, Co, Fe, Mn, Zn, Mg) and Flame Photometer FP902 (Na, Ca, K).

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70
2.6. Statistical Analyses
Basic descriptive statistics (mean, std error, error of mean (SE), std deviation (SD), variance,
coefficient of variation, minimum, maximum and skewness), Factor Analysis (FA) and Principal
Component Analysis (PCA) were done with Minitab version 16 software.
3. Results and Discussion
3.1. TDS
The range in mg/L was between 2.0 and 24.0 with a mean of 7 and coefficient of variation in
percent 71.65(Table 2). This showed that the TDS in the samples were highly varied. The results obtained
in this report were in agreement with those reported for rainwater in Warri, Nigeria (19.37 – 33.38mg/L,
Olowoyo, 2011). Also these results followed the same trend with the results (6.8 – 24.1mg/L) recorded
for some rainwater harvested in Ghana (Akoto et al., 2011). According to Chughtai et al., (2014), the
higher the value of TDS in a water sample, the more the suspended and dust particles in it. The WHO
(2006) guideline for water standard is 500mg/L, when we compared our results with WHO standard it
showed that the rainwater obtained for this work were of high quality.
Table 2: Physico-chemical Properties of rainwater samples
TDS (mg/L) Temp (oC) pH EC (μS/cm) Free CO2 (mg/L)
Mean 7.00 27.67 6.26 13.79 35.46
SE Mean 0.80 0.10 0.12 1.57 7.77
Std Deviation 5.02 0.62 0.72 9.83 48.51
Variance 25.16 0.39 0.52 96.64 52.99
Coeff. Variation 71.65 2.25 11.46 71.26 136.79
Minimum 2.00 27.00 4.30 4.00 12.00
Maximum 24.00 29.00 7.10 48.00 56.00
3.2. Temperature
Low variability (0.3.386 variance; 2.25% coefficient of variation) were recorded. For the results.
The minimum value was 27 and maximum 29oC. High values were recorded in the dry periods. This was
expected because of the high relative humidity. The high temperature in this work was due to high solar
radiation. As usual, the temperature here was in consonant with values from India (27oC, Umerfaruq and
Solanki, 2015), Ethiopia (22.79 – 24.53oC, Yasin et al., 2015) and Nigeria (25.00 – 28.22oC, Waziri et
al., 2012). The values made available here were in conformity with WHO standard (55 – 50oC). The
temperature of water including rainwater depends on season, geographical location and sampling periods

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(Venkatesharaju et al., 2010). It affects rates of chemical reactions in the water body, increases taste and
colour and reduces solubility of gases in water.
3.3. pH
The pH of samples ranged between 4.3 and 7.1 with a variance of 0.515. This showed that the
variation is minimal. About 25% of the values were slightly acidic, while about 75% were acidic in
nature. The sites showed no significant variation in the pH values. Greater percent of the pH values fell
short of the WHO standards of 6.5 – 9.5. The reason might be due to the washing of atmospheric
pollutants into the containers for sampling.
3.4. Electrical Conductivity
Table 2 depicted the mean value of 13.79𝜇S/cm. The values were highly varied (96.64). The
values ranged between 4.0 and 48.0 𝜇S/cm. These results were far less than 1131 - 1278 𝜇S/cm recorded
for waste waters in Pakistan. The differences may have been caused by the use of pesticides, insecticides
and fertilizer in the agricultural purposes in the surrounding areas (Mastoi et al., 2014). Conductivity is
expressed as the ability of water to conduct an electric current. Electrolytes in a solution dissociate into
positive (cations) and negative (anions) and impact conductivity (Limgis, 2001).
3.5. Free Carbon-Dioxide (CO2)
The mean value for free CO2was highest at sample no 34 with 56mg/L while the lowest was
12mg/L. All these were residential areas. The free CO2 when dissolved in rainwater contributes to the
harness of water or rainwater. Free CO2reacts with water partly to form calcium bicarbonate and in the
absence of bicarbonate gets converted to carbonate releasing carbon-dioxide. There were not much
differences in the values obtained in all the sites.
3.6. Metals
Figs 2 and 3 depicted the pie and histogram charts of the metal variables. The charts showed the
variations in the following order: Ca>K>Mg>Zn>Mn>Fe>Cu>Pb>Cr. In all expect Mg there were high
variations in the results obtained for the metals. The values of Na, Ca, K were higher than those of the
trace metals. This is a normal phenomenon. All the macro metals in this work were within WHO
permissible limits for drinking water. It is gratifying to note the content of Pb was low. This is mainly
due to the removal of lead-gasoline vehicles from the roads due to improved technology in manufacturing
of engines and treatment of petroleum products. The overall result is evident that the rainwater and

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72
environment were not polluted. In general, our results were in good agreement with results of Akoto et
al., (2011) and Al-Momani (2003) in analyzed rainwater samples.
C d (ppm) Pb (ppm) C r (ppm) Ni (ppm)
C u (ppm) Co (ppm) N a (ppm) C a (ppm)
K (ppm) F e (ppm) Mn (ppm) Zn (ppm)
Mg (ppm)
0.07
0.11
9.8
10.0
10.5
10.6
10.9
11.2
11.4
11.5
1E-02
12.0
12.3
12.4
12.6
12.9
13.0
13.1
13.4
13.5
13.9
ND
14.5
15.0
15.3
15.4
16.7
16.8
17.0
17.2
18.1
18.2
0.01
18.7
18.9
20.5
21.4
23.0
33.1
18.4
19.5
0.02
0.03
0.04
0.05
0.06
*
Categ ory
Pie Chart of Cd (ppm), Pb (ppm), Cr (ppm), Ni (ppm), Cu (ppm), ...
Fig. 2: Pie Chart of the metal variables
644832160
40
30
20
10
0
Data
Frequency
Mg (pp m)
Pb (p pm)
Cr (ppm)
Cu (ppm)
Na (ppm)
Ca (pp m)
K (ppm)
Fe (pp m)
Mn (pp m)
Zn (pp m)
Variable
Histogram of Pb (ppm), Cr (ppm), Cu (ppm), Na (ppm), Ca (ppm), ...
Fig. 3: Histogram of the metal variables
According to Cerqueira et al., (2014), when metals are present in soluble form, trace metals are
made available. Rates of hydrolysis of trace metals in rainwater depend on the balance of anion and
cation, pH of water, size distribution, the redox potential and chemical nature of the depositing particles
(Morselli et al., 2004).

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The high toxicity of some trace heavy metals have been used as index of pollution (Omoigberale
and Ogbeibu, 2005). Table 3 depicted the correlation matrix of the metals. Although positive correlations
were recorded by all metals, but Ni and Co were not detectable (ND), 10% of the samples had Cd
(0.01mg/L) values. The results showed strong correlations between Cu:Pb, Cu:Cr, Ca:Cr, Zn:Cu, Zn:Mn,
Mg:Mn and Mg:Zn others showed low and weak correlations.
Table 3: Correlation matrix of the metals
Pb Cr Cu Na Ca K Fe MnZn
Cr 0.180
Cu 0.863 0.804
Na 0.239 0.631 0.310
Ca 0.793 0.845 0.7940.000
K 0.068 0.053 0.372 0.010 0.019
Fe 0.105 0.265 0.118 0.281 0.731 0.770
Mn 0.492 0.060 0.056 0.430 0.505 0.7900.111
Zn 0.386 0.500 0.8690.530 0.7690.635 0.084 0.817
Mg 0.620 0.672 0.574 0.005 0.0.009 0.060 0.417 0.965 0.953
3.7. Principal Component Analysis (PCA)
PCA with varimax rotation was utilized and presented in Table 4. The factor loading for PCA
analysis of the metals were shown in this table. Factor loading above 0.1 have been shown in the table,
while values above 0.5 were bold. Eigenvalues greater than 0.9 was employed to identify major metals
associated with the different sources.
Table 4: PCA Varimax Rotation
Variable Factor1 Factor2 Factor3
Pb 0.455 0.833 0.020
Cr 0.904 0.351 0.131
Cu 0.401 -0.011 0.838
Na -0.856 -0.473 -0.069
Ca -0.504 0.737 -0.417
K 0.464 0.010 0.370
Fe -0.219 -0.971 0.011
Mn 0.260 0.025 0.951
Zn 0.892 -0.087 0.345
Mg -0.311 -0.582 0.746
Eigenvalue 5.157 3.463 0.988
Proportion 0.516 0.346 0.099
Cumulative 0.516 0.862 0.961
Variance 5.1573 3.4636 0.9881
% Var 0.516 0.346 0.099

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Factor 1 component contained high loadings for Cr and Zn amounting to 5.2 of variance. These
metals were mostly provided by soil and road dust.
Factor 2 showed a strong loading for Pb and Ca, these are mainly provided by anthropogenic
sources (Table 5) like automobile exhaust, incinerators, waste burning and maybe industrial processes.
Factor 3 had a strong loading for Cu, Mn and Mg this could be attributed to emissions from
industry and vehicles. According to Moreno et al., (2006), industrial activities have been related to
pollution from chemicals.
Table 5: Anthropogenic sources of heavy metals in atmospheric particulate matter
Source: Daiet al., 2015
4. Conclusion
As part of environmental campaign in Nigeria, contamination assessment of rainwater samples
were performed in Akure, Ondo State. Physico-chemical properties of the samples were analysed and

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75
also the metals were determined. All the metals values were within permissible limits of WHO. It is
gratifying to note the low level of Pb, Cd was not detectable, but it is necessary to constantly monitor
these elements because of the effect on human and animal health. PCA was used to determine the sources
of the metals, from the results, three factors were highlighted namely anthropogenic, vehicular emission,
corrosion and wear of vehicle parts. Part of the anthropogenic source (industrial activities) confirmed the
increase in industrial development in Akure, the state capital of Ondo State, Nigeria.
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