Abstract

This paper presents the spatial variations in distribution of certain heavy metals in the Caroni River Basin, Republic of Trinidad and Tobago, which is the most industrialized nation of the Caribbean. Until now, no detailed assessment has been carried out in this area to measure the accumulation indices and associated risks. This study can illustrate the movement and transportation of analysed heavy metals, and can be used for baseline information. Results from the study revealed that the concentration in the river water samples (in μg/L) varies: Cr (5.07 to 6.85), Co (3.47 to 6.07), Ni (5.23 to 9.38), Cu (4.56 to 10.11), Zn (2.13 to 60.91), As (3.97 to 5.7) and Pb (4.04 to 9.92). This study also revealed that these higher concentrations can be attributed to effluents from small-scale industries, unnoticed irrigation processes, and domestic wastes. The San Juan, St Joseph and Arouca rivers were found to be the most polluted, and Cu, Pb, Zn and As were the most abundant metals in the study area. Heavy metals analysed from most of the river-bed and river-bank positions showed very good correlation with respective river water samples (0.98 for river bed and 0.83 for river bank).

INTRODUCTION

River water quality plays an important role in the survival of aquatic life as well as of land organisms. Therefore, anomalous concentrations of heavy metals in rivers (both in the sediment and water), which may have the potential to affect the river water quality, should be controlled and regularly monitored (Navarro et al. 2010; Duncan et al. 2018; Gabrielyan et al. 2018). Sediments influence river water quality and can be used to determine the history of river pollution. Heavy metals are introduced into rivers naturally by rock weathering, soil erosion and dissolution of water-soluble salts or can be introduced by human activities such as mining, industrialization and urbanization. Numerous studies on heavy metal water pollution have been carried out in different parts of the world (such as Duncan et al. 2018; Gabrielyan et al. 2018; Lu & Yu 2018), and can be extended to analyse storm effects in the urban sewage system (Rathnayake & Azamathulla 2017).

Some studies were also carried out in Trinidad and Tobago (such as, Norville 2005; Surujdeo-Maharaj et al. 2007; Kanhai et al. 2014). However, these studies were not focused on the distribution pattern or the enrichment factor or the source characterization of the metal pollution in this major river system in particular.

The purpose of this study was to: (a) investigate heavy metal distribution (Cr, Co, Ni, Cu, Zn, As and Pb) in the river water of the Caroni River Basin; (b) correlate these distributions with river bed and river bank to identify the possible sources of heavy metals.

STUDY AREA

The Caroni River is the largest river in Trinidad and Tobago and it provides potable water for over 40 percent of the country's population (EMA 2008). It flows through the northern and the western part of the island. It originates in the Northern Range and runs through the Caroni Plain and drains into the Gulf of Paria (Suter 1960; Figure 1). The basin drains both the ranges: Northern and Central, and is estimated to be 600 km2 in catchment area (Juman & Ramsewak 2013). The Caroni River is fetched by 18 rivers, of which 12 rivers flow in from the Northern Range and six rivers flow into the basin from the Caroni Plain and Central Range. Nathai-Gyan & Juman (2005) proposed that the major contribution comes from the 12 northern rivers whilst the lesser contribution comes from the southern rivers.

Figure 1

Generalized map of the study area showing the sampling locations.

Figure 1

Generalized map of the study area showing the sampling locations.

The soil type in the study area varies from fine sandy clay and clay in the eastern part to sandy loam in the west (Suter 1960; Table 1). A similar sequence is also found in the underlying bed-rock with shale-siltstone and sandstone to calcareous phyllite to calcareous sandstone (Suter 1960; Table 1).

Table 1

Province, geographic coordinates, soil classes, parent material, and textural class of the collected samples (after Trinidad Soils Map, Soil & Land Capability Unit, Ministry of Agriculture, Land and Fisheries, Government of Trinidad and Tobago)

ProfileRiverCoordinatesSoil classParent materialTextural class
L1 Aripo River 10°36′07.93″
61°12′43.25″ 
Valencia Shale/siltstone Fine sandy clay 
L2 Cumuto River 10°35′15.09″
61°13′03.06″ 
Ecclesville and Brasso Fine sandy clay to clay 
L3 Tumpuna River 10°34′30.97″
61°16′26.98″ 
Calcareous siltstone/calcareous shale 
L4 Caroni River 10°34′56.46″
61°16′15.01″ 
L5 Arima River 10°36′46.71″
61°15′49.02″ 
Piarco Clay rich sandstone Fine sandy loam 
L6 Guanapo River 10°37′12.19″
61°15′03.97″ 
L7 Caroni River 10°37′03.56″
61°24′15.25″ 
Ecclesville and Brasso Calcareous siltstone/calcareous shale Fine sandy clay to clay 
L8  10°35′05.24″
61°20′18.17″ 
L9 Mausica River 10°37′50.98″
61°19′22.00″ 
Diego Martin and La Pastor Mica rich sandstone to sandstone and limestone Fine sandy to sandy loam 
L10 Arouca River 10°38′54.60″
61°21′00.20″ 
Fine sandy loam to sandy clay 
L11 Tacarigua River 10°38′44.84″
61°22′07.14″ 
Maraval Fine sandy to sandy loam 
L12 St Joseph River 10°40′56.22″
61°24′35.96″ 
Maracas and Matelot Calcareous phyllite, limestone and micaceous phyllite Sandy and clay loam 
L13 San Juan River 10°40′13.83″
61°26′59.07″ 
ProfileRiverCoordinatesSoil classParent materialTextural class
L1 Aripo River 10°36′07.93″
61°12′43.25″ 
Valencia Shale/siltstone Fine sandy clay 
L2 Cumuto River 10°35′15.09″
61°13′03.06″ 
Ecclesville and Brasso Fine sandy clay to clay 
L3 Tumpuna River 10°34′30.97″
61°16′26.98″ 
Calcareous siltstone/calcareous shale 
L4 Caroni River 10°34′56.46″
61°16′15.01″ 
L5 Arima River 10°36′46.71″
61°15′49.02″ 
Piarco Clay rich sandstone Fine sandy loam 
L6 Guanapo River 10°37′12.19″
61°15′03.97″ 
L7 Caroni River 10°37′03.56″
61°24′15.25″ 
Ecclesville and Brasso Calcareous siltstone/calcareous shale Fine sandy clay to clay 
L8  10°35′05.24″
61°20′18.17″ 
L9 Mausica River 10°37′50.98″
61°19′22.00″ 
Diego Martin and La Pastor Mica rich sandstone to sandstone and limestone Fine sandy to sandy loam 
L10 Arouca River 10°38′54.60″
61°21′00.20″ 
Fine sandy loam to sandy clay 
L11 Tacarigua River 10°38′44.84″
61°22′07.14″ 
Maraval Fine sandy to sandy loam 
L12 St Joseph River 10°40′56.22″
61°24′35.96″ 
Maracas and Matelot Calcareous phyllite, limestone and micaceous phyllite Sandy and clay loam 
L13 San Juan River 10°40′13.83″
61°26′59.07″ 

MATERIALS AND METHODS

Sample collection

Depending on the topography, type of vegetation, soil type, industrial establishment, population density and accessibility, 13 locations were selected along the Caroni River and its seven important tributaries (Figure 1; Table 1). Sediment and water samples were collected from each location along the following rivers: Aripo River (L1), Cumuto River (L2), Tumpuna River (L3), Arima River (L5), Guanapo River (L6), Mausica River (L9), Arouca River (L10), Tacarigua River (L11), St Joseph River (L12), San Juan River (L13) and three locations along the Caroni River (L4, L7, and L8).

Laboratory analysis

Determination of physicochemical parameters

The standard pH test was carried out using an electronic pH meter (Model 51910, Platinum Series pH Electrode, HACH, Loveland, CO, USA). All pH measurements were performed at room temperature after purifying the pH probe using distillation before every measurement and calibrating the pH meter against standard solutions. The turbidity of the water samples was determined using a 2100N Laboratory Turbidimeter, EPA, 115 Vac (HACH, Loveland, CO, USA). All turbidity tests were performed in accordance with EPA Method 180.1 (USEPA 1983). For all these measurements, duplicate samples were tested and a mean value was obtained for accuracy (BSI 1990).

Heavy metal analysis

Sediment and water samples were analysed according to USEPA Method 200.8 using inductively coupled plasma mass spectrometry (ICP-MS) by the Department of Chemistry, University of West Indies, Trinidad and Tobago. ICP-MS is an analytical technique used to determine total recoverable element concentrations in soil and liquid matrices. This analytical method is appropriate for environmental samples as it is a powerful tool for rapid determination of elements and quantification of metals present in natural waters at trace levels with excellent determination limits (Al-Rimawi et al. 2013).

Statistical analysis

Basic statistical analysis, principal component analysis (PCA) and correlation analysis were carried out for all observed data using the XLSTAT program. Correlation analysis was used as a sorting mechanism of the information of a correlation matrix (Symader & Thomas 1978), while PCA was used to analyse the correlation in heavy metal concentrations at 13 selected locations. Pearson's correlation analysis was applied to quantitatively analyse and determine the relationship between the heavy metals in the water and sediment samples (after Qishlaqi & Moore 2007).

RESULTS AND DISCUSSION

Measured heavy metal concentrations and physicochemical parameters from river water are presented in Table 2, while heavy metal concentrations from river-bed and river-bank locations are presented in Table 3. Table 4 shows the pairwise correlation coefficients between the variations found in the water samples. Figure 2 shows the Pearson correlation coefficient values (R) associated with the heavy metal concentrations in the water, bed and bank samples. Figure 3 shows the loadings for the two principal components calculated from the heavy metal concentrations in the water samples. PCA of heavy metals in river water samples at the site locations is illustrated in Figure 4.

Table 2

Analysed variable concentrations in river water sample

LocationHeavy metal concentration (μg/L)
pHTurbidity (NTU)
CrCoNiCuZnAsPb
L1 5.07 ± 1.01 3.78 ± 0.76 5.94 ± 1.19 5.88 ± 1.18 32.87 ± 6.57 5.23 ± 1.05 5.15 ± 1.03 6.8 ± 0.06 23.4 ± 4.1 
L2 6.31 ± 1.26 3.83 ± 0.77 5.23 ± 1.05 6.37 ± 1.27 60.91 ± 12.18 5.39 ± 1.08 6.11 ± 1.22 6.9 ± 0.24 33.2 ± 8.2 
L3 5.27 ± 1.05 3.47 ± 0.69 5.82 ± 1.16 4.56 ± 0.91 18.07 ± 3.61 5.53 ± 1.11 4.54 ± 0.91 6.9 ± 0.21 15.2 ± 2.9 
L4 6.17 ± 1.23 3.56 ± 0.71 5.83 ± 1.17 5.32 ± 1.06 21.88 ± 4.38 5.04 ± 1.01 8.74 ± 1.75 7.2 ± 0.09 6.0 ± 1.3 
L5 5.89 ± 1.18 3.50 ± 0.70 5.97 ± 1.19 6.11 ± 1.22 34.21 ± 6.84 5.01 ± 1.00 7.14 ± 1.43 8.2 ± 0.15 5.2 ± 1.2 
L6 6.39 ± 1.28 3.89 ± 0.78 6.21 ± 1.24 8.56 ± 1.71 75.15 ± 15.03 4.84 ± 0.97 8.65 ± 1.73 7.7 ± 0.28 5.9 ± 1.8 
L7 5.89 ± 1.18 4.90 ± 0.98 7.01 ± 1.40 6.45 ± 1.29 41.13 ± 8.23 5.70 ± 1.14 5.29 ± 1.06 7.0 ± 0.19 15.6 ± 2.0 
L8 5.54 ± 1.11 5.59 ± 1.12 8.17 ± 1.63 8.70 ± 1.74 60.75 ± 12.15 5.36 ± 1.07 5.88 ± 1.18 6.9 ± 0.06 16.6 ± 2.8 
L9 5.80 ± 1.16 5.35 ± 1.07 8.25 ± 1.65 5.85 ± 1.17 4.03 ± 0.81 4.45 ± 0.89 4.70 ± 0.94 7.2 ± 0.20 6.9 ± 1.7 
L10 5.86 ± 1.17 5.10 ± 1.02 7.86 ± 1.57 5.33 ± 1.07 2.13 ± 0.43 3.97 ± 0.79 4.12 ± 0.82 7.6 ± 0.07 15.5 ± 2.2 
L11 6.47 ± 1.29 5.12 ± 1.02 7.69 ± 1.54 5.86 ± 1.17 7.93 ± 1.59 4.19 ± 0.84 4.04 ± 0.81 7.5 ± 0.22 1.3 ± 0.2 
L12 6.50 ± 1.30 5.45 ± 1.09 9.07 ± 1.81 7.43 ± 1.49 38.35 ± 7.67 4.53 ± 0.91 7.51 ± 1.50 7.4 ± 0.14 34.7 ± 5.1 
L13 6.85 ± 1.37 6.07 ± 1.21 9.38 ± 1.88 10.11 ± 2.02 35.36 ± 7.07 4.78 ± 0.96 9.92 ± 1.98 7.5 ± 0.16 42.0 ± 11.5 
USEPA (2002)  570  470  120 340 65 6.5–8.5a >50b 
CWQG (2001)  10  C C 30 100 C   
WRA (2001)  500  500 500 200  100   
Other international quality guidelines 50a 1–10c 50b 100b 100b 50b 50b   
LocationHeavy metal concentration (μg/L)
pHTurbidity (NTU)
CrCoNiCuZnAsPb
L1 5.07 ± 1.01 3.78 ± 0.76 5.94 ± 1.19 5.88 ± 1.18 32.87 ± 6.57 5.23 ± 1.05 5.15 ± 1.03 6.8 ± 0.06 23.4 ± 4.1 
L2 6.31 ± 1.26 3.83 ± 0.77 5.23 ± 1.05 6.37 ± 1.27 60.91 ± 12.18 5.39 ± 1.08 6.11 ± 1.22 6.9 ± 0.24 33.2 ± 8.2 
L3 5.27 ± 1.05 3.47 ± 0.69 5.82 ± 1.16 4.56 ± 0.91 18.07 ± 3.61 5.53 ± 1.11 4.54 ± 0.91 6.9 ± 0.21 15.2 ± 2.9 
L4 6.17 ± 1.23 3.56 ± 0.71 5.83 ± 1.17 5.32 ± 1.06 21.88 ± 4.38 5.04 ± 1.01 8.74 ± 1.75 7.2 ± 0.09 6.0 ± 1.3 
L5 5.89 ± 1.18 3.50 ± 0.70 5.97 ± 1.19 6.11 ± 1.22 34.21 ± 6.84 5.01 ± 1.00 7.14 ± 1.43 8.2 ± 0.15 5.2 ± 1.2 
L6 6.39 ± 1.28 3.89 ± 0.78 6.21 ± 1.24 8.56 ± 1.71 75.15 ± 15.03 4.84 ± 0.97 8.65 ± 1.73 7.7 ± 0.28 5.9 ± 1.8 
L7 5.89 ± 1.18 4.90 ± 0.98 7.01 ± 1.40 6.45 ± 1.29 41.13 ± 8.23 5.70 ± 1.14 5.29 ± 1.06 7.0 ± 0.19 15.6 ± 2.0 
L8 5.54 ± 1.11 5.59 ± 1.12 8.17 ± 1.63 8.70 ± 1.74 60.75 ± 12.15 5.36 ± 1.07 5.88 ± 1.18 6.9 ± 0.06 16.6 ± 2.8 
L9 5.80 ± 1.16 5.35 ± 1.07 8.25 ± 1.65 5.85 ± 1.17 4.03 ± 0.81 4.45 ± 0.89 4.70 ± 0.94 7.2 ± 0.20 6.9 ± 1.7 
L10 5.86 ± 1.17 5.10 ± 1.02 7.86 ± 1.57 5.33 ± 1.07 2.13 ± 0.43 3.97 ± 0.79 4.12 ± 0.82 7.6 ± 0.07 15.5 ± 2.2 
L11 6.47 ± 1.29 5.12 ± 1.02 7.69 ± 1.54 5.86 ± 1.17 7.93 ± 1.59 4.19 ± 0.84 4.04 ± 0.81 7.5 ± 0.22 1.3 ± 0.2 
L12 6.50 ± 1.30 5.45 ± 1.09 9.07 ± 1.81 7.43 ± 1.49 38.35 ± 7.67 4.53 ± 0.91 7.51 ± 1.50 7.4 ± 0.14 34.7 ± 5.1 
L13 6.85 ± 1.37 6.07 ± 1.21 9.38 ± 1.88 10.11 ± 2.02 35.36 ± 7.07 4.78 ± 0.96 9.92 ± 1.98 7.5 ± 0.16 42.0 ± 11.5 
USEPA (2002)  570  470  120 340 65 6.5–8.5a >50b 
CWQG (2001)  10  C C 30 100 C   
WRA (2001)  500  500 500 200  100   
Other international quality guidelines 50a 1–10c 50b 100b 100b 50b 50b   

C, calculated by water hardness.

Table 3

Analysed heavy metal concentrations (μg/g) in river-bed and river-bank sediment samples

LocationCrCoNiCuZnAsPb
L1 River bed 4.17 ± 1.04 0.56 ± 0.19 5.00 ± 1.25 4.28 ± 1.07 58.17 ± 14.54 5.24 ± 1.31 3.55 ± 0.89 
River bank 13.27 ± 1.73 0.82 ± 0.12 1.95 ± 0.23 3.72 ± 0.52 18.45 ± 2.56 4.12 ± 0.59 10.16 ± 1.32 
L2 River bed 18.72 ± 4.68 5.36 ± 1.69 11.80 ± 2.95 9.40 ± 2.35 72.29 ± 18.07 10.30 ± 2.57 14.69 ± 3.67 
River bank 35.34 ± 4.36 0.15 ± 0.02 0.47 ± 0.06 0.82 ± 0.12 13.00 ± 1.68 5.70 ± 0.59 7.12 ± 0.95 
L3 River bed 10.54 ± 2.63 5.90 ± 1.03 12.99 ± 3.25 10.00 ± 2.50 76.94 ± 19.24 6.80 ± 1.70 8.81 ± 2.20 
River bank 13.92 ± 1.82 7.62 ± 1.03 15.01 ± 2.12 11.12 ± 1.54 78.74 ± 12.05 5.90 ± 0.85 12.78 ± 1.53 
L4 River bed 6.54 ± 1.64 5.24 ± 1.26 13.19 ± 3.30 14.15 ± 3.54 51.69 ± 12.92 7.55 ± 1.89 10.81 ± 2.70 
River bank 7.87 ± 1.32 7.87 ± 1.02 10.26 ± 1.56 12.39 ± 1.02 80.37 ± 15.56 4.60 ± 1.54 38.62 ± 2.96 
L5 River bed 8.70 ± 2.18 8.70 ± 3.01 21.04 ± 5.26 22.81 ± 5.70 87.58 ± 21.89 10.33 ± 2.58 17.49 ± 4.37 
River bank 4.54 ± 0.62 0.49 ± 0.06 1.29 ± 0.29 3.48 ± 0.58 25.37 ± 3.02 2.26 ± 0.39 7.80 ± 1.06 
L6 River bed 7.23 ± 1.81 7.79 ± 2.56 17.39 ± 4.35 16.30 ± 4.08 51.80 ± 12.95 10.42 ± 2.61 15.41 ± 3.85 
River bank 11.43 ± 1.52 3.54 ± 0.52 6.85 ± 1.02 7.63 ± 1.36 33.01 ± 4.36 5.38 ± 0.75 11.12 ± 1.45 
L7 River bed 9.83 ± 2.46 5.52 ± 1.01 12.14 ± 3.03 17.31 ± 4.33 70.80 ± 17.70 8.21 ± 2.05 15.14 ± 3.79 
River bank 13.28 ± 1.76 9.67 ± 1.29 15.11 ± 1.86 15.81 ± 2.36 69.36 ± 9.23 5.94 ± 0.86 17.01 ± 2.34 
L8 River bed 6.99 ± 1.75 3.01 ± 0.84 8.66 ± 2.17 8.19 ± 2.05 49.22 ± 12.31 7.51 ± 1.88 11.67 ± 2.92 
River bank 11.60 ± 1.51 6.12 ± 0.85 9.53 ± 1.38 12.75 ± 1.94 54.56 ± 7.85 5.79 ± 0.75 15.13 ± 2.03 
L9 River bed 9.78 ± 2.45 9.60 ± 1.28 18.20 ± 4.55 19.01 ± 4.75 64.63 ± 16.16 9.34 ± 2.33 11.96 ± 2.99 
River bank 9.30 ± 1.20 10.38 ± 1.53 13.03 ± 1.70 20.60 ± 2.69 48.89 ± 6.14 5.21 ± 0.68 14.19 ± 1.83 
L10 River bed 12.69 ± 3.17 8.24 ± 1.86 15.98 ± 4.00 46.94 ± 11.74 161.40 ± 40.35 9.24 ± 2.31 42.43 ± 10.61 
River bank 12.95 ± 1.69 9.98 ± 1.30 17.84 ± 2.36 28.40 ± 3.54 269.36 ± 35.64 10.06 ± 1.32 64.39 ± 8.96 
L11 River bed 7.17 ± 1.79 8.41 ± 1.56 18.76 ± 4.69 22.30 ± 5.58 89.02 ± 22.26 8.97 ± 2.24 16.67 ± 4.17 
River bank 5.73 ± 0.85 10.45 ± 1.66 16.54 ± 2.36 19.87 ± 2.63 61.07 ± 7.68 4.88 ± 0.63 17.78 ± 2.37 
L12 River bed 5.09 ± 1.27 15.68 ± 2.58 23.82 ± 5.95 31.38 ± 7.85 92.00 ± 23.00 12.08 ± 3.02 11.58 ± 2.89 
River bank 7.34 ± 0.95 8.17 ± 1.08 14.95 ± 1.95 22.36 ± 2.95 95.23 ± 12.65 7.78 ± 1.28 77.41 ± 10.06 
L13 River bed 11.62 ± 2.90 10.45 ± 3.01 26.86 ± 6.72 27.61 ± 6.90 124.63 ± 31.16 12.70 ± 3.18 26.29 ± 6.57 
River bank 6.30 ± 0.94 11.38 ± 1.56 18.31 ± 2.65 17.84 ± 2.31 56.68 ± 7.09 8.05 ± 1.05 20.79 ± 2.58 
LocationCrCoNiCuZnAsPb
L1 River bed 4.17 ± 1.04 0.56 ± 0.19 5.00 ± 1.25 4.28 ± 1.07 58.17 ± 14.54 5.24 ± 1.31 3.55 ± 0.89 
River bank 13.27 ± 1.73 0.82 ± 0.12 1.95 ± 0.23 3.72 ± 0.52 18.45 ± 2.56 4.12 ± 0.59 10.16 ± 1.32 
L2 River bed 18.72 ± 4.68 5.36 ± 1.69 11.80 ± 2.95 9.40 ± 2.35 72.29 ± 18.07 10.30 ± 2.57 14.69 ± 3.67 
River bank 35.34 ± 4.36 0.15 ± 0.02 0.47 ± 0.06 0.82 ± 0.12 13.00 ± 1.68 5.70 ± 0.59 7.12 ± 0.95 
L3 River bed 10.54 ± 2.63 5.90 ± 1.03 12.99 ± 3.25 10.00 ± 2.50 76.94 ± 19.24 6.80 ± 1.70 8.81 ± 2.20 
River bank 13.92 ± 1.82 7.62 ± 1.03 15.01 ± 2.12 11.12 ± 1.54 78.74 ± 12.05 5.90 ± 0.85 12.78 ± 1.53 
L4 River bed 6.54 ± 1.64 5.24 ± 1.26 13.19 ± 3.30 14.15 ± 3.54 51.69 ± 12.92 7.55 ± 1.89 10.81 ± 2.70 
River bank 7.87 ± 1.32 7.87 ± 1.02 10.26 ± 1.56 12.39 ± 1.02 80.37 ± 15.56 4.60 ± 1.54 38.62 ± 2.96 
L5 River bed 8.70 ± 2.18 8.70 ± 3.01 21.04 ± 5.26 22.81 ± 5.70 87.58 ± 21.89 10.33 ± 2.58 17.49 ± 4.37 
River bank 4.54 ± 0.62 0.49 ± 0.06 1.29 ± 0.29 3.48 ± 0.58 25.37 ± 3.02 2.26 ± 0.39 7.80 ± 1.06 
L6 River bed 7.23 ± 1.81 7.79 ± 2.56 17.39 ± 4.35 16.30 ± 4.08 51.80 ± 12.95 10.42 ± 2.61 15.41 ± 3.85 
River bank 11.43 ± 1.52 3.54 ± 0.52 6.85 ± 1.02 7.63 ± 1.36 33.01 ± 4.36 5.38 ± 0.75 11.12 ± 1.45 
L7 River bed 9.83 ± 2.46 5.52 ± 1.01 12.14 ± 3.03 17.31 ± 4.33 70.80 ± 17.70 8.21 ± 2.05 15.14 ± 3.79 
River bank 13.28 ± 1.76 9.67 ± 1.29 15.11 ± 1.86 15.81 ± 2.36 69.36 ± 9.23 5.94 ± 0.86 17.01 ± 2.34 
L8 River bed 6.99 ± 1.75 3.01 ± 0.84 8.66 ± 2.17 8.19 ± 2.05 49.22 ± 12.31 7.51 ± 1.88 11.67 ± 2.92 
River bank 11.60 ± 1.51 6.12 ± 0.85 9.53 ± 1.38 12.75 ± 1.94 54.56 ± 7.85 5.79 ± 0.75 15.13 ± 2.03 
L9 River bed 9.78 ± 2.45 9.60 ± 1.28 18.20 ± 4.55 19.01 ± 4.75 64.63 ± 16.16 9.34 ± 2.33 11.96 ± 2.99 
River bank 9.30 ± 1.20 10.38 ± 1.53 13.03 ± 1.70 20.60 ± 2.69 48.89 ± 6.14 5.21 ± 0.68 14.19 ± 1.83 
L10 River bed 12.69 ± 3.17 8.24 ± 1.86 15.98 ± 4.00 46.94 ± 11.74 161.40 ± 40.35 9.24 ± 2.31 42.43 ± 10.61 
River bank 12.95 ± 1.69 9.98 ± 1.30 17.84 ± 2.36 28.40 ± 3.54 269.36 ± 35.64 10.06 ± 1.32 64.39 ± 8.96 
L11 River bed 7.17 ± 1.79 8.41 ± 1.56 18.76 ± 4.69 22.30 ± 5.58 89.02 ± 22.26 8.97 ± 2.24 16.67 ± 4.17 
River bank 5.73 ± 0.85 10.45 ± 1.66 16.54 ± 2.36 19.87 ± 2.63 61.07 ± 7.68 4.88 ± 0.63 17.78 ± 2.37 
L12 River bed 5.09 ± 1.27 15.68 ± 2.58 23.82 ± 5.95 31.38 ± 7.85 92.00 ± 23.00 12.08 ± 3.02 11.58 ± 2.89 
River bank 7.34 ± 0.95 8.17 ± 1.08 14.95 ± 1.95 22.36 ± 2.95 95.23 ± 12.65 7.78 ± 1.28 77.41 ± 10.06 
L13 River bed 11.62 ± 2.90 10.45 ± 3.01 26.86 ± 6.72 27.61 ± 6.90 124.63 ± 31.16 12.70 ± 3.18 26.29 ± 6.57 
River bank 6.30 ± 0.94 11.38 ± 1.56 18.31 ± 2.65 17.84 ± 2.31 56.68 ± 7.09 8.05 ± 1.05 20.79 ± 2.58 
Table 4

Pairwise correlation coefficients between the variables

CrCoNiCuZnAsPbpHTurbidity
Cr 1.00         
Co 0.39 1.00        
Ni 0.40 0.96 1.00       
Cu 0.52 0.55 0.53 1.00      
Zn 0.17 −0.14 −0.23 0.62 1.00     
As −0.40 −0.43 −0.52 0.02 0.53 1.00    
Pb 0.59 0.00 0.10 0.65 0.49 0.10 1.00   
pH 0.47 0.02 0.16 0.16 −0.09 −0.55 0.34 1.00  
Turbidity 0.26 0.36 0.34 0.47 0.28 0.16 0.33 −0.29 1.00 
CrCoNiCuZnAsPbpHTurbidity
Cr 1.00         
Co 0.39 1.00        
Ni 0.40 0.96 1.00       
Cu 0.52 0.55 0.53 1.00      
Zn 0.17 −0.14 −0.23 0.62 1.00     
As −0.40 −0.43 −0.52 0.02 0.53 1.00    
Pb 0.59 0.00 0.10 0.65 0.49 0.10 1.00   
pH 0.47 0.02 0.16 0.16 −0.09 −0.55 0.34 1.00  
Turbidity 0.26 0.36 0.34 0.47 0.28 0.16 0.33 −0.29 1.00 
Figure 2

Pearson correlation coefficient values (R) associated with the heavy metal concentrations in the water, bed and bank samples.

Figure 2

Pearson correlation coefficient values (R) associated with the heavy metal concentrations in the water, bed and bank samples.

Figure 3

Loadings for the two principal components against heavy metal concentrations in the river water samples.

Figure 3

Loadings for the two principal components against heavy metal concentrations in the river water samples.

Figure 4

PCA of heavy metals in the river water.

Figure 4

PCA of heavy metals in the river water.

The results of this study indicate that the waters in nearly all northern tributaries of the Caroni River are slightly alkaline (pH more than 7.5), while its southern tributaries and the Caroni River itself have neutral pH. The level of pH in aqueous solution affects the leaching power of water and indicates its chemical reaction on sediments. The Northern Range of Trinidad, which is the source of these rivers and which engulfs the majority of the catchment areas of the northern tributaries, consists of many limestone bodies (Suter 1960). The alkalinity in these northern tributaries may be due to the presence of these limestone bodies. The measured pH level in water samples from the present study falls within the normal range (6.5–8.4) for irrigation water (Ayers & Westcot 1994). Water with pH values outside the normal range of 6.5–8.4 may contain excess toxic elements posing a serious threat to aquatic life (APHA 1989).

The trend of the turbidity distribution in the studied river water samples was similar to the trend of pH level in the water samples. This is due to the fact that the northern tributaries of the Caroni River have higher chances of water replenishment (by the water supply from the Northern Range), while the southern tributaries flowing in the plains have less likelihood of getting water. Turbidity indicates the presence of suspended materials in the water and a high level of turbidity can reduce the aesthetic quality of lakes and streams in a significant manner. The turbidity values from all the areas studied were below the acceptable limit (Vardaki & Kelepertsis 1999).

No significant statistical difference was observed in Cr- and As-concentration (p > 0.5) while significant variation was observed in the distribution of the remaining heavy metals (p ≤ 0.5). The concentrations of heavy metals in river water were below the upper permissible values determined by some important international recognized authorities (Hamilton 1994; Vardaki & Kelepertsis 1999; CWQG 2001; WRA 2001; USEPA 2002; Nagpal 2004). Water samples from nearly all Northern Range tributaries showed enriched Cr-, Ni- and Cu-values, especially in the San Juan, St Joseph and Tacarigua rivers, with the highest values observed in the San Juan River. Although the watershed areas which feed these rivers do not have heavy industries, there are a number of light industries there which could be contributing to these metal enrichments. These small-scale activities include chrome-plating outlets, garment industries, metalworks factories, electroplating and electrical parts factories, and food–beverage manufacturing units. Significantly, different distribution patterns were observed in Zn-, As- and Pb-concentrations. Water samples from all the locations showed the maximum values of these metals except those from the Mausica, Arouca and Tacarigua rivers. These values were also comparatively higher in the San Juan and St Joseph rivers, while maximum Pb-concentration was observed in the San Juan River. High concentrations of these metals may be the result of waste from the small-scale paint, battery recycling, electroplating, and chemical cleaning industries in the catchment of these rivers. Unplanned use of agricultural fertilizers and pesticides, and unorganized dumping of domestic waste could also be contributing to the heavy metals in the river catchment areas.

The PCA was used with the two factors (F1 and F2) for all sample frames and the score plot was used for interpreting relations among the observations. In water samples, the factor loadings F1 and F2 (eigenvalues 5.70 and 1.51, respectively) accounted for 69.96% of the initial variability. In the loading plots for the first principal components, only chromium (Cr) was negatively correlated, which identifies that all elements except chromium (Cr) control the variability, whereas PCA analysis suggests that the metal enrichments were mainly by zinc (Zn), copper (Cu), lead (Pb) and arsenic (As). The distribution patterns from the PCA plot show that heavy metal concentrations were considerably higher in the San Juan (L13), St Joseph (L12) and Arouca (L10) rivers. A previous study has already indicated the St Joseph as the most grossly polluted river in this area (Lucas & Alkins-Koo 2004) and present observations have added San Juan and Arouca as possible concerns.

From pairwise correlations between all studied variables in the water samples, no significant correlation was observed between the physicochemical parameters and the metals analysed. The studied metals also represented poor to moderate correlation between themselves. It was observed that most of the metals responsible for enrichment of contamination in the river water (Zn, Cu, Pb and As) illustrated poor pairwise correlation, while moderate correlations were found between other analysed metals.

Inter-element relationships between sediments from river bank and river bed with river water provide information on metals sources and pathways in the environment (Dragović et al. 2008). Heavy metals analysed from most of the river bed and river bank positions showed very good correlation with respective river water samples (with average correlation values of 0.98 and 0.83 for river bed and river bank, respectively), except from the Auroca and Mausica rivers (negative correlations were observed here). It is important to note that this study was carried out during summer, therefore these correlations were expected. However, negative correlations might indicate a source of contamination, which is not related to the river bed or river bank.

CONCLUSION

The studied heavy metals in the river water and adjacent sediment samples from different catchment areas of the Caroni River and its major tributaries varied widely in concentration. New challenges in environmental protection and conservation, which have resulted from global changes, make urgent the need for baseline data to evaluate the potential impact of pollutants to ecosystems, especially in these small island developing states. The present study, therefore, is very important in the context of the Caribbean region, which has very little such information.

Although the heavy metal concentration in the river water was below the maximum allowable international standards, the present observations indicate that San Juan River was the most polluted river followed by the St Joseph and Arouca rivers. It is important to note here that these rivers flow through industrial estates and urban areas. However, more detailed characterization of the catchment areas is required before reaching further conclusions.

Pairwise correlations obtained between physicochemical parameters and the compounds analysed suggest that these parameters might not control the appearance of contamination in the water samples. The correlations between the analysed metals suggest that those metals, which are responsible for the enrichment of contaminations, might come from different sources.

Very strong correlations are in the distribution of heavy metal content between the river water and the river-bank sediments, and between the river water and the river-bed sediments.

It is recommended that appropriate measures are taken by the relevant authorities to mitigate the problems at this early stage.

ACKNOWLEDGEMENTS

The financial assistance from the Campus Research and Publication Fund, University of the West Indies, St Augustine (Ref. No. CRP.3.NOV13.10) is thankfully acknowledged. The author would also like to thank Mr David Cudjoe for assistance with the sampling process and laboratory analysis and Dr Leonette Cox, Department of Chemistry, University of West Indies, Trinidad and Tobago, for assistance with the heavy metal analysis.

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