Health risk indices and zooplankton-based assessment of a tropical rainforest river contaminated with iron, lead, cadmium, and chromium

The study area

The study was carried out on Egbokodo River (longitude 5° 38′ and 5° 41′ and latitude 5° 36′ and 5° 33′) in Warri South Local Government Area of Delta State, Southern Nigeria (Fig. 1), between the periods of September 2008–May 2009. The river is a brackish and tidal River that serves as a source of water for drinking, washing, and fishing to the communities in the catchment area. Three (3) Stations (tagged Stations A, B, and C) were selected about 150 m apart, based on distinct anthropogenic activities. Station A was located at a vandalized oil pipeline, while Stations B and C were located downstream at points of dredging and municipal waste disposal respectively. Station A was 6.3–9.3 m in depth, Station B was 11.4–16.1, and Station C was 7.5–19.5 m during the study duration.

The study area comprises of coarse and interspersed soil with lignite and patches of laterite and sandy clay soil. The climate of the study area is typically tropical. It is characterized by the humid tropical wet and dry climate which is primarily regulated by rainfall. The wet season lasts a period of 7 months (April to October). Rainfall ranged from 15 to 91 mm during this period. The driest months are December to January; with a mean monthly rainfall of 15 mm. The bank of the river was densely shaded by a thick canopy of vegetation, dominated by mangrove plants, Nypa palm, and Rhizophora sp.

Collection of samples (water and zooplankton)

Water samples were collected from the 3 stations using a 1 L sampling bottle which was pre-cleaned with the deionized water at each station. This sampling procedure was repeated monthly from September 2008 to May 2009. The samples were preserved in a cooler and transported to the laboratory where they were refrigerated at − 10 °C before the physiochemical analysis. Preservation and analysis of water samples were according to standard methods of the American Public Health Association (APHA).

Samples of zooplankton were collected at the 3 stations between 0800 and 1100 h by towing a hydrobios plankton net (mesh size 25 µm) with a speed boat at 2 knots, just below the water surface for 5 min at every station. At each station, the filtered zooplankton samples were condensed in a 25 mL plankton bottle and preserved using buffered 4% formalin. Each plankton bottle was properly labeled indicating the stations and dates of collection. This procedure was repeated for 9 months (September 2008–May 2009).

Analysis of water

Determination of pH

The pH was estimated using a _PH meter—Orion Model 290A (ASTM D 1293B) and recorded accordingly every month.

Measurement of temperature (°C)

A mercury-in-glass thermometer was used to measure surface water temperature. A stable initial reading was ensured by shaking it the thermometer carefully. Afterward, the thermometer was left inside the water for about 3 min till a stable reading was observed and recorded.

Determination of phosphate

Five (5) mL antimony molybdate was added to 40 mL of water sample was in a 50 mL measuring cylinder. Afterward, 2 mL of Ascorbic acid was added to the mixture. It was left to stand for 30 min for full colour formation². The absorbance was measured with a UV–visible spectrophotometer at 680 nm.

Phosphate was then calculated thus;

In Eq. (1) above, Y = absorbance of the sample.

C = absorbance of blank

B = absorbance of standard (Eq. 2)

A = absorbance of blank

X = concentration of the standard.

Determination of nitrate

Nitrate was tested using the diazotization method—Alpha 419 C/ASTM D3867. 0.5 mL of (0.1% W/V) NaN₃ was added to the water sample to remove any NO₂ present. 3.0 mL of (2.6% W/V) NH₄Cl solution was added. One (1) mL of (2.1% W/V) Borax solution was added. 0.5–0.6 g of spongy cadmium was added. It was then covered and shaken for some 15 to 20 min. Afterward, 7 mL of the solution was transferred to a 25 mL measuring cylinder. 1 mL of (1.0% W/V in 10% HCl) sulphanilamide reagent and was mixed by swirling. After about 3 min, 1.0 mL N-1—naphthalene diamine dihydrochloride (0.1% W/V) was added and mixed thoroughly². The mark was made-up with distilled water. The blank solution was also subjected to the same treatment as the sample. After about 10–20 min, the absorbance of both the water sample and the blank solutions were measured with a UV–visible spectrophotometer at a wavelength of 543 nm.

Analysis of total petroleum hydrocarbons (TPH)

HP-5 capillary column coated with 5% phenyl methyl siloxane (30 m length × 0.32 mm diameter × 0.25 µm film thickness) (Agilent Technologies) was used as a stationary phase of separation of hydrocarbons from water samples. 1µL of the samples was injected in splitless mode at an injection temperature of 300 °C, and pressure of 13.74psi and a total flow of 21.364 mL/min. Purge flow to split vent was set at 15 mL/min at 0.75 min. The oven was initially programmed at 40 °C (1 min) then ramped at 12 °C/min to 300 °C for 10 min. The temperature of the flame ionization detector was regulated to 300 °C using hydrogen gas. Airflow was at 30 mL/min while nitrogen was used as makeup gas at a flow of 22 mL/min. Agilent 7890B gas chromatography coupled to flame ionization detector (GC-FID) was used for the determination of TPH at 254 nm. After calibration, water samples were analyzed and corresponding TPH concentrations were obtained^3,10.

Analysis of oil and grease (OG)

One (1) L separating funnels with retort stand, 100 mL volumetric flask, glass jar, xylene, and anhydrous sodium sulfate were used in determining the concentrations of oil and grease (OG) in the water.

Extraction

Twenty (20) mL xylene was put in a glass jar containing a water sample. The content of the jar was shaken, poured into the separating funnel and shaken again. It was allowed for phase separation and the bottom layer xylene was drained into a 100 mL volumetric flask through a funnel with a plug of glass wool and about 2/3 full with anhydrous Na₂SO₄.

Another 20 mL xylene was added to the content in the separating funnel, agitated thoroughly and xylene layer was again drained into the same flask. Water was drained into a measuring cylinder and the volume was noted. Separating funnel was rinsed with 20 mL xylene into the same flask as done earlier. It was made up to mark of the extract in the 100 mL volumetric flask with pure xylene.

The oil and grease (OG) was calculated thus:

The concentration of oil reported as OG (mg/L)

In Eq. (3), DF = Dilution factor

CF = Conversion factor from absorbance to mg/L extract

EV = Extraction volume of solvent in (mL).

Analysis of trace metals

Ten (10) mL of water sample was put in a beaker and 2 mL concentrated nitric acid was added to the sample. The mixture was then heated to evaporation and allowed to cool afterward and then transferred into a volumetric flask. It was then allowed to stand for 24 h, after when it was centrifuged at 3000 rpm until clear. The sample was screened for suspended solids which were filtered off before further analysis. The trace metals in the mixture were then read using an atomic absorption spectrophotometer (AAS, Philips model PU 9100) at a wavelength range of 250–350 V using the ABS knob¹⁰.

The experimental procedures were conducted as described by Estefan et al.³⁰ and modified by Jones Jr.³¹.

Quality control and quality assurance

Validation of trace metals

The precision of the AAS was validated by repeating every experimental procedure 3 times. Certified reference materials (CRM) and standard reference materials (SRM) published by the Federal Environmental Protection Agency³² were employed as a guide. The recovery rates ranged from 87 to 95%. The calculated relative standard deviation (SD) was < 6% (determined by Microsoft Excel, 2010), indicating high data reliability. The reference solutions used to obtain the calibration curves were prepared from analyte grade stock solutions containing 1000 mg/L of lead, iron, chromium, and cadmium¹⁵. The blanks and reference solutions were also analyzed using the same method that was applied to the samples. The concentrations were expressed in mg/L.

The limits of detection (LOD) and the limits of quantification (LOQ) were calculated based on the standard deviation of 20 readings obtained for the analytical blanks and the slopes of the analytical curves (LOD = 3σ/slope and LOQ = 10σ/slope). The values (mg/kg) were 0.05–0.07 µg/L for Fe, 0.07–0.123 µg/L for Pb, 0.06–0.121 µg/L for Cd, and 0.043–0.127 µg/L for Cr.

Validation of TPH

Total petroleum hydrocarbon readings of the GC-FID were validated by the certificate (No. TPH-R3-SET, by AccuStandard). The linearity of the calibration range was estimated to ascertain the accuracy of the equipment. The coefficient of variation of the results was validated using LODs and LOQs. The calculation of the percentage recovery for testing accuracy was also conducted. The linearity was tested between 0 and 5.6 μg/L. The LODs and LOQs were calculated from the blank and analyzed by the GC-FID. The limit of detection was calculated using triplicate readings.

Analysis of zooplankton

Analysis of zooplankton was in the order of sorting, counting, and identification. General sorting of zooplankton samples from the 25 mL concentrate was conducted. A sub-sample of 1 mL from the collected sample was put into a hydrobios counting chamber where numbers per mL of sample were computed. Representative specimens were mounted on a glass slide in 100% glycerin pretreated with lignin pink. Relevant parts of the specimens were dissected under a binocular American Optical Corporation microscope (Model 570), using micro dissecting blades. Identification was done under an Olympus Vanox Research microscope (Model 230485) using works of literature such as Boxshall and Braide³³, Crane³⁴, Jeje and Fenando³⁵, Newell, and Newell³⁶, Smirnov³⁷, Wickstead³⁸.

Zooplankton diversity

The density of zooplankton was expressed as the number of organism per mL of was sample using the formula:

N = number of zooplankton individuals per sample³ (Eq. 4).

The number of taxa and relative abundance was documented in detail. The zooplankton diversity was determined using indices of species diversity methods.

The indices employed include species richness, general diversity, and evenness, which were used to express the descriptive properties of the zooplankton samples at each station.

Margalef’s index (d)

In Eq. (5) S = total number of species, N = total number of individuals and ln is the natural logarithm (log_e).

Shannon–Wienner index (H)

This index was used in calculating the general diversity of the zooplankton samples. The index was expressed as:

In Eq. (6) above, N = total number of individual zooplankton, nⁱ = number of individuals in the ith species, the general diversity value (H) was converted to Hⁱ using the formula stated by Ogbeibu³⁹ (Eq. 7):

Evenness index

The Evenness index was used to calculate the degree of evenness in the distribution of the individual zooplankton species recorded according to Ogbeibu⁴⁰

In Eq. 8, H = observed diversity, H_max = the maximum diversity.

Dominance index

Simpson’s index (C) was employed to estimate the dominant species among the sampled zooplankton taxa. It was calculated thus:

nⁱ = number of individuals in the ith species, while N = total number of individuals (Eq. 9).

Using the Hutcheson t-test to calculate the significant differences according to Ogbeibu⁴⁰, the comparison was made between two stations at a time and all were compared in pairs i.e. Station A and B, Station B and C, and Station A and C.

Hutcheson’s formula is given thus:

In Eq. (10) above, 1 and 2 represent the two stations in comparison; H₁ and H₂ represent the Shannon–Weiner indices of the two stations, and S²H₁ and S²H₂ represent variances of Shannon–Weiner indices of the two stations.

Health risk assessment of trace metals in water

Estimation of health risks was computed for adults (males and females separately) and children using adopted indices for referenced literature (Table 1). Data were processed for male and female adults within the age range of 40–50 years old⁴⁰, while the data for children was a combination of male and female children within the range of 11–16 years old⁴¹. The adopted age brackets were representations of age frequency among the community dwellers that were observed to constantly use the river for the stated purposes.

Carcinogenic risk

Considering the constant contact of the community dwellers with the river through drinking, washing, and bathing, there is a likelihood of the inhabitants having health complications at some point in their life time². Health risks caused by different contaminants that enter the body through various exposure routes are generally categorized into carcinogenic and non-carcinogenic risks. Carcinogenic risks are the incremental probability of an inhabitant developing cancer in a lifetime as a result of exposure to carcinogens such as metals.

Carcinogenic risk of the river was therefore calculated according to USEPA⁴³ thus:

The slope factor (SF) values for Fe, Cr, Pb, and Cd were adopted from Isibor et al.¹⁵, while the standard limits were adopted from USEPA⁴² for computations in Eq. (11). The modified total cancer risk was estimated according to the guidelines of USEPA⁴⁴.

The chronic daily intake CDI for dermal (Huang et al.⁴⁷) and ingestion (USEPA⁴³) routes were calculated as stated in Eqs. 12 and 13 respectively

CDI: chronic daily intake dose; CW: concentration of trace metal content in water (mg/L); IR: water ingestion rate (ml/kg/day); CF: conversion factor (kg/mg); EF: Exposure frequency (day/year); ED: exposure duration (years); BW: body weight (kg); AT: average time (day); AF: Skin adherence factor (mg/cm²); EA: exposed surface area of skin (cm²); DAF: dermal absorption factor (Eqs. 12, 13).

The estimated daily intake averaged in a lifetime was converted by the SF directly to the incremental risk of cancer occurrence in a lifetime²³.

The synergistic cancer risk caused by a variety of carcinogens, which is the sum of carcinogenic risk of individual carcinogens in a common exposure route, was taken as the total CR. Usually, the value of total CR ranges from 10⁻⁶ to 10⁻⁴ (U.S. EPA⁴²). Below this range was considered safe and above was declared unaccepted.

Non-carcinogenic risk

Trace metals are also liable to elicit non-carcinogenic health complications in the community dwellers that directly or indirectly use the river. The reference doses for the expected routes of exposure are as presented in Table 2.

Health risk indices were calculated for the individual trace metals thus:

The hazard quotient (HQ) was calculated according to Huang et al.⁴⁷ thus:

In Eq. (14), the adopted reference doses (RfDs) for the oral (ingestion) were700, 0.001, and 3.5 × 10⁻³ mg/kg/d for Fe, Cd, and Pb respectively^48,49, while dermal (absorption) reference doses were 40, 0.075, and 0.00001 5.25 × 10⁻⁴ mg/kg/d for Fe, Pb, and Cd^50,51,52.

Estimation of the total risk posed each toxicant through a combination of the exposure routes was calculated using the total hazard quotient (∑HQ) for the male, female, and children in the population thus:

Due to possible synergistic/ antagonistic interactions among the metals analyzed¹⁵, the cumulative hazard quotient (HI) was estimated as the sum of the overall non-carcinogenic risk posed by individual metal (IARC⁵³, NRC⁵⁴).

It was calculated thus:

HQ represents hazard quotients of the individual metal analyzed (Eqs. 15, 16).

HQ or HI < 1 = unlikely to cause adverse health effects for the exposed populace, while ≥ 1 = unacceptable. The greater the values the greater the probability of the occurrence of adverse health effects in exposed individuals.

Statistical analysis

Descriptive statistics (mean ± standard deviation) of the physicochemical properties and trace metals in water were subjected to analysis of variance (ANOVA) to test for the significant difference. Post hoc Tukey’s HSD test was used to ascertain the actual location of the significant difference. All statistical analyses were conducted at a probability level of 0.05 using SPSS 2010 version. Before ANOVA, the assumption of normality was verified using the Shapiro–Wilk test.

Source: Ecology - nature.com