Heavy metals pollution status of the Katima Mulilo Urban open land wastewater disposal centre and the immediate vicinity

Figures & data

Figure 1. Sketch map of Katima Mulilo urban

Source: Field GPS data of the present study

Figure 2. Mean concentration of the heavy metals in the surface soil (n = 5)

Table 1. Standard criteria used for the assessment of the heavy metals pollution

Heavy metal	Soil MPC (mg/kg)^a	TRF ^b	Average Shale values^C	Igeo criteria	Cf assessment criteria^b	Er assessment criteria^b	PEri assessment criteria^b
Pb	100	5	20	0< Igeo<1	Cf< 1, no contamination	Er< 40, low risk index	PEri< 150, low risk index
Cd	3	30	0.3	Uncontaminated to moderately contaminated
Cr	100	2	90	1< Igeo<2 Moderately contaminated	1 ≤ Cf ≤ 3, moderate contamination	40 ≤ Er< 80 moderate risk index	150 ≤ PEri< 300, moderate risk index
As	10	10	13	2< Igeo<3 Moderately to heavily contaminated
Ni	75	5	68	3< Igeo<4 Heavily contaminated	3 ≤ CF ≤ 6, considerable contamination	80 ≤ Er< 160 considerable risk index	300 ≤ PEri< 600 considerable risk index
Cu	100	5	45	4< Igeo<5 Heavily to extremely contaminated
Co	30	5	19	Igeo≥5 Extremely contaminated	CF > 6, high contamination	160 ≤ Er< 320, high risk index	PEri ≥ 600, high risk index
Mn	1500	1	850
V		2	13
Zn	200	1	95
Fe			46,000

^a= WHO.

^b= Hakanson (1980).

^c= Jonathan, Maina, and Maitera (2016).

MPC = Maximum permissible concentration, TRF = Toxic response factor, Igeo = index of geo-accumulation, Cf = Contamination factor, Er = Ecological risk index, PEri = Potential ecological risk index.

Table 2. ANOVA single factor between the mean concentration of the heavy metals in the surface soil at the different sampling sites

Source of Variation	SS	df	MS	F	P-value	F crit
Between Groups	15.47669	3	5.158897	3.243027	0.031866	2.838745
Within Groups	63.63063	40	1.590766
Total	79.10732	43

Statistically significant (p < 0.05)

Figure 3. Contamination factors of the heavy metals at the sampling sites

Figure 4. Degree of contamination and potential ecological risk indices of the heavy metals at the sampling sites

Figure 5. Ecological risks indices of the heavy metals at the sampling sites

Figure 6. Geo-accumulation indices of the heavy metals

Table 3. Inter-elemental correlation analysis between the heavy metals at the sampling sites

	Pb	Cd	Cr	As	Co	Ni	V	Cu	Zn	Fe	Mn
Pb	1.0000
Cd	0.9580	1.0000
Cr	0.6839	0.8264	1.0000
As	0.7731	0.8874	0.9914	1.0000
Co	0.8661	0.9650	0.9433	0.9729	1.0000
Ni	0.9515	0.9559	0.8545	0.9143	0.9409	1.0000
V	0.9521	0.9913	0.8711	0.9265	0.9766	0.9835	1.0000
Cu	0.7832	0.8597	0.9692	0.9846	0.9393	0.9348	0.9154	1.0000
Zn	0.9390	0.9982	0.8479	0.9023	0.9757	0.9468	0.9891	0.8670	1.0000
Fe	0.7781	0.9229	0.9463	0.9582	0.9836	0.8642	0.9257	0.8976	0.9436	1.0000
Mn	0.9953	0.9564	0.6463	0.7385	0.8508	0.9230	0.9378	0.7361	0.9379	0.7703	1.0000

Hakanson, L. (1980). An ecological risk index for aquatic pollution control: A sedimentological approach. Water Research, 14, 975–1001. doi:10.1016/0043-1354(80)90143-8

 Web of Science ®Google Scholar

Jonathan, B. Y., Maina, H. M., & Maitera, O. N. (2016). Heavy metal pollution assessment in the sediments of Lake Chad, Nigeria sector. Bayero Journal of Pure and Applied Science, 9(1), 213–216. doi:10.4314/bajopas.v9i1.33

 Google Scholar