A Novel Approach for Indexing Heavy Metals Pollution to Assess Groundwater Quality for Drinking Purposes
Abstract
:1. Introduction
2. The Motivation for the New Approach
2.1. Heavy Metal Pollution Index (HPI)
2.2. Mean Metal Index (MI)
2.3. PoS Method
- The numerator term in Equation (3) can lead to the wrong classification. Consider the measured concentration values of zinc of two samples A and B to be 55 and 45 μg/L, respectively, and the highest desirable limit value of zinc is 50 μg/L; the effect of both concentrations will be the same, while in reality, sample A should fail, and sample B should pass the quality test.
- As already known, a higher value of HPI indicates poor water quality and vice versa. Thus, when calculating the individual quality rating using Equation (3), the value adds to the overall index even when is less than .
- The estimation of MI as in Eqnuation (5) considered the concentration value of elements without regarding the toxicity to the overall water quality.
- There are many rating ranges for HPIs as excellent, perfect, good, poor, and very poor regarding the water quality. However, the classifications of water quality by the aforementioned approaches are neither clear nor sufficient to determine the water quality. In theory and practice, the rating should be flexible depending on the level of influence of the individual concentration of elements as per water quality standard. This issue has been handled in developing the proposed MHEI method.
3. Materials and Methods
3.1. Sampling Site, Collection, and Analysis of Data
3.2. Modified Heavy Metal Evaluation Index (MHEI)
3.3. Spatial Interpolation Methods
Inverse Distance Weighted
4. Results and Discussion
4.1. The Behavior of Heavy Metals in the Study Area
4.1.1. Fe, Mn, Zn
4.1.2. Pb, Cd, Cr
4.2. Calculation of HPI, MI, PoS, and MHEI Indices
4.3. Comparison of Indices Results
5. Conclusions
- The spatial distribution of NEI and PEI are in complete agreement with the metals spatial distribution.
- The MI and HPI indexing failed to account for the toxicity of elements in the evaluation of groundwater quality. This may explain why some samples were erroneously indexed. The proposed MHEI considered the element concentration as well as the toxicity in the groundwater quality evaluation dprocess to index the metals thoroughly, thus producing relatively better results.
- The traditional heavy metals indexing techniques, namely MI, HPI, and PoS always take the metal concentration in water sample as a positive pollutant, even when the measured concentration is below the highest desirable limit. However, according to MHEI, heavy metal effect may be measured by a pair of indices, NEI and PEI. Additionally, some major shortcomings in the formulations of conventional indexing methods.
- This study also proposed a more flexible water quality rating system that is more in sync with the standard guidelines documents.
- The performance of the MHEI model proposed was strong, promising, and proved useful for evaluating heavy metals pollution levels in groundwater. It also takes care of many deficiencies of the existing approaches.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Toxic Class | Parameters | Points | P-Class | w | W | Quality Degradation |
---|---|---|---|---|---|---|
5 | Pb | 10 | V | 8 | 0.301887 | High |
5 | Cd | 10 | V | 8 | 0.301887 | |
4 | Cr | 100 | IV | 5 | 0.188679 | Moderate |
3 | Zn | 1000 | III | 3 | 0.113208 | Non-low |
2 | Mn | 5000 | II | 1.5 | 0.056604 | |
1 | Fe | 50,000 | I | 1 | 0.037736 |
MHEI Value Range | Measured Concentration Range | Type of Water |
---|---|---|
−100 ≤ NEI ≤ 0 and PEI = 0 | DL ≥ ≤ | Excellent water |
−100 < NEI ≤ 0 and 0 < PEI ≤ 50 | < ≤ | Good water |
−100 < NEI ≤ 0 and 50 < PEI ≤ 100 | < ≤ | Moderate water |
−100 < NEI ≤ 0 and PEI = 50 | < ≤ | Poor water |
NEI = 0 and PEI > 100 | > | Water unsuitable for drinking purposes |
Parameters | Min. | Max. | Mean | Median | Std. Dev | SSMO (2002) | WHO (2011) | % Exceeding Guideline Value |
---|---|---|---|---|---|---|---|---|
Fe | 36.8 | 5661.4 | 956.99 | 220.3 | 1435.37 | 300 | 300 | 38.89 |
Mn | 19.9 | 304.9 | 75.37 | 43.85 | 74.07 | 500 | 400 | 0.00 |
Zn | 5.4 | 395.0 | 53.49 | 21.3 | 88.2 | 3000 | 3000 | 0.00 |
Pb | ND | 31.0 | 25.09 | 26.95 | 4.22 | 100 | 100 | 0.00 |
Cd | ND | 3.0 | 1.93 | 1.95 | 0.76 | 3.0 | 3.0 | 0.00 |
Cr | ND | 16.0 | 7.06 | 5.0 | 4.58 | 40 | 50 | 0.00 |
Parameters | M | S | I | w | e W | Q | W × Q |
---|---|---|---|---|---|---|---|
Fe | 288.5 | 300 | 100 | 0.0033 | 0.009 | 94.25 | 0.840 |
Mn | 26.0 | 500 | 50 | 0.0020 | 0.005 | 5.333 | 0.029 |
Zn | 21.3 | 3000 | 50 | 0.0003 | 0.001 | 0.973 | 0.001 |
Pb | ND | 3100 | 5.0 | 0.0100 | 0.027 | 0.00 | 0.00 |
Cd | ND | 3.0 | 0.1 | 0.3333 | 0.891 | 0.00 | 0.00 |
Cr | ND | 40 | 5.0 | 0.0250 | 0.067 | 0.00 | 0.00 |
HPI = | 0.87 |
Parameters | M | MAC | M/MAC |
---|---|---|---|
Fe | 288.5 | 200 | 1.443 |
Mn | 26.0 | 50 | 0.520 |
Zn | 21.3 | 500 | 0.043 |
Pb | ND | 10 | 0.00 |
Cd | ND | 1.0 | 0.00 |
Cr | ND | 10 | 0.00 |
MI = Mean value | 0.334 |
Parameters | M | S | w | W | Q |
---|---|---|---|---|---|
Fe | 288.5 | 300 | 1 | 0.037736 | 36.29 |
Mn | 26.0 | 500 | 1.5 | 0.056604 | 2.94 |
Zn | 21.3 | 3000 | 3 | 0.113208 | 0.80 |
Pb | ND | 3100 | 8 | 0.301887 | 0.00 |
Cd | ND | 3.0 | 8 | 0.301887 | 0.00 |
Cr | ND | 40 | 5 | 0.188679 | 0.00 |
PoS = PoS = Aggregation of all | 40 |
Parameters | M | S | I | MAC | W | Q | × Q | PEI | NEI | |
---|---|---|---|---|---|---|---|---|---|---|
Fe | 288.5 | 300 | 100 | 200 | 0.005 | 0.004 | 94.25 | 0.38 | 0.38 | −97.89 |
Mn | 26.0 | 500 | 50 | 50 | 0.020 | 0.016 | −5.33 | −0.09 | ||
Zn | 21.3 | 3000 | 50 | 500 | 0.002 | 0.002 | −0.97 | 0.00 | ||
Pb | ND | 100 | 5.0 | 10 | 0.100 | 0.082 | −100 | −8.15 | ||
Cd | ND | 3.0 | 0.1 | 1.0 | 1.000 | 0.815 | −100 | −81.5 | ||
Cr | ND | 40 | 5.0 | 10 | 0.100 | 0.082 | −100 | −8.5 |
ID | Location | MI | HPI | PoS | MHEI | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Score | Class | Score | Class | Score | Dominant | Class | PEI | NEI | Class | ||
GW01 | Um Galagie | 0.33 | Pure | 0.87 | Suitable for drinking purposes | 40 | Fe | Minimum | 0.38 | −97.89 | Good |
GW02 | Eltogoor | 2.97 | Moderately | 12.61 | 387 | Fe, Mn | Medium | 6.08 | −97.80 | Good | |
GW03 | Hamdan 1 | 1.03 | Slightly | 28.95 | 242 | Pb | Low | 27.73 | −0.03 | Good | |
GW04 | Hamdan 2 | 0.67 | Pure | 0.31 | 37 | Mn | Minimum | 0.49 | −97.80 | Good | |
GW05 | Um Ushar 1 | 0.16 | Very pure | 0.27 | 10 | - | Minimum | 0.00 | −98.26 | Excellent | |
GW06 | Um Ushar 2 | 0.71 | Pure | 0.90 | 116 | Pb | Minimum | 1.89 | −81.87 | Good | |
GW07 | Um Laham | 0.31 | Pure | 0.24 | 46 | - | Minimum | 0.10 | −89.72 | Good | |
GW08 | Um Balagie | 1.79 | Slightly | 6.27 | 274 | Fe, Pb | Low | 4.38 | −81.75 | Good | |
GW09 | Kewaimat | 6.33 | Seriously | 25.73 | 845 | Fe, Mn, Pb | Severe | 14.21 | −89.65 | Good | |
GW10 | Um Samima | 1.21 | Slightly | 59.58 | 327 | Mn, Pb, Cd | Low | 55.85 | −8.15 | Moderate | |
GW11 | Um Gewaiz | 1.30 | Slightly | 58.45 | 362 | Fe, Mn, Pb, Cd, Cr | Medium | 54.66 | 0.00 | Moderate | |
GW12 | Elhadid | 0.25 | Very pure | 0.44 | 27 | - | Minimum | 0.19 | −97.89 | Good | |
GW13 | NUm Nabag | 1.52 | Slightly | 31.90 | 303 | Fe | Low | 28.84 | −8.20 | Good | |
GW14 | Bara | 0.55 | Pure | 0.74 | 88 | Pb | Minimum | 1.75 | −90.71 | Good | |
GW15 | Medaisis | 0.96 | Pure | 2.41 | 142 | Fe, Pb | Minimum | 2.46 | −89.70 | Good | |
GW16 | Namil | 1.90 | Slightly | 95.31 | 495 | Fe, Cd | High | 84.33 | −16.32 | Moderate | |
GW17 | Um Sout | 0.96 | Pure | 80.52 | 332 | Mn, Pb, Cd | Low | 74.06 | −8.56 | Moderate | |
GW18 | Abu Shouk | 2.96 | Moderately | 12.10 | 374 | Fe, Mn | Medium | 5.95 | −97.80 | Good |
Sample Rank | MI | HPI | PoS | MHEI | |||||
---|---|---|---|---|---|---|---|---|---|
ID | Value | ID | Value | ID | Value | ID | PEI | NEI | |
Best | GW05 | 0.16 | GW07 | 0.24 | GW05 | 10 | GW05 | 0.00 | −98.3 |
Worst | GW09 | 6.33 | GW16 | 95.31 | GW09 | 845 | GW16 | 84.3 | −16.3 |
Sample Rank | ID | Fe | Mn | Zn | Pb | Cd | Cr |
---|---|---|---|---|---|---|---|
Best | GW05 | 44.8 | 34.7 | 21 | ND | ND | ND |
GW07 | 48.6 | 29.8 | 19.4 | ND | ND | 5.0 | |
Worst | GW09 | 5661.4 | 304.9 | 395 | 27.6 | ND | ND |
GW16 | 1487.3 | 45.9 | 12 | ND | 3.0 | ND |
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Eldaw, E.; Huang, T.; Elubid, B.; Khalifa Mahamed, A.; Mahama, Y. A Novel Approach for Indexing Heavy Metals Pollution to Assess Groundwater Quality for Drinking Purposes. Int. J. Environ. Res. Public Health 2020, 17, 1245. https://doi.org/10.3390/ijerph17041245
Eldaw E, Huang T, Elubid B, Khalifa Mahamed A, Mahama Y. A Novel Approach for Indexing Heavy Metals Pollution to Assess Groundwater Quality for Drinking Purposes. International Journal of Environmental Research and Public Health. 2020; 17(4):1245. https://doi.org/10.3390/ijerph17041245
Chicago/Turabian StyleEldaw, Elsiddig, Tao Huang, Basheer Elubid, Adam Khalifa Mahamed, and Yahaya Mahama. 2020. "A Novel Approach for Indexing Heavy Metals Pollution to Assess Groundwater Quality for Drinking Purposes" International Journal of Environmental Research and Public Health 17, no. 4: 1245. https://doi.org/10.3390/ijerph17041245