Unlocking the Secrets of River Pollution: Analyzing Organic Pollutants in Sediments—Experimental Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Design
2.2. Chemical Analysis
2.3. Quality Assurance and Control
2.4. Statistical Analysis
2.5. Total Organic Carbon Method (TOC)
3. Result and Discussion
3.1. Composition, Distribution and Concentration LAB
3.2. TOC Evaluation
3.3. Assessment of LAB Reduction and Effluents Treatments Efficiency
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Sample Name | Geographical Coordination | Location Type | Weather Condition | Site Description |
---|---|---|---|---|
SMu1 | N 02°04′06.0″ E 102°33′18.1″ | River | Cloudy | Urban and industry area |
SMu 2 | N 02°03′34.9″ E 102°34′27.0″ | River | Cloudy | Urban and industry area |
SMu 3 | N 02°03′18.0″ E 102°32′23.9″ | River | Cloudy | Urban and industry area |
SKK1 | N 01°27′28.2″ E 103°57′76.2″ | River | Rainy | Urban and industry area |
SKK2 | N 01°26′77.6″ E 103°58′04.6″ | River | Rainy | Urban and industry area |
SKK3 | N 01°25′09.6″ E 103°58′3.31″ | River | Rainy | Urban and industry area |
Compound | b SMu1 | SMu2 | SMu3 | SKK1 | SKK2 | SKK3 |
---|---|---|---|---|---|---|
a C10-LABs (ng·g−1dw) | 16.4 | 8.4 | 8.2 | 9.4 | 7.7 | 6.8 |
C11-LABs (ng·g−1dw) | 25.0 | 14.8 | 14.2 | 16.3 | 13.0 | 12.0 |
C12-LABs (ng·g−1dw) | 41.8 | 19.7 | 18.3 | 25.6 | 20.7 | 18.6 |
C13-LABs (ng·g−1dw) | 69.4 | 27.2 | 25.8 | 41.0 | 32.6 | 29.5 |
C14-LABs (ng·g−1dw) | 35.5 | 21.1 | 20.9 | 26.8 | 21.1 | 21.3 |
LABs (ng.g−1dw) | 188.1 | 91.2 | 87.4 | 119 | 95.2 | 88.3 |
c I/E | 2.2 | 1.7 | 1.7 | 2.0 | 1.8 | 1.7 |
d L/S | 2.67 | 2.02 | 1.99 | 2.4 | 2.5 | 2.6 |
e C13/C12 | 6.71 | 4.18 | 4.15 | 5.1 | 5.2 | 5.2 |
f LAB Degradation (%) | 43 | 33 | 33 | 38 | 35 | 33 |
g TOC(%) | 2.5 | 2.2 | 1.4 | 1.2 | 1.0 | 8.1 |
TOC (mg/g) | 25.4 | 22.2 | 13.8 | 11.5 | 9.0 | 81 |
C11 | C12 | C13 | C14 | Labs | I/E | L/S | C13/C12 | Labdegr | TOC | |
---|---|---|---|---|---|---|---|---|---|---|
C10 | 1.000 | 0.714 | 0.543 | 0.551 | 0.714 | 0.698 | 0.086 | 0.116 | 0.698 | 0.029 |
C11 | 0.714 | 0.543 | 0.551 | 0.714 | 0.698 | 0.086 | 0.116 | 0.698 | 0.029 | |
C12 | 0.943 | 0.812 | 1.000 | 0.941 | 0.600 | 0.667 | 0.941 | 0.143 | ||
C13 | 0.895 | 0.943 | 0.941 | 0.771 | 0.812 | 0.941 | 0.029 | |||
C14 | R | 0.812 | 0.770 | 0.783 | 0.750 | 0.770 | 0.348 | |||
Labs | >0.9 | very strong | 0.941 | 0.600 | 0.667 | 0.941 | 0.143 | |||
I/E | 0.7–0.9 | strong | 0.577 | 0.647 | 1.000 | 0.213 | ||||
L/S | <0.7 | medium | 0.986 | 0.577 | 0.429 | |||||
C13/C122 | 0.647 | 0.290 | ||||||||
Labdegr | 0.213 |
Source | DF | Sum of Square | Mean Square | F Value | Sig * |
---|---|---|---|---|---|
Side | 1 | 92,278.39 | 9227.39 | 10.11 | <0.05 |
Locations | 2 | 114,597.32 | 2291.46 | 50.20 | <0.05 |
Error | 25 | 0.00 | 0.00 | ||
Corrected Total | 6 | 143,098.47 |
Location | N | Maximum LABs (ng/g) a | I/E Ratio b | Degradation c (%) | Reference |
---|---|---|---|---|---|
South Atlantic Estuary | 15 | 210 | 2.5 | 47 | [44] |
Southern Brazil | 3 | 15.3 | 1.4 | 27 | [43] |
Humber Estuary and Wash, UK | 18 | 84.8 | 2.1 | 41 | [45] |
Anzali Wetland, Iran | 167 | 109,000 | 1.3 | 24 | [41] |
Malacca, Malaysia | 1 | 1080 | 2.0 | 39 | [42] |
Muar River, Malaysia | 1 | 32 | 2.8 | 51 | [42] |
Penang Estuary, Malaysia | 1 | 3000 | 1.5 | 29 | [42] |
Prai River, Malaysia | 1 | 25 | 3.4 | 58 | [42] |
Kim Kim River, Malaysia | 1 | 122 | 1.8 | 36 | [42] |
Kim Kim Estuary, Malaysia | 1 | 6 | 1.2 | 21 | [42] |
Nibong Tebal, Malaysia | 1 | 168 | 2.1 | 41 | [42] |
Indonesia | 20 | 42,600 | 2.1 | 41 | [42] |
Sarawak River, Malaysia | 9 | 7390 | 1.0 | 15 | [29] |
SembulanRiver, Malaysia | 6 | 5570 | 1.8 | 36 | [29] |
Zhujiang River | 11 | 2330 | 1.5 | 29 | [40] |
Dongjiang River | 10 | 566 | 1.9 | 38 | [40] |
Xijiang River | 8 | 69.4 | 1 | 15 | [40] |
Pearl River Estuary | 8 | 26 | 1.5 | 29 | [40] |
South China Sea | 28 | 23 | 0.9 | 11 | [40] |
The Pearl River Delta | 96 | 11,200 | 1.7 | 34 | [46] |
Santos Bay, Brazil | 14 | 117 | 2.9 | 55 | [47] |
Dongjiang River | 45 | 410 | 1.4 | 27 | [48] |
Outfalls of paper mills | 3 | 3270 | 1.3 | 24 | [48] |
Jakarta Bay | 7 | 86,800 | 0.9 | 12 | [49] |
Tokyo Bay | 2 | 1110 | 2.8 | 51 | [49] |
Detergents | 10 | 5,300,000 | 1.7 | 34 | [45] |
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Alkhadher, S.A.A.; Suratman, S.; Al-Hazmi, H.E.; Zakaria, M.P.; Szeląg, B.; Majtacz, J.; Drewnowski, J. Unlocking the Secrets of River Pollution: Analyzing Organic Pollutants in Sediments—Experimental Study. Water 2023, 15, 2216. https://doi.org/10.3390/w15122216
Alkhadher SAA, Suratman S, Al-Hazmi HE, Zakaria MP, Szeląg B, Majtacz J, Drewnowski J. Unlocking the Secrets of River Pollution: Analyzing Organic Pollutants in Sediments—Experimental Study. Water. 2023; 15(12):2216. https://doi.org/10.3390/w15122216
Chicago/Turabian StyleAlkhadher, Sadeq Abdullah Abdo, Suhaimi Suratman, Hussein E. Al-Hazmi, Mohamad Pauzi Zakaria, Bartosz Szeląg, Joanna Majtacz, and Jakub Drewnowski. 2023. "Unlocking the Secrets of River Pollution: Analyzing Organic Pollutants in Sediments—Experimental Study" Water 15, no. 12: 2216. https://doi.org/10.3390/w15122216
APA StyleAlkhadher, S. A. A., Suratman, S., Al-Hazmi, H. E., Zakaria, M. P., Szeląg, B., Majtacz, J., & Drewnowski, J. (2023). Unlocking the Secrets of River Pollution: Analyzing Organic Pollutants in Sediments—Experimental Study. Water, 15(12), 2216. https://doi.org/10.3390/w15122216