Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia
Article
Tao, Hai, Al-Hilali, Aqeel Ali, Ahmed, Ali M., Mussa, Zainab Haider, Falah, Mayadah W., Abed, Salwan Ali, Deo, Ravinesh, Jawad, Ali H., Maulud, Khairul Nizam Abdul, Latif, Mohd Talib and Yaseen, Zaher Mundher. 2023. "Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia." Chemosphere. 317. https://doi.org/10.1016/j.chemosphere.2023.137914
Article Title | Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia |
---|---|
ERA Journal ID | 35098 |
Article Category | Article |
Authors | Tao, Hai, Al-Hilali, Aqeel Ali, Ahmed, Ali M., Mussa, Zainab Haider, Falah, Mayadah W., Abed, Salwan Ali, Deo, Ravinesh, Jawad, Ali H., Maulud, Khairul Nizam Abdul, Latif, Mohd Talib and Yaseen, Zaher Mundher |
Journal Title | Chemosphere |
Journal Citation | 317 |
Article Number | 137914 |
Number of Pages | 26 |
Year | 2023 |
Publisher | Elsevier |
ISSN | 0045-6535 |
1465-9972 | |
1879-1298 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.chemosphere.2023.137914 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0045653523001819 |
Abstract | Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions. |
Keywords | Heavy metal contamination; Murray-darling basin ; Spatial analysis ; Soil pollutants |
ANZSRC Field of Research 2020 | 4004. Chemical engineering |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Qiannan Normal University for Nationalities, China |
MARA University of Technology, Malaysia | |
Al-Farahidi University, Iraq | |
Al-Esraa University College, Iraq | |
University of Al-Ameed, Iraq | |
Al-Mustaqbal University College, Iraq | |
University of Al-Qadisiyah, Iraq | |
School of Mathematics, Physics and Computing | |
National University of Malaysia | |
King Fahd University of Petroleum and Minerals, Saudi Arabia |
Permalink -
https://research.usq.edu.au/item/z26z0/statistical-and-spatial-analysis-for-soil-heavy-metals-over-the-murray-darling-river-basin-in-australia
114
total views0
total downloads7
views this month0
downloads this month