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Geographically weighted principal component analysis for characterising the spatial heterogeneity and connectivity of soil heavy metals in Kumasi, Ghana.

ABSTRACT: The use of principal component analysis (PCA) for soil heavy metals characterization provides useful information for decision making and policies regarding the potential sources of soil contamination. However, the concentration of heavy metal pollutants is spatially heterogeneous. Accounting for such spatial heterogeneity in soil heavy metal pollutants will improve our understanding with respect to the distribution of the most influential soil heavy metal pollutants. In this study, geographically weighted principal component analysis (GWPCA) was used to describe the spatial heterogeneity and connectivity of soil heavy metals in Kumasi, Ghana. The results from the conventional PCA revealed that three principal components cumulatively accounted for 86% of the total variation in the soil heavy metals in the study area. These components were largely dominated by Fe and Zn. The results from the GWPCA showed that the soil heavy metals are spatially heterogeneous and that the use of PCA disregards this considerable variation. This spatial heterogeneity was confirmed by the spatial maps constructed from the geographically weighted correlations among the variables. After accounting for the spatial heterogeneity, the proportion of variance explained by the three geographically weighted principal components ranged between 85% and 89%. The first three identified GWPC were largely dominated by Fe, Zn and As, respectively. The location of the study area where these variables are dominated provides information for remediation.

SUBMITTER: Aidoo EN

PROVIDER: S-EPMC8479399 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEnvironmental contamination with heavy metals and metalloids due to industrial, smelting and mining activities have become common in large and growing cities. Kumasi is one of the most industrialized cities in Ghana and experiences metal pollution due to recent and past activities. Although metals are naturally abundant in the area, their accumulation in soils could potentially lead to adverse effects on local ecosystems.ObjectivesThe aims of this study were to determine the distribution, enrichment, geoaccumulation and sources of metals in Kumasi soils and to estimate the contamination factor (CF) and pollution load index (PLI) of these metals in soils.MethodsConcentrations of eight heavy metals and a metalloid were determined in 112 soil samples randomly collected from 31 sampling sites in the area. In addition, 5 soil samples were collected from a pristine site (Kwame Nkrumah University of Science and Technology Botanical Gardens) for data comparison, to determine the local background values for metal concentrations and to evaluate the extent of metal pollution in the study area.ResultsHeavy metals such as zinc (Zn), lead (Pb), cadmium (Cd) and chromium (Cr) were enriched in 65, 32, 58 and 93% of the sampling sites, respectively, and geo-accumulation indexes for Cr, Zn, Cd, mercury (Hg) and Pb showed moderate to extreme contamination in 100, 97, 77, 65 and 45% of the sampling sites, respectively. Principal component and cluster analyses revealed that industrial activities including mining were the major sources of metals in Kumasi soils with high metal input in the community of Suame. Distribution maps revealed hotspots of Cd, nickel (Ni), arsenic (As), cobalt (Co), copper (Cu) and Pb in Suame. The highest CFs for Cu, Cd, Ni, As, Co and Pb highlighted anthropogenic inputs in Suame, while Hg was highest in Mbrom, Zn in Suntreso, and Cr in Aboabo.ConclusionsThe PLI of metals revealed Suame as the most polluted study site, while Anomangye and Bomso were the least polluted.

Project description:The disposal of polymer post-treatment sludge (PTS) from Barekese Water Treatment Plants (WTPs) as organic fertilizer and aquatic feed is a common practice in Ghana, necessitating a thorough evaluation of its ecological and human health risks. This study aims to assess the suitability of PTS samples for soil amendment and fish feed, scrutinizing potential hazards to consumer health and soil. PTS samples were collected from five distinct lateral sections of three clariflocculator tanks. Potentially toxic metals such as Cd, Zn, Pb, Cu, Ni, and Cr were determined using a flame atomic absorption spectrophotometer. The mean concentration of 7.82 ± 2.43, 0.31 ± 0.021, and 0.78 ± 0.042 mg/kg for Mn, Zn, and Pb respectively. The concentrations of Ni, Cr, and Cd were below their detection limits (BDL) in all PTS samples. Upon detailed exposure assessment, ingestion emerged as the primary exposure route for both adults and children, with non-cancer risks (NCR) determined to be below 1 for both age groups. Additionally, an exploration of potential cancer risks (CR) associated with heavy metal exposure in the PTS samples revealed values below the tolerable intake levels ranging from 10-4 to 10-6 for both adults and children (10-8 and 10-9, respectively). This study also employs various ecological indices, such as Nemerow's synthetic pollution index (PN), single factor pollution index (PI), geo-accumulation index (Igeo), contamination factor (CF), potential ecological risk index (PERI), pollution load index (PLI), polymetallic contaminant index (IPD), and ecological risk index (ERI). These indices consistently highlight a low contamination status and ecological sensitivity. Consequently, the study indicates that the presence of metals in the PTS samples does not pose a significant threat to the surrounding environment and human health. Furthermore, this research underscores the inadequacy of relying solely on regulatory limit values in assessing the health risks of waste materials. Such comprehensive assessments are crucial for safeguarding aquatic and human populations.

Project description:Malaria is a mosquito-borne parasitic disease that causes severe mortality and morbidity, particularly in Sub-Saharan Africa. As the vectors predominantly bite between dusk and dawn, risk of infection is determined by the abundance of P. falciparum infected mosquitoes in the surroundings of the households. Remote sensing is commonly employed to detect associations between land use/land cover (LULC) and mosquito-borne diseases. Due to challenges in LULC identification and the fact that LULC merely functions as a proxy for mosquito abundance, assuming spatially homogenous relationships may lead to overgeneralized conclusions.Data on incidence of P. falciparum parasitaemia were recorded by active and passive follow-up over two years. Nine LULC types were identified through remote sensing and ground-truthing. Spatial associations of LULC and P. falciparum parasitaemia rate were described in a semi-parametric geographically weighted Poisson regression model.Complete data were available for 878 individuals, with an annual P. falciparum rate of 3.2 infections per person-year at risk. The influences of built-up areas (median incidence rate ratio (IRR): 0.94, IQR: 0.46), forest (median IRR: 0.9, IQR: 0.51), swampy areas (median IRR: 1.15, IQR: 0.88), as well as banana (median IRR: 1.02, IQR: 0.25), cacao (median IRR: 1.33, IQR: 0.97) and orange plantations (median IRR: 1.11, IQR: 0.68) on P. falciparum rate show strong spatial variations within the study area. Incorporating spatial variability of LULC variables increased model performance compared to the spatially homogenous model.The observed spatial variability of LULC influence in parasitaemia would have been masked by traditional Poisson regression analysis assuming a spatially constant influence of all variables. We conclude that the spatially varying effects of LULC on P. falciparum parasitaemia may in fact be associated with co-factors not captured by remote sensing, and suggest that future studies assess small-scale spatial variation of vegetation to circumvent generalised assumptions on ecological associations that may in fact be artificial.

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Geographically weighted principal component analysis for characterising the spatial heterogeneity and connectivity of soil heavy metals in Kumasi, Ghana.

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