Assessment of potentially harmful elements pollution in the Calore River basin (Southern Italy)

Han

et al. 2019

Water

River water samples between August 2017 (wet season) and March 2018 (dry season) from the Mun River Basin in northeast Thailand were collected and their dissolved heavy metals concentrations (Al, Mn, Fe, Cu, Zn, and Ba) were measured. Compared with international drinking water guidelines, Mn was the dominant pollutant in the dry season. The correlation analysis (CA) suggested that similar sources were shown in each element pair of Al-Fe, Mn-Zn, and Fe-Ba in both seasons. The principal component analysis (PCA) results showed that the dominant source of dissolved heavy metals was sedimentary inputs or colloid destabilization in the wet season, while anthropogenic inputs were the main sources in the dry season, such as agricultural runoff, industrial effluents, and domestic discharge. On the basis of water quality index (WQI), water at most sites in the wet and dry seasons can be categorized as excellent water, except for a few sites with substandard values. The river water posed no significant health risks according to the health risk assessment, but Mn, Fe, and Ba needed to be paid more attention due to the relatively high values. Al, Fe, and Ba were the main dissolved heavy metals flowing into the Mekong River, and Cu contributed to the background value in the Mekong river.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variation of Dissolved Heavy Metals in the Mun River, Northeast Thailand

Han

et al. 2019

Water

“…Dissolved heavy metals are generally more toxic than other phases [7,16]. Many heavy metal elements, such as Ti, Cr, Mn, Fe, Ni, Cu, Zn, Mo, Cd, Sb, Ba, Pb, etc., used to be detected in dissolved form due to industrial and domestic discharge without treatments [17,18,19]. Due to the toxicity, non-degradation, and bio-accumulation of heavy metals, an overbalance of concentrations can make water unsuitable for drinking and even cause severe risks to human bodies [4,20,21,22].…”

Section: Introductionmentioning

confidence: 99%

Distribution, Sources, and Water Quality Assessment of Dissolved Heavy Metals in the Jiulongjiang River Water, Southeast China

Han

Yang

et al. 2018

IJERPH

In this study, the concentration of eight dissolved heavy metals (Ti, Cr, Mn, Fe, Ni, Mo, Sb, and Ba) in 42 water samples from the Jiulongjiang River, southeast China, were determined by inductively coupled plasma mass spectrometry (ICP-MS). Multivariate statistical methods, including correlation analysis (CA) and factor and principal component analysis (FA/PCA), were analyzed to identify the sources of the elements. Water quality index (WQI) and health risk assessment, including hazard quotient (HQ) and hazard index (HI), were used to evaluate water quality and the impacts on human health. Our results were compared with the drinking water guidelines reported by China, the World Health Organization (WHO), and the United States Environmental Protection Agency (US EPA), revealing that Ti, Mn, and Sb were not within approved limits at some sites and might be the main pollutants in the drainage basin. Based on the spatial distributions, Ti, Mn, Fe, Ni, and Mo showed good similarity, indicating that they might come from similar sources along the river. The CA results also showed that Ti, Mn, Fe, Ni, and Mo had a high correlation coefficient. The FA/PCA results identified three principal components (PC) that accounted for 79.46% of the total variance. PC 1 suggested that a mixed lithogenic and urban land source contributed to Ti, Mn, Fe, Ni, and Mo; PC 2 showed that Cr, Ni, and Mo were influenced by the discharge of industrial effluents; Sb had a strong loading on PC 3, which was controlled by mining activities. The results of the WQI indicated that the water in the Jiulongjiang River was basically categorized as excellent water, but the water quality levels in site W5 and N4 were poorer due to urban land use. Hazard quotient and HI values showed that Sb was a potential threat to human health, indicating that preventive actions should be considered in regard to mining activities in the upper reaches of Beixi stream.

“…12B), the widespread enrichment created by calculation made using the continental crust values as a reference fades away, replaced by a much narrower enrichment that take into account the local variability of P and Al, and highlights the anthropogenic P inputs observed around the Lioni and Laviano districts, and even more significantly in the Vitulano municipality where it may be related to the use of phosphate fertilizers in agriculture activities. A continental crust concentration based EF 'hides' the anthropogenic input behind a more general enrichment due to the fact that it does not consider the local geological variability (Reimann and de Caritat, 2005;Albanese et al, 2013;Zuzolo et al, 2017). However, when taking into account the local concentration, the anthropogenic input can be more clearly distinguished from the geogenic enrichment factor.…”

Section: Geochemical Elemental Distribution In the Survey Areasmentioning

confidence: 99%

Geogenic versus anthropogenic behaviour and geochemical footprint of Al, Na, K and P in the Campania region (Southern Italy) soils through compositional data analysis and enrichment factor

Thiombane¹,

Bonito

Albanese³

et al. 2019

Geoderma

Self Cite

Geochemical studies that focus on environmental applications tend to approach the chemical elements as individual entities and may therefore offer only partial and sometimes biased interpretations of their distributions and behaviour. A potential alternative approach is to consider a compositional data analysis, where every element is part of a whole. In this study, an integrated methodology, which included compositional data analysis, multifractal data transformations and interpolation, as well as enrichment factor analysis, was applied to a geochemical dataset for the Campania region, in the south of Italy, focusing in particular on the behaviour, footprints and sources of a smaller pool of elements: Al, Na, K and P. The initial dataset included 3669 topsoil samples, collected at an average sampling density of 1 site per 2.3 km 2 , and analysed (after an aqua regia extraction) by a combination of ICP-AES and ICP-MS for 53 elements. Frequency based methods (Clr biplot, Enrichment Factor computation) and frequency spatial-method (fractal and multifractal plots) allowed identifying the relationships between the elements and their possible source patterns in Campania soils in relation to a natural occurring concentrations in geogenic material (rocks, soils and sediments) or human input. Results showed how the interpretation of concentration and behaviour of Al, Na, K and P was enhanced thanks to the application of data log-ratio transformation in univariate and multivariate analysis compared to the use of raw or log-normal data. Multivariate analyses with compositional biplot allowed the identification of four element associations and their potential association with the underling geology and/or human activities. When focusing on the smaller pool of elements (Al, P, K and Na), these relationships with the unique geology of the region were largely confirmed by multifractal interpolated maps. However, when the local background was used for the calculation of the enrichment factor, the resulting interpolated maps allowed to identify smaller areas where the greater concentrations of P could not be possibly associated to a mineralization (e.g., ultrapotassic rocks) but were more likely to be associated to anthropogenic input such as agriculture activities with potentially extensive use of phosphate fertilizers. The integrated approach of this study allowed a more robust qualitative and quantitative evaluation of elemental concentration, providing in particular new and vital information on the distribution and patterns of P in soils of the Campania region, but also a viable, more robust, methodological approach to regional environmental geochemistry studies.