Refining the diagnostics of non-point source metals pollution to urban lakes based on interaction normalized PMF coupled with Bayesian network

Chang, Xuan; Jia, Ziliang; Feng, Jiashen; Duan, Tingting; Li, Yingxia

doi:10.1016/j.envpol.2022.119194

Cited by 13 publications

(5 citation statements)

References 63 publications

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“…These results indicated that As and Cd were probably affected by human activities. Previous studies have shown that As is the key component of pesticides, the arsenical pesticides were widely used in agricultural activities for the past many years, which may increase As concentration in soils [ 66 , 67 ]. In addition, a large amount of Cd exists in phosphorus fertilizer, which is a symbol element of agricultural activities [ 68 , 69 ].…”

Section: Resultsmentioning

confidence: 99%

Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond

Xiao

Yang

et al. 2022

IJERPH

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Tailings resulting from mining and smelting activities may cause soil heavy-metal pollution and harm human health. To evaluate the environmental impact of heavy metals from tailings on farmland soils in the surrounding area, heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) in tailings and farmland soils in the vicinity of a typical copper tailings pond were analyzed. Contamination status, potential sources, and health risks for farmland soils were investigated. The results showed that the tailings contained a high concentration of Cu (1136.23 mg/kg). The concentrations of Cd and Cu in the farmland soils exceeded the soil quality standard. The geoaccumulation index (Igeo) indicated that the soils were moderately polluted by Cu and Cd, and slightly polluted by Ni, Cr, and Zn. The absolute principal component scores–multiple linear regression (APCS-MLR) model was applied for source apportionment. The results showed that tailings release is the main source of soil heavy-metals contamination, accounting for 35.81%, followed by agricultural activities (19.41%) and traffic emission (16.31%). The health risk assessment suggested that the children in the study region were exposed to non-carcinogenic risks caused by As, while the non-carcinogenic risk to adults and the carcinogenic risk to both adults and children were at acceptable levels. It is necessary to take effective measures to control heavy-metal contamination from tailings releases to protect humans, especially children, from adverse health risks.

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Section: Resultsmentioning

confidence: 99%

Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond

Xiao

Yang

et al. 2022

IJERPH

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“…Published studies have shown that Pb emissions from vehicle exhaust account for two-thirds of total global Pb emissions 41 ; despite the global ban on the production and use of leaded gasoline since 2000, vehicle exhaust emissions are still considered to be the main cause of Pb accumulation in soils 42 . Additionally, the wear and tear of brakes, bearings and tires of automobiles also promote the release of Pb and Zn into the soil environment 43 . The soil samples collected in this study were located in the tourist area of Sayram Lake, where tourist visits reach values of 2,530,000 per year and may contribute significantly to local traffic.…”

Section: Discussionmentioning

confidence: 99%

Source apportionment of soil heavy metals with PMF model and Pb isotopes in an intermountain basin of Tianshan Mountains, China

Zeng

et al. 2022

Sci Rep

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A boom in tourism may lead to the enrichment in heavy metals (HMs) in soils. Contamination with HMs poses a significant threat to the security of the soil environment. In this study, topsoil samples were collected from a tourist area of Sayram Lake, and the concentrations of HMs (Cr, Cu, Ni, Pb, Zn and Cd) were determined. With contamination and eco-risk assessment models, correlation analysis, Pb isotope ratios, redundancy analysis and positive matrix factorization (PMF) model, the risks and sources of HMs in the soil were studied. The Igeo results suggested that Cd was the primary pollutant in the tourist area of Sayram Lake. The potential ecological risk index (PERI) showed that the study area was at low risk, and the pollution load index (PLI) indicated that the study area had a moderate contamination level. Qualitative and quantitative analyses apportioned three sources of HMs, namely, natural sources (38.5%), traffic sources (27.2%) and mixed sources (tourist waste and atmospheric deposition) (34.3%). Redundancy analysis results showed that the HMs content was related to SiO2, Al2O3, TiO2, P2O5, MnO, K2O, Fe2O3 and SOC, and heavy metals tended to be stored in soil particles of grain sizes < 32 µm. These findings are expected to provide useful insights into the source identification of HMs in the soils of mountain tourism areas and provide a scientific decision-making basis for sustainable tourism development and for the assessment of ecological service values in the Tianshan Mountains.

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“…Šmuc et al (2015) show that the pollutants can come from tourism, traffic, and untreated wastewater discharge sources. The supply of pollutants with overland flow from impermeable surfaces in cities can also be substantial (Chang et al, 2022). Kang et al (2022) points to aquaculture activities, indicating that pollutants were accumulated in sediments owing to past cage fish farming.…”

Section: Introductionmentioning

confidence: 99%

“…The determination of the source of pollutants frequently employs simple statistical methods such as the correlation analysis, principal components analysis (Chen et al, 2022; Lin et al, 2016; Zheng et al, 2010), hierarchical cluster analysis (Liu et al, 2012), or positive matrix factorization (PMF) (Chen et al, 2022; Sojka & Jaskuła, 2022). Complex methods are also used, such as the principal component analysis combined with multiple linear regressions (PCA‐MLR) (Wei et al, 2022), PMF combined with a support vector machine classifier (PMF‐SVM) (Li et al, 2020), or PMF and Bayesian network (PMF‐BN) (Chang et al, 2022). Moreover, based on the results of the analysis of bottom sediments from many sampling points within the lake, maps are prepared that present their spatial variability.…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution of trace and rare earth elements of bottom sediments in Lake Ostrowite, Bory Tucholskie National Park, Poland

Sojka,

Choiński,

Siepak

2024

Land Degrad Dev

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Lake pollution has attracted concerns worldwide; especially the excessive accumulation of trace elements (TEs) and rare earth elements (REEs) in bottom sediments can pose a serious threat to ecosystem health. However, there is still a knowledge gap on the level of sediment pollution in lakes isolated from the direct impact of pollution sources, their spatial variability, and also on the factors influencing this state. The aim of this study is to investigate the level and spatial variability of TEs and REEs concentrations, as well as to determine their source and the factors determining their distribution in the bottom sediments of Lake Ostrowite. Lake Ostrowite is the largest and deepest water body located in the Bory Tuholskie National Park (in northern Poland), which completely isolates the lake from the direct impact of pollution sources. The study covered analyses of 32 surface samples of bottom sediments. The concentrations of 24 TEs and 14 REEs were determined using inductively coupled plasma mass spectrometry (ICP‐QQQ‐MS). The assessment of the enrichment of bottom sediments in TEs and REEs employed geochemical background values (GBV) that provided the basis for the calculation of relative concentrations and geochemical indices. The determination of their sources and supply routes was based on the cluster analysis and principal component analysis. The obtained results point to the enrichment of the bottom sediments with TEs and REEs. Relative concentration values of TEs and REEs in reference to geochemical background values were in ranges from 0.01 to 7.31, at an average of 0.99, and from 0.03 to 4.29, averaging 1.76, respectively. The enrichment factor values show moderately severe enrichment of sediments at the study sites. This was primarily determined by the concentrations of Ag (from the TEs group) and Lu (from the REEs group). The metal pollution index values showed an approximate spatial distribution of points in terms of the presence of TEs and REEs. The lowest concentrations of TEs and REEs occurred on the eastern shore of the western basin of Lake Ostrowite. TEs and REEs concentrations in sediments are positively correlated with the content of organic matter and depth and negatively correlated with distance of the sampling point from the river outflow from Lake Ostrowite. On the eastern shore of the western basin, TEs and REEs concentrations are additionally shaped by wind, predominantly from the western direction. With water wave action, organic matter is transported to the central part of the western basin, where it is accumulated. Since the lake is isolated from point and nonpoint pollution sources, relevant from a biogeochemical point of view are dry and wet depositions from the atmosphere as well as aquatic vegetation, shoreline vegetation, forest litter, soil, and groundwater.

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Refining the diagnostics of non-point source metals pollution to urban lakes based on interaction normalized PMF coupled with Bayesian network

Cited by 13 publications

References 63 publications

Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond

Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond

Source apportionment of soil heavy metals with PMF model and Pb isotopes in an intermountain basin of Tianshan Mountains, China

Spatial distribution of trace and rare earth elements of bottom sediments in Lake Ostrowite, Bory Tucholskie National Park, Poland

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