Rapid urbanization affects microplastic communities in lake sediments: A case study of Lake Aha in southwest China

Effective management of pollutants in urban environments is crucial for achieving sustainable cities. Microplastics, as an emerging pollutant widely present in contemporary environments, have received widespread attention in recent years. However, limited studies have reported the impact of rapid urbanization on regional microplastics. In this study, the abundance and composition of microplastic communities in the sediments of Lake Aha were analyzed using a "microplastic community" and slicing the sediments at 5 cm intervals. Results showed that microplastic abundance of sediments in Lake Aha was relatively high (up to 1700 items/kg) and decreased with increasing depth, with the highest abundance found in the surface layer (0-5 cm, 1090 ± 474 items/kg). Hierarchical cluster analysis (HCA), principal component analysis (PCA), and analysis of similarities (ANOSIM) revealed that the different sediment layers could be classified into high and low urbanization level groups based on the composition of microplastic communities. Linear discriminant analysis effect size (LEfSe) indicated that agricultural input was the main source of microplastic pollution during low urbanization levels, characterized by low abundance, large particle size, and high fiber proportion, while urban activities dominated during high urbanization levels, with high abundance, small particle size, high proportion of Polyethylene terephthalate (PET), fragments, and granules, and colorful microplastics. This study clarifies the impact of urbanization on the abundance and composition of microplastics in lake sediments, which has implications for more effective management and control of microplastic pollution in regions undergoing rapid urbanization.

A multivariate statistical approach and water quality index for water quality assessment for the Rokel river in Sierra Leone

The main aim of the study was to use multivariate statistical approach to determine the relationship between parameters, identify the factors affecting the quality of water and interpret and group the water quality parameters. Water quality data was collected during two seasons; wet season spanning from June to August 2019 and dry season spanning from February to April 2019. The physiochemical and microbial parameters measured from the sampling process were turbidity, temperature, pH, electric conductivity, total hardness, calcium carbonates, total dissolved solid (TDS), dissolved oxygen (DO), total suspended solids (TSS), iron, nitrate, phosphate, potassium, sulphate, chromium, fluoride, e. coli and coliform. A total of 406 data set were collected and analysed using Principal Component Analysis, water quality index, cluster analysis and analysis of variance (ANOVA). These data sets were tested for sampling adequacy using Kaiser-Meyer-Olkin and Bartlett's Test and the result on the Kaiser-Meyer-Olkin Measure of Sampling Adequacy obtained was 0.615. The analysis yields Five PCs extraction with eigenvalues >1. These components explained 82.628% of the total variance of the entire components. The maximum water quality index 13 which indicated a grade A and can be treated for water supply. The following parameters Chromium 0.39 mg/l, Iron 1.88 mg/l, turbidity 18.66NTU, Phosphates 26.00 mg/l and fluorides 1.75 mg/l exceeded the WHO guidelines for drinking water. The mean values electrical conductivity is 12.26 μS/cm, 31.8 μS/cm for rain and dry seasons respectively., The following parameters Turbidity, Total Dissolved Solid, Total Suspended solids, Iron, Phosphate, Fluoride and Sulphate shows variation with High during the rain and low during the dry season with significant statical difference with a p value < 0.05. Whereas there is difference between the seasonal values of chromium, Nitrate and Potassium. The ANOVA resulted in P-value >0.05 which indicated no statistically significant different for chromium, Nitrate and Potassium. The seasonal variation was corroborated by cluster analysis with two clusters of C1 and C2. The PCs analysis, cluster analysis and ANOVA gave detailed characterization of the source and group correlation amongst the physiochemical and microbial parameters.

Impact of acid mine drainage on groundwater hydrogeochemistry at a pyrite mine (South China): a study using stable isotopes and multivariate statistical analyses

Combining environmental isotope analysis with principal component analysis can be an effective method to discriminate the inflows and sources of contamination in mining-affected watersheds. This paper presents a field-scale study conducted at an acid mine drainage (AMD)-contaminated site adjacent to a pyrite mine in South China. Samples of surface water and groundwater were collected to investigate transport in the vadose zone using stable isotopes of oxygen (δ¹⁸O) and hydrogen (δD) as environmental tracers. Principal component analysis of hydrogeochemical data was used to identify the probable sources of heavy metals in the AMD. The heavy metal pollution index (HPI) was applied to evaluate the pollution status of heavy metals in the groundwater. The groundwater associated with the Datai reservoir was recharged by atmospheric precipitation and surface water. On the side near the AMD pond, the groundwater was significantly affected by the soluble metals produced by pyrite oxidation. The concentrations of some metals (Al, Mn, and Pb) in all of the samples exceed the desirable limits prescribed by the World Health Organization (Guidelines for drinking-water quality, 4th edn. World Health Organization, Geneva, 2011). Among them, the concentration of Al is more than 30,000 times higher than the desirable limits prescribed by the World Health Organization (2011), and the concentration of Mn is more than 3000 times higher. The HPI values based on these heavy metal concentrations were found to be 10-1000 times higher than the critical pollution index value of 100. These findings provide a reference and guidance for research on the migration and evolution of heavy metals in vadose zone water in AMD-contaminated areas.

Buffer zone-based trace elements indicating the impact of human activities on karst urban groundwater

The tanglesome allocation of landscape types at various spatial dimensions is an important component influencing the quality of groundwater environment in karst cities. Trace elements can be used as indicators of the extent of impact on groundwater which is an effective means of tracing groundwater contamination. In this study, we studied the influence of landscape patterns on trace elements in groundwater of typical karst cities in Southwest China (Guiyang City) on a multi-spatial scale by using multivariate statistical analysis. According to the sampling points, buffer zone scales with different radii (500 m, 1000 m, 1500 m, and 4000 m) were established to quantify the land use model. There are suburban and urban differences in trace element content. The city center has higher levels of trace elements compared to suburban areas, especially Li, Ni, Tl, Cu, Sr, Co, As, and Mn. In addition, the outcomes of the multiple linear regression had shown that the size effect of the association from landscape pattern to trace elements varies with different indicators and parameters. The results of redundancy analysis showed an overall change in trace elements was better interpreted by the landscape pattern of the 1500 m-scale buffer. At the same time, at the 1500 m scale, Ni, Tl, Cu, Co, As, Cr, Sr, Li, and Mn were positively correlated with the urban landscape index (4LPI, 4LSI), influenced by urban anthropogenic activities, while Cd, Zn, and Pb were positively correlated with the cropland landscape index (1AI, 1LPI), influenced by agricultural activities. This study indicates that trace elements are a reliable indicator for tracing groundwater contamination. The buffer zone can reflect the extent of urban impacts on groundwater and provide a new and effective analytical tool for groundwater management.

Coupled controls of the infiltration of rivers, urban activities and carbonate on trace elements in a karst groundwater system from Guiyang, Southwest China

Hydrogeochemical processes of trace elements (TEs) are of considerable significance to river water and groundwater resource assessment and utilization in the karst region. Therefore, seven TEs were analyzed to investigate their contents, spatial variations, sources, and controlling factors in Guiyang, a typical karst urban area in southwest China. The results showed that the average content of TEs in river water (e.g., As = 1.44 ± 0.47 μg/L andCo = 0.15 ± 0.06 μg/L) was higher than that of groundwater (e.g., As = 0.51 ± 0.42 μg/L andCo = 0.09 ± 0.05 μg/L). The types of groundwater samples were dominated by Ca/Mg-HCO₃ and Ca/Mg-Cl types, while those of the river water samples were Ca-Cl and Ca/Mg-Cl types. Principal component analysis (PCA) and correlation analysis (CA) analyses indicated that As and Mn in the groundwater of the study area were related to river infiltration. The end-member analysis further revealed that river infiltration (As = 0.86-1.81 μg/L, Cl/SO₄^2- = 0.62-0.89) and urban activities (As = 0.21-0.32 μg/L, Cl/SO₄^2- = 0.51-0.89) were two main controlling factors of TEs (e.g., As, Co, and Mn) in the study area. In addition, the ion ratios in river and groundwater samples indicated that the weathering of carbonates was also an important control on the hydrogeochemistry of TEs (e.g., Fe and Mn) in Guiyang waters. This study showed that the trace element (TE) contents of groundwater in the Guiyang area were greatly associated with urban input and river recharge, and provided a new perspective for understanding the geochemical behavior of TEs in urban surface and groundwater bodies, which will help the protection of groundwater in the karst areas of southwest China.

Indices and models of surface water quality assessment: Review and perspectives

Many technologies have been designed to monitor, evaluate, and improve surface water quality, as high-quality water is essential for human activities including agriculture, livestock, and industry. As such, in this study, we investigated water quality indices (WQIs), trophic status indices (TSIs), and heavy metal indices (HMIs) for assessing surface water quality. Based on these indices, we summarised and compared water assessment models using expert system (ES) and machine learning (ML) methods. We also discussed the current status and future perspectives of water quality management. The results of our analyses showed that assessment indices can be used in three aspects of surface water quality assessment: WQIs are aggregated from multiple parameters and commonly used in surface water quality classification; TSIs are calculated from the concentrations of different nutrients required for algae and bacteria, and employed to evaluate the eutrophication levels of lakes and reservoirs; HMIs are mainly applied for human health risk assessment and the analysis of correlation of heavy metal sources. ES- and ML-based assessment models have been developed to efficiently generate assessment indices and predict water quality status based on big data obtained from new techniques. By implementing dynamic monitoring and analysis of water quality, we designed a next-generation water quality management system based on the above indices and assessment models, which shows promise for improving the accuracy of water quality assessment.

Source Identification and Health Risk Assessment of Heavy Metals in Soil: A Case Study of Lintancang Plain, Northeast China

To investigate the concentration, source, and potential health risk of soil heavy metals (V, Cr, Ni, Cu, Zn, Pb, Hg), this study determined the concentration of these seven metals in 37 soil samples from Linyi City, southeast of Shandong Province, China. The mean concentrations of the investigated heavy metals followed the sequence: Cr (76.2 mg/kg) > V (70.5 mg/kg) > Zn (70.1 mg/kg) > Ni (34.0 mg/kg) > Pb (31.4 mg/kg) > Cu (23.2 mg/kg) > Hg (1.7 mg/kg). The enrichment factor (EF) and geo-accumulation index (Igeo) indicated an extreme enrichment of Hg (EF > 10, Igeo > 4) within the study area, while a slight enrichment of other metals. According to the toxic risk index (TRI), Hg accounted for the strongest soil toxicity (TRI = 8.07, 64.3%). The risk assessment with hazard index (HI) suggested that the health risks of all metals were acceptable, and the HI of adults was generally lower compared with that of the children. In addition, two principal components (PC) calculated by principal component analysis (PCA) were used to identify the sources of these heavy metals, which were 57.73% for PC 1 (Pb, Cr, Zn, Ni, Hg, Cu and V) and 21.63% for PC 2 (Hg, Cu and V), respectively. Moreover, PC 1 was mainly controlled by anthropogenic inputs, while PC 2 was contributed to by natural sources. Combined with the correlation matrix, it was concluded that there were three different sources for all seven heavy metals.

Occurrence of Potentially Toxic Elements in Bottled Drinking Water-Carcinogenic and Non-Carcinogenic Risks Assessment in Adults via Ingestion

The presence of potentially toxic elements in drinking water can be dangerous for human health because of their bioaccumulation and toxicity, which is a huge concern for many researchers. In the case of bottled water, the exposure to toxic elements is achieved, especially by ingestion, leading to disorders of important functions of the human body. The aim of this study was the detection of some potentially toxic elements, from 50 samples of bottled drinking water, available on the Romanian market. Based on obtained concentrations, an assessment of the carcinogenic and non-carcinogenic health risk was performed. The concentrations of potentially toxic elements analyzed were below the maximum allowable limits, for all contaminants, excluding Pb and Fe. Moreover, the results of total risk via ingestion, showed that 30% of samples had an Hazard Quotient (HQ) < 1, and 70% had an HQ > 1; which implies a potential risk following the consumption of those samples. Concerning total cancer risk, 28% of the samples are in the acceptable level, while 72% of the samples are considered harmful and can lead to a type of cancer after repeated exposure. The study concluded that long term use of bottled water of poor quality may pose a hazard to human health; it is helpful for inhabitants to avoid ingestion of contaminated water.

Comprehensive assessment of water quality and associated health risk by using physicochemical quality indices and multivariate analysis in Terme River, Turkey

The ecosystem and water quality of Terme River, an essential drinking and irrigation water source in the region, are at risk due to anthropogenic pressures. Therefore, the present study aim to present a comprehensive overview of the water quality state and pollution sources of the river. Some physicochemical water quality parameters were analyzed by standard methods along the surface water of river spatiotemporally. The concentrations of major elements and heavy metals (Na, Mg, K, Ca, Al, Cr, Fe, Co, Mn, Ni, Zn, Cd, Cu, Pb, As) were measured in water samples. Relationships between physicochemical data were assessed by using multivariate statistical analysis (MSA) methods. The order of the mean values of cations were as follow: Ca2+ > Mg2+ > Na+ > K+ > NH4+ (32.66, 26.82, 13.29, 6.45, 0.305; mg/L), and order of anions: SO42- > NO3- >F- > NO2- (7.88, 3.988, 1.01, 0.0316; mg/L). Increases in ion concentrations in the downstream zone have been monitored in the summer and autumn months. Average water quality index (WQI) 22, heavy metal pollution index (HPI) 15.61, heavy metal evaluation index (HEI) 0.78, and nutrient pollution index (NPI) 0.404 values indicated that the general water quality of Terme River was fine. All hazard quotient (HQ) and hazard index (HI) values in this study were calculated below the risk threshold (<1). HI-total values (2.48E-01) in children were higher than in adults (2.14E-01). This suggests that children's health is at higher risk than adults. Principal component analysis (PCA) data formed four principal components (PCs) explaining 85.22% of the total variance. These PCs revealed that the significant changes in water quality occurred from point and diffuse sources, including rock types of the basin, soil erosion, domestic wastewater discharges, and agricultural flow of inorganic fertilizers.

Distribution, source, water quality and health risk assessment of dissolved heavy metals in major rivers in Wuhan, China

Heavy metals are released into the water system through various natural processes and anthropogenic activities, thus indirectly or directly endangering human health. The distribution, source, water quality and health risk assessment of dissolved heavy metals (V, Mn, Fe, Co, Ni, Zn, As, Mo, Sb) in major rivers in Wuhan were analyzed by correlation analysis (CA), principal component analysis (PCA), heavy metal pollution index (HPI), hazard index (HI) and carcinogenic risk (CR). The results showed that the spatial variability of heavy metal contents was pronounced. PCA and CA results indicated that natural sources controlled Mn, Fe, Co, Ni and Mo, and industrial emissions were the dominant factor for V, Zn and Sb, while As was mainly from the mixed input of urban and agricultural activities. According to the heavy metal pollution index (HPI, ranging from 23.74 to 184.0) analysis, it should be noted that As and Sb contribute most of the HPI values. The health risk assessment using HI and CR showed that V and Sb might have a potential non-carcinogenic risk and As might have a potential carcinogenic risk to adults and children in the study area (CR value exceeded target risk 10⁻⁴). At the same time, it was worth noting that As might have a potential non-carcinogenic risk for children around QLR (HI value exceeded the threshold value 1). The secular variation of As and Sb should be monitor in high-risk areas. The results of this study can provide important data for improving water resources management efficiency and heavy metal pollution prevention in Wuhan.