Surface water contains a large number of pollutants, particularly human pathogens, organic toxicants and heavy metals. Due to the toxic nature of heavy metals towards marine organisms, its removal from the environment has been a growing issue. The biosorption of heavy metal ions from surface water using fish scales has emerged as an environmentally friendly technique. This study assessed the degree of heavy metals accumulation in the scales of Oreochromis niloticus and determining its efficiency as a bioindicator for Cu, Mn and Fe ions removal in the environment of Wewe and Owabi rivers. This study shows that the levels of Cu, Mn, Fe adsorbed from the Owabi river were 685.70 ± 16.51, 247.06 ± 50.46 and 892.90 ± 96.29 mg/kg, respectively. Moreover, the levels of Cu, Mn and Fe adsorbed from Wewe river were 501.60 ± 77.78, 300.89 ± 54.61     and 413.04 ± 9.92 mg/kg, respectively. Under best optimum adsorption conditions, Cu was the best removed heavy metal ions in both surface water reservoirs. Multivariate analysis showed that Cu and Mn showed association in Owabi river, while Mn and Fe were correlated in Wewe river signifying their similarities to a common anthropogenic activity. The Fourier–transform infrared spectrum revealed the existence of a nitro, amine, and carbonyl groups in the biosorption process. This study highlighted that Oreochromis niloticus scales was an efficient bio–sorbent in removing Cu, Mn and Fe ions from Owabi and Wewe rivers.

The study was conducted to assess surface water quality in Ca Mau peninsula using multivariate statistical analysis. Fifty-one water samples with the parameters of pH, dissolved oxygen (DO), total suspended solids (TSS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonium (N-NH4+), orthophosphate (P-PO43-) and total coliform were used in the evaluation. Water quality is assessed using national standard and water quality index (WQI). The methods of cluster (CA), discriminant (DA), principal component analysis (PCA) were used to analyze the variation patterns of water quality. The surface water was contaminated with organic matters, suspended solids, nutrients, and microorganisms. DA revealed that DO, TSS, BOD5 and pH contributed 76.91% to the seasonal variation of water quality. Water quality is classified from bad to heavily polluted. CA grouped water quality into 7 clusters and DO, TSS, BOD5, COD and coliform of the clusters 1-3 were significantly higher than those of the clusters 4-7. PCA presented that PC1-PC3 was the main sources affecting water quality, explaining 85.45% of the variation in water quality. The sources of pollution can be human (domestic wastewater, waste from agriculture, fisheries, industry, landfills), natural (hydrological regime, rainwater overflow, river bank erosion). pH, DO, BOD5, COD, TSS, N-NH4+, P-PO43- and coliform have an impact on water quality and need to be continuously monitored. However, for the multivariate statistical method to be more effective, an initial data set with several water quality parameters sampling locations is needed. The current results provide scientific information and support local water quality monitoring activities.

International audience | Polycyclic aromatic hydrocarbon (PAH) concentrations and N, C stable isotope signatures were determined in mosses Hypnum cupressiforme Hedw. from 61 sites of 3 European regions: Île-de-France (France); Navarra (Spain); the Swiss Plateau and Basel area (Switzerland). Total PAH concentrations of 100-700 ng g-1, as well as δ13C values of -32 to -29‰ and δ15N values of -11 to -3‰ were measured. Pearson correlation tests revealed opposite trends between high molecular weight PAH (4-6 aromatic rings) content and δ13C values. Partial Least Square regressions explained the very significant correlations (r > 0.91, p < 0.001) between high molecular weight PAH concentrations by local urban land use (<10 km) and environmental factors such as elevation and pluviometry. Finally, specific correlations between heavy metal and PAH concentrations were attributed to industrial emissions in Switzerland and road traffic emissions in Spain.

Contaminant vulnerability in the critical zones like groundwater (GW)-seawater (SW) continuum along the entire Gujarat coast was investigated for the first time through an extensive water monitoring survey. The prime focus of the study was to evaluate whether or not: i) seawater intrusion induced metal load translates to toxicity; ii) in the coastal groundwater, metal distribution follows the pattern of other geogenic and anthropogenic contaminants like NO₃- and F-; and iii) what future lies ahead pertaining to metal fate in association with saturation conditions of the coastal aquifers. The spatial distribution of contaminants depicts that the Gulf of Khambhat area is highly contaminated. Ecological risk assessment (ERA) indicates that the Gujarat coast is experiencing a high ecological risk compared to the southeast coast of India. Investigation results revealed that metals, pH, NO₃, and CO₃ are more vulnerable at the SW-GW mixing interface. An increase in pH is reflected in fewer ionic species of metals in the GW. Salinity ingress due to seawater intrusion (SWI) reduces the toxicities of all trace metals except Cu, attributed to the increase of Ca in GW, leading to dissociation of CuCO₃. Reactive species are dominant for Zn and Cd; and M-CO₃ ligands are dominant for Cu and Pb owing to the undersaturation of dolomite and calcite in the aquifer system. SWI tends to increase the metal load but the toxicity of metals varies with the density of industries, anthropogenic activities, changes in the mixing-induced saturation conditions, and intensive salt production across the coast. Multivariate analysis confirmed that the hydrogeochemical processes change due to GW-SW mixing and dictates over natural weathering. The ecological risk index (ERI) for the Arabian sea is experiencing moderate (300 ≥ ERI>150) to high ecological risk (ERI >600). Children population is likely to encounter a high health risk through ingestion and dermal exposure than adults. Overall, the study emphasizes the complexity of toxicity-related health impacts on coastal communities and suggests the dire need for frequent water monitoring along the coastal areas for quick realization of sustainable development goals.

Rivers can be sinks for potential toxic elements (PTEs) inputted in their systems by both natural and anthropic processes. Many indices have been proposed to assess the contamination degree of sediments and the environmental conditions of surficial water bodies. Above all, enrichment factor (EF) is the most used tool, but also it is the most debated for its limitations. The need for a reference element and for a background/baseline composition makes the EF method dependent on the researcher's expertise, implying that its repeatability may not be granted. Starting from the awareness that geochemical processes, bringing to compositional changes in the environmental matrices, involve multiple elements rather than individual variables, we developed a modified EF (mEF) based on the use of elemental associations. Different multivariate statistical methods (i.e. Robust Principal Component Analysis and Fuzzy Clustering), in a compositional data analysis (CoDA) perspective, were used to set all the terms of the mEF. The mEF was applied to 101 sediment samples collected from a 2 m-long core, covering a sedimentation period of about 150 years (1850–2007), located in the lower Changjiang River (China). The method resulted effective in recognizing most of the signals proceeding from the main natural and anthropogenic events which affected the lower river basin in the considered timespan. The largest geochemical variations recorded fit well the flooding events occurred; besides, the effects produced on the system by the recent socio-economic development (following the end of the civil war in 1949 and the beginning of economic reforms in 1978) and the start-up of the Three Gorges Dam (the world's largest power station since 2012) were also intercepted. The proposed method represents a step forward to enhance the effectiveness of the EF in discriminating geochemical anomalies that may be significant to assess the human historical impact on the environment.

Passive biomonitoring was applied in four Atlantic forest plots in southeast Brazil, affected by different levels of trace metal pollution (OP site located in Minas Gerais State and PEFI, PP and STG located in São Paulo State). Native tree species were selected as biomonitors according to their abundance in each plot and successional classification. Current trace metal concentrations in total suspended particles, leaves of non-pioneer (NPi) and pioneer (Pi) species, topsoil (0–20 cm) and litter and concentration ratios at the plant/soil interface were analyzed to verify the atmosphere-plant-soil interactions, basal concentrations, spatial variations and metal accumulation at the ecosystem level. Redundant analysis helped to identify similar characteristics of metal concentrations in PP and PEFI, which can be influenced by the high concentrations of elements related to anthropogenic inputs. Analysis of variance and multivariate statistics indicated that the trees of OP presented higher concentrations of Cr, Fe, Mn and Ni than those in the other sites. High enrichment of Cd, Fe, Ni in non-pioneer plants indicated that the PP forest (initially considered as the least polluted) has still been affected by metal pollution. Soil collected in STG was enriched by all elements, however these elements were low available for plant uptake. Metal deposited in leaves and litter was an important sink for soil cycling, nevertheless, these metals are not bioavailable in most cases. Non-pioneer tree species revealed to be more appropriate than pioneer species to indicate the current panorama of the contamination and bioavailability levels of trace metals in the tree community-litter-soil interface of the Atlantic forest remnants included in this study.

Biochar has been proven as a soil amendment to improve soil environment. However, mechanistic understanding of biochar on soil physical properties and microbial community remains unclear. In this study, a wood biochar (WB), was incorporated into a highly weathered tropical soil, and after 1 year the in situ changes in soil properties and microbial community were evaluated. A field trial was conducted for application of compost, wood biochar, and polyacrylamide. Microstructure and morphological features of the soils were characterized through 3D X-ray microscopy and polarized microscopy. Soil microbial communities were identified through next-generation sequencing (NGS). After incubation, the number of pores and connection throats between the pores of biochar treated soil increased by 3.8 and 7.2 times, respectively, compared to the control. According to NGS results, most sequences belonged to Anaerolinea thermolimosa, Caldithrix palaeochoryensis, Chthoniobacter flavus, and Cohnella soli. Canonical correlation analysis (CCA) further demonstrated that the microbial community structure was determined by inorganic N (IN), available P (AP), pH, soil organic C (SOC), porosity, bulk density (BD), and aggregate stability. The treatments with co-application of biochar and compost facilitated the dominance of Cal. palaeochoryensis, Cht. flavus, and Coh. soli, all of which promoted organic matter decomposition and ammonia oxidation in the soil. The apparent increases in IN, AP, porosity, and SOC caused by the addition of biochar and compost may be the proponents of changes in soil microbial communities. The co-application of compost and biochar may be a suitable strategy for real world biochar incorporation in highly weathered soil.

Soil contamination in urban environment by trace metals is of public concerns. For better risk assessment, it is important to determine their background concentrations in urban soils. For this study, we determined the background concentrations of 9 trace metals including As, Ba, Cd, Co, Cu, Ni, Pb, Se, and Zn in 214 urban soils in Florida from two large cities (Orlando and Tampa) and 4 small cities (Clay County, Ocala, Pensacola and West Palm Beach). The objectives were to determine: 1) total concentrations of trace metals in urban soils in cities of different size; 2) compare background concentrations to Florida Soil Cleanup Target Levels (FSCTLs); and 3) determine their distribution and variability in urban soils via multivariate statistical analysis. Elemental concentrations in urban soils were variable, with Pb being the highest in 5 cities (165–552 mg kg⁻¹) and Zn being the highest concentration in Tampa (1,000 mg kg⁻¹). Besides, the As and Pb concentrations in some soils exceeded the FSCTL for residential sites at 2.1 mg kg⁻¹ As and 400 mg kg⁻¹ Pb. Among the cities, Clay County and Orlando had the lowest concentrations for most elements, with Cd, Co, and As being the lowest while Ba, Pb and Zn being the highest. Among all values, geometric means were the lowest while 95th percentile was the highest for all metals. Most 95th percentile values were 2–3 folds higher than the GM data, with Pb presenting the greatest difference, being 4 times greater than GM value (58.9 vs. 13.6 mg kg⁻¹). Still they were lower than FSCTL, with As exceeding FSCTL for residential sites at 2.1 mg kg⁻¹. In addition, the linear discriminate analysis showed distinct separation among the cities: Ocala (Ba & Ni) and Pensacola (As & Pb) were distinctly different from each other and from other cities with higher metal concentrations. The large variations among elemental concentrations showed the importance to establish proper background concentrations of trace metals in urban soils.

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating “good” to “excellent” water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl⁻, SO₄²⁻, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄–N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

Environmental pollution can disrupt the interactions between animals and their symbiotic bacteria, which can lead to adverse effects on the host even in the absence of direct chemical toxicity. It is therefore crucial to understand how environmental pollutants affect animal microbiomes, especially for those chemicals that are designed to target microbes. Here, we study the effects of two biocidal nanoparticles (NPs) (Ag and CuO) on the soil bacterial community and the resident gut microbiome of the earthworm Eisenia fetida over a 28-day period using metabarcoding techniques. Exposures to NPs were conducted following OECD test guidelines and effects on earthworm reproduction and juvenile biomass were additionally recorded in order to compare effects on the host to effects on microbiomes. By employing a full concentration series, we were able to link pollutants to microbiome effects in high resolution. Multivariate analysis, differential abundance analysis and species sensitivity distribution analysis showed that Ag-NPs are more toxic to soil bacteria than CuO-NPs. In contrast to the strong effects of CuO-NPs and Ag-NPs on the soil bacterial community, the earthworm gut microbiome is largely resilient to exposure to biocidal NPs. Despite this buffering effect, CuO-NPs did negatively affect the relative abundance of some earthworm symbionts, including ‘Candidatus Lumbricincola’. Changes in the soil bacterial community and the earthworm microbiome occur at total copper concentrations often found or modelled to occur in agricultural fields, demonstrating that soil bacterial communities and individual taxa in the earthworm microbiome may be at risk from environmental copper exposure including in nanomaterial form.