Ecological Risk Assessment and Contamination History of Heavy Metals in the Sediments of Chagan Lake, Northeast China

External magnetic field have significant effects on diversity of magnetotactic bacteria in sediments from Yangtze River, Chagan Lake and Zhalong Wetland in China

Magnetotactic bacteria (MTB) can rapidly relocate to optimal habitats by magnetotaxis, and play an important role in iron biogeochemical cycling. This study aimed to evaluate the contribution of the external magnetostatic field to the diversity of MTB in freshwater sediments from Yangtze River (Changjiang River, CJ), Chagan Lake (CGH) and Zhalong Wetland (ZL). The magnetic field intensity was tightly associated with the community richness of MTB in CJ, whereas it was closely related to the diversity of MTB in CGH and ZL (p < 0.05), elucidating a significant variation in the community composition of MTB. Magnetic exposure time appeared more significant correlation with community richness than diversity for MTB in CJ and CGH (p < 0.05), while an opposite relationship existed in ZL (p < 0.01). Herbaspirillum (93.81-96.48 %) dominated in the sediments of these surfacewatesr regardless of waterbody types, while it shifted to Magnetospirillum in ZL under 100 Gs magnetic field. The network connectivity and stability of MTB deteriorate with the increase of magnetic field intensity. Functional analysis showed that the Two-component system and ABC transporter system of MTB obviously responded to magnetic field intensity and exposure time. Our findings will pave the way to understanding the response mechanism of MTB community in freshwater sediments to the external magnetostatic field.

In situ, high-resolution evidence of metals at the sediment-water interface under ice cover in a seasonal freezing lake

The ice cover in winter as a physical barrier and duration would profoundly impact on changes in endogenous metal loading, migration, and transformation. Although a gradual reduction in duration and occurrence of lake ice cover in boreal lake ecosystems has been confirmed, little attention to the ice-covered period is received compared to open water studies. In this study, novel-developed diffusive gradients in thin films (DGT, ZrO-Chelex) probes were deployed to obtain the in-situ and high-resolution information on metals (Cu, Zn, Pb, Mn, Cd, Cr, and As) at the sediment-water interface (SWI) in a seasonal ice-covered lake, Chagan Lake. In addition, “source-sink” characteristics of each metal related to their endogenous release were determined based on Fick’s first law. Concentrations of labile metals at the SWI demonstrated significant spatial heterogeneity, peaking exactly below the SWI. Compared with other similar studies, concentrations of Pb (0.55 μg/L), Cr (0.58 μg/L), and As (2.4 μg/L) were a little higher even under-ice than that in other freshwater rivers and lakes, indicating potential pollution due to the agricultural intensification and petroleum extraction. The apparent diffusive fluxes suggested that sediments acted as a sink for Pb (−0.01 mg m–2 day–1), Cr (−2.37 mg m–2 day–1), and Cd (−0.1 mg m–2 day–1), diffusing from the overlying water into the sediment, while Cu (0.12 mg m–2 day–1), Zn (0.75 mg m–2 day–1), Mn (15.89 mg m–2 day–1), and As (2.12 mg m–2 day–1) as a source from sediments into the overlying water. Dissolved oxygen was the principal factor (79.5%, P = 0.032), determining the variation of the available metals at the SWI. As the urgent need for research focused on under-ice ecosystem dynamics, this study addressed the previously unknown behavior of the labile metals at the SWI and provided a unique perspective for the lake management during the ice-cover periods when external nutrient input was cut off.

Quality of Bottom Sediments of Sołtmany Lake (Masurian Lake District, Poland) in the Light of Geochemical and Ecotoxicological Criteria—Case Study

The quality of bottom sediment is important for the condition of aquatic environments. High levels of potentially harmful components in sediments negatively affect the quality of surface water environments. Lake bottom sediments are commonly used to control the quality of the environment in terms of both heavy metals and harmful organic compounds. This paper presents new data on the compositions of bottom sediments from Sołtmany Lake, located in the Masurian Lake District (Poland). The aim of this study was to determine the physicochemical properties of bottom sediments and to assess their quality based on geochemical and ecotoxicological criteria. The field study was conducted in July 2021. Thirty sediment samples were collected for analysis from six study sites located in the upper central and lower part of the reservoir. Contamination of the bottom sediments with trace metals was determined on the basis of the geoaccumulation index (Igeo), while an ecological risk assessment was carried out on the basis of calculated values of TEC (Threshold Effect Concentration) and PEC (Probable Effect Concentration) indices. The study shows that the concentration of trace metals in sediments was characterised by slight variation and that the maximum values did not exceed: 1.1 mg·kg−1 for Cd, 8.7 mg·kg−1 for Cr, 10.9 mg·kg−1 for Cu, 7.7 mg·kg−1 for Ni, 12.9 mg·kg−1 for Pb and 52.3 mg·kg−1 for Zn. The analyses further showed that the concentration of trace elements in the sediment surface layer increased in the following order: Zn > Pb > Cu > Ni > Cr > Cd. The maximum pH value of H2O was 7.1, while that of KCl was 7.0. The maximum values of Corg, Ntot, P2O5, K2O and Mg were, respectively: 6.1 g·kg−1, 1.4 g·kg−1, 40.2 mg·100 g−1, 31.2 mg·100 g−1 and 35.1 mg·100 g−1. The assessment of the degree of lake pollution is essential for the conservation of biodiversity and the organisation of environmental management activities.

Analysis of Landscape Change and Its Driving Mechanism in Chagan Lake National Nature Reserve

Lake ecosystems play an important role in regional ecological security and the sustainable development of the economy and society. In order to study the evolution of landscape patterns and the main driving forces in the Chagan Lake Nature Reserve in recent years, we used landscape type data from 2005, 2010, 2015, and 2019 to study the characteristics of the regional landscape’s structural changes. At the same time, the spatial heterogeneity of the driving factors of landscape change was analyzed using the spatial analysis method, and the driving mechanism of landscape change was quantitatively analyzed. The results showed that: (1) from 2005 to 2019, the area of cultivated land, marshland, and water bodies increased, while the area of grassland and the area of bare land decreased. (2) The dominant patch types in the study area formed good connectivity, and the degree of landscape fragmentation increased. (3) In the past 15 years, there has been spatial heterogeneity in the regression coefficients of different driving factors of landscape change: the area with a greater influence of the elevation factor was in the south; the regression coefficient of precipitation showed the spatial distribution characteristics of highs in the west and lows in the east; the gross domestic product had a greater impact on the east and the south; the spatial variation of grain yield was mainly reflected in the southeast and northwest regions; the fishery yield gradually changed from high in the southeast and low in the northwest to the distribution characteristic of decreasing from the east to the southwest; the lake fluorine content showed a distribution pattern that gradually changed from high in the southeast and low in the northwest to high in the middle and low in the north and south; the distribution pattern of the distance to oil production changed from north to southeast to south to north; the distance to the road changed from high in the east and low in the west to the opposite spatial distribution pattern. (4) The interaction of precipitation and lake fluoride content with other factors showed a strong driving effect, which had a significant impact on the landscape change of Chagan Lake Nature Reserve. Since the study area is located in a typical fluorine-rich geochemical environment, human activities, such as the expansion of irrigation areas around Chagan Lake and groundwater exploitation, have accelerated the dissolution of fluorine-containing minerals, promoted the enrichment process of fluorine in Chagan Lake, and enhanced the explanatory power of lake fluorine content in terms of landscape changes. At the same time, the increase in precipitation during the study period is beneficial to the growth of vegetation and the storage of water in lakes, which promotes changes in landscape types such as grasslands and areas of water.

Utilization of Pollution Indices, Hyperspectral Reflectance Indices, and Data-Driven Multivariate Modelling to Assess the Bottom Sediment Quality of Lake Qaroun, Egypt

Assessing the environmental hazard of potentially toxic elements in bottom sediments has always been based entirely on ground samples and laboratory tests. This approach is remarkably accurate, but it is slow, expensive, damaging, and spatially constrained, making it unsuitable for monitoring these parameters effectively. The main goal of the present study was to assess the quality of sediment samples collected from Lake Qaroun by using different groups of spectral reflectance indices (SRIs), integrating data-driven (Artificial Neural Networks; ANN) and multivariate analysis such as multiple linear regression (MLR) and partial least square regression (PLSR). Jetty cruises were carried out to collect sediment samples at 22 distinct sites over the entire Lake Qaroun, and subsequently 21 metals were analysed. Potential ecological risk index (RI), organic matter (OM), and pollution load index (PLI) of lake’s bottom sediments were subjected to evaluation. The results demonstrated that PLI showed that roughly 59% of lake sediments are polluted (PLI > 1), especially samples of eastern and southern sides of the lake’s central section, while 41% were unpolluted (PLI < 1), which composed samples of the western and western northern regions. The RI’s findings were that all the examined sediments pose a very high ecological risk (RI > 600). It is obvious that the three band spectral indices are more efficient in quantifying different investigated parameters. The results showed the efficiency of the three tested models to predict OM, PLI, and RI, revealing that the ANN is the best model to predict these parameters. For instance, the determination coefficient values of the ANN model of calibration datasets for predicting OM, PLI, and RI were 0.999, 0.999, and 0.999, while they were 0.960, 0.897, and 0.853, respectively, for the validation dataset. The validation dataset of the PLSR produced R2 values higher than with MLR for predicting PLI and RI. Finally, the study’s main conclusion is that combining ANN, PLSR, and MLR with proximal remote sensing could be a very effective tool for the detection of OM and pollution indices. Based on our findings, we suggest the created models are easy tools for forecasting these measured parameters.

Environmental Pollution Indices and Multivariate Modeling Approaches for Assessing the Potentially Harmful Elements in Bottom Sediments of Qaroun Lake, Egypt

This research intends to offer a scientific foundation for environmental monitoring and early warning which will aid in the environmental protection management of Qaroun Lake. Qaroun Lake is increasingly influenced by untreated wastewater discharge from many anthropogenic activities, making it vulnerable to pollution. For that, six environmental pollution indices, namely contamination factor (Cf), enrichment factor (EF), geo-accumulation index (Igeo), degree of contamination (Dc), pollution load index (PLI), and potential ecological risk index (RI), were utilized to assess the bottom sediment and to determine the different geo-environmental variables affecting the lake system. Cluster analysis (CA), and principal component analysis (PCA) were used to explore the potential pollution sources of heavy metal. Moreover, the efficiency of partial least-square regression (PLSR) and multiple linear regression (MLR) were tested to assess the Dc, PLI, and RI depending on the selected elements. The sediment samples were carefully collected from 16 locations of Qaroun Lake in two investigated years in 2018 and 2019. Total concentrations of Al, As, Ba, Cd, Co, Cr, Cu, Fe, Ga, Hf, Li, Mg, Mn, Mo, Ni, P, Pb, Sb, Se, Zn, and Zr were quantified using inductively coupled plasma mass spectra (ICP-MS). According to the Cf, EF, and Igeo results, As, Cd, Ga, Hf, P, Sb, Se, and Zr demonstrated significant enrichment in sediment and were derived from anthropogenic sources. According to Dc results, all collected samples were categorized under a very high degree of contamination. Further, the results of RI showed that the lake is at very high ecological risk. Meanwhile, the PLI data indicated 59% of lake was polluted and 41% had PLI < 1. The PLSR and MLR models based on studied elements presented the highest efficiency as alternative approaches to assess the Dc, PLI, and RI of sediments. For examples, the validation (Val.) models presented the best performance of these indices, with R2val = 0.948–0.989 and with model accuracy ACCv = 0.984–0.999 for PLSR, and with R2val = 0.760–0.979 and with ACCv = 0.867–0.984 for MLR. Both models for Dc, PLI, and RI showed that there was no clear overfitting or underfitting between measuring, calibrating, and validating datasets. Finally, the combinations of Cf, EF, Igeo, PLI, Dc, RI, CA, PCA, PLSR, and MLR approaches represent valuable and applicable methods for assessing the risk of potentially harmful elemental contamination in the sediment of Qaroun Lake.

Assessment of Heavy Metal Pollution Levels in Sediments and of Ecological Risk by Quality Indices, Applying a Case Study: The Lower Danube River, Romania

It is a well–known fact that heavy metal pollution in sediments causes serious problems not only in the Danube basin, but also in the large and small adjacent river streams. A suitable method for assessing the level of heavy metals and their toxicity in sediments is the calculation of pollution indices. The present research aims to assess heavy metal pollution in the Lower Danube surface sediments collected along the Danube course (between 180 and 60 km) up to the point where the Danube River flows into the Danube Delta Biosphere Reserve (a United Nations Educational, Scientific and Cultural Organization—UNESCO, protected area). In addition, this monitored area is one of the largest European hydrographic basins. Five heavy metals (Cd, Ni, Zn, Pb, Cu) were analyzed in two different seasons, i.e., the autumn of 2018 and the spring of 2019, using the Inductively Coupled Plasma Mass Spectrometry (ICP– MS) technique. Our assessment of heavy metal pollution revealed two correlated aspects: 1. a determination of the potential risks of heavy metals in sediments by calculating the Potential Ecological Risk Index (RI), and 2. an evaluation of the influence of anthropogenic activities on the level of heavy metal contamination in the surface sediments, using three specific pollution indices, namely, the Geo–Accumulation Index (Igeo), the Contamination Factor (CF), and the Pollution Load Index (PLI). The results of this pioneering research activity in the region highlighted the presence of moderate metal (Ni and Cd) pollution and a low potential ecological risk for the aquatic environment.