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

Identifying toxic elements in water, sediments, and roots of mangrove forest (Avicennia marina) in Chabahar Bay, Sea of Oman

Mangroves play a crucial role in filtering pollutants from water and sediments. However, excessive accumulation of potentially toxic elements (PTEs) has harmful effects on marine organisms. This article investigates the concentration and distribution of PTEs in water, sediment, and the roots of endangered mangrove species in Chabahar Bay, a subtropical coastal wetland. The relationship between PTE absorption and accumulation rates with flow rate, mangrove extent, and sedimentation was also explored. Water, sediments, and aerial roots samples were taken at four stations along the wetland from upstream fresh water toward outfall. According to the results, Cd had more distribution in sediment and water samples and plants did not play as adsorbent in the study area. The lowest and highest PTEs concentrations were detected in water and sediment media, respectively. The average concentrations of PTEs in the sediments in the Chabahar Bay were Fe > Cr > Zn > Ni > Cu > Pb > Co > As > Cd while in aerial roots of the mangroves were Fe > Zn > Ni > Cr > Cu > Co > As > Pb > Cd. Except Zn, As, and Cd, there was a good correlation between increasing PTEs content in the sediments with decreasing flow velocity and increasing vegetation density along stations 3 to 4. In addition, the amount of PTEs uptake by the mangroves was less than that of global wetlands. The results also demonstrated a greater uptake in aerial roots in saline water for Cr, Ni and Co. Since the absorption rate of PTEs by the aerial roots of pneumatophores is slower than that in sediments, elevated concentrations of PTEs in the sediment can disrupt the entire ecosystem, leading to a potential decline in biodiversity. These toxins can enter the food chain, affecting not only organisms directly interacting with the sediment but also higher trophic levels, such as fish and birds.

Relationship between nitrate, heavy metal, and sterols contents in Japanese agricultural soils with risk of groundwater pollution

In Japanese agricultural lands, nitrate-nitrogen contamination of soil and groundwater often occurs due to the application of livestock excrements and compost. Therefore, rural soils in Japan were sampled and analyzed for nitrate-nitrogen leaching, heavy metal content, and sterols associated with livestock excrement and compost to calculate contamination risk indicators. The results were analyzed using self-organizing maps and cluster analysis. Nitrate-nitrogen content using water extraction was detected in most of the sampled soils. In addition, many samples from areas that were already severely contaminated with nitrate-nitrogen showed particularly high concentrations. Coprostanol, an indicator of fecal contamination, was detected in more than half of the samples. The main source of nitrate-nitrogen contamination in these areas is livestock excrement and compost. Self-organization maps showed that areas with high nitrate-nitrogen contamination also corresponded to areas with high copper and zinc soil contents. The self-organization maps and cluster analysis resulted in five clusters: a nitrate-contaminated group mainly originating from livestock excrement and compost, a heavy metal-contaminated group, a general group, a nitrate-contaminated group mainly originating from chemical fertilizers, and a contaminated group with potentially hazardous substances requiring attention. Authorities and decision-makers can use the results to prioritize areas requiring remediation.

Advances in the integration of microalgal communities for biomonitoring of metal pollution in aquatic ecosystems of sub-Saharan Africa

This review elucidated the recent advances in integrating microalgal communities in monitoring metal pollution in aquatic ecosystems of sub-Saharan Africa (SSA). It also highlighted the potential of incorporating microalgae as bioindicators in emerging technologies, identified research gaps, and suggested directions for further research in biomonitoring of metal pollution. Reputable online scholarly databases were used to identify research articles published between January 2000 and June 2023 for synthesis. Results indicated that microalgae were integrated either individually or combined with other bioindicators, mainly macroinvertebrates, macrophytes, and fish, alongside physicochemical monitoring. There was a significantly low level of integration (< 1%) of microalgae for biomonitoring aquatic metal pollution in SSA compared to other geographical regions. Microalgal communities were employed to assess compliance (76%), in diagnosis (38%), and as early-warning systems (38%) of aquatic ecological health status. About 14% of biomonitoring studies integrated microalgal eDNA, while other technologies, such as remote sensing, artificial intelligence, and biosensors, are yet to be significantly incorporated. Nevertheless, there is potential for the aforementioned emerging technologies for monitoring aquatic metal pollution in SSA. Future monitoring in the region should also consider the standardisation and synchronisation of integrative biomonitoring and embrace the "Citizen Science" concept at national and regional scales.

A comparative study of the risk assessment and heavy metal contamination of coastal sediments in the Red sea, Egypt, between the cities of El-Quseir and Safaga

This study aimed to assess the influence of pollution on the quality of sediments and the risks associated with El-Qusier and Safaga Cities, Red Sea, Egypt, during 2021, divided into four sectors, using multiple pollution indices. To achieve that, we evaluated the metal pollution index (MPI), contamination factor (Cf), pollution load index (PLI), contamination security index (CSI), and anthropogenicity (Anp%). Moreover, carcinogenic and non-carcinogenic risks are used for human health hazards. Results indicated that Mn and Fe recorded the highest concentrations, whereas Cd had the lowest. El-Quseir City sediments were found the following metal ions: Fe > Mn > Ni > Zn > Cu > Co > Pb > Cd, where the order in the Safaga City was: Fe > Mn > Zn > Ni > Cu > Pb > Co > Cd. MPI > 1, this is alarming in the study area due to heavy metal pollution. In addition, Cf < 1 in all metals except Cd with contamination degree CD ranged from low to considerable contamination in El-Qusier city. In contrast, contamination ranged from significant to very high in Safaga city. PLI < 1 is lower than the reference at all monitored stations. CSI values ranged from relatively low to moderate. Besides Cd, data reflect each element's low environmental danger (EriMe40). This study's risk index (RI) is low to moderate in Sector 1 and high to extremely high in Sector 2. HQ and HI index < 1 means it is safe for human health in order: HI ingestion > HI dermal. CSR for different pathways was recorded as dermal > ingestion, in which total CSR for all paths is considered harmful, and the cancer risk is troublesome and higher than the reference ranges of 1 × 10-6-1 × 10-4. In conclusion, the examined heavy metals provide environmental hazards across the assessed locations.

Pollution indices of selected metals in tea (Camellia sinensis L.) growing soils of the Upper Assam region divulge a non-trifling menace of National Highway

The study investigated the influence of a National Highway (NH) traversing tea estates (TEs) on heavy metal (HM) contamination in the top soils of Upper Assam, India. The dispersion and accumulation of six HMs, viz. cadmium (Cd), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn), within tea-growing soils were assessed using diverse indices: contamination factor (CF), degree of contamination (DC), enrichment factor (EF), geo-accumulation index (Igeo), modified degree of contamination (MDC), Nemerow pollution index (PINemerow), pollution load index (PLI), potential ecological risk factor (Eri), and potential ecological risk index (RI). The order of HM prevalence was Fe > Mn > Zn > Ni > Cu > Cd. Elevated Cd levels near the NH prompted immediate attention, while Cd and Zn showed moderate pollution in CF, EF, and RI. The remaining metals posed minimal individual risk (Eri< 40), resulting in an overall contamination range of "nil to shallow," signifying slight contamination from the studied metals. From MDC values for investigated metals, it was found to be "zero to very low degree of contamination" at all locations except the vicinity of NH. Soil pollution, as determined by PLI, indicated unpolluted soils in both districts, yet PINemerow values indicated slight pollution. The statistical analysis revealed that there is a significant decrease in most of the indices of HM as the distance from NH increases. The application of multivariate statistical techniques namely Principal Component Analysis and Cluster Analysis showed the presence of three distinct homogenous groups of distances based on different indices. This investigation underscores NH-associated anthropogenic effects on TE soil quality due to HM deposition, warranting proactive mitigation measures.

The influence of climate changes on heavy metals accumulation in Alosa immaculata from the Danube River Basin

This research report provides a comprehensive overview of the historical trends in heavy metal concentrations in the Pontic shad (Alosa immaculata) populations from both the Danube River and the Black Sea, while also exploring the potential influence of global warming on metal accumulation. Through bibliometric modeling analysis, it reveals significant limitations in existing international research, particularly the lack of comprehensive data on the impact of hydroclimatic changes on heavy metal accumulation in Alosa immaculata. Recognizing the critical importance of studies on heavy metal bioaccumulation in Danube shad, this research underscores their significance in defining tolerance thresholds, quantifying the impact of toxic elements along the aquatic food chain, and enhancing the economic sustainability of ichthyofauna monitoring efforts. Furthermore, these studies contribute invaluable insights into the complex dynamics of aquatic ecosystems, offering essential decision-making support for optimizing commercial fishing management practices on the Danube and ensuring robust support systems for industrial fishing endeavors.

The environmental impact of heavy metals in sediments of main valleys in the eastern side of Mosul City, Iraq

Analyzing the geochemical changes in stream sediments can reveal important surface processes on Earth, like weathering, transportation, and cation exchange. The study area is located on the eastern side of Mosul, where valleys named Al-Rashediya, Al-Kharrazi, Al-Khosar, Al-Danffilli, and Al-Shor flow towards the Tigris River. These valleys' sediments contain diverse components like clay minerals, organic matter, iron oxides, carbonates, and heavy metals (H.M.s), either as part of these substances or adsorbed onto them. In this study, 36 sediment samples were gathered from these valleys. They underwent chemical analysis through X-ray fluorescence to ascertain their chemical constituents of major oxides. To understand the distribution of H.M.s in these sediments, correlation coefficient analysis and factor analysis were utilized. The study employed the geoaccumulation index (Igeo) and enrichment factor (E.F.) to evaluate sediment contamination. The results of Igeo ranged from Cr = 0.24 to 1.83, Ni = -0.92 to 0.77, Cu = -2.41 to 0.05, Zn = -1.83 to 0.89, Pb = -1.54 to 0.36, and As = -2.84 to 0.80. These findings suggest that the valley sediments are generally in the range of deficiency to minimal enrichment and moderate enrichment. However, Al-Danffilli Valley shows strong contamination levels for Cu, Zn, and Pb. The E.F. values for Cr = 3.63-12.50, Ni = 1.95-4.19, Cu = 0.69-12.36, Zn = 1.08-16.19, Pb = 1.25-62.16, and As = 0.60-1.79 indicate levels ranging from deficiency to minimal and moderate enrichment. Al-Danffilli Valley, in particular, was identified as ranging from moderate to extremely high enrichment, attributed to its location near industrial areas and its tributaries.

High resolution dissolved heavy metals in sediment porewater of a small estuary: Distribution, mobilization and migration

Identifying the distribution features, mobilization mechanisms and migration processes of heavy metals (HMs) in estuarine sediments is essential to predict their potential toxicity risk and for following contamination remediation. In this study, high-resolution dialysis (HR-Peeper) and a sequential extraction procedure were employed to determine the porewater dissolved iron (Fe), manganese (Mn), arsenic (As), chromium (Cr), vanadium (V), selenium (Se), molybdenum (Mo), nickel (Ni), zinc (Zn) and their geochemical species fractions in sediments of the Xixi River Estuary, Xiamen, China. The results showed that at estuarine sites with high TOC and TS content, sulfate reduction is the main diagenetic pathway of OC degradation and directly inhibits the reduction of Fe/Mn oxides. The mobility of most HMs in porewater profiles was influenced by multiple factors, such as the adsorption-desorption by Fe/Mn oxides, HM-sulfide co-precipitation, and the degradation of OM under different redox conditions. However, no environmental correlation and control factors of Ni and Zn have been found. In addition, the profile-averaged distribution of most HMs showed a seaward increasing trend, probably due to the severe industrial wastewater discharge and increasing salinity responsible for the competitive adsorption of HM ions. The overall positive fluxes of all HMs, together with the higher positive diffusion fluxes of some HMs such as Mn, Cr, V and Zn, suggest that the HMs mobility in small estuarine sediments should be seriously reconsidered due to its high contamination potential.

Investigating the impacts of heavy metal(loid)s on ecology and human health in the lower basin of Hungary's Danube River: A Python and Monte Carlo simulation-based study

This study aimed to determine the environmental and health risks of the heavy metal levels in the Danube River in Hungary. The metals, including Fe, Mn, Zn, Cu, Ni, Cr, Pb, and As, were measured in the period from 2013 to 2019. The Spearman correlation and heatmap cluster analysis were utilized to determine the origin of pollution and the factors that control surface water quality. Several indices, such as the heavy metal pollution index (HPI), metal index (MI), hazard quotient oral and dermal (HQ), hazard index oral and dermal (HI), and carcinogenic risk (CR), were conducted to evaluate the potential risks for the environment and human health. The values of the HPI were between the range of 15 < HPI < 30, which indicated moderate pollution; however, the MI results showed high pollution in Dunaföldvár and Hercegszántó cities. The ecological risk (RI < 30) and HI values (< 1) showed low environmental risks and non-carcinogenic impacts of the existing metals, either on adults or children. The mean CR value of oral arsenic was 2.2E-04 and 2.5E-04 during April-September and October-March, respectively, indicating that children were the most vulnerable to arsenic-carcinogenic oral effects. While lead's CR oral values for children during April-September exceeded the threshold of 1.0E-04, chromium's oral and dermal CR values for both adults and children were 2.08E-04, 6.11E-04, 1.97E-04, and 5.82E-04 during April-September and October-March, respectively. These results demonstrate the potential carcinogenic risks related to chromium exposure within the two pathways in Hungary and highlight the need for effective measures to mitigate these risks.

Human health risk assessment of potentially toxic elements and microplastics accumulation in products from the Danube River Basin fish market

The present study aimed to quantify the concentration levels of potentially toxic elements (PTEs) such as aluminum, arsenic, cadmium, chromium, copper, nickel, lead, zinc, and mercury, as well as microplastics occurrence in various tissues of fish and seafood species, commercialized in the Lower Danube River Basin. A health risk assessment analysis was performed based on the PTEs concentration levels in the muscle tissue. Estimated daily intake (EDI), target hazard quotient (THQ), hazard index (HI), and target cancer risk (TR) of PTEs were calculated. It was observed that the species within the seafood category registered the highest levels of PTEs. For instance, in the muscle tissue of bivalve Mytilus galloprovincialis (from the Black Sea), the highest value was observed in the case of Zn (37.693 mg/kg), and the presence of polystyrene polymer was identified. The values associated with EDI, THQ, HI, and TR of PTE exposure were significantly lower than 1.

Assessing and forecasting water quality in the Danube River by using neural network approaches

The health and quality of the Danube River ecosystems is strongly affected by the nutrients loads (N and P), degree of contamination with hazardous substances or with oxygen depleting substances, microbiological contamination and changes in river flow patterns and sediment transport regimes. Water quality index (WQI) is an important dynamic attribute in the characterization of the Danube River ecosystems health and quality. The WQ index scores do not reflect the actual condition of water quality. We proposed a new forecast scheme for water quality based on the following qualitative classes very good (0-25), good (26-50), poor (51-75), very poor (76-100) and extremely polluted/non-potable (>100). Water quality forecasting by using Artificial Intelligence (AI) is a meaningful method of protecting public health because of its possibility to provide early warning regarding harmful water pollutants. The main objective of the present study is to forecast the WQI time series data based on water physical, chemical and flow status parameters and associated WQ index scores. The Cascade-forward network (CFN) models, along with the Radial Basis Function Network (RBF) as a benchmark model, were developed using data from 2011 to 2017 and WQI forecasts were produced for the period 2018-2019 at all sites. The nineteen input water quality features represent the initial dataset. Moreover, the Random Forest (RF) algorithm refines the initial dataset by selecting eight features considered the most relevant. Both datasets are employed for constructing the predictive models. According to the results of appraisal, the CFN models produced better outcomes (MSE = 0.083/0,319 and R-value 0.940/0.911 in quarter I/quarter IV) than the RBF models. In addition, results show that both the CFN and RBF models could be effective for predicting time series data for water quality when the eight most relevant features are used as input variables. Also, the CFNs provide the most accurate short-term forecasting curves which reproduce the WQI for the first and fourth quarters (the cold season). The second and third quarters presented a slightly lower accuracy. The reported results clearly demonstrate that CFNs successfully forecast the short-term WQI as they may learn historic patterns and determine the nonlinear relationships between the input and output variables.

Detection of reed using cnn method and analysis of the dry reed (phragmites australis) for a sustainable lake area

BACKGROUND

Common reed (Phragmites australis L.) is a highly productive wetland plant and a possible valuable resource of renewable biomass worldwide. For a sustainable management the exploitation of reed is beneficial because the increasing demand for sustainable biomass which presents reed bed areas and wetlands. Knowing the properties of plant biomass obtained from reeds is essential both for the effect on combustion equipment and for the impact on the environment. Brates Lake, situated in Galati, Romania is a natural watershed with reed plantations.

RESULTS

We used the convolutional neural network method combined with the cropped image techniques represent a powerful tool for high-precision image-based biomass detection in lake areas. The study aimed to investigate the morphological and chemical parameters through SEM-EDX analysis and pH, conductivity, nitrate anion, nitrite anion, total nitrogen, sulphate anion, sulphide anion, phosphate anion concentrations were determined from reed extract. The samples have a moderately acidic reaction pH 4.91-4.98. The number of soluble salts in the reed extract is in the range of 3.24-4.70 g/L, the values are within normal limits, providing the plant with the necessary nutrients.

CONCLUSIONS

This is the first time that neural networks are used for the detection and prediction of areas at risk for biodiversity (reduction of water gloss until it disappears, imbalances caused by keeping reeds dry in water) caused by the aggressive and uncontrolled growth of reeds.

Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia

Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (I_geo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using I_geo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.

Chemical speciation and bioavailability of potentially toxic elements in surface sediment from the Huaihe River, Anhui Province, China

In order to understand the characteristics of speciation and ecological risk of potentially toxic element (PTE) pollution in the surface sediment of huaihe river (Anhui province), 23 surface sediment samples were collected. The occurrence characteristics of PTEs (As, Cr, Zn, Cu, Cd, Pb, Mn) were analyzed by modified continuous extraction method (BCR), and the pollution status and potential ecological risk of PTEs were comprehensively evaluated by Pollution Load Index (PLI), Geoaccumulation Index (Igeo), Enrichment Factor (EF) and the risk assessment code (RAC). Results showed that the total concentrations of As, Mn, Cd, Cr, Cu, Pb, and Zn in sediment were 14.98 ± 2.32, 936.02 ± 144.48, 0.32 ± 0.08, 161.73 ± 124.83, 40.44 ± 9.67, 15.46 ± 6.67, and 74.85 ± 26.43 mg/kg, respectively. The mean concentrations of PTEs with the increasing order of Zn < Mn < Cr < Pb < Cu < As < Cd. Most PTEs appeared to mainly associate with a dominant proportion of residual fraction suggesting lower mobility whereas Cd and Mn presented a relative higher exchangeable fraction indicating a great degree of bioavailability and easily ingested by aquatic organism. Results of pollution degree showed that 3 sampling sites belong to the pollution degree of strong pollution, and the other sampling sites belonged to the medium pollution level. The indexes EF revealed moderately enrichment of Cr, minor enrichment of Cd, Mn and As, no enrichment of Cu, Zn and Pb. The values of the Igeo and RAC demonstrated that Cd and Mn pose a high ecological risk, which deserves further attention.

Ecological and Health Risk Assessments of Heavy Metals Contained in Sediments of Polish Dam Reservoirs

This study aimed at investigating the distribution of heavy metals (HMs: Zn, Pb, Cd, Ni, Cr, and Cu) in the bottom sediments of 28 reservoirs covered area of Poland. The paper evaluates the pollution of sediments with HMs and their potential toxic effects on aquatic organisms and human health on the basis of results provided by the Chief Inspectorate of Environmental Protection in Poland. The average concentrations of HMs in the bottom sediments of the reservoirs were as follows: Cd < Ni < Cr < Cu < Pb < Zn. (0.187, 7.30, 7.74, 10.62, 12.47, and 52.67 mg∙dm−3). The pollution load index values were from 0.05 to 2.45. They indicate contamination of the bottom sediments in seven reservoirs. The contamination-factor values suggest pollution with individual HMs in 19 reservoirs, primarily Cr, Ni, Cu, and Pb. The analysis showed that only two reservoirs had the potential for toxic effects on aquatic organisms due to high concentrations of Cd and Pb. The hazard index values for all the analyzed HMs were less than one. Therefore, there was no non-carcinogenic risk for dredging workers. The reservoirs were divided into two groups in terms of composition and concentration values. Reservoirs with higher concentrations of HMs in bottom sediments are dispersed, suggesting local pollution sources. For the second group of reservoirs, HMs’ concentrations may be determined by regional pollution sources. The analysis showed that Pb, Zn, and Cd concentrations are higher in older reservoirs and those with higher proportions of artificial areas in their catchments. Concentrations of Ni, Cu, and Cr are higher in reservoirs in south Poland and those with higher Schindler’s ratios.

Ecological risk assessment and sources identification of heavy metals in surface sediments of a river-reservoir system

Heavy metal contamination of river water and sediments is a global issue affecting ecological health. To reveal heavy metals' ecological risks and biological toxicity in the middle and lower Han River (MLHR), sediment samples collected in this area were analyzed based on a modified ecological risk assessment method (NIRI) and a biological toxicity assessment method. Also, Spearman correlation analysis and Positive Matrix Factorization (PMF) methods were applied to identify the potential sources of heavy metals. The results indicated that the heavy metal content significantly exceeded the background concentrations in Hubei Province. The average potential risk of heavy metals at sampling sites was: Cd > Hg > As > Pb > Cu > Zn. Consequently, high biological toxicity occurred along the MLHR due to the heavy metal enrichment. River damming and water diversion significantly enhanced the hydrologic regime variations and ecological risk in the MLHR. Moreover, two possible pollution sources of the MLHR were identified: one is a combined source of traffic pollution, agricultural pollution, and partial industrial pollution consisting of five heavy metals, Pb, Hg, Zn, Cu, and As, the other is an industrial pollution source dominated by Cd and As. This study provides insights into sediment heavy metal pollution management and ecological risk control in the MLHR and similar rivers worldwide.

Risks Assessment of Potentially Toxic Elements’ Contamination in the Egyptian Red Sea Surficial Sediments

The potential impact of tourism, industrial, and urban activities on Egypt’s Red Sea coastline, which is well-known for its economic and environmental importance, was investigated at fifteen coastal sites. In the present study, the concentration of cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn) in marine sediments from these sites, was determined using Inductively Coupled Plasma Mass Spectrometers (ICP-MS). In detail, various pollution indices, statistical analyses, and spatial distribution patterns were used to assess the pollution status, impacts of human activities, ecological risks, and sources of potentially toxic elements (PTEs) in surface marine sediment. A detailed comparison with up-to-date data was conducted. These sediments were composed predominantly of fine and very fine sands. Mean grain size distribution typically depends on the source of the sediment from the following two prime sources: terrigenous (autochthonous) and biogenic (allochthonous). The detected PTE mean concentrations were as follows: Fe > Mn > Zn > Cr > Ni > Pb > Co > Cu > Cd. Multivariate statistical analysis results revealed their close distribution and association. Cd and Pb levels in the studied area have been slightly impacted by anthropogenic inputs. According to the calculated pollution indices, although a minimal or moderate contamination degree was detected in the study area, it was determined that there was a low to moderate ecological risk. The slightly high degree of contamination and risk centered in the middle of the study area around phosphate mining and related activities. More attention should be given to the concentrations and sources of Cd, Ni, and Pb as the main pollution factors.

Physiological Aspects of Absorption, Translocation, and Accumulation of Heavy Metals in Silphium perfoliatum L. Plants Grown in a Mining-Contaminated Soil

Soil pollution by heavy metals as a result of mining activities is increasingly taking place. Once accumulated in soil, the heavy metals can then be dispersed, with serious effects on the environment and human health. It is therefore necessary to minimize, or even remove, all heavy metals from polluted areas, and one of the environmentally friendly and sustainable methods to do so is phytoremediation. A greenhouse pots experiment was conducted to evaluate the phytoremediation capacity of Silphium perfoliatum L. plants, in the vegetative growth stages, on a soil polluted with Cu, Zn, Cr and Pb, taken from a former mining area compared to an unpolluted soil (Us). The initial heavy metal content of polluted soil (Ps) was 208.3 mg kg−1 Cu; 312.5 mg kg−1 Zn; 186.5 mg kg−1 Cr and 195.2 mg kg−1 Pb. This shows that for Cu and Pb, soil concentrations exceed the intervention threshold, and for Zn and Cr, they are above the alert threshold. The removal efficiency, bioaccumulation factor, translocation factor, metal uptake and contamination factor index of Cu, Zn, Cr and Pb by S. perfoliatum L. were quantified to determine the bioremediation success. The data show that plants grown in Ps accumulated a significantly higher amount of Cu by 189% and Zn by 37.95% compared to Us. The Cr and Pb content of the plants recorded a progressive and significant increase from one developmental stage to another, being more intense between three and five leaves.

Effectiveness and Characterization of Novel Mineral Clay in Cd2+ Adsorption Process: Linear and Non-Linear Isotherm Regression Analysis

The excellent adsorption properties of clay minerals make the optimization of heavy metal removal the subject of numerous research projects. In the present study, ASLAVITAL cosmetic clay (ACC) powder was applied for the removal of Cd2+ from water. The main deposit of ACC clay is the Pădurea Craiului Mountains in Romania. A wide range of morpho-structural approaches (SEM, EDX, FTIR, Raman, XRD) were used to characterize the morphology and elemental composition of the adsorbent. As expected for clay minerals, Al (Wt(%) = 11.4 ± 0.9) and Si (Wt(%) = 13.7 ± 1.4) are the main constituents of ACC. After adsorption, Wt(%) = 0.2 ± 0.01 Cd2+ was detected in the sample. As proved before, the initial metal concentration is the primary influencing factor; therefore, batch adsorption of 10–160 mg/L Cd2+ was investigated. After 190 min, an efficiency of 99% was reached, and the quantity in equilibrium increased from 1–8 mg/g. The best fit in linear form was obtained for the Langmuir II. model, where R2 = 0.954 (RL = 0.037–0.027). Based on linear isotherm models, physical bonds formed between ACC and Cd2+ during the favorable adsorption. For the non-linear fits, the Liu model proved to be the best R2 = 0.965, χ2 = 1.101. Pseudo-II-order kinetic model described the experimental data R2 = 0.988–0.999; qexp and qcalc were almost identical (the differences ranged 0.03–0.34).

Nutrients, Organic Matter, and Trace Elements in Lake Gusinoe (Transbaikalia)

Lake Gusinoe is the second largest freshwater lake in Transbaikalia. Lakes serve as a source for drinking water, irrigation, and as a water source for the electricity, aquatic production, and tourism industry. Currently variations of content nutrients and organic matter differ in different areas of the lake. The content of total nitrogen, phosphorus, organic matter, and dissolved oxygen are distinguished more than 1.2–2.0 times. In accordance with the behavior of elements in the water, three groups of elements can be distinguished. The first group of elements, including Li, Ga, Ge, As, Rb, Sr, Mo, Cd, W, and U, were directly correlated with variations of major elements. The first group of elements showed decreasing concentrations with an increasing amount of total dissolved salt (TDS). The second group of elements, including Fe, Y, Nb, Th, and REE, were correlated oppositely with variations of TDS. The behavior of the third group of elements, including Mn, Zn, Ni, Cu, and Pb, decoupled with TDS. The value of the Eu anomaly was positively correlated with TDS. The water of Lake Gusinoe was extremely enriched by W, Mo, V, U, Li, Sr, and Ga; moderately by Ni, Cu, Ge, As, Rb, Cd, and Pb; and minimally by Al, Cr, Mn, Fe, Co, Zn, Y, Th, and REE.

Emerging and Persistent Pollutants in the Aquatic Ecosystems of the Lower Danube Basin and North West Black Sea Region—A Review

The tremendous impact of natural and anthropogenic organic and inorganic substances continuously released into the environment requires a better understanding of the chemical status of aquatic ecosystems. Water contamination monitoring studies were performed for different classes of substances in different regions of the world. Reliable analytical methods and exposure assessment are the basis of a better management of water resources. Our research comprised publications from 2010 regarding the Lower Danube and North West Black Sea region, considering regulated and unregulated persistent and emerging pollutants. The frequently reported ones were: pharmaceuticals (carbamazepine, diclofenac, sulfamethoxazole, and trimethoprim), pesticides (atrazine, carbendazim, and metolachlor), endocrine disruptors—bisphenol A and estrone, polycyclic aromatic hydrocarbons, organochlorinated pesticides, and heavy metals (Cd, Zn, Pb, Hg, Cu, Cr). Seasonal variations were reported for both organic and inorganic contaminants. Microbial pollution was also a subject of the present review.