Investigating toxic metal levels in popular edible fishes from the South Durban basin: implications for public health and food security

Contamination of the ocean by heavy metals may have ecosystem-wide implications because they are toxic even if present in trace levels, and the relative ease of their bioaccumulation by marine organisms may affect human health, primarily through consumption of contaminated fish. We evaluated metal concentrations in six different popular edible fish species and estimated the potential health risks from consumption of contaminated fish. There was no correlation between fish length and average metal accumulation although the fish species tended to accumulate significantly more Al and Zn (P?<?0.05) than any of the other metals. Significantly higher Mn concentrations were found in fish gills compared to other body parts in all fish species. Bronze seabream, Catface rockcod, and Slinger seabream had significantly higher mean Cr concentration in the liver than in either the tissues or gills. The highest concentration of Zn in fleshy tissue was in Horse mackerel (56.71 μg g^?1) followed by Bronze seabream (31.07 μg g^?1). Al levels ranged from 5.6 μg g^?1 in Atlantic mackerel to 35.04 μg g^?1 in Horse mackerel tissue while Cu and Cr concentrations were highest in the tissues of Horse mackerel (6.83 and 1.81 μg g^?1, respectively) followed by Santer seabream (3.15; 1.09 μg g^?1) and Bronze seabream (3.09; 1.30 μg g^?1), respectively. The highest tissue concentration of Mn was detected in Bronze seabream (8.23 μg g^?1) followed by Catface rockcod (6.05 μg g^?1) and Slinger seabream (5.21 μg g^?1) while Pb concentrations ranged from a high of 8.44 μg g^?1 in Horse mackerel to 1.09 μg g^?1 in Catface rockcod. However, the estimated potential health risks from fish consumption as determined by the target hazard quotient (THQ) and hazard index (HI) were significantly lower than 1, implying that metals were not present in sufficiently high quantities to be of any health and/or food and security concern in the studied fishes.     

Spatial distribution characteristics of soil organic carbon in subtropical forests of mountain Lushan,China

The study on the spatial distribution of forest soil organic carbon (SOC) is of great significance for accurate assessment of carbon storage in forest ecosystems. In the present study, by taking eight kinds of forest soils of Mountain Lushan in the subtropical area as the research object, we studied the spatial distribution characteristics of SOC in this mountainous area. The results showed that the SOC content and SOC density (SOCD) of main forest types in the Mountain Lushan were lower than the national and the world average. The soil layer of Lushan forest was thinner, and the SOC and active SOC (ASOC) contents of different forest types and SOCDs are the highest in the surface soil. SOCD of the topsoil accounts for 32.64–54.03% of the total SOCD in the whole soil profile. Surface litter is an important source of SOC, and the different vegetation types are the important reason for the different spatial distribution of SOC in this area. Soil SOC contents in the high-altitude forest (bamboo forest, deciduous broadleaf forest, Pinus taiwanensis forest, evergreen-deciduous forest, and coniferous-broadleaved mixed forest) were higher than those in the low-altitude forest (evergreen broadleaf forest, shrub, and Pinus massoniana forest). However, the difference in SOC content exhibited at the altitude gradient is significantly lower than that in SOC in the soil profile. This indicates that both soil depth and elevation are the important factors that affected SOC distribution. However, the influence of soil depth on spatial distribution of SOC may be more complex than that of altitude. Vegetation types and soil properties are the main reasons for the large differences of reduction rate in the contents of SOC and ASOC.     

Real<Emphasis Type="Bold">-</Emphasis>time water quality monitoring using Internet of Things in SCADA

Water pollution is the root cause for many diseases in the world. It is necessary to measure water quality using sensors for prevention of water pollution. However, the related works remain the problems of communication, mobility, scalability, and accuracy. In this paper, we propose a new Supervisory Control and Data Acquisition (SCADA) system that integrates with the Internet of Things (IoT) technology for real-time water quality monitoring. It aims to determine the contamination of water, leakage in pipeline, and also automatic measure of parameters (such as temperature sensor, flow sensor, color sensor) in real time using Arduino Atmega 368 using Global System for Mobile Communication (GSM) module. The system is applied in the Tirunelveli Corporation (Metro city of Tamilnadu state, India) for automatic capturing of sensor data (pressure, pH, level, and energy sensors). SCADA system is fine-tuned with additional sensors and reduced cost. The results show that the proposed system outperforms the existing ones and produces better results. SCADA captures the real-time accurate sensor values of flow, temperature, and color and turbidity through the GSM communication.     

Silver near municipal wastewater discharges into western Lake Ontario,Canada

Because of the widespread use of silver nanoparticles in commercial products, discharges of municipal wastewater may be a point source of silver in the aquatic environment. We monitored two sites in western Lake Ontario impacted by discharges from wastewater treatment plants serving the City of Toronto. Concentrations of silver were elevated in bottom sediments and suspended sediments collected at the two sites. We also deployed two types of passive samplers in the water column at the two sites, the newly developed Carbon Nanotube Integrative Samplers for monitoring “CNIS-labile” silver and Diffusive Gradient in Thin Film samplers for monitoring “DGT-labile” silver. Results from these passive samplers indicated that the concentrations of silver at the two sites were either below detection limits or were in the ng/L range. In laboratory experiments where the sediments were re-suspended in Milli-Q water, a small proportion of the silver (i.e., <?25%) was labile and partitioned as colloidal or dissolved silver into the liquid phase after agitation. Nanoparticles tentatively identified as silver nanoparticles were detected by single-particle ICP-MS in suspension after agitation of both suspended and bottom sediments. Therefore, there is a need to assess whether silver species, including silver nanoparticles are transported from wastewater treatment plants into sediments in the aquatic environment. This study is unique in focusing on the in situ distribution of silver in natural waters and in sediments that are potentially impacted by urban sources of nanoparticles.     

Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: a case study Coruh River Basin

In this study, the water quality of the Coruh River Basin, which is located in the Eastern Black Sea Region of Turkey, was evaluated. The water quality data measurement results obtained by the State Hydraulic Works 26th Regional Directorate from four different sites over a course of 4 years between the years 2011 and 2014 in the Coruh River Basin were used as the data. In this study, the water quality was evaluated by using the Canadian Council of Ministers of the Environmental Water Quality Index (CCME WQI) method and discriminant analysis (DA). The water quality of the Coruh River Basin was calculated as 30.4 and 71.35 by using the CCME WQI and classified as “poor,” “marginal,” and “fair”. These values show that the water of the Coruh River Basin is degraded and under threat and its overall quality is not close to natural or desired levels. The monitoring sites were divided into two groups by the cluster analysis (CA). DA is a multivariate analysis technique used to divide individuals or objects into different groups and assign them into predetermined groups. As a result of DA, calcium (Ca) and sulfate (SO₄) were determined to be significant parameters in the determination of the water quality of the Coruh River Basin. The success of DA depends on the percentage of correct classification. As a result of the analysis, 23% of the parameters in the first measurement point, 69.2% of the parameters in the second and third measurement points, and 76.9% of the parameters in the fourth measurement point were classified correctly. Since the second measurement point is the discharge point of a copper mine, it can be said that the water quality parameters measured may provide accurate results in detecting pollution at this point.     

Relationships between aquatic invertebrate communities,water-level fluctuations and different habitats in a subtropical lake

In lakes, the littoral habitat and its invertebrate communities are often exposed to water-level fluctuations. We examined the effects of seasonal changes on water level, substrata availability and benthic fauna in the littoral zone of Peri Lake, a shallow lake that has experienced a strong reduction in water level due to changes in rainfall. In this study, we also examined whether the abundance and composition of aquatic invertebrates differed among the four substrata. Our main objective was to assess the effect of seasonal changes on water level and benthic invertebrates inhabiting the different types of substrata. Benthic invertebrates were sampled four different substrata (Schoenoplectus californicus, sand and stones, allochthonous leaf litter, and macrophyte stands), and we also measured meteorological, physical and chemical variables. We found that complex habitats, such as allochthonous leaf litter and aquatic macrophyte, stand to be colonised by a larger number of macroinvertebrates because they provide more habitats or potential niches for colonisation by different species. In addition, we observed that during periods of low water level, the presence of substrata in the littoral zone decreased, as did the associated biota. Therefore, our results suggest that water level changes have a major functional impact on the littoral zone of the lake, and can affect substratum availability, which also impacts invertebrate communities.     

Treatment technologies for PAH-contaminated sites: a critical review

To reduce environmental and human health risks of contaminated sites, having a comprehensive knowledge about the polycyclic aromatic hydrocarbon (PAH) removal processes is crucial. PAHs are contaminants which are highly recognized to pose threats to humans, animals, and plants. PAHs are hydrophobic and own two or more benzene rings, and hence are resistant to structural degradation. There are various techniques which have been developed to treat PAH-contaminated soil. Four distinct processes to remove PAHs in the contaminated soil, thought to be more effective techniques, are presented in this review: soil washing, chemical oxidation, electrokinetic, phytoremediation. In a surfactant-aided washing process, a removal rate of 90% was reported. Compost-amended phytoremediation treatment presented 58–99% removal of pyrene from the soil in 90 days. Chemical oxidation method was able to reach complete conversion for some PAHs. In electrokinetic treatment, researchers have achieved reliable results in removal of some specific PAHs. Researchers’ innovations in novel studies and advantages/disadvantages of the techniques are also investigated throughout the paper. Finally, it should be noted that an exclusive method or a combination of methods by themselves are not the key to be employed for remediation of every contaminated site but the field characteristics are also essential in selection of the most appropriate decontamination technique(s). The remedy for selection criteria is based on PAH concentrations, site characteristics, costs, shortcomings, and advantages.     

Intra-monsoonal variation of zooplankton population in the Sundarbans Estuarine System,India

The present study was conducted during July 2013 (early phase of monsoon or EM) and September 2013 (later phase of monsoon or LM) to ascertain the intra-monsoonal variation on zooplankton, by selecting 15 study stations in the river Saptamukhi, one of the main estuaries in the Sundarbans Estuarine System (SES). In 2013, SES experienced an unusually high monsoonal rainfall also exacerbated by cloud burst event at Himalayan region (upper stretches of SES) which tremendously increased the river runoff. The present work was aimed to decipher the effect of this unusual precipitation during the monsoon season on zooplankton assemblages along with different hydrological parameters. The abundance of zooplankton was recorded as lower during EM compared to LM. Altogether, 56 zooplankton taxa were identified with copepods forming the predominant population. Thirty-three copepod species were reported with 25 calanoid species forming the bulk of the biomass followed by 5 and 3 species of cyclopoids and harpacticoid, respectively. A combination of multivariate cluster analysis, biotic indices, and canonical correspondence analysis revealed noticeable alterations in the zooplankton community structure across the spatio-temporal scale. Furthermore, significant intra-monsoonal changes in zooplankton population correlated with several hydrological parameters were clearly noticed. Paracalanus parvus, Bestiolina similis and Oithona similis were observed to be the most dominant copepod species in both sampling periods. The result of the present study provides new insight on estuarine zooplankton community after unusual rainfall during monsoon season, and provides further evidence to support the conservation and management of the SES ecosystem.     

Reservoir water quality: a case from Jordan

Jordan relies heavily on reservoirs building and development to cope with water supply challenges, where monitoring and assessment of reservoir water quality are critically important for the sustainable use of these water supplies. Mujib Dam is an important water supply source in central western Jordan. Evaluation of water quality parameters and their spatial distributions (vertical and horizontal) showed near-neutral pH values with nearly similar values from surface to bottom. The vertical profile of DO and TDS in the dammed reservoir showed slight decreasing trends with increasing depth. Although Ca, Mg, Na, and K concentrations varied slightly with depths, their variations showed no trends. Similarly, the vertical and horizontal distribution patterns of Cl, SO₄, HCO₃, NO₃, and PO₄ in Mujib reservoir water showed insignificant variations in surface water layer and relatively unchanged values or decreasing trends through the water column. Higher values of TN have been observed, especially in the western part, suggesting that agricultural activities and livestock farming in the upstream catchment are impacting water quality. Results revealed that weathering and dissolution of rocks are the major source of water chemistry. The majority of trace metal levels (Cd, Cr, Cu, Fe, Mn, Pb, Zn, Co, Ni, Sr, and B) in water showed relatively similar surface and bottom values. The concentrations of COD and BOD₅ in surface water were relatively low with higher concentrations observed in the northwestern corner, coincided with higher levels of chlorophyll a. The average ratio of TN to TP in surface water suggests that phosphorus is the limiting factor for the algal blooms, whereas the average chlorophyll a level in surface water indicates oligo-mesotrophic water.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.