Toxicity assessment of wood preservatives

The article describes the influence of wood preservatives on water bioceonosis. The “battery” of toxicology tests was used to cover luminescent bacteria test, algae growth inhibition test, crustacean and fish lethal tests. The test samples used were pure wood preservative and water after the wood preservative leaching from wood sample. It was observed that the wood preservative is leaching from the wood sample in 10% within 1 month of exposition. Achieved results indicate the necessity of toxic assessment of wood preservative after wood element protection.     

Dioxins and furans in biochars,hydrochars and torreficates produced by thermochemical conversion of biomass: a review

Converting raw biomass into valuable products protects the environment, improves economics, and helps tackle climate change by cutting resource demand and waste production. Thermochemical treatment is a common method for producing biochars, hydrochars and torreficates from biomass and organic wastes, which can also generate dioxins and furans and consequently limit the use of thermochemically converted chars. Here we review the presence of dioxins and furans in chars produced by hydrothermal carbonization, torrefaction, and pyrolysis processes under the influence of temperature, residence time, heating rate, pressure, and feedstock type. Dioxins and furans were mostly below 20 ng total toxic equivalence per kilogram (TEQ kg⁻¹), with the highest level of 113 ng TEQ kg⁻¹ found in over 100 samples of different char types. The most toxic products were hydrochars produced from sewage sludge. Processing temperature and feedstock type were key factors resulting in high dioxin levels in chars, and care should be taken when producing chars at temperatures up to 300 °C or using feedstocks previously contaminated with dioxins or preservatives.

     

Impact of environmental factors on the sampling rate of β-blockers and sulfonamides from water by a carbon nanotube-passive sampler

Passive techniques are a constantly evolving approach to the long-term monitoring of micropollutants, including pharmaceuticals, in the aquatic environment. This paper presents, for the first time, the calibration results of a new CNTs-PSDs (carbon nanotubes used as a sorbent in passive sampling devices) with an examination of the effect of donor phase salinity, water pH and the concentration of dissolved humic acids (DHAs), using both ultrapure and environmental waters. Sampling rates (R_s) were determined for the developed kinetic samplers. It has been observed that the impact of the examined environmental factors on the R_s values strictly depends on the type of the analytes. In the case of β-blockers, the only environmental parameter affecting their uptake rate was the salinity of water. A certain relationship was noted, namely the higher the salt concentration in water, the lower the R_s values of β-blockers. In the case of sulfonamides, water salinity, water pH 7–9 and DHAs concentration decreased the uptake rate of these compounds by CNTs-PSDs. The determined R_s values differed in particular when the values obtained from the experiments carried out using ultrapure water and environmental waters were compared. The general conclusion is that the calibration of novel CNTs-PSDs should be carried out under physicochemical conditions of the aquatic phase that are similar to the environmental matrix.     

Biodegradation of Kupferschiefer black shale organic matter (Fore-Sudetic Monocline, Poland) by indigenous microorganisms

This study provides the first evidence for the direct biodegradation of persistent organic matter extracted from the organic-rich polymetallic black shale ore Kupferschiefer, one of the most important sources of metals in the world. It was demonstrated that an enriched community of indigenous heterotrophic microorganisms isolated from black shale grown under aerobic conditions could utilize shale organic matter as the sole carbon and energy source. Colonization of shale organic matter was observed. The main biodegradation intermediates and products such as phosphonic acid dioctadecyl ester and isoindole-1,3 were detected in the aqueous phase of cultures. The bacterial community showed the ability to PAH biodegradation, assimilation of organic acids and esters as well as lipase activity. The intracellular accumulation of phosphorus by bacteria during growth on organic matter was confirmed. Strains within the genus Pseudomonas were found to dominate the bacterial population at the end of the experiment. The results of this study confirm that indigenous bacteria are likely to play a role in the biotransformation of black shale and can influence the geochemical cycles of ancient organic carbon in the deep terrestrial subsurface. This process may also occur in tailings ponds containing black shale, and cause the mobilization of potentially toxic compounds to the soil and groundwater.     

Removal of petroleum pollutants and monitoring of bacterial community structure in a membrane bioreactor

The long-term operational stability (159 d) in removal of organics and ammonia from synthetic wastewater was investigated. The experiment was carried out in two identical plug flow membrane bioreactors (MBR) (each with a submerged A4 Kubota membrane) operated under aerobic conditions. The vacuum distillate of a crude oil fraction in the emulsified state, which was used to model the petroleum pollutants, was added into the feed medium. The performance of biological treatment was evaluated by physicochemical analyses such as nitrogen forms, COD, and BOD. Additionally, monitoring of PAHs in the wastewaters was performed using HPLC-diode array detector. Moreover, the community structure of bacteria was analyzed by polymerase chain reaction-denaturing gradient gel electrophoresis. The MBR treatment was very effective with reduction by more than 90% of COD and Total Organic Carbon. Nearly complete removal of petroleum originated non-polar micropollutants was observed. The influence of the highest dosage of petroleum pollutants (1000 μLL(-1)) on the bacterial community was noted.     

Styrofoam debris as a potential carrier of mercury within ecosystems

The present paper falls within the trend of research into interactions between various pollutants emitted anthropogenically into the environment and focuses on mercury and styrofoam debris. The study covers part of the Southern Baltic’s drainage area. Apart from styrofoam and beach sand, the research involved mosses, which are bioindicators of atmospheric metal pollution. The research has shown that mercury present in the environment becomes associated with styrofoam debris. The median for mercury concentrations in virgin styrofoam samples (0.23 ng g^?1 dry weight (d.w.)) and in beach sand samples (0.69 ng g^?1 d.w.) was an order of magnitude lower than in the styrofoam debris (5.20 ng g^?1 d.w.). The highest mercury content observed in styrofoam debris (3,863 ng g^?1 d.w.) exceeded the standards for bottom sediment and soil. The binding of mercury to styrofoam debris takes place in water, and presumably also through contact with the ground. A significant role in this process was played by biotic factors, such as the presence of biofilm and abiotic ones, such as solar radiation and the transformations of mercury forms related to it. As a result, mercury content in styrofoam debris underwent seasonal changes, peaking in summertime. Furthermore, the regional changes of mercury content in the studied debris seem to reflect the pollution levels of the environment.     

Lead accumulation and elimination in tissues of Prussian carp, Carassius gibelio (Bloch, 1782), after long-term dietary exposure, and depuration periods

We studied the bioaccumulation of lead in selected tissues of Prussian carp Carassius gibelio (Bloch, 1782) during 12 and 24 months exposure to different doses of this metal in feed and the elimination of lead from tissues during the following 12-month depuration period. Lead concentration was determined using atomic absorption spectrometry method. The highest lead concentrations were observed at 2.0?±?0.54 to 7.4?±?1.1 mg?kg^?1 in the kidney, 3.0?±?0.13 to 5.2?±?0.17 mg?kg^?1 in the bone, and 4.5 (±0.4)?mg?kg^?1 in the hepatopancreas of fish from groups exposed to lead dietary concentration from 8 to 49 mg?kg^?1 for 24 months. The rate of accumulation were generally the highest at the beginning of exposure as evidenced by the highest monthly increments of bioaccumulation observed after 3 months of contamination for muscles, hepatopancreatic gland, intestine, and gills. Also analysis of the monthly increments of lead bioaccumulation in bone tissue and the highly significant coefficients of correlation indicate that the dynamics of accumulation are clearly dependent on dose of exposure. Depuration of accumulated lead from the organs depended mainly on tissue and duration of elimination period. Very rapid depuration was observed in soft tissues such as the intestine or muscles. Very low elimination was observed for scales and bones where until the end of the experiment highly significant lead concentration differences were observed in all groups in relation to the control group. Chronic dietary exposure in the range of 8–49 mg Pb?kg^?1 resulted in no significant effects on the growth and survival of Prussian carp females.     

Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study

The aims of this study are to create an artificial neural network (ANN) model using non-specific water quality parameters and to examine the accuracy of three different ANN architectures: General Regression Neural Network (GRNN), Backpropagation Neural Network (BPNN) and Recurrent Neural Network (RNN), for prediction of dissolved oxygen (DO) concentration in the Danube River. The neural network model has been developed using measured data collected from the Bezdan monitoring station on the Danube River. The input variables used for the ANN model are water flow, temperature, pH and electrical conductivity. The model was trained and validated using available data from 2004 to 2008 and tested using the data from 2009. The order of performance for the created architectures based on their comparison with the test data is RNN > GRNN > BPNN. The ANN results are compared with multiple linear regression (MLR) model using multiple statistical indicators. The comparison of the RNN model with the MLR model indicates that the RNN model performs much better, since all predictions of the RNN model for the test data were within the error of less than ±10 %. In case of the MLR, only 55 % of predictions were within the error of less than ±10 %. The developed RNN model can be used as a tool for the prediction of DO in river waters.