Archives of Environmental Protection

Ligninolytic enzymes are employed for the production of second-generation biofuel to minimize fuel crisis. Additionally, they play a crucial role in global carbon cycle and a variety of applications in food, agriculture, paper and textile industries. On a large scale production of ligninolytic enzymes, microorganisms can be cultured on lignocellulosic wastes. In the present study, proximate analysis including acid detergent lignin (ADL), acid detergent cellulose (ADC), acid detergent fi ber (ADF) and acid insoluble ash (AIA) were performed for Platanus orientalis (chinar), Bauhinia variegata (orchid tree), Pinus roxburghii (chir pine), wheat straw and wheat husk. Platanus orientalis was selected as substrate because of higher lignin contents for the production of ligninolytic enzymes by Aspergillus flavus. Solid State Fermentation was used and Response Surface Methodology was employed for optimizing various parameters and enzymes production. Maximum production was achieved at temperature 32°C, fermentation period 120 hours, pH 4.5, inoculums size 3.5 mL, substrate mesh size 80 mm, substrate size 7 g. Maximum purifi cation of laccase, manganese peroxidase (MnP) and lignin peroxidase (LiP) was achieved with 50%, 60% and 40% ammonium sulfate respectively and it was enhanced by gel filtration chromatography. Characterization of enzymes shows that Laccase has 35°C optimum temperature, 4.5 pH, 0.289 mM Km and 227.27 μM/ml Vmax. Manganese peroxidase has 30°C optimum temperature, 5.5 pH, 0.538 mM Km and 203.08 μM/ml Vmax. Lignin peroxidase has 30°C optimum temperature, 3 pH, 2 mM Km and 2000 µM/ml Vmax. Protein concentrations found in crude extracts and partially purified enzymes are respectively: laccase 1.78 and 0.71 mg/ml, MnP 1.59 and 0.68 mg/ml. LiP, 1.70 and 0.69 mg/ml.

As polycarbonate is frequently used in many products, its accumulation in landfi lls is absolutely harmful to the environment. The aims of this study were the screening and isolation of polycarbonate-degrading bacteria (PDB) and the assessment of their ability in the degradation of polycarbonate (PC) polymers. Nine-month buried-PC films were used for PDB isolation and identification. The biodegradation ability of the isolates was determined by growth curve, clear zone formation, lipase and amylase production, AFM and FTIR. Bacillus cereus and Bacillus megaterium were identifi ed and considered as PDB. The degradation ability of B. megaterium was significantly higher than that of B. cereus. Both were lipase and amylase positive. AFM and FTIR results showed the initiation of bacterial attachment. The PC biodegradation ability of isolates can be very efficient. Finding such efficient isolates (which was less studied before) will promise a decrease in plastic contamination in the future.

The study discusses an experimental method for treatment of high strength domestic sewage on biofilters filled with polyurethane (PUR) waste in the form of trims of upholstery foam. We determined effectiveness of two biological preparations containing effective microorganisms in elimination of organic and biogenic compounds, indicator bacteria and total suspended solids from the sewage pretreated in a septic tank. After four months of work under a hydraulic loading of 76.4 mm∙d^-1 we found the filter with 60 cm foam layer to be the most efficient in the elimination of BOD₅, COD_Cr, NH₄⁺-N and coliform bacteria. An average reduction in these pollutants reached 79.4%, 67.8%, 58.0% and 88.0%, respectively. Vertical filters filled with trims of upholstery foam and supplied with effective microorganisms ensured favorable conditions for development of heterotrophic and nitrifying bacteria without any need for additional aeration.

This study investigated the potential of three microalgae taxonomic groups of Chlorophyta, Cyanoprokaryota and Bacillariophyceae for biogas production. Biogas potential was assessed in mesophilic anaerobic digestion batch tests over a period of 20 days. The cumulative biogas yield (CBY) of Chlorophyta and Cyanoprocaryota was respectively 396.21 mL/g Volatile Solids (VS) and 382.45 mL/g VS. Bacillariophyceae digestion showed lower biogas production of 357.07 mL/g VS. The highest cumulative methane yield (CMY) of 241.25 mL CH₄/g VS was recorded for Cyanoprocaryota biomass, which was signifi cantly higher (p<0.05) than the other two types of microalgae. The highest methane content in biogas of 63.08% was observed with Cyanoprokaryota. Chemical composition of biomass as well as biogas productivity are infl uenced by algal taxonomy.

The paper presents new non-ionic deep eutectic solvent (DES) composed of natural and non-toxic components i.e. guaiacol, camphor and levulinic acid in 1:1:3 molar ratio as a promising absorbent for removal of selected volatile organic compounds (VOCs) including dichloromethane, toluene, hexamethyldisiloxane and propionaldehyde from model biogas. The affi nity of DES for VOCs was determined as vapour-liquid coeffi cients and the results were compared with several well-known DESs based on quaternary ammonium salt as well as n-hexadecane and water. For new DES, the absorption process was carried out under dynamic conditions. The results indicate that non-ionic DES has high affi nity and capacity for VOCs being comparable to n-hexadecane. In addition, absorbed VOCs could be easily desorbed from DES using activated carbon and absorbent could be re-use minimum fi ve times without significant loss of absorption capacity.

The aim of the study was to evaluate the biochemical possibilities of converting waste lignocellulosic biomass to second generation bioethanol. Three substrates were used in the research: barley straw, rye straw and triticale straw. In the first stage of the research bacterial strains capable of converting waste biomass to produce sugars used to produce energy-useful ethanol were selected. Of the eight strains isolated the three with the highest potential were selected on the basis of activity index value. The raw materials were subjected to enzymatic hydrolysis using the simultaneous saccharifi cation and fermentation method (SSF process). Based on the conducted research, it was found that the examined waste biomass is suitable for the production of cellulosic bioethanol. As a result of distillation 10% and 15% (v/v) ethanol was obtained, depending on the strain and the type of raw material. It was demonstrated that the bacterial strain had a greater impact on the effectiveness of the process than the type of straw used.

The present study thoroughly evaluated the effect of hydroxypropyl-β-cyclodextrin (HP-β-CD) on eluting of Aroclor1242 (one kind of PCBs (polychlorinated biphenyls)) from contaminated soil. The factors that might affect eluting efficiency including HP-β-CD concentration, contact time, eluting cycles, temperature, pH, salt content, humic acid, and ultrasonic were all tested to evaluate the PCBs eluting efficiency by HP-β-CD. Results indicated that Aroclor1242 can be eluted effectively from soil by HP-β-CD solution, 81% of Aroclor1242 was eluted from soil by 50 g/L of HP-β-CD solution after three cycles eluting, and the eluting efficiency was improved by increasing temperature and with ultrasonic. Furthermore, it was shown that the humic acid and extreme acidic/alkaline condition both decreased the eluting efficiency. In addition, column eluting experiment was conducted to simulate the practical HP-β-CD eluting of Aroclor1242 from contaminated soil, 18% of the PCBs was eluted from the soil column by 10 g/L of HP-β-CD. Overall, the results indicated the high extract power of HP-β-CD toward PCBs polluted soil and potential use of HP-β-CD for in situ remediation of PCBs contaminated soils.

The presented work introduces a simple modification of coal fl y ash (FA) with 30% solution of H₂0₂, used as a new efficient sorbent for the removal of organic dye crystal violet (CV) in the presence of Cu(II) ions in single- and bi-component systems Cu(II)-CV. FT-IR, TG, SEM-EDS, and XRD suggested that the mechanism of Cu(II) and CV sorption onto FA-H₂O₂ includes ion-exchange and surface adsorption process. Comparing the values of the reduced chi-square test (χ²/DoF) and the determination coefficient R² obtained for CV of the considered isotherms, the fitting degree follows the sequence: Jovanović > Langmuir > Elovich > Freundlich > Redlich-Peterson (R-P) > Tóth > Halsey > BET. Sorption of Cu(II) ions in a single system by means of FA-H₂O₂ was well fi tted by the Langmuir and R-P model. The studies of equilibrium in a bi-component system by means of extended Langmuir (EL), extended Langmuir-Freundlich (ELF), and Jain-Snoeyink (JS) models were analysed. The estimation of parameters of sorption isotherms in a bi-component system Cu(II)-CV has shown that the best of fi t calculated values of experimental data for both sorbates have been the EL model and the JS model, but only in the case of a CV dye. The sorption kinetic of Cu(II) and CV onto FA-H₂O₂ was discussed by means of the PFO, PSO, and intra-particle diff usion models.

Sugar beet molasses vinasse is a high-strength distillery wastewater. It contains colored substances which significantly affect the degree of pollution and toxicity of vinasse. This study aimed to optimize the medium composition and the process condition of sugar beet molasses vinasse decolorization by Lactobacillus plantarum MiLAB393. The research was conducted in two stages: the shake-fl ask stage in the 250 cm³ Erlenmeyer flasks and the batch experiments in the 5 dm³ working volume stirred-tank bioreactor. During the study, the concentrations of glucose and yeast extract were optimized using experimental design of experiments (DOE). The influences of the initial value of pH and pH control, temperature, stirrer speed and glucose concentration on decolorization were tested. The highest color reduction of 24.1% was achieved for an experiment in which 24.93 g/dm³ of glucose was added to the medium and stirrer speed was 200 rpm. This efficiency of 30% v/v sugar beet molasses vinasse decolorization was obtained at non-controlled pH 6.0 and at 35.8°C. It was found that pH control determines vinasse decolorization. When the pH was controlled, decolorization did not exceed 9%. The glucose and yeast extract concentration and the stirrer speed have a great influence on the process. Changes in these parameters may increase biomass growth while decreasing the decolorization.

This paper presents a new concept of disinfection traditionally applied in water treatment systems. The new definition of this process results from the change in its functionality, aims and methods, which guarantee high quality of water supply. The literature review and technical practice demonstrate a demand for disinfection to act as a functional element of the integrated water distribution system and an active intermediate link between the technology of water treatment and the water distribution network. The presented concept of a disinfection process enables evaluation of water treatment, increases its effectiveness in integrated water treatment systems. Such defined disinfection addresses water conservation and its biological stability within the water supply network. The presented here new concept of disinfection assigns its new role and function in the integrated water distribution system. The controlling and diagnostic function of the disinfection defined in the paper provides a transparent and comprehensive method, with considerable application in experimental design, as well as practical solutions for integrated water distribution systems.

High concentrations of nitrogen dioxide in the air, particularly in heavily urbanized areas, have an adverse eff ect on many aspects of residents’ health. A method is proposed for modelling daily average, minimal and maximal atmospheric NO₂ concentrations in a conurbation, using two types of modelling: multiple linear regression (LR) an advanced data mining technique – Random Forest (RF). It was shown that Random Forest technique can be successfully applied to predict daily NO₂ concentration based on data from 2015–2017 years and gives better fit than linear models. The best results were obtained for predicting daily average NO₂ values with R² =0.69 and RMSE=7.47 μg/m . The cost of receiving an explicit, interpretable function is a much worse fit (R² from 0.32 to 0.57). Verification of models on independent material from the first half of 2018 showed the correctness of the models with the mean average percentage error equal to 16.5% for RF and 28% for LR modelling daily average concentration. The most important factors were wind conditions and traffic flow. In prediction of maximal daily concentration, air temperature and air humidity take on greater importance. Prevailing westerly and south-westerly winds in Wrocław effectively implement the idea of ventilating the city within the studied intersection. Summarizing: when modeling natural phenomena, a compromise should be sought between the accuracy of the model and its interpretability.

In our article the ordinary kriging interpolation method was used for a spatial presentation of PM2.5 concentrations. The data used in the research was obtained from the unique PM2.5 measuring system, based on low-cost optical sensors for PM2.5 concentration measurements, working on Wroclaw University of Science and Technology campus area. The data from this system was used as an input for the interpolations that were made for three different days characterized by the highest measured values of PM2.5 – 20.01.2019, 17.02.2019 and 30.03.2019. For each of the selected days, variants with the maximum and minimum PM2.5 values recorded on a given measurement day were presented. In the analyses performed, the ordinary kriging technique and cross-validation, was used as the interpolation and the validation method, respectively. Parameters determining the quality of performed interpolation were Mean Error, Mean Standardized Error, Root Mean Square Error, and Average Standard Error. As the main indicator of quality of interpolation RMSE parameter was used. Analysis of that parameter shows that the higher variability of the data used for interpolation affects its quality. The Root Mean Square Error parameter reached 0.64, 0.94 and 1.71 for the lowest concentrations variants characterized by low spatial variability, and 6.53, 7.51, 11.28 for the highest one, which were characterized by high spatial variability. The obtained results of the research with the use of GIS tools shows that the ordinary kriging method allowed for the correct spatial presentation of the PM2.5 concentration variability in areas not covered by the measurement system.