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The methods of separation of microalgae has a significant impact in the economic aspects of their cultivation. in this study, pine bark was used as a substrate for immobilization of microalgal biomass cultivated in raw municipal sewage. the experiment was conducted in cylindrical photobioreactors (PBRs) with circulation of wastewater. Biomass was cultivated for 42 days. After that time, abundant growth of the biofilm with microalgae on the surface of pine bark as well as improvement of the quality of treated sewage were observed. The efficiency of removal of nutrients from wastewater was 64-81% for total nitrogen and 97-99% for total phosphorus. Moreover, the concentration of suspended solids in sewage was reduced, which resulted in a decrease in turbidity by more than 90%. Colorimetric analysis and Volatile Matter (VM) content in the substrate showed a decrease in the Higher Heating Value (HHV) and concentration of VM due to the proliferation of biofilm.

Assessing the changing parameters of water quality at different points in the river–reservoir system can help prevent river pollution and implement remedial policies. It is also crucial in modeling water resources. Multivariate statistical analysis is useful for the analysis of changes in surface water quality. It helps to identify indicators that may be responsible for the eutrophication process of a reservoir. Additionally, the analysis of the water quality profile and the water quality index (WQI) is useful in assessing water pollution. These tools can support and verify the results of a multivariate statistical analysis. In this study, changes in water quality parameters of the Turawa reservoir (TR), and the Mała Panew river at the point below the Turawa reservoir (bTR) and above the Turawa reservoir (aTR), were analyzed. The analyzed period was from 2019 to 2020 (360 samples were analyzed). It was found that TN, NO2-N, and NO3-N decreased after passing through the Turawa reservoir. Nevertheless, principal component analysis (PCA) and redundancy analysis (RDA) showed that NO2-N and NO3-N contribute to the observed variability of the water quality in the river-reservoir system. PCA showed that pH and PO4-P had a lower impact on the water quality in the reservoir than nitrogen compounds. Additionally, RDA proved that the values of the NO3-N and NO2-N indicators obtained the highest values at the aTR point, PO4-P at the bTR, and pH at the TR. This allows the conclusion that the Turawa reservoir reduced the concentration of NO2-N and NO3-N in comparison with the concentration of these compounds flowing into the reservoir. PCA and RDA showed that both parameters (NO2-N and NO3-N) may be responsible for the eutrophication process of the Turawa reservoir. The analysis of short-term changes in water quality data may reveal additional sources of water pollution. High temperatures and alkaline reaction may cause the release of nitrogen and phosphorus compounds from sediments, which indicates an increased concentration of TP, PO4-P, and Norg in the waters at the TR point, and TP, PO4-P, and NH4-N concentrations at the bTR point. The water quality profile combined with PCA and RDA allows more effective monitoring for the needs of water management in the reservoir catchment area. The analyzed WQI for water below the reservoir (bTR) was lower than that of the reservoir water (TR), which indicates an improvement in water after passing through the reservoir.

The latest research focused on the analysis of algal growth and the dynamics of their growth use the laser diffraction technique, enabling determination of the volume fraction of suspended particles with specific diameters in aqueous solution as well as their fractal dimensions. This study focuses on the possibility of using a laser granulometer to assess the growth dynamics of algae growing in treated wastewater in a hydroponic system, supported by artificial lighting with the use of light-emitting diodes (LEDs). On the basis of the measurements, the fractal dimension (Df) of algae was determined. An attempt was made to apply the modified Avrami equation describing the crystallization process for the analysis of algae growth dynamics in wastewater. Presented results show that the fractal dimension of suspended matter, largely created by algae, in the case of additional lighting of the hydroponic system at night, takes lower values (Df ~ 1.0) than in sewage without additional light source (Df ~ 2.0). In each measurement series, the fractal dimension of particles in the tank with lighting in the end of the experiment was about 33–43% lower than in the tank without LEDs. The analysis of changes in particle diameters calculated on the basis of Avrami equation largely corresponds with the stages of algae growth. During the measurement series with lower air temperatures, the growth of algae in the tank with additional light was faster than in the tank without LEDs. The obtained information can be the basis for determining the effective method of removing algae from wastewater treated in the hydroponic system, before they are discharged to the receiver in order to prevent the outflow of increased concentrations of total suspended solids.

Due fast biomass production, high affinity for N and P and possibilities to CO 2 sequestration microalgae are currently in the spotlight, especially in renewable energy technologies sector. The majority of studies focus their attention on microalgae cultivation with respect to biomass production. Fuel produced from algal biomass can contribute to reducing consumption of conventional fossil fuels and be a remedy for a rising energy crisis and global warming induced by air pollution. Some authors opt for possibilities of using sewage as a nutrient medium in algae cultivation. Other scientists go one step further and present concepts to introduce microalgal systems as an integral part of wastewater treatment plants. High costs of different microalgal harvesting methods caused introduction of the idea of algae immobilization in a form of periphyton on artificial substrates. In the present study the attention has focused on possibilities of using waste materials as substrates to proliferation of periphyton in biologically treated sewage that contained certain amounts of nitrogen and phosphorus.

This work focuses on modelling soil water reserves using an Artificial Neural Network (ANN). Four model variants were established based on 843 records (verified through 268 measurements) of soil water content (SWC) measured at full-scale field sites located in Southwest Poland. It is revealed that commonly recorded climatic data (precipitation and temperature) linked with SWC and field water capacity (FWC) are applicable in the ANN modelling. The basic model (utilising the meteorological data) was the most suitable for soil profiles with thicknesses of 0-25 cm, while in profiles with thicknesses of 0-50 cm and 0-100 cm the comprehensive ANN model (linking climatic data, FWC and SWC) was the most appropriate. Furthermore, comparative studies of the measured and modelled data indicated their statistical convergence, thus providing support for the practical implementation of the proposed ANN modelling.

Treatment of wastewater produced in Service Areas (SA) located on expressways and highways is a worldwide problem because of increasing amount of roads and specific composition of those kinds of sewage. Insufficient removal of pollutants from wastewater discharged into surface water may cause serious environmental problems. In the present study efficiency of treatment of wastewater with high ammonium concentration in biological membrane system used on SA was investigated. Concentrations of ammonia nitrogen in wastewater flowing into bioreactor in none of the tested objects did not fall below 99.0 mg of N-NH4·dm . Because of high ammonium content in sewage and high pH reaching value about 9, it is almost impossible to create favorable conditions for microorganisms that run purification processes resulting in low efficiency of phosphorus and nitrogen removal (reduction of biogenic compounds did not exceed 15%). Treatment of wastewater consisting mainly of urine with commonly used biological membrane technology has to be widely tested to perform suitable quality of discharged wastewater, to provide safety of surface water environment.

The presented study concerns the efficiency of removing nutrients, organic compounds and metal cations from municipal sewage by a cylindrical photobioreactor (PBR) with the biomass of microalgae growing on pine bark. The study was conducted in two cylindrical PBRs fed with municipal wastewater for 42 days. PBRs were internally illuminated with red and blue light at night. The sewage was additionally enriched in CO 2 and CaCO 3. The concentration of NH 4