The processes that affect sediment quality in drainage systems show high dynamics and complexity. However, relatively little information is available on the influence of both catchment characteristics and meteorological conditions on sediment chemical properties, as those issues have not been widely explored in research studies. This paper reports the results of investigations into the content of selected heavy metals (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and polycyclic aromatic hydrocarbons (PAHs) in sediments from the stormwater drainage systems of four catchments located in the city of Kielce, Poland. The influence of selected physico-geographical catchment characteristics and atmospheric conditions on pollutant concentrations in the sediments was also analyzed. Based on the results obtained, statistical models for forecasting the quality of stormwater sediments were developed using artificial neural networks (multilayer perceptron neural networks). The analyses showed varied impacts of catchment characteristics and atmospheric conditions on the chemical composition of sediments. The concentration of heavy metals in sediments was far more affected by catchment characteristics (land use, length of the drainage system) than atmospheric conditions. Conversely, the content of PAHs in sediments was predominantly affected by atmospheric conditions prevailing in the catchment. The multilayer perceptron models developed for this study had satisfactory predictive abilities; the mean absolute error of the forecast (Ni, Mn, Zn, Cu, and Pb) did not exceed 21%. Hence, the models show great potential, as they could be applied to, for example, spatial planning for which environmental aspects (i.e., sediment quality in the stormwater drainage systems) are accounted.

The dynamics of processes affecting the quality of stormwater removed through drainage systems are highly complicated. Relatively little information is available on predicting the impact of catchment characteristics and weather conditions on stormwater heavy metal (HM). This paper reports research results concerning the concentrations of selected HM (Ni, Cu, Cr, Zn, Pb and Cd) in stormwater removed through drainage system from three catchments located in the city of Kielce, Poland. Statistical models for predicting concentrations of HM in stormwater were developed based on measurement results, with the use of artificial neural network (ANN) method (multi-layer perceptron). Analyses conducted for the study demonstrated that it is possible to use simple variables to characterise catchment and weather conditions. Simulation results showed that for Ni, Cu, Cr, Zn and Pb, the selected independent variables ensure satisfactory predictive capacities of the models (R² > 0.78). The models offer considerable application potential in the area of development plans, and they also account for environmental aspects as stormwater and snowmelt water quality affects receiving waters.

Household wastewater is a problem, especially in areas with a dispersed settlement where there is no wastewater collection system or wastewater treatment plant. In this case, it is necessary to build a local or onsite wastewater treatment plant. This paper is an attempt to analyse the possibility of using recycled shredded ABS plastic (acrylonitrile butadiene styrene) as packing media in an experimental vertical flow filter for use in on-site wastewater treatment plants. Studies have shown that shredded recycled ABS is a promising filtration material that has several features important in the treatment process, like a large surface area, high mechanical strength and chemical inertness. The system was operated with a hydraulic load of 50 dm³/m² (3 months). BOD5 (biochemical oxygen demand), COD (chemical oxygen demand), and total suspended solids (TSS) reduction efficiency in the primary effluent was high; 94.4%, 77.8%, and 92.8%, respectively.

This paper reports the results of studies on the concentrations of total suspended solids (TSS) and heavy metals (HMs) (Cu, Zn, Cr, Ni, Cd, Pb) in stormwater. Pollutant loads were calculated for the observed high water stages. Pollutographs showing M/M_c = f(V/V_c) relationships were generated. In the description of the relationships, two functions, namely the exponential and the power functions, were employed. These represented the dynamics of the pollutant washout from the surface of the catchment area. The analyses demonstrated that the exponential function provides a slightly better description of the course of the process compared with the power function. In the former case, correlation coefficients (R) ranged from 0.900 to 0.999, whereas in the latter they ranged from 0.864 to 0.999. The analyses of correlations between the characteristics describing discharge hydrographs and the values of pollutant washout coefficients indicate that the strongest statistical relationships were identified for TSS. It was demonstrated that the value of the washout coefficient for total suspended solids (k_TSS) drops with an increase in rain intensity (q). This also depends on the 10-min precipitation (P_td=10). Regarding the studied heavy metals, a statistically significant impact of the dry period (t_bd) on the washout coefficient was observed only for lead (k_Pb). Taking into account the washout coefficient in the first flush model makes it possible to improve the accuracy of calculations. This is important for understanding the studied phenomenon.

Zinc is one of the more mobile metals in the soil and thus involves the risk of entering the food chain. Zinc compounds are used in the galvanization process, which is assumed to be safe for the environment. However, random events or failures such as unsealing bathtubs with liquid zinc or hydrochloric acid, as well as violent fires in industrial halls, may pose a real threat to the environment, including human health. Therefore, this research was carried out to determine the content of zinc and selected potentially toxic metals in arable soils after a failure in a galvanizing plant located in the village of Dębska Wola (southeastern Poland). In addition, the potential risk associated with excessive accumulation of identified pollutants in the environment was assessed. In order to determine the level of contamination, soil samples were taken, and basic physical and chemical properties were analysed. The concentrations of Zn, Pb, and Cd in the soil were determined using the atomic emission spectrometry technique with inductively coupled plasma (ICP-OES), and pH measurements were performed using the potentiometric method after prior wet mineralisation of the research samples. The analysed samples had a varied pH of the organic–mineral horizon from pH_H2O 4.66 to pH_H2O 5.33 and from pH_KCl 3.89 to pH_KCl 5.06. As a result of a failure, toxic metal fumes were released into the atmosphere, causing concentrations of Zn in the soil samples from 0–5 cm in the range of 1201–2007 mg∙kg⁻¹, as well as Pb (109–509 mg∙kg⁻¹) and Cd (4.6–17 mg∙kg⁻¹). High contents of zinc and lead found in several soil samples are of anthropogenic nature and require detailed monitoring in order to eliminate the risk associated with their accumulation. The study area should be re-analysed to determine the rate of reclamation of degraded soils.

The quality of bottom sediment is important for the condition of aquatic environments. High levels of potentially harmful components in sediments negatively affect the quality of surface water environments. Lake bottom sediments are commonly used to control the quality of the environment in terms of both heavy metals and harmful organic compounds. This paper presents new data on the compositions of bottom sediments from Sołtmany Lake, located in the Masurian Lake District (Poland). The aim of this study was to determine the physicochemical properties of bottom sediments and to assess their quality based on geochemical and ecotoxicological criteria. The field study was conducted in July 2021. Thirty sediment samples were collected for analysis from six study sites located in the upper central and lower part of the reservoir. Contamination of the bottom sediments with trace metals was determined on the basis of the geoaccumulation index (Igeo), while an ecological risk assessment was carried out on the basis of calculated values of TEC (Threshold Effect Concentration) and PEC (Probable Effect Concentration) indices. The study shows that the concentration of trace metals in sediments was characterised by slight variation and that the maximum values did not exceed: 1.1 mg·kg⁻¹ for Cd, 8.7 mg·kg⁻¹ for Cr, 10.9 mg·kg⁻¹ for Cu, 7.7 mg·kg⁻¹ for Ni, 12.9 mg·kg⁻¹ for Pb and 52.3 mg·kg⁻¹ for Zn. The analyses further showed that the concentration of trace elements in the sediment surface layer increased in the following order: Zn > Pb > Cu > Ni > Cr > Cd. The maximum pH value of H₂O was 7.1, while that of KCl was 7.0. The maximum values of C_org, N_tot, P₂O₅, K₂O and Mg were, respectively: 6.1 g·kg⁻¹, 1.4 g·kg⁻¹, 40.2 mg·100 g⁻¹, 31.2 mg·100 g⁻¹ and 35.1 mg·100 g⁻¹. The assessment of the degree of lake pollution is essential for the conservation of biodiversity and the organisation of environmental management activities.