Wastewater is a byproduct of industrial or household waste processes, and its contamination level must be determined before treatment. Discharges of liquid effluents generated by mining operations, ...one of the most prevalent forms of industrial waste water, pose a risk to human health and the environment. This study evaluates the physicochemical quality of industrial liquid effluent discharges from the Boukhadra mine (Algeria). Samples were collected from the washing water to identify the level of contamination of these liquid discharges and to measure physicochemical parameters such as temperature (T), hydrogen potential (pH), Electrical Conductivity (EC), Suspended Solids (SS), Chemical Oxygen Demand (COD), Biological Oxygen Demand for 5 days (BOD5), Oils and Greases (O&G), iron (Fe+2) and Kjeldahl Nitrogen (NTK). It was found that the concentration values of those effluents exceeded the maximum contamination limits specified by international industrial waste standards. A simple and reliable prediction model was developed to estimate DBO5, based on MES, COD, and O&G, by using classical regression analysis and fitting Design of Experiments (DOE) methodology. When comparing the analytical results, it was found that the quadratic model provided a better estimation, with a high correlation coefficient (R2) of 0.9976. The parameters determined in this study will enable engineers to quickly estimate the degree of wastewater contamination and choose adequate treatment strategies.
Nuclear power plants (NPPs) use large amounts of water for cooling; recirculating cooling water systems (RCWS) take water and discharge it to the environment, concentrate natural constituents, and ...introduce chemicals used to maintain the chemical regime of the NPP. Changes in organic matter (OM) content can be caused by natural processes as well as human activities. The subject of the research is OM discharges with return water from RCWS NPPs. The research was carried out using the example of the RCWS Rivne NPP and the water of the Styr River, from which the Rivne NPP uses water. The relevance of the research lies in the assessment of the nonradiative environmental impact of the NPP, with the establishment of a correlation between the OM content and the technological modes of operation of the Rivne NPP. The study results show that the concentrations of the total organic carbon (TOC), the chemical oxygen demand (COD), and the 5-day biochemical oxygen demand (BOD5) are significantly related to the technological mode of operation of the RCWS of the NPP, which is determined by the concentration cycles (in the range of 1.5–5.0) using regression analysis. Therefore, the changes in OM content are correlated with the technological modes of water intake and discharge. The values of the measured environmental concentration (MEC) and the predicted environmental concentration (PEC) are comparable, and the difference between MEC and PEC does not exceed 16%. The proposed formulas were statistically tested by comparing the observed with the predicted BOD5, TOC, and COD and ranged from 27% (COD) to 6–75% (BOD5 and TOC). Moreover, according to the environmental assessment, the Styr River water in the area of influence of the Rivne NPP discharges is classified as class IV, category 6—“poor,” and BOD-5–class II, category 2—“good.” The novelty of the research is the multicomponent evaluation of the OM content by various indicators of TOC, COD, and BOD5 control and determination of the dynamics of their changes with the establishment of variability factors. Thus, the practical value of the study lies in the possibility of applying the methods to other power plants using RCWS.
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The faecal indicator bacteria (FIB) in association with physicochemical parameters were monitored twice a month from 2017 to 2019 in the Kahuwa (KW), Wesha (WS), Tshula (TL), Bwindi (BN), and ...Nyamuhiga (NG) rivers and their tributaries. Results showed severe faecal contamination of waters compared to the WHO standards, and the FIB load levels (Mesophilic aerobic bacteria (MAB), Total coliforms (TC), Faecal coliforms (FC), and Faecal streptococci (FS)) were varied between stations (Kruskal-Wallis test (K) = 703; p < 0.01) and seasons (Fisher's test (F) = 2.13; p < 0.01). However, the presence of pathogenic bacteria such as Escherichia coli, Salmonella typhi, Streptococcus sp., Shigella dysenteriae, Aeromonas sp., Vibrio cholerae, and other bacteria indicative of faecal contamination were reported. Water temperature (WT) and dissolved oxygen (DO) were within the WHO standards for surface waters, except pH for some stations on KW and NG rivers, where it was highly alkaline. The highest nutrients concentrations (PO43–, NH4+, NO2– and NO3–) were recorded in the dry season for all stations, except in KW and NG rivers from the midstream to downstream stations. The structural equations regression model (F test, p ≤ 0.05 with R2) indicated a significant (p ≤ 0.05) positive correlation between the value of physicochemical parameters (WT, pH, PO43–, NH4+, NO2– and NO3–) and that of detected FIB numbers, except for DO which negatively affects bacteria numbers. The FC/FS ratio (1.01 – 4.30) linked polluted waters to human sources while the COD/BOD5 ratio (1.90 – 2.39) categorized them under domestic origin wastewater. The current degradation status of these rivers require a rapid waste management strategy and an efficient sanitation plan development along each catchment. Installation of wastewater treatment plants (WWTPs) with biological treatment can mitigate the ecological and health risks of the rivers and the coastal zone of Lake Kivu.
Wastewater quality modelling plays a vital role in planning and management of wastewater treatment plants (WWTP). This paper develops a new hybrid machine learning model based on extreme learning ...machine (ELM) optimized by Bat algorithm (ELM-Bat) for modelling five day effluent biochemical oxygen demand (BOD5). Specifically, this hybrid model combines the Bat algorithm for model parameters optimization and the standalone ELM. The proposed model was developed using historical measured effluents wastewater quality variables, i.e., the chemical oxygen demand (COD), temperature, pH, total suspended solid (TSS), specific conductance (SC) and the wastewater flow (Q). The performances of the hybrid ELM-Bat were compared with those of the multilayer perceptron neural network (MLPNN), the random forest regression (RFR), the Gaussian process regression (GPR), the random vector functional link network (RVFL), and the multiple linear regression (MLR) models. By comparing several input variables combination, the improvement achieved in the accuracy of prediction through the hybrid ELM-Bat was quantified. All models were first calibrated using training dataset and later tested using validation and based on four performances metrics namely, root mean square error (RMSE), mean absolute error (MAE), the correlation coefficient (R), and the Nash-Sutcliffe model efficiency (NSE). In all, it is concluded that the ELM-Bat is the most accurate model when all the six input were included as input variables, and it outperforms all other benchmark models in terms of predictive accuracy, exhibiting RMSE, MAE, R and NSE values of approximately, 0.885, 0.781, 2.621, and 1.989, respectively.
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•Modelling five day biochemical oxygen demand (BOD5) using six machine learning.•New extreme learning machine optimized Bat algorithm (ELM-Bat) was proposed for modelling BOD5.•The performances of the ELM-Bat were compared with those of the MLPNN, GPR, RVFL and MLR models.•The ELM-Bat was found to be more accurate and significantly outperforms the other benchmarking predictive models.
One of the biggest threats to many lakes is their accelerated eutrophication resulting from anthropogenic pressure, agricultural intensification, and climate change. A very important element of ...surface water protection in environmentally conserved areas is the proper monitoring of water quality and detection of potential threats by examining the physicochemical properties of water and performing statistical analyses that enable possible exposure of unfavourable trends. The article presents the analyses of the results of measurements made in three lakes located in the Sierakowski Landscape Park. As part of the measurements, water quality indicators i.e., phosphorus, nitrogen, BOD5 and COD, were determined monthly for a year at the inflows and outflows of the studied lakes. The test results of selected water quality indicators were analysed using machine learning algorithms i.e., PCA and k-means. The conducted tests enabled statistical estimation of changes in water quality indicators in the reservoirs and evaluation of their correlation.
Integrated On-site Greywater Treatment System (IOGTS) with primary (settling/filtration), secondary (constructed wetland) and tertiary (adsorption) treatment was used to treat greywater from hostel. ...A field scale IOGTS was constructed for hostel located in Sakharale, District Sangli (M.S.) India. The performance evaluation of IOGTS was carried out for a study period of one year. The quality parameters used to assess feasibility of disposal for land application were COD, TKN, suspended solids, and pathogens. The effect of hydraulic loading rate (HLR), Hydraulic Retention Time (HRT) and Organic Loading Rate (OLR) on performance of the system was also studied. A consistent performance (30% COD removal and 70% turbidity removal) was observed in upflow-downflow filter throughout the study. Secondary treatment in IOGTS was evaluated for HLR (10–100mm/d) and OLR (10–350kg COD/ha.d). HLR (40mm/d) and OLR (170kg COD/ha.d) showed a better removal efficiency of COD. Overall performance of IOGTS for COD, TKN and pathogen removal was observed to be 70%, 70% and 85% respectively. Therefore, IOGTS can be considered to be an appropriate treatment option to treat greywater to satisfy effluent standards for its reuse in land application.
A detailed investigation on photooxidation of linear alkyl benzene (LAB) industrial wastewater is presented in this study. The process analysis was performed by varying four significant independent ...variables including two numerical factors (initial pH (3–11) and initial H2O2 concentration (0–20mM)) and two categorical factors (UV irradiation and ozonation). The experiments were conducted based on a central composite design (CCD) and analyzed using response surface methodology (RSM). To assess the process performance, two parameters viz. TCOD removal efficiency and BOD5/COD were measured throughout the experiments. A maximum reduction in TCOD was 58, 53, 51, and 49%, respectively for UV/H2O2/O3, H2O2/O3, UV/O3 and UV/H2O2 processes at the optimum conditions (initial pH of 7, initial H2O2 concentration of 100mM, and reaction time of 180min). A considerable increase in BOD5/COD ratio was obtained in the combined processes (0.46, 0.51, 0.53, and 0.55 for UV/H2O2, UV/O3, H2O2/O3 and UV/H2O2/O3, respectively) compared to the single oxidant process (0.35). The results showed that mineralization of the LAB industrial wastewater in neutral pH is more favored than in acidic and basic pH. Gas chromatography–mass spectrometry (GC–MS) was applied to show the fate of organic compounds. In conclusion, the photooxidation process (UV/H2O2/O3, H2O2/O3, UV/O3 and UV/H2O2) could be an appropriate pretreatment method prior to a biological treatment process.
Anammox and deammonification processes under different five-day biochemical oxygen demand (BOD5) to total nitrogen (TN) ratios (0, 0.1, and 0.2) were investigated in a lab-scale anaerobic sequencing ...batch reactor (ASBR) and full-scale moving bed bioreactor (MBBR) and integrated fixed-film activated sludge (IFAS) systems operated under different conditions (dissolved oxygen (DO) concentrations, solids retention time (SRTs), organic and ammonia-nitrogen (NH3-N) loading rates). Nitrogen removal efficiencies for the lab-scale ASBR anammox process using synthetic wastewater as substrate and two full-scale deammonification processes (MBBR with anaerobic digester centrate as substrate and IFAS with stored landfill leachate as substrate) were >90%, ∼60%, and ∼75%, respectively. Quantitative polymerase chain reaction and polymerase chain reaction-denaturing gradient gel electrophoresis were used to investigate microbial communities on three different attached-growth media: scrub sponges (ASBR), AnoxKaldnes K5 (MBBR) and polypropylene (IFAS). The anammox species, Candidatus Brocadia fulgida was dominant only in the lab-scale anammox system and Candidatus Kuenenia sp. was dominant under DO concentration of 0.3 mg l−1 and organic loading of 0.04 kg-BOD·m−3·d−1. Candidatus Jettenia caeni was dominant at BOD5:TN ratio of 0.2 and organic loading up to 0.39 kg-BOD·m−3·d−1 and NH3-N loading 1.95 kg-N·m−3·d−1. Furthermore, abundance of amoA-AOA populations in lab-scale and two full-scales treatment systems were similar (around 8.04 × 104 to 1.56 × 105 copies/g-sludge) but different predominant AOA species were observed on the different media. Based on the results from this work, maintaining low BOD5:TN ratios could be applied to improve the nitrogen removal efficiency of deammonification processes. While very low BOD5:TN ratio was the primary determinant of deammonification efficiency, other beneficial influences include high specific surface area carriers, low DO concentration, high temperature, and long SRT.
•Temp (>27 °C), BOD5:TN ratio (<0.1) and DO concentration (≤0.3 mg l−1) with longer SRT (>12 d) are factors for sucessfull anammox process.•Ca. Kuenenia sp. may play an important role in a system that was controlled at low DO conc. and moderate organic loading.•Ca. Brocadia fulgida was observed dominantly at NH4+ to NO2− (1:1.3) ratio in the systems.•Ca. Jettenia caeni was possibly an important species in a full-scale system with high organic loading.•Attached-growth systems could retain AOA to coexist with anammox bacteria.
The demographic and urban expansion of the nineteenth century led to a significant reduction in water resources. One of the considered solutions to this problem was to retain water in reservoirs. ...Over the years it has been recognized that the construction of small reservoirs can bring greater benefits than large ones. Large reservoirs are not only associated with substantial economic costs, i.e. for the purchase of land, but they also do not sufficiently serve as the components of a flood protection system. They are also of minor importance in the production of so-called ''white energy” (Lehner et al., 2005) and may have a negative impact on the environment. The size and age of reservoirs as well as the type of water dams and their work regime affect the scale of changes in the natural fluvial environment (Robinson et al., 2003). Small reservoirs are a basic element of small water retention, in which water quality depends to a large extent on their location, the way their catchment areas are managed and the functions they perform (apart from typical retention reservoirs). The catchments used for agricultural purposes may be susceptible to accumulation of biogenic substances (nitrogen and phosphorus), and other pollution (Hejduk, 2010; Kanownik et al., 2013; Kasperek et al., 2013; Wiatkowski et al., 2013). The article initially tested the quality of the water in three reservoirs, different period of operation with use of selected indicators. For the purposes of research and this resultant publication, water quality was tested in three reservoirs differing in operating times. It was assumed that the study period covering autumn, spring and early summer was the period with the most visible changes in concentrations of pollutants. Samples taken from the reservoirs were analysed by determining in turn biological oxygen demand (BOD5), ammonia concentration (NH4), phosphate concentration (PO4) and total suspended solids. The use of indicators allowed for assessing the quality of water in these reservoirs and comparing it in terms of different periods of their operation.
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