Online soft measurement method for chemical oxygen demand based on CNN-BiLSTM-Attention algorithm.

The measurement of chemical oxygen demand (COD) is very important in the process of sewage treatment. The value of COD reflects the effectiveness and trend of sewage treatment to a certain extent, but obtaining accurate data requires high cost and labor intensity. To1 solve this problem, this paper proposes an online soft measurement method for COD based on Convolutional Neural Network-Bidirectional Long Short-Term Memory Network-Attention Mechanism (CNN-BiLSTM-Attention) algorithm. Firstly, by analyzing the mechanism of the aerobic tank stage in the Anaerobic-Anoxic-Oxic (A2O) wastewater treatment process, the selection range of input variables was preliminarily determined, and the collected sample dataset was subjected to correlation analysis. Finally, pH, dissolved oxygen (DO), electrical conductivity (EC), and water temperature (T) were determined as input variables for soft measurement prediction of COD.Then, based on the feature extraction ability of CNN and the advantage that BiLSTM is able to capture the backward and forward dependencies in time series data, combined with the attention mechanism that can assign higher weights to the key data, a CNN-BiLSTM-Attention algorithm model was established to soft measure COD in the effluent from the aerobic zone of the A2O wastewater treatment process. At the same time, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) were utilized Three indicators were used to evaluate the model, and the results showed that the model can accurately predict the value of COD and has a high accuracy. At the same time, compared with models such as CNN-LSTM-Attention, CNN-BiLSTM, CNN-LSTM, LSTM, RNN, BP, SVM, XGBoost, and RF etc., the results showed that the CNN-BiLSTM Attention model performed the best, proving the superiority of the algorithm model.The Wilcoxon signed-rank test indicates significant differences between the CNN-BiLSTM-Attention model and other models.

Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems.

Water quality index (WQI) is a well-established tool for assessing the overall quality of fresh inland-waters. However, the effectiveness of real-time assessment of aquatic ecosystems using the WQI is usually impacted by the absence of some water quality parameters in which their accurately in-situ measurements are impossible and face difficulties. Using a rich water quality dataset spanned from 1980 to 2023, we employed four machine learning-based models to estimate the British Colombia WQI (BCWQI) in the Lake Päijänne, Finland, without parameters like chemical oxygen demand (COD) and total phosphorus (TP). Measurement of both COD and TP is time-consuming, needs laboratory equipment and labor costs, and faces sampling-related difficulties. Our results suggest the machine learning-based models successfully estimate the BCWQI in Lake Päijänne when TP and COD are omitted from the dataset. The long-short term memory model is the least sensitive model to exclusion of COD and TP from inputs. This model with the coefficient of determination and root-mean squared error of 0.91 and 0.11, respectively, outperforms the support vector regression, random forest, and neural network models in real-time estimation of the BCWQI in Lake Päijänne. Incorporation of BCWQI with the machine learning-based models could enhance assessment of overall quality of inland-waters with a limited database in a more economical and time-saving way. Our proposed method is an effort to replace the traditional offline water quality assessment tools with a real-time model and improve understanding of decision-makers on the effectiveness of management practices on the changes in lake water quality.

Electrochemical oxidation of amoxicillin, ciprofloxacin and erythromycin in water: Effect of experimental factors on COD removal.

An alternative method of electrochemical oxidation was employed to degrade persistent compounds in the form of antibiotics using strong oxidizing agents such as hydroxyl ions. A 24 factorial design was employed to check the effect of four factors namely pH, current density, electrolysis time and electrolyte concentration set at their high (+) and low (-) levels on the antibiotics (amoxicillin, ciprofloxacin and erythromycin) degradation in water. The response was obtained in the form of COD (chemical oxygen demand) removal. A prediction model was developed to predict the values of COD removal. Later the main effect, contribution and interactions were studied with Design Expert Software 7.0. About 89.5% COD removal was obtained when pH and time were set at their high level and the other two factors at their low level. It was determined that the pH when set at high level (pH 9) had the most effect (24.68) and contribution (43.6) in the degradation process and hence the removal of COD. This technology of electrochemical oxidation can be employed in industries to efficiently remove pharmaceuticals, paints, dyes and other organic compounds.

Nutritional value, total dry matter losses, effluent production and pollutant potential in Brachiaria brizantha cv. Paiaguás grass / [Valor nutricional, perdas totais de matéria seca, produção e potencial poluidor de efluentes em silagem de Brachiaria brizantha cv. Paiaguás]

The objective of the present study was to evaluate losses, production and polluting potential of the effluent, nutritional value and aerobic stability of silages of Brachiaria brizantha cv. Paiaguás grass, in different particle sizes and compaction density in silage. Three theoretical particle sizes (TTP 5; 8 and 12mm) and three compaction densities (DC 550; 600 and 650kg/m3) were evaluated, distributed in a factorial design (3 x 3), with four repetitions. The highest volume of effluent was found in silages with higher compaction densities (600 and 650kg/m3) and lower TTP (5 and 8mm). The highest chemical oxygen demand and biochemical oxygen demand were registered in the treatment with TTP of 5mm and higher DC (600 and 650kg/m3). Greater in vitro digestibility of DM was verified in the silage chopped at 5 and 8mm. There was no break in aerobic stability for 216 hours. Silage with a low compaction density 550kg/m3 and processing with a theoretical particle size of 12mm reduces effluent losses. In general, the nutritional value of Paiaguás grass was not influenced by the treatments. Different particle sizes and compaction density did not change the aerobic stability of silages.(AU)

Objetivou-se avaliar perdas, produção e potencial poluidor do efluente, valor nutricional e estabilidade aeróbia de silagens do capim Brachiaria brizantha cv. Paiaguás, em diferentes tamanhos de partícula e densidade de compactação na ensilagem. Foram avaliados três tamanhos teóricos de partícula (TTP 5; 8 e 12mm) e três densidades de compactação (DC 550; 600 e 650kg/m3), distribuídos em arranjo fatorial (3 x 3), com quatro repetições. O maior volume de efluente foi verificado nas silagens com maiores densidades de compactação (600 e 650kg/m3) e menores TTP (5 e 8mm). As maiores demanda química de oxigênio e demanda bioquímica de oxigênio foram registradas no tratamento com TTP de 5mm e nas maiores DC (600 e 650kg/m3). Maior digestibilidade in vitro da MS (média de 57,2%) foi verificada na silagem picada a 5 e 8mm. Não houve quebra da estabilidade aeróbia durante 216 horas. A ensilagem com baixa densidade de compactação (550kg/m3) e o processamento com tamanho teórico de partículas 12mm reduzem as perdas por efluente. O valor nutricional da silagem de capim-paiaguás, em geral, não foi influenciado pelos tratamentos. Diferentes tamanhos de partícula e densidade de compactação não alteraram a estabilidade aeróbia das silagens.(AU)

Metagenomic insights into mixotrophic denitrification facilitated nitrogen removal in a full-scale A2/O wastewater treatment plant.

Wastewater treatment plants (WWTPs) are important for pollutant removal from wastewater, elimination of point discharges of nutrients into the environment and water resource protection. The anaerobic/anoxic/oxic (A2/O) process is widely used in WWTPs for nitrogen removal, but the requirement for additional organics to ensure a suitable nitrogen removal efficiency makes this process costly and energy consuming. In this study, we report mixotrophic denitrification at a low COD (chemical oxygen demand)/TN (total nitrogen) ratio in a full-scale A2/O WWTP with relatively high sulfate in the inlet. Nitrogen and sulfur species analysis in different units of this A2/O WWTP showed that the internal sulfur cycle of sulfate reduction and reoxidation occurred and that the reduced sulfur species might contribute to denitrification. Microbial community analysis revealed that Thiobacillus, an autotrophic sulfur-oxidizing denitrifier, dominated the activated sludge bacterial community. Metagenomics data also supported the potential of sulfur-based denitrification when high levels of denitrification occurred, and sulfur oxidation and sulfate reduction genes coexisted in the activated sludge. Although most of the denitrification genes were affiliated with heterotrophic denitrifiers with high abundance, the narG and napA genes were mainly associated with autotrophic sulfur-oxidizing denitrifiers. The functional genes related to nitrogen removal were actively expressed even in the unit containing relatively highly reduced sulfur species, indicating that the mixotrophic denitrification process in A2/O could overcome not only a shortage of carbon sources but also the inhibition by reduced sulfur of nitrification and denitrification. Our results indicate that a mixotrophic denitrification process could be developed in full-scale WWTPs and reduce the requirement for additional carbon sources, which could endow WWTPs with more flexible and adaptable nitrogen removal.

Microbial fuel cell biosensor for the determination of biochemical oxygen demand of wastewater samples containing readily and slowly biodegradable organics.

OBJECTIVES: Single-chamber air cathode microbial fuel cells (MFCs) were applied as biosensors for biochemical oxygen demand (BOD) measurement of real wastewaters with considerable suspended and/or slowly biodegradable organic content. RESULTS: The measurement method consists of batch sample injection, continuous measurement of cell voltage and calculation of total charge (Q) gained during the biodegradation of organic content. Diverse samples were analyzed: acetate and peptone samples containing only soluble readily biodegradable substrates; corn starch and milk samples with suspended and colloidal organics; real domestic and brewery wastewaters. Linear regression fitted to the Q vs. BOD5 measurement points of the real wastewaters provided high (> 0.985) R2 values. Time requirement of the measurement varied from 1 to 4 days, depending on the composition of the sample. CONCLUSIONS: Relative error of BOD measured in the MFCs comparing with BOD5 was less than 10%, thus the method might be a good basis for the development of on-site automatic BOD sensors for real wastewater samples.

A Current Sensing Biosensor for BOD Rapid Measurement.

In order to improve the practicality of the rapid biochemical oxygen demand (BOD) method, a highly sensitive rapid detection method for BOD that is based on establishing the correlation between current and dissolved oxygen (DO) was developed. In this experiment, Bacillus subtilis was used as the test microorganism, and the embedding method was used to achieve quantitative fixation of microorganisms, which could increase the content of microorganisms and prolong the service life of the biological element. The conductivity (COND) probe is used as a sensing element, so that the testing value can be read every second. In the program, the moving average method is used to process the collected data so that the value can be read every minute. National standard samples were detected to test the accuracy and stability of the method. The results showed that relative error and analytical standard deviations were less than 5%. Different polluted water was tested to evaluate its application range. The results showed that relative error was less than 5%. The results of the method are consistent with the results of the wastewater sample obtained by the BOD5 standard method. The proposed rapid BOD current sensing biosensor method should be promising in practical application of wastewater monitoring.

Estimation of potential agricultural non-point source pollution for Baiyangdian Basin, China, under different environment protection policies.

To prevent and control non-point source pollution, many policies have been carried out by government in China. However, the effectiveness of these policies has rarely been evaluated. In this study, the potential and spatial distribution of agricultural non-point source pollution in the Baiyangdian Basin are reported. This investigation considers multiple parameters under various policies with county as a basic unit. The results for the potential pollution from chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total nitrogen (TN) and total phosphorus (TP) are 60.89×104, 3.93×104, 87.05×104 and 15.10×104 Mg, with corresponding intensities of 190, 12, 272 and 47 kg ha-1 for the Baiyangdian Basin in 2016. The highest pollution from COD is attributed to livestock and poultry breeding, whereas TN and TP are dominantly produced by rural domestic sources, and NH3-N is mostly derived from planting. Spatially, distribution of the counties producing larger non-point source pollution presented a northeast to southwest direction, consistent with the Taihang mountain alignment in the basin. The counties with high pollution intensities are mostly in the south and east of the basin. Agricultural non-point source pollution control and prevention policies contributed in pollution reduction. Compared with 2016, the total potential pollution of COD, NH3-N, TN and TP in 2020 decrease by 45.1%, 14.7%, 37.9% and 37.4%, respectively, whereas for an assumed future time (F2), the decreases are 59%, 51.4%, 56.2% and 55.7%, respectively. Prevention measures should focus on reducing pollution from livestock and poultry breeding as well as planting.

Statistical optimization and modeling for color removal and COD reduction of reactive blue 19 dye by mesoporous chitosan-epichlorohydrin/kaolin clay composite.

In current research work, chitosan (Chi) was subjected to subsequent physical and chemical modifications by incorporating kaolin clay (KA) into its polymeric structure, and crosslinking process with a covalent cross-linker namely epichlorohydrin (ECH) respectively. The final product of crosslinked chitosan-epichlorohydrin/kaolin (Chi-ECH/KA) composite was successfully applied for color removal and chemical oxygen demand (COD) reduction of textile dye namely reactive blue 19 dye (RB19) from aqueous environment. The influence of pertinent parameters, i.e. A: Chi-ECH/KA dose (0.02-0.1 g), B: pH (4-10), and C: time (5-30 min) on the RB19 color removal and COD reduction were statistically optimized by using response surface methodology with Box-Behnken design (RSM-BBD). The experimental data of the adsorption kinetic and the adsorption isotherm demonstrated a better fitness to pseudo-second order model and Langmuir isotherm model respectively. Excellent absorption ability of 560.9 mg/g was recorded for Chi-ECH/KA composite. The calculated thermodynamic functions clarified that the RB19 adsorption process was endothermic and spontaneous in nature. The mechanism of RB19 adsorption onto the Chi-ECH/KA may include electrostatic interactions, hydrogen bonding, Yoshida H-bonding, and n-π interactions. This study introduces Chi-ECH/KA composite as an eco-friendly, potential and multi-function composite bio adsorbent for removal of textile dye and COD reduction from aqueous environment.

Ammonium Recovery and Biogas Upgrading in a Tubular Micro-Pilot Microbial Electrolysis Cell (MEC).

Here, a 12-liter tubular microbial electrolysis cell (MEC) was developed as a post treatment unit for simultaneous biogas upgrading and ammonium recovery from the liquid effluent of an anaerobic digestion process. The MEC configuration adopted a cation exchange membrane to separate the inner anodic chamber and the external cathodic chamber, which were filled with graphite granules. The cathodic chamber performed the CO2 removal through the bioelectromethanogenesis reaction and alkalinity generation while the anodic oxidation of a synthetic fermentate partially sustained the energy demand of the process. Three different nitrogen load rates (73, 365, and 2229 mg N/Ld) were applied to the inner anodic chamber to test the performances of the whole process in terms of COD (Chemical Oxygen Demand) removal, CO2 removal, and nitrogen recovery. By maintaining the organic load rate at 2.55 g COD/Ld and the anodic chamber polarization at +0.2 V vs. SHE (Standard Hydrogen Electrode), the increase of the nitrogen load rate promoted the ammonium migration and recovery, i.e., the percentage of current counterbalanced by the ammonium migration increased from 1% to 100% by increasing the nitrogen load rate by 30-fold. The CO2 removal slightly increased during the three periods, and permitted the removal of 65% of the influent CO2, which corresponded to an average removal of 2.2 g CO2/Ld. During the operation with the higher nitrogen load rate, the MEC energy consumption, which was simultaneously used for the different operations, was lower than the selected benchmark technologies, i.e., 0.47 kW/N·m3 for CO2 removal and 0.88 kW·h/kg COD for COD oxidation were consumed by the MEC while the ammonium nitrogen recovery consumed 2.3 kW·h/kg N.

Evaluation of a zeolite/anaerobic buffled reactor hybrid system for treatment of low bio-degradable effluents.

The main objective of this work was to reduce the inhibitory effects of high contents of organics, ammonia, and heavy metals in an anaerobic buffled reactor (ABR), and to prevent the sludge wash-out using zeolites as media. In this work, a pilot scale of ABR with 8 compartments and a working volume of 14.4 L was used, and the last four ABR compartments were filled with a zeolite. The bioreactor was operated at HRTs of 3, 4, and 5 days, zeolite filling ratios of 10, 20, and 30%, and influent chemical oxygen demand (COD) concentrations of 10,000, 20,000, and 30,000 mg/L. The results obtained showed that the maximum removal efficiencies of COD and BOD5 reached 78 and 68%, respectively. The maximum removal was observed at a HRT of 5 days, a 30% medium filling ratio, and a COD of 10,000 mg/L. Increasing the filling ratio in the reactor increased the removal efficiencies of COD and BOD5 but increasing the concentration of the influent COD and decreasing HRT reduced the removal efficiency of the reactor. The initial BOD5/COD ratio was equal to 0.36, which increased by 46% when the medium filling ratio was elevated to 30%. The maximum biogas yield was 0.23 L/g of CODRemoved, and the specific methanogenic activity test verified the toxicity effect of the leachate on the gas-producer organisms. The results of scanning electronic microscopy and EDS showed that the zeolite medium immobilized the microorganisms and a biofilm was formed. Also the zeolite, as a well-known ion exchanger, decreased the concentrations of the major inhibitors (ammonia and heavy metals) and improved the reactor efficiency.

Water quality trend assessment in Jakarta: A rapidly growing Asian megacity.

Megacities are facing serious water pollution problems due to urbanization, rapid population growth and economic development. Water is an essential resource for human activities and socio-economic development and water quality in urban settings has important implications for human and environmental health. Urbanization and lack of sewerage has left the water in Jakarta, Indonesia in a heavily polluted condition. Rigorous assessment of urban water quality is necessary to understand the factors controlling water quality conditions. We use trend analysis to assess the current water quality conditions in Jakarta, focusing on Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), and Total Suspended Solids (TSS). In most monitoring stations analyzed, BOD and TSS concentrations have decreased over time, but from large starting concentrations. DO in most monitoring stations has increased. Although Jakarta's water quality has shown some improvement, it remains heavily impaired. The average value of BOD is low in upper stream stations compared to middle and lower stream stations. BOD and TSS trends of some water quality stations in middle and lower streams show increasing trends. Cluster analysis results suggest three groups for BOD and TSS, and four groups for DO. Understanding water quality conditions and factors that control water quality suggest strategies for improving water quality given current trends in climate, population growth and urban development. Results from this study suggest research directions and management strategies to address water quality challenges.

An environmentally friendly surrogate method for measuring the soluble chemical oxygen demand in wastewater: use of three-dimensional excitation and emission matrix fluorescence spectroscopy in wastewater treatment monitoring.

Gaining rapid knowledge of dissolved organic matter (DOM) proves to be decisive for wastewater treatment plant operators in efforts to achieve good treatment efficiency in light of current legislation. DOM can be monitored by application of fluorescence spectroscopy both online and in real time in order to derive an assessment of DOM oxidation potential. This work presents an eco-friendly alternative method for measuring the soluble chemical oxygen demand (COD) in raw sewage by means of three-dimensional fluorescence spectroscopy. A peak-picking approach has been developed based on a previous parallel factor analysis (PARAFAC) model dedicated to Paris raw sewage. Fluorescence spectroscopy parameters were used to obtain a good prediction model of soluble COD (r2 = 0.799; p < 0.0001; n = 80) for raw sewage. The approach employed in this study serves as a guideline for purposes of implementing online wastewater monitoring and conducting environmentally friendly soluble COD measurements in the laboratory.

Predicting biochemical oxygen demand in European freshwater bodies.

Biochemical Oxygen Demand (BOD) is an indicator of organic pollution in freshwater bodies correlated to microbiological contamination. High BOD concentrations reduce oxygen availability, degrade aquatic habitats and biodiversity, and impair water use. High BOD loadings to freshwater systems are mainly coming from anthropogenic sources, comprising domestic and livestock waste, industrial emissions, and combined sewer overflows. We developed a conceptual model (GREEN+BOD) to assess mean annual current organic pollution (BOD fluxes) across Europe. The model was informed with the latest available European datasets of domestic and industrial emissions, population and livestock densities. Model parameters were calibrated using 2008-2012 mean annual BOD concentrations measured in 2157 European monitoring stations, and validated with other 1134 stations. The most sensitive model parameters were abatement of BOD by secondary treatment and the BOD decay exponent of travel time. The mean BOD concentrations measured in monitored stations was 2.10 mg O2/L and predicted concentrations were 2.54 mg O2/L; the 90th percentile of monitored BOD concentration was 3.51 mg O2/L while the predicted one was 4.76 mg O2/L. The model could correctly classify reaches for BOD concentrations classes, from high to poor quality, in 69% of cases. High overestimations (incorrect classification by 2 or more classes) were 2% and large underestimations were 5% of cases. Across Europe about 12% of freshwater network was estimated to be failing good quality due to excessive BOD concentrations (>5 mg O2/L). Dominant sources of BOD to freshwaters and seas were point sources and emissions from intensive livestock systems. Comparison with previous assessments confirms a decline of BOD pollution since the introduction of EU legislation regulating water pollution.

Sediment Oxygen Demand: A Review of In Situ Methods.

Sediment oxygen demand (SOD) plays a fundamental role in biological and chemical processes within the benthic layer of a water body. Land use, including agricultural land use, can affect SOD. However, a wide variety of approaches have been used for in situ SOD chamber construction and data collection, and modelers frequently use SOD values from the literature, without consideration of the differences in methods. Here, we review existing literature on SOD chambers (32 papers, 1974-2016), compare the differences between in situ and laboratory methods, evaluate the effects of in situ chamber mixing, and discuss common challenges associated with deployment. A cohesive in situ sealed chamber design for use with a multiparameter water-quality instrument is presented as an effort toward standardizing SOD methodology, an important consideration that may facilitate integration of SOD data sets among multiple research efforts.

The evaluation of COD fractionation and modeling as a key factor for appropriate optimization and monitoring of modern cost-effective activated sludge systems.

A study was conducted to characterize the raw wastewater entering a modern cost effective municipal WWTP in Poland using two approaches; 1) a combination of modeling and carbonaceous oxygen demand (COD) fractionation using respirometric test coupled with model estimation (RT-ME) and 2) flocculation/filtration COD fractionation method combined with BOD measurements (FF-BOD). It was observed that the particulate fractions of COD obtained using FF-BOD method was higher than those estimated by RT-ME approach. Contrary to the above, the values of inert soluble fraction evaluated by FF-BOD method was significantly lower than RT-ME approach (2.4% and 3.9% respectively). Furthermore, the values for low colloidal and particulate fractions as well as soluble inert fractions were different than expected from a typical municipal wastewater. These observations suggest that even at low load (10% of the total wastewater treatment inflow), the industrial wastewater composition can significantly affect the characteristics of municipal wastewater which could also affect the performance and accuracy of respirometric tests. Therefore, in such cases, comparison of the respirometric tests with flocculation/filtration COD/BOD measurements are recommended. Oxygen uptake rate profile with settled wastewater and/or after coagulation-flocculation, however, could still be recommended as a "rapid" control method for monitoring/optimising modern cost-effective wastewater treatment plants.

Dimensionally stable Ti/SnO2-RuO2 composite electrode based highly efficient electrocatalytic degradation of industrial gallic acid effluent.

In this work, dimensionally stable Ti/SnO2-RuO2 electrode is successfully prepared using thermal decomposition method for the electrocatalytic degradation of high-concentration industrial gallic acid (GA) effluent in detail. The surface morphology, crystal structure and element analysis of as-prepared Ti/SnO2-RuO2 electrode are characterized by scanning electron microscopy, X-ray diffraction and X-ray fluorescence spectrometer, respectively. In addition, cyclic voltammetry, polarization curve and accelerated life tests are exploited to investigate the electrocatalytic activity and stability of Ti/SnO2-RuO2 electrode. Orthogonal experiment shows that, among the factors (current density, temperature and initial pH), current density is pivotal parameter influencing the degradation efficiency of industrial GA effluent. COD removal and degradation efficiencies of GA effluent reach up to 76.9% and 80.1% after 6 h, respectively, at the optimal conditions (current density of 10 mA cm-2, pH 6 and 35 °C). The degradation of GA effluent follows pseudo-first-order reaction kinetics. This work provides an in-depth theoretical support and application of electrocatalytic technology to the treatment of high-concentration industrial GA effluent.

Is dissolved COD a suitable design parameter for ozone oxidation of organic micropollutants in wastewater?

Ozone oxidation of organic micropollutants in biologically treated wastewater was investigated in pilot-scale after a high- and a low loaded activated sludge process. Higher ozone doses were required to remove organic micropollutants in the effluent wastewater from the high loaded activated sludge process. Further comparison of the micropollutant removal was based on normalized ozone doses, expressed as g O3/g DOC and g O3/g soluble COD (sCOD). A clear difference was noted for the two effluents when the micropollutant removal was normalized by DOC. This difference disappeared almost completely when the removal was linked to ozone doses normalized by sCOD. The dose-response curves for the organic micropollutants were practically linear in the removal range up to 95%. A linear prediction model was developed and compared with literature values to test the transferability of the obtained results. Results from this comparison indicated that the slope of the dose-response functions could be used to predict the removal efficiency of organic micropollutants at a third plant with an average uncertainty of 10%. The modeled ozone requirements were then set in relation to the COD concentrations in the discharged water from approximately 90 Swedish activated sludge treatment plants with and without nitrogen removal. This comparison highlighted the need for a well-functioning biological treatment for an effective ozone oxidation of organic micropollutants. The results in this study suggest that soluble COD should be further explored for design and modeling of ozone oxidation of organic micropollutants in biologically treated wastewater.

Manual or automated measuring of antipsychotics' chemical oxygen demand.

Antipsychotic (AP) drugs are becoming accumulated in terrestrial and aqueous resources due to their actual consumption. Thus, the search of methods for assessing the contamination load of these drugs is mandatory. The COD is a key parameter used for monitoring water quality upon the assessment of the effect of polluting agents on the oxygen level. Thus, the present work aims to assess the chemical oxygen demand (COD) levels of several typical and atypical antipsychotic drugs in order to obtain structure-activity relationships. It was implemented the titrimetric method with potassium dichromate as oxidant and a digestion step of 2h, followed by the measurement of remained unreduced dichromate by titration. After that, an automated sequential injection analysis (SIA) method was, also, used aiming to overcome some drawbacks of the titrimetric method. The results obtained showed a relationship between the chemical structures of antipsychotic drugs and their COD values, where the presence of aromatic rings and oxidable groups give higher COD values. It was obtained a good compliance between the results of the reference batch procedure and the SIA system, and the APs were clustered in two groups, with the values ratio between the methodologies, of 2 or 4, in the case of lower or higher COD values, respectively. The SIA methodology is capable of operating as a screening method, in any stage of a synthetic process, being also more environmentally friendly, and cost-effective. Besides, the studies presented open promising perspectives for the improvement of the effectiveness of pharmaceutical removal from the waste effluents, by assessing COD values.

Electrokinetic treatment of high saline petrochemical wastewater: Evaluation and scale-up.

High total dissolved solids (TDS) wastewater containing high amounts of organics with toxic and recalcitrant characteristics is a major concern in some petrochemical industries. This study was designed to evaluate a novel electrokinetic process for chemical oxygen demand (COD) removal. The removal of COD was carried out in some batch experiments in lab scale and effect of experimental factors such as the pH, current intensity, time, electrodes distances and TDS on the COD removal was evaluated. Also scale-up of the process was done in order to evaluate energy consumption. The obtained findings indicated that best conditions for COD removal were achieved in pH 5, current intensity of 0.5 A and electrodes distance of 2 cm. Pseudo-first-order kinetic model with rate constant of 0.0093 min-1 and significant coefficient of correlation (R2) 0.948 was the best fitted with experimental results. Energy consumption was 32 KWh.m-3 while 80 fold scaling up the reactor resulted in lower energy consumption of 2.1 KWh.m-3. Biodegradability improvement confirmed by BOD5/COD, average oxidation state (AOS) and carbon oxidation state (COS) indicators, Also GC chromatogram of the raw and treated wastewater showed removal and/or degradation of recalcitrant organics to more degradable and simpler compounds.