Determination Of Chemical Oxygen Demand Research Articles

Homojunction-Incorporated Oxygen Vacancy Functionalized Spherical TiO2 Nanocrystals for the Electrochemical Detection of Chemical Oxygen Demand.

Chemical oxygen demand (COD) is a critical criterion for the analytical assessment of the degree of organic contaminants in an aqueous system. Typically, toxic and expensive reagents are employed in standardized COD analysis methods, leading to secondary pollution. In this work, we developed a rapid electrochemical method for COD detection based on the oxidation of hydroxyl radicals for organics in water by using oxygen vacancy doped anatase/rutile-TiO2 nanoparticles as electrooxidation catalysts. Homojunction interface generated increasing oxygen vacancies for enhancing electron-transfer rate and accelerating H2O oxidation to substantially improve ·OH yield. Oxygen vacancy further increased the oxygen evolution potential of the material. Initially, glucose was chosen as a standard analyte to evaluate electrochemical responses, and water from urban wastewater treatment plants was assessed as real samples subsequently. Excellent analytical characteristics were achieved with the A/R-TiO2 sensor under the optimal conditions, exhibiting a linear range from 1 to 300 mg L-1 and detection limit of 0.1 mg L-1 COD. The estimated COD values obtained from the samples were highly consistent with those determined using the conventional standard dichromate method. We have presented a fast, cost-effective, and ecologically sustainable method that outperforms the standard COD analysis method and holds great potential for the accurate determination of COD and boasts high detection sensitivity and a broad linear range.

Simultaneous Determination of Chemical Oxygen Demand, Total Nitrogen, Ammonia, and Phosphate in Surface Water Based on a Multielectrode System.

A technique for monitoring chemical oxygen demand (COD), total nitrogen (TN), ammonia (N-NH4), and phosphate (P-PO4) in surface water with a targeted signal multielectrode system (Cu, Ir, Rh, Co(OH)2, and Zr(OH)4 electrodes) is proposed for the first time. Each water quality index is specifically detected by at least two electrodes with distinct selectivity sensing mechanisms. Cyclic voltammetry and electrochemical impedance measurements are employed for multidimensional signal acquisition, complemented by normalization and Least Absolute Shrinkage and Selection Operator (LASSO) for principal feature extraction and dimension reduction. Multiple linear regression (MLR), partial least-squares (PLS), and eXtreme Gradient Boosting (XGBoost) were employed to evaluate the established prediction model. The precisions of the multielectrode system are ±10%/±5 ppm of COD, ±10%/±0.2 ppm of TN, ±5%/±0.1 ppm of N-NH4, and ±5%/±0.01 ppm of P-PO4. The analysis time of the multielectrode system is reduced from hours to minutes compared with traditional analysis, without any sample pretreatment, facilitating continuous online monitoring in the field. The developed multielectrode system offers a feasible strategy for online in situ monitoring of surface water quality.

An integrated smartphone-based electrochemical detection system for highly sensitive and on-site detection of chemical oxygen demand by copper-cobalt bimetallic oxide-modified electrode.

Aportable and integrated electrochemical detection system has been constructed for on-site and real-time detection of chemical oxygen demand (COD). The system mainly consists of four parts: (i) sensing electrode with a copper-cobalt bimetallic oxide (CuCoOx)-modified screen-printed electrode; (ii) an integrated electrochemical detector for the conversion, amplification, and transmission of weak signals; (iii) a smartphone installed with a self-developed Android application (APP) for issuing commands, receiving, and displaying detection results; and (iv) a 3D-printed microfluidic cell for the continuous input of water samples. Benefiting from the superior catalytic capability of CuCoOx, the developed system shows a high detection sensitivity with 0.335 μA/(mg/L) and a low detection limit of 5.957 mg/L for COD determination and possessing high anti-interference ability to chloride ions. Moreover, this system presents good consistency with the traditional dichromate method in COD detection of actual water samples. Due to the advantages of cost effectiveness, portability, and point-of-care testing, the system shows great potential for water quality monitoring, especially inresource-limited remote areas.

Electrochemical determination of chemical oxygen demand using glucose standard at nickel(II) hydroxide modified electrode

A nickel(II) hydroxide modified glassy carbon electrode (Ni(OH)2/GCE) was developed for rapid and simple electrochemical determination of chemical oxygen demand (COD) which was evaluated using standard COD solution of glucose. The morphology and structure of Ni(OH)2 were investigated by scanning electron microscopy and X-ray diffraction. The electrochemical performance of Ni(OH)2/GCE was investigated by cyclic voltammetry and amperometry. Based on the high electrocatalytic oxidation activity of Ni(OH)2/GCE, the developed sensor showed a linear range of 10 - 340 mg/L with a detection limit of 2.3 mg/L, and a Cl− tolerance of 0.22 mol/L for COD determination. The Ni(OH)2/GCE was applied for the detection of COD in real water samples.

Highly sensitive electrochemical determination of chemical oxygen demand by carbon‐capsulated CuOx derived from Cu foam supported Cu‐MOF

AbstractEfficient detection of chemical oxygen demand (COD) is crucial for effective pollution prevention. Traditional Cu‐based electrodes, widely utilized for COD sensors suffer from issues related to low activity and stability. This study introduced a novel approach by employing a copper foam‐supported metal‐organic frameworks (Cu‐MOF), synthesized through a solvothermal method, which is subsequently pyrolyzed to yield a carbon‐capsulated CuOx/Cu foam electrode. Cyclic voltammetry analysis demonstrated that the carbon‐capsulated CuOx/Cu foam electrode exhibited superior redox activity, notably generating an increased amount of Cu(III) species. This enhancement significantly contributed to the electrocatalytic oxidation of organic compounds. The developed electrode demonstrated a wide linear detection range of 5–600 ppm, with a low detection limit of 0.96 ppm (S/N=3) for COD sensing. Notably, the sensor exhibited excellent anti‐interference capabilities, desirable reproducibility, and stability. The proposed method was successfully applied to determine COD in real water samples. Comparative analysis with the standard potassium dichromate method revealed high accuracy and a low relative error (2.89 %–6.72 %). This innovative approach holds promise for rapid and accurate COD detection, presenting a valuable contribution to environmental monitoring and water quality assessment.

Spectrophotometric determination of COD based on synergistic photocatalysis redox reaction using titanium dioxide nanoparticles and phosphomolybdic heteropoly acid

Chemical oxygen demand (COD) is one of the important indicators to measure the degree of organic pollution in water. In this work, a rapid spectrophotometric method for detection of COD was achieved based on the oxidation of organics in water by photogenerated holes or free radicals and the reduction of phosphomolybdic heteropolyacid by photogenerated electrons by using TiO2 nanoparticles as a photocatalyst. Taking potassium hydrogen phthalate as the COD standard, under the optimal conditions, the absorbance of reduced phosphomolybdic heteropoly acid was linear with COD in the range of 0.50–100 mg L −1. The detection limit for was COD detection was 0.171 mg L −1. The proposed methods was used for the determination of COD in real water samples, and the results were in general agreement with the national standard method. Compared with the direct photo initiated reduction of phosphomolybdic heteropoly acid without TiO2 nanoparticles, the photocatalytic reaction has better stability and higher efficiency.

Photocatalytic method for determining the water quality index

Objective. To evaluate the effectiveness of the application of the new method in laboratory studies of water quality and to determine the optimal conditions for analysis.Materials and methods. Generally accepted methods of analytical chemistry were used to determine the rate of the catalytic oxidation reaction and its practical yield. All measurements were subjected to standard statistical processing.Results. The stages and results of determining the optimal conditions of photocatalytic oxidation are presented. The prospects of using photocatalysis in sanitary supervision institutions are shown.Conclusion. The photocatalytic oxidizing system UV-nano-TiO2-K2Cr2O7 meets all the requirements for the methodology of chemical oxygen demand (COD) determination and is even more rapid, reproducible and accurate in comparison with the certified arbitration method.

Comparison of COD Determination Methods FAS Titrimetric with UV-Vis Spectrophotometry

Liquid waste is one of the factors causing contamination of the aquatic environment. One of the chemical parameters of water quality namely Chemical Oxygen Demand (COD). This research was conducted at three different concentration levels, namely low, medium, and high, with samples of river water, domestic wastewater, and sago liquid waste. The method used is UV-Vis spectrophotometry (SNI 6989.2: 2019) and FAS titrimetry (APHA, 2017 methods 5220 D); for the UV-Vis spectrophotometry method in the range 90 mg/L, the wavelength was measured at 420 nm, while for high levels in the range 100 mg/L x 900 mg/L, it was measured at 600 nm. The quality control parameters used are accuracy and precision parameters. The purpose of this study was to compare the COD determination between UV-vis spectrophotometry and FAS titrimetry and to determine the validity and correlation of the two methods—a comparison of the results of the two methods used in the F test. The results showed that the COD values from UV visible spectrophotometry and FAS titrimetry yielded good precision and accuracy values and met the acceptable limits, namely %RSD 10% and 90% accuracy %R 110%. However, the results of the COD analysis using the UV-Vis spectrophotometry method were lower by 0.8556 than the results of the COD analysis using the FAS titration method, with a correlation coefficient r2 = 0.982. The average concentration of UV-Vis spectrophotometry in samples of sago wastewater was 572.141 mg/L, domestic wastewater was 113.525 mg/L, and river water was 42.98 mg/L. The average COD level of the titrimetric method in sago wastewater was 641.888 mg/L, domestic wastewater was 219.251 mg/L, and river water was 58.016 mg/L. The results of the F test for these two methods produce an Fcount Ftable. The null hypothesis (Ho) is rejected, meaning there is a significant difference between the two methods.

Recent advances in determination of chemical oxygen demand based on photocatalytic oxidation and photoelectrocatalytic oxidation

Recent advances in determination of chemical oxygen demand based on photocatalytic oxidation and photoelectrocatalytic oxidation

Economic rationale for the use of photocatalysis for the determination of chemical oxygen demand of various types of waters

Objective. To evaluate the economic efficiency of the photocatalytic method of oxidation of organic substances in the framework of laboratory analysis.Materials and methods. Standard statistical methodsResults. The high economic feasibility of using photocatalysis to determine chemical oxygen demand (COD) has been demonstrated.Conclusion. The use of the photocatalytic method for determining COD seems economically justified and promising.

A new FTO/TiO2/PbO2 electrode for eco-friendly electrochemical determination of chemical oxygen demand

A new FTO/TiO2/PbO2 electrode for eco-friendly electrochemical determination of chemical oxygen demand

Development of an accurate optical sensor for the in situ real-time determination of the chemical oxygen demand of seawater.

Chemical oxygen demand (COD) is an important indicator for monitoring the quality of seawater. The COD of seawater reflects the levels of organic pollutants in the water. Methods that are commonly used to measure the COD of seawater have high accuracy, good repeatability, and low costs. However, using them for the in situ real-time monitoring of the COD of seawater is unfavorable because they require complex procedures and a long measurement time and may cause pollution to the environment. This paper reports on an optical sensor that accurately determines the COD of seawater in situ. The COD determination is based on the absorption of ultraviolet and visible lights with different wavelengths by organic matter in the water. Single-point LEDs emitting lights with different wavelengths (254, 265, 280, and 546nm) were used as sources of excitation lights, and photodiodes were used as receiving devices. The optical system, circuit system, and mechanical structure of the sensor were efficiently integrated. The inversion of the COD of seawater was obtained after turbidity correction using the multiple linear regression algorithm. The maximum measurement error, detection limit, and repeatability of the sensor were 5%, 0.05 mg/l, and 0.62%, respectively. Moreover, the R2 values for correlations between COD values and absorbance values measured at three wavelengths (254, 265, and 280nm) were above 0.99. Overall, the sensor is suitable for the in situ real-time monitoring of the COD of seawater. It requires a short measurement time and generates no pollution.

Bioremediation of fibreboard sludge by using bacteria and fungi

Sludge produced from the fibreboard industry releases hazardous substances that may damage the environment as well as human health via inhaled air, drinking water, and food consumed. Correspondingly, the aim of this study was to focus on the bioremediation to treat industrial wastewater sludge produced from Evergreen Fibreboard, Parit Raja, Batu Pahat, Johor by using bacteria (Sphingobacterium spiritivorum) and fungi (Aspergillus brasiliensis). Three stages of the investigation were performed, which are the collection of raw materials, the preparation of microbes, and sample analysis, including the determination of COD and heavy metals including Chromium (Cr), Copper (Cu), Arsenic (As), Lead (Pb) and Zink (Zn). From the Chemical Oxygen Demand (COD) test, Aspergillus brasiliensis shows higher potential for sludge bioremediation as 61 mg/L COD was reduced in 14 days compared to the Sphingobacterium spiritivorum which only 31 mg/L was reduced. Meanwhile, the leaching result for heavy metals shows that Zn had the highest concentrations and As was the lowest for 14 and 28 days. Inoculation of Aspergillus brasiliensis shows the lowest leaching concentration for heavy metal elements such as Cr, Cu, As, Pb and Zn compared to Sphingobacterium spiritivorum. The reduction concentrations of these elements are 13%, 22%, 17%, 33% and 6%, respectively. The result shows that the fungi strain has the highest capability to absorb metals compared to the bacteria strain. Indigenous microorganisms in sludge have the lowest potential to reduce COD and heavy metals. However, a combination with the other method such as physical and chemical processes would be recommended to improve the results in the future.

Sensing of chemical oxygen demand (COD) by amperometric detection—dependence of current signal on concentration and type of organic species

The standard method to determine chemical oxygen demand (COD) with K2Cr2O6 uses harmful chemicals, has a long analysis time, and cannot be used for on-site online monitoring. It is therefore necessary to find a fast, cheap, and harmless alternative. The amperometric determination of COD on boron-doped diamond (BDD) electrodes is a promising approach. However, to be a suitable alternative, the electrochemical method must at least be able to determine the COD of water samples independently of the contained substances. Therefore, the current signal as a function of various organic materials was investigated for the first time. It was shown that the height of the signal current depended on the type of organic matter in single-substance solutions and that this substance dependency increases with the amount of COD. Those findings could be explained by the mechanism proposed for this reaction, showing that the selectivity of the reaction depends on the ratio of the concentration of hydroxyl radicals and organic species. We give an outlook on how to improve the method in order to increase the linear working range and avoid signal variance and how to further explain the signal variance.

A carbon-dot fluorescence capillary sensor for the determination of chemical oxygen demand

The development of a highly sensitive, reusable, and microportable sensor for determining the chemical oxygen demand (COD) is very important for performing in situ measurements. A reusable carbon-dot fluorescence capillary sensor is reported here. Citric acid/urea-carbon dots were synthesized by hydrothermal treatment and immobilized on the inner surface of a capillary using sol–gel technology. The sensor were used in conjunction with a recirculating-flow system to establish a set of methods for the indirect determination of COD in water by reaction with KMnO4. The carbon dots reduce KMnO4 to produce MnO2, thereby quenching the fluorescence of the sensor through the adsorption/inner filter effect. We harnessed this mechanism to successfully determine the CODMn (permanganate index) in the range of 0.2–40 mg/L (ΔF = -48.32c + 678.25, r = 0.9996, 0.2–12 mg/L; ΔF = -16.31c + 792.61, r = 0.9998, 8–40 mg/L). The sensor was subsequently regenerated by using ascorbic acid to reduce the carbon dots and remove the MnO2 adsorbed on the inner surface. The sensor could be reused at least 20 times with a relative standard deviation of less than 0.59 %. The proposed method was applied to quantify the COD in potable, waste and natural water. Combining the sensor with the automated flow system is a potential method for in situ real-time monitoring of COD in water.

Large-scale prediction of stream water quality using an interpretable deep learning approach

Deep learning methods, which have strong capabilities for mapping highly nonlinear relationships with acceptable calculation speed, have been increasingly applied for water quality prediction in recent studies. However, it is argued that the practicality of deep learning methods is limited due to the lack of physical mechanics to explain the prediction results of water quality changes. A knowledge gap exists in rationalizing the deep learning results for water quality predictions. To address this gap, an interpretable deep learning framework was established to predict the spatiotemporal variations of water quality parameters in a large spatial region. Mereological, land-use, and socioeconomic variables were adopted to predict the daily variations of stream water quality parameters across 138 sub-catchments in a total of over 575,250 km2 in southern China. The coefficients of determination of chemical oxygen demand (COD), total phosphorus (TP), and total nitrogen (TN) predictions were over 0.80, suggesting a satisfactory prediction performance. The model performance in terms of prediction accuracy could be improved by involving land-use and socioeconomic predictors in addition to hydrological variables. The SHapley Additive exPlanations method used in this study was demonstrated to be effective for interpreting the prediction results by identifying the significant variables and reasoning their influencing directions on the variation of each water quality parameter. The air temperature, proportion of forest area, grain production, population density, and proportion of urban area in each sub-catchment as well as the accumulated rainfall within the previous 3 days were identified as the most significant variables affecting the variations of dissolved oxygen, COD, ammoniacal nitrogen(NH3–N), TN, TP, and turbidity in the stream water in the case area, respectively.

Electrochemical Determination of Chemical Oxygen Demand (COD) in Surface Water Using a Microfabricated Boron-Doped Diamond (BDD) Electrode by Chronoamperometry

Chemical oxygen demand (COD) is an important indicator of the degree of organic pollution in water. However, the development of integrated and batch COD electrochemical sensors has always been challenging. In this study, a three-electrode integrated electrochemical sensor for the measurement of COD in surface water was evaluated. Using microfabrication with a microelectromechanical system (MEMS), the sensor was mass-produced and integrated with boron-doped diamond (BDD), Pt, and Ag/AgCl electrodes on the chip. The determination of glucose in optimal conditions provided a linear range from 5 to 200 mg L−1, a detection limit of 3.899 mg L−1, and satisfactory linearity (R2) of 0.998. As the sensor was fabricated by MEMS technology, good reproducibility was experimentally verified with relative standard deviations less than 4%, which suggests mass production of the sensor. The sensor was calibrated to be relatively stable in the presence of Cl− and NO2 −. A low-cost, miniature (6 mm2), and stable COD sensor was designed using microfabrication technology that may be mass-produced to build a water quality detection network in the Internet of Things era.

Design and Practice of the Experiment on the Determination of Chemical Oxygen Demand in Water Samples by Potassium Permanganate Method under the Interdisciplinary Perspective

Design and Practice of the Experiment on the Determination of Chemical Oxygen Demand in Water Samples by Potassium Permanganate Method under the Interdisciplinary Perspective

Quantitative Estimation of COD Values from an Array of Metal Nanoparticle Modified Electrodes and Artificial Neural Networks

Water quality monitoring has become critical in modern societies in multiple areas and at different stages. In this regard, chemical oxygen demand (COD) has become a key index in water testing, as it readily allows the determination of its overall quality and the presence of organic contaminants. However, conventional COD determination presents several drawbacks in view of the use of toxic reagents and possible interferences. The electrochemical determination of COD can be an alternative with many advantages, especially if using an array of sensors. Herein, the use of an electronic tongue (ET) for the estimation of COD was explored. The proposed ET was formed by an array of five voltammetric electrodes modified with different metal nanoparticles. An artificial neural network (ANN) model was built based on the responses of the array towards glucose and glycine as standards. This model was then used with real and spiked water samples, and the results compared to the electrochemical calibration and the commercial COD colorimetric methods. While the COD values of the real samples were low and outside the range of the ANN model, a satisfactory prediction for the spiked samples was achieved, showing a good agreement with the reference colorimetric method, that was better than the performance of the conventional electrochemical calibration method.

Treatment of dairy wastewater with tubular ceramic membrane

This work illustrates the fabrication of tubular ceramic membrane with extrusion machine using low cost clay materials such as kaolin, quartz, CaCO3, boric acid, feldspar and carboxymethyl cellulose. The raw membrane was kept at ambient temperature for 24 hrs. It is sintered at 950 °C at a heating rate of 0.5 °C per minutes for 6 hrs in stepwise muffle furnace. The fabricated membrane is characterized with pure water permeability and porosity measurement. The pore size of 1.49 µm and permeability of 5.438 × 10−8 m/s.kPa are obtained from pure water permeability test. The tubular membrane was tested for dairy wastewater at different pressure (13.79–55.16 kPa) on a microfiltration range. With increase in the applied pressure the removal rate of chemical oxygen demand (COD) decreases showing optimum removal of 52.08 % at a low pressure of 13.08 kPa. Along with the COD determination, various parameters of the dairy wastewater were also measured like pH, conductivity and turbidity. The obtained pH, conductivity and turbidity of feed are 7.11, 2 mS/cm and 45 NTU respectively. Moreover, the prepared tubular membrane was examined for the fouling mechanism using four conventional pore blocking models.