Chemical Oxygen Demand (COD) is a widely used parameter in analysing and controlling the degree of pollution in water. Methods of analysis based on electrochemical sensors are increasingly being used for COD quantitation, because they could be simple, accurate, sensitive and environmentally friendly. Electro-oxidizing the organic contaminants to completely transform them into CO₂ and H₂O is considered the best method for COD estimation using sensors. In this sense, copper electrodes have been reported based on the fact that copper in alkaline media acts as a powerful electrocatalyst for oxidation of aminoacids and carbohydrates, which are believed to be the major culprits for organic pollution. Cyclic voltammetry was the technique used to obtain the voltammetric responses. Commonly, different organic compounds show different shapes of cyclic voltammograms and different current intensity in different concentrations. In this work, four kinds of copper (Cu) and copper oxide (CuO) electrodes were studied employing the cyclic voltammetry technique: Nafion film covered electrodeposited CuO/Cu electrode (NfCuO/Cu), Cu nanoparticle-graphite composite electrode (Cu-NP), CuO nanoparticle-graphite composite electrode (CuO-NP) and Ni/Cu alloy nanoparticle-graphite composite electrode (Ni/Cu-NP). Actual COD estimations are based on the measurement of oxidation currents of organic compounds. Glucose, glycine, potassium hydrogen phthalate (KHP) and ethylene glycol were chosen to be the standard substances to observe the responses, and correlate current intensity vs. COD values. From the obtained cyclic voltammograms, we can see that glucose is very easy to be oxidized by those four electrodes and electrode NfCuO/Cu shows the best calibration curve of current intensity vs. COD values with a linear range of 19.2~1120.8 mg/L and limit of detection of 27.5 mg/ L (calculated based on the formula 3σ/k). However, the compound KHP is very difficult to be oxidized. Besides, the obtained voltammetric profiles presented different shapes with the tested organic compounds, suggesting this can be used as a potential fingerprint for distinguishing the organic compounds. Consequently, Principle Component Analysis (PCA) technique was applied to try to do multivariate examination. Ongoing work is focused on optimizing measuring condition, modifying electrodes and detecting the COD values of real samples.