A low-cost sensor based on silver nanoparticles for determining chemical oxygen demand in wastewater via image processing analysis

Abstract

Chemical Oxygen Demand (COD) is a quality parameter of superficial water and wastewater that provides information on chemically degradable fractions of organic (and inorganic) pollutants. Although firmly established, the conventional colorimetric method certified by Standard Methods for the Examination of Water and Wastewater of the American Society for Testing and Materials (ASTM) requires a lengthy time for diagnosis, indiscriminate use of toxic chemical reagents and a spectrophotometer, which may not be easily available, especially in developing countries. This report proposes the development of a paper-based sensor functionalized with silver nanoparticles (AgNPs) for measuring COD content in wastewater by Image Processing Analysis. The sensor was employed on samples of real effluents with COD varying from 66 to 1160 mg L⁻¹. The color of the sensor changed from yellow to gray upon its exposure to the effluent, which is a consequence of sulfidation of AgNPs. Digital image processing was used to extract the channels from the RGB (Red-Green-Blue) color system, where the resulting dataset was evaluated with Principal Component Analysis, Multiple Linear Regression and Second Order Regression. The calibration curve presented good linearity (R = 0.96) and the COD content of wastewater was similar to that verified with the conventional method. No statistical difference was observed at a confidence level of 95%. This simple method may be envisaged as a promising alternative tool for the determination of COD in wastewater.