Disinfection is a critical component to ensuring access to quality drinking water and maintaining public health. Chlorine is a disinfectant regularly used in the treatment of drinking water to prevent the growth of microbes. To maintain disinfection throughout the water distribution system (WDS), a residual concentration is desired. To assist in ensuring that concentrations remain above the target minimum residual concentration, typically between 0.2-0.5 mg/L, samples are monitored throughout the WDS. However, a variety of physicochemical and biological changes can occur in drinking water as it travels from the WDS through premise plumbing and to a water user’s tap, and monitoring does not always capture these changes. This poses a problem in both the accuracy of data collected and estimation of a household’s health risk. Here, we propose a method to increase data resolution of chlorine residuals at the tap using cell-phone based colorimetric analysis of DPD chlorine test strips. We’ve shown a relationship between the test strip’s color chemistry, an image’s RGB channels, and the true chlorine residual concentration, verified with the Hach DR900 Colorimeter. We investigate the reliability and accuracy of an automated image processing toolchain using Python with concentration classification down to 0.2 mg/L and up to 2.0 mg/L. We anticipate the development of a text-to-server tool in which water users submit time-stamped, geo-tagged images to a server and receive a response indicating the chlorine concentration range in which their samples have been classified. The data collected will result in a more resolved dataset and can be shared with utilities in real-time to develop a more refined chlorine map and improved boosting strategies, where needed.

Cell-phone based colorimetric analysis of chlorine residual test strips for improved dataset resolution

ACS Spring Meeting 2021

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.