Monitoring disinfection in onsite wastewater treatment systems with a combination of online sensors and water sample analysis for early treatment failure detection

Abstract

Centralized wastewater treatment is often infeasible in remote areas (less than 10,000 people) due to the lack of sewer systems and prohibitive development costs. Onsite wastewater treatment systems (OWTSs), the only viable option for many rural residences, pose monitoring challenges, risking public health and environmental safety during treatment failures. Low cost, real-time online sensors offer a promising solution by employing mathematical models to measure wastewater parameters in situ without extensive manual oversight. If correlated effectively with standard wet chemistry tests, online sensors could address the primary obstacles to ensuring water quality in OWTSs. This research specifically seeks to apply online sensor data collected from a pilot OWTS to predict the effectiveness of disinfection in real time. At present, there is no singular proxy that allows for the evaluation of disinfection. Wastewater treatment systems aim for a fecal coliform count of below 200 colony forming units per 100 mL, but in order to evaluate bacterial loading, incubation (for at least 18 hours) is required. Consequently, bacterial detection is delayed, and treatment failure can go unnoticed. Developing a soft sensor to allow real time detection of treatment failure is challenging because no one variable correlates perfectly with pathogenicity. However, in systems that employ peracetic acid (PAA) as their primary disinfecting agent, pH and dissolved oxygen (DO) levels may provide valuable information. By contrasting water chemistry analysis results with low-cost online sensor data from OWTSs, this research aims to identify effective parameters for remotely monitoring disinfection efficiency and water quality in inaccessible locations. Laboratory analyses of fecal coliform count, alkalinity, TKN, total nitrogen, ammonium, nitrate, nitrite, total dissolved solids (TDS), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) were conducted on water samples from an onsite wastewater treatment system in a remote part of O’ahu’s north shore. Previous studies have demonstrated potential correlations between COD, BOD, and E. coli concentrations and parameters such as turbidity, color, pH, and electrical conductivity. Centralized treatment systems show these promising correlations. This research seeks to expand that success to onsite wastewater treatment, using more robust data sets and triplicate measurements for effluent samples. Through partnership with WaiHome, a local onsite wastewater treatment company, this research will explore additional relationships between wet chemical and online sensor data to optimize monitoring practices, collaborating with engineers and manufacturers to integrate online sensor measurements into decentralized treatment plants. With potential to improve wastewater treatment monitoring across remote areas in Hawai’i and rural America, successful outcomes will enable cost-effective monitoring in real time, mitigating environmental and public health risks associated with OWTS failures.