Physical and chemical variables as proxies for THM formation in wastewater disinfection in a Brazilian treatment plant

Abstract

Chlorination is a widely used disinfection method in Brazil's wastewater treatment plants (WWTPs) due to its cost-effectiveness. However, the formation of DBPs, such as trihalomethanes (THMs), indicates risks to human health and the environment, especially in middle- and low-income countries where DBP monitoring remains limited. To streamline monitoring, we aim to investigate how physical and chemical variables influence THM formation in sewage at a university in Brazil through regression model analysis. Raw wastewater was filtered, diluted into four proportions, and chlorinated using four hypochlorite doses. THM was measured after 24 h of contact time, and the influence of hypochlorite dose, COD, pH, turbidity, and color, on its formation was assessed. A Box-Cox regression model was developed to address nonlinearity and heteroscedasticity, achieving an R² of 87% compared to 80% in the linear regression model. The hypochlorite dose was the primary driver of TTHM formation (80%), followed by turbidity (9.8%), color (8%), and pH (3%). COD was excluded from the final model due to multicollinearity with turbidity and color, simplifying the model for practical application in resource-constrained settings. Chloroform was the dominant THM species, with its formation positively correlated with hypochlorite dose and COD levels. In contrast, brominated species exhibited no consistent patterns. This study highlights the importance of optimizing chlorine dosing and monitoring key physical and chemical parameters to mitigate DBPs formation during wastewater chlorination. The proposed Box-Cox model provides a practical and accessible framework for predicting TTHM formation, contributing to improved water quality management in regions with limited resources.