Drinking water treatment includes a series of processes aimed to remove surface water contaminants to produce safe water for human consumption. Among all pollutants, the natural organic matter (NOM) removal is challenging for drinking water treatment plants (DWTPs). NOM is composed of organic compounds resulting from decomposition and microbiological activity. NOM is heterogeneous, fluctuates, and has the capacity to react with the chemical compounds used during water disinfection, generating disinfection by-products (DBPs), which are regulated compounds due to their toxicity. Coagulation is located in the conventional treatment, which is a process presenting the high potential for NOM removal. Coagulation is a physicochemical process consisting of the addition of some reagents to induce water pollutants sedimentation, ergo removing NOM. Coagulation is a widely implemented treatment and its optimization relies on NOM fractionation and the optimization of coagulation conditions (reagent dosages).

Jordi Suquet Masó thesis “Development of an environmental decision support system to enhance coagulation in drinking water treatment plants” has investigated the optimization of the coagulation process through the development of Environmental Decision Support Systems (EDSS). EDSS are artificial intelligence tools that allow integrating data, models, and expert knowledge providing response systematization and time reduction. Digitalization strikes the water sector as is affecting the whole society. Hence, the appearance of economically competitive online sensors and analyzers provide real-time NOM-related parameters from water source and treatment, and this includes coagulation. These data are continuously recorded in DWTPs databases. The evaluation of this data provides information useful to detect trends and behaviors, and valuable to determine the optimal operational conditions.

The researcher has focused his research on three DWTPs located in Catalonia, which present management challenges related to the Mediterranean basin. His doctoral thesis has involved numerous data acquisition and analysis tasks. From here, some works were performed, related to enhanced coagulation, data evaluation, and scenario identification to conclude with the development and assessment of the enhanced coagulation models which were integrated into a final EDSS proposal.

Results obtained have been published in international scientific journals and will contribute to optimize NOM removal in DWTPs. The main contributions are:

• River water presents unpredictable NOM fluctuations characterized by high turbidity, thus determining the optimum coagulation conditions. In reservoirs, baseline NOM cases are related to extreme weather episodes.
• A specific methodology was developed and enhanced coagulation empirical models were developed for the three case studies.
• Influent NOM scenarios were detected using a clustering algorithm and the optimal operation conditions for coagulation were identified in each case.
• Significant factors for enhanced coagulation models were determined for each scenario and water catchment (river, swamps).
• Hydrophobic NOM dominates peak NOM scenarios. Therefore, it is crucial to remove UV₂₅₄ during coagulation to minimize DBPs.
• An EDSS with a three-level architecture (data acquisition, control, and supervision) has been developed and validated aimed to remove NOM through enhanced coagulation. This system is performed to remove 62% of turbidity, 21% of total organic carbon, and 25% of UV₂₅₄.
• A control system has been developed and tested with real data to minimize the formation of trihalomethanes (THM) through enhanced coagulation.

This thesis has been supervised by Dr Hèctor Monclús and Dr Lluís Godo and will be defended next Friday, July 29th, at Aula Magna of the Faculty of Sciences of the University of Girona.

Main publications: Assessing the effect of catchment characteristics to enhanced coagulation in drinking water treatment: RSM models and sensitivity analysis, Science of the Total Environment, 79910, 2021, 149398, DOI: 10.1016/j.scitotenv.2021.149398 // Development of an environmental decision support system for enhanced coagulation in drinking water production, Suquet et al, Water, 12, 8, 2020, 2115, DOI: 10.3390/W12082115.