pH modeling for maximum dissolved organic matter removal by enhanced coagulation.

Area of Science:

• Water treatment technologies
• Environmental chemistry
• Water quality analysis

Background:

• Enhanced coagulation is crucial for removing dissolved organic matter (DOM) in drinking water.
• Controlling final pH is essential for optimizing DOM removal efficiency.
• Understanding raw water characteristics' impact on post-coagulation pH is vital for treatment plant operations.

Purpose of the Study:

• To investigate correlations between raw water characteristics and final pH after enhanced coagulation.
• To develop predictive models for final pH based on raw water quality.
• To assess the applicability of these models in practical drinking water treatment.

Main Methods:

• Investigated four coagulants: ferric chloride (FeCl3), aluminum sulfate (Al2(SO4)3), polyaluminum chloride (PACl), and high-performance polyaluminum chloride (HPAC).
• Analyzed thirteen Chinese source waters across three seasons, considering raw water quality and DOM fractionation (hydrophobic, higher apparent molecular weight).
• Developed and optimized feed-forward semi-empirical models using correlation analysis.

Main Results:

• Final pH after enhanced coagulation was influenced by removable DOM content, alkalinity, and initial raw water pH.
• Developed semi-empirical models showed low deviations between predicted and actual data during preliminary validation.
• The models successfully correlated raw water characteristics with post-coagulation pH for all four coagulants.

Conclusions:

• Raw water characteristics significantly influence pH after enhanced coagulation for DOM removal.
• The developed predictive models demonstrate potential for practical application in drinking water treatment.
• These models can aid in optimizing coagulation processes and managing final water pH.