@article{discovery10193418,
          volume = {63},
           month = {June},
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
       publisher = {Elsevier BV},
           title = {Enhancing flocculation kinetics assessment: Integrating aggregate size distribution into experimental and modelling frameworks},
            year = {2024},
         journal = {Journal of Water Process Engineering},
        keywords = {Aggregate size distribution, Image analysis, Flocculation, Kinetic modelJar test},
             url = {https://doi.org/10.1016/j.jwpe.2024.105433},
            issn = {2214-7144},
          author = {Moruzzi, RB and De Oliveira, AL and Sharifi, S and Bankole, AO and Campos, LC},
        abstract = {Flocculation is crucial in drinking water treatment, yet conventional techniques like jar tests may lack precision in capturing particle heterogeneity. To overcome this, a non-intrusive image-based system was employed to directly assess flocculation using aggregate size distribution (ASD). Integrating ASD into a kinetic model with a single parameter ({\ensuremath{\beta}}) allowed for tracking ASD during flocculation. Bench and pilot-plant scale experiments validated our approach. Sensitivity analysis confirmed {\ensuremath{\beta}}'s responsiveness to ASD variations (r {\ensuremath{>}} 0.92), with modelling indicating errors averaging around 5\%, underscoring its efficacy in assessing flocculation efficiency. Linking ASD coefficients from bench to pilot-scale models facilitates predicting flocculation performance.}
}