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Published on: November 1, 2018
Grit particle characterization: influence of sample pretreatment and sieving method
Q Plana1, J Carpentier2, F Tardif2
1modelEAU, Département de génie civil et de génie des eaux, Université Laval, 1065, Avenue de la Médecine, Québec (QC), G1 V 0A6, Canada E-mail: queralt.plana.1@ulaval.ca; CentrEau, Water Research Centre, Université Laval, 1065, Avenue de la Médecine, Québec, G1 V 0A6, Canada.
Standardized methods are needed to characterize grit in water resource recovery facilities (WRRFs). This study proposes adapted methods to analyze grit particle size, composition, and density for improved grit chamber design and efficiency.
Area of Science:
- Environmental Engineering
- Wastewater Treatment
- Solid Waste Management
Background:
- Grit accumulation in water resource recovery facilities (WRRFs) causes operational issues like pipe clogging and equipment damage.
- Current grit chamber design and operation lack standardized particle characterization methods, leading to inefficiencies.
- Variability in grit composition necessitates better analytical approaches.
Purpose of the Study:
- To propose a standardized methodology for sampling and characterizing grit particles in WRRFs.
- To provide data for optimizing grit chamber design and modeling.
- To enhance the overall efficiency of grit removal processes.
Main Methods:
- Adaptation and combination of existing methods for grit sampling.
- Particle size distribution analysis via sieving after various pretreatments.
- Determination of organic/inorganic fractions and particle density.
Main Results:
- Established a comprehensive protocol for grit characterization.
- Quantified particle size distribution, organic/inorganic content, and density.
- Highlighted the variability in grit properties influencing WRRF operations.
Conclusions:
- The proposed methodology offers a standardized approach to grit characterization.
- Accurate grit analysis is crucial for effective grit chamber design and performance.
- Optimizing grit removal enhances WRRF efficiency and reduces operational problems.
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