Polyacrylamide Water Treatment Pilot Test Guide

Before conducting a wastewater treatment pilot test (small-scale test), detailed water quality analysis is necessary to ensure the accuracy and practicality of the test data. So, what key parameters should we focus on during the experiment? How can we optimize chemical use to improve treatment results? This article will provide a detailed explanation.

 

Pre-experiment Wastewater Analysis

Before the small-scale test, we need to understand the following key water quality parameters:

• pHValue: Determines the optimal dosage range for the chemicals.
• Pollutant Concentration: Affects the choice and amount of flocculant.
• Influent Flow Rate: Determines the scale of the experiment and chemical dosing ratio.
• On-site Chemical Concentration: Ensures experimental conditions are close to real-world applications.

Experiment Goal: By testing different types of polyacrylamide (PAM) combined with inorganic flocculants (like PAC), we aim to find the best chemical formula and dosage to achieve optimal settling, flotation, or dewatering effects.

 

Wastewater Settling Experiment: How to Determine the Best Flocculant?

🔹 Experiment Steps:

• Prepare the Chemicals: Dissolve PAM at 0.1% and PAC at 5% for use.
• Add Inorganic Flocculant: Add the right amount of PAC to the wastewater sample and mix well.
• Gradually Add PAM: Slowly add the dissolved PAM solution and continue stirring.
• Observe Settling Effect: Focus on floc size, settling speed, and the clarity of the supernatant to determine the best PAM type and dosage.

✅ Experiment Optimization Tips:

• Flocs too small or settling slow? Adjust PAM molecular weight or increase PAC dosage.
• Flocs loose or hard to settle? PAM may be overused or the hydrolysis degree might not match.
• Supernatant still cloudy? Try a higher hydrolysis degree anionic PAM or adjust PAC/PAM ratio.

 

Wastewater Flotation Experiment: How to Optimize PAM Dosage?

The flotation process is mainly used for treating low turbidity, high oil content, or hard-to-settle wastewater. Its core is precisely controlling the flocculant dosage to ensure flocs are suitable for bubble attachment, allowing for quick flotation separation.

🔹 Experiment Steps:

• Determine the amount of inorganic flocculant (PAC) and mix evenly.
• Gradually add PAM and observe the floating of suspended solids.
• Adjust the PAM dosage until the best flotation effect is achieved (flocs are large and tight, and the supernatant is clear).

✅ Experiment Optimization Tips:

• Flocs float slowly or disperse? The PAM molecular weight might be too low; try a different model.
• Too much foam or flocs too light? PAM might be overused, or the bubble size may not be right.
• Supernatant still cloudy? Try increasing PAC dosage or changing PAM charge density.

 

Sludge Dewatering Experiment: How to Choose the Right PAM?

The key in sludge dewatering experiments is choosing the right PAM model to ensure tight flocs, easy water removal, and improved dewatering efficiency.

🔹 Experiment Steps:

• Add PAM alone (usually without inorganic flocculants), and mix evenly.
• Observe floc formation, focusing on floc size, sludge compactness, and water clarity.
• Combine with on-site dewatering equipment (like plate-and-frame or belt filter press) to choose the best PAM model.

✅ Experiment Optimization Tips:

• Loose flocs and high moisture content? PAM ionicity might be too low; switch to a higher ionicity cationic PAM.
• Sludge cake too sticky, hard to dewater? PAM molecular weight might be too high; reduce the molecular weight.
• Filtrate still cloudy? Try increasing PAM dosage or adjusting mixing speed.

 

Summary: How to Optimize Experiments Based on Actual Conditions?

🔹 Every experiment environment is different, so adjust steps and dosage based on water quality, equipment, and goals.

🔹 Through multiple tests, find the best PAM type, dosage, and ratio to improve wastewater treatment efficiency.

🔹 For professional PAM selection advice or customized solutions, feel free to contact us!

Each step in wastewater treatment affects efficiency and cost. Precise experiments make the selection process more scientific!