Using Sensors for Wastewater Surcharge Reduction

When looking for operating cost savings, wastewater surcharges are often targeted because they appear to be an “easy” fix. Logically, this makes sense: If less material enters the drains, fewer pollutants will be present in the wastewater, resulting in lower sewer charges. Yet many facilities encounter difficulties when trying to translate this logic into consistent surcharge reductions.

Typically, a monthly or quarterly sampling event determines the surcharge rate for the entire period. Since that sampling window often lasts only four to five days, achieving a true long term average is challenging: One bad day can impact the annual budget. Changing operator behavior for just a few days is rarely effective, and by the time results are reported – which can sometimes be as much as five or more days after sampling – reconstructing what happened operationally can feel like chasing a moving target.

Now imagine knowing within minutes that more than average amounts of valuable product or raw materials are entering the wastewater system. With that insight, operators and managers can more easily identify process upsets, reinforce better operating practices, or address equipment issues in real time. This is where strategically placed wastewater sensors provide significant value.

When located upstream of treatment (ideally as far upstream as conditions allow, but often near the discharge side of the primary lift station pumps), sensors can provide near real time feedback on the relative strength of wastewater entering the system. Available sensor technologies include opacity/turbidity, Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Ultraviolet-Visible (UV-Vis) spectroscopy, pH, flow, and specific materials (e.g., dairy products).

Sensors used for compliance monitoring are dictated by permit requirements, but wastewater influent sensors are selected based on the facility’s products and processes. Common industry applications include:

• Opacity/Turbidity sensors for dairy, fried food, and bakery operations.
• Dairy sensors (butterfat/casein) for dairy and dairy product facilities.
• COD/BOD sensors for beverage, juice, and bakery wastewater systems.

Hixson routinely integrates influent sensors into wastewater pretreatment systems to identify relative pollutant strength and to trigger alarms when unusually high loadings occur. Each alarm presents an opportunity to correct a process, reduce product loss, and prevent unnecessary surcharges.

While sensors reveal when product loss is occurring, translating sensor data into cost impact is what truly drives action. Product loss directly affects Biochemical Oxygen Demand (BOD₅), a key parameter commonly subject to municipal surcharge fees: Higher BOD₅ means higher wastewater costs, and lost product value.

As a general rule, approximately 2,300 calories yield one pound of BOD₅. More specifically, a product’s BOD₅ contribution can be estimated from its composition using the following equation:

% BOD₅ = 1.031 (% protein) + 0.891 (% fat) + 0.67 (% carbohydrate)

Once the BOD₅ percentage of a product (or an average of multiple products) is known (see Experience in Brief for examples), product loss can be estimated using four steps:

1. Convert % BOD₅ to BOD₅ per pound of product (e.g., 5% BOD₅ = 0.05 lb BOD₅ /lb product).
2. Use flow-proportional sampling to determine the BOD₅ wastewater load:
   Flow (MGD) × 8.34 × BOD₅ (mg/L) = lb BOD₅ /day
3. Estimate product loss: Divide item 2 by item 1.  lb BOD₅ /day ÷ lb BOD₅/lb product = lb product lost/day
4. Estimate bottom line impact by multiplying product loss by ingredient cost, production cost, lost sales opportunity, and wastewater surcharge.

The results can be eye opening. For example, Hixson has observed product losses ranging from $100,000 to over $1 million per year. By pairing real time sensor data with these calculations, facilities can better quantify product losses, evaluate surcharge exposure, and prioritize corrective actions more effectively.

Experience in Brief