data analytics, Data to Insight, Process Modeling

Using Data to Optimize Processes: Part III—Minimizing THM Formation within a WTP

Here is another great post in the series, “Using Data to Optimize Processes” by Ruby Daaman and John Cook of ADMI. This is the third installment focusing on minimizing THM formation within a water treatment plant. As always if you want to contact John personally please email him:

and now…

It has been demonstrated that data can be used to build process models for both natural systems such as rivers, estuaries and groundwater movement over expansive areas, and can also be used to model man-made systems such as water treatment plants (WTP). The last article featured optimizing TOC removal in sedimentation basins.  This article will address optimizing total THM formation (the same approach can be used for HAA5), within the WTP, and for the purposes of brevity, we will begin optimization modeling at the clearwell, just before pumping onto the distribution system.

TTHM Clearwell Model 1 (THMCW1)

The approach is to model the clearwell TTHMs directly. The resulting model (Figure 1) predicts TTHM in the clearwell as a function of:


Figure 1. Measured clearwell THM level (blue) and modeled clearwell THM predictions using cascaded models

Figure 2 shows the response surface with inputs CL2DOSE and CL2CW3-CL2FIN_R displayed.  The first surface has water temperature (TMP) at its minimum value and all other inputs at their mean and the second has TMP at its maximum value and all other inputs at their mean.  The shape of the surface is similar, but the TTHMs in the clearwell are shifted higher.

Figure 2. Response surface of modeled clearwell TTHM levels versus Cl2 in the finished water and ratio of Cl2 in clearwell to filtered water. Note the sensitivity of TTHM levels to temperature as the response surface shifts upwards for TTHMs.

Sensitivity to pH and Alkalinity

As noted in Figures 3 and 4, TTHM formation in the clearwells is sensitive to a combination of coagulation pH and settled water alkalinity.  Chlorine dose is the largest contributor to TTHM formation, but optimizing the coagulation process can reduce the TTHM formation.  Figure 5 demonstrates the sensitivity to TTHM formation as a function of Cl2 dose and coagulation pH.  It is important to note that an increase of chlorine dosing between 1.8 and 4.7 mg/L results in an approximate increase of 80 µg/L in TTHM formation with maximum water temperature (TMP) and average settled water alkalinity (ALK).

Figure 3. Predicted clearwell TTHM levels as a function of temperature (TMP), Cl2, settled water alkalinity (ALK) and coagulation pH.

Figure 4. Top graph shows the predicted vs. actual TTHMACW. Bottom plot show the surface response showing sensitivity of TTHM clearwell formation to pH and alkalinity. Note coagulation pH and alkalinity on the bottom axes.

Figure 5. Shows five “slices” through the response surface. TTHM formation in clearwells as a sensitivity of Cl2 dose and coagulation pH. With temperature (TMP) at its maximum value and ALK at its mean, the model predicts a TTHMACW reduction of approximately 8 µg/L by maintaining the coagulation pH at around 5.4 vs. 6.3.


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4 thoughts on “Using Data to Optimize Processes: Part III—Minimizing THM Formation within a WTP

  1. We certainly agree with your position that data/results should be used to optimize the process of minimizing THM formation. My company ( manufactures an on-line THM monitor which we are just introducing to the US market.

    In anticipation of the EPA’s Stage 2 Disinfection By Product Rule, responsible utilities have invested billions in capital improvements,including GAC, aeration, UV, ozone, micro filtration, new disinfection chemistries, and many other technologies without knowing the exact impact. These utilities will also spend millions annually in additional operating expenses because they do not currently have the ability to get continuous THM measurements.

    We believe that by having the ability to measure the THM results at the plant and along distribution that the utilities will be able to better optimize their process, minimize costs, and stay in compliance.

    Please contact me if you think we can communicate this message to the industry together.

    Rudy Mui

    Posted by Rudy Mui | March 5, 2012, 2:08 am
    • Rudy,

      I think it’s great that your company has developed an online THM monitor, which would be of definite benefit to those utilities struggling to meet Phase 2, and I wish you success with this new instrument. Of course, sometimes HAA5 is problematic or the main driver. The idea behind optimization is to use existing infrastructure, or infrastructure with de minimus modifications, in say, the location of a chemical feed point or perhaps adding instrumentation and automation to better control a process to meet a new regulation.

      The easy solution, from an engineering perspective, is to add another unit process, such as GAC as you mentioned, which will work but carries with it an enormous capital and annual operating burden. The argument most frequently given is “we don’t know what will be regulated in the future, so let’s make sure we remove as much as possible”. I personally think that’s overkill as my crystal ball isn’t that precise and “the future” could mean 15 years. But who knows with any precision what will be required? With all respect, no one. We can’t predict the weather two weeks from now. Typically, the solutions we have developed reduce expenses by optimizing operations in general.

      Posted by John B Cook | March 5, 2012, 11:16 am
  2. John,

    Monitoring is inexpensive compared to construction to add and operate additional GAC filters or other technologies. Even if planning for the future, why spend more money than you need to in the present to meet unknown future regulations?

    Unfortunately, the incentives in the industry historically has been to take the easy way out as engineering firms are financially motivated to over design. However, with government budget cuts, many WTPs are now furloughing workers, making it personal for operators to look for cost savings and more cost effective solutions.

    As you mentioned HAA5, we also make a HAA5 pre concentration unit to facilitate HAA analysis. One of the reasons why current utilities don’t analyze for HAA5 more often is the difficulty of the lab analysis and the inconsistency of the results. If you know any lab that would like to trial such a system, let me know. We’d be happy to talk to them.

    Posted by Rudy Mui | March 5, 2012, 6:12 pm
  3. Has anyone started addressing the monitoring of heavy metals in-situ, and with near-realtime data? If so I would enjoy hearing about the cost trade-offs in energy savings and expendables used. We have developed an XRF system that reports all 18 heavy metals of EPA concern (depending on the day you ask them). And accurately (3 sigma) measure down to low parts per billion (ppb).

    Posted by Lynn Essman | April 17, 2012, 9:34 pm

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