Need feedback if this is possible (first order removal based model)

In summary, a first order removal based model can accurately predict the removal of a substance if certain assumptions are met. These assumptions include a constant removal rate and a well-mixed system. However, there are limitations to using this model, such as its assumption of a constant removal rate and its applicability only to substances that follow first order kinetics. The removal rate constant in this model is determined by analyzing the rate of decrease of the substance over time. To validate the results of a first order removal based model, they can be compared to experimental data or data from other models, and sensitivity analysis can be performed to determine the impact of different variables on the model's results.
  • #1
beebs99
1
0
Please pardon my lack of understanding here. I am a scientist with just limited experience in calculus and de (long time ago too), but I am willing to learn.

I'm in the process of working through a theoretical model for a wastewater treatment plant that removes constituents assuming first order kinetics:

[itex]\frac{d[c]}{dt} = -k[c][/itex]

For convenience, here is the integrated form:

[itex][c]=[c_{o}]e^{-kt}[/itex]

I would like determine the effects of evaporation on removal of the constituent as it moves through the system. Based on simple chemistry, evaporation will have two effects on the concentration of C.

First, as water is evaporated and C is left behind, the concentration of C will increase due to simple enrichment.

But, here is where it gets more tricky, as water is evaporated, the retention time of C will increase within a fixed control volume receiving a constant flow since hydraulic retention time can be written as follows:

[itex]t=\frac{V}{Q}[/itex]

As you can see from the above equation, as the flowrate is decreased, the time for the first order reaction increases and removal is increased.

Now I'm trying to find a way to come up with a set of models to determine the different effects of evaporation on removal of C.

1. normal removal (done, lol):

[itex][c]=[c_{o}]e^{-kt}[/itex]

2. enrichment (no removal)

3. removal and enrichment

4. removal and the lengthened t caused by evaporation

5. removal and enrichment and lengthened t caused by evaporation

I'm having a hell of a time with this... One of the problems is that everything involving the rate equation is based on time observations (lagrangian I believe would be the term), but since I am interested in [C] at a distance from the inflow and time is no longer related to distance as water is removed (t=V/(Q-Evaporation*Area) like it would be in a problem were Q is conserved, I'm not sure how to solve this.

What I have done is create some discretized forms of the equations based on simple substitutions into the integrated first order equation (is this even a legitimate mathematical operation?).

Here's what I have... All equations are based on a simple 1-d discretized model with 100 cell blocks (i from 1-100) 1m apart and a unit surface area of 1m^2.

I first calculated the flow rate leaving each cell assuming that flow through each cell was decreased by Evaporation*Area.

For i from 1 to 100
[itex]Q_{i}=Q_{i-1}-E*A[/itex]

Then my enrichment term (concentration leaving each cell assuming no removal other than simple enrichment) is simply going to be the flow entering the cell divided by the flow leaving:

2. [itex]C_{i}=\frac{Q_{i-1}}{Q_{i}}C_{i-1}[/itex]

To add the combined effects of enrichment and removal (no modified t due to evaporation), I just combined the terms together:

3. [itex]C_{i}=\frac{Q_{i-1}}{Q_{i}}C_{i-1}e^{-kt}[/itex]

To calculate the removal enhancement caused by t increasing due to evaporation, but no enrichment, I used the equation below to calculate [itex]t_{i}[/itex] for each cell i.

[itex]t_{i}=\frac{2V}{Q_{i}+Q_{i-1}}[/itex]

And then substituted into the integrated rate law equation:

4. [itex][c]=[c_{o}]e^{-kt_{i}}[/itex]

And finally a combination of enrichment and modified t:

5. [itex]C_{i}=\frac{Q_{i-1}}{Q_{i}}C_{i-1}e^{-kt_{i}}[/itex]

Are these valid operations?

I'm really at a loss here. I assume there is some other way to do this, but I need some help. If this is in the wrong section please let me know.

Thanks
 
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  • #2
for any help you can give!Yes, the operations you have done are valid. There are other ways to approach this problem, but your approach is valid and would likely yield the desired results. The main idea is to account for the reduction in flow rate due to evaporation, and then use the integrated first order equation to solve for the concentration of C at each location. The key point is to make sure you are using the correct flow rate in all of your equations. You can also try to use a numerical approach to solve this problem if you want to explore different scenarios for evaporation.
 

Related to Need feedback if this is possible (first order removal based model)

1. Can a first order removal based model accurately predict the removal of a substance?

Yes, a first order removal based model can accurately predict the removal of a substance as long as certain assumptions are met. These assumptions include a constant removal rate and a well-mixed system.

2. What are the limitations of using a first order removal based model?

One limitation is that it assumes a constant removal rate, which may not always be the case in real-world situations. Additionally, it may not accurately predict the removal of substances in non-well-mixed systems or when multiple removal processes are occurring simultaneously.

3. How is the removal rate constant determined in a first order removal based model?

The removal rate constant is determined by analyzing the rate of decrease of the substance over time. This can be done through experiments or by using historical data.

4. Can a first order removal based model be used for all types of substances?

No, a first order removal based model is typically only applicable to substances that follow first order kinetics, meaning their removal rate is directly proportional to their concentration.

5. How do you validate the results of a first order removal based model?

One way to validate the results is by comparing them to experimental data or data from other models. Additionally, sensitivity analysis can be performed to determine the impact of different variables on the model's results.

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