Effluent treatment system design

Pergamon PII: SOOOS-2509(97)00186-3

Effluent treatment system design Wen-Chu Janice Kuo and Robin Smith Centre for Process (Received

Integration,

UMIST,

PO Box 88, Manchester

3 June 1996; in revised form 4 February

1997; accepted

M60 1QD. U.K 29 May 1997)

Abstract-This paper addresses the design of distributed effluent treatment systems. In the case of single contaminants, targets are first set for the minimum flowrates in a distributed effluent treatment system. Design methods then allow the targets to be achieved in practice. Previously published methods failed to address important features of the design for multiple treatment processes. In the case of multiple contaminants the treatment network is developed in a staged approach by repeated use of targets and design. Minimum flowrate is not guaranteed for multiple contaminants, but the designer is guided towards the best solutions. Overall, the paper presents improved methods for the design of distributed effluent treatment systems and extends the concepts to retrofit cases. \c 1997 Elsevier Science Ltd

INTRODUCTION

Effluent treatment is most often carried out by collecting aqueous process effluents into a common sewer along with utility effluents such as cooling tower blowdown and then treated in a central facility before being discharged to the receiving water. This centralised treatment might include primary, secondary and tertiary treatment processes. The stages needed depends on the contaminants, their concentrations and the discharge regulations of the effluent. However, the characteristic of centralised treatment systems is that they treat large volumes of wastewater with low concentrations of contaminants resulting from the mixing of wastewater streams before treatment. Eckenfelder et al. (1985), Lankford et al. (1988) and Higgins (1989) highlighted that segregated wastewater treatment could have significant advantages over centralised wastewater treatment. McLaughlin et al. (1992) pointed out that capital and operating costs of most wastewater treatment operations are proportional to the total flowrate of wastewater which flows through the treatment. Also, costs increase with the decreasing concentration for a given mass load of contaminant. Study of the optimal design of wastewater treatment systems has focused on the optimisation of specific units or small groups of units. Few studies have addressed the optimal structure of wastewater treatment systems. What is needed is an approach to the design of effluent treatment systems which segregates effluent streams for treatment in the first instance and only combines them if it is appropriate. Takama et al. (I 980) presented a non-linear programming approach to optimise distributed wastewater treatment systems. Wang and Smith (1994) presented a graphical 4273

representation which allowed targets to be set for the minimum flowrate in a distributed effluent treatment system. These targets were set before the design. Design rules were also developed to allow the targets to be achieved in practice. The design rules were based on the location of the pinch for the system. Streams starting above the pinch for the treatment process are fully treated, those starting at the pinch are partially treated and partially bypass treatment and those starting below the pinch completely bypass treatment. Although the general methodology presented by Wang and Smith (1994) provides valuable insights into the design of distributed effluent treatment systems, there are some drawbacks associated with the method. The method fails to predict the lowest possible target for the treatment flowrate in some cases. The reason for this will be discussed in detail later. In addition, important features of the design for multiple treatment processes in both single and multiple contaminant cases were not addressed. The objectives of the methodology for the design of distributed effluent treatment systems are to:

(i) Choose the most appropriate type and number of treatment operations. (ii) Design a network for the treatment operations which segregates streams for treatment where appropriate and mixes them where appropriate. (iii) The resulting distributed effluent treatment network should bring the effluent streams to their required consent limits for discharge at minimum cost. Because the capital and operating costs of effluent treatment operations are most often dominated by flowrate, the methodology in the first instance

W.-C. J. Kuo and R. Smith

4274 will seek to minimise treated.

the flowrate

of effluent

to be

The methodology presented in this paper thus provides an initial network design which must then be subjected to detailed simulation and costing before the final design is accepted. Such detailed evaluation might lead to features of the initial design being unacceptable, requiring iteration back to the targeting and network design. Previous work also did not address the case of retrofit of the existing system. Upgrade of existing treatment systems to comply with new regulations is an important consideration for which no systematic methods are currently available. This paper presents improved methods for the design of distributed effluent treatment systems and extends the concepts to retrofit cases. NEW TARGETING PROCEDURE FOR SINGLE CONTAMINANTS

Background The method introduced by Wang and Smith (1994) for targeting single contaminants starts by representing the data on a plot of concentration vs contaminant mass removed. Table l(a) presents data for a set of effluent streams. This is a single contaminant problem for which the environmental discharge limit is 30ppm. The data from Table l(a) are presented graphically in Fig. l(a). These individual effluent streams are then combined to produce a composite of the effluent streams as shown in Fig. l(b) (Wang and Smith, 1994). An effluent treatment line then needs to be matched against this curve. The performance of the treatment process can be defined either in terms of a specified outlet concentration or a removal ratio defined by RR

-.LwtCout

=.LCin

.hnCin

800

.

. . . . . ~ . . ..__.

’

(1)

For example 1, the performance of the treatment processes are specified by removal ratios, Table l(b). Applying the treatment processes in Table l(b) will not allow the treatment task to be solved with a single treatment process because of concentration and performance constraints. Figure l(c) shows one possible solution with effluent treatment lines for Treatment Process I (TPI) and Treatment Process II (TPII) matched against the composite effluent curve (Wang and Smith, 1994). Treatment lines have been specified with the steepest slope in order to minimise the flowrate of effluent to be treated. The slope is limited both by the performance specifications for the unit and the pinch for the system (Wang and Smith, 1994). Alternative solutions are possible by changing the distribution of mass loads removed between the two treatment processes. Moreover, the treatment processes might have been put the other way around in the alternative sequence. These two issues of different mass load distributions and different possible sequences will be addressed later. First, let us accept the

Table 1. Wastewater stream and treatment process data fort Example 1 (a) Wastewater stream data Stream Number

Flowrate (t/h)

1 2 3

Concentration @pm)

20 30 50

800 400 200

Removal ratio (%)

Gin,,,_ (ppm)

90 99

600 200

(b) Treatment process data Process Number I II

_

m (kg/h)

(a) Individual

effluent streams

(b) Composite

effluent curve

(c) Possible effluent treatment targets

Fig. 1. The individual effluent streams can be represented by a composite effluent curve.

Effluent treatment system design distribution of mass loads and the sequence and explore whether the target predicted by the method of Wang and Smith (1994) as used in Fig. l(c) actually gives the lowest possible target. Turyeting multiple treatment processes If we now tear the diagram in Fig. l(c) into two parts, the effluent treatment designs for TPI and II can be designed from the procedure presented by Wang and Smith (1994). Streams starting above the pinch for the treatment process are fully treated, those starting at the pinch are partially treated and partially bypass treatment and those starting below the pinch completely bypass treatment. The resulting design for TPI and TPII are shown in Figs 2(b) and (c). Combining the networks for TPI and TPII, the resulting network is shown in Fig. 2(d). In Fig. 2(c) the outlet of TPI with lower concentration C’, is mixed with wastewater stream 3 and fed directly to TPII. We shall designate this kind of arrangement to be treatment processes operating in series. It is a characteristic of the previous targeting method for multiple treatment processes that the design structures which emerge are always series in nature. Yet, it is conceivable that parallel structures might sometimes be attractive, in which the outlet of one treatment does not necessarily feed the next treatment process, and so on. In Fig, 2(b), after TPI the concentration and flowrate of wastewater streams have been changed. Instead of the original concentration order of C, > Cz > C3, the new concentration order after the TPI placement switched to C3 > C’,, where C’, is the outlet concentration of TPI. Thus, the remainder of

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the problem will not behave like the line FG shown in Fig. 2(a). To obtain the true picture after placing TPI we need to replot the new effluent treatment curve based on new concentration order, C3 > C’, Figure 3(a) starts by placing TPI and then constructing the composite effluent curve after TPI has been placed, which is line HJ in Fig. 3(b). Adopting this approach allows the minimum treatment tlowrate for TPII’ to be reduced when compared with Fig. l(c). The original composite effluent curve is also shown in Fig. 3(b) as the dashed curve. The new targeting line for TPII’ actually crosses the original composite effluent curve which would not be allowed by the previous method. If there is only one treatment process, the treatment targeting line should always operate beneath the effluent treatment curve. If the treatment line crosses the effluent treatment curve it is infeasible to achieve the mass transfer task, for reasons presented by Wang and Smith (1994). However, with multiple treatment processes. there are multiple treatment targeting lines and we need to look at the overall treatment system. This means that we should construct a composite of al1 treatment lines to judge the overall feasibility. There might be some treatment targeting lines which cross the composite effluent curve on an individual basis without the composite treatment curve crossing. The composite treatment curve must not cross the composite effluent curve. Figure 4 compares the individual treatment lmes with the composite treatment line based on the new targeting line for TPII’. The composite treatment curve shown in Fig. 3(b) lies below the effluent treatment curve and is therefore feasible. In addition. it

(b) WI

Fig. 2. The design implications

of placing

multiple

treatment

c,

processes

4216

W.-C. J. Kuo and R. Smith

Fig. 3. Basing targets on unmixed streams leads to a result which looks infeasible by the original composite effluent curve.

Effluent Treatment Curve

Curve)

0

m

Fig. 4. The composite treatment line does not cross the effluent composite curve and is therefore feasible.

confirms that TPII only needs the 49.5t/h capacity shown in Fig. 4(a) instead of 77.4 t/h flowrate requirement shown in Fig. l(c). Based on the target in Fig. 4(a), the effluent treatment network for TPII can be obtained from the previous design rules and is shown in Fig. 5(a). The network for the complete system can be obtained by combining Fig. 2(b) and 5(a) as shown in Fig. 5(b). In Fig. 5(b), it can be seen that the treatment processes

operate in parallel since the outlet of TPI does not feed to TPII directly. Such structures could not be obtained from the previous targeting method. Distribution of mass load for multiple treatment processes Consider again the data in Table 1. Figure l(c) shows possible effluent treatment targets to be 50 t/h for TPI and 77.4 t/h for TPII. This result has now

Effluent treatment

been revisited and the true targets shown to be 50 t/h for TPI and 49.5 t/h for TPII. As mentioned previously, alternative solutions are possible by changing the distribution of mass loads removed between the two processes. Wang and Smith (1994) suggested that the maximum mass load should be removed by the cheaper treatment process. This result is straightforward if the ratio of costs for TPII and TPI is extremely high. However, should the mass load allocated to the cheaper treatment process (TPI) always be maximised? Figure 6 shows the option which allocates the maximum mass load to TPI. Comparing the two options in Figs 4(a) and (6), the second shown in Fig. 6 involves a flowrate increase of 50 t/h in TPI while the flowrate required for TPII decreases by 28.2t/h. If there is not a large cost differential between TPI and TPII then the first solution shown in Fig. 4(a) might be economically more attractive.

(a)

-1

Dfscharge I

I

(b)

Fig. 5. Completing treatment

the design leads to a network processes operate in parallel.

in which

system design

3277

One way to optimise the mass load for a system which requires multiple treatment processes is to first fix the relative loads arbitrarily. Having set the targets, this would lead to a structure for the treatment system (Wang and Smith, 1994). Once the structure of the treatment system has been specified we can vary the load on each treatment process to minimise the cost. If we optimise a fixed structure the flow ratio for each bypass stream might change, or the whole bypass stream might be removed, but the basic structure will remain unchanged. Consider the initial structure in Fig. 7. The optimisation might lead to the whole of Stream 1 being fed to Treatment Process 1 as shown in Fig. 7(a) or Stream 3 being fed to Treatment Process 11 completely shown in Fig. 7(b). However, we would not be able to obtain the structure shown in Fig. 7(c) since this involves a fundamental change to the basic structure. Optimisation of the initial structure can, in principle, remove features such as bypasses but structural features cannot be added. Therefore, optimisation of the initial structure will be able to access some structures but others will not be able to be accessed. Thus, fixing the loads arbitrarily early in the procedure means that attractive designs might be missed even after extensive optimisation. An alternative approach shown in Fig. 8 would be to optimise targets instead of optimising a single structure. In optimising targets, the approach would be to vary m, and thus the mass load removed by each treatment process, Fig. 8. At each setting, the target flowrate for each treatment process allows the total cost to be estimated through cost functions which express total costs as a function of treatment flowrates (and mass load if the cost model requires). Thus, in Fig. 8 the cost is optimised based on targets. This shows that total costs vary when the mass load removed from each treatment process is redistributed depending on the cost ratio of TPl to TPII. Four different cost curves are shown in Fig. X. The cost

21.3 t/h Fig. 6. Maximizing

mass load on the cheaper

treatment

process

for Example

1

W.-C. J. Kuo and R. Smith

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Optimize the structure

Fig. 7. Continuous optimisation can change the bypass flowrates but not the structure.

/1 TPI/TPII=l /

i TP I /TP II = 0.8

TP I I TP II = 0.3 c2

1’2

: ‘-,_

14.4

-

-’

:Nc_#M

25.2

i

I

TPI/TPII=0.5

34.2

m,(kgjh)

Fig. 8. The targets can be optimised instead of optimising a design.

curves in Fig. 8 do not represent the absolute cost relating to the different cost ratios, but show the trends. The curves in Fig 8 indicate that different cost ratios for TPI to TPII will produce different locations for the optimum. Thus, we should not always maxi-

mise the mass load removal in the cheaper treatment process. Most importantly, whatever relative costs we are going to use, different effluent treatment structures can be explored in the optimisation by optimising targets.

Effluent treatment system design Each point on the curves shown in Fig. 8, in principle, represents one treatment structure. Alternatively, there might be a range of conditions leading to the same structure. As long as the setting of the mass load which divides the two treatment processes is located within the same region of the composite effluent curve, i.e. between kinks on the composite effluent curve. the resulting structure will turn out to be the same. Thus, in Fig. 8. as long as the setting which divides the two processes is between points E and F the same structures will emerge even though bypass flowrates will change. Once a kink in the composite effluent curve is crossed then different structures will emerge as a result of the change in the effluent stream population comprising that part of the composite effluent curve. Figure 8 shows that some cost ratios are likely to lead to a local optimum if an inappropriate initial setting is chosen. Optimising targets avoids this problem allowing the global optimum to be obtained. Treatment process sequence Figure 9 shows that there could be two alternatives for the same mass load distribution. TPI can be located either prior to or after TPII. Both options should in principle be examined at the targeting stage. However, the performance of some treatment processes will decline with the decreasing concentration for a given mass load of contaminants. For example, if TPI shown in Fig. 9(a) has a maximum inlet concentration constraint, Cin.max, Fig. 9(b) would not be acceptable since the sequence would need TPI to operate at high concentration and it conflicts with the constraint. A practical example of this could be an API separator which achieves a removal ratio of typically 70% for oil removal but it will only be effective at higher oil inlet concentrations. Therefore API separators are used upstream of wastewater treatment to

Fig. 9. Concentration

constraints

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handle the higher oil concentrations. Some treatment process sequences are fixed by these kinds of treatment process constraints. Later we shall consider a refinery case study and revisit this problem. In most cases the treatment process constraints will have a major influence on the sequence. However, if process constraints do not dictate the sequence of treatment processes then one way to solve the problem would be to carry out an exhaustive search across the feasible options. Later we shall introduce a method based on thermodynamics which can help to choose the best sequence. TARGETING

AND DESIGN FOR MULTIPLE CONTAMINANTS

Background So far we have restricted consideration to single contaminants such as chemical oxygen demand or suspended solids. However, most wastewater problems involve multiple contaminants. Wang and Smith (1994) suggested an approach which initially targeted for each contaminant in isolation. The highest flowrate obtained across all contaminants for a treatment process was taken to be the target for the treatment process for the multiple contaminant case. Design for multiple contaminants was carried out by first designing a network for each contaminant in isolation and then merging the sub-networks. By including all features from all sub-networks in the final design a multiple contaminant design was obtained. Table 2 presents data for Example 2 which consists of three wastewater streams containing three contaminants A, B, C at different concentrations. The wastewater concentrations for each contaminant must each be brought down to IOOppm before discharge to the receiving water. Three effluent treatment processes are available in Table 7. Each

might dictate

the treatment

process

sequence

W.-C. J. Kuo

4280

treatment process can only remove one contaminant. The removal ratios of the treatment processes are specified in Table 2. Following the methodology of Wang and Smith (1994) we target and design each individual contaminant. The result is shown in Fig. 10. The next step is to merge the three sub-networks to obtain the final treatment network for all contaminants together. But this is not straightforward. The sub-network shown in Fig. 10(b) suggests that stream 3 should combine with part of Stream 1 and the combined wastewater stream passed to

Table 2. Stream (a) Stream data

and treatment

process

data for Example

2

Contaminant Flowrate

Stream number 1 2 3

(b) Treatment

A

B

C

(t/h)

(ppm)

(ppm)

(ppm)

20 15 5

600 400 200

500 200 1000

500 100 200

process

data Removal

ratio (%)

Contaminant Process number I II III

A

B

C

90 0 0

0 99 0

0 0 80

Contaminant A

0

TPII for removal of contaminant B. On the other hand, Fig. 10(c) suggests that we should take part of stream 3 to mix it with stream 1 and the combined wastewater stream sent to TPII for removal of contaminant C. Those two proposals have inherently incompatible and is a problem fundamental to the previous procedure.

Superstructure

approach

One approach to the solution of this problem is to create a superstructure for the final network containing all structural features from the individual subnetworks. The superstructure should contain all structural features which are candidates for the global optimum network. Optimisation of this superstructure in a combined structural and parameter optimisation will then remove unnecessary features from the design. Figure 11 shows the superstructure of Example 2 based on the three sub-networks from Fig. 10. Six pathways (paths P, Q, R, S, T, U) are included in the structure and they provide all possible treatment process sequences. This enables us to embed all possibilities in the superstructure. In principle, there should not be more than two pathways left after optimisation in the final network for a three treatment process problem. For example, only paths U and Q will be needed in the final design if the treatment process sequence turns out to be TPII followed by TI followed by TPIII. Optimisation of the superstructure would remove unnecessary features. However, it is clear that even for this very simple problem we are left with a complex superstructure to be optimised. This is a difficult mixed integer non-linear optimisation problem. The difficulties in carrying out such

Contaminant B

mA

0

(a) Fig. 10. Multiple

and R. Smith

contaminant

Contaminant C

m6

0

mc

(W problems

start by targeting

and design of each contaminant

in isolation.

Effluent treatment

system design

428

t

Fig.

Il. A superstructure

approach

optimisations are well known, the greatest problem being that of the optimisation finding local optima rather than the global optimum. Figure 11 shows the superstructure which, although complex, is simpler than a superstructure for the original problem which would contain all possible structural features. The dashed lines in Fig. 11 are the extra connections required to include all possible structural features. The superstructure in Fig. 11 is based on the sub-networks for the individual contaminants and thus allows some structural features to be discarded through the physical insight from the targeting procedure for single contaminants. Whilst the superstructure in Fig. 11, based on single contaminant targeting, brings some simplification it is not too significant. It is still a complex network for optimisation. If the treatment process sequence can be determined, the possible combinations can be reduced further. Staged approach to building (I network In principle, the streams detailed in Table 2 can be fed to TPI, TPII or TPIII in any sequence. Single contaminant targeting tells us the combinations of wastewater streams to be treated for different contaminants, but the sequence of treatment processes must be decided through the merging of sub-networks, which often encounters conflicts. The problem seems to be one of a lack of guidelines for merging. On the other hand, the superstructure approach does, in principle, provide a universal solution but the optimisation is difficult and does not allow the designer to interact with the solution. The sub-networks shown in Fig. 10 are based on minimum treatment flowrate required for removal of a certain contaminant. It is important that the three

to multiple

contaminant

I

Discharge

problems

treatment processes should be included but we can only accept one proposal a time. Once the wastewater has been sent to the treatment process selected first, the wastewater flowrates and concentrations of different contaminants will be changed, since some of wastewater streams will have been combined. In total there are six different sequences for the three treatment processes. One way to deal with the problem would be to explore all six different sequences and then choose the best. Let us instead develop a better way based on thermodynamics. Single contaminant targeting for multiple contaminunt problems For each contaminant, targeting tells us what happens to that specific contaminant and how wastewater streams should be segregated for the removal of that contaminant. Unfortunately, we do not know what is happening to other contaminants while we are targeting for the contaminant under consideration. For example, Fig. 12 shows the target and sub-network design. The sub-network design in Fig. 12 shows stream 1 mixing with part of stream 2 to optimise contaminant A removal. But does it create problems for the treatment for contaminant C? The concentration of contaminant C in stream 2 is 100 ppm which is the same as the environmental limit. We should therefore be able to discharge stream 2 directly as far as contaminant C is concerned. If we accept the subnetwork shown in Fig. 12, we have carried out degradation as far as contaminant C is concerned, caused by inappropriate stream mixing. In other words. each sub-network shown in Fig. 10 is proposed by considering contaminant only and minimising treatment flowrate for each treatment process for that

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W.-C. J. Kuo and R. Smith

where AH is heat of mixing; ni is molar flowrate (kmol/h) and Xi is mole fraction for each component. Since wastewater streams are usually dilute solutions and if assumed to be an ideal solutions, AH can be omitted. Therefore, this equation can be rewritten as

Contaminant A

AEx = - RTl,iniln$ I

I

OI

Mixing (4)

.

Fig. 12. Targeting for contaminant A does not account for the mixing of contaminants B and C.

contaminant. However, each sub-network incorporates some degradation in the concentrations of the other contaminants which can result in the treatment flowrate in the following treatment processes to be increased. If the total cost for the effluent treatment system is proportional to the total treatment flowrate for the system, then the lower the total treatment flowrate, the lower the total cost of effluent treatment. The lowest total treatment flowrate will be the sum of all targeting flowrates in the sub-networks. However, we have already concluded that it is not always possible to maintain the features of each sub-network due to the wastewater degradation occurring in each subnetwork. No matter which sub-network we accept, wastewater degradation will happen simultaneously. If wastewater degradation is unavoidable for each treatment process placement, it makes sense to minimise the wastewater degradation as much as possible whilst selecting the treatment process sequence. Evaluation

of wastewater

degradation

In qualitative terms it seems desirable to avoid degradation as much as possible. But before the concept can be made quantitative we need a method to allow degradation to be evaluated. Since wastewater degradation is caused by inappropriate mixing, we need some characteristic which can quantity the extent of mixing. Mixing exergy loss can be used to express how much potential the system loses through mixing and might provide a measure of the extent in the wastewater degradation. Generally, the mixing exergy loss for ideal solutions can be expressed as

AEx=AH-RRT,iniln& 1

I

(2)

where ni is measured in kilomoles per hour. If the contaminants are known, then the mole fractions and mole flowrates can easily be calculated. In this case we might not know the exact molecular weight for each contaminant. Here we shall assume that all contaminants have the same molecular weight as water (Mu20 = 18). Clearly, if information is available on the individual contaminants then it is not necessary to introduce this approximation. The main concern is the value of the exergy loss as a measure of extent of wastewater degradation simply to choose between competing options. To choose the sequence of treatment processes we do not need the exact value of exergy loss but simply the correct relative magnitudes between options. Taking an average molecular weight the above equation can be rewritten as AEx

=

-%imilnd 1.m. mi

I

(5)

where Mi = Mj = M. As an example, the targeting of contaminant A leads to a design involving stream 1 mixing with part of stream 2 before treatment in TPI as shown in Fig. 13(a). Contaminants B and C will be degraded through the mixing and the mixing exergy loss, AExuiC,, should be calculated based on the degradation of these contaminants. In another situation, if contaminant B is being targeted, the mixing exergy loss should be calculated for contaminants A and C as AEx(,,o> as shown in Fig. 13(b). Similarly, AEx~~,~), is calculated if contaminant C is being targeted, as shown in Fig. 13(c). Comparing across options after targeting for each contaminant, the option with the minimum exergy loss, min{AEx}, will indicate the option with minimum wastewater degradation. However, the mixing exergy loss we calculate is based on the ‘untargeted’ contaminants and the calculation basis varies between each contaminant. Therefore, instead of considering the absolute value of the exergy loss, AEx, the mixing exergy loss should be evaluated in terms of percentage change, %AEx, defined as %AEx = g

* 100% I”

Effluent treatment (a)

system design

4283

ON Contaminant

A

Contaminant 1

!,,

cl

I 3

%AEx

B

\

.-

‘:j$Y~ +

’

.

cl

TPII

3

_.

IW cl

%AEx

sl

,,(A, c,

%AEx

,,,(A, ~1

bt

u

Choose mjn. {%AEx,} as the first TP placement. Fig. 13. Calculation

of the mixing

exergy

loss for each contaminant placement.

where AEx is the exergy change across a mixing junction. defined by AEx = Ex,,[ - Exi,. The sub-network with minimum %AEx should be chosen for the first treatment process placement. In Example 2, TPIII has the minimum mixing exergy loss and hence we place TPIII first to remove contaminant C. Re-targeting the remaining problem Once a treatment process has been placed, TPIII in our example, some mixing has also been accepted to achieve the target for the contaminant. The remainder of the effluent treatment problem still needs to be solved, but because of the mixing which has been accepted due to the placement of the treatment process, the remaining wastewater stream data are changed. Therefore, we should re-target the remaining problem. Based on the new stream population and concentrations shown in Fig. 14, the new %AEx’ can be obtained for the remainder of the treatment problem The sub-network with minimum %AEx’ is placed next. Figure 15 shows the network after the placement of TPII. Having placed TPII another new stream population and new concentrations will be created. The new set of stream data will provide us information for the next layer sub-network design. Following this design procedure, the final design for Example 2 is shown in Fig. 16. But will the design in Fig. 16 have lowest total treatment flowrate? Figure 17 shows all possible treatment sequences for Example 2 together with their total treatment flowrates. In Fig. 17 it can be seen that the design with the lowest overall treatment flowrate is Fig. 17(f), which is the one obtained from the procedure. The wrong sequence, Fig. 17(a), will result in a 14% increase in

total treatment flowrate. Treatment processes which can remove more than one contaminant In Example 2, it was specified that each treatment process was only capable of removing a single contaminant. This was done for clarity of explanation. In

target

Contaminant

\

dictates

A

the first treatment

Contaminant

6

Y

Choose min. {%AExi} I Fig. 14. The procedure of targeting and calculation of the mixing exergy loss is repeated on the remaining problem for the other contaminants.

practice, it is likely that treatment processes will be capable of removing more than one contaminant a time. For example, Fig. 18 shows a problem involving two contaminants and three treatment processes. The sub-network for contaminant A suggests that TPI and TPII should operate in parallel, but that for contaminant B suggests that TPI and TPIlI should operate in series. For treatment processes operating in series there is no point calculating the exergy loss associated with the second process. This results from the fact that the mixing losses of the second process depend on the placement of the first processes which has not yet been fixed. %AExlll,, should not be evaluated at this stage. Therefore, we only evaluate and %AEx,,,, and choose the %AEx,,,, %AEx,,, minimum exergy loss as the basis for the first treatment process placement. The difference between %AEx,,~ and %AExl,, is that TPl can accept different stream combinations where different contaminant

W.-C. J. Kuo and R. Smith

4284

__--

‘_____-_____-_________---

Completed previously Fig. 15. After targeting the final contaminant the final network can be completed.

Fig. 16. The final design for Example 2.

(81.7tfh)

(4

(85.311h)

(90.4ffh)

(b)

(EIS.OUh)

(80&/h)

6) Fig. 17. Comparison of different designs for Example 2

removal is concerned. After placement of the first treatment process, there is a new stream population as seen in Example 2. Therefore, the remaining problem should be solved by following the same procedure as before. Discussion Figure 19 shows a problem involving

a complete superstructure for three streams and three treat-

ment processes, in principle involving multiple contaminants. There are two basic elements which bind the entire superstructure. These are the stream combinations and treatment process sequence. The present paper suggests the targeting concept to select the right stream combination for each treatment process and the mixing exergy loss as a measure of the wastewater degradation to determine the treatment process sequence. These two concepts work

Effluent treatment system design

3285

c*:w . c*:k”L Contaminant A

Contaminant B

(Composite treatment targeting curve)

0

m

m-

0

u

u

%AEx, (,,)

%AEx, caj

Discharge .

Choose Min. {%AEx, (bj; %A%, cbj ; ohAExl as the first TP placement

taj 1

u Retarget the remaining problem as before and find the 2nd TP placement, .... and so on. Fig. 18. Calculation of the mixing exergy loss for problems in which the treatment processes affect more than one contaminant.

(Targeting) stream combination h u (Mixing Exergy Loss) TP sequence Fig. 19. The superstructure can be decomposed into two parts, one which dictates the stream combination and the other which dictates the treatment process sequence.

together to resolve the whole superstructure layer by layer. Here the concept of wastewater degradation has been introduced to determine the correct sequence to deal with each contaminant. Whilst such a measure is useful in that it is a physical parameter, its use cannot

guarantee optimality. Degradation of different contaminants will have different implications for different treatment processes, which is not necessarily reflected in the mixing exergy loss. Similarly, the mixing exergy loss cannot translate directly into cost which depends on issues outside those considered. Thus, the

W.-C. J. Kuo and R. Smith

4286

approach does not guarantee optimality in a mathematical sense. It does, however, always guide the designer towards the best solutions. In fact, in the majority of cases it is capable of identifying the best solution. The approach can also be used for initialisation of a superstructure if an approach based on the optimisation of a superstructure is to be used.

APPLYING

THE NEW METHOD

C (wm) 1000 -

TO RETROFIT

With environmental regulations becoming stricter, the retrofit of existing treatment systems to meet more stringent discharge regulations is becoming an important problem. Apart from complying with stricter regulations, an increased effluent load might be created due to changes in capacity or new plants coming on-stream. Whether to accommodate changes in effluent arising or to comply with stricter regulations, the wastewater stream data will change. The obvious solution to such problems is to install a new treatment process downstream of the installation. But can the treatment process be used in a more effective way? Let us explore what the methodology can offer in revamping cases.

Table 3. Wastewater data for an exiting plant Stream number 1 2

Flowrate (t/h)

Ci, (ppm)

10 30

1000 200

Note: Existing environmental limit = 100 ppm. Removal ratio of TPI = 90%. New environmental limit = 50 ppm. Min. outlet cont. of TPII = 10ppm.

12.0 m (kg/h)

v

Fig. 20. An existing design is operating

on target.

C (fwm) t

An example Suppose a wastewater treatment plant exists and was designed to meet an environmental limit set some time previously with the wastewater stream and operating data given in Table 3. The treatment process, TPI, is running at its fully capacity of 26.7 t/h and cannot be increased further. The removal ratio of TPI is fixed at 90% as shown in Fig. 20. To meet new effluent regulations, a new treatment process must be installed to remove an additional mass load of 2 kg/h. Where should the new treatment process be installed? Proposal 1. To install a new treatment process downstream of the existing treatment process. Figure 21 shows the new composite effluent curve based on the new environmental limit together with the treatment line for 26.7 t/h is the existing treatment process. The instinctive change is to install another treatment process, TPII, downstream of TPI as shown in Fig. 21. There would be 22.2 t/h treatment flowrate needed in TPII to meet the requirement. The

.

4.0

0

m(kg/h) r

I

40tIh . 5Owm Discharge Fig. 21.

flowsheet series.

The first proposal installs a new treatment downstream of the existing unit.

in Fig. 21 shows TPI and II operating

unit

in

Proposal 2. Install a new treatment process which will operate in parallel with the existing treatment process. The second option is to let the targeting line of TPII cross the composite effluent curve and start from the pinch point as shown in Fig. 22. As long as the composite treatment curve does not cross the composite effluent curve the solution will be feasible. This is shown as a flowsheet in Fig. 22. Stream 2 which causes the pinch is split into three and then fed to TPI and TPII separately. This scheme enables TPI and TPII to operate in parallel with the result that TPII only needs 10.53 t/h capacity instead of the 22.2 t/h in Proposal 1.

Effluent

treatment

Proposal 3. As Proposul2 hut the new treatment process will remoae more mass load and hence reduce the burden on the existing treatment process. Proposal 2 suggested that treatment line starts at the pinch point. However, the treatment line for TPII can go even further across the pinch. TPII has been assumed to be always capable of bringing the outlet concentration down to a fixed outlet concentration. say IOppm in this case. The maximum inlet concentration is assumed to be far higher than the treated wastewater streams. If so, we can install TPII which operates across the pinch and reduces the mass load on TPI. This would be good for flexibility of operation. Figure 23 shows TPII placed across the pinch and it will only need 7.39 t/h to be treated instead of the 10.53 and 22.2 t/h in the previous cases. The flowsheet shown in Fig. 23 shows TPI and TPII operating in parallel, as Proposal 2, but with the difference that stream 1 with its high concentration has been split and not stream 2. It should be noted that this proposal will only be feasible if TPI it subjected to the removal ratio but not the minimum outlet concentration constraint. Results of the example A summary for the three Table 4.

proposals

is given

system design

42x7

No suggestion is made here that any one of these proposals is better than the others. Detailed examination would be required in a retrofit situation. The example demonstrates that the methodology offers insights into revamping cases and provides a systematic way to identify different options. The new treatment process can be generally installed wherever it is found to be most appropriate after more detailed examination, as long as the resulting composite treatment curve lies below the composite effluent curve. Multiple contaminant problems In both gross-root design and revamping, the problems are multiple contaminant in nature. For most multiple contaminant problems, the bottleneck will be associated with a certain contaminant. Therefore, it is possible to revamp a multiple contaminant process by applying the single contaminant concept. CASE STUDY

Three wastewater streams are produced by a refinery site and must be treated before discharge. The flowrates of the streams and the concentrations of the three contaminants involved (HIS, oil. suspended solids) are given in Table 5. The environmental limits of the concentrations of three contaminants are 5, 20, lOOppm, respectively. No treatment facilities exist and the problem can be

in

C (pm) t

C (pw) t

lOOO}

1000

/

;;EF//i? , 14.0

0

m(kg/h)

Fig. 77. The second proposal

places a new unit in parallel with the existing unit.

Table 4. Summary

m WW

Fig. 23. The third proposal places a new unit in parallel with the existing unit and takes load from the existing unit.

for the retrofit

example ‘I-PI1

TPI

Proposal Proposal Proposal

1 2 3

14.0

6.0

2.0

Flowrate

Mass load

Flowrate

Mass load

(t/h)

(kg/h)

(t/h)

(kg/h)

26.7 26.7 26.1

12.0 12.0 6.684

22.2 IO.53 7.39

2.0 2.0 7.316

4288

W.-C. J. Kuo and R. Smith

treated as a new design. Three new treatment processes can be used. Treatment Process I (TPI) is a foul water stripper which only has an effect on the H2S removal, Treatment Process II (TPII) is a combined process of coagulation, sedimentation and filtration which can treat all three contaminants with different removal ratios and Treatment Process III (TPIII) is an API Separator which mainly treats oil and suspended solids. The removal ratios for the three contaminants are given in Table 6.

Table 5. Wastewater stream data for the refinery case study Contaminant

concentrations @em)

Stream number 1 2 3

Flowrate (t/h)

HIS

Oil

13.1 32.1 56.5

390 16 780 25

10 110 100

Suspended solids 250 400 350

The cost functions for treatment processes are expressed as functions of treatment flowrates and are given in Table 1. These data are taken from previously published information (Takama et al., 1980) but some changes have been made in order to make them more realistic.

Even though it is a multiple contaminant problem with multiple treatment processes, we start by targeting each contaminant in isolation to set up an initialisation. For single contaminant removal, it is obvious that H2S removal cannot be achieved by a single treatment process, either TPI or TPII. As discussed previously, for multiple treatment processes in single contaminant targeting, the mass load allocated to each treatment process must be optimised at the targeting stage. Based on the mass load optimistation, Fig. 24(a) shows the treatment network to remove the H$. Figure 24(b) shows the corresponding network for oil treatment. Since there is only 70%

Table 7. Cost functions Table 6. Removal

ratios for treatment

ratios (X) TPII

Treatment processes

HzS

Oil

TP I TPII TPIII

99.9 90 0

0 70 70

Suspended solids

TPIII

0 98 50

Capital Operating Capital Operating Capital Operating

Note: Annual rate of return Operating hours = 8600 h/yr. f= flowrate treated t/h.

(S) (S/h) ($) (S/h) (S) (S/h)

= 10%.

(a) H,S removal TP I = 37.8 t/h. TP II = 102.3 t/h.

(b) Oil removal TP III = 89.2t/h. TP II = 38.6 t/h. TP II = 38 t/h. TP III = 89.2 t/h.

(c) S.S. TP II = 70.9 t/h.

I3 Fig. 24. Designs

processes

processes TPI

Removal

for treatment

for each contaminant

??

in isolation

for the case study

16,800* j”,’ 1.0* j 12,600* ,j”.’ 0.0067* ,j 4800* ,j”-’ 0

Effluent

treatment

removal ratio for TPII and TPIII neither on its own is enough to meet the environmental limit. After optimisation of the mass load for both treatment processes, there are two alternative sub-networks for oil removal shown in Fig. 24(b) with only 1% cost difference between them, meaning that either could be accepted in principle. However, in practice the removal ratio of an API separator (TPIII) will deteriorate with decreasing inlet concentration. Therefore, the option with the sequence TPIII followed by TPII is taken. Finally, let us consider suspended solids removal. Similar to oil removal. suspended solids can be removed by TPII or TPIII. TPIII alone cannot perform the task but TPII is capable on its own as shown in Fig. 24(c). The contaminants can be targeted in a different order and the resulting sub-networks will be unchanged since each sub-network is targeted as a single contaminant sub-problem at this stage.

Before we evaluate wastewater degradation and decide the treatment process sequence, practical constraints need to be considered. In principle, we must evaluate the wastewater degradation for TPI, TPII and TPIII. It should be emphasised that the wastewater degradation must be evaluated in an appropriate way or it can lead to errors in the process configuration. There might be more than one treatment process required for a single contaminant removal such as H2S or oil. If this is the case, it is misleading to calculate the wastewater degradation of TPII in terms of HIS and oil removal, since the stream data for the evaluation of wastewater degradation of TPII cannot be obtained without TPI or TPIII placement. Therefore, the wastewater degradation should

system design

4289

only be calculated for TPI in HIS removal, TPIII in oil removal and TPII in suspended solids removal. Moreover, a certain treatment process sequence has been embedded in the single contaminant targeting. such that TPII should operate after TPI and TPIII as it was suggested in H2S and oil removal. Hence, wastewater degradation should only be evaluated in terms of TPI and TPIII placement as shown in Figs 24(a) and (b).

Ke-targeting Let us consider Figs 24(a) and (b) in more detail as shown in Figs 25(a) and (b). The sub-networks suggest that TPII should operate either after TPI or TPIII, but we should not calculate the wastewater degradation for TPI and TPIII based on the sub-networks shown in Figs 25(a) and (b). For H2S removal, TPII must treat all wastewater streams in order to meet the environmental limit. However, a treatment flowrate of only 38.6 t/h is required for TPII which will incorporate TPIII to achieve the oil content removal. There are two different targeting treatment flowrates for TPII, and we must choose the one which can achieve the task for removal of both contaminants, i.e. 102.3 t/h for TPII. Therefore, the oil removal targets must be readjusted as shown in Fig. 25(b) to 33.4 t/h for TPIII and 102.3 t/h for TPII. Having done so, all we have to do is to determine the sequence of TPI and TPIII. Based on the stream combinations for TPI and TPIII, the relative wastewater degradation, S/~AEX,,~,,~,,~,~., and ?/oAEx, ,,,, HIs,S.S.,, can be evaluated and hence the sequence of treatment processes can be settled. In this case, TPI should be placed first due to the lower wastewater degradation. After the TPI placement. there will be a new stream population and

(b) Oil removal

(a) H,S removal

EWE%AEx,, ,a,,,s.sj

u

u

Re-targeting

(b’) Oil removal

Choose the min { %AEx, } as first TP placement Fig. 25. Evaluation

of the degradation

for the case study.

W.-C. J. Kuo and R. Smith

4290

Fig. 26. Final design for the case study.

the remaining problem must be solved. There is a constraint in that TPII should be centralised treatment and it is therefore straightforward to set the target of TPIII from overall mass balance. The final wastewater treatment network is shown in Fig. 26. CONCLUSIONS

The general methodology for the design of distributed effluent treatment systems previously presented Wang and Smith (1994) provided valuable insights into the problem. However, the method failed to address important features of the design for multiple treatment processes in both single and multiple contaminant cases. This paper presents an extension of the methodology. An improved method has been presented for targeting treatment flowrate. The distribution of load between multiple treatment processes has also been addressed. The concept of wastewater degradation has been introduced to account for treatment process sequence in multiple contaminant problems. Previous work also did not address the case of retrofit of an existing system. Upgrade of existing treatment systems to comply with new regulations is an important consideration for which no systematic methods are currently available. The methods developed have been applied to the case of retrofit. NOTATION

C C, Ex f Mi mi

ml ni

concentration of contaminant environmental limit exergy targeting flowrate for treatment process molecular weight of component i mass of component i contaminant mass load removed by TPI molar flowrate (kmol/h)

RR TPI TPII TPIII xi

AEx AEx(,, %AEx AH

removal ratio of treatment unit Treatment Process I Treatment Process II Treatment Process III mole fraction for component i exergy loss exergy loss in terms of the mixing degrada tion of contaminant A the percentage exergy loss heat of mixing

Subscripts

H.C. HIS in out S.S. 1,2 3, .

hydrocarbon hydrogen sulphide inlet concentration to an operation out concentration from an operation suspended solids wastewater stream number REFERENCES

Eckenfelder, Jr. W. W., Patoczka, J. and Watkin, A. T. (1985) Wastewater treatment. Chem Engng 60-74. Higgins, T. E. (1989) Hazardous Waste Minimizution Handbook. Lewis Publishers inc. McLaughlin, L. A., McLaughlin, H. J. and Groff, K. A. (1992) Develop an effective wastewater treatment strategy. Chem. Engng Progr. 3442. Mishra, P. N., Fan, L. T. and Erickson, L. E. (1975) Application of mathematical optimization techniques in computer aided design of wastewater treatment systems. In Water-1974, AIChE Symposium Series, Vol. 71, (145) pp. 136-153. Takama, N., Kuriyama, T., Shiroko, K. and Umeda, T. (1980) Optimal water allocation in a petroleum refinery. Comp. Chem. Engng 4, 251-258. Wang, Y. P. and Smith, R. (1994) Design of distributed effluent treatment systems. Chem. Engng Sci. 49(18), 3127-3145.