Estimating the cost of desalination plants using a cost database

Desalination 229 (2008) 10–20

*Corresponding author.

Estimating the cost of desalination plants using a cost database

Michelle K. Wittholz, Brian K. O’Neill*, Chris B. Colby, David LewisSchool of Chemical Engineering, University of Adelaide, Engineering North Building, SA 5005, Australia

Tel. +61 (8) 8303 5446; Fax +61 (8) 8303 4373; email: [email protected]

Received 5 February 2007; accepted revised 8 July 2007

Abstract

Adelaide is the capital city of South Australia, one of the driest states in the world. The city receives its potablewater from a series of water catchments and the River Murray. Unfortunately, the current drought combined withother environmental factors is putting a strain on the River and its water quality is slowly degrading. A potentialsolution to Adelaide’s reliance on the River is desalination of various alternate water sources. The initial step inselecting the appropriate desalination technology is to perform and order of magnitude cost study. A simple techniquefor generating order of magnitude cost estimates is the development of a series of cost correlations based on a costdatabase. A cost database of 300+ desalination plants was collated. The cost database demonstrated that currentlarge-scale desalination plants are capable of producing water in the range of $0.50–$2.00/m3, depending on plantsize. Capital cost correlations as a function of plant capacity have been developed for large scale MSF, MED,SWRO and BWRO plants. Unit product cost (UPC) breakdowns were also developed for these technologies.Using the cost correlations and UPC breakdowns order of magnitude estimates were performed. For the case-studyof metropolitan Adelaide, reverse osmosis (RO) is the cheapest technology for seawater desalination.

Keywords: Desalination; Cost database; Cost factors; Order of magnitude estimate; Cost correlations

1. Introduction

1.1. Desalination throughout the world

Desalination is increasingly used worldwideto supplement (or replace) existing conventionalwater sources in water scarce areas. Currently, lessthan 3% of the world’s total water requirementsare met by desalination. Given the World Water

Council’s [1] prediction of water shortages by2025 there exists potential for increased use ofthis process. Over the past 20 years, technologi-cal advances have significantly decreased the costof producing water using desalination [2].

There are a number of commercially availabledesalination processes, including multiple-effectdistillation (MED), multi-stage flash distillation(MSF), vapour compression (VC), reverse osmo-

doi:10.1016/j.desal.2007.07.0230011-9164/08/$– See front matter © 2008 P ublished by Elsevier B.V.

M.K. Wittholz et al. / Desalination 229 (2008) 10–20 11

sis (RO) and electrodialysis (ED). The mostwidely installed process is RO, followed closelyby MSF. Fig. 1 summarizes the percent installedcapacity of the major desalination processes, assurveyed by the International Desalination Asso-ciation (IDA) in 2002.

The IDA survey reports that in 2002 over15,000 industrial scale desalination plants, withplant capacity exceeding 300 m3/d, were operat-ing world-wide providing a total installed capac-ity of 32.4 million m3/d [3]. Approximately 59%of these plants desalt seawater and the remaining41% treated various quality brackish water sources.The large number of plants operating today is aconsequence of the substantial decrease in the costof desalinated water that has occurred over thepast 30 years.

1.2. Current costs of desalination

The cost of water produced by desalinationvaries greatly depending on various factors (sec-tion 2.2). The recently constructed large scaleplant Tampa Bay, Florida USA reported costs aslow as $0.60/m3 [4] for medium salinity RO whilein Ashkelon, Israel and in Singapore, large scale

ED6%

VC5%

Other2%

MED3%

MSF40%

RO44%

Fig. 1. World’s installed desalination capacity by process[3].

SWRO plants are producing water at around$0.55/m3 [5]. Wade [6] reported slightly highercosts for large-scale seawater membrane and dis-tillation plants with the unit cost of water lying ina range from $0.80 to 1.00/m3. A recent study byDore [5] using past data to forecast the currentcosts of Brackish Water RO (BWRO) and SeaWater RO (SWRO) predicted that the costs laysomewhere in the range of $0.07–0.08/m3 (2002USD) for BWRO and $0.42–0.48/m3 (2002 USD)for SWRO in the near future.

1.3. Case study: City of Adelaide, Australia

Metropolitan Adelaide is the capital city ofSouth Australia (SA), one of the driest states inthe world. Each year the city requires approxi-mately 180 GL of potable water. Up to 90% ofthis potable water requirement is sourced fromthe River Murray, a major arterial river. The RiverMurray is used extensively for agriculture andAdelaide draws its water quota from the reducedflow near the downstream end of the river. Theremaining water requirement is drawn from a sys-tem of water catchments and storage reservoirs.The water distribution system including storagereservoirs and pipelines from the River Murrayare shown in Fig. 2. Unfortunately, the quality ofwater in the Murray is slowly degrading and al-ternate water supplies are being investigated [7,8].There are a number of options for augmenting thecity’s water supply. These include the re-use ofgrey water, waste-water recycling and desalina-tion of either seawater or brackish water. Desali-nation of seawater and brackish water to replacethe city’s potable water demand are consideredattractive options. The purpose of this paper is toestimate the cost of various desalination scenarios.

2. Estimating the cost of water produced bydesalination

2.1. Cost databases

The initial step in estimating the cost of a plant

12 M.K. Wittholz et al. / Desalination 229 (2008) 10–20

Fig. 2. Metropolitan Adelaide’s water distribution sys-tem.

requires the generation of an order of magnitudeestimate. Cost databases are essential for these costestimates as they provide readily accessible datato develop cost correlations. These provide orderof magnitude estimates to determine the likely costof one m3 of water. Hence the designer can rap-idly consider a wide variety of alternative strate-gies, to identify the most competitive option, andprovide a ball-park estimate of the costs involved.

Normally reliable initial estimates of plantcapital costs and the unit product cost (UPC) arebased on databases of previous cost estimates pro-duced within the company. If this option is un-available, then a cost comprised of existing andplanned plant data may be used as a starting point.To date, a few small international cost databaseshave been compiled. Those currently availableinclude work by Ettouney [9], Leitner [10] andPark et al. [11]. In the United States a number of

surveys (for municipal desalination plants) havebeen conducted [10,12] and these provide usefuldata for US plants. In Australia, similar surveyshave been undertaken [13,14]. These provide aninteresting snapshot of the state of desalination.A number of the authors have taken the next stepand have developed relationships between thevarious cost components and plant capacity basedon the collected data [14,15] to predict futurecosts. There have also been attempts to adapt ex-isting plant data to obtain cost estimates for plants[16,10,11]. A large cost database could highlightuseful cost trends and the relationships betweenvarious cost factors.

The normal capacity/cost correlation used inengineering practice is the well-known power lawrule [Eq. (1)]. This law can be used to calculatethe capital cost of a new plant (of known capac-ity) based on the known capital cost of an exist-ing plant. When the value of the exponent m isunknown a value of 0.6, the so-called the “sixth-tenths rule”, is normally assumed. For desalina-tion plants, the exponent is usually closer to 0.8[18].

plant1 plant1

plant2 plant2

Capital cost Plant capacityCapital cost Plant capacity

m⎛ ⎞ ⎛ ⎞

=⎜ ⎟ ⎜ ⎟⎜ ⎟ ⎜ ⎟⎝ ⎠ ⎝ ⎠

(1)

2.2. Cost factors

The cost of producing water using desalina-tion is influenced by a large number of factors.Operating costs include labour, chemical treat-ment, energy, maintenance and spare parts. Manyauthors have presented “typical” cost breakdownsfor various desalination processes. Semiat [19]demonstrated a breakdown of some typical oper-ating costs for SWRO plants and a breakdown ofoperating costs for multi-effect distillation (MED)plants. As expected, the dominant cost contribu-tors for SWRO were energy (electrical power) andfixed charges, as illustrated in Fig. 3. Zhou [20]presented the following generalised fractionalized


operating cost breakdown for thermal processes:

Energy = 87%; Chemicals = 5%; Labour = 8%.

Poullikkas [21] reported that RO operating andmaintenance costs were typically between 15–30% of the UPC. Cost breakdowns are stronglydependent on the features of the individual plantand it is difficult to develop a reasonably accu-rate generic model of the breakdown of costs. Anexample by Wilf [4] demonstrates this point. Wilfinvestigated the sensitivity of UPC to changes inelectricity prices. He demonstrated that doublingthe cost of electricity for a specific RO processincreased the UPC by up to 50%, and changedthe energy percentage accordingly. This illustratesthat even though two different plants may haveidentical total energy requirements per unit ofwater produced, if the cost of energy supplied tothe plants is different then the energy cost as apercentage of the UPC will be different.

2.3. Economy of scale

Economy of scale has been observed for alltypes of desalination technology by various au-thors including Ettouney et al. [9] and for RO by

Fig. 3. RO cost contributions proposed by Semiat [19].

Electric Power44%

Fixed Charges

37%

Consumables (Chemicals)

3%

Maintenance & Parts

7%

Supervision & Labour

4%Membrane

Replacement5%

Poullikkas [21]. Poullikkas also observed thatplant capital and water production costs decreasesignificantly as a function of capacity for plantssmaller than 12,000 m3/d for BWRO and20,000 m3/d for SWRO. However, for plants ex-ceeding this scale, the effect of economy of scalewas not as great.

2.4. The effect of plant location

The location of a plant can often have an im-pact on operating and capital costs. Clearly, lo-cating a plant in countries where labour and landcosts are low often produces an end product sig-nificantly cheaper than in a country where thesecosts are high. This is a strong driver towards eco-nomic globalization that has become so popularin the last two decades. However, a surprisingobservation based on a small desalting cost data-base was made by Park et al. [11] that plant loca-tion had very little observable effect on the costof water. This implies that cost data from aroundthe world can be applied to any location.

2.5. Selection of plant technology based on ca-pacity

Ettouney et al. [9] compiled a small databaseof desalting plants of varying capacity fromaround the world and made some observations onwhich technology was optimal for various typesof feedwaters and plant sizes. They concluded thatfor brackish water RO was the technology ofchoice for all plant capacities. By contrast, forseawater plants with greater than 25,000 m3/dMSF was recommended followed by MED forplants capacities greater than 10,000–25,000 m3/d, whilst for plants with capacities between 3000m3/d and 10,000 m3/d VC was suggested. Theseheuristics were contradicted by the work of Semiat[19] who suggested RO is optimal technology fordesalination at all capacities.


3. Cost database methodology

Desalination cost data was collected from awide variety of sources including surveys, reports,and published journals. These were published overa 35 year timeframe. The available data includedcosts for operating plants, preliminary and feasi-bility designs and tenders from around the world.The data collected included information about theplants including location, the technology beingused, plant capacity, operating life, availability andthe type of water being treated. Cost data collectedincluded the capital cost, fixed cost, operating costper annum and per cubic metre and unit productcost. The capital cost included the plant and landcosts, civil works and amortization. The operat-ing cost per m3 of water produced included thecost of chemicals for pre and post water treatment,energy requirement (including electricity andsteam), spares and maintenance (including mem-brane replacement costs for RO and ED), andlabour.

Data was initially grouped into specific tech-nologies, i.e. SWRO, MSF etc. and then sortedbased on plant capacity. Plant capacities below300 m3/d were excluded as these lay outside thescope of this study. Where data for the same plantwas reported by various authors, the most recentreference was used in the database. If an authorreported a number of different configurations forthe same plant estimate, the most expensive op-tion was included for that capacity. The data setwas further reduced to only include points whichspecified both capacity and capital cost so thatthe power law exponents could be calculated.From the initial 500+ data sets collected, only 331included data for capital costs. There was littleavailable data for large scale plants in Australia.Table 1 shows the number of plants for each tech-nology included in the database.

Plant data was collected spanning the periodfrom 1970 to 2005. Due to the large time span ofthe study, the data was adjusted to present valueusing the chemical engineering plant cost index

Table 1Number of plants included in desalination cost databasefor each technology

Technology Number of plants ED 18 MED 34 MSF 64 BWRO 90 SWRO 112 VC 13 Total 331

(CEPCI), part of the chemical engineering eco-nomic indicators published in the journal Chemi-cal Engineering. Where data was published in aforeign currency, the price was converted intoUSD for that year using the year weighted aver-aged exchange price published by the US FederalReserve Bank. In the case where an exchange ratewas unavailable for that country, the value wasadjusted to present value and then converted toUSD using today’s exchange rate. The effect oflocation was not taken into account based on find-ings from the study by Park et al. [11].

The power law model was fitted to developthe relationship between capital cost and plantcapacity. Simple linear regression using leastsquares was performed to determine the powerlaw exponent, m, for various desalination tech-nologies.

( ) ( )ln Capital cost ln Capacity + constant

m= ×(2)

The UPC is the sum of the amortised capitalcost and the operating costs. However, for thepurpose of this study the UPC was calculated us-ing Eq. (3) below. When unspecified, plant lifewas assumed to be 20 years with plant availabil-ity 90%.


( )Capital cost Annual operating costPlant lifePlant capacity Plant availability

UPC =

+

×

(3)

3.1. Cost factor investigation

Cost factors were based on data which haddetailed cost breakdowns. Data was sorted basedon technology. The fixed cost and operating costpercentages were calculated, and an average valuewas calculated. The ratio of energy cost to oper-ating cost was determined.

4. Results

4.1. Observed trends in UPC

During compilation of this database, the UPCwas observed (as expected) to decrease over thelast 25 years for large-scale RO and MSF plants.This trend is clearly illustrated in Fig. 4. An en-velope has been fitted around the bulk of the datato highlight changes in cost. The data shown inFig. 4 also confirms that the unit cost of large-scale sea water desalination lies in the range of$0.50 and $2.00 (USD) per m3.

Fig. 4. Decrease in UPC for large scale seawater RO and MSF plants.

4.2. Cost correlations4.2.1. Capital cost correlations

When collating data considerable variations incost were evident, even when the plants utilizedidentical technology, feedwater type and size. Anexample occurs for MSF plants with a capacityof 37,850 m3/d; Sommariva [22] suggests a capi-tal cost of US$307million while for the same ca-pacity Ettouney et al. [9] quoted a capital cost ofUS$72 million. To avoid large errors associatedwith such cost discrepancies, the decision wasmade to plot the capital cost of the plants againstcapacity on a logarithmic scale. Obvious outliers(i.e. greater than 50% from the average) were ex-cluded when developing correlations.

As expected, the exponent of 0.6 in the powerlaw equation is much lower than that observedfor desalination plants. The power law coefficientsare summarized in the second column of Table 2.Corresponding R2 values are also included in thistable to give an indication of the goodness of fitof the regression. The data collected for VC waslimited and the resultant correlation was poor.Hence, this case was not included in the results.Likewise, the curve for ED was poorly correlatedwith an R2 value equal to 0.65. Again, this tech-nology was not investigated further for the pur-


Table 2Regression coefficients for various technologies used in the power law model

Technology Exponent, m Constant, c R2 ED 0.75 3.88 0.655 SWRO 0.81 4.07 0.907 BWRO 0.74 3.95 0.814 MSF 0.70 4.86 0.718 MED 0.83 4.13 0.880

pose of this study. Both SWRO and MED pro-duced the largest power law exponents of all thecompeting technologies. This implies that bothtechnologies become more competitive at largercapacities. As expected, BWRO exhibits the low-est capital costs. This is a consequence of the loweroperating pressures required for the low salinityfeedwater. Equipment costs will therefore be lowerthan for SWRO which operates at high pressures.MSF is slightly more expensive than MED, how-ever for large scale plants, the costs approach oneanother. The capital cost trends for each of thesetechnologies can be seen in Fig. 5. Comparingthe trends in Fig. 5 results in the conclusion thatRO has the lowest capital costs for SW desalina-tion. For plants in the range of 1000 to 100,000 m3/dthe variation in capital cost for the different tech-

0.00

100.00

200.00

300.00

400.00

500.00

600.00

700.00

800.00

900.00

0 200000 400000 600000

Capacity (m3/d)

Capi

tal C

ost

(US

D*1

06 )

SWROBWROMSFMED

Fig. 5. Capital cost for various desalination technologies using the power law scale-up model.

nologies is small and both MED and MSF couldbe used, especially if cheap fuel is available.

4.2.2. UPC sorrelations

Correlations for unit product cost as a func-tion of size were attempted. However, given thelarge variations of UPC at any specified capacity,the resulting error rendered the correlations mean-ingless.

4.3. UPC breakdowns

Unfortunately, only 30% of the data in the costdatabase contained detailed cost breakdowns.Consequently, the smaller datasets for VC and ED(see Table 1) did not contain sufficient informa-tion to determine cost factors for these technolo-


gies. Cost breakdowns were subsequently com-pleted for BWRO, SWRO, MSF and MED.

Studies were undertaken to devise a series ofcost factors for each technology. An average costfactor for fixed cost and operating cost was deter-mined. There was significant variation for costfactors including chemicals, labour and spares andmaintenance. As a result, no factors were devel-oped for these contributions. However, the datafor the fraction contributed by energy costs wasconsistent. The energy cost was calculated as afraction of the total operating cost.

Operating costs for both BWRO and SWROwere slightly larger than for thermal processes.By contrast energy costs were higher for MSF andMED. Semiat [19] reported RO cost factors to be37% for fixed charges whilst operating costs were63% and the energy cost was predicted to con-tribute 44% of operating cost. This study foundthe same ratio of fixed changes to operating costshowever the total energy costs were on averagelower than those presented by Semiat. This sur-vey found that the average energy component ofthe operating cost was approximately 75%. Thisis lower than the predictions of Zhou [20] whofound energy for thermal plants to be 85% of op-erating cost. These results are summarized inTable 3.

Coupling the cost breakdowns in Table 3 withthe capital cost correlations developed in Section4.2 permitted determination of the UPC for a rangeof different plant capacities. BWRO produced thelowest UPC as expected, again a consequence ofthe low salinity of the feedwater. The values cal-culated using this database were approximately

Table 3Average cost breakdowns for various technologies

Technology Fixed cost contribution Operating cost contribution Energy cost contribution E/Op. cost SWRO 0.35 0.65 0.35 0.54 BWRO 0.35 0.65 0.3 0.46 MSF 0.4 0.6 0.45 0.75 MED 0.4 0.6 0.45 0.75

twice as high as those predicted the by the data-base compiled by Dore [5]. SWRO was the cheap-est sea water process, with costs for plants largerthan 200,000 m3/d around $0.50/m3. This valuelies in the same range as that predicted by Dore.There was little difference in cost for plant ca-pacities exceeding 200,000 m3/d for MSF andMED. For plants smaller than this, MED wasslightly cheaper. The costs were slightly lowerthan those reported by Wade [6] and lay between$0.80 and $1.00/m3. The calculated UPCs for thevarious technologies across a range of differentcapacities are summarized in Fig. 6.

4.4. A note on errors

A general rule of thumb for order of magni-tude estimates of capital costs is ±30% [23]. Inthis study the error is closer to 50%. The sameerror can be assumed for the UPC.

When analysing the data it was observed thatthere was often an order of magnitude differencein capital cost data for different plants of the samesize and using the same technology. This waspartly caused by the quality of the data. Impor-tant details such as if the land and civil workswere included in the capital cost were not alwaysreported, making it difficult to develop accuratepredictions of cost. Some plants were also devel-oped under a Build Own Operate Transfer(BOOT) scheme which changes the fixed-costpayback structure. Many plants commissioned inthe past decade have a plant life of thirty, insteadof twenty years (assumed in this study) which sig-nificantly decreases the UPC of the product. The


Fig. 6. Predicted UPC based on the cost breakdowns in Table 2 and capital cost correlations.

0.00

0.50

1.00

1.50

2.00

2.50

0 200000 400000 600000

Capacity (m3/d)

UP

C (U

SD/

m3 )

SWROBWROMSFMED

UPC cost breakdowns summarized in Table 1 areonly averages, and are provided to give an indi-cation of the product cost. To develop correlationswith lower errors it would be better to base thedatabase on data published from the same source.

5. Case study: cost of desalination using existingtechnologies for various scenarios in Adelaide

The capital and UPC for various size plantsfor different technologies were calculated usingthe correlations and cost breakdowns developed.These are summarized in Table 4.

Clearly, there are a number of options avail-able for augmenting or replacing Adelaide’s wa-ter with desalination. Clearly brackish water de-salination would be the cheapest option. There isrestricted brackish water available (with the ex-ception of the River Murray) including recycledwastewater and stormwater. This would limitBWRO to smaller scale plants with costs rangingbetween $0.25 and $0.38 ±$0.20. There is morescope for sea water desalination plants. Thesecould be used to augment the existing water sup-ply or possibly even replace it. Large scale SWROplants are the best option. A plant that would aug-ment the city’s water supply by 50% would pro-

duce water for $0.50 ± $0.25/m3. The cost of com-pletely replacing the existing water supply withRO is approximately $0.45 ± $0.23/m3. Theseoptions are competitive with the existing watersupply.

35% of these costs are due to energy (seeTable 3). In the case of RO the energy is in theform of electricity. This is a problem as Australiahas high energy prices compared with other coun-tries. A realistic increase in the cost of electricity,say from $0.10/kWh to $0.15/kWh, could poten-tially increase the UPC by 17.5%. Doubling theelectricity cost would increase the UPC by 35%.Unless the desalination plants are operating in aco-generation system with a power plant, or analternate electricity source, such as nuclear power,is used, there is always the risk that the optionmay no longer be competitive. The developmentof desalination technologies that reduce theamount of power required could also help allevi-ate this problem without the need for new powersources.

6. Conclusions

RO was found to be the cheapest technologyfor large scale sea water desalination. This is fol-


Table 4Summary of costs for different technologies for 4 different capacities

Capacity (m3/d) Capital cost (US$×106) UPC (US$) SWRO 10,000 20.1 0.95 50,000 74.0 0.70 275,000 293.0 0.50 500,000 476.7 0.45 BWRO 10,000 8.1 0.38 50,000 26.5 0.25 275,000 93.5 0.16 500,000 145.4 0.14 MSF 10,000 48.0 1.97 50,000 149.5 1.23 275,000 498.1 0.74 500,000 759.6 0.62 MED 10,000 28.5 1.17 50,000 108.4 0.89 275,000 446.7 0.67 500,000 734.0 0.60

lowed by MSF and MED. Using the correlationsdeveloped, the capital cost of a large scale ROplant is somewhere in the range of 500–1000 mil-lion dollars, depending on the size. Plants couldpotentially produce water in the range of $0.45–0.55/m3. These cost correlations can be used forsimple initial order of magnitude studies to helpdetermine which technology is best suited to thesituation at hand.

ReferencesA complete list of cost database references may be ob-tained from the author.

[1] W. Cosgrove, http://www.abc.net.au/science/news/stories/s803659.htm 2003 accessed September 2005.

[2] T.A. Dabbagh, The management of desalinated wa-ter. Desalination, 135 (2001) 7–23.

[3] IDA, Worldwide Inventory of Desalination Plants.Report 17, Topsfield, Mass., USA, 2002.

[4] M. Wilf, Optimization of seawater RO systems de-sign. Desalination, 138 (2001) 299–306.

[5] M.H.I. Dore, Forecasting the economic costs of de-salination technology. Desalination, 172 (2005) 207–214.

[6] N.M. Wade, Distillation plant development and costupdate. Desalination, 136 (2001) 3–12.

[7] Government of South Australia, South AustralianRiver Murray Salinity Strategy 2001–2015, Depart-ment for Water Resources, Adelaide 2001.

[8] I. Jolly, G. Walker, P. Stace, B. Van der Wel and R.Leaney, Assessing the impacts of dryland salinityon South Australia’s water resources. CSIRO Landand Water, Technical Report 9/00, 2000.

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[10] G.F. Leitner, Water desalination: what are today’scosts. Desalination and Water Reuse Quarterly, 2(1992) 39–43.

[11] M. Park, N. Park, H. Park, H. Shin and B. Kim, Aneconomic analysis of desalination for potential ap-plication in Korea. Desalination, 114 (1997) 209–221.

[12] Leitner and Associates, Survey of US costs and waterrates for desalination and membrane softeningplants, WTTP Report 24, Denver CO, US Depart-ment of the Interior, Bureau of Reclamation, 1997.

[13] L.S. Herbert and D.H. Moffatt, Desalination — asurvey of Australian plants, AWRC Researchproject, 68/6 Canberra, 1970.

[14] B.R. Smith and E.A. Swinton, Desalination costs in


Australia: A survey of operating plants. Desalina-tion, 70 (1988) 3–15.

[15] G. Fosselard and K. Wangnick, Comprehensivestudy on capital and operational expenditures fordifferent types of seawater desalting plants (RO,MVC, ME, ME-TVC, MSF) rated between 200 m3/d and 3000 m3/d. Desalination, 76 (1989) 215–240.

[16] J.E. Browning, Zeroing in on desalting. Chem. Eng.,March 23 (1970) 64–66.

[17] G.F. Leitner, Costs of seawater desalination in realterms, 1979 through 1989, and projections for 1999.Desalination, 76 (1989) 201–213.

[18] C.H. Chilton, Six-tenths factor applies to completeplant cost, Chem. Eng., 57(4) (1950) 112–114.

[19] R. Semiat, Desalination: present and future, WaterInternational, 25(1) (2000) 54–65.

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[21] A. Poullikkas, Optimization algorithm for reverseosmosis desalination economics. Desalination, 133(2001) 75–81.

[22] C. Sommariva and V.S.N. Syambabu, Increase inwater production in UAE. Desalination, 138 (2001)173–179.

[23] M.S. Peters and K.D. Timmerhaus, Plant Design andEconomics for Chemical Engineers. McGraw-Hill,4th ed., Singapore, 1991

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Estimating the cost of desalination plants using a cost database