ryan fu-sum nanofiltration membrane report

NF Preliminary Design Report

Ryan Fu-Sum ENV 4562

2

TABLE OF CONTENTS

Executive Summary ................................................................................................................................................................ 5

Introduction ................................................................................................................................................................ .......... 5

Flow Projection ................................................................................................................................................................ .... 5

Pretreatment ........................................................................................................................................................................ 5

Membrane Process ............................................................................................................................................................. 6

Post-treatment ................................................................................................................................................................ ..... 8

Cost ................................................................................................................................................................ ........................... 8

Flow Projection ...................................................................................................................................................................... 10

Introduction ................................................................................................................................................................ ........ 10

Theory ................................................................................................................................................................ ................... 11

Methods ................................................................................................................................................................ ................ 13

Results ................................................................................................................................................................ ................... 14

Conclusions and Recommendations ......................................................................................................................... 17

Pretreatment ........................................................................................................................................................................... 18

Executive Summary ......................................................................................................................................................... 18

Introduction ................................................................................................................................................................ ........ 19

Theory ................................................................................................................................................................ ................... 20

Procedure ................................................................................................................................................................ ............. 21

Bicarbonate Calculation ............................................................................................................................................ 21

Limiting Salt Calculation ........................................................................................................................................... 21

Limiting Salt Maximum Recovery Rate ............................................................................................................... 21

CaCO3 Recovery Rate, pH, and acid dose ............................................................................................................ 21

Anti-scalent ................................................................................................................................................................ .... 22

Results ................................................................................................................................................................................... 23

Conclusion ................................................................................................................................................................ ........... 26

Recommendation ......................................................................................................................................................... 26

Sources .................................................................................................................................................................................. 26

Appendix A ................................................................................................................................................................ .......... 27

Membrane Process ................................................................................................................................................................ 31

Introduction ................................................................................................................................................................ ........ 31

Background and Theory ................................................................................................................................................ 31

Methods ................................................................................................................................................................ ................ 32

Designing Membrane Array ..................................................................................................................................... 32

3

Equipment................................................................................................................................................................ ....... 32

Valves ................................................................................................................................................................................ 32

Results ................................................................................................................................................................ ................... 34

Membrane selection ................................................................................................................................................... 34

Array configuration ..................................................................................................................................................... 34

Array Expansion ........................................................................................................................................................... 35

Modifying the Array Configuration ........................................................................................................................... 35

Pressure Vessel ............................................................................................................................................................. 36

Auxiliary Equipment ................................................................................................................................................... 38

Backpressure ................................................................................................................................................................ . 39

Conclusion ........................................................................................................................................................................... 41

Recommendation ......................................................................................................................................................... 41

Post Treatment ................................................................................................................................................................ ....... 42

Introduction ................................................................................................................................................................ ........ 42

Alkalinity recovery ...................................................................................................................................................... 42

Hydrogen sulfide stripping ...................................................................................................................................... 42

Aeration ........................................................................................................................................................................... 42

Corrosion control ......................................................................................................................................................... 42

Disinfection..................................................................................................................................................................... 42

Theory ................................................................................................................................................................ ................... 44

Alkalinity recovery ...................................................................................................................................................... 44

Hydrogen sulfide removal ........................................................................................................................................ 44

Aeration ........................................................................................................................................................................... 44

Corrosion Control ........................................................................................................................................................ 44

Disinfection..................................................................................................................................................................... 44

Results ................................................................................................................................................................ ................... 46

Alkalinity Recovery ..................................................................................................................................................... 46

Hydrogen Sulfide Removal ....................................................................................................................................... 47

Aeration ................................................................................................................................................................ ........... 47

Corrosion control ......................................................................................................................................................... 48

Disinfection................................................................................................................................................................ ..... 49

Conclusion ................................................................................................................................................................ ........... 50

Costs ................................................................................................................................................................ ............................ 51

Introduction ........................................................................................................................................................................ 51

Methods & Procedures ................................................................................................................................................... 51

4

Capital Costs Formulas .............................................................................................................................................. 51

O & M ................................................................................................................................................................................. 53

Results & Discussion ....................................................................................................................................................... 55

Pretreatment ................................................................................................................................................................ .. 55

Membrane Process ...................................................................................................................................................... 56

Post-treatment .............................................................................................................................................................. 56

Concentrate Disposal.................................................................................................................................................. 56

Conclusions and Recommendations ......................................................................................................................... 57

References ........................................................................................................................................................................... 58

EXECUTIVE SUMMARY

INTRODUCTION

The City of Camelot currently requires a 4.5 MGD water plant to service its growing population. The City of Camelot currently has a population of 26,220 and is expected to grow above 70,000 people by the year 2030. A ground water source is available for treatment, however, the water is difficult to treat water with high iron content, microbial activity, and organic carbon. This report outlines the preliminary design of a nanofiltration plant than can treat the water source and supply the projected demand for the 20 years to come.

FLOW PROJECTION

The flow projection is statistically modeled from the historical population data of the City of Camelot. The population growth of the City of Camelot is exponential in nature. The water usage per person however levels out and follows a sigmoidal curve. The water usage is expected to be between 75 and 60 gallons per person per day. With this information the City of Camelot will require 6 MGD in 20 years. It is with 90% certainty that the demand will not exceed 6 MGD by the year 2031. The recommended design capacity of the water plant is 4.5 MGD expandable to 6 MGD. These recommendation is based on historical population data collected from the previous 20 years.

PRETREATMENT

The City of Camelot water treatment plant will be treating groundwater with difficult characteristics. The ground water is hard water with mostly calcium and some magnesium. The source water is also very high in iron and contains a small concentration of sodium chloride. For this type of source water, nanofiltration is recommended as the primary treatment process.

Prior to nanofiltration, the source water must be pretreated. The iron is particularly high and must be removed before nanofiltration. Iron can precipitate during the nanofiltration process and damage the membranes used in nanofiltration. Iron can removed through greensand filtration. The greensand oxidizes iron and manganese as it the water flow through the bed. The oxidized metals precipitate and is mechanically filtered by the sieving action of greensand particles. The greensand filter is cleaned by backwashing the filter bed with potassium permanganate. Both iron and manganese are removed at efficiencies over 90%. Sulfur is also removed by greensand filtration, though through chemical reduction rather than oxidation.

Cartridge filters remove any smaller particles or suspended matter that might pass through the greensand filter. The cartridge filters can filter particles as small as 5 microns. Cartridge filters will extend the lifespan of the membranes and reduce overall maintenance cost on the membranes.

Before water can enter the nanofiltration membranes, the source water must be chemically treated to increase the amount of water that recovered from treatment. Chemical pretreatment also protects the membrane from fouling. Fouling by precipitating salts and their damaging crystals can

6

permanently damage the membrane or reduce the efficiency or recovery rate of the membrane. Chemical pretreatment requires adding an acid to lower the pH and prevent precipitation of limiting salts. The limiting salts for the City of Camelot's ground water source are calcium carbonate, barium sulfate and calcium fluoride. Lowering the pH, by chemically treating the source water with 93% sulfuric acid will control calcium carbonate scaling. The addition of carefully considered anti-scalent can control the remaining limiting salts to achieve optimum recovery rates and efficiently produce water. 90% recovery can be achieved, though that may be too high. This pretreatment process adds greater cost, but post treatment costs are benefit from a more rigorous pretreatment process. Sulfur is removed by the greensand filters. This excludes any post-treatment process for sulfur reduction. Odor control problems are avoided and the waste concentrate from the membrane process is cleaner, which may allow for more flexible disposal.

Figure 1: Pretreatment process

MEMBRANE PROCESS

The membranes are the heart of the City of Camelot water treatment plant design. It is at this stage of the treatment process that most the source water contaminants are removed. Nanofiltration is similar the reverse osmosis membranes which are more commonly known. Though, the action of the membrane can be more accurately described as hyperfiltration--as osmosis and osmotic pressure acts in one direction. Nanofiltration membranes reject divalent ions like calcium and magnesium ions. Nanofiltration membranes will also reject large dissolved solids, such as any organics which might impart color or react with chlorine to form disinfection byproducts. Unlike reverse osmosis membranes, nanofiltration membranes are efficient at rejecting monovalent ions like sodium and chloride ions.

Because of the lower rejection characteristics of nanofiltration membranes, the operating pressures are much smaller and the membranes produce a higher flow rate compared to reverse osmosis membranes. Therefore, the pumps can are sized much smaller and power require are less. The pressure vessels can be rated for lower pressures, which can reduce costs.

The membrane process is split into trains or skids for redundancy. Three process trains are recommended with a 70 hp high pressure vertical pumps supplying each trains with 1,040 gallons per minute of feed water. An additional two trains are design to come online to fill the capacity as it is needed.

Greensand Filter Cartridge

Filter

Acid Anti-scalant

To Membrane

Feed Water

7

The process should contain two stages. Two stages are required to achieve recovery rates above 80%. The concentrate from the first stage flows into the second stage where more water is recovered before its exits the final stage a waste concentrate. Figure 2 depicts the flow of the feed water through the nanofiltration membrane as it is recovered into permeate water.

FIGURE 2: MEMBRANE PROCESS

Both stages are comprised of pressure vessels with contain the membrane elements. The design calls for an 8 inch membrane for this moderately sized treatment plant. Table 1 contains design parameters of the selected membrane. Each pressure vessel contains six 8 inch by 40 inch membrane elements. The ratio of first stage elements to second stage elements is 2 to 1. A total 765 elements are required for this configuration.

TABLE 1

Element NF90-400 Surface Area 400 ft2 Permeate Flow Rate NaCl 7,500 gpd MgSO4 9,500 gpd Salt Rejection NaCl 85-95% MgSO4 >95% Maximum permeate flow 6.32 gpm Maximum element recovery 19% Minimum concentrate flow 13 gpm

This configuration can operate at recoveries between 80% and 90%. Boost pumps allow for higher recoveries and better flow through the second stage. Inter-stage boosting also saves energy costs. Energy from the waste stream is transferred to the feed stream with inter-stage boosting.

Instrumentation is necessary to monitor the membrane process to ensure optimal and safe operation of the nanofiltration membranes. Sample panels contain ports with allow membrane

8

elements to be tested routinely for optimal performance. Monitoring the performance of membrane elements allows to process to reliably operate at higher recovery rates. Flow meters and proper valve selection are important in controlling the process.

POST-TREATMENT

The post-treatment process involves adjusting the water so that it may enter the distribution system and meet regulatory standards for disinfection.

The recovered water or permeate water leaving the nanofiltration process is relatively low in dissolved solids and alkalinity. The pH is also low. This water is corrosive to the distribution system if not treated further. Decarbonation adds alkalinity to the permeate water and aeration readjusts the pH upward. Alkalinity adds buffering capacity to the water and stabilizes the pH.

Sulfur removal isn't necessary due to the choice made in using greensand as a pretreatment process. The greensand filter removes sulfur at a high efficiency. Any residual sulfur consumes chlorine.

Alkalinity can be recovered by raising the pH and running the treated water through a decarbonator. CO2 is stripped from the permeate, which shifts the pH to a range where the water has more buffering capacity. Adding a base like calcium oxide allows for greater alkalinity recovery. Taking corrosion in consideration, alkalinity of 2 meq/L is desired for recovery.

During aeration the pH adjusts to the stabilized pH of 7.7. At this point a corrosion control inhibitor can be added along with a disinfectant. The corrosiveness of the water is moderate. The LSI is -0.13. Negative LSI values indicate that there is low scaling potential which exposes the pipes to corrosion. The amount of corrosion inhibitor added is specified by vendor formula specifications.

Disinfection protects public health. The water is required to carry a residual amount of chlorine into the distribution system. 2 mg/L is the target residual concentration. At most, the chlorine demand of sulfur if 3.44 mg/L. Combing the chlorine demand of sulfur and the residual yields a total chlorine dosage of 5.44 mg chlorine per 1 liter water. Because the nanofiltration process effectively removes organic compounds and nitrates, the chlorine demand from other contaminants is low or almost nonexistent. As a result, the formation of carcinogenic disinfection by products is reduced.

COST

The cost estimation for the City of Camelot water treatment plant utilizes EPA and government cost curve data as well as current market prices.

The membrane elements are the most significant cost associated with the capital costs. The price of membrane elements, however, has fallen significantly as the technology has improved. The costs associated with the membrane process include the price of the high pressure pumps, piping, and the pressure vessels as well as instrumentation and cleaning equipment.

9

The second greatest cost associated with capital cost is the building construction and site preparation. The larger the footprint, the easier it is to access the components of the treatment process. Also, reserving space allows for new processes to be integrated. Such contingencies are important if this water treatment plant is to reliable and flexible source of the city's water needs. Table 2 contains the list of cost estimations for the nanofiltration plant.

If concentrate is permitted to be disposed through deep well injection, the cost could be significant for the deep wells. If the concentrate can be sold and incorporated into the reuse system, the impact on cost for concentrate disposal is reduced.

TABLE 2

Item Capital O&M Total /kgal Annual /kgal Property $2,315,508 $0.17 Pretreatment $265,158 $0.02 $82,341 $0.01 Membrane Process $2,403,731 $0.17 $1,122,385 $0.08 Post Treatment $294,891 $0.02 $74,591 $0.01 Concentrate Disposal $500,000 $0.04 Total $7,617,810 $0.54 $2,708,822 $0.19

Labor, power usage, and chemical usage are large factors in the operating costs. Membrane replacement is one of the largest among the operational costs of the nanofiltration plant. The life of the membrane however is not fixed. They membrane replacement was calculated at every 5 years. However, if the membranes are run in optimum conditions the lifespan can be extended past 10 years which significantly reduces operational costs. The greensand filter reduced the amount of chemical dosing that would otherwise be required for the higher capital cost of constructing a filter bed.

RECOMMENDATION

Overall, the estimated capital for this nanofiltration plant is reasonable. This nanofiltration plant design can operate at a high recovery rate and low pressure. Compared to other treatment methods available, the footprint is small. The main advantage of membrane processes however is the final quality of the water and the low formation of disinfection byproducts.

FLOW PROJECTION

INTRODUCTION

The purpose of this report is to project a 20 year flow for a population. The prediction will help determine the design capacity of a water treatment plant so that it can meet the needs of the population for the 20 years to come.

This projection is based on the data provided in Table 1.

TABLE 3

Year Population Flow (MGD) *Flow per Capita (gpcd) 1981 5860 0.31 52.90102 1983 6283 0.36 57.29747 1985 6485 0.38 58.59676 1987 6874 0.42 61.0998 1989 8185 0.55 67.19609 1991 8644 0.58 67.09857 1993 8923 0.58 65.00056 1995 10218 0.75 73.39988 1997 12154 0.79 64.99918 1999 13830 0.91 65.79899 2001 15861 1.05 66.20011 2003 18591 1.24 66.69894 2005 17435 1.21 69.40063 2007 20306 1.46 71.89993 2009 23586 1.71 72.50064 2011 26220 1.72 65.59878 *𝐹𝑙𝑜𝑤 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎 = 𝐹𝑙𝑜𝑤/𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛

11

THEORY

Using statistical regression, best fit models are generated using statistical software to best fit the data points in Table 1. Each model has parameters that are determined through iterations until it converges with the data points.

The independent variable is time in years. The data starts at year 1981.

The three dependent variables of interest are population, flow, and flow per capita.

An example of statistical regression is linear regression. The equation for linear regression is: 𝒇 = 𝒂 + 𝒃 ∗ 𝒙. In linear regression the regression coefficients have to be determined because they are constant. They are also referred to as parameters. One method of estimating the regression coefficients is the Method of Least Squares which was developed in the early 19th century by the French mathematician, Adrien Legendre. This estimating is an operation of the sum of the squares (i.e. SSxx).

The correlation coefficient, sometimes also called the cross-correlation coefficient, is a quantity that gives the quality of a least squares fitting to the

original data. The higher the r2 value, the better the fit.

In regression the standard error of the estimate is the standard deviation of the observed y-values about the predicted y-values. In general, the standard error is a measure of sampling error. Standard error refers to error in estimates resulting from random fluctuations in samples. The standard error is the standard deviation of the sampling distribution of a statistic. Typically the smaller the standard error, the better the sample statistic estimates of the population parameter. The standard error of the estimate is the square root of the Mean Square Errors.

12

The t-test statistic tests the null hypothesis that the coefficient of each independent variable is zero, that is, the independent variable does not contribute to predicting the dependent variable. t is the ratio of the regression coefficient to its standard error.

You can conclude from "large" t values that the independent variable can be used to predict the dependent variable (i.e., that the coefficient is not zero).

P is the P value calculated for t. The P value is the probability of being wrong in concluding that there is a true association between the variables (i.e., the probability of falsely rejecting the null hypothesis, or committing a Type I error, based on t). The smaller the P value, the greater the probability that the independent variable helps predict the dependent variable.

An F-test checks the variance and is usually a ratio of two numbers, where each number estimates a variance. An F-test can be used in the test of equality of two population variances. The F test statistic can be used in Linear Regression to assess the overall fit of the model.

𝐹 𝑡𝑒𝑠𝑡 𝑠𝑡𝑎𝑡𝑖𝑠𝑡𝑖𝑐𝑠 = 𝑀𝑆𝑅/𝑀𝑆𝐸

13

METHODS

Four specific models were tested to best represent the data provided in Table 1: Linear, Exponential, Exponential Rise to Maximum and Sigmoidal. With the aid of SigmaPlot v12.0, the parameters for the associated models were determined using an iterative process. The models and their parameters are listed in Figure 1 through Figure 4.

𝑥 = 𝑖𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒 (𝑦𝑒𝑎𝑟). 𝐹 = 𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒

Figure 1

Polynomial, Linear 𝒇 = 𝒚𝟎 + 𝒂 ∗ 𝒙

Figure 2

Exponential Growth, Single, 3 Parameter 𝒇 = 𝒚𝟎 + 𝒂 ∗ 𝒆𝒙𝒑(𝒃 ∗ 𝒙)

Firgure 3

Exponential Rise to Maximum, Single, 3 Parameter

𝒇 = 𝒚𝟎 + 𝒂 ∗ (𝟏 − 𝒆𝒙𝒑(−𝒃 ∗ 𝒙))

Figure 4

Sigmoidal, Sigmoid, 3 Parameter 𝒇 = 𝒂/(𝟏 + 𝒆𝒙𝒑(−(𝒙 − 𝒙𝟎)/𝒃))

SigmaPlot v12.0

14

RESULTS

Table 2 Population Projections

Polynomial, Linear

𝑓 = 𝑦0 + 𝑎 ∗ 𝑥

R Rsqr Adj Rsqr

Standard Error of Estimate

0.9655 0.9322 0.9273

1765.085

Coefficient Std. Error t P

y0 -1312199 95534.7439 -13.7353 <0.0001

a 663.9728 47.8626 13.8725 <0.0001

Exponential Growth, Single, 3 Parameter

𝑓 = 𝑦0 + 𝑎 ∗ 𝑒𝑥𝑝(𝑏 ∗ 𝑥)

R Rsqr Adj Rsqr


0.9938 0.9876 0.9857

782.8368


y0 1161.396 1627.6957 0.7135 0.4881

a 7.96E-48 1.32E-46 (+inf) <0.0001

b 0.059 0.0082 7.1695 <0.0001


𝑓 = 𝑦0 + 𝑎 ∗ (1 − 𝑒𝑥𝑝(−𝑏 ∗ 𝑥))

R Rsqr Adj Rsqr


0.9655 0.9322 0.9218

1831.716


y0 -1312270 2960679.916 -0.4432 0.6649

a 1.22E+10 3.90E+14 3.12E-05 1

b 5.45E-08 0.0017 3.12E-05 1

Sigmoidal, Sigmoid, 3 Parameter

𝑓 = 𝑎/(1 + 𝑒𝑥𝑝(−(𝑥 − 𝑥0)/𝑏))

R Rsqr Adj Rsqr Standard Error of Estimate

0.9936 0.9872 0.9852

796.1572


a 2.87E+09 9.43E+13 3.04E-05 1

b 18.5993 3.2669 5.6933 <0.0001

x0 2226.99 611187.6327 0.0036 0.9971

Table 3 Flow

Projections

Polynomial, Linear

𝑓 = 𝑦0 + 𝑎 ∗ 𝑥

R Rsqr Adj Rsqr


0.9735 0.9476 0.9439

0.1123


y0 -95.8417 6.0778 -15.7692 <0.0001

a 0.0485 0.003 15.9136 <0.0001


𝑓 = 𝑦0 + 𝑎 ∗ 𝑒𝑥𝑝(𝑏 ∗ 𝑥)

R Rsqr Adj Rsqr


0.9942 0.9883 0.9865

0.055


y0 -0.133 0.1545 -0.8607 0.405

a 3.53E-44 5.56E-43 (+inf) <0.0001

b 0.0501 0.0078 6.4181 <0.0001


𝑓 = 𝑦0 + 𝑎 ∗ (1 − 𝑒𝑥𝑝(−𝑏 ∗ 𝑥))

R Rsqr Adj Rsqr


0.9735 0.9476 0.9396

0.1165


y0 -95.8708 0.2331 -411.352 <0.0001

a 160508.8 0.0004 4.13E+08 <0.0001

15

b 3.02E-07 149244415.

7 2.02E-15 1


𝑓 = 𝑦0 + 𝑎/(1 + 𝑒𝑥𝑝(−(𝑥 − 𝑥0)/𝑏))

R Rsqr Adj Rsqr


0.9947 0.9894 0.9868

0.0545


a 3.1084 1.7551 1.771 0.1019

b 10.0721 3.8155 2.6398 0.0216

x0 2010.298 9.4554 212.6092 <0.0001

y0 0.1594 0.149 1.0699 0.3057

Table 4 Flow per capita

projections

Polynomial, Linear

𝑓 = 𝑦0 + 𝑎 ∗ 𝑥

R Rsqr Adj Rsqr


0.7458 0.5563 0.5246

3.8525


y0 -808.147 208.5157 -3.8757 0.0017

a 0.4376 0.1045 4.1892 0.0009


𝑓 = 𝑦0 + 𝑎 ∗ 𝑒𝑥𝑝(𝑏 ∗ 𝑥)

R Rsqr Adj Rsqr


0.7458 0.5562 0.488

3.9979


y0 -4610006 103684615.7 -0.0445 0.9652

a 4609198 103684595.6 0.0445 0.9652

b 9.49E-08 2.13E-06 0.0445 0.9652


𝑓 = 𝑦0 + 𝑎 ∗ (1 − 𝑒𝑥𝑝(−𝑏 ∗ 𝑥))

R Rsqr Adj Rsqr


2.80E-07 7.82E-14 -0.1538

6.0016


y0 23.3454 12.0032 1.9449 0.0737

a 42.01 24.0064 1.75 0.1037

b 0.0154 0 (+inf) <0.0001


𝑓 = 𝑦0 + 𝑎/(1 + 𝑒𝑥𝑝(−(𝑥 − 𝑥0)/𝑏))

R Rsqr Adj Rsqr


0.8784 0.7717 0.7146

2.9849


a 17.2375 8.8995 1.9369 0.0767

b 2.4157 1.8744 1.2888 0.2218

x0 1985.347 3.1694 626.4142 <0.0001

y0 51.1301 8.5455 5.9833 <0.0001

Figure 1 Projected population

Year

1970 1980 1990 2000 2010 2020 2030

Pop

ulat

ion

(cap

ita)

0

20000

40000

60000

80000

Year vs Population Col 11 vs Predicted Population (Sigmoidal)

16

Figure 5 Projected Flow per Capita

Year

1970 1980 1990 2000 2010 2020 2030

Flow

per

Cap

ita (g

pcd)

20

30

40

50

60

70

80

Year vs Flow per Capita (gpcd) Col 54 vs Projected Flow per Capita (Sigmoidal) 95% Confidence Band 95% Prediction Band

Figure 6

17

CONCLUSIONS AND RECOMMENDATIONS

The exponential growth model (Figure 7) was selected to best represent the flow projections for the data given. Among the models generated, it has the larger R2 value and a smaller Standard Error of Estimate. Table 5 was taken from the graph in Figure 3 to predict the flow for 5, 10, and 20 years, including the confidence interval.

Figure 7 Exponential Growth, Single, 3 Parameter

𝑓 = 𝑦0 + 𝑎 ∗ 𝑒𝑥𝑝(𝑏 ∗ 𝑥)

R Rsqr Adj Rsqr Standard Error of Estimate

0.9942 0.9883 0.9865

0.055


y0 -0.133 0.1545 -0.8607 0.405

a 3.53E-44 5.56E-43 (+inf) <0.0001

b 0.0501 0.0078 6.4181 <0.0001

Table 5 Predicted Flow (MGD) Year Predicted 95% Conf-L 95% Conf-U 2016 2.3409 2.0964 2.5855 2021 3.0454 2.5874 3.5034 2031 5.1135 3.7173 6.5098

18

PRETREATMENT

EXECUTIVE SUMMARY

The raw source water for a 6 MGD NF plant is analyzed for scaling. Pretreatment options are determined based on limiting salts. The maximum recovery rate for each salt is listed in table below:

Salt R CaCO3 Varies with pH BaSO4 0.72 CaF2 0.81 CaSO4 0.94 Ca3(PO4)2 1 CaCO3 scaling can be controlled with acid dosing. However, BaSO4 limits the recovery to 72% if pretreatment is limited to acid only. If pretreatment involves the use of an anti-scalent, there are no limits on the recovery rate because of scaling. An acid is not required if an Avista Vitec anti-scalent is used. Adjusting is the pH is only necessary if the intent is to extend the life of cellulosic membranes.

I recommend using a Vitec anti-scalent for this particular source water. The anti-scalent requires less dosage at a smaller pump rate and there are no limits to the recovery rate from scaling. I also recommend a 5 μm cartridge filter to catch any metal ions that might deposit in the feed system.

R Vitec 1000 Dose (mg/L)

Usage (kg/day) Pump Rate (L/hr)

0.3 4.27 323.27 11.216 0.39 3.72 216.64 7.516 0.47 3.23 156.09 5.415 0.55 2.74 113.15 3.926 0.61 2.38 88.62 3.074 0.66 2.07 71.23 2.471 0.72 2 63.09 2.189 0.75 2 60.57 2.101 0.79 2 57.50 1.995 0.82 2 55.40 1.922 0.85 2 53.44 1.854 0.87 2 52.21 1.811 0.89 2 51.04 1.771 0.91 2 49.92 1.732 0.92 2 49.37 1.713 0.93 2 48.84 1.695 0.94 2 48.32 1.677 0.95 2 47.82 1.659

19

INTRODUCTION

The purpose of this report is to identity the pretreatment options available to the particular raw water parameters listed in Table 1. The pretreatment is for a NF treatment plant with a 6 MGD output. The maximum recovery rate of a NF plant is limited by the solubility of particular salts. Salts concentrate as they pass through a membrane and can precipitate causing the membrane to foul. These salts are referred to as limiting salts. The recovery rate of NF membranes can be improved with chemical agents. The solubility of these salts can be increased with proprietary chemical additions, such as an anti-scalent. The solubility of a particular cation can be increased if the anion of the salt can be deceased. The anion of calcium carbonate, CO3-2, can be decreased with the addition of an acid increasing the solubility of Ca+2. This report will therefore analyze acid dosing and the use of an anti-scalent.

Table 1: Water Quality Parameters

Raw (mg/L) Feed (mg/L)

Cations, mg/l: Aluminum 0.182 Barium 0.03 0.038 Calcium 136.25 139.46 Copper 0.01 0.01 Iron 2.12 2.953 Magnesium 3.89 4.718 Manganese 0.042 0.051 Potassium 0.5 0.779 Sodium 21.2 20.95 Strontium 0.321 Zinc 0.011 Total Cations, mg/l 164.042 169.473

Anions, mg/l: Alkalinity, as CaCO3 34 Alkalinity, as HCO3 41 Bromide 2.5 2.5 Chloride 48.8 54.6 Fluoride 0.5 0.5 Nitrate 2.5 2.5 Sulfate 20.34 279 Total anions, mg/l 380.1 Total ions, mg/l 549.573

Other: Carbon dioxide as CO2, mg/L 29.16 pH 7.2 5.36 Temperature, deg F 78.3 79 Conductivity, mhos 740 TOC, mg/l 9.67 Silicon, mg/l as Si 5.53 5.642 Phosphorus, mg/l as P 0.05 0.35 Boron, mg/l 0.037 0.038 TDS, mg/L 600.4 549.573 Carbonate, mg/L

HPC positive Iron reducing bacteria positive Slime former bacteria positive Sulfate reducing bacteria positive

20

THEORY

NF membranes are subject to many forms of fouling. Deposition of silt (suspended solids), inorganically scaling, biological fouling, and organics interactions can foul membranes. A pretreatment process is required to mitigate these potential sources of fouling.

This report focuses primarily on the scaling potential of the source water. The scaling patenting increases as the ions become more concentrated in the concentrate stream. If the ion product of the salt exceeds the solubility (Ksp) of the salt, the salt will precipitate in the membrane, fouling it.

Some salts can irreversibly foul a membrane like BaSO4. CaCO4 fouling can be clean with an acid wash. Silicates precipitate slowly (from slow kinetics) and can be oversaturated in the concentrate stream if the concentrate moves through the membranes fast enough.

Scale inhibitors or anti-scalents can reduce the amount of inorganic salts that precipitate in the membrane channel. Synthetic polymers can provide goof calcium carbonate and calcium sulfate control.

Some methods of preventing inorganic scaling include: acidifying to remove carbonate ions, limiting the recovery, softening the water source to remove calcium ions, and the use of threshold scale inhibitors.

List of common inorganic foulants:

• Calcium carbonate (CaCO3) • Calcium sulfate (CaSO4) • Barium sulfate (BaSO4) • Strontium sulfate (SrSO4) • Calcium fluoride (CaF2) • Calcium phosphate (CaPO4) • Silica (SiO2) • Ferric hydroxide [Fe(OH)3] • Aluminum hydroxide [Al(OH)3] • Sulfur (S)

21

PROCEDURE

BICARBONATE CALCULATION

The bicarbonate measurements were not given for the raw water. The numbers were back calculated from the feed water alkalinity assuming the raw water and the feed water are in a closed system and that CT is constant and equal for both systems. The Alkalinity for the raw water is listed in Table 2.

[𝐻𝐶𝑂3−] = 𝛼1𝐶𝑇

[𝐶𝑂3−2] = 𝛼2𝐶𝑇

[𝐴𝑙𝑘] = 2[𝐶𝑂3−2] + [𝐻𝐶𝑂3−] + [𝑂𝐻−] − [𝐻+]

LIMITING SALT CALCULATION

The limiting salts can be roughly identified using the Ksp value and ion concentration. The most limiting salt is the salt with the lowest recovery rate, R. The calculations are listed in Table 3 for the raw water ion concentrations.

𝐴𝑛𝐵𝑚 → 𝑛𝐴+𝑝 + 𝑚𝐵−𝑞

𝐾𝑠𝑝 = �[𝐴+]

1 − 𝑅�𝑛

�[𝐵−]

1− 𝑅�𝑚

𝑅 = 1 − �[𝐴+]𝑛[𝐵−]𝑚

𝐾𝑠𝑝�1/(𝑚+𝑛)

LIMITING SALT MAXIMUM RECOVERY RATE

The Ksp value varies with (or is a function of) ionic strength, μ. Ionic strength varies with recovery rate, R. When determining the maximum recovery rate of each limiting salt, the ionic strength of the concentrate has to be considered. The solubility if the limiting salts increases as the ionic strength of the concentrate increases.

𝑅 = 1 − �[𝐴+]𝑛[𝐵−]𝑚

𝐾𝑐�1/(𝑚+𝑛)

𝐾𝑐 =𝐾𝑠𝑝𝛾𝑝𝑛𝛾𝑞𝑚

log 𝛾𝑧 = −0.5 𝑍2 √𝜇1 + √𝜇

𝜇 =1

2(1 − 𝑅)�𝐶𝑖𝑍𝑖2

𝑖

Finding the maximum recovery rate leads to a complex function of R, a left hand side value and a right hand side value. The two values however can be shown to converge at the maximum recovery rate through multiple iterations of R using a spreadsheet, as shown in the appendix.

The convergent values or maximum recovery rates for each limiting salt for the raw water measurements are listed in Table 4.

CACO3 RECOVERY RATE, PH, AND ACID DOSE

The solubility of CaCO3 is a product of the Ca2+

concentration and the CO32- concentration. The CO32- concentration varies with pH and so can be controlled using an acid. Lowering the pH reduces the CO32- concentration. Lowering the CO32- concentration allows more Ca2+ to stay in solution there increasing the maximum allowable recovery rate imposed by this limiting salt.

𝑅 = 1 − �[𝐶𝑎+2][𝐶𝑂3−2]

𝐾𝐶𝑎𝐶𝑂3�1/2

𝐾𝐶𝑎𝐶𝑂3 =𝐾𝑠𝑝𝛾±22

𝐶𝑎𝑟𝑏𝑜𝑛𝑖𝑐 𝑎𝑐𝑖𝑑:

[𝐶𝑂3−2] = 𝛼2𝐶𝑇

22

𝛼2 =1

1 + [𝐻+]𝐾𝑎2𝑐

+ [𝐻+]2𝐾𝑎1𝑐𝐾𝑎2𝑐

𝐾𝑎1𝑐 =𝐾𝑎1𝛾±12

𝐾𝑎2𝑐 =𝐾𝑎2𝛾±2

log 𝛾𝑧 = −0.5 𝑍2 √𝜇1 + √𝜇

𝜇 =1

2(1 − 𝑅)�𝐶𝑖𝑍𝑖2

𝑖

CO32- concentration varies with both the pH and the ionic strength of the concentrate. Using an iterative method, the convergent value, or recovery rate, can be determined for each pH. Figure 1 is graph of the recovery rate of CaCO3 versus pH.

Acid dose is the amount of acid required to reach the target pH.

𝐾𝑎2 =10−𝑝𝐻 �𝐶𝑂3−2𝑝𝐻0 − 𝑥�

𝑥

𝐶𝑂3−2𝑝𝐻0 = 𝛼2𝑝𝐻0𝐶𝑇

𝑥 = 𝑎𝑐𝑖𝑑 𝑑𝑜𝑠𝑒 (𝑒𝑞 𝐿⁄ )

ANTI-SCALENT

For this analysis, Avista anti-scalents were evaluated. The Avista Advisor 3 report is included in this section. The iron, aluminum, and manganese concentrations are set to zero in this evaluation. The concentrations of those metal ions are over 100% saturation according to Avista Advisor. Therefore, the raw water must be treated or handled for properly for those metals not precipitate.

Avista offers eight anti-scalent selections. Avista’s Vitec 1000 was evaluated for this source water. The calculations are all done in

Avista Advisor. The dose, usage, and pump rate are listed in Table 5.

23

RESULTS

Table 2: Water Quality Parameters

Raw (mg/L) Feed (mg/L) Raw Raw

Cations, mg/l: MW (g/gmol) M (mol/L) N (eq/L) Aluminum 0.182 0.182 26.98 6.75E-06 1.35E-05 Barium 0.030 0.038 137.34 2.18E-07 4.37E-07 Calcium 136.250 139.46 40.08 3.40E-03 6.80E-03 Copper 0.010 0.01 63.546 1.57E-07 3.15E-07 Iron 2.120 2.953 55.847 3.80E-05 7.59E-05 Magnesium 3.890 4.718 24.305 1.60E-04 3.20E-04 Manganese 0.042 0.051 54.938 7.64E-07 1.53E-06 Potassium 0.500 0.779 39.098 1.28E-05 1.28E-05 Sodium 21.200 20.95 22.989 9.22E-04 9.22E-04 Strontium 0.321 0.321 87.62 3.66E-06 7.33E-06 Zinc 0.011 0.011 65.39 1.68E-07 3.36E-07 Total Cations, mg/l 164.556 169.473

4.54E-03 8.15E-03

Anions, mg/l: MW (g/gmol) M (mol/L) N (eq/L) Alkalinity, as CaCO3 331.813 34 100.09

Alkalinity, as HCO3 404.514 41 61.01 6.63E-03 6.63E-03 Bromide 2.500 2.5 79.9 3.13E-05 3.13E-05 Chloride 48.800 54.6 35.45 1.38E-03 1.38E-03 Fluoride 0.500 0.5 19 2.63E-05 2.63E-05 Nitrate 2.500 2.5 62.01 4.03E-05 4.03E-05 Sulfate 20.340 279 46.01 4.42E-04 8.84E-04 Total anions, mg/l 479.154 414.1

8.55E-03 8.99E-03

The alkalinity in Table 2 at a pH of 7.2 was back calculated from a pH of 5.36 in the feed water. CT was assumed to be constant and equal for both the raw and feed waters. The table of calculation is listed in the appendix.

Table 3: Limiting Salts pKa Ksp Kc X R CaCO3 8.3 5.01E-09 1.27E-08 1.15 -0.15 CaSO4 4.7 2.00E-05 5.06E-05 0.17 0.83 BaSO4 9.7 2.00E-10 5.06E-10 0.44 0.56 SrSO4 6.2 6.31E-07 1.60E-06 0.03 0.97 CaF2 10.3 5.01E-11 1.01E-10 0.29 0.71 Ca3(PO4)2 6.8 1.58E-07 5.19E-06 0.00 1.00 SiO2 2.7 2.00E-03 3.25E-02 0.00 1.00

24

The most limiting salt for the raw water is CaCO3 followed by BaSO4.

Table 4: Maximum Recovery Rates Salt R CaCO3 Varies with pH BaSO4 0.72 CaF2 0.81 CaSO4 0.94 Ca3(PO4)2 1

The recovery rate for each limiting salt was calculated according the ionic strength of the concentrate as it varied with the recovery rate. Table 4 lists the rates at with the values converged. The table of calculations for each salt is listed in the Appendix.

Figure 1:

Figure 2:

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200 250 300 350

Reco

very

Rat

e

Acid Dose (ppm 100% H2SO4)

CaCO3 Recovery Rate

0

50

100

150

200

250

300

350

4.8 5.3 5.8 6.3 6.8

mg/

L H 2

SO4

pH

Acid Dose vs pH

25

The most limiting salt is CaCO3. The recovery rate of CaCO3 improves at the pH is lowered by dosing the raw water with acid, after which point BaSO4 becomes limiting. Figure 1 is graph of the recovery rate as the raw water is dosed with sulfuric acid. Figure 2 relates acid dosage to the target pH. BaSO4 is limited to 72% recovery. CaCO3 is limited to 72% recovery at a pH of 6.09. After a pH of 6.09, BaSO4 becomes the limiting salt.

Table 5: Acid and Anti-scalent Comparison Output: 6 MGD Acid only (100% solution H2SO4) Vitec 1000 R Acid Dose

(mg/L) pH Usage

(kg/day) Pump Rate (L/hr)

Anti-Scalent Dose (mg/L)

Usage (kg/day)

Pump Rate (L/hr)

0.3 61.3 6.7 4.64E+03 193.37 4.27 323.27 11.216 0.39 78.8 6.6 4.59E+03 191.21 3.72 216.64 7.516 0.47 97.7 6.5 4.72E+03 196.72 3.23 156.09 5.415 0.55 117.8 6.4 4.86E+03 202.69 2.74 113.15 3.926 0.61 138.5 6.3 5.16E+03 214.87 2.38 88.62 3.074 0.66 159.2 6.2 5.48E+03 228.27 2.07 71.23 2.471 0.72 179.5 6.09 5.66E+03 235.93 2 63.09 2.189 0.75 198.8 6 6.02E+03 250.85 2 60.57 2.101 0.79 216.8 5.9 6.23E+03 259.71 2 57.50 1.995 0.82 233.2 5.8 6.46E+03 269.13 2 55.40 1.922 0.85 247.8 5.7 6.62E+03 275.89 2 53.44 1.854 0.87 260.5 5.6 6.80E+03 283.36 2 52.21 1.811 0.89 271.5 5.5 6.93E+03 288.69 2 51.04 1.771 0.91 280.9 5.4 7.01E+03 292.12 2 49.92 1.732 0.92 288.7 5.3 7.13E+03 296.97 2 49.37 1.713 0.93 295.3 5.2 7.21E+03 300.49 2 48.84 1.695 0.94 300.8 5.1 7.27E+03 302.83 2 48.32 1.677 0.95 305.3 5 7.30E+03 304.13 2 47.82 1.659

BaSO4 is limiting at R above .72 for acid only

Only Vitec 1000 anti-scalent was evaluated in this report at raw water pH of 7.2 without acid dosing. However, there were no limiting salts for any of Vitec anti-scalent solutions at their minimum 2 ppm dose. All the limiting salts were below the 100% saturation index if a Vitec anti-scalent is used.

Table 5 compares the different usage rates for the acid and the anti-scalent at different recovery rates. The values in Table 5 were taken Avista Advisor and calculated for 6 MGD output.

26

CONCLUSION

CaCO3 is the most limiting salt followed by BaSO4 then CaF2. CaCO3 can be controlled by acid dosing to about a pH of 6.09 after which BaSO4 becomes limiting. The recovery rate for BaSO4 can only be increased with an anti-scalent. An anti-scalent, Vitec 1000 by Avista, was evaluated for this report using Avista Advisor 3. At the minimum ppm dosage of the anti-scalent (2 ppm), there are no limits to the recovery rate from scaling. Because there is no scaling at the raw water pH of 7.2, no acid dosing is necessary.

RECOMMENDATION

I recommend that the raw water be pretreated with the Vitec 1000 anti-scalent only. The anti-scalent requires a lower overall usage rate and the pump rate is also lower, which reduces costs. The anti-scalent requires smaller pumps, less chemical and less storage in comparison to acid dosing. Acid dosing is required with cellulosic membranes to correct the pH to the 5.5 to 6 range. Correcting the pH for cellulosic membranes extends the service life of those membranes, reducing operational costs.

Because of the large concentration of metal ions, the pretreatment process must be isolated from air or any other oxidizing sources. The precipitates formed by oxidized metals can foul the membrane. Or the metal ions can precipitated before entering the membrane by other methods of pretreatment. I recommend that 5 μm cartridge filter be applied before the feed water enters the membrane to catch any oxidized metals or colloidal suspensions that may foul the membrane.

SOURCES

• Reverse Osmosis and Nanofiltration. 2nd Ed. Manual of Water Supply Practices: M46. American Water Works Association. 2007.

27

APPENDIX A

pH 5.36 7.2 [H+] 4.37E-06 6.31E-08 Ka1 4.27E-07 4.27E-07 Ka2 4.68E-11 4.68E-11 α0 9.11E-01 1.29E-01 α1 8.90E-02 8.71E-01 α2 9.54E-07 6.45E-04 CT 7.60E-03 7.60E-03 CO3

-2 7.25E-09 4.91E-06 HCO3

- 6.77E-04 6.62E-03 Alk (M) 6.73E-04 6.63E-03 Alk as HCO3

- 4.10E+01 4.05E+02

C*z^2 Aluminum 2.70E-05 Barium 8.74E-07 Calcium 1.36E-02 Copper 6.29E-07 Iron 1.52E-04 Magnesium 6.40E-04 Manganese 3.06E-06 Potassium 1.28E-05 Sodium 9.22E-04 Strontium 1.47E-05 Zinc 6.73E-07 HCO3 6.62E-03 CO3 1.96E-05 Bromide 3.13E-05 Chloride 1.38E-03 Fluoride 2.63E-05 Nitrate 4.03E-05 Sulfate 1.77E-03 Σ C*z^2 2.53E-02

28

Pass through P1 P2 P3

0.8 0.9 0.95

R X u y+1 y+2 y+3 y+4 0 1 0.0126273 8.90E-01 6.28E-01 3.51E-01 1.56E-01

0.1 0.9 1.40E-02 8.85E-01 6.14E-01 3.34E-01 1.42E-01 0.2 0.8 1.58E-02 8.79E-01 5.98E-01 3.15E-01 1.28E-01 0.3 0.7 1.80E-02 8.73E-01 5.80E-01 2.93E-01 1.13E-01 0.4 0.6 2.10E-02 8.64E-01 5.58E-01 2.69E-01 9.69E-02 0.5 0.5 2.53E-02 8.54E-01 5.32E-01 2.42E-01 8.00E-02 0.6 0.4 3.16E-02 8.41E-01 4.99E-01 2.09E-01 6.21E-02 0.7 0.3 4.21E-02 8.22E-01 4.57E-01 1.71E-01 4.35E-02 0.8 0.2 6.31E-02 7.94E-01 3.97E-01 1.25E-01 2.47E-02 0.9 0.1 1.26E-01 7.39E-01 2.99E-01 6.61E-02 7.99E-03

pH= 6.09 H= 8.13E-07 pH 6.09 Converges

Carbonic Acid

0.72

Ka1 Ka2 CT Ca

CaCO3

4.2658E-07 4.67735E-11 7.60E-03 3.40E-03

R X Kspc Ka1c Ka2c CO3 X R of Salt ΔR 0.72 0.28 2.52E-08 2.14118E-06 1.05E-10 7.11E-07 0.279 0.721 0.001 0.75 0.25 2.72E-08 2.3121E-06 1.08894E-10 7.54E-07 0.276 0.724 -0.026 0.78 0.22 2.97E-08 2.52982E-06 1.13906E-10 8.06E-07 0.273 0.727 -0.053 0.81 0.19 3.31E-08 2.81732E-06 1.20204E-10 8.73E-07 0.269 0.731 -0.079 0.84 0.16 3.78E-08 3.21561E-06 1.2842E-10 9.59E-07 0.264 0.736 -0.104 0.87 0.13 4.47E-08 3.80568E-06 1.39706E-10 1.08E-06 0.258 0.742 -0.128

0.9 0.1 5.61E-08 4.77232E-06 1.56446E-10 1.25E-06 0.248 0.752 -0.148 0.93 0.07 7.81E-08 6.6441E-06 1.84594E-10 1.54E-06 0.233 0.767 -0.163 0.96 0.04 1.38E-07 1.17204E-05 2.45172E-10 2.14E-06 0.207 0.793 -0.167

29

BaSO4 Ksp Ba (M) SO4 (M) Converges

2.00E-10 2.18E-07 4.42E-04 0.72

R X Kspc X R of Salt ΔR 0.72 0.28 1.00E-09 0.279 0.721 0.001 0.75 0.25 1.08E-09 0.269 0.731 -0.019 0.78 0.22 1.18E-09 0.257 0.743 -0.037 0.81 0.19 1.32E-09 0.244 0.756 -0.054 0.84 0.16 1.50E-09 0.228 0.772 -0.068 0.87 0.13 1.78E-09 0.210 0.790 -0.080

0.9 0.1 2.23E-09 0.187 0.813 -0.087 0.93 0.07 3.11E-09 0.159 0.841 -0.089 0.96 0.04 5.48E-09 0.119 0.881 -0.079

CaF2 Ksp Ca F Converges

5.01E-11 3.40E-03 2.63E-05 0.81

R X Kspc X R of Salt ΔR 0.72 0.28 1.68E-10 0.201 0.799 0.079 0.75 0.25 1.78E-10 0.197 0.803 0.053 0.78 0.22 1.90E-10 0.192 0.808 0.028 0.81 0.19 2.06E-10 0.187 0.813 0.003 0.84 0.16 2.28E-10 0.181 0.819 -0.021 0.87 0.13 2.59E-10 0.174 0.826 -0.044

0.9 0.1 3.07E-10 0.164 0.836 -0.064 0.93 0.07 3.93E-10 0.151 0.849 -0.081 0.96 0.04 6.01E-10 0.131 0.869 -0.091

CaSO4 Ksp Ca (M) SO4 (M) Converges

2.00E-05 3.40E-03 4.42E-04 0.94

R X Kspc X R of Salt ΔR 0.72 0.28 1.00E-04 0.110 0.890 0.170 0.75 0.25 1.08E-04 0.106 0.894 0.144 0.78 0.22 1.18E-04 0.101 0.899 0.119 0.81 0.19 1.32E-04 0.096 0.904 0.094 0.84 0.16 1.50E-04 0.090 0.910 0.070 0.87 0.13 1.78E-04 0.083 0.917 0.047

0.9 0.1 2.23E-04 0.074 0.926 0.026 0.93 0.07 3.11E-04 0.063 0.937 0.007 0.96 0.04 5.48E-04 0.047 0.953 -0.007

30

Ca3(PO4)2 Ksp Ca (M) PO4 Converges

1.58E-07 3.40E-03 1.62E-06 1

R X Kspc X R ΔR 0.9 0.1 5.19E-06 0.002 0.998 0.098

0.91 0.09 1.36E-03 0.001 0.999 0.089 0.92 0.08 1.94E-03 0.001 0.999 0.079 0.93 0.07 2.92E-03 0.000 1.000 0.070 0.94 0.06 4.69E-03 0.000 1.000 0.060 0.95 0.05 8.27E-03 0.000 1.000 0.050 0.96 0.04 1.65E-02 0.000 1.000 0.040 0.97 0.03 3.94E-02 0.000 1.000 0.030 0.98 0.02 1.27E-01 0.000 1.000 0.020

31

MEMBRANE PROCESS

INTRODUCTION

A nanofiltration plant has to be designed to produce 4.5 million gallons a day. The plant must be expandable to 6.0 MGD to accommodate a future increase in demand. The raw is pretreated for limiting salts before entering the membrane. The recovery should be within recovery rate imposed by the limiting salt.

BACKGROUND AND THEORY

Membrane configurations are divided into arrays, stages, vessels, and elements. Source water is usually pretreated before entering the membrane. Membranes treat water by rejecting salts and other dissolved solids. Membrane manufacturers produce membranes with a wide range of rejection characteristics. Nanofiltration membranes have lower rejection characteristics compared to RO membranes. Nanofiltration membranes operate at lower pressures and treat lower TDS source waters.

Spiral wound nanofiltration membranes are manufactured in the same manner as RO membranes. Spiral wound membranes are composed of leaves, which are coated with a rejection layer (polyamide). The leaves are separated by channels. Feed water flows from the feed water or concentrate channel into the permeate channel. The feed water has to overcome the osmotic pressure of the permeate channel to flow into the feed channel. Therefore, the feed water has to be supplied at higher pressures by high pressure pumps to produce permeate. The flow through a membrane element is the flux of the membrane element. These high pressure systems require structurally sound components that can continually operate at those pressures. The construction and reliability of pressure vessels are important aspects in selecting pressure vessels.

As the salts in the feed water stream concentrate, the osmotic pressure across the membrane increases. Thus, membrane arrays are dynamically modeled systems. Computer modeling software is a convenient tool in designing these systems. The purpose of this report is to outline an efficient design for the 4.5 MGD plant. Selection of the proper membrane, configuration, and equipment is vital in identifying a flexible, cost effective, and efficient design.

32

METHODS

DESIGNING MEMBRANE ARRAY

The initial design of the nanofiltration plant starts with the desired permeate flow and limiting recovery rate. Feed water flow rate is calculated from those two parameters.

𝑄𝑓𝑒𝑒𝑑 =𝑄𝑝𝑒𝑟𝑚𝑒𝑎𝑡𝑒

𝑅

Selecting a flux for the membrane element determines the amount of membranes required for this NF plant. The number of stages and elements in each pressure vessel is dependent on the recovery rate. An array is the ratio of the pressure vessels in each stage.

𝑛𝑎𝑟𝑟𝑎𝑦𝑠 =𝑄𝑝𝑒𝑟𝑚𝑒𝑎𝑡𝑒

𝑓𝑙𝑢𝑥 ∗ 𝐴𝑟𝑒𝑎𝑚𝑒𝑚𝑏𝑟𝑎𝑛𝑒 ∗ 𝑛𝑣𝑒𝑠𝑠𝑒𝑙𝑠𝑎𝑟𝑟𝑎𝑦

∗ 𝑛𝑒𝑙𝑒𝑚𝑒𝑛𝑡𝑠𝑣𝑒𝑠𝑠𝑒𝑙

The array setup, permeate flow, recovery rate, and membrane model are inputted into the modeling software. The software used in this evaluation is the DOW’s Reverse Osmosis System Analysis.

Adding backpressure or boost pressure to the system and varying the other parameters improve the permeate TDS or stay within the limits of the manufacturers recommended flow.

EQUIPMENT

MONITORING DEVICE

The flow through the device and the salt concentration of the different channels should be monitored to detect any problems with the membranes. TDS meters can provide real-time data on salt concentrations. Flow meters should be accurate and reliable enough to monitor the recovery rate of the system.

PUMPS

The number of pumps should satisfy the required redundancy of the system. High pressure pumps should operate at their peak efficiency and above the NPSH set by the manufacture to prevent cavitations. Reliability, availability of parts, and delivery are important aspects in pump selection.

ENERGY RECOVERY

Energy recovery is energy cost savings. The pressure in the concentrate stream can be recovered to boost the pressure to a stage or save energy costs on the feed channel pump.

VALVES

Valves are used to NF plants to control flow or apply backpressure to membranes. Since NF operates at high pressures with possibly aggressive or corrosive permeate streams, sturdy and

33

corrosion resistant devices are required for continued operation. Valves must be made from high quality, corrosion resistant steel.

34

RESULTS

MEMBRANE SELECTION

A DOW FILMTEC membrane was evaluated for this water treatment plant. The NF90-400 is an 8 inch by 40 inch membrane element. Large elements have more surface area and are suited to treating large flows. Compared to the other FILMTEC nanofiltration membrane, the NF270-400, the NF90-400 has a higher rejection characteristic and can achieve higher recovery rates compared to the NF270. The NF90 performs better in a 2 stage setup. The NF90 produces lower TDS permeate and will reject more iron than NF270. This permeate can be blended with the source water if the final product water can satisfy both primary and secondary standards. Table 1 details the specifications of the NF90-400.

Table 1: Element Specs Element NF90-400 Surface Area 400 ft2 Permeate Flow Rate NaCl 7,500 gpd MgSO4 9,500 gpd Salt Rejection NaCl 85-95% MgSO4 >95% Maximum permeate flow 6.32 gpm Maximum element recovery 19% Minimum concentrate flow 13 gpm

ARRAY CONFIGURATION

The design evaluated for this 4.5 MDG treatment plant is a two stage design. This allows the plant to achieve higher recovery rates. The target flux for this array is 15 gfd. The target recovery rate is 82%. To achieve recovery rates above 70% in a two stage array, at least 6 elements are required in each pressure vessel. An 84-42 array with 6 elements per pressure vessel was calculated from these target parameters. The 84-42 array was evaluated in DOW’s Reverse Osmosis System Analysis software, or ROSA. Table 2 lists results from that analysis. 8 psig of backpressure was applied to the first stage to avoid exceeding the maximum allowable permeate flow in the first element and also achieve the minimum concentrate flow. DOW does not recommend applying back pressure to membrane elements.

35

Figure 2:

Table 2: Array configuration Stage 1 Stage 2 Total No. Pressure Vessels 84 42 126 No. Elements 504 252 756 Concentrate Flow (gpm) 1420.55 685.45 882 Concentrate TDS (mg/L) 1692.1 3370.45 2238.361 Permeate Flow (gpm) 2390.24 735.1 3120.361 Permeate TDS (mg/L) 35.7 118.57 55.18 % Recovery 63.10% 51.26% 82% Backpressure (psig) 8 0 Flux (gfd) 17.28 10.09 14.88

ARRAY EXPANSION

The treatment plant must expand from a 4.5 MDG plant to a 6 MGD plant. Increasing the flux of the membrane element increases the chance of fouling and can reduce the life of the membrane. Therefore, additional arrays must be added t o meet the additional capacity. Each additional array is can treat up to 0.1087 MGD from Table 3.

Table 3: Projected Expansion to 6 MGD Capacity (MGD)

Element area (ft2)

No. Vessels per array

No elements per vessel

Flux (gfd)

No. arrays

No. vessels

No. elements

MGD/array

4.5 400 3 6 14.88 42 126 756 0.1071 5 400 3 6 15.10 46 138 828 0.1087 5.5 400 3 6 14.98 51 153 918 0.1078 6 400 3 6 14.88 56 168 1008 0.1071

MODIFYING THE ARRAY CONFIGURATION

36

The array can be modified to change the energy requirements, the pressure across the membrane (NDP) and the permeate TDS. From Table 4, increasing the number of arrays can lower energy usage if energy costs are a concern. Lowering the pressure across the membrane, however, allows more salts to pass through the membrane, increasing TDS. Adjusting the recovery rate of the array also affects the energy requirements and the permeate TDS.

Table 4: Effect of Modifying the Number Arrays 4.5 MGD 2-1 Array 10 psig backpressure 82% Recovery 80% efficient pump No. Arrays No. elements Power (kW) Average NDP (psig) Permeate TDS (mg/L) 42 756 165.25 48.84 55.18 43 774 162.04 47.77 56.22 44 792 159 46.77 57.25 45 810 156.11 45.81 58.28 46 828 153.36 44.89 59.3 Table 5: Effect of Varying Recovery Rate 4.5 MGD 84-42 Array 10 psig backpressure 80% efficient pump Recovery Rate Power (kW) NDP (psig) TDS (mg/L) 0.82 165.25 48.84 55.18 0.81 167.7 48.83 53.82 0.8 170.29 48.83 52.61 0.78 175.82 48.82 50.4 0.76 181.7 48.77 48.51 0.74 188.52 48.84 46.81

PRESSURE VESSEL

The feed stream loses pressure as it travels through the membrane as result of friction and flow characteristics. The ROSA software calculates the feed pressure through each membrane. The results are listed in Table 6. The pressure vessel must be designed to operate at these pressures plus a factor of safety. The feed pressure may also increase if the element or the array is later modified. There is a 5 psig drop in pressure between stage 1 and stage 2.

A pressure vessel that is ASME compliant is a good indicator of durability. CodeLine’s 80U30H-6 pressure vessel holds six 8”x40” elements.

37

Table 6: Pressure through elements Element Feed Pressure (psig) Pressure Drop (psig) Stage 1 1 73.38 4.79 2 68.59 3.91 3 64.68 3.16 4 61.52 2.5 5 59.02 1.96 6 57.06 1.47 Stage 2 1 50.59 3.11 2 47.48 2.61 3 44.87 2.19 4 42.68 1.85 5 40.83 1.57 6 39.26 1.34 Stage 1 Concentrate Pressure = 55.59 Stage 2 Concentrate Pressure = 37.92

38

AUXILIARY EQUIPMENT

MONITORING DEVICES

As the membranes age, salt passage increases. Fouling can damage membranes and increase salt passage. TDS meters will detect changes in the salt passage through the system. Large changes in TDS should flag any damage to the membranes. Fouling can cause the permeate flow through the membrane to decrease. Flow meters will detect any such changes in flow and flag fouling issues.

FEED PUMPS

The membrane arrays can be divided into process trains with one high pressure pump controlling each process train. Vertical multistage pumps are common in NF systems. More pumps increase the redundancy of the system should one pump fail. Feed pumps can be integrated with energy recovery systems that recovery energy from the concentrate stream. Variable speed pumps are not necessary for this application.

The pump head needed to develop 74 psig in the first stage is approximately 174 ft. The total feed water flow is 3,125 gpm. Ten EBARA EVMU64 stainless steel vertical multistage pumps can supply 312.5 gpm each and the required pressure at peak efficiency (80%) between 20 and 15 hp (Figure 3 and Figure 4). This divides the NF plant in 10 process trains.

Figure 3: Pump Curve

39

Figure 4: Pump Efficiency Curve

HYDRAULIC TURBOCHARGERS

Hydraulic turbochargers can be used to recover energy while also boosting pressure to other stages with a multistage system. Interstage pressure boosting helps balance the difference in flux between two stages. Table 9 demonstrates the effect of interstage pressure when applied to the 84-42 membrane array. Interstage boosting increased the low flux in stage 2, reduced the high flux in stage 1, and reduced overall salt passage.

Table 8: Pressure Boost Calculation Qf (gpm) Qc (gpm) HTeff Pin (psig) Pout (psig) Pboost 1420.77 685.55 0.65 38.89 10 9.061 Table 9: Interstage Boosting 82% Recovery Pboost= 9 psig 84-42 Array

Flux (gfd) Permeate TDS (mg/L) Stage 1 Stage 2

Boosted 16.16 12.34 53.42 Unboosted 17.28 10.09 55.18

VALVES

Valves can be used to control the flow and the back pressure on membranes. The valves located on the concentrate stream must withstand the high pressures of the concentrate. The concentrate pressure on the stage 1 valve is 56.80 psig. Valves are also needed to cut or route flow to other skids or process trains in the array. Pressure relief valves, check valves, and air relief maintain allow the system to operate.

BACKPRESSURE

Backpressure can be applied to a membrane to reduce the flux through that membrane and conserve pressure as it leaves the pressure vessel. Backpressure is a way of balancing the difference in flux between two stages. If the maximum manufacture recommended permeate flow though a membrane is exceeded, applying backpressure can reduce that flow. If the concentrate flow in the last element falls below the minimum recommended concentrate velocity, applying backpressure to the previous stage increases the flow to the last element. From Table 7, increasing the backpressure to stage 1 increases the allowable recovery rate. DOW recommends that applying backpressure be avoided at all times.

40

Table 7: Stage 1 Backpressure vs. Recovery 4.5 MGD 84-42 Array Backpressure Max Recovery 10 0.83 9 0.82 8 0.82 7 0.81 6 0.81 5 0.8 4 0.8 3 0.79 2 0.79 1 0.78 0 0.78

41

CONCLUSION

Important parameters for the preliminary design of a 4.5 MGD plant can be determined by analysis and selection. The number of membrane elements was determined. A suitable membrane was selected for the particular feed water. The membrane elements were organized in arrays and the pressure vessels were sized according to the number of stages and target recovery rate. The effects of modifying the parameters were observed and tabulated. The necessary auxiliary equipments were identified and the characteristics required from those devices were stated.

RECOMMENDATION

Following the system analyzed in this report, the NF plant should start out as an 84:42 array using DOW FILMTEC NF90-400 membrane elements. The pressure vessels should be ASME compliant and hold six 8”x40” elements. The high pressure pumps should be vertical multistage can-type pumps and operate at peak efficiency with cavitations. Stage 2 of the array should be boosted by the recovered energy from a hydraulic turbocharger. TDS and flow meters should monitor the feed stream and the permeate and concentrate stream. The material of valves, and pipes should be high quality corrosion, resistant steel able to operate at or above the design pressures.

42

POST TREATMENT

INTRODUCTION

This report explores the post-treatment process for a nanofiltration plant.

The permeate water of a nanofiltration membrane process requires further treatment before entering the distribution. Although NF post-treatment is not as intensive as RO post-treatment, the permeate exhibits some of the same characteristics and problems associated with RO permeate.

ALKALINITY RECOVERY

NF membranes have lower rejection characteristics compared to RO membranes. However, a bicarbonate is rejected by the NF membrane. The rejection of bicarbonate lowers the alkalinity of permeate water. Low alkalinity water is very corrosive and aggressive. The alkalinity must also be adjusted before entering a degasifier for hydrogen sulfide stripping. The amount of alkalinity recovery is limited by the pH required to efficiently strip hydrogen sulfide.

HYDROGEN SULFIDE STRIPPING

The EPA established a secondary standard for sulfur in drinking water at 250 ppm or mg/L. The odor of hydrogen sulfide is detectable by humans down to a level of 0.5 ppm. At 1 ppm, sulfur gives water a “swampy” or “musty” odor. At 1-2 ppm, the waters possesses an objectionable “rotten egg” odor. While secondary standards are not enforceable, the odor is a source of complaints. Hydrogen also exerts a chlorine demand in water during disinfection.

GREENSAND PRETREATMENT

Greensand filtration also removes hydrogen sulfide as well as iron and manganese. Depending of the efficiency of the hydrogen sulfide removal by the greensand filter, hydrogen sulfide stripping may not be required.

AERATION

Aeration follows hydrogen sulfide stripping. The calcium carbonate equilibrium adjusts the pH before a disinfectant and corrosion control inhibitors are added.

CORROSION CONTROL

Low TDS, low pH water is aggressive water and corrodes metal piping in the distribution system. There are multiple indices for characterizing water’s corrosion potential. The Langelier Saturation Index (LSI) and Ryznar Stability Index (RSI) both predict the corrosion potential. Corrosion inhibitors added to reduce the corrosion potential of water.

DISINFECTION

43

Disinfection is required by for public distribution systems. The EPA requires of minimum disinfection residual of 0.2 mg/L. The maximum residual for chlorine is 4 mg/L. Ground water under the influence of surface water is required to achieve a log 3 removal/inactivation of Giardia cysts and a log 4 inactivation of viruses. Nitrates and organics exert a chlorine demand, as well as hydrogen sulfide. NF membranes reject large organic molecules and multivalent ions. The NF permeate is therefore low in organics and nitrate. Hydrogen sulfide passes through the chlorine demand. More sulfur passes through the membrane at the lower pH range. In feed water with an adjusted pH of 6, 90% of the sulfur is in the form of hydrogen sulfide.

44

THEORY

ALKALINITY RECOVERY

Bicarbonate can be recovered from dissolve carbon dioxide gases by increasing the pH. Calcium oxide is a caustic that can be added to increase the pH and recover bicarbonate which were rejected during the nanofiltration process.

HYDROGEN SULFIDE REMOVAL

Hydrogen sulfide is removed through degasification. A packed tower is sized for a correct HRT can efficient remove hydrogen sulfide. Hydrogen sulfite removal occurs more efficiently at a pH below 7 where most of the sulfur is the form of hydrogen sulfide.

AERATION

Aeration allows the water to equilibrate after degasification. Calcium carbonate equilibrium can be used to predict the pH equilibrate pH.

CORROSION CONTROL

The Langelier Saturation Index (LSI) and Ryznar Stability Index (RSI) can be calculated to determine the need of a corrosion control inhibitor.

DISINFECTION

45

Chlorine demand from hydrogen sulfide can calculated from a balance chemical equation assuming complete reaction.

46

RESULTS

ALKALINITY RECOVERY

Alkalinity recovery to final Alkalinity of 2 meq/L satisfies the pH required to efficiently remove hydrogen sulfide. It also adjusts the pH within an acceptable range for corrosion control.

Table 1: Calculations for Alkalinity Recovery Alkalinity Recovery

Desired Alkalinity

2 meq/L HCO3

- 122 mg/L HCO3- 0.002 M HCO3

-

Permeate

12.67 mg/L HCO3

-

0.207705 meq/L HCO3- 0.000208 M HCO3

-

202.59 mg/L CO2

0.004604 M CO2

pH= 4.98

HCO3

- required = 1.792295 meq/L HCO3-

Caustic

EW, CaO = 28.04 g/eq

CaO required = 50.25595 mg/L CaO

0.000897 M CaO

Adjusted pH

pH = pKa + log(HCO3-) - log(H2CO3)

pKa = 6.37

H2CO3 = 91.47 mg/L H2CO3 0.001475 M H2CO3

pH = 6.50

pH < 7 for H2S stripping

47

HYDROGEN SULFIDE REMOVAL

The kinetic rates for hydrogen sulfide and carbon dioxide removal by a packed tower were assumed. To achieve a ppm below 0.5, a HRT around 20 minutes is required.

Table 2: Calculations for hydrogen sulfide removal.

H2S stripping

Packed Tower

k, H2S = 0.1 min-1 k, H2CO3 = 0.4 min-1

HRT= 20 min

C = C0e-k(HRT)

C0

3 mg/L H2S

91.4677 mg/L H2CO3

Cfinal

0.406006 mg/L H2S

0.030684 mg/L H2CO3

AERATION

Following degasification, the water readjusts to a stable pH of 7.68.

Table 3: Calculations for aeration Aeration

Feed Water

Ca2+ permeate = 6.23 mg/L

Ca2+ caustic = 35.90 mg/L

Ca2+ total =

42.13 mg/L

0.001053 M Ca2+

HCO3

- = 122 mg/L HCO3-

0.002 M HCO3

-

pHs = pKa2 - pKCaCO3 - log(Ca2+) - log(HCO3

-)

48

pKa2 = 10.3

pKCaCO3 = 8.3

pHs = 7.68

CORROSION CONTROL

Following aeration, corrosion control inhibitors can be added to reduce the corrosion potential of the water before it enters the distribution system. The LSI is negative and requires a corrosion control inhibitor be added.

Table 4: Corrosion calculations Corrosion Control

TDS = 41.17

Ca2+ = 105.32 mg/L as CaCO3

T = 26.11 C Alk = 100.00 mg/L as CaCO3

LSI

LSI = pH - pHs

pHs = (9.3 + A + B) - (C + D)

A = (log(TDS) - 1) / 10

A = 0.061458

B = -13.12 * log(T + 273) + 34.55

B = 2.067077

C = log(Ca as CaCO3) - 0.4

C = 1.622502

D = log(Alk as CaCO3)

D = 2

pHs = 7.81

LSI = -0.13

RSI

RSI = 2(pHs) - pH

49

RSI = 7.94

DISINFECTION

Post aeration, the water is also disinfected to meet regulatory requirements. The remaining hydrogen sulfide exerts a chlorine demand which is included in the final dosage. The chlorine demand of sulfur is significant even after air striping.

Table 5: Chlorine dosage calculations Disinfection

Feed

pH = 7.68

H2S = 0.41 mg/L 1.19413E-05 M H2S

H2S + 4HOCl = SO4

-2 + 6H+ + 4Cl

Chlorine demand of S = 3.44 mg/L as Cl2

Residual =

2 mg/L as Cl2

Chlorine dose = 5.44 mg/L as Cl2

50

CONCLUSION

Following the calculations and results of the post-treatment process, recommendations can be made for treating the NF permeate.

Significant alkalinity recovery is required, 2 meq/L. If the pH is not adjusted before it enters the degasifier, the pH will be too corrosive after aeration.

To avoid odor problems and produce a more palatable drinking water, hydrogen sulfide should be stripped to levels below 0.5 ppm. Hydrogen sulfide also exerts a significant chlorine demand as it enters the disinfection process.

The LSI and Ryznar stability index indicate that a corrosion inhibitor is required. Corrosion generally occurs above a Ryznar index of 6.5-7. The Ryznar index of the treated water is 7.94, well above that range. The dosage requirements are generally propriety in nature, but an orthophosphate bended chemical addition is sufficient to inhibit corrosion. A corrosion inhibitor also reduces the chlorine demand of metals in the distribution system.

This groundwater source is subject to the stringent disinfection rules of surface waters. The recommended chlorine residual is 2 mg/L. Better corrosion control and hydrogen sulfide removal will help the lower the required chlorine dosage required.

51

COSTS

INTRODUCTION

The objective of this report is to estimate a cost figure for the construction of a 4.5 MGD nanofiltration plant. The cost estimation is based on the previous preliminary design reports for pretreatment, nanofiltration, and post-treatment.

METHODS & PROCEDURES

This section contains the formulas used to estimate the capital and operational costs.

CAPITAL COSTS FORMULAS

Building Cost

Cost = Unit Cost ($/m^2) *Ab(m^2) Ab = building area

Electrical wiring

Cost = $/m^3*Cp^0.65 Cp = permeate capacity, m^3/day

Instrumentation

Cost = $300k + $65k*Ns Ns = number of skids

Single Speed Turbine

Cost = 85,000*(HP/100)^0.65

Skid

Cost = PV*Nv+$10k Pv = price per vessel Nv = number vessel

52

Process Piping

Cost = 15.852*X/Y X = permeate capcity, m^3/day X = 1.70E+04 Y = recovery rate

Acid Dosing Equipment

Cost = AC*1000*(X/Y)*30*SC/(1000^2*ρ)+$30k*Ns AC = acid concentration, mL/L SC = storage cost Ns = number of skids X = product capacity, m^3/day Y = recovery rate, % ρ = density acid, g/mL

Antiscalent and Chlorine Dosing Equipment

Cost = C*1000*(X/Y)*20*SC/(1000^2*ρ)+$20k*Ns C = AS or CCC concentration, mL/L SC = Storage cost X = product capacity, m^3/day Y = recovery rate, % ρ = density, g/mL

Membrane Cleaning

Cost = P*Nv*Qv P = $67k/(14vessels)/(50gpm), $/vessel/gpm Nv = number pressure vessels cleaned at one time Qv = flow per pressure vessel, gpm

Degasifier

Cost = 1.5006*X + 3765.7

Odor Control

Cost = 320.9*X^0.6 X = product capacity, m^3/day

53

Generators

Cost = 150,000*(kW/1000)^0.85+50k kW = NF and Building usage kW = 14*(X/Y)/3785 X = permeate capacity, m^3/day Y = recovery rate, %

Clearwell

Below ground storage

Cost = -0.0002*X^2 + 99.004*X + 37941, for capacity < = 3785 m^3

49.084*X + 224887, for capcity > 3785 m^3

Ground storage

Cost = -0.054*X^2 + 104.88*X + 21400, for X <= 333 m^3

-0.0002*X^2 + 39.556*X + 58237, X > 333 m^3

O & M

Electricity usage

Cost = (kWnf+kWhpp+kWrwt+kWpwp)*PA*365*24*Z kWnf = NF and building usage kWhpp = 746*Ns*PS/1000 kWhpp = 111.9 PS = pump size, hp Ns = number of skids kWrwt = raw water pump kWpwp = permeate water pump

Labor costs

Cost = SD*LR*8*365 SD = staff days LR = labor rate

Chemical dosing

54

Cost = C*(X/Y)*365*PA*CC*ρ/100 C = concentration, mL/L X = product capacity, m^3/day Y = recovery rate PA = % availability CC = cost, $/kg ρ = Density, g/mL

Membrane replacement

Cost = Ne*Pe/Lm Ne = number elements Pe = price per element Lm = life of membrane, yr

Cleaning Chemicals

Cost = F*Nm*(D^2*pi*102/4)*1.15*(0.005*PHC+SDC*2)/1000 F = cleaning frequency, /yr Nm = number of modules D = membranes diameter PHC = citric acid cost, $/kg SDC = NaOH cost, $/kg

Cartridge filter replacement

Cost = 23097*CPS-6.24S*NS*12 CPS = capacity per skid, m^3/sec Ns = number of skids

Laboratory fee

Cost = $1,000*12*Ns Ns = number of skids

55

RESULTS & DISCUSSION

Using vendor pricing and design parameters of the nanofiltration system, cost formulas can be applied to project cost estimates. Table 1 show a breakdown of the costs related to each treatment process in the nanofiltration design.

The greatest cost associated with this design is the building cost. Building costs can be reduced by shrinking the square footage, however operation costs or construction for certain elements to the design might increase if operators are given the large enough area in which to carry out maintenance or repair.

Table 1: Cost breakdown Capital

Land $20,000 Buildings $1,950,000 Process Equipment Membranes and pumps $1,155,668 Chemical Feed $150,000 Chlorination $60,000 Aerator $29,321 Process Piping $299,955 Instrument and electrical $840,508 High Service Pumps $110,887 Other $3,021,471

O & M Wages $700,800

Power $261,328 Chemical Supplies $155,640 Maintenance $75,881 Other $1,515,173

PRETREATMENT

The pretreatment process, namely acid and anti-scalant dosing and the required equipment, should be orders of magnitude smaller in terms of cost in comparison to the central membrane process. The cartridge filters are also included in the pretreatment estimate. The greatest cost however is in the piping and storage for the acid and anti-scalent. The anti-scalent for this process is Vitec-3000 and the acid is sulfuric acid does and 170 ppm.

The operating cost of the pretreatment process will change according to the feed water quality. The cost of the greensand filter was estimate using a fact sheet from the U.S. Department of Interior.

56

MEMBRANE PROCESS

The membrane process involves the greatest capital costs. This is due to the price of membranes even though the cost of membranes is falling. The DOW Filmtec NF-400 membranes were priced for the membrane process.

The large capital costs related to the membrane process is the stainless steel piping and pumps for each the process trains. The cost of single speed vertical pumps was estimated for this process.

The operating cost for the pumps were calculated using the energy requirement from the ROSA analysis in the membrane process report.

POST-TREATMENT

The permeate that leaves the membrane process requires further treatment. Adjusting the pH, air stripping, and disinfection are applied to achieve a final product water. The permeate is dosed with caustic to recover alkalinity. The cost of post treatment is reduced by greater pretreatment upfront. The greensand filter excludes the cost of a degasifier with odor control. The greensand improves the disposability of the concentrate waste, but may incur greater operating and capital costs.

CONCENTRATE DISPOSAL

The cost of concentrate disposal was calculated according to the formula presented in the methods section. However, this cost can vary if the concentrate can be reused or even sold. Pretreatment processes like greensand can reduce disposal cost but have greater capital and operational costs. The cost of deepwell injection was not explored for this nanofiltration system.

Table 2 is a summary of the capital and amortized cost related to each item or treatment process. The cost are amortized at 20 years and 10% interest. The membranes are amortized at 5 years.

Table 2: Capital and amortized costs Item Capital O&M Total /kgal Annual /kgal Property $2,315,508 $0.17 Pretreatment $265,158 $0.02 $82,341 $0.01 Membrane Process $2,403,731 $0.17 $1,122,385 $0.08 Post Treatment $294,891 $0.02 $74,591 $0.01 Concentrate Disposal $500,000 $0.04 Total $7,617,810 $0.54 $2,708,822 $0.19

57

CONCLUSIONS AND RECOMMENDATIONS

The estimated capital cost of the 4.5 MDG water treatment plant is $7.6 million with an amortized cost of $0.54/kgal. The costs are amortized at 20 years and interest rate of 10%. The operating cost is $2.7 million with an amortized cost of $0.19/kgal. The greatest capital cost and operating cost may result from the membrane process. If the life of the membrane is extended beyond the 5 year period, the operating cost significantly less. Labor is second largest operating cost after membrane replacement.

58

REFERENCES

S. R. Qasim, E. M. Motley, and G. Zhu. Water Works Engineering: Planning, Design & Operation. Prentice Hall PTR, 2000.

U.S. Department of Interior. “Cost Assumptions for Contaminants Fact Sheet”. April 4, 2011. http://www.usbr.gov/pmts/water/media/pdfs/Assump.pdf

Lee County Florida Utilities. “Tabulation Sheet for Annual purchase of Antiscalent”. April 4, 2011. http://www3.leegov.com/Purchasing/Q-110014/Tabsheet__4_.pdf

H. P. Loh. Process Equipment Cost Estimation Final Report. U.S. Department of Energy. Pittsburgh, PA. 2002.

EV Studio. Cost per Square Foot of Commercial Construction by Region. April 2011. http://evstudio.info/cost-per-square-foot-of-commercial-construction-by-region/

http://www.usbr.gov/pmts/water/media/pdfs/Assump.pdf

http://www3.leegov.com/Purchasing/Q-110014/Tabsheet__4_.pdf

http://evstudio.info/cost-per-square-foot-of-commercial-construction-by-region/

ryan fu-sum nanofiltration membrane report

Documents

flow projection

membrane process