A Novel Trace Elemental Analysis of Potassium Phosphates

Home , Dipotassium phosphate, Sodium phosphates, Tripotassium phosphate

A thesis submitted to the

Graduate School

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Master of Science

in the Department of Chemistry

of the College of Arts and Sciences

Josh Rohman

B.S., University of Cincinnati

June 2008

Committee Chair: William Heineman, Ph.D.

Committee Chair: Julio Landero Figueroa, Ph.D.

Abstract

In the chemical manufacturing industry, it is critical to have an understanding of not only the major components in the product of interest but also the contaminants or trace components.

Potassium phosphates are common to the food and industrial markets, so trace metals are of particular concern in order to protect people as well as processes and equipment from their effects. This can be a particularly difficult task due to the samples having a high dissolved solids content which can cause issues with ICP analyses.

In this study, a method is developed to digest anhydrous tetrapotassium pyrophosphate and analyze for trace metals by inductively coupled plasma optical emission spectrometry (ICP-

OES). The analytes of interest were As, Cr, Fe, Mn, Ni, Pb, and Zn. Reproducibility was performed; however, spike recovery proved to be a better measure of success due to the majority of the analytes being near or below the method detection limit. The recoveries for all analytes ranged from 96.9-102.4%. Although the recovery was successful, the reproducibility of the analytes above the method detection limit had relative standard deviations mostly greater than

10%, which could be a sign that the solid sample was not homogenous since prior studies with liquid tetrapotassium pyrophosphate had relative standard deviations below 5%.

iii

Acknowledgements

I would like to recognize the late Dr. Joseph Caruso for his guidance as I have pursued my advanced degree and accepting me into his research group. His support, encouragement, and insight into the academic world provided me the keys to success in pursuing my degree. I would also like to thank my committee members Dr. William Heineman, Dr. Julio Landero Figueroa,

Dr. Hairong Guan, and Dr. Thomas Ridgway for their time and support in finishing this project.

I would also like to thank my family for supporting me throughout my college career.

Everyone supported me by providing me the time needed to finish this thesis by watching my sons. My industry mentor also deserves a tremendous amount of recognition; Dr. Yonghua Xu provided me an unlimited amount of support while on my Co-op assignment and eventual employment at Sun Chemical. His vast knowledge of analytical chemistry and method development were critical to my project and my current career success. I would like to thank

PotashCorp for allowing me to use their laboratory to perform my experiments.

Lastly, my wife deserves the most thanks. She provided me the support I needed to finish this project. She pushed me to get through the toughest parts of my college career and celebrated all of my successes with me as well. She always found a way to get me the time I needed to work on my thesis and was extremely understanding of the nights I had to stay late in the lab to finish an analysis.

Table of Contents

Abstract…………………………………………………………………………………………… ii

List of Tables……………………………………………………………………………………...vi

List of Figures………………………………………………………………………………….... vii

Introduction……………………………………………………………………………………….. 1

Phosphate Production……………………………………………………………………...1

Uses of Phosphates……………………………………………………………………….. 2

Trace Metals in Potassium Phosphates…………………………………………………… 2

Experimental……………………………………………………………………………………… 4

Instrumentation…………………………………………………………………………… 4

Reagents and Standards…………………………………………………………………... 5

Sample Preparation……………………………………………………………………….. 5

Results and Discussion…………………………………………………………………………… 7

Quality Control…………………………………………………………………………… 7

Digestion………………………………………………………………………………….. 7

Method Validation………………………………………………………………………... 9

Discussion………………………………………………………………………………...12

Conclusions and Future Work……………………………………………………………………17

References……………………………………………………………………………………….. 18

List of Tables

Table Page

1. ICP-OES parameters and conditions…………………………………………………………... 4

2. Digestion parameters…………………………………………………………………………... 6

3. Comparison of digestion acids…………………………………………………………………. 8

4. LOD and LOQ results………………………………………………………………………… 10

5. Wavelengths used during analysis……………………………………………………………. 11

6. Validation results for linear and full fit calibration…………………………………………... 13

List of Figures

Figure Page

1. Chemical reactions that produce TKPP……………………………………………………...... 1

2. As 449.423 nm calibration curve…………………………………………………………… 12

3. Linear versus full fit calibration curves for manganese………………………………………. 15

vii

Introduction

Phosphate Production

Potash in industry today typically refers to potassium salts from underground mining, primarily composed any or all of potassium chloride, potassium sulfate, and potassium nitrate

[1]. It has been used in many applications throughout time, but today it is used primarily in fertilizer and as a feedstock for other industrial chemicals, such as potassium hydroxide.

Potassium hydroxide, or caustic potash, is a strong alkali available in both solution and solid forms [2]. It has many uses in industry; almost all use it for its reactivity towards acids.

Phosphoric acid is produced through two main techniques: thermal and wet. Thermal phosphoric acid is produced from burning elemental phosphorus and the wet method uses phosphate rock, in the form of tricalcium phosphate, and react it with sulfuric acid to yield phosphoric acid. It can be further purified to a food-grade material which is the form used to make potassium phosphates.

Potassium phosphates are produced by reacting phosphoric acid and potassium hydroxide. The potassium phosphate produced depends on the mole ratio of potassium to phosphorus and produces monopotassium phosphate with a 1:1 ratio, dipotassium phosphate with a 2:1 ratio, or tripotassium phosphate with a 3:1 ratio. Potassium phosphates with a 2:1 molar ratio of K:P are the focus of this study, Figure 1 shows the reactions to create dipotassium phosphate (K2HPO4 or DKP) and tetrapotassium pyrophosphate (K4P2O7 or TKPP). Using

Figure 1. Chemical reactions that produce TKPP

H3PO4 + 2KOH  K2HPO4 + 2H2O

2K2HPO4 + Heat  K4P2O7 + H2O

1 dipotassium phosphate as a feedstock, tetrapotassium pyrophosphate is produced by spraying it into a rotating kiln heated above 400°C. The dehydration process provides a white granular solid that can be easily used in industry as a solid or dissolved and used as a liquid [3].

Uses of Phosphates

Phosphoric acid salts such as sodium phosphates and potassium phosphates have many uses. The largest consumer is the food industry who uses them for a multitude of applications from texture-modifying and surface tension modifying to pH control and adding the essential nutrient, phosphorus, to food. Other uses include in drugs as a bowel cleansing agent, in fertilizer to supply phosphorus and/or potassium to the crops, as a paint additive, and in water treatment

[4, 5, 6].

Potassium phosphates were widely used for many years, prior to their ban, in laundry detergents to help bind up hard water minerals, such as calcium and magnesium. This allowed detergent manufacturers to use less surfactant and keep the same cleaning power [6]. There use in foods is typically the same as sodium phosphates; however they are used less frequently due to the cost. A major reason to use potassium phosphates over their sodium counterparts in food products is due to the concerns over sodium content and its’ effects on the cardiovascular system

[7]. Using the same ideology as laundry detergents, potassium phosphates are used in industrial water treatment for inhibiting scale from calcium and magnesium as well as inhibiting corrosion of metal surfaces [8].

Trace Metals in Potassium Phosphates

In the following method development, the analytes of interest are As, Cr, Fe, Mn, Ni, Pb, and Zn. As and Pb were chosen because they are regulated compounds for food grade potassium phosphates based on the Food Chemicals Codex [9]. The remaining compounds are measured

2 due to a likelihood of being present in the manufacturing process. Rotary kilns for producing tetrapotassium pyrophosphate are lined with cast iron, stainless steel, or both and galvanized steel is heavily used in industrial manufacturing due to its corrosion resistance. Fe is monitored for the cast iron uses, Zn is monitored for the galvanized steel uses, and Cr, Mn, and Ni are monitored for stainless steel. Since the feedstock used is made from phosphoric acid and potassium hydroxide, any excess of either can create an even more corrosive environment than the already basic dipotassium phosphate used at a pH of 9.0-9.5. This possible corrosion at elevated temperatures could cause leaching of the components of the various steels [10, 11].

The goal of this method development is to create an efficient and cost effective method for production quality control laboratories to use to evaluate metals in dipotassium phosphate and tetrapotassium pyrophosphate while still maintaining high accuracy and precision. All of these aspects are analyzed to determine the practical method conditions for future uses. Beyond this study, an evaluation of the same extent could be applied to 1:1 and 3:1 molar ratios of K:P to extend this method to the entire potassium phosphate manufacturing community.

Experimental

Instrumentation

Elemental analysis was performed using a Thermo iCAP 6500 Radial ICP-OES (Thermo

Fisher Scientific, Cambridge, United Kingdom) equipped with a quartz EMT style torch, ceramic injector, quartz cyclonic spray chamber, quartz nebulizer, ThemoFlex900 recirculating chiller

(Thermo Fisher Scientific, Cambridge, United Kingdom), and a Cetac ASX-520 autosampler

(Teledyne Cetac Technologies, Omaha, NE, USA) with a carbon fiber sample probe. Internal standard was introduced using a Trident Internal Standard Kit (Glass Expansion, West

Melbourne Vic, Australia) that mixes the internal standard line (0.25 mm ID) with the sample line (0.64 mm ID) using the ICP’s peristaltic pump and 2-tag PVC pump tubing, including the

1.02 mm ID waste line. The instrumental operating conditions are summarized in Table 1.

Table 1. ICP-OES parameters and conditions

RF Power 1150 W

Auxiliary Gas Flow 0.5 L/min

Nebulizer Gas Flow 0.75 L/min

Coolant Gas Flow 12 L/min

Radial Viewing Height 12.0 mm

Peristaltic Pump Rate 50 rpm

# Repeats per wavelength 3

Sample Flush Time 60 s

Chiller Temperature 18.0 °C

Reagents and Standards

All reagents used were of ACS grade or better. All solutions were prepared in 18.0+

MΩ·cm deionized water generated by an Aqua Solutions RODI-C-12BL combination Reverse

Osmosis plus Type I Biological Grade DI System (Aqua Solutions, Inc., Jasper, GA, USA).

Potassium Phosphate Dibasic, Anhydrous, TraceSelect used for matrix matching was purchased from Sigma (Sigma-Aldrich Co, St-Louis, Mo, USA). Nitric acid and hydrochloric acid used for digestion were obtained from EMD (EMD Millipore Corporation, Billerica, MA, USA) and

Puritan (Puritan Products, Inc., Bethlehem, PA, USA), respectively. For the external calibration curve, working solutions were prepared by appropriate dilutions of 10,000 µg/mL stock solutions of As, Cr, Fe, Mn, Ni, Pb, and Zn as well as Sc for the internal standard from Ultra Scientific

(Ultra Scientific, Inc., N. Kingstown, RI, USA).

Sample Preparation

A sample of Tetrapotassium Pyrophosphate Technical Grade Granular, 95+% was obtained from PotashCorp (PCS Purified Phosphates, Harrison, OH, USA). A 500g portion of the sample was split 5 times into 2 portions, one portion of 250g was ground using a Retsch

GM200 knife mill (Verder Scientific, Inc., Newtown, PA, USA) at 4000rpm for 30 seconds to obtain a uniform sample for analysis. The digestions were performed using borosilicate glass beakers and ribbed watch glasses with PTFE magnetic stir bars and 4 in. square digital hot plate stirrers (Thermo Fisher Scientific, Cambridge, United Kingdom); only 1 sample was put on a hot plate at a time. The parameters of the digestions are listed in Table 2.

Table 2. Digestion parameters

Digestion 1 (Nitric Only) Digestion 2 (Aqua Regia)

Sample Size (g) 5 5

DI Water (mL) 2 2

HNO3 (mL) 7 0

Aqua Regia (mL) 0 8

Hot plate Setpoint (°C) 250 250

Digestion Time (min) 20 20

Results and Discussion

Quality Control

A 5 µg/mL solution of scandium was used as the internal standard to account for instrumental variability. The internal standard was mixed with the sample line using a “T” prior to the nebulizer and was fed into the line using the same peristaltic pump as the sample line. To ensure that the calibration curve remained constant throughout, a verification standard was analyzed after each calibration, every ten samples, and at the end of each sample run. Standards ranging from 0.01 µg/mL to 2.00 µg/mL were used for each element. The 0.01 µg/mL standard was used to meet the needs of the coatings industry to attain a 0.1 µg/mL limit of lead in the sample based on ten-fold dilution of the sample.

Digestion

Two digestion methods were initially evaluated to determine the best choice for the method based on Sastre et al. [12]: nitric acid and aqua regia by standard hot-plate digestion.

These two digestions were chosen based on their common uses in the literature [13, 14, 15] and the fact that hydrochloric acid and nitric acid are common acids found in a quality control laboratory. The samples were digested in borosilicate glass beakers using ribbed watch glasses to reduce the loss of sample and acids. The assist in the dissolution of the sample, 2 mL of DI water was added to each beaker and stirred at 350 rpm for 30 seconds to wet the sample then 7 mL of nitric acid was added to nitric digestion and 8 mL of 3:1 HCl:HNO3 was added to the aqua regia digestion.

Since initial trials did not show the typical reddish-brown fumes of aqua regia, samples were digested for a constant time of 20 minutes. The digestion was done on standard laboratory hot plates set at 250 °C and stirring at 350 rpm. 250 °C was chosen because it allowed the

7 sample to completely dissolve and brought the solution to a gentle boil to avoid splashing and potential loss of sample. Due to the amount of dissolved solids in the digest, crystals begin to fall out of solution as soon as it begins to cool. To prevent this, the hot plate was turned off; however, with the sample remaining on the hot plate to keep it warm, the solution is immediately brought up to around 30 mL with DI water which keeps the crystals from precipitating. Once the sample cools it is transferred to a 50 mL volumetric flask and brought to mark with more DI water.

The sample and spike were analyzed in triplicate and run against matrix-matched external standards (outlined later in this paper). Table 3 outlines the results of the different digestions.

Five of the seven elements spiked resulted in better recovery using the aqua regia digestion

Table 3. Comparison of digestion acids

Nitric Only Aqua Regia Element % Recovery R2 Std #1 % Var. % Recovery R2 Std #1 % Var.

As 105 0.9998 -71.8 96 0.9999 -47.4

Cr 97 0.9999 -51.9 99 0.9999 -25.3

Fe 106 0.9999 -53.1 89 1.0000 -22.3

Mn 97 0.9999 -54.6 100 0.9999 -37.5

Ni 91 0.9998 -78.3 103 1.0000 -39.4

Pb 87 0.9998 -70.8 95 1.0000 -35.2

Zn 100 0.9998 -69.2 101 0.9999 -37.0 versus the nitric acid only digestion. There wasn’t a significant difference in the correlation of the calibration curves; however, the instrument software compares the standard measurements against the curve and theoretical concentration and calculates a percent variation from the

8 theoretical value. The lowest standard used in the method for all elements was 0.01 µg/mL. The results in Table 3 show that the accuracy of the lowest standard is not completely ideal (0% being perfect conditions); however, the results in the aqua regia standards were twice as accurate as the nitric only standards.

The standards were made in a matrix of trace metals grade dipotassium phosphate in order to match the form of the samples post-digestion. This allows the method to work for dipotassium phosphate (K2HPO4) as well tetrapotassium pyrophosphate (K4P2O7) since they have the same molar ratio of potassium to phosphorus of 2:1. This will also help to ensure that the suppression of the plasma from the high dissolved solids in the sample and standard will be the same, increasing the accuracy of the results. Another reason for choosing dipotassium phosphate for the matrix is to better represent the decomposition of pyrophosphate to orthophosphate during digestion [16].

Method Validation

Limit of detection (LOD) and limit of quantitation (LOQ) were determined by analyzing a blank prepared in the same manner as the sample. This blank was analyzed ten times and the standard deviation (SD) was calculated from the replicates. LOD and LOQ were calculated as

3*SD and 10*SD, respectively [17, 18]. Table 4 shows the LOD and LOQ for each element at each wavelength. The method detection limit (MDL), based on the lowest standard modified by the sample dilution, is 0.1µg/mL for all elements. Based on the LOQ data, there is at least one wavelength for each method that is around the lowest standard concentration of 0.01 µg/mL, which as mentioned earlier was the target to meet the needs of the coatings industry.

Table 4. LOD and LOQ results

Element - LOD, µg/mL LOQ, µg/mL U, µg/mL Wavelength

As 189 0.0031 0.0104 0.0007

As 193 0.0035 0.0117 0.0007

Cr 267 0.0013 0.0042 0.0003

Cr 283 0.0009 0.0032 0.0002

Cr 284 0.21 0.72 0.05

Fe 238 0.0017 0.0057 0.0004

Fe 239 0.0025 0.0084 0.0005

Fe 259 0.0012 0.0041 0.0003

Mn 257 0.00020 0.00067 0.00004

Mn 259 0.00030 0.00099 0.00006

Mn 260 0.00031 0.00103 0.00007

Ni 221 0.0016 0.0053 0.0003

Ni 231 0.0021 0.0071 0.0005

Ni 341 0.0038 0.0128 0.0008

Pb 216 0.010 0.034 0.002

Pb 220 0.005 0.017 0.001

Pb 261 0.027 0.090 0.006

Zn 202 0.005 0.017 0.001

Zn 206 0.006 0.020 0.001

Zn 213 0.0026 0.0087 0.0006

The method was validated using triplicate determinations over four days by two different analysts. The sample was also spiked in triplicate prior to the digestion step with a mixture of the seven analytes of interest at 5 µg per element. To obtain the most accurate and precise results, the three most sensitive wavelengths were chosen for each element. Table 5 lists all the wavelengths

Table 5. Wavelengths used during analysis

Element Wavelength 1 (nm) Wavelength 2 (nm) Wavelength 3 (nm)

Arsenic 189.042 193.759 449.423

Chromium 267.716 283.563 284.325

Iron 238.204 239.562 259.940

Manganese 257.610 259.373 260.569

Nickel 221.647 231.604 341.476

Lead 216.999 220.353 261.418

Zinc 202.548 206.200 213.856

Scandium* 361.384 *Internal standard measurement only

that were used. After the first analysis, wavelength 449.423 nm for As was removed from future analyses due to the non-linearity of the calibration curve (as shown in Figure 2) with a correlation of only 0.73.

Figure 2. As 449.423nm calibration curve

Discussion

In Table 6, the average reproducibility results, based on 12 samples, with measurement of uncertainty (U=2*SD/sqrt(n) at 95% confidence) and spike recovery results are compared for each element on each line and between a linear regression calibration curve and using the

Thermo iTeva software’s full fit calibration curve that forces the line through every point on the line to create a correlation of 1.0000. Based on a comparison of all of this data, the best line and calibration curve can be chosen to optimize the method for future use. Only two lines were chosen for future use using the linear regression curve, one of which was As 193 having a recovery of 101.2%, %RSD (relative standard deviation) of 8.8% and a measurement of uncertainty that equates to only a ±3% range of results at a 95% confidence level. Having the

Table 6. Validation results for linear and full fit calibration

Linear Calibration Curve Full Fit Calibration Curve

Avg ± U % Avg ± U % Element %RSD %RSD (µg/mL) Recovery (µg/mL) Recovery

As 189 0.32 ± 0.02 11.7% 104.3% 0.38 ± 0.06 28.2% 90.8%

As 193 0.29 ± 0.01 8.8% 101.2% 0.26 ± 0.01 9.0% 89.8%

Cr 267 -0.30 ± 0.05 -29.6% 99.5% 0.01 ± 0.05 655.0% 40.7%

Cr 283 0.21 ± 0.02 18.9% 103.6% 0.23 ± 0.01 6.7% 102.2%

Cr 284 0.20 ± 0.02 17.3% 103.3% 0.22 ± 0.01 6.3% 95.9%

Fe 238 3.2 ± 0.2 13.4% 107.9% 3.1 ± 0.2 13.1% 107.8%

Fe 239 3.2 ± 0.2 12.7% 106.0% 3.2 ± 0.2 12.0% 96.9%

Fe 259 3.2 ± 0.2 12.8% 107.2% 3.1 ± 0.3 15.2% 114.1%

Mn 257 0.02 ± 0.02 231.1% 102.4% 0.034 ± 0.002 9.2% 102.2%

Mn 259 0.02 ± 0.02 212.9% 102.7% 0.037 ± 0.002 10.6% 100.7%

Mn 260 0.02 ± 0.02 232.0% 101.8% 0.032 ± 0.002 10.0% 101.6%

Ni 221 0.27 ± 0.05 29.0% 108.1% 0.30 ± 0.02 13.0% 113.3%

Ni 231 0.28 ± 0.05 30.1% 106.8% 0.30 ± 0.03 17.1% 100.6%

Ni 341 0.31 ± 0.04 23.4% 47.4% 0.33 ± 0.03 17.3% 113.4%

Pb 216 0.00 ± 0.05 7422.5% 100.4% -0.03 ± 0.04 -232.8% 106.8%

Pb 220 -0.01 ± 0.03 -765.7% 111.3% 0.02 ± 0.04 253.6% 144.0%

Pb 261 0.0 ± 0.1 -731.0% 94.4% 0.0 ± 0.1 -479.0% 106.5%

Zn 202 0.27 ± 0.04 27.5% 109.9% 0.36 ± 0.04 19.6% 110.7%

Zn 206 0.26 ± 0.04 29.4% 110.7% 0.35 ± 0.04 20.3% 108.2%

Zn 213 0.29 ± 0.04 25.3% 99.3% 0.34 ± 0.04 20.7% 102.4%

13 best recovery and %RSD out of the 4 options make it an easy choice for future analyses. The other elements were chosen from the full fit calibration curve results, excluding lead.

Using the same logic as with arsenic above, Fe 239 and Zn 213 were chosen due to their recovery and %RSD results of 96.9% and 12.0% for iron, respectively, and 102.4% and 20.7% for zinc, respectively. Ni 231 was chosen completely based on a recovery of 100.6%, significantly better than the next closest at 106.8%. Unfortunately it didn’t have the best %RSD at 17.1% versus 13.0%; however, it wasn’t as bad as the linear lines ranging from 23.4-30.1

%RSD. Lead and manganese require much more in depth analysis since the sample used for the study had concentrations of these two elements below the MDL.

Manganese levels were calculated at 0.02-0.04µg/mL, the highest LOQ was 0.001 µg/mL which when modified by the ten-fold dilution that the samples go through would result in a concentration of 0.01 µg/mL. Therefore, we can safely assume that the calibration curve can be extrapolated down to 0.01 µg/mL, allowing the ability to properly evaluate the results obtained.

The %RSD difference between the samples analyzed using the linear calibration curve and the full fit calibration curve is directly related to the level of manganese in the sample. The full fit calibration curve does a better job of capturing the variation at the lower concentration by curving to fit the intensities obtained rather than being impacted by the higher concentration standards. Figure 3 compares the two calibration curves for manganese at 257.610 nm.

Figure 3. Linear versus full fit calibration curves for manganese

STD1 was the lowest standard concentration used in the calibration curve at 0.01 µg/mL; it can be seen in Figure 3 that the % Diff (difference between the theoretical value and the calculated concentration against the curve) was significantly better for the full fit curve at -0.9% versus -

15.8%, which explains the %RSD variation of approximately 200% for the linear curves versus the approximately 10% RSD for the full fit curves. Another measure that supports the use of the full fit curve for manganese is the level of uncertainty being in the thousandths place versus the hundredths for the linear curve. This says that the results can be determined in the 0.030 µg/mL range to a range of ±0.002 µg/mL or ±6.7% of the result versus 100% using the linear results.

The %RSD and recoveries for all 3 full fit lines were relatively similar, so Mn 259 was chosen due to having the most accurate recovery at 100.7%.

Unfortunately lead does not have the same evaluation opportunity as manganese. The measured values of -0.03-0.02 µg/mL were all less than the MDL of 0.1 µg/mL and the lowest

LOQ for lead was 0.01 µg/mL at 220.353 nm which when modified by the sample dilution would be the same as the MDL. With this in mind, a process of elimination approach was used to determine the best conditions to use for future analyses. The measurement of uncertainty for Pb

261 was only to the tenths place versus the other two lines being in the hundredths place making it a less ideal line since the MDL is in the tenths place. The next line eliminated was Pb 220 since the recoveries for the linear and full fit curves were 111.3% and 144.0%, respectively.

These were significantly higher than Pb 216 with 100.4% and 106.8% for linear and full fit, respectively. Since the amount of lead in the sample was undetectable by this method, the %RSD was not useful for comparison, so recovery alone makes the linear curve for Pb 216 the best choice for future analyses.

Conclusions and Future Work

The primary goal of this method is to provide an accurate, precise, and quick analysis for trace metals in potassium phosphates with a 2:1 K:P ratio. The method is intended to be used in a phosphate production facility’s quality control laboratory. While there are many complexities when analyzing at the 0.1 µg/mL level in the sample, the final validation results were very successful from the accuracy and time point of view. Recoveries of the final chosen lines ranged from 96.9-102.4% for the 7 analytes of interest, well within the 85-115% limit established for

EPA 200.7, which is widely used for wastewater testing [19]. With the majority of %RSDs being

>10%, further studies should focus on improving this component. Since the sample used in the study was solid, there is a possibility of the sample not being homogenous enough causing the higher %RSD.

The next steps of this study would involve evaluation of the homogeneity of the solid samples. If further steps in sample preparation cannot decrease the %RSD then an increase in sample size may be needed. Previous studies have been performed using an aqueous sample of tetrapotassium pyrophosphate, commonly found as a 60% solution from the phosphate industry

[20]; however, the method was not evaluated to the same extent and was only used to evaluate

As, Pb, and Fe due to meeting the FCC requirements for food grade products [9]. Analyzing a

60% tetrapotassium pyrophosphate solution as well as a solid sample of dipotassium pyrophosphate will add to the data obtained in this study and could provide more information to help further increase the accuracy and/or precision of the current method.

References

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