A COMPARISON OF COMMON LABORATORY TECHNIQUES FOR THE

ANALYSIS OF THIOCARBAMATE PESTICIDES

A Thesis

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Tammy Schumacher Donohue

August, 2012

A COMPARISON OF COMMON LABORATORY TECHNIQUES FOR THE

ANALYSIS OF THIOCARBAMATE PESTICIDES

Tammy Schumacher Donohue

Thesis

Approved: Accepted:

______Advisor Dean of the College Dr. Claire Tessier Dr. Chand Midha

______Faculty Reader Dean of the Graduate School Dr. Kim C. Calvo Dr. George R. Newkome

______Department Chair Date Dr. Kim C. Calvo

ii ABSTRACT

The United States Environmental Protection Agency has devised a set of regulations limiting the use of thiocarbamate pesticides for the health and safety of humans and the environment. These regulations dictate the maximum amount of thiocarbamate compounds that may be released or present in soil, waste, and groundwater. Therefore, it is important to be able to determine their concentration accurately and reproducibly. A study was conducted to determine the best way to identify and quantify six thiocarbamate herbicides using equipment commonly found in industrial laboratories. Three analytical methods were tested: gas chromatography-mass spectrometry, high performance liquid chromatography, and infrared spectroscopy. They were chosen for their common usage, broad application, and operative ability. A comparison of these methods was made to determine the most effective technique for thiocarbamate identification and quantification.

iii DEDICATION

To my husband, Chris, whose steadfast belief in me never wavered. Thank you for always letting me know you were behind me, no matter what. I love you.

And to my Research Advisor, Dr. Claire Tessier, who took me on without any reason to, stayed late every week, and taught me that research could be fun.

A very warm and heartfelt thanks to you both.

iv ACKNOWLEDGEMENTS

There were many people whose support was inestimable to the completion of this thesis. First and foremost I’d like to thank my family for their constant support and encouragement.

I would also like to thank Omnova Solutions, Inc. for the generous use of their instrumentation, and for the opportunity to work and learn in such an exceptional environment.

Lastly, I would like to thank Dr. Michael Dunphy of Walsh University.

v TABLE OF CONTENTS Page

LIST OF TABLES …………………………………………………………….. vii

LIST OF FIGURE …………………………...………………………………… viii

CHAPTER

I. INTRODUCTION TO THIOCARBAMATES …………………………….. 1

II. EXPERIMENTAL ……………………………………………………….... 19

2.1. Materials …………………………………………………………. 19

2.2. Solutions …………………………………………………………. 20

2.3. GCMS Liquid Injection ………………………………………….. 22

2.4. GCMS SPME ……………………………………………………. 24

2.5. HPLC …………………………………………………………….. 28

2.6. IR …………………………………………………………………. 30

III. RESULTS AND DISCUSSION ………………………………………….. 32

3.1. GCMS Liquid Injection .………………………………...………. 32

3.2. GCMS – SPME ………………………………………………….. 40

3.3. HPLC ……………………………………………………………. 52

3.4. IR ……………………………………………………………….. 61

IV. CONCLUSIONS ………………………………………………………….. 65

REFERENCES ……………………………………………………………… 67

vi APPENDIX ...... 70

vii LIST OF TABLES

Table Page

1.1 The six thiocarbamate pesticides of interest with their common and scientific names as well as their molecular structures …………….. 4

1.2 Supelco® fiber recommendations based on analyte characteristics ….... 13

2.1 Material Descriptions ………………………………………………….. 20

2.2 Concentrations of the multiple solutions used for this experiment ……. 22

2.3 Temperature program for GC-MS pesticide separation by liquid injection ………………………………………………………… 23

2.4 Temperature program used for SPME optimization testing ………….... 24

2.5 Comparison of fibers examined ……………………………………...… 26

2.6 Solvent gradient for HPLC separation of thiocarbamate pesticides ….... 29

2.7 Isocratic HPLC parameters tested …………………………………….... 29

3.1 Calibration Curve Fittings …………………………………………….... 37

3.2 Limits of Detection for GC-MS by liquid injection ………………….... 38

3.3 GC-MS Limits of Detection and Quantification by liquid injection in parts per million ………………………………………………….….. 40

3.4 Linear correlation coefficient values for SPME pesticide calibration curves ……………………………………………………… 51

3.5 Method detection capabilities for SPME-GC/MS ……..……………… 52

3.6 Average Correlation Coefficient Values for Thiocarbamate Pesticide HPLC Calibration Curves created using Solvent Gradient 1 ... 57

3.7 HPLC background response as determined by Blank Averaging ...... 58 viii 3.8 Limits of Detection and Quantification for the six thiocarbamate pesticides by HPLC ...... 58

ix LIST OF FIGURES

Figure Page

1.1 Molecular structure of carbamate pesticides …………………….…….. 2

1.2 A comparison of the molecular structures of the three types of thiocarbamates ………………………………………………………. 2

1.3 Functionality of thiocarbamate pesticides as dependent on molecular structure …………………………………………………….. 3

1.4 Diagram of a SPME fiber ……………………………………………… 11

3.1 Separation of the Test Solution using GC-MS Temperature Program 1 (Table 2.3) ……………………………………………………………… 33

3.2 Separation of the Test Solution using GC-MS Temperature Program 2 (Table 2.4) ……………………………………………………………… 33

3.3 Calibration curve for methanol dilutions of the Standard Stock Solution for EPTC ……………………………………………………………….. 34

3.4 Calibration curve for methanol dilutions of the Standard Stock Solution for butylate ……………………………………………………………... 35

3.5 Calibration curve for methanol dilutions of the Standard Stock Solution for vernolate ……………………………………………………………. 35

3.6 Calibration curve for methanol dilutions of the Standard Stock Solution for pebulate …………………………………………………………….. 36

3.7 Calibration curve for methanol dilutions of the Standard Stock Solution for molinate ……………………………………………………………. 36

3.8 Calibration curve for methanol dilutions of the Standard Stock Solution for cycloate …………………………………………………………….. 37

x 3.9 Initial SPME GC-MS response using 7 µm PMDS fiber to extract from methanol solvent based pesticide solutions ………………………….... 41

3.10 The effect of multiple extractions from the same vial on analyte peak response …………………………………………………………. 42

3.11 Averaged results of a 2.5% methanol solution containing 1-3 ppm of each pesticide ………………………………………………………. 43

3.12 Effect of sample volume on SPME headspace extraction …………….. 45

3.13 Effects of the addition of sodium chloride to pesticide extraction vials .. 46

3.14 The effect of SPME extraction time on GC-MS peak area response ….. 47

3.15 Effect of agitation speed on pesticide extraction ………………………. 48

3.16 Effect of agitation chamber (extraction) temperature on pesticide extraction …...... 49

3.17 Effect of desorption temperature on peak area response of pesticide chromatograms ……………………………………………………….... 50

3.18 Final SPME calibration curve under optimal extraction conditions …… 51

3.19 HPLC chromatogram of 320 ppm molinate with additional peaks eluted using Solvent Gradient 1 …………………………………………..…… 53

3.20 HPLC calibration curve for molinate using Solvent Gradient 1 ………. 54

3.21 HPLC calibration curve for cycloate using Solvent Gradient 1 ………. 54

3.22 HPLC calibration curve for vernolate using Solvent Gradient 1 ……… 55

3.23 HPLC calibration curve for butylate using Solvent Gradient 1 ………... 55

3.24 HPLC calibration curve for pebulate using Solvent Gradient 1 ……….. 56

3.25 HPLC calibration curve for EPTC using Solvent Gradient 1 …....…..... 56

3.26 HPLC chromatogram of all six thiocarbamate pesticides ...... 59

3.27 HPLC chromatogrom of all six thiocarbamate pesticides ...... 60

3.28 HPLC chromatograom of all six thiocarbamate pesticides ...... 60

xi 3.29 FTIR Spectra of all six Standard Stock Solutions as applied five times to KRS-5 crystals (solvent free, solid state) ...... 62

3.30 FTIR spectra of the Standard Stock Solutions of EPTC as applied ten times to a KBr crystal (solvent free, solid state) ...... 63

3.31 FTIR Spectra of the Standard Stock solution of EPTC sandwiched between two KBr crystals, ratioed to two clean, blank KBr crystals ...... 64

xii CHAPTER I

INTRODUCTION TO THIOCARBAMATES

Thiocarbamates represent a major commercial class of chemical pesticides whose use spans several continents and generates hundreds of millions of dollars in revenue each year.12 Developed during World War II, they have been in mainstream production and use since the 1960’s.13 Thiocarbamates aid in the production of many important crops, including maize and corn, sugarbeets, rice, and soybeans.1 Their success is largely due to their versatile biological significance, and they have been attributed to having hypnotic, analgesic, anesthetic, fungicidal, bactericidal, terbuculostatic, and antiviral properties.4, 5 Thiocarbamates generally serve as graminicides, which are herbicides used to control weedy grasses, and are applied to soil before the emergence of crops.1 Their application is highest in North America and Europe.

The term “pesticide” is used in broad application that includes insecticides, herbicides, and fungicides. Each group includes many chemical families with different actions and a diversity of uses.6 Even though herbicides represent over half

1 of all pesticides, thiocarbamates will be indiscriminately referred to as pesticides for the remainder of the text.7

Thiocarbamates are a subgroup of the carbamate pesticide family. Carbamates are also known as urethanes4, and their molecular structure can be seen in Figure 1.1.

Carbamates are usually derived from amines or from the hydrolysis of chloroformamides.

There are three types of thiocarbamates: O-alkyl, S-alkyl, and dithiocarbamates.5 Figure

1.2 shows a comparison of the three structures.

O R2 C N R1 O R 3

Figure 1.1. Molecular structure of carbamate pesticides.

R1 O R2 R1 S R2 R1 S R2 C N C N C N S R O R S R 3 3 3

a) O-alkyl thiocarbamates b) S-alkyl thiocarbamates c) Dithiocarbamates

Figure 1.2. A comparison of the molecular structures of the three types of thiocarbamates.

According to the World Health Organization (WHO), the three main applications of thiocarbamate pesticides are as insecticides, herbicides, and fungicides. Their molecular structure is determinate of their function, as can be seen in Figure 1.3.

2 O R O 2 O R2 C N C NH2 C N R R1 S R R a) 1 S b) 3 c) 1 S H

Figure 1.3. Functionality of thiocarbamate pesticides as dependent on molecular structure. a) insecticides, b) herbicides, and c) fungicides.

Six particular thiocarbamate pesticides were of particular interest in this study.

Commonly known as EPTC, molinate, cycloate, butylate, vernolate, and pebulate, they were all S-alkyl thiocarbamates. As defined by Figure 1.3, all S-alkyl thiocarbamates are herbicides. All of them are -N,N-dialkyl substituted. They all have an alkyl group attached to the sulfur atom and either two alkyl groups or one alkyl group and one cyclic or hexamethylene group attached to the nitrogen.3 Table 1.1 shows the full molecular structure for the six pesticides of interest, as well as their common and scientific names.

3 Table 1.1. The six thiocarbamate pesticides of interest with their common and scientific names as well as their molecular structures.

Pesticide Scientific Name Structure O CH2CH2CH3 S-ethyl N,N-dipropyl EPTC C N CH CH S thiocarbamate 3 2 CH2CH2CH3

S-ethyl N,N- O CH2CH2CH2

Molinate hexamethylene C N CH CH S thiocarbamate 3 2 CH2CH2CH2

O CH2CH3 S-ethyl N-ethyl-N- C N CH3CH2 S Cycloate cyclohexy

thiocarbamate

CH3

O CH2CHCH3

S-ethyl N,N-diisobutyl Butylate C N thiocarbamate CH CH 3 2 S CH2CHCH3

CH3

O CH2CH2CH3 S-Propyl-N,N-dipropyl C N Vernolate CH CH CH thiocarbamate 3 2 2 S CH2CH2CH3

O CH CH S-propyl-N-ethyl-N-butyl 2 3 Pebulate C N thiocarbamate CH CH CH S 3 2 2 CH2CH2CH2CH3

4 There exists no one, universal method for the synthesis of thiocarbamate pesticides. Several methods are available, but the choice depends mainly on the cost and availability of reagents, ease of reaction, and the desired products.4 Different synthesis methods are applied for primary, secondary, and tertiary thiocarbamates; the degree of substitution is always based on the amine.5 For tertiary thiocarbamates, as the six listed in Table 1.1 all are, Walter et al recommend the thioacylation of alcohols, phenols, and thiols. Other possible reactions include the condensation of carbonyl sulfide (COS) with a secondary amine, the hydration of organic thocyanates in the presence of hydrogen chloride, or the condensation of a thiol with an isocyanate.4 Salvantone/Sahab strongly recommended using the mild and chemoselsective process of reacting cesium carbonate and tetrabutyl ammonium iodide for the thiocarbamation of amines. They state that this reaction has a high yield and short reaction times, while avoiding common side elimination reactions and by-products like isothiocyanates.8

Pesticides have undoubtedly increased agricultural production, but often this advantage comes with undesired consequences. Usually toxic, their presence can have harmful health effects on people ingesting the crops that pesticides were applied to.

Molinate is known to cause sperm morphology, while thiocarbamates containing dichloroallyl groups (diallate and triallate) are mutagenic.3 They also have a negative impact on ecosystems when environmental forces such as wind and rain carry pesticides beyond the boundaries of their intended application. Pesticides are applied to over half of all cropland. The distance they can travel inadvertently can be great, as is the potential for environmental contamination.7,9 For this reason, it is important to have a method to detect the presence of pesticides in many different matrices like soil, water, and the crops

5 themselves. For safety and compliance, it is necessary to go beyond detection and to have the ability to determine the concentration of pesticides present. Toxicity may occur at very low levels, which is why legal regulations control the application of pesticides through Maximum Residue Levels (MRLs).6 Put together in part by the World Health

Oganiztion (WHO), the main objective of the International Programme on Chemical

Safety (IPCS) is to evaluate the effects of chemicals on humans and the environment. In order to do this, they develop risk-assessment methods and laboratory procedures that can be used in many different countries.10 According to the IPCS, there are many methods available for the detection of pesticides; their use is situational and dependent on the type of pesticide to be evaluated and the instrumentation available. Regardless of the schematics of a particular method, all methods follow the same principles: sample a representative portion of the environmental matrix, extract the pesticides and remove interferences, and then identify and quantify the remaining analytes.10

Detection methods generally fall under two categories: multiresidue methods

(MRMs) and single residue methods (SRMs). MRMs are usually preferred as they have the capability to identify several pesticides in one analysis.6 Demand for MRMs has put pressure on their development in order to reduce cost and improve laboratory productivity.7 For their implementation to be practical, MRMs need to be able to distinguish many structurally diverse pesticides and to be able to differentiate between parent compounds and degradation products . The MRL in drinking water for many pesticides is 0.1 ug/L. For a method to become accepted, it needs to have Limits of

Detection (LODs) and Limits of Quantification (LOQs) between 10 and 50% of the

MRL.7

6 Pesticide detection methods based around MRMs are generally time consuming and labor intensive. They usually involve a solvent extraction step with a water-miscible solvent, followed by a clean-up step with an organic solvent to remove impurities, and finally some kind of chromatographic separation with selective detectors. Gas chromatography (GC) and high-performance liquid chromatography (HPLC) are the two most common chromatographic techniques for pesticide determination.6,7

These classical analytical methods use high volumes of expensive and toxic solvents, whose disposal is also costly and environmentally unfriendly. The amount of solvent used is approximately 108-1010 times greater per analysis than the concentration of pesticides to be determined. Another drawback is that they cannot be performed in a time efficient manner, and therefore they are useless as screening methods. Relevant information would not be gained in time to prevent agricultural products from being presented to consumers. It is also difficult to incorporate new pesticides into existing methods.6,11

These disadvantages created a need for simplification and miniaturization of analytical detection methods.6 Eliminating or reducing the solvent extraction step(s) would greatly improve the safety and cost of an analysis. Development of alternatives took form in the shape of solid-phase extraction (SPE) and solid-phase cleanup (SPC) cartridges, matrix solid-phase dispersion (MSPD) and supercritical fluid extraction

(SFE). SFE has proven useful for the extraction of pesticides from matrices like soil, while SPE has become accepted for extraction of all the major pesticides from water.

Thin layer chromatography, or TLC, was previously in common application, but has

7 being outdistanced by the newer chromatographic techniques. It can still be applied as a screening method.7,2

Gas and liquid chromatography have taken the forefront as separation methods for pesticides, but the column details and detectors used still vary greatly. Typically, GCs have been equipped with capillary columns of low polarity with immobilized or cross- linked stationary phases. Liquid chromatographs have found success with reverse-phase

C18 columns with both isocratic or gradient solvent programs.6,7 The detectors have been largely dependent on what types of pesticides were being determined. Universal ultra-violet detectors often did not have the necessary selectivity. Nitrogen-phosphorus detectors (NPD) and electron capture detectors (ECD) have had the most success when paired with a GC, but Tekel et al calls a mass spectrometer (MS) “indispensable for identity confirmation.” He also recommends GC over LC because of its broader spectrum of application and large, searchable libraries. The IPCS recognized the use of gas-liquid chromatography or the use of a GC with colormetric detection of sulfur as successful methods for thiocarbamate residue analyses, but these methods suffer from the same drawbacks as the methods listed above.7,10

Analyte manipulation by derivitiztion has been used to improve the chromatographic behavior of analytes if they are nonvolatile or highly polar, or to improve detection by making a compound more selective with the introduction of halogenated species.7 However, this process requires additional time and increases the likelihood of error with the extra sample handling step.

Because of their common application in pesticide analyses, an experiment was undertaken to determine if gas chromatography or high performance liquid

8 chromatography was the best method for the detection and quantification of the six thiocarbamate pesticides of interest. The general principles of chromatography were summarized concisely by Skoog et al. In his book, Skoog explains that in all chromatography, a sample is conveyed through a column by a mobile phase, which could consist of a gas, liquid, or supercritical fluid. The column contains an immobile stationary phase or different polarity than the mobile phase. The different affinity of the analytes for the two phases is what is responsible for chromatographic separations.

Analytes more attracted to the stationary phase will take longer to pass through the column than those with higher proclivity for the mobile phase.12

Chromatography is said to be an excellent technique for the detection of the absence of an analyte. The elaboration of this statement means that under controlled, equivalent conditions, if the analysis of a sample does not yield a peak at the same retention time as the elution of its standard, it is confirmed that the compound is not present in the sample; at the very least, that it is present below the detection limit for that method.12 As a method in itself, the usefulness of chromatography is limited; however, it is an unequivocal precursor to other spectroscopic techniques without with the analysis of complex mixtures would be impossible. Both GC and HPLC are column chromatographic techniques, where the stationary phase is adhered to a narrow column and the mobile phase is forced through under pressure. For all chromatographic techniques, the parameters that need to be carefully controlled are column temperature, mobile phase flow rate, and injection speed.12 Fortunately the disparity caused by variation in these parameters can be virtually eliminated through the use of software and

9 automation. A brief introduction into the two techniques occurs in the following paragraphs.

There are two forms of gas chromatography: gas-liquid and gas-solid chromatography. Gas-solid chromatography incurs a semi-permanent binding of highly retained analytes to a solid stationary phase. Because of this, its application in the scientific community is limited and will not be discussed further.12 Instead, the focus will be on gas-liquid chromatography, which is commonly shortened to just gas chromatography. In this type of chromatography, an inert gas such as helium, hydrogen, or nitrogen, carries the analytes though a column coated with a liquid stationary phase that is immobilized on an inert solid. The most common type of column is the capillary column, with a small internal diameter of less than 0.5 µm and a length of approximately

30 meters. The column is typically made of glass, with some kind of silica coating depending on the desired polarity of the stationary phase. Unlike in other kinds of chromatography, there is no interaction between the mobile phase and the analytes. The carrier gas only serves to move the compounds through the column. Separation occurs from interaction with the stationary phase. If multiple analytes have similar interactions with the stationary phase, they are they separated by particle size.

The sample is introduced into a very hot vaporization chamber at the head of the capillary column. The temperature of this chamber is traditionally 50 °C above the boiling point of the analyte with the lowest volatility.12 This is to ensure that all components are swept into the column and do not remain in the vaporization chamber.

There are several ways for this introduction to occur. The following experiment focused

10 on two in particular; solid-phase microextraction, which condenses the extraction and injection steps into one, and the more traditional syringe injection.

Solid-phase microextraction, or SPME, seemes like the answer to every analytical chemist’s prayers. It is a relatively new technique that allows for the direct extraction of analytes from almost every matrix imaginable, and it virtually eliminates the need for solvent. The technique has two steps: an adsorption step, where analytes partition from a sample matrix to the stationary phase coating an optical fiber, and the desorption of these analytes into some kind of instrumentation for evaluation; in this case a GCMS. There is very minimal sample preparation, no clean up, and no solvent required.

The operating principles behind SPME were based on those of solid-phase extraction (SPE), except on a much smaller scale. What started out as an optical fiber has evolved in a fused silica rod, one to two centimeters in length, coated with a thin film of different materials acting as stationary phase. This small geometry gives SPME the advantage of rapid mass transfer during extraction and desorption.13 Figure 1.4 is a diagram of a SPME fiber.

Figure 1.4. Diagram of a SPME fiber. 11

The first fiber coating was made of polydimethylsiloxane (PDMS). Rugged and nonpolar, this fiber was very good for extracting nonpolar analytes. As the technique became more wide-spread, new and hybrid coatings were developed using PDMS like a glue to incorporate other materials. Supelco® produces a wide range of fibers and provides recommendations for their use depending up the characteristics of the analytes to be extracted. These characteristics typically include polarity, molecular weight, and volatility, as shown in Table 1.2

12 Table 1.2. Supelco® fiber recommendations based on analyte characteristics. Abbreviations include PDMS for polydimethylsiloxane, DVB for divinylbenzene, and PA for polyacrylate.14

Analyte Recommended Coating Gasses and low molecular 75 µm/85 µm weight compounds (MW 30- Carboxen/PDMS 225) Volatiles (MW 60-2775) 100 µm PDMS Volatiles, amines, and nitro- aromatic compounds (MW 50- 65 µm PDMS/DVB 300) Polar semi-volatiles (MW 80- 85 µm PA 300) Non-polar high molecular weight compounds (MW 125- 7µm PDMS 600) Non-polar semi-volatiles (MW 30 µm PDMS 80-500) Alcohols and polar compounds 60 µm Carbowax (MW 40-275) Flaor compounds: volatiles and 50/30 µm DVB/Carboxen in semi-volatiles, C3-C20 (MW PDMS 40-275) 50/30 µm DVB/Carboxen in Trace compounds (MW 40-275) PDMS on 2 cm fiber Amines and polar compounds 60 µm PDMS/DVB

(HPLC only)

Polyacrylate fibers have improved the extraction of polar compounds, but have a higher distribution constant and take longer to reach equilibrium. Equilibrium is reached when the fiber’s stationary phase becomes saturated and no more analyte can be extracted. Equilibrium depends on several factors, including the partition coefficients of the analytes, stationary phase type and film thickness. The thinnest film available that yields acceptable detection results should be chosen in order to maximize efficiency, as thicker stationary phases take longer to reach equilibrium.13,15,16,17 13 There are three types of SPME extractions: direct injection, headspace, and membrane protected. Their names are accurate portrayals of how they work. Direct injection is when the SPME fiber is inserted directly into a sample matrix. It is highly effective but requires agitation to overcome the fluid shielding that occurs near the fiber, which significantly lowers the diffusion coefficient. For headspace SPME, the fiber is exposed to the volume of air above a sample, where it extracts analytes being released from the sample matrix. This technique is most useful for volatile samples, and it protects the fiber from damage by contact with large molecules. Membrane protected

SPME was also designed with preservation of the fiber in mind and is used for highly polluted samples.13

One of the largest appeals of the SPME technique is its application in the field.

The small, lightweight fibers are easily transported and sampling can be done in as little as a few minutes. Perhaps the most significant aspect is the excellent retention of the extracted analytes on the fiber. This allows adequate time for transport of samples from the field to the laboratory and eliminates the requirement of field instrumentation, significantly reducing cost and increasing ease of operation. Analytes can remain on the fiber for several days without significant losses.13

14 When it comes to GC detectors, there are several qualities necessary:

1. Adequate sensitivity.

2. Good stability and reproducibility.

3. Linear response to solutes over several orders of magnitude.

4. Temperature range capacity from room temperature to greater than 400 °C.

5. Short response times independent of mobile phase flow rate.

6. High reliability and ease of use.

7. Similarity in response toward all solutes, or predictable response for a class of

analytes.

8. Nondestructive of the sample.

No detector has been invented that is in possession of all eight qualities.12 Selection of a detector must depend on the sensitivity and selectivity required, and then on cost and ease of operation. For the current thiocarbamate analysis, gas chromatography was paired with mass spectrometry.

High performance liquid chromatography is the most widely used of all the analytical separation techniques. Sales for instrumentation stretch into the billion dollar mark every year.12 Reasons for its high demand include sensitivity, adaptability, usefulness in analyzing nonvolatile and thermally fragile compounds, and its applicability in many extensive fields of research including carbohydrates and proteins, amino and nucleic acids, hydrocarbons, antibiotics, steroids and other drugs, pesticides, and several metal-organic and inorganic substances.12 Many of these substances would be difficult or impossible to analyze by GC.

15 The operating principles of high performance liquid chromatography are similar to those of gas chromatography. The separation of the analytes is dependent upon their affinity for the stationary or mobile phases, as determined by their partition coefficients.

In this case, however, instead of the mobile phase being an inert carrier gas like in GC, it is always a solvent or combination of solvents. The stationary phase is secured in a matrix of inert material that is chemically and mechanically stable, and is usually made of silica, polystyrene, cellulose, dextran, polyacrylamide, or argose. The form taken by the stationary phase could be microporous, pellicular, or bonded.18

There are two types of HPLC: normal-phase and reverse phase. Normal-phase was the first developed, which had a polar stationary phase and non-polar mobile phase.

Reverse phase chromatography uses nonpolar stationary and semi-polar mobile phase.

RP-HPLC operates on the principles of hydrophobic interactions, and is much more commonly applied. In this phase, nonpolar analytes are retained longer on the stationary phase, while solutes with similar polarities to the mobile phase elute more quickly.

An HPLC consists of four components: a column with stationary phase, the desired mobile phase, pumps for driving the mobile phase through the column, and a detector.18 The type of detector is dependent on the types of analytes one is trying to derive. For instance, the ultra violet or UV detector is the most common type of detector for HPLC, but it would be useless if the species to be detected did not absorb in the ultra violet region.19 Another drawback is that it can only be set to one wavelength, and for a multiresidue analysis with many pesticides, it is likely there would be a wide range of wavelengths of optimal adsorption. If this was the case, a photodiode array detector would be more suitable as it has the capability to scan and record a range of wavelengths.

16 Another option would be a refractive index detector, in which half of a glass cell is purged with pure mobile phase, and through the other half would flow the eluate. The two halves of the cell are separated by a glass plate, and differences in the incident beam are interpreted by the detector.12

Most government laboratories use HPLC for pesticide detection.19 They avoid the drawbacks of GC and can be used to analyze pesticides with a variety of polarities and volatilities.20 However, the US EPA recommends the use of a second column for the avoidance of false positive identifications, which is common in chromatographic techniques. Use of an MS detector also avoids false positives and eliminates the need for a second column, but this option is expensive and less commonly integrated with LC than with GC.19,19

Corcia and Marchetti developed a method for the identification of 89 pesticides using HPLC. These pesticides were selected on the basis of UV absorption, persistence and mobility in an aquatic environment, and extent of agricultural use. For their mobile phase, they implemented a solvent gradient which consisted of 80% water and 20% acetonitrile (CH3CN) that went linearly to 85% CH3CN after 45 minutes. Their flow rate was 1.5 mL/min. They employed the two column approach, using a reverse phase C18 column with a second cyano column for the avoidance of false positives. Their detector was UV set at 220 nm. Under these conditions, they were able to separate and identify four thiocarbamate pesticides that included molinate, butylate, cycloate, and eptam with limits of detection of 9.5, 14, 8, and 9.3 parts per billion, respectively.20

The current study was designed to evaluate several analytical methods for the determination of thiocarbamate herbicides using common laboratory instrumentation.

17 The methods were assessed on cost and accessibility of instrumentation, the degree of complication, and on the achievable Limits of Detection and Quantification. As the two most common pesticide evaluation techniques, HPLC and GC with were selected to be compared. The detectors were refractive index (RI) in series with a photo diode array

(PDA) and MS, respectively. Two methods of introducing a sample into the GC were investigated. Headspace (HS) SPME was selected, and would be compared to the liquid injection of a methanol solution of the six pesticides, which was to represent the final product of a more involved traditional extraction method. These solutions were injected into the GC-MS using a 10 µL syringe. Lastly, incorporation of a technique less common for pesticide evaluation, but one largely present in industrial laboratories, took place in the form of FTIR. The aim of including this technique was to learn what structural information could be elucidated from a non-chromatographic procedure that might aid in the differentiation of one thiocarbamate pesticide from another.

18 CHAPTER II

EXPERIMENTAL

2.1. Materials

All six pesticide standards were purchased from Sigma Aldrich® and ranged from

97.9% purity for pebulate to 99.8% for EPTC. All solvents used were HPLC reagent grade, purchased from J.T. Baker®, except for acetonitrile, which was also HPLC reagent grade but purchased from Acros Organics (Fischer Scientific). Sodium chloride was purchased from VWR International®. All vials were purchased from Gerstel unless otherwise noted. Table 2.1 contains a list of products, including their suppliers and amounts.

19 Table 2.1. Material Descriptions.

Material Purity (%) Amount Supplier EPTC PESTANAL® 99.8 (HPLC) 250 mg Sigma Aldrich Butylate 99.3 (HPLC) 250 mg Sigma Aldrich PESTANAL® Vernolate 99.6 (GC) 250 mg Sigma Aldrich PESTANAL® Pebulate 97.9 (GC) 100 mg Sigma Aldrich PESTANAL® Molinate 98.6 (HPLC) 100 mg Sigma Aldrich PESTANAL® Cycloate 99.6 (GC) 250 mg Sigma Aldrich PESTANAL® Sodium Chloride 99.0 500 g VWR International Water, HPLC Grade 100 4 L J. T. Baker Methanol, HPLC 100 4L J.T. Baker Grade Tetrahydrofuran, 100 4L J. T. Baker HPLC Grade Acetonitrile, HPLC 99.9 4L Acros Organics Grade KRS-5 Crystals - 25 x 5 mm International Crystal Laboratories KBr Crystals - 25 x 5 mm International Crystal Laboratories SPME Fibers - 1 cm Supelco 20 mL Clear Screw- - 100/pack Gerstel Cap Vials for MPS Magnetic Screw - - Gerstel Caps with blue silicone/PTFG septa 2 mL Screw Top vial - 100/pack Agilent Technologies write-on-spot 4 mL vials with - 100/pack MicroLiter Black Cap TLS Analytical Supplies Septa INC

2.2. Solutions

Stock solutions of each pesticide (Table 2.2) were prepared from the individual analytical standards. The standards were injected into separate 250 mL volumetric flasks 20 using a 200 µL glass syringe and diluted to volume with reagent grade methanol. These solutions will be referred to from here as the Standard Stock Solutions, and their concentrations are listed in Table 2.2. To create a Test Solution consisting of all six pesticides, a solution was made by volumetrically transferring 20 milliliters of each

Standard Stock Solution to a flask. This new solution, referred to as the Test Solution, was not diluted to volume. An aqueous solution was created by combining ten mL of each Standard Stock Solution in another 100 mL volumetric flask, and diluted to volume with laboratory deionized water that had been filtered for organic material. This solution, which contained all six pesticides and consisted of 60% methanol, will be referred to as the Working Stock Solution. As needed, several other dilute solutions were made using aqueous dilutions of the Working Stock Solution. These will be referred to as the Dilute

Solution(s), and were made fresh for individual categories of investigation unless otherwise noted. The typical concentration of these Dilute Solutions centered around

2.5% methanol content and the corresponding pesticide concentrations. Appropriate glass stoppers were inserted into the volumetric flasks, which were further sealed with

Parafilm® M until needed.

21 Table 2.2. Concentrations of the multiple solutions used for this experiment.

Thiocarbamate Standard Stock Test Solution Working Stock Dilute Solutions Pesticide Solutions (ppm) Solution (Parts per million) (ppm) (typical ranges in ppm) Solution One per pesticide, One solution, One solution, Dilutions of the Working Description six total solutions. contained all six contained all six Stock Solution. Each pesticides. pesticides. solution contained all six 100% methanol. Aqueous. pesticides. Aqueous. EPTC 456 76.0 45.6 1-3 Butylate 300 50.0 30.0 1-3 Vernolate 300 50.0 30.0 1-3 Pebulate 321 53.5 32.1 1-3 Molinate 320 53.3 32.0 1-3 Cycloate 280 46.7 28.0 1-3 Methanol % 100 100 60 2.5

2.3. GCMS Liquid Injection

Two modes of introducing a sample into the GCMS were explored. Proceedures

for each are discussed in the following sections. Section II.3 covers the application of

traditional liquid injection with a microsyringe. It is the more traditional and commonly

applied technique.

The Test Solution (Table 2.2) was used for this portion of the experiment. This

was used to develop a temperature program to determine if separation of all six pesticides

was possible by Gas Chromatography – Mass Spectrometry (GC-MS).

The instrument used was a 7890 Gas Chromatograph (GC) System from Agilent

Technologies. It was in series with a 5975C inert XL EI/CI Mass Spectrometer Detector

(MSD) with Triple Axis Detector. Attached to the GC was a Gerstel Multipurpose

Sampler MPS 2LX – Twister, which also included a Thermal Desorption Unit (TDU) and

22 Olfactory Detection Port (ODP). The software for analysis was Agilent’s Chemstation with Advanced Data Analysis.

The injection port temperature was 270 °C. Helium was the carrier gas at 1.2 mL/minute through an Agilent J + W narrowbore DB-35 UI column. Column dimensions were 30 m x 0.250 mm x 0.25 µm, with an operating temperature range of 50 to 340°C. A splitless injection was used with a 4 minute solvent delay. A temperature program that successfully separated all six pesticides was developed and is shown in

Table 2.3.

Table 2.3. Temperature program for GC-MS pesticide separation by liquid injection.

Initial column temperature: 50 °C, held for 3 minutes. Temperature increase 12 °C per minute to 200 °C Temperature increase 7 °C per minute to 280 °C

The suitability of the technique for thiocarbamate herbicide analysis was determined. For each pesticide, calibration curves were created from series of dilutions made from the six Standard Stock Solutions. The dilutions were carried out using multiple disposable glass pipets, 20 mL scintillation vials and reagent grade methanol.

The concentrations ranged from the initial stock concentration to less than one part per million.

During the course of this study, the GC-MS underwent several maintenance procedures that necessitated multiple alterations in the method settings. A new column, an Agilent J+W DB-5MS, 30 m x 0.250 mm x 0.25 µm, was installed. The new

23 operative temperature range was -60 °C to 325 °C. The flow rate was reduced to 1.0 mL/minute. A new temperature program was implemented, and can be seen in Table 2.4

Table 2.4. Temperature program used for SPME optimization testing.

Initial column temperature: 100°C, held for zero minutes. Temperature increase 5°C per minute to 200°C Temperature increase 25°C per minute to 280°C

The total run time was 23.2 minutes. New four point calibration curves were created using dilutions of the Standard Stock Solutions. The curves ranged from approximately 2 - 10 parts per million for each pesticide.

2.4. SPME

The second method of introducing a sample into the GCMS was with the use of an optical fiber coated with stationary phase in the technique known as SPME. It is a relatively new technique that is quickly gaining acceptance in the scientific community, especially in the environmental field.

Several optimization parameters were evaluated for their impact on SPME analysis. Gravimetric dilutions of the Working Stock Solution (Table 2.1) were made for each factor, diluting the methanol content to approximately 2.5% and the concentration of each pesticide to between one and five parts per million. The fiber used for extraction was always burned off (cleaned) in accordance to the manufacturer instructions prior to

24 any experimentation. The experiments were performed on the updated GC-MS conditions and temperature programs listed in Table 2.3

OPTIMIZATION PARAMETERS

Multisampling

The effect of multiple extractions on the concentration of a sample was examined.

To do this, equal concentrations of a dilute pesticide solution were put into five 20 mL headspace vials and sealed. Each vial was sampled five times with an 85 µm polyacrylate fiber.

Fiber type

Five different fibers were investigated. They consisted of various stationary phases and thicknesses. The types are listed in Table 2.5. Each fiber was exposed to five vials containing two grams of the same Dilute Solution. After a 15 minute extraction, the fibers were desorbed at the upper limit of their operating temperature, but no higher than

305 °C.

25 Table 2.5. Comparison of fibers examined.

Number Color Phase Film Desorption Reference Thickness Temperature (Manufacturer (µm) (°C) assignation) 1 White Polyacrylate (PA) 85 305 2 Pink Polydimethylsiloxane/diviylbenzene 65 270 (PMDS/DVB) 3 Gray Dibinylbenzene/carbowax/polydimethylsiloxane 50/30 270 (DVB/CAR/PMDS) 4 Red Polydimethylsiloxane (PMDS) 100 280 5 Light Blue Carboxen/polydimethylsiloxane 85 305 (Carboxen/PMDS)

Sample Volume

The effect of sample volume was analyzed by comparing vials with varying

amounts of the same Dilute Solution. The amount of sample ranged from zero to six

grams. Three vials of each amount were sampled, using an 85 µm polyacrylate fiber.

Each vial was extracted for 15 minutes and desorbed at 305 °C for eight minutes.

Extraction time

Sample extraction time was evaluated by placing equal amounts of a Dilute Stock

solution into several 20 mL head space vials and exposing the fiber to them for different

amounts of time. The time ranged from 5 to 120 minutes, and each was evaluated three

times. Agitation speed was 250 rpm at 45 °C.

Salt content

The impact of adding salt to the sample vials was investigated by adding different

amounts of granular sodium chloride to the same amount of Dilute Solution. Salt was

weighed out and placed into 20 mL headspace vials. Four grams of Dilute Solution were 26 added to each vial, and the cap was twisted shut. Three trials were run for each aliquot of salt. Runs were not initiated until the salt was completely dissolved. The vials were agitated at 250 rpm.

Agitation Speed

The effect of agitation speed on sample extraction was investigated by varying the rotations per minute (rpm) of the agitation chamber that held the sample during extraction. The speeds evaluated were 250, 500, and 750 rpm. Three vials containing

1.00 g of salt and 4.00 g of Dilute Solution were extracted at each speed.

Agitation Temperature

The agitation chamber temperature was varied from 45 °C to 90 °C. Three vials were extracted at fifteen degree intervals, with all other extraction parameters held constant. To extend this range and determine if the effect of temperature was linear, a second comparison was made between 30 °C and 45 °C.

Desorption Temperature

The polyacrylate fiber was evaluated for its response to different desorption temperatures. A temperature range of 260 °C to 305 °C was used. Three equivalent sample vials were extracted at every 15 degree interval. A fresh blank vial was used for five minute extractions between each sample and desorbed at 305 °C for eight minutes to ensure no sample carry over into blanks and complete desorption before the next sample extraction.

27 Once the investigations into the parameters above were complete, a calibration curve of multiple dilutions at 2.5% methanol was compiled. A portion of the Working

Stock solution was first diluted to 2.5% methanol using organic filtered deionized water.

From here, this was diluted by half with a 2.5% methanol in water solution. This solution was diluted again 1:3 with the same 2.5% methanol in water solution. Three sample vials at each concentration were prepared, for a total of nine. Each sample vial contained 4.00 g of solution and 1.00 g of sodium chloride. The solutions were extracted using the 85

µm polyacrylate fiber for 30 minutes at 45 °C and with an agitation speed of 250 revolutions per minute. The fiber was desorbed for eight minutes in the 305 °C injection port.

2.5. HPLC

The instrument used for HPLC analysis was a Waters system. It consisted of several parts, including a 600E System Controller as the pump, a 717 plus Autosampler, a

2996 Photo Diode Array Detector, and a 410 Differential Refractometer, all by Waters.

The operating software was Empower® by Waters.

The Test Solution (Table 2.1) was used in a similar fashion as it was for the GC-

MS: to determine if adequate separation between pesticides could be established using

HPLC. A Phenomenex® ProdigyTM 5 µm ODS-3 100 Å LC Column was used, with a

150 x 4.60 mm internal diameter, and particle and pore size of 5 µm and 100 Å, respectively. An initial solvent gradient was developed using HPLC water and acetonitrile (CH3CN). This gradient is shown in Table 2.6.

28

Table 2.6. Solvent gradient for HPLC separation of thiocarbamate pesticides.

Time % % (min) Water CH3CN 0 55 45 4 55 45 9 10 90 12 10 90 15 55 45

The flow rate was one mL/minute. The pesticides were then analyzed separately, using the above solvent gradient program and series of dilutions made from the Standard

Stock Solutions. These dilution series ranged from the full concentration of the solutions to about 15 parts per million, and were used to create calibration curves.

Several isocratic parameters were also explored, and are listed in Table 2.7.

Before the application of any of the isocratic trials, the reference cell in the Waters 410

Differential Refractometer was purged for 15 minutes with the appropriate composition of solvents.

Table 2.7. Isocratic HPLC parameters tested.

Isocratic % % Flow Rate Trial H O Acetonitrile (mL/min) number 2 1 20 80 1.0 2 20 80 0.6 3 25 75 0.6

29 2.6. IR

The Standard Stock Solutions (Table 2.1) were spread on KRS-5 crystals

(thallium bromoiodide) using wooden application rods, and the methanol was allowed to evaporate. Each pesticide was applied five times to the same crystal. The crystals were then analyzed using a Perkin Elmer FTIR Spectrum 2000 Spectrometer, with Spectrum® software, between the range of 4000 to 400 nm. The pesticides were compared with five scanning cycles. These scanning cycles ratioed the pesticide crystals to a blank KRS-5 crystal. The crystals were cleaned with tetrahydrofuran and allowed to dry before application of the next pesticide.

Several blanks were analyzed to determine the baseline of the instrument. The

KRS-5 crystals were cleaned with THF and run without any applied substance. One crystal was run against an empty reference cell, and also two blank crystals were run against each other.

The same operation was performed for potassium bromide, or KBr, crystals, cleaned with methanol instead of THF. For the pesticide analyses, two KBr crystals were cleaned with methanol and allowed to dry. Stock Solution of EPTC (456 ppm) was applied to one KBR crystal using the wooden rod approach. One drop was applied at a time, allowing the methanol to completely evaporate after each drop. Ten drops were applied. After the final solvent evaporation step, the crystal was run against a blank KBr reference crystal.

Post analysis, the two crystals used above were thoroughly cleaned with methanol and allowed to dry. Two additional crystals were cleaned with methanol and allowed to dry, yielding four clean, dry KBr crystals. One drop of 456 ppm Stock Solution of EPTC

30 was applied to one of the KBr crystals. The methanol was not allowed to evaporate; instead, the solvent drop was immediately sandwiched by the addition of a second KBr crystal. This KBR/solvent sandwich was run against a sandwich of two blank KBr crystals, with no solvent in the middle.

All four crystals were cleaned and dried. For a second time, one drop of 456 ppm

Stock Solution of EPTC was sandwiched between two KBr crystals. One drop of pure methanol solvent was sandwiched between the reference KBr crystals, and the two pairs were run against each other.

31 CHAPTER III

RESULTS AND DISCUSSION

3.1 GCMS Liquid Injection

The initial temperature program for GCMS separation of the six thiocarbamate pesticides studied was listed in Table 2.3. Figure 3.1 demonstrates the resolution achieved by this temperature program. The instrument maintanence, along with the introduction of a new column and temperature program (Table 2.4) naturally caused a shift in retention time. To verify that the new method allowed for successful separtion, the Test Solution was injected as it was to verify Temperature Program 1. The new spectra with updated retention times can be seen in Figure 3.2.

32

Figure 3.1. Separation of the Test Solution using GC-MS Temperature Program 1 (Table

2.3).

Figure 3.2 Separation of the Test Solution using GC-MS Temperature Program 2 (Table 2.4).

33 The separations in Figures 3.1 and 3.2 were achieved with good resolution.

Calibration curves were created to determine the instrumental response to concentration.

A series of gravimetric methanol dilutions were made using the Standard Stock Solutions

(Table 2.2). Three series were created for each pesticide, consisting of at least six concentrations from full Standard Stock Solution concentration to below 10 parts per million. Their results can be seen in Figures 3.3 to 3.8.

14000.0

12000.0

10000.0

8000.0 S et 1 6000.0 S et 2 4000.0 Abundance (1*10^4) S et 3 2000.0

0.0 0.0 100.0 200.0 300.0 400.0 500.0 ppm EP TC

Figure 3.3 Calibration curve for methanol dilutions of the Standard Stock Solution for EPTC.

34 12000.0

10000.0

8000.0

6000.0 S et 1

4000.0 S et 2

Abundance (1*10^4) S et 3 2000.0

0.0 0.0 100.0 200.0 300.0 400.0 ppm Butylate

Figure 3.4 Calibration curve for methanol dilutions of the Standard Stock Solution for butylate.

16000.0 14000.0 12000.0 10000.0

8000.0 S et 1 6000.0 S et 2

Abundance (1*10^4) 4000.0 S et 3 2000.0 0.0 0.0 100.0 200.0 300.0 400.0 ppm Vernolate

Figure 3.5 Calibration curve for methanol dilutions of the Standard Stock Solution for vernolate.

35 14000.0

12000.0

10000.0

8000.0 S et 1 6000.0 S et 2 4000.0 Abundance (1*10^4) S et 3 2000.0

0.0 0.0 100.0 200.0 300.0 400.0 ppm Pebulate

Figure 3.6 Calibration curve for methanol dilutions of the Standard Stock Solution for pebulate.

16000.0 14000.0 12000.0 10000.0

8000.0 S et 1 6000.0 S et 2

Abundance (1*10^4) 4000.0 S et 3 2000.0 0.0 0.0 100.0 200.0 300.0 400.0 ppm Molinate

Figure 3.7 Calibration curve for methanol dilutions of the Standard Stock Solution for molinate.

36 12000.0

10000.0

8000.0

6000.0 S et 1

4000.0 S et 2

Abuncance (1*10^4) S et 3 2000.0

0.0 0.0 50.0 100.0 150.0 200.0 250.0 300.0 ppm Cycloate

Figure 3.8 Calibration curve for methanol dilutions of the Standard Stock Solution for cycloate.

37 As shown by the above figures, each pesticide demonstrated a linear response between concentration and peak abundance (area). The average linear regression values of the three series ranged from 0.9926 for Butylate to 0.9983 for EPTC, well within the accepted range for an EPA detection method.21 To help establish the Limit of Detection, low concentration calibration curves were made for each pesticide. A series of dilutions of the Standard Stock Solutions was made as before, but this time the maximum concentration was 15 ppm and decreased to about one ppm. Though only one series was created for each pesticide, the linearity of the curves clearly degraded at low concentrations. It was interesting to note that for the low concentration curves a power trendline showed excellent agreement for all six pesticides. Rather than follow the linear equation of y = mx + b, the power regression equation fits the data to the equation:

y = axb

This raised the questions of which type of regression was best suited for the calibration curves of full concentration. The fits for all of the calibration curves can be seen in Table

3.1.

Table 3.1. Calibration Curve Fittings.

Average Linear Average Power Fit Linear Power Fit R2 for Full R2 for Full R2 for R2 for Low Thiocarbamate Concentration Concenteration Low ppm Range Liquid Range Liquid ppm Curves Injection Injections Curves EPTC 0.9983 0.9887 0.9805 0.9967 Butylate 0.9926 0.9963 0.9797 0.9990 Vernolate 0.9944 0.9927 0.9709 0.9976 Pebulate 0.9961 0.9930 0.9787 0.9976 Molinate 0.9951 0.9935 0.9663 0.9983 Cycloate 0.9950 0.9936 0.9587 0.9992

38

It was found to be extremely interesting that the fits for both a power and linear regression were so well applicable to the curves of the full range of concentrations. No altercation really exists, as both fall within the EPA’s acceptable range. However, because of the linear regression’s slight deviation at lower concentrations, it may be necessary to apply the power formula for the detection of very low concentrations.

For the Limits of Detection and Quantification, the method of Thomsen et al was applied.22 The areas where pesticide elution would occur, based on retention times, were integrated on multiple blanks. The averages and standard deviations were determined, and from there the LoD (3*STDEV+AVG) and LoQ (3*STDEV+AVG), as shown in

Table 3.2.

Table 3.2. Limits of Detection for GC-MS by liquid injection.

EPTC Butylate Vernolate Pebulate Molinate Cycloate AVG of blanks 8436 6393 11437 11235 10512 10621 STD Dev of blanks 452 537 1522 989 1395 337 LoD 9793 8003 16004 14202 14697 11633 LoQ 12959 11761 26660 21127 24464 13995

The numbers in Table 3.2 are arbitrary units put into the equation of the calibration curve to calculate for concentration. Since three calibration curves (from three series of dilutions) were established for each pesticide, the values of the areas of

LoD and LoQ from Table 3.2 were applied to each one, and the average was used as the final representation of the method’s limits of detection and quantification, as given in

Table 3.3.

39 Table 3.3. GC-MS Limits of Detection and Quantification by liquid injection in parts per million.

LOD LOQ LOD LOQ Pesticide (ppm) (ppm) (ppb) (ppb) EPTC 0.04 0.05 4.00 5.00 Butylate 0.025 0.037 2.50 3.70 Vernolate 0.039 0.064 3.90 6.40 Pebulate 0.045 0.066 4.50 6.60 Molinate 0.04 0.065 4.00 6.50 Cycloate 0.041 0.048 4.10 4.80

3.2. GCMS - SPME

The initial extractions attempted SPME were very similar in nature to the liquid injections. A series of dilutions using methanol solvent were created and analyzed using a 7 µm PMDS fiber. Supelco ® recommended this fiber type for non-polar high molecular weight compounds.14 It was chosen for initial extraction not due to the polarity, but because of the relatively high molecular weight of the thiocarbamate pesticides.

However, initial results were extremely poor and irreproducible. Responses (fiber absorption) varied greatly. An example of this is demonstrated in the attempted calibration curves of butylate under these conditions. At times, there was a glimpse of linear tendency, but the next series or even the next data point would prove false any sort of trend.

40 2500.0

2000.0

1500.0 S et 1 1000.0 S et 2

Abundance (1*10^4) S et 3 500.0

0.0 0.0 100.0 200.0 300.0 400.0 ppm Butylate

Figure 3.9. Initial SPME GC-MS response using 7 µm PMDS fiber to extract from methanol solvent based pesticide solutions.

According to the literature reviewed, most SPME extractions are performed in aqueous matrices.11,16 The organic solvent most likely acted as an interference with the analyte extraction. This observation initiated the testing of several different solvent concentrations. Water with 2.5% methanol seemed to be the optimal operating concentration; it was a balance between eliminating solvent interferences and retaining a high enough analyte concentration to accurately quantify the thiocarbamates (about 1-3 ppm, created from aqueous dilutions of the Working Stock Solution).

After the optimal concentration of methanol had been established, an investigation into the effect of multi-sampling was carried out. SPME largely has not been used as a quantitative extraction technique, meaning the removal of all the analyte from the sample. While possible, as pointed out by Prosen et al., it requires several extractions from the sample vial while retaining the previously injected analytes on a low temperature column.11 This is both a time consuming and meticulous process. Instead, 41 SPME has been mainly applied as an equilibrium technique. The amount extracted onto the fiber is proportional to the concentration in the sample and dependent on the volatility of the analytes and type and thickness of the stationary phase. Individual extractions may not remove significant amounts of analytes, but even a few extractions from the same sample vial can affect the concentration and resulting peak areas. This point is demonstrated in Figure 3.10.

Figure 3.10. The effect of multiple extractions from the same vial on analyte peak response.

Obviously concentration could not be accurately represented by sampling the same vial multiple times. Instead, all subsequent analyses consisted of only one extraction per vial, and the conclusions were drawn from the results of multiple vials containing equivalent solutions.

The next part of optimizing the SPME extraction process was to investigate different stationary phases. As shown in Table 2.5, five fiber types were selected based 42 on their phase type and thickness. A Dilute Solution was created from an aqueous dilution of the Working Stock solution. Multiple 20 mL headspace vials were each filled with two grams of this new solution. Five vials were extracted by each fiber, and the

GCMS results were averaged.

As shown by Figure 3.11 below, the 100 µm PDMS fiber and the 85 µm PA fiber showed the highest affinity for the pesticides. Because molinate and cycloate, the pesticides with the lowest responses to any fiber, showed slightly greater proclivity for the 85 µm polyacrylate fiber, it was decided that this was the best fiber to proceed with for other optimization parameters.

Fiber Adsorptivities

45000000 40000000 35000000 85 µm PA 30000000 65 µm PDMS/DVB 25000000 50/30 µm DVB/CAR/PDMS 20000000 100 µm PDMS

Peak Area Area Peak 15000000 10000000 85 µm Carboxen/PDMS 5000000 0

EPTC Butylate Vernolate Pebulate Molinate Cycloate Thiocarbamate

Figure 3.11. Averaged results of a 2.5% methanol solution containing 1-3 ppm of each pesticide. Each SPME fiber extracted five vials containing two grams of solution. Extraction time was 15 minutes at 45 °C.

The factors evaluated for their effect on SPME adsorption were chosen based on literature review and experimental observation.11 The volume of sample and amount of

43 salt put in each vial, extraction time, agitation temperature and speed, and desorption time and temperature were all predicted to have an impact on analyte adsorption onto the fiber.

Some parameters, like pH, were not investigated because it has been noted in previous research to have minimal effect.17

Sample Volume

Vials with varying amounts of the same solution were compared to determine if sample volume had an impact on fiber extraction. Because of the nature of SPME headspace extraction, the upper limit of sample volume was constrained to the area below the full extension of the fiber. Four volumes were evaluated: one, two, four, and six grams. Three vials were created at each volume, and their averaged results were plotted, as shown in Figure 3.12. Analyte adsorption seemed to increase slightly with increased sample volume. Four grams was decided upon as the accepted amount for further investigations as it provided adequate response while keeping experimental overhead and waste within reason.

44

Figure 3.12. Effect of sample volume on SPME headspace extraction. Each point is an average of three extractions. Extraction time was 15 minutes at 45 °C.

Salt Content

It is well know that the addition of a salt can decrease the solubility and increase the partition coefficient of analytes in aqueous solutions.(Boyd-Boland 60). This theory was tested by holding all other experimental parameters constant and varying the amount of NaCl added to the extraction vials. Starting with no salt, the addition of up to four grams were made to vials containing four grams of sample. The salt was allowed to completely dissolve before extraction.

As can be seen by Figure 3.13, there was a noticeable improvement with the initial inclusion of one gram of sodium chloride. Increased allotments of salt did not have equivalent enhancement effects until the addition of four grams. The response with the one gram of salt was deemed sufficient without the longer time required for the

45 dissolution of four grams of salt into solution in order to achieve the higher extraction response.

Figure 3.13. Effects of the addition of sodium chloride to pesticide extraction vials.

Extraction time

Once equilibrium has been reached, the fiber is saturated with sample and unable to adsorb more. Several equilibrium times have been suggested, however, depending on the detection limits required, it is not necessary to achieve equilibrium. Accurate calibration curves can be constructed as long as extraction time and other extraction conditions are carefully controlled.11 In this instance, use of an automated sampling system made this possible. A dilute solution was made from the working standard solution, and various extraction times were tested.

46

Figure 3.14. The effect of SPME extraction time on GC-MS peak area response. Four grams of salt were used per sample. Each data point is the average of three samples.

As shown by Figure 3.14, it did not appear that any of the pesticides were able to reach equilibrium in an extraction time of two hours. Because the oven temperature program was 23.2 minutes, an extraction time of 30 minutes was deemed a sufficient balance between optimizing response and sampling efficiency.

Agitation

The agitation speed was tested at regular intervals between the minimum agitation speed (250 rpm) and maximum agitation speed (750 rpm). Based on the results shown in

Figure 3.15, it appeared that increased agitation speed had an adverse effect on extraction efficiency.

47

Figure 3.15. Effect of agitation speed on pesticide extraction.

The optimal extraction temperature in the agitation chamber was experimentally determined to be 45 °C. This was determined by running multiple solutions at 15 degree intervals from 45 to 90 °C, and these results were plotted in Figure 3.16.

48

Figure 3.16. Effect of agitation chamber (extraction) temperature on pesticide extraction.

Desorption

The amount of time and at what temperature the analytes are removed from the fiber in the injection of the GC was the final parameter examined. Skoog recommended that the temperature of the GC injection port be 50 °C above the boiling point of the analyte with the lowest volatility to ensure that all compounds are swept into the GC column. This would have set the desorption temperature at over 350 °C.23 No fiber that

Supelco® produces can withstand temperatures above 340 °C.14,24 Fortunately, the low volatilities of the thiocarbamates made lower injection port temperatures possible.25,23

Several desorption times were tested, as can be seen in Figure 3.17. Four desorption temperatures were tested at 15 degree intervals up to 305 °C, which was five degrees above the recommended operating temperature but below the maximum operation temperature. Higher desorption temperatures were likely to decrease fiber lifespan.24

49

Figure 3.17. Effect of desorption temperature on peak area response of pesticide chromatograms.

From Figure 3.17 it can clearly be seen that the higher operating temperatures significantly increased the amount of pesticides reaching the detector. Even though CITE said most analyte desorption occurs within seconds of entering the desorption chamber, ghost peaks were seen in blanks between samples until desorption time was increased to

8 minutes at 305 °C.

Once all of the optimization parameters had been determined, the final calibration curve for SPME extraction was created. The high sensitivity of the method allowed for a series of dilutions under two parts per million. Three dilutions for each pesticide, repeated three times each and averaged to yield the final calibration curve. These results can be seen in Figure 3.18. The correlation coefficients can be seen in Table 3.4, and the detection limits based on Thomsen’s calculations can be seen in Table 3.5.22

50

Figure 3.18. Final SPME calibration curve under optimal extraction conditions, which were 30 minute extractions using an 80 µm polyacrylate fiber that was desorbed for 8 minutes. Vials consisted of four grams of sample and one gram of NaCl at 2.5% methanol. Agitation occurred at 250 rpm at 45 °C.

Table 3.4. Linear correlation coefficient values for SPME pesticide calibration curves.

Linear Correlation Pesticide Coefficient (R2) EPTC 0.9715 Butylate 0.9683 Vernolate 0.9749 Pebulate 0.9787 Molinate 0.6147 Cycloate 0.9610

51 Table 3.5. Method detection capabilities for SPME-GC/MS.

LOD LOQ LOD LOQ Pesticide (ppm) (ppm) (ppb) (ppb)

EPTC 0.0007 0.0023 0.6889 2.2960

Butylate 0.0002 0.0008 0.2305 0.7688

Vernolate 0.0001 0.0004 0.1338 0.4462

Pebulate 0.0001 0.0005 0.1424 0.4747

Molinate 0.0019 0.0063 1.9028 6.3015

Cycloate 0.0002 0.0005 0.1634 0.5448

3.3. HPLC

As can be seen in Table 2.1, several of the pesticide standards were evaluated for purity by HPLC analysis. The solvent composition varied from 50/50 % water/acetonitrile for molinate to 25/75 % water/acetonitrile for butylate. EPTC was in the middle with 40/60 % water/acetonitrile. The flow rates were 1.8, 1.4, and 1.4 mL/minute for molinate, butylate, and EPTC respectively, with UV detections set at 225,

215, and 210 nm (Appendix A). Solvent Gradient 1 (Table 2.6) was developed based on the precedents set by Sigma-Aldrich for the pesticide certificates of analysis (COAs). A gradient was implemented to compensate for the different percent of solvents used in the

COA methods for different pesticides. A flow rate of one mL/min was used to try to ensure adequate separation. The photodiode array detector was set to scan between wavelengths of 210 to 400 nm. While acceptable separation between all six pesticides was apparently achieved, the chromatograms were never without the presence of several 52 unidentifiable peaks. These peaks became more prevalent at higher wavelengths. An example of the typical chromatogram with interfering peaks can be seen below in Figure

3.19.

Figure 3.19. HPLC Chromatogram of 320 ppm molinate with additional peaks eluted using Solvent Gradient 1.

Also of note in Figure 3.19, there was an obvious wandering baseline, which may have interfered with proper pesticide identification and quantification. Because of the sharp decrease at about ten minutes, the area sampled for peaks resolving during this time for Limit of Blank determination may have resulted in a higher Limit of Blank (LoB),

Limit of Detection (LoD), and Limit of Quantification (LoQ) than was accurate. The largest peak for each pesticide was used as the quantifiable peak.

A series of solutions of decreasing concentration were made using gravimetric methanol dilutions of the Standard Stock Solutions (Table 2.2). These dilutions were separated using Solvent Gradient 1. The optimum wavelength was determined to be 210 nm. This gave the best resolution and least interferences for all six pesticides. The main pesticide peak was integrated, and the resulting peak area was plotted against 53 concentration to produce calibration curves. Three sets of dilutions were created for each pesticide, ranging from the undiluted Standard Stock Solution concentration to about 20 ppm. The calibration curves can be seen below.

Figure 3.20. HPLC calibration curve for molinate using Solvent Gradient 1.

Figure 3.21. HPLC calibration curve for cycloate using Solvent Gradient 1.

54

Figure 3.22. HPLC calibration curve for vernolate using Solvent Gradient 1.

Figure 3.23. HPLC calibration curve for butylate using Solvent Gradient 1.

55

Figure 3.24. HPLC calibration curve for pebulate using Solvent Gradient 1.

Figure 3.25. HPLC calibration curve for EPTC using Solvent Gradient 1.

56 The average correlation coefficient values for the calibration curves above can be seen in Table 3.6. The linearity for this method was well established down to 20 ppm.

To determine the LOD and LOQ, the areas of the baseline during the time-frame for pesticide elution were measured for 12 methanol blanks.26 These areas were averaged, and the standard deviation, or STDev, was calculated. According to Thompsen et al,22

LoD = 3 x STDev + Average

LoQ = 10 x STDev + Average

These formulas were used to calculate the LoDs and LoQs for all six thiocarbamate pesticides as analyzed by HPLC and Solvent Gradient 1, and can be seen in Table 3.5.

Table 3.6. Average Correlation Coefficient Values for Thiocarbamate Pesticide HPLC Calibration Curves created using Solvent Gradient 1.

Average Correlation Thiocarbamate Coefficient Molinate 0.9932 Cycloate 0.9972 Vernolate 0.9986 Butylate 0.9981 Pebulate 0.9982 EPTC 0.9973

Numerical values for HPLC detectable concentrations were determined using the values from Table 3.6 and the linear equations based on the calibration curves for each pesticide. These can be seen in Table 3.7.

57 Table 3.7. HPLC background response as determined by Blank Averaging.

Thiocarbamate Average STDEV LoD LoQ Molinate 934 161 1418 2547 Cycloate 504 167 1006 2177 Vernolate 411 63 599 1039 Butylate 661 109 987 1747 Pebulate 443 62 630 1066 EPTC 517 80 757 1317

Translation of these numbers into parts per million and parts per billion was accomplished by using the linear equation provided by the concentration curves. These values are displayed in Table 3.8 below.

Table 3.8. Limits of Detection and Quantification for the six thiocarbamate pesticides by HPLC.

LOD LOQ LOD LOQ Pesticide (ppm) (ppm) (ppb) (ppb) Molinate 0.1627 0.5414 16.27 54.14 EPTC 0.1418 0.4104 14.18 41.04 Pebulate 0.2757 0.8099 27.57 80.99 Vernolate 0.0628 0.1935 6.28 19.35 Cycloate 0.0653 0.1975 6.53 19.75 Butylate 0.2766 0.8019 27.66 80.19

In an effort to improve these results, several isocratic methods were explored as listed in Table 2.7. As Figure 3.26 shows, removing the solvent gradient improved the baseline, but the separation of the pesticides and the recurrence of excess peaks was adversely affected.

58

Figure 3.26 HPLC chromatogram of all six thiocarbamate pesticides. 80/20 % CH3CN/H2O at one mL/minute.

Along with a change in retention time, the identification of the peaks became difficult as the resolution decreased. The next variable to be altered was the flow rate, decreased from one mL/min to 0.6 mL/min in an effort to try to improve separation. This was mildly successful, but still did not remove the excess peaks. The results for this can be seen in Figure 3.27.

59

Figure 3.27 HPLC Chromatogram of all six thiocarbamate pesticides. 80/20 % CH3CN/H2O at 0.6 mL/minute.

One last attempt was made to try to improve the chromatographic results of the

HPLC technique. The solvent ratios were adjusted to 75/25 % CH3CN/H2O. The chromatograph is shown in Figure 3.28.

Figure 3.28 HPLC Chromatogram of all six thiocarbamate herbicides. 75/25 % CH3CN/H2O at 0.6 mL/minute.

60 Increasing the percent water in the solvent mixture and decreasing the flow rate improved separation for isocratic elution. However, resolution was poor and baseline noise became problematic. In addition, co-elution of excess peaks was never remedied.

Because of the severity of these drawbacks in the isocratic methods, the initial solvent gradient was designated the accepted HPLC method. This method had demonstrated success in separating and resolving all six thiocarbamate pesticides below 20 ppm.

Though extraneous peaks still occurred, they did not elute in places that interfered with quantification of another pesticide.

3.4. IR

Thiocarbamates have previously been investigated by FTIR.27,28,29, 30,31 Several attempts were made to elicit acceptable FTIR spectra from both liquid and solid state samples. The procedures used were based on those of Keresztury et al.28 The samples were introduced using two different crystals, which were KRS-5 (thallium-bromide) and

KBr.

The first attempt was on KRS-5 crystals. To increase concentration, five drops of the Standard Stock Solutions was applied one on top of the other to the crystals. The solvent was allowed to evaporate between drops. Though a thin white film could be seen, on the crystal, the spectra were unsatisfactory.

61 Vernolate

Cycloate

Pebulate

A Molinate

Butylate

EPTC

4000.0 3000 2000 1500 1000 400.0 cm-1

Figure 3.29. FTIR Spectra of all six Standard Stock Solutions as applied five times to KRS-5 crystals (solvent free, solid state).

As can be seen by Figure 3.29, the FTIR spectra yield little valuable information.

Though the Perkin Elmer Spectrum 2000 software automatically corrected for atmospheric conditions, there appeared to be significant noise from water and carbon dioxide. There was no structural information to describe the pesticide. Before beginning this experiment, it had been anticipated that pesticides’ carbon-sulfur, -oxygen, and - nitrogen bonds would be visible by IR. Because of this lack of initial response, it was deemed time and cost efficient to work with one pesticide until an acceptable method of introduction was found. EPTC was chosen because its Standard Stock Solution was the most concentrated and therefore had the highest probability of being detectable.

The same application procedure as above was carried out using KBr crystals, except this time ten drops of Standard Stock Solution was applied. The crystals were cleaned with methanol prior to use.

62 -0.038

-0.05

-0.06

-0.07

-0.08 A

-0.09

-0.10

-0.11

-0.12 -0.123 4000.0 3000 2000 1500 1000 400.0 cm-1

Figure 3.30. FITR spectra of the Standard Stock Solutions of EPTC as applied ten times to a KBr crystal (solvent free, solid state).

Even less signal was produced by application to the KRS crystals than with the

KRS-5. For this reason, it was concluded that solid state FTIR would not be a useful technique for the acquisition of valuable information about the pesticides, and other liquid phase FTIR was explored.

For liquid phase FTIR, one drop of the Standard Stock Solution of EPTC was applied to a clean KBr crystal. The methanol was not allowed to evaporate, but instead it was sealed in by placing a second clean, dry KBr crystal on top of the first. This produced a kind of “ETPC sandwich.” For the blank, two clean and dry KBr crystals were sandwiched together with no solution or solvent between them. Unfortunately, only the methanol spectrum was captured.

63

1.22

1.1

1.0

0.9

0.8

0.7

0.6 A 0.5

0.4

0.3

0.2

0.1

-0.03 4000.0 3000 2000 1500 1000 400.0 cm-1 Figure 3.31. FITR spectra of the Standard Stock Solution of EPTC sandwiched between two KBr crystals, ratioed to two clean, blank KBr crystals. Sample was in liquid state.

To try to counteract this effect, a single drop of methanol was placed in between the blank reference crystals. This attempt also failed.

Unfortunately, no spectra were obtained that provided useful information regarding the pesticides’ structures or concentration with either solid or liquid state FTIR.

Because of how little information was gathered during the initial experiments, it was concluded that the Standard Stock Solution concentrations were not high enough to detect by FTIR without time consuming and difficult preconcentration steps. Therefore the technique was abandoned in favor of the more useful chromatographic techniques.

64 CHAPTER IV

CONCLUSIONS

The experiments described in this paper were a comparison of different techniques using equipment commonly found in both industrial and government laboratories for the detection and quantification of six thiocarbamate pesticides. The capabilities of chromatography were extensively investigated. A less traditional method for evaluating environmental samples was also explored in the application of Fourier

Transform Infrared Spectroscopy. Unfortunately, it was discovered that the original preparation of the pesticide standards in methanol solvent eliminated the possibility of gaining useful information from this technique.

Success in detection and quantification of the pesticides was found in both high performance liquid chromatography and gas chromatography. The universal photo-diode array detector was limited by the noisy and wandering baseline of the solvent gradient in

HPLC. Visual evaluations of the chromatographs for this technique observed that solutions under 20 parts per million began to waiver in their attractive Gaussian formation. Based on calibration curves, the method designed and implemented for HPLC was able to detect pesticides as low as six parts per billion and to quantify as low at 19 parts per billion for vernolate. Pebulate and butylate were the pesticides with the highest limits of detectability, about 27 (LOD) and 80 (LOQ) ppb each.

65 Two methods for introducing a sample into a Gas Chromatograph-Mass

Spectrometer system were discussed and evaluated; the traditional method of syringe injection of a liquid sample and the more modern and fast-developing technique of Solid-

Phase Microextraction. No matter which method of introduction was applied, GC/MS had lower detection limits than HPLC. Between the two methods, SPME had lower limits of detection and quantification. This fact, coupled with SPME ‘s convenience and lack of sample preparation and preconcentration, clearly identified SPME-GCMS as the best methods for thiocarbamate pesticide evaluation.

SPME’s low cost and high applicability for extraction in many real life situations is responsible for its explosive expansion as an accepted analytical technique. Its shortcomings of limited stationary phase options and delicate fiber nature are likely to be addressed as demand increases. Besides its main application of extraction from environmental matrices like soil and water, there are many more fields this technique could transition into. For example, industrial hygiene and biotoxicity. SPME fibers could be exposed to work environments to verify the safety of employees in a matter of minutes. Bioaffinity coatings are only just beginning to be developed, and could have significant impact on the amount of invasive procedures sustained by patients. It could also confirm the presence of certain materials in body fluids much more rapidly and with higher certainty than current methods. There are many aspects to this technique that make so valuable, most notably its speed and convenience, accuracy and sensitivity, and broad range of application.

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69 APPENDIX

MANUFACTURER CERTIFICATES OF ANALYSIS FOR THIOCARBAMATE

STANDARDS

70 Figure 1. Certificate of Analysis for Pebulate standard.

71 72 Figure 2. Certificate of Analysis for EPTC.

73 74 Figure 3. Certificate of Analysis for Cycloate.

75 76 Figure 4. Certificate of Analysis for Butylate.

77 78 Figure 5. Certificate of Analysis for Molinate.

79 Figure 6. Certificate of Analysis for Vernolate.

80

81