PORTABLE NAPHTHENIC ACID SENSOR FOR OIL SANDS APPLICATIONS

M.T. Taschuk1, Q. Wang

1, S. Drake

1, A. Ewanchuk

2, M. Gupta

1,

M. Alostaz2, A. Ulrich

2, D. Sego

2, Y.Y. Tsui

1

1. Dept. of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada T6G 2V4 2. Dept. of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, Canada T6G 2W2

ABSTRACT Napthenic Acids (NA) are a byproduct of oil sands operations which may be toxic. Current methods for NA detection and concentration measurements in process-affected water (PAW) require site samples to be sent to an analytical chemistry facility, a costly and time-consuming step. To eliminate this bottleneck, we have developed a field-portable fluorescence sensor capable of detecting NA in water at concentrations below 10 mg L

−1 in seconds.

Our prototype sensor is also capable of detecting NA at the tens of ppm level in PAW without any sample preparation. Our device uses ultraviolet light-emitting diodes and a compact charge-coupled device spectrometer to excite and measure NA fluorescence signatures. Our system is capable of measuring the full excitation-emission spectrum of NA in PAW, with excitation wavelengths between 265 nanometers (nm) and 340 nm and emission wavelengths between 200 nm and 800 nm. In this paper we report on our instrument design, develop an optical theory to characterize the performance, characterize NA sensitivity, and report avenues for further improvements and miniaturization of our device.

INTRODUCTION Background Monitoring the presence, migration and biodegradation of naphthenic acids (NA) in oil sands process-affected waters (PAW) is an essential component of assessing and mitigating their environmental and operational impacts. NA are toxic to aquatic life (Clemente and Fedorak, 2005; Allen, 2008) and are a major source of corrosion in the oil industry (Slavcheva et al., 1999). Previous studies have demonstrated that petroleum NA show characteristic fluorescence

when excited by ultraviolet (UV) light in the range of 260 nm to 350 nm (Kavanagh et al., 2009; Brown et al., 2009). One approach to acquiring such signatures is an excitation-emission matrix (EEM), which requires recording fluorescence spectra from multiple excitation wavelengths. EEM measurements can, in principle, determine which of the NA family is present in a given sample. Such analysis is useful for assessing the toxicity of PAW, which depends on the molecular weight of the NA contaminants (Frank et al., 2009). Portable instruments for fluorescence characterization of hydrocarbons in various matrices have been studied for many years (Alarie et al., 1993; Baird and Nogar, 1995; Hart and JiJi, 2002; Obeidat et al., 2008). As low-cost, high power optical sources and improved battery technologies have become available, portable instruments have decreased in size and weight. However, instrument performance has remained roughly constant, producing limits of detection (LOD) in the parts-per-million (ppm) and parts-per-billion (ppb) range. Early work by Alarie et al. had a similar objective to the work described here (Alarie et al., 1993). They designed a portable instrument for on-site contaminant detection, including hydrocarbons in groundwater and hazardous waste sites. The instrument was a ruggedized version of a lab instrument, occupying a suitcase sized (48 cm by 40 cm by 21 cm) optical system. A similar volume of batteries was required to run the system, and the total weight was 22.5 kg. The system was highly sensitive, achieving low ppm to high ppb LOD. A similar system was reported by Baird et al. a few years later (Baird and Nogar, 1995). Although the system was smaller (16 cm by 16 cm by 20 cm), its chemical detection performance was not clearly described. As ultraviolet light-emitting diodes (LED) became commercially available, portable instruments began to use this low-cost source (Hart and JiJi, 2002; Obeidat et al., 2008). The first use of LEDs for obtaining excitation-emission matrices (EEM)

was by Hart et al. (Hart and JiJi, 2002), using seven LEDs at wavelengths between 370 nm and 636 nm. A 1/4 m imaging spectrometer (Oriel MS260i) was used with a cooled charge-coupled device (CCD) detector. The system obtained LOD in the ppb to part-per-trillion (ppt) level for fluorescent dyes. Although the system developed by Hart et al. is not portable due to the spectrometer, it is a clear demonstration of the capabilities of LEDs as an excitation source. A fully portable system using LEDs and an Ocean Optics spectrometer was reported by Obeidat et al. (Obeidat et al., 2008). This EEM-capable system is small and light weight (1.5 kg, 24 cm by 15 cm by 5 cm). The wavelengths used were between 405 nm and 640 nm. System performance was characterized using fluorescent dyes and several plant extracts; nanomolar LOD were achieved for the dyes and the plant extracts could be distinguished using the EEM. In this paper we present a portable fluorescence instrument for characterization of NA in PAW from the oil sands industry. Our prototype is a step towards miniature sensors for detecting hydrocarbons, and will be used to characterize fluorescence signatures and demonstrate the utility of LEDs for compact oilsands instrumentation. Although our long-range goal is a miniature device, the current instrument has utility as a screening instrument for field use. We test prototype performance with diesel and NA in water, demonstrate NA detection below 10 ppm, and demonstrate that our system can detect NA in PAW with no sample preparation.

Instrument Design & Characterization Instrument Specifications Our completed prototype is shown in Fig. 1. The sensor uses LEDs at different UV wavelengths for fluorescence excitation. The UV emission is focused on the sample by an off-axis parabolic mirror. The same mirror collimates the sample’s fluorescent emission for analysis with a compact CCD spectrometer (Ocean Optics). This version has been encased in ABS plastic pipe to provide a robust container for use in the field. Table 1 gives detailed specifications.

Figure 1: Picture of completed prototype encased in ABS pipe. From top to bottom, control switches to select excitation wavelength, compact CCD spectrometer (inside ABS pipe), parabolic optics for focusing UV LEDs, sample holder and laptop to control spectrometer. Not shown: LED array, control circuitry and emission relay optics. Table 1: Instrument specifications. Specification Value Physical Diameter 12 cm Height 53 cm Weight (no base plate) 4 kg Weight (with base plate) 8.5 kg Excitation Repetition Rate 1 kHz Pulse Width 10 µs 265 nm 11 mW 280 nm 18 mW 295 nm 19 mW 310 nm 25 mW 320 nm 14 mW 340 nm 16 mW Emission f/# 4 Spectral Resolution 380 pm

Optical Theory To better understand the expected behaviour of the instrument, we have derived the special case of a distributed fluorescent emitter in an absorbing analyte for our instrumental characteristics and geometry, which differs from conventional bench top instruments. This analysis allows comparison of prototype performance with the theoretical limits, and gives insight into how to improve the instrument. Consider the case of an infinitesimal slice of PAW inside the cuvette at a distance x from the cuvette’s front face, excited by a LED. The fluorescent emission observed by the instrument can be written as

€

dφ = e−αemitxΘ x( )dx [1]

where αemit is the absorption coefficient of the

analyte at the emission wavelength, and Θ(x) is the

fluorescent brightness in units of µJ Sr−1

cm-3

. The expected fluorescence strength is given by the quantum efficiency of the analyte, η, and the

energy absorbed, Eabs. Applying the Beer-Lambert law, and differentiating for the expected absorption of the infinitesimal slice, Θ(x) can be written as

€

Θ x( ) =η

4πEabs x( ) =

η

4πEtargetαexcitee

−αexcite x [2]

where Etarget is the incident energy on the sample, αexcite is the analyte’s absorption coefficient at the

excitation wavelength, and the factor of 4π corrects

for the isotropic fluorescent emission. The total expected emission can be found by integrating Eqn. 1 and is

€

Φ Etarget ,αexcite,αemit( ) =

η

4πEtargetαexcitee

−αexcitexe−αemit xdx

0

Lc

∫ [3]

€

Φ Etarget ,αexcite,αemit( ) =

η

4πEtarget

αexcite

αexcite +αemit

1− e−Lc αexcite +αemit( )[ ]

[4] where Lc is the length of our cuvette. We estimate the depth of field of our parabolic mirror at ≈ 2 cm, so the cuvette length presents the limiting factor. Following the treatment described previously

(Taschuk et al., 2008), it is possible to write the expected signal produced by our prototype, S, as

€

S = LTRdetectorΦ Etarget ,αexcite,αemit( ) [5]

where L is the detector luminosity, with units of Sr cm

2, T represents the detector losses (unitless),

and R is the detector gain with units of Counts µJ

−1. In the limit of strong absorption,

α >> Lc, the fluorescence signal will be saturated

and will not depend on concentration. In the limit of weak absorption, α << Lc, the fluorescence signal

will be negligible. For the case of α ∼ Lc, we

expect a quasilinear behaviour. We tested the expected behaviour using diesel in chloroform, which allowed us to test a wide concentration range. A representative diesel signal is shown in Fig. 2a, which shows the fluorescence signature for a 4 parts per thousand concentration. The peak at 265 nm is reflected light from the excitation LED. Diesel signals were numerically integrated from 300 nm to 460 nm; the results for different concentrations are given in Fig. 2b. The line in Fig. 2b is a best fit to Eqn. 5; an absorption coefficient of ≈ 4200 cm

−1 is obtained.

Overall, the expected behaviour is observed: a quasilinear region at low concentrations followed by a saturated signal at higher concentrations. However, at very high concentrations, the model fails to capture the observed behaviour. One possible explanation for this discrepancy is the rapidly changing Fresnel losses as one moves from a solution dominated by diesel to one dominated by chloroform. Another effect that has not been captured is solvent fluorescence quenching, which may affect the results here (Patra and Mishra, 2002). Further work will be required to incorporate these effects. Such work will also allow a direct evaluation of some of the instrumental factors. Although t is possible to estimate luminosity, some prototype components are not fully specified by the manufacturer, rendering a reliable estimate of detector responsivity very difficult. However, this will require precise knowledge of the analyte solutions used to characterize the instrument.

Figure 2: (a) Representative diesel spectrum at a concentration of 4 10

-3 in chloroform. Diesel

signatures were integrated numerically and are shown in (b) for different concentrations. The line in (b) is a best fit of Eqn. 5 to the data, excluding the bulk diesel data point. An absorption coefficient of ~ 4200 cm

-1 is

obtained. Signal Analysis Figure 3 gives a representative background corrected spectrum collected by our. Good fits to the LED signatures and primary PAW fluorescence peak are achievable with a skew normal distribution (O’Hagan and Leonard, 1976):

€

P x( ) = 2exp −x − x0( )

2

2σ 2

1+erf

a x - x0( )

2

[6] where α is a measure of distribution asymmetry.

This is an empirical fit only. Best fits to the LED peak, the PAW fluorescence peak, and a

Figure 3: Characteristic spectrum from our prototype. Three components have been identified and fit. From left to right, the scattered light from the LED, the NA peak, and a green artifact from the UV LEDs. green defect associated with the UV LED are also shown in Fig. 3. The fit may be used to remove the LED signature, or to numerically integrate the fluorescent intensity observed by the prototype. The green defect will be easily removed with a short-pass filter in a future prototype. Dark current in Ocean Optics spectrometers can add significant background to the spectra acquired with our prototype. For each integration time used here, a background spectrum was taken with no light incident on the detector. This background was subtracted from all spectra prior to analysis.

Instrumental Performance Comparison with Benchtop Instrument Our prototype output was compared with that from a benchtop fluorescence spectrometer for PAW samples at different excitation wavelengths. Since the linewidth of the excitation light in the bench top instrument is much narrower than that of the prototype, it was necessary to remove the scattered light from the LEDs, using the procedure described above. The normalized spectra from both instruments are shown in Fig. 4. Qualitatively, the agreement between the two instruments is excellent. In cases where the LED signature fully overlaps with the emission spectrum, the LED removal will require further work. However, in the context of a screening instrument, the current performance is considered acceptable.

Figure 4: Comparison of normalized spectra obtained with prototype and bench-top standard at excitation wavelengths of (a) 270 nm, (b) 280 nm and (c) 310 nm. With reflected light from the UV LEDs has been removed, the agreement between the prototype and standard instrument is excellent. In some cases removal of the LED signature is not yet optimized, and will require further work.

NA limit of detection in filtered PAW To determine if our prototype could detect NA at industrially relevant levels, samples from three industrial sites were measured. Prior to fluorescence measurements, samples were filtered for particles larger than 450 nm. Concentration of NA in the filtered PAW was determined using Fourier-transform infrared spectroscopy (FTIR), which required additional sample preparation using a process similar to that outlined by Jivraj et al. (1995). FTIR sample preparation starts with 500 mL of filtered PAW; sample pH is raised to 11.5 by adding NaOH. Subsequently, 25 mL of dichloromethane (DCM) is added to the sample. The sample is shaken, and the DCM is drained. This entire process is repeated three times. The sample’s pH is then lowered to 2 by adding HCl; and rinsed three times with 25 mL of DCM. The DCM is allowed to evaporate overnight, and NA residue is collected on the beaker. The residue is collected by adding 30 mL DCM to the beaker, and then measured in the FTIR. To determine concentration the 1706 cm

−1 and 1743 cm

−1 peak

heights are measured and combined. The FTIR is calibrated using commercially available NA (Sigma Aldrich), rather than petroleum-derived NA. To produce samples at different concentrations filtered PAW samples were diluted with deionized. The fluorescence from each sample was measured at each excitation wavelength. The quartz cuvettes used to hold the samples were triple rinsed with deionized water between measurements. Integration time was 5 seconds, and 5 averages were used for a total measurement time of 25 seconds. Background removal was as described above. For each spectrum, the NA fluorescence peak was fit with a skew Gaussian distribution. The peak was numerically integrated to calculate total signal strength. Noise was estimated from the standard deviation of pixel-to-pixel variation in an adjacent region of the spectrum with no features. The signal-to-noise ratio (SNR) is defined as

€

SNR =S λ( )dλ∫

σ Nchannels

[7]

Figure 5: (a) Signal-to-noise ratio as a function of NA concentration, and best linear fits to the data set. (b) Sample spectrum for 13 ppm NA in filtered PAW. The PAW peak at 340 nm is still clearly visible, even without removal of the LED signature. Excitation wavelength was 285 nm, integration time was 5 seconds, and 5 spectra were averaged. The open symbols are unfiltered samples and were excluded from the fits. where S is as defined in Eqn. 5, σ is single channel

noise, and Nchannels is the peak width. Noise is scaled to the peak width using the conventional N

1/2 from Poisson noise. The SNR for the three

different sites and an excitation wavelength of 285 nm is given in Fig. 5a. Differences are observed between different sample sources, but are linear within them. SNR is remains excellent at the 10 ppm level. NA signatures in unfiltered PAW The performance of our prototype on unfiltered samples was also tested, and the results are shown in Fig. 6. These samples were cloudy,

Figure 6: Fluorescence signature of NA in unfiltered PAW from (a) Albian, (b) Suncor and (c) Syncrude. The NA peak is clearly visible in all samples, even without removing the LED signature. This indicates that the prototype can be successfully applied in the field with little or no sample preparation. The features above 500 nm are leaked room light. indicating significant scatter in the visible wavelengths. However, despite increased scattering, the NA signature can be clearly

observed in the unfiltered samples for all three industrial sites. This is a promising result, as it indicates that the prototype can measure samples obtained from the field with little or no preparation.

Discussion We have developed a field portable LED-based fluorescence spectrometer that can measure NA at industrially relevant levels. Although this initial result is promising, we feel that there are significant improvements that can be made to enhance its performance, and greatly reduce its size. The following is a discussion of alternative techniques for NA detection and opportunities for improving performance of our prototype. In general, the tradeoff is between ease-of-use and/or measurement time and performance. For example, laser-induced fluorescence (LIF) routinely achieves LOD in the ppb range, but requires high power lasers. There is a broad literature on LIF for hydrocarbon detection in water (Kenny et al., 1987; Taylor et al., 1993; Filippova et al., 1993; Lewitzka et al., 1999). The performance is excellent, but high-powered lasers are not well-suited for field use, and are certainly not portable. Several standard chemical techniques have been applied to detection of NA in water, including gas chromatography mass spectroscopy (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) (Scott et al., 2008), capillary high-performance liquid-chromatography quadrupole time-of-flight mass-spectroscopy (HPLC/QTOF-MS) (Bataineh et al. 2006) and synchronous flourescence spectroscopy (SFS) (Kavanagh et al., 2009). Scott et al. (2008) have compared GC-MS and FTIR for quantifying NA concentrations, and found that GC-MS is about 100 times more sensitive with a LOD of 10 ppb. Moreover, Scott et al. (2008) report that FTIR consistently reports a higher concentration that GC-MS, although the ratio varies with sample source. This result is troubling for the calibration of our instrument, and other work that depends on FTIR. It was already clear from the LOD work presented above that discrepancies exist between the concentration reported by the FTIR and the fluorescence intensity reported by our instrument, as seen in Fig. 5. When considered in combination with the observations of Scott et al. (2008), it is clear that obtaining additional calibration standards should be a priority. Despite these issues, the factor reported by Scott et al. suggests that the

performance of our prototype is better than that reported here. It is possible that the performance reported here will improve, pending additional investigations. Bataineh et al. (2006) have developed an HPLC/QTOF-MS technique for characterizing NA and studying biological remediation. They report excellent absolute detection limits in the pg range. The technique is also capable of NA speciation by carbon number and Z-series, and should lead to a better understanding of NA toxicity and the efficacy of the different NA remediation techniques. However, significant sample preparation is required to achieve the performance reported by Bataineh et al., and is not well suited to field use. From the perspective of a field instrument, more promising is the comparison of our instrument with the lab based work by Kavanagh et al. (Kavanagh et al., 2009). While the LOD from Kavanagh’s work is not clear, they report signals down to a few mg L−1

. The performance of our prototype is in the same range, and we expect improvements are possible. While the other techniques can achieve significantly better performance than our prototype, none of them are well-suited for field use, and all of them require sample preparation. Here we have demonstrated a prototype instrument that detects NA in water at the ppm level, with little or no sample preparation. Moreover, several opportunities exist for improving the performance of our instrument in future versions. Inspection of Eqn. 4 and Eqn. 5 suggests two avenues for improving performance: increased power on target (Etarget) and increased luminosity (L). It is clear from our model and the results presented in Fig. 2 that the only method for increasing signal levels it to increase Etarget; the other parameters, η and α are physical constants

of the analyte. Optical power can be improved by increasing the number of LEDs in the system, or by waiting for increased power in a LED package - doubling time for LED power is approximately 2.3 years (Steele, 2007). The other route to improved performance is to increase the luminosity of our system through increased f-number or aperture size. Both should be possible with improved optical design.

Conclusion Monitoring the presence and migration of NA in PAW is desirable for environmental and economic reasons; reducing the potential for toxic releases and improving the lifetime of oil sands industrial plants, respectively. We have developed a field portable LED-based fluorescence spectrometer that can measure NA below the 10 ppm level. Our prototype uses LED wavelengths between 265 nm and 340 nm as an excitation source, and a compact CCD Ocean Optics spectrometer as a detector. Although other techniques can achieve better limits of detection, our instrument is field-portable, and capable of measuring NA in PAW without sample preparation. In addition to this initial promising result, through development of an optical theory for our device we have identified several feasible routes to improving performance of our instrument in future versions.

Acknowledgements The authors gratefully acknowledge Professor Michael Brett of the University of Alberta and the NRC National Institute for Nanotechnology for valuable discussions. In addition, we gratefully acknowledge funding from the Natural Sciences and Engineering Research Council of Canada (NSERC), the Oil Sands Tailings Research Facility (OSTRF), the Canadian Institute for Photonics Innovations (CIPI), the Canada School of Energy and Environment (CSEE), Alberta Innovates Technology Futures (AITF) and the Integrated Nanosystems Research Facility at the University of Alberta.

REFERENCES Alarie, J., T. Vo-Dinh, G. Miller, M. Ericson, D.

Eastwood, R. Lidberg, M. Dominguez (1993). Development of a battery-operated portable synchronous luminescence spectrofluorometer. Rev. Sci. Instrum., 64:2541– 2546.

Allen, E. W. (2008). Process water treatment in

Canada’s oil sands industry: I. Target pollutants and treatment objectives. J Environ Eng Sci, 7:123–138.

Baird, W., N. Nogar (1995). Compact, self-

contained optical spectrometer. Applied Spectroscopy, 49:1699– 1704.

Bataineh, M., A.C. Scott, P.M. Fedorak, J.W. Martin (2006). Capillary HPLC/QTOF-MS for Characterizing Complex Naphthenic Acid Mixtures and Their Microbial Transformation. Analytical Chemistry 78: 8354 - 8361

Brown, L. D., M. Alostaz, A. C. Ulrich (2009).

Characterization of Oil Sands Naphthenic Acids in Oil Sands Process-Affected Waters Using Fluorescence Technology. In 62nd Canadian Geotechnical Conference, Halifax, Nova Scotia, 1–7.

Clemente, J., P. Fedorak (2005). A review of the

occurrence, analyses, toxicity, and biodegradation of naphthenic acids. Chemosphere, 60:585–600.

Filippova, E., V. Chubarov, V. Fadeev (1993). New

possibilities of laser fluorescence spectroscopy for diagnostics of petroleum-hydrocarbons in natural-water. Can J Appl Spectrosc, 38:139–144.

Frank, R. A., K. Fischer, R. Kavanagh, B. K.

Burnison, G. Arsenault, J. V. Headley, K. M. Peru, G. V. D. Kraak, K. R. Solomon (2009). Effect of Carboxylic Acid Content on the Acute Toxicity of Oil Sands Naphthenic Acids. Environ. Sci. Technol., 43:266–271.

Hart, S., R. JiJi (2002). Light emitting diode

excitation emission matrix fluorescence spectroscopy. Analyst, 127:1693–1699.

Jivraj, M., M. Mackinnon, B. Fung (1995).

Naphthenic Acid Extraction and Quantitative Analysis With FT- IR Spectroscopy. In Syncrude Analytical Manuals, 4th Edition, Research Department, Syncrude Canada Ltd., Edmonton, AB.

Kavanagh, R. J., B. K. Burnison, R. A. Frank, K. R.

Solomon, G. V. D. Kraak (2009). Detecting oil sands process-affected waters in the Alberta oil sands region using synchronous fluorescence spectroscopy. Chemosphere, 76:120–126.

Kenny, J., G. Jarvis, W. Chudyk, K. Pohlig (1987).

Remote laser-induced fluorescence monitoring of ground- water contaminants: prototype field instrument. Instrumentation Science & Technology, 16:423–445.

Lewitzka, F., U. Buenting, P. Karlitschek, M. Niederkrueger, G. Marowsky (1999). Quantitative analysis of aromatic molecules in water by laser-induced fluorescence spectroscopy and multivariate calibration techniques. Proceedings of SPIE, 3821:331.

Obeidat, S., B. Bai, G. D. Rayson, D. M. Anderson,

A. D. Puscheck, S. Y. Landau, T. Glasser (2008). A multi-source portable light emitting diode spectrofluorometer. Applied Spectroscopy, 62:327–332.

O’Hagan, A., T. Leonard (1976). Bayes estimation

subject to uncertainty about parameter constraints. Biometrika, 63:201–203.

Patra, D., A. Mishra (2002). Total fluorescence

quantum yield and red shift of total fluorescence maximum as parameters to investigate polycyclic aromatic compounds present in diesel fuel. Spectroscopy Letters, 35:125–136.

Scott, A. C., R. F. Young, P. M. Fedorak (2008).

Comparison of GC-MS and FTIR methods for quantifying naphthenic acids in water samples. Chemosphere, 73:1258–1264.

Slavcheva, E., B. Shone, A. Turnbull (1999).

Review of naphthenic acid corrosion in oil refining. Brit Corros J, 34:125–131.

Steele, R. V. (2007). The story of a new light

source. Nat Photonics, 1:25–26. Taschuk, M.T., Y. Godwal, Y.Y. Tsui, R.

Fedosejevs, M. Tripathi, B. Kearton (2008). Absolute characterization of laser-induced breakdown spectroscopy detection systems. Spectrochim Acta B, 63:525–535.

Taylor, T., G. Jarvis, H. Xu, A. Bevilacqua, J.

Kenny (1993). Laser-based fluorescence EEM instrument for in-situ groundwater monitoring. Instrumentation Science & Technology, 21:141–162.