Manish Gupta This email address is being protected from spambots. You need JavaScript enabled to view it., Andrew P. Chan, Michael N. Sullivan, Rupal M. Gupta

Nikira Labs Inc., Mountain View, CA 94043, USA


Received: January 27, 2022
Revised: June 13, 2022
Accepted: July 18, 2022

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.220046  

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Cite this article:

Gupta, M., Chan, A.P., Sullivan, M.N., Gupta, R.M. (2022). Trace Measurements of Ethylene Oxide Using Cavity-enhanced Absorption Spectrometry near 3066 cm–1. Aerosol Air Qual. Res. 22, 220046. https://doi.org/10.4209/aaqr.220046


HIGHLIGHTS

  • Mid-infrared laser analyzer to detect trace levels of ethylene oxide.
  • New fit function to account for ambient absorption.
  • Real-time ethylene oxide measurements with ±1 ppb (1σ, 60 s) precision.
  • Used to measure deliberate ethylene oxide releases in ambient air.
 

ABSTRACT


Ethylene oxide (EtO) is a key carcinogen that is widely used in the chemical manufacturing and biotechnology industries. Recent work has suggested that permissible exposure limits for EtO be reduced from 1–5 ppm to sub-ppb levels. Such new standards will require new methodologies that are capable of measuring EtO with the requisite precision. In this paper, we demonstrate a new analyzer based on cavity-enhanced absorption spectrometry that utilizes a broad EtO absorption feature near 3066 cm–1. A fit function is developed that includes water, methane, and EtO absorbances and accounts for absorption both inside and outside the cavity. A methane standard is used to determine the cavity gain factor, and the EtO absorbance spectrum is empirically determined. The final system shows excellent linearity from 0–909 ppb EtO (R2 ~0.9999) with a measurement precision of better than ± 1 ppb (1σ, 60 seconds) that improves to ± 0.5 ppb (1σ, 15 minutes). Deliberate ambient EtO releases demonstrate the instrument’s utility in rapidly detecting hazardous conditions. Further work will include improving the measurement precision and directly comparing the system to EPA Method TO-15.


Keywords: Ethylene oxide, Cavity ringdown, ICOS, EtO


1 INTRODUCTION


In 2018, 2.92M metric tons of ethylene oxide (EtO) was produced in the United States (ACC, 2019). Most of this EtO was used as an intermediate chemical to produce glycols, ethoxylates, and ethanolamines. Additionally, it was also used in medical sterilization and the food industry. It has long been known that EtO is a carcinogen (Hogstedt et al., 1986; Shore et al., 1993), and the Occupational Safety and Health Administration (OSHA) has set permissible 8-hour and 15-minute exposure limits of 1 ppm and 5 ppm respectively (OSHA Standard 1910.1047; OSHA, 1971). After an extensive review of the available data, the U.S. Environmental Protection Agency (U.S. EPA) Integrated Risk Information System (IRIA) program concluded (U.S. EPA, 2016a, 2016b) that the “…confidence in the hazard characterization of EtO as ‘carcinogenic to humans’ is high.” Using this data, the EPA has assigned a total cancer unit risk (inhalation unit risk) estimate for EtO of 3.3 × 10–3 µg m3 (~12 ppt), though recent studies (Vincent et al., 2019; Haney et al., 2020) suggests that this unit risk estimate may be too low and a value of ~2 ppb may be more appropriate.

These new standards will require new measurement technologies. Currently, EtO is measured via EPA Methods (U.S. EPA, 1999; Ambient Air Monitoring Group EPA/OAQPS/AQAD, 2019), TO-15 and TO-15A. Briefly, a discrete air sample is captured in a Summa canister (or similarly coated container) and shipped to a laboratory for analysis. The canister contents are directed through a solid adsorbent which preconcentrates the volatile organic compounds (e.g., EtO) as well as some common air constituents (e.g., CO2). Cryogenic cooling is then used to remove most of the CO2 prior to compound separation via a gas chromatography column. Finally, the EtO concentration is measured via selective ion or scanning mass spectrometry.

Though this method is extensively used, it has several limitations that make it difficult to address the emerging EPA need to measure low ppt-levels of EtO. Foremost, EtO is typically characterized by its major m/z peaks at 44 and 29, which are confounded by CO2 and other co-eluting species (e.g., trans-2-butene, acetaldehyde, and others) respectively. This limitation can be partially overcome by minimizing leaks, using a longer column, and exploiting other m/z peaks at 15, 41–43 and 56; however, this reduces the sensitivity of the analysis, making it unable to quantify low levels of EtO. An extensive study (Eklund et al., 2004) of ethylene oxide monitoring using U.S. EPA Method TO-15A showed that Summa canister samples filled with dry nitrogen are stable for up to 15 days and can provide EtO detections limits of 0.25 ppb, which is approximately 10–20 times higher than the EPA targets noted above. Moreover, EtO production was observed in blank canisters filled with humid air at 50% relative humidity (Hoisington and Herrington, 2021). Though mitigated by an extensive cleaning procedure, this production mechanism produced 0.5–1 ppb of EtO in a standard canister in 1–2 weeks of storage. In addition to sensitivity, cross-interference, and storage issues, EPA Method TO-15 requires the acquisition and transport of discrete air samples. Thus, the measurement is not real-time or continuous and may not be representative of actual, average EtO concentrations. Finally, as described above, accurate and sensitive EtO analysis requires extensive infrastructure and expertise, making it more complex and expensive.

There are several alternatives to EPA Method TO-15 that provide real-time EtO measurements, including EPA Methods TO-18, 320, and 25A that use online gas chromatography, Fourier Transform Infrared (FTIR), and flame ionization detection respectively. However, all these methods suffer from limited sensitivity and cross-interference (Shappley and Yelverton, 2019). Recently, near-infrared cavity ringdown spectroscopy has been used to quantify EtO at the ppb-level (Lucic et al., 2021), and this method may prove to useful for source monitoring.

In this paper, we present an ethylene oxide analyzer based on cavity-enhanced absorption spectrometry near 3066 cm–1 that is capable of making real-time measurements with sub-ppb precision. Previously, high-resolution FTIR spectra of ethylene oxide (Sharpe et al., 2004; Johnson et al., 2004) show strong absorption features near 3060 cm–1 and 1270 cm–1; however, tunable diode laser absorption spectrometry has only been used (Lytkine et al., 2010) near 5907 cm–1. This latter work showed a precision of 17 ppm (1σ) using a 63.5 cm cell and extrapolated to a measurement precision of 30 ppb assuming a much longer pathlength (100 meters) and 10× reduction in noise using wavelength modulation spectroscopy. In this work we achieve a measurement precision of better than ± 1 ppb (1σ, 60 seconds) by using a substantially stronger absorption feature and a high-finesse cavity to provide a very long effective pathlength.

 
2 METHODS


 
2.1 Experimental Setup

The experimental setup is shown schematically in Fig. 1. A 25 mW distributed feedback DFB diode laser with incorporated TEC operating near 3066 cm–1 (3262 nm) with a linewidth of ~3 MHz (0.0001 cm–1) at 6°C (Nanoplus GmbH) is mounted onto a heatsink and collimated using an AR-coated asphere (NA = 0.56) mounted on an x/y/z stage. The collimated beam is directed into a high-finesse optical cavity comprised of two highly-reflective, 1-inch diameter mirrors (R > 99.8% at 3066 cm–1, LayerTec GmbH). In order to minimize coherent interferences within the cavity, the cavity is intentionally misaligned, and the laser beam is slightly defocused akin to Integrated Cavity Output Spectroscopy (ICOS) (O’Keefe, 1998) and off-axis ICOS (Baer et al., 2002). The mid-infrared DFB diode laser was repeatedly tuned over 4 cm–1 by varying its injection current from 0–150 mA at a rate of 8 kHz. 8000 transmission spectra were averaged prior to analysis, yielding an analyzer data reporting rate of 1 Hz.


Fig. 1. Schematic overview of experimental setup.Fig. 1. Schematic overview of experimental setup.

Light transmitted through the cavity is focused by an AR-coated, f/1 silicon asphere, passed through an optical filter, and directed onto a thermo-electrically cooled InAsSb detector (Thorlabs). The detector is AC-coupled and provides a gain of 10000 V/A, a responsivity of ~1.2 A/W at 3263 nm, and a bandwidth of 100 kHz. Note that, due to the low bandwidth of the system, the effective optical pathlength of the cavity cannot be determined by cavity ringdown measurements (O’Keefe and Deacon, 1988). Instead, fits to a known absorption are used to determine the cavity gain factor as described below.

In an ideal incoherent cavity enhanced absorption spectrometry system, approximately I0 × T/2 milliwatts of light transmit through the cavity, where I0 = 25 mW is the incident laser power and T ~0.1% is the mirror transmission (T ~1–R). Thus, in an ideal situation, ~12 μW of laser light would be focused onto the detector, resulting in a peak signal of ~140 mV. However, due to large losses in the mirror coatings (e.g., absorption and scatter coatings), the measured detector signal is only a few mV. To avoid limiting the system performance by bit-noise in the data acquisition system, the detector signal is passed through a 10 kW terminator and into an inverting amplifier with a gain of 200. The amplifier output is digitized by a custom data acquisition board at 4 MS s1 and collected by a computer. The data acquisition board also provides a voltage ramp with a 90% duty cycle that is connected to a laser driver (Thorlabs) that controls the laser current and temperature.

The gas samples are generated by a programmable permeation oven (VICI Metronics) containing an ethylene oxide permeation tube that provides a permeation rate of 1799 ng min1 at 45°C. Different gases can be flowed through the permeation oven, including nitrogen, SCUBA air, ambient air (pushed by a small diaphragm pump), and 80 ppm CH4/N2. The pressure in the cavity is measured by a Baratron pressure gauge (MKS). In order to control the pressure in the cavity and maintain it at ~500 Torr, the upstream permeation oven flow rate is set, and gas is pulled through the cavity using a 3-head diaphragm vacuum pump (KNF) whose flow rate is manually controlled by a needle valve.

 
2.2 Data Analysis

Simulated spectra of probe region are shown in Fig. 2 for a gas sample containing 1% water vapor, 4 ppm methane, and 1 ppm ethylene oxide. The former was simulated using HITRAN parameters (Rothman et al., 2009), whereas the latter two species used data tabulated by Pacific Northwest National Laboratory (PNNL) (Sharpe et al., 2004). Note that the entire PNNL and HITRAN databases were surveyed, and no other compounds were found to have absorptions exceeding 0.0002 for 1 ppm compound in a 1-meter pathlength (1/100th the optical depth of ethylene oxide). Critically, carbon dioxide does not optically absorb in region as confirmed by both the HITRAN and PNNL spectral databases. Thus, we anticipate that the data analysis routine only needs to include water vapor, methane, and ethylene oxide.

Fig. 2. Simulated absorption spectra of water vapor (blue), methane (orange), and ethylene oxide (green) in the spectral probe region. Note that no other compounds in the PNNL database were found to absorb in this region.Fig. 2. Simulated absorption spectra of water vapor (blue), methane (orange), and ethylene oxide (green) in the spectral probe region. Note that no other compounds in the PNNL database were found to absorb in this region.

A sample measured cavity-enhanced transmission spectrum of ambient air containing ~1.5% water vapor and ~2 ppm methane is shown in Fig. 3. Each data point represents 0.25 μs, commiserate with the sampling rate. Initially, from datapoints 10–180, the laser is off and the detector is measuring its baseline offset. From datapoints 180–980, the laser current is being increased from 31–156 mA. This increase in current results in an increase in power and a change in laser frequency by approximately 4 cm–1, with increasing current resulting in decreasing frequency. Superimposed on this increasing laser intensity are absorption features due to the compounds shown in Fig. 2. Since ambient air contains very little ethylene oxide (< 1 ppb), the observed absorption features are due to water vapor and methane. 

Fig. 3. Raw measured detector signal (black) with 500 Torr of ambient air in the cavity corrected for an offset value and fit Eq. (1) as (red) described in the text. The sampling rate is 4 MHz (0.25 μs datapoint–1) and 8000 spectra were averaged over 1 second.
Fig. 3.
 Raw measured detector signal (black) with 500 Torr of ambient air in the cavity corrected for an offset value and fit Eq. (1) as (red) described in the text. The sampling rate is 4 MHz (0.25 μs datapoint1) and 8000 spectra were averaged over 1 second.

After subtracting the detector offset, the transmitted intensity, I, is fit to:

 

where x is the datapoint (equivalent to the time axis), P is the partial pressure of the indicates species, I0(x) is the transmitted intensity in the absence of all absorption (approximated by a 2nd order polynomial), G is the cavity gain factor, ODoutside is the optical depth due to ambient air absorption of water and methane outside the cavity, and ODinside is the optical depth due to sample absorption inside the cavity. Eq. (1) is a combination of the Beer-Lambert-Bouguer Law and the absorption equation for cavity-enhanced absorption spectrometry (Baer et al., 2002). For water vapor and methane, the optical depth as a function of frequency, f, is expressed using the standard HITRAN formulation. For example, for methane, OD(f) is given as:

 

where N is a function of temperature, T, and is 2.479e19 × 296/T, L is the relevant pathlength, Si is the linestrength of the ith tablulted line, LW is the Lorentz width of the feature, and DW is the Doppler width of the feature (function of total pressure and temperature). A similar expression is used for water vapor. All tabulated line parameters (line frequencies, line strengths, broadening coefficients…) are taken from the HITRAN database. OD(f) for ethylene oxide is determined by measuring the basis set as described below. The total optical depth is then expressed as the sum of all components.

Since optical depth is expressed as a function of frequency and the measured intensity is a function of datapoint, the etalon function is approximated as:

 

where en are coefficients determined from the fit. Note that, though the actual laser tuning curve is more complex, it can be well approximated by a 2nd-order polynomial over a small tuning range. A more accurate measure of f(x) can be obtained by measuring the laser transmission through a germanium etalon of known length. This method may be employed in the future to further characterize the laser tuning curve.

Using this fit function, the gas temperature, gas pressure, and pathlength outside the cavity are fixed, whereas the species’ partial pressures, baseline coefficients, and etalon coefficients are floated. The cavity gain factor is measured as described below and then fixed for all subsequent analyses.

In order to limit computational overhead, a subset of the HITRAN database is used to obtain the tabulated parameters. This subset spans from 3061–3071 cm–1 and only includes water and methane lines with line strengths greater than 1024 cm molecule–1 and 1022 cm molecule–1 respectively.

 
2.3 Determination of the Cavity Gain Factor

The cavity gain factor, G, is typically determined from the mirror reflectivity, R:

 

This reflectivity is usually measured via cavity ringdown spectroscopy on the empty (or nitrogen-filled) cell. However, due to the limited bandwidth of the detector (100 kHz), the cavity gain factor was determined by measuring dilutions of an 80 ppm CH4/nitrogen standard from 0–7.3 ppm. The measured methane concentration (ppm) was then compared to the actual methane concentration and the gain factor was adjusted to yield a slope of ~1. Using this method, we obtained highly linear results with a slope of 0.999 and an intercept of –0.011 by using a gain factor of 740 (Fig. 4). This suggests mirror reflectivity R ~99.86%, consistent with the manufacturer’s indication that R > 99.7 %.

Fig. 4. By adjusting cavity gain factor to 740, the actual versus measured methane concentration yielded a slope of ~1 and an intercept of ~0.Fig. 4. By adjusting cavity gain factor to 740, the actual versus measured methane concentration yielded a slope of ~1 and an intercept of ~0.

 
2.4 Measuring and Incorporating the Ethylene Oxide (EtO) Basis Set

Unlike water and methane, ethylene oxide absorption features are not in the HITRAN database. They have been measured and disseminated by Pacific Northwest National Laboratory (PNNL) (Sharpe et al., 2004); however, the FTIR resolution of 0.125 cm–1 is insufficient for the high-resolution laser spectrometry presented here. Therefore, measurements of 500 Torr dry nitrogen and 500 Torr of 475 ppb EtO/N2 were used to construct the EtO absorption basis set. The measured dry nitrogen transmission spectrum was fit to Eq. (1) to determine I0(x). The cavity-enhanced EtO absorbance, AE, was then determined as:

 

where IE and IN2 are the measured transmission spectra with and without EtO respectively. Finally, a spectrum of ambient air with no EtO was measured and fit to determine the etalon function, f(x). Combining these measurements and smoothing the resulting absorbance spectrum with a 3rd-order Savitzky-Golay filter (boxsize = 41 points) to minimize noise yielded the EtO basis set shown in Fig. 5. Note that the data, which has been scaled to represent the absorption of 475 ppb EtO in a 1-meter pathlength, is in good agreement with the PNNL results, but slightly shifted in frequency.

 Fig. 5. Measured (black dots) and smoothed (red) basis set for 475 ppb EtO in a 1-meter pathlength. The published PNNL FTIR spectrum is included in green.
Fig. 5.
 Measured (black dots) and smoothed (red) basis set for 475 ppb EtO in a 1-meter pathlength. The published PNNL FTIR spectrum is included in green.

This EtO basis set, BEtO(f), was incorporated into the fit by adding an EtO term to the optical depth:

 

where CEtO is a coefficient that is linearly proportional to the EtO concentration, and the basis set was linearly interpolated at for all values of f. This methodology has been successful used to determine gas concentrations from measured basis sets (Le et al., 2008; Dong et al., 2011). As noted in these references, the basis set coefficient (CEtO) is a direct measurement of the target gas concentration. This linear relationship between CEtO and the actual concentration of EtO was determined empirically as presented below.

 
3 RESULTS AND DISCUSSION


 
3.1 Linearity and Relationship between CEtO and EtO Concentration

In order to determine the relationship between CEtO and the actual EtO concentration as well as gauge the linearity of the analyzer, the permeation oven dilution was adjusted to produce concentrations of EtO ranging from 0–909 ppb. The resulting data (Fig. 6) was fit to line with zero intercept and yielded a slope of 2064.3 with a R2 ~0.9999, suggesting that the analyzer provides a very linear response over this dynamic range. Note that the accuracy of the proportionality coefficient, CEtO, is limited by the accuracy of the permeation tube to ± 15%. 

 Fig. 6. Measured EtO coefficient (CEtO) versus actual EtO concentration from 0–909 ppb. Note that the analyzer provides a highly linear response (R2 ~0.9999) and the slope yields a conversion factor of 2064 between the measured EtO coefficient (CEtO) and EtO concentration.Fig. 6. Measured EtO coefficient (CEtO) versus actual EtO concentration from 0–909 ppb. Note that the analyzer provides a highly linear response (R2 ~0.9999) and the slope yields a conversion factor of 2064 between the measured EtO coefficient (CEtO) and EtO concentration.

 
3.2 Measurement Precision

The analyzer’s measurement precision was determined by continuously measuring a sample of 60.5 ppb EtO/air for ~8 hours. The data and resulting Allan variance are shown in Fig. 7. The Allan variance shows how the measurement standard deviation scales with measurement time (Skřínský et al., 2009). Note that the system provides a short-term precision of ± 1.7 ppb (1σ, 10 s) that improves to better than ± 0.5 ppb (1σ) with 15 minutes of averaging. In accordance with the EPA Procedure for the Determination of the Method Detection Limit (40 CFR 136), this suggests a method detection limit (MDL) of 1.5 ppb for the cavity-enhanced methodology presented here. Previous work on EPA Method TO-15 canister sampling (Eklund et al., 2004) showed a MDL of 2 ppb for a 10 ppb spike of EtO in non-dried ambient air using a similar relationship between measurement standard deviation and MDL. Ideally, the precision of the spectroscopic technique would have been measured at a lower EtO concentration; however, the minimum generatable EtO concentration of 60.5 ppb was limited by the permeation tube rate and oven dilution flow.

Fig. 7. Allan deviation plot showing the measurement precision as a function of data averaging time. The raw data is shown in the inset.Fig. 7. Allan deviation plot showing the measurement precision as a function of data averaging time. The raw data is shown in the inset.

 
3.3 Ambient Air Monitoring

Subsequent to the validation studies above, the analyzer was used to monitor ambient air in the laboratory during three deliberate ethylene oxide releases from the permeation oven. The cell inlet was disconnected from the permeation oven and sampled ambient air through a 0.1-micron Teflon membrane filter. The measured ethylene oxide values as a function of time are shown in Fig. 8, and clearly demonstrate the ability of the system to detect ethylene oxide leaks and hazards at low levels.

Fig. 8. Measured EtO concentrations in ambient air during three deliberate EtO releases.Fig. 8. Measured EtO concentrations in ambient air during three deliberate EtO releases.

 
4 CONCLUSION AND FUTURE WORK


In this contribution, we have presented the test results of a mid-infrared, cavity-enhanced analyzer capable of providing real-time, rapid (1 Hz), ppb-level measurements of ethylene oxide. The technique will enable the accurate quantification of EtO source emissions, as well as enable fast alarm level measurements in facilities that generate or use large quantities of EtO.

In order to address next-generation EtO monitoring needs, the instrument precision needs to be improved by a factor of ~10–30. The methodology presented here can be improved in several ways to approach this goal. Foremost, the one-inch diameter mirrors can be replaced by two-inch diameter mirrors. Previous work (Baer et al., 2002) has shown that this decreases the noise of cavity-enhanced absorption spectrometry by a factor of ~10 by providing better incoherent coupling. Likewise, since the system is limited by detector signal and thus requires an external amplifier, a higher power laser, reinjection (Leen and O’Keefe, 2014), and mirror coatings with less absorption/scatter should also improve the SNR of the analyzer. Finally, a DC-coupled detector may help mitigate long-term changed in baseline curvature. Note that, since water is a strong optical absorber in the spectral region, using higher reflectivity mirrors is not expected to improve the analyzer performance.

In addition to improving the instrument precision, the system accuracy may be substantially increased by using gravimetric standards or intercomparisons to EPA Method TO-15, instead of permeation tubes. In order to account for changes in temperature and pressure, the EtO basis set can be further developed under different environmental conditions and appropriately interpolated. Likewise, the linearity of the instrument should be confirmed under varying water vapor and methane concentrations. Finally, the analyzer should be deployed outside, under real-world conditions, and directly compared to EPA Method TO-15.

 
ACKNOWLEDGMENTS


We gratefully acknowledge that this work was supported by the EPA SBIR Program under contract number 68HERC21C0016. We also acknowledge Ned Shappley in providing insight into the needs and limitations of current ethylene oxide monitoring as well as helpful comments in preparing this manuscript.


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