The influence of water vapour on the determination of glutaraldehyde vapour concentrations using an electrochemical fuel cell sensor

Abstract

The effects of relative humidity (40–90% RH) and varying glutaraldehyde vapour concentrations (< 0.1 ppm) on the response of an electrochemical fuel cell sensor have been investigated over time (0–400 s). These studies have identified changes in the response of the fuel cell with time after sampling. In particular, it has been found that the maximum cell output for water vapour occurs ca. 10 s after sampling whilst the response to glutaraldehyde occurs much later (> 100 s). For mixtures containing different ratios of water and glutaraldehyde vapours, the time taken to reach maximum fuel cell response varies between 10 and 100 s, depending on the ratio of the two vapours. For instance, glutaraldehyde vapour containing higher % RH has been found to result in shorter times to reach maximum fuel cell response. A comparison was made between measuring glutaraldehyde vapour concentrations in the presence of water vapour at the maximum fuel cell response and also at a fixed interval (240 s) after sampling. Such a comparison resulted in a reduction in the standard error from 36% to 5% for a glutaraldehyde vapour sample (0.023 ppm) measured at different values of relative humidity (40 to 80%). Examination of the effect of the sample volume (30–60 ml) on the response of the fuel cell shows, as expected, an approximate doubling of the fuel cell response. Optimisation of the fuel cell measurement parameters to measure a 60 ml sample leads to a lowering of the limit of detection from 0.083 ppm (for data taken at the maximum cell response) to 0.017 ppm for data measured 240 s after sampling. In the light of recent reductions in the legal limits for exposure to glutaraldehyde, this has important implications for the measurement of glutaraldehyde vapour in the workplace.

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Introduction

Glutaraldehyde is commonly used in hospitals as a cold sterilizing agent for medical equipment that would otherwise be damaged by autoclaving.¹ The sterilisation process often involves manual washing of equipment which can expose staff to glutaraldehyde vapour. It is well known that glutaraldehyde vapour is a strong irritant of the eyes, nose, throat and skin² and, in 1996, an Occupational Exposure Standard (OES) of 0.2 ppm averaged over 15 min was set by the Health and Safety Executive in the UK.³ In January 1998, this OES for glutaraldehyde was withdrawn and a new glutaraldehyde limit of 0.05 ppm was put in place.⁴ Importantly, this was set as a maximum exposure limit (MEL) indicating that the glutaraldehyde vapour concentration should be kept as low as reasonably possible and always below the MEL. This represented a major change for UK legislation. The lowering of the allowable vapour concentration combined with the fact that this is effectively a threshold limit means that a rapid, accurate and precise method of determining glutaraldehyde vapour concentrations is essential for future glutaraldehyde monitoring in the workplace.

Currently, there are four methods commonly used for workplace glutaraldehyde vapour monitoring. Two of these methods involve pumping fixed gas volumes through an absorbent material followed by chromatographic analysis. For instance, silica gel can be used as an absorbent followed by gas chromatography (FID).⁵ The second example of this type of method involves derivatisation of glutaraldehyde on a 2,4-dinitrophenylhydrazine (DNPH) impregnated cartridge followed by HPLC (UV detection).⁶ A further example also involves derivatisation by DNPH which is impregnated on an absorbent fitted in a badge and this method operates on the principle of passive sampling.⁷ A comparison of these methods shows that whilst the first two procedures give detection limits of 0.005 ppm and 0.004 ppm for 15 min samples at 1 L min⁻¹(below the current UK and US OES values), they only provide time weighted average (TWA) data.⁸ A similar situation exists for the DNPH impregnated badge (limit of detection, LOD, is 0.03 mg m⁻³ or 0.007 ppm for 15 min sample). All of these methods require subsequent laboratory analysis of the glutaraldehyde itself or its DNPH derivative. In practice, the results of this analysis are only available at least 24 h after sampling is complete. This means that none of these methods are suitable for measuring the UK or US threshold limit values that are currently the legal standards for glutaraldehyde vapour.

By comparison, the measurement of alcohols and aldehydes using electrochemical fuel cell sensors can provide almost instantaneous measurements and this technology has been widely and successfully applied to ethanol vapour determination in particular.^9,10 This type of sensor is, therefore, important in the context of workplace glutaraldehyde monitoring as it has been recommended that the shortest sampling time possible should be used to meet the requirements for monitoring a threshold limit value.¹¹

It has been reported that fuel cell (amperometric gas sensor) detectors can show selectivity for alcohols and aldehydes over ketones, ethers, carboxylic acids and hydrocarbons.¹² Selectivity is of particular importance when working at very low concentrations of target analyte where the fuel cell response may become vulnerable to the influence of one of the components of fuel cell such as the electrolyte solution. Water vapour, which ironically is also essential to fuel cell operation, is the most important example of such a species. We have therefore studied the effects of relative humidity (%RH) on the fuel cell response at a range of glutaraldehyde concentrations and over time. The influence of changing sample volume has also been investigated. Optimisation of the measurement parameters has shown that the effects of relative humidity on glutaraldehyde vapour determination using fuel cell technology can be significantly reduced and a new limit of detection has been determined

Experimental

A series of experiments were carried out with the aims of (i) studying fuel cell response against time whilst varying relative humidity in the presence of a fixed glutaraldehyde vapour concentration, (ii) studying fuel cell response against time whilst varying relative humidity and glutaraldehyde vapour concentration and (iii) the effect of varying the sample volume on fuel cell response. The data from these experiments was then used to optimise the measurement parameters for the fuel cell and a new limit of detection was measured for this sensor.

A Glutaraldemeter Mark 3 hand-held sensor (PPM Ltd.) was used for all experiments. Fig. 1 shows a schematic diagram of the fuel cell within the sensor (Lion Laboratories) which consisted of a Pt black electrode deposited onto the surface of porous PVC supports. Two of these supports were then sandwiched back to back and the porous PVC impregnated with sulfuric acid (6 mol dm⁻³). Measured volumes of the standard atmospheres of gas generated using a flow line were passed over the fuel cell. The output from the fuel cell was converted to digital signal, amplified and transferred into a text file on a personal computer. The output of the fuel cell was then plotted as arbitrary units against time.

Fig. 1 Schematic diagram of the fuel cell detector.

Fig. 2 shows a schematic diagram of the vapour generator used to produce standard atmospheres. Air (flow rate ca. 600 ml min⁻¹) was first passed through an activated carbon column (Omnifit) to remove any potential VOC impurities then through a column containing molecular sieves (Omnifit) to remove water vapour before being split. The two resulting air flows were then passed either through Line A or Line B. For Line A, the air was passed through the two Drechsel bottles, connected in series, each containing 1000 ml of an aqueous solution of glutaraldehyde (Amresco) with a concentration ranging from 0.11 to 0.22 kg L⁻¹. For line B, the air was passed through a further Drechsel bottle containing 500 ml of deionised water. All three of these Drechsel bottles were placed in a circulating water bath held at 298 K ± 1 K. Vapours containing varying concentrations of glutaraldehyde and relative humidity were generated by varying the flow rates of air through Lines A and B.

Fig. 2 Schematic diagram of glutaraldehyde vapour generating line.

The relative humidity and glutaraldehyde concentration generated were sampled periodically to ensure consistency. Relative humidity was measured at the sample port (Fig. 2) using a hygrometer (Rotronic hygrometer A1 series). The concentration of glutaraldehyde vapour generated was measured by passing the generated atmosphere (7 L) over a 2,4-dinitrophenylhydrazine (DNPH) sorbent cartridge (Supelco) using a Buck Industrial Hygiene pump (Supelco) at a rate of 300 ml min⁻¹. The DNPH–glutaraldehyde derivative was then eluted from the cartridge using 10 ml of HPLC grade acetonitrile by gravity feed elution with a flow rate of less than 3 ml min⁻¹. At the sampling port, room temperature fuel cell exposure was studied by passing the generated atmospheres over the anode using a pump. The fuel cell was allowed to recover (ca. 5 min) to a steady state between measurements.

HPLC was carried out using a C₁₈ column (Waters; 5 µm, column dimensions were 3.9 mm x 150 mm). Analysis was carried out with an isocratic mobile phase consisting of 70∶30 acetonitrile∶water and detection was at 360 nm (Waters 486E UV detector). Calibration of the HPLC was carried out using standards prepared in house (2µg ml⁻¹ to 40 µg ml⁻¹) from glutaraldehyde 2,4-dinitrophenylhydrazone (Supelco).

Results and discussion

Standardisation of the glutaraldehyde vapour generator

Two peaks are observed in the HPLC data for the DNPH–glutaraldehyde derivatives with retention times of 3.04 and 3.47 min. These peaks arise from the cis- and trans-DNPH–glutaraldehyde derivatives. When calculating the area of the peaks for the calibration curve, the sum of the areas of these two peaks was used. This was carried out to ensure that no error is included in the graph as a result of differing cis∶trans ratios between the standards. The data show a linear relationship across the range of standards used (2 to 40 mg l⁻¹).

Effect of relative humidity

Fig. 3 shows the fuel cell response over time (0 to 300s) when it is exposed to atmospheres containing 0.023 ppm glutaraldehyde and varying amounts of water vapour. The data at 77% relative humidity show a very steep increase in response and a short time to peak (the time to reach the maximum cell output) at ca. 5 s. This is followed by a gradual decrease in cell output, reflecting oxidation of glutaraldehyde and then fuel cell recovery.

Fig. 3 Graphs (30 ml sample volume) to show fuel cell response over time for 0.023 ppm glutaraldehyde vapour as %RH varies between 47 and 77%

It is also worth noting that in the standby mode, the cell is normally short circuited (potential difference of zero between the two electrodes). Such cells produce a positive or negative response for an increase or decrease in humidity (compared with 40%) respectively. These changes are manifested by a maximum cell output after ca. 5 s. Therefore, it is safe to assume that the response shown at that time scale in Fig. 3 is due to a change in the humidity and not due to an interaction between water vapour and glutaraldehyde. The response of a fuel cell normally derives from an oxidisable fuel being supplied to one electrode with oxygen acting as an oxidant at the other. The signal observed from changes in humidity only can be attributed to a variation in the concentration of the electrolyte (through dilution and concentration). However, it is more likely that that the steady state position involves reactions that include oxygen and water. A change in humidity will certainly influence the steady state potential of one of the electrodes. This point will be discussed in more detail in the future.

It should be noted that %RH values expected in the workplace generally range from 40 to 75% RH at ca. 298 K. Furthermore, the output of the fuel cell becomes questionable when the concentration of glutaraldehyde is below 0.1 ppm. The glutaraldehyde concentration used to produce the data in Fig. 3 has been chosen for two reasons; firstly, it is below the current UK and US OES limits. Secondly, the influence of water vapour starts to dominate the time to reach maximum fuel cell output when the concentration of the glutaraldehyde vapour drops below 0.1 ppm. For instance, for a glutaraldehyde concentration of 0.2 ppm, even a high %RH does not significantly influence the response. It is only when the glutaradehyde concentration drops, for instance by a factor of ten, that significant %RH effects can be observed. The data show that the fuel cell response changes with time depending on the level of water molecules present. For instance at lower %RH (47%), there is very little response from the fuel cell at t = 10 s, reflecting the low concentration of water molecules present. The influence of %RH can be quantified by comparing the trend in the time taken to reach maximum fuel cell output for each relative humidity tested. For instance, for a relative humidity of 47%, the time to peak is 68s, moving to 39s at 63% RH and 10s at 77% RH. The shorter time to peak as the %RH increases reflects the increasing influence of water vapour on the initial fuel cell response. By comparison, the increase in “time to peak” observed by lowering %RH is ascribed to the increasing importance of the signal arising from glutaraldehyde. These factors are important for glutaraldehyde determination if the glutaraldehyde concentration is determined at the maximum cell response. The data also show that the fuel cell takes longer to recover at low %RH compared to the situation when more water vapour is present.

Fig. 3 shows an additional interesting feature in that the cell response is the same 240 s after sampling, for all the relative humidity levels between examined in this work. This implies that using the fuel cell response at ca.240 s rather than the maximum response would reduce %RH influence when measuring low glutaraldehyde concentrations.

To investigate this effect further, the fuel cell response has been measured at varying relative humidities and glutaraldehyde concentrations and the data are shown in Fig. 4. The data show two important features at around 240 s after sampling. The first is that the graphs for differing relative humidity but the same glutaraldehyde concentration do cross over, as seen in Fig. 3, showing that this feature occurs across a range of glutaraldehyde concentrations. The second is that there is an incremental increase in fuel cell response, at this cross over point, with increasing glutaraldehyde concentration. This has important implications for the fuel cell detection of glutaraldehyde vapour implying that cell response should be taken at a fixed time after sampling rather than at the maximum which is the current practice.

Fig. 4 Fuel cell response over time as the glutaraldehyde vapour concentration varies from (a) 0.023 ppm to (b) 0.035 ppm to (c) 0.047 ppm and %RH from 31 to 83%.

Effect of volume sample on glutaraldehyde vapour determination

The effect of increasing sample volume (from 30 ml to 60 ml) on fuel cell response has been investigated on the basis that, if water vapour interference can be minimized, increasing sample volume should lead to a lower limit of detection. Bearing in mind the new UK MEL of 0.05 ppm and the data from preliminary experiments, the fuel cell response was studied in the following experiments for glutaraldehyde concentrations ranging from 0.012 to 0.070 ppm whilst relative humidity was varied from ca. 40 to 90% as before. Increasing the sample volume has two effects. The first is to approximately double the maximum fuel cell response as might be expected. When a least squares regression line is fitted to the data for maximum fuel cell response to various glutaraldehyde concentrations (Table 1), treating the varying %RH values as error bars, the gradient of the line for the 60 ml data (y = 30x + 0.3, R² = 0.99) is approximately twice that of the equivalent line for the 30 ml data (y = 17x + 0.1, R² = 1.00) again as expected. A second change is that the cross over point shifts from ca. 200 s to ca.280 s with the increased sample volume (this also occurs as the glutaraldehyde concentration is lowered from 0.047 to 0.012 ppm). This suggests that the fuel cell is taking longer to recover. In order to balance the need for rapid and accurate glutaraldehyde measurements across a range of %RH and glutaraldehyde concentrations close to 0.05 ppm, a fixed time measurement taken at 240 s has been compared with maximum fuel cell response.

Table 1 Cell outputs, for 60 ml sample volume, at the maximum fuel cell response and at 240 s after sampling for a range of relative humidities and glutaraldehyde vapour concentrations

Glutaraldehyde concentration(ppm)	Temp./K	%RH	Maximum fuel cell response			Cell output after 240 s
			Time to reach cell output/s	Cell output(arbitary units)	Average cell output ± standard error (% error)	Cell output(arbitary units)	Average cell output ± standard error (% error)
		66	48	1.599	1.713 ± 0.114 (6.7%)	0.894	0.908 ± 0.014 (1.5%)
0.047	298 ± 0.3	74	42	1.724		0.912
		80	37	1.815		0.917
		51	60	1.104	1.303 ± 0.255 (19.6%)	0.678	0.711 ± 0.033 (4.6%)
0.035	298 ± 0.3	60	51	1.248		0.727
		81	27	1.558		0.728
		40	78	0.671	0.972 ± 0.247 (35.7%)	0.484	0.509 ± 0.025 (5.0%)
0.023	298 ± 0.3	60	45	0.928		0.514
		81	18	1.319		0.530
		42	95	0.362	0.672 ± 0.436 (64.9%)	0.303	0.318 ± 0.015 (4.7%)
0.012	298 ± 0.3	59	38	0.548		0.324
		81	13	1.108		0.328

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Table 1 shows the readings taken at the maximum fuel cell response and that which occurs at a fixed time after sampling (240 s). The data show that the maximum fuel cell response occurs at different times after sampling depending on the varying proportions of water or glutaraldehyde vapour present. For instance, the greater the %RH the shorter the time period to reach maximum output, implying that the output consists of a greater proportion of water vapour influencing the fuel cell output, rather than glutaraldehyde. This effect becomes more pronounced as the glutaraldehyde concentration decreases as expected. Table 1 also shows the mean and standard error calculated from maximum cell output for a range of %RH at each glutaraldehyde concentration. The data show an increasing percentage error as the glutaraldehyde concentration drops (7% at 0.047 ppm compared to 65% at 0.012 ppm). By comparison, the output at 240 s reflects a greater contribution from glutaraldehyde with incremental increases in cell output observed for increasing glutaraldehyde concentration but much smaller errors associated with varying %RH (only 5% at 0.012 ppm). These data indicate that it is possible to reduce measurement interference effects from water vapour. This is further illustrated when the background environmental concentration (BEC) for glutaraldehyde vapour determination is calculated using both data from the maximum fuel cell response (BEC = 0.05 ppm) and that at 240 s after sampling (BEC =0.006 ppm) for a 60 ml sample volume. The BEC has been calculated as the glutaraldehyde concentration corresponding to twice the blank value from the y axis. The blank value has been taken as the intercept of the y axis along a line drawn along the upper error bars of the regression line (0.44 arbitary units) for maximum fuel cell output and 0.12 arbitary units for 240 s output.

Finally, the limit of detection for the fuel cell response has been calculated as the blank plus 3σ² using standard methods.¹³ Blank values have been measured at %RH values ranging from 40 to 98%. The data show a higher blank value (0.029 ppm) and standard deviation (0.018 ppm) for the maximum fuel cell response data compared to the 240 s data (0.010 ppm and 0.002 ppm, respectively) reflecting the greater influence of water vapour in the former. The combination of these two factors gives rise to a LOD value for the maximum fuel cell response (0.083 ppm) which is greater than the current UK MEL for glutaraldehyde compared to an LOD of 0.017 ppm for the 240 s data.

Conclusions

The data presented in this work show that the response of a Pt black fuel cell exposed to water and glutaraldehyde vapour varies over time. We have also found that different responses over time are observed for the two species (water producing an earlier response than glutaraldehyde) and that this can be used to differentiate between the two chemicals when measuring the glutaraldehyde concentration. A series of experiments have shown that determining glutaraldehyde concentration 240 s after sampling minimises the influence of water vapour on the reading. By using a sample volume of 60 ml, a new limit of detection of 0.017 ppm has been determined.

The potential for reducing chemical interferences has important implications for the use of fuel cells for monitoring of VOCs. One advantage of the use of fuel cells in atmospheric monitoring is their applicability to a wide range of chemicals. However, this can also result in problems of interferences from competing compounds on the fuel cell surface. If the contribution to the fuel cell response from different species can be identified, it may be possible to extend the use of different time to peak measurements to other fuel cell sensors and, accordingly, interferences from other compounds could also be minimized.

Acknowledgements

We gratefully acknowledge the Teaching Company Directorate for funding for DLE (TCS Grant Award No. 2023) and Mr Russ Bromley for his helpful advice during the TCS programme.

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