The use of sensor arrays for environmental monitoring: interests and limitations Wilfrid Bourgeois,a Anne-Claude Romain,b Jacques Nicolasb and Richard M. Stuetz*c a
School of Water Sciences, Cranfield University, Cranfield, UK MK43 0AL. E-mail:
[email protected]; Fax: 144 1234751671; Tel: 144 1234750111 b Department of Environmental Monitoring, Fondation Universitaire Luxembourgeoise (FUL), Avenue de Longwy 185, BP6700 Arlon, Belgium. E-mail:
[email protected]; Fax: 132 63 230800; Tel: 132 63 230857 c Centre for Water and Waste Technology, School of Civil and Environmental Engineering, The University of New South Wales, Sydney NSW, 2052, Australia. E-mail:
[email protected]; Fax: 161 293138624; Tel: 161 293855944 Received 15th July 2003, Accepted 18th September 2003 First published as an Advance Article on the web 13th October 2003 Continuous, in situ monitoring of air, water and land quality is fundamental to most environmental applications. Low cost and non-invasive chemical sensor arrays provide a suitable technique for in situ monitoring. Their ability and performance under realistic conditions is discussed in this paper. Published studies report promising results despite a number of limitations that are associated with both the technology itself and its application in ever changing ambient conditions. Early investigations include the analysis of single substances as well as odour and wastewater organic load monitoring. Reported applications typically highlight the sensitivity of the currently available sensors to changes in temperature, humidity and flow rate. Two types of approaches are recommended to deal with these effects: either working under fixed experimental conditions or measuring the external parameters to numerically compensate for their change. The main challenge associated with the use of non-specific sensor arrays lies in establishing a relationship between the measured multivariate signals and the standards metrics that are traditionally used for quality assessment of gas mixtures. For instance, odour monitoring requires calibration against olfactometric measurements while investigations of wastewater samples still need to be correlated with organic pollution parameters such as BOD, COD or TOC. On the other hand, results obtained in the field have demonstrated how sensor arrays can be readily used as simple alarm devices or as early warning systems based on a general air/water quality index.
presented which illustrate some of the practical and technical limitations of sensor arrays for environmental monitoring.
1. Introduction Non-specific sensor arrays (electronic noses) that can detect and recognize both simple and complex gas mixtures have been commercially available since the mid-1990’s1 and have initially been applied to the food and drink industry. More recently, environmental monitoring has become an area of growing interest for electronic nose manufacturers. As public awareness of environmental issues rises and governments take on international commitments to reduce emissions, many industries are now faced with tighter tolerance margins and a rising demand for rigorous quality criteria. As a result, instrument manufacturers have sought to provide suitable environmental monitoring solutions. Although original work carried out with laboratory-based systems and more recent field investigations have shown promising results and a great potential, the number of trials carried out under realistic conditions is relatively limited. As a result, the application of sensor arrays to environmental monitoring remains particularly challenging. It appears that despite the versatility and potential for noninvasive, on-line implementation of electronic noses, the technology has yet to be embraced by the end-user and reported examples of real-size commercial applications are still relatively few. Consequently there is a case for environmentally relevant studies to be reviewed. Likewise, a number of practical and fundamental issues remain to be addressed before sensor array systems eventually become widely accepted. This paper aims to discuss the specific challenges associated with a range of environmental applications. Reported attempts that have used electronic nose technology are reviewed and examples are 852
2. Environmental monitoring requirements In the rapidly developing field of environmental monitoring, the advancement of increasingly sophisticated instrumentation has emerged in areas, which, traditionally, had seen little changes.2 Applications include a broad range of activities, but mainly the potentially polluting industrial installations such as those of the energy, defence, chemical, paper, food, agriculture and waste processing (landfill sites, wastewater treatment plants) industries. The diversity of sectors represented is the source of many opportunities for the environmental industry, but also in many cases, of costly method development in order to suit application-specific requirements. Table 1 shows some of the relevant characteristics that should be taken into Table 1 Requirements for environmental monitoring systems Parameter/specificity
Example
1 2 3 4 5 6 7 8 9
Qualitative/Quantitative analysis Air (gas)/Water (liquid)/Soil (solid) Chemical/Physical Continuous/Discrete On-line/Off-line, in situ/Remote Invasive/Non-invasive Controlled/Variable, Harsh/Normal Operator (e.g. hand held)/Automated Autonomous (battery)/Mains
Application type Sample type Measured property Measurement type Location of device Sampling Environment Operation Power
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DOI: 10.1039/b307905h
consideration when developing a sensing system for environmental applications. Because the need for environmental monitoring devices is generally driven by legislation, compliance with the regulatory bodies specifications and the standardised validation of new techniques is often mandatory. At the same time, independent performance accreditation is also becoming increasingly important for operators looking to optimise their pollution monitoring investments.2 With the growing number of instruments and manufacturers now, comparability and compatibility between devices are equally important considerations that could determine system success and commercial viability. Last but foremost, simplicity, rapidity, robustness, as well as size and reliability are essential qualities that have become priorities when monitoring the environment.3 Despite the increasing range and diversity of techniques currently available, continuous, on-line measurement systems remain largely limited by environmental factors, interferences, fouling problems, short lifetime and the need for chemical reagents as well as frequent calibrations.
3. The interests of sensor array to environmental monitoring New emerging technologies such as non-specific sensor arrays can, in principle, meet these requirements and provide a suitable solution to a wide range of environmental applications. For instance, in the case of odour monitoring in ambient air, there is no technique available for continuous measurement of odour nuisances and the current standard methods of odour measurements cannot be applied to on-line monitoring. Indeed, olfactometry measurements, realised by human panel,4 are not appropriate for real-time and continuous operation on site. Alternatively, chemical analysis of an odorous mixture by gas chromatography/mass spectrometry can provide specific information but they have the following disadvantages when applied to broader environmental odour measurements:5,6 – Most environmental odours are complex mixtures of components and single substance analysis may not provide a representative picture of the odour as perceived by humans – The limit of analytical detection may be higher than the threshold of smell – Interactions between different odorants and interfering background substances may lead to synergistic or antagonistic effects – They remain mostly lab-based, and relatively costly techniques. With the recent research efforts and investments, as well as the latest developments in computing technologies, so called electronic noses have become commercially available and have demonstrated their ability to discriminate between samples of various nature as well as monitor changes in quality with time. The list of potential applications of the sensor arrays and the number of system designs reported in the literature is growing, encouraged by the development of new sensor materials and the appearance of smaller, more versatile and more sensitive devices. The various types of chemical sensors commonly used for sensor arrays and their respective principles, designs and applications have been extensively described in the literature. For instance, Wolff et al.,7 presented Surface Acoustic Wave Sensors (SAW’s) as being a first choice for sensing in harsh environments. Other classes of sensors applicable to environmental studies including Bulk Acoustic Wave (BAW’s), Conducting Polymers (CP’s) and Metal Oxide Sensors (MOS) have also been reviewed,8–14 with many studies focussing on the interest and development of a particular sensor class for the detection of target environmental gases or substances such as NOx, SOx, CO, CO2, O3, H2S, NH3 and VOC’s.14–22 Recent years have also seen the appearance and
rapid development of optical-based sensor arrays which rely on the color/fluorescence change patterns obtained from an array of chemo-responsive metalloporphyrins23 or other fluorescent dyes24–27 coupled to an optical detection device. Not surprisingly these advances in sensor technology have been the key factor in the development of sensor array systems. Since totally selective sensors based on key–lock interactions do not exist for the detection of hazardous organic substances, the cross-selectivity of selected elements can be exploited in a sensor array by applying different algorithms of multicomponent analysis and pattern recognition.28 Other reasons for interest include the versatility and potential for low cost and small size devices. However, this is still a relatively new discipline, and little effort has so far been devoted to the implementation of fully operational devices for environmental applications as seen in other fields such as the foodstuff, beverages and perfumes industries. Technological progresses and the search for new markets are eventually contributing to a more widespread assessment of commercial or prototype instruments for environment-orientated studies.
4. Application of sensor arrays to environmental monitoring Analysis of single substances Early investigations related to the environment include the detection of fuel mixtures29 and oil leaks.30 In more recent studies, Sugimoto et al.,31 Ueyama et al.32 and Ogawa and Sugimoto33 reported recent progress in detecting low levels of hydrocarbons (oils, petrol) in river water samples using QCMbased devices and advanced humidity and temperature control systems. Volatile organic compounds represent an important class of air pollutant and the analysis of organic vapors using sensor arrays is now well documented. In particular compounds such as ethanol, propanol, butanol, acetone, toluene, benzene, xylene, n-octane, methane, cyclohexane, trichloromethane, tetrachloromethane, tetrachloroethylene, have all been successfully investigated using tin oxide based sensor arrays34–41 as well as CP’s42 and BAW.28,43 Other environmentally relevant studies include the detection of insecticides,44 nerve and blister agents,45 refrigerant gases46 and pollen.47 However much of the original work was carried out with laboratory based prototype systems under carefully controlled conditions. Effectively, although new sensor materials and designs are continuously being reported, the major limitation of currently available sensors remains their sensitivity to changes in temperature, humidity and flow rate. There are two possible approaches to deal with these effects. The first is to work under fixed experimental conditions. As demonstrated by Bourgeois and Stuetz,48 Ueyama et al.,32 Ogawa and Sugimoto33 and Bourgeois et al.,49 careful system design and sample preconditioning can help minimize changes in the relative humidity (RH) of the sample. Then again, when considering the practical application of a sensor array, this can make the overall instrument more complex and expensive and can also affect its portability or limit sample throughput. The second approach is to measure these parameters and calibrate the sensors under varying humidity levels in order to compensate for changes in subsequent data analysis. This parametric compensation approach has been favoured in a number of applications where RH was used as an input to artificial neural networks.28,37,38,43 Yet, despite the relative success in detecting or identifying individual chemicals (or at best a combination of known substances) in the laboratory, many of these experiments do not reflect the reality of most environmental applications where pollutants must be analysed rapidly in ever changing background conditions and in the presence of interfering compounds. Indeed, the problem becomes even J. Environ. Monit., 2003, 5, 852–860
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20 and 32 element conducting polymer arrays 12 element conducting polymer array 12 element conducting polymer array Stuetz et al. Stuetz et al.;57 Stuetz and Fenner58
Comparison of electronic noses and olfactometry for cattle-slurry related odours Detection of tainted water samples Comparison of electronic nose against olfactometry for 10 sewage treatment works 56
Persaud et al.
Misselbrook et al.55
Measurement of odourous components of pig slurry
20 element conducting polymer array
Instrument found to be insensitive compared to olfactometry. Able to discriminate between odours at high concentrations Instrument capable of discriminating between different odour components and produced output proportional to odorant concentration Average sensor output explained y60% of the variance in odour concentration. Odour concentrations in the range 100–1000 ou m23 considered Tainted samples successfully identified at concentrations as low as 1 pg l21 Strong correlation between nose output and odour concentration found when odour from single source is considered. Poorer correlations between nose output and odours from several sources 20 element conducting polymer array
System type
Assessment of odours from livestock wastes
While the measurement and detection of environmental pollutants can be successful under laboratory-controlled conditions, continuous in situ monitoring remains the most challenging aspect of environmental sensing. In the field, the ever changing temperature and humidity conditions as well as rain and wind are major constraints for the use of sensor arrays. At the same time, the monitored sample itself can change in composition and in concentration as a result of cyclic (e.g. diurnal, seasonal) variations in the process studied or in the emission rates of a particular substance. Nevertheless the rapid detection of a pollution event has become highly desirable for most regulated industries. The following examples show some of the latest developments in this area and illustrate
Hobbs et al.53
5. Continuous monitoring in the environment
Application
Early investigations involving real wastewater samples,64,65 demonstrated that a commercial array of 12 CP sensors could be used for monitoring organic pollution as a good correlation between the sensors output and the 5-day Biochemical Oxygen Demand test (BOD5) was observed for periods of 4 weeks or less. The findings showed the enormous potential of the technique and suggested that it could be used for predicting organic load content and for process control at a wastewater treatment plant. A similar study using an array of 12 MOS sensors, confirmed the ability of non-specific sensor arrays to monitor routine parameters (COD, TSS and VSS) in a treated domestic effluent.66
Authors
Measurement of wastewater organic load
Table 2 Examples of the application of sensor arrays to environmental odour problem (Gostelow et al.5)
Reported developments in complex odour analysis have typically been limited to quality assessment in the food, drink and perfume industries and so far fewer attempts have been made to characterise and measure complex odours in the environment. Cross-reactive sensor arrays present a real interest since they naturally perform an integration to yield a unique response pattern (or fingerprint) for complex but distinctive odours, without requiring the mixture to be broken down into its individual components. This is advantageous when the only required information is the composite composition of the odour of concern.9 Perera et al.50 used various pattern recognition analysis of e-nose data in order to control bad odours in landfill sites. In a review of odour measurement techniques for sewage treatment works, Gostelow et al.5 listed some examples of sensor array application to environmental odour problems (Table 2). Romain et al.,51 successfully used an array of 12 commercial tin oxide sensors to identify real malodour samples collected in the field at various concentration and under a wide range of operating and weather conditions. These developments follow results from preliminary investigations on synthetic single-component odours and the study of the influence of humidity and temperature.52 These examples of environmental odour measurement illustrate some of the possible future applications of electronic noses for air quality.59 This is of particular interest to annoyance odour assessment since non-specific sensor arrays can potentially provide an objective quantitative measure of odours as perceived by humans. However, some obstacles remain to their successful application, not least being the need for calibration against olfactometric measurements.57,58 It has been pointed out that development has to a large extent focused on the discriminatory capabilities of sensor arrays.5 Future development would also need to address the relationship between sensor output and odour intensity.60–63
Comments
Odour monitoring
54
more challenging if the analysis of complex mixtures like odours or organic load content in water samples is considered.
some of the limitations underlined above. The potential and future prospects of sensor arrays for these applications are discussed accordingly. Air pollutants Despite the relatively limited number of reported studies, continuous air quality monitoring is an area of growing interest where important field-based knowledge is currently being gained. Recently, Persaud et al.67 used a hybrid sensor array consisting of 20 CP’s and 6 BAW’s (quartz crystal microbalance devices: QCM’s) to continuously monitor the environment of a confined system over a 6-month period. The study was carried out in the MIR space station during the MIR-95 and DARA MIR-97 missions, and showed that the system was capable of monitoring the changes in air quality in real-time as the cosmonauts carried out their daily duties. It also proved useful in detecting simulated pollution as well as accidental leakage and fire events. Notably it was reported that after 1.5 year the system showed little drift or degradation. Other field investigations have used MOS sensors for air quality monitoring in an urban environment.68,69 The good correlations between the sensor responses and in situ conventional NOx and CO instruments measurements demonstrated the potential of the device in terms of sensor performance and selectivity under real operating conditions. Still, further development would require the long-term stability and calibration requirements (duration, frequency, amount of data needed) to be addressed. Menzel et al.70 developed an ‘‘original signalprocessing model to allow on-line assessment of the air quality where fast monitoring of highly variant gas environment is required’’. Although some practical and technical limitations remain, these studies show that the technology may be gradually reaching maturity
weather conditions is an effective but fastidious solution. Alternatively, the use of a reference humidity sensor for parametric compensation or the addition of an external control system are often preferred but are still being investigated. The success of a device for environmental application lies in its simplicity and ease of use. For instance, air filtration and sampling systems often require costly maintenance and the use of pure air or reference gas, often encountered in laboratory tests, is not convenient in the field. Romain et al.51 developed a simple sensor system (Fig. 1) capable of detecting a single odour event that corresponds to the daily emptying of the settling pond of a sugar factory. Results have shown that online recognition of malodours is realisable even with simple devices. Fig. 2 shows results of in situ monitoring in a printshop. Discriminant function analysis (DFA) was used to discriminate between the non-odourous air (outside air) and the printshop odour. The authors noticed that systems in which the sensors were in static contact with the ambient air (without a pump) showed random signal variations due to the air movement around the sensors.71 For this reason, working with a constant gas flow across the sensors is recommended. It was also shown that temperature regulation of the sensor chamber is required for the MOS sensors to function adequately. Besides the limitations of the sensors and the device itself, the real challenge lies in the establishment of a relationship between the measured signal and the odour characteristic (quality and concentration). In environmental applications, qualification of
Odours Continuous monitoring of malodours emitted by industrial and waste processing installations cannot be carried out using conventional olfactometry techniques and the application of biomarkers such as H2S and NH3 provides limited and often site specific olfactory information.5 There is a clear need for plant managers to measure odour releases in real time as these events are often indicative of process characteristics. Similarly, the objective identification of the source of an odour annoyance as perceived by the public, and the determination of the time of an incident has become highly desirable. Although the detection threshold and selectivity of sensor arrays remain limiting, and reported studies using electronic nose technology have highlighted a number of difficulties, odour annoyance monitoring could soon become a reality. In the field, odours vary frequently and rapidly, mainly as a result of changes in the process and meteorological conditions. These changes in the chemical composition of the odour generated by the same source induce high dispersion of sensors signals. This generally results in the overlapping of clusters obtained by classification models such as linear discriminant analysis. In addition, rapid fluctuations of the malodour require a high sampling frequency. As a rule, the response time of the sensors themselves is not so much of an issue but the response time of the whole device can often be improved by reducing dead volumes in the system as well as using adequate gas flow rates. On the other hand, the sensor’s recovery time is typically the limiting factor to achieving high measurement frequencies for continuous monitoring applications. Thus, further research and development in this area is still required from sensor manufacturers. The influence of relative humidity (RH) and temperature also needs to be considered. In order to take these perturbations into account, the development of a classification model under a wide range of operating and
Fig. 1 Photograph of MOS-based sensor array system (Capteur 1 Figaro sensors) used by Romain et al.51
Fig. 2 Example of on-line monitoring of an odorous source (print shop), Discriminant function analysis was performed on a training data set and the classification functions obtained for each class (‘‘non odorous’’ and ‘‘printshop’’) were then applied on-line to new data. (Nicolas et al.72). Classification results were confirmed by the absence/ presence of an odour as perceived by the operator.
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the malodours usually refers to polluting source (e.g. landfill site) or to a particular process (e.g. aeration of compost piles) and conventional classification techniques can potentially be applied and adapted to on-line monitoring.72 In contrast, on-line quantitative analysis has so far proved to be a more challenging exercise. In the absence of standard measurement techniques, the association of sensor array data to the perceived intensity of an odour requires new methodologies to be developed. At present quantitative measurements of odours rely on correlations with human olfactometry data and/ or the perception of the odour intensity by the instrument’s operator at the time of sampling. However, this approach is hampered by the subjectivity of the evaluation, the non-linear relation between the perceived intensity of an odour and its concentration, as well as by adaptation phenomena (decreased perception) as a result of extended exposure to that odour.1 This complicates the elaboration of quantitative models. Moreover, once/if a quantitative relationship has been established, the model may be site specific and its validity over long periods of time must be demonstrated before sensor array systems can be used for quantitative analysis. Water The use of electronic noses to monitor water quality in the field is still a virtually unexplored domain with only a handful of applications reported so far. Perhaps one of the most promising areas of all is the detection of hydrophobic and highly volatile organic compounds (VOC’s) in water systems. The recent developments in on-line detection of oils and petroleum hydrocarbons,32,33 have arisen from the recent advances in sensor technology discussed earlier as well as from progresses in computing and pattern recognition. Similarly, previous studies on the detection of VOC’s and organic pollution in wastewater have led to the on-line evaluation of sensor array systems for the protection of process treatment plants.64,65,73 The first obstacle when dealing with liquid samples is to generate or collect a headspace gas that can be reliably and safely measured by the sensor array. With parameters such as flow, temperature or suspended solids constantly changing, the major difficulty lies in drawing a headspace sample that is representative of the liquid phase. Bourgeois and Stuetz48 and Bourgeois et al.49 have shown the interest of using a temperature-controlled flow-cell to externally produce a reproducible headspace from a continuously flowing wastewater. A photograph of the on-line measurement system is given in Fig. 3. These on-line studies have all used a similar ‘‘purge and control’’ approach that proved satisfactory for research and development purposes. However, these prototype instruments still require some form of contact with the liquid phase. Truly non-invasive electronic noses would be highly desirable for a number of field based applications. As with air and odour monitoring applications, such devices could become a reality over the next few years given that sufficient experience and knowledge is gained in the field with current systems, and that further technological advances are made in order to deal with humidity and temperature changes. In many cases, variation in the organic content of a wastewater influent can be associated with changes in temperature and consequently also affects relative humidity. This shows the difficulty of establishing an independent relationship between the response of RH and temperature sensitive sensors and the variable of interest. It also underlines the need to calibrate the instrument using data acquired under wide ranging conditions. Fig. 4 shows how an array of 8 CP sensors can continuously monitor for changes in the organic strength of a wastewater influent with the dilution effect of rain clearly visible. Although the relationship between the sensor response and organic load has been demonstrated,65,74 many difficulties remain. For instance, variations in the flow of a liquid stream will result in a change in 856
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Fig. 3 Photograph of on-line measurement system showing sampling vessel (temperature controlled flow-cell) and CP-based sensor array module (Prosat, Marconi Applied Technologies UK). (Bourgeois and Stuetz75)
Fig. 4 Plot of sensor responses showing diurnal variations observed during a week (01/03/01-06/03/01) with dilution effect of rain. (Bourgeois et al49).
the particulate content through sedimentation or re-suspension. These changes in the suspended solids concentration directly affect the amount and nature of VOC’s that can be detected by a sensor array. Fig. 5 illustrates the effect of reduced flow on the sensor profiles as a result of a pump failure at the inlet of a wastewater treatment plant. These findings were confirmed the next day when the pump was stopped for maintenance. While these observations may be of interest to plant operators for the rapid detection of operating anomalies, it also emphasises the need to better understand and take into account (i.e. measure and/or control) the effect of variables such as flow and temperature for quantitative analysis. Other types of sensor array applications may not require such accurate control. For example, Fig. 6 shows the detection of a pollution incident (diesel spill) in a wastewater matrix.75 These results indicate how sensor arrays can be readily used for alarm level applications and to give an indication of water quality using a general quality index (e.g.: 1–5 scale). Simple sensory early warning devices which can detect sudden changes in a
Fig. 5 Plot of sensor responses showing operating anomalies (main pump failure). Cranfield University sewage works.
Fig. 6 Plot of sensor responses showing the detection of an unknown discharge in the wastewater influent. (Bourgeois and Stuetz75)
process stream present a commercial interest in a number of industries and would also represent a unique opportunity to gain the necessary expertise manufacturers need for the development of more complex quantitative instruments.
6. Discussion Real-time sensing of water as well as air and odour monitoring have a number of common limitations which are distinctive of the technology. Sensor drift is one of the most serious impairments of chemical and biochemical sensors.76 There are various types of drift which are mostly a result of poisoning or ageing of the sensors, or environmental changes such as temperature and pressure variations. Bourgeois et al.74 discussed the effects of drift and the importance of the amount of data that is used for model training, on the prediction of the organic content of wastewater (using multiple linear regression). Romain et al.77 pointed out the importance of drift three years after the first real malodours measurement. This showed serious consequences on the classification results and also underlined the difficulty of modelling this effect with a calibration mixture. Despite efforts to improve long term
stability, manufacturers are yet to release sensors that are not affected by drift at all. With constantly changing environmental background conditions, sensor array systems that require the use of a reference gas or other calibration standard, cannot always be applied to continuous monitoring applications in the field. For similar reasons the choice of a particular type of sensor can be limited by power consumption requirements where autonomous, portable instruments are concerned. Finally, the practicality and simplicity of an environmental monitoring system is an area of major concern to the end user. The recent application of automated sensor arrays to continuous measurement has shown how easy it is to become data rich. Indeed the large datasets and the amount of information that is being generated by such devices can rapidly become overwhelming for the operators. One of the major challenges is to be able to systematically reduce the dimensionality of the incoming data while preserving all relevant information. So far there has been no systematic approach to the problem of data preprocessing and analysis. It seems that the choice of a suitable output (desorption signal, baseline, transient/maximum response, etc.) and analysis protocol (PCA, PLS, ANN, etc.) is often the result of trial and error, largely based on personal intuition or experience. Unfortunately this is a time consuming process which requires highly skilled personnel. Still there is no guarantee that the selected methodology is optimal nor that it will perform adequately when applied in real time if new conditions are encountered. To some extent the same may apply when considering the choice of the particular sensors that constitute an array although laboratory investigations now give a good indication of their capabilities.
7. Conclusions The control of air and water quality still chiefly relies on the use of traditional environmental monitoring techniques that often require sampling and subsequent laboratory analysis. Despite the recent appearance of commercial devices that can be implemented in the field, new low cost innovative techniques for continuous and non-invasive monitoring are still needed. Electronic nose technology exhibits several possibilities for environmental monitoring which are not proposed by classical J. Environ. Monit., 2003, 5, 852–860
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Table 3 Summary table of practical and technological limitations of sensor arrays Practicalities
Technological shortcomings
– – – – –
– Long term drift, reliability and reproducibility of sensors – Selectivity/sensitivity of sensor – Compatibility between systems (i.e. transferability)
Rapidly changing environment (humidity, temperature, pressure) Amount of data generated, choice signal/output variable Data analysis and lack of standard procedures Need for calibration/reference which must be representative of in situ conditions Lengthy training and development phases
techniques. These are essentially, low cost, low maintenance, small size and in some cases low power consumption. The true potential of sensor arrays for environmental monitoring is discussed in this paper, with references to a number of published studies. The originality of sensor arrays mainly lies in their ability to provide qualitative information, other than chemical concentration and composition. This makes the technology particularly attractive in a number of applications. For instance, knowledge of the overall ‘‘quality of the compost pile’’ rather than ethanol concentration values, might be highly desirable for process control and decision making. Similarly these devices are potentially suited to the control of specific pollutions such as malodours emissions for which no other technique of on-line continuous measurement has yet been proposed. At present, the technology is still in its evaluation phase. But already, and despite the foreseeable difficulties associated with a strongly multidisciplinary subject, promising results have been obtained from in situ investigations. A number of limitations have been highlighted, both associated with the technology itself and its application to environmental studies. Many of the difficulties mentioned are already the subject of extensive research in the sensor community while others may require more development and practical evaluation before sensor arrays for environmental monitoring become a commercial reality. In the current state of the art, electronic nose systems suffer from both practical limitations and a number of technological shortcomings that are summarised in Table 3. Seven years on, the common expectation that ‘‘smarter noses’’ using more advanced ANN would handle problems such as sensor drift, noise and non-linearities, and would rapidly become a reality as stated by Craven et al.,78 still appears rather optimistic as the same limitations listed by the authors still apply today, despite the considerable improvements. On the other hand, the authors’ prediction that smaller devices with reduced weight, cost and power consumption would open new markets has proved to be true with regard to environmental monitoring. Although the difficulties listed above remain common to most applications (food, medicine, laboratory measurements…), they become more challenging when in situ monitoring is considered. The harsh conditions found in the field can rapidly cause damage to the sensors and frequent replacements may be needed. Unfortunately due to the low reproducibility of sensor manufacturing, a new learning phase of the array is generally necessary. In this multidisciplinary and demanding discipline, simplicity is mandatory. The development of a simple alarm level device and use of a relative (variable) air/water quality index could be the first step towards commercial success. This could be used as a stepping stone for the development of more complex systems which are needed for more demanding applications.
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References 1 J. W. Gardner and P. N. Bartlett, Electronic Noses: Principles and Applications, Oxford University Press, Oxford, 1999. 2 J. Plumey, Quality monitoring for compliance assurance, in The Spencer’s Guide to the UK Environmental Industry 1999, B. M. Publishing, Gerrards Cross, Bucks, UK, 1999, pp. 43–45. 3 J. Nicolas, Surveillance de l’environnement: Me´thodologie., Edition
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Academia-Bruylant-coll. Pe´dasup–2nd edn, 1998-ISBN 2-87209352-4, 1998. European determination of odour concentration measurement by dynamic olfactometry, prEN 13725, 04–2002. P. Gostelow, S. A. Parsons and R. M. Stuetz, Odour measurements for sewage treatment works, Water Res., 2001, 35(3), 579– 597. G. Preti, T. S. Gittleman, P. B. Staudte and P. Luitweiler, Letting the nose lead the way–malodorous components in drinking water, Anal. Chem., 1993, 65, 699A–702A. U. Wolff, F. L. Dickert, G. K. Fischerauer, W. Greibl and C. C. W. Ruppel, SAW sensors for harsh environments, IEEE Sens. J., 2001, 1(1), 4–13. D. M. Wilson, S. Hoyt, J. Janata, K. Booksh and L. Obando, Chemical sensors for portable, handheld field instruments, IEEE Sens. J., 2001, 1(4), 256–274. K. J. Albert, N. S. Lewis, C. L. Schauer, G. A. Sotzing, S. E. Stitzel, T. P. Vaid and D. R. Walt, Cross-reactive chemical sensor arrays, Chem. Rev., 2000, 100, 2595–2626. J. R. Vig, Temperature-insensitive dual-mode resonant sensors–A review, IEEE Sens. J., 2001, 1(1), 62–68. D. S. Ballantine, R. M. White, S. J. Martin, A. J. Ricco, G. C. Frye, E. T. Zellers and H. Wohltjen, Acoustic Wave Sensors: Theory, Design, and Physico-chemical Applications, Applications of Modern Acoustics Series, Academic Press, 1996, p. 436. J. W Grate, S. J. Martin and R. M White, Acoustic Wave Microsensors (Part 1), Anal. Chem., 1993, 65, 940–948. J. W Grate, S. J. Martin and R. M White, Acoustic Wave Microsensors (Part 2), Anal. Chem., 1993, 65, 987–996. D. D. Lee and D. S. Lee, Environmental gas sensors, IEEE Sens. J., 2001, 1(3), 214–224. K. Buhlmann, B. Schlatt, K. Cammann and A. Shulga, Plasticised polymeric electrolytes: new extremely versatile receptor materials for gas sensors (VOC monitoring) and electronic noses (odour identification/discrimination), Sens. Actuators, B, 1998, 49, 156– 165. M. De Wit, E. Vanneste, H. J. Geise and L. J. Nagels, Chemiresistive sensors of electrically conducting poly(2,5-thienylene vinylene) and copolymers: their response to nine organic vapors, Sens. Actuators, B, 1998, 50, 164–172. M. C. Carotta, G. Martinelli, L. Crema, M. Gallana, M. Merli, G. Ghiotti and E. Traversa, Array of thick film sensors for atmospheric pollutant monitoring, Sens. Actuators, B, 2000, 68, 1–8. T. Becker, L. Tomasi, C. Bosh-v. Braunmuhl, G. Muller, G. Sberveglieri, G. Faglia and E. Comini, Ozone detection using low power-consumption metal-oxide gas sensors, Sens. Actuators, A, 1999, 74, 229–232. T. Becker, S. Muhlberger, C. Bosh-v. Braunmuhl, G. Muller, T. Ziemann and K. V. Hechtenberg, Air pollution monitoring using tin-oxide-based microreactor system, Sens. Actuators, B, 2000, 69, 108–119. C. Dejous, D. Rebiere, J. Pistre, C. Tiret and R. Planade, A surface acoustic wave gas sensor: Detection of organophosphorous compounds, Sens. Actuators, B, 1995, 24–25, 58–61. M. Rapp, B. Bob, A. Voigt, H. Gemmeke and H. J. Ache, Development of an analytical microsystem for organic gas detection based on surface acoustic wave resonators, Fresenius’ J. Anal. Chem., 1995, 352, 699–704. E. T. Zellers, J. Park, T. Hsu and W. A. Groves, Establishing a limit of recognition for a vapor sensor array, Anal. Chem., 1998, 70, 4191–4201. K. S. Suslick and N. A. Rakow, A colorimetric nose: ‘‘smellseeing’’, in Artificial Chemical sensing, Olfaction and Electronic nose (ISOEN 2001), ed. J. R. Stetter and W. R Penrose, Electrochem Soc. Inc. USA, 2001, pp. 8–14. G. A. Bakken, G. W. Kauffman, P. C. Jurs, K. J. Albert and S. S. Stitzel, Pattren recognition analysis of optical sensor array data to detect nitroaromatic compound vapors, Sens. Actuators, B, 2001, 79, 1–10.
25 D. R. Walt, T. Dickinson, J. White, J. Kauer, S. Johnson, H. Engelhardt, J. Sutter and P. Jurs, Optical sensor arrays for odour recognition, Biosens. Bioelectron., 1998, 13, 697–699. 26 S. R. Johnson, J. M. Sutter, H. L. Engelhardt, P. C. Jurs, J White, J. S. Kauer, T. A. Dickinson and D. R. Walt, Identification of multiple analytes using an optical sensor array and pattern recognition neural networks, Anal. Chem., 1997, 69, 4641–4648. 27 T. A. Dickinson, K. L. Michael, J. S. Kauer and D. R. Walt, Convergent, self-encoded bead sensor arrays in the design of an artificial nose, Anal. Chem., 1999, 71, 2192–2198. 28 A. Hierlemann, U. Weimar, G. Kraus, M. Schweizer-Berberich and W. Gopel, Polymer-based sensor arrays and multicomponent analysis for the detection of hazardous organic vapours in the environment, Sens. Actuators, B, 1995, 26–27, 126–134. 29 R. J. Lauf and B. S. Hoffheins, Analysis of liquid fuels using a gas sensor array, Fuel, 1991, 70, 935–940. 30 H. V. Shurmer, The fifth sense: on the scent of the electronic nose, IEEE Rev., 1990(March), 95–98. 31 I. Sugimoto, M. Seiyama and M. Nakamura, Detection of petroleum hydrocarbons at low ppb levels using quartz resonator sensors and instrumentation of a smart environmental monitoring system, J. Environ. Monit., 1999, 1(2), 135–142. 32 S. UeyamaK. Hijikata and J. Hirotsuji, Water monitoring system for oil contamination using polymer-coated quartz crystal microbalance chemical sensor, in Instrumentation, Control and Automation, (IWA-ICA 2001), Malmo, Sweden, conference preprints, 2001, pp. 287–292. 33 S. Ogawa and I. Sugimoto, Detecting odorous materials in water using quartz crystal microbalance sensors, in Instrumentation, Control and Automation, (IWA-ICA 2001), Malmo, Sweden, conf. preprints, 2001, pp. 317–322. 34 A. Szczurek, P. M. Szecowka and B. W. Licznerki, Application of sensor array and neural networks for quantification of organic solvent vapors in air, Sens. Actuators, B, 1999, 58, 427–432. 35 E. Llobet, R. Ionescu, S. Al-Khalifa, J. Brezmes, X. Vilanova, X. Correig, N. Barsan and J. W. Gardner, Multicomponent gas mixture analysis using a single tin oxide sensor and dynamic pattern recognition, IEEE Sens. J., 1997, 1(3), 207–213. 36 D. S. Lee, H. Y. Jung, J. W. Lim, J. S. Huh and D. D. Lee, Recognition of VOC gases using the nanocrystalline thick film SnO2 gas sensor array and pattern recognition analysis, in Tech. Dig. 8th Int. Meeting Chem. Sens., Basel, Switzerland, 2000. 37 G. Faglia, F. Bicelli, G. Sberveglieri, P. Maffezzoni and P. Gubian, Identification and quantification of methane and ethyl alcohol in an environment at variable humidity by an hybrid array, Sens. Actuators, B, 1997, 44, 517–520. 38 J. Orts, E. Llobet, X. Vilanova, J. Brezmes and X. Correig, Selective methane detection under varying moisture conditions using static and dynamic sensor signals, Sens. Actuators, B, 1999, 60, 106–117. 39 J. Getino, L. Ares, J. I. Robla, M. C. Horillo, I. Sayago, M. J. Fernandez, J. Rodrigo and J. Gutierrez, Environmental applications of gas sensor arrays: combustion atmospheres and contaminated soils, Sens. Actuators, B, 1999, 59, 249–254. 40 R. M. Negri, S. Reich, D. Fernandez, A.-C. Romain, J. Nicolas and A. Lamagna, Identification of pollutant gases with a multisensorial arrange, Proc. ISOEN 1999, Tu¨bingen, September, 1999, 20–22, 372–375. 41 M Negri and S. Reich, Identification of pollutant gases and its concentrations with a multisensor array, Sens. Actuators, B, 2001, 75, 172–178. 42 C. Furlong and J. R. Stewart, Using a portable electronic nose for identification of odorous chemicals, in Electronic Noses and Olfaction 2000, conference proceedings, Brighton, UK, 2000, 285– 290. 43 F. L. Dickert, O. Hayden and M. E. Zenkel, Detection of volatile compounds with mass-sensitive sensor arrays in the presence of variable ambient humidity, Anal. Chem., 1999, 71, 1338–1341. 44 R. E. Baby, M. Cabezas and E. N. Walsoe de Reca, Electronic nose: a useful tool for monitoring environmental pollution, Sens. Actuators, B, 2000, 69, 214–218. 45 R. E McGill, V. K. Nguyen, R. Chung, R. E. Shaffer, D. DiLella, J. L. Stepnowski, T. E. Mlsna, D. L. Venezky and D. Dominguez, The ‘‘NRL-SAWRHINO’’: a nose for toxic gases, Sens. Actuators, B, 2000, 65, 10–13. 46 C. Delpha, M. Lumberas and M. Siadat, Discrimination of Forane 134a and carbon dioxide concentrations in an air conditioned atmosphere with an electronic nose: influence of the relative humidity, Sens. Actuators, B, 2001, 80, 59–67. 47 E. L. Kalman, F. Winquist and I. Lundstrom, A new pollen
48 49
50
51 52
53
54 55
56 57 58 59 60 61 62
63 64 65 66 67 68
69
70
71
detection method based on an electronic nose, Atmos. Environ., 1997, 31(11), 1715–1719. W. Bourgeois and R. M. Stuetz, Measuring wastewater quality using a sensor array: prospects for real-time monitoring, Water Sci. Technol., 2000, 41(12), 107–112. W. Bourgeois, P. Hogben, A. Pike and R. M. Stuetz, Development of a sensor array based measurement system for continuous monitoring of water and wastewater, Sens. Actuators, B, 2003, 88, 312–319. A. Perera, T. Pardo, T. Sundi, R. Gutierrez-Osuna, S. Marco and J. Nicolas, IpNose: Electronic nose for remote bad odour monitoring system in landfill sites, Proceedings of the 8th conference Eurodeur, Paris, June, 2001, pp. 19–21. A. C. Romain, J. Nicolas, V. Wiertz, J. Maternova and Ph. Andre, Use of a simple tin oxide sensor array to identify five malodours collected in the field, Sens. Actuators, B, 2000, 62, 73–79. A. C. Romain, J. Nicolas and Ph. Andre, In situ measurement of olfactive pollution with inorganic semiconductors: limitation due to the influence of humidity and temperature, Semin. Food Anal., 1997, 2, 283–296. P. J. Hobbs, T. H. Misselbrook and B. F. Pain, Assessment of odours from livestock wastes by photoionisation detector, electronic nose, olfactometry and gas chromatography-mass spectrometry, J. Agric, Eng. Res., 1995, 60, 137–144. K. C. Persaud, S. M. Khaffaf, P. J. Hobbs and R. W. Sneath, Assessment of conducting polymer odour sensors for agricultural malodour measurements, Chem. Senses, 1996, 21, 495–505. T. H Misselbrook, P. J. Hobbs and K. C. Persaud, Use of an electronic nose to measure odour concentration following application of cattle slurry to grassland, J. Agric. Eng. Res., 1997, 66, 213–220. R. M. Stuetz, M. White and R. A. Fenner, Use of an electronic nose to detect tainting compounds in raw and treated potable water, J. Water Services Res. Technol.–Aqua, 1998, 47, 223–228. R. M. Stuetz, G. Engin and R. A. Fenner, Sewage odour measurements using a sensory panel and an electronic nose, Water Sci. Technol., 1998, 38, 331–335. R. M. Stuetz and R. A. Fenner, Electronic nose technology: a new tool for odour management, Water Qual. Int., 1998, July/Aug, 15– 17. F. Di Francesco, An electronic nose for odour annoyance assessment, Atmos. Environ., 2001, 35(7), 1225–1234. G. Hudon, C. Guy and J. Hermia, Measurement of odor intensity by an electronic nose, J. Air Waste Manage. Assoc., 2000, 50, 1750–1758. O. Ramalho, Correspondences between olfactometry, analytical and electronic nose data for 10 indoor paints, Analusis, 2000, 28(3), 207–215. R. Gutierrez-Osuna, S. S. Schiffman and H. T. Nagle, Correlation of Sensory Analysis with Electronic Nose Data for Swine Odor Remediation Assessment, 3rd European Congress on Odours, Metrology and Electronic Noses, Paris, France, 2001. R. Stuetz and J. Nicolas, Sensor arrays: an inspired idea or an objective measurement of environmental odours? Water Sci. Technol., 2001, 44, 53–58. R. M. Stuetz, R. A. Fenner and G. Engin, Characterisation of wastewater using an electronic nose, Water Res., 1999, 33, 442– 452. R. M. Stuetz, S. Georges, R. A. Fenner and S. J. Hall, Monitoring wastewater BOD using a non-specific sensor array, J. Chem. Technol. Biotechnol., 1999, 74, 1069–1074. T. Dewettinck, K. Van Hege and W. Verstraete, The electronic nose as a rapid sensor for volatile compounds in treated domestic wastewater, Water Res., 2001, 35(10), 2475–2483. K. C. Persaud, A smart gas sensor for monitoring environmental changes in closed systems: results from the MIR space station, Sens. Actuators, B, 1999, 2–3(55), 118–126. E. Traversa, Y. Sadaoka, M. C Carotta and G. Martinelli, Environmental monitoring field tests using screen-printed thickfilm sensors based on semiconducting oxydes, Sens. Actuators, B, 2000, 65, 181–185. M. C. Carotta, G. Martinelli, L. Crema, C. Malagu, M. Merli, G. Ghiotti and E. Traversa, Nanostructured thick-film gas sensors for athmospheric pollutant monitoring: quantitative analysis on field tests, Sens. Actuators, B, 2001, 76, 336–342. R. Menzel and J. Goschnick, Gradient gas sensor microarrays for on-line process control a new dynamic classification model for fast and reliable air quality assessment, Sens. Actuators, B., 2000, 68, 115–122. J. Nicolas, A-C. Romain, V. Wiertz, J Maternova and P Andre, Using the classification model of an electronic nose to assign
J. Environ. Monit., 2003, 5, 852–860
859
72
73 74
75
860
unknown malodours to environmental sources and to monitor them continuously, Sens. Actuators, B, 2000, 69, 366–371. J. Nicolas, A-C. Romain and J. Maternova, Chemometrics methods for the identification and monitoring of an odour in the environment with an electronic nose, Sens. Chemometrics, 2001, 75–90. W. Bourgeois, G. Gardey, M. Servieres and R. M Stuetz, A chemical sensor array based system for protecting wastewater treatment plants, Sens. Actuators, B., 2003, 91(3), 109–116. W. Bourgeois, M. Gaugler and R. M. Stuetz, On-line evaluation of a sensor array for monitoring changes in effluent quality, in Instrumentation, Control and Automation, (IWA-ICA 2001), conf. preprints, Malmo, Sweden,2001, pp 271–278. W. Bourgeois and R. M. Stuetz, Use of a chemical sensor array for detecting pollutants in domestic wastewaters, Water Res., 2002, 36, 4505–4512.
J. Environ. Monit., 2003, 5, 852–860
76 M. Holmberg, F. A. M. Davide, C. Di Natale, A. D’amico, F. Winquist and I. Lundstro¨m, Drift counteraction in odour recognition applications: Lifelong calibration method, Sens. Actuators, B., 1997, 42(3), 185–194. 77 A. C. Romain, J. Nicolas and Ph. Andre, Three years experiment with the same tin oxide sensor arrays for the identification of malodorous sources in the environment, Sens. Actuators, B, 2002, 84, 271–277. 78 M. Craven, E. L. Hines, J. W. Gardner, D. Morgan, P. Hogan and P. A. Ene, Bacteria detection and classification using artificial neural network in conjunction with an electronic nose, in International Conference on Neural Networks and Expert Systems in Medicine and Healthcare, Univ. of Plymouth, UK, August 1994, pp. 23–26.
