Improvement of Odor Intensity Measurement Using Dynamic Olfactometry

By Jiang, John; Coffey, Patrick; Toohey, Brendan

ABSTRACT

Odor intensity reveals a dose-effect relationship between inhaled odor and perceived odor sensation by the receptors, while odor concentration reflects the odor strength at the emission sources. The study reports significant improvements in experimental procedures in establishing the odor concentration-intensity (OCI) relationships using a newly developed digital olfactometer. The improvements in experimental procedures have been made to meet the requirements of both the VDI guideline 3882.1 and the European standard (EN13725). Several areas which could affect the reliability of the results have been identified in some similar studies. The latest digital olfactometer was calibrated automatically to ensure accurate and repeatable dilution ratios. Cross contamination has been eliminated through the instrument design and extensive cleaning procedures, making random presentation possible. Stringent panelist screening and continuous performance monitoring ensures consistent sensitivity of the panel. The extension of odor intensity category to temperature sensation gives a reference to assist judgments of perceived odor sensation. The DynaScent calculation method has simplified odor intensity calculation and can be applied to many odor samples. A total of 38 odor samples from three alumina refinery sites and two sewage treatment plants were collected for analysis. The results have confirmed the efficiency of the olfactometer. Distinct Odor Concentrations (DOCs) were calculated for each sample using both VDI and DynaScent methods. A student t test on two major odor types confirmed that there are no significant differences between two methods. The study has shown the DOCs for refinery odor and wastewater odor are in the range of 3.8-15.4 and 4.2-15.6 odor unit (OU)/m^sup 3^ respectively. The study demonstrated that the improvements are critical in achieving reliable odor intensity measurement. This can lead to the setup of quantitative odor impact criteria for different industries and sites.

INTRODUCTION

In Australia, most state environmental protection authorities have introduced a quantitative odor impact assessment approach to regulate odor impacts from industrial and agricultural activities. The approach uses dynamic olfactometry to quantify the source strength expressed as odor emission rates. Meteorological data including hourly wind speed, direction, and atmospheric stabilities, along with the odor emission rates are input into an air dispersion model (such as Ausplume) so that odor concentration isopleths can be plotted. The area at which the predicted odor concentration is equal to the odor impact criterion is defined as the odor impact area. In the past, the selection of odor impact criteria has been largely dependent on information from literature. The development of scientific-based odor impact criteria is needed to provide convincing results to both industry and stakeholders.

Odor intensity measurement technique has been applied for the determination of biofilter performance and for the determination of odor impact in the ambient air.1-3 Lately, the technique has been used to establish industry-specific and site-specific odor impact criteria.4-8 The odor intensity category of “distinct” has been selected as the odor criterion. It is required that the odor concentration-intensity (OCI) relationship first be established so that the odor impact criterion, expressed as odor concentration, can be derived from the distinct odor intensity category.

The study used the recently developed DynaScent digital olfactometer9,10 to determine odor concentrationintensity relationships for wastewater and alumina refinery odors. It reported several significant improvements on instrument performance, experimental procedures, panelist training, and calculation method.

Literature Review

Odor intensity is one of four dimensions that an odor exhibits. If the odor concentration is related to the physical strength of the odor, the odor intensity is related to the perceived sensation by the human. On the analogy of human sensation, the odor concentration is similar to the water temperature measured by a thermometer in degrees, and the odor intensity refers to the temperature sensation, like cold or warm.

In 1992, the Association of German Engineers published the guideline “VDI 3882 Part 1 Olfactometry – Determination of Odor Intensity.”1 The guideline, with some modifications, was applied to develop odor impact criteria for the poultry industry in Western Australia in 1996 5,6 With the introduction of the European standard on odor concentration measurement using dynamic olfactometry in 2003, there are several improvements, which are necessary in the odor intensity measurement, as described below.

Instrument performance in terms of accuracy and repeatability of the dilution ratios remains to be addressed. The accuracy of the dilution ratios must be within 20% of the set points. Despite the claims made by the manufacturers to meet the instrumental performance criteria in the EN13725, the calibration results using the calibration method conformed to the standard are rarely available in public domain. Until 1980, early studies in psychophysics have concluded that the possible sources of discrepancies in different studies11,12 were largely related to the preparation of stimulus magnitude. It was suggested that analytical and calibration errors were large, because the stimuli concentrations were low. In recent studies, two research groups have developed odor intensity relationships for the same swine odor using the same dynamic olfactometer, yet their relationships were markedly different.13,14

The effect of cross-contamination was clearly evident in a study when a mass flow controller (MFC)-based olfactometer was used.15 The odor intensity category at the odor threshold level was reported to be greater than the “weak” level. However, all of these studies were performed using a sequential presentation order to minimize cross- contamination. The obvious disadvantage of this method was that panelists might anticipate the correct response to odor delivered at the sniffing cups in ascending order. Should this happen, the results will not be reliable.

In addition to instrumental performance, the reliability of odor intensity measurement can be related to the interpretation of the odor intensity category. The guideline uses a category scaling (0- 6) in classifying the odor intensity without any reference. This is more variable and less consistent than master scaling, which uses either a master odorant or cross-modality matching.1 It is vital that the panelists are well trained and instructed on how to rate the intensity of the odor using some reference.

The VDI calculation is a manual calculation and requires individual judgment for each sample by the operator. It was difficult to make the calculation method compatible with computer technology. This could introduce human errors and increase the labor cost.

The first odor intensity study in Australia using a dynamic olfactometer found that the MFC-based olfactometer required further improvements.5,6 This led to the development of the Wang olfactometer (a prototype of the Dyna Scent Digital Olfactometer9) at the University of New South Wales in 1998 that could present the odor in a random presentation order without the danger of contaminating the olfactometer. Follow-up studies for pig and dairy industries have further confirmed the success of odor intensity measurement using the newly developed olfactometer.7-10

EXPERIMENTAL WORK

Sample Collection

There were three alumina refineries and two wastewater treatment plants involved in the study. At each alumina refinery, two to four sources were sampled. At each source, two samples were collected. At each wastewater treatment plant, three sources were identified and sampled four times.

Odor samples from various odor sources were collected in new Nalophan TA bags using the DynaDrum sampling apparatus.9 The system has a built-in vacuum pump and can be either vacuumed or pressurized. The sampling bag was first half filled with the sample for 30 sec under vacuum and then was expelled for 30 sec under pressure. A 1-min (5-L) sample was then collected into the bag. This procedure is to minimize sample losses during sampling and transportation. For highly odorous or hot and wet sources, the DynaSampler predilution probe was used to predilute the sample up to 40 times and avoid condensation and possible loss of odor in the sample bag.

Odor Concentration Measurement

Odor concentration measurement was performed using a digital olfactometer as per European standard (EN137252003; ref16). Unlike its predecessors, the olfactometer uses no flow measurement device (such as rotameter or mass flow meter), which eliminates the sources of contamination, the shortest possible connection between the sniffing cups and gas mixing tube to minimize contamination, as well as dilution fluctuation caused by the back pressure. In addition, the olfactometer uses needle valves that can be flushed with a high speed of >200 km/hr and a pressure of 400 kPa without comprising the performance of the olfactometer with three levels of flushing (between samples, be\tween testing rounds, and between dilution steps) during the operation.

Odor testing laboratory performance is evaluated against two criteria: instrument performance and sensory performance. The olfactometer was calibrated using a highperformance mass flow meter with a resolution of 0.03 mL/min. The calibration results confirmed that the instrumental performance exceeds the requirements of both the Australian/New Zealand standard AS/NZS 4323.3:2001(17) and the European standard EN 13725:2003.16

Table 1. Extended odor intensity categories

The panelists were screened using n-butanol and qualified after the panelists passed the selection criteria (their averaged butanol threshold is between 20 and 80 ppb, and the antilog of standard deviation calculated from the logarithms [log10] of 10 individual thresholds is <2.3).16,17 Their performances were continuously monitored over the testing period. If any of the panelists failed the criteria, he/she was removed from the list.

The odorous gas sample is presented at various dilutions to one of two sniffing ports at random, whereas the other contains only odorless air. For each dilution ratio, each panelist, in turn, sniffs both ports and chooses one or the other port as being the one with the odorous sample (i.e. makes a “forced choice”). In addition to their forced choice (left or right) between the two ports, the panelists are required to indicate whether their confidence is based on a “guess,”"inkling,” or “certainty.” The process is then repeated with doubled odor strength presented at the sniffing ports (ascending order) until all of the panelists choose the correct port with certainty. This is one round. For each sample, two rounds are processed. The odor concentration is then calculated using the retrospective screening procedure.

As specified in the VDI standard 3882 Part 1, the major testing steps are: (1) determination of odor concentration first in accordance with the European standard; (2) automatic selection of six dilution steps starting from the measured odor concentration; (3) random presentation order in dilution steps; and (4) use of one blank. After the panelists qualify at the screening test, training in sensory intensity rating was provided using hot water and an infrared thermometer. Water at various temperatures was placed in a glass cup. Each panelist put his/her index finger into the cup while reading the water temperature on the thermometer. Using the extended odor intensity categories (Table 1), the odor intensity above the weak level was analogous to the sensation intensity of the corresponding water temperature.

An odor sample at a concentration higher than the odor threshold is released from the left port. Odor-free air is released from the right sniffing port. The panelists sniff in turn and make their judgment on odor intensity using the descriptors specified in Table 1. After all of the panelists have made their assessment, the procedure is repeated but at a different odor concentration to be randomly selected.

On the basis of previous odor measurement experience, several modifications to the VDI method have been made: (1) calibrated olfactometer to deliver accurate and repeatable dilution ratios; (2) extensive decontamination procedures between samples, between series, and between dilution steps; (3) odor type-based odor intensity measurement, which allows the odor intensity for individual types of odor and combined odor sources to be calculated without mixing the odor together; (4) DynaScent calculation method for odor intensity presentation; and (5) improved the interpretation of the odor intensity categories and panelist training.

Figure 1. Example of DynaScent calculation method (centrifuge 3).

Table 2. Example of odor intensity measurement results (centrifuge 3).

VDI Calculation Method

For calculating odor concentration-intensity relationship, the detailed calculation procedures can be found in the VDI 3882.1 guideline. In summary, the following steps are taken to calculate the OCI relationship (e.g., see Table 2): (1) for each dilution step, the occurrence of OII at each dilution step is counted, which results in a matrix where the vertical column is the OII and the horizontal row is the dilution ratio; (2) for each dilution step, the percentage greater than the corresponding oil is calculated, and for oil, the frequency is plotted linearly against its corresponding logarithm dilution numbers; (3) the characteristic dilution number (CDN) is derived at where the percentage is equal to the 50%; and (4) the OCI relationship is the linear relationship between the CDN and its corresponding logarithm dilution ratio.

Table 3. Comparison of OCI relationships using DynaScent and VDI calculation methods: wastewater treatment plants.

RESULTS

The sample collection and testing was carried out within 2 weeks in a mobile odor testing laboratory near the site. In the morning of each day, four to six samples were collected from preselected odor emission sources. The samples were brought back and tested in the afternoon. For each sample, both odor concentration and odor intensity were carried out consecutively to avoid cross- contamination between the samples. Between samples, the operator checked each sniffing cup at the end of the flushing to ensure that there was no contamination from the previous sample.

A total of 38 odor samples have been analyzed for odor concentration and OCI relationships. Results of odor concentrations and odor intensity for all of the samples from wastewater and alumina refinery are listed in Table 3 and Table 4, respectively. For each sample, odor concentrations were reported, and the slopes and intercepts of the regression line using both VDI and DynaScent calculation methods are also listed along with their corresponding DOCs and coefficient of regression (R^sup 2^).

The DOCs calculated from two methods have been compared using the Student ? test. For wastewater treatment plants, DOCs using both calculation methods have shown no significant difference (P = 0.98; n = 23). For Alumina refinery, DOCs using both methods have also shown no significant difference (P = 0.83; n = 15). One of the odor intensity measurement results is demonstrated in Table 2. For each sample, duplicate series were carried out. For each series, all of the dilution steps are presented in random order. The dilution ratio is calculated to be 2 to the power of the dilution step. For example: a dilution step of 11 has a dilution ratio of 2048. One blank sample was randomly presented along with other dilution steps. The panelist’s responses are shown numerically between 0 and 6, which represent the perceived odor intensity (see Table 1). The step- by-step calculation procedures using the VDI method are illustrated in Table 5. For the same sample, the corresponding OCI relationship using the DynaScent calculation method is shown in Figure 1.

DISCUSSION

The current study has used the latest developed digital olfactometer to improve the accuracy of the dilution ratios. The efficiency of contamination was clearly demonstrated throughout the study. This made it possible to use the random presentation. In general, the panelists could respond to the perceived odor in a more consistent manner after the panelists have been trained using hot water. The improved calculation method has further increased the reliability of the odor-intensity relationship.

Accuracy of Dilution Ratio

In recent years, more and more evidence suggests that instrumental performance of the olfactometer is the biggest source of error in odor measurement. Despite requirements in the European standard that the olfactometer must be calibrated at least once every year for accuracy and instability, many odor-testing laboratories have not yet demonstrated compliance to the instrumental performance requirements. In fact, most olfactometers do not include a user calibration feature and can only be calibrated by the manufacturers.

Table 4. Comparison of OCI relationships using DynaScent and VDI calculation methods: alumina refineries.

In the experience described here, many dynamic olfactometers with rotameters and MFCs will have great difficulty meeting instrumental performance requirements. It is believed that some laboratories use a “span adjustment” approach to deal with this problem.18 Some odor testing laboratories in Australia use accuracy and precision derived from n-butanol odor threshold results to substitute for instrument accuracy and precision. In the latest interlaboratory comparison study organized by the Victoria Environmental Protection Agency,19 noncompliance of laboratory performance was reported for four laboratories, despite all of the odor laboratories having National Analysis and Testing Authority laboratory accreditation.

The olfactometer used has been calibrated at least every 3 months depending on its usage. This calibration requires the settings of the olfactometer to be adjusted.10 In the past, odor testing laboratories only reported the calibration of individual rotameters or MFCs. Furthermore, a more frequent calibration check on the accuracy of the dilution ratio is also carried out once every month. Should noncompliance of the accuracy and instability of the instrument be observed, the olfactometer is scheduled for calibration. In the study, the olfactometer was calibrated ~2 months before the project and was checked for accuracy at the commencement of the study and checked again on the completion of the study. The accuracy and instability of the olfactometer met specified requirements at all of the stages.

Table 5. Example of VDI calculation results.

Decontamination of the OIfactometer

Many odor samples can easily adsorb onto the contact surfaces of the olfactometer, such as tubing, rotameter, or MFC, which will result in olfactometer contamination. For odor concentration measurement, the odor concentrations at the sniffing c\ups are below the odor threshold and are normally undetectable in most dilution steps. However, for odor intensity measurement, which presents the odor above its odor threshold in all of the dilution steps, the random presentation could easily contaminate the olfactometer at a low dilution ratio. This contamination can be carried over to the next dilution step to make the odor detection earlier.

It was reported that for rotameter- or MFC-based olfactometers, a flushing time of 3 hr was required to complete one odor intensity sample using random presentation and five panelists.20 In the authors’ experience during the odor concentration measurement, it normally took >12 hr to flush a contaminated olfactometer with MFCs. It would take an even longer time if the olfactometer was used for odor intensity measurement, where higher concentrations are presented.

The panelists’ responses for the blank have recorded oil of very weak or no odor. This has confirmed the efficient decontamination of the olfactometer. The operator frequently checks both sniffing ports for any residual odor between the series during operation and manually extends the flushing time to ensure there is no odor left between series. This process normally takes only 30-90 sec.

Presentation Order

From the author’s practical experience since 1996 and other researchers’ experience,21 if a sequential presentation order was used during the experiment, it only takes a few presentation rounds for a panelist to figure out the presentation pattern. The panelist will start to enter the corresponding responses effortlessly. It also takes very little time for every member of the panel to anticipate the response for the next dilution step.

Despite the use of random presentation order, the responses have shown an expected trend that the higher odor intensity indices were registered at higher concentration levels at the sniffing cups and the lower odor intensity indices at lower concentration levels. In most cases, the odor intensity indices of between O and 1 were reported around the odor threshold. The results have also shown a strong correlation between the perceived odor sensation and the POC at the sniffing cup. This confirms that the olfactometer delivered the required dilution ratios and was efficiently decontaminated.

Interpretation of the Odor Intensity Categories

The interpretation of odor intensity categories is an important step toward a reliable odor intensity relationship. Using the analogy from other human senses, detection, recognition, and annoyance are the three stages in sensing the environment. Detection is the first positive response that our brain responds to. Recognition is the result that our brain matched the signal with the memory. At this level, the brain has the mark for the reoccurrence. Annoyance is the warning signal that our brain is capable to respond to. For the odor intensity assessment, it is expected that detection covers the odor intensity indices of 1 and 2, recognition covers the odor intensity indices of 3 and 4, and annoyance covers the odor intensity indices of 5 and 6.

Unlike odor assessment carried out in the field, odor intensity assessment is performed within an odor-free environment which creates a constant background odor. The use of a single sniffing station composed of two sniffing cups has also ensured that all of the panelists have ~2 min resting time between assessments for the sense of smell to recover from the odor exposure.

Having trained the panelists in sensory recognition and scaling using the temperature sensation, the panelists have demonstrated improved performance in the ability to record the odor intensity categories. In the past, panelists have had some difficulties in deciding how they selected the odor intensity category. With the linkage between odor intensity and the temperature sensation, panelists were able to make informed assessment on the odor intensity, in particular, over a long period of time.

OCI Calculation Method

Calculation method is a very important step in developing a reliable OCI relationship. The VDI calculation method uses a complicated statistical model, which is based on the distribution of odor intensity categories. VDI calculation method is an indirect method that correlates the odor intensity indices with the dilution ratios (not the odor concentration presented at the sniffing cup). It can only be applied one sample at a time, and it is difficult to apply the method to different environmental samples. This also makes it difficult to apply the results in odor regulation. Clearly, the VDI method is used to determine how much reduction of an odor control measure is required to achieve the necessary reduction in odor sensation. The method is a manual process, because the frequency is plotted against the logarithm of the dilution number. In the study, linear regression is assumed so that the calculation can be programmed (Table 5). From the study, it was found that limited characteristic dilution numbers (CDNs) are left after the removal of insufficient data series at the top where I is 5 and/or at the bottom where I is O. There is no corresponding CDN where I is 6. As a result, only 4 CDNs, where I is 1-4, are plotted against the logarithm of the dilution numbers. For calculating the DOC where I is 3, this regression line may not be sufficient to cover the range if a reliable DOC is to be calculated.

The DynaScent calculation method assumes that the odor intensity scales are hybrid. Their numeric expressions are mathematically averaged and plotted against the logarithm of the IOCs (see Figure 1). This approach simply correlates the perceived odor and the POC and generates the graphic presentation. Most of all, the approach normalizes the initial odor concentrations from different measurements. It enables more odor intensity results from the same odor type to be plotted on the same chart and results in a single correlation line.

From an odor regulation point of view, it is more important that a more reliable relationship between odor intensity and the POC be established from many samples. This relationship can lead to the determination of the odor impact criterion with greater confidence.

OCI Relationship

By definition, at the odor threshold, the oil is expected to be 0.5. The small variations observed in the study were largely contributed to by the difference in odor sensitivity of the panelists, although all of the panelists passed the screening test. This was observed during the odor concentration measurement when all of the panelists did not register a correct and certainty response (OU of 1) at the same dilution step in a round. In some situations, panelists with higher sensitivity confirmed the detection of the odor a step earlier than others. In the subsequent odor intensity measurement, the most sensitive panelist might register the oil of very weak, whereas the rest of the panelists could not detect the odor (oil of O). It is more likely that the intercept will be >0.5 if the panel has several sensitive panelists. On the contrary, the intercept will be <0.5 if the panel has less sensitive panelists.

The subsequent study has confirmed that the intercept values for each type of odor will be more accurate at meeting the expected 0.5 value if more odor samples are analyzed and plotted.22 An increase in the number of samples taken means that more data points can be used to gain a more representative trend line. This will also help to remove any bias caused by outliers (points that are very distant from the average).

The intercept of the OCI relationship can also be an indication of instrument performance. OCI relationship for a piggery was the first case that used the same olfactometer.8 The study was a trial case for odor intensity. A DOC of 3.8 OU/m^sup 3^ is the smallest DOC in all of the studies so far. At that time, the olfactometer did not have the feature of decontamination. The intercept is -1.4. In a later dairy project,23 the same olfactometer was equipped with limited flushing capability. The intercept for the dairy odor was ~0.6. From the earlier mentioned studies carried out on similar sources to those included here,15 numerous samples had an intercept >2. In some cases, the intercept reached the odor intensity category of distinct at the odor threshold level. It is, therefore, extremely important that the olfactometer have the flushing procedure to reduce cross-contamination.

The correlation between odor intensity and odor concentration makes it possible that odor impact criteria can be defined on the basis of odor perception. In the past, the selection of odor criteria for defining the odor impact area was not supported by as rigorous a scientific method.

CONCLUSIONS

This study has applied the latest digital olfactometer in establishing odor concentration-intensity relationships. A total of 15 odor samples from 8 different sources at 3 alumina refinery sites and a total of 23 odor samples from 6 different sources at 2 sewage treatment plants were collected for analysis. The study confirmed that the DOCs for refinery odor and wastewater odor are in the range of 3.8-15.4 and 4.2-15.6 OU/m^sup 3^, respectively.

The review of the previous studies confirmed that reliable odor intensity measurement was strongly related with the instrument performance. The study found that accuracy of the dilution ratios was the most important parameter for reliable odor intensity measurement. It is necessary that the presentation order should be randomized to avoid the anticipation of the panelists’ responses. Therefore, olfactometers equipped with rotameters and MFCs may not be suitable for odor intensity measurement.

On the basis of the VDI 3882.1 guideline, several significant improvements in experimental procedures have been made to be consistent with the latest European standard EN13725. The accurate dilution ratio and efficient decon\tamination made it possible to present the dilutions randomly. The cleaning procedures between samples, between series, and between dilution steps have proved to be necessary in odor intensity measurement. The study confirmed the efficiency of the decontamination in the study.

The study has extended the category scale to the master scale with the introduction of the cross modality matching. Odor intensity categories were then further related to the detection, recognition, and annoyance of an odor. It was found that these changes have greatly improved the repeatability and reproducibility of the results.

The comparison of DynaScent and VDI calculation methods has shown that there is no significant difference in DOCs. The VDI method is a manual calculation process and can only be used for single sample or samples with the same initial concentration at one time. The new calculation method, which is compatible with the European standard EN13725, is simple and can be applied to many samples from the same type of odor to derive one regression line. With the increase of sample numbers, it is more like to produce much more reliable DOCs results.

An odor concentration-intensity relationship can be used to determine the odor impact criteria. To avoid odor complaints, the odor intensity in the vicinity of the sources should not exceed the distinct level. Furthermore, the odor intensity measurement can also be applied to determine the ambient odor level using the odor intensity categories. Contrary to the field panel, the use of a dynamic olfactometer in the laboratory can avoid the adaptation of the panelists and can produce more reliable results. With increasing experience in using odor intensity measurement, it is believed that the improved method can become an effective tool in solving odor complaints.

IMPLICATIONS

The development of odor regulations requires a quantitative assessment of the perceived odor. Odor intensity measurement correlates the perceived odor sensation and the inhaled odor level. The dose-effect relationship is used to define the DOC at the level of recognition. Consequently, the value defines the odor impact area when an odor dispersion model is used. The technique has been proven as an effective tool in developing site-specific or industry- specific odor impact criteria.

REFERENCES

1. VDI 3882.1-Olfactometry-Determination of Odor Intensity; Verein Deutscher Ingenieure: Dusseldorf, Germany, 1992.

2. VDI 3940 Part 1, Determination of Odorants in Ambient Air by Field inspections-Determination of the Frequency of Identifiable Odour in Ambient Air-Grid Measurement; Verein Deutscher Ingenieure: Dusseldorf, Germany, 2003.

3. Verein Deutscher Ingenieure. VDI 3940 Part 2, 2, Determination of Odorants in Ambient Air by Field Inspections-Determination of the Frequency of Identifiable Odour in Ambient Air-Plume Measurement; Verein Deutscher Ingenieure: Dusseldorf, Germany, 2003.

4. Guidance for the Assessment of Environmental Factors- Assessment of Odour Impacts from New Proposals No 47; Environmental Protection Authority: Western Australia, 2002.

5. Jiang, J.; Sands, J. Report on Odour Emissions from Poultry Farms in Western Australia, Principal Technical Report; Centre for Water and Waste Technology, University of New South Wales: Sydney, Australia, 1998; Available at http://www.environ.wa.gov.au/pubs/ (accessed 2006).

6. Jiang, J.; Sands, J. Report on Odour Emissions from Poultry Farms in Western Australia, Supplementary Technical Report; Centre for Water and Waste Technology, University of New South Wales: Sydney, Australia, 1998; Available at http://www.environ.wa.gov.au/ pubs/ (accessed 2006).

7. Jiang, J. Development of Odour Impact Criteria Using Odour Intensity Measurement and Community Survey. Presented at 2nd International Conference on Air Pollution from Agricultural Operations, Des Moines, IA, October 2000.

8. Jiang, J. Development of Odour Impact Criteria for the Australian Pig Industry; Prepared for Australian Pork Limited, The University of New South Wales: Sydney, Australia, 2001.

9. EnvironOdour Web site. Available at http:// www.environodour.com.au/ (accessed 2004).

10. Jiang, J. Development of the Next Generation Olfactometer- Dynascent, Odour Management Review; Ministry of the Environment: Japan, Beppu City, 2002.

11. Seinfeld. J. Atmospheric Chemistry and Physics of Air Pollution; John Wiley & Sons, Inc.: New York, 1998.

12. Amos, T.; Hyman, Odour Measurement and Control. In Patty’s Industrial Hygiene and Toxicology, 3rd rev. d.; clayton, G.D.; Clayton, F.E., Eds.; Wiley-Interscience: New York, 1982; pp 665- 705.

13. Chen, Y.; Bundy, D.; Hoff S. Development of the Relationship Between Odor Intensity and Threshold Dilution Ratio for Swine Units; J. Air & Waste Manage. Assoc. 1999, 49, 1082-1088

14. Nicolai, R.E.; Clanton, C.J.; Guo, H. Modeling the Relationship Between Detection Threshold and Intensity of Swine Odours. In Proceedings of the second International Conference: Air Pollution from Agricultural Operations, American Society of Agricultural Engineers; St. Joseph, Ml, 2000; pp 296-304.

15. Schulz, T.; Balch, A.; Bowly, S. Odour Intensity Measurement: An Overview of Its Potential for Use in Odour Impact Assessment and Control; Clean Air Environ. Qual. 2002, .”36, 38-41.

16. Standard prEN 13725, Air Quality-Determination of Odour Concentration by Dynamic Olfactometry; Comitt Europen de Normalisation: Brussels, Belgium, 2001.

17. AS/NZS 4323.3:2001 Stationary Source Emissions-Part 3: Determination of Odour Concentration by Dynamic Olfactometry. Standards Australia: Sydney, Australia, 2001.

18. van Harreveld, A.P.; Heeres, P.; Harssema, H. A Review of 20 Years of Standardization of Odor Concentration Measurement by Dynamic Olfactometry in Europe, J. Air & Waste Manage. ASSK, 1999, 49, 705-715.

19. Bardsley, T.; Demetriou, J. Interlaboratory Odour Study Conducted With EPA Approved Method; Publication sr2; Victoria Environment Protection Agency: Melbourne, Australia, 2003.

20. Schulz, T. Response to CASANZ on David Pitt’s Criticism of Modified VDI 3882 Intensity Testing Method; Available at http:// www.casanz.org.au/ (accessed 2003).

21. Pitt, D. Letter to the Editor. Clean Air Environ. Qua/. 2003, 37, 8-10.

22. Jiang, J.; Coffey, P.; Toohey, B., Odour Intensity Measurement for Wastewater and Alumina Industries; Presented at 17th International Clean Air & Environment Conference, Hobart, Australia, May 3-6, 2005.

23. Jiang, J. Use of Odour Intensity in Impact Assessment; Presented at National Workshop on Odour Assessment for Piggeries, Mascot, Australia, November 13-14, 2002.

John Jiang

EnvironOdour Australia Pty Ltd., Rosebery, New South Wales, Australia

Patrick Coffey

Alcoa Alumina Australia, Applecross, Western Australia, Australia

Brendan Toohey

Western Australia Water Corporation, Leederville, Western Australia, Australia

About the Authors

John Jiang is the director of EnvronOdour Australia Pty Ltd. Patrick Coffey is a senior environmental officer ay Alcoa Alumina Australia. Brendan Toohey is a manager of odour management at Western Australia Water Corporation. Address correspondence to: John Jiang, EnvronOdour Australia Pty Ltd., Suite 305, 414 Gardeners Road, Rosebery New South Wales 2018, Australia; phone: + 612- 93266699; fax: +612-9326-6699; e-mail: j.jiang@environodour. com.au.

Copyright Air and Waste Management Association May 2006

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