Tong Park Pty Ltd. Pink Pond Odour. Research Study

Transcription

1 Tong Park Pty Ltd Pink Pond Odour Research Study Final Report November 2001 Part of APL Project No Telephone: Fax: fsa@fsaconsulting.net Website:

2 PROJECT TITLE: Tong Park Pty Ltd Pink Pond Odour Research Study RESEARCH ORGANSIATION: FSA Environmental PRINCIPAL INVESTIGATOR: Mr Eugene McGahan FSA Environmental PO Box 2175 TOOWOOMBA Q 4350 Ph: Fax: fsa@fsaconsulting.net Website: PROJECT TERM: Project commencement date: January 2001 Project completion date: November 2001 When referring to this document, the following reference should be used: McGahan E.J., Nicholas P.J., Watts P.J., Galvin G., Lowe S., Stepnuk L.M. and Casey, K.D Tong Park Pink Pond Odour Research Odour Study. Report Prepared for Tong Park Pty Ltd and Australian Pork Limited, November Report No 5590/4, 4 October 2001, 5590 Final Report.doc Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 1

3 Table of Contents 1. EXECUTIVE SUMMARY INTRODUCTION PIGGERY ODOUR SOURCES Area Source Odour Sampling Existing Pond Odour Emission Data Australian Research Other Research Odour emission rate versus loading rate Factors Affecting Pond Odour Emission Manure Handling and Anaerobic Digestion Pond Loading Rate Pond Design Rational Design Standard Pink Ponds CURRENT ODOUR SEPARATION GUIDELINES FOR PIGGERIES PROJECT PROPOSAL Introduction Methodology DATA COLLECTION Experimental design and planning Odour collection Description of Piggery Ponds Sampled Piggery A Piggery B Piggery C Piggery D Piggery E Olfactometry Effluent Sampling Sludge Sampling Ammonia Sampling Effluent Loading Rate RESULTS Pond Loading Rates...41 Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 2

4 7.2. Effluent Analysis Pond Pinkness Ammonia Analysis Sludge Analysis Odour Emission Rate DATA ANALYSIS Average Pond Emission Rates Effect of Loading Rate on Odour Emission Rate Effect of Ammonia Emission on Odour Emissions Effect of Pond Chemistry on Odour Emission Rate Effect of Pink Ponds (Chlorophyll a) on Odour Emission Rate Effect of Pond Chemistry on Pink Ponds (Chlorophyll a) Effect of VS:TS Ratio of Sludge on Sludge Accumulation CONCLUSIONS IMPLICATIONS AND RECOMMENDATIONS REFERENCES ACKNOWLEDGEMENTS APPENDIX A INDEPENDENT REVIEW Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 3

5 Tables Table 1 - Piggery Pond Odour Emission Rates (Schulz and Lim, 1993)...13 Table 2 Pond Odour Emissions versus Wind Speed and Stability Class...14 Table 3 - Piggery Pond Odour Emission Rates (Smith et al., 1999)...16 Table 4 Study milestones...29 Table 5 Loading rates of piggeries initially investigated...31 Table 6 - Pond loading rates (kg/day) Table 7 - Total and active volumes (m 3 ) for each pond...41 Table 8 - K factor and loading rates (g of VS/m³/day) for each pond...41 Table 9 - Effluent Analysis results for each pond surveyed...42 Table 10 Ammonia Concentrations and emissions from wind tunnel...43 Table 11 - VS:TS ratios of sludge at various depths...43 Table 12 - Odour emission rates, E and E 1 for Piggery A...44 Table 13 - Odour emission rates for Piggery B...45 Table 14 Odour emission rates (E 1 ) for Piggery B...45 Table 15 - Odour emission rates, E and E 1 for Piggery C...46 Table 16 - Odour emission rates, E and E 1 for Piggery D...46 Table 17 - Odour emission rates, E and E 1 for Piggery E Table 18 - Two day average OER, total odour emission and odour emission per SPU for all 5 piggeries...48 Figures Figure 1 - Piggery A pond with sampling and loading sites shown...34 Figure 2 - Piggery B pond with sampling and loading sites shown...34 Figure 3 - Piggery C pond with sampling and loading sites shown...35 Figure 4 - Piggery D pond with sampling and loading sites shown...35 Figure 5 - Piggery E pond with sampling and loading sites shown...36 Figure 6 - OER (OU/m²/s) versus VS loading rate (% of maximum design loading rate)...49 Figure 7 - OER (OU/m²/s) as a function of active volume per SPU...50 Figure 8 - OER (OU/m²/s) as a function of total volume per SPU...50 Figure 9 - Odour emission per SPU versus active volume per SPU...51 Figure 10 - Odour emission per SPU versus total volume per SPU...51 Figure 11 - Total odour emission versus kilograms of volatile solids added per day.52 Figure 12 - Odour emission rate versus kilograms of volatile solids added per m² of surface area...52 Figure 13 Relationship between ammonia emission rate and odour emission rate53 Figure 14 Relationship between Chlorophyll a and odour emission rate...54 Figure 15 Relationship between pond electrical conductivity and Chlorophyll a concentrations...54 Figure 16 Relationship between pond ph and Chlorophyll a concentrations...55 Figure 17 Relationship between pond Iron concentration and Chlorophyll a concentrations...55 Figure 18 Percentage of VS degraded based on VS:TS ratio of sludge...56 Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 4

6 Photographs Photograph 1 Heavily-loaded Anaerobic Pond (with upsurging of sludge)...18 Photograph 2 Heavily loaded Anaerobic Pond (with floating vegetation)...18 Photograph 3 Pink Anaerobic Pond...26 Photograph 4 Pink Secondary Pond...26 Photograph 5 Wind Tunnel Sampling Equipment...33 Photograph 6 Wind Tunnel Sampling on Anaerobic Pond B...33 Photograph 7 Odour Sampling on Pond A...36 Photograph 8 Pond B (fine scum around edges)...37 Photograph 9 Pond C (effluent inlet on left foreground)...37 Photograph 10 Pond D (inlet on right hand side)...38 Photograph 11 Pond E...38 Photograph 12 DPI Multiple Panellist Dynamic Olfactometer...39 Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 5

7 1. EXECUTIVE SUMMARY Odour emissions are currently the most significant community amenity issue facing the Australian pig industry. Siting of piggery developments is constrained by the need to have large buffers to reduce odour impact on neighbouring receptors. The buffer requirements are calculated using either standard procedures provided by regulatory authorities or odour modelling. There is currently limited data on the odour emission from piggeries. However, from this data it is estimated that as much as 80% of the odour is emitted from the treatment ponds. The odour emission rate is expressed as a rate per m² of pond surface area. From the currently available data it is assumed the emission rate for a primary pond is six times greater than for a secondary pond. Hence, the main odour source is the primary treatment pond. The Queensland Department of Primary Industries has adopted standard odour emission rates to be used in modelling for a primary treatment pond and a secondary treatment pond. It is assumed that the variation in odour emission rate from ponds is probably driven by pond loading rate, pond age, microbiological population, sludge accumulation, pond chemistry, pond temperature, surface crusting and possibly other, as yet unidentified, factors. For example, there is substantial practical experience that suggests that odour emissions from ponds that support purple-sulphur bacteria ( pink ponds ) are substantially less than black, bubbling anaerobic ponds. It is accepted that the condition (and therefore, odour emission rate) of primary ponds varies greatly from highly-odorous, heavily-loaded ponds to low-odour, lightly-loaded ponds. However, at present, there is not enough data available to distinguish between different types of primary ponds and their odour emission rate. Anaerobic piggery ponds are currently designed to provide a minimal treatment volume based on volatile solids loading rates for a region, plus some allocation for sludge accumulation. This maintenance of active volume is provided to minimise odour generation, but to date no data has been collected on the influence of volatile solids loading rate on pond odour emission rate. Much of the emissions data collected in the past have not included measurements that provide an indication of which factors most affect pond odour emissions. For this project, data was collected from a number of anaerobic ponds to provide information on odour emissions from anaerobic ponds, including which factors influence odour emission rate. Five ponds were sampled over a six- week period in February/March Two sets of odour emission data were collected from each pond on two separate days. Odour samples were collected using a grid pattern to provide a representative odour emission rate for each pond. Pond loading rates were estimated from predictions of manure production for each piggery and surveys of pond volumes. Ammonia emission rates and pond chemistry measurements were also conducted for each pond. Pond chemistry measurements included ph, redox, electrical conductivity, pond temperature, total N, total P, ortho P, sulphates, sulphides, total VFA, VS, TS, chlorophyll a, sodium, calcium, potassium, magnesium, copper, zinc and total iron. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 6

8 The collected data was primarily analysed to determine if relationships existed between pond loading rates and odour emission rates. The data was also analysed to determine if relationships existed between pond chemistry and emission rate; concentration of purple sulphur bacteria (psb) and emission rate; pond chemistry and psb. The odour emission data collected as part of this study does not support the theory that odour emission rate will increase at the same rate as the volatile solids loading rate per unit volume. Total odour emission rates appear to be more dependent on the total amount of VS added to the pond, regardless of the loading rate of volatile solids per unit volume. No relationship was found between the amount of purple sulphur bacteria (psb), as measured by chlorophyll a in the pond, and the odour emission rate. This suggests that the amount of psb (pinkness) does not influence the level of odour emission from an anaerobic piggery pond. However, increased pond ph, electrical conductivity and iron concentrations all appeared to reduce the concentration of chlorophyll a in the pond. No relationship was found between any measures of the pond chemistry and odour emission rate. There was also no relationship between pond ammonia emission rate and odour emission rate. The ability of each pond to treat volatile solids was examined by considering the VS:TS ratio within the sludge. It was found that the ponds with higher volatile solids loading rates had higher VS:TS ratios in the sludge. This suggests that ponds with higher loading rates have less ability to degrade VS and will thus have a higher sludge accumulation rate (require more frequent desludging). Based on the findings of this study it is recommended that further work be performed on anaerobic ponds at a commercial scale. This work should include odour emission measurements conducted over an extended period on two ponds with different volatile solids loading rates. Both ponds should receive the same amount of volatile solids, but have significantly different volumes. This would provide sufficient information on different ponds to determine if there is a difference in total pond odour emissions. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 7

9 2. INTRODUCTION In Queensland, the impact of odours on residents of neighbouring houses is a major issue to be addressed when approving a new piggery. There are two methods that can be used to assess odour nuisance. The first method involves the use of standard formulae that are described in the Government guidelines. This method is designed for small single-unit piggeries of standard design and configuration and is not suitable for large or multi-site piggeries. The second method involves modelling the dispersion of odours from the proposed piggery and comparing the predicted odour impact against acceptability criteria used by the Department of Primary Industries (DPI). The odour dispersion modelling allows multiple-site piggeries with non-standard designs to be assessed. The dispersion model used is AUSPLUME V4.0, which is a Gaussian plume dispersion model accepted by regulatory authorities across Australia. The model requires the following input data: Hourly wind speed, direction, stability class, temperature and mixing height climate data for an extended period usually one full year or longer. The location co-ordinates for all odour sources. The location co-ordinates for each neighbouring house and town (receptors). The surface roughness of the land between the odour sources and each receptor. The odour emission rate for each odour source. A standard method and protocol for odour modelling at a piggery has been developed by FSA Environmental and accepted by DPI. This method uses odour concentrations measured using dynamic olfactometry to an accepted standard. While there may be some shortcomings with the method due to lack of suitable data, it is accepted by government. There is little room to deviate from the accepted protocol. In the standard protocol, it is accepted that the major odour sources are the piggery sheds and the waste treatment ponds. For piggery sheds, the odour emission rate is mainly dependent on the number of pigs in the shed, the manure removal method, ventilation and temperature. The variation of odour emission rate with pond type is probably driven by pond loading rate, pond age, microbiological population, sludge accumulation, pond chemistry, pond temperature, surface crusting and possibly other, as yet unidentified, factors. For example, there is substantial practical experience that suggests that odour emissions from ponds that support purple-sulphur bacteria ( pink ponds ) are substantially less than black, bubbling anaerobic ponds. Using the currently available pond-emission data, the DPI adopted standard odour emission rates for a primary treatment pond and a secondary treatment pond. The odour emission rate is expressed as a rate per m² of pond surface area. The rate for a primary pond is six times greater than from the secondary ponds. Hence, the main odour source is the primary treatment pond. It is accepted that the condition (and therefore, odour emission rate) of primary ponds varies greatly from highly-odorous, Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 8

10 heavily-loaded ponds to low-odour, lightly-loaded ponds. However, at present, there is not enough data available to distinguish between different types of primary ponds. The available data and subsequent modelling suggests that, for a typical piggery in Queensland, 10% to 20% of the odour from the site comes from the sheds and 80% to 90% of the odour comes from the ponds. Given the scarcity of pond emission data and the high contribution of anaerobic ponds to total piggery emissions, this project aimed to provide more information on odour emissions from anaerobic ponds and which factors influence odour emission rate. Hence, this study was undertaken for three primary reasons: 1. There is limited data on odour emission rates from piggery anaerobic ponds and what factors affect odour emission rate. 2. The design standards currently adopted to size piggery anaerobic ponds were based on predictions of odour detection from 25 years ago and methods of sampling and analysing odour have vastly improved since then. 3. There is a sufficient amount of anecdotal evidence that the presence of purple sulphur bacteria in piggery anaerobic ponds is an indication of good pond function and reduced odour emissions, but no odour emission measurements have been conducted to confirm this. The aims of this study were to: 1. Determine odour emission rates from a piggery anaerobic lagoon based on particular operating parameters. 2. Improve the understanding of which factors influence odour emissions to enhance currently adopted methods of pond design. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 9

11 3. PIGGERY ODOUR SOURCES There are many potential odour sources at a piggery. They can include: Piggery sheds Effluent treatment ponds Effluent irrigation areas Manure stockpiles Compost stockpiles Carcase disposal areas. In the standard protocol, it is accepted that the major odour sources are the piggery sheds and the waste treatment ponds. FSA Environmental (Watts 1999a) undertook a research project funded by the Pig Research and Development Corporation (PRDC) in which all available piggery odour emission data around the world was collated and summarised. It was found that very limited good-quality data is available. For piggery sheds, there is enough data available from the Netherlands, USA and Australia for reasonable estimates of shed odour emissions to be made. The odour emission rate is mainly dependent on the number of pigs in the shed, the manure removal method and temperature. However, for effluent treatment ponds, the only Australian data that has been collected is from a limited number of ponds, with a minimum number of data points. At the time that this data was collected, no complementary information was gathered, such as pond volatile solids loading rate. Developments in odour measurement techniques and standards over the past ten years have resulted in significant changes to the methods used for sampling and analysing odour emissions. These changes have reduced variation in results and improved consistency between research groups. These changes have resulted in difficulty comparing data gathered using old methods with data gathered using current methods (Watts, 1999a) Area Source Odour Sampling Area sources are the most difficult odour source from which to estimate odour emission rates. This is because there is no way of directly measuring or sampling emissions from the surface. The emission rate must therefore be estimated indirectly from the odour concentration of a sample of air following mixing with the emitting source. The major problems are that: There is no substantial mass flow of air to sample; and The emission rate typically varies both temporally and spatially. Odours from area sources are emitted through volatilisation or evaporation of odorous compounds at the surface and from the movement of bubbles of gas from the body of the pond to the surface. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 10

12 Odour volatilisation occurs by diffusion at the surface / air interface. The process happens when odorous compound concentrations at the surface are much higher than ambient air concentrations. The odorous compounds volatilise, or diffuse into the air, in an attempt to reach equilibrium between the surface and the overlying air. Convective mass transfer takes place in the overlying air. Convection occurs when air flows over the surface, sweeping odorous compounds into the air near the surface. The convective mass transfer rate relates directly to airflow velocity over the surface. Together, diffusion, convection and gaseous bubble release determine rates of volatilisation of odorous compounds and odour emission rates from extensive surfaces to the air. The relative importance of diffusion and bubble release is unknown but for active ponds, bubble release is obvious and significant. This issue has been researched extensively in Australia in recent years due to odour issues associated with intensive livestock systems (mainly cattle feedlots). In Toowoomba, the University of Southern Queensland and the Department of Primary Industries have published numerous papers on the topic (Smith and Hancock 1992, Smith 1993, Smith and Watts 1994 (a & b), Smith 1995, Smith 1996, Smith and Kelly 1996). In Sydney, the Centre for Water and Wastewater Technology has also undertaken similar work (Bliss et al. 1995, Jiang et al. 1995). Review papers have been prepared. From this work, the following conclusions have been drawn. For piggery ponds or piggery waste spreading areas, the possible odour sampling techniques are: Physical surface sampling methods Downwind sampling methods. For physical sampling methods, the two most common types are: Flux hoods (isolation chambers) Wind tunnels For downwind sampling methods, the options include: The TPS method The STINK method A detailed discussion of this issue is included in Watts (1999a). In regard to the choice between a flux hood and a wind tunnel, Watts (1999a) concluded that: The flux hood (isolation chamber) was not designed to take into account convective mass transfer caused by air movement above an emitting surface. The aerodynamics of the device does not guarantee the repeatability and reproducibility of the emission rates measured. Although not universally accepted, our view is that the device should not be used to determine the emission rates from an area surface for use in dispersion modelling. In our opinion, the portable wind tunnel system simulates wind movement in the atmosphere and is considered to be a more appropriate sampling technique in the determination of odour and VOC emissions from an area surface than flux hoods. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 11

13 3.2. Existing Pond Odour Emission Data Australian Research Smith et al. (1999) concludes that ponds are the major source of odours at typical Australian piggeries contributing about 75% of all emissions. Camp Scott Furphy Pty Ltd (1993) concluded that 82% of odour emissions from the Scone piggery resulted from the pond system. However, given this importance, there are a very limited number of odour emission measurements available for piggery ponds in Australia. The data available are Schulz and Lim (1993) and Smith et al. (1999). Schulz and Lim (1993) derived emission rates using wind tunnels floating on pond surfaces. Their wind tunnel had an exposed base area, 1000 mm long and 600 mm wide. Measured cross flow speed within the hood ranged from 0.2 to 0.4 m/s. Emission rates from anaerobic ponds ranged from OUm/s. For facultative ponds, emission rates ranged from OUm/s and aerobic ponds varied from OUm/s. Due to poor pond descriptions in their data, it is impossible to be able to assign emission rates to specific pond conditions. Their complete data is given in Table 1. These results were obtained using sound sample handling and storage procedures, but the olfactometry was not undertaken to a standard that can be compared to current methods as no butanol thresholds were quoted. However, these emission rates apply to the wind tunnel measurements at a specific wind speed and wind speed adjustments can be made. These can be performed using the methodologies outlined by Smith (1993). It is understood that the Schulz and Lim (1993) wind tunnel measurements were made with a tunnel wind speed of 0.3 m/s at an average height of m above the pond surface. The stability conditions in a wind tunnel can be most closely described as neutral as there should be no significant temperature gradient in the tunnel and solar radiation effects can be excluded. A logarithmic profile can be used for the wind speed adjustment with a roughness height of 0.03 m to represent the surface roughness of ponds. As outlined by Pollock (1997), the exponent for liquid surfaces should be 0.5 (as derived by UNSW) as opposed to 0.63 for feedlot surfaces derived by Smith and Watts (1994a). Some uncertainty exists as to the most appropriate exponent to use as the work of Smith and Watts (1994a) seems to indicate that the exponent is dependent on the physical dimensions of each wind tunnel. Hence, for the wind tunnel data, the odour emission rate varies with tunnel wind speed according to: V M ( U / U ) 0. 5 E = E EQUATION 1 T M where E v = odour emission rate at tunnel wind speed, u t E m = base odour emission rate measured at tunnel wind speed, u m u t = wind tunnel speed (m/s) u m = tunnel wind speed for base odour measurements, i.e. 0.3 m/s. 0.5 = adopted exponent Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 12

14 Watts (1999a) found that a wide range of different wind tunnel designs and operating wind speeds have been used. Equation 1 can be used to normalise the data from various studies to a standard wind speed. TABLE 1 - PIGGERY POND ODOUR EMISSION RATES (SCHULZ AND LIM, 1993) Odour Source Odour Concentration (OU) Specific Odour Emission Rates (OUm/s) Anaerobic Pond 270± ±5.7 Aerobic Pond 154± ±2.6 Facultative Pond 208± ±4.9 Anaerobic Treated Effluent 134± ±1.9 Pond (no scum) Anaerobic Treated Effluent Pond (with scum) 183± ±3.3 Aerobic Treated Effluent Pond (no scum) Aerobic Treated Effluent Pond (with scum) Facultative Treated Effluent Pond (no scum) Anaerobic Treated Effluent Pond (with scum) 106± ± ± ± ± ± ± ±3.3 The formula to convert wind speed at 10 m (for example) to wind speed at m (i.e. tunnel speed) in neutral stability is: U T 10 ( z0 2 ) ln( 10 / z ) ln / = U EQUATION where u t = wind tunnel speed (m/s) u 10 = wind speed at 10 m z 0-1 = surface roughness for anemometer at 10 m (0.3 m) z 0-2 = surface roughness for pond (0.03 m). This reduces to UT 10 = U 0.41 EQUATION 3 It is accepted that atmospheric stability would also affect odour emission rate. This is because stability affects both the slope of the wind speed profile and the degree of turbulence. These two factors are partially co-dependent so accounting for both these factors would not be valid. Pollock (1997) and Kaye (1997) detail a methodology to deal with wind profile treatments and these were agreed by the Scone piggery commissioners to be valid. (The Scone case concerned a large piggery proposal near Scone, NSW (CMPS&F, 1993) in which odour was the major concern). Ormerod (1991 and 1994) details a treatment to deal with turbulence Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 13

15 effects based on vertical mixing heights. The Ormerod methodology would result in a 50% reduction in pond emission rate for F class stability and the Pollock method would result in a 60% reduction. Kaye and Jiang (1999) use a different approach to the same problem. They agree that Equation 2 represents the relationship between tunnel wind speed and odour emission rate. They then relate tunnel wind speed to ambient wind speed using U T N = U10 EQUATION 4 10 where u t = wind tunnel speed (m/s) u 10 = wind speed at 10 m N = the wind profile exponent The wind profile exponent, n, is assigned on the basis of the Pasquill stability class. For their work, they used exponents in AUSPLUME for Irwin Urban conditions. The exponents for stability classes A, B, C, D, E, and F were 0.15, 0.15, 0.2, 0.25, 0.4 and 0.6 respectively. The AUSPLUME manual recommends using the Irwin Rural profiles for rural applications. The rural exponents for stability classes A, B, C, D, E, and F are 0.07, 0.07, 0.1, 0.15, 0.35 and 0.55 respectively. Hence, for neutral stability (Class D), n=0.15 (rural) and Equation 4 reduces to UT 10 = U 0.52 EQUATION 5 For the purposes of their study, they modified the wind speed categories in AUSPLUME to better reflect the importance in odour situations of low wind speeds. Table 2 shows the selected wind speed categories. Using Eqns 1 and 4, it is possible to calculate the relative pond odour emission rates for different wind speeds at 10 m and stability classes as compared to the wind tunnel measurements. Table 2 shows the relative pond odour emissions expressed as a percentage of a measurement made in a wind tunnel with an average height of m at 0.3 m/s tunnel wind speed. For stability class F, the emission rate is 42% of the Stability Class D data. This is a similar result to the Ormerod methodology described above. TABLE 2 POND ODOUR EMISSIONS VERSUS WIND SPEED AND STABILITY CLASS Wind Speed Category Speed Rate (m/s) Median Wind Speed Stability Class A B C D E F (m/s) Relative Odour Emission Rate (%) % 86% 80% 72% 46% 30% % 149% 139% 125% 80% 52% % 192% 180% 161% 104% 67% % 227% 213% 190% 123% 79% % 257% 241% 216% 139% 90% 6 > % 399% 374% 335% 216% 139% Assumptions: Ambient wind speed measured at 10 m Tunnel height m Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 14

16 Tunnel wind speed 0.3 m/s Eqns 1 and 4 used. Although important to odour modelling, this analysis is completely theoretical and is not supported with experimental data. We are not aware of any pond odour emission measurements made under a range of wind speeds and stability classes that could confirm this analysis. More recently, Smith et al. (1999) has undertaken odour emission rate measurements from piggery ponds in Queensland. Emission rates were determined using both wind tunnels (Smith and Watts, 1994a) and back-calculation (Smith 1995) methods. Table 3 shows the data obtained by Smith et al. (1999). This data shows a wider range of emission rates than given by Schulz and Lim (1994). The emission rates from primary anaerobic ponds are similar to Schulz and Lim (1994) at OUm/s but, importantly, the data shows that the emission rates from secondary facultative ponds are typically less than 10 OUm/s and many were less than 5 OUm/s (normalised data). This data was collected using sound sampling methodology. Olfactometry was carried out to the NVN 2820 method with butanol thresholds recorded. The measured emission rates have been normalised to the odour emission rate with a wind speed of 1 m/s measured 1 m above the pond surface (E* 1 ). The theory outlined above of varying odour emission rates with wind speed and stability class was used to develop the separation guidelines for piggeries in Queensland. The standard odour emission rates used were averaged from the results of Smith et al (1999) as 30 OU/m 2.s for primary (anaerobic) ponds and 5 OU/m 2.s for secondary (facultative) ponds (E* 1 ). Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 15

17 TABLE 3 - PIGGERY POND ODOUR EMISSION RATES (SMITH ET AL., 1999) Description Sampling Method C (OU) Stability Class V (m/s) at 1 m height E (OUm/s) E 1 * (OUm/s) Site 1A Unit 1 anaero east Ambient 41 C Unit 1 anaero east Ambient 26 C Unit 1 anaero west Ambient 197 C Unit 1 anaero west Ambient 117 C Unit 1 anaero west Ambient 215 C Unit 2 primary Ambient 197 C Unit 2 primary Ambient 279 C Unit 2 primary Ambient 181 C Unit 1 second east Ambient 29 C Unit 1 second east Ambient 8 C Unit 1 second west Ambient 38 C Unit 1 second west Ambient 9 C Unit 2 secondary Ambient 26 C Unit 2 Secondary Ambient 13 C Tertiary Ambient 11 C Tertiary Ambient 5 C Site 2B Anaerobic Pond Ambient 98 C Site 3B Facultative Pond Ambient 12 A Facultative Pond Ambient 10 A Site 6B Anaerobic Pond Ambient 256 A Anaerobic Pond Ambient 256 A Anaerobic Pond Ambient 117 A Anaerobic Pond Ambient 148 C Anaerobic Pond Ambient 81 C Anaerobic Pond Ambient 45 C Anaerobic Pond Ambient 55 C Anaerobic Pond Wind Tunnel 121 n/a Anaerobic Pond 110 n/a Anaerobic Pond 110 n/a Anaerobic Pond 90 n/a Anaerobic Pond 121 n/a Anaerobic Pond 134 n/a Facultative Pond 58 n/a Facultative Pond 55 n/a Facultative Pond 27 n/a Facultative Pond 33 n/a Facultative Pond 16 n/a Facultative Pond 22 n/a Facultative Pond 20 n/a E 1 * is the odour emission rate normalised to an ambient wind speed of 1 m/s measured at 1 m height above the pond surface. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 16

18 The following discussion is taken from Smith et al. (1999). Emissions from the Site 1A ponds were relatively low. The unit 1 primary (or anaerobic) west pond is 16 years old. As part of an upgrade of unit 1 waste storage system, the unit 1 primary east pond was built 10 years ago. Comparing the emission rates of these two ponds shows that the odour emission rate is much greater in the older (and therefore more heavily loaded) pond. The unit 2 primary pond is nearly 12 years old and is quite heavily loaded. The piggery manager is currently planning to de-sludge this pond. This indicates recognition of the high loading rate (and corresponding high odour emission rate) and supports the idea that the recommended design life of ponds is about 8 to 10 years. The other secondary (or facultative) and tertiary (or wet weather storage) ponds have much lower odour emission rates due to their low organic loading. {Unit 2 is piggery D sampled as part of this study and had still not been desludged.} Given the age and management of these ponds it is reasonable to assume the emission rates from the two older primary ponds are greater than for a typical, well managed primary (or anaerobic) pond. Since emission measurements were taken under the same conditions on the same day, the greater emission rates from these two ponds could be assumed to be due to the higher loading rates of the ponds (although loading rates were not measured). When corrected to emission rates corresponding to a wind speed of 1 m/s, the emission rates from the anaerobic and primary ponds compare well with the measurements of Schulz and Lim (1993). The results from Site 6B show odour emission rates substantially greater than those measured at Site 1A. The average odour emission rates for the anaerobic and facultative ponds in Trial A were 19.9 and 2.3 OUm²/s, respectively, while the average rates for the similar ponds measured in Trial B were 31.2 and 6.8 OUm²/s, respectively. This is due largely to the poor management conditions at the Site 6B ponds, where severe overloading was occurring. Again when corrected to a wind speed of 1 m/s the majority of the rates are comparable to those of Schulz and Lim (1993). Although the documentation is not clear, it is understood that the work of Schulz and Lim (1993) and Smith et al. (1999) was conducted on what could be described as heavily-loaded ponds. Characteristics of this type of pond include: Organic loading rate greater than recommended by the Rational Design Method Dark colour Dark, floating scum Upsurging of sludge from the pond bed on large odour bubbles Non-uniform bubbling across the surface Acrid or sour character to the odour. Photograph 1 and Photograph 2 show these characteristics. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 17

19 PHOTOGRAPH 1 HEAVILY-LOADED ANAEROBIC POND (WITH UPSURGING OF SLUDGE) PHOTOGRAPH 2 HEAVILY LOADED ANAEROBIC POND (WITH FLOATING VEGETATION) Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 18

20 Other Research Heber (1998) investigated the effect of lagoon aeration on odour emissions from piggery ponds. Odour concentrations were measured with the Purdue University dynamic olfactometer, but no butanol thresholds were reported. Odours were sampled from the pond surface using a buoyant wind tunnel of individual design. The chamber sampling area was 0.76 m² and had a clear height of 150 mm. Chamber width and lengths were not quoted. The chamber was operated with a surface velocity of 1.1 m/s, which is much higher that currently adopted standards for measuring emission rates from ponds in Australia of 0.3 to 0.5 m/s using wind tunnels. The sampling methodology used was sound, but the differences in design between the Heber wind tunnel and the wind tunnels used in Australia are likely to influence results. The aerated pond was a conventional anaerobic pond in which aerators had been installed. It had a volume of 16.3 ML and a surface area of 9655 m². The organic loading rate was 142 g VS/m³/day compared to the locally recommended loading rate of 96 g VS/m³/day. Lagoon slurry temperature was 20 C. The COD, BOD, TSS, VS and DO of the samples taken near the surface of the lagoon were 7105, 1646, 1450, 1040 and 0.04 mg/l respectively. Slurry ph was 8.1. (These parameters are similar to many Australian anaerobic ponds.) Over a four-day period, odour emission rates varied from 1.5 to 2.05 OUm/s with an average of 1.67 OUm/s. For comparison, odour emissions from non-aerated anaerobic lagoons at two other piggeries were measured. Lagoons #1 and #2 had organic loading rates of 80 and 51 g VS/m³/day respectively. Odour emission rates were 11.7 and 7.9 OUm/s respectively with an average of 9.6 OUm/s. These data can be converted to a tunnel wind speed of 0.3 m/s as used by Schulz and Lim (1993) using Equation 1. The average odour emission rate from the aerated lagoon is 0.87 OUm/s and from the non-aerated lagoons, it is 5.0 OUm/s. The nonaerated lagoon data (i.e. typical anaerobic pond) is about 20%-25% of data collected in Australia using wind tunnels. It is difficult to estimate how much of this variation would be due to the design differences between the odour sampling equipment used in the different studies. Odour emission measurements were collected by Heber et al. (2000a) from two anaerobic ponds with different loading rates. Two odour samples were collected from each of two locations on each pond at six separate visits. Samples were collected using a buoyant wind tunnel (Heber et al., 2000b). This wind tunnel was designed to collect low concentration odour emissions, and hence differs considerably from the wind tunnels used in recent Australian piggery pond studies. It is difficult to estimate the relationship between this Heber wind tunnel and the wind tunnels used in Australian studies, but some difference in results would be expected. Odour samples were analysed using an AC SCENT olfactometer using methods compatible with the 1999 CEN TC264 Olfactometry Standard (ie equivalent to the Australian Standard). Lagoon effluent was analysed for ph, total solids (TS), volatile solids (VS), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), ammoniacal nitrogen (NH 4 + -N) and phosphorous (P). Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 19

21 Both ponds sampled were the first cell of a two-stage lagoon for a breed-to-wean piggery. Pond A was estimated to have a typical loading rate equating to 62.5 g VS/m³/day. Pond B was estimated to have a light loading rate equating to 22.4 g VS/m³/day. The mean odour emission from pond A was 6.2 OU/m²s and from pond B was 2.9 OU/m²s. The results indicated generally higher emissions from pond A, although after statistical analysis of the data, no significant difference was found. Of the effluent characteristics, pond A had higher concentrations of TS, TKN, NH 4 + -N and P, but lower VS. Due to the small amount of data obtained from this work, it is difficult to draw any conclusions. On most occasions, significant variation in odour emissions was found from the samples from different locations on the one pond on the same day. This agrees with results found in Australia suggesting significant variation in the odour emissions from different points on a pond surface at a given time (DPI, unpublished). Thus, to obtain an accurate estimate of overall pond emissions, it is necessary to take a number of samples across the pond Odour emission rate versus loading rate The finding of Smith et al. (1999) that odour emissions from a heavily-loaded anaerobic pond is much higher than lightly-loaded facultative ponds is supported by Heber (1998) and Overcash et al. (1976). Overcash et al. (1976) undertook an experiment in North Carolina to determine the response of unaerated ponds to different loading rates with specific emphasis on constituent removals and odour potential. Field pilot-scale ponds were constructed with 2 mm thick steel in a cylindrical shape 3.5 m in diameter and 2.5 m high. The effluent depth was kept at 1.85 m giving a treatment volume of 17.5 m³. Once a week, raw pig manure from an underfloor pit was added to the ponds at a range of loading rates. The reference loading rate was 2.3 m³ of pond volume per 45 kg pig. This was the current Soil Conservation Standard design recommendation for anaerobic piggery ponds. It was calculated that this was equivalent to 96 g VS/m³/day and 960 kg BOD/ha/day. One heavier and a number of lighter loading rates were also used. Odour emissions were determined using a panel of observers. The methodology was inexact and qualitative according to current standards. However, the researchers drew the following conclusions. 1. Based upon a periodic field observations and odour panel rankings, it was concluded that there was a discernible odour threshold for unaerated swine waste lagoons loaded at approximately 9.2 to 18.4 m³/45 kg pig. Odour was not manure-like nor was an odour always detectable for lagoons with more than 18.4 m³/45 kg pig. For lagoons with less than 9.2 m³/45 kg pig, odour was not always detectable, but when found, it was characteristic of swine manure and hence deemed offensive. 2. Individual consensus indicated that the frequency or probability of odour detection when visiting the unaerated lagoon site was 80% for the unit at 0.6 m³/45 kg pig, 60% for 2.3 m³/45 kg pig, 20% for 4.6 m³/45 kg pig, and little odour for units with 9.2 m³/45 kg pig or greater. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 20

22 This work confirms the results of Smith et al. (1999) that heavily-loaded anaerobic ponds produce considerably more odour than lightly-loaded facultative ponds. The 1976 North Carolina work is the current US method of sizing swine lagoons for odour control (Tyson, 1998). However, since this time there have been substantial improvements in odour collection and measurement, with olfactometry standards now making data collection more repeatable and comparable. This advancement now enables researchers to better understand what factors influence odour emissions and revisit currently adopted methods of pond design Factors Affecting Pond Odour Emission Intuition would suggest that a number of factors may influence odour emission, including pond loading rate, pond age, microbiological population, sludge accumulation, pond chemistry, pond temperature and surface crusting. Design parameters currently adopted for determining pond size using the Rational Design Standard are VS loading rate, pond temperature and sludge accumulation Manure Handling and Anaerobic Digestion The conventional method for handling piggery wastewater in Australia is to direct it via gravity from the sheds, and/or pump it via a sump, to an anaerobic pond. Effluent from the anaerobic pond may be further treated in subsequent ponds. The total solids (TS) in the wastewater can be divided into volatile (organic) and fixed (ash) solids. Theoretically up to 90% of the volatile solids (VS) can be reduced in an anaerobic pond, with carbon, nitrogen, hydrogen and oxygen lost from the system as gaseous carbon dioxide, methane, water and ammonia. For complete anaerobic digestion, VS are converted to volatile fatty acids, which are then converted to gas. The fixed solids (non-biodegradable) and any undigested VS (dead cells) accumulate as sludge. The design criterion for anaerobic ponds is to have the total volume match the anticipated organic loading rate (active volume), plus an allowance for sludge accumulation (sludge volume). Volatile fatty acids are a major source of odour from anaerobic ponds (Hobbs et al., 1997). Branched chain volatile fatty acids form when proteins (organic nitrogen) excreted in the faeces are digested. The degradation of volatile fatty acids in anaerobic ponds produces methane gas (methanogenesis). Under high pond loading rates, methanogenesis can be inhibited by high concentrations of ammonia, hydrogen sulphide, or volatile fatty acids, increasing the likelihood of odour emissions. In ponds with a reduced surface to volume ratio, the stability of the anaerobic environment at depth may reduce the odour generation potential of the fatty acids (Hobbs et al., 1998). However, if the pond volume has been reduced by sludge deposition, and if the surface area is large and prone to turbulence, then the generation of unacceptably high odour emissions is inevitable. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 21

23 Pond Loading Rate The primary function of an anaerobic effluent pond is to reduce the organic matter in the effluent by converting complex carbohydrates to simple compounds. The pond loading rate is therefore an indication of the mass of organic matter (volatile solids) to be treated daily per unit of pond volume. This can be estimated from standard text book values (ASAE Standards, 1997) or more accurately predicted from the digestibility of the diet and mass balance principles - DMDAMP, McGahan et al. (2000). This work showed that for a typical Australian diet, a Standard Pig Unit (SPU) produces approximately 110 kg of TS/yr and 90 kg of VS/yr. A SPU is a unit of measurement for determining the size of a pig production unit in terms of waste output. One SPU produces an amount of VS equivalent to that produced by an average sized grower pig (approximately 40 kg). An accurate estimate of the pond loading rate requires: the number of pigs in each class; the amount and type of feed fed and % feed wastage for each pig class; any effluent pre-treatment such as solids screening; pond dimensions (volume); and pond sludge depth (volume). The volume of the pond available for treating effluent is assumed to be the volume of supernatant, or liquid effluent. This is calculated as the total pond volume less deposited sludge. It is currently assumed that no significant treatment occurs within the sludge layer. However, recent research by Anderson et al. (2000) has investigated the properties of undisturbed sludge in anaerobic piggery effluent ponds. A grid was established across the pond and samples of sludge collected concurrently from varying depths in the profile. Properties measured included: solids concentration; chemical oxygen demand (COD); total phosphorous; potassium concentration; total Kjeldahl nitrogen (TKN); and particle size distribution. Four strata within the sludge layer were defined 1. Concentrated zone (CZ) bottom 33%, characterised by a significant increase in the concentration of nutrients with depth and larger sludge particle sizes. 2. Active zone (AZ) 22% immediately above CZ, characterised by a slight increase in the concentration of nutrients with depth and active decomposition. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 22

24 3. Dilute zone (DZ) 22% immediately above AZ, characterised by low nutrient concentration as waste quickly passes through this layer. 4. Sludge/supernatant interface 22% immediately above DZ, characterised by the mixing of fresh waste with the end products of AZ. A detailed survey of the sludge layers was not performed as part of their study. However sludge was collected at 0.5 m intervals from each pond and analysed for TS and VS. This data was inconclusive in determining which parts of the sludge could be considered as active volume. Thus, active volume was assumed to be the supernatant volume only Pond Design Rational Design Standard The most common methods for designing anaerobic treatment ponds are either the Rational Design Standard or variations of it. This method was developed by Barth (1985) and was based on 3 requirements: Control of lagoon odour. Allowance for sludge accumulation. Maintain a minimum treatment volume. Climate has a large effect on the biological activity of a pond. Anaerobic activity within piggery ponds is reduced with lower average ambient temperatures. The volatile solids (VS) loading rate is adjusted using a factor (k), which varies according to piggery location. Higher average ambient temperatures in an area give a higher optimum pond loading rate. For instance, an area with a k factor of 1.0 has twice the ability to degrade organic material as a lagoon with a k factor of 0.5. The standard VS loading rate (100 g VS/m³/day) is multiplied by the temperature dependent k factor to calculate the minimum required active volume of a pond (Equation 6). Not all the solids that enter the pond are degradable. Approximately 20% of the solids in fresh piggery waste are fixed (ash) and are not degradable. A certain percentage of the VS also degrades very slowly and will remain in the pond (dead cells). The rate at which solids accumulate in the bottom of the pond is called the sludge accumulation rate (SAR). This is generally measured as a volume per kg of total solids (TS) added. Few methods are available for estimating SAR accumulation in anaerobic ponds. The most widely accepted is that reported by Barth (1985), where he estimated SAR as m³/kg of TS added. This figure is regarded in Queensland as being an over-estimate of SAR, with measured SAR for piggeries in southern Queensland being lower than this. The research by Anderson et al. (2000) outlined in Section obtained an accurate estimate of the sludge volume in an anaerobic pond after 15 years continuous use. The figure they obtained was found to be 79% lower than the sludge volume estimated using the ASAE method. Equation 7 is used to calculate the required volume for sludge. The minimum required active volume is added to the sludge volume to give a total required pond volume (Equation 8). Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 23

25 The Rational Design Standard also requires the calculation of a maximum volatile solid loading rate based on a 20% odour detection rate. This is calculated from a standard VS loading rate for odour control (61 g VS/m³/day), multiplied by the temperature dependent k factor (Equation 9). Whichever is the larger, the volume required for odour control (Equation 9) or the volume required for active plus sludge (Equation 8) is used as the total design volume of an anaerobic pond. Active vol. (m 3 ) = VS loading (g/day) / (k factor x 100 (g/m³/day)) EQUATION 6 Sludge vol. (m 3 ) = TS loading (kg/yr) x SAR (m 3 /kg) x Pond life EQUATION 7 Total pond volume = Active vol. + Sludge vol. EQUATION 8 Vol. for odour control (m 3 ) = VS loading (g/day) / 61 (g/m³/day) x k factor EQUATION 9 For the Darling Downs in south-east Queensland (where this current study was conducted), a typical VS loading rate is 85 g VS/m³/day (100 g VS/m³/day times a k factor of 0.85). Thus, if a Standard Pig Unit (SPU) produces 250 g VS/day (90 kg/yr), then the required active volume per SPU is approximately 3 m³. If we assume the SAR is m³/kg of TS added and the pond is designed to last 10 years before desludging, with a TS production/spu of 110 kg/yr, then a required sludge volume would be approximately 3 m³. This gives a total pond volume (active + sludge) of 6 m³/spu for a piggery on the Darling Downs with allowance for 10 years sludge accumulation. If the total volume for odour control is calculated it equates to about 5 m³/spu. Because the volume required for active plus sludge is greater than the volume for odour control, this is used as the total design pond volume. The adopted method for designing anaerobic ponds in Queensland is to calculate the required active and sludge volumes (Equations 6, 7 and 8), because these are generally greater than the volume required for odour control (Equation 9) Pink Ponds Purple sulphur bacteria (psb) have the potential to reduce pond odour by oxidising hydrogen sulphide into elemental sulphur during photosynthesis. They occur in anaerobic environments that have reduced sulphur present. They give the pond a brownish purple to pink colour, depending on the population. The conditions required to maintain a healthy population of psb is not well known. Work by Gilley et al. (2000) suggests that high levels of dietary copper fed in weaner diets may reduce the potential for psb to proliferate, whereas dietary zinc may inversely promote its growth. Other conditions that may reduce the potential for the presence of psb are high salinity level (>6 ds/m) and the presence of antimicrobials in the ponds. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 24

26 Schulte and Koelsch (1998) reported the results of a detailed study of eight anaerobic lagoons and the survey of an additional 28 anaerobic lagoons in Nebraska. The results were collected in early spring and again in mid-summer. As the reported temperature range for the summer sampling is closest to Australian conditions, only the summer results will be discussed here. Bacteriochlorophyll a (Bchl a) was used as a measure of the abundance of psb, with values between and mg/l obtained at the lagoon surface. Bchl a concentrations in purple lagoons were significantly greater than in non-purple lagoons (P = 0.02). Average ph values for purple and non-purple ponds were 7.4 and 7.8 respectively (statistically different at the P = level). The oxidationreduction potential (redox) at the surface was found to vary from -266 mv to -321 mv, and was less negative for purple lagoons than non-purple lagoons (P = 0.006). No relationship was found between psb and volatile solids loading rate, but the purple lagoons were found to have comparatively high volumes of flush and cleaning water per animal unit. Solids, alkalinity, salinity and COD concentrations were lower in purple lagoons compared to non-purple lagoons, but were not statistically different. Ammonium concentrations were statistically lower in purple lagoons than in nonpurple lagoons (P = 0.01). Salinity levels in excess of approximately 6 ds/m were associated with consistently low levels of Bchl a. Hydrogen sulphide oxidised by psb is abundant in animal waste ponds because of sulphate-reducing bacteria, which reduce sulphate to hydrogen sulphide. The elemental sulphur formed by psb eventually returns to sulphate, completing the sulphur cycle. Anecdotal evidence suggests that the presence of purple sulphur bacteria is an indication of good lagoon function and reduced odour production. However, there are no odour emission studies to confirm this. Unlike heavily-loaded ponds, pink ponds have the following characteristics: Uniform bright pink to dark purple-brown colour Little floating scum Few large bubbles fine uniform bubbles across the pond surface Musky character to odour. Photograph 3 and Photograph 4 show typical pink ponds. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 25

27 PHOTOGRAPH 3 PINK ANAEROBIC POND PHOTOGRAPH 4 PINK SECONDARY POND Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 26

28 4. CURRENT ODOUR SEPARATION GUIDELINES FOR PIGGERIES The current method for assessing new and expanding piggery developments in Queensland uses the AUSPLUME Gaussian dispersion model (McGahan et al., 2000). Odour emission data used in the model was derived from recent studies of the odour emission rates from Queensland piggeries (Smith et al., 1999, Watts 1999a). This was used in the AUSPLUME dispersion model to develop an empirical formula for calculating separation distance. The method also allows for modelling of individual enterprises with site-specific meteorological data. In developing the guidelines, five different odour impact objectives were chosen to represent different receptor types. The odour impact objectives, measured at the 99.5 percentile, one-hour average odour concentration to the NVN 2820 standard were 5 OU (representing a large town > 2000 persons), 10 OU (a town > 100 persons), 15 OU (a small town > 20 persons), 20 OU (a rural residential development), and 25 OU (an individual rural residence). Different air quality objectives were chosen for different receptor types, based on the assumption that there is a greater chance that people will be adversely affected by odour from larger centres. It is envisaged that these guidelines can be enhanced with better data on odour emissions from piggeries, more reliable climate data from intensive livestock production areas and an improved understanding of how odour from piggeries impacts on neighbouring receptors. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 27

29 5. PROJECT PROPOSAL 5.1. Introduction This study was undertaken for three primary reasons: 4. There is limited data on odour emission rates from piggery anaerobic ponds and what factors affect odour emission rate. 5. The design standards currently adopted to size piggery anaerobic ponds were based on predictions of odour detection from 25 years ago and methods of sampling and analysing odour have vastly improved since then. 6. There is a sufficient amount of anecdotal evidence that the presence of purple sulphur bacteria in piggery anaerobic ponds is an indication of good pond function and reduced odour emissions, but no odour emission measurements have been conducted to confirm this. The aims of this study were to: 3. Determine odour emission rates from a piggery anaerobic lagoon based on particular operating parameters. 4. Improve the understanding of which factors influence odour emissions to enhance currently adopted methods of pond design. The current DPI guidelines for siting piggeries are based on odour emission data from a limited number of piggery ponds (see Section 3.2). Observations from researchers collecting these odour emissions suggest that the ponds tested had high loading rates. To establish relationships between emission rates and factors such as loading rate and pond chemistry, data was collected from a range of anaerobic ponds in south east Queensland. Previous data collected on odour emissions was performed to the NVN2820 standard, which has since been superseded by a new Australian standard based on the latest European standard (CEN TC264). This Australia / New Zealand Standard (Stationary source emissions - determination of odour concentration by dynamic olfactometry (AS/NZS )) was used to perform all the odour measurements for this study Methodology The methodology followed was: 1. Discussions with Intensive Livestock Environmental Management Services, DPI research and regulatory staff regarding an experimental design. 2. Select ponds with a range of loading rates and colours. Draw up and review list of ponds within hours of Toowoomba Establish information readily available Establish access to ponds Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 28

30 3. Collect odour emission samples Collect multiple odour samples from each pond surface to determine an average odour emission rate of each pond Replicate sampling two days later to determine if there is changes in odour emission rates over this period 4. Take meteorological measurements (wind speed, temperature etc) to record climatic conditions at the time of odour sampling. 5. Take pond supernatant samples and analyse to determine pond chemistry. 6. Take pond sludge samples and analyse for TS and VS. 7. Determine the odour concentration of the samples using olfactometry to the new Australian Standard. 8. Calculate the odour emission rates and analyse the data. 9. Independently review the report. TABLE 4 STUDY MILESTONES Item Completion 1. Experimental design and planning 16/02/01 2. Odour sampling 13/04/01 3. Data analysis 08/06/01 4. Report preparation and review 03/08/01 Appendix A gives the independent review. The review was undertaken on a draft of this report. Comments and suggestions from that review have been included in this final report. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 29

31 6. DATA COLLECTION FSA Environmental and Intensive Livestock Environmental Management Services (DPI) undertook the work for Tong Park Pty Ltd. This study has been included as part of Australian Pork Limited (APL) Project 1628 Anaerobic Piggery Pond Odour Emissions that is administered by the National Centre for Engineering in Agriculture. This study will supply additional information to the APL project and improve the understanding of odour emissions from anaerobic piggery ponds. At five sites (5 anaerobic ponds) sampling was undertaken on two separate days. The second piggery sampled (Piggery B) was sampled a second time at the end of the process to investigate any variability in pond emissions over time. Each pond was sampled for odour emission rate (OER), volatile fatty acids (VFA), purple sulphur bacteria (psb) expressed as chlorophyll a, total nitrogen, ammonium nitrogen, total phosphorus, ortho-phosphorus, copper, zinc, iron, calcium, magnesium, sodium, chloride, sulphides, sulphates, pond temperature, pond electrical conductivity, redox potential, ph and sludge depth. Climatic parameters were also recorded for additional down-wind odour samples conducted by DPI and to note any large variations in climatic data between ponds during the study. To determine the average OER's for each pond, a number of points were sampled across the entire pond in a grid pattern. This sampling technique was required to account for the large variability of emission rates likely to be encountered across the pond surface, which was previously experienced by the research team Experimental design and planning Stage one of the project involved site visits to twelve piggeries on the Darling Downs to assess their suitability for odour sampling. As part of each visit the following was collected: Pig population, diets and feed usage (where available) Pond dimensions were surveyed using GPS Pond batters and total depth was measured with a pole Depth to sludge layer was measured with a turbidity meter Effluent electrical conductivity, ph and redox potential values were measured in-situ with meters A number of effluent samples were collected from the pond surface and batched for analysis. The pig population, diet and feed usage were used to provide an estimate of the daily waste production using the PigBal model (McGahan et al., 2000). The pond information was collated to provide an estimate of the active volume available for treating effluent. Combining the two sets of data provided an estimate of the waste production and active pond volume and hence pond loading rate, as shown in Table 5. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 30

32 TABLE 5 LOADING RATES OF PIGGERIES INITIALLY INVESTIGATED Piggery Number of Pigs (SPU) Active Volume (m 3 ) Loading Rate (g VS/m³/day) Max. VS Loading Rate* (g VS/m³/day) Loading Rate as % of Max. A 1,457 2, B 1,761 7, C 9,596 4, D 6,000 6, E 14,992 59, F 9,212 14, G 1,970 7, H I J 4,900 6, K 2,422 2, L * Maximum VS loading rate was determined by location To obtain a range of loading rates, five piggeries were selected (A, B, C, D and E). The other ponds were discarded for one of the following reasons: they were irregular in shape (had varying depths and cells) an odour suppressant was used in the feed they were very small and didn t represent a large commercial piggery they had a similar loading rate to a pond already selected 6.2. Odour collection Odour samples were collected and analysed from the five ponds selected. Samples were taken using a wind tunnel as designed by the UNSW Environmental Odour Laboratory (EOL), within the Centre for Water and Waste Technology, University of New South Wales (Jiang et al. (1995) and Bliss et al. (1995)). The wind tunnel was placed on the pond surface to ensure an efficient seal between the pond surface and the wind tunnel. Ambient air was passed through an activated carbon filter to remove any ambient odours before passing through the wind tunnel. The velocity in the tunnel was measured using a TSI Model 8355 hot wire anemometer to determine air velocity and hence calculate flow rates. The wind tunnel was suspended on a gantry system. This gantry allowed the wind tunnel to be lifted and lowered to various locations on the pond without disturbing the surface. Photograph 5 and Photograph 6 show the wind tunnel sampling equipment and sample collection from the surface of an anaerobic pond. Samples of the odorous air were drawn from the wind tunnel through Teflon tubing into Melinex bags (Polyethylene Terephthalate). The empty sample bag was placed in a rigid plastic container and the air in this container was then evacuated at a controlled rate and the bag filled. All wetted parts of the sampling train exposed to the odorous gases were composed of stainless steel (Grade 316) or Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 31

33 polytetrafluoroethylene (PTFE). All bags were pre-conditioned by filling with odorous air from the wind tunnel then evacuated prior to the sample being collected. Each sample was collected over a period of 6 minutes. Odour sample collection points used for each pond were sufficiently separated from the edge of the ponds to avoid the internal batters of the pond. This provided a uniform depth of effluent below each sampling point on a given pond. Samples were collected from multiple points on each pond to account for the variability in odour emissions from individual points. The odour emissions measured in this study show variation of greater than 100% within the points sampled each day on each pond. Odour concentrations were measured according to the Australian Standard for olfactometry (AS/NZS Stationary source emissions determination of odour concentration by dynamic olfactometry). Tests of the same odour undertaken in one laboratory in compliance with the standard will provide a maximum difference between results of a factor of 3 in 95% of cases. Some of the results obtained for this experiment showed differences between points of greater than 3. As the laboratory used undergoes compliance testing according to the standard, results that are different by greater than a factor of 3 indicate differences in the odour emissions between sample points. The olfactometry laboratory used has also tested the effect of using different speeds within the wind tunnel (DPI, unpublished). The wind tunnel was located on a point on a pond surface and odour samples were collected at different tunnel wind speeds. Odour concentrations determined by olfactometry for the samples collected were very similar, suggesting that the sampling and testing were undertaken to a sufficient standard. The olfactometry laboratory used has determined its lower limit of detection as 6 OU (Galvin, pers. comm.). This means that the equipment is capable of presenting odours to the standard at a level of 6 OU. In practice, sample bag size limits the ability of the olfactometer to reliably test odour concentrations below 11 OU. In this study, one point returned an odour concentration of 8 OU and two points returned values of 10 OU. All other points were above 11 OU. Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 32

34 Gantry Carbon filter Wind tunnel Fan (air supply) PHOTOGRAPH 5 WIND TUNNEL SAMPLING EQUIPMENT Sampling drum Sampling line PHOTOGRAPH 6 WIND TUNNEL SAMPLING ON ANAEROBIC POND B Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 33

35 6.3. Description of Piggery Ponds Sampled Piggery A Piggery A is located west of Toowoomba. The piggery is a farrow-to-finish operation, with a capacity of 1457 standard pig units (SPU). The pond was desludged approximately 3 years before odour sampling was conducted. N Wind tunnel sampling point Effluent loading site FIGURE 1 - PIGGERY A POND WITH SAMPLING AND LOADING SITES SHOWN Piggery B Piggery B is located at Wacol, west of Brisbane. The piggery is a grower unit where the pigs arrive at 8 weeks and leave at 20 weeks (males) and 24 weeks (females). The piggery operates with a 1761 SPU capacity. The anaerobic pond at this piggery has been operating for approximately 3 years and has never been desludged. N Wind tunnel sampling point Effluent loading site FIGURE 2 - PIGGERY B POND WITH SAMPLING AND LOADING SITES SHOWN Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 34

36 Piggery C Piggery C is located on the Darling Downs. The piggery is a 1000 sow farrow-tofinish operation, with a SPU capacity of Six months ago the piggery decommissioned the original primary pond for desludging. The secondary pond is currently being used as the primary pond and this is where the odour samples were collected. N Wind tunnel sampling point Effluent loading site FIGURE 3 - PIGGERY C POND WITH SAMPLING AND LOADING SITES SHOWN Piggery D Piggery D is located on the Darling Downs. The piggery operates as a 700 sow farrow to finish operation, with some pigs removed from the piggery as weaners. The piggery operates at a capacity of 6767 SPU. The piggery pond is approximately 15 years old and has never been desludged. N Wind tunnel sampling point Effluent loading point FIGURE 4 - PIGGERY D POND WITH SAMPLING AND LOADING SITES SHOWN Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 35

37 Piggery E Piggery E is located on the Darling Downs. The piggery is a 1200 sow farrow-tofinish operation. It has a SPU capacity of 14,992. The piggery has 3 ponds. Sampling was undertaken on the primary pond, which is approximately 9 years old and has never been desludged. N Wind tunnel sampling point Effluent loading point FIGURE 5 - PIGGERY E POND WITH SAMPLING AND LOADING SITES SHOWN PHOTOGRAPH 7 ODOUR SAMPLING ON POND A Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 36

38 PHOTOGRAPH 8 POND B (FINE SCUM AROUND EDGES) PHOTOGRAPH 9 POND C (EFFLUENT INLET ON LEFT FOREGROUND) Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 37

39 PHOTOGRAPH 10 POND D (INLET ON RIGHT HAND SIDE) PHOTOGRAPH 11 POND E Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 38

40 6.4. Olfactometry Odour concentration was determined using an eight (8) panellist, triangular, forcedchoice dynamic olfactometer developed by the Queensland Department of Primary Industries. This olfactometer has been constructed to meet the requirements of the Draft Australia / New Zealand Standard - Air Quality - Determination of Odour concentration by dynamic olfactometry (EV/ ). (This draft has now been issued as AS4323.3:2001). Odour analysis was undertaken according to the Draft Australia / New Zealand Standard - Air Quality - Determination of Odour concentration by dynamic olfactometry (EV/ ). All panellists were screened for n-butanol sensitivity as per the requirements of the Draft Australia / New Zealand Standard - Air Quality - Determination of Odour concentration by dynamic olfactometry (EV/ ). Each panellist booth has three sniffing ports, one of which presents diluted odour air while the other two present clean odour free air. For each presentation, each panellist was required to indicate via a keypad, which port contained the odorous air (i.e. makes a forced choice ) and the certainty of their choice (guess, inkling or certain). A panellist scored correctly only if they selected the correct port and were certain of their choice. A range of at least five dilution steps, each differing from the next by a factor of two, was presented to the panellists in steps of ascending concentration; the whole range being presented three times. Panellists' individual thresholds were calculated as the geometric mean of the highest dilution at which they consistently scored correctly, and the lowest dilution at which they scored incorrectly. The group threshold (which equates with the odour concentration) was calculated as the geometric mean of individual panellists' thresholds, following exclusion of individual thresholds that differed from the group by more than a factor of five. PHOTOGRAPH 12 DPI MULTIPLE PANELLIST DYNAMIC OLFACTOMETER Tong Park Pty Ltd, Pink Pond Odour Research Study Page No. 39