Comparison of on-pond measurement and back calculation of odour emission rates from anaerobic piggery lagoons

Comparison of on-pond measurement and back calculation of odour emission rates from anaerobic piggery lagoons

Odours are emitted from numerous sources and can form a natural part of the environment. The sources of odour range from natural to industrial sources and can be perceived by the community dependant upon a number of factors. These factors include frequency, intensity, duration, offensiveness and location (FIDOL). Or in other words how strong an odour is, at what level it becomes detectable, how long it can be smelt for, whether or not the odour is an acceptable or unacceptable smell as judged by the receptor (residents) and where the odour is smelt. Intensive livestock operations cover a wide range of animal production enterprises, with all of these emitting odours. Essentially, intensive livestock in Queensland, and a certain extent Australia, refers to piggeries, feedlots and intensive dairy and poultry operations. Odour emissions from these operations can be a significant concern when the distance to nearby residents is small enough that odour from the operations is detected. The distance to receptors is a concern for intensive livestock operations as it may hamper their ability to develop new sites or expand existing sites. The piggery industry in Australia relies upon anaerobic treatment to treat its liquid wastes. These earthen lagoons treat liquid wastes through degradation via biological activity (Barth 1985; Casey and McGahan 2000). As these lagoons emit up to 80 per cent of the odour from a piggery (Smith et al., 1999), it is imperative for the piggery industry that odour be better quantified. Numerous methods have been adopted throughout the world for the measurement of odour including, trained field sniffers, electronic noses, olfactometry and electronic methods such as gas chromatography. Although these methods all have can be used, olfactometry is currently deemed to be the most appropriate method for accurate and repeatable determination of odour. This is due to the standardisation of olfactometry through the Australian / New Zealand Standard for Dynamic Olfactometry and that olfactometry uses a standardised panel of 'sniffers' which tend to give a repeatable indication of odour concentration. This is important as often, electronic measures cannot relate odour back to the human nose, which is the ultimate assessor of odour. The way in which odour emission rates (OERs) from lagoons are determined is subject to debate. Currently the most commonly used methods are direct and indirect methods. Direct methods refer to placing enclosures on the ponds to measure the emissions whereas indirect methods refer to taking downwind samples on or near a pond and calculating an emission rate. Worldwide the odour community is currently divided into two camps that disagree on how to directly measure odour, those who use the UNSW wind tunnel or similar (Jiang et al., 1995; Byler et al., 2004; Hudson and Casey 2002; Heber et al., 2000; Schmidt and Bicudo 2002; Bliss et al., 1995) or the USEPA flux chamber (Gholson et al., 1989; Heber et al., 2000; Feddes et al., 2001; Witherspoon et al., 2002; Schmidt and Bicudo 2002; Gholson et al., 1991; Kienbusch 1986). The majority of peer reviewed literature shows that static chambers such as the USEPA flux chamber under predict emissions (Gao et al., 1998b; Jiang and Kaye 1996) and based on this, the literature recommends wind tunnel type devices as the most appropriate method of determining emissions (Smith and Watts 1994a; Jiang and Kaye 1996; Gao et al., 1998a). Based on these reviews it was decided to compare the indirect STINK model (Smith 1995) with the UNSW wind tunnel to assess the appropriateness of the methods for determining odour emission rates for area sources. The objective of this project was to assess the suitability of the STINK model and UNSW wind tunnel for determining odour emission rates from anaerobic piggery lagoons. In particular determining if the model compared well with UNSW wind tunnel measurements from the same source; the overall efficacy of the model; and the relationship between source footprint and predicted odour emission rate.