Improving bioaerosol exposure assessments of composting facilities — Comparative modelling of emissions from different compost ages and processing activities
Introduction
Composting is reliant on the presence of various microorganisms, such as fungi and bacteria, which may become airborne and pose a risk to human health (Douwes et al., 2003). In response to perceived public health concerns, the Environment Agency of England and Wales (the environmental regulator) requires a risk assessment for licensed composting facilities that have a sensitive receptor within 250 m of their boundaries (Environment Agency, 2001). This must examine, among other hazards, the dispersal of airborne microorganisms or bioaerosols from the site (Wheeler et al., 2001; Environment Agency, 2002; Pollard et al., 2006). In this context, sensitive receptors may include a residence, school or office building. The aim of the risk assessment is to inform risk management. However, the quality of the risk assessment is dependant on the availability and quality of the bioaerosol source term data employed (Pollard et al., 2006). This data is frequently limited, in part because of the practical difficulties of microbiological analyses, but also due to cost constraints.
There is a growing body of research that examines the concentrations of bioaerosols in and around composting facilities (e.g. Danneberg et al., 1997; Swan et al., 2002; Sanches-Monedero and Stentiford, 2003; Taha et al., 2005, Taha et al., 2006). Many studies that attempt to predict the dispersal of bioaerosols from facilities use simple methods (e.g. Millner et al., 1980, Lighthart and Mohr, 1987; Swan et al., 2003; ADAS/SWICEB, 2005) and so are not able to take into account the full range of atmospheric and local conditions that could affect bioaerosol dispersion. Air dispersion models were developed to predict dispersion of pollutants, such as the nitrogen oxides, based on emissions and meteorological inputs, and have successfully been used for assessing odour dispersion from industry (e.g. Environment Agency, 2002). However, the use of these models for bioaerosol dispersion has been limited, as dispersion models may not be able to fully take into account the mechanisms of release of bacteria and fungi.
According to McCartney (1994), environmental factors such as wind speed, turbulence, humidity and water availability will influence when spores are released. Although these parameters are taken into account by dispersion models when predicting downwind concentrations, there are very few ‘at source’ measurements of bioaerosol concentrations that link these parameters to the concentrations measured. Furthermore, certain characteristics of bioaerosols complicate the use of dispersion models; in particular, their ability to form aggregates or clumps once released and the loss of viability that may occur as they are emitted from the compost windrow (Wheeler et al., 2001).
Our own research (Taha et al., 2004, Taha et al., 2005, Taha et al., 2006, Taha et al., 2007) focuses on improving the quality of regulatory risk assessments for composting by providing:
- (i)
accurate source term data at the point of release (Taha et al., 2006); and
- (ii)
developing new methods for improving sampling and enumeration of bioaerosols (Taha et al., 2007).
Here, we propose further improvements by presenting the refinement of air dispersion modelling for the prediction of downwind bioaerosol concentrations at off-site points of exposure.
We present results from measuring on site and predicting the dispersal of bioaerosols from a green waste composting research facility in southern Wales. The advantage of sampling at this facility was that the processes on site could be adjusted to aid the sampling activities; for example, timing of shredding and screening. The objectives of the study were (i) to characterise the source term bioaerosol emissions, taking into consideration storage properties, compost age and dispersal during agitation using a windrow turner, front-end loader, screener and shredder; and (ii) to compare the predicted downwind concentrations modelled by two separate dispersion models. We seek to improve bioaerosol exposure assessments by refining the methods currently used to estimate downwind dispersal of compost emissions.
In order to estimate the static pile emission flux rate and bioaerosol active dispersal emission rate during agitation, the single source Gaussian plume model SCREEN3 (USEPA, 1995) was used to initially estimate bioaerosol depletion curves (Taha, 2005). SCREEN3 is a screening-level model that adopts steady-state Gaussian plume algorithms and meteorological scenarios to estimate worst-case dispersal. This was followed by the application of advanced modelling using the ADMS 3.3 air dispersion model (Carruthers et al., 1994; CERC, 2003). ADMS is an advanced steady state, Gaussian-like dispersion model, capable of modelling continuous plumes, short duration releases and transport over complex terrain. The model simulates point, line, area and volume sources, and can estimate pollutant concentrations at a number of user defined receptors. The model has been shown to perform in a comparable manner to similar new generation models (Hanna et al., 2000). Using the model results, we infer the possible influences that bioaerosol properties such as inactivation and microbial agglomeration may have on the depletion curves (decrease in concentration with distance) produced by the models.
Section snippets
Material and methods
The study site is a research composting facility handling ca. 12000 m3 of shredded green waste per annum in windrows under a 1500 m2 building with open sides. Samples were taken from compost windrows (passive emissions) aged at 1, 2, 4, 6, 8, 12 and 16 weeks, and during agitation activities (active emissions) on site, such as turning, shredding and screening. For turning activities, measurement was conducted on 1, 4, 8 and 12 week old compost. Sampling was undertaken between January and March
Results and discussion
Bioaerosol concentrations measured using the wind tunnel and directly above the compost pile (passive emissions) are presented in Fig. 1, Fig. 2. Background bioaerosol concentrations measured at the site boundary are shown in Table 2. Although measurements were taken upwind and downwind, A. fumigatus and actinomycetes were not detected. Bioaerosol concentrations and the estimated emission rates downwind from the various processing activities are presented in Table 3 and Fig. 3. The source
Discussion
The source depletion curves presented by this study still have some caveats with them due to the clumping tendency of bioaerosol (physical decay) and deactivation (biological decay) caused by sunlight and heat. Although the clumping tendency of bioaerosols has been discussed in regard to their dispersion (e.g. Wheeler et al., 2001), there is little published research data to support any conclusions regarding this tendency, particularly in association with composting facilities. Previous
Conclusions and future work
We have presented data demonstrating the ability to measure the concentration of bioaerosols emitted ‘at source’ during static conditions and for agitation activities, from compost of different ages. From these results, we have estimated the emission flux of bioaerosols from compost-processing activities, using a simple screening-level dispersion model and a more advanced new generation dispersion model. We have previously concluded that agitation activities result in releases of bioaerosols in
Acknowledgements
This research is partly supported by the Ministry of Health, Malaysia. MPMT was seconded to Cranfield University through the Malaysian Continuing Professional Development Scheme. AT is sponsored by an EPSRC doctoral training award. GHD is an Environment Agency supported Postdoctoral Fellow (Science Project P1-514). We acknowledge the technical support of Dr Martin Lowe, Visiting Fellow, Integrated Waste Management Centre; Mike Smith and Dr Nina Sweet of the Environment Agency and Dr David
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