The theoretical perspective was used to explain the time course of three sets of experimental data:
1) Dog sausage cut to five particle sizes.
2) Pig faeces well mixed with bulking material and composted at five temperatures in the psychrophic/mesophilic range.
3) Penetration of oxygen into a composting pile.
To fit the theoretical perspective to actual data, some computational and derivational compromises were needed to accommodate the growth phase and determine particle size distribution in the mixed faeces.
7.3.1 The Growth Phase
The main micro-environment computational form needed to be adapted to describe the growth phase. The micro-environment framework is derived from an assumption that oxygen penetrates further into a particle at each interval as substrate is degraded in the outer layers. This state does not exist during the growth phase as biomass is building up. The increased VOR resulting from the increased biomass results in oxygen penetrating less
distance at each time interval. One of the implications of this is that micro-environment thickness can become negative, producing an error in the calculations. This issue was solved by considering this phase to be a single micro-environment with a new total
thickness calculated at each interval. This differed from the standard micro-environment formulation where a new micro-environment formed at each interval and the thickness was fixed thereafter.
The two formulations modelled their respective phases well but the transition from one formulation to the other required managing. In particular:
the transition time was taken to be the end of the slow fraction growth phase. This was used as occasionally the slow fraction NB would exceed the reduction in the fast fraction substrate – generating a negative z;
the oxygen penetration depth at this point was allocated equally between each interval generated micro-environment, for subsequent calculations.
7.3.2 Accommodating a Range of Particle Sizes and Bulking
Material
For a composting pile with a range of particle sizes, where the composting time course is influenced by particle size, the observed composting rate is a combination of all time courses. An effective average particle size is proposed to simplify the analysis. This is further complicated where a moist substrate (faeces) is well mixed with bulking material. In this case, in addition to different sized particles having different time courses, the time course of the bulking material differs substantially from the time course of the faeces. A simple averaging of the energy density of the fractions over the mixture will give erroneous results, as the faeces are most likely to exist on the surface of the bulking material, or as individual particles, and as the faeces will have a higher quantity of fast fraction, they will have a composting time course that differs from BM. A mass balance approach to this issue was used in this work.
7.3.3 Particle Size Trials
Five cubical particle sizes were composted and the composting time course of each size measured. Parameters were first determined for the small particle size reactor, assuming only the dog sausage was composting and then, using these parameters, the model
successfully predicted the peak composting rate over all particle sizes. However it did not predict a rewarming phase that occurred in the larger particle sizes.
Two explanations for this rewarming are proposed:
Diffusion of substrate has occurred as proposed by Hamelers (2001).
Alternative electron acceptors are being utilised.
It was not possible to establish which of these processes was an explanation for the observed effect, or whether both exist concurrently.
7.3.4 Temperature Trials
Temperature influences many aspects of the composting time course and there is not a „clear‟ signal from the experimental data. These other aspects arise from two sources.
The temperature effect on all of:
o the solubility of oxygen in water;
o the oxygen diffusion coefficient;
o the rate constant.
Scale analysis shows that as a consequence of micro-environment development, an increased rate constant will decrease the oxygen penetration depth and reduce the proportion of the particle which is aerobic. This effect predicts that a doubling of the rate constant will only result in an increase in the observed composting rate of √2 = 1.4.
For this trial, the rate constants and fraction proportions were determined for each
composting temperature and then the rate constants were compared with those predicted by the Arrhenius equation using a rate constant consistent with a Q10 = 2.
The data were inconclusive in predicting the temperature effect, possibly due to the
mixture of particle sizes in this composting mix meaning the small particle sizes dominated the pile composting rate resulting in the micro-environment effect being poorly expressed. However, some trends were noted, particularly:
A temperature effect that appears to differ between each fraction‟s rate constant, and the amount of fraction that is accessed. Better techniques for determining parameters may reliably determine whether this is a real effect.
Despite the trial duration being pre-determined by a Q10 = 2, the 20 °C reactor
composted more than its colder reactors, suggesting a Q10 >2 for this temperature
range (6-20 °C).
In addition, the fast fraction rate constants were particularly high with this pig faeces substrate, almost 1 order of magnitude higher than the highest published rate constant in
the composting literature, and comparable to Hamelers‟ results (discussed below). An explanation for a rate constant of this magnitude is discussed below. However, the possibility of enzyme activity rather than microbial growth must also be considered. Other effects of temperature have been reported in the literature. For example, Dalias et al., (2001) found the labile fraction increased with increasing temperature, while
Christensen & Harremoës, (1978) distinguished between short-term temperature dependence and long-term temperature dependence in nitrifying and denitrifying organisms.
7.3.5 Diffusion into the Pile
From a micro-environment perspective, the penetration of oxygen into a pile can be seen as two intertwined phases and micro-environment analysis can be used in each phase, albeit with different parameters e.g. diffusion of oxygen in air and concentration of oxygen in
air, compared with the diffusion and concentration of oxygen in water. The two phases are:
gas phase (pores or the FAS component of the matrix);
particle phase (the focus of micro-environment analysis in this thesis).
The time course of particles deeper in the pile can be predicted by a combination of the lowered oxygen concentration in the air surrounding the particle, producing a reduced peak composting rate and different composting time course, and the offset of this time course due to the delay in oxygen reaching the pores around the particle. A third effect is predicted arising from the gradually increasing pore oxygen concentration surrounding the particle, which would result in thicker micro-environments within the particle and
consequently a different time course from a particle held at constant oxygen concentration. The experimental data from a 400 mm deep compost pile showed the predicted effect on the composting time course of the lowered oxygen concentration with different depths. However, diffusion in the gas phase was not modelled, therefore there was no offset in the modelled data.
Extension of micro-environment analysis to gas phase modelling would require appraisal of those models that adjust the diffusion coefficient for the gas-filled porosity, and determine their applicability to composting.