## Application of diffusion laws to composting: theory, implications, and experimental testing

##### Abstract

Understanding the fundamentals of composting science from a pragmatic perspective of necessity involves mixtures of different sizes and types of particles in constantly changing environmental conditions, in particular temperature. The complexity of composting is affected by this environmental variation. With so much "noise" in the system, a question arises as to the need to understand the detail of this complexity as understanding any part of composting with more precision than this level of noise is not likely to result in greater understanding of the system. Yet some compost piles generate offensive odours while others don‟t and science should be able to explain this difference. A driver for this research was greater understanding of potential odour, which is assumed to arise from the anaerobic core of a composting particle. It follows that the size of this anaerobic core could be used as an indicator of odour potential. A first step in this understanding is the need to determine which parts of a composting particle are aerobic, from which the anaerobic proportion can be determined by difference. To this end, this thesis uses a finite volume method of analysis to determine the distribution of oxygen at sub-particle scales. Diffusion laws were used to determine the thickness of each finite volume. The resulting model, called micro-environment analysis, was applied to a composting particle to enable determination of onion ring type volumes of compost (called micro-environments) containing substrates (further subdivided into substrate fractions) whose concentrations could be determined to high precision by the application of first-order degradation kinetics to each of these finite volumes. Determination of the oxygen concentration at a micro-environment's inner boundary was achieved by using the Stępniewski equation. The Stępniewski model was derived originally for application to soil aeration and enables each micro-environment to have its own oxygen uptake rate and diffusion coefficient.
This first version of micro-environment analysis was derived from the simpler solution to diffusion laws, based on the assumption of non-diffusible substrate. It was tested against three sets of experimental data with two different substrates:
Particle size trials using dog sausage as substrate – where the peak composting rate was successfully predicted, as a function of particle size.
Temperature trials using pig faeces and a range of particle sizes – the results showed the potential of micro-environment analysis to identify intriguing temperature effects, in particular, a different temperature effect (Q10) and fraction proportion was indicated for each substrate fraction. Smaller particle sizes, and possibly outward diffusion of substrate confounded a clear experimental signal.
Diffusion into a pile trials which showed that the time course of particles deeper in the pile could be predicted by the physics of oxygen distribution. A fully computed prediction would need an added level of computational complexity in micro-environment analysis, arising from there being two intertwined phases, gas phase and substrate (particle) phase. Each phase needs its own micro-environment calculations which can not be done in isolation from each other.
Unexplainable parts of the composting time course are likely to be partly explained by the outward diffusion of substrate towards the inward-moving oxygen front. Although the possibility of alternative electron acceptors can not be discounted as a partial explanation. To test the theory, a new experimental reactor was developed using calorimetry. With an absolute sensitivity of 0.132 J hr-1 L-1 and a measurement frequency of 30 minutes, the reactor was able to detect the energy required to humidify the input air, and "see" when composting begins to decline as oxygen is consumed. Optimisation of the aeration pumping frequency using the evidence from the data was strikingly apparent immediately after setting the optimum frequency. Micro-environment analysis provides a framework by which several physical effects can be incorporated into compost science.... [Show full abstract]