Influence of free air space on microbial kinetics in passively aerated compost.

The influence of free air space (FAS) on passively aerated composting has been reported, but the quantitative relationship between FAS and the microbial kinetics in passively aerated compost has not been investigated. This relationship was studied by composting dairy manure and straw in an enclosed, passively aerated, cylindrical vessel. Based on this experimental system, conceptual and numerical models were developed in which the compost bed was considered to consist of layered elements, each being physically and chemically homogeneous. The microbial activity in each layer was represented in order to predict oxygen and substrate consumption and the release of water and heat. Convective transport of air, moisture, and heat through the layers was represented. Microbial growth and substrate consumption rates were described using modified first-order kinetics for each of the mesophilic and thermophilic temperature regimes. The values of the microbial kinetic parameters were adjusted for each layer based on an innovative, non-linear, statistical analysis of temperature histories recorded at different layers in the compost bed during three treatments (i.e., FAS values of 0.45, 0.52, and 0.65). Microbial kinetic rate constants were found to follow a sigmoid relationship with FAS, with correlation coefficients (R(2)) of 0.97 for the mesophilic stage and 0.96 for the thermophilic stage. Temperature histories and airflow measurements from a fourth treatment (FAS value of 0.57) were used as an independent check of the model's performance. Simulation results indicate that the model could predict the general trend of temperature development. A plot of the residuals shows that the model is biased, however, possibly because many parameters in the model were not measured directly but instead were estimated from literature. The result from this study demonstrates a new method for describing the relationship between microbial kinetics (k(max)) and substrate FAS, which could be used to improve the design, optimization, and management of passively aerated composting facilities.

A statistical method for the analysis of nonlinear temperature time series from compost.

Temperature is widely accepted as a critical indicator of aerobic microbial activity during composting but, to date, little effort has been made to devise an appropriate statistical approach for the analysis of temperature time series. Nonlinear, time-correlated effects have not previously been considered in the statistical analysis of temperature data from composting, despite their importance and the ubiquity of such features. A novel mathematical model is proposed here, based on a modified Gompertz function, which includes nonlinear, time-correlated effects. Methods are shown to estimate initial values for the model parameter. Algorithms in SAS are used to fit the model to different sets of temperature data from passively aerated compost. Methods are then shown for testing the goodness-of-fit of the model to data. Next, a method is described to determine, in a statistically rigorous manner, the significance of differences among the time-correlated characteristics of the datasets as described using the proposed model. An extra-sum-of-squares method was selected for this purpose. Finally, the model and methods are used to analyze a sample dataset and are shown to be useful tools for the statistical comparison of temperature data in composting.