A relatively simple dynamic model based on microbial process kinetics has been developed for aerobic composting. Differential equations describing microbial, substrate, and oxygen concentrations, as well as moisture and temperature profiles have been derived as a function of vessel size and aeration rate. Microbial biomass growth was described using Monod growth kinetics as a function of degradable substrate concentration, oxygen concentration, moisture content, and compost temperature. Facility and fan operating costs have been included to permit economic optimization of the process. Predicted results demonstrated the ability of the model to quantify and describe the influence of multiple interacting factors (temperature, oxygen, moisture, and substrate availability) on the process driving the composting: microbial growth kinetics. Future development of the approach should be undertaken to provide a robust engineering model that can be used to evaluate and design environmentally sound composting facilities. An example application is presented along with data from a laboratory scale composter.

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Body heat storage changes of cattle were measured by means of simultaneous direct and indirect calorimetry and by thermometry in an environment that alternated in temperature between 12 and 25 °C. When the calorimeter temperature was increased deep body temperature (T c ) increased by approximately 0-5 °C, mean surface temperature (T t ) by 3 °C and mean body temperature (determined from calorimetry, T s ) by 1 °C, but these increases were not fully sustained during the next 24 h. Changes in the three temperatures were related by the equation: AT b = a.AT c + (l -a) AT S where a was found to be 0-89+ 0027 (S.E.).

The purpose of this study was to develop and validate a dynamic simulation model to be employed in accurate prediction of microclimate in a greenhouse as a function of dynamic environmental factors. The model has options to evaluate the effects of location, time of the year, orientation, single and double polyethylene glazings, conventional and heat pump heating and cooling systems, open and confined greenhouse systems, CO 2 enrichment, variable shading, and the use of night curtains. Conventional gas furnace and evaporative cooling, respectively, provided heating and cooling in the conventional system. In the heat pump systems, gas-fired heat pump units provided both heating and cooling. The heat pump systems were operated both as an open and a completely confined system. Outputs of the simula tion model included both temporal and vertical distribution of air, leaf, floor and cover temperatures, CO 2 , relative humidity, solar radiation, and photosynthetically active radiation in addition to the dynamics of photosynthesis, respiration, transpira tion, energy and CO 2 use and fixation. Comparison of experimental and predicted results showed that the compared microclimatological parameters were in fairly good agreement. The greenhouse model developed in this study is useful for ecologists, plant scientists, and engineers to evaluate individual or combined effects of various forcing functions on the enclosed environment and plant responses; and to develop control strategies for different parameters. INTRODUCTIONAccurate prediction models for greenhouse and plant growth performance can be used as a design tool and in economic feasibility analyses as well. A dynamic analysis is required for more accurate prediction and control of greenhouse thermal environments. In addition to experimental tests, efforts have been made to predict the greenhouse environment under both steady state and transient conditions. Some reported work on greenhouse models and thermal performance tests include the work of Chandra et al. (1981), Glaub and Trezek (1981), Kindelan (1980), Navas et al. (1998), Pita andVargues (1998), andRijsdijk and Hauter (1993). The purpose of this study was to develop and validate a dynamic simulation model to be employed in accurate prediction of greenhouse energy and moisture exchanges as a function of dynamic environmental factors such as solar energy, outside temperatures and moisture levels, plant moisture and energy exchanges and heat removal or storage. This article deals with the model development, validation and preliminary simulation results.

Heat stored in the body of cattle subjected to a daily 10 C C range of environmental temperature was measured by calorimetry and thermometry. The daily range of bodycore temperature of the animals was of the order of 0-5 °C but mean skin temperature cycled with a range of approximately 6 °C. Calorimetric estimates of changes in mean body temperature showed good agreement with thermometric estimates when core and mean body temperature changes were weighted in the ratio a: (1 -a) where a was found to be 0-85. This result is consistent with the findings of another study where cattle were subjected to abrupt changes in environmental temperature, the combined best estimate of a from the two studies being 0-86 + 0-014 (s.E.). The 10 °C range of daily environmental fluctuation resulted in a daily variation of approximately 1 °C in mean body temperature, which is equivalent to the amount of heat produced by the animals every 40 min. It is suggested that a weighting factor a = 0-86 could be employed, using thermometry only, to estimate fluctuations in body heat storage which are likely to occur in animals subjected to fluctuating environmental conditions in the field.