Manure-DNDC is a process based model which describes manure organic matter turnover and gas emissions, where the relations between environmental factors and reactions such as decomposition, hydrolysis, nitrification, volatilisation etc are incorporated in a computable framework in order to estimate carbon dioxide, nitrous oxide and ammonia emissions.
Each component on a farm where manure is stored and emissions emanate (e.g., feedlot, lagoon, compost, anaerobic digester and cropping field) can be selected and integrated in the model to describe the facilities on any given farm. The variations in environmental factors in each facility drive the biochemical reactions (Li et al., 2012) and since the model is based upon thermodynamic principles and chemical reaction kinetics it can be applied to a variety of livestock facilities as well as cultivated soils. Manure-DNDC requires livestock herd, farm facility specifications, daily weather, soil and manure management practise data to be inputted to the model. It runs at a daily time-step for at least one year, where daily and annual pools and fluxes of C, N, P and water are outputted.
In 2012, Li et al. published research in which datasets of air emissions from six US farms and one Scottish pasture were used to verify the model with sensitivity analysis showing that Manure-DNDC is able to cope with the complexity simulating air emissions from livestock farms. The model results showed that reduction in greenhouse gas emissions by 30% and ammonia emissions by 36% was potentially possible on a New York dairy farm, through a combination in changes in feed quality, planted crop type and lagoon coverage.
Further development of Manure-DNDC will consider additional functionality to address nutritional functions for livestock, indirect emissions of GHG’s (transportation, feed import and machinery) and an economic analysis.