Manure-DNDC: a biogeochemical process model for quantifying greenhouse gas and ammonia emissions from livestock manure systems

Abstract

From the point of view of biogeochemistry, manure is a complex of organic matter containing minor minerals. When manure is excreted by animals, it undergoes a series of reactions such as decomposition, hydrolysis, ammonia volatilization, nitrification, denitrification, fermentation etc., from which carbon dioxide (CO 2 ), nitrous oxide (N 2 O), methane (CH 4 ) and ammonia (NH 3 ) can be produced. Based on the principles of thermodynamics and reaction kinetics, these reactions are commonly controlled by a group of environmental factors such as temperature, moisture, redox potential, pH, substrate concentration gradient etc. The relations among the environmental factors, the reactions and the gas production have been incorporated in a process-based model, Manure-DNDC, to describe manure organic matter turnover and gas emissions. Using Manure-DNDC, the users can construct a virtual farm by selecting and integrating one or more of the candidate farm facilities (i.e., feedlot, compost, lagoon, anaerobic digester and cropping field) parameterized in the model. Manure-DNDC calculates variations of the environmental factors for each component facility based on its technical specifications, and then utilizes the environmental factors to drive the biogeochemical reactions. To verify the applicability of Manure-DNDC for livestock farms, seven datasets of air emissions measured from farms across the U.S. plus a Scotland pasture were utilized for model tests with encouraging results. A dairy farm in New York was used to assess the impacts of alternative management practices on the gas mitigation. The modeled results showed that a combination of changes in the feed quality, the lagoon coverage and the planted crop type could reduce greenhouse gas emission by 30 % and NH 3 by 36 % at the farm scale.

The Lancet Countdown: tracking progress on health and climate change

“…Greenhouse gas emissions associated with agriculture (including livestock systems and biogeochemical processes) will be quantifi ed with the use of existing models (eg, the DAYCENT or DeNitrifi cation-DeComposition [DNDC] models). [69][70][71] An understanding is needed of the potential for multiple environmental factors to aff ect food systems, and the nuances within and between countries and cultures. Further work will be required to refi ne indicators for this area, and the scientifi c community is invited to suggest potential metrics and data sources.…”

Development of mathematical models to predict volume and nutrient composition of fresh manure from lactating Holstein cows

“…Therefore, manure volume and associated nutrient concentrations are vital input variables for manure and soil models, e.g. Manure-DNDC (Li et al 2012). Furthermore, manure volume plays a key role in land applications.…”

“…Manure volume estimates are required to calculate the nutrient concentrations, which govern primarily the rate of reactions responsible for manure nutrient transformations (Li et al 2012). In the presence of DMI, the model (Eqns 1, 6, 7 and 22, collectively) predicted T E well (RMSPE% = 13.0%).…”

“…Manure and soil models (e.g. the Manure-DNDC model (Li et al 2012)) attempt to represent quantitatively the effects of substrate availability and environmental factors on these reactions and thereby predict greenhouse gas emissions and NH 3 volatilisation from dairy farms at barn, manure storage and land application levels (Li et al 2012). Carbon (C), nitrogen (N) and water content in fresh manure from dairy cows are major input variables to the Manure-DNDC model and are estimated using factors such as milk yield and diet composition.…”

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

“…Approaches to simulate soil N 2 O emissions vary from using simple EFs which are multiplied by the total N inputs to the field to process-based models that simulate the underlying microbial processes that, through interactions with the soil physical and chemical environment, affect soil N turnover and N 2 O emissions (Li et al, 2012). The more complex models may use the 'Hole-in-the-Pipe' conceptual approach by Firestone and Davidson (1989), whereby the N intermediates from nitrification and denitrification processes are substrates for N 2 O and N 2 production.…”