Abstract
Assessing and improving the sustainability of dairy production systems is essential to secure future food production. This requires a holistic approach to reveal trade-offs between emissions of the different greenhouse gases (GHG) and nutrient-based pollutants and to ensure that interactions between farm components are taken into account. Process-based models are essential to support whole-farm mass balance accounting. However, since variation between process-based model results can be large, there is a need to compare and better understand the strengths and limitations of various models. Here, we use a whole-farm mass-balance approach to compare five process-based models in terms of predicted carbon (C), nitrogen (N) and phosphorus (P) flows and potential global warming impact (GWI) associated with milk production at the animal, field and farm-scale. We include two whole-farm models complemented by two field-scale models and one animal-based model. A whole-farm mass-balance framework was used to facilitate model comparison at different scales. GWIs were calculated from predicted emissions of methane (CH4) and nitrous oxide (N2O) and soil C change. Results show that predicted whole-farm GWIs were similar for the two whole farm models, ManureDNDC and IFSM, with a predicted GWI of 9.3 and 10.8 Gg CO2eq. year−1 for ManureDNDC and IFSM, respectively. Enteric CH4 emissions were the single most important source of greenhouse gas emissions contributing 47%–70% of the total farm GWI. Model predictions were comparable, that is, within a factor of 1.5, for most flows related to the animal, barn and manure management system. In contrast, predicted field emissions of N2O and ammonia (NH3) to air, N and P losses to the hydrosphere and soil C change, were highly variable across models. This indicates that there is a need to further our understanding of soil and crop N, P and C flows and that measurement data on nutrient and C flows are particularly needed for the field. In addition, there is a need to further understand how anaerobic digestion influences manure composition and subsequent emissions of N2O and NH3 after application of digestate to the field. Empirical data on manure composition before and after anaerobic digestion are essential for model evaluation.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 31-44 |
| Number of pages | 14 |
| Journal | Agriculture, Ecosystems and Environment |
| Volume | 237 |
| DOIs | |
| State | Published - Jan 16 2017 |
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All Science Journal Classification (ASJC) codes
- Ecology
- Animal Science and Zoology
- Agronomy and Crop Science
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Comparison of process-based models to quantify nutrient flows and greenhouse gas emissions associated with milk production. / Veltman, Karin; Jones, Curtis D.; Gaillard, Richard; Cela, Sebastian; Chase, Larry; Duval, Benjamin D.; Izaurralde, R. César; Ketterings, Quirine M.; Li, Changsheng; Matlock, Marty; Reddy, Ashwan; Rotz, Alan; Salas, William; Vadas, Peter; Jolliet, Olivier.
In: Agriculture, Ecosystems and Environment, Vol. 237, 16.01.2017, p. 31-44.Research output: Contribution to journal › Article
TY - JOUR
T1 - Comparison of process-based models to quantify nutrient flows and greenhouse gas emissions associated with milk production
AU - Veltman, Karin
AU - Jones, Curtis D.
AU - Gaillard, Richard
AU - Cela, Sebastian
AU - Chase, Larry
AU - Duval, Benjamin D.
AU - Izaurralde, R. César
AU - Ketterings, Quirine M.
AU - Li, Changsheng
AU - Matlock, Marty
AU - Reddy, Ashwan
AU - Rotz, Alan
AU - Salas, William
AU - Vadas, Peter
AU - Jolliet, Olivier
PY - 2017/1/16
Y1 - 2017/1/16
N2 - Assessing and improving the sustainability of dairy production systems is essential to secure future food production. This requires a holistic approach to reveal trade-offs between emissions of the different greenhouse gases (GHG) and nutrient-based pollutants and to ensure that interactions between farm components are taken into account. Process-based models are essential to support whole-farm mass balance accounting. However, since variation between process-based model results can be large, there is a need to compare and better understand the strengths and limitations of various models. Here, we use a whole-farm mass-balance approach to compare five process-based models in terms of predicted carbon (C), nitrogen (N) and phosphorus (P) flows and potential global warming impact (GWI) associated with milk production at the animal, field and farm-scale. We include two whole-farm models complemented by two field-scale models and one animal-based model. A whole-farm mass-balance framework was used to facilitate model comparison at different scales. GWIs were calculated from predicted emissions of methane (CH4) and nitrous oxide (N2O) and soil C change. Results show that predicted whole-farm GWIs were similar for the two whole farm models, ManureDNDC and IFSM, with a predicted GWI of 9.3 and 10.8 Gg CO2eq. year−1 for ManureDNDC and IFSM, respectively. Enteric CH4 emissions were the single most important source of greenhouse gas emissions contributing 47%–70% of the total farm GWI. Model predictions were comparable, that is, within a factor of 1.5, for most flows related to the animal, barn and manure management system. In contrast, predicted field emissions of N2O and ammonia (NH3) to air, N and P losses to the hydrosphere and soil C change, were highly variable across models. This indicates that there is a need to further our understanding of soil and crop N, P and C flows and that measurement data on nutrient and C flows are particularly needed for the field. In addition, there is a need to further understand how anaerobic digestion influences manure composition and subsequent emissions of N2O and NH3 after application of digestate to the field. Empirical data on manure composition before and after anaerobic digestion are essential for model evaluation.
AB - Assessing and improving the sustainability of dairy production systems is essential to secure future food production. This requires a holistic approach to reveal trade-offs between emissions of the different greenhouse gases (GHG) and nutrient-based pollutants and to ensure that interactions between farm components are taken into account. Process-based models are essential to support whole-farm mass balance accounting. However, since variation between process-based model results can be large, there is a need to compare and better understand the strengths and limitations of various models. Here, we use a whole-farm mass-balance approach to compare five process-based models in terms of predicted carbon (C), nitrogen (N) and phosphorus (P) flows and potential global warming impact (GWI) associated with milk production at the animal, field and farm-scale. We include two whole-farm models complemented by two field-scale models and one animal-based model. A whole-farm mass-balance framework was used to facilitate model comparison at different scales. GWIs were calculated from predicted emissions of methane (CH4) and nitrous oxide (N2O) and soil C change. Results show that predicted whole-farm GWIs were similar for the two whole farm models, ManureDNDC and IFSM, with a predicted GWI of 9.3 and 10.8 Gg CO2eq. year−1 for ManureDNDC and IFSM, respectively. Enteric CH4 emissions were the single most important source of greenhouse gas emissions contributing 47%–70% of the total farm GWI. Model predictions were comparable, that is, within a factor of 1.5, for most flows related to the animal, barn and manure management system. In contrast, predicted field emissions of N2O and ammonia (NH3) to air, N and P losses to the hydrosphere and soil C change, were highly variable across models. This indicates that there is a need to further our understanding of soil and crop N, P and C flows and that measurement data on nutrient and C flows are particularly needed for the field. In addition, there is a need to further understand how anaerobic digestion influences manure composition and subsequent emissions of N2O and NH3 after application of digestate to the field. Empirical data on manure composition before and after anaerobic digestion are essential for model evaluation.
UR - http://www.scopus.com/inward/record.url?scp=85007206577&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007206577&partnerID=8YFLogxK
U2 - 10.1016/j.agee.2016.12.018
DO - 10.1016/j.agee.2016.12.018
M3 - Article
AN - SCOPUS:85007206577
VL - 237
SP - 31
EP - 44
JO - Agriculture, Ecosystems and Environment
JF - Agriculture, Ecosystems and Environment
SN - 0167-8809
ER -