An integral assessment of carbon and nitrogen emissions in dairy cattle production systems: Comparing dynamic process-based greenhouse gas emissions factors with IPCC Tier 1 and Tier 2 approaches in confinement and pasture-based systems

The assessment of greenhouse gases (GHG) and nitrogen (N) emissions is essential for climate change mitigation. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines for GHG quantification at both national and global levels. However, the IPCC Tier 1 (T1) and Tier 2 (T2) estimates, mostly used in national inventories, rely on generic emission factors (EFs) and empirical equations that are not suitable for case-specific assessments on individual farms. Thus, a more advanced Tier 3 (T3) methodology is needed to reflect the impact of key factors on emissions and reveal the effect of emission mitigation measures. Here we compare the IPCC T1 and T2 estimates to results from a cascade of process-based (PB) models referred to as T3 approach, for farm-level emissions. The results showed that the estimates from PB models differ significantly from those of the IPCC T1 and T2 estimates and allow more capability to predict variation. Moreover, PB models account for temporal changes and the underlying mechanisms responsible for GHG and N emissions. These models can be adopted for case-specific GHG assessment and project future mitigation strategies under different climate scenarios, regional contexts and on-farm management. Additional to the known applicability of PB models to estimate enteric methane and soil emissions, the present study demonstrates for the first time in Germany and Europe the effectiveness of Manure-DNDC model in simulating ammonia (NH 3 ) and methane (CH 4 ) barn emissions, highlighting the potential for using PB models in case-specific GHG and N assessments for the whole manure management chain. Overall, this study presents options for a methodology in case-specific GHG assessment that can capture the effect of climate change and mitigation measures. • IPCC Tier 1 and 2 estimates may be unsuitable for case-specific GHG assessments • A combined use of Dutch Tier 3 enteric methane and (Manure)DNDC models was followed • Process-based Tier 3 models may be more beneficial for case-specific GHG estimates • Manure-DNDC model was able to simulate NH 3 and CH 4 barn emissions satisfactorily • Process-based models key for carbon farming, measurement reporting & verification

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Publication Details

Journal
Journal of Cleaner Production
Published
2024-12-13
DOI
https://doi.org/10.1016/j.jclepro.2024.144479
Citations
4
Primary Topic
Agriculture Sustainability and Environmental Impact
Type
article
Field-Weighted Citation Impact
1.84

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article

An integral assessment of carbon and nitrogen emissions in dairy cattle production systems: Comparing dynamic process-based greenhouse gas emissions factors with IPCC Tier 1 and Tier 2 approaches in confinement and pasture-based systems

Dominika Król, Jürgen Zentek, Barbara Amon, Tony J. van der Weerden et al.
4 citations
Journal of Cleaner Production
Agriculture Sustainability and Environmental Impact
1.84
article

An integral assessment of carbon and nitrogen emissions in dairy cattle production systems: Comparing dynamic process-based greenhouse gas emissions factors with IPCC Tier 1 and Tier 2 approaches in confinement and pasture-based systems

Dominika Król, Jürgen Zentek, Barbara Amon, Tony J. van der Weerden, Thomas Amon, David Janke, A. Bannink, Gary Lanigan, Latifa Ouatahar, Pierre Beukes, Sabrina Hempel, Jia Deng
article en
4 citations

Abstract

The assessment of greenhouse gases (GHG) and nitrogen (N) emissions is essential for climate change mitigation. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines for GHG quantification at both national and global levels. However, the IPCC Tier 1 (T1) and Tier 2 (T2) estimates, mostly used in national inventories, rely on generic emission factors (EFs) and empirical equations that are not suitable for case-specific assessments on individual farms. Thus, a more advanced Tier 3 (T3) methodology is needed to reflect the impact of key factors on emissions and reveal the effect of emission mitigation measures. Here we compare the IPCC T1 and T2 estimates to results from a cascade of process-based (PB) models referred to as T3 approach, for farm-level emissions. The results showed that the estimates from PB models differ significantly from those of the IPCC T1 and T2 estimates and allow more capability to predict variation. Moreover, PB models account for temporal changes and the underlying mechanisms responsible for GHG and N emissions. These models can be adopted for case-specific GHG assessment and project future mitigation strategies under different climate scenarios, regional contexts and on-farm management. Additional to the known applicability of PB models to estimate enteric methane and soil emissions, the present study demonstrates for the first time in Germany and Europe the effectiveness of Manure-DNDC model in simulating ammonia (NH 3 ) and methane (CH 4 ) barn emissions, highlighting the potential for using PB models in case-specific GHG and N assessments for the whole manure management chain. Overall, this study presents options for a methodology in case-specific GHG assessment that can capture the effect of climate change and mitigation measures. • IPCC Tier 1 and 2 estimates may be unsuitable for case-specific GHG assessments • A combined use of Dutch Tier 3 enteric methane and (Manure)DNDC models was followed • Process-based Tier 3 models may be more beneficial for case-specific GHG estimates • Manure-DNDC model was able to simulate NH 3 and CH 4 barn emissions satisfactorily • Process-based models key for carbon farming, measurement reporting & verification

Journal of Cleaner ProductionVol. 486
Teagasc - The Irish Agriculture and Food Development Authority (IE), University of New Hampshire (US), AgResearch (NZ), DairyNZ (NZ), Leibniz Institute for Agricultural Engineering and Bioeconomy (DE), Applications Research (United States) (US), University of Zielona Góra (PL), Freie Universität Berlin (DE), Wageningen University & Research (NL)
Department of Agriculture, Food and the Marine, Ireland, Teagasc, Leibniz-Gemeinschaft
Openalex Percentile: Top 14%
Agriculture Sustainability and Environmental Impact
1.84
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