Nitrogen loss factors of nitrogen trace gas emissions and leaching from excreta patches in grassland ecosystems: A summary of available data

Cai, Yanjiang; Akiyama, Hiroko

doi:10.1016/j.scitotenv.2016.07.222

Cited by 54 publications

(29 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast, other studies did measure EFs up to 1.0% (e.g., Japan 0.86%, China 1.0%, and UK 0.53%, Table ). All these studies suggest that the IPCC Tier 1 N 2 O EF overestimates N 2 O emissions from dung patches (Figure ), which is consistent with the mean EF (0.28%) for cattle dung patches in the meta‐analysis by Cai and Akiyama ().…”

Section: Discussionsupporting

confidence: 81%

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Zhu

Merbold

Pelster

et al. 2018

Global Biogeochemical Cycles

View full text Add to dashboard Cite

To improve estimates of agricultural greenhouse gas emissions in sub‐Saharan Africa, we measured over six individual periods of 25–29 days fluxes of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) with subdaily time resolution from dung patches of different quality (C/N ratio: 23–41) and quantity (0.5 and 1.0 kg) on a Kenyan rangeland during dry and wet seasons. Methane emissions peaked following dung application, whereas N2O and CO2 fluxes from dung patches were similar to fluxes from rangeland soils receiving no N additions. Greenhouse gas emissions scaled linearly with dung quantity during both seasons. Dung with a low (23) C/N ratio produced up to 10 times more CH4 than dung with a high (41) C/N ratio. Overall, CH4 emission factors (EFs) ranged from 0.001 to 0.042%, lower than those derived in temperate regions. Cumulative CO2 and N2O emissions were similar for all treatments across the different seasons. The N2O EF ranged from 0 to 0.01%, less than 1% of the Intergovernmental Panel on Climate Change Tier 1 default EF (2%) for N2O emissions from dung and urine patches, likely because of the low dung N content (9.7–16.5 g N kg−1 dry matter). However, these results were consistent with the updated cattle dung EF (0.2%) developed for Kenya in 2016/2017 (EF database ID# 422665). In view of the wide range of climates, soils, and management practices across sub‐Saharan Africa, development of robust GHG EFs from dung patches for SSA requires additional studies.

show abstract

Section: Discussionsupporting

confidence: 81%

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Zhu

Merbold

Pelster

et al. 2018

Global Biogeochemical Cycles

View full text Add to dashboard Cite

show abstract

“…The available reactive N is used by microbial nitrification and denitrification processes where significant amounts of N 2 O can be produced (Selbie et al, 2015). A nonlinear response of N 2 O emissions to N loading has been shown previously (Cardenas et al, 2010), and urine patches of cattle have exceptionally high N loading rates (up to 2000 kg N ha −1 ), making them especially prone to high N 2 O losses (Selbie et al, 2015).…”

Section: Introductionmentioning

confidence: 90%

Grazing-related nitrous oxide emissions: from patch scale to field scale

et al. 2019

View full text Add to dashboard Cite

Abstract. Grazed pastures are strong sources of the greenhouse gas nitrous oxide (N2O). The quantification of N2O emissions is challenging due to the strong spatial and temporal variabilities of the emission sources and so N2O emission estimates are very uncertain. This study presents N2O emission measurements from two grazing systems in western Switzerland over the grazing season of 2016. The 12 dairy cows of each herd were kept in an intensive rotational grazing management. The diet for the two herds of cows consisted of different protein-to-energy ratios (system G: grass only diet; system M: grass with additional maize silage) resulting in different nitrogen (N) excretion rates. The N in the excretion was estimated by calculating the animal nitrogen budget taking into account the measurements of feed intake, milk yield, and body weight of the cow herds. Directly after the rotational grazing phases, background and urine patches were identified based on soil electric conductivity measurements while fresh dung patches were identified visually. The magnitude and temporal pattern of these different emission sources were measured with a fast-box (FB) chamber and the field-scale fluxes were quantified using two eddy covariance (EC) systems. The FB measurements were finally upscaled to the field level and compared to the EC measurements for quality control by using EC footprint estimates of a backward Lagrangian stochastic dispersion model. The comparison between the two grazing systems was performed during emission periods that were not influenced by fertilizer applications. This allowed the calculation of the excreta-related N2O emissions per cow and grazing hour and resulted in considerably higher emissions for system G compared to system M. Relating the found emissions to the excreta N resulted in excreta-related emission factors (EFs) of 0.74±0.26 % for system M and 0.83±0.29 % for system G. These EF values were thus significantly smaller compared to the default EF of 2 % provided by the IPCC guidelines for cattle excreta deposited on pasture. The measurements showed that urine patch emission dominated the field-scale fluxes (57 %), followed by significant background emissions (38 %), and only a small contribution of dung patch emission (5 %). The resulting source-specific EFs exhibited a clear difference between urine (1.12±0.43 %) and dung (0.16±0.06 %), supporting a disaggregation of the grazing-related EFs by excreta type in emission inventories. The study also highlights the advantage of a N-optimized diet, which resulted in reduced N2O emissions from animal excreta.

show abstract

“…been shown previously (Cardenas et al, 2010), and urine patches of cattle have exceptionally high N loading rates (up to 2000 kg N ha −1 ), making them especially prone to high N 2 O losses (Selbie et al, 2015).…”

Section: Introductionmentioning

confidence: 74%

“…Historically, most studies used static chambers to quantify N 2 O emissions (Flechard et al, 2007). Chamber measurements are ideal to quantify emissions on a small spatial scale and to attribute the measured fluxes to certain emission drivers, but for excreta emissions these measurements were often performed on manually applied urine and dung patches (Bell et al, 2015;Cai and Akiyama, 2016). Additionally, due to the strong heterogeneity of the emissions from a pasture (Cowan et al, 2015;Flechard et al, 2007) chamber techniques are not ideal to compute field-scale emissions for grazing systems.…”

Section: Introductionmentioning

confidence: 99%

Response to Referee #2

Voglmeier¹

2019

Preprint

View full text Add to dashboard Cite

Grazed pastures are strong sources of the greenhouse gas nitrous oxide (N 2 O). The quantification of N 2 O emissions is challenging due to the strong spatial and temporal variabilities of the emission sources and so N 2 O emission estimates are very uncertain. This study presents N 2 O emission measurements from two grazing systems in western Switzerland over the grazing season of 2016. The 12 dairy cows of each herd were kept in an intensive rotational grazing management. The diet for the two herds of cows consisted of different protein-to-energy ratios (system G: grass only diet; system M: grass with additional maize silage) resulting in different nitrogen (N) excretion rates. The N in the excretion was estimated by calculating the animal nitrogen budget taking into account the measurements of feed intake, milk yield, and body weight of the cow herds. Directly after the rotational grazing phases, background and urine patches were identified based on soil electric conductivity measurements while fresh dung patches were identified visually. The magnitude and temporal pattern of these different emission sources were measured with a fast-box (FB) chamber and the field-scale fluxes were quantified using two eddy covariance (EC) systems. The FB measurements were finally upscaled to the field level and compared to the EC measurements for quality control by using EC footprint estimates of a backward Lagrangian stochastic dispersion model. The comparison between the two grazing systems was performed during emission periods that were not influenced by fertilizer applications. This allowed the calculation of the excreta-related N 2 O emissions per cow and grazing hour and resulted in considerably higher emissions for system G compared to system M. Relating the found emissions to the excreta N resulted in excreta-related emission factors (EFs) of 0.74 ± 0.26 % for system M and 0.83 ± 0.29 % for system G. These EF values were thus significantly smaller compared to the default EF of 2 % provided by the IPCC guidelines for cattle excreta deposited on pasture. The measurements showed that urine patch emission dominated the field-scale fluxes (57 %), followed by significant background emissions (38 %), and only a small contribution of dung patch emission (5 %). The resulting source-specific EFs exhibited a clear difference between urine (1.12 ± 0.43 %) and dung (0.16 ± 0.06 %), supporting a disaggregation of the grazing-related EFs by excreta type in emission inventories. The study also highlights the advantage of a N-optimized diet, which resulted in reduced N 2 O emissions from animal excreta.

show abstract

Nitrogen loss factors of nitrogen trace gas emissions and leaching from excreta patches in grassland ecosystems: A summary of available data

Cited by 54 publications

References 54 publications

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Grazing-related nitrous oxide emissions: from patch scale to field scale

Response to Referee #2

Contact Info

Product

Resources

About