Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Saggar SSubject: search.filters.subject.Soil

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    Meta-analysis of New Zealand's nitrous oxide emission factors for ruminant excreta supports disaggregation based on excreta form, livestock type and slope class.
    (Elsevier B.V., 2020-08-25) van der Weerden TJ; Noble AN; Luo J; de Klein CAM; Saggar S; Giltrap D; Gibbs J; Rys G; Jenerette D
    Globally, animal excreta (dung and urine) deposition onto grazed pastures represents more than half of anthropogenic nitrous oxide (N2O) emissions. To account for these emissions, New Zealand currently employs urine and dung emission factor (EF3) values of 1.0% and 0.25%, respectively, for all livestock. These values are primarily based on field studies conducted on fertile, flatland pastures predominantly used for dairy cattle production but do not consider emissions from hill land pastures primarily used for sheep, deer and non-dairy cattle. The objective of this study was to determine the most suitable urine and dung EF3 values for dairy cattle, non-dairy cattle, and sheep grazing pastures on different slopes based on a meta-analysis of New Zealand EF3 studies. As none of the studies included deer excreta, deer EF3 values were estimated from cattle and sheep values. The analysis revealed that a single dung EF3 value should be maintained, although the value should be reduced from 0.25% to 0.12%. Furthermore, urine EF3 should be disaggregated by livestock type (cattle > sheep) and topography (flatland and low sloping hill country > medium and steep sloping hill country), with EF3 values ranging from 0.08% (sheep urine on medium and steep slopes) to 0.98% (dairy cattle on flatland and low slopes). While the mechanism(s) causing differences in urine EF3 values for sheep and cattle are unknown, the 'slope effect' on urine EF3 is partly due to differences in soil chemical and physical characteristics, which influence soil microbial processes on the different slope classes. The revised EF3 values were used in an updated New Zealand inventory approach, resulting in 30% lower national N2O emissions for 2017 compared to using the current EF3 values. We recommend using the revised EF3 values in New Zealand's national greenhouse gas inventory to more accurately capture N2O emissions from livestock grazing.
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    Review and update of a Nutrient Transfer model used for estimating nitrous oxide emissions from complex grazed landscapes, and implications for nationwide accounting
    (John Wiley and Sons Inc on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, 2022-09-30) Vibart R; Giltrap D; Saggar S; Mackay A; Betteridge K; Costall D; Rollo M; Draganova I; Zhu-Barker. X
    In New Zealand, nitrous oxide emissions from grazed hill pastures are estimated using different emission factors for urine and dung deposited on different slope classes. Allocation of urine and dung to each slope class needs to consider the distribution of slope classes within a landscape and animal behavior. The Nutrient Transfer (NT) model has recently been incorporated into the New Zealand Agricultural GHG Inventory Model to account for the allocation of excretal nitrogen (N) to each slope class. In this study, the predictive ability of the transfer function within the NT model was explored using urine deposition datasets collected with urine sensor and GPS tracker technology. Data were collected from three paddocks that had areas in low (<12°), medium (12-24°), and high slopes (>24°). The NT model showed a good overall predictive ability for two of the three datasets. However, if the urine emission factors (% of urine N emitted as N2 O-N) were to be further disaggregated to assess emissions from all three slope classes or slope gradients, more precise data would be required to accurately represent the range of landscapes found on farms. We have identified the need for more geospatial data on urine deposition and animal location for farms that are topographically out of the range used to develop the model. These new datasets would provide livestock urine deposition on a more continuous basis across slopes (as opposed to broad ranges), a unique opportunity to improve the performance of the NT model.