Wednesday, August 16, 2017
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Measurement of nitrous oxide emissions from soils

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The InveN2Ory project (project AC0116) is led by Dr Dave Chadwick and comprises 5 interlinked workpackages (WP) each led by an appropriate research expert. Nine different organisations are involved in the research consortium: ADAS, AFBI, CEH, Met Office, Rothamsted Research, SAC, University of East Anglia, Prof. Keith Smith (University of Edinburgh), University of Aberdeen. Workpackage leaders are named below:

        Dr Dave Chadwick (Rothamsted Research, North Wyke – 
            PI of project and leader of WP1)

        Dr Bob Rees (SAC, Edinburgh – leader of WP2)

        John Williams (ADAS, Boxworth – leader of WP3)

        Prof Pete Smith (University of Aberdeen – leader of WP4)

        Dr Ute Skiba (CEH, Edinburgh – leader of WP5)


WP 1 Prioritisation phase

The prioritisation phase is limited to the first 6 months of the project and aims to;  a) Identify the key soil / climate zones and sources of N2O that require further measurements in order to generate country specific emission factors; b) develop standard protocols for experimental design, measurements, data handling, statistical analysis and risk assessments; c) identify suitable proxies to accompany plot scale experimental N2O emission factor measurements.

WP 2 Measurements of direct and indirect N2O emissions

A number of tillage and grassland sites have been selected based on knowledge of recently completed and current projects where N2O measurements have been made, on contrasting soil types and climatic situations throughout England, Scotland, Wales and Northern Ireland. At these experimental field sites, N2O emission measurements are being measured, using a standard experimental protocol for static chamber methodology, from key sources: N fertilisers, manures, and dung and urine deposition by grazing stock. In order to quantify effects of potential mitigation methods on N2O emissions from these N sources, additional aims include quantifying the effect of nitrification inhibitors, fertiliser types, manure and fertiliser timings, as well as the effects of urine and dung deposition timings on N2O emissions. We are also investigating the form of the relationship between fertiliser N application rate and N2O emission, as there is growing evidence that it is non-linear.

The effect of slurry application techniques on N2O emissions will also be assessed to generate EFs for a future proofed reporting tool which may need to reflect methodologies aimed at reducing ammonia emissions from slurry spreading. Also, much needed N2O measurements from solid manure applications will be made at most livestock manure experimental sites. Indirect N2O EFs associated with leached nitrate and ammonia emissions are being assessed at appropriate sites, whilst N2O sampling from drainage/runoff and groundwater samples from three contrasting catchments are also being quantified.


Static chambers in position in a growing wheat crop . Chambers have been stacked on top each other to accommodate the height of the wheat as it grows
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Nitrous oxide chambers on a winter wheat crop in Gilchristan, Scotland (SAC):

 

 
WP 3 Identification of proxies

The project will develop and assess the use of proxies which could be useful (to both policy makers and modellers) in assessing the impact of changes in agricultural practices and soil and climatic conditions on N2O emissions at national, regional, farm and field levels. For example, farm nutrient balances and nitrogen use efficiency per unit of agricultural product may be useful proxies at farm and regional scales, whilst soil-based proxies such as soil wetness and soil mineral N content may be more appropriate for the field scale. 'Blind' modelling will be used to test the predictive capacity of the proxies identified.

The project will develop and assess the use of proxies which could be useful (to both policy makers and modellers) in assessing the impact of changes in agricultural practices and soil and climatic conditions on NO emissions at national, regional, farm and field levels. For example, farm nutrient balances and nitrogen use efficiency per unit of agricultural product may be useful proxies at farm and regional scales, whilst soil-based proxies such as soil wetness and soil mineral N content may be more appropriate for the field scale. 'Blind' modelling will be used to test the predictive capacity of the proxies identified.


WP 4 Modelling

The measurements made as part of this project will provide essential data to generate a series of country specific EFs, and to validate mechanistic models. Models will be used to interpolate where data are missing at the measurement sites and to assess the attribution of flux measurements to different drivers for defining Tier 2 EFs. Although some mitigation will be tested experimentally, potential mitigation methods will also be assessed through modelling. Tier 2 EFs will also be estimated through modelling (e.g. soil, climate, region, crop, rotation, fertilizer specific) and we will quantify the confidence of (or uncertainty about) EFs. Spatial modelling (Tier 3 runs) will estimate N2O emissions for the whole of the UK.

WP 5 Verification of N2O emissions

Verification of measured and modelled emissions of N2O will occur at a range of temporal and spatial scales. The potential uncertainty of using static chambers to address spatial and temporal variation in N2O emissions will be determined using fast-flux (rapid in situ sensor technology) and automated chambers. Upscaling from emissions measured using chambers to the field scale will be assessed via comparison of static chambers and eddy covariance methodologies, whilst modelled emissions will be assessed seasonally through continued high-resolution sampling at the field scale. Inverse modelling of atmospheric N2O concentrations at specific locations within the UK will be used to verify emissions at the regional and national scales.


 
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