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SID 5 Research Project Final Report

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Project identification

1. Defra Project code CC0251

2. Project title

new Methods to quantify Agricultural Nitrous oxide Emissions (MANE)

3. Contractororganisation(s)

Centre of Ecology and Hydrology (CEH)Bush Estate, PenicuikMidlothian                         

54. Total Defra project costs £ 228,003

5. Project: start date................ 01 April 2001

end date................. 31 September 2004

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Executive Summary7. The executive summary must not exceed 2 sides in total of A4 and should be understandable to the

intelligent non-scientist. It should cover the main objectives, methods and findings of the research, together with any other significant events and options for new work.

Rational and ObjectivesThe agricultural industry is the single largest source of the greenhouse gas nitrous oxide, contributing to more than 70% of the national emission rate, traffic is an increasing important source, currently contributing to about 8 % of the national emission rate. Of all the greenhouse gases the national estimate of nitrous oxide emissions is the most uncertain, due to high spatial and temporal variability of the biological sources. This uncertainty cannot easily be met by the conventional methodology: enclosure method using mostly small chambers < 1 m diameter. The objectives of MANE (new Methods to quantify Agricultural Nitrous oxide Emissions) were to develop new, better methods to identify nitrous oxide concentrations and emission rates from its main sources. The detailed objectives were

(1) to develop and demonstrate a novel “drive-around” plume method using a vehicle-mounted tunable diode laser (TDL), for direct, precise and continuous measurements of N2O emission rates from recently fertilised grasslands and arable land, heaps of solid manure, slurry lagoons and livestock buildings, (2) to determine the seasonal variations of N2O emissions from grassland and from heaps of solid manure, using a combination of three methods: long-term TDL-based micrometeorological flux measurements, the tracer ratio technique, and chambers, (3) to develop and apply a method for monitoring the UK spatial, seasonal and inter annual variations of agricultural N2O emissions at the local, regional and country scale.

Summary of results

1) Development of the plume method for N2O flux measurementsThe plume method is based on the principal that emissions from a source generate a plume of enhanced concentrations downwind. The enhanced concentration is measured by either walking or driving through. The plume method was applied at three scales: a point source of an outdoor dung heap, a local source of a 33 ha agricultural area in SE Scotland and to a regional source of 136 km 2 dominated by intensively managed grazed grasslands in Cumbria. Plumes of N2O at all scales could be identified easily. This method can be used successfully to calculate fluxes from well defined point sources for example, dung heaps or isolated fields. Driving downwind of larger areas, sources of above background N2O emissions can be identified, for example recently fertilised fields, compost heaps tractor operations and road traffic. This method could be developed into a valuable tool identifying very quickly hotspots of N 2O emissions within a region or farm (TV detector van approach).

2) Seasonal variations of N2O emissions from manure heaps and managed grasslandsSeasonal variations of N2O emissions from two important agricultural sources, a dung heap and a managed grassland field, were controlled by rainfall.

a) An entire poultry manure heap was covered; N2O emissions increased with approaching winter and increasing rainfall to 91 mg N2O t-1 d-1. This suggests that the N2O emission is positively influenced by the moisture content of the manure surface. Comparison of the cover method with conventional small chambers and the tracer ratio method was not satisfactory. When using the chamber method very large differences between sampling positions as well as large differences between measurement days characterise these data. The cover method indicated a higher emission rate than the chamber method by about a factor of four. Results of the tracer ratio method measurements show mean daily N2O emission rates from the heap two orders of magnitude greater than the rates measured by the other two methods. The main restriction on robust measurements using the tracer ratio method is the difficulty in measuring the small rise in N2O concentration in the air passing over the broiler litter heap. In spite of these discrepancies, the results showed that N2O fluxes from manure heaps are 2 orders of magnitude larger than fluxes typically recorded from agricultural soils. b) Nitrous oxide emissions were measured at the field scale using the eddy covariance method and analysis of N2O concentrations by tunable laser spectroscopy. Measurements were almost continuous for a one-year period and included three nitrogen fertilisation events. Such detailed measurements of N 2O at the field scale are unprecedented in the UK. The response to the same rate of nitrogen fertilisation was determined by the rainfall amount prior to fertiliser application. In June 2002, when total rainfall in the 7 days before fertilisation was 38 mm N 2O emissions peaked at 2.5 mg N2O-N m-2 s-1 within 24 hours of fertilisation. The subsequent fertilisation events did not induce large N2O emission peaks and the relationship between rainfall and N2O emission was not linear. Very wet soils (78 mm rain during the 7 days prior fertiliser application) provided optimal

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conditions for the reduction of N2O to N2 by microbial denitrification. Dry soils (0.8 mm rain during the 7 days prior fertiliser application) did not create the necessary anaerobic environment for N2O production. Diurnal changes in N2O, with maximum emissions at noon and minimum emissions during the night were observed during periods of large N2O emission rates. The total annual N2O emission from this 16 ha cut grassland was 5.5 kg N2O-N ha –1 y-1 or 2.8% of the nitrogen fertiliser applied, and was in agreement with N2O emissions measured by chambers on nearby plots of the same grassland management.

3) Development of a nitrous oxide monitoring network for Britain Changes in the atmospheric concentrations of the long-lived greenhouse gas nitrous oxide (N 2O) are monitored routinely at relatively few sites distributed around the globe. Such measurements have provided data on the seasonal and inter-annual change and global increase in atmospheric N 2O and provided the data for inverse modelling to deduce the original emissions. We have developed a monitoring network across the typical land uses of a single country, Great Britain, to provide information on the spatial and temporal variation of atmospheric N2O and used the data to verify national emission inventories. A network of 87 sites was established across Great Britain, representing the main geographical and climatic regions and the 4 dominant land use categories: livestock dominated agriculture (‘livestock’), urban (‘urban’), rural areas with urban influence (‘mixed’), remote extensively managed land (‘background’). Cumulative monthly air samples were sampled continuously into containers, which are then sent to CEH-Edinburgh for analysis of N2O and CH4 by tuneable diode laser (TDL) spectroscopy. The network was run for a two-year period (2002 & 2003). Monthly N2O concentration measurements showed large spatial and temporal variability, but concentrations were mostly smaller from the 56 sites dominated by livestock farming (320.5 ± 1.5 ppb N2O) than from the 13 urban locations (329.4 ± 16.5 ppb N2O) or the 16 sites in rural areas subjected to some urban influence (mixed category) (328.2 ± 8.1 ppb N2O). The seasonal, inter-annual variations correlated with air temperature and rainfall in areas dominated by agriculture or agriculture with some urban influence, with r2 coefficients ranging from 24% to 81.2%. However in urban areas, where the main source of N2O is the emission from vehicles, soil emissions are not related (r2 = 1.5%). 2003 was a very unusual year with extremely dry weather conditions during February, August, October and November and a very warm summer. Due to this spring dryness, N2O concentrations in livestock dominated areas were smaller than in the previous year and did not show the expected fertiliser induced concentration increase. Interestingly, variations and magnitude of N2O concentrations for the mixed and urban, but not for the livestock dominated agricultural sites, were much larger than in the previous year. A very similar pattern was observed for atmospheric CH4 concentrations. The reason for this increase in both gases is not understood yet, but highlights the problem of inter-annual climatic variations triggering a different behaviour depending on land use.

The concentration measurements were compared with CEH’s recently created spatially disaggregated inventory of N2O emissions for GB. This was achieved by modelling the transport and dispersion of N2O based on the emission inventory, using the Lagrangian atmospheric transport model FRAME (Fine Resolution Atmospheric Multi-species Exchange model. The spatial distribution of concentrations displays a similar pattern to that for the emission map but with reduced fine scale variability due to the advection of emitted concentrations between neighbouring grid cells. The average N2O concentration calculated by FRAME was 321.3 ± 0.8 ppb, which is smaller than the average value of 323.3 ± 8.8 ppb measured by the 87 sites of the air monitoring networks. For the agricultural regions of Britain dominated by livestock management N2O concentrations predicted from our 5*5 km2 spatial N2O emission inventory were in reasonable agreement with the measured concentrations and thereby validate CEH’s estimate of agricultural N2O emission. Our estimate uses a multilinear regression model for soil emissions and suggests that agriculture contributes to 73% (121 kt N2O y-1) of the total GB N2O emissions (165 kt N2O y-

1). This estimate is 36% larger than the National N2O inventory calculated using the standard IPPC methodology.

4) ConclusionNon-invasive methods measuring nitrous oxide emissions from the main agricultural and non-agricultural sources at the source, field and regional scale have successfully been developed. The plume method can readily identify emission hotspots within the landscape. Eddy covariance and tracer ratio methods and large covers for confined sources, are suitable for detailed measurements of fluxes from a field, providing high temporal resolution. The concentration-monitoring network provides a relatively cheap method to monitor the spatial and temporal variations of nitrous oxide (and other gases if required) across the country.

Project Report to Defra8. As a guide this report should be no longer than 20 sides of A4. This report is to provide Defra with

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details of the outputs of the research project for internal purposes; to meet the terms of the contract; and to allow Defra to publish details of the outputs to meet Environmental Information Regulation or Freedom of Information obligations. This short report to Defra does not preclude contractors from also seeking to publish a full, formal scientific report/paper in an appropriate scientific or other journal/publication. Indeed, Defra actively encourages such publications as part of the contract terms. The report to Defra should include: the scientific objectives as set out in the contract; the extent to which the objectives set out in the contract have been met; details of methods used and the results obtained, including statistical analysis (if appropriate); a discussion of the results and their reliability; the main implications of the findings; possible future work; and any action resulting from the research (e.g. IP, Knowledge Transfer).

CC0251NEW METHODS TO QUANTIFY AGRICULTURAL NITROUS OXIDE EMISSIONS (MANE)

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U. Skiba, C. Di Marco, D. Fowler and I. Simmons, D. Famulari, U. Dragosits, T. Dore, R. Storeton-West, A. McDonald, E. Nemitz, CEH Edinburgh, Bush Estate, Penicuik, Midlothian.

Robert Sneath and L. McCartney, Silsoe Research Institute, BedfordArjan Hensen, ECN, Netherlands

BackgroundThe agricultural industry is the largest source of the greenhouse gas nitrous oxide (N 2O) and contributes to over 70 % of the UK annual total emission. Of the major greenhouse gases, N2O emissions are the least well quantified at the country scale.

ObjectivesThe objectives of this project were (1) to develop and demonstrate a novel “drive-around” plume method using a vehicle-mounted tunable diode laser (TDL), for direct, precise and continuous measurements of N2O emission rates from recently fertilised grasslands and arable land, heaps of solid manure, slurry lagoons and livestock buildings, (2) to determine the seasonal variations of N2O emissions from grassland and from heaps of solid manure, using a combination of three methods: long-term TDL-based micrometeorological flux measurements, the tracer ratio technique, and chambers, and (3) to develop and apply a method for monitoring the UK spatial, seasonal and interannual variations of agricultural N2O emissions at the local, regional and country scale.

Method 1 Flux measurements of plumes of agricultural N2O using a tunable diode laser

a. Develop “drive round” plume methods using a vehicle mounted tunable diode laser for direct, real time continuous measurements of N2O emissions from grasslands, heaps of solid manure, slurry lagoons and livestock buildings. b. Validate the method against known N2O emission from controlled release. c. Apply the new method in farm scale studies at three locations.

1 a. Development of the “drive round” plume methodWe have developed the ’’drive round” and “walk through” plume method and tested if such method can be used for quick and easy identification of large sources of N2O and other conservative tracegases. We have concentrated on measurements in East Lothian, one of the most prolific arable region in Scotland and on Cumbria, where grasslands are intensively managed for livestock grazing. The plume method is based on the principal that emissions from sources at the surface generate a plume of enhanced concentrations downwind. The requirements for this methodology to work are sensitive instruments capable to measure very small concentration differences of N2O at a high temporal resolution. CEH’s tunable diode laser (TDL) was tuned to an absorption line of 2207 cm -1 and, operating at a frequency of 10 Hz, proved adequate to resolve N2O mixing ratio differences of less than 1 ppb in 1-min measurement periods. The tunable diode laser was placed in the mobile laboratory, with the sample inlet attached to the sonic anemometer housing, which was screwed onto the roof of the truck at a height of 5 m. Wind speed and N2O concentrations were measured at 10 Hz. Data were continuously recorded, using the software Labview to log the data, to perform analog-digital conversions and to calculate fluxes in real time. The route of the travel was recorded by GPS. The land use, any farm management activities and traffic downwind of the TDL sample inlet were recorded in detail by video, still camera and pen and paper. The TDL was calibrated for N2O using a standard gas mixture of 305 ppb N2O in nitrogen every 30 minute throughout the measurement periods. Fluxes of N2O were calculated either using a Gaussian plume equation which calculates the source strength from wind speed and direction, distance from source, height of emission measurement and roughness length of the terrain derived from the turbulence data

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(Hensen and Scharff, 2001), or by using a simple box model were the flux was calculated from the product of concentration increase over the study area, the flowrate of wind through the area, divided by the dimensions of the area. The reported N2O concentrations are the ‘raw’ concentrations measured by the TDL. As we are interested in differences of concentrations it was not necessary to adjust the measured concentrations to the minimum background concentration of 319 ppb, which is measured at Macehead, Ireland and Shetland in westerly airflow.

Results We present three different approaches to the “drive round” plume method, varying in the scale of measurement, ranging from a single source (dung heap), to the field scale and then regional scale. The methodology of measurement was in principal the same and only varied in the speed of travel through the plume. For the single dung heap it was more appropriate to walk rather than drive through the plume, at the field scale resolution of plumes was possible at a travel speed between 20-30 miles/h and at the regional scale travel was at 50 miles/h, in order to minimise the influence of local point sources.

1) The plume of N2O from a single dung heap

Skiba et al. 2005. Agriculture, Ecosystems & Environment, Special Issue, in press.Measurements were made on sheep grazed grassland containing a dung heap of solid cattle manure at Easter Howgate, near Edinburgh, Scotland (NT 239641). The heap accumulated gradually between January and May with material from the nearby cattle sheds. The heap was 50 m long, 3 m high and 5 m wide at one end and tapering to 1.5 m high and 3 m wide at the other end. From these measurements the total volume was estimated to be approximately 300 m3, and the surface area was estimated to be 600 m2. Atmospheric N2O concentrations were measured directly by tunable diode laser spectroscopy (TDL) during 28 th and 31st May 2002. Plumes of N2O were measured, by positioning the TDL sample inlet line at a constant height of 2 m at several distances downwind and upwind of the heap for 1 - 2 minute periods; and in addition by walking slowly through the plume when wind conditions were stable. The sample location in relation to the heap was determined using a global positioning system. Wind speed (cup anemometers) and wind direction was measured at a height of 2 m and 1-min-averages were recorded by data logger (Campbell, 23x). A typical graph of the plume measurements is shown in Fig. 1. In the first few seconds of the trace upwind N 2O concentrations were measured, followed by walking through the plume at constant distance and height downwind of the heap.

Figure 1 (left graph): A typical trace of the plume of N2O concentrations upwind and downwind of the dung heap, measured by tunable laser spectroscopy.

Figure 2 (right graph): Changes in atmospheric N2O concentrations with distance downwind of the dung heap on 30th May 2002.

The plume measurement shown in Fig. 1 was carried out 30 m downwind of the heap at a wind speed of 4.8 m s-1 and a wind direction of 238o. The average upwind and plume concentrations were 315.1 ± 1.2 ppb (n = 250) and 323.8 ± 4.79 ppb (n = 380), respectively.

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The source strength calculated by the Gaussian plume equation was 21.9 mg N2O s-1, which is 4 g N2O-N m-3 d-1. On 31 May the N2O sources strength of the heap was measured in detail by a series of 2-minute concentration measurements up and downwind of the source. During this period, variations in N2O concentrations were less than 1.2 % of the average concentration (n = 100). Wind speeds, wind directions and distance from source ranged from 2.6 to 5.3 m s -1, 235 to 290o and 15 to 45 m, respectively. The largest concentrations were measured closest to the dung heap and declined exponentially with increasing the distance of measurements from 11 to 45 m downwind of the source (Fig. 2). Taking into account distance, windspeed, and height of the measurements, the Gaussian plume model calculated an average source strength of 5.3 g N2O-N h-1, ranging from 1.4 – 6.7 g N2O-N m-3 d-1.

2) The plume of N2O measured at the field scale

An example of the drive round plume method is shown in Fig. 3. This particular run occurred on the 30 March through a small flat region in East Lothian (33 ha), containing a mixture of spring and winter cereals, a small poultry farm, various dung heaps and an organic farm. During our measurements farmers were fertilising winter cereal. The meteorological conditions were cloudy with westerly wind at 5 m s-1. The average driving speed was 20 miles h-1. Typically the upwind concentrations of this area were 312 ± 0.8 ppb N2O, measured over the 4-minute period before entering the study area and 1 minute after leaving the study area. The concentrations measured in the study area over a 8.5 minute time period ranged from ambient to maximum peaks of 325 ppb N2O. The average concentration increase was 2.6 ± 2.7 ppb (Fig. 4). Using a simple box model suggests that for this period the N 2O emission rate was 290 ng N2O m-2 s-1.

Figure 3: Nitrous oxide concentration measurements from an agricultural region in East Lothian, 30 March 2004

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Figure 4: The N2O concentration plot during the ‘drive-around’ trip on 31.03.2004, Boggs Holding in East Lothian. The pink arrow shows the wind direction, and the black arrows indicate the mobile lab direction. The contribution of the enclosed area (field) to the enhanced concentration can be observed from this plot, in the SW tract of the field. On the lower part of the plot an abrupt concentration enhancement can be observed (blue spots amongst red ones), and this was due to a dung heap plume recorded in proximity of the road.

Figure 5: N2O concentration plots recorded along the coastline (left) and along a tract in land (right), when the wind was blowing from SW, on 02 June 2004. The left picture refers to the tract from Maryport to Silloth (12:00 – 12:45). The concentrations are very even and quite low in comparison to the right chart, which was recorded along a tract 18 km inland from Rosley towards Aspatria, which crossed mainly silage fields and grazed grassland, including sheep and cattle. The average unadjusted concentrations measured by the TDL were 297.5 ppbV along the coastline and 305.5 ppbV along the tract in land (10:00 – 10:45), the average windspeed 1.9 m s–1 and the boundary layer height 1474 m.

3) The plume of N2O at the regional scale

The study region chosen was NW Cumbria, a high rainfall area of intense grassland management and livestock grazing, and known from our N2O emission inventory (Sosanzka et al, 2002) to be one of the N2O hotspot areas within GB. The A 595 from Carlisle to Maryport in the south, the Solway Firth in the west and the B 5302 from Carlisle to Silloth bordered the

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area in the north. N2O concentrations were measured in westerly airflow whilst driving at about 50 mph using two mobile laboratories (ECN and CEH) driving in opposite directions. Simultaneously manual samples of background air were taken at 15 min intervals at the seaside in Maryport. A sonic anemometer was positioned just outside the southeastern edge of the study area, collecting data of wind speed and direction continuously throughout the 2 days of June 1st and 2nd. The boundary layer height was calculated by ECN from radiosonde measurements taken at noon at Boulmer near Newcastle upon Tyne and Castor Bay at the east coast of Northern Ireland. N2O concentrations in the air coming off the sea, measured both by TDL’s and the manual sampling system were consistently lower than those measured further inland, as shown in Fig. 5. In this particular example the concentration difference between N2O measured in ‘clean air’ over the sea and 18 km inland was 8 ppb, suggesting an average flux of 7.8 ng N2O m2 s-1.

1 b. Validate the plume method against known N2O emission from controlled releaseThe plume method described in section a. was validated against the tracer ratio method by CEH and SRI in May 2002. Nitrous oxide and SF6 (both 100%) were released simultaneously 50 m upwind from the measuring point. SRI used Tedlar bags to collect samples for subsequent analysis of SF6 and N2O by gas chromatography and ECD. CEH made direct measurements of N2O by TDL from the same location. The release rate of N2O was 2604 ml min –1 (1.9 g s-1) and that of SF6 53.1 & 27.5 ml min-1. The wind speed was 3.2 and 3.8 m s-1. After initial problems with flow of SF6, the differences between release and recapture of SF6

and N2O by both the GC analysis of SF6 and N2O and the TDL analysis of N2O was less than 10%.

1 c. Apply the new method in farm scale studies at three locationsThis objective was met indirectly by applying the ‘drive around’ plume method to the regions of intensive and diverse agricultural activities in East Lothian and Cumbria. We have shown that plumes of N2O from point sources, at the local and regional scale can be identified easily. This method can be used successfully to calculate fluxes from well defined point sources for example, dung heaps or isolated fields. The approach described in sections 2 and 3 successfully identified sources of above background N2O emissions, as shown by the compost heap and tractor operation in Figure 3, and could be a valuable tool in identifying very quickly unreasonable hotspots of N2O emissions within a region or farm (TV detector van approach). However, if N2O emission rates need to be calculated the more detailed approach of section 1 needs to be applied to the particular N2O hotspot.

Method 2Application and comparison of eddy covariance and the tracer ratio method

to make long- term field scale N2O measurements.

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a. Apply continuous N2O flux measurement by eddy covariance with tunable diode laser spectroscopy (TDL) at the field scale, to determine the seasonal variations of N2O emissions from grassland.

b. Apply continuous N2O flux measurement by tracer ratio technique and gas chromatography to determine the seasonal variations of N2O emissions from heaps of solid manurec. Carry out intercomparison of the eddy covariance method with the tracer ratio technique and static chambers.

2 a. Field scale N2O flux measurements from grassland using eddy covariance Di Marco et al, Water Air & Soil Pollution 2004: Focus, 4, 143-149.

Introduction: The spatial and seasonal influence on agricultural N2O emissions has mostly been studied using small chambers (Clayton et al., 1994, Christensen et al., 1996) with the disadvantage that each chamber can investigate just a small area (<1m2) and a large number of chambers is needed to get a representative estimate of fluxes from field sites with high spatial variability such as grasslands. The micrometeorological technique chosen for the present study provides flux measurements integrated on large scales, depending on the sampling height and avoiding the problem of spatial and temporal variability of N2O emissions.

Materials and Methods: The experiment was carried out over intensively managed grassland at Easter Bush, located 10 km south of Edinburgh, Scotland (55˚52'N, 3˚2'W Grid Ref: NT245641). Flux measurements were made from 6 June 2002 to 20 June 2003 almost continuously. The instruments were situated on the boundary between two grassland fields of approximately 16 ha in total. The fields consist of a clay loam soil mainly covered (>95%) with Lolium perenne, partially grazed and fertilized three times per year with NPK fertilizer. Previous studies of the wind direction frequency distribution at Easter Bush (1998 to 2002) showed that the dominant direction was from the SW sector, providing homogeneous fetch suitable for micrometeorological measurements (Milford et al., 2001).NPK fertilizer was applied to both fields at a rate of 60 kg N ha -1on 7 June 2002 and at 50 kg N ha-1on 10 August 2002. In March 2003 the two fields were fertilized on two different days: one field with NPK at 84 kg N ha-1 on 17 March and the other with NH4NO3 at 51.7 kg N ha-1 on 20 March. In June 2003 NPK fertilizer was applied at a rate of 48 kg N ha-1.The N2O fluxes were determined using the eddy covariance method, which expresses the turbulent vertical flux density F of a trace gas as the covariance between the vertical wind and trace gas density fluctuations as follows: where and are the fluctuations of the 15-minute average vertical wind velocity and trace gas density, respectively. N2O concentrations were measured with a tuneable diode laser absorption spectrometer (TDLAS, Aerodyne Res. Inc. Billerica, Mass. U.S.A.) scanning the single N2O line at 2209.5 cm-1 and wind speed with a sonic anemometer (METEK), fixed on the same mast (2.5 m high) where the TDL inlet was positioned. Under field conditions this spectrometer allowed to measure N 2O concentrations at 10 Hz with a precision of 1%. Fluxes were calculated from 10-Hz measurements integrated over 15-minute intervals. Wind speed and concentration raw data were detrended using a linear fit to remove a possible additional low frequencies component on the signal which is not related to the local flux. No high frequency filtering was used. To avoid distortions caused by obstacles in the fetch, data from outside the good fetch sectors were removed. Only data from 200° to 315º and 25º to 70º were retained.

Results: The measurements between 6 June 2002 and 20 June have generated 3218 hours of N2O concentration measurements suitable for flux calculation by eddy covariance (Fig. 6). A clear response to fertilization was observed the day after the 7 June (mean daily emission of 1.5 mg N2O-N m-2s-1) and 10 August (69 ng N2O-N m-2s-1) N application. Peaks in the emissions were also observed on 16 September (72 ng N2O-N m-2s-1), 24 April (63 ng N2O-N

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m-2s-1) and 15 May (49 ng N2O-N m-2s-1) when the terrain was compacted and animals were moved in adjacent fields. Gaps of data were caused by the wrong wind direction, power cuts and problems with TDL behaviour. Daily fluxes were obtained by averaging the available data.

Figure 6: N2O flux measurements at Easter Bush site. Daily values from June 2002 to June 2003. Vertical bars show

fertilization events.

Rainfall data recorded at Easter Bush were used to investigate the relationship between the wetness of the soil and N2O losses. Rainfall is not always representative of the soil water content because of the nature and the texture of the soil, but will give qualitative information of the soil condition. During the month of June 2002 107 mm of rainfall and a mean air temperature of 16°C were registered at Easter Bush. Immediately after fertilizer application on 7 June, a quick response in N2O losses was observed and peaked at 2.5 mg N2O-N m-2s-1 about 24 hours after fertilizer application (Fig. 7), showing an average daily emission of 1.5 mg N2O-N m-2s-1 on the first day after the fertilization. This pulse was equivalent to 1.3% of the total N fertilizer applied. Daily emissions then decreased and ranged from 91 ng N2O-N m-2s-1 to 244 ng N2O-N m-2s-1 for 10

days after the event. About 20 days after fertilizer application, from 26 June until 30 June,

N 2O losses decreased to a daily average ranging from 7 ng

N 2O-N m-2s-1 to 21 ng N2O-N m-

2s -1. Negative fluxes might be due to advection or storage effects

that are not taken into account in this preliminary analysis.

Figure 7: N2O fluxes at Easter Bush in June 2002.Error bars show the uncertainty in a daily average flux.

From 11 to 17 June N2O emissions showed a clear diurnal pattern (maximum value at noon and minimum during the night), also emphasized by the relationship with the sensible heat flux. The correlation coefficient between sensible heat flux H and N2O flux (R2 = 0.72) on 15 June (Fig. 8) confirmed the air turbulence influence on N2O fluxes, considering that sensible heat flux provides information about the exchange of turbulent energy between surface and

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atmosphere. In August the rainfall measured at Easter Bush during the period of fertilization showed days with high rates of rainfall (from 5 to 20 mm) alternated by dry days. The response of N2O emissions after the fertilizer application was less pronounced than in June. On 12 August a maximum flux of 554 ng N2O-N m-2 s-1 was measured. For the rest of the month fluxes were mostly un-detectable.

Figure 8. Correlation between N2O fluxes and sensible heat flux at Easter Bush on 15 June 2002.

March 2003 was a very dry month with 30 mm of rainfall and temperature about 2ºC above the 5.6ºC normal monthly average. The absence of water in the soil inhibited denitrification and N2O emissions (Dobbie et al., 1999) with a result of very small fluxes for the whole month (daily average ranging between 4 and 27 ng N2O-N m-2 s-1) in spite of the high spring N fertilizer application input (Table 1). Table 1 shows a summary of the soil and meteorological variables fundamental for their contribution to N2O emissions for the months of June, August and March and N2O flux measured. In June 39 mm of rain was evenly distributed during 1 week, whereas in August 78 mm of rain fell in 2 days during the week before fertilization. The differences in rainfall pattern are the most likely reason why the big “pulse” observed in June was not detected in August.

Table 1: Summary of environmental conditions and N2O emissions for the three fertilisation events: June 2002, August 2002, March 2003.

Fertilisationevent

Soil temperature

range

(oC)

Total rainfall during

7 days before fertilization

(mm)

Rate ofN addition

(kg ha-1)

Average daily N2O flux range after

fertilizer application(ng N2O-N m-2 s-1)

June 02 11-18 39 60 7 -1532

August 02 14.5-18.5 78 50 13- 44March 02 2-7 0.8 84 4-27

Discussion: The three fertilization events presented very different environmental conditions, which were reflected in the magnitude of the N2O fluxes measured. Clear diurnal variations of N2O emissions were only observed after N from fertilization in June and they agree with previous studies (Smith et al., 1998). The maximum flux value (15-min average) measured on the 8th of June at 14:30 (GMT) was 3.2 mg N2O-N m-2s-1, which is extraordinarily large. The fact that such large values do not appear in the literature might be explained by the method used

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R2 = 0.72

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sensible heat flux H (W m -2)

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for measuring. The eddy correlation technique allows continuous measurements with fluxes calculated every 15 minutes integrated over an area of 0.01-1 km2, whereas static chambers, which are most widely used to measure N2O emissions, provide usually only one flux measurement per hour and therefore have a larger probability of missing big emission peaks.Although calculation of annual fluxes cannot be easily generalized because of large inter annual differences due to different conditions, they contribute to estimate the potential emission of a particular type of field. Total annual emission from Easter Bush estimated by gap filling is likely to be 5.5 kg N2O-N ha-1y-1 or 2.8% of the fertilizer N input. Interpolation of 15 min average values was used for gap filling June 2002 data and interpolation of 1h average values was adopted for the rest of the data. This result is very similar to the cumulative N 2O flux (4.08 kg N2O-N ha-1y-1 representing 1.36% of the fertilizer N input) measured during the same period with static chambers in Cowpark, a nearby, similarly managed grassland field. (S. K. Jones, personal communication).

2 b. Apply continuous N2O flux measurement by tracer ratio technique and gas chromatography to determine the seasonal variations of N2O emissions from heaps of solid manureSneath et al. 2005. Agriculture, Ecosystems & Environment, Special Issue, in press.

Objectivesa. To measure seasonal variations of N2O emissions from long-term stored poultry muck heaps using the tracer ratio methodb. To compare tracer ratio, cover and chamber methods over a broiler manure heap at SRI from July 2003 for 7 months

Materials and Methods1.1 Tracer ratio: The use of the tracer ratio method to measure GHG emissions from manure involves simulating the GHG source with a tracer gas release, measuring the ratio of GHG and tracer concentrations upwind (Up) and downwind (Dn) of the source and calculating the GHG

emission rate (QGHG)

where: QGHG : GHG emission rate; QSF6 : SF6 release rate; CGHGDn, CGHGUp : Downwind and upwind GHG concentrations; CSF6Dn, CSF6Up : Downwind and upwind SF6 concentrations.

Sulphur hexafluoride (SF6) was continuously released from a cylinder under pressure at a flow rate controlled by the mass flow controller as a tracer gas from the manure heap surface. To simulate the surface area source, SF6 was released through manifold with 12 outlets located on the manure surface. Two sampling points were located near the heap including the upwind sampling point and the downwind sampling point at 1 m above ground level. Air was continuously pumped by means of two diaphragm pumps from both sampling points. Every 30 minutes a sequence was started to sample first one position then the other. These two samples were analysed with a GC with an Electron capture detector.

1.2 Chambers: Four small round chambers were inserted about 10 cm deep into the heap about 1 m from the concrete base. The N2O flux was determined using the static method, by closing the chambers at weekly intervals. The air enclosed was sampled and analysed for N2O by gas chromatography.

Figure 9. The heap of broiler litter with the cover in position.

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1.3 Cover: On three occasions the heap was covered using a polyethylene sheet as a large scale chamber (Fig 9). The N2O concentrations were measured at 15 min. intervals at two points inside the cover using the sampling system. The cover was left on for periods up to 4 hrs.

1.4 Broiler litter: The broiler litter came from one of the buildings of a leading UK producer. The birds had been bedded on pelleted straw at one day old and no more litter added to the building. The litter (28 t) was formed into a heap 13.5 m long, 3m at the base and initially 2m to the apex. It subsequently settled to 1.4m high at the time the cover method measurements took place. Initial dry matter content of the litter was 45% and the Kjeldahl nitrogen content 34.7g/kg.

Results1. Chamber resultsThe Chambers were used on 16 occasions from August 2003 to January 2004; all measurements were taken in the same places. The emission rate varied depending on the measuring position, position 3 and 4 often produced a much higher value than the other positions. Very large differences in emission rates between positions as well as large differences between measurement days characterise these data. The increasing emission rate with approaching winter and increasing rainfall (recorded between July 2003 and January 2004) suggests that the emission rate is positively influenced by the moisture content of the litter surface layer.

Figure 10: Mean emission rates, measured by the chamber method between July 2003 and January 2004.

2. Cover method results1. The cover method was employed on three occasions. An example of the data collected using this method on 21 November 2003 (Fig. 10) shows the concentration increase during the covered period. Emission rates quickly reach a steady state, which suggests that the cover was not influencing the emission rate greatly (Fig. 11). The emission rate measured by the cover method was 91 mg t-1 d-1 on 21 Nov. compared with 16 mg t-1 d-1 measured by the chamber method on the same day (Table 2). Large spatial variability of N2O emissions from the dung heap was observed as indicated by the large standard deviation in Table 2. Both measurement systems calculated N2O fluxes, which were 2 orders of magnitudes larger than fluxes typically recorded from agricultural soils.

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chamber emission measurements

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Figure 10 (left graph): Change in N2O concentration whilst cover was in place on 21 Nov 2003. Figure 11 (right graph); Cumulative N2O emission rate, measured by the cover method, 21 Nov 2003.

3. Tracer ratio resultsThe emission rates measured from the 28 tonne heap of broiler litter are shown in Fig. 12. The data collected had to be carefully selected using a set of rules drawn up to ensure that the data that was used for the calculations were robust. Account was taken of the precision of the GC; the minimum of SF6 to be used was set at 0.2 ppb. Results with very low tracer gas concentrations corresponding to wrong wind direction were eliminated and results with GHG or/and tracer gas concentrations higher than calibration concentrations which corresponded to very low wind velocity were also eliminated. Mean N2O emission rate from the heap from 3 Oct to 12 December was 162 mg t-1 h-1 or 3900 mg t -1 d-1.This is an order of magnitude greater than the rates measuredby the other two methods. Themain restriction on good measurements of emission ratesusing this method is the ability to measure the small rise in N2Oconcentration in the air passingover the broiler litter heap. Thisproblem has been experienced Figure 12: Mean daily emission of N2O, mg t-1h-1, using the tracer ratio method.before when monitoring N2O emissions from dairy cattle manure.

4. Comparison of emission ratesThe emissions rates measured are compared in Table 2. The cover method produced mean emission rates with the lowest standard deviation compared with the chambers or the tracer ratio method. There was an enormous difference between the tracer ratio results and the two cover methods, possibly caused by the inability of the apparatus to measure the small differences in gas concentration or errors in the measure of the SF6 release rate.

Table 2: Summary of mean emission rates measured by the three methodsMethod Mean emission, mg t-1 d-1 StdChambers 2.69 4.47Cover 11.5 2.6

25.6 13.991 29.8

Tracer ratio 3888 6384

Conclusions

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N2O concentration changes whilst covered 21/11/2003

y = 9.807x + 462.28R2 = 0.9406

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When using the chamber method very large differences between sampling positions as well as large differences between measurement days characterise these data. The cover method showed increasing emission rate with approaching winter and increasing rainfall suggests that the emission rate is positively influenced by the moisture content of the litter surface layer. The cover method indicated a higher emission rate than the chamber method by about a factor four. Results of the tracer ratio method measurements show mean daily N2O emission rates from the heap two orders of magnitude greater than the rates measured by the other two methods. The main restriction on robust measurements using the tracer ratio method is the difficulty in measuring the small rise in N2O concentration in the air passing over the broiler litter heap.

2 c. Carry out intercomparison of the eddy covariance method with the tracer ratio technique and static chambers.

This objective was met by the joint experiment between SRI and CEH downwind of the dung heap near Edinburgh, May 2002. Some of data from this experiment have already been described under Method 1, objective a (Fig 1 &2) and objective b. The objective discussed in this section here was altered slightly, because the dung heap provided a strong point source of N2O and analysis of concentration measurements by Gaussian plume theory was more appropriate than by eddy covariance.

MethodsChambers: Seven small round chambers (40cm diameter and 20 cm high) were inserted 10 cm deep into the heap on the summit of the heap. SRI determined the N 2O flux using the static method, by closing the chambers for periods of 5 to 15 min and subsequent analysis, of the air sample collected, by gas chromatography. CEH used the flow-through, dynamic approach, whereby the same chambers were fitted with a small (1/4 inch) inlet hole at the side of the chamber wall in the centre of the chamber lid. The TDL sample line (25 m long) was attached to the outlet opening in the flat aluminium lid and air passed into the TDL at a rate of 3 l min -1. N2O concentrations were measured until chamber concentrations reached equilibrium, usually within 30 minutes of chamber closure.Plume method was used by CEH and is described in section Method 1. a. 1 (Fig 1 &2)Tracer ratio technique was used by SRI and is described in the materials and methods section of Method 2 b. Here SF6 was released from the top of the heap at a height of 3 m and a flowrate of 50 ml min-1 during the same period when plume were measured by TDL. Samples of air were collected into 3 l Tedlar bags over 5 to 10 min periods 15 to 50 m downwind of the SF6 source and were analysed for SF6 and N2O by gas chromatography within 48 hours of collection.

Results The SF6 tracer ratio and Gaussian plume methods provided much smaller emissions rates than the chamber methods (Table 3). Such discrepancy between chamber and micrometeorological methods was also reported from a fertilised grassland field where chambers provided larger N2O fluxes than eddy covariance and flux gradient methods (Smith et al., 1994). The lack of agreement between the plume and chamber methods, but at the same time verification of the validity of the tracer ratio and Gaussian plume approach (Method 1 b), suggests that the static and dynamic chambers in our study overestimated the source strength of the heap. Reasons for this overestimate may be large spatial variability, which can not be accounted for by small chambers and placement of the chambers onto the warmer ridge of the heap compared to the cooler slopes. We conclude that chamber methods are very valuable in assessing the spatial and temporal variability of a dung heap. The overall source strength, however, can be assessed more accurately using large-scale methodologies such as the plume and tracer ratio studies discussed here.

SID 5 (2/05) Page 18 of 27

Table 3 Comparison of the N2O source strength (g N2O-N h-1) of the dung heap calculated by four methodsMethod Average Min Max Number of

observationsStatic chambers 634* 419 1758 4Dynamic chambers 3941* 36 18966 7SF6 tracer ratio method 180 93 482 5GaussianPlume method 66 17 84 8*assume a heap surface area of 600 m2, with low N2O emissions (chambers 1 – 3) on the slopes (400 m2) and high emissions (chambers 4 - 9) on the summit (200 m2).

Method 3

Development of a method to monitor UK agricultural N2O emissions- the MONACO method – (Monitoring N2O concentrations Across the COuntry)

Rational Changes in the atmospheric concentrations of the long-lived greenhouse gas nitrous oxide (N2O) are monitored routinely at relatively few sites distributed around the globe (i.e. Derwent et al, 1998). Such measurements have provided data on the seasonal and inter-annual change and global increase in atmospheric N2O and provided the data for inverse modelling to deduce the original emissions. We have developed a monitoring network across the typical land uses of a single country, Great Britain, to provide information on the spatial and temporal variation of atmospheric N2O and used the data to verify national emission inventories. The objectives of this part of Method 3 are:

a. Develop a method to measure the UK spatial, seasonal and interannual variations of agricultural N2O emissions at local, regional and country scale. b. Apply the method to quantify the UK agricultural N2O source strength, the spatial and

seasonal variability in N2O emissions and the overall UK N2O emission from all sources.

Site description and methodsMANE proposed a network of 33 sites with monthly cumulative measurements for a one year period. The sites were chosen to provide an even distribution of the geographical spread and landuse (urban, agricultural/ natural/ some urbanisation and agricultural) across Britain and contained 2 ‘background’ sites, located in areas of no known large sources of emissions, 15 sites in close vicinity to livestock rearing, predominantly cattle (‘agricultural’), 14 sites in locations of a mixture of urban development and agriculture (‘mixed’) and 2 sites were in the city centres of Edinburgh and London (‘urban’) (Fig. 13). These sites were part of the existing ammonia network, run by CEH. In addition this network benefited from overlapping DEFRA funding of two projects utilising the same methodology developed within MANE: 1) 20 sites in two 20*20 km clusters in the cattle grazed regions of Cumbria and Devon were set up as part of the foot and mouth project in February 2002. 2) In December 2002 a further 11 sites were set up in ex-mining locations across GB (mostly urban), also funded by DEFRA (Fig. 13). In order to provide information on the inter-annual variations of N2O concentrations, 13 sites of the MANE funded network were continued for a second year together with the 11 ex-mining locations in mainly urban regions and the 20 site clusters in Cumbria and Devon.

Figure 13: Nitrous oxide network in the UK. The red dots represent the sites from Devon network; the black dots show Cumbria sites; blue

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0 200 400 600

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ones represent the Ammonia National Network sites and the brown ones are the sites from the ‘Mines’ project around the country.

Cumulative monthly air samples were collected into containers, which were then sent to CEH-Edinburgh for analysis by Tuneable Diode Laser (TDL) spectroscopy. A very simple device was used for sample collection: small cheap air pumps with a low flow rate (<1ml/min) to sample the air continuously for a month period and large metallized plastic bags to collect the gas samples at 1.5m height. The balloons were enclosed in cardboard boxes and were posted to and from the site operators and CEH. Once received at CEH the samples were measured within few days for N2O and also CH4. Concentrations were determined relative to calibration standards (305.7 ppb). Every sample was measured for 30 s with the TDL operating at 1Hz. The sample bags were tested for leakages. Quality tests on a total of 50 air-tight balloons showed that after a one month storage period concentrations varied up to 0.7% (about 2 ppb) in 57% of the cases and by less than 1 % (3 ppb) in about 80% of the bags.

Figure 14: Annual average N2O concentrations measured in GB. The site locations are ordered by land use.

The error bars represent monthly variations.

Results: N2O concentration measurements

Average annual concentrations measured for the first and second year periods at all network sites funded through the MANE project are shown in Fig. 14. The locations are ordered according to the dominant land use. The two ‘background sites’ were not different from the sites dominated by livestock agriculture. Unfortunately the remote site kept for the second year measured large increases in concentration from July 03 onwards. The cause for this increase is unknown, no increase in agricultural activity or contamination by traffic was reported from the site operator, and a link to the unusual weather conditions could not be observed.

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rgh

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Background Mixed sources Agricultural Urban sites

Monthly N2O concentrations measurements show large spatial and temporal variability, the

temporal variability is demonstrated here by 2 sites in locations dominated by livestock rearing at the west coast of GB (North Wyke and Auchencruive), 2 sites in the east of GB (Bush & nature reserve) in rural areas with some influence of traffic; and 2 sites in inner city locations of London and Edinburgh (Fig 15). Due to problems with the TDL, concentrations for June, August and December 2002 were not taken into consideration.

Figure 15: An example of monthly N2O concentration changes at 6 network locations.

The reason for the seasonal variations was investigated at sites for which meteorological data were available. Of the main climatic parameters: wind speed, wind direction, pressure, air temperature and rainfall, the latter two provided the best correlation with monthly changes in N2O concentrations (Fig. 16), for example concentrations measured at the Bush site, which is located in a predominantly agricultural location with few busy roads surrounding, N2O concentrations correlated best with air temperature.

Figure 16: Variations in monthly N2O concentrations related to air temperature at Bush (Midlothian) (left graph) and partially to rainfall at Sutton Bonnington, near Nottingham (right graph).

At a similar site at Sutton Bonnington, N2O concentrations correlated with air temperature changes in September, October and November 2002 and from April to November 2003, but changing rainfall patterns were more important from January to May 2003 (Fig. 16).

In order to estimate a correlation between N2O concentration, temperature and rainfall for the sites for which climatic data were available a multiple regression analysis was performed. Nitrous oxide concentrations at sites dominated by agriculture or agriculture with some urban influence (mixed) correlated with the two meteorological variables much better than the two urban sites, with R2 coefficients ranging from 24% to 81.2% for the agricultural and mixed land uses compared to 1.4 to1.6% for the cities. This confirms the influence of climatic conditions on N2O emissions from agricultural and mixed sources. In the urban locations, were the main source of N2O are emissions from vehicles, especially those fitted with catalytic converters. Consequently the correlation between urban concentrations and the parameters rainfall and temperature, which control the emission rates from soils, was very poor.

Further analysis of these data was carried out by including the measurements funded by the two other projects mentioned above (Fig. 17). 2003 was a very unusual year with extremely dry weather conditions during February, August, October and November and a very warm summer. Due to this spring dryness, N2O concentrations in livestock dominated areas were smaller than in the previous year and did not show the expected fertiliser induced

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North Wyke (Devon) Auchencruive (Ayrshire) Bush (Mid Lothian) Nature reserve (East Anglia)London Edinburgh

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concentration increase. Interestingly, N2O concentrations from the mixed and urban, but not from the livestock dominated agricultural sites, were much larger than in the previous year and varied greatly between months (Fig. 17). A very similar pattern was observed for atmospheric CH4 concentrations. The reason for this increase in both gases is not understood yet, but highlights the problem of inter-annual climatic variations triggering a different behaviour depending on land use.

Figure 17: Average monthly concentrations of N2O (left graph) and CH4 (right graph) for the main landuse categories ‘background’ (blue lines and symbols, 2 sites (s) in 2002 and 1 s in 2003), ‘livestock’ (pink, 56 s in 2002, 45 s in 2003), ‘mixed’ (green, 13 s in 2002 & 9 s in 2003), ‘urban’ (blue) for N2O 2 s in 2002 & 13 s in 2003. For CH4 the 11 urban sites in 2003 in mining areas are shown separately by purple symbols and lines.

Average N2O concentrations for the entire measurement period were mostly smaller from the 56 sites dominated by livestock farming (320.5 ppb N2O) than from the 13 urban locations (329.4 ppb N2O) or the 16 sites in rural areas subjected to some urban influence (mixed category) (328.2 ppb N2O) (Table 4). The concentration measurements at the 2 background sites were not smaller than the concentrations at the livestock dominated sites, unfortunately only 1 background site was maintained for the entire 2 year measurement period (MANE only funded 1 year), with periods of dubious high concentrations.

Table 4: Average annual N2O concentrations (ppb) for each landuse category

Landuse AverageN2O (ppb)

Std. deviation

Minimum Maximum No. of sites

‘Background’ 321.0 1.4 320.0 322.0 1 -2*

‘Livestock’ 320.5 4.5 315.0 342.0 56‘Mixed’ 328.2 8.1 313.0 349.0 16‘Urban’ 329.4 16.5 314.0 364.0 13 * 2 sites in 2002, only 1 site in 2003

The concentration measurements were compared with CEH’s recently created spatially disaggregated inventory of N2O emissions for GB (Skiba et al, in preparation and Skiba et al, 2001). This was achieved by modelling the transport and dispersion of N2O based on the emission inventory, using the Lagrangian atmospheric transport model FRAME (Fine Resolution Atmospheric Multi-species Exchange model (Singles et al, 1998) as described in detail below.

Modelling the transport and dispersion of N2O across the United Kingdom with the FRAME modelIntroduction: The Fine Resolution Atmospheric Multi-species Exchange model (FRAME) is a Lagrangian atmospheric transport model. Initially it was developed to focus on ammonia gas and ammonium aerosol (Singles et al., 1998) but since has changed to a robust multi-species model able to accurately represent the dispersion and deposition of sulphur, heavy metals and oxidised nitrogen as well as reduced nitrogen.

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The model: The FRAME domain covers the British Isles with a 5 km resolution on a grid with dimensions 172 in the west-east direction and 244 in the south-north direction. The model consists of 33 vertical layers with variable depth ranging from 1m in the lowest layer to 200 m in the upper layer. Gaseous emissions of N2O are input in to a column of air and their vertical mixing is calculated using k-theory eddy diffusivity. For N2O, the model simulation was reduced to a simple representation of horizontal advection and vertical dispersion. Dry deposition of N2O gas to the surface and washout by precipitation were assumed to be zero and no gas phase chemical reactions were included. The model includes a diurnal cycle, with the boundary layer height varying as a function of the time of day. During the daytime, the diffusivity parameters are parameterised with the boundary layer mixing height and the geostrophic wind speed to represent a combination of mechanical and convective mixing. During the nighttime, the geostrophic wind-speed and the Pasquill stability class determine the diffusivity parameters. A wind frequency rose is used to weight the trajectories according to their relative directional frequency and a wind speed rose to allocate a suitable wind speed to each trajectory direction. The wind speed rose was generated from the harmonic mean of the directionally dependent wind speeds. Underlying data were available in electronic format from the British Atmospheric Data Centre. The model uses a 1o resolution in the angle between trajectories and a total of 120, 000 trajectories are included in a single simulation. The model code is written in High Performance Fortran and executed on a Beowulf Linux cluster comprising 60 dual processors. The run time for a single simulation is approximately 10 minutes with all processors employed.

A map of the surface concentration of N2O was generated by the FRAME model based on a spatially disaggregated inventory of N2O emissions for each 5 km2, which was created for the NERC GANE programme. The inventory includes the main sources of N2O. Soil emissions were calculated using a multi linear regression equation from the parameters: N input, soil water content and soil temperature (Sozanska et al, 2002). Emissions from industry, transport, rivers, estuaries, atmospheric N deposition and livestock were calculated as advised by DEFRA and the IPCC. It was assumed that all emissions, except the industrial emissions, were released into the lowest vertical layer of FRAME (1 m). In the case of the emissions of N2O from the 10 industrial plants, stack parameters were available for three plants. For the remaining seven point sources, default stack parameters were used for the plume rise calculation in the model (stack height 160 m, exit velocity 16 m s -1, exit temperature 150 oC, stack diameter 5 m). The concentration of N2O imported to the model domain during westerly and northerly air-flow was assumed to be 319 ppb, based upon the measurements of baseline concentrations of radiatively active gases at a remote site at Mace Head in Ireland by Derwent et al. (1998).

Results: The surface N2O concentrations calculated by FRAME are illustrated in Fig.18. The data refers to the enhancement of N2O concentrations above the background level of 319 ppb. The spatial distribution of concentrations displays a similar pattern to that for the emissions but with a lesser fine scale variability due to the advection of emitted concentrations between neighbouring grid cells. The concentrations were highest in central England, East Anglia, Devon and NW England. Concentrations are lowest in Scotland, coastal areas and the hill areas of Wales and the Northern Pennines. The Northern Ireland data were not considered here, as the underlying emission map does not include it.

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Figure 18: Nitrous oxide surface concentrations above a background of 319 ppb modelled by FRAME. The scale of enhancement spreads from 0 (pale blue) to 3.84 ppb (red).

Average annual N2O concentrations measured by the 87 network sites ranged from 320 to 364 ppb, which is a difference of 44 ppb. This spread in concentrations was not simulated by FRAME, the range of modelled concentrations was only 319 to 323 ppb. Possible reasons for this discrepancy are that 1) some sites measure high concentrations from nearby sources, 2) the point sources are not accurately represented in the emissions inventory and 3) most likely that the strong local variability in emissions is currently not resolved by the coarse grid size of 5 km2 employed in FRAME.

Average N2O concentration calculated by FRAME for all 87 network sites was 321.3 ± 0.8 ppb, which is lower than the average value of 323.3 ± 8.8 ppb measured by the air monitoring networks. This may suggest that the imported concentration of 319 ppb used in FRAME was an underestimate and can be explained by the fact that the background concentration measurements were made a coastal site in western Ireland whilst it may be expected that air imported from Europe in south-easterly trajectories would contain somewhat enhanced concentrations at the south-eastern boundary of the FRAME domain. For the measurement locations in remote locations and in livestock dominated areas the agreement between measured and modelled concentrations is acceptable (Figure 19a). For the 56 ‘livestock’ locations FRAME predicted an average annual concentration of 321.3 ± 0.62 ppb, the measured data provided an annual concentration of 320.5 ± 4.5 ppb. However the agreement for the 29 sites with urban influence (mixed and urban categorise) was poorer (Figure 19b). FRAME modelled concentrations were 321.5 ± 0.81 ppb compared to average annual measured concentrations of 328.7 ± 12.3 ppb. In particular for areas dominated by urban influences our knowledge of the magnitude and dispersion of the sources and our ability to model these needs to be improved.

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Figure 19: Comparison of Frame modelled N2O concentrations with average annual concentrations measured by the N2O networks. a) in areas dominated by livestock and remote ‘background’ areas, b) areas with urban influences (land use categories ‘mixed’ and ‘urban’). The solid line represents the ideal 1:1 ratio between predicted and measured concentrations.

Figure 20: Total annual nitrous oxide emissions from all major sources in Great Britain at a resolution of 5 km. The sources included are: N2O emissions from agriculture (N fertiliser and manure management), atmospheric N deposition, rivers & estuaries, industries, transport

For the agricultural regions of Britain dominated by livestock management N2O concentrations predicted from our 5*5 km2 spatial N2O emission inventory were in reasonable agreement with the measured concentrations and thereby validate CEH’s estimate of agricultural N2O emission (Fig 20). Our estimate uses a multi linear regression model for soil emissions and

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suggests that agriculture contributes to 73% (121 kt N2O y-1) of the total GB N2O emissions (165 kt N2O y-1). This estimate is 36% larger than the National N2O inventory calculated using the standard IPPC methodology.

ReferencesChristensen, S., Ambus P., Arah J. R. M., Clayton H., Galle B., Griffith D. W. T.,. Hargreaves K. J, Klemedtsson L., Lind A. M., Maag M., Scott A., Skiba U., Smith K. A., Welling M. & Wienhold F. G., (1996) Atmos. Environ. 30, 4183-4190.

Clayton, H., Arah J. & Smith K. A., (1994) Journal of Geophysical Research 99, 16,599-516,607.

Derwent R.G., Simmonds P.G., O’Doherty S., Ciais P. & Ryall D.B., (1998) Atmos.Environ, 32, 3703-3715.

Dobbie, K. E., McTaggart I. P. & Smith K. A., (1999) Journal of Geophysical Research 104, 26,891-826,899.

Hensen, A. & Scharff, H., (2001) Water Air & Soil Pollution 1, 455 – 464.

IPCC, (1997) Stabilization of atmospheric greenhouse gases: physical, biological and socio-economic implications.

Milford C., Theobald M. R., Nemitz E. & Sutton M., (2001) Water, Air and Soil Pollution 1, 167-176.

Singles, R., Sutton M.A. & Weston K.J., (1998) Atmos. Environ., 32, 393-399.

Skiba U., Sozanska M., Metcalfe S. & Fowler D., (2001) Water Air & Soil Pollution 1, 109 – 118.

Smith, K. A., Thomson P. E., Clayton H., McTaggart I. P. & Conen F. (1998),Atmos.Environ, 32, 3301-3309.

References to published material9. This section should be used to record links (hypertext links where possible) or references to other

published material generated by, or relating to this project.

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Publications generated from this work to date:

Skiba, U., Di Marco, C., Hargreaves, K., Sneath, R., McCartney, L. 2005. Nitrous oxide emissions from a dung heap measured by chambers and plume methods. Agriculture, Ecosystems & Environment, Special Issue, in press.

Di Marco C., Skiba U., Weston K. and Hargreaves, K. 2004, Field scale N2O flux measurements from grassland using eddy covariance, Water, Air & Soil Pollution: Focus, 4, 143-149.

Sneath, R.W., Beline, F., Hilhorst, M.A., 2004. Monitoring GHG from manure stores on organic and conventional dairy farms. Agriculture, Ecosystems & Environment, Special Issue, in press.

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