Nitrous Oxide From Grass Fed Beef Cows

• Journal Listing
• Elsevier Sponsored Documents
• PMC6024564

Sci Full Environ. 2018 Sep 1; 635: 607–617.

The contribution of cattle urine and dung to nitrous oxide emissions: Quantification of state specific emission factors and implications for national inventories

D.R. Chadwick,^{a, ⁎} Fifty.M. Cardenas,^b M.S. Dhanoa,^b North. Donovan,^b T. Misselbrook,^b J.R. Williams,^c R.E. Thorman,^c K.L. McGeough,^d C.J. Watson,^d M. Bong,^e S.G. Anthony,^f and R.M. Rees^e

D.R. Chadwick

^aSchool of Environment, Natural Resource and Geography, Bangor University, Bangor LL57 2UW, UK

L.Thou. Cardenas

^bRothamsted Enquiry, North Wyke, Devon EX20 2SB, U.k.

M.South. Dhanoa

^bRothamsted Research, North Wyke, Devon EX20 2SB, U.k.

N. Donovan

^bRothamsted Research, North Wyke, Devon EX20 2SB, Uk

T. Misselbrook

^bRothamsted Inquiry, North Wyke, Devon EX20 2SB, Uk

J.R. Williams

^cADAS Boxworth, Battlegate Rd., Cambridge CB23 4NN, UK

R.E. Thorman

^cADAS Boxworth, Battlegate Rd., Cambridge CB23 4NN, UK

K.Fifty. McGeough

^dAgri-Food and Biosciences Found, 18a, Newforge Lane, BT9 5PX, Belfast, U.k.

C.J. Watson

^dAgri-Nutrient and Biosciences Establish, 18a, Newforge Lane, BT9 5PX, Belfast, United kingdom of great britain and northern ireland

1000. Bell

^eastwardScotland's Rural Higher (SRUC), West Mains Road, Edinburgh EH9 3JG, UK

S.G. Anthony

^fADAS Wolverhampton, Titan 1 offices, Coxwell Avenue, Wolverhampton Science Park, Wolverhampton WV10 9RT, UK

R.M. Rees

^eScotland's Rural Higher (SRUC), West Mains Road, Edinburgh EH9 3JG, Great britain

Received 2018 Mar 12; Revised 2018 Apr 10; Accepted 2018 Apr x.

Abstract

Urine patches and dung pats from grazing livestock create hotspots for production and emission of the greenhouse gas, nitrous oxide (N₂O), and represent a big proportion of total Northward₂O emissions in many national agricultural greenhouse gas inventories. As such, at that place is much involvement in developing land specific N₂O emission factors (EFs) for excretal nitrogen (EF_iii, pasture, range and paddock) deposited during gazing. The aims of this study were to generate separate North₂O emissions information for cattle derived urine and dung, to provide an evidence base for the generation of a country specific EF for the UK from this nitrogen source. The experiments were also designed to determine the effects of site and timing of application on emissions, and the efficacy of the nitrification inhibitor, dicyandiamide (DCD) on Due north_twoO losses. This co-ordinated prepare of fifteen plot-calibration, twelvemonth-long field experiments using static chambers was conducted at five grassland sites, typical of the soil and climatic zones of grazed grassland in the UK. We show that the average urine and dung N_twoO EFs were 0.69% and 0.19%, respectively, resulting in a combined excretal N₂O EF (EF₃), of 0.49%, which is <25% of the IPCC default EF_iii for excretal returns from grazing cattle. Regression assay suggests that urine N₂O EFs were controlled more past composition than was the case for dung, whilst dung N₂O EFs were more related to soil and environmental factors. The urine N₂O EF was significantly greater from the site in SW England, and significantly greater from the early grazing season urine application than afterward applications. Dycandiamide reduced the N₂O EF from urine patches by an boilerplate of 46%. The significantly lower excretal EF_iii than the IPCC default has implications for the Britain'due south national inventory and for subsequent carbon footprinting of UK ruminant livestock products.

Keywords: Grassland, Greenhouse gas, Nitrous oxide, Cattle, Urine patch, Dung pat, Nitrification inhibitor, Dicyandiamide, Inventory

Graphical abstract

one. Introduction

Grazed grasslands support a significant proportion of sheep and cattle production throughout Europe and other parts of the Globe, converting human-inedible plant biomass into human edible animal products but with generally low nitrogen (N) use efficiencies. The ruminant beast converts much of the organic Northward in plant biomass into highly reactive and bioavailable N (Nr), peculiarly as excreted in the urine. It is thought that iii.08 Mt. of N is deposited by grazing livestock in Europe, and this value is thought to exist every bit much as ca. 0.61 Mt. N in the United kingdom of great britain and northern ireland (UNFCCC, 2016). It is well documented that urine additions to grassland soils result in significant quantities of North₂O production and emission, mainly due to the soil microbial processes of nitrification and denitrification (Selbie et al., 2015), following the addition of readily available North and carbon (C), and the effects of significantly increased percentage of water-filled pore space (WFPS) inside the urine patch (van der Weerden et al., 2017).

Deposition of North in urine patches tin stand for an equivalent application rate of 200–2000 kg Due north ha⁻ⁱ (Selbie et al., 2015), depending on the poly peptide content of the sward, livestock type, age and phase of lactation. A meta-analysis past Selbie et al. (2015) indicates average urine patch N loading rates of 613 kg N ha⁻ⁱ and 345 kg North ha⁻¹ for dairy cows and beefiness cattle, respectively. Clearly, North loading rates in urine patches are in excess of optimal institute utilize efficiency, increasing the risk of excess Due north being lost to the environment via nitrate (NO₃ ⁻) leaching (de Klein and Ledgard, 2001; Di and Cameron, 2007), ammonia (NH₃) volatilization (Lockyer and Whitehead, 1990; Laubach et al., 2013; Burchill et al., 2017), Due north₂O (Di and Cameron, 2008; Krol et al., 2016; Van der Weerden et al., 2017; Minet et al., 2018) and Due north_two (Clough et al., 1998) emissions. All of these N loss pathways (except North₂O losses) typically represent a significant agronomic loss, and all simply North₂ loss have detrimental furnishings on the surround.

At these high rates of N loading, the N_twoO emission is likely to be disproportionally greater than emissions from N sources applied at lower N loading rates, eastward.thousand. typical fertiliser Northward applications at agronomic rates. A curvilinear response of Due north_twoO emissions to N loading has been shown previously, e.g. Cardenas et al. (2010) for fertiliser Due north (NH₄NO₃) applications between 0 and 375 kg Northward ha⁻¹ to grazed swards. Bell et al. (2015) likewise showed a non-linear response of Due north₂O fluxes to NH_ivNO_iii applications (0–400 kg N ha⁻ⁱ) to cut grass. More than specifically for urine applications, de Klein et al. (2014) demonstrated greater North₂O emissions, every bit a percent of N practical, i.e. emission factors (EFs), (0.34%) from urine patches receiving an N loading of 1200 kg ha⁻¹ compared to urine patches with a lower Northward loading (0.10% from a loading of 200 kg ha⁻¹) on a freely draining soil, although a linear relationship between North_iiO EFs and urine N loading was observed on a poorly tuckered soil. van Groenigen et al. (2005) found no result of N loading in urine patches on the N_twoO EF.

For excretion during cattle grazing, the default IPCC N₂O EF (pasture, range and paddock) is 2% for (combined excretal urine + dung EF) (cf to 1% for fertiliser N), whilst the N₂O EF for sheep excretal Due north during grazing is simply 1% (IPCC, 2006). UNFCCC submissions for 2015 from unlike countries (using IPCC Tier 1/ii, 2006 Guidelines) show that direct North_iiO emissions post-obit N deposited to soil by grazing livestock represents from <5% (e.g. in Nihon) to >65% (in New Zealand) of total national direct soil N₂O emissions (Fig. one), with greater contributions coming from countries where livestock graze for meaning periods of the year (UNFCCC, 2016). As this source of direct Northward_twoO emissions is significant to many national agronomical greenhouse gas inventories, there is increasing interest in developing country specific EFs that better reverberate national soils and climatic conditions (e.k. Krol et al., 2016 for Ireland).

Almanac (year 2014) agricultural Northward_iiO emissions and direct N₂O emissions from excreta deposited by grazing livestock (pasture, range and paddock), expressed as a percent of the total agricultural N₂O emission, from unlike nations (source: UNFCCC, 2016).

Nearly Nr excreted during grazing is in the urine, which is generally comprised of urea that requires hydrolysis to gratuitous NH₄ ⁺ (Selbie et al., 2015). In dung, near N is in the organic course, and requires mineralisation over a longer time period to provide a pool of NH_four ⁺ for nitrification and NO₃ ⁻ for denitrification. The split betwixt urine and dung for total excretal N will depend on dietary protein intake compared with requirement past the animal (every bit protein intake increases above requirement proportionally more Northward will be excreted equally urine (Broderick, 2003; Reed et al., 2015), and partially on the digestibility of the protein in the nutrition (with a higher proportion of less digestible protein being excreted as faecal N). The UK GHG and ammonia emission inventories to date have causeless threescore% of total Due north excretion by cattle to be every bit urine and 40% equally dung (Webb and Misselbrook, 2004), in common with other Western European countries (Reidy et al., 2008). Disaggregating emissions to urine and dung offers an improved understanding of the sources of Northward_iiO from grazed pastures, and hence how they could exist mitigated.

Since direct N₂O emissions from grazing livestock represent such a large term in national agricultural greenhouse gas inventories, there has been pregnant interest in understanding factors that contribute to North₂O production and emission from this source, e.g. soil type (Clough et al., 1998), urine composition (Kool et al., 2006; Gardiner et al., 2016), weather weather (Krol et al., 2016), and in exploring strategies to reduce emissions. For example, Monaghan and de Klein (2014) have suggested restricting the duration of fall and wintertime grazing to reduce higher North_twoO fluxes associated with urine deposition to moisture soils (Qui et al., 2010; Krol et al., 2016). Other studies take explored how manipulating the natural urine limerick, due east.m. hippuric acid content, can reduce N_twoO production from the urine patch (Clough et al., 2009), and there has been much interest in the use of constructed nitrification inhibitors to reduce both NO₃ ⁻ leaching and N₂O emissions from urine patches (Hatch et al., 2005; Di and Cameron, 2012; Barneze et al., 2015). New Zealand and Irish gaelic research groups have taken this a stride farther, in exploring how the nitrification inhibitor dycandiamide (DCD) can be delivered to urine patches to reduce Due north_twoO emissions, e.g. through boluses (Ledgard et al., 2008), in drinking h2o (Welten et al., 2014), and in feed (Luo et al., 2015; Minet et al., 2016, Minet et al., 2018). Even so, recent publicity and research has demonstrated that there are potential unintended consequences of using nitrification inhibitors, such as contagion of milk products, e.chiliad. via root or foliar uptake (Marsden et al., 2015; Pal et al., 2016) and increased ammonia emissions (Lam et al., 2017), then researchers are exploring new inhibitor products, including biological nitrification inhibitory compounds targeted at ruminant production (Gardiner et al., 2016; Balvert et al., 2017; Luo et al., 2018) that may be deemed more acceptable to the public in the futurity.

The Uk greenhouse gas R&D community undertook a big number of field trials to quantify North₂O EFs from a range of different N sources (viz, different fertiliser N forms, different manure types, and urine and dung deposited by grazing livestock (Chadwick et al., 2011), as office of a larger plan to improve the reporting tool for the national inventory of agricultural greenhouse gas emissions that amend represents the soils, climate and N direction in the Britain. In this newspaper, we summarise the results of the first co-ordinated set of plot-based experiments aimed at generating new North₂O emissions data for disaggregated urine and dung deposition to soil, from which country specific Northward_iiO EFs tin can be derived that are relevant to UK soils and climate. Some of the individual site experimental results can exist found in Bong et al. (2015) and Cardenas et al. (2016). In the experiments, we tested whether season of urine and dung deposition (early on grazing, mid grazing, later grazing period) influenced the North₂O EF. Nosotros as well tested the efficacy of the nitrification inhibitor, dicyandiamide (DCD), to reduce N_twoO emissions. An additional reference treatment was included in each experiment, a standardised artificial (synthetic, produced in the laboratory) urine treatment, with the aim of using the information from this treatment to help disentangle the effects of urine composition from soil and climate furnishings on North₂O EFs.

The specific aims of this study were to: i) make up one's mind split up directly N_iiO EFs for cattle urine and dung, 2) determine if flavour of urine and dung degradation afflicted the direct Due north_twoO emission, iii) assess the effects of site on direct N₂O emissions from urine, iv) evaluate the efficacy of the nitrification inhibitor, DCD, to reduce directly North_iiO emissions from urine, and v) assess the influence of using the combined experimentally derived urine and dung Northward_twoO EF on national N₂O emissions.

2. Materials and methods

two.1. Site selection

Five experimental sites were selected to cover the range of typical grassland soils and climate throughout the United kingdom of great britain and northern ireland, with 2 sites in England, one in Scotland, one in Wales and one in Northern Ireland (see locations in Fig. two). Descriptions of the sites are shown in Table 1. There take been few previous studies in the UK where N_iiO EFs have been quantified from urine and dung deposition that are IPCC compliant (IPCC, 2000, IPCC, 2006) (i.eastward. where emission measurements were too made from control plots, and where measurements lasted for upward to 365 days), that these sites needed to provide an advisable range of soil texture and climate. All the same, some practicality was also considered in site selection; location could non be excessively far from a inquiry base to ensure timely measurements, since >xxx measurement occasions were needed during each 12-month experimental period. Four measurement teams, from different Britain organisations, ADAS, AFBI, Rothamsted Research - N Wyke and SRUC, conducted the xv experiments, following an agreed joint experimental protocol to ensure aspects of the urine and dung management, sleeping accommodation deployment, and coincident measurements were made in a similar style.

Site location, climate average (1981 to 2010) rainfall and temperature, and distribution of dominant soil types.

Tabular array one

Site and soil characteristics. Soil parameters for the 0–x cm layer.

Site	Country	Altitude (chiliad)	thirty yr boilerplate annual rainfall (mm)	xxx twelvemonth average annual air temperature (°C)	Clay content (%)	Soil pH	Organic matter content (%)	Bulk density (1000 cm−iii)
Crichton	Scotland	l	1140	ix.1	13	5.6	3.05	1.07
Drayton	England	47	628	10.3	59	7.6	4.84	0.90
Hillsborough	Northern Ireland	128	908	ix.0	23	6.0	9.82	0.ninety
North Wyke	England	185	1042	x.0	37	v.7	v.forty	0.62
Pwllpeiran	Wales	213	1570	10.0	29	5.5	5.40	0.92

Experiments were conducted on established grasslands where the dominant pasture plant was Lolium perenne, which is typical of UK livestock systems (Fig. 2). Each experiment comprised iii replicate blocks with five treatments, so a total of 15 plots were sampled on every occasion. There were 5 urine patches or 5 dung pats per plot (to account for variability in soil weather) with one bedchamber per patch/pat, hence 45 chambers per experiment. There were also control plots that received no treatment awarding. Applications were made in the spring, summer and autumn (to separate plots), to simulate excretal degradation in early-, mid- and late- grazing season. Livestock were excluded from grazing the experimental areas at least six months prior to the first of any experiment. This minimised whatever straight effect of previous deposition of excreta on N_twoO emissions.

2.2. Urine and dung provision

The experimental design resulted in the need for ca. 200 l of fresh cattle urine and ca. 300 kg dung for each experiment. Urine and dung were collected from the institutions summarised in Table 2 inside seven days of an experiment starting, and stored in sealed containers (un-acidified) at <four °C. Table 2 summarises the origin of the urine and dung used in each experiment.

Table 2

Sources of urine and dung for the experiments.

	Cattle type	Age and approx. live weight	Diet
Crichton	Lactating dairy cows	iii–7 years erstwhile (ca 600 kg)	Grass silage + concentrates (half-dozen.5 kg DM caput−1 day−1)
Drayton	Lactating dairy cows	6 years old (ca. 600 kg)	Concentrate blend, hay, straw, grass silage, maize silage
Hillsborough	Lactating dairy cows	3–5 years quondam (ca. 600 kg)	Grass silage + concentrates (4 kg DM head−1 day−1)
Due north Wyke	Lactating dairy cows	six years onetime (ca. 600 kg)	Concentrate blend, hay, straw, grass silage, maize silage
Pwllpeiran	Lactating dairy cows	6 years quondam (ca. 600 kg)	Concentrate blend, hay, straw, grass silage, maize silage

2.3. Treatments

Urine and dung were removed from common cold storage at least 12 h earlier application to the soil, to allow them to reach ambient temperature prior to application to the soil. Urine and dung were applied at typical N loading rates and volumes. The volumetric loading rate was based on a typical one.eight fifty per urination event (Misselbrook et al., 2016). Since the N content of the collected urine varied between feeding trials, the N loading rate varied between an equivalent rate of 340 and 570 kg ha⁻¹, with an average loading rate of 455 kg Due north ha⁻¹ (see Table 4a). Dung was applied at an equivalent charge per unit of 20 kg m⁻ⁱⁱ, representing typical deposition by grazing cattle (Sugimoto and Brawl, 1989), with an average loading charge per unit of 835 kg N ha⁻ⁱ (range 625–1020 kg Due north ha⁻¹; Tabular array 4b). Since urine limerick could not be controlled between experiments, a standard bogus urine treatment was included at each site as a reference treatment. This was to let the effects of soil and climate to exist determined. The artificial urine recipe of Kool et al. (2006) was used in all experiments.

Table 4a

Average urine composition, and North and C loading rates for each experiment.

For urine + DCD treatments, an additional half dozen.5 kg N ha⁻¹ was supplied in the inhibitor. DM = dry matter.

Archived data sources: Bell et al. (2017); Cardenas et al. (2017); McGeough et al. (2017); Thorman et al., 2017a, Thorman et al., 2017b.

		Urine							Artificial urine
Site	Grazing flavor menses	Total N loading (kg ha−1)	pH	DM (%)	Total North (g fifty−1)	Urea-N (mg fifty−i)	NH4 +-Due north (mg l−1)	NOthree −-N (mg l−1)	Total N loading (kg ha−1)	pH	DM (%)	Total Due north (thousand l−ane)	Urea-Due north (mg 50−1)	NHiv +-North (mg l−ane)	NO3 −-N (mg l−1)
Crichton	Early	480	–	4.9	ix.60	6332	120	–	180	–	ane.4	3.threescore	1318	–	–
	Mid	420	–	four.6	8.forty	8127	240	–	425	–	three.five	8.50	9264	–	–
	Late	435	–	4.9	eight.lxx	6231	100	–	425	–	iii.5	8.fifty	9264	–	–
Drayton	Early	540	seven.5	five.five	10.eighty	x,780	825	0.five	501	vii.i	4.half-dozen	ten.01	9820	25	0.5
	Mid	454	ix.0	4.5	9.07	8540	4870	1.five	495	seven.3	3.ix	ix.91	8340	39	0.0
	Late	471	8.ane	5.ii	9.43	8480	315	0.0	495	7.one	4.7	nine.90	10,040	25	0.0
Hillsborough	Early on	432	9.0	5.5	8.64	2900	6917	0.0	510	7.seven	4.vi	ten.20	7335	100	115.0
	Mid	338	eight.9	v.3	half dozen.75	375	5862	27.0	502	7.6	five.0	10.04	8035	55	126.0
	Tardily	354	9.0	4.ii	seven.07	767	6216	41.0	504	8.ii	4.5	x.08	8048	88	163.0
Northward Wyke	Early	405	8.iii	5.three	8.10	6521	554	0.0	440	8.2	4.3	8.80	7079	18	0.1
	Mid	429	7.3	4.8	8.57	6284	1230	ane.0	481	7.v	4.two	9.61	6833	<50	0.4
	Late	435	9.2	iv.v	8.70	7382	2020	ii.v	423	7.4	3.4	8.45	7774	<l	0.eight
Pwllpeiran	Early	565	9.3	five.6	11.xxx	10,100	2743	0.3	495	9.3	4.4	nine.91	9620	315	0.3
	Mid	568	seven.viii	5.five	eleven.37	6840	822	0.3	498	7.4	3.9	9.96	7840	25	0.2
	Late	505	seven.8	four.7	ten.10	8820	115	0.3	508	vii.5	four.ane	10.15	ten,040	25	0.0

Table 4b

Average dung composition, and N and C loading rates for each experiment.

DM = dry matter.

Archived data sources: Bell et al. (2017); Cardenas et al. (2017); McGeough et al. (2017); Thorman et al., 2017a, Thorman et al., 2017b.

	Grazing season menstruation	Full N loading (kg ha−1)	pH	DM (%)	Total N (k kg−ane DM)	NH4 +-N (mg kg−ane DM)	NO3 −-N (mg kg−one DM)
Crichton	Early	1020	–	12.nine	5.10	410	0.0
	Mid	680	–	eleven.5	3.xl	260	0.0
	Late	720	–	10.vi	3.60	230	0.0
Drayton	Early	840	7.6	18.9	22.2	5020	24.5
	Mid	736	7.6	36.2	ten.two	3680	6.nine
	Late	802	seven.8	27.0	xiv.8	4443	0.0
Hillsborough	Early	980	6.nine	14.5	iv.ninety	500	0.0
	Mid	976	7.iii	fourteen.3	4.90	669	0.0
	Late	1008	7.7	14.3	5.00	683	0.0
North Wyke	Early on	911	7.0	14.v	31.iv	3035	0.1
	Mid	625	7.iv	21.one	48.0	4310	21.half-dozen
	Late	771	7.five	twenty.5	18.8	2940	20.8
Pwllpeiran	Early	769	seven.v	24.five	15.7	5095	25.ii
	Mid	823	7.3	23.3	17.vii	6497	7.9
	Late	866	7.5	24.1	eighteen.0	5833	3.5

A urine treatment containing DCD was added, with DCD practical at a rate of 10 kg ha^−one equivalent (supplying 6.five kg N ha⁻¹ equivalent), and was mixed with urine (only) merely before application, to maximise initial co-location of DCD and NH_iv ⁺ in the soil contour. This approach too simulated the event of delivering DCD via boluses (Ledgard et al., 2008), feed (Luo et al., 2015; Minet et al., 2016, Minet et al., 2018) and via water troughs (Welten et al., 2014). The post-obit treatments were established:

• •

  Urine (target 500 kg Northward ha⁻¹)

• •

  Urine + DCD (target 500 kg N ha⁻¹ + 6.v kg N ha⁻ⁱ in DCD)

• •

  Artificial urine (500 kg Northward ha^−one; Kool et al., 2006 recipe)

• •

  Dung (target 800 kg Northward ha⁻¹)

• •

  Control (no additions)

Five chambers were ready up for each treatment plot, and 3 replicate plots per treatment were arranged in three blocks. Tabular array 4a, Table 4b shows application rates for urine and dung at each site.

2.4. Handling applications

Urine treatments were practical to an surface area of 0.half dozen k × 0.half-dozen thousand within a frame to facilitate infiltration (rather than runoff) using a watering can. After application, static chambers were inserted centrally into this expanse. Dung pats were spread to cover the unabridged area within the sleeping room. Nosotros recognise that urine and dung patches are not normally this large, and take "edges", but this method of application was deemed the most appropriate to simulate the urine patch and dung pat. It is possible that by applying the N source across the whole area of the chamber that North_twoO production and emission may have been affected, but there is no evidence to suggest that this would result in either an under- or over-estimate of the truthful emission (Marsden et al., 2016). In addition to the urine and dung patches that were established for the N_twoO bedchamber measurements, larger areas of grassland (ii one thousand × 2 m) on each plot (i.due east. three replicates per treatment) were treated with either urine or dung at the same rate, allowing multiple soil sampling occasions for soil NO_iii ⁻, soil NH₄ ⁺ and soil moisture.

2.5. Nitrous oxide measurements

We used the non-steady state static bedchamber approach to mensurate Northward₂O fluxes (Cardenas et al., 2016). The shape and size of the chambers were 0.4 m × 0.4 thou × 0.25 m (high) for the ADAS, N Wyke and AFBI experiments, and 0.4 m diameter × 0.3 k (high) for the SRUC experiments, with private chamber areas of 0.16 and 0.xiii m², respectively. Chambers were opaque. Chamber headspace sampling followed the protocol detailed in Chadwick et al. (2014), whereby chambers were airtight for a period of 40 min and a headspace sample taken at this fourth dimension (T₄₀). Ten ambient air samples (5 at the start and five at the end of the chamber closure period) were used to provide the T₀ concentration. Gas samples were placed in pre-evacuated 20 ml vials and transported back to individual laboratories for assay past gas chromatography. Five chambers were assigned randomly per plot; these generated one mean flux per plot. The headspace sampling assumed a linear increment in headspace N₂O concentration (as evidenced by previous research; Chadwick et al., 2014). This linear response was checked on each sampling occasion by measuring the headspace concentration at 10 min intervals up to 60 min subsequently closure, from i bedchamber per block.

Sampling frequency was 4–five times in the first week subsequently treatment application, 4–5 times in the 2nd week, two times per week for the adjacent two weeks, and so once per week for ane month. Sampling frequency was then reduced further, eventually to in one case per calendar month until the finish of the experiment (12 months), resulting in ca. 30 samples over the 12-month flow following application in order to comply with IPCC recommendations (IPCC, 1996).

two.6. Other measurements

2.6.1. Dung and urine composition

Dung and urine sub-samples were taken on the 24-hour interval of application and characterised by measuring pH (in H₂O), dry matter (DM), total N (by Kjeldahl) and total organic carbon content, either using a modified Walkley-Blackness approach, or analysis by a TOC analyser (uv persulphate oxidation). The readily available N content was as well determined, i.e. ammonium N (NH₄ ⁺-Northward) and nitrate Due north (NO₃ ⁻-Northward). In addition, two xxx ml sub-samples of urine were taken from each block and preserved by diluting 1:3 with HPLC grade deionised water. The showtime sample was acidified by adding i M H₂SO_four to reduce the pH to three (using a pH meter). To the 2d sample, 100 μl chloroform was added. Both sub-samples were stored at −xx °C before assay for urea, hippuric acrid, allantoin, uric acid and creatinine, by HPLC (using methods described in Kool et al., 2006).

two.6.2. Soil mineral Northward and moisture decision

Soil NH₄ ⁺-N and NO₃ ⁻-N: Soil samples (0–10 cm) were taken from the dedicated sampling areas of each plot on 10–12 occasions during the 12-month experiment. Fresh soil was passed through a 5 mm sieve earlier extracting with 2 M KCl and filtering. Filtrates were frozen prior to analysis for NH₄ ⁺-N and NO₃ ⁻-Northward concentrations past colorimetric determination (Singh et al., 2011) using Skalar segmented flow analysers.

Soil moisture content: sub-samples of the sieved soil were weighed (fresh weight) before oven drying at 105 °C overnight, and then reweighed. Soil moisture content was converted to %WFPS using the bulk density of the site (run into below) and a particle size density of 2.65 chiliad cm^three.

2.half dozen.3. Majority density

Three representative bulk density measurements were fabricated per site, one per block (walking and sampling a 'W' route across each block), at the start of the experiment, using 100 cmⁱⁱⁱ majority density rings, and drying at 105 °C overnight.

ii.6.four. Weather data

Daily rainfall and hourly air and soil (0–5 cm) temperature were recorded on site, or daily data used from a nearby weather station (within 1 km) (Table 3).

Tabular array 3

Weather and soil data for the different urine and dung applications.

Archived information sources: Bell et al. (2017); Cardenas et al. (2017); McGeough et al. (2017); Thorman et al., 2017a, Thorman et al., 2017b.

			Whole measurement period		Initial 30 d after awarding			Twenty-four hour period of application
Site	Grazing season period	Measurement period	Total rainfall (mm)	Average temperature (°C)	Total rainfall (mm)	Average temperature (°C)	Boilerplate WFPS (%)	Daily rainfall (mm)	Average daily temperature (°C)	WFPS (%)
Crichton	Early	03/04/12–18/03/13	1325	8.6	60	7.5	51.9	0.i	5.3	41.4
	Mid	27/06/12–10/06/xiii	1262	viii.7	125	14.7	58.3	2.3	12.ix	54.8
	Late	08/10/12–25/09/13	1142	nine.1	137	7.half-dozen	69.8	0.0	8.4	64.vi
Drayton	Early	02/05/13–17/04/fourteen	726	ten.7	78	10.nine	twoscore.1	0.0	10.0	43.6
	Mid	15/08/xiii–29/07/fourteen	769	9.4	l	15.eight	31.0	1.4	20.5	27.5
	Belatedly	17/10/13–14/10/14	787	8.0	123	ix.0	45.2	0.0	12.5	42.five
Hillsborough	Early on	two/04/12–ane/04/thirteen	1191	8.0	77	vi.3	84.1	i.4	8.3	88.5
	Mid	25/06/12–24/06/13	1110	8.two	102	xiv.0	89.3	0.0	12.1	83.ane
	Tardily	17/09/12–16/09/13	1080	viii.2	135	8.8	89.9	0.8	10.9	89.7
North Wyke	Early	fifteen/05/12–09/05/13	1405	9.6	143	thirteen.ix	57.5	0.vi	7.4	58.three
	Mid	03/07/12–11/06/thirteen	1246	9.4	103	13.6	62.0	7.vi	15.4	62.four
	Late	26/09/12–10/09/13	1288	ix.five	160	9.1	63.1	11.1	12.4	71.6
Pwllpeiran	Early	eleven/04/xiii–27/03/14	1878	10.iv	96	8.4	44.viii	5.seven	7.viii	44.1
	Mid	04/07/13–16/06/xiv	1844	ten.viii	61	17.2	36.7	0.0	xiv.four	44.ane
	Tardily	12/09/13–27/08/14	1841	10.vi	98	thirteen.six	44.8	xiii.6	fourteen.iv	42.2

two.seven. Information processing and statistics

The North₂O flux for each chamber was calculated past inbound data for the sample vials N₂O concentration, air temperature, closure period and chamber heights into a standard spreadsheet used by all project partners. The mean of the v chambers per plot was calculated and used for subsequent calculations of cumulative emissions, using the trapezoidal rule (Cardenas et al., 2010). EFs were calculated by subtracting cumulative N_iiO emissions from command plots from treatment plots in the aforementioned cake. For the urine handling with DCD the Northward content in the DCD was taken into business relationship for the calculation of the EF. EFs uniformity of distribution were checked and, if necessary, Box Cox transformation was used on all N_iiO data to normalise distribution. Statistical analyses were designed to test:

• i)

  the effect of geographical site on North₂O EFs for the dissimilar treatments

• ii)

  the effect of season of awarding on Due north_iiO EFs for different treatments

• 3)

  the difference between urine and dung N₂O EFs

• iv)

  the effect of DCD in reducing N_iiO EFs from urine application

Treatment effects and their interactions were evaluated using the F-test in analysis of variance (ANOVA) of each site according to the randomised block design. Multiple comparing of treatment ways, if significant, were tested using the Tukey method (Hsu, 1996). When 'treatment × flavour' interaction was significant then treatments were compared inside each season, and seasons were compared with each handling. In addition, all five sites were combined using REML Meta-analysis in Genstat (VSN International, 2015) where the fixed effects model included main effects and interactions of sites, treatments and seasons (random effects model accounted for the design factors).

Multiple regression analysis (frontward selection process in Genstat) was used to explore the key soil (% clay, pH, initial % WFPS, average WFPS for first 30 days), environs (boilerplate temperature for the first xxx days, average temperature for 365 days subsequently application, total rainfall for the get-go 30 days, total rainfall for 365 days after application) and urine/dung composition (full urine/dung N content, total urine urea content, total urine/dung ammonium content, uric acid content, hippuric acrid content, allantoin content, creatinine content, N application rate) factors that controlled the cumulative N₂O fluxes and N_twoO EFs. The main effects of up to (maximum) 10 terms was estimated. No interaction terms were included for selection. In developing a multiple regression model, correlation among the predictor factors (known every bit multicollinearity) can affect model equation stability. For this modelling exercise, we used the statistical parcel Genstat (Genstat 18th Ed.; VSN International, 2015), which has the congenital-in facility to check for whatsoever multicollinearity issues (any such trouble can be dealt with by using Genstat Procedure "Ridge" regression which incorporates Principal Component (PCA) regression).

3. Results

3.1. Urine and dung composition

The N content of the urine used in the 15 experiments (Tabular array 4a) were typical for cattle urine (Dijkstra et al., 2013; Selbie et al., 2015; Gardiner et al., 2016), ranging from 6.eight to xi.4 m l⁻¹ (average nine.xi g fifty⁻ⁱ ± 0.35). In most cases urea-N represented between sixty and 100% of the full North content. However, for the three experiments at Hillsborough, the low urea-North content of the urine was linked to a high urine ammonium-N content (Table 4a), indicating hydrolysis of urea prior to application to the soil. Since urea hydrolysis is such a rapid procedure once urine has been deposited on the soil, we do non consider the N_iiO emissions from the 3 Hillsborough experiments to take been directly affected by this.

Concentrations of the purine derivatives in the urine varied markedly between the different seasons of drove for the different experiments at each site, and between sites (Table 5).

Table 5

Concentrations (g l⁻¹) of purine derivatives in cattle urine used in the experiments. *Detection limit of the analytical arroyo.

To convert from mg molecule l⁻ⁱ to mg N l^−one, multiply hippuric acid past 0.078138, allantoin by 0.354161, uric acid by 0.333115, and creatinine by 0.371287.

Archived data sources: Bell et al. (2017); Cardenas et al. (2017); McGeough et al. (2017); Thorman et al., 2017a, Thorman et al., 2017b.

Site	Grazing season period	Hippuric acrid	Allantoin	Uric acid	Creatinine
Crichton	Early	9.17	2.42	0.thirty	0.68
	Mid	i.57	ane.70	0.45	1.29
	Belatedly	7.69	three.89	0.41	0.77
Drayton	Early	<0.50*	ii.83	0.48	0.58
	Mid	<0.50*	<0.40*	0.55	0.62
	Tardily	8.02	iii.51	0.54	0.68
Hillsborough	Early on	<0.50*	0.74	0.15	0.xl
	Mid	<0.l*	<0.twoscore*	0.06	<0.10*
	Belatedly	<0.50*	<0.xl*	0.12	<0.10*
Northward Wyke	Early on	3.92	1.91	0.37	0.76
	Mid	<0.50*	<0.forty*	0.40	0.52
	Late	4.86	<0.twoscore*	0.35	0.52
Pwllpeiran	Early	5.13	0.84	0.36	0.81
	Mid	<0.50*	<0.twoscore*	0.31	0.25
	Late	8.92	3.67	0.03	0.73

This reflects differences in the diets that cattle were fed prior to drove of the urine on each occasion (come across Table two for a summary of the diets), and differences betwixt cattle groups at each collection site. However, concentrations are typical of those reported in the literature (Dijkstra et al., 2013; Selbie et al., 2015; Gardiner et al., 2016). The measured N contained in the purine derivatives represented from 3 to 28% of the total N content of the urine (average 12.five% ± 0.02).

The total N content of the dung ranged from 3.4 to 48.0 g kg⁻¹ (DM), whilst the DM content ranged from x.six–36.2% (Tabular array 4b). The full N loadings in the urine and dung treatments were typical for cattle, 338–568 kg ha⁻¹ (average 455 ± 17.6) and 625–1020 kg ha⁻¹ (boilerplate 835 ± 31.9), respectively. These values are within reported ranges (Selbie et al., 2015).

3.two. Weather

Annual rainfall was greater than the 30-year mean in ii (of the three) Crichton experiments, and all iii experiments at Drayton, Hillsborough, North Wyke and Pwllpeiran. Boilerplate almanac air temperature was similar to the 30-twelvemonth mean at Crichton and Pwllpeiran, cooler at Hillsborough and North Wyke, and warmer at Drayton. All the same, it is more likely that the weather conditions immediately before urine and dung awarding, and inside the beginning three months after application would accept the most influence on N₂O production and emission (come across Table 3).

3.3. Nitrous oxide emissions

3.3.1. Controls

Background (control) cumulative N₂O emissions ranged from −0.03–1.26 kg N_iiO-N ha⁻ⁱ for all sites and all experiments, with an boilerplate from the data in Table 6 of 0.49 kg North_iiO-N ha⁻¹ (±0.10). From the meta-assay, we discover that across all seasons, the Due north_iiO emissions from the controls were significantly greater from the Crichton, North Wyke and Pwllpeiran sites compared to the Drayton site (p < 0.05). Within an individual site, emissions from controls also varied between seasons of application, peculiarly at the North Wyke site. At that place was no statistically significant relationship between the urine N_iiO EF and the cumulative annual N_twoO emission from the control plots (p > 0.05). Beyond all sites, Northward₂O emissions from the command plots at the early grazing application timing were significantly greater than from the late-grazing application (p < 0.05). Regression modelling indicated that the cardinal factors controlling the magnitude of the almanac Northward₂O fluxes from control plots were soil organic carbon content, clay content, bulk density, WFPS during the outset 30d subsequently application, and average almanac temperature, with these factors accounting for ca. 56% of the variance in emissions. The resulting total regression equation was: Cumulative N₂O flux (kg Northward ha^−one) = three.981–0.0846 SOC − 0.02220 initial WFPS + 0.01052 × 30d WFPS − i.683 Majority density − 0.01807 Clay content − 0.0408 × 365d average temperature.

Table 6

Average cumulative N₂O emissions and Due north_twoO EFs from the urine and dung treatments at each experimental site for each application. (Values in italics are standard errors of the mean).

Archived data sources: Bell et al. (2017); Cardenas et al. (2017); McGeough et al. (2017); Thorman et al., 2017a, Thorman et al., 2017b.

Within each site/timing experiment (rows), average total North_twoO emissions or Northward₂O EFs between excretal N sources with different letters are significantly different (p < 0.05, N = 3).

		Cumulative emissions of Due northiiO (kg NtwoO ha−1)					NorthwardiiO EF (% of applied N)
Site	Grazing season period	Command	Urine	Urine +DCD	Artificial urine	Dung	Urine	Urine +DCD	Artificial urine	Dung
Crichton	Early	0.96a 0.23	1.92a 0.20	i.25a 0.09	0.93a 0.09	2.15a 0.51	0.20a 0.06	0.06a 0.03	−0.02a 0.13	0.12a 0.03
	Mid	0.61a 0.17	5.18b 0.82	five.07b 1.03	5.29b 0.thirty	2.00a 0.09	1.09b 0.18	1.05b 0.28	1.10b 0.06	0.20a 0.03
	Late	0.79a 0.32	2.21a 0.66	1.79a 0.24	1.49a 0.sixty	one.55a 0.12	0.33a 0.15	0.23a 0.12	0.16a 0.18	0.11a 0.03
Drayton	Early	0.18a 0.06	2.02a 0.11	one.35a 0.fourteen	i.86a 0.05	0.85a 0.17	0.34a 0.03	0.21a 0.02	0.34a 0.01	0.08a 0.02
	Mid	0.03a 0.09	0.86a 0.08	0.74a 0.07	0.82a 0.08	0.95a 0.05	0.18a 0.00	0.15a 0.00	0.16a 0.01	0.12a 0.01
	Late	−0.03a 0.05	7.68d 1.79	4.73bc one.35	half-dozen.47 cd 0.42	2.56b 0.35	1.64c 0.37	1.00b 0.28	1.31bc 0.08	0.32a 0.04
Hillsborough	Early	0.36a 0.10	four.78a 1.xi	1.46a 0.42	10.87b iv.84	1.98a 0.twenty	one.02a 0.26	0.25a 0.12	two.06b 0.96	0.17a 0.03
	Mid	0.23a 0.04	1.20a 0.15	1.52a 0.44	one.96a 0.61	ane.73a 0.45	0.29a 0.05	0.38a 0.14	0.34a 0.thirteen	0.15a 0.04
	Late	0.15a 0.05	0.31a 0.07	0.20a 0.04	0.67a 0.xi	0.51a 0.15	0.05a 0.03	0.01a 0.00	0.10a 0.03	0.04a 0.01
N Wyke	Early	one.26a 0.13	xiii.26d 0.50	5.54b 0.69	11.06c 0.43	2.50a 0.43	2.96c 0.xiv	1.09b 0.20	two.23c 0.12	0.14a 0.06
	Mid	0.80a 0.07	3.19b 0.51	2.93b 0.50	4.16b 0.89	3.24b 0.52	0.56b 0.eleven	0.49ab 0.10	0.70b 0.18	0.39a 0.08
	Late	0.03a 0.xiii	0.52a 0.29	0.59a 0.eleven	0.34a 0.23	0.82a 0.17	0.11a 0.04	0.12a 0.02	0.07a 0.02	0.10a 0.01
Pwllpeiran	Early	0.49a 0.eighteen	3.45c 0.34	i.59ab 0.31	3.15c 0.23	2.17bc 0.31	0.52b 0.07	0.19a 0.07	0.54b 0.03	0.22a 0.05
	Mid	0.42a 0.04	2.11b 0.thirteen	0.94ab 0.03	1.81b 0.15	2.13b 0.33	0.30b 0.03	0.09a 0.01	0.28b 0.03	0.21ab 0.04
	Late	0.52a 0.07	four.14b 0.39	i.78a 0.13	3.52b 0.36	5.08c 0.81	0.72c 0.09	0.25a 0.02	0.59bc 0.08	0.53b 0.09
Average of all sites and seasons							0.69 0.20	0.37 0.09	0.66 0.18	0.19 0.03

iii.iii.two. Urine

Examples of daily N₂O fluxes are shown in Fig. 3 for the late-flavor urine, dung and command treatments at the Drayton site. These data evidence two distinct peaks in N_twoO fluxes, something observed in several of the experiments (due east.g. Cardenas et al., 2016), suggesting the peaks in emission are associated either with dissimilar processes (eastward.thou. denitrification of soil NO₃ during the starting time peak as a issue of the carbon add-on in the urine, and nitrification of the urine NH_iv source during the 2d top), or different pools of N being the substrate for denitrification (e.one thousand. the starting time top associated with the urine-derived NH_four, and the 2d tiptop associated with other more recalcitrant pools, due east.g. N independent in purine derivatives). Further research using labelled urine N compounds would help reveal the underpinning processes and/or Northward sources responsible for the two peaks in emission.

Daily mean North₂O fluxes following urine and dung treatments at Drayton after a late-season awarding. (North = 3, vertical bars are standard error of the hateful).

The hateful urine North₂O EF was 0.69% (±0.twenty), ranging from 0.05–2.96 (Table 6). Across all seasons of application, the meta-analysis showed that the N₂O EF was significantly greater from the North Wyke site than other sites (p < 0.05) (Fig. 4). Whilst beyond all sites, the North₂O EF was significantly greater following an early-grazing awarding (p < 0.05) (Fig. five). DCD reduced the N₂O EF from urine in 13 of the 15 experiments, although this reduction was just significant in 5 of these experiments (Tabular array half-dozen). The average N₂O EF for the urine + DCD treatment was 0.37% (±0.09) (Table vi). So, the use of DCD resulted in an average reduction in the North₂O EF of 46%, although the range in efficacy was broad, i.e. from an increase in the Due north₂O EF of 32% (mid-season application at Hillsborough) to a reduction of 75% (at the same site from the early-flavour application).

Average North_iiO EF (beyond iii seasons of application) for each site, for urine and dung treatments.

Inside each urine/dung treatment, average N_iiO EFs (from meta-analysis) between sites with unlike messages are significantly different (N = 3, vertical lines are standard error of the hateful).

Effect of urine/dung treatment awarding timing (beyond all sites) on average North_iiO EF.

Inside each handling, boilerplate N_iiO EFs (from meta-analysis) between timings of awarding with different letters are significantly different (Northward = 3, vertical lines are standard error of the mean).

three.iii.3. Artificial urine

The mean artificial urine N_twoO EF was similar to that of the existent urine, 0.66% (±0.18) (Table 6), and at that place was a good human relationship between the North₂O EFs for existent and bogus urine (r^two = 0.77). Beyond all seasons, the meta-analysis showed that the Northward₂O EF from the bogus urine was significantly greater at North Wyke and Hillsborough (p < 0.05) than the other sites (Fig. iv). Beyond all sites, the greatest North_iiO EF occurred post-obit the early-grazing application (p < 0.05) (Fig. 5).

three.3.4. Dung

The mean N₂O EF for dung (from the meta-assay) was 0.19% (±0.03), with a range of 0.04–0.53 (Tabular array 6), which was significantly lower than for urine (p < 0.05). The meta-analysis showed there was no issue of site or season of application on the North₂O EF from dung (p > 0.05) (Fig. 4, Fig. 5).

three.4. Factors affecting Northward_twoO fluxes from urine and dung

It is clear that there were significant (p < 0.05) effects of excretal N source and flavor of awarding at each site, as well as 'treatment' × 'season' interactions (Tabular array 7).

Table 7

Significance F-test probabilities for cumulative N_twoO emission and N₂O EF, by timing of application, site, and timing of awarding × site interactions, from randomised block design ANOVA for each experiment.

		Treatments	Application time	Interaction
Crichton	Total NtwoO EF	<0.001 0.012	<0.001 <0.001	<0.001 0.019
Drayton	Total NtwoO EF	<0.001 <0.001	<0.001 <0.001	<0.001 0.002
Hillsborough	Full Due north2O EF	0.006 0.035	<0.001 0.002	0.014 0.042
Due north Wyke	Total NtwoO EF	<0.001 <0.001	<0.001 <0.001	<0.001 <0.001
Pwllpeiran	Total N2O EF	<0.001 <0.001	<0.001 <0.001	<0.001 0.093

3.four.1. Urine

Multiple regression analysis showed that the factors that best explained cumulative N₂O emissions from urine awarding mainly included urine limerick and soil pH. The factors explaining 91.1% of the variance in cumulative N₂O emissions from urine patches are shown via this equation: Cumulative N_twoO flux (kg N ha^−ane) = −61.94 + 38.50 urine creatinine content −0.0042 urine urea N content +0.003310 urine ammonium Due north content +0.002801 urine total nitrogen content +4.115 soil pH −1.036 urine hippuric acrid content +4.340 urine pH −viii.06 urine uric acid content. >75% of the variance in total N₂O flux was explained by the urine total North, urea-N, ammonium-North, uric acid and creatinine content.

The full equation of factors explaining 91.1% of the urine N_iiO EF was; EF% = −15.9 + viii.776 urine creatinine content −0.0009595 urine urea Northward content −0.0007965 urine ammonium N content +one.014 soil pH +0.0005941 urine total nitrogen content −0.2563 urine hippuric acid content +ane.116 urine pH −ii.059 urine uric acid content. >75% of the variance in Due north_iiO EF was explained by the urine total N, urea-N, ammonium-Northward, uric acid and creatinine content.

3.4.2. Dung

In contrast to urine, multiple regression showed that the factors that best explained cumulative N₂O emissions from dung application included environmental and soil factors (besides as dung factors). The full equation, explaining 68.3% of the variance in cumulative Northward_twoO emissions from dung in this report was; Cumulative N_iiO flux (kg N ha⁻ⁱ) = four.15–0.0579 initial %WFPS −0.308 365d average temperature −0.805 soil pH −0.0408 dung nitrate N content −0.00082 full nitrogen applied +1.053 soil organic carbon −10.50 soil dry bulk density +i.927 dung pH.

The full equation of factors explaining 66.five% of the dung N_iiO EF was; EF% = −0.295 + 0.0001187 dung ammonium Northward content +0.01784 30d %WFPS − 0.01473 dung nitrate Northward content − 0.002143 total nitrogen applied − 0.02343 30d average temperature + 0.1159 soil organic carbon +0.1747 dung full nitrogen content +0.0452 365d average temperature.

iv. Discussion

Urine North₂O EFs were significantly greater (boilerplate 0.69%) than the dung Northward₂O EFs (boilerplate 0.nineteen%), signifying the importance of the Nr content as a substrate for the soil processes, nitrification and denitrification, responsible for N₂O production. Our urine and dung N₂O EFs are similar to some of those measured by New Zealand researchers, summarised by Kelliher et al. (2014). In New Zealand, urine N₂O EFs are categorised by livestock species and farming system (lowland, hill land low and high slope), and our results are more similar to the N_iiO EFs for the hill-country low slope dairy cattle urine (average of 0.84%) and dung (boilerplate of 0.20%). By dissimilarity, Krol et al. (2016) reported larger boilerplate urine and dung N_iiO EFs for 9 experiments conducted in Ireland of i.18% (urine) and 0.39% (dung); EFs approximately double the values we have measured. In this series of experiments, Krol et al. (2016) applied urine at a higher Northward loading rate (average of 720 kg Northward ha^−ane) than in our study (boilerplate of 455 kg N ha⁻¹). All the same, the greater N_twoO EF from the dung in the Irish study (0.39%) was despite using a lower N loading charge per unit (average of 459 kg N ha^−ane) than in our study (835 kg N ha^−ane), suggesting that North loading was not the merely factor resulting in the greater urine Due north₂O EFs in these Irish experiments. Soil and environmental factors appeared to have been more conducive to N₂O production and emission in this Irish written report.

In our report, DCD reduced the urine N₂O EFs by an average of 46%, although there was considerable variability in its efficacy to reduce N₂O emissions (between sites and between seasons). In a related written report, McGeough et al. (2016) took soil from these five United kingdom of great britain and northern ireland grassland sites, and an boosted four arable sites, and demonstrated that the efficacy of DCD to inhibit nitrification was controlled past the interaction between temperature, soil clay content and soil organic matter. Moreover, this written report ended that DCD was more than constructive in arable soils than in these grassland soils (McGeough et al., 2016). The average DCD N_iiO mitigation efficacy we measured (46%), and the range of efficacy that we measured are similar to other studies. For example, Selbie et al. (2014) showed that DCD increased the urine N₂O EF by an average of +four% (a small increase) for urine applied at a loading rate of 500 kg Due north ha⁻¹, but resulted in a 30% reduction for urine practical at thou kg N ha⁻¹ (in New Zealand). Misselbrook et al. (2014) reported a greater efficacy of DCD to reduce the urine N_iiO EF, by 70% on a sandy clay loam in SW England. Recently, Minet et al. (2018) showed DCD, applied at x kg ha⁻ⁱ, could reduce the urine North_twoO EF by 34% (from 0.80% to 0.52%), but that DCD applied at 30 kg ha⁻¹ reduced the urine N₂O EF further, by 64%. Annotation: efficacy of DCD is often reported for cumulative emissions, with reported values beingness much higher than the efficacy of reducing the EF itself (east.g. Selbie et al., 2014). All the same, the efficacy of DCD to reduce North₂O EFs is needed if national inventories are to be modified accordingly.

We constitute show of the effect of timing on N₂O EFs, with larger EFs occurring following early-flavour urine awarding/deposition (Fig. 5). Krol et al. (2016) likewise explored the consequence of season of urine application on Northward₂O EFs from Irish grasslands, and showed that EFs varied seasonally, with the highest EFs in the autumn, and that emission were also dependent on soil type. Indeed, relationships between the magnitude of N₂O EFs with "generic" flavor of deposition should be interpreted with caution, equally soil and environmental conditions can vary markedly within a season. Hence, the importance of using statistical regression modelling to explore the key controls. Whilst there were insufficient data from our 15 experiments to be able to explore the relationships between cumulative N₂O emissions, North₂O EFs and climate/soil with certainty, the limited regression assay showed that Due north₂O emissions associated with urine were more than related to urine composition than environmental and soil factors, whilst for dung which has a relatively low inorganic N content, N₂O emissions were too controlled past soil and ecology factors. Krol et al. (2016) as well used regression modelling to show the importance of rainfall and temperature before, and soil moisture deficit after, application of excretal deposition, on N₂O emissions from ix experiments on Irish grasslands. We recognise the limitations of conducting regression assay on such small information sets. Yet, at that place is potential to generate a much larger data set by combining data from studies where soils and climate are like, and where similar protocols were followed, e.g. Krol et al. (2016), Minet et al. (2018), and data from some New Zealand experiments, to explore the controls of N₂O emissions from urine and dung deposition, and generate improved EFs. Importantly, our unique dataset of daily Northward₂O fluxes, cumulative emissions and emission factors, too every bit soil mineral Northward and moisture data with weather condition, soil and site data take all been archived for future employ by researchers (Bell et al., 2017; Cardenas et al., 2017; McGeough et al., 2017; Thorman et al., 2017a; Thorman et al., 2017b), and to let integration with time to come datasets that get available.

To calculate a provisional excretal N₂O EF, based on the data presented in this study, we presume a 60:40 separate betwixt the total N excreted in urine and dung (Webb and Misselbrook, 2004). We estimate a combined excretal N_twoO EF, based on our mean urine and dung N₂O EFs data of 0.49%. These UK information have now been combined with the very few additional IPCC compliant United kingdom of great britain and northern ireland experimental datasets (see Misselbrook et al., 2014) to generate a new state specific Due north₂O EF of 0.44%. This is <25% of the IPCC (2006) default EF for cattle grazing excreta (EF₃), and ca. 50% of the default EF for sheep grazing excreta. If we substitute this new pasture, range and paddock EF for both cattle and sheep into the IPCC, 2006 methodology for calculating the Great britain inventory, we judge a reduction of xi.vi kt Northward_twoO (18% less N₂O for UK agriculture for 2015) and for total U.k. agricultural GHG emissions, a reduction of 3.4 Mt. CO₂e, or 7% for UK agriculture for 2015. This new EF is used in dorsum-casting to 1990, and so has no bearing on meeting the UKs aggressive greenhouse gas mitigation target. However, a reduced GHG emission from agriculture means that a greater proportion of the emission can be "offset" by carbon sequestration, and suggests that e.g. state sparing strategies may be more realistic (Lamb et al., 2016). The lower state specific pasture, range and paddock EF₃ also has implications for computing carbon footprints of ruminant livestock products in the Great britain.

Clearly, this written report focussed on cattle urine and dung where applications were made to lowland mineral soils, and where urine and dung were nerveless from cattle fed "lowland" diets. So, questions ascend about a) extrapolating the N₂O EF data to sheep; indeed the IPCC default sheep urine Due north_twoO EF (1%) is greater than the new combined cattle excreta North_twoO EF from our study, and b) extrapolating the new N_twoO EF data to beef and sheep grazing in the uplands, on much more organic and potentially acidic soils, and where weather and soil weather as well as urine/dung limerick may be very different.

five. Conclusions

This was the first co-ordinated written report in the Great britain to generate data to develop a country specific grazing excreta North₂O EF for cattle. Results confirmed that urine is the greatest source of Due north_iiO compared to dung, and that the nitrification inhibitor, DCD, offers the potential to reduce N₂O emissions from urine patches, although its efficacy across the sites and seasons was variable. Understanding what controls this variability, and the development of cost effective delivery mechanisms need to be addressed if this technology is to exist adopted. Importantly, the results of this report provide evidence that for the UK soil and climatic conditions, the North_twoO EF for grazing excreta for cattle is significantly lower (0.49%) than the IPCC default (2%) with implications for both authorities and the ruminant livestock industries as they seek to run into challenging greenhouse gas mitigation targets and greenhouse gas emission roadmaps, respectively. Further questions arise in terms of the validity of extrapolating these information from cattle to sheep grazing, and from mineral to organic soils.

Data argument

Our unique datasets of daily Due north₂O fluxes, cumulative emissions and emission factors, as well as soil mineral North and moisture data with conditions, soil and site information from all fifteen experiments take been archived for future use by researchers (see: Bell et al., 2017; Cardenas et al., 2017; McGeough et al., 2017; Thorman et al., 2017a; Thorman et al., 2017b), and to allow integration with future datasets that go bachelor.

Acknowledgements

The authors are grateful to the UK Section for Environment, Food and Rural Affairs (Defra), the Section of Agriculture and Rural Development (now the Department of Agriculture, Environs and Rural Diplomacy) in Northern Ireland, and the Scottish Government and the Welsh Government for financial support via the InveN_iiOry projection (AC0116). The work past Rothamsted Research was additionally supported by the Biotechnology and Biological Sciences Research Council (Bbs/E/C/000I0320). Nosotros would likewise like to thank Jon Moorby (IBERS, Wales, Great britain), Reading University, SRUC (Scotland, Britain) and Conrad Ferris (AFBI, Northern Ireland, Great britain), for provision of cattle urine and dung.

References

Balvert Due south., Luo J., Schipper L. Practice glucosinolate hydrolysis products reduce nitrous oxide emissions from urine affected soil? Sci. Total Environ. 2017;603–604:370–380. [PubMed] [Google Scholar]

Barneze A.S., Minet E.P., Cerri C.C., Misselbrook T. The upshot of nitrification inhibitors on nitrous oxide emissions from cattle urine depositions to grassland nether summer conditions in the UK. Chemosphere. 2015;119:122–129. [PubMed] [Google Scholar]

Bell G., Rees R., Cloy J., Topp K., Bagnall A., Chadwick D. Nitrous oxide emissions from cattle excreta applied to a Scottish grassland: effects of soil and climatic conditions and a nitrification inhibitor. Sci. Full Environ. 2015;508:343–353. [PubMed] [Google Scholar]

Bell Thousand.J., Rees R.M., Cloy J.K., Topp C.F.E., Bagnall A., Chadwick D.R. 2017. Agricultural greenhouse gas inventory research platform - InveN ₂ Ory. Dung and urine experimental site in Dumfries, 2012. Version:1. [dataset] Freshwater Biological Association [publisher] [Google Scholar]

Broderick G.A. Effects of varying dietary protein and energy levels on the production of lactating dairy cows. J. Dairy Sci. 2003;86:1370–1381. [PubMed] [Google Scholar]

Burchill W., Lanigan M.J., Forrestal P.J., Misselbrook T., Richards K.K. Ammonia emissions from urine patches amended with N stabilized fertilizer formulations. Nutr. Cycl. Agroecosyst. 2017;108:163–175. [Google Scholar]

Cardenas L.M., Thorman R., Ashlee N., Butler M., Chadwick D.R., Chambers B., Cuttle S., Donovan North., Kingston H., Lane S., Scholefield D. Quantifying annual Due north₂O emission fluxes from grazed grassland under a range of inorganic fertiliser nitrogen inputs. Agric. Ecosyst. Environ. 2010;136:218–226. [Google Scholar]

Cardenas L.M., Misselbrook T.M., Hodgson C., Donovan North., Gilhespy South., Smith K.A., Dhanoa 1000.South., Chadwick D. Effect of the application of cattle urine with or without the nitrification inhibitor DCD, and dung on greenhouse gas emissions from a United kingdom grassland soil. Agr. Ecosyst. Environ. 2016;235:229–241. [PMC costless commodity] [PubMed] [Google Scholar]

Cardenas L.Grand., Misselbrook T.H., Donovan N. 2017. Agricultural Greenhouse Gas Inventory Inquiry Platform - InveN ₂ Ory. Dung and urine experimental site in Devon, 2012. Version:1. [dataset] Freshwater Biological Association [publisher] [Google Scholar]

Chadwick D.R., Rees R.Thou., Williams J., Smith P., Skiba U.M., Hiscock Yard., Manning A.J., Watson C., Smith 1000.A., Anthony South.G., Moorby J., Mottram T. 2011. Improving the national inventory of agricultural nitrous oxide emissions from the Uk (InveN₂Ory). Non-CO₂ Greenhouse Gases (NCGG-6) Scientific discipline, Policy and Integration (Conference Proceedings). 2011. Amsterdam. [Google Scholar]

Chadwick D.R., Cardenas L., Misselbrook T.H., Smith 1000.A., Rees R.M., Watson C.J., McGeough M.L., Williams J.R., Cloy J.Chiliad., Thorman R.E., Dhanoa Grand.South. Optimizing chamber methods for measuring nitrous oxide emissions from plot-based agricultural experiments. Eur. J. Soil Sci. 2014;65:295–307. [Google Scholar]

Clough T.J., Ledgard S.F., Sprosen 1000.South., Kear M.J. Fate of Northward-15 labelled urine on four soil types. Plant Soil. 1998;199:195–203. [Google Scholar]

Clough T.J., Ray J.L., Buckthought L.E., Calder J., Baird D., O'callaghan G., Sherlock R.R., Condron 50.M. The mitigation potential of hippuric acrid on N₂O emissions from urine patches: an in situ conclusion of its effect. Soil Biol. Biochem. 2009;41:2222–2229. [Google Scholar]

de Klein C.A.Yard., Ledgard S.F. An analysis of environmental and economic implications of nil and restricted grazing systems designed to reduce nitrate leaching from New Zealand dairy farms. I. Nitrogen losses. N. Z. J. Agric. Res. 2001;44:201–215. [Google Scholar]

de Klein C.A., Luo J., Woodward K.B., Styles T., Wise B., Lindsey S., Cox N. The effect of nitrogen concentration in synthetic cattle urine on nitrous oxide emissions. Agric. Ecosyst. Environ. 2014;188:85–92. [Google Scholar]

Di H.J., Cameron Thousand.C. Nitrate leaching losses and pasture yields as affected by unlike rates of animal urine nitrogen returns and awarding of a nitrification inhibitor - a lysimeter written report. Nutr. Cycl. Agroecosyst. 2007;79:281–290. [Google Scholar]

Di H.J., Cameron One thousand.C. Sources of nitrous oxide from 15N-labelled animal urine and urea fertiliser with and without a nitrification inhibitor, dicyandiamide (DCD) Aust. J. Soil Res. 2008;46:76–82. [Google Scholar]

Di H.J., Cameron Chiliad.C. How does the application of different nitrification inhibitors affect nitrous oxide emissions and nitrate leaching from cow urine in grazed pastures? Soil Utilise Manag. 2012;28:54–61. [Google Scholar]

Dijkstra J., Oenema O., Van Groenigen J.W., Spek J.Due west., Van Vuuren A.M., Bannink A. Diet effects on urine limerick of cattle and North₂O emissions. Creature. 2013;7:292–302. [PubMed] [Google Scholar]

Gardiner C.A., Clough T.J., Cameron K.C., Di H.J., Edwards 1000.R., de Klein C.A.M. Potential for forage diet manipulation in New Zealand pasture ecosystems to mitigate ruminant urine derived Northward₂O emissions: a review. North. Z. J. Agric. Res. 2016;59:301–317. [Google Scholar]

Hatch D., Trindad H., Cardenas L., Carneiro J., Hawkins J., Scholefield D., Chadwick D. Laboratory report of the effects of two nitrification inhibitors on greenhouse gas emissions from a slurry-treated arable soil: touch on of diurnal temperature wheel. Biol. Fertil. Soils. 2005;41:225–232. [Google Scholar]

Hsu J.C. Chapman & Hall; London: 1996. Multiple Comparisons Theory and Methods. [Google Scholar]

IPCC . Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. IPPC/OECD/IEA; Uk: 1996. Intergovernmental panel on climate change, 1996. [Google Scholar]

IPCC . Intergovernmental Console on Climate Modify, 2000. Skillful practice guidance and uncertainty management in national greenhouse gas inventories. In: Penman J., Kruger D., Galbally I., Hiraishi T., Nyenzi B., Emmanuel S., Buendia L., Hoppaus R., Martinsen T., Meijer J., Miwa K., Tanabe K., editors. Intergovernmental Panel on Climate Change (IPCC) IPCC/OECD/IEA/IGES; Hayama, Japan: 2000. [Google Scholar]

IPCC . Affiliate 11: North₂O Emissions from Managed Soils, and CO₂ Emissions from Lime and Urea Awarding. In: De Klein C., Novoa R.Southward.A., Ogle S., Smith 1000.A., Rochette P., Wirth T.C., McConkey B.G., Mosier A., Rypdal K., editors. Intergovernmental Panel on Climate Change, 2006. Guidelines for National Greenhouse Gas Inventories Agriculture, Forestry and Other State Use Intergovernmental Console on Climate Change. 2006. http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_11_Ch11_N2O&CO2.pdf [Google Scholar]

Kelliher F.M., Cox Northward., van der Weerden T.J., de Klein C.A.M., Luo J., Cameron K.C., Di H.J., Giltrap D., Rys Thousand. Statistical analysis of nitrous oxide emission factors from pastoral agronomics field trials conducted in New Zealand. Environ. Pollut. 2014;186:83–86. [PubMed] [Google Scholar]

Kool D.Grand., Hoffland E., Abrahamse S.P.A., van Groenigen J.Due west. What artificial urine composition is adequate for simulating soil N₂O fluxes and mineral N dynamics? Soil Biol. Biochem. 2006;38:1757–1763. [Google Scholar]

Krol D.J., Carolan R., Minet E., McGeough K.L., Watson C.J., Forrestal P.J., Lanigan Thou.J., Richards K.G. Improving and disaggregating N_twoO emission factors for ruminant excreta on temperate pasture soils. Sci. Total Environ. 2016;568:327–338. [PubMed] [Google Scholar]

Lam S.K., Suter H., Mosier A.R., Chen D. Using nitrification inhibitors to mitigate agricultural Northward_iiO emission: a double-edged sword? Glob. Chang. Biol. 2017;23:485–489. [PubMed] [Google Scholar]

Lamb A., Greenish R., Bateman I., Broadmeadow M., Bruce T., Burney J., Carey P., Chadwick D., Crane East., Field R., Goulding Thousand., Griffiths H., Hastings A., Kasoar T., Kindred D., Phalan B., Pickett J., Smith P., Wall E., zu Ermgassen Due east.Thousand.H.J., Balmford A. Land sparing as a mechanism to offset greenhouse gas emissions from agriculture. Nat. Clim. Modify. 2016;6(five):488–492. [Google Scholar]

Laubach J., Taghizadeh-Toosi A., Gibbs S.J., Sherlock R.R., Kelliher F.M., Grover S.P.P. Ammonia emissions from cattle urine and dung excreted on pasture. Biogeosciences. 2013;10:327–338. [Google Scholar]

Ledgard S.F., Menneer J.C., Dexter M.G., Kear M.J., Lindsey S., Peters J.S., Pacheco D. A novel concept to reduce nitrogen losses from grazed pastures by administering soil nitrogen process inhibitors to ruminant animals: a study with sheep. Agric. Ecosyst. Environ. 2008;125:148–158. [Google Scholar]

Lockyer D.R., Whitehead D.C. Volatilization of ammonia from cattle urine applied to grassland. Soil Biol. Biochem. 1990;22:1137–1142. [Google Scholar]

Luo J., Ledgard S., Wise B., Welten B., Lindsey Southward., Judge A., Sprosen Thousand. Upshot of dicyandiamide (DCD) delivery method, awarding rate, and flavour on pasture urine patch nitrous oxide emissions. Biol. Fertil. Soils. 2015;51:453–464. [Google Scholar]

Luo J., Balvert S.F., Wise B., Welten B., Ledgard S.F., de Klein C.A.Yard., Lindsey S., Judge A. Using culling forage species to reduce emissions of the greenhouse gas nitrous oxide from cattle urine deposited onto soil. Sci. Full Environ. 2018;610-611:1271–1280. [PubMed] [Google Scholar]

Marsden Grand.A., Scowen G., Loma P.W., Jones D.Fifty., Chadwick D.R. Plant acquisition and metabolism of the constructed nitrification inhibitor dicyandiamide and naturally-occurring guanidine from agronomical soils. Constitute Soil. 2015;395:201–214. [Google Scholar]

Marsden Yard.A., Jones D.L., Chadwick D.R. Disentangling the outcome of sheep urine patch size and N loading rate on cumulative N_twoO emissions. Anim. Prod. Sci. 2016;56:265–275. [Google Scholar]

McGeough K.L., Watson C.J., Müller C., Laughlin R.J., Chadwick D.R. Show that the efficacy of the nitrification inhibitor dicyandiamide (DCD) is affected by soil properties in Uk soils. Soil Biol. Biochem. 2016;94:222–232. [Google Scholar]

McGeough K.L., McNeill 1000., Laughlin R.J., Watson C.J. 2017. Agricultural Greenhouse Gas Inventory Inquiry Platform - InveN _ii Ory. Dung and urine experimental site in Canton Downwards, 2012. Version:ane. [dataset] Freshwater Biological Association [publisher] [Google Scholar]

Minet E.P., Ledgard Southward.F., Lanigan M.J., Murphy J.B., Grant J., Hennessy D., Lewis E., Forrestal P., Richards K.G. Mixing dicyandiamide (DCD) with supplementary feeds for cattle: an effective method to deliver a nitrification inhibitor in urine patches. Agric. Ecosyst. Environ. 2016;231:114–121. [Google Scholar]

Minet Eastward.P., Ledgard Due south.F., Grant J., Murphy J.B., Krol D.J., Lanigan Grand.J., Luo J., Richards Chiliad.G. Feeding dicyandiamide (DCD) to cattle: an effective method to reduce N₂O emissions from urine patches in a heavy-textured soil under temperate climatic conditions. Sci. Total Environ. 2018;615:1319–1331. [PubMed] [Google Scholar]

Misselbrook T.H., Cardenas Fifty.M., Camp V., Thorman R.Due east., Williams J.R., Rollett A.J., Chambers B.J. An assessment of nitrification inhibitors to reduce nitrous oxide emissions from UK agriculture. Environ. Res. Lett. 2014;9 [Google Scholar]

Misselbrook T.Yard., Fleming H., Camp Five., Umstatter C., Duthie C.-A., Nicoll L., Waterhouse T. Automated monitoring of urination events from grazing cattle. Agric. Ecosyst. Environ. 2016;230:191–198. [Google Scholar]

Monaghan R.M., de Klein C.A.G. Integration of measures to mitigate reactive nitrogen losses to the surroundings from grazed pastoral dairy systems. J. Agric. Sci. 2014;152:45–56. [Google Scholar]

Pal P., McMillan A.K., Saggar S. Pathways of dicyandiamide uptake in pasture plants: a laboratory study. Biol. Fertil. Soils. 2016;52:539–546. [Google Scholar]

Qui W.H., Di H.J., Cameron K.C., Hu C.10. Nitrous oxide emissions from brute urine as affected by flavour and a nitrification inhibitor dicyandiamide. J. Soils Sediments. 2010;10:1229–1235. [Google Scholar]

Reed 1000.F., Moraes Fifty.Eastward., Casper D.P., Kebreab E. Predicting nitrogen excretion from cattle. J. Dairy Sci. 2015;98:3025–3035. [PubMed] [Google Scholar]

Reidy B., Dammgen U., Dohler H., Eurich-Menden B., van Evert F.One thousand., Hutchings N.J., Luesink H.H., Menzi H., Misselbrook T.H., Monteny Grand.J., Webb J. Comparison of models used for national agricultural ammonia emission inventories in Europe: liquid manure systems. Atmos. Environ. 2008;42:3452–3464. [Google Scholar]

Selbie D.R., Cameron Thousand.C., Di H.J., Moir J.Fifty., Lanigan Yard.J., Richards Thou.K. The effect of urinary nitrogen loading rate and a nitrification inhibitor on nitrous oxide emissions from a temperate grassland soil. J. Agric. Sci. 2014;152(S1):159–171. [Google Scholar]

Selbie D.R., Buckthought Fifty.E., Shepherd M.A. Chapter four-the challenge of the urine patch for managing nitrogen in grazed pasture systems. Adv. Agron. 2015;129:229–292. [Google Scholar]

Singh U., Sanabria J., Austin East.R., Agyin-Birikorang South. Nitrogen transformation, ammonia volatilization loss, and nitrate leaching in organically enhanced nitrogen fertilizers relative to urea. Soil Sci. Soc. Am. J. 2011;76:1842–1854. [Google Scholar]

Sugimoto Y., Ball P.R. Nitrogen losses from cattle dung. In: Desroches R., editor. Proceedings XVI International Grassland Congress. Vol. I. 1989. pp. 153–154. Nice. [Google Scholar]

Thorman R.E., Nicholson F.A., McMillan S., Shrosbree A., Smith K.E., Williams J.R. 2017. Agricultural Greenhouse Gas Inventory Inquiry Platform - InveN ₂ Ory. Dung and urine experimental site in Warwickshire, 2013. Version:1. [dataset] Freshwater Biological Association [publisher] [Google Scholar]

Thorman R.E., Lathwood T., Nicholson F.A., Shrosbree A., Smith K.E., Williams J.R. 2017. Agricultural Greenhouse Gas Inventory Research Platform - InveN _ii Ory. Dung and urine experimental site in Ceredigion, 2013. Version:i. [dataset] Freshwater Biological Association [publisher] [Google Scholar]

van der Weerden T.J., Styles T.Chiliad., Rutherford A.J., de Klein C.A.M., Dynes R. Nitrous oxide emissions from cattle urine deposited onto soil supporting a wintertime forage kale crop. N. Z. J. Agric. Res. 2017;threescore:119–130. [Google Scholar]

van Groenigen J.W., Kuikman P.J., de Groot W.J., Velthof G.L. Nitrous oxide emission from urine-treated soil as influenced by urine composition and soil physical conditions. Soil Biol. Biochem. 2005;37:463–473. [Google Scholar]

VSN International . VSN International; Hemel Hempstead, Britain: 2015. Genstat for Windows 18th Edition.Genstat.co.u.k. Web page: [Google Scholar]

Webb J., Misselbrook T.H. A mass-flow model of ammonia emissions from UK livestock production. Atmos. Environ. 2004;38:2163–2176. [Google Scholar]

Welten B.G., Ledgard South.F., Luo J. Administration of dicyandiamide to dairy cows via drinking water reduces nitrogen losses from grazed pastures. J. Agric. Sci. 2014;152:150–158. [Google Scholar]

harrisonmosters.blogspot.com

Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024564/

Share this post