AP42 Section:

Background Ch Reference:

Title:

9.2.1

4 49

N.J. Hutchings, et al., "A Model of Ammonia Volatilization From a Grazing Livestock Farm," 4tmospheric Environment, 30(4):589-599, 1996.

1352-2310(95)00315-0

A MODEL OF AMMONIA VOLATILIZATION FROM A GRAZING LIVESTOCK FARM

N. J. HUTCHINGS Macaulay Land Use Research Institute. Craigiebuckler, Aberdeen AB9 2QJ. U.K

S. G . SOMMER Danish Institute a i Plant and Soil Science, Departmenl of Soil Science, Foulum Research Centre.

8830 Tjclc, Denmark

and

S. C. JARVIS Institute of Crass and Environmental Research. North Wyke. Okehampton. Devon EX20 2%. U.K.

(Firs! receiwd I8 March 1995 and inf inal /orm I Augosr 1995)

Abstract-A dynamic model was developed to predict the ammonia volatilization lrom grazing livcstock lams and to allow potential control measures to be evaluated. The relationships within the model were bascd on the underlying physical and chemical processes but empirically based factors were used to reduce the demand lor input data and where the understanding of the underlying processes war inadcquate. On a daily basis. the model simulates the partitioning oi dietary nitrogen into dung and urine and its subsequent Fate within the pasture or the slurry handling system.The late oldry matter and water addcd in dung, urine and from other sources is also predicted. The model illurtratcs !he indirect interactions between ammonia sources. highlights the influence ol slurry management an ammonia losses. stresses the need for integrated. whole l a m mezsurements and demonstrates that assessments ol the impact o l control measures may be misleading unless considered at the scale ol the whole lam.

Key word index: Mod4 ammonia volatilization, animal housing. slurry. manure. Urine

INTRODUCTION

Animal production systems are the major source of atmospheric NH, in Europe (Buijsman et nl., 1987). Deposition of this NH, may contribute to undesired changes in oligotrophic ecosystems (Schulze er nl., 1989) and volatilization reduces the nutrient value of animal manures.

Previous studies have assessed the magnitude of NH, losses at a large scale and the specific contri- bution of agriculture (e.g. Buijsman et nl., 1987; ApSimon et nl,, 1987; Jarvis and Pain, 1990). Esti- mates of agriculture's contribution difier widely (Lee and Dollard, 1994). indicating the need for improved information. Others have considered the losses asso- ciated with specific on-farm sources such as animal housing (Janssen and Krause, 1990) or waste storage (Olesen and Sommer, 1994) or farming practices such as slurry spreading or grazing (e.g. van der Molen et a!., 1990; Pain er al., 1989; Jarvis et al.. 1991; Sommer et al.. 1991). On-farm NH, sources are often linked, as. for example. where excreta are voided in animal housing. transferred to a slurry store and then event-

ually applied to the land. Assessing the true impact of control measures designed to limit NH, loss requires a whole farm approach. Earlier models capable of simulating NH, volatilization at the farm scale have been static (Hansen et 01.. 1990) and often embedded within models of the whole N economy (Scholefield et of., 1991; van de Ven, 1992). There is a need for a dynamic model which focuses closely on NH, vola- tilization at the farm level if detailed estimates of the NH, losses from livestock farms are to be obtained and the true efiectiveness of control measures as- sessed. The first version of such a model is presented here.

MODEL STRUCTURE

The model simulates NH, sources on grazing livestock farms or the part of mixed enterprise farms that is used for grazing livestock. The model tracks the N input as animal feed until it is lost by volatilu- ation or the area of land on to which it was depos- ited/applied ceases to be an active NH, source. The routes of N Row within the model are shown in Fig. 1.

i

I

. 'i

1

590 N. I. HUTCHINGS er nl

forage/fssd N

4 Animals

H o u s I n g _.+ NH3

slurry deposition application

Field

Fig. I . The major routes for nitrogen Row In the NH, vola- tilization model.

Three general assumptions are made: (a) the live- stock are managed and behave as a single flock or herd, (b) volatilization of ammonia is nowhere limited by urease activity and (c) where two sources occupy the same land area in sequence, the second source does not interact with the first.

The model operates with a daily time step o r less as losses are often nonlinearly related to environmental parameters, so estimating losses using a weekly or monthly figure could lead to serious error in the estimates of NH, loss.

A generaked NH, source

The sources of NH, on a farm share a common feature. The NH, is volatilized from the surface of an aqueous solution of NH; and is then transported through a pathway with a finite resistance t o the free atmosphere. Ignoring the concentration of", in the free atmosphere, the volatilization of NH, from an aqueous solution x ( A x ; kg d-') can be described as

where a, is the surface area of solution exposed to the air (m'). TAN, is the total aqmoniacal N (TAN) in solution x (kg m-'), Q, is a dimensionless equilibrium coefficient determining the NH, gas in the air for a given concentration of TAN in solution x , r , is the resistance to NH, transvort between the surface of solution x and the free atmosphere (d m-I), V , is the

mass of the solution (kgm-'j and 7 is the drnslcy 01 the solution, assumed here to have the same value water (loo0 kgm-'1. This relationship is used as the basis for submodels of all the major sources on the farm.

Following Sherlock and Goh (1985a). Q. can be described as

where K,,,is theHenry'slawcoefficient and .K%,,.., is the dissociation coefficient of ammonium:

where 0, and pH, are, respectively. the temperature ("C) and pH of the liquid. The resistance to trmsport (rr) will vary between sources, as described i n detail below.

The rate of NH, loss predicted by equation ( I ) is very sensitive to the pH over the range comnionly encountered in urine and slurry. The pH of slurry and urine changes with time of exposure to air as NH,. C 0 2 and H,O are lost. Also, the relationship between volatilization and initial pH varies between slurries due to variations in the buffering capacities of thc liquids (Husted er a/., 1991). At present the changes with time and variation between slurries cannot be easily predicted. The approach adopted here is to simulate A, as a function of the initial value of pH, using equation ( I ) . Although the rate of loss is allowed to vary between the types of source, it is accepted that differences in buffering capacity will lead to error in simulating volatilization within a type.

An index of symbols is shown in Appendix A.

ANIMAL SUBMODEL

The use of equation (1) requires the quantity and form o f N and the volumeofurinelslurry to be known for each source. The faecal dry matter production must also be calculated as the solids content of slurry influences the NH, lost after land application.

Faeces

(Df.,; k g D M d - ' ) is The daily faecal dry matter output on the farm

Dr,r = StFdI - 1,) (4 where a, is the apparent digestibility of the feed (kgDM(kgDMj-'), S, is the number of animals on the farm and F, is the quantity of feed eaten per animal (kgDM animal-I).

Faecal N is mainly of microbial origin (SCA. 1990) so the concentration of N in faeces varies little in response to variations in that of the feed. We assume a constant N concentration in fae@ (CY; kgN(kgDM)-'). The faecal N production

LV,,,: 1

l h e \I

\dlerc neigh.

[;rive

Thc culi ltr :initmi

where

:inim:i (kg k p :tnd I

(kg N Thc

Illy (1

wherc is the :and I,

It h

durr) Kroo here to th, mim: Scrar Iosse! on t h .1\\ur only " I , , :

used thou: hefor

Stl hour and Ntha these the f, ioos 10 se atur, at a cons port

lust r

. ,.

A model or ammonia volatilization from a grazing livestock farm 591

11

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e

1s

2

5

t )

'I

1 ; I

3

'2

I

1

S

i

, 1 t I

I I

I

i

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I

I I

i

I

( N , , , ; k g N d - ' ) can be calculated as

Nr., = Dr,r~r. ( 5 )

The water contained within the faeces (V, , , ; kg d- ' ) is

Vc.8 = &.,8 (6)

where the faecal moisture content p (kg (kg dry weight)-') is assumed to be a constant.

Urine The urinary N production (Nu,,; k g N d - ' ) is cal-

culated by subtracting the N partitioned to milk, new animal tissue and faeces from the total intake

where ch,, is the N concentration in the feed sup- ply (kgN(kgDM)- ' ) , M, is the milk yield (kg animal"d-'), cm is the N concentration in milk (kgkg-I), K, is the empty body weight gain (kgd- ' ) and c, is the N concentration in new tissue (kgNkg-').

The mass of urine produced (Vu,,; kgd-I) is

where u, is the urination rate (kg urination-') and ur is the frequency (urinationsanimal-'d-'). Both Y.

and ur are assumed to be constants.

A M h l O N I A LOSSES FROiM A N I M A L HOUSES

I t has been shown that similar amounts of", are lost per unit area from the floor and the surface of slurry stored beneath the floor (Voorburg and Kroodsma, 1992; Oosthoek et 01.. 1990). It is assumed here that losses occur from an area ( a , ; m2) equal to the sum of the area of flooring occupied by the animals and the surface area of any slurry storage. Scraping the floor is assumed lo have no effect on losses as a thin layer of manure is assumed lo be left on the floor after scraping (Oosthoek et ai., 1991). It is assumed that the NH, emitting surfaces are formed only by freshly voided urine so TAN,,, = Nu,8 and VI , , = Vu,,. The effect of diluting urine with any water used for washing animals or flushing is ignored, al- though this water (Vw,8; kg d-') is added to the slurry before it is passed to the slurry store.

Studies have shown that NH, loss from animal houses is related to the indoor temperature (Muck and Richards, 1983; Burton and Beauchamp, 1986). Although this would be expected from equation (3), these losses are also due to increased ventilation, as the farmers try to limit the rise in indoor temperature (Oosthoek et nl.. 1990). There appears no simple way to separate these direct and indirect effects of temper- ature. The equilibrium coefficient (e,.,) is calculated at a temperature of 20°C; temperature effects are considered together with the resistance to NH, trans- port (below). The pH is assumed to be that of urine

(a model input) unless floor washings are artificially acidified, when the target pH is used.

The air flow pattern transporting the NH, outside the housing is a complex function of both house design and ventilation strategy (Janssen and Krause, 1990). For simplicity, the resistance to transport (r , , , ; d m-') is simulated using a relationship found by Manneheck and Oldenburg (1991) which relates loss to the temperature of ventilation air, which we equate to the mean daily air temperature outside (8,; T). The losses reported by Mannebeck and Oldenburg (1991) are here normalized by the loss at 20°C and multiplied by a housing-specific constant (X,) to obtain r , . , for both naturally and artificially ventilated housing:

r , . , = X,(I - 0.027 (20 - 0, ) ) . (9)

The housing-specific constant is used to adjust losses to match observed values. This relationship combines the effect of outside temperature on inside temper- ature, of ventilation rate and the effect of both inside temperature and ventilation rate on NH, loss. The loss from animal housing ( A l , , ; kgNd-') is then

where H, is the proportion of the day during which the animals are housed. This submodel assumes that there is no interaction between faeces and urine (no buffering) and that losses are confined to the propor- tion of the day during which the animals are housed.

A M M O S I A LOSS FROM STORED SLURRY

The surface area of the source (a2 ; m') is assumed to be that of the slurry store. The TAN is evaluated as the amount of ammoniacal N in the store (TAN,,,; kg) and the volume by the volume of slurry present ( V z , , ; kg). Mineralization of slurry organic N is ignored. The use of bulk parameters will not accurately reflect conditions at the slurry surface but pH changes and stratification within the slurry are too poorly understood to predict with accuracy (Ole- sen and Sommer, 1994). A compromise is made by introducing a store-specific resistance to adjust the predicted loss to match empirical data (see below).

The equilibrium coefficient (e2. ,) is calculated equating the surface temperature to air temperature whilst the pH is assumed to be the mean for the whole store. Stratification will also introduce inaccuracies in Q2,, and these are also partially overcome by the store-specific resistance.

The wind speed affects the resistance to transport of NH, ( r z , , ; d m - ' ) through its effect on the aero- dynamic resistance to transport from the slurry surface to the free atmosphere. Following Olesen and Sommer (1994), r2 . , is made the sum of a boundary layer resistance (rb.,; d m- I). an aerodynamic resist- ance (r . , , ; dm- ' ) , a cover resistance (re.,; d m - ' ; the

592 N. I. HUT<

Table 1. Surface resistance for a range 01 coverings for slurry store^

Cover resistance C o w type (dm-' x lo-')

0

Crust 2.13

Calculated from data in Sommer et (11. (1993).

resistance of the ith slurry surface covering) and a store-specific resistance (rT; d m-I). The values of rb., and r,,, are determined in the manner described by Olesen and Sommer (1994) and then converted to daily values. The assumptions of adequate fetch and neutral stability that underlie this approach are un- likely to be met in full within a slurry store. This inadequacy is overcome by the use of the empirically determined store-specific resistance. The value of r c , , for a variety of materials used for covering the slurry surface has been determined empirically (Table 1).

The rate of loss of NH, from stored slurry ( A 2 , , ; kgNd- ' ) is

Ifthestoredriesout ( V I , , falls tozero),all the remain- ing TAN is assumed l o volatilize but the dry matter remains.

Loading frequency and poricion

Ammonia loss rates are increased if fresh slurry is loaded on to the slurry surface as this increases the concentrations of NH: in the surface layer and dis- rupts any crust. Loss rates then fall over the sub- sequent 24-48 h as NH,' in the surface layer is de- pleted and a crust re-forms. This effect is incorporated within the model by reducing the cover resistance to zero for the day on which slurry is added to the surface of the store.

AMMONIA VOLATILIZATION DURING APPLICATION OF SLURRY

Micrometeorological measurements have shown that losses during application using conventional

:HINGS et (11.

u9901 found losses of up to n e a v

e TAN when usine an irrie greater losses in this 1att-h due to the measurement technique used. We assume a proportion, n, of the applied TAN is lost during application.

In the presence o f a crop and when application is by broad spreader, a proportion of . the slurry will be intercepted by the plant canopy. It is assumed that an amount 7 (kgm-') of the slurry applied by broad spreading methods to planted land is intercepted by the crop. We assume there will be no direct foliar absorption and that all the TAN in intercepted slurry will be lost by volatilization.

Ammonia volatilized during spreading ( A s , , : kgNd-') is:

for spreading to land with a crop

for spreading to bare soil

where R 2 . , is the mass of slurry applied (kg) and a, , , is the area covered by the slurry (mz).

AiMMONlA LOSS FROM APPLIED SLURRY

Unlike the sources in animal housing and manure storage, the source within an area to which slurry has been applied is not replenished. As a result, the rate of loss from surface-applied slurry is commonly highest shortly after application, declining rapidly thereafter (e.& Pain et al.. 1989: S u e r er ai., 1991; Sommer and Ersbdl. 1994). The slurry NH,' at risk of loss decreases with time through volatilization and through infiltration into the soil. The NH: that enters the soil becomes bound with the soil's cation ex- change complex and is largely protected from volatil- ization. Here we identify the mass of slurry from which volatilization can take place (V4,,. kg) to be on or very near the soil surface. This mass is reduced by infiltration and evaporation and increased by rainfall. The TAN in this mass is decreased by volatilization and infiltration. Any upward movement of NH: in the soil is ignored. The etTect of rainfall on NHI volatilization has been included as empirical data suggest that this is important (Beauchamp et 01.. 1982). The volatilization from slurry applications is described in Appendix B.

spreaders, trail hose application and a cable-driven

ation during application to be less than 4 % of the TAN applied. However, Boxberger and Gronauer - -

/

Efect of applicafion and cultiuarion methods Ammonia losses from slurry vary depending on the

choice of application or cultivation technique. The -mechanisms by which the different techniques affect loss vary. For example, rotovating the soil Surface

- Trua:

PX.2 Trail Sod : Deer

-

- 'R

unde

prio ing whil app' VOlL

(ea . The the sho,

v

dec; m u cult sim afte

app

(AP

API c

for SlUl

Fii in (e:

fill "0

A model ol ammonia volatilization kom a grazing livestock farm 593

Table 2. Adjustments made to properties of slurry applications to reflect eiiects of different cu~tivationr

Treatment Adjustment Sources'

Pre-application harrowing Increase I . by 220% Sommers and E r s b l l (1994) Trail hose application Sod injection Deep injection

Reduce o1 by 30% Reduce V,. TAN, and D, by 90% Reduce V,, TAN, and D, by 99.5%

Dohler (1990) and Bless el 01. (1991) Klarenkck and Bruins (1991) Klarenkck and Bruins (1991)

'Representative figures were taken from a few sources lor demonstration purposes; an extensive revicw W a s not undcrtakcn.

'plied h the been jume uring

: is by i l l be !at an >road :d by ioliar h r r y

' ,A , ,# ;

(12)

(13)

a,.# is

.anure r! has -ate of ishest -salter .mmer .I loss ! and enters > n ex- olatil-

from be on

Led by .iinfall. .zation H; in : NH, .I data 91 af., ions is

on the .s. The < affect iurface

prior to application appears to reduce loss by increas- ing the infiltration rate (Sommer and Ersbell, 1994) whilst any reduction achieved by injection or post- application cultivation is due to a reduction in the volume and area of slurry exposed to the atmosphere (e.g. van der Molen et al., 1990 Chardon et of., 1990). The relationships used within the model to simulate the effect of application/cultivation techniques are shown in Table 2.

Where cultivation does not occur immediately after application, the potential for reducing losses is decreased (Klarenbeek and Bruins, 1991) and losses must be partitioned between the pre- and post- cultivation periods. This is achieved by separately simulating the losses for the periods before and after cultivation, using equations (87) and (B8) (Appendix B).

Applied slurry losses submodel

Given that slurry applications can be NH, sources fo ra number ofdays, the total NH, loss from applied slurry on day I is

4,,= Aa.6.r (14) 6- L

where A+.,, is the volatilization on day t from an application made on day b . Volatilization is followed until V4,b , , falls tozeroor theTAN,,b., < 10-'kgm-2.

Behaviour OJ submodel

The behaviour of the applied slurry submodel is illustrated in Fig. 2. Note that the effect of varying the difference between rainfall and evaporation rate in- creases with increasing solids content of the slurry. In fact, for a slurry with no solids, rainfall and evapor- ation rate increase and decrease, respectively, the duration of volatilization, but if all other factors re- main constant, neither has an eRect on the cumulative loss from a given application.

AMMONIA LOSSES FROM URINE PATCHES

Ammonia losses from grazing animals vary with the environment (Whitehead and Raistrick, 1991) and with thelevel of fertilizer N applied(Jarvis et af.. 1989; Bussink, 1990). In N. Europe, the proportion o f N ex- creted during grazing that is volatilized is generally small (around 10% or less), but is significant in abso- lute terms as excretal N flows can be large (Scholefield er af., 1991).

The losses from urine patches are treated in the model as though they were slurry applications with a zero solids content. N o allowance is made for the time taken for urea to hydrolyse to NH:. However, as with broad spread slurry, an amount q is assumed to be intercepted by the grass crop and all the NH, within it lost. There is good evidence that this makes a n important contribution to losses from urine patches (Sherlock and Goh, 1985b; Whitehead and Raistrick, 1991). The urine contains no suspen- ded solids so a time step of 1 d is used during the simulation.

0 so 100 1M 200

Slurry dry matter (g DM kg-')

TOTAL LOSS FROIM THE FARM

Thetotal NH, loss from tbefarm(A, , ; kgNd- ' ) i s

Fig. 2. The volatilization of NN, as affected by dry matter (15) ,=, in the slurrv for five values of excess rainfall

594 N. 1. HUTCHINGS et 01.

Appropriate parameter values were either obtained from the literature or estimated by fitting submodel predictions to observed values. In each case, the data source is shown in Appendix A.

N o attempt has been made t o validate the model. Although estimates of farm emissions of NH, based on N balance models are available (Jarvis, l993), the authors are unaware of any data set that would allow the model to be validated at the farm scale. The presence within the housing and slurry store sub- models of specific house and store factors precludes validation in these cases. The slurry/urine submodel could be validated if a data set could be obtained in which both pH and infiltration rate were measured over the duration of volatilization. The submodel predicts responses to environmental factors that agree qualitatively with those in the literature. The predic- tions are within the range of values found in the literature, but such is the breadth ofthat range that it would be difficult to d o otherwise. There is an urgent need for simultaneous measurement of ammonia losses from the various on-farm sources over periods of weeks or months.

EXAMPLE SIWJLATIONS

Type oflioesrock system

The model was used t o simulate the NH, loss from two contrasting types of livestock systems, beef cattle and dairy cows, under the same weather conditions. The quantity and quality of feed and animal growth or milk production for each system are shown in Table 3 and were based on examples given in SCA (1990). The stock number within the dairy system was chosen such that the annual N input to both systems was the same, The duration of the simulation was I yr, starting on I November and with an empty slurry store. Daily weather data were obtained for the Foulum Research Centre, Denmark, for 1991-1992; mean temperature 7.8"C. total precipitation 730 mm

and mean wind speed 3ms- ' . The evapor:tlion r.lIc was equated to the potential evapotranspiratian r.llc

(annual total 405 mm). During the grazing ,dLI!< 180 to 365 inclusive), the beef cattle weru not hntlrnf whereas the dairy cows were housed for 8 h d - I

The slurry utilization strategy aimed t,, s i n , t l ~ a l c applications to spring and autumn sown cercill crc,p, or spring grass whilst also encompassing :I r:lnpc ,,r environmental conditions. Slurry applicatintts made within both systems at intervals of 5 d irom d:ly 200(17May)atarateof30m'ha- ' uniilihcslurry store was emptied (day 240 and day 225 for tile hyf and dairy systems, respectively). The first three plications in the spring were made to bare soil. tile remainder to fields with acropcover. Within the ditir? system, the slurry that accumulated over t he gruiti8 period was fully utilized by further applic;ttions 10

bare soil. beginning on day 345 (IO Oclohcrl and finishing on day 364 (30 October).

The N excretion per dairy animal (121 kgNyr ' I was a little higher than the 108 kgN yr-' ohl:tincd from the regression equation of Kirchgessner ct ,a1. (1991). The equivalent value for the heel c:~tt Ic (40kgNyr- ' ) is intermediate between the ligtircs for calves and young cattle found by Mandenloot (1992). The ammonia loss from the beef and dairy systems represented 10 and 21%. respectively. of thu N excreted, These are lower than the 24 and 27% calculated in ECETOC (1994), reflecting the highcr dietary N-concentration assumed in the laller rcport.

Over 6.5 times more NH, was lost per dairy :tnitn:Il than per beef animal (Table4a), emphasizing the nccd to disagregga1e national animal numbers into dilicr- ent functional classes. The diferences cannot he rc- moved by using simple scaling factors such :Is i l l -

take or body size because they arise from SYSten1:lllc variations in animal intake, feed quality nnd farm management.

A greater proportion of the N input to the d:lirY system was lost than from the beef cattle system (Table 4a). Despite a greater export of N in milk than

Table 3. Characteristics of the example beef cattle and dairy systems

Beef Dairy

Number Feed intake Dieestibilitv of feed

1w 21.8 kg animal- 'd- ' 1.5 16.6

% 70 15 N ;n feed . Yo 1.6 2.6

0 18.8 Milk production kg anima1-ld-l

3.3 m2 animal-'. pH,,, 8.0, V.,, 333 kgd-'. slurry transferred to store weekly; slurry Store: 01 18.9m2. pH?,, 1.1, 0, ZSOm', no surface covering. filling location a1 fop: spreading: n 0.02. application: pH.,, 7.1. 1, 230kgm-'. slurry applied by broad spreading, grazing: pH,,, 8.0.

Valuer for urine pH are intermediate between those of urine and Urine- treated soil (Hayner and Williams, 1992) or slurry(Sommer and Olesen. 1991). The remaining values are derived frorn dam i n SAC (1989). Sommer and Olesen (1991) and Lilly (1994).

Animal growlh kganimal-'d-' 0.6 o

Characteristics common to both systems: housing:

system

I h i r y

- tlcer - - Conlrol I

BWJ - A R C D A + C +

Doiry A R C D A + C i

Can1r expand?

in anin dairy s N was I tion of beefs! soil vii or thr offers prolor housir were t

hand1 butioi dairy a per volati

€ffecr Thm

alteri (e+. (

e e s d

.e

I f

-e ? 'Y :I

ie 'V g

d

'S

I.

0

' 1 d 84.

le :S

21

'Y le % :r

21

:d r- e- n- ic m

.I.

ry m i n

A model o i ammonia volatilization lrom a grazing livestock farm 595

Table 4. Predicted annual losses of NH,-N from the two livestock farming systems described in Table 3

(a) Total annual inputs. outputs and losses for each system ~~~ ~

N input Total N N in TAN NH,-N % o l N Loss per per animal input milkltissue excreted lost input animal

Svstem ( k d (ks) ( k d I k d (kR) lost 0%) .

Beef 44 4380 416 1869 484 11.0 4.2 Dairv 138 4379 101 I 2299 710 16.2 25.5

(b) Distribution of losses

Ammonia source ( O h )

System Grazing House Storage Spreading Applied

Beef 25 9 28 3 36 Dairy 14 7 47 3 29

Table 5. ERcct of applying control measures on NH, IOISCS from the bcelcattle and dairy systems

Ammonia losses (as percentage of losses without control measures)

Control measure Grazing House Storage Spreading Applied Total loss

Beef A B C D A + C + D Doiry A B C D A + C + D

100 100 1w I 0 0 100

100 100 100 100 100

68 100 100 IW 68

70 100 IW 100 70

102 41 33

100 33

101 53 55

100 56

107 I I4 114

0 0

IW IO 113 0 0

to1 111 I62

9 I5

101 I13 189

9 19

98 84

to4 64 45

99 83

106 70 51

Control measure: A, reduce floor and store surface area per animal from 3.3 to 2.3m'; E, cover slurry storage with expanded clay; C, c o w slurry storage with lid: D, apply slurry by rod injcctian.

in animal tissue, the higher quality of feed used in the dairy system meant a greater proportion of the feed N was excreted as TAN. In addition, a greater propor- tion of this TAN was lost from the dairy than from the beef system (33% vs 26%). The TAN can pass t o the soil via two routes: deposition as urine during grazing or through the slurry handling system. The latter offers greater opportunities for N H 3 loss owing t o prolonged exposure ofthe slurry surface in the animal housing, storage and after application. The beef cattle were not housed during the summer so the slurry handling system was inactive, lowering its contri- bution to the total loss (Table 4b). In contrast, the dairy slurry handling system was active throughout a period 'when the environmental conditions for volatilization were most favourable.

Effectiveness oJconrrol measures The losses from animal housing can be reduced by

altering the design and management of the housing (e.g. Groenestein, 1994) whilst those from storage can

be reduced by covering the slurry store (e.g. d e Bode, 1991: Sommer et al., 1993). The effectiveness of both methods was tested (Table 5). EKective reductions in the losses from animal housing or slurry storage were less effective in reducing losses from the whole system. I n most cases, this was because the reduction in loss led to a n increase in the concentration of TAN in the slurry so there was a n increase in losses from sub- sequent sources.

The consequences of using a lid on the slurry store were more complex. In this case, in addition to retain- ing more TAN in the slurry, the lid prevented rain- water entering. This raised the solids concentration in the slurry and, at the time of application, reduced the rate of infiltration into the soil. The eKect of this was to increase volatilization from the applied slurry so the use ofa lid on the slurry store had little impact on the total loss from the whole system.

Slurry injection was the most eKective single method of reducing losses proportionately more so in the beef than the dairy system because losses after application were of greater importance. Even greater

596

reductions were possible when a combinat ion Of SeV- Buijsman E.. Maas H. F. M. and A~~~~ w. A, 11, IIu,:l era1 control methods was used, a l though the differ- Anthropogenic "3 emissions i n Europe. . ~ l n , , , s r h ~ . r , ~ .

ence between the beef and dairy systems persisted. Enuironmenr 21, 1009.1022. Burton D. L. and Beauchamp E. G. (1986) ~ i ~ ~ ~ , ~ ~ ~ These interactions between "3 sources high- from swine housings. Ayric, ,,,asrur 15, 59.7,,

light the need t o consider the fate ofexcreta at a f a rm Bussink D. W. 119901 Ammonia volat i~izal ion fr,,,,, ~ , , ~ l ~ . level when assessing the effectiveness of control Iionally grazed sward. 1. EfTectsofmana.cm,.n, , ~ " ..I-.. ,

N. J. HUTCHINGS ei 01.

measures.

Chardon W. J.. van der Molen. J. and van Fnasrcn 11, <; (1990) Modelling ammonia emissions from amble lil,,d, Ammonia and Odour Emission jrom Liwsruck p ,,,, 1 (edited by Ncilsen. V. C., Pain B. F. and H a r t u n f J.,. rp 156165. cEc,

de BodeM. J.C.(199I)Odourand ammaniaemirs i~rn~,r l lm manure storage. 0dou, E,,,i,$ri ,,,, ~ ,i ,,,,, Livesrock Produrrion (edited by Nielsen v. c.. v ~ , ~ , , ~ , , , ~ J. H. and L"ermit6 P.), pp. 59-66, Elsevier A, ,~ I ,~J Science. London

decomposition and release of nutrients from ~ ( 1 ~ ,,,,I\, New Ph,ro,ogisr 115, 139-147, ohler H. (1990) Laboratory and field experimcnts f<,, mating ammonia losses from pig and cattle slurry fdl,,u. ing application. In Ammonia ond Odour Emi.vsicm I r , ~ r , ,

CONCLUSIOSS

T h e substantially greater loss of NH, per animal f rom dairy cattle t han from beefcattle emphasizes the need t o distinguish betweendifferentclassesofanimal when calculating losses on a farm, region or nat ional scale. T h e use of dynamic models such as the present one is a means by which emission factors can be

actions that occur within and between the various

,+,,mania

amended, T h e model highlights the complex inter- Dickinson c. H. and Craig G. (1990) EffCCIS Of W.ller I11c

sources of", on livestock farms. These interactions will modify the erectiveness of control measures a n d the model clearly demonstrates that it is imDOrtant to consider the fate o f excreta a t a farm level when assessing such measures.

T h e model requires improvement, particularly t o the simulation of losses from housing, of chemical transformations within the urine and slurry and of slurry infiltration. A sensitivity analysis a n d a review of parameter values a re required. Inclusion of the losses that occur from solid manures is also a priority as m a n y livestock farms still handle animal wastes in this form. All the control methods considered led to a n increase in NH: entering the soil. This NH: will enter the soil N cycle and increase the potential for other pollution, e.g. NO3 leaching or loss of N20 to the atmosphere. This emphasizes the need to adop t a holistic approach 10 farm N management,

Arlmoaledy~menrs-This work was funded by the Scottish Office Dcpartmcnt of Agriculture and Fishcrier. Edinburgh, the Ministry or Environment, Copenhagen. and the Ministry of Agriculturc. Fisheries and Food, London.

REFERENCES

Liiesioek Producrion (edited by Neilren V. C.. Plin H. I.. and Hartung J.), pp. 132-140. CEC. Brursela.

ECETOC (1994) Ammonia emissions to air in Wurtern Europe. Technical Report No. 62. pp. 1-196. ECETOC'. Brussels.

Croencstein C. M. (1994) Animal-waste managrmeni ;and emission ofammonia from livestock housing ryrtemr: licld studies. I n Liuesrock Enoironmenr I V . 4th Inr Sjnip.. Uni. versity or Warwick. pp. 1169-1175. American Socicty uf Agricultural Engineers, St Joseph. Michigan.

Hanren J. F.. Olercn J. E.. Munk I., Heniur U. M.. Hoy. J. I.. Rude S.. Slefenren M., Huld T., Guul-Simonsen I... Danfaer A,. Boise" S. and Mikkclsen S. A. (1990) Nitrogen in animal manure. Beretning No. S2100-1990. pp. 1-127. Danish lnsrilutc of Plant and Soil Scicnce (in Danish).

Haynes R. J. and Williams P. H. (1992) Changer in soil solution composition and pH in urine-affected arcar of pasture. J . Soil Sci. 43. 323-334.

Husted S.. Jcnscn L. S. and Jsrgcnrcn S. S. (1991) Reducing ammonia loss from cattle slurry by the use of acidifying additivcs: the role of the buffer system. J . Sri. Fd Ayric'. 57. 335-349.

Janssen J. and Krause K..H. (1990) Mcssun und simulation yon ammoniak koncentrationen i n stillen. In Ammonicrk in der umwell (edited by Dohler H. and van den Weghr 14.1. pp. 21.1-21.12. KTBL-Schriften-Vertriieb im Landwirt- schaflsverlag GmbH. Miinster-Hiltrup.

Jarvis S. C. 119931 Nitroecn cvclinz and losses from dairy ~, . ~-~~~ ~1 ~

rams. Soil Use Mnnagemenr 9.99-105. ApSimon H. M.. Krurc M. and Bell N. J. 8. (1987) Ammonia ,+vis s. c. and Pain B. F. (1990) Ammonia volatilization

emissions and their role i n atmosphericdeparition. Armo- from agricultural land. proc. No. 298. p. 35. The Fcrtiliscr spheric Enuironmenr 21, 1939-1946. Society. London.

Arman W. A. H. and van Jaarsveld H. A. (1991) A variable Jarvis s. c . , Hatch D. J. and Roberts D. H.(1989)ThceRect~ resolution transport model applied for NH. i n Europe. of grassland management on nitrogen losses from grazed Armosphwie Enuironmenr 26A. 445464. swards through ammonia volatilization; the relationrhlp

Besuchamp E. G.. Kidd G. E. and Thurtell G.11982)Ammo- to excretal N returns frorn cattle. J. ogrir. Sci., Camb. I 12- nia volatilization from liquid dairy cattl manurc in the 205-216. field. Con. J. Soil Sri. 62, 11-19. Jarvis S. C.. Hatch D. J. and Lockycr D. R. (1991) hlicro-

less H. G., Bcinhaucr R. and Sattclmachcr B.(1991) Ammo; meteorological studies of ammonia emission from grazed nia emission from slurry applied to wheat stubble and swards. J . ogric. Sci., Comb. I l l , 101-109- rape in North Germany. J agrie. Sci.. Camb. 117,225-231. Kirchgessencr M., Windis& w. m d Krcuzcr M. (1991) Stik-

Borberger J. and Gronauer A. (1990) NH,-emission wah- stomemission laktierendcr Milrchkuhe uber die G U k In

rend der Aursigmistaur b r i n x In Ammoniak in der Abhangigkcit yon der Leistungsintenritat. Agrobiol. Res. umwelr. Krrislaufe. wirkungen. mindenrng (edited by Dahlcr 44, 1-13. H. and Van den Weghe H.), pp. 42.142.5. KTBL-Schrif- KI rcnbeek J. V. and Bruins M. A. (1991)AmmOniaCmi~~ion ten-Verfricb im Landwirtrchalts vcrlag GmbH. Miinrter- d r i e r land spreading slurries. In Ammonia and

Odour Emissions jrom Lirenock Produrrion (cdltcd by

o d

Sieisen V. C pp. 107-115. I

I es I). S . and D I

,slim~ter of e J,,,I~. Emir. P

~ i ~ l y A. 11994) T conducljvi

pcrrncameter. ~landerslaot F.

ins rtikrtofve prdstatian ' en paardcnhc

hlannehcck H. i &ct of differ, <,nd Ammonia Niclsen V.C.. Elrevier Appi

h ( u ~ k R. E. ant nitrogen in fr

olcstn I. E. an: wind speed a from stored 2 j67-2574.

Ousthock J., K T hchemassnah sionen B U S 51

DGhler H. i

KTBL-Schril GmbH. Mur

Oarthoek 1.. K nia emission ! and Ammonic Niclren V. pp. 3141. E

Pain B. F., Ph J. V. (1989) I tion during slurry 10 gra

Phillips V. R.. I aKecting the after land 11 Odour Emis Nielscn V. ' 98-106. Elsr

SAC119891 In by Chadwic burgh.

SCA (1990) Fr mimnrr. pp. Victoria.

Scholcfield D. K. C. (1991)

165-177. Schulrc E.-D..

L.. Tamm 1

of nitrogen

nitrogen dc Poll. 48.45

Sherlack R. I monia vola aqueous u n of simplifie

Sherlock R. R nia volatili; ous urca ap plified mod

Sommer S. C ammonia Pla,rreovl. E English).

Sornmer S. C conrent an applied cat

A model of ammonia volatilization from a grazing livestock farm 597

1987) "ceric

losscs

rota. nnual :d by P W S .

H. G. nd. In :(elion .I. pp.

i from : fiom rburg ,plied

,n the pats.

r esti- )IlOW. Jrom B. F.

estcm TOC,

t and i: field Uni-

ety of

', J. J.. n F., rogen 1-12), ;sh). n soil ear O f

k i n g lifying -ir. 57,

ilation mioniok he H.), dwirt-

dairy

zation rtiliscr

effects ;razed ,mship h. 112.

vlicro- :razed

I Stik- ilk in I. Res.

isrion 'o and xi by

Niclscn V. C.. Voorburg J . H. and L'Hermit; P.). pp. 107-1 15. Elrevier Applied Science. London.

Lee D. S. and Dollard G. J. (1994) Uncertainties in current estimates of emissions of ammonia in the United King- dom. Eocir. Poll. 86, 267-217.

Lilly A. (1994) The determination of field-saturated hydrau- l ic conductivity in some Scottish soils using the Guelph permcamcter. Soil Use Management IO, 72-78.

Mandcrrloot F. (1992) Bedrijfseconomishe gevolgen bcperk- ing stikstolverlirren op melkveebedrijven. Report 138, Proelitation voor de Rundvechouderij Schapenhoudcrij cn Paardenhouderij, Lelyrtad.

Manncbcck H. and Oldenburg J. (1991) Comparison of the effect ofdifferent systems on ammonia emissions. In Odour ond Ammonia EmirrionE/rom Liuestock Farming (edited by Niclrcn V.C.. Voorburg 1. H. and L'Hcrmit; P.). pp. 42-49. Elsevier Applied Science. London.

Muck R. E. and Richards B. K. (1983) Losses of manurial nitrogcn in free-stall barns. Ayric. Waster 7, 65-79.

Olesen J. E. and Sommer S. G. (1994) Modelling effects of wind speed and surface cover on ammonia volatilization from stored pig slurry. Atmospheric Encironmmt 17. 2561-2574.

Oosthoek J . , Kroodsma W. and Hoekrma P. (1990) Betrieb- lichcmarrnahme zur minderung von ammoniakemis- sionen aus stallen. In Ammoniok in der umwelt (edited by Dohler H. and van den Weghe H.), pp. 29.1-29.23. KTBL-Schriftcn-Verlrieb im Landwirtschaftsverlag GmbH. M\inster-Hiltrup.

Oorlhoek J.. Kroodsma W. and Hoeksma P. (1991) Ammo- nia emission from dairy and pig housing systems. In Odow and Ammonia Emissions/rom Lioerrock Farming (edited by Nielsen V. C.. Voarburg J. H. and L'Hermit; P,). pp. 31-41, Elrevier Applied Science. London.

Pain 8. F.. Phillips V. R.. Clarkson C. R. and K lareokk J. V. (1989) Loss of nitrogen through ammonia volatilisa-

slurry to grassland. J Sri. Fd Ayric.. 47, 1-12. &? tiun during and following application of pig or cattle

Phillips V. R.. Pain B. F. and Klarenbeek 1. V.(1991)Factorr affecting the odour and ammonia emissions during and after land spreading of animal sIurrics. In Ammonia and Odour Emissions /rum Liuestork Producrion (:dited by Nielscn V. C.. Vaorburg J . H. and L'Hemite P.), pp. 98-106. Elrevier Applied Science. London.

SAC (I9891 In Form M o n o y ~ m m r Handbook 1989/90(edited by Chadwick L.). Scottish Agricultural Colleges, Edin-

J

burgh. SCA (1990) Fceding Stondardsjor Ausrralian Lioesrock. Ru-

minants. pp. 1-266. CSlRO Publications, East Melbourne, Victoria.

Sommer S. G . and Ersbell S. K. (1994) Soil tillage effects on ammonia volatilisation from surface applied or injected animal slurry. J. Emir. Qual. 23. 493-498.

Sommcr S. G.. Olcsen J . E. and Christensen B. T. (1991) ERects of temperature, wind speed and air humidity on ammonia volatilization from surface applicd cattle slurry. 1. ogric. Sci.. Comb. 117, 91-100

Sommer S. G., Christensen B. T., Nielscn N. E. and Schjem+~g, J. K. (1993) Ammonia volatilizalion during storage of cattle and pig slurry: eKect of surface cover. 1. ayric Sci., Comb. 121, 63-11.

Svensron L. (1994) Ammonia volatilization following ap- plication of livcstock manure 10 arable land. J . ogric. Enyny Res. 58, 241-260

Van de Ven, G. W. 1. (1992) Grasmod, a grassland manage- ment model to calculate nitrogen losses from grassland, pp. 1-109. Centre for Agmbiological Research, Wagenin- gen.

van dcr Molcn I., Bciljaars A. C., Chardon W. J.. Jury W. A. and van Faassen H. G. (1990) Ammonia volatilization from arable land after application of cattle slurry. 2. Deri- vation of a transfer model. Neth. I. agric. Sci. 38.239-254.

Voorburg 1. H. and Kroodsma W. (1992) Volatile emissions of housing systems for cattle. Liuestock Proc. Sci. 31, 57-70.

Whitehead D. C. and Raistrick N. (1991) EKects of some ewironmental factors on ammonia volatilization from simulated livestock urine applied to soil. Biology Fcrtilify Soils 11, 279-284.

APPENDIX A NOMENCLATURE

Variables subscripted f are the values an day I. Variables subscripted x are the values far NH, source number x where source number I = animal housing. 2 =stored slurry. 3 =loses during application, 4-= applied slurry and 5 = urine patches.

A x , , NH, volatilization lrom source x (kgNd-') AF,! total loss of NH, from the farm (kgNd")

Srore aoriablur TAN,,, mass of TAN (kgm-'1 TAN,,,,,

V,, , , Vr,b,,

D x , , , D.,*

mass of TAN within slurry (x = 4) or urine ( x = 5) dcpositcd on day b (kgm-') as abovc but for the wet weight of slurry or urine (kgm") as abovc but for the dry weight ofslurry solids

Schulrc E.-D., De Vries W.. Hauhs M.. Rosen K., Rasmursen L.. Tamm C.-0 . and Nilsson J. (19891 Critical loads for nitrogen deposition on forest ecosystems. War. Air Soil Poll. 48, 451456.

Shcrlock R. R. and Goh K. M. 11985a) Dynamics of am- monia volatilization from simulated urine patches and aqueous urea applied to pasture. II. Theoretical derivation of simplified model. F'erriliwr Rcs 6, 3-22.

Sherlock R. R. and Goh K. M. (1985b) Dynamics ofammo- nia volatilization from simulated urine patches and aque- ous urea applied to pasture. 111. Field verification ofa sim- plified model. Fertilizer Re.5, 6, 23-36.

Sommcr S. G. (1989) Spreading of slurry: volatilization 01 ammonia and distribution of applied slurry. Tidskr. Planreod. 93.323-329 [in Danish: summary and legends in English).

Sommer S. G. and Olesen J. E. (1991) EKect of dry matter content and temperature on ammonia loss from surfacc- applied cattle slurry. J . Enuir. Qual. 20, 679-683. '

Model inpurs o, apparent digestibility of animal feed

(kgDM(kgDM)-') 0, outside air temperature ('C) o, area olroofing and yard that contributes water to

the slurry (m') c,,, nitrogen concentration in the feed supply

(kgN(kgDM)-') E , evaporation rate (kgm"d-') F, quantity or feed eaten per animal (kgDMani-

mal-' d-'1 H, proportion of the day during which the animals

are housed I, soil infiltration rate (kgm-'d-') K, empty body weight gain 1kgd-l) M. milk yield (kganimal-'d-') p, precipitation rate (kgm-'d-') R , ., mass of manure removed from the animal housing

lkgl

598 N. 1. HUTCHINGS et nl.

R2.f

S,

mass ofslurry removed from the slurry store to be applied to land (kg) number of animals on the farm

xrnerers and secondary auriables water content of fames (kg(kgDM)-') = 6.9' specific weight of slurry (kgm-') = loo0 volatilia.tion rate paramcter (kgm-'d-'), equa- tion (810) dry mattec added in bedding and spilt feed (kg DM animal-ld-') = 0.96'. interception of slurry or urine by crop (kgm-') -0.2t proportion of slurry or urine TAN lost during spreading = 0.02 constantsdetermining the effect olslurrysolids on infiltration concentration or nitrogen in faeces (kgN(kgOM)-') =0.025* concentralion of nitrogen in milk (kgN(kgDM)-') =0.0053f concentration or nitrogen i n new' animal tissue (kgN(kgtisrue)-l) =0.024: daily faecal dry matter output of the animals (kgDMd-I) infiltration rate during the jth lime step within an area that received slurry on day b (kgm-'d-l) minimum infiltration rate (kgm-'d-l) infiltration rate (kgm-'d- ') = 0.02 Faecal nitrogen production (kgNd") urinary nitrogcn production (kg N d - l ) villuc of the equilibrium coefficient (equation (2)) resistance to NH, transport from the animal housing to the atmosphere (dm- ' ) resistance to NH, transport from the slurry store to the atmosphere ( d m - l ) aerodynamic resistance (d m- ' ) boundary layer resistance (d m - l )

resistance or the ith slurry surface covering in the slurry store ( s m - l ) store-specific resistance (d m - ') = 0.000301$ urination frequency (urinations animal-' d - ' ) = 18 urination rate (kgurination-') = 1.6' area o r a single urine palch (m') = 0.68' mass of urine produced (kgd-') mass of water i n faeces (kgd-I) water used in animal housing for washing animals or Rushing (kg) = 33311 roofand yard runoR(kgd-') housing-specific constant = 0,00843..

Data sources: 'Dickinron and Craig (1990). tSherlack and Goh (1985b). :SCA l1990),$01esen and Sommer (1994),qvan de Ven (1992). IlHanren el nl. (1990). **Mannckck and Oldenburg ( I 990).

APPENDIX 8: THE TIME COURSE OF NH, LOSS IN SLURRY APPLICATIOSS AND URINE PATCHES

The rate of change of TAN present in the rlurrylurine remaining on the soil surface (TAN,:kgm-lj can be dc- scribed as

dTAN, QJTAN, TAN, I- IW

dr 1. v. V,

where I =infiltration rate (kgm-'d'l) and the remaining parameters are defined as in equation (I). To improve clarity.

-=

Rcarranging equation (81) gives

dt. (B31 1 ( E + 1) -dTAN, = --

TAN. V ,

The volume (V=,,; m-') changes due to infiltration, cvapor. ation and rainfall and at timer

(84) Vs,, = Vx,o - (1 + E - p) r

where V z , o is the mass at time t = 0, p = precipitation rate (kpm-'d-l) and E =evaporation rate (kgm-'d-'). Sub. stituting for V , in equation (83) and integrating gives

IBS) TAN,,, = K(V,,, - ( I + E - p)rp*'Jt''*6-pl

(86)

whcrc TAN,,, is thc TAN present at t imet = 0 (kgm-'). Volatilization and infiltration can be rapid so the loss on

each day is simulated using I small time steps ofduration Sr = 0.01 d. The volatilization during the j t h time step of day

t from slurry (X = 4) Or urine (r: = 5 ) applied on day b (Ax,b.,.;; kgNd-') is: . when ( I b , , , ; + E, - p,) = 0

K = TAN,,, ( Vz,o)-lM *JNll + F - l l l

L

= ax,b- TAN..b.,,, E + l e , , . ;

X ( l - ~ x P ~ - ~ + ~ ~ , , , j / ~ , . ~ , , , ; ~ r ) ~ 187)

otherwise

A x , b , , , ; = a x , b p TAN,,,,,,, ( I - expK*-

x (Vx,b,,, - ( I b , , , ; + E, - p, )Sr )"" ' , , " " . , ,+"~ ' ,~J E + l b , , . ;

(88)

where is the area ofapplication/depasition made on day b Im'), V.,b,,,, and lb,,,, are, respectively. the TAN present above the soil surface Ikgm-'). the mass of rlurrylurine above the soil surface (kgm-') and the infiltra- tion rate ( k g m - l d - ' ) at the beginning of the j l h time stcp for applicationsldepositionr made on day h. E, and p, are, respectively, the evaporation and precipitation rate on day r Ikgm-'d-l). E and Kb,,,, are dcfined as

Q=.~.,Y I , , , ,

E = -

). (89) K, ,,,, = In (TAN,,,,, ;( Vx,b , , , ;)-"' * ' ~ ~ ~ l ' ' l * ~ ~ + E ~ - n l l

I f Vb, , , ,+ I falls to or below zero during a time step. then

and no further volatilization takes place. The infiltration rate in the absence of slurry solids is

determined by that of the soil (I.: kg m-' d-l) . In reality. volatilization has been observed to increase with the concen. tration of slurry solids as increasing ~iscosify reducer infilt- ration (Sommer and Olcscn, 1991: Svensson. 1994). The infiltration rate is assumed Io be limited either by the soil or the slurry:

lb , , , , = min(I,.lJ (811)

where I , is the infiltration ratc determined by the slurry (kgm-' d-I). The relationship between slurry composition and viscosity is poorly understood so 1. is related directly to

the concentral

where; and p the slurry rem mer and Olese 31.9, respectiv tion ratc appr high. lcading 1 ]OW rate 01 105

tion. This was arbitrary mini

The resistai ncr outlined f< resistance. Th, temperature e assumed to be tion.

Volatilizatic blA. ,h , , ; kgd

I t t i l i d >:dues]

The masse: dcfinedat the

TAP.

The pH of th,

lnirid rulues.

The initial

V

where us is tt

Concentration of solids in V,:

iere ; and p are constants. It i s assumed that the solids in :slurry remain on the soil surface. Using data from Som-

Or and olesen (1991), < and p were evaluated as 6.950 and '9 . . respectively. With thcse parameter values. the infiltra- ;n rate approaches zero when the solids concentration is jh. leading to excessive expenditure of time simulating the w rate of loss that occurs as the slurry TAN nears cxhaus-

r (,n. This was overcome by constraining I, to bc 2 I,, an bitrary minimum infiltration rate.

,recipitation ,The resistance IO transport (r&,*) is simulated in the man- I 8 m - l d - I). ss outlined for losses from slurry stores. omitting the cover

rating gives tistance. The equilibrium coefficient is calculated with the ~ , ~ , , , * ~ - ~ , pcrature equated to air temperature whilst the pH i s

&mcd to be that of the slurrylunnc at the time ofapplica-

It.

iltration, evap

. .. The masses of slurry. TAN and suspended solids are fined at the time of application, when b = rand a,,) = a,,,:

ation rate on & %*

here U, is the area of a single wine patch (m').

). 18;

a time step, Ihd

*E,.D,,,

d slurry solids " d-'). In rcali .e with theconcel isity reduces iniil

ither by thc soil nsson, 1994).

(81 I Nned by the sIu

i related directly 1