Climate and crop-responsive emission factors significantly alter estimates of current and future...

Climate- and crop-responsive emission factorssignificantly alter estimates of current and future nitrousoxide emissions from fertilizer use

H E L E N C . F LY N N *, J O S M I T H *, K E I T H A . S M I T H w , J I M W R I G H T w 1 , P E T E S M I T H * and

J O N M A S S H E D E R z*School of Biological Sciences, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen AB24 3UU, UK,

wSchool of GeoSciences, University of Edinburgh, Darwin Building, Mayfield Road, Edinburgh EH9 3JU, UK, zSimulistics Ltd,

ETTC, King’s Buildings, Mayfield Road, Edinburgh EH9 3JL, UK

Abstract

The current Intergovernmental Panel on Climate Change (IPCC) default methodology

(tier 1) for calculating nitrous oxide (N2O) emissions from nitrogen applied to

agricultural soils takes no account of either crop type or climatic conditions. As a result,

the methodology omits factors that are crucial in determining current emissions, and has

no mechanism to assess the potential impact of future climate and land-use change.

Scotland is used as a case study to illustrate the development of a new methodology,

which retains the simple structure of the IPCC tier 1 methodology, but incorporates crop-

and climate-dependent emission factors (EFs). It also includes a factor to account for the

effect of soil compaction because of trampling by grazing animals. These factors are

based on recent field studies in Scotland and elsewhere in the UK. Under current

conditions, the new methodology produces significantly higher estimates of annual N2O

emissions than the IPCC default methodology, almost entirely because of the increased

contribution of grazed pasture. Total emissions from applied fertilizer and N deposited

by grazing animals are estimated at 10 662 t N2O-N yr�1 using the newly derived EFs, as

opposed to 6 796 t N2O-N yr�1 using the IPCC default EFs. On a spatial basis, emission

levels are closer to those calculated using field observations and detailed soil modelling

than to estimates made using the IPCC default methodology. This can be illustrated by

parts of the western Ayrshire basin, which have previously been calculated to emit

8–9 kg N2O-N ha�1 yr�1 and are estimated here as 6.25–8.75 kg N2O-N ha�1 yr�1, while the

IPCC default methodology gives a maximum emission level of only 3.75 kg N2O-

N ha�1 yr�1 for the whole area. The new methodology is also applied in conjunction with

scenarios for future climate- and land-use patterns, to assess how these emissions may

change in the future. The results suggest that by 2080, Scottish N2O emissions may

increase by up to 14%, depending on the climate scenario, if fertilizer and land

management practices remain unchanged. Reductions in agricultural land use, however,

have the potential to mitigate these increases and, depending on the replacement land

use, may even reduce emissions to below current levels.

Keywords: agricultural soils, climate change, emission factors, fertilizer, grazing, IPCC, land-use

change, nitrous oxide, modelling, Scotland

Received 10 December 2004; revised version received 17 March 2005 and accepted 22 March 2005

Introduction

Nitrous oxide (N2O) is a potent greenhouse gas. Its

global warming potential (cumulative radiative forcing)

is 296 times greater than that of carbon dioxide (IPCC,

2001a). Microbial processes in soils account for 65% of

Correspondence: Helen Flynn, tel. 1 44 1224 273810,

fax 1 44 1224 272703, e-mail: [email protected] address: Department of Geography, University of

Southampton, Highfield, Southampton SO17 1BJ, UK.

Global Change Biology (2005) 11, 1522–1536, doi: 10.1111/j.1365-2486.2005.00998.x

1522 r 2005 Blackwell Publishing Ltd

the global annual emissions of N2O (IPCC, 1995), and

for cultivated soils, levels of nitrogen (N) fertilizer

applied have a major influence on the rate of emissions.

The current Intergovernmental Panel on Climate

Change (IPCC) default (tier 1; IPCC, 2001b) methodol-

ogy for calculating direct N2O emissions from agricul-

tural soils uses emission factors (EFs), which specify

that a fixed proportion of the N applied will be emitted

as N2O (IPCC, 1997). The default values for these EFs

take no account of the effect of crop type or climate:

factors that are known to regulate N2O production. The

absence of crop- and climate-dependent EFs not only

omits important factors in controlling emissions, but

also results in a methodology that cannot be used to

assess the impact of potential future land use and

climate change on N2O emissions.

The research described in this paper uses Scotland as

a case study area to illustrate the development of crop-

and climate-dependent EFs. The newly derived EFs are

then used to assess how potential future climatic- and

land-use changes may affect N2O emissions from

fertilizer applications in Scotland. These EFs were

derived principally from field experiments carried out

in Scotland and the rest of the UK, but may be

applicable in similar climatic zones in other countries,

or the approach could equally be used to derive EFs

tailored to other regions from relevant field experi-

ments within those regions. The new EFs were used,

along with calculations of annual N inputs from

mineral fertilizers and manure applications at a 2 km

grid resolution, to produce maps of current N2O

emissions. These were compared with calculations

made using the IPCC default methodology. The impact

of future rainfall and temperature changes on N2O

emissions were then assessed, along with potential

changes in land use. The crop-specific aspect of the

methodology allows calculation of the sensitivity to

climate change of emissions from different land-use

types. Combined with the climate dependence, this

allows regions of high emission risk to be identified,

allowing future research priorities to be set, and

potential options to mitigate increases in N2O emissions

to be identified. The methodology reflects the effect of

site-specific processes on emissions without including

detailed descriptions of the individual processes.

Explicit simulation of the individual processes at

each site would require more detailed information

than is currently available. This approach (a tier 2

methodology; IPCC, 2001b), contrasts with previous

approaches (such as Brown et al., 2002) in which

detailed process-based models were used (a tier 3

methodology; IPCC, 2001b), with estimation techniques

to fill gaps in the input data needed to run the more

complex model.

Materials and methods

Annual nitrogen inputs

The amount and spatial distribution of N fertilizer

applied in Scotland were estimated for both mineral

fertilizers and organic (manure) additions. Agricultural

census data are available for 2 km grid-squares, which

are derived by combining parish-level summary data

with a gridded land cover map (http://datalib.ed.

ac.uk/EUDL/agriculture/griddata.html). Scotland was

therefore subdivided into the 2 km grid-squares used

by the Agricultural Census. Mineral fertilizer inputs

were calculated by multiplying the number of hectares

of a crop in each grid-square (data from the Agricultur-

al Census for the year 2000) by the annual fertilizer

application data for that crop, taken from the British

Survey of fertilizer Practice (BSFP) (Anon, 2000a). For

crops such as soft fruit that are not included in the

BSFP, the N requirements from the fertilizer Recom-

mendations report (Anon, 2000b) were used instead of

the annual fertilizer application from the BSFP. This

approach gave approximately the same total amount of

N applied as was estimated using the ‘other tillage’

fertilizer application rate from the BSFP, but was more

spatially explicit. Inputs to land uses not described as

crops or managed grasslands were not included in the

estimates. This should not cause a significant under-

estimate of fertilizer-induced N2O emissions, as set-

aside and rough grazing land do not receive significant

levels of fertilizer, and there are currently less than

200 ha of forestry land which have nitrogen fertilizers

applied to them (W. Mason, personal communication,

Forestry Commission). It should be noted that the

spatial distribution of applied N estimated by this

approach reflects only the distribution of crop types.

The BSFP produces averaged data, based on a small

percentage of farms in each size class, and taking no

account of soil type. Using these national averages for

different crop types produces a spatial distribution that

is based solely on the distribution of crop types.

However, because no spatial data for fertilizer applica-

tions are currently available, this is the best estimate

possible.

The amount of N applied as manure or slurry is more

difficult to estimate than the amount applied as mineral

nitrogen as no data on organic applications are

currently available. IPCC estimates of N production

by cattle and sheep, and the division between manure

deposited directly onto grazing land, and manure

that is collected and applied to crops (IPCC, 2001b),

were used, together with animal numbers in each

grid-square from the Agricultural Census (2000). It

was assumed that all manure produced within a

N I T R O U S O X I D E E M I S S I O N S F R O M F E R T I L I Z E R U S E 1523

r 2005 Blackwell Publishing Ltd, Global Change Biology, 11, 1522–1536

grid-square was disposed of within that square. This

means that for grid-squares where there were no crops

grown, it was assumed that all the manure was

deposited directly by animals onto grazing land. This

assumption results in a conservative estimate of organic

N fertilizer use.

Fertilizer-derived N2O emissions under currentconditions

The IPCC default methodology was used to provide a

baseline for comparison with estimates of N2O emis-

sions obtained using the new EFs. The IPCC default

method uses an EF of 1.25% for all the N applied to

agricultural land, after correcting for losses because of

NH3 and NOx volatilization. The Agricultural Census

gives only animal numbers per grid-square and does

not specify whether they are grazed on managed

(fertilized) grassland or rough grazing. Therefore,

grazing-related emissions cannot be separated to allow

only those from fertilized fields to be considered. N

deposited directly by animals onto grazing land has a

higher N2O EF of 2%.

The Scotland-specific emissions were calculated in

the same way as the IPCC default emissions, but with

the default EFs replaced by the newly derived EFs.

These depend on a combination of crop type, fertilizer

type and climatic factors, and are summarized in Table

1. Figures 1 and 2 illustrate how the climate-specific EFs

are controlled by rainfall and temperature.

Origin of the newly derived EFs

A relationship between climatic conditions and the EF

for grassland was reported in Dobbie et al. (1999). This

equation relates N2O emissions to rainfall around the

time of fertilization, and corrects for temperature. The

equation was applied on a monthly basis to calculate

emissions from mineral N inputs. Total mineral N

inputs were divided into monthly inputs using percen-

tage levels of N input by month from the BSFP (Anon,

2000a). The effects of assuming this distribution of

fertilizer applications on the N2O emissions calculated

are discussed further below (see Discussion). Spatial

monthly climate data was taken from the baseline

(1961–1990) UKCIP data set (www.ukcip.org.uk). For

N2O emissions from N deposited on to grassland by

grazing animals, EFs were calculated using the annual

average climate data only, as the temporal distribution

of the inputs is unknown.

Climate-variable EFs were also used to estimate

emissions from potatoes, and other arable crops, such

as leafy vegetables (excluding cereals and oilseed rape).

These crops show a distinctly different distribution of

EFs to cereals and oilseed rape and instead fit well into

the grassland EF distribution (Dobbie et al., 1999;

Dobbie & Smith, 2003). This, combined with evidence

that heavy precipitation increases N2O emissions from

potato fields (Flessa et al., 2002), suggests that, at our

current level of understanding, these crops may be

Table 1 Summary of emission factors

Land-use category and

N source

IPCC

default EF New EF

Arable: cereals/OSR (%)

Mineral N 1.25 0.6

Organic N 1.25 0.5

Arable: Potatoes/other (%)

Mineral N 1.25 Climate

variable*

Organic N 1.25 0.5

Cut grass (%)


variable*

Organic N 1.25 0.5

Grazed grass (%)


variable*� animal

multiplierwN deposited by animals 2 Climate variablez

*Climate variable EF ðusing monthly climate dataÞ ¼

ð51:004�monthly rainfallÞ�614:9791000 � 2ððdaily temp�12Þ=10Þ

(Dobbie et al., 1999).

wAnimal multiplier (to account for trampling effects) 5 2 for

cows and 1.3 for sheep (based on Oenema et al., 1997).

zAs above, but using annual average values for monthly

rainfall and daily temperature, and for rough sheep grazed

land, the default EF of 2% was taken as the maximum (based

on Oenema et al., 1997).

IPCC, Intergovernmental Panel on Climate Change; EF,

emission factor. OSR, oilseed rape.

0%

2%

4%

6%

8%

10%

12%

14%

0 2 4 6 8 10 12 14 16Temperature (°C)

Em

issi

on fa

ctor

100130160190220

Rainfall (mm)

Fig. 1 Response of climate variable emission factors to average

monthly temperature at different monthly rainfall.

1524 H . C . F LY N N et al.


assumed to respond to climate in the same way as

grassland. By contrast, cereals and oilseed rape do not

show a clear response to changes in rainfall level (Smith

& Dobbie, 2002). Therefore, a crop-specific EF was used

for these crops, which is the mean of the EFs reported

for cereals and oilseed rape in the UK (Dobbie et al.,

1999; Dobbie & Smith, 2003).

Emissions from rough, sheep-grazed land are much

lower than from fertilized grassland grazed by cattle,

because of reduced trampling effects and the less

concentrated nature of the N excretion (Oenema et al.,

1997). This observation was accounted for in two ways:

the default EF of 2% for N deposited by animals was

taken as the maximum for the climate-variable EFs for

rough grazing land, and an animal effects multiplier,

which accounts for trampling effects on mineral N

emissions, was set at 2 for cattle and 1.3 for sheep

(based on Oenema et al., 1997). This required further

assumptions as the Agricultural Census grid-square

data is not of sufficient resolution to allow allocation of

animals to individual fields. Therefore, all fertilized

grazing land was treated as cattle grazed if there were

any cows recorded within that grid-square. For rough

grazing land, using a 2% maximum EF assumes that

this category has low emissions associated with sheep

grazing, but the calculation allows for higher N input

levels associated with cattle grazing. Also, rough

grazing which occurs within grid-squares alongside

managed grazing, did not have the 2% maximum

applied as it is not possible to allocate animals between

grazing land types within grid-squares. In summary,

the approach assumes that the majority of fertilized

pastures are cattle grazed, while rough unfertilized

pasture is sheep grazed, but the calculations allow for

deviations from this assumption by accounting for all

manure inputs, and only capping EFs for rough grazing

land in grid-squares with no managed pastures.

The EF for applied organic N was taken from studies

of grassland emissions, which highlight the low

emissions from spreader applied slurry and farmyard

manure (D. Chadwick, personal communication). The

value of 0.5% lies within the 0.01–1.65% range of

emissions reported for organic fertilizers applied to

Scottish soils (Akiyama et al., 2004). Under laboratory

conditions, N2O emissions of 0.2% of applied N have

been reported from cattle manure and surface-applied

slurry (Flessa & Beese, 2000; Akiyama et al., 2004).

Comparing the results for applied urea N with Scottish

field studies however, suggests that these emissions

may be closer to 0.5% under field conditions (Akiyama

et al., 2004). In the absence of studies into N2O

emissions, from applied organic N fertilizers for land

uses other than grassland, this EF is assumed to apply

to all crop types. Emissions from organic N applications

were not deemed to be climate variable. This is in

accordance with Ball et al. (2004), who carried out field

studies in Scotland, and reported that use of organic

manures avoids the very high fluxes associated with

heavy rainfall occurring around the time of application,

and can therefore mitigate total N2O emissions over a

growing season by approximately 90% in comparison

with mineral fertilizers.

EFs were not adjusted for soil properties such as

texture or wetness class, as transient properties rather

than permanent soil features appear to be dominant in

determining emissions. This is discussed in detail

below (see Discussion).

Fertilizer-derived N2O emissions under future climaticconditions

Predictions for climate change (UKCIP dataset;

www.ukcip.org.uk) were derived from the HadCM3

climate model, which was used to implement four

IPCC emission scenarios (IPCC, 2000). The four

scenarios considered, based on the predicted cumula-

tive CO2 emissions between 1990 and 2100, are as

follows: the ‘low’ emissions scenario assumes that the

cumulative emissions will be less than 1100 Gt C, the

‘medium–low’ scenario assumes emissions between

1100 and 1450 Gt C, the ‘medium–high’ scenario as-

sumes emissions between 1450 and 1800 Gt C, while the

‘high’ scenario assumes that the cumulative emissions

will exceed 1800 Gt C over the period.

The UKCIP database includes rainfall and tempera-

ture predictions for each scenario, for three future time

steps: 2020, 2050 and 2080. These data, in 50 km grid-

squares covering the whole of Scotland, were used to

estimate how N2O emissions might change in response

to climate change. Crop areas, fertilizer inputs and

animal numbers were kept constant and the new

0%

2%

4%

6%

8%

10%

12%

14%

20 40 60 80 100

120

140

160

180

200

220

Em

issi

on fa

ctor

1512963

Rainfall (mm)

Temperature(°C)

Fig. 2 Response of climate variable emission factors to monthly

rainfall at different average monthly temperatures.



emission methodology was used. Therefore, emissions

from land use and fertilizer categories which have fixed

EFs remained constant, while emissions from categories

with climate variable EFs were adjusted according to

predicted changes in the Scottish climate.

Fertilizer-derived N2O emissions under future climaticconditions and future land-use patterns

The ATEAM project (www.pik-potsdam.de/ateam/)

has produced Europe-wide land-use change scenarios

for each of the IPCC future scenarios, based on the

IPCC emission scenario narratives (IPCC, 2000), at a

resolution of 100 � 100 (Rounsevell et al., 2005). Besides

climate change, the narratives also reflect changes in

socio-economic factors. These are based on many

dimensions but the two most important are the relative

orientation of the scenario toward economic or envir-

onmental considerations, and toward global or regional

development objectives. Therefore, the land-use change

scenarios incorporate responses to climate change,

socio-economic conditions, and a consideration of

land-use processes and competition between land-use

types. The scenarios are entirely consistent, both

internally and with the future climate scenarios, and

therefore, represent the most plausible descriptions of

potential future changes currently available. The

changes in the extent of arable crops and grassland

across Scotland from these scenarios were therefore

used to adjust the predicted emissions for each future

scenario, as a more consistent approach than arbitrarily

set scenarios. The calculations do not take into account

emissions from any alternative land use.

Results

Annual nitrogen inputs

Using data for the year 2000, total fertilizer mineral N

inputs are estimated to be 196 thousand tonnes (Gg) per

year, of which 37% is applied to crops and 63% to grass.

This estimate assumes that the percentage of wheat

sown in spring is 3% (the UK average for 2001, from

http://www.hgca.com/c-stats/fileindex.html ‘UK

Spring and Winter cereals.xls’) as the BSFP gives

different fertilizer input levels for winter and spring

wheat, but the Agricultural Census gives only total

wheat areas.

Of the 21186 2 km grid-squares covering Scotland,

49% contain no crops and therefore have no input of

mineral N. Those squares that are amended with

mineral N, are amended with amounts of fertilizer

ranging from 1661 to 53 184 kg per grid square, of

which the median value is 15 585 kg. These values

equate to 4.2–133.0 kg N ha�1 yr�1, with a median of

39.0 kg N ha�1 yr�1, calculated as an average applica-

tion rate for the grid-square. This illustrates that inputs

are highly concentrated in some areas rather than being

evenly spread across the country (see Fig. 3).

Table 2 shows the national levels of organic N

production and how it is disposed of. As with mineral

inputs, no organic N is applied to the 49% of squares in

which no crops are grown. In those squares where

organic N is applied, between 683 and 44 549 kg

are added per grid-square, which equates to 1.7–

111.4 kg N ha�1 yr�1 (see Fig. 4). As well as being

generally lower than mineral N applications, the

pattern of application for organic N is also much more

concentrated in the southwest.

Fertilizer-derived N2O emissions under currentconditions

Using the IPCC default methodology, total N2O

emissions for Scotland are estimated as 6 796 t N2O-

N yr�1, of which 50% are emissions from mineral and

organic fertilizer application and 50% are emissions

from N deposited by grazing animals. Table 3 shows a

Fig. 3 Annual mineral N fertilizer applications.

1526 H . C . F LY N N et al.


full breakdown of emissions according to land use and

fertilizer type. Figure 5 shows the spatial distribution of

emissions, illustrating that total annual N2O-N emis-

sions vary from 0 to 1369 kg per grid-square, which

equates to a maximum of 3.42 kg N2O-N ha�1 yr�1. The

mean annual N2O-N emission is 321 kg per grid-square,

or 0.80 kg N2O-N ha�1 yr�1. As the same EF is used for

all fertilizer applications regardless of crop type, the

contribution of each land-use type to total emissions is

only dependent on the proportion of each crop and the

amount of fertilizer applied to it. This means that the

spatial distribution of emissions directly reflects the

spatial distribution of fertilizer inputs, with the highest

emissions in the southwest and the east of Scotland.

Table 2 Organic N production and disposal

Animal

Numbers

(� 106)

N production/

animal (kg yr�1)

Total N

production

(Gg yr�1)

N deposited by animals

on grazing land (Gg yr�1)

N applied to crops and

nongrazed grass (Gg yr�1)

Sheep 9.18 20 183 87% 13%

Dairy cattle 0.26 100 26 8% 92%

Other cattle 1.76 70 123 33% 67%

Total 332 202 (211*) 130 (121*)

Animal numbers taken from the Agricultural Census (2000). N production per animal, and division between deposited and applied

N, taken from IPCC (2001b).

*Corrected for areas where there are no crops to receive application of organic N.

Fig. 4 Annual organic N fertilizer applications.

Table 3 Contributions of land-use and fertilizer type to total

annual Scottish N2O emissions as calculated by the default

and new methodologies (t N2O-N yr�1)

Land-use category

and N source

IPCC default

methodology

New

methodology

Arable: cereals/oilseed rape

Mineral N 743 357

Organic N 422 169

Total 1165 526

Arable: potatoes/other

Mineral N 71 135

Organic N 89 35

Total 160 170

Cut grass

Mineral N 403 867

Organic N 702 281

Total 1105 1148

Grazed grass (managed)

Mineral N 983 4250

N deposited by animals 2260 3466

Rough grazing*

N deposited by animals 1123 1102

Total 4366 8818

Total fertilizer induced

emissions

3413 6094

Total emissions including

grazing deposited N

6796 10 662

*Includes only grid-squares with no managed grazing. Where

rough grazing occurs within grid-squares which also contain

managed grassland, any N deposited by grazing animals is

included in the managed grazing deposited N category as the

agricultural census data do not allow animals to be divided up

between grazing land types within a grid-square.

IPCC, Intergovernmental Panel on Climate Change.



Substituting the newly derived EFs for the IPCC

default values results in an increase in the estimate

from 6796 to 10 662 t N2O-N yr�1, of which 57% are

emissions from applied fertilizer and 43% are emissions

from N deposited by grazing animals. As this metho-

dology uses different EFs for different crop types,

fertilizers and climates, the contribution of each land-

use type is different from that given by the IPCC

default methodology, and the contributions also vary

across the country depending on climatic conditions.

For comparison with the IPCC default methodology

results, a full breakdown of the contributions from

different crop and fertilizer types is shown in Table 3.

The spatial distribution of these emissions is illustrated

in Fig. 6. Total N2O emissions vary from 0 to 3 476 kg

per grid-square per year, which equates to a maximum

of 8.69 kg N2O-N ha�1 yr�1. The mean annual N2O-N

emission is just over 500 kg per grid-square, or

1.25 kg N2O-N ha�1 yr�1. Emissions are most highly

concentrated in the southwest, and to a lesser extent

in the southeast. Of the individual land use categories,

grazed grass makes the greatest contribution; as

illustrated in Fig. 6e, emissions from this category

alone can reach 7.36 kg N2O ha�1 yr�1.

Comparing the results from the two methodologies

indicates that using default EFs produces higher

emissions from cereals and oilseed rape but reduces

the role of other land uses, most significantly grazing.

Fertilizer-derived N2O emissions under future climaticconditions

Total annual N2O-N emissions from Scotland may

increase from the current level of 10 662 t to between

10 958 and 11 015 t by 2020, between 11196 and 11 519 t

by 2050, and between 11 425 and 12 179 t by 2080,

depending on climate change scenario. Therefore, total

national N2O emissions may increase by up to 14% by

2080 if land use and fertilizer application remain as

they are. Table 4 shows how emission levels increase for

each land-use category. While emissions from cereals

and oilseed rape are predicted to remain constant and

Fig. 5 Current N2O-N emissions calculated using default methodology: (a) total annual emissions, (b) cereals/oilseed rape emissions,

(c) potatoes/other emissions, (d) cut grass emissions and (e) grazed grass emissions.

1528 H . C . F LY N N et al.


emissions from rough grazing may only increase by 1%,

emissions from potatoes and other arable crops may

increase by up to 10% by 2080 under the worst-case

scenario (high), cut grass may increase by up to 11%

and emissions from fertilized cattle pasture by 18%.

The spatial distribution of the change in the current

emission levels was calculated for the three time steps

and four climate change scenarios. Figure 7 illustrates

the results for 2080. Note the sharp changes in

estimated emissions, resulting from the boundaries of

the cells of the UKCIP climate data, and thus reflecting

the importance of climate. In all cases, the greatest

increase is in the southwest of Scotland while the

southeast is the second most sensitive area to climate

change. The northeast also shows high increases in

emissions by 2080 for the medium–high and high

scenarios.

By 2020, N2O emissions from the most sensitive areas

to climate change may increase by a maximum of

between 0.28 and 0.33 kg N2O-N ha�1 yr�1 (not shown).

Projecting further into the future increases both the rise

in emissions and the degree of variation between the

scenarios. By 2050, the maximum increase for the low

climate change scenario is 0.50 kg ha�1 yr�1 while the

high climate change scenario predicts a rise of up to

0.80 kg N2O-N ha�1 yr�1 above current emission levels

(not shown). By 2080, the maximum increase may be

between 0.71 and 1.43 kg N2O-N ha�1 yr�1, respectively

(Fig. 7). These changes mean that maximum total N2O

emissions may reach between 9.4 kg N2O-N ha�1 yr�1

(low scenario) and 10.1 kg N2O-N ha�1 yr�1 (high sce-

nario) by 2080.

These predictions do not provide a full projection of

future emissions: they account only for changes in

temperature and precipitation, not changes in fertilizer

application or animal densities because of CAP reform

or other agricultural policies. They indicate how

emissions could change under future climate condi-

tions if agricultural land use and fertilizer regime

remain as they are currently. The emission levels,

Fig. 6 Current N2O-N emissions calculated using new methodology: (a) total annual emissions, (b) cereals/oilseed rape emissions, (c)

potatoes/other emissions, (d) cut grass emissions and (e) grazed grass emissions.



therefore, represent a baseline for the future under a

‘business as usual’ type scenario, allowing the impact of

mitigation strategies to be assessed.

Fertilizer-derived N2O emissions under future climaticconditions and future land-use patterns

Under the high future scenario, the amount of land

used to grow arable crops in the main agricultural

regions could decrease by 34% by 2020, 46% by 2050,

and 75% by 2080. Under the low future scenario, the

decreases could be 21% by 2020, 29% by 2050, and

around 55–80% by 2080 (Fig. 8a, b). These scenarios are

based on considerations of economic viability, as well

as, climatic factors.

Changes of this magnitude could have a significant

effect on emissions, particularly in the east. However,

arable crops make up the smallest percentage of N2O

emissions and their contribution is predicted to decline

in the future, in comparison with grassland. Arable

crops in Scotland are predicted to produce between 699

and 700 t N2O-N yr�1 by 2020 for the low and high

climate change scenarios, respectively. Therefore, an

average decrease of 21% or 34% would equate to a

reduction of 147 or 238 t N2O-N yr�1, respectively. For

the low scenario, total predicted emissions would be

decreased by just over 1% by 2020, while for the high

scenario, the decrease would equate to 2%. These

decreases would reduce, but not negate, the impact of

climate change, which is predicted to increase total

national N2O emissions by around 3% by 2020. By 2050,

these changes in arable land use would equate to a 2%

decrease in total emissions for the low scenario and a

3% decrease for the high scenario. Climate change,

however, is predicted to increase emissions by 5–8%,

depending on scenario. By 2080, under the low

scenario, changes in arable land use would decrease

total national N2O emissions by 3% and under the high

scenario, the decrease would equate to 4%. These

changes are not sufficient to remove the effect of climate

change, which is predicted to cause a 7–14% increase in

emissions by 2080. Note that the predictions do not take

into account emissions from replacement land use.

For grassland, reductions could be of a similar order

of magnitude but would cover a much larger area,

because of the more extensive nature of grassland in

Scotland. Under the high future scenario, the amount of

land used to grow grass in the main areas of fertilized

grassland could decrease by 30% by 2020, 40% by 2050,

and 67% by 2080. Under the low future scenario, by

2020 and 2050 the majority of areas of intensive

grassland could decrease in spatial extent by less than

10%, and by 2080 these decreases are likely to be greater

but very spatially variable (Fig. 8c, d). Again, these

scenarios are based on economic, as well as climatic,

factors.

Table 4 Predicted future N2O-N emissions depending on climate change scenario (t N2O-N yr�1)

Low Medium–low Medium–high High

2020 2050 2080 2020 2050 2080 2020 2050 2080 2020 2050 2080

Arable: cereals/Oilseed rape

Mineral N 357 357 357 357 357 357 357 357 357 357 357 357

Organic N 169 169 169 169 169 169 169 169 169 169 169 169

Total 526 526 526 526 526 526 526 526 526 526 526 526

Arable: potatoes/other crops

Mineral N 138 141 144 139 142 145 139 143 149 139 145 152

Organic N 35 35 35 35 35 35 35 35 35 35 35 35

Total 173 176 179 174 177 180 174 178 184 174 180 187

Cut grass

Mineral N 893 914 933 896 922 945 896 929 977 898 941 997

Organic N 281 281 281 281 281 281 281 281 281 281 281 281

Total 1174 1195 1214 1177 1203 1226 1177 1210 1258 1179 1222 1278

Grazed grass (managed)

Mineral N 4378 4479 4576 4392 4521 4632 4392 4554 4790 4402 4616 4890

N deposited by animals 3603 3712 3819 3618 3759 3883 3618 3796 4065 3629 3865 4183

Rough grazing

N deposited by animals 1105 1108 1111 1106 1109 1112 1106 1110 1115 1106 1111 1116

Total 9086 9299 9506 9116 9389 9627 9116 9460 9970 9137 9592 10 189

Total applied fertilizer induced emissions 6250 6376 6495 6268 6428 6564 6268 6468 6758 6280 6543 6880

Total emissions including all grazing deposited N 10 958 11196 11 425 10 992 11 296 11 559 10 992 11 374 11 938 11 015 11 519 12 179

1530 H . C . F LY N N et al.


Fig. 7 Changes in total N2O-N emissions from current levels under different climate scenarios for the year 2080: (a) low, (b) medium–

low, (c) medium–high and (d) high.



Changes in the extent of grassland could have a very

significant impact on N2O emissions because this land

use contributes the major part of the emissions and is

predicted to increase in relative importance in the

future. For the high scenario, likely changes are similar

across the country, and it is therefore reasonable to

1532 H . C . F LY N N et al.


assume a proportional reduction in all types of grass-

land. Using this assumption, it is estimated that

reductions in grassland area could reduce predicted

total annual N2O emissions by 28% by 2020, 38% by

2050, and 63% by 2080. Not only would this negate the

effect of climate change, but it would also reduce

emissions significantly below current levels. For the

low scenario however, there is a high degree of spatial

variation in the land-use change scenarios and therefore

a blanket reduction is not reasonable. Calculating

changes in the emissions with any degree of confidence

would require the patterns of land-use change and

grassland emissions to be overlaid, as emission levels

are also very spatially variable. This is difficult to do

accurately because the data grids are different resolu-

tions and projections, and so the changes are not

reported here.

These results suggest that overall reductions in

agriculture could not only negate the effects of climate

change, but also reduce total N2O emissions to below

their current level. The extent of this reduction in

emissions is dependent on the nature of the replace-

ment land use.

Discussion

This study has derived new regionally specific, crop-

and climate-responsive N2O EFs by bringing together

recent field studies of N2O emissions from different

crop types in the UK. The approach retains the

simplicity of the IPCC tier 1 methodology, but also

incorporates climate and crop dependence as a tier 2

method, without introducing the complexity of full

process-based modelling (tier 3). The new factors allow

application to large areas at the relatively high spatial

resolution at which data are now available. The IPCC

default methodology produces an estimate of emissions

from grazed pasture that is only 50% of the estimate

made using the new approach. This is because the IPCC

methodology does not allow for climate dependence, or

include the impact of trampling, which is particularly

significant for cattle. The areas that have the highest

emissions under the new methodology tend to be those

with the highest climate-variable EFs, because of wet

and mild conditions, which favour denitrification. They

also show a high concentration of fertilized cattle-

grazed pastures, the land-use category which is most

affected by increases in these EFs, as emissions from

applied mineral N are further enhanced because of soil

compaction by trampling. As the most climate-sensitive

land use, fertilized pasture produces the highest

absolute emissions, and is also likely to increase by

the greatest percentage as mild and wet conditions are

predicted to become more prevalent in Scotland under

the future climate scenarios.

This has global implications: in 2000, there were over

59 million hectares of permanent pasture in Western

Europe alone (FAOSTAT, 2004), where similar changes

in emissions as observed in Scotland because of

trampling and climate effects might be expected to

hold. Under the IPCC methodology, these areas could

all be assigned the same EFs as for Scotland. Across the

world as a whole, this figure rises to 3489 million

hectares, grazed by 1337 million cattle and 1050 million

sheep (FAOSTAT, 2004).

Several inventories of emissions have been published

previously. Brown et al. (2001) used the IPCC metho-

dology, while Skiba et al. (1996) used average emissions

from different land uses measured in the field and then

scaled up according to total crop areas. A UK wide

inventory of N2O emissions from farmed livestock,

including emissions from manure applied as fertilizer,

has also been produced (Chadwick et al., 1999). These

estimates show similar trends to the results presented

here, in terms of the contribution of different land uses

and fertilizer types, indicating that managed grazing is

the major source of N2O emissions, and that applied

manure makes a significantly smaller contribution than

applied mineral N fertilizers. It is not possible to make a

direct comparison, as the estimates are not broken

down spatially within the UK, but calculations carried

out by Chadwick et al. (1999) indicate how excluding

trampling effects can result in significant underesti-

mates of emissions from grazing land.

Estimates made using an adapted version of DNDC

have been reported on a regional scale (Brown et al.,

2002). Emissions from Scotland for 1990, were esti-

mated as 1950 t N2O-N from fertilizer applications,

370 t N2O-N from applied manure and 500 t N2O-N

from N deposited on grazing land. Emissions were

also broken down according to crop type, with Scottish

grassland accounting for 2470 t N2O-N, cereals for

220 t N2O-N, and other crops for 130 t N2O-N. For most

categories, these estimates are of the same order of

Fig. 8 Predicted changes in agricultural area from current (baseline) levels under different Intergovernmental Panel on Climate

Change (IPCC) climate change scenarios for the year 2080: (a) arable land-use, low scenario, (b) arable land-use, high scenario, (c)

grassland, low scenario and (d) grassland, high scenario Advanced Terrestrial Ecosystem Analysis and Modelling (ATEAM) data

reproduced with permission from ATEAM EU project. Note: Some areas labelled here as 0% change are predicted to increase, but none of

these areas are in Scotland.



magnitude as those produced by this study (Table 5).

The contribution of grassland as estimated by DNDC is,

however, much lower in terms of both mineral N

applications and deposited manure. Despite this, the

EFs produced by DNDC were within the same range as

the climate-variable EFs calculated in this study.

Therefore, the lower estimate is likely to be because of

a combination of DNDC not accounting for trampling

effects, and also treating deposited manure differently.

Similarly, the emissions from mineral fertilizers calcu-

lated in this study are higher than calculated by Brown

et al. (2002) because of the high losses from mineral

fertilizer associated with trampling. A similar pattern of

highest emissions in the southwest, followed by areas

on the east coast, as found here, was also reported in

the DNDC study (Brown et al., 2002). The total

agricultural N2O emission levels were averaged over

entire counties, so the per hectare levels are not directly

comparable with those presented here. The observation

that trampling contributes a much greater proportion of

the emissions than the processes incorporated in the

model used by Brown et al. (2002), suggests that

trampling needs to be included in such models for

estimating future N2O emissions.

Lilly et al. (2003) calculated spatial N2O emissions for

two areas of Scotland, using a methodology that scaled

up field measurements from different land uses and

soil types. The technique made use of Geographical

Information Systems (GIS) to combine soil, climate and

land cover data, producing maps of soil wetness classes

and land use to which representative emission levels

could be assigned. The methodology includes climate

dependence, and as it is based on measured emissions

from land uses including grazing, inherently accounts

for trampling effects. The results obtained are on a finer

spatial scale than those presented in this study but the

emission levels are similar. Lilly et al. (2003) calculated

that annual N2O emissions from a large part of the

western Ayrshire basin (in the south west of Scotland)

are 8–9 kg N ha�1, with pockets of 2–3 kg N ha�1 and

over 10 kg N ha�1, while the eastern area emits below

1 kg N ha�1. This study reports emissions of 6.25–

8.75 kg N ha�1 for the western area, and below

1.25 kg N ha�1 for the rest of the basin. For the Lothians

(south east of Scotland), Lilly et al. (2003) calculated

emissions varying from 5 to 9 kg N ha�1 for most of the

coastal area, with the more inland areas emitting either

1–3 kg N ha�1, or over 9 kg N ha�1. This study reports

emissions of 1.25–5 kg N ha�1 for the coastal area, and

either below 1.25 kg N ha�1, or 6.25–8.75 kg N ha�1 for

the inland areas. This indicates that estimates made

using the Scotland-adjusted methodology are compar-

able with those made by a very different methodology

based on field measurements and detailed modelling of

soil moisture conditions. In contrast, the IPCC default

methodology produces maximum emission levels of

only 3.75 kg N ha�1 for both these areas. The crop- and

climate-responsive, regionally specific EFs used here

provide a balance between existing techniques retain-

ing the simplicity of the IPCC default EFs, providing

estimates of N2O emissions which more closely reflect

in situ processes, but without the fine-scale, detailed

data requirement of more complex modelling.

Both, the methodology presented here and all

previous attempts to model the spatial distribution of

emissions, are affected by numerous sources of un-

certainty that remain difficult to quantify. For example,

there are likely to be regional and crop-specific

variations in the timing of N application, yet no

routinely collected data are available to describe such

differences. This study assumed that all agricultural

land has mineral N applied across 9 months of the year,

concentrated in spring and early summer. This reflects

the timing of total fertilizer applications averaged for

the whole of Scotland. However, any individual field is

likely to receive between one and three applications,

depending on the crop type (Lilly et al., 2003). In the

absence of more detailed information on the spatial

timing of applications, applying the national average

across the country was deemed preferable to assigning

Table 5 Estimates of N2O emissions from Scotland, calculated using a range of different approaches (t N2O-N yr�1)

Approach

N2O emissions broken down

according to source of nitrogenTotal

emissions

from all

sources

N2O emissions broken down

according to crop typeTotal

emissions

from all

crops

Mineral

fertilizer

Applied

organic

wastes

Deposited of

grazing land Grassland

Cereals and

Oilseed rape*

Other

crops

IPCC default (this study) 2200 1213 3383 6796 5471 1165 160 6796

New methodology (this study) 5609 485 4568 10 662 9966 526 170 10 662

DNDC Brown et al. (2002) 1950 370 500 2820 2470 220 130 2820

*The estimates of Brown et al. (2002) include only cereals in this category, so are expected to be lower than the other approaches.

1534 H . C . F LY N N et al.


typical dates for fertilizer applications. The level of

error associated with this assumption is entirely

dependent on monthly climatic variations and is

therefore likely to differ from year-to-year. Similarly,

the spatial distribution of livestock at the time of the

June agricultural census may be unrepresentative of the

livestock distribution at other times of the year.

The greatest individual source of uncertainty in the

application of an EF-based methodology is arguably the

effect of soil properties, both on the level of emissions,

and on their response to climatic variation. In this

study, EFs were not adjusted for soil properties such as

texture or wetness class. This is because clear evidence

has been obtained in a 3-year experimental study across

several contrasting Scottish sites (Dobbie et al., 1999)

that EFs depend much more on soil water-filled pore

space (WFPS) and temperature when fertilizer N is

applied, than on properties such as texture, and that

rainfall around the time of fertilization is a useful

surrogate variable for the WFPS. These conclusions are

strongly reinforced by the results of a successor study

carried out across much of Great Britain (Dobbie &

Smith, 2003). The regression model linking EF with

rainfall and temperature used here is based directly on

the relationships in Dobbie et al. (1999), which were

obtained for soils ranging in texture from sandy loam to

clay loam. The organic matter contents of Scottish soils,

particularly under grassland, are generally well above

those of most temperate soils, and the topsoils are

strongly aggregated. Many of the soils are developed

on impervious glacial tills, even though the topsoil

textures are quite coarse, and are characterized by

water tables close to the surface for much of the year.

The result is that matric suctions are often very small,

and the %WFPS values are consequently often high.

Under such conditions, substantial N2O emissions may

occur within hours of applying granular mineral N

fertilizer to the surface, in soils across the texture range;

the most plausible explanation for this is that anaerobic

microsites where N2O production by denitrification can

take place (e.g. Leffelaar, 1986; Smith, 1997) exist within

the organic-rich topsoil aggregates, even in the sandier

soils. The sensitivity of the emissions to short-term

fluctuations in near-surface moisture conditions means

that the latter have a bigger impact than the general soil

hydrological regime, used as the basis for modelling

emissions by Lilly et al. (2003). Further evidence that

high emissions can occur from coarser-textured soils is

provided by Skiba & Ball (2002). They measured N2O

emissions from 13 Scottish arable soils, all under winter

barley, and observed a large difference in emissions

(two orders of magnitude), with by far the highest

postfertilization emissions associated with a freely

drained sandy loam, followed by an imperfectly

drained sandy clay loam. A relationship between

emissions and a combination of bulk density and clay

content was established, but despite uniformity of land

use, land management and mineral N fertilizer input, it

was found to be significant in only one case out of four.

Given the uncertainties which still exist, concerning the

impact of soil properties such as texture on N2O emis-

sions, more data are required before any quantitative

texture-related function can be included in an EF model.

Previous studies have produced national inventories

of emissions, while others have reported empirical

relationships between emissions and climatic condi-

tions. This is the first work to combine the two to

produce future inventories based on predicted climate

change. Combined with the detailed spatial and land-

use breakdowns, this allows mitigation strategies to be

suggested and future research to be focused on regions

and land-use types of key concern in the future. The

work also highlights the importance of taking land-use

changes into consideration, and illustrates that careful

management of land has the potential to reduce the

emissions to below current levels.

The IPCC is currently revising its Guidelines for

National Greenhouse Gas Inventories. In this revision,

due for completion in 2006, agriculture, forestry and

other land-use categories will be brought together into

a single consistent framework. As part of this process,

default EFs will be updated where better values are

available. Further, tier 2 methods, that retain an EF

approach but use regionally specific EFs, will be

elaborated. This study suggests that the use of crop-

and climate-responsive EFs have significant potential

for use in emission inventories, and they could be

explored for use in other regions.

This work highlights the contribution of managed

pastures to N2O emissions, particularly in areas, which

currently have, or are predicted to have in the future, a

wet and mild climate such as in southwest Scotland.

For example, some regions of New Zealand are

predicted to experience an increase in precipitation of

approximately 20% and up to 3 1C higher temperatures

by 2080 (New Zealand Climate Change Office, 2004). The

country currently has 13 863 thousand hectares of

permanent pasture and significantly more grazing ani-

mals than Scotland: 9 million cattle and 42 million sheep

in 2000 (FAOSTAT, 2004). While the results may also be

applicable to other, similar bioclimatic regions, ideally,

regionally specific crop- and climate-responsive EFs

should be derived from experiments within those regions.

Acknowledgements

Land-use data from the ATEAM project (Advanced TerrestrialEcosystem Analysis and Modelling; www.pik-potsdam.de/



ateam/; contract EVK2-2000-00075) were used. Climate datafrom UKCIP were used. UKCIP02 climate data are r CrownCopyright 2002. The UKCIP02 Climate Scenario data have beenmade available by the Department for Environment, Food andRural Affairs (DEFRA). DEFRA accepts no responsibility for anyinaccuracies or omissions in the data nor for any loss or damagedirectly or indirectly caused to any person or body by reason of,or arising out of, any use of this data. Agricultural census datawere purchased from EDINA at the Edinburgh Data Library(http://datalib.ed.ac.uk/EUDL/agriculture/griddata.html).The grid-square agricultural census data are derived from thedata obtained for recognized geographies from the ScottishExecutive Environment and Rural Affairs Department (SEER-AD), the Department of Environment, Food and Rural Affairs(DEFRA), and the Welsh Assembly.

H. Flynn would like to thank Martin Wattenbach forassistance with the GIS work. The authors are grateful toSEERAD for funding this work under contract number UEH/007/03 and to the two anonymous reviewers for theirconstructive comments.

References

Anon (2000a) The British Survey of Fertilizer Practice. BSFP

Authority.

Anon (2000b) Fertiliser Review. Fertiliser Manufacturers Associa-

tion, Peterborough.

Akiyama H, McTaggart IP, Ball BC et al. (2004) N2O, NO, and

NH3 emissions from soil after the application of organic

fertilizers, urea and water. Water, Air and Soil Pollution, 156,

113–129.

Ball BC, McTaggart IP, Scott A (2004) Mitigation of greenhouse

gas emissions from soil under silage production by use of

organic manures or slow-release fertilizer. Soil Use and

Management, 20, 287–295.

Brown L, Armstrong Brown S, Jarvis SC et al. (2001) An

inventory of nitrous oxide emissions from agriculture in the

UK using the IPCC methodology: emission estimate, uncer-

tainty and sensitivity analysis. Atmospheric Environment, 35,

1439–1449.

Brown L, Syed B, Jarvis SC et al. (2002) Development and

application of a mechanistic model to estimate emission of

nitrous oxide from UK agriculture. Atmospheric Environment,

36, 917–928.

Chadwick DR, Sneath RW, Phillips VR et al. (1999) A UK

inventory of nitrous oxide emissions from farmed livestock.

Atmospheric Environment, 33, 3345–3354.

Dobbie KE, McTaggart I.P, Smith KA (1999) Nitrous oxide emis-

sions from intensive agricultural systems: variations between

crops and seasons, key driving variables, and mean emission

factors. Journal of Geophysical Research, 104, 26891–26899.

Dobbie KE, Smith KA (2003) Nitrous oxide emission factors for

agricultural soils in Great Britain: the impact of soil water-

filled pore space and other controlling variables. Global Change

Biology, 13, 204–218.

FAOSTAT (2004) Food and Agriculture Organization of the

United Nations statistical databases. http://apps.fao.org/.

Flessa H, Beese F (2000) Laboratory estimates of trace gas

emissions following surface application and injection of cattle

slurry. Journal of Environmental Quality, 29, 262–268.

Flessa H, Ruser R, Schilling R et al. (2002) N2O and CH4 fluxes in

potato fields: automated measurement, management effects

and temporal variation. Geoderma, 105, 307–325.

Intergovernmental Panel on Climate Change (IPCC) (1995) In:

Climate Change 1995 (eds Houghton JT et al.), Cambridge

University Press, Cambridge, UK.

IPCC (1997) Greenhouse gas emissions from agricultural soils.

In: Greenhouse Gas Inventory Reference Manual. Revised 1996

IPCC Guidelines for National Greenhouse Gas Inventories

(eds Houghton JT et al.), UK Meteorological Office, Bracknell,

UK.

IPCC (2000) Special Report on Emissions Scenarios. Cambridge


IPCC (2001a) Climate Change: The Scientific Basis. Cambridge


IPCC (2001b) Good Practice Guidance and Uncertainty Management

in National Greenhouse Gas Inventories. Intergovernmental

Panel on Climate Change (IPCC), Institute for Global

Environmental Strategies, Tokyo, Japan.

Leffelaar PA (1986) Dynamics of partial anaerobiosis, denitrifica-

tion, and water in a soil aggregate: experimental. Soil Science,

142, 352–366.

Lilly A, Ball BC, McTaggart IP et al. (2003) Spatial and temporal

scaling of nitrous oxide emissions from the field to the

regional scale in Scotland. Nutrient Cycling in Agroecosystems,

66, 241–257.

New Zealand Climate Change Office (2004) Preparing for

Climate Change: A Guide for Local Government in New Zealand.

Ministry for the Environment, Wellington, New Zealand

pp. 6–7.

Oenema O, Velthof GL, Yamulki S et al. (1997) Nitrous oxide

emissions from grazed grassland. Soil Use and Management, 13,

288–295.

Rounsevell MDA, Ewert F, Reginster I et al. (2005) Future

scenarios of European agricultural land-use. II: estimating

changes in land-use and regional allocation. Agriculture,

Ecosystems and Environment, 107, 117–135.

Skiba U, Ball B (2002) The effect of soil texture and soil drainage

on emissions of nitric oxide and nitrous oxide. Soil Use and

Management, 18, 52–60.

Skiba U, McTaggart IP, Smith KA et al. (1996) Estimates of

nitrous oxide emissions from soil in the UK. Energy Conversion

and Management, 37, 1303–1308.

Smith KA (1997) The potential for feedback effects induced by

global warming on emissions of nitrous oxide by soils. Global

Change Biology, 3, 327–338.

Smith KA, Dobbie KE (2002) Nitrous oxide emissions from

agricultural soils and the potential for their reduction. Final Project

Report, DEFRA Contract CC0233.

1536 H . C . F LY N N et al.


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