Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

N2O: DIRECT EMISSIONS FROMAGRICULTURAL SOILSA C K N O WL E D G E M E N T S
This paper was written by Keith Smith (University of Edinburgh, UK), Lex Bouwman (RIVM, Bilthoven, The
Netherlands) and Barbara Braatz (ICF Consulting, Washington, DC., USA)ABSTRACTThe OECD/IPCC/IEA phase II development of the Revised 1996 IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC Guidelines) methodology for agricultural sources of N2O (IPCC, 1997; Mosier et al., 1998)
includes methodologies for calculating both direct and indirect emissions of N2O related to agricultural
production. It takes into account anthropogenic N inputs including synthetic fertilizers, animal wastes and otherorganic fertilizers, biological nitrogen fixation by crops, cultivation of organic soils, and mineralization of crop
residues returned to the field. Direct sources include those where N2O is emitted directly to the atmosphere from
cultivated soils and fertilized and/or grazed grassland systems. Indirect emissions result from transport of N fromagricultural systems into ground and surface waters through drainage and surface runoff, or emission as ammonia
or nitrogen oxides and deposition elsewhere, causing N2O production.
Worldwide consumption of synthetic N fertilizers has increased by about 150% since 1970 to about 82 Tg N y-1
in 1996. Animal wastes used as fertilizer supplied an estimated additional 65 Tg N y-1 in 1996, compared with 37
Tg N y-1 in 1950. This increase in N use is now widely recognised as a major factor in the increase in N2Oemissions indicated by increases in atmospheric concentration. The evidence points to a further major increase
from agricultural sources in the future, with increases in food production.
Much research published since the adoption of the present default emission factors (1.25% of N applied assynthetic and organic fertilizers, crop residues etc, and 2% of the N deposited by grazing animals) strongly
suggests that seasonal weather fluctuations and management variables (e.g. the timing of irrigation), and crop
type in a given region, have a large impact on fluxes. This poses the question of whether an analysis of existingdata may lead to modified emission factors. This will be an important theme of the workshop discussions. The
alternative to experimental determination of these factors is modelling, and the potential for the use of models inthis context is reviewed. Difficulties with complex models, including the issue of the scales on which they
operate, may make simplified summary models a desirable option for developing updates of emission factors.
This paper reviews the problems associated with the acquisition of activity data, quantification of uncertainties,
and the achievement of completeness in source identification and calculation. It also identifies corrections thatare needed to the present IPCC Guidelines, and examines the issue of accounting for mitigation measures. In
relation to this last topic, it is concluded that careful attention needs to be given to the impact of measures taken
to mitigate CO2 or CH4 emissions on those of N2O. With regard to inventory quality, it is concluded that a key
concept is independent, objective review to assess the effectiveness of the internal QC programme, and to reduceor eliminate any inherent bias in the inventory processes. Several types of external reviews, or audits, may beappropriate for the inventory of direct N2O emissions from agricultural soils.

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1

INTRODUCTION

1.1

Nature, magnitude and distribution of source

1.1.1

Mechanisms Responsible for Formation of N 2 O

Direct emissions of nitrous oxide, N2O, from soils result primarily from microbially driven nitrification anddenitrification processes, together with non-biological chemodenitrification. Nitrification is the aerobic microbial
oxidation of ammonium ions to nitrite via NH2OH, and then to nitrate:
NH4+ → NH2OH → NO2- → NO3When oxygen is limiting, ammonium oxidisers can use NO2- as an alternative electron accetor and produce N2O(“nitrifier denitrification” (Granli and Bøckman, 1994).
N2O is also formed in the course of denitrification, the anaerobic microbial (mainly bacterial) reduction of nitrate
successively to nitrite and then to the gases NO, N2O and N2:
NO3- → NO2- → NO → N2O → N2
Chemodenitrification involves, as its name implies, the chemical reduction of nitrite ion to N2O by compounds
such as amines present in soil organic matter, and by inorganic ions (Fe2+, Cu2+), particularly in subsoils (Granli
and Bøckman, 1994). It is less important than nitrification or biological denitrification as a source of N2O fromagricultural soils.
Microbial production of N2O is dependent on the presence in the soil of suitable mineral N substrates, i.e.
ammonium and nitrate. Thus additions of mineral N fertilizers, and N from other sources such as animal manures,
crop residues, N2-fixing crops, and sewage sludge (from which ammonium is released by mineralisation) to
agricultural soils are recognised as major drivers of N2O emissions (Bøckman and Olfs, 1998). Additionally,
there is an additional “background” source due to the mineralisation of soil organic matter (humus), and wheresoils have only relatively recently been brought into cultivation the accelerated decomposition of OM that may
have slowly accumulated over thousands of years under natural forest or grassland vegetation will enhance this“background” source. Organic (peat) soils that have been drained and cultivated can give rise to particularly highN2O fluxes (Kasimir-Klemedtsson et al., 1997).

1.1.2

Previous assessments of the soil source

In the IPCC (1992) assessment, the global N2O emissions from natural soils were estimated to be in the range 3.2-7.7
Tg N y-1, while the additional emission from agricultural soils was very uncertain (0.03-3.0 Tg N y-1). IPCC (1995)
estimated the direct contribution from agricultural soils receiving N from mineral fertilizers, manure and N2-fixing
legumes at 3.5 (1.8-5.3) Tg N y-1, i.e. nearly 25% of the total global source strength of 14.7 Tg N y-1. More recently,
using the IPCC Phase II methodology (IPCC, 1997), the direct emissions from agricultural soils have been estimatedat 2.1 (0.4-3.8) Tg N y-1, with a total from agricultural systems (including emissions from animal production andindirect emissions derived from N of agricultural origin) of 6.3 Tg N y-1 (Mosier et al., 1998).

1.1.3

Source distribution

Worldwide consumption of synthetic N fertilizers has increased 20-fold since 1950 and by about 150% since1970, to about 82 Tg N y-1 in 1996 (Mosier and Kroeze, 1999). About half of current consumption is in Asia, andmuch of the recent increase has occurred in this region. Animal wastes used as fertilizer supplied an estimatedadditional 65 Tg N y-1 in 1996, compared with 37 Tg N y-1 in 1950 (Mosier and Kroeze, 1999). This increase in
N use is now widely recognized as a major factor in the increase in N2O emissions indicated by increases inatmospheric concentration. The evidence points to a further major increase from agricultural sources in the
future, in view of projections that point to a further doubling of N fertilizer use in developing countries by 2025
(Vitousek and Matson, 1993; Bouwman, 1998). Intensive use of animal manure as fertilizer is a feature of
agricultural systems as diverse as intensive dairy cattle rearing in NW Europe and 1-2 ha subsistence farms in E
and SE Asia, and as livestock numbers rise the tendency will be for the N input from this source to increase(Bouwman and van der Hoek, 1997).

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1.2
1.2.1

Current state of inventory methodologies
Emission factor and regression approaches

In emission factor approaches emission estimates are derived by combining measurement data with geographic
and statistical information on the ecosystem processes and economic activity. This can be represented as:
EQUATION 1
E = A ● Ef
where E is the emission, A the activity level (e.g. area of a functional unit, animal population, fertilizer use,burning of biomass) and Ef the emission factor (e.g. the emission per unit of area, animal, unit of fertilizer appliedor biomass burnt). When using the emission factor approach, both the stratification scheme for delineating
functional types (e.g. management systems, ecosystems, environmental provinces or entities) as a basis for
scaling, and the reliability of the emission factor determine the accuracy of the flux estimates.

1.2.2

Current default emission factor for direct soil emissions

From field studies of at least 1 year’s duration, Bouwman (1996) derived the following relationship for direct
N2O emissions from agricultural soils:
EQUATION 2
E = 1 + 0.0125 ● F
Where E is the emission rate (kg N2O-N ha-1 y-1), the value of 1 kg N ha-1 is the background emission rate and F isthe fertilizer application rate (kg N ha-1 y-1). He suggested that although this may not be adequate to estimate
emissions for local conditions or specific crops it may be sufficient for global analyses. The most recent IPCC
methodology (IPCC, 1997) for estimating direct N2O emission from synthetic fertilizer applied to agricultural soils isbased on Bouwman’s (1996) work. It assumes the emission to be a fixed percentage, 1.25 ± 1 %, of the N applied.
The same emission factor is also applied to commercial organic fertilizers, non-commercial applications ofanimal waste, N in cultivated N-fixing crops (product + residue) and N in other crop residues ploughed into thesoil. Also, the IPCC default approach assumes the emission to be a fixed proportion of the unvolatilised portionof the N applied. (The default values for this portion are 90% for synthetic fertilizers, 80% for organic fertilizers
and animal waste, and 100% for all other categories). The default values for emissions from cultivated histosols
are 5 and 10 kg N2O-N ha-1 y-1 for temperate and tropical climates, respectively. That for N deposition by grazing
animals is 2% of the unvolatilised N.
Many studies have appeared in the last few years that provide substantial additional data on direct emissions.
Table 1 lists some of the results from studies over whole crop seasons (or 12- month periods of grassland
management), and Figure 1 (A. R. Mosier, pers. comm.) shows the distribution of emission factors for data
published since 1994 over study periods ranging from a few days to 2 years, together with earlier data from
Bouwman (1996) relating to studies of ≥80 days’ duration.
Smith et al. (1998a) found that the average emission factor for sites in Scotland in the early 1990s was less thanthe default value of 1.25% of the mineral N applied, and suggested that this might be a result of the generally
lower temperatures at these sites than those covered by the review. However, results for 1997 and 1998 (seasons
with higher than average summer rainfall) gave emission factors for grassland, potato and broccoli that were all
greater than the default value, while those for small-grain cereal crops remained low (Table 1, Figure. 2; Dobbie
et al, 1999). Data from Colorado, USA has shown comparable differences between small grain crops and maize(A.R. Mosier, pers. comm.), but a wider data comparison including data from many regions did not reveal any
such overall effect (Mosier and Kroeze, 1999). Further data analysis is desirable to determine whether, within
this dataset, differences between the emissions from different crops can be identified within other particulargeographical or climatic zones.

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TABLE 1
SOME RECENT PUBLISHED DATA ON N2O EMISSION FACTORS FOR GRAZED AND UNGRAZED INTENSIVE GRASSLAND AND
ARABLE LAND

Source of N/ Crop or land use

Country

Emission factor (%)

Reference

Grassland

UK (1992-4)

0.2-1.4

Clayton et al., 1997

Grassland

UK (1997-8)

0.6-7.1

Dobbie et al., 1999

Arable (small grains)

UK (1994-7)

0.2-0.7

Smith et al., 1998a;

Arable (other crops)

UK (1996-8)

1.2-11.2

Dobbie et al., 1999†

Flessa et al., 1995

Mineral fertilizer

Arable (wheat)

Germany

5.0-8.8

Arable (wheat/barley/sugar beet/OS rape)

Germany

0.7-8.5

Kaiser et al., 1998

Arable (maize)

Canada1.0-4.0

MacKenzie et al., 1998

Arable (wheat)

Mexico1.7-3.8

Ortiz-Monasterio et al., 1996

Arable (maize)

China (NE)

2.0

Chen et al., 1997

Arable (rice)

China

0.3-1.2‡

Xu et al., 1997

Grassland

Costa Rica

6.8

Veldkamp et al., 1998

BananaCosta Rica

1.3-2.9

Veldkamp & Keller,1997

GrasslandUK

0.1-1.4

Yamulki et al., 1998*

Grassland

Germany0.4-1.3

Poggemann et al., 1995*

Grassland

Netherlands

1.0-1.99

Velthof et al., 1996*

Grassland

New Zealand

0.2-1.0

Carran et al., 1995*

Grassland

UK (1996-7)

1.7-3.8

Smith et al., 1998b

Dung / urine (spread)

Dung / urine deposited
During grazing*cited in Oenema et al., 1997.
†

No account taken of unknown amount of mineral N released from 10 t ha-1 of FYM.

‡

No account taken of unknown amount of mineral N released from 5 t ha-1 of pig manure.

Temporal variability
There was a 20-fold variation in annual flux at one grassland site between 1992 and 1998 reported by Dobbie etal. (1999), with the dominant factor being the rainfall around the time of fertilizer application. Flessa et al (1995)
and Kaiser et al. (1998) found that a large proportion of the annual N2O emission from arable land in Germany
followed soil freezing/thawing in winter, as found in earlier work from continental climates (e.g. Goodroad and
Keeney, 1984). In recent years at least, erratic winter weather has resulted in large variations in the extent towhich such freeze/thaw events occur, in many countries, so this suggests that the contribution of such weatherchanges to emissions may vary dramatically from year to year. These observations indicate that a prolonged
period of study is required in many regions before a robust annual mean flux can be obtained, even for one site,
because of short-term vagaries in the weather, both in summer and winter. In hot dry environments where
irrigation is applied, obviously such variations due to weather are minimised. However, variations in the system
of management can be almost as important. For example, variations in time elapsed between fertilization, sowing
and irrigation in a wheat system in Mexico have been shown by Ortiz-Monasterio et al. (1996) to have a large
impact on N2O.

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Figure 1

Frequency distribution of N2O emission factors(percent of fertilizer N applied) for 36 temperatestudies published since 1993, together with data from
Bouwman (1996) for measurement periods > 80 days
and for which the emissions from fertilized plots had
been corrected by subtraction of emissions from anunfertilized control (data for flooded rice notincluded).

Source: A.R. Mosier, pers.Comm. 1999

Figure 2

Annual N2O emission plotted against the amount of
fertilizer N applied, for crops grown in the cooltemperate zone (Scotland).

Continuous line is regression line from Bouwman’s (1996) analysis of emission factors published at that time.
: grassland; : arable (non-cereal) crops; : cereal crops (wheat, barley).
Source: Dobbie et al 1999

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2

METHODOLOGICAL ISSUES

2.1

Selection of good practice methods

It is good practice to use country-specific data, where they are available, for activity levels and conversion factors(e.g. fertilizer consumption, crop production, harvest index), and for N2O emission factors. A decision tree is a
useful device for identification of sources and sub-sources and determination of the methodology to be applied to
calculate emissions, depending on the availability of data and the importance of the source.
Where emissions are described with emission factor or regression approaches, variability can be used instead of
the usual practice of averaging out the heterogeneity. This is done, for example, by presenting frequency
distributions for regions or functional types, or the standard deviation for grid boxes. In many cases the point-bypoint uncertainty is not known. However, even the indication of the maximum and minimum values could be
more helpful than the mean alone for sensitivity and quantitative uncertainty analysis.
Where distinct and easily identified differences in structure and composition of agro-ecosystems coincide withthe functions or management conditions relevant to trace-gas fluxes at the scale considered, the delineation offunctionally different types or production/ management systems provides a useful basis both for measurement
strategies, and development of emission factors. Appropriate selection of classes may lead to reducing thenumber of sites to be sampled so as to derive a reliable emission factor. Maps provide a useful basis fordelineation, and in recent years remote sensing of (agro-) ecosystem characteristics has been used increasingly forclassification and modelling. Such approaches use the variability of a system or landscape instead of ignoring it.

2.1.1

Process models

Reliable regional or global estimates of trace gas emissions depend on an examination of methodologies toreduce the current high uncertainty in the estimates. One potential way to do this is to develop predictive flux
models. Such models have been developed for different processes and gas species on different scales.
The regression relationship based on Bouwman (1996) outlined in Section 1.2.2 above is an example of a simple
empirical model. Several “process-oriented” models of greater complexity have been developed over recent
years, that simulate N trace gas emissions as part of more general simulations of C and N biogeochemicaltransformations in terrestrial ecosystems. These models include CENTURY-NGAS (Parton et al., 1994, 1996),
DNDC (Li et al., 1992), ExpertN (Engel and Priesack, 1993), and NASA-CASA (Potter et al., 1997). Also,
several still more detailed process-based models have been published over the last 10 years (see references in
Frolking et al., 1998). Both the DNDC and ExpertN models were developed specifically for agroecosystems, andtogether with CENTURY-NGAS AND NASA-CASA have been used in a recent model comparisons, in which N2Oemissions from three contrasting agricultural systems were simulated and the predicted values compared with themeasured ones. In most cases the simulated annual N2O fluxes were within a factor of about 2 of the measured
fluxes, although some periods of emission were considerably over- or under-estimated (Frolking et al., 1998).
Often, available data are too limited to satisfy the input requirements of complex models. To overcome thisproblem, sometimes summary models have been developed using key parameters which control the flux andwhich have been identified by detailed process modelling and/or by experimental observation. An approach ofthis type has been used recently to simulate the N2O emission from cool temperate grassland sites in Scotland.
The data of Clayton et al. (1997) and McTaggart et al. (1997) for N2O flux, soil mineral N content, temperature
and water-filled pore space (WFPS) for one site in the 1992-93 and 1993-94 seasons (in fact, one of the datasets
used by Frolking et al., 1998 – see above) have been used to predict the emissions at the same site and elsewhere
in 1997 and 1998. The fluxes were assumed to be capable of exceeding 10 g N2O-N ha-1 d-1 only when the
topsoil mineral N content was >10 mg kg-1 soil, and then flux ranges of 1-10, 10-100 or 100-1000 g N2O-N ha-1
d-1 were predicted according to the temperature/WFPS regime at the time (Conen et al., 1999). Integration of thelog-mean values over time gave generally good agreement with measured fluxes, over a wide range (Figure 3).
Mosier et al. (1998) suggested that process models should be utilised in future inventory methodology
development. Consideration should be given to the question of how such models might be used, for example:•

together with non-spatially explicit subdivisions of a region in areas with similar conditions for N2O fluxes; or•in combination with geographical information on soils and climate (or weather) and management; or•for the purpose of developing “mean” emission factors for the region/district/province considered.

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Figure 3

Comparison of predicted and measured seasonal N2O
emissions from different arable crops and intensive
grassland in Scotland.

Source : Connen et al, 1999

Arising out of the information contained in Section 1.2.2 above, it appears that although the existing default value
for direct soil emissions was the “least bad” method available at the time it was adopted, there is a potential for
updating it, and possibly for refining it to give regional variations according to climate, and possibly according to
special aspects of management practice. The variation in flux with soil water content has been identified as amajor controlling variable in grassland in regions as different as the cool temperate zone (e.g. Dobbie et al.,1999) and the humid tropics (Veldkamp et al., 1998). Up to half the annual emission from arable land can begenerated by winter freeze-thaw events (Flessa et al., 1995; Kaiser et al., 1998). Ways in which the emission
factor could be modified to take account of such effects should be a priority area for new synthesis work.
Current IPCC default emission factors for N2O are given in Table 2.
The gross imbalance in experimental effort between environments in the developed countries and the developing
countries needs to be addressed, particularly as the balance of N fertilizer use is progressively shifting towards
the latter, and as the climates where this N is used are generally at the warmer end of the climatic range. A
coordinated programme that studies emissions from the major crop/soil systems of some of the larger countries,e.g., Brazil, China, India, Indonesia, Nigeria, Pakistan, Vietnam, should be a priority.
Relevant questions relating to methodology development at this stage are:•

Are IPCC defaults adequate? Can they be (or should they be) updated, disaggregated, and/or further refined?
In particular, should there not be different default values for different N inputs (e.g. animal waste, andcombinations of synthetic fertilizers with crop residues or organic manures, may produce a higher percentage
N2O than synthetic fertilizers alone)?

•

What are the uncertainties associated with the default emission factors? Is there any bias in the way they
have been derived?

•

Should countries be asked to calculate, wherever possible, emissions based on both default values and on
locally derived factors, where they are clearly representative?

•

What are the implications of this for uncertainties in, and compatibility among, national inventories?

•

What should happen if a country uses a default emission factor, but has some information that suggests thatthe default may not be entirely appropriate?

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Should there be guidelines/criteria for developing “acceptable” local emission factors? (e.g. for fertilizerderived N2O, that emissions should be measured at a specified frequency following a fertilization application,then at specified reduced frequencies until the next application and after post-harvest cultivation, etc.) What
are key considerations with respect to applicability of emission factors under different conditions?

•

Is additional research needed?

In spite of the difficulties associated with making emission estimates, it is worth noting that the latest revision to
the IPCC Guidelines (IPCC, 1997; Mosier et al., 1998) has been used to make an estimate of N2O emissions at
the global level, and when this estimate was used as input to a simple atmospheric box model the observed
increase in atmospheric N2O with time could be explained reasonably well (Kroeze et al., 1999).
TABLE 2CURRENT IPCC DEFAULT METHOD FOR CALCULATING N2O EMISSIONS FROM DIRECT SOURCES
SourceCrop production

1

N content

Emission factor

Amount of N applied - 10% NH3 + NOx loss

Synthetic N fertilizer
Animal excreta used as fertilizer &other organic fertilizers

Amount of N applied - 20% NH3 + NOx loss

1.25%

Biological nitrogen fixation

Amount of N is 2 ● harvested crop biomass ● Ncontent (3%) for pulses and soybeans

1.25%

Crop residues2

Amount of N is 2 ● harvested crop ● N content
minus harvested parts (45%) minus fraction ofcrop residue that is burnt in field (25% indeveloping countries, <10% in developed
countries) minus fractions used as biofuel and inconstruction

1.25%

Cultivation of organic soils

Area of cultivated organic soils

Temperate regions: 5 kg
N2O-N ha-1 y-1
Tropical regions: 10 kg
N2O-N ha-1 y-1

Livestock production3

N in animal excreta dropped during grazing

2.0%

Grazing
1 Excluding glasshouse farming.
2

Excluding root biomass.

3

Excluding direct emissions of N2O from animals through nitrate reduction in the gut of animals.

Source: IPCC 1997.

2.2

Activity data

The major forms of economic land use activities generating emissions of N2O and other trace gases include
livestock and crop production. Livestock production is the most complex system. To estimate N2O emissions fromanimal manure during and after application as a fertilizer, the following information is required: the number ofanimals in each category (e.g. dairy cattle), N excretion per head by animal type, and the mode and amount ofmanure application, together with the emission factors. For proper estimates of the ammonia and nitrogen oxides loss
(see Table 2) from animal waste, it is essential to know the weather conditions during spreading (turbulence, airtemperature, air humidity and rainfall), the properties of the soil to which the manure is applied, the amount ofmanure per unit area, and the period between application and cultivation.
Outside Europe and North America all these data are scant. Data on animal populations by category, and within acategory (according to age and weight class) are almost non-existent. For many countries only the total number ofanimals within a category is available for a specific year. Data are not available on some animal categories, suchas house pets, horses, buffalo, donkeys, camels. Estimates for regions within countries may be available, but do
not always correspond to the official statistics or are outdated.
In many countries it is difficult to obtain data on the amount and composition (mineral N, organic N, recalcitrant
N) of animal waste for different age classes within animal categories. Therefore, these data have to be estimated368

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from the "average" animal in a particular country or production system. Geographic data on the application rate
and timing of manure application, soil conditions, and weather conditions during application are not available. In
addition to spatial variability, manure application rates, and mode and timing of application, show a strong
interannual variability, which is not easy to include in scaling exercises.
Data on crop production systems that are essential for estimating trace gas fluxes include fertilizer use (including
animal manure and other organic inputs) and the mass of residues which is ploughed into the soil (in units of N),
or the amount produced of the crop(s) whose residues are ploughed under (in units of biomass). Such data may
be available for regions within countries but may not always correspond to the official statistics or may be outdated.
In summary, the economic and attribute data generally have to be inferred from aggregated country totals for thedifferent land-use systems.

2.3

Uncertainty

Parallel to the IPCC sector-specific workshops on good practice guidance, the IPCC is completing a programmeof work on emissions inventory uncertainty. This work will result in recommendations to the IPCC on approaches
to assessing and managing uncertainty. During the IPCC Inventory Experts Group Meeting in Paris (October1998), technical experts in the uncertainty programme came up with a series of questions to be answered in the
sector workshops. These questions are presented in the general background paper, and are elaborated below inthe context of direct N2O emissions from agricultural soils. This working group should discuss and provide
answers to these questions. These answers will contribute to the uncertainty programme’s work on establishing ageneral methodological approach to managing uncertainties in GHG inventories. The UNFCCC Secretariat’s
recent report on “Methodological Issues Identified While Processing Second National Communications:Greenhouse Gas Inventories” (UNFCCC/SBSTA/1998/7) noted that all Annex I Parties who reported
uncertainties with their inventory estimates characterized the uncertainty associated with N2O emissions fromagricultural soils as “high”.
Table 3 lists the types of activity data required for this source category.
TABLE 3
ACTIVITY DATA REQUIRED FOR ESTIMATION OF DIRECT N2O EMISSIONS FROM AGRICULTURAL SOILS
Type of Activity Data

Units
1

kg N/yr

1,2

kg N/yr

Commercial synthetic fertilizer consumption
Commercial organic fertilizer consumption

Livestock and poultry wastes that are applied to soils

kg N/yr

Crop product and residues of nitrogen-fixing crops

kg N/yr

Crop residue returned to soils

kg N/yr

Histosol area cultivated (by climatic zone)

ha/yr

1

It is desirable to collect disaggregated data on individual crops.

2

This value should not include animal waste nitrogen used as commercial fertilizer if the “livestock and poultry wastes that are
applied to soils” data include this nitrogen.

Important questions that should be addressed by the working group on direct N2O emissions from agriculturalsoils include:•

Can quantitative uncertainties be identified for the sub-sources in this source?

•

Can these uncertainties be derived empirically or must expert judgement be used?

•

Are qualitative uncertainty estimates more appropriate in some cases?

•

Are there sub-sources for which uncertainty cannot be estimated?

•

Might uncertainties change over time?

Data on mineral fertilizer production and consumption are probably more reliable than any other data needed foremission estimation. National and international fertilizer manufacturers’ associations can provide good data, andare complemented by national, EU, FAO, OECD etc. statistics-gathering activities covering all major countries,
providing information on consumption, exports and imports, that form part of normal economic management.

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Any gaps are likely to be comparatively minor. Problems such as collection of statistics on bases other thancalendar years are relatively minor as long as 12-month continuous periods can be identified, and as long as theapproach is consistent and transparent, because changes in rates of consumption are fairly gradual.
The uncertainties associated with the other headings in Table 3 are evidently much greater. This poses thefollowing additional questions:•

How might uncertainties vary if international rather than country-specific data are used for the activity data?
(Note that many of the activity data are derived from other data, the individual uncertainties of which willneed to be estimated.)•

What additional work is needed to quantify these uncertainties?

•

Can areas of potential covariance between emissions estimates for sub-sources in this source and othersources or sub-sources be identified?

•

Are there weak spots or areas of inconsistency within this source that should be emphasized (i.e., missing
sub-sources, systematic errors, trend errors)?

•

What documentation is necessary for the default and specific uncertainty estimates?

2.4

Completeness

The OECD/IPCC/IEA phase II development of the IPCC Guidelines methodology for agricultural sources of
N2O was recently described by Mosier et al. (1998), including methodologies for calculating both direct andindirect emissions of N2O related to agricultural production. The methodology attempts to relate N2O emissions
to the agricultural nitrogen cycle and to systems into which N is transported once it leaves agricultural systems.
The methodology is based on the utilization of N as a nutrient for plant growth. Anthropogenic N inputs into
agricultural systems include N from synthetic fertilizers, animal wastes and other organic fertilizers, biologicalnitrogen fixation by crops, cultivation of organic soils, and mineralization of crop residues returned to the field.
Direct sources include those where N2O is emitted directly to the atmosphere from cultivated soils and fertilized
and/or grazed grassland systems. Indirect emissions result from transport of N from agricultural systems into
ground and surface waters through drainage and surface runoff, or emission as ammonia or nitrogen oxides anddeposition elsewhere, causing N2O production.
Basically, the proposed methodology is an emission factor approach. The general rules for calculating N2Oemissions for the different direct sources are listed in Table 2 above.
From the list it is clear that the methodology involves, in fact, an inventory of inputs of N in agricultural soils. It
is complete, since it represents all major agricultural flows of N.
Soil sink
The “soil N2O sink” has merited a question mark in IPCC assessments hitherto, but it is appropriate to address
the issue here. There is clear evidence that in very wet soils, significant reductions of N2O can occur in the soil
before it can escape to the atmosphere, thus reducing the net emission. However, the magnitude of the uptake of
N2O already in the atmosphere is not clear, though some studies have reported small negative (i.e. sink) fluxes;
these have usually been trivial compared with emissions. There is a very good reason for this, which is that theconditions required for N2O reduction inhibit the corresponding transport of the N2O to the microbial sites where
reduction takes place. This contrasts with methane oxidation, in which the conditions promoting the oxidation
also favour the transport of the substrate.
It would be desirable to attempt to put an upper limit on the size of the sink. As it may well be at least two ordersof magnitude less than the source, this would make the sink <0.04 Tg N ha y-1.

2.5

Other important issues

2.5.1

Linkages with other sources

Some of the databases used to derive activity data for this source will be used to derive emission estimates forother sources. Countries need to ensure that:•370

consistent activity data sets are used,

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories•

consistent conversion factors are applied to activity data, and•the totals of activity data across sources and sub-sources are correct.

For example, crop production data may be used to estimate non-CO2 emissions from agricultural residue burning,
N2O emissions from agricultural soils, non-CO2 emissions from biofuel combustion, and CH4 emissions and carbon
sequestration from waste management. In this case, not only should the source of crop production data be the samefor all four sources, but also the residue to crop mass ratios and other conversion factors (dry matter fractions, carbon
and nitrogen fractions) used to estimate emissions from the latter four sources must be consistent.1
Also, the crop residue production that is implied by the crop production statistics for each crop should beconsistent with the assumptions used to estimate the amounts of residue that are burned, ploughed under, used as
fuel, treated as waste, and the amounts that are used in other applications that might not be included in theinventory (e.g. as fodder and construction material). Another example is animal waste data, which in addition to
being used in the agricultural soil calculations, are used to estimate CH4 emissions from manure management andmay be used to estimate non-CO2 emissions from biofuel combustion. In countries that utilise animal wastes in avariety of applications (e.g. as fertilizer, fodder, construction material, and biofuel), the sum of the parts should
not be greater than the whole. The working group should review and document these linkages among sector andsubsector activity data so that QA/QC guidance can be developed for this source.

2.5.2

Corrections to Revised 1996 IPCC Guidelines

The Agriculture chapter of the IPCC Guidelines includes methodologies to estimate CH4 emissions from entericfermentation; CH4 and N2O emissions from manure management; CH4 emissions from rice cultivation; CH4, CO,
N2O, and NOx emissions from savanna burning and from agricultural residue burning; and N2O emissions fromagricultural soils. Activity data and emission factors overlap between source categories; however, there are someinconsistencies in the default values and use of these variables across and within sub-sections of the IPCC
Guidelines. The following is a preliminary list of inconsistencies across sub-sections.
Nitrogen Fractions
Table 4.19 default parameter for the fraction of nitrogen in N-fixing crops (FRACNCRBF) in Agricultural Soils
sub-section (p. 4.94) is inconsistent with the default values for soya beans in agriculture residue burning section.
Residue to crop product mass ratios
The Residue Burning sub-section contains crop-specific values (Table 4-17), while the “Residue crop
application” part and the “Biological N fixation” part of the Agricultural Soils sub-section assume a ratio of 1 for
all crops. Also, the procedures for estimating crop residue mass vary between the Residue Burning and theAgricultural Soils sub-sections. (Note: The table of conversion factors in the Residue Burning subsections
contains errors [i.e., dry matter fractions from Strehler and Stutzle], and should be corrected.)
Manure Management System Usage
Table 4-21, p. 4.101, in Agricultural Soils sub-section is inconsistent with Table B-3 in Appendix B in Manure
Management sub-section. Both are based on Safely et al., 1992. Table B-3 is the most updated and should
replace Table 4-21.
Daily Spread
The Reference manual uses the term “daily spread” to mean two different processes. “Daily spread” is used in thecontext of Safley et al.’s (1992) work (i.e., to mean a waste management technique), as well as to encompass all
forms of application of wastes to soils (daily spreading, spraying after storage, etc. ). Both usages of the term
appear in the Agricultural Soils sub-section. The latter use of the term should probably be dropped from the
Guidelines to avoid confusion, and another term be devised for this process.
Dry Weights
It is not clear if the dry weight conversions are oven dry or air dry. This should be clarified and conversions
should be consistent across sources.
Within the Agricultural Soils sub-section itself, there are some errors, inconsistencies, and areas for
improvement. Table 4 highlights a preliminary list of errors and offers corrected formulas as well asrecommendations for further improvements. The text should also be revised to incorporate any changes.

1

At present, some of the default values in the Guidelines are not consistent across source categories.

N2O: Direct Emissions from Agricultural Soils

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2.5.3

Accounting for mitigation measures

At the third Conference of the Parties to the UNFCCC in December 1997, Annex I Parties agreed to legallybinding emission reduction commitments which are specified in Annex B of the Kyoto Protocol. Article 7 of theProtocol requires decisions on the use of inventories to demonstrate compliance with commitments be made by
the Conference of the Parties serving as the Meeting of the Parties at its first session (COP/MOP1), and Article 5
requires the COP/MOP1 to make decisions on national systems for inventories, including decisions on revisions
to the IPCC inventory methods based on work of the IPCC. Now that there are binding national commitments
under the Kyoto Protocol to the UNFCCC, the IPCC should consider the ability of the IPCC inventory methods
to accurately account for mitigation measures. COP/MOP1 may be in place by 2001 or 2002; therefore, the IPCC
should reach conclusions on this issue by 2001.
The current IPCC method for estimating direct N2O emissions from agricultural soils may not capture all of theemission impacts of possible national mitigation measures, depending upon how the method is implemented.
Implementation depends, in part, upon the clarity and detail of the methodology description in the IPCC
Guidelines.
The current IPCC method for estimating N2O emissions from this source utilises three types of primary activity data:•

Additions of nitrogen to soils from fertilizer application (synthetic and organic, including animal wastes),
cultivation of nitrogen-fixing crops, and incorporation of crop residues;•

Mineralisation of soil organic matter (humus) through cultivation of histosols, and•Additions of nitrogen to soils from grazing animals.

Mitigation activities that directly reduce the magnitude of these activities (e.g., reduced national consumption offertilizers, reduced national populations of grazing animals) will be reflected in national inventories because theunderlying primary activity data will reflect these changes. However, mitigation measures that affect a) the
conversion factors that are applied to the primary activity data, or b) the emission factors that are applied to thefinal activity data, may not be reflected in national inventories unless the inventory calculations incorporate thesechanges accurately. This may be particularly problematic if mitigation measures are implemented to reduce a
different GHG source than N2O from agricultural soils, and the effects on sources that are not being targeted
directly are not evaluated or monitored. For example, if livestock feed practices are altered to improve livestock
productivity (and reduce associated CH4 emissions from digestion), and this results in a change in nitrogenexcretion per head, new nitrogen excretion rates will need to be developed and used in the inventory calculations.
Another example is soil and crop management practices to increase soil carbon stocks, such as use of no-tillrather than tillage systems or use of “organic” rather than conventional cropping systems (e.g. Drinkwater et al.,1998). If these management practices also result in altering the fraction of applied nitrogen that is emitted as
N2O, and the emission factor is not revised, this additional benefit will not be captured in the national inventory.
This working group should consider examples of other mitigation measures whose emission impacts might not becompletely captured, and develop recommendations for improvements to the Guidelines to address this potential
shortcoming. There are two primary issues to consider:•

Guidance to users for the selection of appropriate stratification schemes for emission estimates, based on thescale of the exercise and the available spatial data, and the development of site-specific emission factors, and•A discussion of the possible impacts of mitigation measures across sources.

3

REPORTING AND DOCUMENTATIONThe UNFCCC Secretariat’s recent report on “Methodological Issues Identified While Processing Second
National Communications: Greenhouse Gas Inventories” (UNFCCC/SBSTA/1998/7) noted that while mostcountries reported N2O emissions from agricultural soils, the thoroughness of reporting was highly variable
among countries.

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Referencea

FracR default value = 0.45 kg N/kg crop-N

The N2O emission is expressed as a percent (e.g.,
gN2O-N/102gN) in Appendix A, Table A-1

FracR default value = 0.5 kg N/kg crop-N because
text assumes aboveground residue/crop mass ratio
equals 1. Also, definition of FracR on page 4.93
should be corrected to “fraction of abovegroundcrop biomass (residue + product) that is removed
from the field as crop.

Recommended Improvements

Subtract fraction used in construction, fractionused as biofuel, and fraction used as fodder:(1-FracBURN-FracBIOFUEL-FracCNST- FracFOD)

Include organic fertilizers other than crop
residues and animal wastes. State the default
volatilization fraction for these fertilizers.

Based on Table 4-17, the factor of 2 is much too
low for pulses & soybeans. Current equation
does not apply to fodder crops such as alfalfa.

Acknowledge that some countries use some of
their animal waste as animal feed or forconstruction: FAW = (Nex ● (1-(FracFUEL +FracGRAZ + FracCNST +FracAF+ FracGASM)

Change name to FracProd because the variable’s
definition is the amount of total abovegroundbiomass that is removed as product. However,this variable is not needed if the equation for
FCR is corrected as shown in top row above.

Include nitrogen from organic fertilizers otherthan crop residues and animal wastes.

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TABLE 4

FCR = [Crop0 ● Res0/Prod0 ● FracDM ● FracNCR0]+ [CropBF ● ResBF/Prod0 ● FracDM ● FracNCRBF] ●(1-FracBURN)

Corrected Approach

CORRECTIONS TO SECTION 4.5 (IPCC GUIDELINES) GREENHOUSE GAS EMISSIONS FROM AGRICULTURAL SOILS
Current Approach
FCR = 2 ● [Crop0 ● FracNCR0 + CropBF ●FracNCRBF] ● (1-FracR) ● (1-FracBURN)

N2ODIRECT = [(FSN + FAW+ FBN + FCR) ●EF1] +FOS ● EF2

Pg 4.92,
Equation 1

Pg 4.92,
Equation 1
FBN = 2 ● CropBF ● FracNCRBFThe N2O emission is expressed as gN/kg ofnitrogen in Appendix A, Table A-1

Replace footnote c on Solid storage and drylot
with footnote b (To be reported under “Manure
Management”)

FBN = (CropR + CropBF) ● FracNCRBF where CropR
is the crop residue specific to the crop.

Pg 4.96

Footnote c on Solid storage and drylot (To bereported under “Agricultural Soils” under direct
soil emissions from agricultural fields after
spreading)

FAW = (Nex ● (1-(FracFUEL+ FracGRAZ +FracGASM)

Pg 4.92,
Equation 1
Pg 4.92,
Equation 1

Pg 4.104, Table
4-22

NLEACH = [NFERT+NEX] ● FracLEACH

Pg 4.94, Table
4.19

Pg 4.106,

All page references from Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference Manual

Equation 3aNote: These corrections should be made in Workbook as well.

N2O: Direct Emissions from Agricultural Soils

Background Paper

3.1

Current IPCC reporting guidelines2

The IPCC Guidelines are used to guide countries in the preparation and submission of inventories of annual
greenhouse gas emissions and sinks to the UNFCCC Secretariat. The Guidelines establish:
Standard tables, definitions, units, and time intervals for reporting all types of emissions to ensure consistency ofreporting across countries;
The necessary documentation to enable comparison of national inventories, including worksheets, major
assumptions, methodological descriptions, and enough data to allow a third party to reconstruct the inventory
from national activity data and assumptions, and an uncertainty assessment.
Nitrous oxide emissions from agricultural soils are reported under the IPCC category 4D, within the Agriculture
sector. At present, the Reporting Instructions do not disaggregate this category into sub-sources, e.g., directemissions from agricultural soils, direct emissions from grazing animals, indirect emissions from agriculturalsoils and livestock wastes. As distinct (but related) components, these three sub-sources could each be listed as aseparate category under agricultural soils.
Estimates of N2O emissions from agricultural soils are reported in Vol 1 IPCC Table 4: Sectoral Report for
Agriculture, which calls for estimates for each agricultural source of CO2, CH4, N2O, and precursor gases (NOx,CO, NMVOC) except agricultural soil sources of CO2 (which are reported in Vol 1 IPCC Table 5: Sectoral
Report for Land-Use Change and Forestry). Currently, the table does not have a separate entry for each of the
sub-sources within the N2O from agricultural soils source. Because this source is composed of three distinct subsources that are based on partially, but not completely, overlapping activity data and emission factors, reportingby sub-source rather than by source total would be more meaningful and transparent to third party reviewers. The
working group should determine what level of disaggregation (to the three sub-sources, or further) would be
optimal in terms of transparency.
Estimates of N2O emissions from agricultural soils are also reported in aggregate in IPCC Tables 7A (Summary
Report), 7B (Short Summary Report), and 8A (Overview Table). The working group should determine what levelof disaggregation is appropriate in these tables too. And given the recommended level of disaggregation, theworking group should also evaluate the use of “PART”, “ALL”, “NE”, and IE, and “OE” in the Table 8A and theadequacy of the Disaggregation Key (IPCC Table 8B).
In addition to the lack of transparency in the reporting tables, there is also a lack of clear guidance on reportingof how estimates were calculated. Issues to consider in order to address this shortcoming include:•

Reporting of the estimation methodology, including algorithms and equations used and assumptions made;•

Reporting of the source and nature of activity data and emissions factors, including analysis of trends;•

Reporting of how emission estimates may have changed from previous inventories, and•Reporting on QA/QC procedures.

3.2

Confidential business information

The activity data and conversion factors needed to estimate direct N2O emissions from agricultural soils are all
likely to be publicly available. No issues associated with data confidentiality are expected to arise in reporting
emission estimates from this source.

2

Note from authors: This section reflects the state of IPCC reporting guidance in early 1999, when this paper was
written. Since then, revised reporting tables for national greenhouse gas inventories have been drafted andagreed to by the Conference of the Parties (see http://www.unfccc.int/resource/docs/cop5/07.pdf). These
revised reporting tables, which are referred to as the “Common Reporting Format”, address many of the issues
discussed in this section.

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

4

INVENTORY QUALITY

4.1

Introduction

Inventory quality assurance and quality control (QA/QC) is a process integral to the development of a credible
inventory. A well-developed and well-implemented quality assurance programme fosters confidence in the final
inventory results regardless of the purpose and goal of the inventory. A successful quality assurance programme
requires internal quality control procedures and an unbiased, external review and audit. The internal QC activities
are designed to ensure accuracy, documentation, and transparency. The external review process is designed tominimize errors that occur in the preparation of emission inventories, and reduce or eliminate potential inherent
bias. Figure 4 outlines the flow of information and processes followed at each step.
Figure 4

Inventory QA/QC Process
Data Collection Agencies

Internal QC:

Activity data and calculations

Documentation:

Activity data provided to the government agency, and results of internal QC

Inventory Agency
Review/QA:

Activity Data, emission factors, and calculations

Internal QC:

Compilation of national inventory from activity data, conversion factors, and emission
factors

Documentation:

Results of compilation and results of QA/QC

Reporting:

Official submission to UNFCCC

External Review
External Review:

External audit, stakeholders, peer & public review of inventory results, externalverification against other data etc.

Documentation:

Results of external review

UNFCCC Secretariat
External Review:

4.2
4.2.1

Requires standard format and transparency – ensure consistency with other inventories
and external data

Internal inventory QA/QC systems
Data collection agency activities

Activity Data QC
The personnel that collect data are responsible for reviewing the data collection methods, checking the data toensure they were collected and aggregated correctly, and cross-checking the data with previous years to ensure
the data are reasonable. The basis for the estimates, whether statistical surveys or “desk estimates,” must be
reviewed and described as part of the QC effort. The various data sets that are required for the direct N2Oemissions from agricultural soils would be collected by different agencies and/or organizations:

N2O: Direct Emissions from Agricultural Soils

375

Background Paper

Commercial Fertilizer Consumption Data
Commercial fertilizers include both synthetic and organic fertilizers. Annual synthetic fertilizer consumption
data are generally available in-country; if not, statistics on fertilizer production, consumption and trade areavailable on the internet from the International Fertilizer Industry Association (which gives data on the various
fertilizer types), as well as the reports on fertilizer use by crops compiled by FAO (FAO/IFA/IFDC, 1994, andlater editions). This information may become important if emission factors for individual crops/crop groups aredeveloped in the future. Annual commercial organic fertilizer consumption data may or may not be available; ifavailable, these data, and the synthetic fertilizer data, would typically be collected by a country’s ministry ofagriculture or a fertilizer trade organization.
Livestock and Poultry Wastes that are Applied to Soils
These data will be obtained from the N2O from manure management inventory. The personnel that obtain thesedata for the soil calculations are responsible for determining that the values used do not include wastes that are
deposited by grazing animals and wastes that are used for other purposes (such as for biofuel or feed).
Crop Product and Residues of Nitrogen-Fixing Crops, and Crop Residue Returned to Soils
These data will be derived from annual crop production statistics. These statistics are generally collected by acountry’s ministry of agriculture or similar organization; if not, FAO statistics may be used.
Histosol Area Cultivated (By Climatic Zone)
These data may be difficult for many countries to obtain. While geo-referenced databases of soil types are
generally available from the ministry of agriculture or similar organization, information on which areas arecultivated may not be readily available. In some cases, an academic research study may have compiled these data
at a national or regional level.
Wastes from Grazing Animals
These data will be obtained from the N2O from manure management inventory.
Activity Data Documentation
Documentation is a crucial component of the review process because it enables reviewers to identify mistakes
and suggest improvements. The following information should be included in the documentation:•

A detailed description of the methods used to collect the activity data, and•A discussion of potential areas of bias in the data, including a discussion of whether any of the data may be
misrepresentative of the country.

4.2.2

Inventory agency activities

Inventory Agency Review (QA) of Activity Data
Before accepting the activity data, the inventory agency should assess the activity data. This review involves
close cooperation with the personnel responsible for collecting, compiling, and analyzing the data. The
assessment should include a review of the detailed methods used to collect the data, including a review of any
surveys and interviews performed to collect the data. In addition, the assessment should include a comparison of
the activity data with historical data and with similar data used for other sources in the inventory, and anevaluation of the potential for bias and areas for improvement.
Inventory Agency QC on Compiling National Emissions
In addition to a thorough quality assessment of data discussed above, the inventory agency should ensure that theprocesses of aggregating and converting activity data to develop the national inventory undergoes quality control.
This should include, among other things:•

Cross-referencing the crop product and crop conversion factors with values used to estimate emissions fromother sources;•

Ensuring that all bottom-up activity estimates are complete and that there has been no double counting ofactivity levels among sources, and•Comparing with national trends to look for anomalies.

In addition, the emission factors should also undergo review. QC procedures include reviewing the values
available (default or otherwise) and documenting the rationale for selecting specific values.

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Inventory Agency Documentation on Compiling National Emissions
Documentation is a crucial component of the review process because it enables reviewers to identify mistakes andsuggest improvements. If default emission factors are not used, a detailed description of the equations and/or
approach used to derive emission factors is needed. The input parameters must be defined and the process by which
they are obtained must be described. The frequency of data collection and estimation, and results of determinationsof accuracy and precision, must be elaborated. In addition, a standardized reporting form is recommended to provide
transparent information on the steps taken to calculate the emission factors and derive the activity data. Each stepshould contain the numbers used in each calculation, including the source of any data collected.

4.3

External inventory QA/QC systems

External QA activities include a planned system of review and audit procedures conducted by personnel not
actively involved in the inventory development process. The key concept is independent, objective review toassess the effectiveness of the internal QC programme, the quality of the inventory, and to reduce or eliminate
any inherent bias in the inventory processes. Several types of external reviews, or audits, may be appropriate forthe inventory of direct N2O emissions from agricultural soils.
Third party audit by an accredited organisation, expert, independent third party
An audit of the documentation and calculations ensures that each number is traceable to its origin.
Expert (peer) review
Although a detailed peer review would be appropriate when a procedure for determining N2O emissions is first
adopted or revised; it would not be needed on an annual basis. Such a review is designed to ensure that themethodology is rigorous, accurate, and that the data and assumptions reflect the best available information.
Stakeholder review
Review by industrial organizations and government can provide a forum for review of the methods used.
Public review
Some countries make their entire inventory available for public review and comment. This process may result ina range of comments and issues broader than those from other review processes.

5

CONCLUSIONS

Direct emissions of N2O from agricultural soils have increased substantially over the last few decades, in parallel withincreasing use of N fertilizers. Current emissions, which have been estimated by the IPCC Phase II methodology to beabout 2.1 Tg N y-1, are likely to increase still more in future, as inputs of N to agriculture continue to rise.
The present IPCC default emission factor for N2O of 1.25±1.0 percent of the N applied must necessarily stand forthe time being, but there is considerable scope for more data analysis to see whether significant differences
between crop types and/or between regions and climatic zones are now discernible. In some variable
environments, several years of study will be needed to derive robust mean emission values. The soil sink for N2O
is unlikely to exceed 1 percent of the soil emission source
In compiling national GHG inventories, it is good practice to use country-specific data, where available, for theactivity data and N2O emission factors. It is also desirable, if the data are available, to report frequency
distributions for emission factors, rather than just to average out the heterogeneity. There is a potential for
reducing the present high uncertainty in emission estimates through the development of predictive flux models.
In the course of calculating N2O emissions at the country level, there is a need to ensure consistency in activity
data sets, crop conversion factors and the like. Also, a number of corrections are required to the methodologies
contained in the IPCC Guidelines, to remove inconsistencies. Disaggregation of agricultural soil emissions into
component sub-sources would improve the transparency of the information.
Improvements to methods for estimating emissions may also be needed to determine the impacts of possible
mitigation measures, both those aimed directly at N2O reduction but also soil management measures designed toincrease soil carbon.

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To satisfy quality assurance and quality control requirements, there needs to be detailed documentation of themethods used to compile activity data and the approach used to derive emission factors, coupled withindependent review and audit procedures.

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