analysis of methodologies for calculating greenhouse gas

Analysis of methodologies for calculating greenhouse gas and ammonia emissions and nutrient balances
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M e t h o d o l o g i e s & W o r k i n g p a p e r s
ISSN 1681-4789
ISSN 1977-0375
2011 edition
M e t h o d o l o g i e s a n d W o r k i n g p a p e r s
Analysis of methodologies for calculating greenhouse gas and ammonia emissions and nutrient balances
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and nutrient balances
Analysis of methodologies for calculating greenhouse gas and ammonia emissions and nutrient balances This document is the result of the DireDate project's task 3. DireDate stands for 'Direct and indirect data needs linked to the farms for agri-environmental indicators'. The DireDate project is a study financed by Eurostat, European Commission, and undertaken by a consortium led by ALTERRA (NL) (Service Contract 40701.2009.001-2009.354). The general objective of DireDate is “to create a framework for setting up a sustainable system for collecting a set of data from farmers and other sources that will serve primarily European and national statisticians for creating the agreed 28 agri-environmental indicators (AEIs) and thus serve policy makers, but as well agricultural and environmental researchers, observers of climate change and other environmental issues linked to agriculture”.
Authors and affiliation
Barbara Amon, Nicholas Hutchings Stefan Pietrzak Finn P. Vinther Per K. Nielsen Hanne D. Poulsen Ib S. Kristensen
Department of Sustainable Department of Agro-ecology Institute for Land Reclamation Agricultural Systems, and Environment and Grassland Farming University of Natural Resources University of Aarhus IMUZ and Applied Life Sciences, Denmark Falenty, Poland Wien, Austria
Editors
Johan Selenius, Ludivine Baudouin, Anne Miek Kremer - Eurostat
The views expressed in this document are those of the authors and do not necessarily reflect the views of the European Commission and/or of the institutions or countries in which authors work. Neither the European Commission nor authors are responsible for the use that may be made of the information contained in this document.
4Analysis of methodologies for calculating greenhouse gas and ammonia emissions and nutrient balances
Table of Contents
1.2 Nitrogen and phosphorus balances........................................................................... 8
1.4 Conclusions and Recommendations ....................................................................... 12 1.4.1 Methodologies............................................................................................. 12 1.4.2 Importance of coefficients........................................................................... 12 1.4.3 Detailed procedures needed for emission abatement strategies ............... 12 1.4.4 Data collection ............................................................................................ 13
2 Introduction ........................................................................................................................... 14
3 Data requirements in relation to emissions of greenhouse gases and ammonia................. 15
3.1 Aim........................................................................................................................... 15
4 Analysis of data necessary to estimate emissions of greenhouse gases and CLTRP compounds from manure management................................................................................ 18
4.1 Basic Data................................................................................................................ 18
4.3 CH4 emissions from manure management.............................................................. 20
4.4 N2O from manure management............................................................................... 22
4.6 NH3 emissions from manure management.............................................................. 23
4.7 Data requirements to estimate NH3 and GHG emissions........................................ 24 4.7.1 Data requirements ...................................................................................... 24 4.7.2 Data collection ............................................................................................ 27
5 Data necessary for the calculation of N and P balances ...................................................... 31
5.1 General .................................................................................................................... 31
5.3 Data requirements for N and P balances ................................................................ 38 5.3.1 Farm nitrogen balance................................................................................ 38 5.3.2 Soil nitrogen balances ................................................................................ 40 5.3.3 Phosphate balances ................................................................................... 41
6 Coefficients related to emissions of GHG, ammonia and N balances.................................. 45
6.1 Gaseous emission coefficients ................................................................................ 45
6.2 Nitrogen excretion.................................................................................................... 45 6.2.1 Estimating nitrogen retained in animal products......................................... 46 6.2.2 Estimating nitrogen consumed in feed ....................................................... 46 6.2.3 Calculating nitrogen excretion .................................................................... 47
7 Sampling strategy ................................................................................................................. 50
7.1 Disaggregation of emissions of GHG and NH3, and of N balances ........................ 50
7.2 Stratified sampling strategy ..................................................................................... 50
8 Conclusions and recommendations...................................................................................... 52
References .................................................................................................................................. 53
1 Summary
Agriculture has relatively large shares in the total emissions of ammonia (NH3) and the greenhouse gases methane (CH4) and nitrous oxide (N2O) into the atmosphere. These gases have also relatively large ecological impacts, including (e.g. Sutton et al., 2011):
• A decline in human health, due to NH3 induced formation of particle matter (PM2.5) and smog;
• Plant damage through high NH3 concentrations in air;
• A decrease in species diversity of natural areas due to N enrichment through atmospheric deposition of NH3;
• Acidification of soils because of deposition of NH3;
• Global warming because of emission of CH4 and N2O; and
• Stratospheric ozone destruction due to N2O
Nitrogen (N) and phosphorus (P) are the main crop growth limiting nutrients in agriculture. Losses of N and P into the wider environment have major ecological impact, including the abovementioned impacts, and
• Pollution of ground water and drinking water due to nitrate leaching;
• Eutrophication of surface waters due to N P enrichment, leading to excess and possibly toxic algal blooms and a decrease in faunal and floristic species diversity.
Moreover, the production of N fertilizers is energy-intensive and accompanied by large CO2 emissions. Phosphorus fertilizers are produced from scarce rock phosphate resources, which will be depleted within decades unless appropriate measures are taken. Hence, N and P balances are key agri-environmental indicators.
There are various diffuse sources of NH3, CH4 and N2O in agriculture. Estimating these sources accurately is not without difficulty. Also, N and P balances of agricultural systems are not easy to assess. Because of the importance and complexities involved in the accounting of ammonia and greenhouse gas emissions, and of N and P balances of agricultural systems, a special task (Task 3) of DireDate related to analysing the methodologies for calculating NH3, CH4, N2O emissions and N and P balances. Particular emphasis was given to the coefficients used in the calculations and the underlying data needs, and to identify best practices for these calculations, based on available scientific research.
The purpose of this Report is to briefly summarize the results of Task 3 of the DireDate Project. The objective of Task 3 is:
• To analyze the methodologies for calculating greenhouse gas and ammonia emission and nutrient balances (nitrogen and phosphorus), with particular stress on the coefficients used in the calculations and the underlying data needs, and
• To identify best practices for these coefficient calculations, based on available scientific research.
1 Summary
1.1 Greenhouse gas and ammonia emissions
Greenhouse gas emissions from agriculture occur from a number of sources. Dominant sources of methane (CH4) are enteric fermentation, manure management and wetlands, including paddy rice fields (Figure 1). Direct sources of nitrous oxide (N2O) are manure management and agricultural soils. Indirect sources of N2O are the emission of ammonia (NH3) and the leaching of nitrate (NO3) from agriculture (Figure 1).
Figure S1: Schematic representations of the main sources of NH3, CH4, and N2O emissions in agricultural systems
Emissions of greenhouse gases are within the scope of the UN Framework Convention on Climate Change (UNFCCC) whereas those of ammonia are within the scope of the UN Convention on Long- Range Transboundary Air Pollution (CLTRP). Guidance on the methodologies for calculating greenhouse gas and ammonia emissions is provided in the IPCC Guidelines (‘the Guidelines’) and the EMEP/EEA Air Pollution Emission Inventory Guidebook (‘the Guidebook’) respectively. The trend seen within both UNFCCC and CLRTP is for emission limits to be progressively reduced over time. For both greenhouse gas and ammonia emissions, agriculture represents a major source. When faced with the need to reduce emissions, countries are usually faced with a choice between a number of different abatement measures. The implementation of abatement measures will often result in an increased cost to agriculture and to the environmental authority that must monitor compliance. Identifying the most cost-effective abatement measures for agriculture requires a range of activity data to be collected.
Emissions are estimated by multiplying activity data with emission factors. Compiling the national inventory therefore comprises two main steps: (i) obtaining national activity data and (ii) choosing emission factors (either default or country specific emission factors).
Agricultural emissions strongly depend on the animal housing, and on the manure management system (MMS) distribution. These data are a mandatory pre-requisite for accurate emission estimates, with a low range of uncertainty. The impact of mitigation measures on the national emissions reported under UNFCCC and CLRTP must be documented and this is only possible if representative data on the MMS distribution are available. A lack of these data leads to two major disadvantages:
1 Summary
1. Country-specific values can only to a small extent be integrated in the national emission inventory. Major parts of the inventory must be set up with default values that misrepresent the processes typically found in the respective country.
2. Due to the lack of activity data, the effect of mitigation measures cannot be included in the national emission inventory.
1.2 Nitrogen and phosphorus balances
The gross nitrogen and phosphorus balances provide holistic indicators of the related environmental pressure exerted by agriculture. For N, significant losses occur to the atmosphere in the form of ammonia, nitrous oxide, nitric oxide (NO) and dinitrogen (N2). Ammonia, nitrous oxide and nitric oxide are pollutants, whereas the emission of dinitrogen reduces the effectiveness of manure and fertilisers and the fertility of soils. Nitrogen is lost to aquatic environments in the form of nitrate, ammonium and dissolved organic N, all of which can lead to pollution and all of which reduce the fertility of the soil. The nitrogen flows and losses in agricultural systems are schematically shown in Figure 2.
Unlike greenhouse gas and ammonia emissions, countries are not required to report N and P balances for agriculture as part of any international conventions. As a consequence, there is no organisation equivalent to the IPCC or UNECE who has responsibility for standardising and improving the methodology to calculate such balances. However, OECD has established a de facto standard for gross N balances, and the soil N balance calculated by the CAPRI model has gained acceptance in European policymaking. Furthermore, the Task Force on Reactive Nitrogen (TFRN), established under CLRTP, is currently establishing national N balances that include agriculture. As an organisation established within an international convention and dedicated specifically to N, we consider that that in the long term, the TFRN is the appropriate organisation to standardize and improve the methodology related to N balances. We note, however, that while the scientific community is strongly represented in the TFRN, the number of statisticians is low. We would therefore encourage representatives of national statistical bureau to become more involved in the work of this organisation.
Figure S2: Schematic representations of the main nitrogen flows and losses in agricultural systems.
1 Summary
1.3 Data needs and data collection
The data needs for calculating NH3, CH4, N2O emissions and N and P balances are relatively large, especially for large emissions sources, because of the required accuracy for estimates of large sources. Currently, these data are not always available in Member States.
Based on experiences in various countries, it is suggested that farm structure surveys should be carried out every five years for collecting information about housing systems, manure storage systems and manure application techniques. Table 1 presents the list of data that should be collected. Table 1 distinguishes the following main NH3, CH4 and N2O emissions sources:
1. housing (cattle, pigs, and poultry),
2. water management,
4. slurry and farmyard manure application techniques, and
5. the diets of the animals.
Table 1 qualifies data requirements into “optimum” and “minimum” data collection requirements. Activity data listed under “minimum requirement” must be collected, because without these data, a proper inventory reporting is not possible. The effect of mitigation measures cannot be shown in the inventory and the cost effectiveness of mitigation measures cannot be assessed. Activity data listed under “optimum requirement” should be collected for more accurately estimating inventories. They offer more possibilities for country-specific and cost-effective mitigation measures and enable the assessment of environmental impacts of farm management practices. For most of these data, the additional effort for collecting them is small and the additional effect is large.
1 Summary
Table S1: Data to be collected through surveys at farm level
Activity data collection Reasoning Housing cattle - minimum requirement
Liquid / solid system Tied / loose housing
EF* differ between both systems, system has great influence on subsequent losses
Grazing Necessary for estimation a consistent N flow, necessary for NH3 and N2O emission estimates, IPCC requires data on grazing
Housing cattle – optimum requirement Subcategory of housing systems prevalent in the country Floor system Yard
Considerable differences in emissions; easy to answer for the farmer; necessary for the assessment of mitigation measures
Housing pigs - minimum requirement
Liquid / solid system EF differ between both systems, system has great influence on subsequent losses
Housing pigs – optimum requirement Subcategory of housing systems prevalent in the country Floor system Yard Air scrubber
Housing poultry - minimum requirement Housing system Manure treatment
Considerable differences in EF; easy to answer for the farmer
Housing poultry - optimum requirement Drinkers
Frequency of manure removal from the house
Water management – optimum requirement Cleaning of the house, water addition to slurry Diluted slurry emits less NH3
Slurry storage - minimum requirement
Slurry store cover Great influence on NH3 emissions; cost effective mitigation measure; likely to become mandatory in the future
Slurry storage - optimum requirement Store size
Slurry treatment
Slurry storage during warm and cold season
Considerable differences in emissions; Easy to answer for the farmer; necessary for the assessment of mitigation measures
FYM storage - optimum requirement Size of the store and duration of storage FYM treatment Direct FYM application Duration of FYM storage Cover of FYM stores
1 Summary
Activity data collection Reasoning Slurry application - minimum requirement
Application technology
NH3 emissions after slurry application are by far the largest contributors to total NH3 emissions. Emissions can be effectively abated by low emission application techniques. Some countries give subsidies for low emission application techniques. Environmental effect of these subsidies does not show up if activity data are unavailable.
Application to grassland or arable land Differences in EF
Slurry application – optimum requirement Timing and amount of application
Incorporation after application
Considerable differences in emissions; easy to answer for the farmer; necessary for the assessment of mitigation measures; esp. timing and amount of application are low cost or even no cost mitigation measures. They will only show up in the inventory if activity data are available.
FYM application - minimum requirement Application to grassland or arable land Differences in EF
Incorporation after application Drastically reduces NH3 emissions; only measure available to reduce NH3 emissions after FYM application.
Animal diet – optimum requirement
Components of cattle diet
Important influence on N excretion and CH4 emissions from enteric fermentation; information will greatly help to improve national defaults on CH4 emissions from enteric fermentation, N and VS excretion; all mitigation measures set at the beginning of the chain will have the largest potential to reduce emissions
Components of pig diet
Important influence on N and VS excretion; information will greatly help to improve national defaults N and VS excretion; all mitigation measures set at the beginning of the chain will have the largest potential to reduce emissions
Phase feeding for pigs
One of the most effective measures to reduce N emissions from pig manure; measure can be implemented a low or no costs; farmers might even gain by reducing N content in the pig diets.
Farm-scale data - minimum requirements Number of livestock present, with major livestock categories identified separately
Required for calculating NH3 and N2O emissions and for calculating or checking N and P balances
Import of N fertiliser Required for calculating NH3 emission and N balances Import of protein supplements Import of energy supplements Export of protein-rich cereals Export of other cereals
Required for calculating or checking N and P balances
Farm-scale data -optimum requirements Import of animal manure Import of other organic manure Import of bedding material Export of animal manure Export of straw
These data enable a more accurate calculation of N and P balances and are necessary if N and P balances are to be disaggregated below the national scale.
* Emission Factors
1 Summary
1.4 Conclusions and Recommendations
1.4.1 Methodologies
The methodologies for calculation of greenhouse gas and ammonia emissions are enshrined in international law, so are not for discussion. In nearly all European states, agriculture is defined as a key source with regards to greenhouse gas and ammonia emissions. As such, Member States are obliged to use a Tier 2 methodology for inventory reporting. Tier 2 methodologies require data that are both detailed and respect the relationships between emission sources. These data can only be collected by sampling at the farm scale.
The methodologies for calculating N balances are not enshrined in international law. The OECD/EUROSTAT gross N balance represents the difference between the inputs and outputs of N to agriculture, divided by the land area occupied. As such, it is equivalent to a farm N balance and represents a holistic indicator of the potential environmental impact. The current methodology requires the estimation of the input of N by livestock excretion and the output of N in crop products used by livestock on the same farm, both of which are difficult to obtain. Since there are no significant gaseous N emissions from the animals themselves, these inputs and outputs could be replaced by the N in imported animal feed and the N exported in animal products, where these can be estimated with greater accuracy.
The impact of agricultural N on the aquatic environment is likely to be more closely related to a soil N balance than to a farm N balance. When calculating a soil N balance, it is recommended to use the country-specific N excretion values reported under UNFCCC and the Tier 2 methodology of the EMEP/EEA Air Pollutant Emission Inventory Guidebook for calculating the gaseous emissions of N in animal housing and manure storage, and after field application of manure or fertiliser.
1.4.2 Importance of coefficients
Obtaining accurate values for the coefficients used in calculating emissions or nutrient balances is essential. The default values provided in the IPCC Guidelines and the EMEP/EEA Guidebook are intended to be reasonable estimates for the specified geographic area. These default values often disguise a wide geographic variation in actual values, either due to variations in climate or to regional variations in agricultural practices. In addition, the default values presented in the various guidance documents generally relate to situations where no abatement measures have been implemented. Member States are encouraged to use nationally or regionally appropriate values of the coefficients. It is good practice to support the use of these coefficients with empirical measurements. The consequences of relatively small errors in coefficients can be significant. It is important that the source of the coefficients used is documented. Where default values are used, the source should be indicated.
The value of some coefficients varies with agricultural practice. For example, the emission of ammonia following field application of animal manure depends on the manure application method used. The coefficients may need to be updated periodically to take account of significant changes in agricultural practices.
1.4.3 Detailed procedures needed for emission abatement strategies
The trend seen within both UNFCCC and CLRTP is for emission limits to be progressively reduced over time. For both greenhouse gas and ammonia emissions, agriculture represents a major source. As noted
1 Summary
above, for implementing abatement measures the use of Tier 3 methodologies is generally recommended. The implementation of abatement measures will often result in an increased cost to agriculture and environmental authority that must monitor compliance.
Identifying the most cost-effective abatement measures for agriculture usually requires data that exceeds that which is necessary to support a Tier 2 approach for calculating emissions. This is because the complex and very varied nature of agriculture results in large differences in the abatement measures that are available and their associated costs.
1.4.4 Data collection
Agricultural emissions strongly depend on the animal housing, and on the manure management system distribution. These data are a mandatory pre-requisite for accurate emission estimates that with a low range of uncertainty. The impact of mitigation measures on the national emissions reported under UNFCCC and CLRTP must be documented and this is only possible if representative data on the manure management system are available. It is recommended to collect activity data via surveys at farm level every five years.
Development of cost-effective mitigation measures relating to greenhouse gas and ammonia emissions or nitrate leaching require relational statistics that can only be obtained by a farmer surveys. Since farm management of nutrients tend to vary systematically with farm type (cattle, pig etc) and size, such surveys can be usefully stratified according to farm type and size.
Some European countries have already collected activity data at farm level. The data surveys were carried out with great success and the national inventories could be improved. Country specific mitigation options and potentials were identified. It was found that the only way forward towards a more sustainable and environmentally friendly, yet at the same time economically viable, agriculture was to gain better knowledge of farm management practices. Only then can practically feasible, efficient and economic mitigation measures be proposed and implemented.
2 Introduction
2 Introduction
Agriculture exerts various effects on the environment. These effects depend on both the agricultural activities and the environmental conditions. Agriculture in the European Union (EU) is highly diverse and also dynamic, as agriculture responds to changes in markets, technological developments and governmental policy. As a consequence14, effects of agriculture on the environment are spatially diverse and change over time.
The Common Agricultural Policy (CAP) and Rural Development and Environmental Regulations and Directives of the EU have a strong influence on agriculture and its effects on the environment. The general objectives of these policies are to making EU agriculture more productive, competitive and environmental sound, whilst safeguarding the livelihoods and natural values of rural areas. Member States of the EU are required to report regularly to the European Commission on the effectiveness of the aforementioned policies. Agri-environmental indicators (AEIs) increasingly play a role in assessing the effectiveness of agri-environmental policy measures.
At present much data and information is collected by Member States as input for the agreed 28 agri- environmental indicators (AEIs). Each AEI consists of one or more parameters/data/coefficients that together provide the AEI. The AEIs are supposed to reflect the state or trend of a certain agri- environmental variable. However, at present agricultural statistics mainly focus on economic and production issues and less on agri-environmental issues. Consequently, agricultural statistics are used, or modified towards, the objectives of the AEIs. The usefulness of this practice depends on the geo- reference of the data (‘Does the data reflect spatially explicit activities/trends?’), geo-physical setting of the farm (‘Does the data reflect differences in farm strategies?’) and continuity of data collection (‘Is the data collected in a consistent and systematic monitoring protocol?’).
The general objective of the service contract ‘DireDate’ is “to create a framework for setting up a sustainable system for collecting a set of data from farmers and other sources that will serve primarily European and national statisticians for creating the agreed 28 agri-environmental indicators and thus serve policy makers, but as well agricultural and environmental researchers, observers of climate change and other environmental issues linked to agriculture”. DireDate is carried out by a consortium of 5 research institutions from 5 Member States and has 9 different tasks.
The objective of task 3 is to
To analyze the methodologies for calculating greenhouse gas and ammonia emission and nutrient balances (nitrogen and phosphorus), with particular stress on the coefficients used in the calculations and the underlying data needs, and
To identify best practices for these coefficient calculations, based on available scientific research.
3 Data requirements in relation to emissions of greenhouse gases and ammonia
3.1 Aim
• calculate accurate emissions and
• identify cost-effective abatement measures.
3.2 General
Emissions of greenhouse gases are within the scope of the UN Framework Convention on Climate Change (UNFCCC) whereas those of ammonia are within the scope of the UN Convention on Long- Range Transboundary Air Pollution (CLTRP). Guidance on the methodologies for calculating greenhouse gas and ammonia emissions is provided in the IPCC Guidelines (‘the Guidelines’) and the EMEP/EEA Air Pollution Emission Inventory Guidebook (‘the Guidebook’) respectively.
Following the recent revision of the Guidebook, both the Guidelines and Guidebook use a Tier approach. In this approach, minor emission sources may be calculated using the simple Tier 1 methodologies whereas more important (‘key‘) sources should as a minimum be calculated using the more detailed Tier 2 methodologies. Reporting bodies are encouraged to use more detailed methodologies than the Tier 2 approach (Tier 3) if possible and if this would result in more accurate reporting.
There is a difference in the definition of Tier 2 and Tier between the Guidebook and the IPCC Guidelines. The Tier 2 methodology of the IPCC guidelines has a level of detail that allows to show the effect of some mitigation options (e.g. shift in manure management systems, biogas production). Whereas the Guidebook requires a Tier 3 approach if the effect of mitigation measures other than the reduction of livestock numbers is to be shown.
Although data collection to support Tier 3 methodologies will usually be more expensive than to support the Tier 2 alternatives, the overall cost to society may be lower. This is because the explicit inclusion of abatement measures in the calculation of emissions nearly always requires the use of a Tier 3 methodology. For example, using a Tier 2 methodology under the Convention on Long Range Transboundary Air Pollution, the emissions from livestock are calculated by multiplying the annual average population by a default emission factor. If a country to the conventions chooses to use a Tier 2 methodology for a particular pollutant, the only abatement measure available is to reduce the population of livestock.
Alternatively, the country could choose to implement technical abatement measures that would justify using lower emission factors than the defaults stipulated in the Tier 2 methodology (i.e. they would use a Tier 3 methodology). The country might well find that the combined cost to society of implementing abatement measures and of increasing data collection to support a Tier 3 methodology is lower than the cost of reducing livestock numbers.
Tier 3 methodology does not necessarily imply the application of highly complicated models. A Tier 3
approach is the only possibility to show the reduction of emissions through country specific abatement technologies. In order to encourage more environmentally friendly and sustainable ways of farming, the application of Tier 3 approaches is strongly recommended. There is no restriction on the form of Tier 3, provided it can supply estimates that can be demonstrated to be more accurate than Tier 2. If data are available, emission calculations may be made for a greater number of livestock categories than listed under the Tier 2 approach. Mass balance models developed by the reporting country may be used. A Tier 3 method might also utilize the calculation procedure outlined under Tier 2, but with the use of country-specific EFs or the inclusion of abatement measures. The effect of some abatement measures can be adequately described using a reduction factor i.e. proportional reduction in emission compared with the unabated situation. Tier 3 methods must be well documented to clearly describe estimation procedures and will need to be accompanied by supporting literature.
3.3 Identifying cost-effective abatement measures
The trend seen within both UNFCCC and CLRTP is for emission limits to be progressively reduced over time. For both greenhouse gas and ammonia emissions, agriculture represents a major source. As noted above, for implementing abatement measures the use of Tier 3 methodologies is generally recommended. The implementation of abatement measures will often result in an increased cost to agriculture and environmental authority that must monitor compliance.
When faced with the need to reduce emissions, countries are usually faced with a choice between a number of different abatement measures. The main items to be taken into consideration when assessing the relative costs of different abatement measures are as follows:
• The capital and maintenance cost to farmers of new equipment or facilities.
• The cost to farmers of any increased demand for labour.
• The extent to which other costs can be offset (e.g. fertilizer costs).
• The costs are regulating authority of additional data collection and reporting requirements.
• Any positive or negative interactions with other policy measures (e.g. Nitrates Directive, animal welfare legislation).
Identifying the most cost-effective abatement measures for agriculture usually requires data that exceeds that which is necessary to support a Tier 2 approach for calculating emissions. This is because the complex and very varied nature of agriculture results in large differences in the abatement measures that are available and their associated costs. This can be illustrated by three examples related to abating ammonia emissions:
1. Non-ruminant livestock (e.g. pigs) are often housed throughout the year. For reasons of welfare and productivity, this housing is usually ventilated using a limited number of fans. Air filtration units can be attached to the ventilation system to remove ammonia. In contrast, ruminant livestock are often housed through all part of the year in open-sided housing, where air filtration is not feasible.
2. Applying slurry to fields by injecting it into the soil is a very effective way of reducing ammonia emissions from this source. However, the technique is not usable on stony soils or on steeply sloping land.
3. The cost of implementing abatement technology depends strongly on the size of farm. Economies of scale mean that the cost of abatement per head of livestock is normally much lower large farms and small ones.
The complexity of agriculture and the dependence of costs on a range of interrelated factors means that in order to identify cost-effective abatement measures, it needs to be possible to establish relationships between data e.g. livestock type x housing type x farm size. In addition to assisting in the estimation of abatement costs, the ability to establish relationships between data is necessary to enable knock-on effects of abatement measures to be assessed. For example, applying abatement measures to reduce losses of nitrogen from animal housing, manure storage and from field-applied manure, reduces the cost of applying commercial mineral nitrogen fertiliser.
4 Analysis of data necessary to estimate emissions of greenhouse gases
4 Analysis of data necessary to estimate emissions of greenhouse gases and CLTRP compounds from manure management
Agricultural activities contribute to emissions of greenhouse gases and ammonia through a variety of processes. Greenhouse gas and ammonia emissions from the following agricultural sources have to be calculated:
1. CH4, N2O, and NH3 emissions from domestic livestock
1a. CH4 emissions from enteric fermentation
1b. CH4 emissions from manure management
1c. N2O emissions from manure management
1d. NH3 emissions from manure management
2. CH4, N2O, and NH3 emissions from agricultural soils (including indirect N2O emissions)
CH4 and N2O emissions from manure management are calculated following the IPCC methodology. NH3 emissions are estimated according to the methodology described in the CORINAIR Emission Inventory Guidebook.
Emissions are estimated by multiplying activity data with emission factors. Compiling the national inventory therefore comprises two main steps:
1. Assessment of national activity data
2. Assessment of emission factors – either default or country specific emission factors.
4.1 Basic Data
Some basic data are required for most of the emission estimates.
Livestock population characterisation. Basic livestock population characterisation is needed for Tier 1 and Tier 2 emission estimates. It comprises information on livestock species and categories, annual population, milk production, and climate. It is of vital importance to use a consistent livestock characterisation across all categories of animal-related emission sources.
To ensure consistency across animal-related emission sources, characterisation of livestock sub- categories and assessment of annual population is described in the IPCC guidelines. Through the harmonisation between IPCC and CORINAIR guidelines, a consistent livestock population characterisation between the two guidelines was achieved. Data on livestock population can be taken from the national statistics.
Milk Production.: Average annual milk production for dairy cows is required. Milk production data are necessary for estimating the CH4 emission factor for enteric fermentation. Data can be taken from the national statistics.
Weight: Default emission factors for methane emissions from enteric fermentation are based in the assumptions, that the average weight of a dairy cow in Western Europe is 550 kg (Reference Manual, Table A-I). If country specific data are available, countries are encouraged to use them.
Climate: Emission factors are climate dependent. It is thus necessary to consider the climate under which livestock is managed in each country. In the IPCC Guidelines, Reference Manual, chapter 4.2.3, three climate regions are defined in terms of annual average temperature: cool (<15°C), temperate (15°C – 25°C), and warm (>25°C).
4.2 CH4 emissions from enteric fermentation
A simple Tier 1 method and are more complex Tier 2 method are available to estimate CH4 emissions from enteric fermentation. In most cases, the Tier 2 method is applied for emission estimates from cattle (dairy and non-dairy). CH4 emissions from enteric fermentation of the other livestock categories are mostly calculated with the Tier 1 method as they are of less importance for the whole budget.
The IPCC guidelines propose the following formula to estimate CH4 emissions from enteric fermentation:
Emissions [kg yr-1] = (Intake [MJ day-1] * Ym * 365 [days yr-1]) / 55.65 [MJ (kg of CH4)-1]
where:
Ym = methane conversion rate
The feed intake estimates are used in the Tier 2 enteric fermentation emissions estimate, and in the estimates of CH4 and N2O emissions from manure management and direct and indirect N2O emissions.
Feed Intake Estimate: The feed intake of a representative animal in each sub-category is estimated to support the Tier 2 emissions estimates. To support the enteric fermentation Tier 2 method, detailed data requirements and equations are included in the IPCC Guidelines to estimate feed intake. The IPCC guidelines propose the following formula for the calculation of gross energy intake of cattle and sheep:
GE = [(NEm + NEmob. + NEa + NEl + NEw + NEp)/(NEma/DE)] +
[(NEg + NEwool ) / (NEga/DE)]} / (DE/100)
Where:
GE = gross energy intake [MJ day-1]
NEm = net energy required by the animal for maintenance [MJ day-1]
NEmob. = net energy due to weight loss (mobilised) [MJ day-1]
NEa = net energy for animal activity [MJ day-1]
NE = net energy for lactation [MJ day-1]
NEw = net energy for work [MJ day-1]
NEp = net energy required for pregnancy [MJ day-1]
NEma/DE= ratio of net energy available in a diet for maintenance to digestible energy consumed
NEg = net energy needed for growth [MJ day-1]
NEwool = net energy required to produce a year of wool [MJ day-1]
NEga/DE= ratio of net energy available for growth in a diet to digestible energy consumed
DE = digestible energy expressed as a percentage of gross energy
Due to a lack in data availability it is not always possible to estimate gross energy intake following the formula proposed in the IPCC guidelines. In the "IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (GPG)1" it is stated that “for inventory agencies that have well-documented and recognised country-specific methods for estimating GE intake based on animal performance data, it is good practice to use the country-specific methods.” So, the alternative to the IPCC methodology is to gain country specific data on feed intake and diet composition.
4.3 CH4 emissions from manure management
The IPCC Guidelines include two tiers to estimate CH4 emissions from livestock manure. The Tier 1 approach is a simplified method that only requires livestock population data by animal category and climate region, in order to estimate emissions. The Tier 2 approach provides a detailed methodology for estimating CH4 emissions from manure management systems, and is encouraged to be used for countries where a particular livestock category represents a significant share of emissions. This method requires detailed information on animal characteristics and the manner in which manure is managed. Using this information, emission factors are developed that are specific to the conditions of the country.
Tier 2 methane emissions from manure management are estimated by the following formula:
EFi = VSi * 365 [days yr-1] * Boi * 0.67 [kg m-³] * Σ MCFjK * MS% ijK jK
1 Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
Where:
EFi = annual emission factor (kg) for animal type i (e.g. dairy cows)
VSi = average daily volatile solids excreted (kg) for animal type i
Boi = maximum methane producing capacity (m³ per kg of VS) for manure produced by animal type i
MCFjK = methane conversion factors for each manure management system j by climate region K
MS% ijK = fraction of animal type i`s manure handled using manure systems j in climate region K
Average daily volatile solids (VS) excretion: The IPCC GPG recommend the following: “The best way to obtain average daily VS excretion rates is to use data from country-specific published sources. If average daily VS excretion rates are not available, country-specific VS excretion rates can be estimated from feed intake levels.”
B0: The preferred method to obtain the maximum methane producing capacity of manure (B0) is to use data from country-specific sources, measured with a standardised method. As up to now no country specific B0 values have been determined, the inventories have to be compiled with IPCC default. Inventory accuracy could be considerably improved, if country specific B0 values were determined. B0 values were derived from limited and highly variable data. They are thus connected with high uncertainties.
Methane conversion factor (MCF) Values: Default MCF values are provided in the IPCC Guidelines for different manure management systems and climate zones. As up to now no country specific MCF values are available, the inventories have to be compiled with IPCC default MCF values. This is another weak point, as default MCF values are only laboratory based and have so far not been verified under field conditions. IPCC encourages measurements of emissions from manure management under field conditions in order to improve the basis of emission estimates.
Default MCF values are presented in the IPCC Guidelines. The guidelines contain a range of manure management practices and assign specific emission factors to them. In order to apply the Tier 2 approach, it is necessary to have country specific activity data on manure management system distribution.
Manure management systems: Data on distribution of manure management systems in each livestock category are important for accurate emission estimates. There are considerable differences in emission factors between manure management systems. Manure management offers promising options for mitigation of greenhouse gas emissions. It is of crucial importance to have country specific data on manure management system distribution. Only with these data available can the effect of more environmentally friendly and sustainable ways of manure management be shown in national emission inventories.
The GPG recommend the following: “The best means of obtaining manure management system distribution data is to consult regularly published national statistics. If such statistics are unavailable, the preferred alternative is to conduct an independent survey of manure management system usage.”
4.4 N2O from manure management
All emissions of N2O taking place before the manure is added to soils are to be reported under “Manure Management”. For the estimation of N2O emissions from manure management systems only a Tier 1 approach is available. The IPCC Guidelines method for estimating N2O emissions from manure management entails multiplying the total amount of N excretion (from all animal species/categories) in each type of manure management system by an emission factor for that type of manure management system. Emissions are then summed over all manure management systems (see formulas below).
N excretion per manure management system:
Nex(MMS) = ∑(T)[N(T) x Nex(T) x MMS(T)]
Where:
N(T) = number of animals of type T in the country
Nex(T) = N excretion of animals of type T in the country [kg N animal-1 yr-1]
MMS(T) = fraction of Nex(T) that is managed in one of the different distinguished manure management systems for animals of type T in the country
T = type of animal category
N2O emission per manure management system:
N2O(MMS) = ∑[ Nex(MMS) x EF3(MMS)]
Where:
N2O(MMS) = N2O emissions from all manure management systems in the country [kg N yr-1]
Nex(MMS) = N excretion per manure management system [kg yr-1]
EF3(MMS) = N2O emissions factor for an MMS [kg N2O-N per kg of Nex in MMS]
N excretion. N excretion for each livestock category present in a country must be determined. The IPCC guidelines propose default values for N excretion. These default values, however, do not properly reflect country specific conditions. It is desirable to use national N excretion rates in order to reduce uncertainty in the estimates.
N2O emission factors. The IPCC guidelines give tentative default values for N2O emission factors from animal waste management systems. The default emission factors were derived from a very limited amount of research and are thus connected with an uncertainty range of –50 % to + 100 %. They are, however, at the moment the best estimates available for the calculation of N2O emissions from AWMS.
Manure management systems: The manure management system distribution data used to estimate N2O emissions from manure management are the same as those that were used to estimate CH4 emissions from manure management. It is again of crucial importance to have national data on manure management system distribution.
4.5 N2O from agricultural soils
Direct N2O emissions are caused by different N-inputs to soils. The IPCC 1996 method for calculating direct N2O emissions from soils is based on the assumption that 1.25% of all nitrogen inputs to agricultural soils are emitted in the form of N2O (expressed as N). In this method, nitrogen inputs are corrected for gaseous losses through volatilization of NH3 and NOx.
• Nitrogen sources considered are:
• Animal manures on pastures
• Crop residues remaining on the field after harvest
• Application of sewage sludge on agricultural soils
The nitrogen inputs from all sources are added and the direct N2O emissions from agricultural soils are calculated using the emission factor of 1.25%. This method estimates the total direct N2O emissions, irrespective on type of soils, of land use (e.g. grassland and cropland soils) and of vegetation, irrespective of the nitrogen compounds (e.g. organic, inorganic nitrogen), and irrespective of climatic factors.
4.6 NH3 emissions from manure management
Ammonia emissions from manure management are estimated according to the EMEP/EEA atmospheric emission inventory guidebook. In the Tier 2 methodology, the flow of total ammoniacal nitrogen (TAN or mineral N) is followed through the manure management system. The relative volumes of flow through the different pathways are determined by country-specific information on animal husbandry and manure management systems, while the proportion volatilised as ammonia at each stage in the system is treated as a percentage, based on measured values and expert judgement.
The detailed methodology requires input data of animal numbers, nitrogen excretion and manure management systems.
Total ammoniacal nitrogen (TAN) content in excreta: The detailed method makes use of the total ammoniacal nitrogen (TAN) when calculating emissions. The initial share of TAN must be known as well as any transformation rates between organic N and TAN.
N excretion by manure management system: N excretion rates and data on manure management system distribution are required. Data needs are harmonised with those described under the sections “CH4 emissions” and “N2O emissions”.
NH3 emissions from storage: NH3 emission estimates differentiate between emissions from the animal house and emissions from manure stores. NH3 emissions from storage are estimated from the amount of N left in the manure when the manure enters the store. Specific emission factors are available for a range of stores and covers of stores. Mitigation through lower emissions from stores can only be shown if national activity data on manure storage are available.
NH3 emissions from manure application: After estimation of NH3 emissions from housing and storage, the remaining N is field applied. Different NH3 emission factors are suggested dependent on the target of land spreading: emissions are thought to be higher on grassland soils than on cropland soils, because
infiltration of applied animal waste is slower. Specific emission factors are available for a range of technical options of manure application (e.g. band spreading, injection, ploughing in after application). Many of these options are low cost options that can effectively reduce emissions after manure application. Activity data are needed to apply these detailed emission factors and show the effect of sustainable manure application.
4.7 Data requirements to estimate NH3 and GHG emissions
Emissions are estimated by multiplying activity data with emission factors. Compiling the national inventory therefore comprises two main steps: The assessment of national activity data and the assessment of emission factors (either default or country specific emission factors). Agricultural emissions strongly depend on the animal housing, and on the manure management system (MMS) distribution. These data are a mandatory pre-requisite for accurate emission estimates that comprise a low range of uncertainty. Mitigation measures can only show up, if representative data on the MMS distribution are available. A lack of these data leads to two major disadvantages: 1. Country specific values can only to a small extent be integrated in the national emission inventory. Major parts of the inventory must be set up with default values that do not always represent processes typically found in the respective country. 2. Due to the lack in activity data, the effect of mitigation measures can not show up in the national emission inventory.
4.7.1 Data requirements
The data in Tables 1 and 2 below are based on the inputs to the IIASA manure management model, supplemented with items added by Nick Hutchings, Wilfried Winiwarter and Zig Klimont (IIASA). The columns IPCC and UNECE show whether the data are already required to satisfy the reporting demands of the UNFCCC or CLTRP. The items highlighted in red are those that IIASA indicated where necessary for identifying economically optimal emission abatement measures.
The data listed in Tables 1 and 2 are required to enable the application of a Tier 2 or Tier 3 methodology for the estimation of CH4, N2O and NH3 emissions. Only with detailed activity data can the emission estimation equations be applied. The investigation of policy options and the documentation of abatement measures that have been implemented will usually require the use of higher Tier methodologies. Higher Tier methodologies require activity data to be reported in greater detail. Data items that need to be reported in greater detail are highlighted in yellow in Table 1.
The values for emissions reported under UNFCCC and CLTRP are expressed on an annual basis. However, collecting data that permit emissions to be estimated with a higher temporal resolution may be of value to policymakers of the following reasons:
• There is evidence to suggest that the damage to certain ecosystems is related to shorter periods of high atmospheric ammonia concentrations, rather than the total annual deposition.
• The formation of secondary particulates that can damage human health results from an interaction between ammonia and other atmospheric pollutants. The extent to which the seasonal distribution of the emission of ammonia interacts with the seasonal distribution of these other pollutants is therefore of importance.
• The emission of ammonia and some greenhouse gases from agricultural sources is dependent upon certain meteorological parameters, so knowledge about the seasonal variation in activities related to these emissions permits more accurate reporting.
Table 1: Data relating to manure management (needed for each livestock category)
Data item Units IPCC UNECE Ease Notes
N-excretion kg N yr-1 X X 3 National defaults available, more detailed data must be collected
C-excretion kg C yr-1 X 3 VS excretion required
Solid and liquid manure system
% X X 1
Time spent grazing hours day-1 X X 2 Ideally include seasonal distribution
Time spent on yards hours day-1 X X 2 Ideally include seasonal distribution
Yard flooring – no leachate capture
% X 1 Ideally indicate the surface covering (concrete, bare soil, woodchips, other)
Yard flooring – leachate capture
% X 1 Ideally indicate the surface covering (concrete, bare soil, woodchips, other)
Amount of straw added as bedding
kg DM head-1 yr-1
% X 2
Percentage of manure that is spread directly from animal housing to land. Ideally include seasonal distribution
Housing: fully-slatted floor
Housing: scrubbers or biofilters
% X 1
Manure separation % X 1 Percent of manure that is separated into solid and liquid fractions
Manure to anaerobic digester (AD)
% X 1 Should be included into UNECE as well
Supplement added to AD: Food waste
Mg yr-1 X 2
Mg yr-1 X 2
Mg yr-1 X 2
Data item Units IPCC UNECE Ease Notes
Slurry stored in open tanks
% X 1
% X 1
% X X 1
% X X 1
Manure incinerated % X 1
% (X) 1
Liquid manure = slurry or separated liquid fraction. Ideally include seasonal distribution
Solid manure applied to fields
% (X) 1
Solid manure = farmyard manure or separated solid fraction. Ideally include seasonal distribution
Manure application technique: Broadcast – no incorporation
% (X) 1
% (X) 1
% (X) 1
DM = dry matter
(X) = for UNECE; data needed to reliably estimate the effect of abatement measures
(X) = for soil N balance; data required to calculate manure and nitrogen applied to the soil
Ease = ease of data collection (1 = easy, 2 = moderate, 3 = difficult)
Green: Data required by UNFCC or CLRTP. These data are a prerequisite for Tier 2 and 3 approaches.
Yellow: Data required by UNFCC or CLRTP but which needs to have greater detail to be useful for policymaking. These data are helpful for Tier 3 approaches. However, a Tier 3 approach does not necessarily require all these data. Prioritsation is shown later in this document.
Table 2: Data related to field emissions
(X) = data required to calculate manure and nitrogen applied to the soil
Ease = ease of data collection (1 = easy, 2 = moderate, 3 = difficult)
Green: Data required by UNFCC or CLRTP. These data are a prerequisite for Tier 2 and 3 approaches
Yellow: Data required by UNFCC or CLRTP but which needs to have greater detail to be useful for policymaking . These data are helpful for Tier 3 approaches. However, a Tier 3 approach does not necessarily require all these data. Prioritsation is shown later in this document.
4.7.2 Data collection
Most of the data in Tables 1 and 2 can easily be implemented into a questionnaire to be filled in by farmers. E.g. Austria and Switzerland have already carried out such survey with great success. In Switzerland, the survey “DYNAMO” was carried out to assess manure management system distribution (Menzi et al. 2003, Reidy & Menzi 2005a, b, Reidy et al. 2008b, Kupper et al. 2010a,b). The data were included into the National Emission Inventory and potentials for abatement options were calculated based on the country specific data on manure management systems (Reidy & Menzi 2005c, 2007, Reidy at al. 2008a, Reidy et al. 2009).
In Austria, the survey “TIHALO” has been carried out on a representative sample of Austrian farms (Amon et al. 2007). The farmers were able to fill in the questionnaire without additional help. A sample of the TIHALO questionnaire is attached to this report (Questionnaire_TIHALO.pdf). The results of the TIHALO survey were included into the Austrian National Emission Inventories (Amon & Hörtenhuber 2008, 2009). Through inclusion of national activity data, inventory uncertainties were reduced. NH3 emissions from animal husbandry were reduced by 7.1 % only by estimating the national inventory with more accurate activity data.
Data item Units IPCC UNECE Ease Notes Ammonium nitrate Mg N X X 1 Application rate required Ammonium sulphate Mg N X X 1 Application rate required Calcium ammonium nitrate Mg N X X 1 Application rate required
Anhydrous ammonia Mg N X X 1 Application rate required Urea Mg N X X 1 Application rate required Nitrogen solutions Mg N X X 1 Application rate required Ammonium phosphates Mg N X X 1 Application rate required
Organic manure Mg N X X 2 Sewage sludge, municipal compost, application rate required
Immediate incorporation of urea % X 1
Imported material for bedding MG N X 2
Crop residue returned to field Mg DM X 3
Crop residue burnt Mg DM X 3 Quarterly resolution needed for arctic environment/albedo effect
The REGULATION (EC) No 1166/2008 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 19 November 2008 on farm structure surveys and the survey on agricultural production methods and repealing Council Regulation (EEC) No 571/88 (EU 2008) lists in Annex V several characteristics for the survey on agricultural production methods. These characteristics are as well helpful for the setting up of good emission estimated and for the proposal of mitigation measures. The following items have direct influence on the estimation of GHG and NH3 emissions from agricultural activities. They could directly be implemented into a survey on manure management practices as described above.
Animal grazing: The level of detail would be sufficient and the questions could easily be answered by the farmers.
Animal housing: The level of detail would be sufficient and the questions could easily be answered by the farmers. In addition to the animal house, the survey should include questions on a yard and its utilisation.
Manure application: In this section, additional questions would be needed: time of the year, when manure is applied, crop to which manure is applied, manure application technique.
Manure storage and treatment: In this section, additional questions would be needed: manure stored during warm and cold season, manure treatment options (biogas, separation, aeration, composting), type of cover (solid, tent, straw, floating covers).
The data requirements described here go in some aspects beyond the data requirements described in the TAPAS report from Belgium (Vervaet et al. 2006).
The animal house needs to include a question on yards
Manure storage must ask for cover, treatment and storage during warm and cold season
Manure application must ask for timing and application technique
Farm structure surveys should be carried out every five years. They should include the items listed in Table 3. Table 3 gives a concise list of items that should be collected at farm level in order to improve inventory reporting, show the effect of mitigation measures, assess environmental impact of farm management practises and reduce uncertainties in inventory estimates. The data in Table 3 are a prerequisite for the proposal of cost effective and practical mitigation measures.
Table 3 distinguishes emission sources: housing cattle, housing pigs, housing poultry, water management, slurry storage, farmyard manure (FYM) storage, slurry application, farmyard manure (FYM) application and animal diet. Data collection for the emission sources is divided into “optimum requirement” and “minimum requirement”. Activity data listed under “minimum requirement” MUST be collected. Without these data, a proper inventory reporting is not possible. The effect of mitigation measures cannot be shown in the inventory and the cost effectiveness of mitigation measures cannot be assessed. ”. Activity data listed under “optimum requirement” SHOULD be collected in order to even more accurately estimate inventories. They offer more possibilities for country specific and cost effective mitigation measures and enable the assessment of environmental impacts of farm management practices. For most of these data, the additional effort for collecting them is small and the additional effect is big.
Table 3: Data to be collected through surveys at farm level
Activity data collection Reasoning
Housing cattle - minimum requirement Liquid / solid system Tied / loose housing
EF* differ between both systems, system has great influence on subsequent losses
Grazing Necessary for estimation a consistent N flow, necessary for NH3 and N2O emission estimates, IPCC requires data on grazing
Housing cattle – optimum requirement Subcategory of housing systems prevalent in the country Floor system Yard Air scrubber
Housing pigs - minimum requirement
Liquid / solid system EF differ between both systems, system has great influence on subsequent losses
Housing pigs – optimum requirement Subcategory of housing systems prevalent in the country Floor system Yard Air scrubber
Housing poultry - minimum requirement Housing system Manure treatment
Considerable differences in EF; easy to answer for the farmer
Housing poultry - optimum requirement Drinkers
Frequency of manure removal from the house
Water management – optimum requirement Cleaning of the house, water addition to slurry Diluted slurry emits less NH3
Slurry storage - minimum requirement
Slurry store cover Great influence on NH3 emissions; cost effective mitigation measure; likely to become mandatory in the future
Slurry storage - optimum requirement Store size Slurry treatment Slurry storage during warm and cold season
Considerable differences in emissions; Easy to answer for the farmer; necessary for the assessment of mitigation measures
Activity data collection Reasoning
FYM storage - optimum requirement Size of the store and duration of storage FYM treatment Direct FYM application Duration of FYM storage Cover of FYM stores
Slurry application - minimum requirement
Application technology
NH3 emissions after slurry application are by far the largest contributors to total NH3 emissions. Emissions can be effectively abated by low emission application techniques. Some countries give subsidies for low emission application techniques. Environmental effect of these subsidies does not show up if activity data are unavailable.
Application to grassland or arable land Differences in EF Slurry application – optimum requirement
Timing and amount of application
Incorporation after application
Considerable differences in emissions; easy to answer for the farmer; necessary for the assessment of mitigation measures; esp. timing and amount of application are low cost or even no cost mitigation measures. They will only show up in the inventory if activity data are available.
FYM application - minimum requirement Application to grassland or arable land Differences in EF
Incorporation after application Drastically reduces NH3 emissions; only measure available to reduce NH3 emissions after FYM application.
Animal diet – optimum requirement
Components of cattle diet
Important influence on N excretion and CH4 emissions from enteric fermentation; information will greatly help to improve national defaults on CH4 emissions from enteric fermentation, N and VS excretion; all mitigation measures set at the beginning of the chain will have the largest potential to reduce emissions
Components of pig diet
Important influence on N and VS excretion; information will greatly help to improve national defaults N and VS excretion; all mitigation measures set at the beginning of the chain will have the largest potential to reduce emissions
Phase feeding for pigs
One of the most effective measures to reduce N emissions from pig manure; measure can be implemented a low or no costs; farmers might even gain by reducing N content in the pig diets.
* Emission Factors
5 Data necessary for the calculation of N and P balances
5.1 General
Unlike the situation for greenhouse gas and ammonia emissions, there is currently no international legal framework relating to nitrogen and phosphorus balances. As a consequence, there is no legally- established international standard terminology or methodology for these balances. The lack of a standardised terminology has led different authors to refer to the same calculation methodology by different names or to refer to different calculation methodologies by the same name. The terminology used in this report is summarised in Annex “Consolidated list”.
It is important to distinguish between nutrient balances and nutrient budgets; nutrient balances calculate the difference between the input and output of a nutrient across the system boundary. This calculation also enters a nutrient budget but in addition, the balance (or surplus) is then partitioned between loss pathways.
A farm nitrogen budget is shown in figure 1
Figure 1: A farm nitrogen budget
The main inputs to the farm are mineral fertiliser, imported animal manure, fixation of atmospheric nitrogen by some (mainly leguminous) crops, deposition from the atmosphere and livestock feed. Inputs in seed and bedding used for animals are generally minor inputs, although the latter can be significant for some traditional animal husbandry systems. The main outputs from the farm are in crop and animal products, and in exported manure. Gaseous losses occur from manure in animal housing, in manure storage and after field application. Other gaseous losses occur from fields; from applied fertiliser, crops, soil and crop residues. Losses to ground and surface water occur via leaching or run off of nitrates, ammonium and dissolved organic nitrogen (DON). On poorly managed farms, nitrogen can also be lost in run off from animal housing, animal holding areas and manure storage.
The main nitrogen flows within the farm are in the consumption of crop products by the livestock, the return of nitrogen to the field in the excreta of grazing animals, use of straw from the fields as bedding in livestock housing and the removal of manure from animal housing and manure storage for field application.
The farm phosphate budget is shown in figure 2. The main difference between the nitrogen and phosphate budgets is the lack of gaseous emissions in the latter.
Figure 2: Farm phosphate budget
5.2 Methodologies related to nitrogen
There are three nitrogen balances in common usage.
5.2.1 Farm gate nitrogen balance
A farm gate nitrogen balance calculates the amount of nitrogen imported into the farm in commodities and subtracts from it the amount exported from the farm in agricultural products. This is illustrated in Fig. 3 below. The farm gate nitrogen balance is usually divided by the land area associated with the agricultural production, so that the result is expressed in terms of kg N ha-1 year-1. The advantage with this balance is that with the exception of manure imports and exports, it relies on readily documented commodity flows. However, it has the disadvantage that it ignores a number of inputs that under certain circumstances can make a major contribution to the supply of nitrogen to the farm. For example, biological nitrogen fixation can make a major contribution to nitrogen supply, particularly on organic farms. As a result, this indicator must be considered obsolete.
Figure 3: Farm gate nitrogen balance
5.2.2 Farm nitrogen balance
A farm nitrogen balance calculates the amount of nitrogen entering the farm and subtracts from it the amount of nitrogen exported from the farm in agricultural products. The difference between the two represents the amount of nitrogen lost to the environment, plus changes in the amount stored within the farm (principally in the soil). This is illustrated in Fig. 4 below. The farm nitrogen balance is usually divided by the land area associated with the agricultural production, so that the result is expressed in terms of kg N ha-1 year-1. The farm nitrogen balance is also sometimes referred to as the farm nitrogen surplus. The rationale for this indicator is that it reflects the average nitrogen pollution potential of agricultural land within the area under consideration (i.e. farm, region, state etc).
Figure 4: Components of a farm nitrogen balance
Atm. dep. = Atmospheric deposition, Fixation = biological fixation.
5.2.3 Gross nitrogen balance
A gross nitrogen balance calculates the difference between a. the sum of livestock excretion, mineral and organic fertiliser, seeds and biological fixation and b. crop products removed by harvesting or by grazing. This is illustrated in Fig. 5 below. This balance is used by the OECD/EUROSTART (OECD 2007) and although not expressed explicitly, appears to have the same rationale as the farm nitrogen balance.
Figure 5: Gross nitrogen balance; components included (bold) and associated flows (grey)
As for the farm balance, the gross nitrogen balance requires information on the nitrogen input in fertiliser, imported manure, fixation, seeds and plants, and atmospheric deposition. In addition, the gross nitrogen balance requires information on the excretion of nitrogen by livestock on the farm. The nitrogen flows through animal housing and manure storage (the greyed flows in Fig. 5) are not considered explicitly. In addition to information on the export of crop products from the farm, the gross nitrogen balance also requires the output of nitrogen in forage consumed by grazing animals and the removal of crop products for use as feed for animals. Like the farm nitrogen balance, the gross nitrogen balance represents the amount of nitrogen lost to the environment, plus changes in the amount stored in the soil.
5.2.4 Soil nitrogen balance
A soil nitrogen balance is shown in Fig. 6.
A soil nitrogen balance calculates the difference between (a) the total N input to the fields via livestock manure, mineral and organic fertilisers, seeds, biological fixation and crop residues and (b) the total N output from the fields via harvested crop yield. This balance is used by CAPRI (Leip et al, 2010). Although the soil nitrogen balance is relatively simple, it requires much more information than is necessary for a farm or gross nitrogen balance. In order to calculate the amount of nitrogen applied to the fields in organic manure produced on the farm, the excretion by livestock must be calculated and the gaseous emissions of nitrogen in animal housing and manure storage must be estimated. When calculating a soil nitrogen balance at the scale of the MS, it is appropriate to use the country specific nitrogen excretion values reported under UNFCCC and the Tier 2 methodology of the EMEP/EEA Air Pollutant Emission Inventory Guidebook for calculating the gaseous emissions of nitrogen in animal housing and manure storage. Additional information is also required on the nitrogen taken up by the crop that is returned to the soil in crop residues.
Figure 6: The components of a soil nitrogen balance.
Components in grey must be quantified in order to calculate the nitrogen in manure applied to the soil.
5.2.5 Changes in soil nitrogen storage
Changes in soil nitrogen storage are commonly assumed to be zero. This is the case for OECD and for CAPRI. This assumption is reasonable for the long-term. However, given the nature of the dynamics of carbon and nitrogen in the soil, the long-term should be considered 50 to 100 years. Empirical measurements made in Denmark and in the famous Rothamsted long-term field experiments in the United Kingdom have found significant changes in soil nitrogen storage over time. These changes appear to be related to the changing structure of agricultural production. Thirty to 50 years ago, many farms had mixed production enterprises i.e. they produced both crops and livestock. The increasing specialisation of agricultural production in the last 50 years has resulted in notable differences in the inputs of organic matter to the soil on different farm types. On farms that choose to specialise in arable production, the removal of livestock has led to a reduction in organic matter inputs into the soil via animal manure and crop residues. The reduction in input of crop residues is mainly associated with the disappearance of grass from the crop rotation, since this crop contributes much more organic matter to the soil than arable crops. This has led to a reduction in the soil nitrogen storage of up to 30 kg ha-1 year-1. The reduction in soil storage on farms that choose to specialise in pig production is somewhat less. In contrast, soils on farms that choose to specialise in cattle production has seen accumulation is in soil nitrogen of 30-50 kg ha-1 year-1.
Further, changes in soil nitrogen storage are likely to be of major importance where wetlands. peatland and coastal areas have been drained for agriculture. Such soils typically have high or very high initial levels of organic matter, due to the anaerobic or acidic conditions that existed prior to drainage. Drainage leads to aerobic conditions developing for some or all the year, resulting in the mineralization of organic matter and the release of mineral nitrogen. In such situations, 100-300 kg ha-1 of organic nitrogen may be released annually, until the organic rich top layer finally disappears.
Assessing the change in soil nitrogen storage is difficult because the amount stored is large compared to the changes that typically occur in a single year. It is possible to do over the medium term (about 10 years) if a sufficiently large number of samples are taken. However, on former wetland or marine areas, measurements are complicated by reductions in the height of the soil surface, due to compaction and to the loss of carbon in gaseous form.
Data relating to changes in cropping pattern and livestock density over time can be used to detect whether farms have differed substantially in their development trajectory over time.
5.2.6 Choice of balance
A farm nitrogen balance and the gross nitrogen balance depend on losses to both atmospheric and aquatic environments, so are broad indicators of the potential environmental impact of agricultural nitrogen. They largely rely on inputs and outputs that can be quantified from existing documentable sources (e.g. farm accounts). In contrast, the soil nitrogen balance depends to a great extent upon losses of nitrate, so is a better indicator of the potential impact on the aquatic environment. This relationship could be improved further by subtracting the ammonia emission associated with field application of manures and fertilisers (see section on ammonia emission). However, calculation of a soil nitrogen balance demands estimates of livestock nitrogen excretion and the emissions of nitrogen in animal housing and storage. The data necessary to obtain these estimates are more difficult to obtain and associated with greater uncertainty than those necessary for the calculation of the farm nitrogen balance.
5.2.7 Revision of methodologies
Gross nitrogen balance
As noted by OECD (2007), estimates of nitrogen excretion obtained from manure sampling vary widely. The excretion of nitrogen by livestock and the nitrogen consumed by livestock in feed produced on the farm are two of the four elements of the livestock nitrogen balance (the other two being imported livestock feed and exported animal products). Over the lifetime of an animal, the nitrogen stored in the animal is zero. To maintain the continuity of nitrogen (i.e. since nitrogen is neither lost or created, just redistributed), the following must be true:
imported feed N + farm-produced feed N = animal production N + N excreted (Equation 1)
By rearranging this equation, one obtains:
N excreted = imported feed N + farm-produced feed N - animal production N (Equation 2)
As noted by OECD (2007), the estimate of farm-produced feed nitrogen appears both in the input and output terms of the gross nitrogen balance:
Input = imported manure + fertiliser + excretion + other N inputs (Equation 3)
Output = exported manure + marketed crops + farm-produced feed (Equation 4)
Substituting for excretion:
Input = imported manure + fertiliser + imported feed + farm-produced feed - animal production + other N inputs (Equation 5)
As a result, the estimate of farm-produced feed nitrogen cancels out and the gross nitrogen balance is calculated from the following:
Input = imported manure + fertiliser + imported feed + other N inputs (Equation 6)
Output = exported manure + marketed crops + animal production (Equation 7)
The imported animal feed and exported animal products can be more easily and more accurately determined than the farm-produced animal feed (e.g. via farm accounts). We therefore consider that the gross nitrogen balance would be more accurately calculated using equation 6 and 7.
The gross nitrogen balance does not include the import of nitrogen in bedding for livestock. For organic, high welfare and some traditional livestock husbandry, the demand for bedding can be substantial and may require the import of bedding material. This can be illustrated if one considers an organic dairy farm where the livestock are kept in loose housing/deep litter that requires the import of an average of 5 kg straw dry matter ha-1 d-1. If the concentration of N in the straw is on average 1%, this is equivalent to just over 18kg N ha-1 yr-1. Using typical Danish values, this would increase the gross nitrogen balance by 16%. We consider the input of nitrogen and via imported bedding should be added to the gross nitrogen balance .
If the recommendations concerning the calculation methodology and the inclusion of imported bedding are accepted, the gross nitrogen balance and the farm nitrogen balance become synonymous.
Soil nitrogen balance
Some clarification of terminology is required concerning the use of crop residues and crop products in the calculation of the soil nitrogen balance. Leip et al (2010) refer to crop products and crop residues. OECD/EUROSTAT refer to crop residues, marketed crops and non-marketed crops. The OECD/EUROSTAT terminology is to be preferred as it is clearer. However, it could be usefully modified as follows:
• Crop residues = plant material left on the field after harvesting.
• Marketed crops = all crop products sold and exported from the farm.
• Non-marketed crops = all crop products that are produced on the farm and used on the farm.
The reason for suggesting these changes is to en

analysis of methodologies for calculating greenhouse gas

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