AARHUSUNIVERSITY

NH3 Emissions from Fertilisers

Nick Hutchings, Aarhus University

J Webb, Ricardo-AEA

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Some history• Lack of scientific documentation for the Guidebook methodology• Review of literature (AU Environmental Sciences)• Mean emission factor for each fertiliser type

• Some increases in emission factors (especially urea)

• Additional data found (Bouwman et al 2002 database)• More detailed analysis (AU Agroecology + Ricardo-AEA)

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Statistical analysis (1)• Variables considered:• Fertiliser type

• Measurement method

• Location (indoor, outdoor)

• Application method (broadcast, incorporated etc)

• Soil type

• Soil pH

• Soil CEC

• Crop type (bare soil, grass, maize, rice, other cereals)

• Temperature

• Rainfall intensity (mm/day)

• Data are unbalanced• Many data are missing from individual observations 3

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Statistical analysis (2)• No significant differences between measurement methods or crop types• Significant differences between indoor/outdoor and application method• For Guidebook, estimate emissions for application outdoor and broadcast• Group fertilisers into types:• Urea

• Fertilisers containing urea (e.g. UAN, UAS)

• Fertilisers not containing urea (e.g. CAN, AN, AS)

• Assume effect of soil and climate characteristics operate independently:• Soil characteristics – soil pH, soil CEC. Assume fertiliser type x pH interaction

• Climate characteristics – temperature and rainfall intensity

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Results• Significant differences between urea (U), fertilisers with urea (U+) and

fertilisers without urea (U-)

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Results• Significant differences between urea (U), fertilisers with urea (U+) and

fertilisers without urea (U-)• Significant positive effect of soil pH• Significant fertiliser type x soil pH interaction

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Results• Significant differences between urea (U), fertilisers with urea (U+) and

fertilisers without urea (U-)• Significant postive effect of soil pH• Significant fertiliser type x soil pH interaction

• Significant negative effect of soil CEC• Only for U

7ORIGINAL

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Results

8REVISED

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Results• Significant differences between urea (U), fertilisers with urea (U+) and

fertilisers without urea (U-)• Significant postive effect of soil pH• Significant fertiliser type x soil pH interaction

• Significant negative effect of soil CEC• Only for U

• Significant effect of temperature• Correlation between temperature and soil moisture?

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Results• Significant differences between urea (U), fertilisers with urea (U+) and

fertilisers without urea (U-)• Significant postive effect of soil pH• Significant fertiliser type x soil pH interaction

• Significant negative effect of soil CEC• Only for U

• Significant effect of temperature• Correlation between temperature and soil moisture?

• Strong negative effect of rainfall intensity

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Examples• pH 7, soil CEC 20 meq/100g• Strasbourg:• March: 6º C, rainfall intensity 1.2 mm/day = 12% (U), 12% (U+), 3% (U-)

• June: 17º C, rainfall intensity 2.5 mm/day = 13% (U), 13% (U+), 4% (U-)

• Florence:• February: 7º C, rainfall intensity 2.5 mm/day = 6% (U), 7% (U+), 2% (U-)

• June: 22º C, rainfall intensity 1.8 mm/day = 18% (U), 19% (U+), 6% (U-)

• Current emission factors:• pH ≤ 7 U 21%, U+ 11 to 16%, U- 1 to 9%

• pH >7 U 21%, U+ 11 to 16%, U- 1 to 25%

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Development of Tiered methodologies• Develop Tier 3• Use Tier 3 to develop Tier 2• Use Tier 2 to develop Tier 1

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Tier 3 methodology• Use a model that accounts for:• Fertiliser type (U, U+, U-)

• Soil pH and soil CEC

• Temperature and rainfall intensity

• Need to know how much of each type of fertiliser used on which soil types (pH and CEC) and when (temperature and rainfall intensity):• Parties wishing to use this Tier 3 need these data

• For Tier 2, make assumptions

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Tier 2 methodology• Use agro-ecological zones

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Tier 2 methodology in practice• Divide land area between agro-ecological zones (AEZ)• Partition each AEZ into areas with soil pH >7 and pH ≤ 7• For Europe, use European Soil Database

• Partition each AEZ x soil pH area between crop types (“grass + double cropping” or “all other crops”)• For Europe, JRC resources?

• For each fertiliser type, partition the national amount used between the different AEZ x soil pH x crop combinations in proportion to their contribution to the total land area.• Use the emission factor for each AEZ x soil pH x crop combination to calculate

the ammonia emission• Sum the ammonia emissions from each AEZ x soil pH x crop combination to

calculate the total ammonia emission15

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Land area

AEZ 1 AEZ 2

pH>7 pH≤ 7 pH>7 pH≤ 7

GrassOther crops

GrassOther crops

GrassOther crops

GrassOther crops

Partition each fertiliser type to these areas

Multiply by the emission factor specified for each area

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Tier 2 methodology emission factors (1)• Obtain mean daily air temperature and monthly rainfall for 5-6 locations within

each AEZ• Calculate mean rainfall intensity per location

• Estimate start of the growing season• For grass, start is monthly air temperature >=6ºC, for other crops, >=8ºC

• Estimate end of the growing season for grass• Monthly air temperature <6ºC

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Tier 2 methodology emission factors (2)• For grass, assume fertiliser is applied at the start of every full 6 week of the

growing season• Calculate application dates

• Calculate air temperature and rainfall intensity at these dates

• Use Tier 3 model to calculate emission factors for each date

• Calculate the average emission factor

• For other crops, assume fertiliser is applied at the start of the growing season and then 6 weeks later• Repeat procedure as for grass

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Tier 1 methodology• Fertiliser consumption by type is available for all countries (FAO)• Assume that 50% of the land has a soil pH ≤ 7, 50% >7• Assume that the grass:other crop area is 50:50• Calculate an emission factor specific for the U, U+, U- types

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Conclusions• Data in scientific literature allows a Tier 3 methodology to be developed• Dataset is unbalanced (not all important variables measured in all experiments)

• Data from commonly-used low-emission fertilisers (e.g. CAN) are under-represented

• Data from commonly-used high-emission fertilisers (e.g. urea) are over-represented

• Aggregation of data from different fertiliser types was necessary

• Additional, standardised and balanced measurement experiments are required• Focus on commonly-used fertiliser types

• Focus on most important variables

• Further work required to complete development of Tier methodologies

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