Emission estimates for pesticides due to agricultural praxis

1
Emission estimates for pesticides due to
agricultural praxis

• Steen Gyldenkærne and Peter B. Sørensen
• National Environmental Research Institute, Denmark

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Outline

• Pesticide data
• Agricultural praxis
• Land cover maps
• Models distribution of data
• Results

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Pesticide consumption
Fungicides
Total pesticides
Herbicides
Insecticides
Source EUROSTAT
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Available pesticide data

• EUROSTAT
• - only chemical classes (TAPAS, Technical Action
  Plans for Agricultural Statistics are trying to
  improve pesticide data)
• - All MS have at least sales data
• - some MS potentially have good use data not yet
  compiled
• - problems of confidentiality
• Country specific sales data on active ingredients
  (Most north European countries)
• - problems of confidentiality
• - by adding expert judgement of pesticides
  distribution between crops (like in Denmark) an
  increased potential for distribution is possible
• - does only partly take into account actual
  farming praxis
• 3. Country specific consumption data (UK, Sweden
  and the Netherlands)
• - Questionnaires to farmers (FADN data)
• - limited data transferring to other countries
  (cluster analysis)
• - should be representative for all pesticides,
  crops and climatic zones
• - is the data reliable?
• - up-scaling to national sales data?
• Data from chemical companies and NGOs (PAN-
  Pesticide Action Network)

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Available pesticide data
Source Pan Germany (http//www.pan-germany.org/do
wnload/fs_cz_20engl.pdf)
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Agricultural praxis

• The need/use of pesticides depends on
• Crop parameters
• Mono culture increase the pesticide input in
  general
• High nitrogen allowances increase the need for
  growth regulators and insecticides
• High value crops have higher pesticide input
  rates
• Climatic conditions
• Warm climate increase the need for insecticides
• (limited need for insecticides in the Nordic
  countries)
• Humid climates increase the need for herbicides
  and fungicides
• Availability of pesticides
• Few restrictions increase the use of soil
  disinfectants instead use of crop rotation
• Few restrictions gives space for use of very
  toxic and broad spectrum pesticides
• Education and awareness of the farmers
• Pesticide support systems may reduce pesticide use

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Crop type distribution in EU

• What are the need and how precise should it be?
• 
  ?
• Use of national statistics
• Use of co-drivers Land use maps, soil type,
  climate, FADN (Farm Accountancy Data Network)

5050 km2 1010 km2 55 km2 11 km2 100100 m2
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Available crop growth data

• National, regional and local level from
  Statistical Bureaus
• NUTs 1 - National
• NUTs 2 - Subnational (e.g. Bundesländern in
  Germany)
• NUTs 3 - County
• NUTs 4 - Municipality
• NUTs 5 - Parish
• If higher NUTs are used there is less need for
  other co-drivers to determine the actual crop
  growth in different areas

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Land Cover map

• CORINE Land Cover is a vector or raster based map
  of Europe
• Minimum vector area app. 100 ha
• Not all of the vector area is suitable for crop
  growing
• Several crop classes
• Other maps of interest
• LPIS (Land Parcel
• Information System),
• very precise
• Remote Sensing

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Increased localisationby adding crop growth
drivers

• Soil type
• Slope
• Temperature
• Water availability

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Crop growing areas in Europe1010 km2 (CORINE
and NUTs 3 and 4)
Sugar beets
Grassland
Potatoes
Maize
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Example of a pyrethroid distribution
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ENRISK risk mapping
Source Environmental Risks from Agriculture in
Europe http//www.ecnc.nl/jump/page/503/Environmen
tal20Risks20from20Agriculture20in20Europe.htm
l
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Conclusions

• The risk to be mapped should be defined cleary
• - in relation to toxicity (acute, chronic and
  selectivity)
• in relation to concentration (pesticide
  directive)
• Climatic conditions should be taken into account
• degradation rate, DT50
• pesticide movement in soil (water flow)
• higher pest pressure in warmer climates
• Crop growth
• land use maps are very essential to define areas
  with high risk
• high value crops are sprayed more intensively
  than low value crops
• If the risk is additive then a simple
  distribution based on expert judgement will often
  be sufficient
• If the risk is considered to increase for certain
  pesticide combinations then data based on
  questionnaires should be preferred in order to
  include actual farming practice