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Pesticide statistics in Eastern Europe, Caucasus and Central Asia. Guna Karlsone, CSB of Latvia. Necessity of the information. Consumption of pesticides and pesticide risk are one of the key agri-environmental indicators;
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Pesticide statistics in Eastern Europe, Caucasus and Central Asia Guna Karlsone, CSB of Latvia
Necessity of the information • Consumption of pesticides and pesticide risk are one of the key agri-environmental indicators; • Along with the development of agricultural production also pesticide use is growing and the data on pesticides in the monitoring and management of the pesticides in the ways that minimize risks to public health and the environment are sufficient • Calculation of indicators requires high-quality and appropriate-level statistical data and information on pesticides; • Information is necessary for policy-makers as well as agricultural and environmental researchers.
Existing legislation on pesticide statistics • It is considered that currently in Europe there is legislation for each stage of the plant protection product circulation; • Plant protection in EU is regulated by: • Directive 2009/128/EC of theEuropeanParliament and Council of 21 October 2009 establishing a framework of Community action to achieve the sustainable use of pesticides; • Regulation (EC) No 1107/2009 of the European Parliament and Council of 21 October 2009 concerning the placing of plant protection products on the market; • Regulation (EC) No 1185/2009 of the European Parliament and Council of 25 November 2009 concerning statistics on pesticides; • Regulation (EC) No396/2005 of the European Parliament and Council of 23 February 2005 on maximum residue levels on pesticides in or on food and feed of plant and animal origin and amending Council Directive 91/144/EEC; • Directive 2009/127/EC amending Directive 2006/42/EC with regard to machinery for pesticide application.
Indicator characterising intensity of pesticide use • The most obvious indicator characterising intensity of pesticide use is quantity of active substances applied per hectare of cultivated area. • Why does new Regulation stipulate the collection of data on pesticides by crop and per each active substance? • When statistical data on volume applied shows a reduction in the weight of active substances it does not allow concluding that it results in the reduction of use or risks. • The reason behind it – many new active substances are applied at much lower rate per hectare than older products they are replacing, causing significant reduction in the weight applied.
Data collection • Sales statistics is a base for providing simple statistics on pesticide use; • Total sale includes sale in sectors outside agriculture – non-agricultural use, e.g., forestry, weed control in industry or application on public areas; • Collection of sales data can be used to substitute data from the survey on pesticide usage. Such data collection is much cheaper, and therefore it can be performed annually, still it is not sufficient for detailed risk analyses.
International Code of Conduct • The International Code of Conduct on Distribution and Use of Pesticides (adopted by the Hundred and Twenty-third Session of the FAO Council in November 2002 – this is voluntary instrument affecting pesticide use; • Box 3 lists Code of Conduct articles related to the data collection and analysis: • Necessary to set up programmes for collection and storage; • 6.1.8. of the Box – have to collect and record data on the import, export, manufacture, formulation, quality, quantity and use of pesticides, to follow trends in pesticide use for economic and other purpose. • The International Code of Conduct on Distribution and Use of Pesticides is supported by the FAO member states, crop protection industry etc., including all 12 EECCA countries; • Binding instrument that primarily is related to pest management or trade, but have implications for pesticide use in International Plant Protection Convention (IPPC) – international agreement on plant health, aim to protect plants also using pesticides.
Conclusions • 11 countries filled in the questionnaire; • 70% of the countries indicated that data on pesticides are obtained by institutions supervised by the Ministry of Agriculture; • In 3 countries data were compiled by the national statistical institutions (Armenia, Georgia and Ukraine), basing on the information obtained from customs information; in the case of Georgia – from survey; • Unfortunately Uzbekistan mentioned only the responsible institution (Ministry of Agriculture) and no data were sent.
How current situation may be improved • Code of Conduct on the distribution and use of pesticides recommends to: • set up cooperation and coordination among relevant ministries and involved stakeholders to identify issues and look for solutions how to improve dataset on pesticide consumption; • set up competencies and responsibilities (agreements, responsible persons, data transmissions with deadlines etc.).
B. Description of data quality assurance and control procedures for the production of indicator
Quality assurance - conclusions • Countries were asked to deal with problems, solutions found, further steps envisaged or needed; • Georgia described the problems, and Russian Federation gave explanation on how to collect data; • Quality assurance has not been described; • Question linked to quality were not correctly understood and /or left blank. HOW CURRENT SITUATION CAN BE IMPROVED : • Accuracy and completeness are the key aspects of quality; • Try to describe what quality control procedures have been applied by responsible institution (not only mentioned responsible institution); • Additional methodological and explanatory information on the issue is needed;
Conclusions • Code of Conduct on the Distribution and Use of Pesticides stipulates that transparency and public access to information are important elements; • In general, the countries, which published data in paper form, have data also on the Internet.
Conclusions and how situation may be improved • Situation in regional pesticide statistics is not satisfactory yet; • Only 5 countries (41.7%) have data usable for the calculation of the comparable indicator – pesticide use per unit of agricultural land (kg/ha) • Belarus: In principle very good and complete data set (also at regional level), but due to methodology inconsistencies it is incomparable. Data are provided in terms of physical weight, but not in terms of active substances. • Russian Federation: It is not clear weather total pesticides consumption corresponds only to the agricultural sector (if yes, how it has been calculated). If total consumption includes also forestry and other non-agricultural sector and agricultural area is available from crop or land use statistics, the indicator becomes comparable.
(continued) • Tajikistan: It was mentioned that in statistics system data on pesticides are not available (responsible institution-Ministry of Agriculture). Data have been submitted (in tons) only for major groups of substances without total consumption and total area of agricultural land. • Uzbekistan: Country reported that data on pesticides are obtained in the system of Ministry of Agriculture, unfortunately information was not submitted. • Moldova: Reported that there is no pesticide statistics developed in the country. It was recommended to start collecting data (sown area of crops in 2011 comprises 1447.2 thsd ha, also area of vineyards is significant).
(continued) • Georgia: As data in the survey on pesticide use were considered to be unrealistic and only areas treated are known, it is recommended to collect data using other information sources (customs information etc.). • Main findings: • Data sources were not defined clearly enough. This led to misunderstandings and difficulties when interpreting the results; • In order to be able to calculate comparable pesticide use indicator, data should be as complete as possible; • Metadata should accompany all datasets and sources; • Countries with missing data are kindly reminded to provide the missing data or to start collecting them; • Thanks to the countries that provided complete and comparable datasets.
