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A. Relevance and sustainability context

A.1 Policy relevance

The use of pesticides has various negative effects on non-target organisms, the environment and human health. Therefore, political regulations exist to monitor the use of pesticides and associated risks (2009/128/EC). Furthermore, reduction targets have been set for the use of these substances (Farm to Fork Strategy - COM(2020) 381 final). However, the extreme heterogeneity of pesticides and their active ingredients makes assessing pesticide use difficult.

The EU Commission introduced in 2019 the so-called Harmonized Risk Indicator (HRI) to ensure risk assessment (2019/782/EC). But this indicator has been criticised by scientists due to the weighting factors applied to different active substances (European Court of Auditors, 2020; UBA 2023). Consequently, it will not be considered further here; instead, the in Pesticide Load Index (PLI) is suggested as core indicator. This indicator was originally introduced in Denmark[1] and is currently the subject of various research projects at a European level.

[1] Pesticide Load Index (PLI) that is currently used as a basis for taxation in Denmark (Kudsk et al 2018).

A.2 Sustainability and/or comparative evaluation options

There are political objectives to reduce the use of pesticides and thus the environmental and health risks posed by these substances.

Accordingly, progress towards these targets could be presented as a percentage value, either as a ratio of current use to the target value, or as the distance to the target.

B. Data availability

B.1 Stage of development

This indicator is considered a New indicators: Indicators not previously reported in an official capacity, but well established through research projects.

Today, the Indicator is already calculated ex-post by the Julius Kühn Institute. The method for weighting the risks to the environment and health has not yet been finalised.  However, the results of an initial draft can already be viewed in an online tool (https://sf.julius-kuehn.de/pesticide-dbx/) and can be compared with other approaches.

For ex-ante analysis a similar approach is implemented under some modification into the CAPRI model (Keske and Witzke, 2022) and is part indicator on Biodiversity Friendly Practices (BFP).

To apply both approaches (ex-post and ex-ante), it is necessary to harmonise the underlying databases and weighting factors.

B.2 Data sources

Sales volumes are currently used. Ideally, output quantities should be recorded.

The indicator integrates the environmental behaviour of the active substances, their risk to various organisms and the risk to human health. The weighting of these three elements into one indicator is the subject of current research (EU SUPPORT project).

Another open point is the number of product databases that are to be stored for the risk assessment. For the modelling of bioeconomy scenarios in CAPRI, pesticide use schemes for some advanced biomass crops (e.g. woody plants, grasses) are currently missing.

B.3 Coverage over time and replicability

Time coverage is from 1996 to 2024. Sales data is updated annually.

B.4 Coverage across scales and sectors; compatibility

Coverage of agricultural sector.

JKI Database: The PLI is reported on a national scale

CAPRI: modelling is on NUTS II level

C. Considerations for operationalization

C.1 Feasibility: Fit for monitoring

The indicators is considered "Robust" – the indicator is fit, but with acceptable uncertainty and/or potential challenges. See the explanations above.

C.2 Institutions

JKI for ex-post analysis and CAPRI Team (Thünen or Euro Care) for ex-ante

C.3 Future prospects

A continuation of currently available monitoring is very likely since it is part of European monitoring of pesticide risks.

C.4 Costs, considerations and reproducibility

Data is already being collected and processed for the purpose of monitoring agricultural pesticide use. Agriculture is the largest user of these substances and is part of the bioeconomy. In this respect, existing reports should be easy to integrate into bioeconomy monitoring. Costs will be incurred as part of the targeted improvements. Costs beyond this mainly concern the coverage of new agricultural crops.

C.5 Potential for automation

Strong potential for automation as annually data and models already exist (2019/782/EC).

C.6 Presentation options and breakdown / sub-indicator needs

A bar chart is suitable for the national resolution (and already used).

In the case of regionalisation, a representation as a map would be more suitable; trends could be indicated by additional symbols (e.g. one arrow per district).

C.7 Potential for scenario integration

Scenario integration is already done, the indicator is already part of CAPRI output parameters. See the explanations above.

C.8 Interlinkages and alignment with other monitoring activities

(2019/782/EC) and also the Biodiversity Strategy and Farm to Fork Strategy (see above).

Further Comments:

From 2026, farmers will have stricter documentation obligations (COM 2023/564). They will have to record the use of pesticides in more detail and electronically. Nevertheless, this will not improve the data basis, as this will only be requested for inspection if necessary.

References

Legend

Tier

Tier I describes the 30 core, priority indicators defined by the project that are highly relevant to represent a specific thematic area and which together with other Tier I indicators forms a systemic perspective of the various risks, opportunities and trade-offs within the Bioeconomy.

Tier II describes explanatory indicators that are of high priority and help to provide more specific information on trends within specific thematic areas.

Stage of development

Established:
Indicators which are already reported in other official monitoring systems

Semi-established:
Indicators which are developed by e.g. federal research institutes as part of long-term and regularly updated initiatives

New
Indicators not previously reported in an official capacity, but well established through research projects

Developing
Indicators under development with some reporting in new state-of-the research projects, but not subject to multiple years of revision and replication

Future
Indicator gaps requiring research for possible future integration

Robustness

Very robust:
methodologically sound, reliable, and fit for bioeconomy monitoring

Robust:
fit, but with acceptable uncertainty and/or potential challenges

Sufficient:
possibly fit, but with foreseeable challenges

Weak:
currently unfit, but short-term potential

Insufficient:
currently unfit, but with long-term potential