Policy coherence for the protection of water resources against agricultural pollution in the EU and Norway.
Published In: Review of European Comparative & International Environmental Law, 2023, v. 32, n. 3. P. 485 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Platjouw, Froukje Maria; Nesheim, Ingrid; Enge, Caroline 3 of 3
Abstract
Throughout the European Union (EU), agricultural practices contribute significantly to the pollution of water resources by nitrates, phosphorus and pesticides. This article sheds light on the degree of horizontal legal coherence between the main EU legal and policy instruments applicable to the protection of water resources from agricultural pollution. After identifying key coherence challenges at the EU level, the article thoroughly assesses the regulatory and governance approach in Norway. The key question is how certain EU‐level coherence challenges could be mitigated at a national level through mechanisms aimed at facilitating cross‐sectoral coordination and policy coherence. Three types of mechanisms have been selected for this purpose: (i) legal mechanisms, including cross‐referencing and joint institutional responsibility for implementation; (ii) the establishment of platforms for cross‐sectoral policy coordination or actor participation; and (iii) the establishment of monitoring and reporting processes that ensure access to information and data sharing. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Review of European Comparative & International Environmental Law. 2023/11, Vol. 32, Issue 3, p485
- Document Type:Article
- Subject Area:Agriculture and Agribusiness
- Publication Date:2023
- ISSN:2050-0386
- DOI:10.1111/reel.12509
- Accession Number:173778176
- Copyright Statement:Copyright of Review of European Comparative & International Environmental Law is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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