Mapping Cumulative Environmental Risks: Examples from the EU NoMiracle Project View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-04

AUTHORS

Alberto Pistocchi, Jan Groenwold, Joost Lahr, Mark Loos, Marelys Mujica, Ad M. J. Ragas, Robert Rallo, Serenella Sala, Uwe Schlink, Kathrin Strebel, Marco Vighi, Pilar Vizcaino

ABSTRACT

We present examples of cumulative chemical risk mapping methods developed within the NoMiracle project. The different examples illustrate the application of the concentration addition (CA) approach to pesticides at different scale, the integration in space of cumulative risks to individual organisms under the CA assumption, and two techniques to (1) integrate risks using data-driven, parametric statistical methods, and (2) cluster together areas with similar occurrence of different risk factors, respectively. The examples are used to discuss some general issues, particularly on the conventional nature of cumulative risk maps, and may provide some suggestions for the practice of cumulative risk mapping. More... »

PAGES

119-133

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10666-010-9230-6

DOI

http://dx.doi.org/10.1007/s10666-010-9230-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021243358


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10666-010-9230-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10666-010-9230-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10666-010-9230-6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10666-010-9230-6'


 

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