Publikation:
Improving the risk assessment of pesticides through the integration of Human Biomonitoring and Food Monitoring Data: a case study for chlorpyrifos

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dc.contributor.authorTarazona, Jose V.
dc.contributor.authorGonzález-Caballero, Maria Carmen
dc.contributor.authorAlba-Gonzalez, Mercedes de
dc.contributor.authorKolossa-Gehring, Marike
dc.contributor.authorWeber, Till
dc.date.accessioned2024-06-16T13:10:54Z
dc.date.available2024-06-16T13:10:54Z
dc.date.issued2022
dc.description.abstractThe risk assessment of pesticide residues in food is a key priority in the area of food safety. Most jurisdictions have implemented pre-marketing authorization processes, which are supported by prospective risk assessments. These prospective assessments estimate the expected residue levels in food combining results from residue trials, resembling the pesticide use patterns, with food consumption patterns, according to internationally agreed procedures. In addition, jurisdictions such as the European Union (EU) have implemented large monitoring programs, measuring actual pesticide residue levels in food, and are supporting large-scale human biomonitoring programs for confirming the actual exposure levels and potential risk for consumers. The organophosphate insecticide chlorpyrifos offers an interesting case study, as in the last decade, its acceptable daily intake (ADI) has been reduced several times following risk assessments by the European Food Safety Authority (EFSA). This process has been linked to significant reductions in the use authorized in the EU, reducing consumers exposure progressively, until the final ban in 2020, accompanied by setting all EU maximum residue levels (MRL) in food at the default value of 0.01 mg/kg. We present a comparison of estimates of the consumerââą Ìs internal exposure to chlorpyrifos based on the urinary marker 3,5,6-trichloro-2-pyridinol (TCPy), using two sources of monitoring data: monitoring of the food chain from the EU program and biomonitoring of European citizens from the HB4EU project, supported by a literature search. Both methods confirmed a drastic reduction in exposure levels from 2016 onwards. The margin of exposure approach is then used for conducting retrospective risk assessments at different time points, considering the evolution of our understanding of chlorpyrifos toxicity, as well as of exposure levels in EU consumers following the regulatory decisions. Concerns are presented using a color code, and have been identified for almost all studies, particularly for the highest exposed group, but at different levels, reaching the maximum level, red code, for children in Cyprus and Israel. The assessment uncertainties are highlighted and integrated in the identification of levels of concern. © 2022 by the authors.en
dc.format.extent1 Onlineresource (16 pages)
dc.format.mediumonline resource
dc.identifier.doihttps://doi.org/10.60810/openumwelt-300
dc.identifier.urihttps://openumwelt.de/handle/123456789/2635
dc.language.isoeng
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectHuman-Biomonitoring
dc.subjectChlorpyrifos
dc.titleImproving the risk assessment of pesticides through the integration of Human Biomonitoring and Food Monitoring Data: a case study for chlorpyrifos
dc.typeWissenschaftlicher Artikel
dc.type.dcmitext
dc.type.mediumcomputer
dspace.entity.typePublication
local.bibliographicCitation.journalTitleToxics
local.bibliographicCitation.originalDOI10.3390/toxics10060313
local.bibliographicCitation.volume10 (2022), Heft 6
local.collectionAufsätze
local.contributor.authorId00311895
local.contributor.authorId02190353
local.contributor.authorId02190354
local.identifier.catalogId02492826
local.ingest.leader06504naa a2200000uu 4500
local.jointTitleIMPROVING THE RISK ASSESSMENT OF PESTICIDES THROUGH THE INTEGRATION OF HUMAN BIOMONITORING AND FOOD MONITORING DATA A CASE STUDY FOR CHLORPYRIFOS
local.reviewtrue
local.sourcecatalog
local.source.urihttp://creativecommons.org/licenses/by/4.0/deed.de
local.staffPublicationtrue
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relation.isAuthorOfPublication.latestForDiscovery0c3b6c3e-eff4-42d8-94e9-07a4fee4049c
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