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22 results for “pesticide risk”
Exposure to pesticides data for residents and bystanders, and for environmental risk assessment
<p>In 2014, EFSA has commissioned a study to review and evaluate all published data related to the exposure to pesticides for residents and bystanders and for environmental risk assessment. The aim was to conduct a literature review and to produce a database containing all published data (predominately peer-reviewed publications supplemented by grey-literature) for the last 25-years, which will support the non-dietary exposure assessment to pesticides for bystanders and residents, as well as daily air concentration (vapours and aerosols) of pesticides, drift values from spray, seed and granular applications, and dislodgeable foliar residues.</p> <p>The data has been collated via a systematic and extensive literature review defined and managed according to a pre-defined 'review protocol'. The data was also exported in a format that meets the requirements of the EFSA Data Collection Framework (DCF).</p> <p>Based on quality and relevance criteria, articles and related studies have been selected. For dislodgeable foliar residues the assessment includes 27 articles (containing 49 discrete studies); for air concentrations, 26 articles (containing 84 discrete studies); for resident and bystander exposure, 5 articles (containing 8 discrete studies); and for drift values 55 articles (containing 275 discrete studies). </p> <p>For dislodgeable foliar residues the data retained covered 17 crops (including grass, glasshouse crops, lucerne, and citrus) and 29 pesticides; for air concentrations the data retained covered 21 crops (including fruit, glasshouse crops, ornamentals, grass, vegetables and cereals) and 39 pesticides. For drift values, the data covers a range of crops and landscapes from cereals, grass and turf, orchards, vineyards and regenerated forestry. The vast majority of the data retrieved applies to field studies for liquid spray drift, measured either as ground deposits or collected at various heights and were conducted using fluorescent tracers rather than pesticides. No data was found for microbials (biopesticides). For resident and bystander exposure, many articles were rejected due to the applied inclusion/exclusion criteria.</p>
C2D2: An Open-Source, Pan-European, Harmonised Crop Development Database for Use in Regulatory Pesticide Exposure Modelling and Risk Assessment.
<p>There is a regulatory need for crop development dates to assess current default values used within chemical exposure assessments as well as to justify refinements within risk assessments. However, a readily available pan-European crop phenology database covering key FOCUS (FOrum for the Co-ordination of pesticide fate models and their USe) crops and scenarios to meet this need is not currently available. Therefore, we describe the development of a harmonised, pan-European, CropLife Europe Crop Development Database, C2D2, that is fully aligned with this regulatory requirement utilising efficacy trials data generated for regulatory submissions when registering plant protection products under Regulation (EU) 1107/2009. Evaluation of C2D2 against an independent dataset showed good agreement for equivalent time periods, crop growth stages and geographical regions. We illustrate how this database can be used to evaluate existing default crop development dates mandated by regulatory agencies for use within exposure assessments. Despite the large dataset compiled and the geographical coverage of C2D2, not all FOCUSsw/gw scenarios have sufficient data to facilitate comparison, with less significant scenarios, like FOCUSgw Porto, being under-represented. For those scenarios with sufficient data, clear differences between C2D2 and crop development dates assumed in the FOCUS modelling framework (using the AppDate tool) are often indicated over some/many growth stages suggesting that amendment of the existing representation of crop development within the risk assessment process may be required. C2D2 is freely available under a Creative Commons licence to facilitate innovation in exposure science to allow for more accurate and realistic risk assessment leading to enhanced crop and environmental protection.</p>
Raw data files associated with the paper "Beyond generalists: the Brassicaceae pollen specialist Osmia brevicornis as a prospective model organism when exploring pesticide risk to bees"
<p>These are the raw data CSV files associated with the results described in the paper "Beyond generalists: the Brassicaceae pollen specialist Osmia brevicornis as a prospective model organism when exploring pesticide risk to bees".</p> <p>By Sara Hellström, Verena Strobl, Lars Straub, Wilhelm H. A. Osterman, Robert J. Paxton, Julia Osterman</p>
Annexes to the EFSA external scientific report "Proposed prospective scenarios for cumulative risk assessment of pesticide residues"
<p>In the context of prospective cumulative risk assessment of pesticides, different options and scenarios for a tiered approach were investigated by means of 15 case studies for the cumulative assessment group associated with an effect on the motor division of the nervous system (CAG-NAM) and 15 case studies for the cumulative assessment group associated with an effect on hypothyroidism (CAG-TCF) (doi:10.2903/sp.efsa.2021.EN-6811). The results of the prospective exposure calculations are reported in the following annexes:</p> <p><strong>Annex A</strong>: Acute exposure calculations - CAG-NAM</p> <p><strong>Annex B</strong>: Chronic exposure calculations - CAG-TCF</p> <p><strong>Annex C</strong>: Results supporting the discussion on prospective acute scenarios - CAG-NAM</p> <p><strong>Annex D</strong>: Results supporting the discussion on prospective chronic scenarios - CAG-TCF</p> <p>The case studies reported above also include fictitious data, which were included for assessing the relevance of the various parameters in these calculations. The results of these case studies do not represent real estimates of exposure or risk, nor do they represent the formal outcome of a risk assessment.</p>
consumer risk perception toward pesticide stained tomatoes in Uganda
<p>A data set for measuring consumer risk perception towards pesticide-stained tomatoes in Uganda (sample 4 major regions in Uganda)</p>
Dataset for: Expanding risk predictions of pesticide resistance evolution in arthropod pests with a proxy for selection pressure
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Data for: Developmental origins of Parkinson’s disease risk: perinatal exposure to the organochlorine pesticide dieldrin leads to sex-specific DNA modifications in critical neurodevelopmental pathways in the mouse midbrain
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Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA
<p>Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA.</p> <p>Harmonized methodology for retrospective dietary cumulative risk assessment (CRA) of pesticides was established by the European Commission (EC) and the European Food Safety Authority (EFSA) in 2018, in close collaboration with the Dutch National Institute for Public Health and the Environment (RIVM). An update of this regulatory methodology (RM) was proposed and adopted by EFSA in 2022 in a CRA on craniofacial alterations. This updated RM was implemented in version 10 of the MCRA software and validated as part of the first action defined in the third framework partnership agreements between EFSA and RIVM. This report describes the implementation of this updated methodology in the MCRA software for risk assessment. This is done from a proposed framework of standard regulatory actions (SRAs). SRAs offer a user-friendly and simple to use option for regulators to perform retrospective and prospective CRAs in MCRA according to agreed-upon RMs. In particular, this report provides guidance on the use of an SRA for a retrospective dietary CRA for craniofacial alterations according to the updated RM in MCRA version 10.</p> <p>Detailed results of the comparison between reported by MCRA and EFSA’s SAS® software and MCRA formatted input files for the catalogues and secondary data are presented in the following annexes:</p> <ul> <li>Annex A – Comparison of the MOET at different percentiles reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. </li> <li> <p>Annex B – Comparison of risk-driver contributions reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. </p> </li> </ul> <ul> <li> <p>Annex C – MCRA formatted input data file containing the primary entity catalogues for the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> <li> <p>Annex D – MCRA formatted input data file containing the secondary data for the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> <li> <p>Annex E – MCRA formatted input data file containing the unit- variability factors for the Tier II calculations of the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> <li> <p>Annex F – MCRA formatted input data file containing the unit- variability factors for the Tier I calculations of the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> </ul> <p> </p>
Not all regions with high pesticide risk deserve priority concern
<p>The datasets with 14 sheets contain basic data on pesticide use in China since 1991, parameters of four widely used pesticides (carbofuran, chlorpyrifos, atrazine and acetochlor), and related changing legacies, concentrations, and ecological risk in multimedia of each basin for 30 years. The detailed content can be found in the sheet 'Readme'.</p>
Retrospective cumulative dietary risk assessment of craniofacial alterations by residues of pesticides
<p>EFSA established cumulative assessment groups and conducted retrospective cumulative risk<br> assessments for two types of craniofacial alterations (alterations due to abnormal skeletal<br> development, head soft tissue alterations and brain neural tube defects) for 14 European populations<br> of women in childbearing age. Cumulative acute exposure calculations were performed by probabilistic<br> modelling using monitoring data collected by Member States in 2017, 2018 and 2019. A rigorous<br> uncertainty analysis was performed using expert knowledge elicitation. Considering all sources of<br> uncertainty, their dependencies and differences between populations, it was concluded with varying<br> degrees of certainty that the MOET resulting from cumulative exposure is above 100 for the two types<br> of craniofacial alterations. The threshold for regulatory consideration established by risk managers is<br> therefore not exceeded. Considering the severity of the effects under consideration, it was also<br> assessed whether the MOET is above 500. This was the case with varying levels of certainty for the<br> head soft tissue alterations and brain neural tube defects. However, for the alterations due to<br> abnormal skeletal development, it was found about as likely as not that the MOET is above 500 in<br> most populations. For two populations, it was even found more likely that the MOET is below 500.<br> These results were discussed in the light of the conservatism of the methodological approach.</p> <p>The indicators of craniofacial alterations, input and output data for the exposure assessment are reported in the following annexes:</p> <p>• Annex A – Indicators of craniofacial alterations collected for 85 selected active substances;<br> • Annex B1 – Input data for the exposure assessment of CAG-DACL;<br> • Annex B2 – Input data for the exposure assessment of CAG-DAH;<br> • Annex C1 – Output data for the Tier I exposure assessment of CAG-DAC;<br> • Annex C2 – Output data for the Tier I exposure assessment of CAG-DAH;<br> • Annex D1 – Output data for the Tier II exposure assessment of CAG-DAC;<br> • Annex D2 – Output data for the Tier II exposure assessment of CAG-DAH.</p>
Data for: Pesticide Risks in Small Streams -- How to Get as Close as Possible to the Stress Imposed on Aquatic Organisms
<p>The dataset contains concentrations profiles of 213 agricultural pesticides in surface water samples. Half-day composite samples were taken from five small streams in Switzerland from the beginning of March to the end of August 2015. Half-day samples from discharge events were measured individually, whereas half-day samples taken during dry weather periods between discharge events were pooled to samples of variable lengths (five days on average) and then measured resulting in 34 to 60 measured samples per site.</p>
Data from: Chiral pesticides selectively influence the dissemination of antibiotic resistance genes: An overlooked environmental risk
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Data from: Risk of potential pesticide use to honeybee and bumblebee survival and distribution: a country-wide analysis for The Netherlands
Aim: Bees play an important role in natural ecosystems and the world's food supply. In the past decades, bee abundance and diversity have declined globally. This has resulted in decreased pollination services for natural ecosystems and the agricultural sector at the field scale. One of the causes of the decline in bee abundance and diversity is the use of pesticides. Linking pesticide use, land use and bee presence could provide crucial insights into areas and pesticides that pose a significant threat to the abundance and diversity of bees. Obtaining actual figures of farmer pesticide use is rarely possible. Therefore, we designed a method to study the effects of potential pesticide use on the survival and distribution of honey- and bumblebees. Location: The Netherlands. Methods: A pesticide risk model was implemented incorporating a hazard quotient as the risk assessment. The number of allowed pesticide active ingredients per crop that could pose a risk to honeybees and bumblebees were linked to the Dutch crop parcel locations for 2015 and 2016. The potential pesticide risk maps were analyzed using honeybee colony survival and bumblebee presence data. Results: Non-significant negative effects of potential pesticide risk on honeybee colony survival and bumblebee presence were found. A significant negative effect of greenhouses was identified for both honeybees and bumblebees. The most important factors in the models predicting honeybee colony survival and bumblebee presence were urban land areas and natural grasslands respectively, both showing a positive effect. Main conclusions: Here, the first attempt to estimate and map pesticide risk to bees in the Netherlands in a country-wide manner is presented. The results could provide crucial high-resolution insights for bee conservation action and facilitate the increase of pollination services in natural ecosystems and the agricultural sector on a local and country-wide scale.
Pesticide risk during commercial apple pollination is greater for honeybees than other managed and wild bees
<p>Data and code relating to the manuscript “Pesticide risk during commercial apple pollination is greater for honeybees than other managed and wild bees”</p> <p>Files are organized as follows</p> <p><strong>input</strong> - contains the main data files.</p> <ul> <li> <p>all_pesticide2019.csv – contains the pesticide residue data for all samples</p> </li> <li> <p>LD50.csv – contains pesticide LD50s in PPB</p> </li> <li> <p>ld50_per_bee.csv – contains pesticide LD50s in ug / honeybee</p> </li> <li> <p>nesting_type.csv – lists nesting types of the different bee samples</p> </li> <li> <p>pesticide_type.csv – lists pesticides by their type</p> </li> <li> <p>short_name.csv – lists short bee names</p> <p><strong>folder “gis”</strong></p> <ul> <li>hive_distance_matrix.csv – distances from each orchard to other sites</li> <li>sitelocation.csv – contains coordinates of sites</li> </ul> </li> </ul> <p><strong>code</strong> - contains the scripts to analyze the input files</p> <ul> <li>pesticide_analysis.R – is the main anaylsis for the paper</li> <li>unadjusted_pesticide_analysis.R – is a copy of most of the code above but without LD50 weight adjustements</li> </ul> <p><strong>ld50 adjust</strong> - contains the inputs and code for the ld50 adjustments I ran</p> <ul> <li>ld50_adjust.R – is the code to calculate our the adjustements</li> <li>2020_BeeTox_database_acute_contact_publication_final_R1.csv – is the data file taken from pamminger publication</li> </ul>
The value of increased spatial resolution of pesticide usage data for assessing risk to endangered species: Data, notebooks, and results
<p>Decision makers often cite data quality as a limitation in environmental management. Value of information approaches evaluates the benefit of new data collection for management outcomes. Pesticide exposure risk assessment for endangered species is one context where data limitations may affect decisions and a value of information type approach could be useful for identifying optimal data <span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>quality and resolution. Under the U.S. Federal Insecticide, Fungicide and Rodenticide Act, the U.S. Environmental Protection Agency (EPA) is responsible for registering pesticides before they can be sold and regularly reviewing pesticides. Section 7 of the Endangered Species Act requires that the EPA consider potential impacts of pesticides to listed endangered species and critical habitats in this process, and for the Services—U.S. Fish and Wildlife Service and National Marine Fisheries Service—to complete a formal Section 7 consultation if the EPA deems it necessary. The current process is time‐intensive, lacks transparency and confidence among stakeholders, and leaves hundreds of unreviewed pesticides on the market. Increasing the resolution of pesticide usage data could address these concerns by improving estimated overlaps between species ranges and pesticide usage. Thus, we evaluated the relative importance of different resolutions of pesticide usage data for assessing expected carbaryl exposure to endangered plant species endemic to California. We found that spatially explicit, township resolution usage data (~36</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span> <span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>mile</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><sup>2</sup><span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>) excluded 33% of terrestrial plants (55/168) and 51% their critical habitats (27/53) from requiring a Section 7 consultation, while coarser resolution data excluded none. In contrast, the EPA's biological evaluation for carbaryl only excludes 4% of terrestrial plants (nationally) from requiring formal Section 7 consultation. This suggests high‐resolution data could increase pesticide review efficiency and decrease the amount of time pesticides remain on the market without a formal evaluation.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></p>
Data for: Pesticide Risks in Small Streams – How to Get as Close as Possible to the Stress Imposed on Aquatic Organisms
<p>The dataset contains concentrations profiles of 213 agricultural pesticides in surface water samples. Half-day composite samples were taken from five small streams in Switzerland from the beginning of March to the end of August 2015. Half-day samples from discharge events were measured individually, whereas half-day samples taken during dry weather periods between discharge events were pooled to samples of variable lengths (five days on average) and then measured resulting in 34 to 60 measured samples per site.</p>
Pesticides--Health Fertility and Reproductive Risk
ClinicalTrials.gov study NCT00015561. IPD Sharing: Not stated. Countries: 1. Publications: 5.
The value of increased spatial resolution of pesticide usage data for assessing risk to endangered species: Data, notebooks, and results
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Data from: Risk of potential pesticide use to honeybee and bumblebee survival and distribution: a country-wide analysis for The Netherlands
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Data from: Risk assessment of pesticide seed treatment for farmland birds using refined field data
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