Literature DB >> 19238990

Predicting pesticide environmental risk in intensive agricultural areas. II: Screening level risk assessment of complex mixtures in surface waters.

Roberto Verro1, Antonio Finizio, Stefan Otto, Marco Vighi.   

Abstract

In a previous article, a procedure for assessing pesticide ecotoxicological risk for surface water was applied to all active ingredients in a pilot basin. This data set has been used to assess the composition of pesticide mixtures that are likely to be present in surface waters as a consequence of pesticide emissions from the crops grown within the basin (maize, soybean, sugar beet, and vineyard). Temporal evolution of the mixture composition has been evaluated as a function of the different contamination patterns (drift and runoff). Ecotoxicological risk has been assessed for the mixtures released by individual crops and from all the relevant crops cultivated in the basin. The different role of drift and runoff, as well as the temporal trends of exposure and risk are compared. Daphnia is the most affected among the three indicator organisms considered, particularly from drift mixtures after insecticide application on vineyard. The highest risk for algae occurs during runoff events in spring. In most risk events, one or a few chemicals are usually responsible for more than 80% of the toxic potency of the mixture. The CA model for predicting mixture response is assumed to be a reliable approach for assessing risk for ecologically relevant pesticide mixtures.

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Year:  2009        PMID: 19238990     DOI: 10.1021/es801858h

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  8 in total

1.  Growth rate of Pseudokirchneriella subcapitata exposed to herbicides found in surface waters in the Alqueva reservoir (Portugal): a bottom-up approach using binary mixtures.

Authors:  Joanne Pérez; Inês Domingues; Amadeu M V M Soares; Susana Loureiro
Journal:  Ecotoxicology       Date:  2011-03-30       Impact factor: 2.823

2.  Evaluation of FOCUS surface water pesticide concentration predictions and risk assessment of field-measured pesticide mixtures-a crop-based approach under Mediterranean conditions.

Authors:  Ana Santos Pereira; Michiel A Daam; Maria José Cerejeira
Journal:  Environ Sci Pollut Res Int       Date:  2017-06-06       Impact factor: 4.223

3.  A novel method for assessing risks to pollinators from plant protection products using honeybees as a model species.

Authors:  Stefania Barmaz; Simon G Potts; Marco Vighi
Journal:  Ecotoxicology       Date:  2010-07-22       Impact factor: 2.823

4.  Risk assessment of an organochlorine pesticide mixture in the surface waters of Qingshitan Reservoir in Southwest China.

Authors:  Honghu Zeng; Xin Fu; Yanpeng Liang; Litang Qin; Lingyun Mo
Journal:  RSC Adv       Date:  2018-05-15       Impact factor: 4.036

5.  The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity by binary mixtures of chlorpyrifos and four other insecticides.

Authors:  Chen Chen; Yanhua Wang; Xueping Zhao; Qiang Wang; Yongzhong Qian
Journal:  Ecotoxicology       Date:  2013-12-23       Impact factor: 2.823

6.  Injury frequency and severity in crayfish communities as indicators of physical habitat quality and water quality within agricultural headwater streams.

Authors:  Tyler C Wood; Peter C Smiley; Robert B Gillespie; Javier M Gonzalez; Kevin W King
Journal:  Environ Monit Assess       Date:  2020-03-10       Impact factor: 2.513

7.  Assessing interactive mixture toxicity of carbamate and organophosphorus insecticides in the yabby (Cherax destructor).

Authors:  Ben Pham; Ana Miranda; Graeme Allinson; Dayanthi Nugegoda
Journal:  Ecotoxicology       Date:  2018-09-04       Impact factor: 2.823

8.  Mix-Tool: An Edge-of-Field Approach to Predict Pesticide Mixtures of Concern in Surface Water From Agricultural Crops.

Authors:  Antonio Finizio; Andrea Di Guardo; Luca Menaballi; Anna Barra Caracciolo; Paola Grenni
Journal:  Environ Toxicol Chem       Date:  2022-06-09       Impact factor: 4.218

  8 in total

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