In silico environmental risk assessment improves efficiency for pesticide safety management.

Computational tools Exposure assessment Pesticide safety management Toxicity prediction

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
15 Jan 2024
Historique:
received: 03 08 2023
revised: 09 10 2023
accepted: 14 10 2023
medline: 27 11 2023
pubmed: 20 10 2023
entrez: 20 10 2023
Statut: ppublish

Résumé

Pesticides are indispensable to maintain crop quality and food production worldwide, but their use also poses environmental risks. Pesticide risk assessment involves a series of complex, expensive and time-consuming toxicity tests. To improve the efficiency and accuracy for assessing the environmental impact of pesticides, numerous computational tools have been developed. However, there is a notable deficiency in critical analysis or a systematic summary of environmental risk assessment tools and their applicable contexts. Here, many of the current approaches and tools for assessing environmental risks posed by pesticides are reviewed, and the question of whether these tools are fit for use on complex multicomponent scenarios is discussed. We analyze the adaptations of these tools to aquatic and terrestrial ecosystems, followed by the provision of resources for predicting pesticide concentrations in environmental medias, including air, soil and water. The successful application of computational tools for risk assessment and interpretation of predicted results will also be discussed. This assessment serves as a valuable resource, enabling scientists to utilize suitable models to enhance the robustness of pesticides risk assessments.

Identifiants

pubmed: 37858821
pii: S0048-9697(23)06505-1
doi: 10.1016/j.scitotenv.2023.167878
pii:
doi:

Substances chimiques

Pesticides 0
Soil 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

167878

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yang-Yang Gao (YY)

National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang 550025, PR China.

Wei Zhao (W)

National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang 550025, PR China.

Yuan-Qin Huang (YQ)

National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang 550025, PR China.

Vinit Kumar (V)

National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang 550025, PR China.

Xiao Zhang (X)

National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang 550025, PR China.

Ge-Fei Hao (GF)

National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang 550025, PR China; National Key Laboratory of Green Pesticide, Central China Normal University, Wuhan 430079, PR China. Electronic address: gefei_hao@foxmail.com.

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