An assessment of environmental and toxicological risk to pesticide exposure based on a case-based approach to computing

International Conference on Energy Engineering and Environmental Protection 2016

能源学;生态环境科学

Coelho, Cristina^1 ; Vicente, Henrique^1,2 ; Rosário Martins, M.^3 ; Lima, Nelson^4 ; Neves, Mariana^5 ; Neves, José^2

Departamento de Química, Escola de Ciências e Tecnologia, Universidade de Évora, Évora, Portugal^1

Centro Algoritmi, Universidade Do Minho, Braga, Portugal^2

Departamento de Química, Laboratório HERCULES, Escola de Ciências e Tecnologia, Universidade de Évora, Évora, Portugal^3

Centro de Engenharia Biológica, Micoteca da Universidade Do Minho, Universidade Do Minho, Braga, Portugal^4

Deloitte, London, United Kingdom^5

关键词: Aggregate exposure;    Case-based approach;    Environmental fate;    Explicit treatments;    Knowledge representation and reasoning;    Occupational environment;    Pesticide degradation;    Pesticide exposure;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/52/1/012091/pdf
DOI  :  10.1088/1742-6596/52/1/012091

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Pesticide environmental fate and toxicity depends on its physical and chemical features, the soil composition, soil adsorption, as well as residues that may be found in different soil slots. Indeed, pesticide degradation in soil may be influenced by either biotic or abiotic factors. In addition, the toxicity of pesticides for living organisms depends on their adsorption, distribution, biotransformation, dissemination of metabolites together with interaction with cellular macromolecules and excretion. Biotransformation may result in the formation of less toxic and/or more toxic metabolites, while other processes determine the balance between toxic and a nontoxic upcoming. Aggregate exposure and risk assessment involve multiple pathways and routes, including the potential for pesticide residues in food and drinking water, in addition to residues from pesticide use in residential and non-occupational environments. Therefore, this work will focus on the development of a decision support system to assess the environmental and toxicological risk to pesticide exposure, built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based attitude to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.