Department of Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza, 1, 20126 Milano, Italy.
Ecotoxicol Environ Saf. 2011 Nov;74(8):2156-66. doi: 10.1016/j.ecoenv.2011.07.011. Epub 2011 Aug 25.
Mixture toxicity is a real world problem and as such requires risk assessment solutions that can be applied within different geographic regions, across different spatial scales and in situations where the quantity of data available for the assessment varies. Moreover, the need for site specific procedures for assessing ecotoxicological risk for non-target species in non-target ecosystems also has to be recognised. The work presented in the paper addresses the real world effects of pesticide mixtures on natural communities. Initially, the location of risk hotspots is theoretically estimated through exposure modelling and the use of available toxicity data to predict potential community effects. The concept of Concentration Addition (CA) is applied to describe responses resulting from exposure of multiple pesticides The developed and refined exposure models are georeferenced (GIS-based) and include environmental and physico-chemical parameters, and site specific information on pesticide usage and land use. As a test of the risk assessment framework, the procedures have been applied on a suitable study areas, notably the River Meolo basin (Northern Italy), a catchment characterised by intensive agriculture, as well as comparative area for some assessments. Within the studied areas, the risks for individual chemicals and complex mixtures have been assessed on aquatic and terrestrial aboveground and belowground communities. Results from ecological surveys have been used to validate these risk assessment model predictions. Value and limitation of the approaches are described and the possibilities for larger scale applications in risk assessment are also discussed.
混合物毒性是一个现实世界的问题,因此需要能够在不同地理区域、不同空间尺度以及可用数据量不同的情况下应用的风险评估解决方案。此外,还必须认识到需要针对非目标生态系统中的非目标物种评估生态毒理学风险的特定地点程序。本文介绍的工作涉及农药混合物对自然群落的实际影响。最初,通过暴露建模和使用可用毒性数据来预测潜在的群落效应,从理论上估计风险热点的位置。浓度加和(CA)的概念被应用于描述多种农药暴露导致的反应。开发和完善的暴露模型具有地理参考(基于 GIS),并包含环境和物理化学参数,以及有关农药使用和土地利用的特定地点信息。作为风险评估框架的测试,该程序已应用于合适的研究区域,特别是意大利北部的梅洛河盆地(River Meolo basin),这是一个以集约化农业为特征的集水区,也是一些评估的比较区域。在研究区域内,对水生和陆地地上和地下群落中的单个化学物质和复杂混合物的风险进行了评估。生态调查的结果用于验证这些风险评估模型的预测。描述了这些方法的价值和局限性,并讨论了在风险评估中更大规模应用的可能性。