RESUMO
Addressing the wide range of marine pollution problems facing the global ocean requires a continual transfer of credible, relevant and timely scientific information to policy and decision makers in coastal and ocean management. The United Nations GESAMP (Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection) is a long-standing scientific advisory group providing such information on a wide range of marine topics and emerging issues of concern to ten UN Sponsoring Organizations. This paper presents an overview of GESAMPs operation and examples of its current work. The group's scientific output is often cited by national governments, inter-governmental groups, and a range of non-governmental groups. Given the growing concerns about ocean health and the impacts of many stressors in an era of climate change, the development of timely and effective ocean policy and decision making would benefit from wider recognition and application of GESAMPs work.
Assuntos
Conservação dos Recursos Naturais , Poluição Ambiental , Políticas , Oceanos e MaresRESUMO
While probabilistic methods gain attention in hazard characterization and are increasingly used in exposure assessment, full use of the available probabilistic information in risk characterization is still uncommon. Usually, after probabilistic hazard characterization and/or exposure assessment, percentiles from the obtained distributions are used as point estimates in risk characterization. In this way, all information on variability and uncertainty is lost, while these aspects are crucial in any risk assessment. In this paper, we present a method to integrate the entire distributions from probabilistic hazard characterization and exposure assessment into one risk characterization plot. This method is illustrated using di(2-ethylhexyl) phthalate as an example. The final result of this probabilistic risk assessment is summarized in a single plot, containing two pieces of information: the confidence we may have in concluding there is no risk, and the fraction of the population this conclusion applies to. This information leads to a better informed conclusion on the risk of a substance, and may be very useful to define the necessary measures for risk reduction.