海洋倾倒风险评估:化学生物浓度、商业鱼类捕捞和人类鱼类消费变化所带来的不确定性分析

J. Lipton
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引用次数: 0

摘要

人类食用被倾倒在美国中大西洋沿岸的城市污水污泥污染的海洋生物可能会对健康构成重大威胁。为了保护人类健康,研究人员对这些风险进行了建模。这些模型未能反映参数变率带来的不确定性。进行了一项分析,以检查生物浓度变化、商业鱼类捕捞量和海产品消费对风险估计的影响。当将这些参数的可变性纳入风险模型时,计算出的人类健康风险变化了三个数量级。已公布的滴滴涕和多氯联苯在不同鱼类中的生物浓度因子呈对数正态分布(v = 5)。0, 0 =。6为DDT, p=5.2, a=。多氯联苯为8)。这一关系被用于模拟因食用BCF未知的物种而产生的健康风险。估计了健康风险超过关键监管阈值(例如10 -6)的可能性。然后编制风险“权变表”,表明在不同模型假设下超过目标风险阈值的概率。最后,在人类健康风险的蒙特卡罗模拟中,使用了BCF、商业鱼类捕捞量和鱼类消费的分布。结果表明,参数变异性可导致健康风险估计值的范围跨越当前的风险管理阈值。因此,如果不明确考虑,这种可变性可能导致基于风险的决策错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ocean Dumping Risk Assessment: Analysis Of Uncertainties Imposed By Variability In Chemical Bioconcentration, Commercial Fish Landings, And Human Fish Consumption
Human consumption of marine organisms that have been contaminated by municipal sewage sludges dumped of the U.S. mid-Atlantic coast may pose significant health risks. In order to protect human health, researchers have modeled these risks. Such models have failed to reflect uncertainties imposed by parameter variability. An analysis was conducted to examine the effects of variability in bioconcentration, commercial fish landings, and seafood consumption on risk estimates. Calculated human health risks varied by three orders of magnitude when variability in these parameters was included in the risk model. Published bioconcentration factors (BCF) for DDT and for PCBs in different fish species were found to be log-normally distributed ( v = 5 . 0 , 0 = . 6 for DDT and p=5.2, a=.8 for PCBs) . This relationship was used to model health risks stemming from consumption of species for which BCF are unknown. The probability of health risks exeeding critical regulatory threshold (e.g. 10 -6) was estimated. Risk "contingency tables," indicating the probability of exceeding target risk thresholds under different model assumptions, were then compiled. Finally, distributions of BCF, commercial fish landings, and fish consumption were used in a Monte-Carlo simulation of human health risks. Results indicate that parameter variability can lead to a range of estimated health risks which straddles current risk-management thresholds. Thus, if not explicitly considered, this variability can lead to errors in risk-based decision-making.
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