Probabilistic approaches in the effect assessment of toxic chemicals. What are the benefits and limitations?

There is an ongoing discussion whether in the environmental risk assessment for chemicals the so called 'deterministic' approach using point estimates of exposure and effect concentrations is still appropriate. Instead, the more detailed and scientifically sounder probabilistic methods that have been developed over the last years are widely recommended. Here, we present the results of a probabilistic effect assessment for the aquatic environment performed for the pesticide methyl parathion and compare them with the results obtained with the common deterministic approach as described in the EU Technical Guidance Document. Methyl parathion was chosen because a sufficient data set (acute toxicity data for about 70 species) was available. The assumptions underlying the probabilistic effect assessment are discussed in the light of the results obtained for methyl parathion. Two important assumptions made by many studies are: (i) a sufficient number of ecologically relevant toxicity data is available, (ii) the toxicity data follow a certain distribution such as log-normal. Considering the scarcity of data for many industrial chemicals, we conclude that these assumptions would not be fulfilled in many cases if the probabilistic assessment was applied to the majority of industrial chemicals. Therefore, despite the well-known limitations of the deterministic approach, it should not be replaced by probabilistic methods unless the assumptions of these methods are carefully checked in each individual case, which would significantly increase the effort for the assessment procedure.     

我国地表水新烟碱类杀虫剂对水生生物安全的威胁

针对我国新烟碱类杀虫剂（NNIs）使用量大且地表水中浓度逐渐上升的现状,基于物种敏感度分布法,利用危害商法和概率风险评价法评估了我国地表水中NNIs对淡水水生生物的单一和复合生态风险,并对我国地表水质监管NNIs提出了目标建议值.结果表明：（1）单一化合物,吡虫啉的急性危害最大,吡虫啉和啶虫脒的慢性危害较大,最敏感生物均为昆虫;（2）海南省是地表水NNIs浓度最高的地区,急慢性危害最大;（3）联合毒性的概率曲线表明,5种NNIs对5%淡水水生生物产生慢性联合毒性的概率高达92.12%,严重威胁我国水生生物的安全;（4）基于物种敏感度分布曲线得到毒性参考值,结合危害商和概率风险评价的结果,建议我国保护水生生物安全的地表水质监管目标值分别为吡虫啉0.01μg·L^-1、噻虫啉0.03μg·L^-1、啶虫脒0.04μg·L^-1、噻虫胺0.22μg·L^-1和噻虫嗪0.24μg·L^-1.总之,我国地表水中NNIs浓度已经威胁到水生生物的安全,必须加强监管.     

长埔——西岭锡矿资源定量评价模型

本文以长埔——西岭锡矿带的76个矿床为基础从中选取17个已知成型矿床,分别用矢量长度法和最优分割法进行地质变量的优化选择与储量等级规模的划分;采用特征分析与逻辑信息法建立锡矿资源半定量和定量评价广义模型;并对该区59个矿化点进行含矿性及可能矿床规模的定量预测评价,筛选出6个找矿靶区。     

基于风险指引的核电厂设计改进评价研究

核电厂概率安全评价(PSA)可以论证核电厂的风险满足安全目标,也是对运行核电厂进行风险管理的有效工具,例如核电厂的在役检查、安全分级、技术规格书优化等。核电厂的风险指引管理是在确定论的基础上,充分利用概率安全评价的结果进行风险影响评价,以此来论证决策的合理性。核电厂的重要设计改进通常基于传统的工程分析结果,没有分析其对核电厂整体风险的影响。重点探讨风险指引决策的基本原则以及方法,以核电厂设计改进实例探讨如何在分析时引入风险指引方法,并提出相关建议。     

Preventing the Spread of Invasive Species: Economic Benefits of Intervention Guided by Ecological Predictions

Abstract:  Preventing the invasion of freshwater aquatic species is the surest way to reduce their impacts, but it is also often expensive. Hence, the most efficient prevention programs will rely on accurate predictions of sites most at risk of becoming invaded and concentrate resources at those sites. Using data from Vilas County, Wisconsin (U.S.A.), collected in the 1970s, we constructed a predictive occurrence model for rusty crayfish ( Orconectes rusticus ) and applied it to an independent data set of 48 Vilas County lakes to predict which of these were most likely to become invaded between 1975 and 2005. We nested this invasion model within an economic framework to determine whether targeted management, derived from our quantitative predictions of likely invasion sites, would increase the economic value of lakes in the independent data set. Although the optimum expenditure on lake protection was high, protecting lakes at this level would have produced net economic benefits of at least $6 million over the last 30 years. We did not attempt to determine the value of nonmarket benefits of protection; thus, our results are likely to underestimate the total benefits from preventing invasions. Our results demonstrate that although few data are available early in an invasion, these data may be sufficient to support targeted, effective, and economically rational management. In addition, our results show that ecological predictions are becoming sufficiently accurate that their application in management can produce net economic benefits.     

MACROSCALE HYDROLOGIC MODELING FOR REGIONAL CLIMATE ASSESSMENT STUDIES IN THE SOUTHEASTERN UMTED STATES1

ABSTRACT: A macroscale hydrologic model is developed for regional climate assessment studies under way in the southeastern United States. The hydrologic modeling strategy is developed to optimize spatial representation of basin characteristics while maximizing computational efficiency. The model employs the “grouped response unit” methodology, which follows the natural drainage pattern of the area. First order streams are delineated and their surface characteristics are tested so that areas with statistically similar characteristics can be combined into larger computational zones for modeling purposes. Hydrologic response units (HRU) are identified within the modeling units and a simple three‐layer water balance model, Soil and Water Assessment Tool (SWAT), is executed for each HRU. The runoff values are then convoluted using a triangular unit hydrograph and routed by Muskingum‐Cunge method. The methodology is shown to produce accurate results relative to other studies, when compared to observations. The model is used to evaluate the potential error in hydrologic assessments when using GCM predictions as climatic input in a rainfall‐runoff dominated environment. In such areas, the results from this study, although limited in temporal and spatial scope, appear to imply that use of GCM climate predictions in short term quantitative analyses studies in rainfall‐runoff dominated environments should proceed with caution.     

PREDICTION OF TWO-YEAR PEAK STREAM-DISCHARGES USING NEURAL NETWORKS1

ABSTRACT: The cascade correlation neural network was used to predict the two-year peak discharge (Q₂) for major regional river basins of the continental United States (US). Watersheds ranged in size by four orders of magnitude. Results of the neural network predictions ranged from correlations of 0.73 for 104 test data in the Souris-Red Rainy river basin to 0.95 for 141 test data in California. These results are improvements over previous multilinear regressions involving more variables that showed correlations ranging from 0.26 to 0.94. Results are presented for neural networks trained and tested on drainage area, average annual precipitation, and mean basin elevation. A neural network trained on regional scale data in the Texas Gulf was comparable to previous estimates of Q₂ by regression. Our research shows Q₂ was difficult to predict for the Souris-Red Rainy, Missouri, and Rio Grande river basins compared to the rest of the US, and acceptable predictions could be made using only mean basin elevation and drainage areas of watersheds.     

AERMOD与估算模式在环境影响评价中的应用与比较研究

简单描述了大气环境影响评价中的AERMOD模型及估算模式,采用这两种预测模式对同一生活垃圾填埋场无组织排放的NH3、H2S进行了预测。比较两种模式的预测结果可以看出,估算模式仅能预测小时值,AERMOD模式可同时预测小时值、日平均值、年平均值。在污染源、预测范围、运行周期相同的情况下,不论哪种预测模式,污染物的最大落地浓度均与排放源强呈正比,敏感点处的落地浓度均与污染物源强呈正比、与距离呈反比。预测结果同时说明,估算模式是一种保守的预测模式,其预测结果比AERMOD模式大,可作为进一步预测模式的有效补充。     

基于参数不确定性的地下水污染治理多目标管理模型

引入随机Pareto控制排序和随机小生境技术,提出基于参数随机变化的改进小生境Pareto遗传算法,用于求解不确定性条件下地下水污染治理多目标管理模型.同时,利用顺序高斯条件模拟的蒙特卡罗方法,结合不确定性分析和风险评估,分析不同渗透系数条件点数对污染物运移结果不确定性和污染风险评价的影响.最后将该方法应用于一个考虑渗透系数为随机变量的二维地下水污染修复算例中.结果分析表明,该方法可为地下水污染治理提供变异性较小的Pareto管理策略,是一种稳定可靠的多目标随机优化方法.     

概率火灾安全分析方法研究

为分析和评估火灾对设备、建筑物等敏感目标结构安全的影响,结合化工定量风险评估方法和气体爆炸概率安全分析方法,提出概率火灾安全分析策略和实施流程。该方法包括火灾危害辨识、泄漏速率计算、火灾后果模拟、频率分析、绘制频率超越热载荷曲线、结构响应分析等关键步骤。以某柴油罐区为例,通过频率分析和火灾模拟,绘制出频率超越热载荷曲线,假定火灾风险可接受准则为10-4/a,求得对应的可信热载荷为21 kW/m2,并以此值作为结构热响应分析的输入参数。火灾概率安全分析方法侧重于描述火灾热辐射强度及其对应的发生可能性,判定敏感目标遭遇的可信火灾热载荷强度和结构热响应行为,评估消防减灾措施效果,确保结构完整性和可用性,不评价工艺系统潜在火灾风险的高低。