Managing Uncertainty in Risk-Based Corrective Action Design: Global Sensitivity Analysis of Contaminant Fate and Exposure Models Used in the Dose Assessment

A variance-based global sensitivity analysis (GSA) was applied to the dose assessment model used in the risk-based corrective action methodology of environmental risk analysis to identify key sources of variability and uncertainty and quantify the relative contribution of these sources to the variance of estimated dose. GSA was performed applying extended Fourier amplitude sensitivity test technique. The soil-to-air contaminant transport pathway within an inhalation exposure scenario was addressed. Three persistent semi-volatile carcinogenic chemicals, including polychlorinated biphenyls, benzo(a)pyrene, and 2,3,7,8-tetrachlorodibenzo-p-dioxin, were chosen as contaminants of concern.     

利用神经网络法对胺类有机物急性毒性的分类及定量预测

运用三层误差反向传播网络对５１种胺类有机物进行了结构－毒性关系的研究,进入的结构参数为分子连接性指数信息理论指及分子量等６种均可通过分子拓扑图直接计算获得的指标。毒性参数选用大鼠经口ＬＤ５０,根据其大小将样本分为３类：高毒,中毒,低毒,在神经网络模型上作出差别归类,并分别对每类进行定量预测。     

杀虫双对土壤脲酶影响的研究

通过对土壤脲酶受杀虫双影响的研究．结果表明,杀虫双对不同生态区土壤脲酶活性具有明显的抑制作用,随杀虫双浓度的增加,酶活性持续减小、计算得到了土壤酶活性的生态剂量ＥＤ５０值,获得了北方(?)土和南方红壤污染的;临界浓度为４８９和２４６ｇ/ｋｇ;Ｌａｎｇｍｕｉｒ模型可较好表征酶活性与尿素浓度间的定量关系;土壤脲酶活性和最大表观酶活性均可表征土壤受杀虫双污染程度的大小。     

梵净山自然保护区基岩的天然γ辐射水平

梵净山自然保护区地表和深部２６种基岩的γ辐射值为７．４ｘ１０－８－１６．７ｘ－８ＧＹ·ｈ－１。讨论了该区基岩的γ辐射水平及分布的主要特点。     

新疆核试验场周围地区主要食品中~(90)Sr(锶)、~(137)Cs(铯)水平及其所致居民剂量

本文报道了新疆核试验场周围地区9个调查区17种主要食品中~(90)Sr、~(137)Cs含量分别为1.1～72.3,0.3～40.7×10~(-2)B_q·Kg~(-1);3个对照区分别为1.6～68.4,0.6～27.4×10~(-2)B_q·K_g~(-1)。两地区同类食品中~(90)Sr、~(137)Cs平均含量基本一致。调查区~(90)Sr、~(137)Cs所致成年居民有效剂量当量值分别为2μSV(集体剂量当量为30.0人· SV);0.3μSV(4.5人· SV)。对照区分别为2.2μSV(集体剂量当量为20.9人·SV);0.4μSV(3.0人·SV)。可见我国核试验产生的~(90)Sr、~(137)Cs对核试验场周围地区食品没有造成明显的局部污染,所致居民剂量当量负担仅为我国天然外照射所致年有效剂量当量(952μSV)的0.2％和0.03％。对该地区的广大居民健康不会产生有害的影响。     

一种考虑子体影响的放射性剂量评价方法及其应用

给出了一种考虑子体影响的放射性剂量评价方法,并用此法对铀尾矿中234U通过地下水迁移对人体所致剂量进行了估算.结果表明,子体230Th对整个剂量的贡献值远远大于母体234U.因此,在剂量评价中,需要考虑子体的影响,尤其是计算结果和剂量限值比较接近时,考虑子体的影响尤为必要,只有这样才能保证安全需要.     

青岛市区土壤天然放射性核素的外照射水平估算研究

城市的辐射环境质量对于人居和发展规划有重要意义。利用伽玛能谱仪对青岛市区内的天然放射性核素进行了大规模高密度的现场测量,采用Beck公式计算了离地面1m高处的空气吸收剂量率,进而计算了外照射年有效剂量、外照射指数和等效镭浓度,对研究区的外照射水平进行了系统的评价。与和其他国家全国比较,虽然该区的空气吸收剂量率较高,但是其他衡量天然放射性核素外照射水平的指标均在容许范围之内。因此该区属于外照射水平的安全区域,人居环境不受影响。     

Qualitative and quantitative assessment of the risk from the exposure to fetotoxic chemical compounds

A new mathematical dose-response model for the expected probability of toxic response and also for the expected measure of the overdispersion parameter for the reproductive and developmental risk assessment is proposed. The model for the expected probability of toxic response is an improvised Weibull dose-response model incorporating the litter-size effect while the model for the overdispersion parameter is a polynomial function of the dose level. A beta-binomial distribution for the number of offspring showing toxic responses in a litter satisfactorily accounts for the extra-binomial variation and the intralitter correlation of responses of these pups. Confidence limits for low-dose extrapolation are based on the asymptotic distribution of the likelihood ratio. The safe dose for human exposure is then calculated by simple linear extrapolation. The model for overdispersion allows us to obtain the estimates of the overdispersion parameter at these dosages. This was not possible in the earlier models. The proposed model is illustrated by an application to a study on the effect of exposure to diethylhexylphthalate in mice. The results are compared with those obtained by Chen and Kodell (1989) who have applied the simple Weibull dose-response model to the same data set.This paper was prepared with partial support from the United States Environmental Protection Agency under a Cooperative Agreement Number CR-815273. The contents have not been subject to Agency review and therefore do not necessarily reflect the views or policies of the Agency and no official endorsement should be inferred.     

Continuous dose-response modeling and risk analysis with the gamma and reciprocal gamma distributions

Kodell and West (1993) describe two methods for calculating pointwise upper confidence limits on the risk function with normally distributed responses and using a certain definition of adverse quantitative effect. But Banga et al. (2000) have shown that these normal theory methods break down when applied to skew data. We accordingly develop a risk analysis model and associated likelihood-based methodology when the response follows either a gamma or reciprocal gamma distribution. The model supposes that the shape (index) parameter k of the response distribution is held fixed while the logarithm of the scale parameter is a linear model in terms of the dose level. Existence and uniqueness of the maximum likelihood estimates is established. Asymptotic likelihood-based upper and lower confidence limits on the risk are solutions of the Lagrange equations associated with a constrained optimization problem. Starting values for an iterative solution are obtained by replacing the Lagrange equations by the lowest order terms in their asymptotic expansions. Three methods are then compared for calculating confidence limits on the risk: (i) the aforementioned starting values (LRAL method), (ii) full iterative solution of the Lagrange equations (LREL method), and (iii) bounds obtained using approximate normality of the maximum likelihood estimates with standard errors derived from the information matrix (MLE method). Simulation is used to assess coverage probabilities for the resulting upper confidence limits when the log of the scale parameter is quadratic in the dose level. Results indicate that coverage for the MLE method can be off by as much as 15% points and converges very slowly to nominal coverage levels as the sample size increases. Coverage for the LRAL and LREL methods, on the other hand, is close to nominal levels unless (a) the sample size is small, say N < 25, (b) the index parameter is small, say k 1, and (c) the direction of adversity is to the left for the gamma distribution or to the right for the reciprocal gamma distribution.     

Multiplicity-adjusted Inferences in Risk Assessment: Benchmark Analysis with Continuous Response Data

We develop and study multiplicity adjustments for low-dose inferences in environmental risk assessment. Application is intended for risk analysis studies where human, animal, or ecological data are used to set safe levels of a hazardous environmental agent. A modern method for making inferences in this setting is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the “benchmark dose” are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this note, we discuss approaches for doing so with continuous, nonquantal response data.