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1.
城市活动断层探测和断层活动性评价问题   总被引:5,自引:5,他引:3       下载免费PDF全文
根据近年来城市活动断层探测与地震危险性评价的实际工作,归纳了探测工作中在地质地貌、地球化学和地球物理探测中存在的问题,针对性提出了相应的建议,以进一步推进这一工作  相似文献
2.
南四湖表层底泥重金属污染及其风险性评价   总被引:5,自引:5,他引:32  
通过对南四湖表层底泥中的重金属元素浓度分析,揭示出南四湖不同湖区重金属污染物空间分布特征.利用潜在生态风险指数(RI)和地质积累指数(Igeo)两种指标相结合的方法对表层底泥中重金属污染程度进行评价.结果表明,南四湖上级湖的重金属污染主要以汞为主,并依据潜在生态风险指数将南四湖上级湖分为三个生态风险功能区: 昭阳湖轻污染区;独山湖中等污染区和南阳湖重污染区.  相似文献
3.
乌梁素海水体汞的分布特征及污染风险评估   总被引:4,自引:2,他引:2       下载免费PDF全文
于2011年1月采集乌梁素海表层水样,对湖水中重金属Hg含量进行分析.结合Hg的空间分布特征,利用单因子指数综合污染评价指数与健康风险评价模型对Hg污染程度与风险进行评估.结果表明,乌梁素海表层水体中Hg的平均浓度为1.04μg/L,所有监测点Hg的含量都超出地表水Ⅲ类标准和国家渔业用水标准,50%的监测点超出了地表水Ⅳ类标准.水体中Hg的分布模式与流域排污口位置、入湖口及水动力条件有一定关系,高值区域分布在入湖口相对集中的西北与东北部,湖泊南部与出口处的含量相对较低,处于中等水平.乌梁素海湖水中Hg的非致癌性污染物所致的健康危害风险度介于0.75×10-9~2.15×10-9a-1之间,Hg所致的健康危害风险度的贡献率在71.43%~92.44%之间,表明Hg污染水平与健康风险都较高,应该给予特别关注.  相似文献
4.
为了解巢湖湖区及主要出入湖河流沉积物中重金属的污染特征,对表层沉积物中重金属元素含量进行分析,基于地积累指数法、潜在生态风险指数法和沉积物质量基准法对沉积物污染风险进行评价,并对沉积物重金属来源进行初步分析.结果表明,河流沉积物中重金属的平均含量显著高于湖区,是湖区沉积物重金属含量的1.18~5.15倍,其中南淝河Cu、Zn、Pb、As和Hg含量较高,分别是背景值的3.53、16.98、3.98、5.84和23.11倍,西半湖Cu、Zn、Pb、Cd和Hg平均含量要高于东半湖,是全湖平均的1.04~1.45倍.地积累指数法和Håkanson潜在生态风险指数法评价结果均表明,Cd和Hg是主要的生态风险贡献因子,在所调查的表层沉积物中Cd和Hg数值分别为43.17~3870.94和29.96~924.57,已处于较大风险数值.此外,源分析结果表明,巢湖湖区及主要出入湖河流表层沉积物中Cu、Zn、Pb、Cr、Hg和As相关性显著,具有相似的来源,可能来自于工业废水与生活污水.  相似文献
5.
2D Monte Carlo versus 2D Fuzzy Monte Carlo health risk assessment   总被引:3,自引:3,他引:10  
Risk estimates can be calculated using crisp estimates of the exposure variables (i.e., contaminant concentration, contact rate, exposure frequency and duration, body weight, and averaging time). However, aggregate and cumulative exposure studies require a better understanding of exposure variables and uncertainty and variability associated with them. Probabilistic risk assessment (PRA) studies use probability distributions for one or more variables of the risk equation in order to quantitatively characterize variability and uncertainty. Two-dimensional Monte Carlo Analysis (2D MCA) is one of the advanced modeling approaches that may be used to conduct PRA studies. In this analysis the variables of the risk equation along with the parameters of these variables (for example mean and standard deviation for a normal distribution) are described in terms of probability density functions (PDFs). A variable described in this way is called a second order random variable. Significant data or considerable insight to uncertainty associated with these variables is necessary to develop the appropriate PDFs for these random parameters. Typically, available data and accuracy and reliability of such data are not sufficient for conducting a reliable 2D MCA. Thus, other theories and computational methods that propagate uncertainty and variability in exposure and health risk assessment are needed. One such theory is possibility analysis based on fuzzy set theory, which allows the utilization of incomplete information (incomplete information includes vague and imprecise information that is not sufficient to generate probability distributions for the parameters of the random variables of the risk equation) together with expert judgment. In this paper, as an alternative to 2D MCA, we are proposing a 2D Fuzzy Monte Carlo Analysis (2D FMCA) to overcome this difficulty. In this approach, instead of describing the parameters of PDFs used in defining the variables of the risk equation as random variables, we describe them as fuzzy numbers. This approach introduces new concepts and risk characterization methods. In this paper we provide a comparison of these two approaches relative to their computational requirements, data requirements and availability. For a hypothetical case, we also provide a comperative interpretation of the results generated.  相似文献
6.
There is an urgent need for the development and implementation of modern statistical methodology for long-term risk assessment of extreme hydrological hazards in the Caribbean. Notwithstanding the inevitable scarcity of data relating to extreme events, recent results and approaches call into question standard methods of estimation of the risks of environmental catastrophes that are currently adopted. Estimation of extreme hazards is often based on the Gumbel model and on crude methods for estimating predictive probabilities. In both cases the result is often a remarkable underestimation of the predicted probabilities for disasters of large magnitude. Simplifications do not stop here: assumptions of data homogeneity and temporal independence are usually made regardless of potential inconsistencies with genuine process behaviour and the fact that results may be sensitive to such mis-specifications. These issues are of particular relevance for the Caribbean, given its exposure to diverse meteorological climate conditions.In this article we present an examination of predictive methodologies for the assessment of long-term risks of hydrological hazards, with particular focus on applications to rainfall and flooding, motivated by three data sets from the Caribbean region. Consideration is given to classical and Bayesian methods of inference for annual maxima and daily peaks-over-threshold models. We also examine situations where data non-homogeneity is compromised by an unknown seasonal structure, and the situation in which the process under examination has a physical upper limit. We highlight the fact that standard Gumbel analyses routinely assign near-zero probability to subsequently observed disasters, and that for San Juan, Puerto Rico, standard 100-year predicted rainfall estimates may be routinely underestimated by a factor of two.  相似文献
7.
High concentrations of air pollutants in the ambient environment can result in breathing problems with human communities. Effective assessment of health-impact risk from air pollution is important for supporting decisions of the related detection, prevention, and correction efforts. However, the quality of information available for environmental/health risk assessment is often not satisfactory enough to be presented as deterministic numbers. Stochastic method is one of the methods for tackling those uncertainties, by which uncertain information can be presented as probability distributions. However, if the uncertainties can not be presented as probabilities, they can then be handled through fuzzy membership functions. In this study, an integrated fuzzy-stochastic modeling (IFSM) approach is developed for assessing air pollution impacts towards asthma susceptibility. This development is based on Monte Carlo simulation for the fate of SO2 in the ambient environment, examination of SO2 concentrations based on the simulation results, quantification of evaluation criteria using fuzzy membership functions, and risk assessment based on the combined fuzzy-stochastic information. The IFSM entails (a) simulation for the fate of pollutants in ambient environment, with the consideration of source/medium uncertainties, (b) formulation of fuzzy air quality management criteria under uncertain human-exposure pathways, exposure dynamics, and SPG-response variations, and (c) integrated risk assessment under complexities of the combined fuzzy/stochastic inputs of contamination level and health effect (i.e., asthma susceptibility). The developed IFSM is applied to a study of regional air quality management. Reasonable results have been generated, which are useful for evaluating health risks from air pollution. They also provide support for regional environmental management and urban planning.  相似文献
8.
Integration degree of risk in terms of scene and application   总被引:2,自引:2,他引:0  
Risk is a scene in the future associated with some adverse incident. Scene means something seen by a viewer, or felt by individuals or various societal groups. Any risk assessment is to model some aspects of the scene for risk. Different aspects for assessment leads to different scene. In this paper, we suggest the integration degree of risk to distinguish characters of risks with respect to the aspects. The total number of factors of a risk system determines the macro degree and the granulation scale for measuring a risk reflects the micro degree. A simple framework depends on the degrees provides an explanation of the integrated risk. The most common model for risk assessment is available for the two-freedom-degree serial risk. A case studying flood risk shows the application to explain what the risk is, where the information is incomplete and we use the information diffusion technique to estimate the risk. Project 40771007 supported by National Natural Science Foundation of China.  相似文献
9.
 There exist many sites with contaminated groundwater because of inappropriate handling or disposal of hazardous materials or wastes. Health risk assessment is an important tool to evaluate the potential environmental and health impacts of these contaminated sites. It is also becoming an important basis for determining whether risk reduction is needed and what actions should be initiated. However, in research related to groundwater risk assessment and management, consideration of multimedia risk assessment and the separation of the uncertainty due to lack of knowledge and the variability due to natural heterogeneity are rare. This study presents a multimedia risk assessment framework with the integration of multimedia transfer and multi-pathway exposure of groundwater contaminants, and investigates whether multimedia risk assessment and the separation of uncertainty and variability can provide a better basis for risk management decisions. The results of the case study show that a decision based on multimedia risk assessment may differ from one based on risk resulting from groundwater only. In particular, the transfer from groundwater to air imposes a health threat to some degree. By using a methodology that combines Monte Carlo simulation, a rank correlation coefficient, and an explicit decision criterion to identify information important to the decision, the results obtained when uncertainty and variability are separate differ from the ones without such separation. In particular, when higher percentiles of uncertainty and variability distributions are considered, the method separating uncertainty and variability identifies TCE concentration as the single most important input parameter, while the method that does not distinguish the two identifies four input parameters as the important information that would influence a decision on risk reduction.  相似文献
10.
Concentrations of persistent organic pollutants including polychlorinated biphenyls (PCBs), organochlorine (OC) pesticides and dioxin-like compounds were measured in green-lipped mussels, Perna viridis, collected from seven mariculture zones in Hong Kong between September and October in 2002 in order to evaluate the status, spatial distribution and potential sources of pollution in these areas. Concentrations ranged from 300 to 4400 ng/g lipid weight for total OCs and 170–1000 ng/g lipid weight for total PCBs (based on 28 congeners). Relatively smaller DDT concentrations in mussels compared with previous studies suggest reduced discharges of DDTs from nearby regions into Hong Kong waters. Detection of a mixture of HCH isomers in the mussels indicated that Hong Kong waters were predominantly contaminated by technical HCHs rather than lindane. Mussel samples from all sampling locations elicited significant dioxin-like activity in the H4IIE-luc bioassay. The greatest magnitude of dioxin-like response (39 pg TEQ/g wet wt.) was detected in mussels from Ma Wan in the western waters of Hong Kong, which is strongly influenced by the Pearl River discharge. Human health risk assessment was undertaken to evaluate potential risks associated with the consumption of the green-lipped mussels. Risk quotient (RQ) for dioxin-like compounds was greater than unity suggesting that adverse health effects may be associated with high mussel consumption.  相似文献
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