Probabilistic ecological risk assessment of cadmium in the Bohai Sea using native saltwater species

Predicted no-effect concentration （PNEC） is often used in ecological risk assessment to determine low-risk concentrations for chemicals. In the present study, the chronic data from native saltwater species were used to calculated PNEC values using four methods： log-normal distribution （ETX 2.0）, log-triangle distribution （US EPA＇s water quality criteria procedure）, burr III distribution （BurrliOZ） and traditional assessment fac-tor （AF）. The PNECs that were calculated using four methods ranged from 0.08 μg/L to 1.8 μg/L. Three of the SSD-derived PNECs range from 0.94 to 1.8 μg/L, about a factor of two apart. To demonstrate the use of SSD-based PNEC values and comprehensively estimate the regional ecological risk for cadmium in surface water of the Bohai Sea, in the Liaodong Bay, Bohai Bay, and Laizhou Bay, China, the dissolved cadmium con-centrations were measured and obtained 753 valid data covering 190 stations from July 2006 to November 2007. Based on three ecological risk assessment approaches, namely hazard quotient （HQ）, probabilistic risk quotient and joint probability curve （JPC）, the potential ecological risk of cadmium in surface water of the Liaodong Bay, Bohai Bay, and Laizahou Bay were estimated. Overall, the ecological risk of cadmium to aquatic ecosystem in the whole Bohai Sea was at acceptable ecological risk level, the order of ecological risk was Liaodong Bay〉Bohai Bay〉Laizhou Bay. However, more concerns should be paid to aquatic ecological risk in the Liaodong Bay which is the home of many steel, metallurgy and petrochemical industrial in China.

Pesticide residues in bayberry(Myrica rubra)and probabilistic risk assessment for consumers in Zhejiang,China

As pesticide residues in bayberry has raised serious concern from the public in China, a monitoring survey was carried out during 2013–2014 and 157 samples were analyzed in total. Twenty-three pesticides were detected among the 44 pesticides analyzed and at least one pesticide was detected in 63% of 99 samples. Whereas 45.6% of samples were found with two or more pesticide residues, and 23.6% of samples with four or more pesticide residues. Probabilistic risk assessments indicated that estimated daily intake（EDI） of cyhalothrin at the P97.5th percentile level is 1.11 times larger than the acceptable daily intake（ADI） for children, the estimated short-term intake（ESTI） at the P97.5th percentile level is 1.9 and 1.78 times larger than the acute reference dose（ARf D） for adult and children, respectively, indicating the potential risk concern from pyrethroids. EDI of the pesticides with anti-androgenic effects ranged from 0.15–2.46 of ADI, the probability of exposure exceeding the ADI was 7.1 and 31.1% for adults and children, respectively, the probability of exposure of pyrethroids exceeding the ADI was 3.8% for children. Exposures for other pesticides and groups were below 1.0. Because the co-occurrence of frequency of cyhalothrin and cypermethrin was 9.55%, the combinations of pesticides detected with anti-androgenic effects has not been found in the present monitoring, the results indicate that the pesticide residues in bayberry will not constitute serious public health risk, however, they are significant for the management of pesticide use on bayberry and dietary health risk in China.

Over-limit risk assessment method of integrated energy system considering source-load correlation

In an integrated energy system,source-load multiple uncertainties and correlations lead to an over-limit risk in operating state,including voltage,temperature,and pressure over-limit.Therefore,efficient probabilistic energy flow calculation methods and risk assessment theories applicable to integrated energy systems are crucial.This study proposed a probabilistic energy flow calculation method based on polynomial chaos expansion for an electric-heat-gas integrated energy system.The method accurately and efficiently calculated the over-limit probability of the system state variables,considering the coupling conditions of electricity,heat,and gas,as well as uncertainties and correlations in renewable energy unit outputs and multiple types of loads.To further evaluate and quantify the impact of uncertainty factors on the over-limit risk,a global sensitivity analysis method for the integrated energy system based on the analysis of covariance theory is proposed.This method considered the source-load correlation and aimed to identify the key uncertainty factors that influence stable operation.Simulation results demonstrated that the proposed method achieved accuracy to that of the Monte Carlo method while significantly reducing calculation time.It effectively quantified the over-limit risk under the presence of multiple source-load uncertainties.

Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.

A Fuzzy Probabilistic Influence Diagram Method to Assess Marine Configuration Risk

A risk assessment method for marine configuration based on Fuzzy Probability Influence Diagram （FPID） and Failure Mode and Effect Analysis （FMEA） is established in this paper. Considering the fuzzy characteristic of the two key inputs such as event happening probability and relation probability, the method induces fuzzy probability into the PID risk assessment for marine configuration, where defuzzification is performed using the centroid method to determine the risk at a given grade of a probabilistic item. FMEA as a traditional qualitative analysis method is used to determine the effect factor structure. An application of the presented method for the offshore jacket platform is implemented. The method can be widely applicable although only offshore platform is analyzed here.

Multi-mycotoxin exposure and risk assessments for Chinese consumption of nuts and dried fruits

In this study, 15 mycotoxins were detected in 233 nut and dried fruit samples from China. The 15 mycotoxins included aflatoxins （AFs： AFB1, AFB2, AFG1 and AFG2）, trichothecene toxins （TCs： T-2, ZEA, ENA, ENA1, ENB, ENB1 and BEA）, Alternaria toxins （ATs： TEN, AOH and AME） and ochratoxin A （OTA）. The mycotoxins were detected in 47.6% of the samples and all 15 of the mycotoxins were found. Two samples were positive for AFB1 and exceeded the maximum tolerable levels allowed in China. The contamination levels of the mycotoxins found in nuts, dried jujubes, raisins, dried figs and dried Iongans were in the ranges of 0.1-462.7, 0.2-247.3, 0.8-10.1,0.2-384.1 and 0.1-89.2 μg kg^-1, respectively. Dried figs （80.0%） had the highest incidence of mycotoxins, followed by dried Iongans （60.0%）, dried jujubes （57.1%）, nuts （43.6%） and raisins （26.7%）. The estimated daily intake （EDI） values of each individual mycotoxin and all of the mycotoxins collectively were calculated by both the deterministic approach （DA） and the probability approach （PA）. For risk characterization, dietary exposure to TCs, ATs and OTA through consumption of nuts and dried fruits according to both approaches, showed no health risk to Chinese adults by exposure to either individual mycotoxins or in combination. To the best of our knowledge, this is the first work in which risk assessment of multimycotoxins is performed, specifically including the emerging ENNs and BEA, in nuts and dried fruits of China.

Risk Assessment of Nitrogen Discharge from a Coastal Watershed

Probabilistic risk assessment （PRA） uses probability theory to quantify the probability of occurrence of an event. In this study, PRA was conducted for the discharge of excess nitrogen （N） from an agricultural （Jiulong River） watershed in Southeast China. Using fault tree analysis, a type of PRA, the probability of occurrence of excess N discharge into the river during a runoff event was evaluated both qualitatively and quantitatively. Land use maps, soil maps, fertilizer use records, and expert opinions were used to determine probabilities of individual events within the fault tree and to calculate the overall probability of excess N discharge during a runoff event. Qualitative analysis showed that the risk of excess N discharge was mainly related to crop and livestock practices in the watershed. Proper management of tillage, fertilizer, and manure was necessary to control N releases. Quantitative assessment results indicated that alternative practices including reduction of fertilization, installation of vegetative strip buffer around the pig farms, and installation of more riparian buffers along the Jiulong River could reduce the likelihood of N discharge through runoff.

Risk Assessment Framework and Algorithm of Power Systems Based on the Partitioned Multi-objective Risk Method

针对平均风险指标无法区分高损失-低概率事件及低损失-高概率事件的缺点,提出了电力系统的分割多目标风险分析框架。该框架将电力系统的风险状态细分为低损失、中等损失和高损失3个风险范围,并提出3个损失范围条件风险函数和条件风险概率的概念。采用经典的容量停运表模型,建立了这些条件期望指标的计算方法。对IEEE-RTS及TH-RTS2000系统进行了分割多目标风险评估,研究不同负荷水平下系统风险在3个损失范围的分布及转移情况,并分析损失分割点对系统风险的影响。通过分割多目标风险分析,风险分析者和决策者可以权衡系统的平均风险以及高、中、低损失范围的条件期望风险,从而对系统的风险状况有一个全面和深入的了解。

Recent Research Advances in the Risk Assessment Method of an Underground Pressure Pipeline

This paper reviews the risk assessment method of an underground pressure pipeline, introduces the risk assessment method of expert grading, fuzzy integrative assessment, probabilistic risk assessment and extenics assessment in an underground pressure pipeline. Moreover, it puts forward the developing orientation of risk assessment.

Risk Assessment,Management and Application in Nuclear Power Plant Operation

To introduce the basic concepts of technical specification of nuclear power plant,a risk assessment and management technique based on the probabilistic safety analysis( PSA) method was proposed. The risk-informed method was used,and an example was given to show how to use some specific risk metrics like CDF / LERF /ICDP / ILERP to analyze and manage the risk associated with activities in nuclear power plant operation. The advantage of this technique can be concluded from this paper,and this technique should be used more widely and deeply in nuclear industry.

Maritime Oil Spill Risk Assessment for Hanhikivi Nuclear Power Plant

Fennovoima is planning to build a new nuclear power plant unit-Hanhikivi 1, on a greenfield site in Northern Finland. A nearby maritime oil spill accident is one of the external events analysed in the probabilistic risk assessment of the plant. In the worst case, the oil could cause a loss of the ultimate heat sink by blocking the sea water intake screens. By considering the maritime traffic, oil transport and oil spill accident data in the Baltic Sea area, the annual probabilities of nearby, significant oil spills are evaluated. Event tree analysis is used to evaluate the probability that significant amount of oil enters the plant intake tunnel. The spill behaviour is considered, including oil spreading, dissolution, dispersion and movement due to wind and currents. In addition, oil combat measures including the use ofoil booms and skimmers are evaluated.

基于毕达哥拉斯模糊概率Petri网的FPSO单点关键部件风险评估

为准确对FPSO单点系泊系统关键部件进行风险评估,通过产生式规则建立概率Petri网络模型,基于德尔菲法的结构熵权法确定专家权重,并引入毕达哥拉斯模糊集理论收集、聚合专家意见得到基本事件的模糊可能性得分和模糊失效概率,利用概率推理算法迭代出最终的失效概率,并进行基本事件重要度分析。实例分析结果表明,引起单点系泊系统发生失效的主要因素有电滑环电刷磨损、电滑环负载电流较高、液滑环结构物晃动冲击、液滑环润滑不充分、电滑环电压过高击穿等。针对主要风险因素提出预防和控制措施,能够保障系统安全正常地运转。

PRA在焦化厂污染土壤健康风险评价中的应用

以北京市某炼焦化学厂场地污染调查为依据,采用PRA(概率风险评价)研究了15个人体暴露参数和土壤中污染物浓度不确定性对苯、苯并[a]芘健康风险评价结果的影响.结果表明:对于表层和深层土壤,苯、苯并[a]芘各暴露途径及总暴露途径PRA95%分位值均小于相应DRA(确定性风险评价)风险值;该场地整个土层中苯的PRA总风险值为1.5×10-8～6.9×10-3,苯并[a]芘为2.3×10-9～2.2×10-3,二者95%分位值分别为3.8×10-4和1.1×10-4;苯、苯并[a]芘的DRA总风险值分别为PRA96.8%和99.1%分位值,并且二者的DRA总风险值/PRA95%分位值分别为1.5和3.2,表明DRA风险值偏保守.参数敏感性分析表明,对苯总风险不确定性贡献较大的为深层土壤中的苯浓度(贡献率为94.63%,下同)和成人暴露周期(4.12%),苯并[a]芘为表层土壤中苯并[a]芘浓度(92.63%)、成人暴露周期(2.40%)、儿童每日土壤摄入量(2.12%)和儿童暴露周期(1.21%).

玻璃生产场地土壤中砷的污染特征及其概率风险评估

砷(As)主要通过采矿、冶炼和燃煤等工业过程进入环境,然而玻璃生产中使用大量含砷原料,却鲜见相关土壤污染的报道.为探究玻璃生产场地土壤中As污染及健康风险情况,采用统计分析、正定矩阵因子模型(PMF)、体外测试、蒙特卡洛模拟等方法,研究了曾进行50余年生产活动的某平板玻璃厂土壤中As的污染浓度、空间分布及来源,并进一步结合生物可给性和本土化暴露参数(体质量、室内暴露频率、室外暴露频率、每日空气呼吸量),计算了健康风险水平及风险控制值.结果表明:该平板玻璃厂493件土壤样品中As的超标率达21.5%,As最大浓度位于平拉车间,高达317 mg/kg,其中80.3%来自配合料泄露.土壤中As的生物可给性范围为10.24%~54.35%,土壤理化性质对生物可给性结果具有显著影响.As的致癌风险范围为2.23×10^(−7)~1.22×10^(−3),95%分位值为5.77×10^(−5),危害商范围为9.49×10^(−3)~56.08,95%分位值为2.62;相应地,基于致癌风险的As风险控制值为0.50~3.57 mg/kg,其5%分位值为0.75 mg/kg,略低于传统点评估方法(DRA)的风险控制值(1.13 mg/kg).参数敏感性分析结果表明,生物可给性对风险控制值计算结果的影响(−64.38%)最大,其次是体质量,成人与儿童的敏感性分别为10.96%及19.18%,其余参数的敏感性均小于10%.总之,玻璃生产场地土壤中As污染不可忽视,使用本土化的暴露参数,并且将生物可给性纳入现有健康风险方法有助于更加全面客观地评估其健康风险水平,可为环境管理提供决策依据.

基于PRA方法的风险分析系统设计

探讨了应用概率风险评估（ＰＲＡ）方法进行工程项目风险分析的可行性，在此基础之上研究给出了一个基于ＰＲＡ方法的风险分析系统。该系统可用于工程项目的风险分析建模和评估，具有一定的理论及工程实用价值。

基于PRA方法风险评价系统的设计与研究

针对动态系统安全性分析的需要,设计并实现了一个新的风险评价系统。该系统在PRA方法的基础上,在风险评估过程中综合运用多种动态系统的安全性建模和危险分析技术,能够较好地适应动态系统风险评估的需求。

基于PRA的网络安全风险评估模型

概率风险分析被广泛应用于社会各领域,如交通、能源、化工处理、航天、军事等。文章采用概率风险分析的方法,对网络的逻辑构成、网络攻击和攻击结果进行分析,通过故障树描述了网络系统被攻击的原因与途径,并建立了风险评估模型。

基于概率神经网络和层次分析法的硐室群施工风险评估

地下硐室群施工风险研究尚处于起步阶段,为快速准确评判风险因素,预防施工安全事故,利用概率神经网络(PNN)和层次分析法(AHP)建立风险评估模型,并研发硐室群施工风险评估软件。通过统计分析硐室群施工风险因素,设置工程地质、自然、设计施工和管理4个一级风险因素,23个风险控制指标,建立针对硐室群施工的风险指标体系。收集典型样本数据后,基于PNN对施工风险等级进行评判,同时采用AHP定量分析风险因素权重,迅速捕捉风险点,采取风险控制措施并优化施工方案。运用研发软件对重庆轨道交通18号线歇台子站硐室群施工进行风险评价,得到风险概率等级为Ⅳ,在施工过程中需要重点监测和控制地下水、围岩等级和支护及时性等带来的影响,实例评价结果与现场情况相吻合,验证了该评估软件的有效性和实用性。研究表明:针对硐室群施工建立的指标体系和评估方法能有效预测风险级别,实时指导施工过程,确保地下硐室群施工安全。

考虑新能源随机波动和T接线的城市电网连锁故障风险评估

新能源的大量接入给城市电网的安全运行和重要用户可靠供电带来很大挑战,其功率的随机波动易引发电网出现连锁故障风险。提出了一种考虑新能源出力随机波动和城市电网110k V网架T接线开关投切的连锁故障风险评估方法。该方法在连锁故障发生概率和后果严重度的计算中都计及了系统状态的概率分布特性的影响,并采用基于半不变量法的概率潮流计算反映系统状态与新能源功率二者的概率分布特性之间的关系。另外,建立包含110 kV网架T接线开关投切的最小切负荷的混合整数非线性规划模型,并以最小切负荷量来表征系统在连锁故障的严重度。此优化模型通过决策故障下的各组T接线开关的投切状态,减少连锁故障下的切负荷量,进而有效降低连锁故障的风险。同时,通过机会约束描述重要用户负荷节点电压的安全运行范围,以确保重要用户负荷不停电的概率满足给定的置信水平,从而保证重要用户的安全可靠供电。最后,通过某个实际城市片区电网算例验证了所提出的连锁故障风险评估方法的正确有效性。

基于PRA的交会对接任务可靠性评估

为有效评估交会对接任务过程的可靠性指标,提出了基于概率风险评价(PRA)的交会对接任务可靠性评估方法,该方法是通过事件树描述各事件或功能的可靠性与任务可靠性之间的关系,同时通过概率风险模型描述事件或功能的可靠性与设备可靠性之间的关系。根据我国航天领域可靠性工作现状,提出了交会对接过程可靠性评估的工程流程。