太原市土壤重金属污染空间分布及评价

以太原市土壤作为研究对象,系统研究了太原市城市土壤及工业区土壤中Cr、Ni、Cu、Zn、As、Cd、Pb的污染水平和分布,并对污染状况进行了评价.研究表明,太原市土壤中重金属的含量分别为Cr:35.35—848.80mg·kg-1,Ni:4.00—99.57 mg·kg-1,Cu:4.89—266.99 mg·kg-1,Zn:45.16—677.01 mg·kg-1,As:0.66—35.46 mg·kg-1,Cd:nd—1.00 mg·kg-1,Pb:15.61—1240.41 mg·kg-1.其中城市土壤重金属含量较低,工业区土壤重金属含量较高,受到多种重金属的复合污染.以土壤环境质量国家二级标准值作为评价标准,用单项污染指数和综合污染指数对太原市土壤重金属污染进行评价,结果显示太原市大部分城市土壤未受7种重金属污染,只有6.7%的地区处于轻污染水平;工业区土壤污染严重,污染程度从高至低为化工厂(重污染)热电厂(重污染)化肥厂(重污染)第一电厂(中度污染)建筑工地(中度污染)焦化厂(轻污染).7种重金属在太原市土壤中的空间分布规律不同,且均与工业区分布相关,工业区是太原城市土壤重金属污染的重要来源.     

食物链途径人体健康风险评估的关键内容探讨

食物是人类生存的重要保障,食品安全事关人类生命健康.食品污染始于农田耕地,还包括生产制造、包装、贮存、运输、加工等环节,每个步骤处理不当都可能发生食品安全问题.农田为食物来源的基石,是空气、水体中污染物的汇,随着城市的扩张,人类经济活动导致农田污染加剧.人类从食物中摄取污染物与经口、呼吸、皮肤的途径一样,是人体健康风险评估不可缺少的考量因素之一.我国对食品安全非常重视,2010年1月原卫生部根据《食品安全法》建立《食品安全风险监测管理规定》和《食品安全风险评估管理规定》(试行),这两份文件涵盖了从土壤到餐桌一系列的风险过程.但由于每个过程产生的原因、污染物影响机制均不同,规定离具体实际应用目标还很远.2014年环保部以保护生态环境,保障人体健康为根本,为加强污染场地环境保护监督管理,规范污染场地人体健康风险评估,发布了《污染场地风险评估技术导则》,该文建立了土壤污染造成人体健康风险评价的操作方法.然而导则考虑了经口、皮肤、呼吸及饮用地下水等9种暴露途径和评估模型,唯独缺少经食物链暴露这一重要途径的相关内容.本文以英、美两国食物链途径的场地污染风险评估为依据开展了详细探讨,深入分析了评估程序中关于土地利用方式的分类、目标人群暴露特征、污染物在食物链中传输路径、模型选取及暴露参数等内容,以期为我国制定《食物链暴露途径风险评估导则》提供一定的参考依据和指导方法.     

进出口工业化学品风险管理与风险评估进展

我国是世界化学品生产和贸易的大国。大量化学品的生产和进出口贸易给我国化学品风险管理和风险评估带来了巨大挑战。在借鉴发达国家和经济组织对化学品风险管理经验和评估技术的基础上,我国在近年来也逐步开展了化学品的管理和控制,以应对当前日益突出的化学品环境安全和健康安全事故。本文从我国化学品管理与国外化学品风险管理之间的对比出发,在梳理化学品管理政策发展的过程中,重点就我国环境保护部门对有毒和进口化学品、新化学物质和废弃危险化学品以及质检部门对进出口工业化学品的管理和控制措施,以及化学品的评估技术进行了综述。通过与发达国家就化学品风险管理与评估技术的对比,指出我国目前化学品管理和评估的不足与欠缺,并提出一些可行的应对措施与办法,为完善我国化学品风险管理和评估提供一定的参考。     

利用N-乙酰-β-D-氨基葡萄糖苷酶含量评价农药对花翅摇蚊种群发育的影响

为了进一步探索种群水平的生态风险评估方法,本文利用β-N-Acetyl-D-glucosaminidase(NAGase)的变化量来监测农药对摇蚊种群发育的影响。从花翅摇蚊Chironomus kiiensis体内分离纯化得到电泳纯的NAGase,并通过免疫大白兔制得NAGase的多克隆抗体。运用间接非竞争ELISA法检测抗体特异性,结果表明其与共同存在于水体的一些生物的NAGase的交叉反应率为隆线溞4.41%、老年低额溞3.12%、多刺裸腹溞3.40%、中华薄壳介4.17%、日本沼虾3.23%、白纹伊蚊7.50%、小球藻0.5%。运用抗体测得毒死蜱、氰戊菊酯和阿维菌素3种杀虫剂对于摇蚊NAGase释放量的12 d-EC50分别为1.2012、0.0043和0.6281μg·L-1,以NAGase活力作为测试终点,测得相应的12 d-EC50:1.4765、0.0051和0.6756μg·L-1,两者差异不显著,但均显著低于以死亡作为测试终点的12 d-LC50:4.8171、0.0954和2.1340μg·L-1,且毒力大小均为氰戊菊酯阿维菌素毒死蜱。上述结果表明,利用NAGase多克隆抗体可以特异性地检测农药对花翅摇蚊种群发育的影响。     

A new pre-assessment model for failure-probability-based-planning by neural network

At present, the prediction of failure probability is based on the operation period for laid pipelines, and the method is complicated and time-consuming. If the failure probability can be predicted in the planning stage, the risk assessment system of gas pipeline will be greatly improved. In this paper, the pre-laying assessment model is established to minimize risk of leakage due to piping layout. Firstly, Fault Tree Analysis (FTA) modeling is carried out for urban natural gas pipeline network. According to expert evaluation, 84 failure factors, which can be determined in the planning stage, are selected as the input variables of the training network. Then the FTA model is used to calculate the theoretical failure probability value, and the failure probability prediction model is determined through repeated trial calculation based on BP (Back Propagation Neural Network) and RBF (Radial Basis Function), for obtaining the optimal network parameter combination. Finally, two prediction models are used to calculate the same example. By comparing our pre-assessment model with the theoretical prediction consequences of the fault tree, the results show that the error of RBF prediction model can be close to 3%, which proves the validity and correctness of the method.     

Dynamic-risk-informed safety barrier management: An application to cost-effective barrier optimization based on data from multiple sources

An integrated approach for performance assessment and management of safety barriers in a systemic manner is needed concerning the prevention and mitigation of major accidents in chemical process industries. Particularly, the effects of safety barriers on system risk reduction should be assessed in a dynamic manner to support the decision-making on safety barrier establishments and improvements. A simulation approach, named Simulink-based Safety Barrier Modeling (SSBM), is proposed in this paper to conduct dynamic risk assessment of chemical facilities with the consideration of the degradation of safety barriers. The main functional features of the SSBM include i) the basic model structures of SSBM can be determined based on bow-tie diagrams, ii) multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) may be combined to update barrier failure probabilities and initiating event probabilities, iii) SSBM is able to handle uncertainty propagation in probabilistic risk assessment by using Monte Carlo simulations, and iv) cost-effectiveness analysis (CEA) and optimization algorithms are integrated to support the decision-making on safety barrier establishments and improvements. An illustrative case study is demonstrated to show the procedures of applying the SSBM on dynamic risk-informed safety barrier management and validate the feasibility of implementing the SSBM for cost-effective safety barrier optimization.     

Risk assessment of safety level in university laboratories using questionnaire and Bayesian network

Accidents in university laboratories not only create a great threat to students’ safety but bring significant negative social impact. This paper investigates the university laboratory safety in China using questionnaire and Bayesian network (BN) analysis. Sixteen influencing factors for building the Bayesian net were firstly identified. A questionnaire was distributed to graduate students at 60 universities in China to acquire the probability of safe/unsafe conditions for sixteen influencing factors, based on which the conditional probability of four key factors (human, equipment and material, environment, and management) was calculated using the fuzzy triangular theory and expert judgment. The determined conditional probability was used to develop a Bayesian network model for the risk analysis of university laboratory safety and identification of the main reasons behind the accidents. Questionnaire results showed that management problems are prominent due to insufficient safety education training and weak management level of management personnel. The calculated unsafe state probability was found to be 65.2%. In the BN analysis, the human factor was found to play the most important role, followed by equipment and material factor. Sensitive and inferential analysis showed that the most sensitive factors are personnel incorrect operation, illegal operation, and experiment equipment failure. Based on the analysis, countermeasures were proposed to improve the safe management and operation of university laboratories.     

Methodology for Natech coupling risk assessment using correlative multi-criteria decision-making method

When a natural disaster occurs, it may damage multiple industrial facilities in a certain area at the same time, and the resulting Natech events may have an impact on the surrounding industrial facilities, generating coupling risk. In this study, the assessment of Natech events coupling risk is conducted using the method of correlated multi-criteria decision-making, and the knowledge of fuzzy measures is introduced to solve the uncertainty problem in Natech coupling risk. Natech Coupling Risk Index is constructed to involve physical and functional facilities. The concept of equivalent population is proposed to compare the risks generated by physical facilities and functional facilities. And economic indicators are added to calculate the comprehensive risk value. The purpose of this contribution is to enable local government managers to use their expertise and resources and the existing risk assessment of the plants themselves and rely on the scoring of experts limitedly to quickly and easily identify potential high Natech risk areas. In the calculation process of coupling risk, the government can also take the lead to promote information communication between different plants and other industrial subjects. The proposed method was applied in a realistic chemical industry area in Guangzhou, China and in a hypothetical town. The result shows that the physical risk may be transferred to the population and economy through the coupling between industrial facilities and the functional link between functional facilities and population and economy.     

Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.     

Simulation of scenario characteristics of LPG tank explosion accident and its contribution to emergency planning: A case study

Leakage and explosion of hazardous chemicals during road transportation can cause serious building damage and casualties, and adoption of highly-efficient emergency rescue measures plays a critical role in reducing accidental hazards. Considering a liquefied petroleum gas (LPG) transport tanker explosion accident that occurred in Wenling, Zhejiang Province, China on June 13, 2020 as example, this study proposes a risk assessment framework. This framework recreates the leakage and explosion of the accident process using FLACS v10.9, suggests plans for evacuation, describes the rescue areas of different levels, and explores the influence of environmental factors on the evacuation and rescue areas. The results show that simulated and predicted distributions of fuel vapour cloud concentration and explosion overpressure can provide a reference basis for rapid rescue activities; the characterization of the dynamic effects of wind speed, wind direction, and temperature with respect to the evacuation and rescue areas can be used as theoretical support for on-site adjustment of rescue forces. The role of obstacles can prevent the expansion of the evacuation areas under low wind-speed conditions, and the presence of highly congested obstacles determines the level of the rescue area. The results obtained are important for the risk analysis and the development of emergency rescue measures in case of explosion accidents associated with transportation of hazardous chemicals on high-hazard and high-sensitive road sections.