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.     

爆炸超压场景下危化品社会风险对允许规划人口密度的影响分析*

为研究危化品重大危险源基于社会风险基准的规划管控影响,采用我国标准规定的定量风险评价方法,TNT当量炸药简化方法,针对最大TNT当量炸药、事故发生总累计频率、人口密度分布控制参数等不同工况条件,对比分析国土开发强度的允许人口密度受社会风险约束影响的变化规律。研究结果表明:人口密度指数分布控制参数Nk与Nb的允许取值随最大TNT当量炸药和事故发生总累计频率降低而提高;确定工况下,允许总人口规模受最大TNT当量炸药影响很小;在最大TNT当量炸药大于100 t或事故发生总累计频率小于1×10-8次/a时可按最大事故场景进行规划控制分析。     

Integrating long-term stewardship goals into the remediation process: natural resource damages and the Department of Energy

The United States and other developed countries are faced with restoring and managing degraded ecosystems. Evaluations of the degradation of ecological resources can be used for determining ecological risk, making remediation or restoration decisions, aiding stakeholders with future land use decisions, and assessing natural resource damages. Department of Energy (DOE) lands provide a useful case study for examining degradation of ecological resources in light of past or present land uses and natural resource damage assessment (NRDA). We suggest that past site history should be incorporated into the cleanup and restoration phase to reduce the ultimate NRDA costs, and hasten resource recovery. The lands that DOE purchased over 50 years ago ranged from relatively undisturbed to heavily impacted farmland, and the impact that occurred from DOE occupation varies from regeneration of natural ecosystems (benefits) to increased exposure to several stressors (negative effects). During the time of the DOE releases, other changes occurred on the lands, including recovery from the disturbance effects of farming, grazing, and residential occupation, and the cessation of human disturbance. Thus, the injury to natural resources that occurred as a result of chemical and radiological releases occurred on top of recovery of already degraded systems. Both spatial (size and dispersion of patch types) and temporal (past/present/future land use and ecological condition) components are critical aspects of resource evaluation, restoration, and NRDA. For many DOE sites, integrating natural resource restoration with remediation to reduce or eliminate the need for NRDA could be a win-win situation for both responsible parties and natural resource trustees by eliminating costly NRDAs by both sides, and by restoring natural resources to a level that satisfies the trustees, while being cost-effective for the responsible parties. It requires integration of remediation, restoration, and end-state planning to a greater degree than is currently done at most DOE sites.     

A framework for assessing the impact of land use policy on community exposure to air toxics

Our research focuses on the linkage between land use planning policy and the spatial pattern of exposure to air toxics emissions. Our objective is to develop a modeling framework for assessment of the community health risk implications of land use policy. The modeling framework is not intended to be a regulatory tool for small-scale land use decisions, but a long-range planning tool to assess the community health risk implications of alternative land use scenarios at a regional or subregional scale. This paper describes the development and application of an air toxic source model for generating aggregate emission factors for industrial and commercial zoning districts as a function of permitted uses. To address the uncertainty of estimating air toxics emission rates for planned general land use or zoning districts, the source model uses an emissions probability mass function that weights each incremental permitted land use activity by the likelihood of occurrence. We thus reduce the uncertainty involved in planning for development with no prior knowledge of the specific industries that may locate within the land use district. These air toxics emission factors can then be used to estimate pollutant atmospheric mass flux from land use zoning districts, which can then be input to air dispersion and human health risk assessment models to simulate the spatial pattern of air toxics exposure risk. The model database was constructed using the California Air Toxics Inventory, 1997 US Economic Census, and land assessment records from several California counties. The database contains information on more than 200 air toxics at the 2-digit Standard Industrial Classification (SIC) level. We present a case study to illustrate application of the model. LUAIRTOX, the interactive spreadsheet model that applies our methodology to the California data, is available at http://www2.bren.ucsb.edu/~mwillis/LUAIRTOX.htm.