Explosion at an aluminum factory caused by the July 2018 Japan floods: Investigation of damages and evacuation activities

An explosion at an aluminum factory occurred due to floods in Soja City, Okayama Prefecture, in July 2018. This study investigates the accident, its overall impact on local residents, and emergency management activities. The results of the study showed that several nearby structures and homes were damaged by the explosion. Concern for more explosions has led to the evacuation of residents of Shimobara area of Soja City. In Shimobara, residents had carried out voluntary disaster prevention activities before the disaster. After the explosion, Shimobara residents were able to evacuate safely in cooperation with the voluntary disaster prevention organization and the local government agency. The study revealed that there was a lack of information on chemical accident hazards shared by the factory with local government authorities and first responders, as well as with local residents. In order to be better prepared for technological accidents, and in particular accidents caused by natural disasters (known as Natechs), mechanisms for information sharing between companies and municipalities should be adopted.     

A fuzzy expert system for soil characterization

As soil is a natural resource not always renewable, the risk characterization of contaminated soils is an issue of great interest. Artificial Intelligence (AI), based on Decision Support Systems (DSSs), has been developed for a wide range of applications in contaminated soil management. Decision trees have already shown to be easy to interpret and able to treat large scale applications. Fuzzy logic gives an improvement in the perturbations and the variance of the training data, due to the elasticity of fuzzy set formalism. In this study, we have developed a classificatory tool applied to characterize contaminated soil in function of human and environmental risks. Knowledge engineering for constructing the Soil Risk Characterization Decision Support System (SRC-DSS) involves three stages: knowledge acquisition, conceptual design and system implementation. A total of 26 parameters were divided into three groups to facilitate the configuration of the expert system: source attributes, transfer vector attributes, and local properties. Sixteen case studies were evaluated with the SRC-DSS. In comparison with other techniques, the results of the current study have shown that SRC-DDS is an excellent tool to classify and characterize soils according to the associated risk.     

3S与在线监测技术在环境模型研究中的应用

结合环境信息系统的研究现状和研究实例，首先分析了3S和在线监测技术与环境模型研究结合的必要性，并分析指出了3S、在线监测技术在环境模型研究中潜在的应用范围，然后剖析了3S技术与环境模型研究结合的三阶水平，最后介绍了3S在环境规划模型研究中的理想结合框架。     

Ecological Modelling by ‘Ecological Modelling'

On the basis of a statistical analysis of the papers published in Ecological Modelling from 1975 to 1996, it has been attempted to examine the development of the field of ecological modelling and systems ecology. It was found that while models of aquatic ecosystems and management issues were more in focus in the 1970s, terresterial ecosystems and ecological theory have gained attention during the 1990s. Interest in ecotoxicological models seems to have increased only slightly during the entire period. It is interesting that financial support for the area of ecological modelling and systems ecology is closely related to the number of publications, which can be seen from the number of papers published by various countries in the journal. Hopefully, this clear message can be used to show to politicians that these relationships are real.     

Assessing Conservation Management's Evidence Base: a Survey of Management-Plan Compilers in the United Kingdom and Australia

Abstract:  Conservation management is becoming increasingly resource intensive as threats to biodiversity grow through habitat destruction, habitat disturbance, and overexploitation. To achieve successful conservation and sustainable use of natural resources, we need to scientifically evaluate the effectiveness of conservation interventions and provide an efficient framework through which scientific evidence can be used to support decision making in policy and practice. We conducted the first formal assessment of the extent to which scientific evidence is used in conservation management through a questionnaire survey and follow-up interviews of compilers of protected-area management plans from major conservation organizations within the United Kingdom and Australia. Our survey results show that scientific information is not being used systematically to support decision making largely because it is not easily accessible to decision makers. This, in combination with limited monitoring and evaluation of effectiveness of management interventions, results in the majority of decisions being based on experience rather than on evidence. To address this problem we propose using an evidence-based framework adapted from that used in the health services and explain how we are currently putting an equivalent framework into practice by establishing review and dissemination units to serve the conservation sector.     

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology.     

A Knowledge-Based Approach to the Assessment of Watershed Condition

The Ecosystem Management Decision Support (EMDS) system is an application framework for knowledge-based decision support of ecological assessments. EMDS integrates geographic information system and knowledge base system technologies to provide an analytical tool for environmental assessment and monitoring. The basic objective of EMDS is to improve the quality and completeness of environmental assessments and the efficiency with which they are performed. The USDA Forest Service and the U.S. Environmental Protection Agency have cooperatively developed an EMDS knowledge base for watershed condition assessment. Specifically, this knowledge base evaluates watershed processes, patterns, general effects of human activity, and fisheries habitat suitability. Such assessments are based on spatially explicit input data concerning current conditions and reference conditions which are subsequently interpreted by user-defined "fuzzy" membership functions. In this paper we describe basic components of our knowledge base for assessing watershed condition and illustrate its application within northern Idaho and northwestern Montana.     

构建环境监测管理决策支持系统的初步设想

阐述了环境监测管理决策支持系统的信息来源，介绍了基础数据库的建立方式，指出环境监测管理决策支持系统包括系统储备信息、系统更新信息、请求信息和解决方案信息，由用户、语言系统、知识系统和问题处理系统组成，具备基础数据管理、决策支持和环境预警功能，具有实用性、开放性和高效性。     

Internet Web-Based Information System for Scrap Vehicle Disposal in Taiwan

The scrap vehicle recycling program was formally initiated in 1995 when the illegal dumping issues of scrap tires and cars turn out to be intolerable in the society of Taiwan. The inherent complexity of such a recycling program, however, by integrating many public and private sectors that functions as a whole from the collection, storage, transport, treatment, and the disposal of scrape vehicles, makes the entire managerial efficiency hard to be maintained. Therefore, the state-of-the-art information technology via the use of the Internet platform becomes an indispensable tool to present a good communication mechanism, to provide the essential information sharing between all users and agencies, and to end up with improving the overall managerial efficiency. The idea using advanced web database along with geographical information system to help general public to dump their scrap vehicles smoothly and to make governmental agency control the disposal procedure easily could be one of the best solutions from the long-term environmental management perspective. This paper, representing contemporary progress of environmental management skill performed by the Foundation for Reduction, Reuse and Recovery, sponsored by the Environmental Protection Administration (EPA) in Taiwan, is designed to illustrate how to build up such a system, as named by the Scrap Vehicles Recycling Program Information System (SVRPIMS) in order to meet the requirement from both supply and demand sides of scrap vehicles disposal. Experience gained in this study indicates that the SVRPIMS successfully integrates the Coldfusion^® and Mapguide^® software engineering technologies on the World Wide Web (WWW) platform. After actual implementation in 1999, it proved that communication between users and agencies at various levels in the recycling program became much easier through instant information retrieval and analysis via such a system. Besides, SVRPIMS also provides two decision-support functionalities to assist in automatic search for the most appropriate dumping site for the users and to perform possible trading of spare parts for the recyclers through a logistic optimization analysis.     

MODELKEY. Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity (5 pp)

BACKGROUND: Triggered by the requirement of Water Framework Directive for a good ecological status for European river systems till 2015 and by still existing lacks in tools for cause identification of insufficient ecological status MODELKEY (http:// www.modelkey.org), an Integrated Project with 26 partners from 14 European countries, was started in 2005. MODELKEY is the acronym for 'Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity'. The project is funded by the European Commission within the Sixth Framework Programme. OBJECTIVES: MODELKEY comprises a multidisciplinary approach aiming at developing interlinked tools for an enhanced understanding of cause-effect-relationships between insufficient ecological status and environmental pollution as causative factor and for the assessment and forecasting of the risks of key pollutants on fresh water and marine ecosystems at a river basin and adjacent marine environment scale. New modelling tools for risk assessment including generic exposure assessment models, mechanistic models of toxic effects in simplified food chains, integrated diagnostic effect models based on community patterns, predictive component effect models applying artificial neural networks and GIS-based analysis of integrated risk indexes will be developed and linked to a user-friendly decision support system for the prioritisation of risks, contamination sources and contaminated sites. APPROACH: Modelling will be closely interlinked with extensive laboratory and field investigations. Early warning strategies on the basis of sub-lethal effects in vitro and in vivo are provided and combined with fractionation and analytical tools for effect-directed analysis of key toxicants. Integrated assessment of exposure and effects on biofilms, invertebrate and fish communities linking chemical analysis in water, sediment and biota with in vitro, in vivo and community level effect analysis is designed to provide data and conceptual understanding for risk arising from key toxicants in aquatic ecosystems and will be used for verification of various modelling approaches. CONCLUSION AND PERSPECTIVE: The developed tools will be verified in case studies representing European key areas including Mediterranean, Western and Central European river basins. An end-user-directed decision support system will be provided for cost-effective tool selection and appropriate risk and site prioritisation.