Score averaging for alien species risk assessment: a probabilistic alternative

In many biological risk assessment problems and specifically those involving invasive alien species and quarantine pests, ordinal scoring systems are used as a basis for risk quantification. Frequently, the problem is disaggregated into a series of components to allow a more structured and systematic evaluation. Each component is then scored and an overall measure of risk calculated from the set of scores. No satisfactory method exists to compute an overall measure of risk and most practitioners have resorted to score-averaging. Here we describe an approach involving the linear mapping of scores to notional probabilities to allow the use of conditional probability to derive an overall measure. Initial results give better discrimination between high and low risk cases and closer correspondence with independent expert judgement than does score-averaging.     

Privileged Knowledge and Social Change: Effects on Different Participants of Using Geographic Information Systems Technology in Natural Resource Management

The use of geographic information systems (GIS) technology in natural resource management has expanded rapidly: It is the preferred tool of spatial data analysis addressing large landscapes and is typically the presentation medium for conveying landscape-scale scientific findings to all kinds of audiences. In a case study using the Coastal Landscape Analysis and Modeling Study in western Oregon, it was found that the use of GIS to analyze and display natural resource data in that project produced a variety of responses among different participants and participant groups. The findings offer insights into the workings of groups attempting public involvement in natural resource management.     

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors

INTRODUCTION: Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. METHOD: The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. RESULTS: This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. IMPACT ON INDUSTRY: "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.     

Regional Scale Stressor‐Response Models in Aquatic Ecosystems1

Abstract: A systematic method for identification and estimation of regional scale stressor‐response models in aquatic ecosystems will be useful in monitoring and assessment of aquatic resources, determination of regional nutrient criteria and for increased understanding of the differences between regions. The model response variable is chlorophyll a, a measure of algal density, while the stressors include nutrient concentrations from the USEPA Nutrient Criteria Database (NCD) for lakes/ponds and reservoirs of the continental United States. The NCD has observations for both stressors and biological responses determined using methods that are not consistently available at the continental scale. To link multiple environmental stressors to biological responses and quantify uncertainty in model predictions, we take a multilevel modeling approach to the estimation of a linear model for prediction of log Chlorophyll a using predictors log TP and log TN. The multilevel modeling approach allows us to adjust the impact of covariates at all levels (observation, higher level groups) for the simultaneous operation of contextual and individual variability in the outcome. Here, we wish to allow separate regression coefficients for inference regarding similarities and differences between each of 14 ecoregions, and between the two water‐body types, lakes/ponds and reservoirs. We are also interested in the nuisance effects of the categorical variables indicating the type of nitrogen measurements (three levels) and the type of chlorophyll a measurements (four levels) used. Model‐based determination of nutrient criteria points to an apparent incompatibility of criteria developed for nutrient stressors and eutrophication responses using current Environmental Protection Agency’s guidance.     

Assessing the value of information for water quality management in the North Sea

Global Earth Observation (GEO) is one of the most important sources of information for environmental resource management and disaster prevention. With budgets for GEO increasingly under pressure, it is becoming important to be able to quantify the returns to informational investments. For this, a clear analytical framework is lacking. By combining Bayesian decision theory with an empirical, stakeholder-oriented approach, this paper attempts to develop such a framework. The analysis focuses on the use of satellite observations for Dutch water quality management in the North Sea. Dutch water quality management currently relies on information from 'in situ' measurements but is considering extending and deepening its information base with satellite observations. To estimate returns to additional investments in satellite observation, we analyze the added value of an extended monitoring system for the management of eutrophication, potentially harmful algal blooms and suspended sediment and turbidity in the North Sea. First, we develop a model to make the potential contribution of information to welfare explicit. Second, we use this model to develop a questionnaire and interpret the results. The results indicate that the expected welfare impact of investing in satellite observation is positive, but that outcomes strongly depend on the accuracy of the information system and the range of informational benefits perceived.     

企业环境信息披露的外部影响因素实证研究

本文以111家重污染行业的A股上市公司为样本,对企业环境信息披露的外部影响因素进行研究,对政府环保投入、公众环保意识、区域经济水平和社会监督水平等因素与企业环境信息披露水平之间的关系进行了理论分析和实证检验.研究结果显示:从整体上来说外部因素与企业环境信息披露水平呈负相关关系,说明现阶段企业环保工作所处的外部环境不容乐观;其中,区域经济发展水平与企业环境信息披露水平显著负相关;政府环保投入与企业环境信息披露水平显著正相关,但其影响程度随着经济发展水平的提高而减小;公众环保意识和社会监督水平对企业环境信息披露水平无显著影响.最后,提出了转变经济发展方式、加强政府宏观调控和完善企韭环境信息披露制度等政策建议.     

青海湖鸟岛植被演替和动物分布特点

近年来,由于青海湖水位下降、土地沙化、植被退化、人类活动等诸多因素的影响,青海湖鸟岛的生态环境也受到极大影响,本文探讨随气候因素和人类活动的影响,青海湖鸟岛地区动植物种类、数量、分布的变化情况。     

城市内河表层沉积物氮形态及影响因素

采用连续分级提取法对许昌市清潩河河道10个表层沉积物样品中氮形态含量进行测定, 分别得到离子交换态氮(IEF-N)、弱酸可提取态氮(WAEF-N)、强碱可提取态氮(SAEF-N)、强氧化剂可提取态氮(SOEF-N)和非可转化态氮(NTN), 探讨了不同形态氮分布特征、影响因素及其对河道水环境潜在的风险. 结果表明,沉积物中总氮(TN)含量为2140~9470mg/kg, 与沉积物有机质含量沿河道变化趋势基本一致; 可转化态氮(TTN)的优势形态从上游至下游逐渐由IEF-N向SAEF-N再向SOEF-N转化, 逐渐趋于稳定; IEF-N含量受沉积物有机质、pH值及上覆水体氨氮和悬浮物含量影响, 且与TN极显著相关, 说明清潩河沉积物TN含量可以作为河道内源污染风险判断的重要指标; 此外上覆水体较高的COD含量对SAEF-N和NTN的沉积、较高的氨氮含量对IEF-N和TN的释放以及总磷含量对NTN活性的增强等都产生影响.因此, 在开展清潩河水环境综合整治时, 需考虑水相与沉积物相的相互作用, 同步开展治理工作.     

胶州湾潮滩湿地CHBr3通量特征及影响因素研究

在2016年7月~2017年5月期间,运用静态箱法对胶州湾潮滩湿地系统的CHBr₃排放通量进行了观测,并对影响CHBr₃通量的主要影响因子进行了探究.结果表明,胶州湾潮滩湿地是CHBr₃的排放源,互花米草湿地和光滩释放CHBr₃的通量均值分别为10.92nmol/（m²×d）和8.96nmol/（m²×d）,说明互花米草湿地在一定程度上能够促进CHBr₃的排放.不同潮滩湿地之间CHBr₃的排放通量有明显区别.互花米草湿地在夏秋季节较高的CHBr₃通量可能主要是受温度和植被生物量的影响,光滩在冬春季节较高的CHBr₃通量可能与冻融循环过程有关.胶州湾潮滩湿地环境因素变化比较复杂,CHBr₃的排放通量受多种因素的影响.温度对CHBr₃排放通量的影响显著,而植被生长状况、水盐条件和营养元素等对CHBr₃排放通量的影响也不容忽视.     

某市工业源重金属污染源评价

针对某市工业源废水中6种重金属污染物产生现状,利用全国第一次污染源普查云南省数据,用等标污染负荷法计算出各种重金属污染负荷和负荷比,及每个工厂(地区)总的重金属污染负荷和负荷比,对某市工业废水重金属污染源进行评价,利用ARCGIS对该区域重金属产生量进行分析,明确重金属污染源空间分布规律,画出有重金属产生的企业的分布图,各种重金属产生空间分布图,和某市各乡镇的污染负荷等级图。结果表明该地区重金属污染源污染负荷的大小排列顺序是砷>汞>铅>六价铬>铬>镉。各企业的重金属源总污染负荷大小为化工厂>盐化昆明盐矿>盐化厂分厂>蓄电池厂>金属原料加工厂>电源厂>材料厂>废旧电瓶场>铸件厂。某市各镇的重金属污染源污染负荷大小排序为B镇>G镇>D镇>E镇。