水质监测领域报表工具的研究与应用

水质报表是水环境监测领域内系统的重要组成部分,为加快水质报表的开发,增强水质报表的可维护性,设计独立于系统并且符合水质报表特性的报表工具。该报表工具分为报表设计器和报表服务器两部分,设计器提供可视化的报表编辑界面,允许用户自己设计报表函数,服务器负责报表的调用和解析并且采用缓存机制提高报表的运行效率,将该报表工具应用于水质环境监测及分析系统以验证其实用性,结果证明,该水质报表工具具有较高的灵活性和可扩展性。     

Black swans,cognition, and the power of learning from failure

Failure carries undeniable stigma and is difficult to confront for individuals, teams, and organizations. Disciplines such as commercial and military aviation, medicine, and business have long histories of grappling with it, beginning with the recognition that failure is inevitable in every human endeavor. Although conservation may arguably be more complex, conservation professionals can draw on the research and experience of these other disciplines to institutionalize activities and attitudes that foster learning from failure, whether they are minor setbacks or major disasters. Understanding the role of individual cognitive biases, team psychological safety, and organizational willingness to support critical self‐examination all contribute to creating a cultural shift in conservation to one that is open to the learning opportunity that failure provides. This new approach to managing failure is a necessary next step in the evolution of conservation effectiveness.     

化学物质水体归趋与影响数据库(CAFE)，一种用于评估水环境中化学物质溢出水平的工具

化学物质水体归趋与影响 (简称CAFE)数据库是一个允许快速并无限制访问数据的集中式数据库。CAFE将现有的32 377种化学物质的归趋数据和4 498种化学物质的毒性效果数据整合至用户友好的工具中,以物种敏感度分布(SSD)的形式总结毒性数据,并提供了相关的1%和5%危害浓度(HC₁和HC₅)。为探究CAFE数据与报道的化学事故之间的联系,一项数据可用性评估显示,2000年至2014年间在美国国家应急中心呈报的55种化学物质中,32种物质的归趋和20种物质的毒性在CAFE中均有记录;2003年至2014年间由美国海洋及大气管理局呈报的205种化学物质中,86种物质的归趋和103种物质的毒性在CAFE中也均有记录。我们假设2种化学物质在环境中溢出(丙烯腈,溢出量为625桶 ;变性乙醇,溢出量为857桶),根据模型对其环境浓度进行模拟,进而说明CAFE在实际中的应用。在24 h时程的SSD中,大多数物种很可能分别在溢出后最初的35 min内和15 h内受到丙烯腈和变性酒精的影响。丙烯腈浓度在溢出后45 min已低于HC₅(17 mg?L^L-1),变性酒精浓度在溢出后60 h已低于HC₅(2 676 mg?L^L-1)。将100种化学物质以CAFE数据为基础得出的HC₅与发表的HC₅进行对比,我们发现超过一半的数值都在2倍差异以内,较少的一部分数值则超过了10倍差异。CAFE的发展提高了获取相关环境信息的能力,并可能应用于水体环境污染物溢出分析之外的更多领域。
精选自Adriana C. Bejarano, James K. Farr, Polly Jenne, Valerie Chu, Al Hielscher. The chemical aquatic fate and effects database (CAFE), a tool that supports assessments of chemical spills in aquatic environments. Environmental Toxicology and Chemistry: Volume 35, Issue 7, pages 1576–1586, July 2016. DOI: 10.1002/etc.3289
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3289/full
     

数字化核电站SGTR事故操纵员认知分析

核电站主控室数字化后的人因特征包括数字化规程、警报系统、操作班组信息共享、界面管理任务,它们对操纵员认知可靠性都有重要影响。IDA认知模型把操纵员认知过程分为信息(Information)、诊断(Diagnosis)/决策(Decision)、执行(Action)3个阶段。按IDA模型把数字化核电站主控室操纵员SGTR事故认知过程分为3个阶段,对每个阶段进行操作分析,找到操纵员在SGTR事故认知过程各阶段最容易发生的失误和主要失误。操纵员认知失误发生的原因在于界面管理任务增大了认知难度以及数字化后缺乏情景意识等。     

Assessing sustainable development in urban areas using cognitive mapping and MCDA

As interest in sustainability-related issues has increased over recent years, so too has urban sustainability risen to the fore, in academic, practitioner, and policymaking circles alike. Urban sustainability requires a balance between environmental concerns, the economy, and social development in urban areas. However, over the years, there has been an exponential increase in urban density, accompanied by increased economic activity and high levels of consumption, which have hindered urban planning and made the sustainable management of urban areas more difficult. It has therefore become increasingly necessary to combine the interests of the various stakeholders involved in – or affected by – urban planning measures, in order to achieve a balance between their needs, those of the environment and future generations, and the need for economic development. Sustainability evaluation models can in this sense be considered a baseline condition for sustainable development. However, most existing evaluation systems present limitations in terms of criteria identification and the calculation of the respective trade-offs. To address these issues, the current study aims to combine cognitive mapping and the Analytic Hierarchy Process (AHP) to prioritize the determinants of sustainable development in urban areas. The advantages and limitations of our proposal are also analyzed.     

组合类产品筛选试验通用工装设计

目的 提高组合类产品在进行环境应力筛选随机振动试验时的试验效率,规范无工装产品的安装固定方式及试验方法,降低试验人员的体力消耗,保障试验的安全和质量.方法 通过设计通用工装,并对工装进行仿真分析和试验验证,保证工装具备通用性的同时,满足振动控制曲线允差符合相关标准的要求.结果 经过试验验证,通用工装满足尺寸小于600 ...     

SELECTION OF WASTE DISPOSAL SITES USING GIS1

ABSTRACT: Geographic Information Systems (GIS) technology is used to identify candidate sites for a solid waste disposal facility in the Gölbasi region of Turkey that has suffered from the negative impact of a current but poorly-located open-dump site on the environment. The municipality of Gölbasi has noticed its deleterious effect on the environment, and has thus decided to dismiss this open-dump site and search for new landfill sites. In this study, the procedure followed under a GIS framework rejects the unacceptable sites considering environmental factors exclusively, other than economic and political issues, contained in the form of multiple layers of attribute information to select the candidate sites for landfilling wastes through an overlay analysis performed by GIS software, ARC/INFO V 7.1. For the spatial data requirements of GIS, a number of thematic map layers (ground water, wetlands and swamp areas, surface water, roads, topographic contours, ecological features, settlements, erosion susceptibility zones, and soil type) are prepared in digital form. In this application, GIS is considered as a screening tool in a site selection process to narrow the number of candidate sites, subsequently leading to one or more sites for detailed investigation. Preliminary ranking for a group of potential sites is done on the basis of simple calculations coupled with on-site field studies.     

一种人因可靠性分析(HRA)方法

从控制论角度说明人因可靠性分析方法，在分析现有两代人因可靠性分析方法不足的基础上，结合控制论，提出了一种新的人因可靠性分析方法的构想。     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.