我国的GHS之路

GHS是全球化学品统一分类和标签制度的简称,其主要内容是按化学品的物理、健康和环境危害对物质和混合物进行分类,并统一危险公示要素.介绍了GHS及我国启程GHS的意义,阐述了各相关方为应对、健全和完善GHS所作出的努力,分析了我国GHS道路上存在的障碍,并展望了未来GHS工作方向.     

我国化学品分类和标签与GHS的差距分析

为明确我国现阶段实施GHS存在的问题,促使我国化学品分类和标签满足GHS要求。研究了我国化学品分类标准、标签标准与GHS存在的差距。发现了《危险化学品名录》没有分类标准,并且未涵盖GHS爆炸物中的不稳定爆炸物和1.2项、1.5项、1.6项爆炸物,易燃气溶胶,以及除急性毒性以外的健康危害和环境危害的化学品,剧毒化学品、有毒物质存在不同监管部门分类标准不统一,现行多套危险化学品标签标准问题。提出了在《危险化学品名录》中明确规定危险性分类标准;统一剧毒化学品、有毒品分类标准;在相关的危险化学品法规中明确规定危险化学品标签应符合的标准。     

航空维修差错模式及差错成因的灰色关联分析

提出一种基于HFACS-ME框架和灰色关联分析法的航空维修差错模式和差错成因之间关系的分析方法。利用该方法分别从"模式—成因"和"成因—模式"2个方向,以"技能差错"和"身体状态差"为例,对差错模式和差错成因之间的关系进行分析,得到影响"技能差错"的主要差错成因依次为空间狭窄、培训不足、工具损坏、身体状态差、精神状态差、空间阻碍,以及"身体状态差"主要影响的差错模式为记忆差错、决策差错、技能差错。结果表明,灰色关联分析法对航空维修差错模式和差错成因之间关系的分析是有效的、可行的。     

欧日中实施GHS政策的对比和思考

通过研究欧盟、日本和我国实施全球化学品统一分类和标签制度(GHS)的基本情况,并从实施GHS的框架体系、实施GHS的时间节点、GHS的危险类别和GHS危险类别的判定,4个方面对欧盟、日本和我国实施GHS的现状进行重点研究。通过对比分析得出我国当前实施GHS主要存在4个方面的问题,即缺乏实施GHS的综合法律、实施GHS缓冲期的设置存在问题、缺乏开展GHS分类的配套指南、没有合理的运用"积木原则"。结合我国的实际情况提出3个方面的建议:适时推动我国GHS法律法规体系的建设、在各部门的协作下编制我国的GHS分类指南、合理的运用"积木原则"。通过分析表明:欧盟实施的GHS政策最为完善且力度最强,日本次之;由于充分利用"积木原则",欧盟的GHS类别与日中存在一定的差异;欧日中在数据运用和GHS危险判定原则上存在差异。     

Fisher法确定稳定分类数

对Fisher法确定稳定分类数作了一些改进,提出利用β值指标来衡量分类的稳定程度,进而确定合理的分类个数。在实际应用中,证明了该方法是可行的。     

基于HFACS-BN模型的危险化学品事故人因路径分析*

为提高危险化学品安全管理水平,收集我国134起以人为主因的危险化学品事故,构建危险化学品事故的HFACS-BN模型,并基于贝叶斯网络对危险化学品事故中的人因路径及各因素灵敏度进行分析。研究结果表明:行为违规是导致事故的最主要不安全行为;在复杂路径中,环境因素和操作者状态具有较高的灵敏度,与其相关的风险认知与处理不当是阻碍事故预防的关键因素;在非复杂路径中,操作者状态与运行计划不当具有较高的灵敏度,其所涉及的监督违规、组织过程和组织氛围,是导致危险化学品事故的根本起点,并可依此分析事故直接原因和间接原因;操作者状态在2种路径中均表现出高灵敏度,因此化工企业在人员管理上要加强关注职工状态,减少不安全行为的出现。     

EVALUATION OF THE ROSGEN STREAM CLASSIFICATION SYSTEM IN CHEQUAMEGON‐NICOLET NATIONAL FOREST,WISCONSIN1

ABSTRACT: Data collected from 121 stream reaches during 1991 to 1993 were evaluated to determine the applicability of the Rosgen Stream Classification System (RSCS) to the low relief terrain within the Chequamegon‐Nicolet National Forest (CNNF) in Wisconsin, USA. All reaches were classified to RSCS Level I and II except that 10.7 percent had sinuosities below the continuum limits and one reach had a predominantly organic substrate. Five of eight possible RSCS Level I types were observed including B, C, D, A, E, and F; 86 percent were C and E types. Seventeen of 94 possible RSCS Level II types were observed. Most reaches were slightly entrenched, had low to moderate width/depth ratios, relatively low sinuosity, low slope, and sand or gravel as the dominant channel material. Discriminant analyses were used to verify the applicability of RSCS for streams within the CNNF; discriminant functions correctly classified 92.5 and 94.7 percent of the Level I and II RSCS types, respectively. When limits for E and F types were modified slightly at Level II by adding an additional category for slopes less than 0.1 percent (a modification we recommend for low relief terrain), discriminant functions correctly classified 99.1 percent of the types. Adding another slope break at 0.3 percent produced similar results. Based on our analyses, RSCS works well within the CNNF and is probably applicable to other areas with low‐relief terrain.     

无量纲廓线函数对稳定度分类的影响

讨论了无量纲廓线函数对稳定度分类标准计算结果的影响,利用北京325m气象铁塔的超声脉动资料和常规梯度观测资料,对4种无量纲廓线函数进行比较.结果表明,对于北京地区Businger-Hick公式最合适,风速比法稳定度分类标准不是稳定度级别的单调函数.     

INTEGRATING DEMOGRAPHIC AND LANDSAT (TM) DATA AT A WATERSHED SCALE1

ABSTRACT: Recurrent calls for integrated resource management urge that an understanding of human activities and populations be incorporated into natural resource research, management, and protection efforts. In this paper, we hypothesize that watersheds can be a valuable geography for organizing an inquiry into the relationship between humans and the environment, and we present a framework for conducting such efforts. The framework is grounded in the emerging field of landscape ecology and incorporates demographic theory and data. Demography has been advanced by technological capabilities associated with the 1990 Census. Employing Geographic Information System (GIS) tools, we couple Landsat Thematic Mapper (TM) land cover data with census‐derived housing density data to demonstrate the operation of our framework and its utility for better understanding human‐landscape interactions. In our investigation of the Kickapoo Watershed and two sub‐ watersheds, located in southwestern Wisconsin, we identify relationships between landscape composition and the distribution and social structure of human populations. Our findings offer insight into the interplay between people and biophysical systems.     

基于机器学习分类算法解析EIS数据的有机涂层性能评价方法

目的 基于机器学习分类算法快速评估有机涂层的防腐性能。方法 通过实验室加速试验模拟涂层真实的退化过程,并根据测得的电化学数据,分析不同退化阶段的等效电路元件参数。随后,采用随机抽样方法获取大量数据,用于机器学习模型训练。通过对比支持向量机(SVM)、k最近邻(k-NN)和随机森林(RF)3种不同的机器学习算法,以及多种输入特征集训练的涂层性能分类器模型的准确率,分析最适合用于涂层性能快速评估的机器学习算法和电化学特征。结果 根据不同输入特征训练的k-NN和RF模型均表现出良好的预测效果,而SVM模型的预测效果相对较差。根据不同频率范围训练的分类器模型中,在低频区表现最佳,而在高频区表现较差。结论 基于阻抗虚部、虚部+实部和阻抗模值3种输入特征训练的RF分类器模型的预测效果最准确。不同频率区间内,低频区的阻抗特征更能准确表征涂层性能。