双重预防机制在家具制造业的应用与实践

为了减少安全事故的发生,进一步加强和规范企业生产现场的安全管理,探索双重预防机制在企业安全管理中的应用,结合家具制造企业安全生产现状,运用风险分级管控与隐患排查的相关理论,详细论述了企业构建双重预防体系的要点及方法,并提出了双重预防体系的监督与考核机制。实践结果证明,双重预防机制是一个统一的有机结合体,只有将风险分级管控体系和隐患排查治理体系有机结合,才能将导致事故发生的根源性因素进行有效识别和管控,双重预防机制建设也是一个动态管理的过程,需要及时进行监督、考核和调整。     

某矿低铜废石综合回收利用项目职业病危害预评价

为了对某矿业有限公司低铜废石综合回收利用项目可能产生的职业病危害因素进行辨识、分析和评价,采用检查表、类比法相结合的原则对该项目的铲装、破碎、运输、筑堆等工艺进行分析评价,并利用经验法对浸出、萃取电积工艺进行分析评价。结果表明:类比工程中绝大部分粉尘、噪声检测点的浓（强）度符合国家标准;化学毒物、工频电场接触浓（强）度符合国家标准;电积车间的通风满足要求;萃取车间的事故通风能力不足。评价方法及通风计算方法对同类项目具有借鉴意义。     

自愿减排项目碳泄漏：内涵、类别及应对

自愿减排项目是碳排放交易市场抵消机制的运行载体,灵活的自愿减排抵消机制是碳排放交易市场的补充,对应对全球气候变化问题具有重要意义。碳泄漏,作为严重影响抵消项目减排效率的热点问题值得关注。目前,中国已形成较大规模的自愿减排市场,截至2018年底,国家发展改革委共签发了约7200万tCO_2当量减排量,我国在建立健全自愿减排抵消市场机制的过程中,需要把握项目碳泄漏的负外部性这一实质,厘清其运行机理并积极应对。本文旨在系统阐述该问题,并为进一步实现抵消项目减排潜力提供思路和方向:从自愿减排项目碳泄漏的内涵与定义出发,首先对项目碳泄漏的分类进行梳理,并依据产生途径的不同重点分析了活动转移排放、生命周期、市场路径、生态以及技术泄漏的作用机制、影响因素及其相应的研究方法;其次从具体项目应用、系统项目应用和宏观应用三个层面讨论了应对自愿减排项目碳泄漏问题的管理对策;最后结合我国自愿减排抵消市场的实际情况,建议未来抵消项目碳泄漏的应对和管理应在分门别类对其概念进行精准定义的基础上将解决措施的成本效益考虑在内,此外,在评估泄漏量时需要同时测算不同类型的碳泄漏,探究其协同效应以免高估其泄漏程度。     

生活垃圾强制分类形势下的多源废荧光灯管回收管理机制建议

废荧光灯管的来源广泛,包括工业来源和社会来源,社会来源又包括居民来源,企业事业单位、公共场所等机构来源,具有多来源的特性。废荧光灯管中含有汞,若不经过妥善处理,会造成环境污染,对人的身体健康造成危害。随着国内生活垃圾分类的开展,废荧光灯管作为生活垃圾中有害垃圾的典型类别被强制分类,但仍存在很多问题。本文梳理了我国废荧光灯管的产生情况、LED灯替代情况,并对美国、欧盟、日本和我国国内典型城市的废荧光管理情况进行了总结。针对我国废荧光灯管的回收现状,从责任主体、责任划分、收集渠道、资金机制等角度提出了相关的管理建议,为推动我国废荧光灯管的管理提供借鉴。     

Indigenous Systems of Forest Classification: Understanding Land Use Patterns and the Role of NTFPs in Shifting Cultivators’ Subsistence Economies

This article discusses the system of classification of forest types used by the Pwo Karen in Thung Yai Naresuan Wildlife Sanctuary in western Thailand and the role of nontimber forest products (NTFPs), focusing on wild food plants, in Karen livelihoods. The article argues that the Pwo Karen have two methods of forest classification, closely related to their swidden farming practices. The first is used for forest land that has been, or can be, swiddened, and classifies forest types according to growth conditions. The second system is used for land that is not suitable for cultivation and looks at soil properties and slope. The article estimates the relative importance of each forest type in what concerns the collection of wild food plants. A total of 134 wild food plant species were recorded in December 2004. They account for some 80–90% of the amount of edible plants consumed by the Pwo Karen, and have a base value of Baht 11,505 per year, comparable to the cash incomes of many households. The article argues that the Pwo Karen reliance on NTFPs has influenced their land-use and forest management practices. However, by restricting the length of the fallow period, the Thai government has caused ecological changes that are challenging the ability of the Karen to remain subsistence oriented. By ignoring shifting cultivators’ dependence on such products, the involvement of governments in forest management, especially through restrictions imposed on swidden farming practices, is likely to have a considerable impact on the livelihood strategies of these communities.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

香港灌丛植被的数量分类与环境关系分析

灌丛是香港植被的主要组成部分,2005年1—3月在香港地区(包括香港岛、九龙、新界和大屿山岛)设置样地,利用组平均法(UPGMA)和除趋势对应分析法(DCA)对香港灌丛群落进行聚类和排序分析. 结果表明,灌丛植被可划分为7个群落类型:桃金娘、米碎花、岗松、苏铁蕨、大头茶、山油柑和细齿柃. DCA排序揭示了灌丛群落的分布格局与环境因子的生态关系,DCA排序第1轴反映了灌丛群落所在环境的湿度梯度,排序图的对角线指示出海拔梯度,也反映了温度的变化. 结合物种多样性分析发现,物种多样性指数随海拔的升高而减少,说明水热条件和海拔是制约灌丛植被分布格局的主要因素.      

基于层次分析法的有毒作业场所职业危害程度分级指标研究

我国目前职业危害形势依然严峻,急、慢性职业中毒案例时有发生。对可能引起急、慢性职业中毒的有毒作业场所,按照其职业危害严重程度实施分级、分重点监管,成为我国职业危害监管工作需要解决的迫切需求。实施有毒作业场所分级监管的关键,是确定合理的分级指标,从而将有毒作业场所区分开。本文应用层次分析法,对有毒作业场所的各项评价指标进行分析,并最终确定毒物浓度超标倍数作为最终的分级指标,从而为制定有毒作业场所分级标准,开展有毒作业场所分级监管提供科学的依据。     

乡镇垃圾分类循环利用现状——以闽侯县上街镇为例

由于我国乡镇经济的迅速发展以及乡镇村民生活水平加速提高,乡镇的垃圾种类及数量趋向于城市.乡镇村民居住较为分散,垃圾分类、收集、循环利用相较于城市困难,因此推进乡镇垃圾分类循环利用迫在眉睫.本文从闽侯县上街镇展开调查,以乡镇垃圾分类、回收循环利用为关键词展开分析,并从上街镇垃圾分类循环利用模式存在的问题进行分析、总结和建...     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.