An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

基于面板数据的土地投入对经济增长的影响-以浙江省为例

采用生产函数与面板数据回归模型相结合的研究手段,以地处经济发达地区的浙江省为实证研究区域对土地要素投入对经济增长的影响进行了定量的研究。研究结果表明：(1)就规模效应而言,浙江省的经济增长处于规模报酬不变的发展阶段;(2)浙江省经济增长对劳动力要素的投入最为敏感,其中土地要素、劳动力要素和资本要素增加1个单位的投入量对经济增长的推动为 0.247 3、0.538 5 和 0.321 6;（3）固定资产投入在研究期间是浙江省经济增长的主要推动力,其贡献率达到6823%,而劳动力要素与土地要素则分别为2346%和625%;(4)浙江省土地利用不够集约,在研究期间土地要素对经济增长的影响能被资本要素与劳动力要素有效替代,而劳动力要素则难以被资本投入与土地投入有效替代,劳动集约型产业应该成为浙江省未来发展方向之一。     

Risk assessment tools incorporating human error probabilities in the Japanese small-sized establishment

Although it has been estimated that as many as 80% of all occupational accidents have human errors as a cause, no risk assessment tools incorporating human-related elements have been developed for small companies. Human error probability (HEP) and human error analysis (HEA) have been used for large-scale, safety-critical industries for last three decades, but these tools are not suitable for smaller, more general industries that comprise the majority of accident settings.Here, we describe and verify a risk assessment tool that includes human-related elements for small companies. The tool expands on traditional risk assessment methods, such as matrix, risk graph and numerical scoring method, by adding human-related elements. The tool is easy-to-use in occupational environments, and includes assessments of human behavior and potentially outdated machinery at work place.     

复杂社会技术系统安全事故的成因结构敏感性及预防对策研究

简要回顾现有复杂社会技术系统安全事故的成因理论存在的局限性,根据大量统计资料和经验总结构建事故成因理论的缺陷。该研究试图从分析和推理入手,根据复杂社会技术系统运行机制及事故成因结构敏感性特征,探索由于新技术快速普及应用而不断涌现的复杂社会技术系统的失效机制及事故的成因理论;解释复杂社会技术系统安全事故的严重程度差异性、时间方向性及情境依赖性;为任何因新技术普及应用而产生的人造系统的安全分析及事故预防提供理论和方法支撑。     

人-机系统事故预防理论研究

分析人-机系统事故发生原因,剖析经典以人失误为主因的事故致因模型存在的不足,在该模型基础上增加"刺激"形成的原因,构建了改进事故致因模型。对两模型进行比较研究,指出人机工程学与防止事故的关系,提出了人机工程学防止事故的方法,并给出人机界面合理性主观评价检查表。研究及论证表明:预防人-机系统事故的本质在于有效防止人失误的发生,除安全管理措施以外,最重要的是人机工程学问题,笔者提出的基于人机工程学的人-机系统事故预防理论,对人-机系统事故的预防起到积极的指导作用。     

基于卫星夜间灯光数据的中国分省碳排放时空模拟

中国能源统计数据"横向不可比,纵向不可加"现象依然突出,尤其是分省能源消费统计千差万别,给分省碳排放评估带来了较大困难,如何利用卫星遥感数据科学合理地估算中国分省碳排放是当前亟须研究的问题。本文运用DMSP/OLS全球稳定夜间灯光数据,在通过相互校正、年内融合和年际间校正等系列处理得到中国分省稳定夜间灯光数据的基础上,首先分别构建中国分省稳定夜间灯光亮度DN值与人均碳排放和单位面积碳排放之间的时空地理加权回归模型,两个模型整体效果均较好,拟合优度分别高达96.74%和99.24%;其次运用稳定夜间灯光亮度DN值对分省人均碳排放和单位面积碳排放进行时空模拟;最后运用人口规模和土地面积对分省碳排放进行估算。估算结果显示:(1)整体来看,2000—2013年年均碳排放模拟值与实际值6.3349×109t较为接近,两个模型的相对误差均在0.5%以内。(2)分年度来看,所有年份的相对误差均在5%以内,2006年分省加总碳排放模拟值与实际碳排放6.2036×109t最为接近,绝对误差和相对误差均较小,两个模型模拟值的相对误差均为0.04%。(3)分省域来看,2000—2013年年均碳排放模拟值与实际碳排放均非常接近,除海南和宁夏外,其余28个省区市的相对误差均在1%以内。(4)分年度分省域来看,以2013年为例,40%省份的相对误差在2%以内,70%省份的相对误差在5%以内。从整体、分年度、分省域、分年度分省域的估算结果来看,基于稳定夜间灯光数据的中国分省碳排放时空模拟效果良好。因此,运用卫星夜间灯光数据可以较为准确地对中国分省碳排放进行估算和预测,为卫星遥感影像数据服务分省碳排放监测和评估提供一种补充性参考。     

Carbon dioxide emissions from cities in China based on high resolution emission gridded data

Based on the China high resolution emission gridded data (1 km spatial resolution), this article is aimed to create a Chinese city carbon dioxide (CO₂) emission data set using consolidated data sources as well as normalized and standardized data processing methods. Standard methods were used to calculate city CO₂ emissions, including scope 1 and scope 2. Cities with higher CO₂ emissions are mostly in north, northeast, and eastern coastal areas. Cities with lower CO₂ emissions are in the western region. Cites with higher CO₂ emissions are clustered in the Jing-Jin-Ji Region (such as Beijing, Tianjin, and Tangshan), and the Yangtze River Delta region (such as Shanghai and Suzhou). The city per capita CO₂ emission is larger in the north than the south. There are obvious aggregations of cities with high per capita CO₂ emission in the north. Four cities among the top 10 per capita emissions (Erdos, Wuhai, Shizuishan, and Yinchuan) cluster in the main coal production areas of northern China. This indicates the significant impact of coal resources endowment on city industry and CO₂ emissions. The majority (77%) of cities have annual CO₂ emissions below 50 million tons. The mean annual emission, among all cities, is 37 million tons. Emissions from service-based cities, which include the smallest number of cities, are the highest. Industrial cities are the largest category and the emission distribution from these cities is close to the normal distribution. Emissions and degree of dispersion, in the other cities (excluding industrial cities and service-based cities), are in the lowest level. Per capita CO₂ emissions in these cities are generally below 20 t/person (89%) with a mean value of 11 t/person. The distribution interval of per capita CO₂ emission within industrial cities is the largest among the three city categories. This indicates greater differences among per capita CO₂ emissions of industrial cities. The distribution interval of per capita CO₂ emission of other cities is the lowest, indicating smaller differences of per capita CO₂ emissions among this city category. Three policy suggestions are proposed: first, city CO₂ emission inventory data in China should be increased, especially for prefecture level cities. Second, city responsibility for emission reduction, and partitioning the national goal should be established, using a bottom-up approach based on specific CO₂ emission levels and potential for emission reductions in each city. Third, comparative and benchmarking research on city CO₂ emissions should be conducted, and a Top Runner system of city CO₂ emission reduction should be established.     

Future implications of urban intensification on residential water demand

Over recent decades Auckland, New Zealand, metropolitan area has vastly expanded as a result of rapid population growth and low-density housing developments. In order to manage the uncontrolled low-density urban sprawl, Auckland Council proposed a compact city model through promoting higher density housing developments. In order to understand the implications of this transition on future residential water demand, this study first evaluated water consumption in three major housing types in Auckland including single houses, low-rise and high-rise apartments. Using the geographic information system, the water consumption information, estimated from a large sample of 60,000 dwellings across Auckland, was subsequently integrated with the Proposed Auckland Unitary Plan outlining the future housing composition over different areas in Auckland. Through developing different growth scenarios, the study showed that the housing transition from single houses to more intensified multi-unit houses cannot considerably affect the average per capita water consumption in Auckland.     

航空维修人为差错影响因素分析中的模糊层次分析法

航空维修中的人为差错影响因素分析对于预防事故发生至关重要,如何定量分析及辨识出主要影响因素是亟待解决的问题。为此,结合航空维修实际,提出运用群组模糊层次分析法对人为差错影响因素进行量化排序和分类,归纳细化了影响因素层次体系,并给出了分析计算流程。以一起由维修人为差错所引发的航空事故为例进行了实证分析,结果表明:该方法能够辨识出航空维修中人为差错产生的主要影响因素,进而对制订最优事故预防方案,控制和减少该类事故的发生有积极意义。同时该方法对其他行业中的人为差错主要影响因素辨识有着一定的参考价值。     

基于人工神经网络理论的建筑物火灾安全评价研究

依据建筑物火灾危险性的影响因素,应用人工神经网络理论及系统安全方法,建立了建筑物火灾危险性的评价指标体系,该方法摆脱了评价过程中的随机性和参评人员主观上的不确定性及其认识上的模糊性等缺点,大大提高了准确性。为了验证评价模型的准确性,将该理论应用到某高校图书馆火灾危险性评价中,快速、准确地得到了安全评价结果,取得了满意效果,为建筑物防火设计以及安全管理提供了可行的依据。