国内外空气质量监测网络设计方法研究进展

如何设计效率高、代表性好、目的性强的空气质量监测网络,是长期以来空气质量监测工作的难点与关键。随着环境管理水平的提高,环境空气质量监测网络的设计成为当前研究的热点之一,国内外很多学者对其进行了广泛的研究。文章对美国、欧盟和我国关于空气质量监测网络设计的规范进行了简要评述和比较分析,并参考国内外一些关于空气质量监测网络设计的研究和应用实例,对当前主要的设计方法及应用进展进行了综述。     

Dynamic failure probability analysis of urban gas pipeline network

The gas pipeline network is an essential infrastructure for a smart city. It provides a much-needed energy source; however, it poses a significant risk to the community. Effective risk management assists in maintaining the operational safety of the network. The risk management of the network requires reliable dynamic failure probability analysis. This paper proposes a methodology of condition monitoring and dynamic failure probability analysis of urban gas pipeline network. The methodology begins with identifying key design and operational factors responsible for pipeline failure. Subsequently, a causation-based failure model is developed as the Bowtie model. The Bowtie model is transformed into a Bayesian network, which is analyzed using operational data. The key contributory factors of accident causation are monitored. The monitored data is used to analyze the updated failure probability of the network. The gas pipeline network's dynamic failure probability is combined with the potential consequences to assess the risk. The application of the approach is demonstrated in a section of the urban gas pipeline.     

Design of an Air-Quality Surveillance System for Buenos Aires City Integrated by a NO x Monitoring Network and Atmospheric Dispersion Models

This paper presents an air-quality surveillance system designed to detect the occurrence of air pollutant concentrations greater than a reference level in an urban area. The system is integrated by an air-quality monitoring network and atmospheric dispersion models simulations. An objective methodology to design an urban air-quality monitoring network is proposed. This methodology is based on the analysis of air-quality modelling results. The procedure is applied to design an air-quality monitoring network to control NO _x concentration levels in Buenos Aires City. Results indicate that six monitors will detect the occurrence of concentration greater than the air-quality guidelines with an efficiency of about 67%. Once a violation is detected, results of atmospheric dispersion models will help in the determination of affected areas. Four possible examples are included to illustrate the assistance that the results of atmospheric dispersion models can bring to a better estimation of possible affected areas in the city. Combining these results with the last census data, an estimation of the inhabitants possibly exposed is obtained.     

Ecosystem classification for EU habitat distribution assessment in sandy coastal environments: An application in central Italy

Many recent developments in coastal science have gone against the demands of European Union legislation. Coastal dune systems which cover small areas of the earth can host a high level of biodiversity. However, human pressure on coastal zones around the world has increased dramatically in the last 50 years. In addition to direct habitat loss, the rapid extinction of many species that are unique to these systems can be attributed to landscape deterioration through the lack of appropriate management. In this paper, we propose to use of an ecosystem classification technique that integrates potential natural vegetation distribution as a reference framework for coastal dune EU Habitats (92/43) distribution analysis and assessment. As an example, the present study analyses the EU Habitats distribution within a hierarchical ecosystem classification of the coastal dune systems of central Italy. In total, 24 land elements belonging to 8 land units, 5 land facets, 2 land systems and 2 land regions were identified for the coastal dunes of central Italy, based on diagnostic land attributes. In central Italy, coastal dune environments including all the beach area, mobile dunes and all the fixed-dune land elements contain or could potentially hold at least one EU habitat of interest. Almost all dune slack transitions present the potentiality for the spontaneous development of EU woodlands of interest. The precise information concerning these ecosystems distribution and ecological relationships that this method produces, makes it very effective in Natura 2000 European network assessment. This hierarchical ecosystem classification method facilitates the identification of areas to be surveyed and eventually bound, under the implementation of EU Habitat directive (92/43) including areas with highly disturbed coastal dune ecosystems.     

Ecological network determination of sectoral linkages, utility relations and structural characteristics on urban ecological economic system

Analyzing the structure and functioning of the urban system revealed ways to optimize its structure by adjusting the relationships among compartments, thereby demonstrating how ecological network analysis can be used in urban system research. Based on the account of the extended exergy utilization in the sector of urban socio-economic system, which is considered as the composition of extraction (Ex), conversion (Co), agriculture (Ag), industry (In), transportation (Tr), tertiary (Te) and households (Do) sectors, an urban ecological network model is constructed to gain insights into the economic processes oriented to sustainable urban development. Taking Beijing city as the case, the network accounting and related ecological evaluation of a practical urban economy are carried out in this study in the light of flux, efficiency, utility and structure analysis. The results showed that a large quantity of energy and resources have to be consumed to maintain the structure and function of a city. The thermodynamic efficiencies of individual sector in Beijing remain at a low level. The social system in Beijing is a highly competitive network, and there are 8 competitive relations and only two mutualistic ones. The Domestic and Agricultural sector are the major controlling factors of the system. Moreover, the assessment results of Beijing are compared with the other three socio-economic systems, Norway, UK and Italy, and the ecological network function and structure comparisons are correspondingly illuminated and discussed. The conclusions indicate that the exergy-based network analysis can be refined to become an integrative tool for evaluation, policy-making and regulation for urban socio-economic system management concerning structure and efficiency at urban levels.     

空气自动监测网络数据审核自动化实现的创新与实践

阐述了在城市空气质量自动监测网络的质量保证管理中,使用计算机数据审核系统对监测数据进行自动审核的设计思想及其采取的创新手段;详细介绍了该系统在山东省的使用情况。     

基于RBF神经网络的城市建成区面积预测研究——兼与BP神经网络和线性回归对比分析

城市建成区面积预测是城市研究的一个核心问题,其与城市经济社会之间表现为一种复杂的非线性关系,传统的方法模型难以精确预测。作为一种较新的人工神经网络模型,RBF神经网络能以任意精度全局逼近任意非线性关系,表现出了极强的处理复杂非线性系统的能力。以合肥市建成区面积预测为例,构建了基于RBF网络的预测模型,作为对比,同时用BP神经网络、一元线性回归和多元线性回归模型进行了预测。预测结果的综合分析表明,在预测精度上,RBF网络＞BP网络＞多元线性回归模型＞一元线性回归模型。研究显示,RBF网络能为城市建成区面积预测提供一种新思路和新方法,进而可为城市土地利用及其规划制定提供科学的决策依据     

基于交通运输成本的环鄱阳湖区“轴 辐”物流网络构建研究

针对湖域物流体系的特征,提出了基于交通运输成本的“轴 辐”物流网络分析思路,考虑到多种交通运输因素提出了科学测度综合分析方法。通过建立指标体系,得到分析结果确定物流网络各等级轴心城市,采用加权平均旅行时间测度时间成本,利用势能模型确定轴心辐射范围,构建环鄱阳湖区“轴 辐”物流网络体系。研究认为：环鄱阳湖区已形成以南昌市为一级轴心,九江市等5个县市区为二级轴心,其他县市区为三级轴心的物流网络;环鄱阳湖区物流网络呈现“一核五心”的运输成本空间格局;轴心城市之间已形成4条主要的物流轴线,二级轴心城市辐射范围与实际的地级市行政区划范围基本吻合,三级轴心城市辐射范围与各县市区的行政区划基本对应;环鄱阳湖区物流水平整体上呈现“北高南低、西强东弱、中部突出”的空间格局,并出现北部区域不均衡、东部部分区域较弱、南部整体较弱的情况     

Application of Neural Networks in Active Noise Reduction Systems

Active noise reduction systems based on a control unit in the form of a finite impulse response filter assume the linearity of every single component. Neural networks, which have so far been seldom used in this field, are a kind of a filter with the ability to project nonlinear characteristics of an active noise reduction system. This paper presents some simulation research studies of active noise reduction systems based on neural networks. Also presented are results of the operation of systems with different levels of complexity as well as the influence of different parameters of a neural network and of the system itself on those results.     

滇池水污染物浓度预测的人工神经网络模型

本文针对滇池日益严重的水污染现状,根据云南昆明西苑隧道断面2004年-2010年的监测资料,建立了基于BP神经网络的主要污染指标预测模型,并对其进行训练检验,研究结果表明：独立样本中pH、溶解氧、氨氮、高锰酸盐浓度的预测值与监测值的线性相关系数分别为0．952、0．967、0．945、0．936。结果证明该模型预测精度满足要求,通过准确地预测湖泊水污染物可以为治理湖泊营养化和综合利用水资源、规划管理、决策提供重要的科学依据。