湖泊水质监测布点优化

本文对湖泊监测布点优化的方法是主成分分析法、分层抽样法.经过对原监测点聚类、分层抽样、测点可靠性检验的程序,得到了客观表征污染物分布特征及总体污染水平的优化测点.     

主成份分析在大气测点优化研究中的应用

本文利用乌鲁木齐市大气环境质量历年监测统计资料,用主成份分析、模糊相似优先比法,对大气测点进行了优化研究,获得了代表乌鲁木齐市大气污染浓度水平和分布特征的优化测点。     

武汉市城区大气监测优化布点研究

对武汉市城区网格布点实测ＴＳＰ、ＳＯ２获取了城区大气污染总体水平的数据，运用Ｆｉｓｈｅｒ最优分割方法，求出城区５个优化测点数，运用模糊聚类方法对武汉城区４８个网格测点的ＴＳＰ、ＳＯ２污染强度置信水平进行聚类；运用日均值和百分位数逼近方法检验；结合优化布点原则等，最终确定的ＴＳＰ、ＳＯ２的５个优化测点能集中反映城区大气环境中ＴＳＰ、ＳＯ２的总体污染水平。     

南京市区域环境噪声监测方案的优化

目前,国内通常采用的城市环境噪声普查方法是网格布点、大样本一次性测量。南京市自1980年开始开展这项工作,按规范以500×500米网格城区布设测点205个,每年各测点昼,夜分别监测一次约8分钟,计算各测点等效连续A声级的算术平均值(以下简称网格平均声级Leq)。鉴于噪声传播的随机性、局限性,各测点的监测数据反映的仅是测点附近某一时段的噪声状况,而并非该网络0.25km~2的年度噪声水平,因而普查结果所表明的主要是全市环境噪声总体统计结果及分布规律。然而这些信息又是城市环境质量评价、管理、各城市间宏观声环境的比较所必不可少的,环境部门必须定期耗费大量人力物力完成此项工作。     

沈阳市大气监测站点优选方法研究

2. 优选原则 ① 多项污染指标综合优选原则:对测点中的TSP、SO_2、NO_x、CO四项污染指标同时进行综合优选。对超标严重的污染物给予优先考虑的权重。②优选出来的测点其数据要与历年全市各功能区测点的平均值具有一定可比性。     

环境噪声场图在环境噪声监测中的应用

环境噪声的“污染图”应是连续分布的噪声物理场.故可以根据各测点的分贝值的大小,勾画出测区噪声场强度分布图,即环境噪声场图(或环境噪声分贝等值图).该图     

紫外光诱导荧光分析仪结合多元线性回归算法在城市河流常规污染指标监测中的应用

为建立一种针对城市河流水体常规污染指标的快速原位监测方法,首次运用紫外光诱导荧光分析仪对扬州市60条城市河流进行水体三维荧光光谱(EEM)测量,形成了具有多样性的水质样本集合。利用峰值拾取法、相关性分析和主成分分析3种方式从三维荧光光谱中提取溶解性有机物(DOM)污染信息,结合多元线性回归算法(MLR),建立与化学需氧量(COD_Cr)、高锰酸盐指数(I_Mn)、氨氮(NH₃-N)和总磷(TP)4项常规水质污染指标相关的预测模型。研究结果表明,峰值拾取法结合相关性分析可以有效地反映水体EEM中的污染特征和状况,由此建立的4项水质指标预测模型训练集决定系数均>0.82,预测结果与国家及行业标准方法分析值之间具有较低的均方根误差,说明该预测方法具有较好的准确度和精密度,为城市广域水体的高效、原位监测提供了一种有效的解决方案。     

土壤重金属污染生态风险评价方法综述

生态风险评价是风险论与生态学、环境科学、地学等多种学科相互交叉的边缘学科.以土壤生态系统为对象,介绍了目前已有的几类重金属污染生态风险评价方法,包括概念模型法、数学模型法、指数法、形态分析法、植物培养法等.指出根据研究目的与污染特性选择适当的评价方法,可以为土壤生态风险管理提供科学信息.     

国控城市大气测点确定方法——国家大气环境监测优化布点研究(三)

一、布点原则 1.能较全面地反映城市范围大气污染平均水平、污染状况的变化规律、污染浓度范围及分布规律; 2.突出反映城市所属类型的大气污染特点。重工业城市、高硫煤区、特异性污染地区、人口集中城市、旅游城市,对外开放城市等,在测点的选择上应有侧重; 3。结合城市规划、经济发展计划和能源利用情况布设测点,使之能相对稳定一段时期;     

优化布点的TOPSIS法研究

针对多目标系统的优化布点问题,尝试提出用改进的TOPSIS法研究水质环境监测点位的优化,并建立改进的TOPSIS法优化模型.实例分析表明,该方法充分利用了优化矩阵的信息,优选结果符合客观实际,可用于环境监测点位的优化布点.     

固定污染源监测断面的选择对流量测定的影响

监测断面的选择在废气污染源监测中起着相当重要的作用 ,在无法找到完全符合技术规范要求的监测断面时 ,以前常将监测断面选择在砖砌烟囱上的方法。通过实验 ,否定了该方法应用于测定废气流量较小的污染源的可行性 ,提出了应用于测定废气流量较小的污染源时 ,较为成熟的监测断面选择方案。     

Monitoring Studies of Augusta Bay Marine Waters

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a tunction of bme or as spatial function.In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of particular pollution indices. With the increase in the number of sampling points, the amount of data increases and examining the results and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Principal Component Analysis (PCA).The use of the PCA in this work has been applied to the analysis of twenty three different sampling points in three seasonal sampling cruises in the same year. This led to recognition of the influence and the localisation of wastewaters in the Augusta bay after measuring the water pollution parameters.The PCA made evident the difference between some sampling sites whose data were initially thought to be similar where the presence of hot industrial water discharge or urban wastewater determines the permanent water quality.Furthermore, it has allowed a choice of more significant parameters for monitoring programs and more representative sampling site locations.     

环境空气监测点位的管理办法

阐述了加强环境空气监测点位管理的重要性，指出了目前环境空气监测点位管理中存在的问题，提出设置监测点位时，既要考虑监测点的位置和数量，又要考虑监测点周围的人为活动、流动污染源、固定污染源和面源的影响。     

Spatial distribution and source identification of persistent pollutants in marine sediments of Hong Kong

A data matrix, obtained during a 3-year monitoring period (2007–2009) from 45 sampling sites in Hong Kong marine, was subjected to determine the spatial characterization and identify the sources of main pollutants. Indicator analyses indicated that polycyclic aromatic hydrocarbons (PAHs), nickel, manganese, and arsenic (As) were at safe levels. Five heavy metals (zinc, lead, cupper, cadmium, chromium (Cr)) were moderate to severe enrichment at some sites. Inner Deep Bay and Victoria Harbor were considered as hot spots for PAHs and the heavy metals, while Tolo Harbor was highly polluted by the heavy metals. Cluster analysis classified the 45 sampling sites into three groups, representing different pollution levels. Principal component analysis/factor analysis identified four principal components (PCs) and explained 84.9 % of the total variances, standing for persistent pollution, N factor, P and Cr factor, and As factor, respectively. Group A was highly polluted by persistent pollution, group B was the less polluted group, and subgroup B1 was less affected by PC3 and PC4 than subgroup B2. Group C, considered as the moderately polluted group, was greatly affected by N factor or persistent pollution, while subgroup C2 received more N pollution than subgroup C1.     

环境空气质量分析的实践与探讨

以丹东市环境空气质量分析为例对当前采用的环境空气质量分析方法的优缺点进行了评述,指出采用全市多点位平均值分析环境空气质量具有一定缺欠,它们的均值会平滑掉重污染点的监测峰值,反映不出城市应有的污染来;应把对重污染点的监测值的分析作为重点,辅以全市多点位的平均值,分析环境空气污染特征、变化规律,进而查找其污染原因,提出可行的减少或消除环境空气污染的措施和办法。     

珠江三角洲地区空气自动监控网络数据空间模拟适用方法

珠江三角洲地区已构建起区域性空气质量自动监测网络,由于初步建立的自动监控网络监测站点对整个区域而言极其有限,如以单离散数据形式发布则不能反映出区域空气污染的连续变化特征和全貌.对有限点位监测结果进行空间模拟研究才能满足反映区域性污染状况的需求.通过运用、比对、评价不同空间插值模型于自动监控网络离散站点的模拟应用,提出了珠江三角洲自动监控网络数据空间模拟适用方法.     

Multivariate Statistical Analysis of Meteorological and Air Pollution Data in the ‘Campo De Gibraltar’ Region, Spain

A complete statistical analysis of meteorological and air pollution data was carried out in the ‘Campo de Gibraltar’ region (in the South of Spain) from 1999 to 2002. This is a heavy industrialized area where, up to date, very few air pollution studies have been made. The main objectives of the study presented here have been the characterization of the meteorological and (gaseous and particulate) air pollution conditions in the area, and the relations between them. Multivariate statistical techniques, such as Principal Component Analysis (PCA), have been applied to the data. The results show that air quality in the area is highly dependent on meteorological conditions such as wind persistence and direction, dispersion capability of the atmosphere, and humidity content. On average, sulphur dioxide and nitrogen oxide air pollution, mainly caused by fuel-oil combustion and traffic, respectively, is not very high. However, an important number of exceedences of the limits established by the EU Directive 1999 for PM10 (particulate matter with a diameter less than 10 μm) have been observed in some points of the area. A significant percentage of these exceedences (about 22% on average) are likely caused by African dust intrusions, which usually take place from May to August. From gaseous and particulate air correlations, it seems that anthropogenic activities contribute with about 19% on average.     

Integrated Environmental Assessment of the Mid-Atlantic Region with Analytical Network Process

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account the interdependency among variables, the method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic Region of the United States, we were able to point out areas which were in relatively poor condition and/or vulnerable to future deterioration regarding various environmental aspects. The method offered an easy and comprehensive way to combine the strengths of conventional multivariate statistics (PCA) and decision-making science tool (ANP) for integrated environmental assessment.     

近岸海域区域环境质量综合评价体系构建及应用实例

建立了适用于我国现阶段海洋环境质量监测现状的基于水、沉积物和生物三大介质污染状况的近岸海域海洋环境质量综合状况评价体系,包括评价指标体系的选择、评价及等级分级标准的确定、评价流程的确定等内容。用所建立的综合评价体系对锦州湾海域进行了评价,评价结果表明,锦州湾海域总体状况较差,受到了严重污染,与锦州湾海域的实际污染状况相符,验证结果表明了该综合评价体系的适用性。     

Application of multivariate statistical techniques in the assessment of water quality in the Southwest New Territories and Kowloon, Hong Kong

The application of different multivariate statistical techniques for the interpretation of a complex data matrix obtained during 2000?C2007 from the watercourses in the Southwest New Territories and Kowloon, Hong Kong was presented in this study. The data set consisted of the analytical results of 23 parameters measured monthly at 16 different sampling sites. Hierarchical cluster analysis grouped the 12 months into two periods and the 16 sampling sites into three groups based on similarity in water quality characteristics. Discriminant analysis (DA) provided better results both temporally and spatially. DA also offered an important data reduction as it only used four parameters for temporal analysis, affording 84.2% correct assignations, and eight parameters for spatial analysis, affording 96.1% correct assignations. Principal component analysis/factor analysis identified four latent factors standing for organic pollution, industrial pollution, nonpoint pollution, and fecal pollution, respectively. KN1, KN4, KN5, and KN7 were greatly affected by organic pollution, industrial pollution, and nonpoint pollution. The main pollution sources of TN1 and TN2 were organic pollution and nonpoint pollution, respectively. Industrial pollution had high effect on TN3, TN4, TN5, and TN6.