Self-Organizing Maps for Integrated Environmental Assessment of the Mid-Atlantic Region

A new method has been developed to perform environmental assessment at regional scale. This involves a combination of a self-organizing map (SOM) neural network and principal component analysis (PCA). The method is capable of clustering ecosystems in terms of environmental conditions and suggesting relative cumulative environmental impacts of multiple factors across a large region. Using data on land-cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic region, the method was able to indicate areas that are in relatively poor environmental condition or vulnerable to future deterioration. Combining the strengths of SOM with those of PCA, the method offers an easy and useful way to perform a regional environmental assessment. Compared with traditional clustering and ranking approaches, the described method has considerable advantages, such as providing a valuable means for visualizing complex multidimensional environmental data at multiple scales and offering a single assessment or ranking needed for a regional environmental assessment while still facilitating the opportunity for more detailed analyses.     

村镇公共安全评价体系研究——以河北省沧州市南大港一分区为例

将环境承载力评价理论引入到农村公共安全研究中,根据农村公共安全环境承载力指标体系的构建原则,选取一级指标5个,二级指标10个,基于鱼骨图分析法建立村镇公共安全体系。结合统计软件SPSS,采用主成分分析法(PCA),对村镇公共安全体系进行排序,找出影响村镇公共安全水平的重要因子,为改善村庄公共安全风险提供了重要参考价值。结果表明:一分区各村公共安全承载能力差异较大,且基础设施承载因子和土地承载因子是影响村庄公共安全承载能力最重要因子,加大公共安全基础设施的投入、有效利用闲置土地,可以较好地提高村镇公共安全承载能力。     

运城市区秋冬季大气PM2.5中重金属污染特征及健康风险评估

为了解山西省运城市大气细颗粒物（PM_2.5）中重金属的污染特征和来源及其健康风险,于2020年10月15日—2021年2月14日对运城市大气PM_2.5样品进行连续采集,使用微波消解-电感耦合等离子质谱法（ICP-MS）分析了样品中的铬（Cr）、锰（Mn）、镍（Ni）、铜（Cu）、锌（Zn）、砷（As）、镉（Cd）和铅（Pb）等8种重金属元素的质量浓度。结果表明,采样期间,ρ（PM_2.5）平均值为78.96μg/m³,采暖季ρ（PM_2.5）为（79.84±43.79）μg/m³,高于非采暖季（76.54±23.97）μg/m³,采暖季和非采暖季ρ（PM_2.5）均值均超过《环境空气质量标准》（GB 3095—2012）中的二级标准。富集因子法分析表明,Ni、Cu、Zn、As、Cd和Pb的富集因子均高于10,其中Cd元素的富集因子平均值达到1.089,表明受人为污染影响严重。主成分分析结果表明,运城市区秋冬季大气中重金属主要有3个来源,分别为混合燃烧源、机动车尾气源、工业排放源。健康风险评价结果显示,经手口摄入暴露强度最大,呼吸吸入暴露强度最小,皮肤接触暴露强度居中;儿童在3种暴露途径的总暴露剂量高于成人,儿童重金属暴露风险高于成人。各途径的非致癌风险强度叠加值＜1,表明非致癌风险较小;但As、Pb的非致癌风险相对较高。4种重金属的呼吸吸入途径致癌风险程度排序为：As＞Cr＞Cd＞Ni,单种重金属的致癌风险（TR）值以及重金属的总致癌风险（R）值均＜10^-6,表明本研究中重金属不具有致癌风险。     

Calibration and uncertainty analysis of a simple model of silica-limited diatom growth in the Elbe River

A simple Lagrangian water quality model was designed to investigate the hypothesis of sporadic silica limitations of diatom growth in the lower Elbe River in Germany. For each fluid parcel a limited reservoir of silica was specified to be consumed by diatoms. The model's simplicity notwithstanding, a set of six selected model parameters could not be fully identified from existing observations at one station. After the introduction of prior knowledge of the ranges of meaningful parameter values, calibration of the over-parameterised model manifested itself primarily in the generation of posterior parameter covariances. Estimations of the covariance matrix based on (a) second order partial derivatives of a quadratic cost function at its optimum and (b) Monte Carlo simulations exploring the whole space of parameter values gave consistent results. Diagonalisation of the covariance matrix yielded two linear parameter combinations that were most effectively controlled by data from periods with and without lack of silica, respectively. The two parameter combinations were identified as the essential inputs that govern the successful simulation of intermittently decreasing chlorophyll a concentrations in summer. A satisfactory simulation of the pronounced chlorophyll a minimum in spring, by contrast, was found to be beyond the means of the simple model.     

Conceptual classification model for Sustainable Flood Retention Basins

The aim of this paper is to recommend a rapid conceptual classification model for Sustainable Flood Retention Basins (SFRB) used to control runoff in a temperate climate. An SFRB is an aesthetically pleasing retention basin predominantly used for flood protection adhering to sustainable drainage and best management practices. The classification model was developed on the basis of a database of 141 SFRB using the River Rhine catchment in Baden (part of Baden-Württemberg, Germany) as a case study. It is based on an agglomerative cluster analysis and is intended to be used by engineers and scientists to adequately classify the following different types of SFRB: Hydraulic Flood Retention Basin, Traditional Flood Retention Basin, Sustainable Flood Retention Wetland, Aesthetic Flood Retention Wetland, Integrated Flood Retention Wetland and Natural Flood Retention Wetland. The selection of classification variables was supported by a principal component analysis. The identification of SFRB in the data set was based on a Ward cluster analysis of 34 weighted classification variables. Scoring tables were defined to enable the assignment of the six SFRB definitions to retention basins in the data set. The efficiency of these tables was based on a scoring system which gave the conceptual model for the example case study sites an overall efficiency of approximately 60% (as opposed to 17% by chance). This conceptual classification model should be utilized to improve communication by providing definitions for SFRB types. The classification definitions are likely to be applicable for other regions with both temperate oceanic and temperate continental climates.     

Model reduction via principal component truncation for the optimal design of atmospheric monitoring networks

A numerically efficient methodology for the optimal design of monitoring networks aiming at the surveillance of accidental atmospheric release is proposed in this paper. In a realistic context, the design of such a network requires the knowledge of a database of potential dispersion accidents occurring in the domain of the study. An objective function measures the ability of a potential network to provide measurements in order to reconstruct any accidental plume taken from the database. In the optimisation of such cost functions with respect to networks, most of the computational time is spent in the evaluation of the function, especially if the accidents database is large. In this paper we show how to optimally reduce this database and how this affects the design via a mathematical expansion in the cost function. We introduce methods based on principal component analysis, which are rigorous when the cost function is of least-squares type. These methods are then tested and validated with success on the design of a radionuclides monitoring network to be deployed over France. This is the so-called Descartes network which will be operated by the French Institute for Radiation and Nuclear Safety. These techniques are then applied on Descartes to solve several issues that are computationally demanding, but are also of more general interest, such as: how should one sequentially deploy the stations of the network? How is affected the optimal network when other European potential radiological sources are taken into account?     

Measuring environmental degradation by using principal component analysis

The objective of the paper is to measure environmental degradation on the basis of some selected indicators by the application of a simple multivariate technique known as Principal Component Analysis. For this purpose the study considered six variables, namely, GDP per capita, fuel consumption, total fertility rate, water supply, sanitation, and electricity. However, because of unavailability of data, the variables such as technology relating to environment, waste disposal, air pollution, women/gender issues relating to environment, corruption, democracy etc. could not be considered. The results show that principal components explain about 62% of the variations in the level of environmental degradation. The variables like GDP per capita, fuel consumption, water supply and electricity played a major role in classifying the countries in terms of environmental degradation compared to the variables, sanitation and total fertility rate. The findings show that countries which have high GDP per capita, low fuel consumption, higher percentage of people having access to water supply and sanitation as well as electricity ranked higher in terms of environmental quality despite high fertility rate as shown by the spectacular example of Saudi Arabia. By contrast, those countries which have low percentage of population having access to safe water and sanitation as well as electricity, high fuel consumption and high fertility were ranked lower in terms of environmental quality despite high per capita income, as shown by the example of Angola which is placed in lowest position among the 51 selected countries. The results also show that correlation between poverty and environmental degradation is particularly acute in African countries where high population growth is acting as an exacerbating factor. The study concluded that high fertility has much impact on environmental degradation in case of poorer countries than in case of rich countries.

Throughfall chemistry in a spruce chronosequence in southern Poland

The chemical composition of throughfall and canopy leaching, as well as the acid neutralizing capacity and alkalinity depended on the age of Norway spruce (Picea abies Karst) stands and season of the year. A higher amount of sulphur and strong acids was deposited to the soil in the older age classes. Concentrations of SO(4)(2)(-), K(+), H(+), Mn(2+), Fe(2+) and Zn(2+) in throughfall were higher than in bulk precipitation in any season. This suggests that these ions were washed out or washed from the surface of needles and/or barks. The other ions NO(3)(-), NH(4)(+), Ca(2+) and Mg(2+) were retained by the canopy, in particular Ca(2+) and Mg(2+) during the growing season in young stands. Principal component analysis identified five factors responsible for the data structure and suggested the major anthropogenic emission sources were acidic emission (SO(4)(2)(-)+NO(3)(-)), heavy metals-dust particles (Fe(2+)+Mn(2+)+Zn(2+)), ammonium (NH(4)(+)) and H(+), while the natural-origin emission was mineral dust (Na(+)+K(+)+Ca(2+)+Mg(2+)).     

A multivariate statistical analysis of surface water chemistry data--the Ankobra Basin, Ghana

R-mode hierarchical cluster and principal component analysis (PCA) were simultaneously applied to surface water hydrochemical data from three different locations, Ankwaso, Dominase and Prestea, along the Ankobra Basin, Ghana, to extract principal factors corresponding to the different sources of variation in the hydrochemistry, with the objective of defining the main controls on the hydrochemistry at the basin scale. Using the Kaiser criterion, principal components (PC) were extracted from the data and rotated using varimax normalization, for each location. The varimax rotation ensured that variation in the data was maximized for easy interpretation of the results. The analysis reduced 30, 33 and 33 data points, respectively, for Ankwaso, Dominase and Prestea to four, three and four PC representing the sources of variation in the hydrochemistry at the three different locations. Though the PC analysis proved to be more robust at unveiling the sources of variation in the hydrochemistry than the R-mode hierarchical cluster analysis (HCA), the combined use of both techniques resulted in more reliable interpretations of the hydrochemistry. On the basis of these analyses, the hydrochemistry of the basin is controlled largely by the weathering of minerals (silicates, carbonates, gypsum and apatite) from the underlying meta-sediments of the Birimian and Tarkwaian Systems, and the decay of organic matter from the heavily forested regions. Concentrations of the major chemical parameters are within naturally acceptable limits and do not pose threats to the local ecology and humans. There is no strong evidence of high anthropogenic impacts on the major anions and cations used for this research, though there are variations at the different locations studied. The hydrochemistry at Ankwaso is principally controlled by the weathering of silicate minerals, whereas those of Dominase and Prestea are, respectively, influenced by precipitation and domestic wastewaters, and the decay of organic matter.     

混凝反应中确定影响因素影响力大小的研究

该文在对合成洗涤剂废水进行混凝反应实验基础上,针对影响因素影响力大小的不同问题,使用主分量分析方法。对输入输出权矩阵进行处理和分析,对各影响因素影响力大小顺序进行了研究。分析结果表明,跟传统经验吻合较好,更重要的是对影响因子赋权方面提供了有力的理论依据,对混凝反应的理论分析于实验设计提供了新的思路。