天津市大气环境监测数据的主成分分析

本文采用主成分分析法分析了天津市大气环境监测数据,得到两个主成分;环境质量主成分和风沙主成分;根据主成分点图,将一年分成３个阶段;采暖期,非采暖期和风沙期。     

Spatial error propagation when computing linear combinations of spectral bands: The case of vegetation indices

The collection of accurate and timely information on land use, crops, forest and vegetation are increasingly based on remote sensing spectral measurements produced by satellites. The most recent spacecrafts like the Earth Observing 1 (EO-1) produce a rich source of information being endowed with hyperspectral sensors that can provide up to 200 or more channels. In many instances such a multivariate signal has to be reduced to just one single value per pixel representing a particular characteristic of land. Linear combinations of bands are the general form of many indices. Since each individual image used to construct indices contains errors, when combined they produce a propagation of errors, a process that can distort a final output map. In this paper we measure the extent of error propagation when building linear vegetation indices. We consider three types of indices: the difference vegetation index (DVI), selected Kauth-Thomas indices (SBI, GVI and WET), and principal components, using benchmarking examples taken from the remote sensing literature. The main implication emerging from these examples is that the SBI and the first principal component are the indices more prone to error propagation. The formalization presented here allows a user to derive measures of error propagation in cases where technical characteristics of a sensor and physical characteristics of a landscape are known. These results can help a user to choose between alternative vegetation indices, and to associate a measure of reliability with such indices.     

不同甘蔗基因型光合特性的数值分类

对30个甘蔗基因型光合性状进行数值分类、主成分、聚类和判别分析研究认为，甘蔗基因型间光合性状存在较大差异；利用主成分分析选出3个主成分，方差累计贡献率达到98．5％，蒸腾速率、气孔导度为第一主成分的主导因子，而净光合速率和气孔导度分别为二、三主成分的主导因子；经系统聚类将30个基因型分为三大类，在聚类分析基础上用判别分析选出对甘蔗光合性状数值分类有显著影响的4个光合参数，建立3个判别能力较高的判别模型．表5图1参22     

武汉市青山区道路尘碳组分污染特征及来源分析

为研究武汉市道路尘中碳组分污染特征及来源,于2018年5月在武汉市青山区采集道路尘样品,用热光碳分析仪测定样品中有机碳(OC)、元素碳(EC)、烟炱(soot)和焦炭(char)含量,并使用特征比值法、相关分析及主成分分析法对道路尘碳组分污染特征和来源进行探讨分析.结果表明,道路尘中OC、EC、soot和char含量平...     

基于主成分分析的中国南方干旱脆弱性评价

干旱脆弱性是干旱灾害形成的根本原因。遵循全面性、系统性和可操作性原则,选取水资源脆弱性、经济脆弱性、社会脆弱性、农业脆弱性和防旱抗旱能力脆弱性5个准则层,共32个指标,建立了中国南方农业干旱脆弱性评价指标体系,运用主成分分析的理论方法确定评价指标权重,建立中国南方地区的干旱脆弱性评价模型,得到不同省市的干旱脆弱性指数、分级阈值和区划,以期为南方地区防旱减灾工作提供基础数据和理论支持。得出以下结论,（1）通过主成分分析法得到四个主成分,第一主成分方差贡献率为54.90%,主要反映农业脆弱性和社会脆弱性;第二主成分方差贡献率为23.64%,主要反映水资源脆弱性和经济脆弱性;第三主成分和第四主成分所占比重较小,主要反映防旱抗旱能力脆弱性。（2）以4个主成分的方差贡献率为系数建立南方干旱脆弱性评价模型,得到中国南方干旱脆弱性综合评价得分及其排名,其中水资源脆弱性由高到低依次为云南、广西、贵州、四川、重庆和广东;经济脆弱性由高到低依次为广西、云南、贵州、四川、重庆和广东;社会脆弱性由高到低依次为贵州、云南、广西、重庆、四川和广东;农业脆弱性从高到低依次为贵州、云南、广西、重庆、四川和广东;防旱抗旱能力脆弱性由高到低分别为云南、贵州、四川、广西、重庆和广东;干旱脆弱性综合评价由高到低依次为云南、贵州、广西、四川、重庆和广东。（3）对干旱脆弱性指数进行正态分布性检验,发现该指数基本服从正态分布。根据正态分布原理,得到干旱脆弱性分级阈值,将干旱脆弱性指数小于0.3842定义为低风险,大于1.0758定义为高风险,介于两者之间的定义为中等风险,获得干旱脆弱性分级区划图。广东省位于干旱的低脆弱区,四川和?     

自然保护区管理有效性评价指标分析

根据154个国家级自然保护区的问卷调查结果,运用主成分分析法对26项管理评价指标进行分析,确定了影响保护区管理有效性的6个主要指标类体系。其结果表明:对管理有效性产生较大影响的主成分包括:物资保障、监控管理、经济开发收益、管理权归属、行政执法和交流合作。6个主成分对于管理有效性的贡献率比较分散,累计贡献率为68.671%;其中物资保障主成分贡献率最大,达26.011%。     

Ozon in Waldökosystemen aus atmosphärenchemischer und pflanzenphysiologischer Sicht

The trend of rising ozone concentrations in forest ecosystems and the phytotoxicity of ozone demand a realistic risk assessment according to an internationally accepted and flux-based quality standard. Ozone fluxes within the canopy are influenced by chemical gas-phase reactions with nitrogen oxide and biogenic hydrocarbons and by surface deposition processes. Therefore, a differentiation of the ozone flux within the canopy is needed between stomatal uptake and other transport pathways. The Eddy Covariance technique is the method of choice for the determination of trace gas fluxes relevant for ozone chemistry. This method is also used for stomatal conductance measurements based on evapotranspiration fluxes and for emission measurements of biogenic hydrocarbons by PTR-MS. Although considerably research efforts were directed to canopy measurements in recent years, the underlying processes are not fully understood yet. Thus, major differences occur in the ratios of stomatal ozone uptake, non-stomatal deposition and gas-phase chemistry between different studies. Furthermore, the vertical concentration gradients within the canopy measured at several forest sites are rather inconsistent and the existing deposition models do rarely account for chemical transformation and detoxification processes. Only a simultaneous measurement of all photochemically relevant trace gases, plant physiological parameters at different sites and forest species over entire vegetation periods, and model parameterization according to the measurement results from the experimental sites will contribute to the clarification of the canopy processes and will ensure realistic risk assessments.     

玉米/花生间作条件下土壤环境因子的相关性和主成分分析

玉米/花生间作具有明显的间作优势,对作物生长和产量均有促进作用。为了阐明玉米/花生间作效应机制,测定了玉米/花生间作根际土壤养分含量、酶活性和微生物数量的变化规律,并对这些环境因子进行相关性和主成分分析。结果表明,与单作玉米和单作花生相比,玉米/花生间作显著提高了根际土壤的全氮、有效氮、有效磷含量以及脲酶和酸性磷酸酶活性,促进了间作玉米根际土壤细菌和微生物总数量显著增加。相关分析表明,有效磷含量与脲酶和酸性磷酸酶活性呈极显著正相关(P<0.01),脲酶活性和酸性磷酸酶活性显著正相关(P<0.05),真菌和放线菌数量显著正相关(P<0.05)。总钾含量和p H值、蔗糖酶活性呈显著负相关(P<0.05),蛋白酶和过氧化氢酶呈极显著负相关(P<0.01)。主成分分析获得3个主成分,解析贡献率分别为48.981%,43.617%和7.402%。第一主成分主要是放线菌、真菌、有效磷等组成,第二主成分主要为有机质和p H,第三主成分主要是总氮和细菌。经标准化后计算栽培措施得分显示:间作花生得分最高1.937,其次是间作玉米1.008,两者均显著高于单作玉米和单作花生。该研究表明玉米/花生间作系统的生态环境优于单作系统,机制解析为玉米/花生间作可明显促进土壤有效氮磷含量、脲酶和酸性磷酸酶活性及微生物数量的增加,进而改善土壤微生态环境。     

广州市空气污染物和气象要素的主成分与典型相关分析

用主成分和典型相关分析方法分析广州市近4a(2001—2004年)的空气污染物与气象要素之间的关系,按夏半年、冬半年和全年3个时间尺度分别进行。结果表明:污染物数据所得到的主成分分别代表机动车污染源(汽油燃烧和扬尘)和工业污染源(工业燃煤和燃油),气象数据的主成分分析表明空气的温度、湿度及对流速度对空气污染作用明显,而污染物和气象要素的主成分分析表明气温高低和空气干湿程度对大气污染的影响较大。污染物与气象要素两组数据之间的典型相关分析表明污染物与气象要素之间存在显著的相关关系,其中温度和风速对气态污染物有显著影响。     

典型铜尾矿库周边土壤重金属复合污染特征

应用了Hakanson潜在生态风险指数法、相关分析法、主成分分析法对德兴铜矿尾砂库周边土壤Cu、Zn、Ni、Pb、Cr和Cd复合污染特征进行研究,定量确定了铜尾矿库潜在生态风险程度、主要污染因子和潜在生态风险因子。结果表明:铜矿尾矿库周边土壤受到不同程度的重金属污染,该地区平均潜在生态风险污染指数超过600,具有极高的潜在生态风险;各重金属潜在生态风险参数由高至低顺序为Cd、Cu、Pb、Ni、Cr、Zn,其中Cd为主要潜在生态风险因子。进一步通过主成分分析法研究了重金属的污染特性,发现前3个主成分贡献率分别为:65.033%、18.825%、6.243%,第一主成分反映了Zn、Ni、Cr的信息,第二主成分反映了Cu和Cd的信息,第三主成分反映Pb的信息。     

Testing ecological models: the meaning of validation

The ecological literature reveals considerable confusion about the meaning of validation in the context of simulation models. The confusion arises as much from semantic and philosophical considerations as from the selection of validation procedures. Validation is not a procedure for testing scientific theory or for certifying the ‘truth’ of current scientific understanding, nor is it a required activity of every modelling project. Validation means that a model is acceptable for its intended use because it meets specified performance requirements.Before validation is undertaken, (1) the purpose of the model, (2) the performance criteria, and (3) the model context must be specified. The validation process can be decomposed into several components: (1) operation, (2) theory, and (3) data. Important concepts needed to understand the model evaluation process are verification, calibration, validation, credibility, and qualification. These terms are defined in a limited technical sense applicable to the evaluation of simulation models, and not as general philosophical concepts. Different tests and standards are applied to the operational, theoretical, and data components. The operational and data components can be validated; the theoretical component cannot.The most common problem with ecological and environmental models is failure to state what the validation criteria are. Criteria must be explicitly stated because there are no universal standards for selecting what test procedures or criteria to use for validation. A test based on comparison of simulated versus observed data is generally included whenever possible. Because the objective and subjective components of validation are not mutually exclusive, disagreements over the meaning of validation can only be resolved by establishing a convention.     

Etude du cycle annuel des Chaetognathes planctoniques de la rade de Villefranche par la méthode d'analyse des composantes principales

The study of the cycle of chaetognaths during 1967 was carried out using samples collected with a Juday-Bogorov net at 1 station in the entrance of the bay by vertical hauls (75 m-0 m). Among the 13 sorted categories of chaetognaths, the principal component analysis singles out 2 communities (made up from the abundant species) and 3 isolated species. The first 3 components carry 71.1% of the total variance. An attempt to identify components, using partial correlations, shows that the first component is a trophic relation, the second the vertical stability of the water, the third a factor of development of young stages. The correlation between the physical and biological factors and the components account for 45% of the total information.     

Combining data and simulated data for space–time fields: application to ozone

This paper presents a theory for modeling random environmental spatial-temporal fields that allows simulated data (numerical-physical model output) to be combined with measurements made at fixed monitoring sites. That theory involves Bayesian hierarchical models that provide temporal forecasts and spatial predictions along with appropriate credibility intervals. A by-product is a method for re-calibrating the simulated data to bring it into line with the measurements for certain applications. While the approach covers a broad domain of potential applications, this paper addresses a field of particular importance, ground level ozone concentrations over the eastern and central USA. A univariate model is developed and illustrated with hourly ozone fields. A multivariate alternative is also provided and illustrated with daily concentration fields. The forecasts and predictions they provide are compared with those from other approaches.     

夏季渭河西安段溶解性有机质(DOM)的特征、分布及来源分析

通过紫外吸收光谱,三维荧光光谱结合平行因子分析(EEMs-PARAFAC)方法及主成分分析(PCA),研究了夏季渭河西安段水体中的溶解性有机质(DOM)的组成、来源,及其与水质指标的相关性.在研究区域共检出2种类别5个不同的DOM组分,分别为类腐殖质荧光组分C1、C2、C3、C5和1个类蛋白类荧光组分C4,5个组分具有...     

SPACSYS: Integration of a 3D root architecture component to carbon, nitrogen and water cycling—Model description

It is an ongoing challenge to develop and demonstrate management practices that increase the sustainability of agricultural systems. Soil carbon and nitrogen dynamics directly affect soil quality, crop productivity and environmental impacts. Root systems are central to the acquisition of water and nutrients by plants, but are also a major pathway for the inputs of carbon and nutrients to soil. The complexity of both biotic and abiotic interactions, combined with stochastic changes in root architecture, makes it difficult to understand below-ground dynamics on the basis of experimentation alone. The integration of dynamic models of above-ground growth, three-dimensional root system demography, and interactions between plants and the environment, into one single model is a major challenge because of the complexity of the systems.In order to understand the interaction between a plant and the environment, it is advantageous to develop a model framework to integrate submodels that simulate various plant and environmental components. The objective of this paper is to outline a mechanistic and process-based model, which is capable of simulating interactions among environmental conditions around plants, plant growth and development, nitrogen and carbon cycles, with a three-dimensional root system submodel as an interface.The model presented in this paper is a mixed dimensional, multi-layer, field scale, weather-driven and daily time-step dynamic simulation model. The current version includes a plant growth and development component, a nitrogen cycling component, a carbon cycling component, plus a soil water component that includes representation of water flow to field drains as well as downwards through the soil layers, together with a heat transfer component. The components themselves and linkage among components are designed using object-oriented techniques, which makes the model robust, understandable and reusable. The components are implemented in the C++ programming language, and inputs and outputs of all components are organised as a database in either Microsoft^® SQL Server 2000, Access 2000 or MySQL5.0. Root architecture is visualised by using the OpenGL graphics system. Preliminary validation with two separate experimental datasets shows that the model can reasonably simulate root systems, nitrogen cycling, water movement and plant growth.     

新疆博格达山北坡表土花粉散布特征

基于博格达山北坡68个表土样品花粉组合特征,对比植物群落样方调查结果,借助聚类分析、主成分分析方法,探讨了表土花粉组合与现代植被分布的关系。研究表明,(1)博格达山北坡表土花粉可划归5个不同植被带,湿度是影响其分布的主要因素,藜科(Chenopodiaceae)、蒿属(Artemisia)、云杉属(Picea)花粉分布受气流影响显著,忽略它们对其他植被带花粉组合的干扰,表土花粉与现代植被分布对应良好。各植被带均有其特有的花粉组合方式,山地荒漠带藜科-蒿属组合占绝对优势,山地草原带演替为蒿属-藜科-禾本科(Poaceae)-蔷薇科(Rosaceae)组合,山地森林带以云杉属-桦木属(Betula)-蒿属-藜科-禾本科为主,高山草甸带以蒿属-云杉属-藜科-莎草科(Cyperaceae)组合为特征,高山垫状植被带表现为蒿属-藜科-蔷薇科-云杉属组合。(2)草本植物花粉含量(62.7%)优势明显,乔、灌木(37.3%)次之。蒿属(23.1%)、藜科(21.5%)、云杉属(18.1%)、莎草科(9.4%)、禾本科(8.6%)、桦木属(5.7%)、蔷薇科(5.3%)等科(属)含量高、变幅大,为最主要的花粉类型,可作为古气候研究的重要依据,藜科、蒿属产量大、易传播,表现出超代表性,云杉属代表性较好,莎草科则受自身结构及保存条件等多重因素影响呈低代表性。(3)蒿属/藜科(A/C)比值不仅能将山地荒漠带、山地草原带区分开,还能指示研究区域湿度变化,古环境重建时可作为区域有效湿度的代用指标。     

基于高光谱技术的土壤镉污染分级评价研究

提出一种利用高光谱技术进行土壤镉污染分级评价的方法。以FieldSpec 3地物光谱仪采集厂矿区土壤光谱反射率175份,随机分成校正集（135份）和检验集（40份）。光谱经小波去噪和标准归一化（SNV）处理后,以主成分分析法（PCA）降维。将降维所得的前5个主成分数据为输入变量,分别采用Fisher线性判别、Byes逐步判别、模糊模式识别、BP-ANN判别以及SVM 5种方法建立了土壤镉污染分级评价模型,并利用40个未知样对模型进行检验。结果表明：Fisher线性判别准确率为77.5%,Byes逐步判别与模糊模式识别预测为80.0%,BP-ANN模型预测精度为82.5%,SVM模型预测精度最高,达85.0%。说明采用高光谱技术进行土壤镉污染分级评价是可行,其中SVM是建模的优选算法。     

Beurteilung des Ozonrisikos für die Waldregionen Bayerns am Beispiel des Jahres 2002 und des Extremtrockenjahres 2003 auf der Basis der externen Ozonexposition und der internen Ozonaufnahme

Background, aim, and scope Increasing background concentrations of ground-level tropospheric ozone and more frequent and prolonged summer drought incidences due to climate change are supposed to increase the stress on Bavarian forests. For such scenarios growth reduction and yield losses are predicted. Sustainable forest management in Bavaria aims to significantly increase the proportion of beech (Fagus sylvatica L.) because of its broad ecological amplitude. In our regional study different approaches for calculating ozone impact were used to estimate the risks for Bavarian forests in the average climatic, rather moist year 2002 and the extremely dry year 2003.Materials and methods Measurements were conducted for eleven forest ecosystem sites and two forest research sites representing typical Bavarian forest stands under different climatic conditions and situated in different altitudes. For risk assessment currently used approaches were applied either based on the calculation of the cumulative ozone exposure (external dose; MPOC maximal permitted ozone concentration; critical level AOT40_phen? accumulated ozone exposure over a threshold of 40 nl [O₃] l^–1, for the effective phenolgy of beech) or based on the calculation of the phytomedically relevant ozone flux into the stomata (internal dose, critical level AF_st>1,6, accumulated stomatal flux above a flux threshold of 1.6 nmol O₃?m^–2 PLA; PLA = projected leaf area). For calculations continuously recorded ozone concentrations and meteorological and phenological data from nearby rural open field background measuring stations from the national air pollution control and from forested sites were used. Additionally ozone induced leaf symptoms were assessed.Results The exposure-based indices AOT40_phen and MPOC as well as the flux-based index AF_st>1.6suggest that Bavarian forests are at risk from O₃ during a rather moist average year concerning climate conditions (2002) as well as in an extreme dry year (2003). Thus, growth reductions of 5?% are predicted when thresholds are exceeded. Threshold exceedance occurred in both years at all plots, mostly already at the beginning of the growing season and often even many times over. Ozone induced leaf symptoms could be detected only on a few plots in a very slight occurrence.Discussion The results for the applied critical level indices differed depending on climatic conditions during the growing seasons: Regarding exposure-based indices, the highest degree of threshold exceedance occurred in the dry year of 2003 at all plots; the flux-based approach indicated the highest stomatal ozone uptake and thus an increased risk at moist sites or during humid years, whereas the risk was decreasing at dry sites with prolonged water limitation. Hence, soil and accordingly plant water availability was the decisive factor for the flux-modelled internal ozone uptake via stomata. Drought and increased ozone impact can generate synergistic, but also antagonistic effects for forest trees. At water limited rather dry forest sites restricted transpiration and thus production, but concurrently lower ozone uptake and reduced risk for damage can be expected.Conclusions, recommendations, and perspectives For realistic site-specific risk assessment in forest stands the determination of the internal ozone dose via modeling flux based internal stomatal ozone uptake is more appropriate than the calculation of the external ozone dose. The predicted 5?% growth reductions are in discrepancy with the frequently observed increment increase during the last decades in forest stands. Comprehensive and significant statistical verification for ozone induced forest growth reduction as well as the systematic validation of thresholds for ozone in the field is still lacking. However, a multiplicity of different specific new and retrospective growth analysis data should allow closing the gap. Moreover, the determination of canopy transpiration with sap flow measurements is a novel approach to provide cause-effect related, site specific results for the effective internal ozone dose as well as for canopy water supply and consecutively for regional risk estimation. A further future objective is the refinement of O₃ flux modelling by further consideration of soil/water budget characteristics and the above mentioned improved estimations of crown and canopy transpiration. Further, the introduction of threshold ranges for forest trees in view of their specific regional climatic conditions and their validation in real forest stands is necessary for developing meaningful ozone risk predictions for forests.     

三峡库区高阳平湖水体富营养化主要驱动因子研究 ——基于主成分分析法

研究各种水质因子(水温、溶解氧、电导率、pH、营养盐等)对三峡库区支流水体富营养化的驱动效果,为库区支流水体富营养化的防控与治理提供科学依据.于2018年11月至2019年10月在三峡库区高阳平湖进行了12次样品采集,获取了水温、水体pH、营养盐、水体溶解氧等指标数据,利用主成分分析法研究三峡库区支流水体富营养化状况,...     

Monitoring sustainable agriculture in Southeast Asia

Monitoring agricultural sustainability requires careful summarising of indicators collected over time into indices representing facets of sustainability. When the number of variables exceeds the number of observations, interpretation of components from ordinary principal component analysis is usually difficult because of minimal or absence of sparsity among the loadings. This is also true for time series indicators that exhibit non-stationarity. A framework for the assessment of agricultural sustainability in a regional context is proposed. Sparse principal component analysis is used in constructing indices of agricultural sustainability that are then used to characterise the state of agricultural development and the dynamics of agricultural growth in Southeast Asia.