bluuebunny/crossref_metadata_2025 huggingface dataset:
Archaeological Chemical Analysis
Authors: Pollard A. Mark , Heron Carl
Published: September 2006

In recent years, archaeology has interacted more and more with the physical sciences. In particular, chemical analysis has been established as a significant contributor to science‐based archaeology. The principal applications include compositional analysis of natural and synthetic materials and residues to ascertain artifact manufacturing processes and use; chemical and isotopic studies of biological remains and identification of plant and animal residues to investigate ancient diet, nutrition, and resource use; the determination of geographical sources of procurement or production of materials to establish long‐distance contact or trade; and the processes governing preservation and decay of materials and scientific investigation in the context of conservation and restoration.

This article explores the role of chemical analysis in archaeology and highlights the importance of the findings in contributing to our understanding of the past. In particular, taking examples from the last 200 years, it demonstrates that chemical analysis of archaeological materials is not a routine application but one thatmust be informed by a thorough knowledge of the archaeological context, degradative processes, and material – environment interactions. Case studies span a wide range of elemental, isotopic, and molecular investigations with a bibliography comprising nearly 200 publications.
Ultrafast Laser Technology and Spectroscopy
Authors: Reid Gavin D. , Wynne Klaas
Published: September 2006

Ultrafast laser technology and spectroscopy involves the use of femtosecond (10
−15
 s) laser and other (particle) sources to study the properties of matter. The extremely short pulse duration allows one to create, detect and study very short‐lived transient chemical reaction intermediates and transition states. Ultrafast lasers can also be used to produce laser pulses with enormous peak powers and power densities. This leads to applications such as laser machining and ablation, generation of electromagnetic radiation at unusual wavelengths (such as millimeter waves and X‐rays), and multiphoton imaging. The difficulty in applying femtosecond laser pulses is that the broad frequency spectrum can lead to temporal broadening of the pulse on propagation through the experimental set‐up. In this article, we describe the generation and amplification of femtosecond laser pulses and the various techniques that have been developed to characterize and manipulate the pulses.
Microwave Techniques
Authors: Smith Frank , Xiong Guohua
Published: September 2006

A concise yet comprehensive review of the use of microwave‐assisted techniques for sample preparation in analytical chemistry is presented. A historical review of the development of the field is followed by summaries of the most significant theoretical principles, available instrumentation and safety considerations. The major part of the review concerns recent applications of the techniques to the preparation of a wide range of sample types. These include environmental, soil, biological, clinical, food, pharmaceutical, mineral, ceramic and industrial samples. Examples of microwave‐assisted drying and fusion of analytical samples are also given. Throughout, reference is made to the most important review articles. Where appropriate, original papers are summarized and cited.
Multivariate Image Analysis
Authors: Geladi Paul , Grahn Hans F.
Published: September 2006

Multivariate image analysis (MIA) is a methodology for analyzing multivariate images, where the image coordinates are position (two‐ or three‐dimensions) and variable number. Multivariate images can have typical sizes 1024 × 1024, 512 × 512, 256 × 256 etc. and have between two and many hundreds of variables. The variables can be wavelength, electron energy, particle mass and many others. Image analysis concentrates mainly on spatial relationships between pixels in a grey level image. MIA concentrates on the correlation of structure between the variables to provide extra information useful for exploring images and classifying regions in them. The many variables can be transformed into a few latent variable images containing condensed information. The sheer size of the data arrays necessitates visualization of raw data, intermediate data and analysis results.

All physical techniques for measuring materials can be made into imaging techniques, describing not only a property, but also its position in a plane or volume. All imaging techniques can be expanded to become multivariate. Multivariate imaging is used in three major fields: remote sensing, medical imaging and microscopy (including macroscopy). In microscopy it can be used to study materials and biological processes by optical, electron and charged particle techniques.
Analytical Problem Solving: Selection of Analytical Methods
Authors: Ullman Alan H. , Thorpe Thomas M. , Boutilier Glenn D.
Published: September 2006

This article of the Encyclopedia explains that analytical chemistry is problem solving and provides a systematic procedure to follow that will increase the likelihood of successfully providing a solution to the problem. The problem solving process is shown in a simple flow chart diagram with amplification in the text.
Spot Test Analysis
Authors: Jungreis Ervin
Published: September 2006

Sensitive and selective qualitative tests based on chemical reactions using small amounts of complex and reagents are referred to as “spot tests”. The target is to reach the utmost sensitivity and selectivity with a minimum of physical and chemical operations.

Rapid advances in spectral, chromatographic, nuclear, mass spectroscopic and electroanalytical research have changed analytical chemistry spectacularly and developed highly sophisticated analytical tools. At the same time another development has taken place in certain distinct areas of application in exactly the opposite direction. This is the search for simple, compact and inexpensive analytical devices for semiquantitative evaluation of certain elements or compounds where such approximate evaluation has diagnostic value at least in the first stage of examination.

Major manufacturers of chemical reagents concentrated their efforts mainly in a number of applicative areas, namely clinical analysis, forensic tests, air and water quality control (QC) tests and soil and food QC tests.

It must be emphasized that the applicability of spot test methodology is limited and for the exact determination of chemical substances, complex analytical procedures are unavoidable. Although the use of spot and screening tests is marginal, the margin, however, is quite significant.
Acid Rain Modeling
Authors: Holland David M. , Sirois Alain
Published: September 2006

This article provides an overview of existing statistical methodologies for the estimation of site‐specific and regional trends in wet deposition. The interaction of atmospheric processes and emissions tend to produce wet deposition data patterns that show large spatial and temporal variability. We conclude that a number of approaches are useful for trend estimation, but no one method is appropriate for all purposes.
Action Levels, Regulatory
Authors: van Ee Jeffrey
Published: September 2006

Environmental data are often collected to assess whether an action level or regulatory standard has been exceeded. If a statistician is involved in the decision‐making process, it is often at the latter stages when the data have already been collected and a comparison is needed; however, at times a statistician may not be involved. In either case, a major problem in making the comparisons is a lack of understanding of basic assumptions and principles that lie behind the important comparisons. The US Environment Protection Agency (EPA) has advanced for years the ‘Data Quality Objective’ (DQO) process to define better basic issues in the decision‐making process and to aid in communicating acceptable costs and errors in the decision‐making process between stakeholders. Although the DQO process is performance‐based and provides real opportunities for cost savings, it can be misinterpreted. A major problem occurs when the basic principles that underlie the setting of the action‐level or regulatory standard and the representativeness of the sample data for comparison purposes are not applied concurrently.
Adaptive Designs
Authors: Flournoy Nancy
Published: September 2006

In adaptive designs, study information is used during the experiment to alter treatment allocation probabilities. In this article, the term ‘treatment’ is used as it is generally used in the experimental design literature to reference
any
intervention. For example, in addition to interventions for improving health, treatments may be doses of a pesticide or other contaminant. Adaptive designs are natural when subjects, or other experimental units, arrive sequentially or in batches. Fully sequential designs, in which allocation decisions are updated after each observation, are the most efficient, but can be impractical when observations are delayed or when there are multiple locations for the experiment. Breaking the design into two or more stages provides a reasonable compromise in many cases; such designs are also adaptive.
Multivariate Adaptive Regression Splines
Authors: Kooperberg Charles
Published: September 2006

The multivariate adaptive regression splines (MARS) algorithm was developed by Friedman as a nonparametric method for multiple regression. The MARS algorithm uses adaptively selected spline functions. Because of its adaptivity MARS is often able to model functions that express high variation in one region of the predictor space and are smoother in other parts.
Added Risk
Authors: West R. Webster
Published: September 2006

Dose–response studies of environmental toxins are designed to determine the detrimental effects associated with exposure to the toxin, over a particular range of exposures. To properly quantify the toxic effect of a toxin, the
background risk
of no exposure to the toxin, R(0), must first be specified. The additional risk incurred by exposure to a dose,
d
, of the toxin is then called the added risk (AR) at this dose and is given by AR(
d
) = R(
d
) – R(0).
Air Quality
Authors: Swithenbank J. , Nasserzadeh V. , Goh Y.R.
Published: September 2006

The emission of pollutants from industrial processes has become a question of considerable public and scientific concern in the light of evidence of their extreme toxicity. The main problem with toxic emissions from combustion processes is the requirement for expensive gas cleaning systems to meet the increasingly stringent US and EC legislations. While the technology for the cleanup of particulate matter and acid gases is comparatively straightforward, it is the limitation of the emissions of dioxins, furans and heavy metals which is now of particular concern. Although the problem with heavy metals in the environment is due to their toxic effects on human health, it has been shown that in some cases organic heavy metal compounds are very much more toxic than inorganic species.
Air Quality Indicators, Pollutant Specific
Authors: Hunt William F.
Published: September 2006

Pollutant‐specific air quality indicators can be extremely useful in communicating environmental information to the public, air pollution control officials, the private sector, governmental officials and regulators, and academia. Indicators are needed to translate environmental data into a form that is readily understood. An indicator must be able to translate complex information into a form that is readily understood by decision‐makers, as well as by laymen. To accomplish this, this article will examine the use of US National Ambient Air Quality Standard (NAAQS) related pollutant‐specific air quality indicators. These air quality indicators can play an important communications role in examining air trends, compliance status, and the overall effectiveness of environmental policies/regulations.
A
merican
S
ociety for
T
esting and
M
aterials
Authors: Esterby S.R.
Published: September 2006

The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.
Ames Assay
Authors: Margolin Barry H. , Kim Byung‐Soo
Published: September 2006

Who would have thought that
Salmonella
bacteria, the very same strains that are the bane of travelers, would also contribute to human health via their use in bioassays for genetic mutation? Developed by Ames and colleagues in the early 1970s, the Ames assay continues to hold a preeminent position in genetic toxicology. Its applications have grown increasingly diverse, ranging from attempts at cancer prediction to screening of industrial byproducts for possible mutagens. The assay is currently conducted in thousands of laboratories worldwide. The Ames assay has produced a wealth of experimental data over the last two decades. During the same period many authors have proposed mechanistic models for the analysis of Ames data. Much of this modeling, based on radiation ‘hit theory’, derives from the work of Haynes and Eckardt.
Aquatic Toxicology
Authors: Bailer A. John , Oris James T.
Published: September 2006

Aquatic toxicology is the study of poisons in freshwater and marine environments. As a field of formal study, aquatic toxicology is relatively new in the larger field of environmental toxicology and has borrowed heavily from the methods and procedures of mammalian toxicology. Thus, many environmetric developments and issues are common among aquatic, mammalian, and environmental toxicology. There are, however, several features of aquatic toxicology that bring unique problems to the field. First and foremost is the fact that a main goal is the protection of a wide variety of habitats and organisms, encompassing all known phyla. Humans can be a focus (e.g. drinking water standards), but they are often considered rather as just one of many organisms in a particular ecosystem. In aquatic toxicology, therefore, statistical issues arise at the individual, population, community, and ecosystem level.
Artificial Intelligence
Authors: Hand David J.
Published: September 2006

Artificial intelligence (AI) is a product of the computer age. Although people have fantasized about making intelligent creations since the dawn of time, until the latter half of the twentieth century the motive power for these creations was magic. Machines such as Babbage's Analytical Engine suggested that a mechanical solution might be feasible, but limitations in precision manufacturing prevented this from getting very far. It was not until the advent of electronics and the computer that researchers began to see that the dream might one day be a practical reality, and now progress towards genuine thinking machines has begun to occur.
Atmospheric Dispersion: Basic
Authors: Mikkelsen Torben
Published: September 2006

This entry provides a discussion of the most important meteorological and atmospheric phenomena that influence air pollution from a single source. Emphasis is given to dispersion and its physics in the near range (0–20 km). The article focuses on meteorological phenomena that have significance for both regulatory design, accidental release and for emergency management.
Atmospheric Dispersion: Complex Terrain
Authors: Egan Bruce A. , Snyder William H.
Published: September 2006

Atmospheric dispersion processes in complex terrain are generally more complicated than flows over simple, homogeneous, relatively flat terrain. This is because the nonhomogeneity of the terrain not only alters the airflow fields and the turbulence (diffusion intensities) in both the horizontal and vertical directions, but it also affects the consequences of solar heating and radiative cooling on the development of local circulations and flows. Although important over homogeneous terrain, the vertical profiles of wind velocity and temperature are even more important factors when considering complex terrain.
Attributable Risk
Authors: Benichou Jacques
Published: September 2006

Attributable risk (AR) was initially introduced by Levin as a measure to quantify the impact of smoking on lung cancer occurrence. Gradually, it has become a widely used measure to assess the consequences of an association between an environmental exposure factor and a disease at the population level.
BACI
Design
Authors: Smith Eric P.
Published: September 2006

The purpose of impact assessment is to evaluate whether or not a stressor has changed the environment, which components are adversely affected and to estimate the magnitude of the effects. The evaluation of impact involves comparative methods. Early approaches to impact assessment involved the use of computer simulation models to predict the impact. Decisions were then made based on the soundness of those predictions. Although the data used to interpret effects are quite varied, the methods for analysis are often quite similar and involve comparison of impact areas with control areas. When information is available prior to the potential impact, the design is often referred to as a Before–After Control‐impact (BACI) design. Several variations on the basic design have been proposed and are discussed in this article.
Benchmark Analysis
Authors: Crump Kenneth
Published: September 2006

The benchmark approach is a statistical procedure applied to dose–response data from toxicologic, clinical or epidemiologic studies. It can be used to set health standards or guidelines for exposures to toxic substances. Such guidelines include those promulgated by the United States Environmental Protection Agency (USEPA) called references doses (RfDs), for oral exposures, or reference concentrations (RfCs), for exposures through the ambient air. The USEPA defined the RfD as ‘an estimate (with uncertainty spanning perhaps an order of magnitude) of a daily exposure to the human population, including sensitive subgroups, that is likely to be without an appreciable risk of deleterious effects during a lifetime’.
Benthic Ecology
Authors: Reynolds Colin S.
Published: September 2006

Benthos is the name given to the flora and fauna occurring on, in or close to the bottom substrata of aquatic environments, including lakes, ponds, rivers and streams, and the sea. In this respect, the term serves to distinguish the biota from those of the open water or ‘pelagic zone’. Benthic ecology is concerned with the biotic interrelationships of the benthos and its environments. Thus separated from pelagic ecology, the ecology of aquatic substrata is nevertheless an integral component of the ecology of the entire system.
Bioabundance
Authors: Ickstadt Katja
Published: September 2006

Bioabundance is a quantity that describes the number of individuals of a species in an area of interest, either directly or through other measurements such as biomass or percentage of cover. It is the underlying quantity of interest in a number of ecological investigations, such as monitoring population sizes and studying the spatial or space–time pattern of a single plant or animal species in a region or plot. It is also the key ingredient for analysing biodiversity, the relative abundance of several or all species in an ecological community.
Biological Assay
Authors: Coull Brent A. , Ryan Louise M.
Published: September 2006

Biological assay (also called
bioassay
) refers to methods for characterizing the potency of a stimulus based on the outcome of its application to living organisms. Traditionally, statistical methods in bioassay have focused on the estimation of the relative potency of a standard and a test drug. In environmental health research, interest often focuses on characterizing the dose–response relationships between a health effect and one or more exposures. In this setting, bioassay plays an important role in the assessment of toxicity of potentially hazardous substances; such studies (a) confirm associations between health effects and environmental exposures observed in environmental epidemiological studies, (b) provide insight into biological mechanisms underlying exposure effects, and (c) yield dose–response information that is vital for regulatory decision making. Such studies play a large role in carcinogenesis, teratogenesis, mutagenesis, and other toxicity studies, with statistical methods for analyzing bioassay data varying depending on the type of study. This article illustrates some general issues in the analysis of bioassay data by focusing on the simple setting of a rodent toxicological bioassay.
Monitoring, Biological
Authors: Smith Eric P.
Published: September 2006

In the environmental context, biological monitoring refers to the gathering of information on biological organisms to assess the environmental impact or the biological health of the environment. In a strict sense, the term applies to a continuing collection of data used to establish whether explicitly stated quality control conditions are being met. Other terms that are related include biological surveys, assessment, and surveillance. A survey typically involves a single sampling time, while surveillance suggests repeated surveys. Biological assessment often refers to the evaluation of the health of a system and thus involves interpretation of the collected information.
Boxplot, Bivariate
Authors: Iglewicz Boris
Published: September 2006

A variety of graphical displays are available for summarizing bivariate data. These include scatter plots, local density plots, and smoothed curve scatter plots. Color is sometimes used effectively to describe local densities. The popularity of the univariate boxplot makes it tempting to derive practical bivariate versions that summarize the key features of bivariate data. Several such bivariate boxplot constructions will be described in this article.
Bivariate Extreme Value Distribution
Authors: Teugels Jozef L.
Published: September 2006

In many situations within environmetrics, investigators deal with bivariate measurements. While each of the components might have its own extreme characteristics, frequently there is a need for insight into the simultaneous happening of two or more extreme events. First a few theoretical aspects are dealt with on how to model the dependence and the location of more information in the literature is indicated. Some specific applications of bivariate extremes within an environmental context are then described.
Boxplot
Authors: Iglewicz Boris
Published: September 2006

Tukey introduced several basic exploratory data analytic tools that have since found great popularity and extensive usage. These tools include the stem‐and‐leaf display, the five‐number summary, and a graphical univariate data summary called a box‐and‐whisker plot, which is now typically called a boxplot. The five‐number summary is the basis of a boxplot. It consists of the median, the lower and upper quartiles, and the smallest and largest observation.
Branching Process
Authors: Athreya K.B.
Published: September 2006

The study of the growth and development of many species of animals, plants and other organisms over time may be approached in the following manner. At some point in time a set of individuals called ancestors or the zeroth generation is identified. These produce offspring and the collection of offspring of all the ancestors constitutes the first generation. The offspring of these first generation individuals constitute the second generation and so on. If one specifies the rules by which the offspring production takes place then one could study the behavior of the long time evolution of such a process, called a
branching process
. Questions of interest are the long term survival of such a process or its extinction, the growth rate of such a population, fluctuation of population sizes, effects of control mechanicisms etc. In this article several simple mathematical models and some results for these will be discussed. Many of the assumptions made, especially the one about independence of lines of descent, are somewhat idealistic and unrealistic. Nevertheless, the models do prove useful in answering some general questions, since many results about long term behavior deviate somewhat from the basic assumptions.
B
ritish
E
cological
S
ociety
Authors: Sheail John
Published: September 2006

The British Ecological Society is a learned society, a registered charity, and a company limited by guarantee. With a membership of about 4500 spread around the world, its core activities are the publication of the results of research in ecology, the development of scientific meetings, and the promotion of ecological awareness through education. In the formal language of its mission statement, the Society's purpose is ‘to advance and support the science of ecology and publicize the outcome of research in order to advance knowledge, education and its application’.
Capture–Recapture Methods
Authors: Gould William R. , Pollock Kenneth H.
Published: September 2006

Capture–recapture methods have a long history of use, but most recently have received greater attention from biologists and statisticians due to their frequent application. The Petersen method, in which a single mark, release and recapture is made, forms the basis for many of the more sophisticated methods that exist today. The basic principle inherent to capture–recapture is that given knowledge of the size of a marked subset of a population, one can estimate demographic information on the larger population of interest. Closed population models do not allow for migration or mortality or natality. Open population models allow for these processes and thus are more intensely parameterized. Capture–recapture models often require specific assumptions that may prove to be invalid. For example, in some models all animals are assumed to have equal capture probabilities on a given capture occasion. Thus, more realistic models with weaker assumptions are being developed by incorporating multiple recapture periods, multiple sources of recoveries, improved sampling designs, and age and spatial structure into the modelling process. In addition, combinations with other survey types and enhanced technology, e.g. radio telemetry, have allowed additional information sources to be included in estimating important demographic parameters.
Carcinogenesis, Environmental
Authors: Ryan Louise
Published: September 2006

A significant proportion of cancer cases are likely to be attributable to the environment, especially when broadly interpreted to include lifestyle choices such as smoking and diet, as well as chemical exposures encountered in the workplace, air, water or in our food.
Catastrophical Risk
Authors: Chichilnisky Graciela
Published: September 2006

This article analyses decision under uncertainty, motivated by problems emerging from global environmental risks. These are typically low‐probability events with major irreversible consequences. For such risks the Von Neumann–Morgenstern (NM) Axioms for decision‐making under uncertainty are not appropriate, since they are insensitive to low‐probability events. The article introduces an alternative set of axioms that require sensitivity to both low and large probability events. Through a representation theorem in functional analysis, the results characterize all the operators whose maximization leads to the fulfillment of these axioms. They involve a convex combination of expected utility and a criterion based on the desire to avoid low‐probability and potentially catastrophical events. It is shown that the new axioms help resolve the Allais paradox. Open questions about risk aversion, games under uncertainty and calculus of variations are discussed.
Categorical Data
Authors: Imrey Peter.B. , Simpson Douglas G.
Published: September 2006

Categorical data refers to counts of events or individuals observed through some defined process and often allocated to subgroups, or categories, corresponding to levels of one or more attributes. This article reviews methods for interpreting collections of such counts, when they arise from apparently random environmental processes and may be treated as dependent variables relative to potentially explanatory factors or covariates. After introducing basic terminology including measures of relative frequency and association, we review the Poisson probability distribution. This is followed by the binomial, multinomial and hypergeometric distributions and products thereof, that result from conditioning upon sums of independent Poisson counts. These form the basis for modeling the random variation in observed categorical data. For modeling structural relationships, generalized linear models are first defined, and Poisson regression, logistic regression, and log‐linear models are each considered within that framework. We then summarize several methods for analyzing the correlated counts that occur when observing a categorical dependent variable on the same observational units under several measurement conditions or at multiple observation times, or on multiple observational units within matched sets. These methods include weighted least‐squares functional regression, conditional logistic regression, Cochran–Mantel–Haenszel tests, generalized linear mixed models, and analyses using generalized estimating equations. Finally, we briefly comment on Bayes and empirical Bayes methods, spatial modeling, exact methods, and add inevitably ephemeral comments on the status of software at the turn of the millenium.
Censored Data
Authors: Buhamra Sana S. , Al‐Ibrahim A.H.
Published: September 2006

Data with values below detection are often coded to the detection level or to a specified constant. These values are known as
censored values
and the data are referred to as
left censored data
. If such data were analyzed using traditional methods, the estimates obtained from the analysis would always be contaminated with some unspecified amount of bias. Methods have been developed that allow for the unbiased estimation of the parameters in the presence of censored values.
Center for Statistical Ecology and Environmental Statistics
Authors: Patil G.P.
Published: September 2006

The Center for Statistical Ecology and Environmental Statistics is a unit in the Department of Statistics of the Pennsylvania State University and was initiated under a cooperative agreement between the US National Oceanic and Atmospheric Administration (NOAA) and the Pennsylvania State University as a formal substitute for the earlier Penn State Program in Statistical Ecology and Environmental Statistics in operation since 1969. The Center is the first of its kind in the nation and in the world, and enjoys a national and international reputation. Broad research areas of the Center relate to statistical ecology, environmental statistics, and quantitative risk analysis, with emphasis on mathematical statistics, statistical methodology, and data interpretation and improvement for future use. The adopted approach is to advance statistics for environment, ecology, and environmental health, and to advance environmental and ecological theory and practice using valid statistics.
Change‐in‐Ratio
Authors: Udevitz Mark S.
Published: September 2006

Change‐in‐ratio (CIR) methods are used to estimate parameters for ecological populations subject to differential removals from population subclasses. Subclasses can be defined according to criteria such as sex, age or size of individuals. Removals are generally in the form of closely monitored sport or commercial harvests. Estimation is based on observed changes in subclass proportions caused by the removals.
Chemometrics
Authors: Park Kwang‐Su , Spiegelman Clifford H.
Published: September 2006

A definition of chemometrics by Massart et al. is as follows: ‘Chemometrics is a chemical discipline that uses mathematics, statistics and formal logic (a) to design or select optimal experimental procedures; (b) to provide maximum relevant chemical information by analyzing chemical data; and (c) to obtain knowledge about chemical systems.’ In an application to the industry, point (c) of the definition can be changed as follows: (c′) to obtain knowledge about chemical systems for monitoring or controlling operation of systems. Chemometrics applications are quite broad, often involving both traditional and nontraditional statistical techniques in the chemical sciences. Frequently, the novel aspects of chemometric practice deal with problems of high correlations and very high dimensionality within the data.
Classification
Authors: Simeonov V.
Published: September 2006

The aim of a classification procedure for environmental studies is to reveal similarities (or dissimilarities) between groups of objects (e.g. sampling sites or sampling periods), characterized by the values of a set of variables (e.g. chemical or physical parameters, analytes).
Clean Air Acts
Authors: El‐Shaarawi Abdel
Published: September 2006

National, provincial, state, or municipal authorities in most developed countries have established legislations or Acts to control air pollution emissions and to protect human health and the general environment.
Climatology
Authors: Henderson‐Sellers Ann
Published: September 2006

Climatology, once the study of ‘average weather’, now encompasses the atmosphere, hydrosphere, cryosphere, land surface and biosphere. Modern climatology includes not only these components but importantly their interactions involving detailed global observing systems and complex computer‐based numerical models. People's interest in climatology has been, and is likely to continue to be, concerned with social issues of habitability and sustainability. We tend to evaluate climate in personal terms: Is it too hot or too cold? Is the air pleasant to breathe? Is there enough water for drinking and for growing crops? Does it feel comfortable? These characteristics are interdependent; together forming the climate system and posing a larger question: Can this planet continue to sustain life?
Clustering
Authors: Marriott F.H.C.
Published: September 2006

Cluster analysis is concerned with the subdivision of individual objects into natural groups on the basis of collected data relating to these objects. The data may consist of observations on each object, or of perceived similarities or dissimilarities between pairs. As a statistical technique, cluster analysis is a form of ‘unsupervised classification’, as opposed to supervised classification, in which the groups and the group membership of the data are known, and are used to form rules to classify future observations. It is closely related to ordination, including principal component analysis and projection pursuit. These techniques are often used to justify the results of cluster analysis.
Multicollinearity
Authors: Wakefield Jon
Published: September 2006

Multicollinearity is said to occur when at least one column of the design matrix is linearly dependent on the other columns, and can cause problems of both interpretation and computation in regression analysis. The problem manifests itself when a regressor is highly correlated with another regressor, or a linear combination of a number of regressors. This does not guarantee multicollinearity, however, since two vectors may have correlation one, but be orthogonal. Sometimes this phenomenon is referred to as collinearity but, in this article, this term is reserved for the situation in which several points lie on a line.
Community Food Webs
Authors: Deangelis Don
Published: September 2006

Community food webs describe the feeding relationships, or trophic interactions, between species in an ecological community. Food webs can be represented both pictorially and mathematically. Historically, the mathematical study of community food webs developed from two different lines of inquiry. The first line extended the predator–prey models of Lotka and Volterra to describe the dynamics of communities of many species. The second line derived from the study of the flows of energy in ecosystems, beginning with Lindeman. Ecologists studying the dynamics, and researchers focusing on the energy flows of community food webs found it useful to model food webs with sets of differential equations, one equation for each species (or ‘trophospecies’, aggregations of species sharing the same prey and predators) in the system.
Community, Ecology
Authors: Philippi Tom
Published: September 2006

Ecological communities are the set of potentially interacting species co‐occurring at one place. The field of community ecology investigates both the pattern and processes of ecological communities, the structure of communities, and what factors and processes determine that structure. The three main approaches to these questions are comparing naturally occurring variations in communities across both space and time, comparing responses to experimental manipulations, and theoretical modeling. As a field, community ecology partially overlaps with population ecology, landscape ecology, ecosystem ecology and biogeography.
Compartmental Analysis
Authors: Becka Michael
Published: September 2006

Ecological, toxicological and pharmacological research is often concerned with the answer to the question of how a substance is processed within a biological system. The exact knowledge of the corresponding kinetic pattern forms the basis for a useful answer. To understand and to characterize kinetic processes, as well as to identify nonlinear kinetics, compartmental analysis yields an useful approach.
Competing Risk
Authors: Gupta R.C.
Published: September 2006

In studies of risk assessment due to environmental exposures, we are interested in the mortality due to a particular disease when several other diseases are acting on a person's life. The method of analyzing survival data in such a population is called competing risk analysis. We also have a fundamental assumption that each death takes place due to a single cause.

When an individual is considered, only his time of death and cause of death are noted. These competing risk data provide insufficient information to determine the joint distribution of the survival times, giving rise to the identifiability problem. In this article we introduce the cause specific hazard functions and discuss their estimation and testing, in the case of independent and dependent models. We also address the identifiability problem and suggest some ways to deal with the competing risk data in the presence of association between the latent survival times
Composite Sampling
Authors: Patil G.P.
Published: September 2006

The high costs of laboratory analytical procedures frequently strain environmental and public health budgets. Whether soil, water or biological tissue is being analyzed, the cost of testing for chemical and pathogenic contaminants can be quite prohibitive. Composite sampling can substantially reduce analytical costs because the number of required analyses is reduced by compositing several samples into one and analyzing the composited sample. By appropriate selection of the composite sample size and retesting of select individual samples, composite sampling may reveal the same information as would otherwise require many more analyses. Many of the limitations of composite sampling have been overcome by recent research, thus providing more widespread potential for the use of composite sampling to reduce costs of environmental and public health assessments, while maintaining and often increasing the precision of sample‐based inference.
Computer‐Intensive Methods
Authors: Fortin Marie‐Josée , Jacquez Geoffrey M. , Shipley Bill
Published: September 2006

With recent advances in the power of personal computers, reference distributions of statistics are now often generated using computer‐intensive methods. Several terms are erroneously used interchangeably when referring to such computer‐intensive statistical methods, including ‘resampling techniques’, ‘Monte Carlo’, ‘permutation’, ‘randomization’ and ‘bootstrap’. These techniques are not interchangeable but are fundamentally different in terms of their statistical mechanics. The generic terms ‘resampling techniques’ and ‘computer‐intensive methods’ refer to all methods in which the observed data are used to generate a reference distribution by means of randomization. This reference distribution is then used to assess the significance of a statistic calculated from the observed (not randomized) data. Significance is evaluated under the assumption that the statistic computed using the observed data is sampled from the reference distribution generated with a randomization technique.
Concentration, Ambient
Authors: Hopke Philip K.
Published: September 2006

The atmosphere consists of both gases and condensed phases. The concentrations of these components are not constant, with the variability being inversely related to reactivity of the individual species. More highly reactive components such as reactive organic compounds have distributions with larger relative standard deviations than low reactivity species. There are variations in concentrations between the northern and southern hemispheres. There are generally higher concentrations of various components in the northern hemisphere than in the southern hemisphere. These differences are the result of higher human populations in the northern hemisphere, as well as the relatively slow mixing that occurs across the equator between the two hemispheres.
Conditional Simulation
Authors: Shafer John M.
Published: September 2006

Conditional simulation, also referred to as stochastic imaging, is a stochastic simulation process whereby equally probable realizations of a spatial random function are created with each realization honoring discrete data values at specific locations or geometric patterns, i.e. ‘conditioned’ on the data. Conditional simulations of a random function satisfy two exactitude constraints, the local exactitude of honoring data values and the global exactitude of reproduction of a specified spatial correlation structure. The random variable may be categorical such as an indicator of the presence or absence of some feature (e.g. rock type), or spatially continuous such as porosity or ore grade. Conditional simulation is often used to address problems associated with the spatial distribution of physical properties relevant to the mining industry and several fields of earth sciences, especially hydrogeology, contaminant hydrology, meteorology, and gravimetry. Through Monte Carlo analysis, for example, conditional simulation can be used to evaluate the uncertainty in numerical model parameter values and the translated uncertainty in model response.
Confounding
Authors: Waller Lance A.
Published: September 2006

Confounding can be described in its simplest possible notion as ‘a confusion of effects’.
Creel Surveys
Authors: Jones Cynthia
Published: September 2006

The term
creel survey
is applied to sampling surveys that target recreational anglers. The name comes from the woven wooden basket, or creel, that freshwater anglers use to hold captured fish while they continue fishing. Traditionally, the survey is conducted on‐site at access points along the water and the angler is asked about the fish species that have been targeted, the numbers of each species caught and released, and the time spent fishing. These data are used to estimate the total catch and effort for that recreational fishery in order to manage its harvest. Additionally, other measures such as catch per unit effort are used to assess qualities of the fishery that lead to angler satisfaction with his/her recreational experience. Anglers can also be contacted by other means, such as by telephone or mail, and may also be asked other questions, such as those related to economic expenditures.
Critical Loads
Authors: Hirst David
Published: September 2006

In the 1960s and 1970s it became clear that air pollution was causing damage to ecosystems across the world, and in particular acid rain was thought to be damaging forests and water bodies long distances from the pollutant source. International agreements were necessary in order to reduce emissions of these pollutants, and it was therefore necessary to quantify both current damage, and the level of reductions that would reduce damage to acceptable levels. Critical loads (CLs) were therefore defined in the 1979 Geneva Convention on Long‐range Transboundary Air Pollution, as ‘a quantitative estimate of an exposure to one or more pollutants below which significant harmful effects on specified sensitive elements of the environment do not occur according to present knowledge’. The first CLs were defined and calculated for acidity due to sulfur (S) deposition. These were superseded by acidity CLs due to combined nitrogen (N) and S deposition. There are now also CLs for nutrient N, and more recently ‘critical levels’ have been defined for ozone. CLs have now been defined and mapped for all natural and semi‐natural areas in Europe. The data are held at the Co‐ordination Center for Effects at the National Institute of Public Health and the Environment in the Netherlands (RIVM).
Cross‐Scale Morphology
Authors: Allen Craig R. , Holling C.S.
Published: September 2006

The scaling of physical, biological, ecological and social phenomena has become a major focus of efforts to develop simple representations of complex systems. Much of the attention has been on discovering universal scaling laws that emerge from simple physical and geometric processes. But there are regular patterns of departures both from those scaling laws and from continuous distributions of attributes of systems; these departures often demonstrate the development of self‐organized interactions between living systems and physical processes over narrower ranges of scale. Cross‐scale morphology refers to morphological attributes of animals that are influenced by interaction with ecological structures and patterns at different scales.
Cross‐Validation
Authors: Friedl Herwig , Stampfer Erwin
Published: September 2006

Cross‐validation is a resampling technique that is often used for the assessment of statistical models, as well as selection amongst competing model alternatives. Basically, it is a method to estimate the prediction error of statistical predictor functions. This technique can be very useful in data problems involving minimal distributional assumptions. It has found many applications ranging from linear regression, partial least squares, ridge regression, classification and discrimination, to smoothing and neural networks, in univariate as well as in multivariate settings. Cross‐validation is rooted in the well‐known phenomenon that estimating prediction error on the same data used for model building tends to give downward‐biased estimates. The reason for this is that the parameter estimates are optimized to reflect the peculiarities of the dataset. When new data arrive, the model usually performs worse than expected on the grounds of assessment measurements on the training set. A reliable method to estimate the prediction error is especially necessary for very flexible models, e.g. neural networks and tree‐based classifiers, where overfitting is ubiquitous.
Databases, Health Assessment
Authors: Ross N. Phillip , Geyer Susan
Published: September 2006

Environmental issues – in particular questions about the relationship of environmental pollution to human and ecological health – are becoming more numerous and controversial. The ideal approach to assessing potential health risks from environmental exposure is to conduct well‐designed, prospective, environmental, epidemiological studies. However, prospective epidemiological studies are difficult and expensive to undertake, and even retrospective studies can be prohibitively complex. Reliable environmental data are not easy to find and often they may not have been collected in a manner that makes then easy to use. The purpose of this article is to provide an overview of the major databases that have potential for providing data on environmental pollution as related to measures of human and ecological health.