Relevant bibliographies by topics / Environmental chemistry Statistical methods

Academic literature on the topic 'Environmental chemistry Statistical methods'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Environmental chemistry Statistical methods"

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Ziegel, Eric R., and J. Einax. "Chemometrics in Environmental Chemistry: Statistical Methods." Technometrics 38, no. 4 (November 1996): 412. http://dx.doi.org/10.2307/1271332.

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Whitbeck, Michael. "Chemometrics in environmental chemistry, statistical methods." Chemometrics and Intelligent Laboratory Systems 34, no. 1 (August 1996): 131–32. http://dx.doi.org/10.1016/0169-7439(96)00008-1.

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Czermiński, J., A. Iwasiewicz, Z. Paszek, A. Sikorski, and Richard G. Brereton. "Statistical methods in applied chemistry." Analytica Chimica Acta 244 (1991): 296. http://dx.doi.org/10.1016/s0003-2670(00)82518-0.

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Simeonov, Vasil. "Basic Multivariate Statistical Methods for Environmental Monitoring Data Mining: Introductory Course for Master Students." Chemistry-Didactics-Ecology-Metrology 25, no. 1-2 (December 1, 2020): 35–56. http://dx.doi.org/10.2478/cdem-2020-0002.

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Abstract The present introductory course of lectures summarizes the principles and algorithms of several widely used multivariate statistical methods: cluster analysis, principal components analysis, principal components regression, N-way principal components analysis, partial least squares regression and self-organizing maps with respect to their possible application in intelligent analysis, classification, modelling and interpretation to environmental monitoring data. The target group of possible users is master program students (environmental chemistry, analytical chemistry, environmental modelling and risk assessment etc.).
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Bucur, Elena, Andrei Vasile, Luoana Florentina Pascu, Carol Blaziu Lehr, and Gabriela Geanina Vasile. "Environmental Impact Assessment Regarding Indoor Air Quality Using Statistical Methods." Revista de Chimie 69, no. 11 (December 15, 2018): 3225–28. http://dx.doi.org/10.37358/rc.18.11.6718.

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This paper brings into attention of the indoor air specialists new information regarding the assessment of the potential cumulated impact of the air chemical compounds and microclimate factors on materials; for exemplification it was selected a wooden church made by oak and the monitoring values for temperature, humidity and the concentration of four chemical compounds with a destructive potential on organic materials generally: NO2, SO2, O3 and PM2.5.
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Hipel, K. W. "Stochastic and statistical methods in hydrology and environmental engineering." Stochastic Hydrology and Hydraulics 9, no. 1 (March 1995): 1–11. http://dx.doi.org/10.1007/bf01581755.

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Bruggemann, Rainer, and Lars Carlsen. "Partial Order in Environmental Chemistry." Current Computer-Aided Drug Design 16, no. 3 (June 2, 2020): 257–69. http://dx.doi.org/10.2174/1573409915666190416160350.

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Background: The theory of partial order is a branch of Discrete Mathematics and is often seen as pretty esoteric. However, depending on a suitable definition of an order relation, partial order theory has some statistical flavor. Here we introduce the application of partial order for environmental chemistry. Objective : We showed that partial order is an instrument, which at the same time, has both data exploration - and evaluation potency. Methods: The partial order theory was applied in this study. It depends on four indicators which describe the environmental hazards of chemicals. Results : Nineteen organic chemicals were found within a monitoring study in the German river Main and were taken as an exemplary case. The results indicated that chemicals can have a high risk on the environment, however, the type of risk is different and should not conceptually merge into a single quantity. Conclusions: Partial order theory is of help to define different regulations and environmental management plans.
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Hölzel, Helen, Maximilian Muth, Dominik Lungerich, and Norbert Jux. "Cover Picture: Addressing Environmental Challenges of Porphyrin Mixtures Obtained from Statistical Syntheses (Chemistry ‐ Methods 3/2021)." Chemistry–Methods 1, no. 3 (February 23, 2021): 135. http://dx.doi.org/10.1002/cmtd.202100014.

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Veselík, Petr, Marie Sejkorová, Aleksander Nieoczym, and Jacek Caban. "Outlier Identification of Concentrations of Pollutants in Environmental Data Using Modern Statistical Methods." Polish Journal of Environmental Studies 29, no. 1 (December 9, 2019): 853–60. http://dx.doi.org/10.15244/pjoes/112620.

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Sinha, Parikhit, Michael B. Lambert, and V. Lyle Trumbull. "EVALUATION OF STATISTICAL METHODS FOR LEFT-CENSORED ENVIRONMENTAL DATA WITH NONUNIFORM DETECTION LIMITS." Environmental Toxicology and Chemistry 25, no. 9 (2006): 2533. http://dx.doi.org/10.1897/05-548r.1.

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Dissertations / Theses on the topic "Environmental chemistry Statistical methods"

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Sofer, Tamar. "Statistical Methods for High Dimensional Data in Environmental Genomics." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10403.

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In this dissertation, we propose methodology to analyze high dimensional genomics data, in which the observations have large number of outcome variables, in addition to exposure variables. In the Chapter 1, we investigate methods for genetic pathway analysis, where we have a small number of exposure variables. We propose two Canonical Correlation Analysis based methods, that select outcomes either sequentially or by screening, and show that the performance of the proposed methods depend on the correlation between the genes in the pathway. We also propose and investigate criterion for fixing the number of outcomes, and a powerful test for the exposure effect on the pathway. The methodology is applied to show that air pollution exposure affects gene methylation of a few genes from the asthma pathway. In Chapter 2, we study penalized multivariate regression as an efficient and flexible method to study the relationship between large number of covariates and multiple outcomes. We use penalized likelihood to shrink model parameters to zero and to select only the important effects. We use the Bayesian Information Criterion (BIC) to select tuning parameters for the employed penalty and show that it chooses the right tuning parameter with high probability. These are combined in the “two-stage procedure”, and asymptotic results show that it yields consistent, sparse and asymptotically normal estimator of the regression parameters. The method is illustrated on gene expression data in normal and diabetic patients. In Chapter 3 we propose a method for estimation of covariates-dependent principal components analysis (PCA) and covariance matrices. Covariates, such as smoking habits, can affect the variation in a set of gene methylation values. We develop a penalized regression method that incorporates covariates in the estimation of principal components. We show that the parameter estimates are consistent and sparse, and show that using the BIC to select the tuning parameter for the penalty functions yields good models. We also propose the scree plot residual variance criterion for selecting the number of principal components. The proposed procedure is implemented to show that the first three principal components of genes methylation in the asthma pathway are different in people who did not smoke, and people who did.
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FREITAS, SONIA MARIA DE. "STATISTICAL METHODOLOGY FOR ANALYTICAL METHODS VALIDATION APPLICABLE CHEMISTRY METROLOGY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=4058@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
A metodologia estatística escolhida para validação de métodos analíticos aplicável à metrologia em química é fundamental para assegurar a qualidade, comprovar a eficiência e demonstrar a exatidão dos resultados das medições nas análises químicas. Essa metodologia, desenvolvida em conformidade com o rigor metrológico, resulta num sistema de medições validado, confiável e com incertezas quantificadas. Este trabalho propõe uma metodologia geral para validação de métodos analíticos. A metodologia desenvolvida resultou de uma síntese de métodos parciais descritos na literatura, e inclui uma escolha crítica de técnicas mais adequadas dentro das alternativas existentes. A abordagem proposta combina quatro diferentes aspectos da validação: a modelagem da curva de calibração; o controle da especificidade do método; a comparação da tendência e precisão (repetitividade e precisão intermediária) do método com um método de referência; e a estimação das componentes de incerteza inerentes a todos esses aspectos. Como resultado, além de uma proposta para validação de métodos para uso em análises químicas, obtêm- se a função de calibração inversa e as incertezas expandidas, que permitem obter os resultados analíticos associados aos valores da resposta, com suas respectivas incertezas associadas. Na modelagem geral para obtenção da curva de calibração, empregam-se técnicas estatísticas para avaliação da linearidade e para o cálculo do mínimo valor detectável e do mínimo valor quantificável. A especificidade do método analítico é avaliada pela adição de padrões a um conjunto de amostras representativas e posterior recuperação dos mesmos, com ajuste por mínimos quadrados e testes de hipóteses. Para estudar a tendência e a precisão do método quando comparado a um método de referência, utiliza-se um modelo hierárquico de quatro níveis e a aproximação de Satterthwaite para determinação do número de graus de liberdade associados aos componentes de variância. As técnicas estatísticas utilizadas são ilustradas passo a passo por exemplos numéricos.
The use of statistical methodology for analytical methods validation is vital to assure that measurements have the quality level required by the goal to be attained. This thesis describes a statistical modelling approach for combining four different aspects of validation: checking the linearity of the calibration curve and compute the detection and the quantification limits; controlling the specificity of the analytical method; estimating the accuracy (trueness and precision) of the alternative method, for comparison with a reference method. The general approach is a synthesis of several partial techniques found in the literature, according to a choice of the most appropriate techniques in each case. For determination of the response function, statistical techniques are used for assessing the fitness of the regression model and for determination of the detection limit and the quantification limit. Method specificity is evaluated by adjusting a straight line between added and recovered concentrations via least squares regression and hypotheses tests on the slope and intercept. To compare a method B with a reference method A, the precision and accuracy of method B are estimated. A 4-factor nested design is employed for this purpose. The calculation of different variance estimates from the experimental data is carried out by ANOVA. The Satterthwaite approximation is used to determine the number of degrees of freedom associated with the variance components. The application of the methodology is thoroughly illustrated with step-by-step examples.
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Yansane, Alfa Ibrahim Mouke. "Statistical Methods for Panel Studies with Applications in Environmental Epidemiology." Thesis, Harvard University, 2011. http://dissertations.umi.com/gsas.harvard:10049.

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Pollution studies have sought to understand the relationships between adverse health effects and harmful exposures. Many environmental health studies are predicated on the idea that each exposure has both acute and long term health effects that need to be accurately mapped. Considerable work has been done linking air pollution to deleterious health outcomes but the underlying biological pathways and contributing sources remain difficult to identify. There are many statistical issues that arise in the exploration of these longitudinal study designs such as understanding pathways of effects, addressing missing data, and assessing the health effects of multipollutant mixtures. To this end this dissertation aims to address the afore mentioned statistical issues. Our first contribution investigates the mechanistic pathways between air pollutants and measures of cardiac electrical instability. The methods from chapter 1 propose a path analysis that would allow for the estimation of health effects according to multiple paths using structural equation models. Our second contribution recognizes that panel studies suffer from attrition over time and the loss of data can affect the analysis. Methods from Chapter 2 extend current regression calibration approaches by imputing missing data through the use of moving averages and assumed correlation structures. Our last contribution explores the use of factor analysis and two-stage hierarchical regression which are two commonly used approaches in the analysis of multipollutant mixtures. The methods from Chapter 3 attempt to compare the performance of these two existing methodologies for estimating health effects from multipollutant sources.
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Farhat, Hikmat. "Studies in computational methods for statistical mechanics of fluids." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0026/NQ50157.pdf.

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Agrawala, Gautam Kumar. "Regional ground water interpretation using multivariate statistical methods." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2007. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Lafleur, Josiane. "Hybrid microscale analytical methods for environmental analysis." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86503.

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The contamination of natural resources by human activity can have severe socio-economical impacts. Environmental analytical chemistry plays an essential role in the solving of these environmental problems. However, conventional environmental analytical procedures are generally lengthy and necessitate several steps. Hybrid microscale analytical techniques have been developed with the objective of minimizing the number of sample preparation steps, avoiding the use of organic solvents and reducing the size of the samples required for an analysis as well as increasing the speed of analyses.
An Inductively Heated - Electrothermal Vaporizer (IH-ETV) was coupled to an Inductively Coupled Plasma Mass Spectrometer (ICP-MS) to vaporize mercury from single human hair strands without any prior sample preparation, such as the destruction of its matrix by digestion. The results were comparable to those obtained with a reference method.
For samples requiring chromatographic separation, sample handling was minimized by direct coupling of the chromatographic procedure to an ICP-MS through Laser Ablation (LA). Cr3+ and Cr6+ were separated on silica gel High Performance Thin Layer Chromatography plates (HPTLC) using aqueous mobile phases. LA was used to volatilize the chromium species directly from the chromatographic stationary phase material for ICP-MS detection. This procedure allows for a rapid separation and quantification, and requires only 0.5 μL of sample.
The same procedure was used to couple miniature Solid Phase Extraction (SPE) columns implemented on centrifugal microfluidic discs to an ICP-MS to determine pre-concentrated metal chelates from drinking water. The miniature SPE devices require only 1 - 600 μL samples, allowing a reduction of three to four orders of magnitude in sample size compared to the conventional procedure, and the device requires no more than a simple motor to actuate fluid flow. The centrifugal microfluidic SPE discs can be used to perform up to eight extractions simultaneously and allow the easy storage of samples before transport to the laboratory for LA-ICP-MS analysis.
Finally, the centrifugal microfluidic SPE discs were modified to allow their coupling to absorption and fluorescence spectrometers. As well as the advantages listed above, this hyphenated system allows the in-situ screening of aquatic organic pollutants trapped on the SPE column directly in the field using simple and small light sources and detectors.
La contamination des ressources naturelles par l'activité humaine peut avoir des impacts socio-économiques graves pour les communautés qui en dépendent et la chimie analytique environnementale constitue un élément essentiel dans la résolution de ces problèmes environnementaux. Cependant, les procédés conventionnels d'analyse sont généralement longs et nécessitent plusieurs étapes. Plusieurs techniques hybrides ont été développées afin de: minimiser le nombre d'étapes nécessaires à la préparation d'un échantillon, éviter l'utilisation de solvants organiques, réduire la taille des échantillons, en plus de réduire le temps nécessaire pour compléter une analyse.
Un vaporisateur électrothermique à chauffage induit (IH-ETV) fut couplé à un plasma à couplage inductif avec détection par spectrométrie de masse (ICP-MS). Cette procédure permet de quantifier le mercure contenu dans un brin de cheveu sans aucune préparation préalable de l'échantillon, telle que la destruction de sa matrice par digestion. Les résultats obtenus sont comparables à ceux obtenus avec la méthode de référence.
Afin d'obtenir plus d'information sur la forme physico-chimiques de certains éléments, il est avantageux d'associer des techniques séparatives simples à l'ICP-MS. La chromatographie en couches minces (CCM) fut couplée directement à L'ICP-MS, à l'aide d'un système d'ablation laser (LA). Après leur spéciation sur du gel de silice à l'aide d'un éluant à base d'eau, Cr3+ et Cr6+ ont étés prélevés directement sur la phase stationnaire par LA. Cette procédure à permis la spéciation et quantification rapide du chrome à partir d'un échantillon de 0.5 µL.
La méthode LA-ICP-MS fut également utilisée pour déterminer des complexes métal-8-hydroxyquinoline préconcentrés par adsorption sur des microcolonnes d'extraction en phase solide (SPE) incorporées à des plateformes microfluidiques centrifuges. Ces dispositifs miniatures de SPE nécessitent des échantillons de 1 - 600 µL, une réduction de trois à quatre ordres de grandeur, comparativement à la méthode conventionnelle, en plus d'éliminer l'élution du complexe chélaté à l'aide d'un solvant organique. Ce dispositif permet l'extraction simultanée de huit échantillons et peut aussi servir à entreposer les échantillons durant leur transport au laboratoire pour l'analyse par LA-ICP-MS.
Finalement, ces plateformes microfluidiques ont été modifiées pour permettre le couplage avec un spectromètre d'absorption ou d'émission. En plus des avantages susmentionnés, ce dispositif permet le contrôle de polluants organiques aquatiques directement sur le site d'échantillonnage par absorbance et fluorimétrie mesurées directement sur la microcolonne SPE.
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Bell, Madison. "Developing Statistical and Analytical Methods for Untargeted Analysis of Complex Environmental Matrices." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/41626.

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The main objective of this thesis was to develop statistical and analytical methods for untargeted analyses of complex environmental matrices like soil and sediment. Untargeted analyses are notoriously difficult to perform in matrices like soil and sediment because of the complexity of organic matter composition within these matrices. This thesis aimed to (1) Develop and compare extraction methods for untargeted analyses of soil and sediment while also developing data handling and quality control protocols; (2) Investigate novel applications of untargeted analyses for environmental classification and monitoring; and (3) Investigate the experimental factors that can influence the organic matter composition of untargeted extractions. CHAPTER TWO is a literature review of metabolomics protocols, and these protocols were incorporated into a proposed workflow for performing untargeted analysis in oil, soil, and sediment. This thesis contains the first application of untargeted analysis to freshwater lake sediment organic matter (i.e. sedimentomics) in CHAPTER THREE, and this has implications for discovering new biomarkers for paleolimnology (APPENDIX ONE). I demonstrated successful extraction methods for both sedimentomics and soil metabolomics studies in CHAPTER THREE and CHAPTER FIVE, respectively, using the proposed workflow from CHAPTER TWO. I also applied sedimentomics to the classification of lake sediments using machine learning and geostatistics based on sediment organic matter compositions in CHAPTER FOUR; this was a novel application of sedimentomics that could have implications for ecosystem classifications and advance our knowledge of organic matter cycling in lake sediments. Lastly, in CHAPTER FIVE I determined microbial activity, extraction method, and soil type can all influence the composition of soil organic matter extracts in soil metabolomics experiments. I also developed novel quality controls and quantitative methods that can help control these influences in CHAPTER FIVE and APPENDIX THREE. APPENDIX TWO was written in collaboration with multiple researchers and is a review of all “omics” types of analyses that can be performed on soil or sediment, and how methods like the untargeted analysis of soil and sediment organic matter can be linked with metagenomics, metatranscriptomics, and metaproteomics for a comprehensive metaphenomics analysis of soil and sediment ecosystems. In CHAPTER SIX the conclusions and implications for each chapter and overall for this thesis are detailed and I describe future directions for the field. In the end the overall conclusions of this thesis were: 1) Quality controls are necessary for sedimentomics and soil metabolomics studies, 2) Sedimentomics is a valid technique to highlight changes in sediment organic matter, 3) Soil metabolomics and sedimentomics yield more information about carbon cycling than traditional measurements, and 4) Soil metabolomics organic matter extractions are more variable and require more quality controls.
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Elayouty, Amira Sherif Mohamed. "Time and frequency domain statistical methods for high-frequency time series." Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8061/.

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Advances in sensor technology enable environmental monitoring programmes to record and store measurements at high-temporal resolution over long time periods. These large volumes of high-frequency data promote an increasingly comprehensive picture of many environmental processes that would not have been accessible in the past with monthly, fortnightly or even daily sampling. However, benefiting from these increasing amounts of high-frequency data presents various challenges in terms of data processing and statistical modeling using standard methods and software tools. These challenges are attributed to the large volumes of data, the persistent and long memory serial correlation in the data, the signal to noise ratio, and the complex and time-varying dynamics and inter-relationships between the different drivers of the process at different timescales. This thesis aims at using and developing a variety of statistical methods in both the time and frequency domains to effectively explore and analyze high-frequency time series data as well as to reduce their dimensionality, with specific application to a 3 year hydrological time series. Firstly, the thesis investigates the statistical challenges of exploring, modeling and analyzing these large volumes of high-frequency time series. Thereafter, it uses and develops more advanced statistical techniques to: (i) better visualize and identify the different modes of variability and common patterns in such data, and (ii) provide a more adequate dimension reduction representation to the data, which takes into account the persistent serial dependence structure and non-stationarity in the series. Throughout the thesis, a 15-minute resolution time series of excess partial pressure of carbon dioxide (EpCO2) obtained for a small catchment in the River Dee in Scotland has been used as an illustrative data set. Understanding the bio-geochemical and hydrological drivers of EpCO 2 is very important to the assessment of the global carbon budget. Specifically, Chapters 1 and 2 present a range of advanced statistical approaches in both the time and frequency domains, including wavelet analysis and additive models, to visualize and explore temporal variations and relationships between variables for the River Dee data across the different timescales to investigate the statistical challenges posed by such data. In Chapter 3, a functional data analysis approach is employed to identify the common daily patterns of EpCO2 by means of functional principal component analysis and functional cluster analysis. The techniques used in this chapter assume independent functional data. However, in numerous applications, functional observations are serially correlated over time, e.g. where each curve represents a segment of the whole time interval. In this situation, ignoring the temporal dependence may result in an inappropriate dimension reduction of the data and inefficient inference procedures. Subsequently, the dynamic functional principal components, recently developed by Hor mann et al. (2014), are considered in Chapter 4 to account for the temporal correlation using a frequency domain approach. A specific contribution of this thesis is the extension of the methodology of dynamic functional principal components to temporally dependent functional data estimated using any type of basis functions, not only orthogonal basis functions. Based on the scores of the proposed general version of dynamic functional principal components, a novel clustering approach is proposed and used to cluster the daily curves of EpCO2 taking into account the dependence structure in the data. The dynamic functional principal components depend in their construction on the assumption of second-order stationarity, which is not a realistic assumption in most environmental applications. Therefore, in Chapter 5, a second specific contribution of this thesis is the development of a time-varying dynamic functional principal components which allows the components to vary smoothly over time. The performance of these smooth dynamic functional principal components is evaluated empirically using the EpCO2 data and using a simulation study. The simulation study compares the performance of smooth and original dynamic functional principal components under both stationary and non-stationary conditions. The smooth dynamic functional principal components have shown considerable improvement in representing non-stationary dependent functional data in smaller dimensions. Using a bootstrap inference procedure, the smooth dynamic functional principal components have been subsequently employed to investigate whether or not the spectral density and covariance structure of the functional time series under study change over time. To account for the possible changes in the covariance structure, a clustering approach based on the proposed smooth dynamic functional principal components is suggested and the results of application are discussed. Finally, Chapter 6 provides a summary of the work presented within this thesis, discusses the limitations and implications and proposes areas for future research.
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Gong, Mengyi. "Statistical methods for sparse image time series of remote-sensing lake environmental measurements." Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8608/.

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Remote-sensing technology is widely used in Earth observation, from everyday weather forecasting to long-term monitoring of the air, sea and land. The remarkable coverage and resolution of remote sensing data are extremely beneficial to the investigation of environmental problems, such as the state and function of lakes under climate change. However, the attractive features of remote-sensing data bring new challenges to statistical analysis. The wide coverage and high resolution means that data are usually of large volume. The orbit track of the satellite and the occasional obscuring of the instruments due to atmospheric factors could result in substantial missing observations. Applying conventional statistical methods to this type of data can be ineffective and computationally intensive due to its volume and dimensionality. Modifications to existing methods are often required in order to incorporate the missingness. There is a great need of novel statistical approaches to tackle these challenges. This thesis aims to investigate and develop statistical approaches that can be used in the analysis of the sparse remote-sensing image time series of environmental data. Specifically, three aspects of the data are considered, (a) the high dimensionality, which is associated with the volume and the dimension of data, (b) the sparsity, in the sense of high missing percentages and (c) the spatial/temporal structures, including the patterns and the correlations. Initially, methods for temporal and spatial modelling are explored and implemented with care, e.g. harmonic regression and bivariate spline regression with residual correlation structures. In recognizing the drawbacks of these methods, functional data analysis is employed as a general approach in this thesis. Specifically, functional principal component analysis (FPCA) is used to achieve the goal of dimension reduction. Bivariate basis functions are proposed to transform the satellite image data, which typically consists of thousands/millions of pixels, into functional data with low dimensional representations. This approach has the advantage of identifying spatial variation patterns through the principal component (PC) loadings, i.e. eigenfunctions. To overcome the high missing percentages that might invalidate the standard implementation of the FPCA, the mixed model FPCA (MM-FPCA) was investigated in Chapter 3. Through estimating the PCs using a mixed effect model, the influence of sparsity could be accounted for appropriately. Data imputation can be obtained from the fitted model using the (truncated) Karhunen-Loeve expansion. The method's applicability to sparse image series is examined through a simulation study. To incorporate the temporal dependence into the MM-FPCA, a novel spatio-temporal model consisting of a state space component and a FPCA component is proposed in Chapter 4. The model, referred to as SS-FPCA in the thesis, is developed based on the dynamic spatio-temporal model framework. The SS-FPCA exploits a flexible hierarchical design with (a) a data model consisting of a time varying mean function and random component for the common spatial variation patterns formulated as the FPCA, (b) a process model specifying the type of temporal dynamic of the mean function and (c) a parameter model ensuring the identifiability of the model components. A 2-cycle alternating expectation - conditional maximization (AECM) algorithm is proposed to estimate the SS-FPCA model. The AECM algorithm allows different data augmentations and parameter combinations in various cycles within an iteration, which in this case results in analytical solutions for all the MLEs of model parameters. The algorithm uses the Kalman filter/smoother to update the system states according to the data model and the process model. Model investigations are carried out in Chapter 5, including a simulation study on a 1-dimensional space to assess the performance of the model and the algorithm. This is accompanied by a brief summary of the asymptotic results of the EM-type algorithm, some of which can be used to approximate the standard errors of model estimates. Applications of the MM-FPCA and SS-FPCA to the remote-sensing lake surface water temperature and Chlorophyll data of Lake Victoria (obtained from the European Space Agency's Envisat mission) are presented at the end of Chapter 3 and 5. Remarks on the implications and limitations of these two methods are provided in Chapter 6, along with the potential future extensions of both methods. The Appendices provide some additional theorems, computation and derivation details of the methods investigated in the thesis.
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Zibdeh, Hazim S. "Environmental thermal stresses as a first passage problem." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/49971.

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Due to changes of the thermal environment, thermal stresses are produced in structures. Two approaches based on the stochastic process theory are used to describe this phenomenon. The structure is idealized as a long hollow viscoelastic cylinder. Two sites are considered: Barrow (AK) and Yuma (AZ). First passage concepts are applied to characterize the reliability of the system. Crossings are assumed to follow either the behavior of the Poisson process or Markov process. In both cases, the distribution of the time to first passage is taken to be the exponential distribution. Because the material is viscoelastic, statistically and time varying barriers (strengths) with Normal, Log-Normal, or Neibull distributions are considered. Degradation of the barriers by aging and cumulative damage are incorporated in the analysis.
Ph. D.
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Books on the topic "Environmental chemistry Statistical methods"

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Einax, Jürgen, ed. Chemometrics in Environmental Chemistry - Statistical Methods. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-540-49148-4.

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J, Breen Joseph, Robinson Philip E. 1948-, American Chemical Society. Division of Environmental Chemistry., and American Chemical Society Meeting, eds. Environmental applications of chemometrics. Washington, D.C: American Chemical Society, 1985.

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Einax, J. Chemometrics in environmental chemistry: Applications. Berlin: Springer, 1995.

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Jørgensen, Sven Erik. Handbook of estimation methods in ecotoxicology and environmental chemistry. Boca Raton, La: Lewis Publishers, 1998.

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W, Zwanziger Heinz, and Geiss Sabine, eds. Chemometrics in environmental analysis. Weinheim: VCH Verlagsgesellschaft, 1997.

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Sherlock, Elizabeth Jane. Evaluation of static and kinetic prediction test data and comparison with field monitoring data. Ottawa, ON: CANMET, 1995.

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Fortin, Marie-Jose e. Spatial analysis: A guide for ecologists. Cambridge, N.Y: Cambridge University Press, 2005.

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Hopke, Philip K. Development of multivariate analysis procedures for Ontario air quality data: R.A.C. Project no 311 PL : final report. [Toronto, Ont.]: Environment Ontario, 1990.

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E, Zünd Richard, ed. Statistical methods in analytical chemistry. New York: Wiley, 1993.

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Meier, Peter C., and Richard E. Zünd. Statistical Methods in Analytical Chemistry. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2000. http://dx.doi.org/10.1002/0471728411.

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Book chapters on the topic "Environmental chemistry Statistical methods"

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Nendza, Monika. "Statistical methods." In Structure—Activity Relationships in Environmental Sciences, 63–88. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5805-7_4.

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Kissling, Grace E. "Statistical Methods." In The Clinical Chemistry of Laboratory Animals, 1105–20. Third edition. | Boca Raton : Taylor & Francis, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315155807-26.

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Bajpai, A. C., Irene M. Calus, and J. A. Fairley. "Descriptive Statistical Techniques." In Methods of Environmental Data Analysis, 1–35. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-010-9512-9_1.

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Bajpai, A. C., Irene M. Calus, and J. A. Fairley. "Descriptive Statistical Techniques." In Methods of Environmental Data Analysis, 1–35. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2920-6_1.

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Starzak, Michael E. "Statistical Mechanics." In Mathematical Methods in Chemistry and Physics, 359–408. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-2082-9_7.

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Dominici, Francesca, and Ander Wilson. "Statistical Methods for Environmental Epidemiology." In Handbook of Environmental and Ecological Statistics, 547–86. Boca Raton : Taylor & Francis, 2018.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315152509-24.

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Nelson, Jon P. "Meta-analysis: Statistical Methods." In Benefit Transfer of Environmental and Resource Values, 329–56. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9930-0_15.

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Aiello-Lammens, Matthew, and John A. Silander. "Statistical Methods for Modeling Traits." In Handbook of Environmental and Ecological Statistics, 371–400. Boca Raton : Taylor & Francis, 2018.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315152509-16.

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Fuentes, Montse, Brian J. Reich, and Yen-Ning Huang. "Statistical methods for exposure assessment." In Handbook of Environmental and Ecological Statistics, 445–64. Boca Raton : Taylor & Francis, 2018.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315152509-19.

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Krall, Jenna R., and Howard H. Chang. "Statistical methods for source apportionment." In Handbook of Environmental and Ecological Statistics, 523–46. Boca Raton : Taylor & Francis, 2018.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315152509-23.

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Conference papers on the topic "Environmental chemistry Statistical methods"

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Zwagerman, Ralph. "Development of ISO18363-4 / AOCS Cd29f-2021: A new standardized method to quantify MCPDE and GE in edible oils." In 2022 AOCS Annual Meeting & Expo. American Oil Chemists' Society (AOCS), 2022. http://dx.doi.org/10.21748/dqcb6439.

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In August 2021 the International Organization for Standardization (ISO) Â has published part 4 to the ISO 18363 series of methods to quantify MCPD- and glycidyl esters in edible oils. AOCS will follow by publishing the method as AOCS Cd 29f-2021 in 2022. This new method describes a high throughput method for the quantification of these process contaminants, for which the EU has recently updated its legislation on the maximum levels allowed in edible oils. In short, its chemistry is based on fast alkaline transesterification of the fat matrix, which also cleaves the MCPDE and GE esters before the analytes are derivatization and analysis by GC-MS/MS. An in vitro correction for glycidol overestimation, which can occur in alkaline environment, is included. In the fall of 2018 both ISO and AOCS technical committees agreed to standardize the method in cooperation. An overview is given of the standardization project together with statistical data collected during the collaborative study together with a short introduction to the chemistry of the method.
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Manoppo, Yance, Leny S. Latuny, N. J. de Kock, and J. Wattimena. "Detecting indications of cheating in school exams of chemistry subjects using several statistical methods." In 1ST INTERNATIONAL SEMINAR ON CHEMISTRY AND CHEMISTRY EDUCATION (1st ISCCE-2021). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0110485.

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Huo, Jinsheng, and Yan Jiang. "Statistical Methods in Ground Water: Review and Applications." In World Environmental and Water Resources Congress 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41114(371)76.

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Almazan, P. Planas. "Statistical Error Control for Radiative Software Based on Monte Carlo Methods." In International Conference On Environmental Systems. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1993. http://dx.doi.org/10.4271/932258.

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Sato, Hirofumi, Chisa Kikumori, and Shigeyoshi Sakaki. "Coronene-transition metal complex: View from quantum chemistry and statistical mechanics." In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2009: (ICCMSE 2009). AIP, 2012. http://dx.doi.org/10.1063/1.4771837.

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Pathak, Chandra S., John R. Mecikalski, Ramesh S. Teegavarapu, and Jayanthi Srikishen. "Design of Solar Radiation Sensor Network Using Geo-Statistical Methods." In World Environmental and Water Resources Congress 2009. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41036(342)596.

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Olekhno, Nikita, Alina Rozenblit, Pavel Seregin, and Maxim Gorlach. "Statistics-induced topological States of interacting anyons." In INTERNATIONAL CONFERENCE ON PHYSICS AND CHEMISTRY OF COMBUSTION AND PROCESSES IN EXTREME ENVIRONMENTS (COMPHYSCHEM’20-21) and VI INTERNATIONAL SUMMER SCHOOL “MODERN QUANTUM CHEMISTRY METHODS IN APPLICATIONS”. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0031727.

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Goly, Aneesh, and Ramesh S. V. Teegavarapu. "Assessment of Various Statistical Downscaling Methods for Downscaling Precipitation in Florida." In World Environmental and Water Resources Congress 2013. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784412947.105.

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Ashkar, F. "Reflections on Some Methods Used to Fit Statistical Distributions to Hydrological Data." In World Water and Environmental Resources Congress 2004. Reston, VA: American Society of Civil Engineers, 2004. http://dx.doi.org/10.1061/40737(2004)287.

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Len, Przemysław. "The Use Of Statistical Methods in Creation of the Urgency Ranking of the Land Consolidation and Land Exchange Works." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.212.

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In the analyzes of the urgency of the land consolidation and land exchange works, and particularly in the spatial comparative analyzes it is helpful to use methods of multivariate statistics, which allows the determination of synthetic measure. Synthetic measures substitute the large set of attributes of the object with one aggregate variable, allowing ordering the analyzed objects (villages) in terms of the phenomenon in question of the urgency of carrying out the work of consolidation and exchange of land. The aim of the paper is to determine measures for the urgency of carrying out the works of consolidation and exchange of land according to the method proposed by Z. Hellwig and comparison of the obtained results with the results obtained using the zero unitarisation method (ZUM). The aim of the analyzes is to verify (check), how the use of different methods of aggregation of the same diagnostic variables affects the results of research. The subject of the research consists of 14 precincts located in the municipality Białaczów, in the Łódzkie voivodship region. To construct the synthetic measure for the urgency of carrying out the works of consolidation and exchange of land 5 groups of features characterizing the works related to consolidation and exchange of land were adopted.
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Reports on the topic "Environmental chemistry Statistical methods"

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Wurtz, Ron E. Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2. Office of Scientific and Technical Information (OSTI), March 2018. http://dx.doi.org/10.2172/1432977.

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Anderson, Andrew, and Mark Yacucci. Inventory and Statistical Characterization of Inorganic Soil Constituents in Illinois: Appendices. Illinois Center for Transportation, June 2021. http://dx.doi.org/10.36501/0197-9191/21-007.

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This report presents detailed histograms of data from the Regulated Substances Library (RSL) developed by the Illinois Department of Transportation (IDOT). RSL data are provided for state and IDOT region, IDOT district, and county spatial subsets to examine the spatial variability and its relationship to thresholds defining natural background concentrations. The RSL is comprised of surficial soil chemistry data obtained from rights-of-way (ROW) subsurface soil sampling conducted for routine preliminary site investigations. A selection of 22 inorganic soil analytes are examined in this report: Al, Sb, As, Ba, Be, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Ni, K, Se, Na, Tl, V, and Zn. RSL database summary statistics, mean, median, minimum, maximum, 5th percentile, and 95th percentile, are determined for Illinois counties and for recognized environmental concern, non-recognized environmental concern, and de minimis site contamination classifications.
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Anderson, Andrew, and Mark Yacucci. Inventory and Statistical Characterization of Inorganic Soil Constituents in Illinois. Illinois Center for Transportation, June 2021. http://dx.doi.org/10.36501/0197-9191/21-006.

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This report presents a statistical analysis of the Regulated Substances Library (RSL) developed by the Illinois Department of Transportation. The RSL is comprised of surficial soil chemistry data obtained from rights-of-way subsurface soil sampling conducted for routine preliminary site investigations. The 3.7-million-record RSL database is compared with four independent studies of inorganic soil constituents of naturally occurring soils in Illinois. A selection of 22 inorganic soil analytes are examined in this study: Al, Sb, As, Ba, Be, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Ni, K, Se, Na, Tl, V, and Zn. RSL database summary statistics, mean, median, minimum, maximum, 5th percentile, and 95th percentile, are determined for Illinois counties and for recognized environmental concern, non-recognized environmental concern, and de minimis site contamination classifications. The RSL database at a 95% confidence level is compared with current and proposed thresholds for defining naturally occurring soil concentrations for the selected analytes. The revised thresholds proposed by Cahill in 2017 are predominantly larger than the current standards found in the Tiered Approach to Corrective Action Objectives rules and are in better agreement with observed distributions of soil concentrations for both naturally occurring and RSL soils. A notable exception is antimony (Sb), for which Cahill proposed a reduced threshold similar in magnitude to the median for many Illinois Department of Transportation districts.
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Wraight, Sarah, Julia Hofmann, Justine Allpress, and Brooks Depro. Environmental justice concerns and the proposed Atlantic Coast Pipeline route in North Carolina. RTI Press, March 2018. http://dx.doi.org/10.3768/rtipress.2018.mr.0037.1803.

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This report describes publicly available data sets and quantitative analysis that local communities can use to evaluate environmental justice concerns associated with pipeline projects. We applied these data and analytical methods to two counties in North Carolina (Northampton and Robeson counties) that would be affected by the proposed Atlantic Coast Pipeline (ACP). We compared demographic and vulnerability characteristics of census blocks, census block groups, and census tracts that lie within 1 mile of the proposed pipeline route with corresponding census geographies that lie outside of the 1-mile zone. Finally, we present results of a county-level analysis of race and ethnicity data for the entire North Carolina segment of the proposed ACP route. Statistical analyses of race and ethnicity data (US Census Bureau) and Social Vulnerability Index scores (University of South Carolina’s Hazards & Vulnerability Research Institute) yielded evidence of significant differences between the areas crossed by the pipeline and reference geographies. No significant differences were found in our analyses of household income and cancer risk data.
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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.
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Yurovskaya, M. V., and A. V. Yushmanova. Complex Investigations of the World Ocean. Proceedings of the VI Russian Scientific Conference of Young Scientists. Edited by D. A. Alekseev, A. Yu Andreeva, I. M. Anisimov, A. V. Bagaev, Yu S. Bayandina, E. M. Bezzubova, D. F. Budko, et al. Shirshov Institute Publishing House, April 2021. http://dx.doi.org/10.29006/978-5-6045110-3-9.

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The collection contains materials of the VI All-Russian Scientific Conference of Young Scientists "Complex Investigations of the World Ocean", dedicated to the discussion of the main scientific achievements of young specialists in the field of oceanology, modern methods and means of studying the World Ocean. Within the framework of the conference, issues of modern oceanology were considered in sections: ocean physics, ocean biology, ocean chemistry, marine geology, marine geophysics, marine ecology and environmental management, oceanological technology and instrumentation, as well as interdisciplinary physical and biological research of the ocean. Along with the coverage of the results obtained in the course of traditional oceanological expeditionary research, attention was paid to the development of modern methods of studying the ocean: numerical modeling and remote sensing methods of the Earth from space.
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Starkey, Eric, Daniel McCay, Chrisopher Cooper, and Mark Hynds. Assessment of estuarine water and sediment quality at Cape Hatteras National Seashore and Cape Lookout National Seashore: 2021 data summary. National Park Service, October 2022. http://dx.doi.org/10.36967/2294854.

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In July 2021 the Southeast Coast Network conducted an assessment of water quality in the vicinity of Cape Hatteras and Cape Lookout National Seashores as part of the National Park Service Vital Signs Monitoring Program. Monitoring was conducted following methods developed by the Environmental Protection Agency (EPA) as part of the National Coastal Assessment Program (EPA 2010). Laboratory analysis measured chlorophyll a and total and dissolved concentrations of nitrogen and phosphorous. Field measurements included water temperature, pH, dissolved oxygen, and salinity. Water clarity, which requires a Secchi depth measurement, was obtained when possible. All measured parameters were rated as good, fair, or poor based on thresholds set by the EPA (2012). All measured parameters were rated as good, fair, or poor based on thresholds set by the EPA (2012). Water clarity was not calculated at all sites due to the shallow depth of the water in the sound. Of the sites where water clarity could be assessed (5 sites), four measured good and one fair. Sites that were too shallow to measure water clarity had water column conditions that did not preclude light from penetrating to the bottom of the water body so no ecological effects would be expected.Turbidity measurements ranged from 1.0 to 8.0 FNU (Formazin Nephelometric Units) and are good (i.e. < 25 NTU [Nephelometric Turbidity Units]) according to North Carolina Standards (NC Administrative Code 2019). Note that turbidity units of FNU and NTU are roughly equivalent. Chlorophyll a concentration was rated good at 29 sites (97%), and fair at one site (3%). Dissolved inorganic nitrogen (DIN) concentration was good at all 30 sites (100%). Dissolved inorganic phosphorus (DIP) concentration was good at all 30 sites (100%). Dissolved oxygen concentration (bottom) was rated good at all 30 sites (100%). A water-quality condition summary index was calculated for each site sampled at Cape Hatteras and Cape Lookout National Seashores based on the categorical assessments of chlorophyll a, DIN and DIP concentrations, dissolved oxygen, and water clarity. This summary index indicated good water-quality conditions at all thirty sites (100%). Based on the summary water-quality index rating, overall water-quality conditions at Cape Hatteras and Cape Lookout National Seashores during sampling in 2021 were good. For sediment, ecological condition was ranked as good at 30 sites (100%). As a result, no adverse impacts to benthic organisms due to sediment contamination are anticipated at any of the sampled sites. This ranking was assigned according to the 2010 Environmental Protection Agency, National Coastal Condition Assessment (NCCA) thresholds for sediment chemistry.
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Hutchinson, M. L., J. E. L. Corry, and R. H. Madden. A review of the impact of food processing on antimicrobial-resistant bacteria in secondary processed meats and meat products. Food Standards Agency, October 2020. http://dx.doi.org/10.46756/sci.fsa.bxn990.

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For meat and meat products, secondary processes are those that relate to the downstream of the primary chilling of carcasses. Secondary processes include maturation chilling, deboning, portioning, mincing and other operations such as thermal processing (cooking) that create fresh meat, meat preparations and ready-to-eat meat products. This review systematically identified and summarised information relating to antimicrobial resistance (AMR) during the manufacture of secondary processed meatand meat products (SPMMP). Systematic searching of eight literature databases was undertaken and the resultantpapers were appraised for relevance to AMR and SPMMP. Consideration was made that the appraisal scores, undertaken by different reviewers, were consistent. Appraisal reduced the 11,000 initially identified documents to 74, which indicated that literature relating to AMR and SPMMP was not plentiful. A wide range of laboratory methods and breakpoint values (i.e. the concentration of antimicrobial used to assess sensitivity, tolerance or resistance) were used for the isolation of AMR bacteria.The identified papers provided evidence that AMR bacteria could be routinely isolated from SPMMP. There was no evidence that either confirmed or refuted that genetic materials capable of increasing AMR in non-AMR bacteria were present unprotected (i.e. outside of a cell or a capsid) in SPMMP. Statistical analyses were not straightforward because different authors used different laboratory methodologies.However, analyses using antibiotic organised into broadly-related groups indicated that Enterobacteriaceaeresistant to third generation cephalosporins might be an area of upcoming concern in SPMMP. The effective treatment of patients infected with Enterobacteriaceaeresistant to cephalosporins are a known clinical issue. No AMR associations with geography were observed and most of the publications identified tended to be from Europe and the far east.AMR Listeria monocytogenes and lactic acid bacteria could be tolerant to cleaning and disinfection in secondary processing environments. The basis of the tolerance could be genetic (e.g. efflux pumps) or environmental (e.g. biofilm growth). Persistent, plant resident, AMR L. monocytogenes were shown by one study to be the source of final product contamination. 4 AMR genes can be present in bacterial cultures used for the manufacture of fermented SPMMP. Furthermore, there was broad evidence that AMR loci could be transferred during meat fermentation, with refrigeration temperatures curtailing transfer rates. Given the potential for AMR transfer, it may be prudent to advise food business operators (FBOs) to use fermentation starter cultures that are AMR-free or not contained within easily mobilisable genetic elements. Thermal processing was seen to be the only secondary processing stage that served as a critical control point for numbers of AMR bacteria. There were significant linkages between some AMR genes in Salmonella. Quaternary ammonium compound (QAC) resistance genes were associated with copper, tetracycline and sulphonamide resistance by virtue of co-location on the same plasmid. No evidence was found that either supported or refuted that there was any association between AMR genes and genes that encoded an altered stress response or enhanced the survival of AMR bacteria exposed to harmful environmental conditions.
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