[EN] Water is the foundation for all biological life on Earth and one of the basic links between the biosphere and atmosphere. It is equally fundamental for humans and nature (Tolba, 1982). In an environment of growing scarcity and competition for water, increasing the understanding of all fluxes of the water cycle lies at the heart of the scientific community's goals. Traditionally, water and vegetation have been considered as different systems. However, it is necessary to take a holistic approach which considers the question of the water cycle in an integrated manner by taking into account both: blue water and green water (Birot et al., 2011). Around this idea, the new discipline Ecohydrology emerged in the early 20th century and, from then; it has grown steadily as shown by the increasing number of research lines and scientific papers related to this new field. However, most of the current hydrological models includes the vegetation as static parameter and not as state variable. There are some exceptions taking explicitly the vegetation as state variable but in those cases, the models' complexity and parametrical requirements increase substantially. In practice, we have to deal against the 'data scarcity - high parametrical requirements' issue really often. To reduce that issue, two strategies can be applied: (1) simplification of the models' conceptual scheme and (2) increase of data availability by incorporating new sources of information. In this thesis, we explored the use of a distributed parsimonious ecohydrological modelling (with low parametrical requirements) calibrated and validated exclusively with remote sensing data. First, we used the parsimonious ecohydrological model proposed by Pasquato et al. (2015) in an experimental plot located in a semi-arid Mediterranean forest. The results in this previous stage suggested that the model was able to adequately reproduce the dynamics of vegetation as well as the soil moisture variations. In other words, it has been shown that a parsimonious model with simple equations can achieve good results in general terms. But, as long as we applied the model at plot scale, the challenging task to reproduce the spatial variation of the vegetation and water cycle remained. To explore the spatio-temporal variation of the vegetation and the water cycle, the distributed version of the parsimonious ecohydrological model used previously was applied in a basin located in Kenya, concretely in the Upper Ewaso Ngiro River basin. In order to explore the potential applicability of the satellite data, we calibrated the model using exclusively the NDVI provided by NASA. First of all, we had to deal with the fact that we were not calibrating the model with only one temporal series such as historical streamflow as usual. In fact, satellite data is composed by one temporal series per pixel. We had to identify how to use spatio-temporal (and not only temporal) data during models' calibration and validation. In that sense, unfortunately, there is still a deep lack in literature. A methodology based on the use of Empirical Orthogonal Function analysis was proposed and successfully applied. This experience provided amazing and promising results. The obtained results demonstrated that: (1) satellite data of vegetation dynamics contains an extraordinary amount of information that can be used to implement ecohydrological models in scarce data regions; (2) the proposed semi-automatic calibration methodology works satisfactorily and it allows to incorporate spatio-temporal data in the model parameterization and (3) the model calibrated only using satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet point. It is important to highlight the positive consequences of this last result particularly in ungauged basins where the use of satellite data could be an alternative in order to obtain a proxy of the streamflow at outlet point. / [ES] El agua es la base de toda vida biológica en la Tierra y uno de los enlaces básicos entre la biosfera y la atmósfera. Es igualmente fundamental para los seres humanos y la naturaleza (Tolba, 1982). Tradicionalmente, el agua y la vegetación se han considerado como sistemas diferentes pero es claramente necesario tomar un enfoque holístico que considere la cuestión del ciclo del agua de una manera integrada, teniendo en cuenta tanto el agua azul como el agua verde (Birot et al., 2011). Alrededor de esta idea surgió la nueva disciplina llamada Ecohidrología a principios del siglo XX y desde entonces, no ha dejado de crecer tal y como demuestran el creciente aumento de líneas de investigación y publicaciones científicas relacionadas con este nuevo campo. Sin embargo, la mayoría de los modelos hidrológicos actuales incluye la vegetación como un parámetro estático y no como una variable de estado. Hay algunas excepciones que toman explícitamente la vegetación como variable de estado, pero en esos casos, la complejidad y el número de parámetros a determinar de los modelos aumentan sustancialmente. En la práctica, tenemos que hacer frente a la temible combinación de "escasez de datos - alto número de parámetros a determinar" con mucha frecuencia. Para reducir este problema, se pueden aplicar dos estrategias: (1) simplificar la complejidad conceptual de los modelos y así reducir el número de parámetros a calibrar, y/o (2) aumentar la disponibilidad de datos mediante la incorporación de nuevas fuentes de información. En esta tesis, hemos explorado el uso de un modelo ecohidrológico distribuido y parsimonioso (con pocos parámetros a determinar) que ha sido completamente calibrado y validado exclusivamente con datos de teledetección. En primer lugar, se utilizó el modelo ecohidrológico parsimonioso propuesto por Pasquato et al. (2015) en una parcela experimental situada en un bosque mediterráneo semiárido. Los resultados obtenidos en esta primera etapa de la tesis sugirieron que el modelo era capaz de reproducir adecuadamente la dinámica de la vegetación, así como las variaciones de humedad del suelo. En otras palabras, se pudo demostrar que un modelo parsimonioso con ecuaciones simples puede lograr buenos resultados en términos generales. Pero, como el modelo había sido aplicado a escala de parcela, todavía quedaba como tarea pendiente reproducir la variación espacial de la vegetación y del ciclo hidrológico. Para explorar la variación espacio-temporal de la vegetación y del ciclo del agua, se aplicó la versión distribuida del modelo ecohidrológico y parsimonioso utilizado previamente en una cuenca situada en Kenia. Con el fin de explorar la posible aplicabilidad de los datos de satélite, calibramos el modelo utilizando exclusivamente el NDVI proporcionada por la NASA. Se aplicó con éxito una metodología basada en el uso de la identificación de las funciones ortogonales empíricas (EOF por sus siglas en inglés). Esta última prueba proporcionó resultados prometedores: (1) los datos de satélite contienen una cantidad extraordinaria de información que puede ser usado para implementar modelos ecohidrológicos en regiones donde no se dispone de tal cantidad de información; (2) la metodología de calibración propuesta funciona satisfactoriamente y permite incorporar datos espacio-temporales en el proceso de parametrización del modelo, y (3) el modelo calibrado sólo con datos de satélite es capaz de reproducir tanto la dinámica espacio-temporal de la vegetación así como el caudal observado en el punto de desagüe de la cuenca. Es importante destacar las consecuencias positivas de este último resultado sobre todo en cuencas no aforadas, donde el uso de datos de satélite podría ser una alternativa para obtener una aproximación del recurso en el punto de desagüe. / [CAT] L'aigua és la base de tota vida biològica a la Terra i un dels enllaços bàsics entre la biosfera i l'atmosfera. És igualment fonamental per als éssers humans i la naturalesa (Tolba, 1982). Tradicionalment, l'aigua i la vegetació s'han considerat com a sistemes diferents però és clarament necessari prendre un enfocament holístic que considere la qüestió del cicle de l'aigua d'una manera integrada, tenint en compte tant l'aigua blava com l'aigua verda (Birot et al., 2011). Al voltant d'aquesta idea va sorgir la nova disciplina anomenada Ecohidrología a principis del segle XX i des de llavors, no ha deixat de créixer tal com demostren el creixent augment de línies de recerca i publicacions científiques relacionades amb aquest nou camp. No obstant això, la majoria dels models hidrològics actuals inclou la vegetació com un paràmetre estàtic i no com una variable d'estat. Hi ha algunes excepcions que prenen explícitament la vegetació com a variable d'estat, però en aquests casos, la complexitat i el nombre de paràmetres a determinar dels models augmenten substancialment. En la pràctica, hem de fer front a la temible combinació de "escassetat de dades - alt nombre de paràmetres a determinar" amb molta freqüència. Per reduir aquest problema, es poden aplicar dues estratègies: (1) simplificar la complexitat conceptual dels models i així reduir el nombre de paràmetres a calibrar, i/o (2) augmentar la disponibilitat de dades mitjançant la incorporació de noves fonts d'informació. En aquesta tesi, hem explorat l'ús d'un model ecohidrològic distribuït i parsimoniòs (amb pocs paràmetres a determinar) que ha estat completament calibrat i validat exclusivament amb dades de teledetecció. En primer lloc, es va utilitzar el model ecohidrològic i parsimoniòs proposat per Pasquato et al. (2015) en una parcel·la experimental situada en un bosc mediterrani semi-àrid. Els resultats obtinguts en aquesta primera etapa de la tesi van suggerir que el model era capaç de reproduir adequadament la dinàmica de la vegetació, així com les variacions d'humitat del sòl. En altres paraules, es va poder demostrar que un model parsimoniòs amb equacions simples pot aconseguir bons resultats en termes generals. Però, com el model havia estat aplicat a escala de parcel·la, encara quedava com a tasca pendent reproduir la variació espacial de la vegetació i del cicle hidrològic. Per explorar la variació espai-temporal de la vegetació i del cicle de l'aigua, es va aplicar la versió distribuïda del model ecohidrològic i parsimoniòs utilitzat prèviament en una conca situada a Kenya. Al mateix temps, amb la finalitat d'explorar la possible aplicabilitat de les dades de satèl·lit, calibrem el model utilitzant exclusivament el NDVI proporcionat per la NASA. Es va aplicar amb èxit una metodologia basada en l'ús de la identificació de les funcions ortogonals empíriques (EOF per les seues sigles en anglès). Aquesta última prova va proporcionar resultats sorprenents i prometedors. De fet, els resultats obtinguts van demostrar que: (1) les dades de satèl·lit contenen una quantitat extraordinària d'informació que pot ser usada per implementar models ecohidrològics en regions on no es disposa de tal quantitat d'informació; (2) la metodologia de calibratge proposat funciona satisfactòriament i permet incorporar dades espai-temporals en el procés de parametrització del model, i (3) el model calibrat només amb dades de satèl·lit és capaç de reproduir tant la dinàmica espai-temporal de la vegetació així com el cabal observat en el punt de desguàs de la conca. És important destacar les conseqüències positives d'aquest últim resultat sobretot en conques no aforades, on l'ús de dades de satèl·lit podria ser una alternativa per obtenir una aproximació del recurs en el punt de desguàs. / Ruiz Pérez, G. (2016). On the use of satellite data to calibrate a parsimonious ecohydrological model in ungauged basins [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/72639 / TESIS

A major part of the terrestrial sediment in the ocean comes from the land via river plume. There are four stages in sediment dispersal from rivers into the sea: supply via plume, initial deposition, resuspension and transport by waves and currents or by the slope failure, and long-term net accumulation. We can understand the dispersion and transport of the river plume by in situ observations of hydrodynamic of the plume field. Therefore, it is helpful to study river plume hydrodynamics, such as winds, tides, waves, and currents. The purpose of this study is to identify the type of plume dynamics by analyzing the temporal and spatial variability of hydrological structures observed around the Gaoping River mouth. We observed the bottom and surface time series of temperature, salinity, turbidity, suspended sediment concentration, and velocity profile by instrument mounted at the tetrapods and a moored buoy during July 28 to 30 in 2009 and July 30 to August 2 in 2011. Besides, we investigated the spatial structures of the river plume in Gaoping River mouth by using a fishing boat in 2009. We also acquired satellite images to assist our study. The results showed that the river discharges during 2009 was lower than daily average discharge. Combined the temporal and spatial observations and satellite images, we determined that the river plume turned west during the ebb tide was influenced by Coriolis force and winds. The buoyancy-driven current velocity was 0.15 m/s and the maximum of wind-driven current velocity was 0.30 m/s. The wind strength index (Ws) determines whether a plume¡¦s along-shelf flow is in a wind-driven or buoyancy-driven state. Ws is the ratio of the wind-driven and buoyancy-driven along-shelf velocities. If |W_s | > 1 on average the wind velocity more than 5.9 m/s. The wind velocity reached this threshold during most of the ebb periods, and around that value in the flood time. Flood currents combined with cross-shore wind pushed the river plume to swing to the east. The data were analyzed by empirical orthogonal function (EOF) analysis. The results indicated that winds and waves were the main factors influencing plume dynamics during low-discharge period. During the field experiment in 2011, the river discharge was greater than daily average discharge. The buoyancy-driven and the maximum of wind-driven current velocities were 0.30 and 0.12 m/s, respectively. The wind velocity did not reach the threshold that was 11.67 m/s. The buoyancy-driven current was more significant than wind-driven current. By analyzing the ocean color of satellite images, the river plume was spreading from the river mouth and toward west during ebb. The time series data also showed that there was plume signal at the same time. The average cross-shore current velocity was 0.52 m/s, being larger than the buoyancy-driven current. Therefore, the tide was the main factor deciding where the plume discharged. The first eigemode of EOF suggested that current was the most important factor influencing plume dynamics during high-discharge period. The second eignmode described the dominant influence of wind.

No description available.

Estuaries are vital environmental and economic resources, providing habitat for thousands of species, absorbing runoff, and supporting recreation and commerce. Yet, despite their importance, estuaries are threatened by human activities. Empirical Orthogonal Function (EOF) analysis and Cross Spectral techniques were used in the analysis and prediction of estuarine morphology. The estuaries selected for study were Suisun Bay, CA and Mobile Bay, AL. It was found that EOF is an effective and efficient technique to analyze morphology, a coupling with cross spectral methods such as Fourier Transformation (FFT) resulted in determination of forcing functions responsible for imparting variance to the bathymetry. In both the estuaries it was found that the first two eigenvalues represented almost 80% of the morphological/bathymetric dataset. The second eigenfunction was found to be closely dependent on the freshwater inflows to the estuaries. EOF analysis on Suisun Bay revealed that the bay is depositional particularly in the shallow bays of Honker and Grizzly, whereas the main channels as well as Carquinez Straits maintained their depths throughout the period studied. Utilizing a Cross spectral technique, Amplitude Response Function (ARF), temporal eigenfunctions for the bay were determined for year 2100. The temporal eigenfunctions were predicted for cases where river inflows to the bay were varied by 1 standard deviation unit. These predicted eigenfunction values combined with the eigenvalues resulted in the recovery of predicted depths for year 2100. It was found that Suisun Bay remains depositional through the year 2100 and maintains depths in the main channels as well as Carquinez Straits. This depositional behavior results in the decrease of bay volume to almost 40% of the volume in 1989. EOF analysis on Mobile Bay revealed that the bay is predominantly depositional except in the navigation channel and the shoreline of the Bay. The navigation channel maintaining it depth is attributed to the regular dredging carried to facilitate shipping. The second temporal eigenfunction showed a close correlation with river inflows as in the case of Suisun Bay. However, a cross correlation performed on the second temporal eigenfunction and inflows revealed that the response of the eigenfunction is perturbed by almost 9 years, as opposed to 6 to 9 years for Suisun Bay. An ARF on the temporal eigenfunctions combined with a reverse EOF resulted in the formation of bathymetric datasets for the year 2100 for inflows variation of 1 standard deviation. It was revealed that increasing the flows results in an increase of bay volume by approximately 30% and a decrease in flows results in a loss of volume by approximately 20%.

The developing flow field in a parallel plate microchannel, induced by wall motion, has been modeled numerically. This type of flow simulates the physical driving mechanism that exists in electro-osmotically generated flow with large channel diameter-to-Debye length ratios (Z). The physics of the flow field were compared between the moving wall model (MWM) and electro-osmotic flow (EOF) at Reynolds numbers of 1 and 1800, and Z > 2500. Also, Z-values between 50 and 500 were studied to investigate the accuracy of the MWM. Results show that for Z-values greater than 100 the MWM shows good agreement with EOF. The dynamics of the developing flow field for the MWM were explored for channel length-to-hydraulic diameter ratios (aspect ratio) of 5, 10, 20 and 40 at ten Reynolds numbers, Re (based on the wall velocity), below Re < 2000. The results show that far from the inlet the maximum fluid velocity occurs at the walls, as is expected, and the minimum velocity occurs at the channel center. Near the channel inlet, however, the centerline velocity is not a minimum but reaches a local maximum due to a resulting pressure imbalance generated by the wall motion. As the aspect ratio increases, the centerline velocity tends to approach the wall velocity far downstream from the inlet. Increases in the Reynolds number have the opposite effect on the centerline velocity. The hydrodynamic developing region, defined by that section of the channel where the wall shear stress is changing, also depends on the channel aspect ratio and Re, and is greater than the developing region for classical pressure-driven flow of a parallel plate channel. Also, the flow field physics was analyzed for a process called electro-mobility focusing (EMF). EMF is a process that separates and detects species of like charge with the use of electro-phoresis and EOF utilizing a varying voltage gradient. The velocity distribution and the effective diffusion were solved for analytically, for both a linear and non-linear voltage gradient, using the MWM and the creeping flow approximations. The resulting equations aid in optimizing the detection system by forcing the lowest effective diffusion (uniform velocity profile) to the detection location.

This thesis develops an optimal interpolation method that takes daily precipitation values collected from weather stations and produces precipitation estimates on a grid. The method, called Hybrid 2.0, combines EOF-based linear interpolation with the nearest-station method. Gridded monthly precipitation is first obtained via EOF, then distributed among days via nearest station. Hybrid 2.0 builds on an earlier method, called Hybrid 1.0, that applies an inverse-distance weighting method to obtain gridded monthly values. Hybrid 2.0 uses these monthly Hybrid 1.0 values as inputs when constructing EOF functions. The data used in this thesis were obtained from the Meteorological Service of Canada. Few weather stations were located in the northern and mountain regions of Alberta prior to 1950. As a result, the Hybrid 1.0 gridded results underestimate precipitation in these regions for that period. The main contribution of Hybrid 2.0 is a substantial reduction in this bias, obtained by implicitly taking topographic elevation into account. Bias reduction is achieved by extracting EOFs from Hybrid 1.0 output for 1951-2002, when many more stations were present in the northern and mountain regions. Hybrid 2.0 is shown to be more accurate in interpolating both monthly and daily precipitation in Alberta, when compared with Hybrid 1.0 and other methods. The thesis also provides detailed analyses of precipitation trends and droughts using the gridded Hybrid 2.0 daily values. Optimality of the selected EOF modes and sensitivity to data error in the EOF-based linear reconstruction are also discussed in this thesis. Agricultural uses of historical climate data have become extremely important. Applications include: enabling prompt, optimal decisions on market prices and disaster aid, designing future agricultural practices such as adaptation to climate and technology changes, and managing risks for agricultural producers and governments in areas such as drought monitoring. Many applications require a reliable interpolation technique to accurately reconstruct daily climate estimates onto grids of various resolutions. The gridded Hybrid 2.0 daily precipitation values produced by this thesis satisfy this requirement and can be used as inputs for many agricultural applications. / Applied Mathematics

No description available.

Im ersten Teil wurde Probenvorbereitungs-Methoden und instrumentelle Methoden zur Organofluor-Bestimmung verglichen, um Vor- und Nachteile bei der Summenparameter-Analytik von per- und polyfluorierten Alkylverbindungen (PFAS) zu identifizieren. Daher wurden Oberflächenwasserproben aus der Spree in Berlin und Industrieabwasserproben mit zwei PFAS-Summenparametern analysiert – dem extrahierbaren (EOF) und dem adsorbierbaren organisch gebundenen Fluor (AOF). Beide PFAS-Summenparameter wurden mit zwei fluorsensitiven Detektionssystemen analysiert – Hochauflösender Kontinuumstrahler-Graphitofen Molekülabsorptionsspektrometrie (HR-CS-GFMAS) und combustion Ionenchromatographie (CIC). HR-CS-GFMAS erwies sich im Vergleich zu CIC als der empfindlichere und schnellere Ansatz mit höherer Präzision. Im zweiten Teil wurde eine neue Methode zur PFAS-Summenparameteranalyse und EOF-Bestimmung in Bodenproben auf Basis von HR-CS-GFMAS entwickelt und optimiert. EOF-Massenanteile wurden bei mehrfacher Extraktion und Nutzung der Festphasenextraktion (SPE) zur Entfernung anorganischen Fluors untersucht. Bei einem Vergleich der optimierten Methode mit und ohne SPE zeigte sich eine drastische Diskriminierung von Organofluor-Verbindungen mittels SPE. Im dritten Teil wurden Organofluor-Massenbilanzen in aquatischen Systemen anhand von Oberflächenwasser- und Schwebstoffproben (SPM) untersucht. SPM-Proben wurden mit vier komplementären Analysemethoden analysiert – target und non-target, direct total oxidizable precursor assay (dTOPA) und EOF. Daher wurden drei Organofluor-Massenbilanzansätze für die räumlich und zeitaufgelöste SPM-Probenanalyse verwendet: (I) Identifizierung von oxidierbaren PFAS-Vorläufer, (II) Identifizierung des Anteils der identifizierten und nicht identifiziertes EOF und (III) PFAS-target, PFAS dTOPA, non-target-Screening und EOF-Analyse, um das nicht identifizierte EOF aus Ansatz (II) weiter zu entschlüsseln. / In the first part, a comparison of sample preparation and instrumental methods for organofluorine determination was used to identify advantages and disadvantages in sum parameter analysis of per- and polyfluoroalkyl substances (PFASs). Therefore, surface water samples from the Spree River in Berlin, Germany and industrial effluent samples were analyzed using two PFAS sum parameters – the extractable (EOF) and adsorbable organically bound fluorine (AOF). Both PFAS sum parameters were analyzed using two fluorine sensitive detection systems – high-resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) and combustion ion chromatography (CIC). HR-CS-GFMAS turned out to be the more sensitive and faster approach accompanied with higher precision compared to CIC. In the second part, a new method for PFAS sum parameter analysis and EOF determination in soil samples based on HR-CS-GFMAS was developed and optimized. EOF mass fractions were investigated upon multiple extraction and utilization of solid phase extraction (SPE) for inorganic fluorine removal. In a comparison of the optimized method with and without SPE, a highly biased discrimination of organofluorines using SPE was shown. In the third part, organofluorine mass balances were investigated in aquatic systems using surface water and suspended particulate matter (SPM) samples. SPM samples were analyzed using 4 complementary analytical methods – target and non-target HRMS, direct total oxidizable precursor assay (dTOPA) and EOF. Therefore, 3 organofluorine mass balance approaches were used for SPM sample analysis in spatial and time resolved manner: (I) Identification of oxidizable PFAS precursors, (II) Identification of the proportion of identified and unidentified EOF and (III) PFAS target, PFAS dTOPA, non-target screening and EOF analysis to further unravel the unidentified EOF from approach (II).

Near-surface soil moisture is a key state variable of the hydrologic cycle and plays a significant role in the global water and energy balance by affecting several hydrological, ecological, meteorological, geomorphologic, and other natural processes in the land-atmosphere continuum. Presence of soil moisture in the root zone is vital for the crop and plant life cycle. Soil moisture distribution is highly non-linear across time and space. Various geophysical factors (e.g., soil properties, topography, vegetation, and weather/climate) and their interactions control the spatio-temporal evolution of soil moisture at various scales. Understanding these interactions is crucial for the characterization of soil moisture dynamics occurring in the vadose zone. This dissertation focuses on understanding the spatio-temporal variability of near-surface soil moisture and the associated physical control(s) across varying measurement support (point-scale and passive microwave airborne/satellite remote sensing footprint-scale), spatial extents (field-, watershed-, and regional-scale), and changing hydro-climates. Various analysis techniques (e.g., time stability, geostatistics, Empirical Orthogonal Function, and Singular Value Decomposition) have been employed to characterize near-surface soil moisture variability and the role of contributing physical control(s) across space and time. Findings of this study can be helpful in several hydrological research/applications, such as, validation/calibration and downscaling of remote sensing data products, planning and designing effective soil moisture monitoring networks and field campaigns, improving performance of soil moisture retrieval algorithm, flood/drought prediction, climate forecast modeling, and agricultural management practices.

Per- and polyfluorinated substances (PFAS) are compounds that consist of a carbon chainbackbone that is partially or entirely fluorinated, with an addition of a functional group. SomePFAS are known as persistent organic pollutants (POPs) and have therefore been drawing a lot ofattention as well as increased concerns. PFAS have been detected in humans, wildlife and theenvironment and some have exhibited toxic effects such as hepatotoxicity, immunotoxicity,reproductive toxicity and endocrine disruption as well as being persistent and bioaccumulative.Serum, plasma and whole blood have been used as biomonitoring matrices in many studies toevaluate human exposure to PFAS. Restrictions have been applied to some PFAS, but thesecompounds are still ubiquitous. This study will investigate the performance (recovery, matrixeffect (ME) in terms of intra-/inter-day repeatability) of ion-pair extraction (IPE) and solid phaseextraction with weak anion exchange (SPE-WAX). The extraction methods were adapted fromliterature and 13 PFAS were selected for this work based on prior biomonitoring studies. Thetarget PFAS content was analyzed with liquid chromatography coupled with tandem massspectrometry (LC-MS/MS). The extraction methods were also compared for extractableorganofluorine (EOF) extraction in terms of blank levels as well as the amount extracted withdifferent methods; the EOF content was measured with combustion ion chromatography (CIC).The EOF levels were used to estimate the amount of unidentified organofluorine (UOF), to avoidunderestimating potential health hazards. Samples extracted using IPE had an average ionizationenhancement of 9%, while SPE-WAX showed an average ionization suppression of -1%. SPEWAXshowed higher average recoveries for procedural blanks (78%), horse serum (96%) andhuman serum (95%) in comparison to IPE (69%, 36%, 88%, respectively). The CIC analysis forEOF content was observed to be below MDL (&lt;50 ng/mL F) with some contaminations observedin the procedural blanks.