Volatile organic compounds in seawater

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Woods Hole Oceanographic Institution January 1979Vapor phase stripping and solid adsorbent trapping were applied to seawater and related samples to concentrate volatile organic compounds. The concentrates were subsequently analyzed by glass capillary gas chromatography and combined gas chromatography-mass spectrometry. The compound identities and the spatial and temporal distributions of their concentrations were used to determine some sources, transformations, and transport mechanisms of organic matter in the sea. Volatile organic compounds were determined in seawater samples from the Sargasso Sea, the western Equatorial Atlantic, and the upwelling region off Peru. Pentadecane was present in all three areas in surface samples at 10-40ng/kg and decreased to 1-2 ng/kg in the deep water. A source related to the transformation of the algal fatty acid, hexadecaugic acid, by zooplankton is proposed since anthropogenic and direct phytoplankton sources are unlikely. C2-alkylated benzenes were found in the upwelled water off Peru at about 4 ng/kg in the surface (5 and 20m), 3 ng/kg below the thermocline (100m), and 2 ng/kg or less in deeper water. A surface or atmospheric source is required to produce this distribution. C6-C10 aldehydes were also found in seawater from off Peru. The direct correlation of their concentrations with chlorophyll a and with oxygen indicated that they are derived from chemical oxidation of algal metabolites, for example, unsaturated fatty acids. Total volatiles in the oligotrophic Sargasso Sea were about 10-30 ng/kg while the biologically productive upwelling region off Peru contained up to 100 ng/kg. The temporal variations of volatile organic compound concentrations were investigated in coastal seawater from Vineyard Sound, Massachusetts. Pentadecane and heptadecane showed large summertime concentration increases which were ascribed to benthic algal sources. Laboratory incubations of benthic algal samples supported this conclusion. The saturated hydrocarbons, from C13-C17, and alkylated benzenes and naphthalenes were all abundant after an oil spill several miles from the sampling site. C2- and C3- benzenes were the most persistently abundant volatile compounds and their concentrations were observed to be 2-10 times higher than average immediately after summer weekends, peak periods of tourist and recreational activities on Cape Cod. Naphthalene and its homologues were more abundant in the winter than in the summer. C6-C10 aldehydes were observed year-round, but showed a concentration maximum at the time of the late-winter phytoplankton bloom. C12-C15 aldehydes were also found in abundance at that time. Oxidation of algal matter by zooplankton or photochemically-produced oxidizing agents may produce the aldehydes, since laboratory cultures of phytoplankton did not produce these oxygenated volatiles. An alkene, structurally similar to the known benthic algal gamone, fucoserraten, was also found in Vineyard Sound seawater and in the upwelling region off Peru. Its appearance in Vineyard Sound samples coincided with the period of expected algal reproductive activity in February and March. Dimethyl polysulfides were found in coastal seawater. They may be produced within the water from precursors such as methyl mercaptan or other known polysulfide metabolites. Total volatile concentrations in Vineyard Sound seawater varied between 2OO and 500 ng/kg for the period from January to June. Maximum concentrations occurred during the late-winter phytoplankton bloom and again in the spring from anthropogenic inputs of hydrocarbons. The highest concentrations of C2- and C3-benzenes found in Vineyard Sound seawater coincided with motorboat use in the immediate vicinity of the sampling station. The average year-round isomer distribution most closely resembled distributions from gasoline and auto exhaust dissolved in seawater, consistent with an inboard or inboard/outboard motorboat source. Atmospheric and runoff delivery of C2- and C3-benzenes to Vineyard Sound seawater during the period from spring through fall was concluded to be of lesser importance. The atmosphere may serve as a buffer for seawater concentrations of the aromatic compounds, supporting low concentrations in the winter and limiting high concentrations in the summer.Financial support came from ONR Contract N-000-14-74~C0262 NR 083-004, NSF Grant OCE 22781, Sea Grant 04-7-158-44104 and 04-8-MOI-149, and the W.H.O.I. Education Office

Ampliação e aplicação do método semi-empírico topológico (IET) em modelos QSRR/QSPR/QSAR para compostos alifáticos halogenados e cicloalcanos

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas. Programa de Pós-Graduação em Química.Este estudo foi desenvolvido para avaliar a capacidade de prognóstico do índice semi-empírico topológico (IET) em estimar a retenção cromatográfica (IR) de compostos alifáticos halogenados e cicloalcanos. Também foram desenvolvidos modelos de QSPR/QSAR para prever importantes propriedades físico-químicas, termodinâmicas e atividades biológicas. O modelo de QSRR do IRExpde 141 haloalcanos e o IET mostrou boa qualidade estatística (r2=0,9995; SD=8; r2cv=0,999). A partir do modelo de QSPR obtido entre o ponto de ebulição, Bp(ºC), com o IET (N=86; r2=0,9971; SD=4,2; r2cv=0,997), foram calculados os valores para um grupo externo de 24 compostos (r2=0,9931; SD=7,6). Uma boa correlação entre o ponto de fusão, Mp (°C), e o IET foi obtida (N=43; r2=0,9865; SD=6,1; r2cv=0,985). As correlações obtidas entre os valores calculados e experimentais de log P foram de r2=0,9871 e r2=0,9750, respectivamente para os Métodos Semi-Empírico Topológico e Contribuição dos Fragmentos. Esses resultados mostram a capacidade de prognóstico do IET para propriedades físico-químicas e termodinâmicas. A habilidade de prognóstico do IR pelo IET também foi verificada usando fases estacionárias com diferentes polaridades. Resultados satisfatórios foram encontrados aplicando o IET para estimar o IR de 48 cicloalcanos (r2=0,9905; SD=7; r2cv=0,997) e Bp(°C) (N=33; r2cv=0,988). Esse método permitiu retirar informações sobre as características estruturais, eletrônicas e geométricas das moléculas que estão influenciando no processo de retenção cromatográfico e a distinção entre isômeros cis/trans dos compostos estudados

Development and critical evaluation of group contribution methods for the estimation of critical properties, liquid vapour pressure and liquid viscosity of organic compounds.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2006.Critical properties, liquid vapour pressures and liquid viscosities are important thermophysical properties required for the design, simulation and optimisation of chemical plants. Unfortunately, experimental data for these properties are in most cases not available. Synthesis of sufficiently pure material and measurements of these data are expensive and time consuming. In many cases, the chemicals degrade or are hazardous to handle which makes experimental measurements difficult or impossible. Consequently, estimation methods are of great value to engineers. In this work, new group contribution methods have been developed for the estimation of critical properties, liquid vapour pressures and liquid viscosities of non-electrolyte organic compounds. The methods are based on the previous work of Nannoolal (2004) & Nannoolal et al. (2004) with minor modifications of structural group definitions. Critical properties, viz. critical temperature, critical pressure and critical volume, are of great practical importance as they must be known in order to use correlations based on the law of corresponding states. However, there is a lack of critical property data in literature as these data are difficult or in many cases impossible to measure. Critical property data are usually only available for smaller molecules of sufficient thermal stability. The proposed group contribution method for the estimation of critical properties reported an average absolute deviation of 4.3 K (0.74%), 100 kPa (2.96%) and 6.4 cm3.mol1 (1.79%) for a set of 588 critical temperatures, 486 critical pressures and 348 critical volumes stored in the Dortmund Data Bank (DDB (2006)), respectively. These results were the lowest deviations obtained when compared to ten well known estimation methods from literature. In addition, the method showed a wider range of applicability and the lowest probability of prediction failure and leads to physically realistic extrapolation when applied to a test set of components not included in the training set. For the estimation of the critical temperature using the new method, knowledge about the normal boiling point is required. If there is no information on the latter property, then the previous group contribution estimation method can be employed for estimation. Because of their great importance in chemical engineering, liquid vapour pressures have received much attention in literature. There is currently an abundance of experimental data for vapour pressures, especially for smaller molecules, but data are scarce or of low quality for larger and more complex molecules of low volatility. The estimation of liquid vapour pressures from molecular structure has met with very limited success. This is partly due to the high quality predictions required for vapour pressures for use in the design of for example distillation columns. This work presents a new technique for the estimation of liquid vapour pressures by developing a two-parameter equation where separate parameters model the absolute value and slope while at the same time the equation is able to approximate the nonlinearity of the curve. The fixed point or absolute value chosen was the normal boiling point for which a large amount of experimental data is available. A group contribution estimation of the slope was then developed which showed nearly no probability of prediction failure (high deviation). Employing experimental normal boiling points in the method, an absolute relative deviation of 6.2% in pressure for 1663 components or 68835 (68670 from DDB and 165 from Beilstein) data points was obtained. This result is in comparable accuracy or slightly higher in deviation than correlative models such as the Antoine and DIPPR equations (direct correlations). A test of the predictive capability by employing data that were not used in the training set also showed similar results. Estimations are possible up to the inflection point or a reduced normal boiling temperature of ±1.2. If there is no information about the experimental normal boiling point, two options are recommended to obtain this value. The first and more reliable is back-calculation using the known boiling point at other pressures and the estimated slope of the vapour pressure equation. Results in this case are similar to cases where experimental normal boiling points were used. The second possibility is to estimate the normal boiling point using the method developed previously. In this case, an absolute relative deviation of 27.0% in pressure is obtained. The saturated liquid viscosity is an important transport property that is required for many engineering applications. For this property, experimental data are limited to mostly simple and more common components and, even for these components the data often cover only a small temperature range. There have been many different approaches to estimate liquid viscosities of organic compounds. However, correlative and empirical methods are often the only or preferred means to obtain liquid viscosities. The technique used for the estimation of the liquid viscosity is similar to that in case of liquid vapour pressures, i.e. a two-parameter equation models the absolute value, slope and the non-linearity of the curve. As there was no convenient reference point at a standard viscosity available to model the absolute value (viscosity reference temperature), an algorithm was developed to calculate this temperature which was chosen at a viscosity of 1.3 cP. This work then presents a group contribution estimation of the slope and using calculated or adjusted reference temperatures, an absolute relative deviation of 3.4% in viscosity for 829 components or 12861 data points stored in the DDB was obtained. This result is in comparable accuracy or slightly higher in deviation than correlative models such as the Andrade and Vogel equations (direct correlations). The estimation method has an upper temperature limit which is similar to the limit in case of liquid vapour pressures. If no data are available for a viscosity close to 1.3 cP then, as in case of the vapour pressure estimation method, the temperature can be back calculated from data at other viscosity values. Alternately, the viscosity reference temperature can be estimated by a group contribution method developed in this work. This method reported an average absolute deviation of 7.1 K (2.5%) for 813 components. In case both the slope and absolute value were estimated for the liquid viscosity curve, an average absolute deviation of 15.3 % in viscosity for 813 components or 12139 data points stored in the DDB was obtained. The new method was shown to be far more accurate than other group contribution methods and at the same time has a wider range of applicability and lower probability of prediction failure. For the group contribution predictions, only the molecular structure of the compound is used. Structural groups were defined in a standardized form and fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions. To enable comparison, chemical family definitions have been developed that allow one to automatically classify new components and thus inform the user about the expected reliability of the different methods for a component of interest. Chemical family definitions are based on the kind and frequency of the different structural groups in the molecule

Prediction of the physical properties of pure chemical compounds through different computational methods.

Ph. D. University of KwaZulu-Natal, Durban 2014.Liquid thermal conductivities, viscosities, thermal decomposition temperatures, electrical conductivities, normal boiling point temperatures, sublimation and vaporization enthalpies, saturated liquid speeds of sound, standard molar chemical exergies, refractive indices, and freezing point temperatures of pure organic compounds and ionic liquids are important thermophysical properties needed for the design and optimization of products and chemical processes. Since sufficiently purification of pure compounds as well as experimentally measuring their thermophysical properties are costly and time consuming, predictive models are of great importance in engineering. The liquid thermal conductivity of pure organic compounds was the first investigated property, in this study, for which, a general model, a quantitative structure property relationship, and a group contribution method were developed. The novel gene expression programming mathematical strategy [1, 2], firstly introduced by our group, for development of non-linear models for thermophysical properties, was successfully implemented to develop an explicit model for determination of the thermal conductivity of approximately 1600 liquids at different temperatures but atmospheric pressure. The statistical parameters of the obtained correlation show about 9% absolute average relative deviation of the results from the corresponding DIPPR 801 data [3]. It should be mentioned that the gene expression programing technique is a complicated mathematical algorithm and needs a significant computer power and this is the largest databases of thermophysical property that has been successfully managed by this strategy. The quantitative structure property relationship was developed using the sequential search algorithm and the same database used in previous step. The model shows the average absolute relative deviation (AARD %), standard deviation error, and root mean square error of 7.4%, 0.01, and 0.01 over the training, validation and test sets, respectively. The database used in previous sections was used to develop a group contribution model for liquid thermal conductivity. The statistical analysis of the performance of the obtained model shows approximately a 7.1% absolute average relative deviation of the results from the corresponding DIPPR 801 [4] data. In the next stage, an extensive database of viscosities of 443 ionic liquids was initially compiled from literature (more than 200 articles). Then, it was employed to develop a group contribution model. Using this model, a training set composed of 1336 experimental data was correlated with a low AARD% of about 6.3. A test set consists of 336 data point was used to validate this model. It shows an AARD% of 6.8 for the test set. In the next part of this study, an extensive database of thermal decomposition temperature of 586 ionic liquids was compiled from literature. Then, it was used to develop a quantitative structure property relationship. The proposed quantitative structure property relationship produces an acceptable average absolute relative deviation (AARD) of less than 5.2 % taking into consideration all 586 experimental data values. The updated database of thermal decomposition temperature including 613 ionic liquids was subsequently used to develop a group contribution model. Using this model, a training set comprised of 489 data points was correlated with a low AARD of 4.5 %. A test set consisting of 124 data points was employed to test its capability. The model shows an AARD of 4.3 % for the test set. Electrical conductivity of ionic liquids was the next property investigated in this study. Initially, a database of electrical conductivities of 54 ionic liquids was collected from literature. Then, it was used to develop two models; a quantitative structure property relationship and a group contribution model. Since the electrical conductivities of ionic liquids has a complicated temperature- and chemical structure- dependency, the least square support vector machines strategy was used as a non-linear regression tool to correlate the electrical conductivity of ionic liquids. The deviation of the quantitative structure property relationship from the 783 experimental data used in its development (training set) is 1.8%. The validity of the model was then evaluated using another experimental data set comprising 97 experimental data (deviation: 2.5%). Finally, the reproducibility and reliability of the model was successfully assessed using the last experimental dataset of 97 experimental data (deviation: 2.7%). Using the group contribution model, a training set composed of 863 experimental data was correlated with a low AARD of about 3.1% from the corresponding experimental data. Then, the model was validated using a data set composed of 107 experimental data points with a low AARD of 3.6%. Finally, a test set consists of 107 data points was used for its validation. It shows an AARD of 4.9% for the test set. In the next stage, the most comprehensive database of normal boiling point temperatures of approximately 18000 pure organic compounds was provided and used to develop a quantitative structure property relationship. In order to develop the model, the sequential search algorithm was initially used to select the best subset of molecular descriptors. In the next step, a three-layer feed forward artificial neural network was used as a regression tool to develop the final model. It seems that this is the first time that the quantitative structure property relationship technique has successfully been used to handle a large database as large as the one used for normal boiling point temperatures of pure organic compounds. Generally, handling large databases of compounds has always been a challenge in quantitative structure property relationship world due to the handling large number of chemical structures (particularly, the optimization of the chemical structures), the high demand of computational power and very high percentage of failures of the software packages. As a result, this study is regarded as a long step forward in quantitative structure property relationship world. A comprehensive database of sublimation enthalpies of 1269 pure organic compounds at 298.15 K was successfully compiled from literature and used to develop an accurate group contribution. The model is capable of predicting the sublimation enthalpies of organic compounds at 298.15 K with an acceptable average absolute relative deviation between predicted and experimental values of 6.4%. Vaporization enthalpies of organic compounds at 298.15 K were also studied in this study. An extensive database of 2530 pure organic compounds was used to develop a comprehensive group contribution model. It demonstrates an acceptable %AARD of 3.7% from experimental data. Speeds of sound in saturated liquid phase was the next property investigated in this study. Initially, A collection of 1667 experimental data for 74 pure chemical compounds were extracted from the ThermoData Engine of National Institute of Standards and Technology [5]. Then, a least square support vector machines-group contribution model was developed. The model shows a low AARD% of 0.5% from the corresponding experimental data. In the next part of this study, a simple group contribution model was presented for the prediction of the standard molar chemical exergy of pure organic compounds. It is capable of predicting the standard chemical exergy of pure organic compounds with an acceptable average absolute relative deviation of 1.6% from the literature data of 133 organic compounds. The largest ever reported databank for refractive indices of approximately 12 000 pure organic compounds was initially provided. A novel computational scheme based on coupling the sequential search strategy with the genetic function approximation (GFA) strategy was used to develop a model for refractive indices of pure organic compounds. It was determined that the strategy can have both the capabilities of handling large databases (the advantage of sequential search algorithm over other subset variable selection methods) and choosing most accurate subset of variables (the advantages of genetic algorithm-based subset variable selection methods such as GFA). The model shows a promising average absolute relative deviation of 0.9 % from the corresponding literature values. Subsequently, a group contribution model was developed based on the same database. The model shows an average absolute relative deviation of 0.83% from corresponding literature values. Freezing Point temperature of organic compounds was the last property investigated. Initially, the largest ever reported databank in open literature for freezing points of more than 16 500 pure organic compounds was provided. Then, the sequential search algorithm was successfully applied to derive a model. The model shows an average absolute relative deviations of 12.6% from the corresponding literature values. The same database was used to develop a group contribution model. The model demonstrated an average absolute relative deviation of 10.76%, which is of adequate accuracy for many practical applications

Scientific Assessment of Stratospheric Ozone: 1989, volume 2. Appendix: AFEAS Report

The results are presented of the Alternative Fluorocarbon Environmental Acceptability Study (AFEAS), which was organized to evaluate the potential effects on the environment of alternate compounds targeted to replace fully halogenated chlorofluorocarbons (CFCs). All relevant current scientific information to determine the environmental acceptability of the alternative fluorocarbons. Special emphasis was placed on: the potential of the compounds to affect stratospheric ozone; their potential to affect tropospheric ozone; their potential to contribute to model calculated global warming; the atmospheric degradation mechanisms of the compounds, in order to identify their products; and the potential environmental effects of the decomposition products. The alternative compounds to be studied were hydrofluorocarbons (HFCs) with one or two carbon atoms and one or more each of fluorine and hydrogen

Natural Occurrence of Volatile Mono-/Polyhalogenated amd Aromatic/Heteroaromatic Hydrocarbons in Hypersaline Environments

Volatile compounds are important substances for tropospheric and stratospheric chemistry. Anthropogenic sources of specific gases causing greenhouse effect, stratospheric ozone depletion, groundlevel ozone formation and aerosol formation are well known. Additionally, many natural sources, like oceans, wetlands and forests, have been investigated and assessed for their atmospheric impact previously. While emissions from natural sources are often affiliated to biotic mechanisms, model reactions demonstrated also the importance of abiotic reactions. As such furan formation from catechol was successfully accomplished in this work using Fenton chemistry with a well defined biomimetic bispidine Fe2+ complex. Furthermore, abiotic formation of ethylfuran from ethylcatechol was demonstrated. The work in hand also deals with the amalgamation of model reaction and the natural release of volatile compounds from Western Australian salt lakes and the Dead Sea. On the one hand, Fe2+ was determined as the predominant active iron species in most natural hypersaline ecosystems. On the other hand, the release of several aromatic and nonaromatic hydrocarbons, furanoic compounds, sulfur and selenide containing compounds and halogenated compounds was investigated in correlation with geochemical parameters like pH, iron and organic carbon content. Benzene, toluene, ethylbenzene and xylene emissions, normally attributed to anthropogenic sources, correlated significantly with the iron content of Australian salt lake sediments demonstrating their genuine natural abundance. The same was observed for furan and hitherto mostly unnoticed n-alkyl chlorides with a C3-C8 carbon structure. Furthermore, a connection between emissions of methylfurans and their homologoues methylthiophenes was observed indicating a mutual precursor and similar formation mechanism in the soils/sediments. Aside from various known natural chlorinated, brominated and iodinated compounds, new compounds were identified like 3-chlorofuran. Additionally, natural tetrachloromethane formation in acidic salt lakes was postulated supported by various results. Relevance of these compounds for the atmospheric chemistry was assessed with regard to ultrafine particle formation in Western Australia and reactive IO/BrO over the Dead Sea