Solvent swing adsorption for the separation of acrylonitrile from process water

Adsorption is a commonly applied method when organic components need to be removed from aqueous streams. The recovery of the adsorbed components can however be challenging and therefore in many cases, the sorbent material is regenerated without recovering the adsorbed components (e.g. thermal regeneration of activated carbon). The combination of two or more separation techniques—which results in so called hybrid technologies—offers new possibilities for efficient separation processes which allow not only the removal of organic components from a water stream but also the recovery of the organics. Solvent Swing Adsorption is a hybrid separation technology which is based on the combination of adsorption with extraction and which allows the separation of dissolved organic components from water. This thesis describes the development of the Solvent Swing Adsorption technology for the recovery of dissolved acrylonitrile from an aqueous process stream. Solvent Swing Adsorption is based on the shift in the adsorption equilibrium of a sorbate when the composition of the liquid phase is changed. An organic component which needs to be separated from a water stream is in a first step adsorbed onto a solid sorbent in a fixed bed. In a second step, the component is desorbed from the sorbent material by feeding a solvent to the column which has a high affinity for the adsorbed component. During the desorption step, very high concentrations of the organic component are obtained in the solvent stream at the column outflow. As a last step, the solvent is removed from the fixed bed by flushing the column with water. The liquid mixtures which are produced in the Solvent Swing Adsorption process are treated by use of distillation. For the separation of dissolved acrylonitrile from a process water stream by use of Solvent Swing Adsorption, a suitable sorbent material was selected. Dowex Optipore L-493, Amberlite XAD-1180, activated carbon, zeolite H-BEA-150, and silica gel were preselected based on a literature research. These five adsorbents were evaluated in batch experiments to determine the acrylonitrile loading on the sorbent materials and — by varying the temperature in the batch experiments — the reversibility of the acrylonitrile adsorption. Based on these experiments, Dowex Optipore L-493 was selected as sorbent material due to its high capacity for acrylonitrile, due to the reversibility of the acrylonitrile adsorption, and due to the fast intraparticle mass transfer of acrylonitrile. The selection for an efficient desorption solvent was made based on a combination of computer aided molecular design (CAMD), in which the Hansen model was applied, and batch equilibrium experiments. Acetone, acetaldehyde, methanol, ethanol, and trimethylamine were preselected by use of CAMD and tested by use of equilibrium experiments. Because of its high affinity for acrylonitrile, its miscibility with water, its low boiling point, and its good environmental, health and safety properties, acetone was chosen as a desorption solvent. The acrylonitrile loading on Dowex Optipore as a function of the liquid phase composition was determined experimentally using batch experiments and described using three different models: the Langmuir isotherm, an activity based isotherm, and the model of Minka and Myers. It was found that the acrylonitrile loading is strongly dependent on the acetone concentration in the liquid phase. The acrylonitrile equilibrium loading at a concentration of 10 kg m-3 in water is 0.29 kg kg-1. This value drops to 0.02 kg kg-1 when the solvent is pure acetone. The reasons for this decrease are the low bulk phase acrylonitrile activity when the solvent contains a large fraction of acetone and the competition for adsorption sites between acrylonitrile and acetone. By applying the theory of Minka and Myers, acrylonitrile loadings for concentrations which are much higher than used in the experiments were predicted from the binary isotherms (acrylonitrile adsorption from water, acrylonitrile adsorption from acetone, acetone adsorption from water). The intraparticle mass transfer of acrylonitrile in the Dowex Optipore particles was described by applying the theories of Fick and of Maxwell-Stefan. The intraparticle diffusion coefficients were found by comparing the results of kinetic experiments (zero-length column experiments) with kinetic models. Two models were used which are based on Fick’s diffusion: the homogeneous surface diffusion model and the pore diffusion model. A third diffusion model was based on pore diffusion according to Maxwell-Stefan. Intraparticle pore diffusion coefficients of acrylonitrile in a water solution and in an acetone solution were found which are in the same range as the bulk diffusion coefficient of acrylonitrile in water and in acetone, respectively. For the diffusion of acrylonitrile in acetone, a Maxwell-Stefan diffusion coefficient of 1.2·10-9 m2 s-1 was found. For the diffusion of acetone in water, the Maxwell-Stefan diffusion coefficient is 1.4·10-9 m2 s-1 and for the diffusion of acrylonitrile in water 4.5 · 10-9 m2 s-1. These diffusion coefficients are remarkably large for liquid phase intraparticle diffusion which is advantageous for the Solvent Swing Adsorption process as relatively high superficial velocities can be applied. The findings from the experiments and from the modeling concerning adsorption equilibrium and kinetics were used in the development of a column model. A model was built based on plug-flow with axial dispersion. The liquid film mass transfer coefficients and the intraparticle diffusion coefficients were combined which resulted in overall mass transfer coefficients. The acrylonitrile breakthrough curve, the acrylonitrile peak during the desorption step, and the acetone removal from the column by use of water were determined experimentally. For this purpose, columns with a length of 0.112 m and 0.430 m filled with Dowex Optipore L-493 were used. The liquid was pumped over the columns with velocities of 1.70 · 10-4 m s-1 to 1.89 · 10-4 m s-1. The experimental results of the acrylonitrile adsorption and the acetone removal from the column can be described well with the developed model. The acrylonitrile desorption is described fairly well. Reasons for the difference between model and experiments are mainly the inaccuracies in the description of the acrylonitrile adsorption equilibrium and in the description of the mass transfer. The axial dispersion coefficient has only a small influence on the shape of the concentration curves in the column outflow. Based on the column model, two process schemes for the Solvent Swing Adsorption process were developed. The relatively simple non-recycle process consists of an adsorption step, a desorption step, and an acetone removal step. Two distillation columns are necessary in order to separate the resulting liquid mixture. The recycle process is more complex. A few recycle streams are included in the process, in order to increase the acrylonitrile concentration in the outflow. In this way, the separation goals can be reached by use of only one distillation column. However, the total volume of the adsorption/desorption columns is larger than for the non-recycle mode and the length of one adsorption/desorption cycle is longer. It was found — experimentally and by use of the column model — that the acrylonitrile is desorbed from the solid sorbent efficiently and it appears in the outflow of the column in a narrow and high peak. The acetone removal from the column by use of water is however much slower. An acetone/water mixture is produced with a volume which is larger than the volume of the acetone/acrylonitrile/water mixture which originates from the acrylonitrile desorption. Not only the acetone/acrylonitrile/water mixture needs to be distilled but also the acetone/water mixture which makes the process less energy efficient. Table 1: Comparison of cycle length and distillation costs for the non-recycle mode and the recycle mode. Non-recycle mode Recycle mode Length of adsorption/desorption cycle, h 5.2 15.6 Volume distilled, m3 h-1 0.87 + 2.40 = 3.27 2.60 Cost for distillation, e h-1 36 24 For a column length of 2 m, the cycle length for one adsorption/desorption cycle, the volume which needs to be distilled, and the energy costs for the distillation are given in Tab. 1. For both operating modes, a benefit of 114 e h-1 is generated by the recovery of the acrylonitrile which means that both modes can be economically feasible. The length for one adsorption/desorption cycle is three times shorter for the non-recycle mode than for the recycle mode which makes the non-recycle mode much more flexible. Additionally, for the non-recycle mode the total volume of the Solvent Swing Adsorption columns is smaller than for the recycle mode and only two storage tanks are required whereas six storage tanks are used if the recycle mode is applied. In order to make the Solvent Swing Adsorption process more energy efficient, the use of acetaldehyde as desorption solvent could be taken into consideration. Acetaldehyde has a higher affinity for acrylonitrile than acetone and a lower boiling point. However, it is more flammable, more reactive, and more dangerous to health than aceton

The Role of Tarski’s Declarative Semantics in the Design of Modeling Languages

This paper focuses on Tarski`s declarative semantics and their usefulness in the design of a modeling language. We introduce the principles behind Tarski`s approach to semantics and explain what advantages this offers in the context of modeling languages. Using sentential logic we demonstrate the necessity and sufficiency of Tarski`s semantics for effectively addressing several issues that arise in the design of modeling languages. We explain what role Tarski`s semantics play in the organization of a modeling language. This role is compared to the analogous roles of denotational semantics and operational semantics. We show that in the context of a modeling language Tarski`s semantics are complementary to the other two kinds of semantics. The paper is intended to assist modeling language researchers and designers, particularly in connection with the UML - a language that in its current form does not feature Tarski`s declarative semantics

European summer climate variability in a heterogeneous multi-model ensemble

Recent results from an enhanced greenhouse-gas scenario over Europe suggest that climate change might not only imply a general mean warming at the surface, but also a pronounced increase in interannual surface temperature variability during the summer season (Schär etal., Nature 427:332-336, 2004). It has been proposed that the underlying physical mechanism is related to land surface-atmosphere interactions. In this study we expand the previous analysis by including results from a heterogeneous ensemble of 11 high-resolution climate models from the PRUDENCE project. All simulations considered comprise 30-year control and enhanced greenhouse-gas scenario periods. While there is considerable spread in the models' ability to represent the observed summer variability, all models show some increase in variability for the scenario period, confirming the main result of the previous study. Averaged over a large-scale Central European domain, the models simulate an increase in the standard deviation of summer mean temperatures between 20 and 80%. The amplification occurs predominantly over land points and is particularly pronounced for surface temperature, but also evident for precipitation. It is also found that the simulated changes in Central European summer conditions are characterized by an emergence of dry and warm years, with early and intensified depletion of root-zone soil moisture. There is thus some evidence that the change in variability may be linked to the dynamics of soil-moisture storage and the associated feedbacks on the surface energy balance and precipitatio

The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Background Lactobacillus reuteri is a gut symbiont of a wide variety of vertebrate species that has diversified into distinct phylogenetic clades which are to a large degree host-specific. Previous work demonstrated host specificity in mice and begun to determine the mechanisms by which gut colonisation and host restriction is achieved. However, how L. reuteri strains colonise the gastrointestinal (GI) tract of pigs is unknown. Results To gain insight into the ecology of L. reuteri in the pig gut, the genome sequence of the porcine small intestinal isolate L. reuteri ATCC 53608 was completed and consisted of a chromosome of 1.94 Mbp and two plasmids of 138.5 kbp and 9.09 kbp, respectively. Furthermore, we generated draft genomes of four additional L. reuteri strains isolated from pig faeces or lower GI tract, lp167-67, pg-3b, 20-2 and 3c6, and subjected all five genomes to a comparative genomic analysis together with the previously completed genome of strain I5007. A phylogenetic analysis based on whole genomes showed that porcine L. reuteri strains fall into two distinct clades, as previously suggested by multi-locus sequence analysis. These six pig L. reuteri genomes contained a core set of 1364 orthologous gene clusters, as determined by OrthoMCL analysis, that contributed to a pan-genome totalling 3373 gene clusters. Genome comparisons of the six pig L. reuteri strains with 14 L. reuteri strains from other host origins gave a total pan-genome of 5225 gene clusters that included a core genome of 851 gene clusters but revealed that there were no pig-specific genes per se. However, genes specific for and conserved among strains of the two pig phylogenetic lineages were detected, some of which encoded cell surface proteins that could contribute to the diversification of the two lineages and their observed host specificity. Conclusions This study extends the phylogenetic analysis of L. reuteri strains at a genome-wide level, pointing to distinct evolutionary trajectories of porcine L. reuteri lineages, and providing new insights into the genomic events in L. reuteri that occurred during specialisation to their hosts. The occurrence of two distinct pig-derived clades may reflect differences in host genotype, environmental factors such as dietary components or to evolution from ancestral strains of human and rodent origin following contact with pig populations

Tambora 1815 as a test case for high impact volcanic eruptions: Earth system effects

The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the ‘Year Without a Summer’ of 1816 in Europe and North America. Although a tragic event—tens of thousands of people lost their lives—the eruption also was an ‘experiment of nature’ from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO2 injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tambora's effect on the weather systems to be addressed. Climate models respond to prescribed Tambora-like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO2. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged

Spectral Analysis of the Chandra Comet Survey

We present results of the analysis of cometary X-ray spectra with an extended version of our charge exchange emission model (Bodewits et al. 2006). We have applied this model to the sample of 8 comets thus far observed with the Chandra X-ray observatory and ACIS spectrometer in the 300-1000 eV range. The surveyed comets are C/1999 S4 (LINEAR), C/1999 T1 (McNaught-Hartley), C/2000 WM1 (LINEAR), 153P/2002 (Ikeya-Zhang), 2P/2003 (Encke), C/2001 Q4 (NEAT), 9P/2005 (Tempel 1) and 73P/2006-B (Schwassmann-Wachmann 3) and the observations include a broad variety of comets, solar wind environments and observational conditions. The interaction model is based on state selective, velocity dependent charge exchange cross sections and is used to explore how cometary X-ray emission depend on cometary, observational and solar wind characteristics. It is further demonstrated that cometary X-ray spectra mainly reflect the state of the local solar wind. The current sample of Chandra observations was fit using the constrains of the charge exchange model, and relative solar wind abundances were derived from the X-ray spectra. Our analysis showed that spectral differences can be ascribed to different solar wind states, as such identifying comets interacting with (I) fast, cold wind, (II), slow, warm wind and (III) disturbed, fast, hot winds associated with interplanetary coronal mass ejections. We furthermore predict the existence of a fourth spectral class, associated with the cool, fast high latitude wind.Comment: 16 pages, 16 figures, and 7 Tables; accepted A&A (Due to space limits, this version has lower resolution jpeg images.

Requirements Engineering Education in the 21st Century, an Experiential Learning Approach

RE use in industry is hampered by a poor understanding of RE practices and their benefits. Teaching RE at the university level is therefore an important endeavor. This education can ideally be provided at the university level as an integrated part of developing the requisite RE and software engineering technical skills, shortly before students become engineers and enter the workforce. However, much social wisdom is packed into RE methods. It is unrealistic to expect students with little organizational experience to understand this body of knowledge. The course described in this paper uses an active, affective, experiential pedagogy giving students the opportunity of experiencing a simulated work environment that demonstrates the social/design-problem complexities and richness of a development organization in the throws of creating a new product. Emotional and technical debriefing is conducted after each meaningful experience so that students and faculty, alike, can better understand the professional relevancies of what they have just experienced. This includes an examination of the many forces experienced in industrial settings but not normally discussed in academic settings. The course uses a low-tech social simulation rather than software simulation so that students learn through interaction with real people and therefore are confronted with the complexity of true social relationships

Experiential learning approach for requirements engineering education

The use of requirements engineering (RE) in industry is hampered by a poor understanding of its practices and their benefits. Teaching RE at the university level is therefore an important endeavor. Shortly before students become engineers and enter the workforce, this education could ideally be provided as an integrated part of developing the requisite business skills for understanding RE. Because much social wisdom is packed into RE methods, it is unrealistic to expect students with little organizational experience to understand and appreciate this body of knowledge; hence, the necessity of an experiential approach. The course described in this paper uses an active, affective, experiential pedagogy giving students the opportunity to experience a simulated work environment that demonstrates the social/design–problemcomplexities and richness of a development organization in the throes of creating a new product. Emotional and technical debriefing is conducted after each meaningful experience so that students and faculty, alike can better understand the professional relevancies of what they have just experienced. This includes an examination of the many forces encountered in industrial settings but not normally discussed in academic settings. The course uses a low-tech social simulation, rather than software simulation, so that students learn through interaction with real people, and are therefore confronted with the complexity of true social relationships

Robot-Assisted Hybrid Esophagectomy Is Associated with a Shorter Length of Stay Compared to Conventional Transthoracic Esophagectomy:A Retrospective Study

Aim. To compare the peri- and postoperative data between a hybrid minimally invasive esophagectomy (HMIE) and the conventional Ivor Lewis esophagectomy. Methods. Retrospective comparison of perioperative characteristics, postoperative complications, and survival between HMIE and Ivor Lewis esophagectomy. Results. 216 patients were included, with 160 procedures performed with the conventional and 56 with the HMIE approach. Lower perioperative blood loss was found in the HMIE group (600 ml versus 200 ml, p<0.001). Also, a higher median number of lymph nodes were harvested in the HMIE group (median 28) than in the conventional group (median 23) (p=0.002). The median length of stay was longer in the conventional group compared to the HMIE group (11.5 days versus 10.0 days, p=0.03). Patients in the HMIE group experienced fewer grade 2 or higher complications than the conventional group (39% versus 57%, p=0.03). The rate of all pulmonary (51% versus 43%, p=0.32) and severe pulmonary complications (38% versus 18%, p = 0.23) was not statistically different between the groups. Conclusions. The HMIE was associated with lower intraoperative blood loss, a higher lymph node harvest, and a shorter hospital stay. However, the inborn limitations with the retrospective design stress a need for prospective randomized studies. Registration number is DRKS00013023