Increasing the Dissolution Rate of Polystyrene Waste in Solvent-Based Recycling.

Solvent-based recycling of plastic waste is a promising approach for cleaning polymer chains without breaking them. However, the time required to actually dissolve the polymer in a lab environment can take hours. Different factors play a role in polymer dissolution, including temperature, turbulence, and solvent properties. This work provides insights into bottlenecks and opportunities to increase the dissolution rate of polystyrene in solvents. The paper starts with a broad solvent screening in which the dissolution times are compared. Based on the experimental results, a multiple regression model is constructed, which shows that within several solvent properties, the viscosity of the solvent is the major contributor to the dissolution time, followed by the hydrogen, polar, and dispersion bonding (solubility) parameters. These results also indicate that cyclohexene, 2-pentanone, ethylbenzene, and methyl ethyl ketone are solvents that allow fast dissolution. Next, the dissolution kinetics of polystyrene in cyclohexene in a lab-scale reactor and a baffled reactor are investigated. The effects of temperature, particle size, impeller speed, and impeller type were studied. The results show that increased turbulence in a baffled reactor can decrease the dissolution time from 40 to 7 min compared to a lab-scale reactor, indicating the importance of a proper reactor design. The application of a first-order kinetic model confirms that dissolution in a baffled reactor is at least 5-fold faster than that in a lab-scale reactor. Finally, the dissolution kinetics of a real waste sample reveal that, in optimized conditions, full dissolution occurs after 5 min.

Application of chemometric tools in the QSAR development of VOC removal in plastic waste recycling.

Deodorization and, in a broader sense, the removal of volatile organic compounds (VOCs) from plastic waste have become increasingly important in the field of plastic recycling, and various new decontamination techniques have been developed. Both in research and industrial practice, the selection of VOCs has been random or unsubstantiated, making it difficult to compare studies and assess decontamination processes objectively. Thus, this study proposes the use of Statistical Molecular Design (SMD) and Quantitative Structure - Activity Relationship (QSAR) as chemometric tools for the selection of representative VOCs, based on physicochemical properties. Various algorithms are used for SMD; hence, several frequently used D-Optimal Onion Design (DOOD) and Space-Filling (SF) algorithms were assessed. Hereby, it was validated that DOOD, by dividing the layers based on the equal-distance approach without so-called 'Adjacent Layer Bias', results in the most representative selection of VOCs. QSAR models that describe VOC removal by water-based washing of plastic waste as a function of molecular weight, polarizability, dipole moment and Hansen Solubility Parameters Distance were successfully established. An adjusted-R2 value of 0.77 ± 0.09 and a mean absolute error of 24.5 ± 4 % was obtained. Consequently, by measuring a representative selection of VOCs compiled using SMD, the removal of other unanalyzed VOCs was predicted on the basis of the QSAR. Another advantage of the proposed chemometric selection procedure is its flexibility. SMD allows to extend or modify the considered dataset according to the available analytical techniques, and to adjust the considered physicochemical properties according to the intended process.

Enhanced removal of refractory humic- and fulvic-like organics from biotreated landfill leachate by ozonation in packed bubble columns.

Biotreated landfill leachate contains much refractory organics such as humic and fulvic acids, which can be degraded by O3. However, the low O3 mass transfer and high energy cost limit its wide application in landfill leachate treatment. Previous studies proved that packed bubble columns could enhance the O3 mass transfer and increase the synthetic humic acids wastewater degradation, but the performance of packed bubble columns in real wastewater treatment has not been investigated. Therefore, this study aims to evaluate the feasibility of application of packed bubble column in the real biotreated landfill leachates treatment and provide insights into the transformation of organic matters in leachates during ozonation. Packed bubble columns with lava rocks or metal pall rings (LBC or MBC) were applied and compared with a non-packed bubble column (BC). At an applied O3 dose of 8.35 mg/(Lwater sample min), the initial COD (400 mg/L) was only removed for 26% in BC and 32% in MBC while this was 46% in LBC, indicating LBC has the best performance. GC-MS analysis shows that raw biotreated leachate contains potential endocrine disruptors such as di(2-ethylhexyl) phthalate (DEHP). 61% of DEHP was removed in LBC and the least intermediate oxidation products from humic- and fulvic-like organics was detected in LBC. The highest O3 utilization efficiency (89%) and hydroxyl radical (OH) exposure rate (3.0 × 10-10 M s) were observed in LBC with lowest energy consumption (EEO) for COD removal of 18 kWh/m3. The enhanced ozonation efficiency in LBC and MBC was attributed to the improved O3 mass transfer. Besides, LBC had additional adsorptive and catalytic activity that promoted the decomposition of O3 to generate OH. This study demonstrates that a packed bubble column increases removal and decreases energy use when treating landfill leachate, thus promoting the application of ozonation.

Towards a general kinetic microalgae model: Extending a semi-deterministic green microalgae model for the cyanobacterium Arthrospira platensis and red alga Porphyridium purpureum.

Mathematical models for microalgae and cyanobacteria are seldomly validated for different algal species, as such limiting their applicability. Therefore, in this research, a previously developed kinetic model describing the growth of the green microalgae species Chlorella vulgaris was used to simulate the growth of the cyanobacterium Arthrospira platensis and the red alga Porphyridium purpureum. Based on a global sensitivity analysis, the model parameter µmax,A was calibrated using respirometric-titrimetric data. Calibration yielded values of 5.76 ± 0.17 d-1, 2.06 ± 0.16 d-1 and 1.06 ± 0.09 d-1 for Chlorella vulgaris, Arthrospira platensis and Porphyridium purpureum, respectively. Model simulations revealed that the biological growth equations in this model are adequate. However, increased light intensities triggered a survival mechanism for Arthrospira platensis, which is currently not taken into account by the model, leading to bad model accuracy under these circumstances. Future work should address the most important survival mechanisms and include those in the model to widen its applicability.

Intensified ozonation in packed bubble columns for water treatment: Focus on mass transfer and humic acids removal.

Ozonation has been widely applied for the oxidation of contaminants in wastewater, and the disinfection of water. However, low ozone (O3) mass transfer efficiency in common ozonation reactors requires high O3 doses and causes high energy consumption. In this study, to intensify the O3 mass transfer and oxidation of humic acids (HA) solution, a lava rock packed bubble column (LBC) and a metal pall ring packed bubble column (MBC) were developed and evaluated. In comparison with non-packed bubble column (BC), both LBC and MBC enhanced the O3 mass transfer efficiency and the generation of hydroxyl radicals, thereby increasing the HA removal from an aqueous solution. At applied O3 dose of 33.3 mg/(Lcolumn h), the HA removal efficiency in BC was only 47%. When MBC and LBC were applied, it increased to 66% and 72%, respectively. Meanwhile, the O3 utilization efficiency in LBC reached 68%, which was higher than that in MBC (50%) and BC (21%). Consequently, LBC has the lowest energy consumption (EEO) for HA removal (1.4 kWh/m3), followed by MBC (1.6 kWh/m3) and BC (2.9 kWh/m3). LBC had better performance than MBC due to the adsorptive and catalytic roles of lava rock on the ozonation process. This study demonstrates the advantages of using lava rocks as packed materials in O3 bubble column over metal pall rings in intensifying O3 mass transfer and organic matters removal, which provides some insights into promoting the industrial application of O3.

Model based analysis of carbon fluxes within microalgae-bacteria flocs using respirometric-titrimetric data.

With the emerging need of nutrient recycling in resource recovery facilities, the use of microalgae-bacteria flocs has received considerable attention in the past few years. However, although the main biological processes are already known, the complex interactions occurring between algae and bacteria are not fully understood. In this work, a combined respirometric-titrimetric unit was used to assess the microorganisms' kinetics within microalgae-bacteria flocs under different growth regimes (i.e. photoautotrophic, heterotrophic and mixotrophic) and different ratios of inorganic (IC) to organic carbon (OC) (IC:OC-ratios). Using this respirometric-titrimetric data, a new model was developed, calibrated and successfully validated. The model takes into account the heterotrophic growth of bacteria, the photoautotrophic, heterotrophic and mixotrophic growth of algae and the production and consumption of extracellular polymeric substances (EPS) by both bacteria and algae. As such, the model can be used for detailed analysis of the carbon fluxes within microalgae-bacteria flocs in an efficient way. Model analysis revealed the high importance of the EPS regulatory mechanism. Firstly, under heterotrophic growth conditions, OC-uptake occurred during the first 10-15 min. This was linked with internal OC storage (49% of added OC) and EPS production (40%), as such providing carbon reserves which can be consumed during famine conditions. Moreover, the algae were able to compete with bacteria for OC. Secondly, under photoautotrophic conditions, algae used the added IC to grow (57% of added IC) and to produce EPS (29%), which consecutively stimulated heterotrophic bacteria growth (20%). Finally, under mixotrophic conditions, low IC:OC-ratios resulted in an extensive OC-storage and EPS production (50% of added C) and an enhanced microalgal CO2 reuse, resulting in an increased algal growth of up to 29%.

A semi-mechanistic model describing the influence of light and temperature on the respiration and photosynthetic growth of Chlorella vulgaris.

The influence of light and temperature on microalgae kinetics has been assessed extensively and many models have been developed. However, limited attention has been paid to the influence of light and temperature on microalgae respiration and growth under conditions inducing (strong) photoinhibition and no clear consensus has been made on which model to use. Based on experimental data collected using a combined respirometer-titrimeter, a previously developed microalgae model (Decostere et al., 2016b) was first extended with a respiration process (r = rmin + δ µ). It was found that the dark respiration (rmin) was depending on both light and temperature and increased at conditions inducing photoinhibition and heat stress. Furthermore, out of five models describing the influence of light and temperature on the microalgae growth rate, the model of Dermoun et al. (1992) was determined to be the best suited model.