Waste to Carbon: Influence of Structural Modification on VOC Emission Kinetics from Stored Carbonized Refuse-Derived Fuel

The torrefaction of municipal solid waste is one of the solutions related to the Waste to Carbon concept, where high-quality fuel—carbonized refuse-derived fuel (CRDF)—is produced. An identified potential problem is the emission of volatile organic compounds (VOCs) during CRDF storage. Kinetic emission parameters have not yet been determined. It was also shown that CRDF can be pelletized for energy densification and reduced volume during storage and transportation. Thus, our working hypothesis was that structural modification (via pelletization) might mitigate VOC emissions and influence emission kinetics during CRDF storage. Two scenarios of CRDF structural modification on VOC emission kinetics were tested, (i) pelletization and (ii) pelletization with 10% binder addition and compared to ground (loose) CRDF (control). VOC emissions from simulated sealed CRDF storage were measured with headspace solid-phase microextraction and gas chromatography–mass spectrometry. It was found that total VOC emissions from stored CRDF follow the first-order kinetic model for both ground and pelletized material, while individual VOC emissions may deviate from this model. Pelletization significantly decreased (63%~86%) the maximum total VOC emission potential from stored CDRF. Research on improved sustainable CRDF storage is warranted. This could involve VOC emission mechanisms and environmental-risk management

The Jerusalem Balsam–a case study of a 150-year-old sample

The Jerusalem Balsam (JB) was formulated in the pharmacy of the Saint Savior monastery in the old city of Jerusalem in 1719. According to traditional sources, JB was based on an ethanolic extract of an herbal mixture. Several variations of the formulation could be found in European Pharmacopoeias, mostly recommended as an antiseptic product [1]. During the current study, an original sample of JB prepared approximately in the year 1870, as well as four contemporary samples of different variations in composition, were analyzed by gas chromatography coupled with mass spectrometry with the aid of solid phase microextraction, as well as by the liquid injection approach. About sixty different compounds have been identified in the materials–mostly essential-oil constituents. Additionally, the LC-MS and NMR (1H, HSQC, and TOCSY) profiles have been measured for the analyzed samples. Several fingerprint compounds, specific for the herbal material were found in this way. Furthermore, JB samples were tested for cytotoxicity. Two normal (J774E.1 and NIH/3T3) and two cancer cell lines (CLBL-1 [2] and CLBL70 [3]) were used in this experiment. All tested JB samples showed no cytotoxic or were very slightly toxic to normal cell lines. Only one JB sample, the almost 150-year-old one, showed a strong cytotoxic activity but only towards cancer cell lines, with the efficiency of 80-90%

Thermodynamic and Quality Performance Studies for Drying Kiwi in Hybrid Hot Air-Infrared Drying with Ultrasound Pretreatment

The present study examined the effect of ultrasonic pretreatment at three time the levels of 10, 20 and 30 min on some thermodynamic (effective moisture diffusivity coefficient(Deff), drying time, specific energy consumption (SEC), energy efficiency, drying efficiency, and thermal efficiency) and physical (color and shrinkage) properties of kiwifruit under hybrid hot air-infrared(HAI) dryer at different temperatures (50, 60 and 70 °C) and different thicknesses (4, 6 and 8 mm). A total of 11 mathematical models were applied to represent the moisture ratio (MR) during the drying of kiwifruit. The fitting of MR mathematical models to experimental data demonstrated that the logistic model can satisfactorily describe the MR curve of dried kiwifruit with a correlation coefficient (R2) of 0.9997, root mean square error (RMSE) of 0.0177 and chi-square (χ2) of 0.0007. The observed Deff of dried samples ranged from 3.09 × 10−10 to 2.26 × 10−9 m2/s. The lowest SEC, color changes and shrinkage were obtained as 36.57 kWh/kg, 13.29 and 25.25%, respectively. The highest drying efficiency, energy efficiency, and thermal efficiency were determined as 11.09%, 7.69% and 10.58%, respectively. The results revealed that increasing the temperature and ultrasonic pretreatment time and decreasing the sample thickness led to a significant increase (p < 0.05) in drying efficiency, thermal efficiency, and energy efficiency, while drying time, SEC and shrinkage significantly decreased (p < 0.05)

Thermodynamic and Quality Performance Studies for Drying Kiwi in Hybrid Hot Air-Infrared Drying with Ultrasound Pretreatment

The present study examined the effect of ultrasonic pretreatment at three time the levels of 10, 20 and 30 min on some thermodynamic (effective moisture diffusivity coefficient(Deff), drying time, specific energy consumption (SEC), energy efficiency, drying efficiency, and thermal efficiency) and physical (color and shrinkage) properties of kiwifruit under hybrid hot air-infrared(HAI) dryer at different temperatures (50, 60 and 70 °C) and different thicknesses (4, 6 and 8 mm). A total of 11 mathematical models were applied to represent the moisture ratio (MR) during the drying of kiwifruit. The fitting of MR mathematical models to experimental data demonstrated that the logistic model can satisfactorily describe the MR curve of dried kiwifruit with a correlation coefficient (R2) of 0.9997, root mean square error (RMSE) of 0.0177 and chi-square (χ2) of 0.0007. The observed Deff of dried samples ranged from 3.09 × 10−10 to 2.26 × 10−9 m2/s. The lowest SEC, color changes and shrinkage were obtained as 36.57 kWh/kg, 13.29 and 25.25%, respectively. The highest drying efficiency, energy efficiency, and thermal efficiency were determined as 11.09%, 7.69% and 10.58%, respectively. The results revealed that increasing the temperature and ultrasonic pretreatment time and decreasing the sample thickness led to a significant increase (p SEC and shrinkage significantly decreased (p < 0.05)

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

Drying is one of the common procedures in the food processing steps. The moisture content (MC) is also of crucial significance in the evaluation of the drying technique and quality of the final product. However, conventional MC evaluation methods suffer from several drawbacks, such as long processing time, destruction of the sample and the inability to determine the moisture of single grain samples. In this regard, the technology and knowledge of hyperspectral imaging (HSI) were addressed first. Then, the reports on the use of this technology as a rapid, non-destructive, and precise method were explored for the prediction and detection of the MC of crops during their drying process. After spectrometry, researchers have employed various pre-processing and merging data techniques to decrease and eliminate spectral noise. Then, diverse methods such as linear and multiple regressions and machine learning were used to model and predict the MC. Finally, the best wavelength capable of precise estimation of the MC was reported. Investigation of the previous studies revealed that HSI technology could be employed as a valuable technique to precisely control the drying process. Smart dryers are expected to be commercialised and industrialised soon by the development of portable systems capable of an online MC measurement

Optimization and Prediction of the Drying and Quality of Turnip Slices by Convective-Infrared Dryer under Various Pretreatments by RSM and ANFIS Methods

Drying can prolong the shelf life of a product by reducing microbial activities while facilitating its transportation and storage by decreasing the product weight and volume. The quality factors of the drying process are among the important issues in the drying of food and agricultural products. In this study, the effects of several independent variables such as the temperature of the drying air (50, 60, and 70 °C) and the thickness of the samples (2, 4, and 6 mm) were studied on the response variables including the quality indices (color difference and shrinkage) and drying factors (drying time, effective moisture diffusivity coefficient, specific energy consumption (SEC), energy efficiency and dryer efficiency) of the turnip slices dried by a hybrid convective-infrared (HCIR) dryer. Before drying, the samples were treated by three pretreatments: microwave (360 W for 2.5 min), ultrasonic (at 30 °C for 10 min) and blanching (at 90 °C for 2 min). The statistical analyses of the data and optimization of the drying process were achieved by the response surface method (RSM) and the response variables were predicted by the adaptive neuro-fuzzy inference system (ANFIS) model. The results indicated that an increase in the dryer temperature and a decline in the thickness of the sample can enhance the evaporation rate of the samples which will decrease the drying time (40–20 min), SEC (from 168.98 to 21.57 MJ/kg), color difference (from 50.59 to 15.38) and shrinkage (from 67.84% to 24.28%) while increasing the effective moisture diffusivity coefficient (from 1.007 × 10−9 to 8.11 × 10−9 m2/s), energy efficiency (from 0.89% to 15.23%) and dryer efficiency (from 2.11% to 21.2%). Compared to ultrasonic and blanching, microwave pretreatment increased the energy and drying efficiency; while the variations in the color and shrinkage were the lowest in the ultrasonic pretreatment. The optimal condition involved the temperature of 70 °C and sample thickness of 2 mm with the desirability above 0.89. The ANFIS model also managed to predict the response variables with R2 > 0.96