500 Naturwissenschaften und Mathematik
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The management of the liquid fraction of digestate produced from the anaerobic digestion of biodegradable municipal solid waste is a difficult affair, as its land application is limited due to high ammonium concentrations and the municipal waste that water treatment plants struggle to treat due to high pollutant loads. The amount of leachate and the pollutant load in the leachate produced by landfills usually decreases with the time, which increases the capacity of landfill leachate treatment plants (LLTPs) to treat additional wastewater. In order to solve the above two challenges, the co-treatment of landfill leachate and the liquid fraction of anaerobic digestate in an industrial-scale LLTP was investigated along with the long-term impacts of the liquid fraction of anaerobic digestate on biocoenosis and its impact on LLTP operational expenses. The co-treatment of landfill leachate and liquid fraction of anaerobic digestate was compared to conventional leachate treatment in an industrial-scale LLTP, which included the use of two parallel lanes (Lane-1 and Lane-2). The average nitrogen removal efficiencies in Lane-1 (co-treatment) were 93.4%, 95%, and 92%, respectively, for C/N ratios of 8.7, 8.9, and 9.4. The average nitrogen removal efficiency in Lane-2 (conventional landfill leachate treatment), meanwhile, was 88%, with a C/N ratio of 6.5. The LLTP’s average chemical oxygen demand (COD) removal efficiencies were 63.5%, 81%, and 78% during phases one, two, and three, respectively. As the volume ratios of the liquid fraction of anaerobic digestate increased, selective oxygen uptake rate experiments demonstrated the dominance of heterotrophic bacteria over ammonium and nitrite-oxidising organisms. The inclusion of the liquid fraction of anaerobic digestate during co-treatment did not cause a significant increase in operational resources, i.e., oxygen, the external carbon source, activated carbon, and energy.
To realize a reliable and cost-effective application of high-temperature superconductive (HTS) equipment at high-voltage (HV) levels, the influence of thermally induced gas bubbles on the dielectric strength of different solid insulating materials in liquid nitrogen (LN2) was investigated. A heatable copper tape electrode arrangement was developed simulating HTS tapes with insulation in between. AC breakdown measurements were performed without and with forced boiling on insulating papers, polypropylene laminated paper (PPLP) and polyimide (PI) films. Under nucleate boiling the influence of bubbles on the dielectric strength of all materials was not significant. However under film boiling the dielectric strength of the insulating papers decreased to a level comparable to their dielectric strength in air, demonstrating the insufficient impregnation of porous materials under film boiling. For PI there was no degradation at all. PPLP retained about 70% of its basic dielectric strength in LN2.
AbstractThis paper discusses the comparison of two methods to achieve thermal comfort utilising air conditioning (AC) system in a small indoor space – adaptive control and fuzzy control. Thermal comfort indoors is performed to provide comfortability individually or for a group of people. Due to the small indoor space which usually a bit cramped, crowded and less airy, the ambience can be very uncomfortable either for doing sedentary or active work, thus the AC system can be very useful to provide thermal comfort. Both methods can be utilised depending on how thermal comfort is viewed and how the level of thermal comfort is decided. Every method has its own advantage and limitations, and will be covered in this paper as well.
Climate change includes the change of the long-term average values and the change of the tails of probability density functions, where the extreme events are located. However, obtaining average values are more straightforward than the high temporal resolution information necessary to catch the extreme events on those tails. Such information is difficult to get in areas lacking sufficient rain stations. Thanks to the development of Satellite Precipitation Estimates with a daily resolution, this problem has been overcome, so Extreme Precipitation Indices (EPI) can be calculated for the entire Colombian territory. However, Colombia is strongly affected by the ENSO (El Niño—Southern Oscillation) phenomenon. Therefore, it is pertinent to ask if the EPI’s long-term change due to climate change is more critical than the anomalies due to climate variability induced by the warm and cold phases of ENSO (El Niño and La Niña, respectively). In this work, we built EPI annual time series at each grid-point of the selected Satellite Precipitation Estimate (CHIRPSv2) over Colombia to answer the previous question. Then, the Mann-Whitney-Wilcoxon test was used to compare the samples drawn in each case (i.e., change tests due to both long-term and climatic variability). After performing the analyses, we realized that the importance of the change depends on the region analyzed and the considered EPI. However, some general conclusions became evident: during El Niño years (La Niña), EPI’s anomaly follows the general trend of reduction -drier conditions- (increase; -wetter conditions-) observed in Colombian annual precipitation amount, but only on the Pacific, the Caribbean, and the Andean region. In the Eastern plains of Colombia (Orinoquía and Amazonian region), EPI show a certain insensitivity to change due to climatic variability. On the other hand, EPI’s long-term changes in the Pacific, the Caribbean, and the Andean region are spatially scattered. Still, long-term changes in the eastern plains have a moderate spatial consistency with statistical significance.
Abstract
Two types (with and without a hydrolysis stabilizer) of polyamide 6.6 (PA6.6) reinforced with 30% w/w glass fibres were examined against the influence of automotive cooling fluids, e.g. ethylene glycol aqueous solutions. The overall goal was to find a methodology to compare the performance of PA6.6 materials against the impacts of the hydrolysis environment. The stabilizer effect on the hydrolytic resistance of the materials was assessed using tensile tests according to ISO 527, and their strain‐at‐break values were evaluated in more detail. The degradation mechanism of both PA types was monitored by infrared spectroscopy and SEM. The material lifetime was described by the Arrhenius equation. The results show that the hydrolysis stabilizer operates effectively at low temperature but exhibits weak performance above 130 °C, which is explained by faster consumption of the stabilizing agent. © 2021 The Authors. Polymer International published by John Wiley & Sons Ltd on behalf of Society of Industrial Chemistry.
In this work, supported cellulose acetate (CA) mixed matrix membranes (MMMs) were prepared and studied concerning their gas separation behaviors. The dispersion of carbon nanotube fillers were studied as a factor of polymer and filler concentrations using the mixing methods of the rotor–stator system (RS) and the three-roll-mill system (TRM). Compared to the dispersion quality achieved by RS, samples prepared using the TRM seem to have slightly bigger, but fewer and more homogenously distributed, agglomerates. The green γ-butyrolactone (GBL) was chosen as a polyimide (PI) polymer-solvent, whereas diacetone alcohol (DAA) was used for preparing the CA solutions. The coating of the thin CA separation layer was applied using a spin coater. For coating on the PP carriers, a short parameter study was conducted regarding the plasma treatment to affect the wettability, the coating speed, and the volume of dispersion that was applied to the carrier. As predicted by the parameter study, the amount of dispersion that remained on the carriers decreased with an increasing rotational speed during the spin coating process. The dry separation layer thickness was varied between about 1.4 and 4.7 μm. Electrically conductive additives in a non-conductive matrix showed a steeply increasing electrical conductivity after passing the so-called percolation threshold. This was used to evaluate the agglomeration behavior in suspension and in the applied layer. Gas permeation tests were performed using a constant volume apparatus at feed pressures of 5, 10, and 15 bar. The highest calculated CO2/N2 selectivity (ideal), 21, was achieved for the CA membrane and corresponded to a CO2 permeability of 49.6 Barrer.
The oxidation of cumene and following cleavage of cumene hydroperoxide (CHP) with sulfuric acid (Hock rearrangement) is still, by far, the dominant synthetic route to produce phenol. In 2020, the global phenol market reached a value of 23.3 billion US$ with a projected compound annual growth rate of 3.4% for 2020–2025. From ecological and economical viewpoints, the key step of this process is the cleavage of CHP. One sought-after way to likewise reduce energy consumption and waste production of the process is to substitute sulfuric acid with heterogeneous catalysts. Different types of zeolites, silicon-based clays, heteropoly acids, and ion exchange resins have been investigated and tested in various studies. For every type of these solid acid catalysts, several materials were found that show high yield and selectivity to phenol. In this mini-review, first a brief introduction and overview on the Hock process is given. Next, the mechanism, kinetics, and safety aspects are summarized and discussed. Following, the different types of heterogeneous catalysts and their performance as catalyst in the Hock process are illustrated. Finally, the different approaches to substitute sulfuric acid in the synthetic route to produce phenol are briefly concluded and a short outlook is given.
Different methods have been proposed for in situ root-length density (RLD) measurement. One widely employed is the time-consuming sampling of soil cores or monoliths (MO). The profile wall (PW) method is a less precise, but faster and less laborious alternative. However, depth-differentiated functions to convert PW RLD estimates to MO RLD measurements have not yet been reported. In this study, we perform a regression analysis to relate PW results to MO results and determine whether calibration is possible for distinct crop groups (grasses, brassicas and legumes) consisting of pure and mixed stands, and whether soil depth affects this calibration. The methods were applied over two years to all crop groups and their absolute and cumulative RLD were compared using a linear (LR) and multiple linear (MLR) regression. PW RLD was found to highly underestimate MO RLD in absolute values and in highly rooted areas. However, a close agreement between both methods was found for cumulative root-length (RL) when applying MLR, highlighting the influence of soil depth. The level of agreement between methods varied strongly with depth. Therefore, the application of PW as the main RLD estimation method can provide reliable estimates of cumulative root distribution traits of cover crops.
The increase in greenhouse gas emissions, mainly due to the burning of fossil fuels and land use change, has led to changes in the global climate. Agriculture is one of the economic sectors most vulnerable to the impacts generated by climate change. For this reason, the challenge facing humanity today is to develop innovative solutions to address the complexity of agricultural sustainability.
On the other hand, sugarcane is one of the crops that emits the most pollutants into the atmosphere, mainly due to the burning of sugarcane before and after harvesting. Most of these atmospheric pollutants are precursors of climate change and have an impact on the health and quality of life of communities. Moreover, this agricultural practice causes the gradual deterioration of the soil, directly affecting sugarcane production. Consequently, several sugarcane-producing countries have established regulations or dispositions to eliminate this agricultural practice, and one option to eliminate it is the mechanization of harvesting. However, its implementation implies social, environmental, and economic impacts that must be analyzed systemically to avoid potential failures during the technological transition process. It is for this reason that this research, through the MICMAC method, focused on identifying the variables associated with the reduction of sugarcane burning in Campos dos Goytacazes and Tamasopo, to subsequently analyze their direct and indirect interrelationship, and, thus, determine the opportunities and limitations of each locality for the reduction of sugarcane burning.
Through this analysis, it became evident that although the technological transition is an imminent step for the sustainability of sugarcane cultivation, certain factors such as legislation, technological innovation, and the perception of the stakeholders regarding the consequences of sugarcane burning, is what defines in the study sites the speed and subsequent success of this process of change towards green harvesting.
Table Tennis Tutor: Forehand Strokes Classification Based on Multimodal Data and Neural Networks
(2021)
Beginner table-tennis players require constant real-time feedback while learning the fundamental techniques. However, due to various constraints such as the mentor’s inability to be around all the time, expensive sensors and equipment for sports training, beginners are unable to get the immediate real-time feedback they need during training. Sensors have been widely used to train beginners and novices for various skills development, including psychomotor skills. Sensors enable the collection of multimodal data which can be utilised with machine learning to classify training mistakes, give feedback, and further improve the learning outcomes. In this paper, we introduce the Table Tennis Tutor (T3), a multi-sensor system consisting of a smartphone device with its built-in sensors for collecting motion data and a Microsoft Kinect for tracking body position. We focused on the forehand stroke mistake detection. We collected a dataset recording an experienced table tennis player performing 260 short forehand strokes (correct) and mimicking 250 long forehand strokes (mistake). We analysed and annotated the multimodal data for training a recurrent neural network that classifies correct and incorrect strokes. To investigate the accuracy level of the aforementioned sensors, three combinations were validated in this study: smartphone sensors only, the Kinect only, and both devices combined. The results of the study show that smartphone sensors alone perform sub-par than the Kinect, but similar with better precision together with the Kinect. To further strengthen T3’s potential for training, an expert interview session was held virtually with a table tennis coach to investigate the coach’s perception of having a real-time feedback system to assist beginners during training sessions. The outcome of the interview shows positive expectations and provided more inputs that can be beneficial for the future implementations of the T3.