Laboratoř integrace procesů

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Oxyfuel Combustion Makes Carbon Capture More Efficient
(AMER CHEMICAL SOC, 2024-01-10) Fózer, Dániel; Mizsey, Peter; Varbanov, Petar Sabev; Szanyi, Ágnes; Talei, Saeed
Fossil energy carriers cannot be totally replaced, especially if nuclear power stations are stopped and renewable energy is not available. To fulfill emission regulations, however, points such as emission sources should be addressed. Besides desulfurization, carbon capture and utilization have become increasingly important engineering activities. Oxyfuel technologies offer new options to reduce greenhouse gas emissions; however, the use of clean oxygen instead of air can be dangerous in the case of certain existing technologies. To replace the inert effect of nitrogen, carbon dioxide is mixed with oxygen gas in the case of such air combustion processes. In this work, the features of carbon capture in five different flue gases of air combustion and such oxyfuel combustion where additional carbon dioxide is mixed with clean oxygen are studied and compared. The five different flue gases originate from the gas-fired power plant, coal-fired power plant, coal-fired combined heat and power plant, the aluminum production industry, and the cement manufacturing industry. Monoethanolamine, which is an industrially preferred solvent for carbon dioxide capture from gas streams at low pressures, is selected as an absorbent, and the same amount of carbon dioxide is captured; that is, always that amount of carbon dioxide is captured, which is the result of the fossil combustion process. ASPEN Plus is used for mathematical modeling. The results show that the oxyfuel combustion cases need significantly less energy, especially at high carbon dioxide removal rates, e.g., higher than 90%, than that of the air combustion cases. The savings can even be as high as 84%. Moreover, 100% carbon capture was also be completed. This finding can be due to the fact that in the oxyfuel combustion cases, the carbon dioxide concentration is much higher than that of the air combustion cases because of the inert carbon dioxide and that higher carbon dioxide concentration results in a higher driving force for the mass transfer. The oxyfuel combustion processes also show another advantage over the air combustion processes since no nitrogen oxides are produced in the combustion process.
ENERGY MANAGEMENT OF BUILDINGS WITH A FOCUS ON MUNICIPALITIES
(UNIV MARIBOR PRESS, 2024-02-06) Smutková, Karolína; Gregor, Jiří; Varbanov, Petar Sabev; Stehlík, Petr
Due to the climate situation, the EU policy, the impact of the coronavirus pandemic and the war in Ukraine, it is necessary for municipalities to take a conceptual approach to their energy sector. A big topic of this issue and also the subject of this paper is the energy optimization of municipal buildings. The reality in the Czech Republic is that municipalities, with a few exceptions, do not combine data on energy and water consumption with the actual technical condition of the buildings concerned, so they have no basis for decision-making and individual projects are often dealt with in an unconceptual and ad-hoc manner. The methodology is based on an analysis of the situation in the South Moravian Region and a questionnaire survey of the Union of Towns and Municipalities of the Czech Republic. This article identifies the key areas that affect the energy efficiency of buildings and therefore specific data should be collected from these areas to form the basis for setting up the energy management of the city.
A waste separation system based on sensor technology and deep learning: A simple approach applied to a case study of plastic packaging waste
(ELSEVIER SCI LTD, 2024-04-15) Pučnik, Rok; Dokl, Monika; Fan, Yee Van; Vujanović, Annamaria; Novak Pintarič, Zorka; Aviso, Kathleen B.; Tan, Raymond R; Pahor, Bojan; Kravanja, Zdravko; Čuček, Lidija
Plastic waste pollution is a challenging and complex issue caused mainly by high consumption of single-use plastics and the linear economy of "extract-make-use-throw". Improvements in recycling efficiency, behaviour changes, circular business models, and a more precise waste management system are essential to reduce the volume of plastic waste. This paper proposes a simplified conceptual model for a smart plastic waste separation system based on sensor technology and deep learning (DL) to facilitate recovery and recycling. The proposed system could be applied either at the source (in a smart waste bins) or in a centralised sorting facility. Two smart separation systems have been investigated: i) the one utilising 6 sensors (near-infrared (NIR), humidity, temperature, CO2, CH4, and a laser profile sensor) and ii) the one with an RGB camera to separate packaging materials based on their composition, size, cleanliness, and appearance. Simulations with a case study showed that for a camera-based sorting, Inception-v3, a DL model based on convolution neural networks (CNN), achieved the best overall accuracy (78%) compared to ResNet-50, MobileNet-v2, and DenseNet-201. In addition, the separation resulted in a higher number of misclassified items in bins, as it focused solely on appearance rather than material composition. Sensor-based sorting faced limitations, particularly with dark colouration and organic matter entrapment. Combining the information from sensors and cameras could potentially mitigate the limitations of each individual method, thus resulting in higher purity of the separated fractions.
Optimizing plastics recycling networks
(Elsevier, 2023-06-14) Aviso, Kathleen B.; Baquillas, Jonna C.; Chiu, Anthony S. F.; Jiang, Peng; Fan, Yee Van; Varbanov, Petar Sabev; Klemeš, Jiří; Tan, Raymond R
Plastic pollution is a serious sustainability issue facing the global community. Fragments of macroplastics and microplastics pollute terrestrial and aquatic ecosystems, while nanoplastics can also degrade air quality. The recent COVID-19 pandemic also exacerbated the problem. Large-scale commercial use of plastics recycling technologies is hindered by various socio-economic barriers. In particular, cross-contamination of mixed plastic streams is prevalent due to imperfect waste segregation. The concept of Plastics Recycling Networks is intro-duced to facilitate planning of reverse supply chains using optimization models. In this work, basic Linear Programming and Mixed-Integer Linear Programming models are developed for matching sources of waste plastic with plastic recycling plants within Plastics Recycling Networks. These models allocate streams while considering the ability of recycling plants to tolerate contaminants. Two illustrative case studies are analyzed to demonstrate the effectiveness of the models, and policy implications for mitigation of plastic pollution are dis-cussed. These models enable planning of networks with some tolerance for contaminants in plastic waste, and can be the basis for developing new variants to handle additional real world aspects.
Conversion of novel non-edible Bischofia javanica seed oil into methyl ester via recyclable zirconia-based phyto-nanocatalyst: A circular bioeconomy approach for eco-sustenance
(Elsevier, 2023-05-01) Ameen, Maria; Zafar, Muhammad; Ramadan, Mohamed Fawzy; Ahmad, Mushtaq; Makhkamov, Trobjon; Bokhari, Syed Awais Ali Shah; Mubashir, Muhammad; Chuah, Lai Fatt; Show, Pau Loke
The current study assesses Bischofia javanica Blume's potential as novel non-edible seed oil for environmentally benign biodiesel production using phyto-nanocatalyst, i.e., green nanoparticles (NPs) of zirconium oxide (ZrO2) synthesized with aqueous leaf extract of the same plant via the biological method. Using response surface methods, the maximum yield (95.8 wt.%) was obtained at a 1:6 oil-to-methanol molar ratio, 2.5 wt.% catalyst loading, 70 degrees C reaction temperature and 2 h of reaction time. In addition, advanced analytical techniques such as Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) with energy dispersive X-ray (EDX) were used to characterize green nanoparticles. Six peaks in the GC-MS spectrum were identified, showing the presence of six different methyl esters such as methyl palmitate, methyl linoleate, methyl oleate, methyl stearate, methyl linolenate and methyl 11-eicosenoate. In addition, 1HNMR and 13CNMR confirmed the high conversion yield of the esters group with distinct peaks at 3.649 ppm and 174.19 ppm. Biodiesel prepared from Bischofia javanica has fuel qualities that meet international standards. Fuel properties were found analogous to international standards viz. ASTM and EN. These include flash point (80 degrees C), density at 15 degrees C (0.8623 kg/L), kinematic viscosity (5.32 mm2/s), cloud (-11 degrees C), pour point (-8 degrees C) and sulphur content of 0.00047 wt.%. The results indicate that the green nanocatalyst and synthesized biodiesel from the Bischofia javanica appear to be highly reliable and cost-effective candidates for producing sustainable and eco-friendly biodiesel to overcome energy crises and climatic deteriorations, which would assist in the shift from a linear to a circular economy.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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