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SSRN 2023年

作者： Santos, Diego Haltiery Rosa, Laura Pereira Alves, Cleidson Rosa Simão, Lisandro Arcaro, Sabrina Klegues Montedo, Oscar Rubem Raupp-Pereira, Fabiano Graduate Program in Materials Science and Engineering University of the Extreme South of Santa Catarina Criciúma88806-000 Brazil Department of Civil Engineering Federal Institute of Santa Catarina Criciúma88813-600 Brazil Research Group on Sustainability and Waste Management Postgraduate Program in Environmental Technology University of Ribeirão Preto Ribeirão Preto14096-900 Brazil Brazil

The growing disparity between the high extraction of natural resources and low use of waste as alternative mineral resources will aggravate the scarcity of natural reserves. Therefore, the current linear economy model must be converted to sustainable economic models, such as the circular economy. To achieve this transition, it is important that waste recovery strategies are implemented with a continuous search for solutions for these materials. Thus, this study investigates the waste from the processing of nepheline syenite stone, to promote its valorization as an alternative mineral resource. The classification, potentiality, quantity/viability and applicability (CPQvA) criteria are used as tools to aid decision-making for the waste valorization. The environmental, physical, chemical, morphological, and durability characteristics of nepheline syenite waste (NSW) are analyzed. The results showed evidence for the substitution of NSW for up to 100% of fine aggregates and 25% of Portland cement in civil construction. Furthermore, NSW yields recoveries of more than 90% of potassium for use in agriculture, and up to 70% of iron ore for use in steelworks. Therefore, the results indicate that NSW is viable for different applications, contributing to industrial symbiosis and a strategy for advancing the circular economy. © 2023, The Authors. All rights reserved.

关键词： Sustainable development

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Challenges and opportunities for third-generation ethanol production:A critical review

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engineering Microbiology 2023年第1期3卷 22-36页

作者： Caroline Müller Thamarys Scapini Alan Rempel Ederson Rossi Abaide Aline Frumi Camargo Mateus Torres Nazari Viviani Tadioto Charline Bonatto Marcus Vinícius Tres Giovani Leone Zabot Luciane Maria Colla Helen Treichel Sérgio Luiz Alves Jr Laboratory of Yeast Biochemistry Federal University of Fronteira SulCampus ChapecóSC 484Km 2ChapecóSCBrazil Laboratory of Microbiology and Bioprocess Environmental Science and TechnologyFederal University of Fronteira SulCampus ErechimRS 135200ErechimRSBrazil Graduate Program in Civil and Environmental Engineering University of Passo FundoBR 285Passo FundoRSBrazil Department of Chemical Engineering Federal University of Santa Maria1000Roraima AvenueSanta MariaRS 97105-900Brazil Laboratory of Agroindustrial Processes Engineering Federal University of Santa Maria1040Sete de Setembro st.Cachoeira do SulRSBrazil

In recent decades,third-generation(3G)biofuels have become a more attractive method of fuel production,as algae cultivation does not infringe on resources needed for food ***,algae can adapt to different environments,has high photosynthetic efficiency(CO_(2)fixation),and has a high potential for carbohydrate *** prevalence of algae worldwide demonstrates its ability to adapt to different environments and climates,proving its biodiversity and *** can be grown in wastewater,seawater,and even sewage,thus ensuring a lower water footprint and greater energy efficiency during algal biomass *** of this,the optimization of 3G ethanol production appears to be an excellent alternative to mitigate environmental impacts and increase energy and food *** critical review presents(i)the stages of cultivation and processing of micro and macroalgae;(ii)the selection of yeasts(through engineering and/or bioprospecting)to produce ethanol from these biomasses;(iii)the potential of seawater-based facilities to reduce water footprint;and(iv)the mass and energy balances of 3G ethanol production in the world energy *** article is,above all,a brainstorm on the environmental viability of algae bioethanol.

关键词： Algae ethanol Biomass Energy balance Seawater Water footprint Yeasts

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Robust Causality and False Attribution in Data-Driven Earth Science Discoveries

arXiv

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arXiv 2022年

作者： Eldhose, Elizabeth Chauhan, Tejasvi Chandel, Vikram Ghosh, Subimal Ganguly, Auroop R. Department of Civil Engineering Indian Institute of Technology Bombay Mumbai India Interdisciplinary Program in Climate Studies Indian Institute of Technology Bombay Mumbai India Sustainability and Data Sciences Laboratory Department of Civil and Environmental Engineering Northeastern University BostonMA United States Pacific Northwest National Laboratory RichlandWA United States

Causal and attribution studies are essential for earth scientific discoveries and critical for informing climate, ecology, and water policies. However, the current generation of methods needs to keep pace with the complexity of scientific and stakeholder challenges and data availability combined with the adequacy of data-driven methods. Unless carefully informed by physics, they run the risk of conflating correlation with causation or getting overwhelmed by estimation inaccuracies. Given that natural experiments, controlled trials, interventions, and counterfactual examinations are often impractical, information-theoretic methods have been developed and are being continually refined in the earth sciences. Here we show that transfer entropy-based causal graphs, which have recently become popular in the earth sciences with high-profile discoveries, can be spurious even when augmented with statistical significance. We develop a subsample-based ensemble approach for robust causality analysis. Simulated data, and observations in climate and ecohydrology, suggest the robustness and consistency of this approach. © 2022, CC BY.

关键词： Risk perception

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Quantum Kernel-Based Long Short-term Memory for Climate Time-Series Forecasting

Quantum Kernel-Based Long Short-term Memory for Climate Time...

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Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Yu-Chao Hsu Nan-Yow Chen Tai-Yu Li Po-Heng Henry Lee Kuan-Cheng Chen NARlabs National Center for High-Performance Computing Hsinchu Taiwan Cross College Elite Program National Cheng Kung University Tainan Taiwan National Synchrotron Radiation Research Center Hsinchu Taiwan Department of Electrical and Electronic Engineering Imperial College London London UK Department of Civil Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

We present the Quantum Kernel-Based Long Short-Term Memory (QK-LSTM) network, which integrates quantum kernel methods into classical LSTM architectures to enhance predictive accuracy and computational efficiency in climate time-series forecasting tasks, such as Air Quality Index (AQI) prediction. By embedding classical inputs into high-dimensional quantum feature spaces, QK-LSTM captures intricate nonlinear dependencies and temporal dynamics with fewer trainable parameters. Leveraging quantum kernel methods allows for efficient computation of inner products in quantum spaces, addressing the computational challenges faced by classical models and variational quantum circuit-based models. Designed for the Noisy Intermediate-Scale Quantum (NISQ) era, QK-LSTM supports scalable hybrid quantum-classical implementations. Experimental results demonstrate that QK-LSTM outperforms classical LSTM networks in AQI forecasting, showcasing its potential for environmental monitoring and resource-constrained scenarios, while highlighting the broader applicability of quantum-enhanced machine learning frameworks in tackling large-scale, high-dimensional climate datasets.

关键词： Quantum computing Accuracy Computational modeling Time series analysis Predictive models Computational efficiency Forecasting Kernel Long short term memory Meteorology

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Optimizing dispersion of torrefied spent coffee grounds for enhanced biochar-EVA composite properties through sodium percarbonate-assisted treatment

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Journal of Industrial and engineering Chemistry 2025年

作者： Lee, Kuan-Ting Gabriela, Situmorang Chen, Wei-Hsin Rajendran, Saravanan Selvarajoo, Anurita Department of Chemical and Materials Engineering Tunghai University Taichung407 Taiwan International Master Degree Program on Energy Engineering National Cheng Kung University Tainan701 Taiwan Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Instituto de Alta Investigación Universidad de Tarapacá Arica1000000 Chile Department of Civil Engineering Faculty of Science and Engineering University of Nottingham Malaysia

This study aims to optimize biochar by combining 10 % sodium percarbonate with 90 % spent coffee grounds and torrefying at 300 °C for 30 min. Biochar enhances black color dispersion in a composite when blending the optimal biochar and ethylene vinyl acetate. The maximum carbon content of the optimal biochar is 59.97 %, exhibiting similar dispersion, packing density, pore size, and contact angle to carbon black. The optimal biochar's specific surface area and total pore volume are 7.12 m2·g−1 and 0.0018 cm3·g−1, respectively, 2.9 times and 1.2 times that of untreated torrefied spent coffee grounds with SP treated. The mechanical properties of the composite, which is blended with 15 wt% of the optimal biochar to ethylene vinyl acetate through trade-off analysis, indicate a tensile strength and Young's modulus of 1.03 MPa and 9.69 MPa, respectively. As the amount of blended optimal biochar increases, the tensile strength decreases while Young's modulus increases. Compared with a composite blended with the same 15 wt% of carbon black, the tensile strength and Young's modulus are 0.77 MPa and 9.55 MPa, respectively. In conclusion, the optimal biochar is a potential alternative material that could replace carbon black. This finding aligns with the developmental direction of achieving negative carbon emissions, promoting a circular economy and valorizing waste. © 2025 The Korean Society of Industrial and engineering Chemistry

关键词： Tensile strength

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Integrated Photoelectrochemical (Pec)-Forward Osmosis (Fo) System for Hydrogen Production and Fertigation Application

SSRN

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SSRN 2023年

作者： Zavahir, Sifani Elmakki, Tasneem Gulied, Mona Shon, Ho Kyong Park, Hyunwoong Kakosimos, Konstantinos E. Han, Dong Suk Center for Advanced Materials Qatar University PO Box 2713 Doha Qatar Center for Technology in Water and Wastewater School of Civil and Environmental Engineering University of Technology Sydney SydneyNSW2007 Australia School of Energy Engineering Kyungpook National University Daegu41566 Korea Republic of Chemical Engineering Program Texas A&M University at Qatar Doha Qatar Department of Chemical Engineering Qatar University PO Box Doha2713 Qatar

An integrated system with a photoelectrochemical (PEC) unit and forward osmosis (FO) in tandem operation was proposed in this study to combat water, energy, and food (WEF) deficiency. In an engineered approach, a combination of ammonium sulfite and ammonium sulfate solution was used to represent the wet flue gas desulfurization products of the ammonia scrubbing process commonly employed in oil and gas producing countries. In a continuous operating system, we showed that a sulfurous solution in the PEC process was oxidized under simulated sunlight to produce hydrogen, the ultimate clean energy, at a reduced titania nanotube array (TNA) working electrode (Energy). Then, the oxidized sulfurous solution entering the draw solution compartment of the FO unit was diluted when the system operated against simulated brackish water as the feed solution (Water). Recirculation of the draw solution effluent ensures continuous operation of the PEC and FO systems. Further application of this draw solution effluent as a cultivation solution to a basil plant at a certain time point showed visually favorable growth compared to the case supplied with tap water (Food). © 2023, The Authors. All rights reserved.

关键词： Effluents

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Optimizing H-Darrieus Wind Turbine Performance with Double-Deflector Design

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Energies 2024年第2期17卷 503页

作者： Chen, Wei-Hsin Lam, Trinh Tung Chang, Min-Hsing Jin, Liwen Chueh, Chih-Che Augusto, Gerardo Lumagbas Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan International Degree Program on Energy Engineering National Cheng Kung University Tainan701 Taiwan Department of Energy Engineering National United University Miaoli360 Taiwan Institute of Building Environment and Sustainable Technology School of Human Settlements and Civil Engineering Xi’an Jiaotong University Xi’an712000 China Mechanical Engineering Department De La Salle University 2401 Taft Avenue Manila0922 Philippines

This study aims to improve an H-Darrieus vertical-axis wind turbine (VAWT) by imposing a novel double-deflector design. A computational fluid dynamics (CFD) model was implemented to examine the aerodynamic characteristics of the VAWT with double deflectors. Geometrics factors related to the locations of the two deflectors were considered, and the orthogonal array based on the Taguchi method was constructed for CFD simulation. The CFD results were further provided as the training data for the artificial neural network (ANN) to forecast the optimal configuration. The results indicate that the performance of a VAWT with a double-deflector design could exceed that of a bare VAWT or that of one using a single deflector. The mean power coefficient for a bare VAWT is 0.37, although it could be much higher with a proper setup using double deflectors. The prediction of ANN analysis is consistent with the result of CFD simulation, in which the difference between the ANN prediction and CFD simulation is generally less than 4.48%. The result confirms the accuracy of the prediction of the optimal VAWT performance with a double-deflector design. © 2024 by the authors.

关键词： Neural networks

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Theoretical Prediction of Drying Shrinkage of Concretes Containing Fine Recycled Aggregate

SSRN

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SSRN 2022年

作者： Rivetti, Marianna Luna Sousa de Andrade, Gabriella Puente Lima, Paulo Roberto Lopes Filho, Romildo Dias Toledo Polytechnic School of UFBA Civil Engineering Graduation Program R. Prof. Aristídes Novis 2 - Federação Salvador Brazil Rua Moniz Aragão Nº360 Rio de Janeiro Brazil Technology Department Civil and Environmental Engineering Graduation Program Av. Transnordestina s/n Feira de Santana Brazil

The existing models for the prediction of deformations resulting from drying shrinkage of concrete still cannot describe the drying shrinkage of concrete with recycled fine aggregate. This study presents the shrinkage strain obtained experimentally and that calculated with theoretical models. Two classes of concrete were produced with the substitution of 0%, 20%, and 50% of fine natural aggregate for fine recycled aggregate. The theoretical analysis indicates that all models tend to underestimate the shrinkage strain. Therefore, a correction function was proposed and adjusted according to the experimental data to predict the shrinkage of the concrete with recycled fine aggregates. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Advancements in algal membrane bioreactors: Overcoming obstacles and harnessing potential for eliminating hazardous pollutants from wastewater

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Chemosphere 2023年第1期336卷 139291页

作者： Mofijur, M. Hasan, M.M. Sultana, Sabrina Kabir, Zobaidul Djavanroodi, F. Ahmed, Shams Forruque Jahirul, M.I. Badruddin, Irfan Anjum Khan, T.M. Yunus Centre for Technology in Water and Wastewater School of Civil and Environmental Engineering University of Technology Sydney UltimoNSW2007 Australia Mechanical Engineering Department Prince Mohammad Bin Fahd University Al Khobar 31952 Saudi Arabia School of Engineering and Technology Central Queensland University QLD4701 Australia Department of Soil Water and Environment University of Dhaka Dhaka1000 Bangladesh School of Environmental and Life Sciences University of Newcastle NSW2258 Australia Science and Math Program Asian University for Women Chattogram4000 Bangladesh Mechanical Engineering Department College of Engineering King Khalid University Abha61421 Saudi Arabia

This paper offers a comprehensive analysis of algal-based membrane bioreactors (AMBRs) and their potential for removing hazardous and toxic contaminants from wastewater. Through an identification of contaminant types and sources, as well as an explanation of AMBR operating principles, this study sheds light on the promising capabilities of AMBRs in eliminating pollutants like nitrogen, phosphorus, and organic matter, while generating valuable biomass and energy. However, challenges and limitations, such as the need for process optimization and the risk of algal-bacterial imbalance, have been identified. To overcome these obstacles, strategies like mixed cultures and bioaugmentation techniques have been proposed. Furthermore, this study explores the wider applications of AMBRs beyond wastewater treatment, including the production of value-added products and the removal of emerging contaminants. The findings underscore the significance of factors such as appropriate algal-bacterial consortia selection, hydraulic and organic loading rate optimization, and environmental factor control for the success of AMBRs. A comprehensive understanding of these challenges and opportunities can pave the way for more efficient and effective wastewater treatment processes, which are crucial for safeguarding public health and the environment. © 2023

关键词： Bioreactors

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Using Remote Sensing to Catalyze Urban Climate Studies in Underserved Communities

Using Remote Sensing to Catalyze Urban Climate Studies in Un...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Reginald Blake Hamidreza Norouzi Marzi Azarderakhsh Abdou Bah Julia Rivera Provost Office New York City College of Technology Brooklyn New York USA Civil Engineering Technology Department New York City College of Technology Brooklyn New York USA CUNY – Graduate Center New York City College of Technology Brooklyn New York USA Improving Undergraduate STEM Education Program New York City College of Technology Brooklyn New York USA

For too many undergraduate minority students, remote sensing and its plethora of applications to geophysics yet remain new, foreign, and mysterious. These students, even with the requisite STEM backgrounds, lack the exposure, the awareness, the understanding, and the engagement in the foray of remote sensing and the unique lens it provides to probe and unearth new ways of gaining knowledge about the environment. To strengthen undergraduate education, to adequately prepare candidates to become the next generation of geoscientists, to empower and sustain underserved neighborhoods, and to assist in replenishing the geoscience workforce, unique paradigms of teaching and learning about remote sensing are needed. At the Center for Remote Sensing and Earth System Sciences (ReSESS) at the New York City College of technology (City Tech), remote sensing is used as a catalyst to attract and to engage students from underserved communities in studying urban climate within their local neighborhoods. Results indicate that this approach of using remote sensing to attract students to urban climate increased awareness and understanding in the geosciences, and it motivated students to share their newfound knowledge in environmental sustainability initiatives with their fellow local citizens.

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