Article
Engineering, Environmental
Edward Ren Kai Neo, Jonathan Sze Choong Low, Vannessa Goodship, Kurt Debattista
Summary: Increasing plastic recycling rates is crucial for addressing plastic pollution, and new technologies like chemometric analysis of spectral data show great potential for improving plastic sorting efficiency. In this study, a novel deep learning architecture called PolymerSpectraDecisionNet (PSDN) was developed to accurately identify commonly recycled plastics from infrared and Raman spectral datasets. PSDN outperformed end-to-end neural networks and demonstrated the ability to distinguish between weathered and unaged polymer samples.
RESOURCES CONSERVATION AND RECYCLING
(2023)
Article
Chemistry, Analytical
Kiah Edwards, Louwrens C. Hoffman, Marena Manley, Paul J. Williams
Summary: South African legislation regulates the classification and labeling of raw beef patties to combat meat fraud and protect consumers. A study investigated the use of near-infrared hyperspectral imaging (NIR-HSI) as an alternative authentication technique. The results showed that NIR-HSI could accurately distinguish between different patty categories, offering a reliable solution for rapid identification and authentication of processed beef patties.
Article
Green & Sustainable Science & Technology
Edward R. K. Neo, Jonathan S. C. Low, Vannessa Goodship, Stuart R. Coles, Kurt Debattista
Summary: Automated sorting of plastic waste through chemometric analysis of spectral data is crucial for improving plastic waste management. This study introduces a new Multi-modal Plastic Spectral Database (MMPSD) containing FTIR, Raman, and LIBS data, which serves as the basis for Spectral Conversion Autoencoders (SCAE) to generate synthetic data from different modalities. The combination of multi-modal deep learning and SCAE significantly improves classification accuracy compared to uni-modal approaches. The application of SCAE in industrial sorting using FTIR sensors can further enhance accuracy while reducing costs.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Environmental
Hon Huin Chin, Petar Sabev Varbanov, Fengqi You, Farooq Sher, Jirf Jaromfr Klemes
Summary: This study utilizes machine learning approach to evaluate the recyclability of plastic waste by categorizing the quality trends of polymers, aiming to maximize the waste quality grading system and resource utilization.
RESOURCES CONSERVATION AND RECYCLING
(2022)
Article
Environmental Sciences
Shanyu Zhou, Hermann Kaufmann, Niklas Bohn, Mathias Bochow, Theres Kuester, Karl Segl
Summary: This study investigates the feasibility of detecting and identifying different types of plastics using hyperspectral data and deep learning models. It creates a comprehensive database and uses spectral libraries to classify various plastics and non-plastic materials. The results show that the random forest model has the best classification performance and high accuracy for unknown plastics and background surfaces.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Chemistry, Analytical
Puneet Mishra, Menno Sytsma, Aneesh Chauhan, Gerrit Polder, Erik Pekkeriet
Summary: Spectral imaging is widely used in analytical chemistry to assess the spatial distribution of physicochemical properties in samples. However, the main challenge lies in the extensive system integration and calibration modeling required by the available sensors. To address this, this study presents an intelligent All-In-One spectral imaging laboratory system that enables standardized automated data acquisition and real-time model deployment.
ANALYTICA CHIMICA ACTA
(2022)
Article
Engineering, Environmental
Wooseok Sim, Si Won Song, Subeen Park, Jin Il Jang, Jae Hun Kim, Yeo-Myoung Cho, Hyung Min Kim
Summary: The widespread use of plastic materials has led to an increase in plastic consumption, resulting in the production of primary and secondary microplastics. Current analytical methods lack insight into the size and shape of microplastics, and are time-consuming and susceptible to interference. In this study, a hyperspectral Raman method was developed to quickly quantify and characterize large volumes of plastics. The system successfully obtained Raman spectra of microplastics and effectively classified them, demonstrating its potential for real-world applications.
JOURNAL OF HAZARDOUS MATERIALS
(2024)
Article
Multidisciplinary Sciences
Abderrahim Diane, Taoufiq Saffaj, Bouchaib Ihssane, Reda Rabie
Summary: An innovative and rapid method for predicting mass loss of cement samples using a combination of Machine Learning (ML) and Hyperspectral Imaging (HSI) has been presented. By optimizing the predictive model performance, this method proves its reliability and accuracy in predicting analyte concentration. The results demonstrate the possibility of using HSI and ML for fast monitoring of water content in cement samples.
Article
Chemistry, Multidisciplinary
Haili Jia, Canhui Wang, Chao Wang, Paulette Clancy
Summary: Scanning transmission electron microscopy-based electron energy loss spectroscopy spectral imaging (STEMEELS-SI) is widely used in material research to capture a wealth of information. However, information extraction from noisy and overlapping edges in the data set is still challenging. To address this, we developed a machine learning method based on non-negative robust principal component analysis, which improves the analysis of EELS spectral images. Our algorithm greatly improves image quality compared to traditional methods and expands the characterization of nanomaterial systems by EELS-SI.
Article
Agricultural Engineering
Sahand Assadzadeh, Cassandra K. Walker, Linda S. McDonald, Joe F. Panozzo
Summary: This study constructed predictive models of flour milling yield (MY)% using image and spectral data. The models, including multiple linear regression, support vector regression, and Gaussian process regression, were built based on extracted features from the data. The results showed that the combination of all features as input variables for a Gaussian process regression model achieved the best accuracy.
BIOSYSTEMS ENGINEERING
(2022)
Article
Food Science & Technology
Y. Dixit, M. Al-Sarayreh, C. R. Craigie, M. M. Reis
Summary: This study demonstrates a novel approach to develop global calibration models for predicting intramuscular fat (IMF) and pH across various red meat species and muscle types. These prediction models, developed using Partial Least Squares Regression (PLSR) and Deep Convolutional Neural Networks (DCNN), showed high accuracy in predicting pH and IMF values in red meat samples.
Article
Chemistry, Analytical
An-Qi Chen, Hai -Long Wu, Tong Wang, Xiao-Zhi Wang, Hai-Bo Sun, Ru-Qin Yu
Summary: This study used chemometric analysis to determine the category and proportion of adulterated oil in Camellia oil (CAO). The results showed that EEMF fingerprints coupled with machine learning can provide intelligent and accurate authenticity detection of CAO.
Article
Environmental Sciences
Kevin Jacq, William Rapuc, Alexandre Benoit, Didier Coquin, Bernard Fanget, Yves Perrette, Pierre Sabatier, Bruno Wilhelm, Maxime Debret, Fabien Arnaud
Summary: This study compares several supervised classification algorithms to analyze sedimentary structures in lake sediments. The results show that the Short Wave Infrared (SWIR) sensor is the best choice for creating robust classification models with discriminant analysis, while the Visible Near-Infrared (VNIR) sensor is affected by surface reliefs and structures. The combined use of hyperspectral imaging and machine learning improves the characterization of sedimentary structures compared to conventional methods.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Agronomy
Maylin Acosta, Isabel Rodriguez-Carretero, Jose Blasco, Jose Miguel de Paz, Ana Quinones
Summary: Visible and near-infrared hyperspectral imaging was used to determine the nutrient contents in persimmon leaves. The models based on partial least square regression achieved satisfactory results for nitrogen, phosphorous, calcium, magnesium, and boron, but lower prediction rates were attained for potassium, iron, copper, zinc, and manganese.
Article
Spectroscopy
Lilian Skokan, Andreas Ruediger, Cyril Muehlethaler
Summary: This study proposes the use of principal component analysis (PCA) as an exploratory method to improve the reconstruction of obliterated serial numbers stamped in polymer materials. PCA provides better visual contrast and can highlight relevant variance in the original dataset for various polymers. The results show that PCA is effective in maintaining information integrity and enhancing reconstruction capabilities in polyethylene, offering potential applications in criminal investigations and trials.
JOURNAL OF RAMAN SPECTROSCOPY
(2022)
Article
Green & Sustainable Science & Technology
Ruisheng Ng, Zhiquan Yeo, Jonathan Sze Choong Low, Bin Song
JOURNAL OF CLEANER PRODUCTION
(2015)
Article
Green & Sustainable Science & Technology
Tobias Bestari Tjandra, Ruisheng Ng, Zhiquan Yeo, Bin Song
JOURNAL OF CLEANER PRODUCTION
(2016)
Article
Green & Sustainable Science & Technology
Zhiquan Yeo, Ruisheng Ng, Bin Song
JOURNAL OF CLEANER PRODUCTION
(2016)
Review
Green & Sustainable Science & Technology
Zhiquan Yeo, Donato Masi, Jonathan Sze Choong Low, Yen Ting Ng, Puay Siew Tan, Stuart Barnes
JOURNAL OF INDUSTRIAL ECOLOGY
(2019)
Article
Engineering, Environmental
Piya Kerdlap, Jonathan Sze Choong Low, Daren Zong Loong Tan, Zhiquan Yeo, Seeram Ramakrishna
RESOURCES CONSERVATION AND RECYCLING
(2020)
Article
Chemistry, Multidisciplinary
Zi-Yu Khoo, Eugene Hong Zhuang Ho, Yuqiong Li, Zhiquan Yeo, Jonathan Sze Choong Low, Jie Bu, Leonard Sze Onn Chia
Summary: Carbon capture and utilization (CCU) is a key pathway to reduce carbon emissions. This study focuses on the carbon abatement potential of a CO2 mineralization technology for CCU in Singapore, which converts CO2 into solid carbonates or sand using waste-to-energy plant emissions and serpentine mineral. Life cycle assessment (LCA) methodology was employed to analyze the net carbon emissions, showing that the technology abates 115.78 kg CO2-eq per tonne of CO2 input, with emissions mainly coming from transportation and activation processes. Possible strategies to enhance the carbon abatement potential include sourcing materials regionally and using renewable energy.
JOURNAL OF CO2 UTILIZATION
(2021)
Article
Engineering, Environmental
Amos Wei Lun Lee, Edward Ren Kai Neo, Zi-Yu Khoo, Zhiquan Yeo, Yee Shee Tan, Shuyun Chng, Wenjin Yan, Boon Keng Lok, Jonathan Sze Choong Low
Summary: The COVID-19 pandemic has led to a surge in global face mask consumption, with reusable EFL masks showing lower environmental impact compared to single-use surgical masks, emitting less CO2 and generating less waste.
RESOURCES CONSERVATION AND RECYCLING
(2021)
Article
Engineering, Environmental
Piya Kerdlap, Jonathan Sze Choong Low, Daren Zong Loong Tan, Zhiquan Yeo, Seeram Ramakrishna
Summary: This study introduces UM3-LCE3-ISN, a multi-level matrix-based methodology for life cycle environmental and economic evaluation of industrial symbiosis networks (ISNs). The methodology can unify conflicting assumptions and data used by different models and obtain more holistic assessment results.
INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT
(2022)
Proceedings Paper
Engineering, Industrial
Zhiquan Yeo, Jonathan Sze Choong Low, Daren Zong Loong Tan, Si Ying Chung, Tobias Bestari Tjandra, Joshua Ignatius
26TH CIRP CONFERENCE ON LIFE CYCLE ENGINEERING (LCE)
(2019)
Proceedings Paper
Green & Sustainable Science & Technology
Jonathan Sze Choong Low, Tobias Bestari Tjandra, Fajrian Yunus, Si Ying Chung, Daren Zong Loong Tan, Benjamin Raabe, Ng Yen Ting, Zhiquan Yeo, Stephane Bressan, Seeram Ramakrishna, Christoph Herrmann
25TH CIRP LIFE CYCLE ENGINEERING (LCE) CONFERENCE
(2018)
Proceedings Paper
Engineering, Industrial
Benjamin Raabe, Jonathan Sze Choong Low, Max Juraschek, Christoph Herrmann, Tobias Bestari Tjandra, Yen Ting Ng, Denis Kurle, Felipe Cerdas, Jannis Lueckenga, Zhiquan Yeo, Yee Shee Tan
24TH CIRP CONFERENCE ON LIFE CYCLE ENGINEERING
(2017)
Proceedings Paper
Engineering, Industrial
Zhiquan Yeo, Jonathan Sze Choong Low, Ruisheng Ng, Hui Xian Tan
23RD CIRP CONFERENCE ON LIFE CYCLE ENGINEERING
(2016)
Proceedings Paper
Engineering, Industrial
Hui Xian Tan, Zhiquan Yeo, Ruisheng Ng, Tobias Bestari Tjandra, Bin Song
22ND CIRP CONFERENCE ON LIFE CYCLE ENGINEERING
(2015)
Proceedings Paper
Engineering, Industrial
Yeo Zhiquan, Ng Ruisheng, Song Bin
22ND CIRP CONFERENCE ON LIFE CYCLE ENGINEERING
(2015)
Article
Engineering, Environmental
Yui Kawasaki, Sayaka Nagao-Sato, Misa Shimpo, Kahori Fujisaki, Emi Yoshii, Rie Akamatsu, Petra Warschburger
Summary: This study qualitatively describes sustainable dietary behaviors (SDBs) that Japanese and German adults can implement in their lives, and quantitatively compares the similarities and differences in understanding SDBs between the two samples. The study found that Japanese participants were more focused on food waste prevention, while German participants were more focused on solving environmental problems.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Kechun Chen, Yuan Ding, Liming Yang, Zhihao Wang, Haoxuan Yu, Difan Fang, Yufa Feng, Liying Hu, Chenxi Xu, Penghui Shao, Xubiao Luo, Liang Chen
Summary: This study proposes a targeted repair scheme for the recovery of graphite anodes from spent LIBs by systematically characterizing and analyzing the structure and composition of spent graphite (SG). The results show that the repair scheme achieves effective SG repair and the repaired graphite anode displays excellent lithium storage performance.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Takao Ueda, Shigeki Koyanaka, Tatsuya Oki
Summary: Fires caused by accidental crushing of batteries are a serious issue in the e-waste recycling process. A new in-line sorting system that uses X-ray scanning and deep learning has been developed to accurately detect batteries. Through a validation study, the system achieved higher accuracy compared to other existing programs.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Hannes Geist, Frank Balle
Summary: Research on circular economy often lacks empirical data, especially in the theory of circular process design and design for remanufacturing. This study systematically collected and analyzed engineering data on seven remanufacturing processes in the European automotive remanufacturing industry for the first time, providing empirical support for circular engineering challenges, potentials, and solutions.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Xiaojing Li, Fan Lue, Nanlin Liao, Hua Zhang, Na Yang, Pinjing He
Summary: This study assesses and predicts the greenhouse gas emissions on the timeline as waste treatment technologies develop in Shanghai from 1991 to 2025 using the Life Cycle Assessment (LCA) methodology. The findings demonstrate that GHG emission has reached net-zero in 2019 owing to the application of alternative technologies and waste segregation.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Bingchun Liu, Haoyang Wang, Xiaoqin Liang, Yibo Wang, Zijie Feng
Summary: The expansion of the photovoltaic market has resulted in a significant increase in PV waste. Therefore, conducting scientific research to determine the importance of the circular economy for sustainable growth in the PV industry is essential. The study demonstrates that accurate prediction of PV installed capacity and quantifying the importance of recycling in balancing the supply and demand of raw materials can be achieved through a multi-factor installed capacity prediction model and recovery potential prediction.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Review
Engineering, Environmental
Chuanzhen Zhang, Baojing Gu, Xia Liang, Shu Kee Lam, Yi Zhou, Deli Chen
Summary: Reactive nitrogen is crucial for agriculture and human nutrition, but mismanagement can have detrimental effects on human health and ecosystem services, hindering the achievement of the 2030 Sustainable Development Goals. Progress towards nitrogen-related targets varies across countries, highlighting the need for integrated management to achieve overall synergies.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Alessandro Gatto, Marijke Kuiper, Corina van Middelaar, Hans van Meijl
Summary: This study examines the economic and environmental effects of transitioning towards more circular food systems in the European Union (EU27) by feeding animals with low-opportunity-cost feed and better utilizing local feed resources. The results show that providing subsidies for circularity and promoting the use of low-cost feed can increase animal production, but also have negative impacts on land use and emissions. On the other hand, promoting domestic feed sourcing through import tariffs can decrease animal production and greenhouse gas emissions in agriculture. However, complementary policies are needed to mitigate drawbacks and enhance benefits of a more circular agri-food system.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Jinbo Zhang, Liu Chen, Yulei Xie, Pingjian Yang, Zheng Li, Huaicheng Guo, Yang Zhang, Lirong Liu
Summary: This study examines the impact of carbon taxes on low-carbon development and climate change mitigation. By constructing a cross-system bi-layer model, the study finds that reasonable carbon taxes can promote the stability of the energy network, reduce carbon emissions and air pollutants, and optimize production efficiency and the structure of the energy system. This study contributes to a better understanding of the effects and implementation pathways of carbon taxes.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Konstantin Born, Mehmet Metehan Ciftci
Summary: Increasing recycling of metals is important for reducing reliance on mining, but it cannot fully meet future metal demand. Primary production of metals is expected to continue rising, highlighting the need for alternative circular economy strategies such as demand reduction and mitigating harmful impacts of primary metal production.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Yinqiu Ma, Lin Huang, Jiahui Li, Wei Cao, Yumei Cai
Summary: Afforestation and reforestation, such as China's Grain for Green Program, have shown to effectively mitigate greenhouse gas emissions and contribute to carbon sink capacity. This study highlights the significant carbon potential of the program and its potential application in other countries to reduce CO2 in the atmosphere.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Arlind Dervishaj, Kjartan Gudmundsson
Summary: This paper reviews digital tools for supporting the Circular Economy (CE) in the built environment and provides suggestions. The study identifies limitations in the functionalities of current tools, including a lack of representative data for LCA and underdeveloped circularity indicators. Further development is needed in terms of interoperability aspects, integration of more sources of data for LCA and circularity, and possibilities for a comprehensive evaluation of design choices.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Mohamadreza Y. Azarfam, Anuj Maheshwari, Frank D. Blum, Siddhesh Chaudhari, Clinton Switzer, Ranji Vaidyanathan, Jay C. Hanan, Sudheer Bandla
Summary: This study introduces a feasible method for manufacturing recycled composites using post-consumer carpets and recycled resin. The resulting composites have impressive strength and modulus, surpassing commercial thermoplastics and making them suitable for structural applications. This research presents a promising approach to address carpet landfilling and reduce reliance on additives.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Pujiang Shi, Tianle Huang, Hong Kit Lim, Chiew Kei Tan, Jong-Min Lee, Chor Yong Tay
Summary: This study developed a highly porous bioadaptive 3D sponge-like construct from plastic materials in discarded keyboards for advanced in vitro applications. The findings demonstrate the potential of using discarded keyboards as a waste-to-resource feedstock to achieve waste reduction and maximize value-capture.
RESOURCES CONSERVATION AND RECYCLING
(2024)
Article
Engineering, Environmental
Kuo-Jui Wu, Hailing Qiu, Caiyan Huang, Anthony S. F. Chiu, Ming-Lang Tseng
Summary: Government resource allocation practices for achieving carbon neutrality should be guided by dynamic system theory to identify potential dynamics. Carbon intensity control dynamics have a significant influence on other dynamics.
RESOURCES CONSERVATION AND RECYCLING
(2024)