Publications

@article{Cholidis2025,

title = {Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management},

author = {Dimitrios Cholidis and Nikolaos Sifakis and Nikolaos Savvakis and George Tsinarakis and Avraam Kartalidis and George Arampatzis},

doi = {10.3390/en18081941},

issn = {1996-1073},

year  = {2025},

date = {2025-04-10},

urldate = {2025-04-00},

journal = {Energies},

volume = {18},

number = {8},

publisher = {MDPI AG},

abstract = {<jats:p>Hybrid renewable energy systems (HRESs) are being incorporated and evaluated within seaports to realize efficiencies, reduce dependence on grid electricity, and reduce operating costs. The paper adopts a genetic algorithm (GA)-based optimization framework to assess four energy management scenarios that embed wind turbines (WTs), photovoltaic energy (PV), an energy storage system (ESS), and an energy management system (EMS). The scenarios were developed based on different levels of renewable energy integration, energy storage utilization, and grid dependency to optimize cost and sustainability while reflecting the actual port energy scenario as the base case. Integrating HRES, ESS, and EMS reduced the port’s levelized cost of energy (LCOE) by up to 54%, with the most optimized system (Scenario 3) achieving a 53% reduction while enhancing energy stability, minimizing grid reliance, and maximizing renewable energy utilization. The findings show that the HRES configuration provides better cost, sustainability, and resiliency than the conventional grid-tied system. The unique proposed EMS takes it a step further, optimizing not just the energy flow but also the cost, making the overall system more efficient—and less costly—for the user. ESS complements energy storage and keeps it functional and reliable while EMS makes it completely functional by devising ways to reduce costs and enhance efficiency. The study presents the technical and economic viability of HRES as an economic and operational smart port infrastructure through its cost-effective integration of renewable energy sources. The results reinforce the move from conventional to sustainable autonomous port energy systems and lay the groundwork for forthcoming studies of DR-enhanced port energy management schemes. While prior studies have explored renewable energy integration within ports, many lack a unified, empirically validated framework that considers HRES, ESS, and EMS within real-world port operations. This research addresses this gap by developing an optimization-driven approach that assesses the techno-economic feasibility of port energy systems while incorporating real-time data and advanced control strategies. This study was conducted to enhance port infrastructure and evaluate the impact of HRES, ESS, and EMS on port sustainability and autonomy. By bridging the gap between theoretical modeling and practical implementation, it offers a scalable and adaptable solution for improving cost efficiency and energy resilience in port operations.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Papadaki2025,

title = {Analysis of Hybrid Renewable Energy Systems for European islands: Market Dynamics, Opportunities and Challenges},

author = {Antonia Papadaki and Nikolaos Savvakis and Nikolaos Sifakis and Georgios Arampatzis},

doi = {10.1016/j.sftr.2025.100601},

issn = {2666-1888},

year  = {2025},

date = {2025-04-03},

urldate = {2025-06-00},

journal = {Sustainable Futures},

volume = {9},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Karkou2024b,

title = {Process innovations and circular strategies for closing the water loop in a process industry},

author = {Efthalia Karkou and Athanasios Angelis-Dimakis and Marco Parlapiano and Nikolaos Savvakis and Owais Siddique and Antonia Vyrkou and Massimiliano Sgroi and Francesco Fatone and George Arampatzis},

doi = {10.1016/j.jenvman.2024.122748},

issn = {0301-4797},

year  = {2024},

date = {2024-10-02},

journal = {Journal of Environmental Management},

volume = {370},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Karkou2024,

title = {Industrial circular water use practices through the application of a conceptual water efficiency framework in the process industry},

author = {Efthalia Karkou and Chuan Jiet Teo and Nikolaos Savvakis and Johann Poinapen and George Arampatzis},

doi = {10.1016/j.jenvman.2024.122596},

issn = {0301-4797},

year  = {2024},

date = {2024-09-24},

journal = {Journal of Environmental Management},

volume = {370},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Terlouw2025,

title = {Designing multi-energy systems in Mediterranean regions towards energy autonomy},

author = {Tom Terlouw and Nikolaos Savvakis and Christian Bauer and Russell McKenna and George Arampatzis},

doi = {10.1016/j.apenergy.2024.124458},

issn = {0306-2619},

year  = {2024},

date = {2024-09-19},

urldate = {2024-09-24},

journal = {Applied Energy},

volume = {377},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lounis2024,

title = {Evaluation Methodology for Circular and Resilient Information Systems},

author = {Stavros Lounis and Anastasios Koukopoulos and Timoleon Farmakis and Maria Aryblia},

doi = {10.3390/app14178089},

issn = {2076-3417},

year  = {2024},

date = {2024-09-09},

journal = {Applied Sciences},

volume = {14},

number = {17},

publisher = {MDPI AG},

abstract = {<jats:p>Digital technologies nowadays provide essential support for companies, making them a priority for businesses and a prominent area of study for researchers. In response to the increasing emphasis on sustainability and resilience, new information systems are developing to meet evolving business needs, namely circular and resilient information systems (CRISs). These systems integrate with traditional ones to optimise key performance indicators (KPIs) related to circularity and resiliency. Despite extensive methodologies for evaluating traditional information systems, systems designed for circularity and resiliency need to be assessed in parallel and in depth. Existing evaluations focus on efficiency and user satisfaction but often neglect the unique demands of circularity and resiliency. This study introduces a novel evaluation methodology for CRISs. Through a case study of an innovative system and the established literature, we address real-life needs and challenges in manufacturing. In particular, the system serves the needs of three distinct case studies: Carbon Fibre-Reinforced Polymer (CFRP) waste utilisation in drone manufacturing, recovery of magnets from Waste Electrical and Electronic Equipment (WEEE), and the repurposing of citrus processing waste into juice by-products. Our methodology is built on the 5W1H method to make our approach context-specific and aligned with each case’s unique requirements, making it also replicable for other industries. Our findings offer insights and a tool for practitioners and researchers to evaluate CRIS performance. The research highlights the importance of a two-fold evaluation approach for CRISs, evaluating both pilot-specific KPIs and the system’s technical performance. Policy implications suggest the need for regulatory frameworks and incentives to support the adoption, as well as evaluation, of CRISs and promote sustainable and resilient industrial practices.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sifakis2024,

title = {Techno-economic optimization of a novel industrial hybrid renewable energy system based on the waste-to-X principle},

author = {Nikolaos Sifakis and Nikolaos Savvakis and Marina Petropoulou and George Arampatzis},

doi = {10.1016/j.enconman.2024.118613},

issn = {0196-8904},

year  = {2024},

date = {2024-06-01},

journal = {Energy Conversion and Management},

volume = {313},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lu2024,

title = {A semantic model-based systems engineering approach for assessing the operational performance of metal forming process},

author = {Jinzhi Lu and George Tsinarakis and Nikolaos Sarantinoudis and George Arampatzis and Xiaochen Zheng and Dimitris Kiritsis},

doi = {10.1016/j.cie.2024.110042},

issn = {0360-8352},

year  = {2024},

date = {2024-03-04},

urldate = {2024-03-24},

journal = {Computers & Industrial Engineering},

volume = {190},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Teo2023b,

title = {Life cycle environmental impact assessment of slaughterhouse wastewater treatment},

author = {Chuan Jiet Teo and Efthalia Karkou and Ozana Vlad and Antonia Vyrkou and Nikolaos Savvakis and George Arampatzis and Athanasios Angelis-Dimakis},

doi = {10.1016/j.cherd.2023.11.016},

issn = {0263-8762},

year  = {2023},

date = {2023-11-17},

journal = {Chemical Engineering Research and Design},

volume = {200},

pages = {550--565},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sarantinoudis2023,

title = {Model-Based Simulation Framework for Digital Twins in the Process Industry},

author = {Nikolaos Sarantinoudis and Georgios Tsinarakis and Panagiotis Dedousis and George Arampatzis},

doi = {10.1109/access.2023.3322926},

issn = {2169-3536},

year  = {2023},

date = {2023-10-09},

journal = {IEEE Access},

volume = {11},

pages = {111701--111714},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{environments10010001,

title = {Industrial Symbiosis in the Balkan-Mediterranean Region: The Case of Solid Waste},

author = {Athanasios Angelis-Dimakis and George Arampatzis and Andreas Alexopoulos and Antonia Vyrkou and Andreas Pantazopoulos and Vasilis Angelis},

url = {https://www.mdpi.com/2076-3298/10/1/1},

doi = {10.3390/environments10010001},

issn = {2076-3298},

year  = {2023},

date = {2023-01-01},

journal = {Environments},

volume = {10},

number = {1},

abstract = {The treatment of waste and especially solid waste, the type with the highest increase in terms of annual generation over the last decade, is a key issue in the Balkan and Mediterranean region. Piecemeal efforts to deal with it within the prevailing linear economy model were not successful since the techniques used such as recycling and reusing could not be effective with the existing products. A definitive solution requires the switch to a new model, the circular economy model, which will facilitate the tackling of the excessive use of virgin raw materials and waste generation. The design and development of a digital solid waste reuse platform in the context of the EU-funded Interreg Project SWAN involving four countries: Albania, Bulgaria, Cyprus and Greece, was a step in this direction. The present paper based on the evidence drawn from this project examines the current situation and the future trends in the solid waste reuse and industrial symbiosis schemes in this region.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{s23187858,

title = {Soft Sensing of LPG Processes Using Deep Learning},

author = {Nikolaos Sifakis and Nikolaos Sarantinoudis and George Tsinarakis and Christos Politis and George Arampatzis},

url = {https://www.mdpi.com/1424-8220/23/18/7858},

doi = {10.3390/s23187858},

issn = {1424-8220},

year  = {2023},

date = {2023-01-01},

journal = {Sensors},

volume = {23},

number = {18},

abstract = {This study investigates the integration of soft sensors and deep learning in the oil-refinery industry to improve monitoring efficiency and predictive accuracy in complex industrial processes, particularly de-ethanization and debutanization. Soft sensor models were developed to estimate critical variables such as the C2 and C5 contents in liquefied petroleum gas (LPG) after distillation and the energy consumption of distillation columns. The refinery’s LPG purification process relies on periodic sampling and laboratory analysis to maintain product specifications. The models were tested using data from actual refinery operations, addressing challenges such as scalability and handling dirty data. Two deep learning models, an artificial neural network (ANN) soft sensor model and an ensemble random forest regressor (RFR) model, were developed. This study emphasizes model interpretability and the potential for real-time updating or online learning. The study also proposes a comprehensive, iterative solution for predicting and optimizing component concentrations within a dual-column distillation system, highlighting its high applicability and potential for replication in similar industrial scenarios.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlee,

title = {Data for the project management, life cycle inventory, costings and energy production of a ground-mounted photovoltaic farm in Greece},

author = {George Tsinarakis and Victor Kouloumpis and Anastasia Pavlidou and George Arampatzis},

doi = {10.1016/j.dib.2023.109260},

year  = {2023},

date = {2023-01-01},

journal = {Data in Brief},

volume = {48},

pages = {109260},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articled,

title = {Governance framework for autonomous and cognitive digital twins in agile supply chains},

author = {Kostas Kalaboukas and Dimitris Kiritsis and George Arampatzis},

doi = {10.1016/j.compind.2023.103857},

year  = {2023},

date = {2023-01-01},

journal = {Computers in Industry},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SAVVAKIS2023139055,

title = {Multiple energy resources integration in the food industry: A technoeconomic analysis},

author = {Nikolaos Savvakis and Nikolaos Sifakis and Xenofon Kotakidis and Georgios Arampatzis},

url = {https://www.sciencedirect.com/science/article/pii/S0959652623032134},

doi = {https://doi.org/10.1016/j.jclepro.2023.139055},

issn = {0959-6526},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Cleaner Production},

volume = {426},

pages = {139055},

abstract = {This study focuses on exploring sustainable energy solutions for the industrial sector, with a particular emphasis on meeting the electrical and thermal needs of the local bakery industry. Several alternative energy sources were proposed in this study, including solar irradiation, and the utilization of agricultural residues (such as olive tree pruning and residues of tomato crop). An anaerobic digestion (AD) reactor, a photovoltaic (PV) system, wind turbines (WT), a gasification system, and a combined heat and power (CHP) unit were used as parts of the developed hybrid renewable energy system (HRES). The objective was to optimize the system's performance by considering renewable energy sources (RES) penetration, energy cost, and ecological footprint. Furthermore, this investigation identified research gaps in the supply of thermal energy demand using renewable energy sources in an industrial setting and evaluated the integration of waste-to-energy technologies in HOMER Pro. Through modelling, optimization, and evaluation, different HRES configurations were assessed to determine the most cost-effective and optimal system for the bakery industry. The optimal suggested HRES showed a 65% reduction (from 0.4362 €/kWh to 0.1533 €/kWh) in the levelized cost of electricity (LCOE). Gasification achieved better results than AD, with the addition of a gasifier leading to a 40% decrease in the LCOE. The renewable fraction for the optimal HRES was 87.9%. There was a reduction in carbon dioxide emissions by 63%, while the HRES had a payback time of 3.17 years. Overall, the findings of this study show that utilizing local biomass and waste can play a significant role in the energy transition, leading to cost reduction and improved economic performance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlec,

title = {Waste Management and the Circular Economy in Cyprus—The Case of the SWAN Project},

author = {Athanasios Angelis-Dimakis and George Arampatzis and Andreas Alexopoulos and Andreas Pantazopoulos and Ioannis Vyrides and Nikolaos Chourdakis and Vasilis Angelis},

doi = {10.3390/environments9020016},

year  = {2022},

date = {2022-01-01},

journal = {Environments},

volume = {9},

pages = {16},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articleb,

title = {Cognitive Digital Twins for Resilience in Production: A Conceptual Framework},

author = {Pavlos Eirinakis and Stavros Lounis and Stathis Plitsos and George Arampatzis and Kostas Kalaboukas and Klemen Kenda and Lu Jinzhi and Jože Rožanec and Nenad Stojanovic},

doi = {10.3390/info13010033},

year  = {2022},

date = {2022-01-01},

journal = {Information},

volume = {13},

pages = {33},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KOULOUMPIS2022495,

title = {A model for estimating life cycle environmental impacts of offshore wind electricity considering specific characteristics of wind farms},

author = {Victor Kouloumpis and Adisa Azapagic},

url = {https://www.sciencedirect.com/science/article/pii/S2352550921003067},

doi = {https://doi.org/10.1016/j.spc.2021.10.024},

issn = {2352-5509},

year  = {2022},

date = {2022-01-01},

journal = {Sustainable Production and Consumption},

volume = {29},

pages = {495-506},

abstract = {Offshore wind electricity is becoming an important source of renewable energy due to its global warming potential (GWP). However, the GWP can vary significantly, depending on many factors, including the capacity of the installation, distance from the shore, supporting structure and maintenance requirements. Currently, there is a lack of life cycle assessment (LCA) studies that take these specific conditions into account. As a consequence, developers and policy makers rely on average GWP values which could lead to inaccurate estimates of the GWP and other impacts. To address this gap, this paper presents a new model for estimating the life cycle impacts of offshore wind electricity taking into account specific technical characteristics of individual installations and whole wind farms. Aimed at non-experts, the model provided freely with this paper is developed in Excel and follows the ISO 14040/44 LCA methodology. Supported by the built-in background LCA databases, it requires users to specify only a few key characteristics of an existing or proposed installation, thus facilitating quick and yet robust estimations of impacts. Eleven impacts can be considered, including GWP, depletion of resources, human toxicity and eco-toxicities. The application of the model is illustrated by quantifying the LCA impacts of 20 offshore wind farms (OWF) operating in the UK. The results show that the impacts vary considerably with the specific characteristics of OWF, including the age, type and size of wind turbines, their capacity and distance from the shore. For example, the GWP ranges by a factor of three (6.4–19.5 g CO2 eq./kWh) and the other impacts by a factor of 2.2–3.2. The developed model can be used by designers, developers and policy makers to customise the inputs for a specific OWF and estimate the impacts quickly and cost-efficiently, without the need for prior expertise in LCA and extensive data collection.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{app12020870,

title = {A Discrete Process Modelling and Simulation Methodology for Industrial Systems within the Concept of Digital Twins},

author = {George Tsinarakis and Nikolaos Sarantinoudis and George Arampatzis},

url = {https://www.mdpi.com/2076-3417/12/2/870},

doi = {10.3390/app12020870},

issn = {2076-3417},

year  = {2022},

date = {2022-01-01},

journal = {Applied Sciences},

volume = {12},

number = {2},

abstract = {A generic well-defined methodology for the construction and operation of dynamic process models of discrete industrial systems following a number of well-defined steps is introduced. The sequence of steps for the application of the method as well as the necessary inputs, conditions, constraints and the results obtained are defined. The proposed methodology covers the classical offline modelling and simulation applications as well as their online counterpart, which use the physical system in the context of digital twins, with extensive data exchange and interaction with sensors, actuators and tools from other scientific fields as analytics and optimisation. The implemented process models can be used for what-if analysis, comparative evaluation of alternative scenarios and for the calculation of key performance indicators describing the behaviour of the physical systems under given conditions as well as for online monitoring, management and adjustment of the physical industrial system operations with respect to given rules and targets. An application of the proposed methodology in a discrete industrial system is presented, and interesting conclusions arise and are discussed. Finally, the open issues, limitations and future extensions of the research are considered.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{app112411790,

title = {Cyber-Physical LPG Debutanizer Distillation Columns: Machine-Learning-Based Soft Sensors for Product Quality Monitoring},

author = {Jože Martin Rožanec and Elena Trajkova and Jinzhi Lu and Nikolaos Sarantinoudis and George Arampatzis and Pavlos Eirinakis and Ioannis Mourtos and Melike K. Onat and Deren Ataç Yilmaz and Aljaž Košmerlj and Klemen Kenda and Blaž Fortuna and Dunja Mladenić},

url = {https://www.mdpi.com/2076-3417/11/24/11790},

doi = {10.3390/app112411790},

issn = {2076-3417},

year  = {2021},

date = {2021-01-01},

journal = {Applied Sciences},

volume = {11},

number = {24},

abstract = {Refineries execute a series of interlinked processes, where the product of one unit serves as the input to another process. Potential failures within these processes affect the quality of the end products, operational efficiency, and revenue of the entire refinery. In this context, implementation of a real-time cognitive module, referring to predictive machine learning models, enables the provision of equipment state monitoring services and the generation of decision-making for equipment operations. In this paper, we propose two machine learning models: (1) to forecast the amount of pentane (C5) content in the final product mixture; (2) to identify if C5 content exceeds the specification thresholds for the final product quality. We validate our approach using a use case from a real-world refinery. In addition, we develop a visualization to assess which features are considered most important during feature selection, and later by the machine learning models. Finally, we provide insights on the sensor values in the dataset, which help to identify the operational conditions for using such machine learning models.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9646963,

title = {A Security-Aware Framework for Designing Industrial Engineering Processes},

author = {Panagiotis Dedousis and George Stergiopoulos and George Arampatzis and Dimitris Gritzalis},

doi = {10.1109/ACCESS.2021.3134759},

year  = {2021},

date = {2021-01-01},

journal = {IEEE Access},

volume = {9},

pages = {163065-163085},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nu13062076,

title = {Changing Dietary Behavior for Better Biodiversity Preservation: A Preliminary Study},

author = {Wajdi Belgacem and Konstadinos Mattas and George Arampatzis and George Baourakis},

url = {https://www.mdpi.com/2072-6643/13/6/2076},

doi = {10.3390/nu13062076},

issn = {2072-6643},

year  = {2021},

date = {2021-01-01},

journal = {Nutrients},

volume = {13},

number = {6},

abstract = {Broadly consumed dietary patterns, such as the European and Western ones, are exerting pressures on biodiversity both in Europe and globally, and shifting toward a sustainable dietary pattern has thus become a must. This paper constitutes a preliminary communication of the results of a research project on the issue. In this study, the pressures of three dietary patterns (European, Western, and Mediterranean) on biodiversity are addressed in terms of land use, water use, greenhouse gas emissions, and eutrophication impact indicators. The environmental impacts are calculated based on a compositional analysis of each dietary pattern and the environmental footprints of the corresponding food groups. Food balance sheets published by the FAO are used as a basis for the compositional analysis, while the environmental footprints of each of the representative food products are retrieved from related life cycle assessment (LCA) studies. The results show that a shift from the European to the Mediterranean dietary pattern would lead to 10 m2/capita/day land savings, 240 L/capita/day water savings, 3 kg CO2/capita/day reduction in greenhouse gas emissions, and 20 gPO4eq/capita/day reductions in eutrophication potential. Likewise, a shift from the Western to the Mediterranean dietary pattern would lead to 18 m2/capita/day land savings, 100 L/capita/day water savings, 4 kg CO2/capita/day reduction in greenhouse gas emissions, and 16 gPO4eq/capita/day reduction in eutrophication potential. Based on these findings, it is clear that this shift is urgently needed as a step toward environmentally sustainable dietary patterns, such as the Mediterranean one, to preserve biodiversity for future generations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1177/0734242X21989413,

title = {SWAN platform: A web-based tool to support the development of industrial solid waste reuse business models},

author = {Athanasios Angelis-Dimakis and George Arampatzis and Tryfonas Pieri and Konstantina Solomou and Panagiotis Dedousis and George Apostolopoulos},

url = {https://doi.org/10.1177/0734242X21989413},

doi = {10.1177/0734242X21989413},

year  = {2021},

date = {2021-01-01},

journal = {Waste Management & Research},

volume = {39},

number = {3},

pages = {489-498},

abstract = {The SWAN platform is an integrated suite of online resources and tools for assessing industrial symbiotic opportunities based on solid industrial waste reuse. It has been developed as a digital solid waste reuse platform and is already applied in four countries (Greece, Bulgaria, Albania and Cyprus). The SWAN platform integrates a database with the spatial and technical characteristics of industrial solid waste producers and potential consumers, populated with data from these countries. It also incorporates an inventory of commercially implemented best practices on solid industrial waste reuse. The role of the SWAN platform is to facilitate the development of novel business cases. Towards this end, decision support services, based on a suitable matching algorithm, are provided to the registered users, helping them to identify and assess potential novel business models, based on solid waste reuse, either for an individual industrial unit (source/potential receiver of solid waste) or a specific region.},

note = {PMID: 33570022},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{app11094103,

title = {Implementation of Cognitive Digital Twins in Connected and Agile Supply Networks—An Operational Model},

author = {Kostas Kalaboukas and Joze Rožanec and Aljaž Košmerlj and Dimitris Kiritsis and George Arampatzis},

url = {https://www.mdpi.com/2076-3417/11/9/4103},

doi = {10.3390/app11094103},

issn = {2076-3417},

year  = {2021},

date = {2021-01-01},

journal = {Applied Sciences},

volume = {11},

number = {9},

abstract = {Supply chain agility and resilience are key factors for the success of manufacturing companies in their attempt to respond to dynamic changes. The circular economy, the need for optimized material flows, ad-hoc responses and personalization are some of the trends that require supply chains to become “cognitive”, i.e., able to predict trends and flexible enough in dynamic environments, ensuring optimized operational performance. Digital twins (DTs) is a promising technology, and a lot of work is done on the factory level. In this paper, the concept of cognitive digital twins (CDTs) and how they can be deployed in connected and agile supply chains is elaborated. The need for CDTs in the supply chain as well as the main CDT enablers and how they can be deployed under an operational model in agile networks is described. More emphasis is given on the modelling, cognition and governance aspects as well as on how a supply chain can be configured as a network of connected CDTs. Finally, a deployment methodology of the developed model into an example of a circular supply chain is proposed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{su12219120,

title = {Should Photovoltaics Stay at Home? Comparative Life Cycle Environmental Assessment on Roof-Mounted and Ground-Mounted Photovoltaics},

author = {Victor Kouloumpis and Antonios Kalogerakis and Anastasia Pavlidou and George Tsinarakis and George Arampatzis},

url = {https://www.mdpi.com/2071-1050/12/21/9120},

doi = {10.3390/su12219120},

issn = {2071-1050},

year  = {2020},

date = {2020-01-01},

journal = {Sustainability},

volume = {12},

number = {21},

abstract = {Renewable energy technologies like photovoltaics may be considered an indispensable component of a low-carbon electricity mix, but social acceptance should not be taken for granted. For instance, in Greece there are still claims, especially in rural areas, regarding the land use and the competition against more traditional economic activities such as grazing. An argument in favor of confining to roof-mounted photovoltaic installations is the additional infrastructure requirements for ground-mounted larger-scale photovoltaics. These requirements reduce and could potentially negate their environmental benefits. The aim of this study is to investigate the life cycle environmental impacts of commercial ground-mounted photovoltaic farms and compare them against residential roof-mounted photovoltaic installations. Data were gathered for a 500 kW ground-mounted photovoltaic installation and for five roof-mounted installations of 10 kW capacity, each from the same area at the prefecture of Pella in Northern Greece. An LCA (Life Cycle Assessment) was performed and results show that panel production is the main contributor for both types and that ground-mounted photovoltaics—when no transmission/distribution infrastructure is considered—have lower impacts than the roof-mounted residential photovoltaic installations for all impact categories except terrestrial ecotoxicity. However, when located further than 10.22 km from grid connection, ground-mounted photovoltaics have higher impacts for almost all environmental impact categories.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{article,

title = {Energy savings and reduced emissions in combined natural and engineered systems for wastewater treatment and reuse: the WWTP of Antiparos Island, Greece},

author = {Patritsia-Maria Stathatou and Panagiotis Dedousis and George Arampatzis and Helen Grigoropoulou and D Assimacopoulos},

doi = {10.5004/dwt.2019.23995},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

journal = {Desalination and water treatment},

volume = {159},

pages = {13-23},

abstract = {Europe’s water service providers are under increasing pressure to deliver improved and affordable water services to a growing population, whilst reducing the amount of energy used, lowering the environmental impact of water and wastewater treatment processes, and coping with climate change. These challenges have prompted research on natural processes for wastewater treatment, such as constructed wetlands (CWs), providing low-energy treatment potential and storage capacity. As the performance of natural treatment processes may be limited by several factors (e.g. climatic conditions, space restrictions), considerable research concentrates on investigating their combination with engineered pre- or post-treatment processes to improve their performance and increase their treatment resilience. The aim of this paper is to assess and demonstrate the advantages of combined natural and engineered systems (cNES) over purely engineered treatment systems with regard to energy savings and reduced environmental impacts. The case of a cNES located in the island of Antiparos in Greece for the treatment and reuse of municipal effluents is investigated, focusing on the energy savings and the reduction of greenhouse gas (GHG) emissions from the natural treatment process. The performance of the system, which involves CWs for the secondary treatment of effluents, was assessed using an integrated modelling and simulation environment (baseline scenario). An alternative scenario was also built, substituting the CWs with a conventional activated sludge (CAS) process for the secondary treatment of effluents to achieve the same effluent quality as in the baseline scenario. Energy consumption and generation of GHG emissions was assessed for both scenarios, and a comparison between the two systems was conducted, highlighting the significant energy savings and the reduced GHG emissions produced by the cNES: the CAS system consumed about 3,000 times more energy, producing about 50 times more total GHG emissions compared with CWs. The results of the current analysis demonstrated that cNES involving CWs can provide a competitive alternative to purely engineered systems for wastewater treatment and reuse in isolated insular communities and small municipalities, also contributing to water scarcity reduction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{su11092539,

title = {Evaluating the Environmental Performance of Solar Energy Systems Through a Combined Life Cycle Assessment and Cost Analysis},

author = {Maria Milousi and Manolis Souliotis and George Arampatzis and Spiros Papaefthimiou},

url = {https://www.mdpi.com/2071-1050/11/9/2539},

doi = {10.3390/su11092539},

issn = {2071-1050},

year  = {2019},

date = {2019-01-01},

journal = {Sustainability},

volume = {11},

number = {9},

abstract = {The paper presents a holistic evaluation of the energy and environmental profile of two renewable energy technologies: Photovoltaics (thin-film and crystalline) and solar thermal collectors (flat plate and vacuum tube). The selected renewable systems exhibit size scalability (i.e., photovoltaics can vary from small to large scale applications) and can easily fit to residential applications (i.e., solar thermal systems). Various technical variations were considered for each of the studied technologies. The environmental implications were assessed through detailed life cycle assessment (LCA), implemented from raw material extraction through manufacture, use, and end of life of the selected energy systems. The methodological order followed comprises two steps: i. LCA and uncertainty analysis (conducted via SimaPro), and ii. techno-economic assessment (conducted via RETScreen). All studied technologies exhibit environmental impacts during their production phase and through their operation they manage to mitigate significant amounts of emitted greenhouse gases due to the avoided use of fossil fuels. The life cycle carbon footprint was calculated for the studied solar systems and was compared to other energy production technologies (either renewables or fossil-fuel based) and the results fall within the range defined by the global literature. The study showed that the implementation of photovoltaics and solar thermal projects in areas with high average insolation (i.e., Crete, Southern Greece) can be financially viable even in the case of low feed-in-tariffs. The results of the combined evaluation provide insight on choosing the most appropriate technologies from multiple perspectives, including financial and environmental.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1504/IJDSS.2019.104566,

title = {Supporting decisions for the application of combined natural and engineered systems for water treatment and reuse},

author = {G Arampatzis and P-M Stathatou and P Scaloubakas and D Assimacopoulos},

url = {https://www.inderscienceonline.com/doi/abs/10.1504/IJDSS.2019.104566},

doi = {10.1504/IJDSS.2019.104566},

year  = {2019},

date = {2019-01-01},

journal = {International Journal of Decision Support Systems},

volume = {4},

number = {2},

pages = {96-114},

abstract = {Combined natural and engineered systems (cNES) for water/wastewater treatment are well suited for application in many rural and semi-rural areas, especially those with water demand and wastewater production peaks related to tourism, farming and their nexus. The planning, implementation and operation of cNES is not a trivial task. A decision support system for the implementation of cNES, based on a user-oriented approach, is presented. Decision support is organised not into tools or tasks, but into a set of services targeted all potential user types, identified and parameterised through user's analysis. Six decision-making stages identified, leading to the specification of three generic types of services: 1) an information service, based on a knowledge repository; 2) a suite of tools service, implemented as a sustainable ecosystem of decision support tools; 3) a guidance service, based on a knowledge reasoning system that identifies typical application cases and produces analytic roadmaps towards achieving user goals.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{environments5020024,

title = {Life Cycle Assessment and Water Footprint of Hydrogen Production Methods: From Conventional to Emerging Technologies},

author = {Andi Mehmeti and Athanasios Angelis-Dimakis and George Arampatzis and Stephen J. McPhail and Sergio Ulgiati},

url = {https://www.mdpi.com/2076-3298/5/2/24},

doi = {10.3390/environments5020024},

issn = {2076-3298},

year  = {2018},

date = {2018-01-01},

journal = {Environments},

volume = {5},

number = {2},

abstract = {A common sustainability issue, arising in production systems, is the efficient use of resources for providing goods or services. With the increased interest in a hydrogen (H2) economy, the life-cycle environmental performance of H2 production has special significance for assisting in identifying opportunities to improve environmental performance and to guide challenging decisions and select between technology paths. Life cycle impact assessment methods are rapidly evolving to analyze multiple environmental impacts of the production of products or processes. This study marks the first step in developing process-based streamlined life cycle analysis (LCA) of several H2 production pathways combining life cycle impacts at the midpoint (17 problem-oriented) and endpoint (3 damage-oriented) levels using the state-of-the-art impact assessment method ReCiPe 2016. Steam reforming of natural gas, coal gasification, water electrolysis via proton exchange membrane fuel cell (PEM), solid oxide electrolyzer cell (SOEC), biomass gasification and reforming, and dark fermentation of lignocellulosic biomass were analyzed. An innovative aspect is developed in this study is an analysis of water consumption associated with H2 production pathways by life-cycle stage to provide a better understanding of the life cycle water-related impacts on human health and natural environment. For water-related scope, Water scarcity footprint (WSF) quantified using Available WAter REmaining (AWARE) method was applied as a stand-alone indicator. The paper discusses the strengths and weaknesses of each production pathway, identify the drivers of environmental impact, quantify midpoint environmental impact and its influence on the endpoint environmental performance. The findings of this study could serve as a useful theoretical reference and practical basis to decision-makers of potential environmental impacts of H2 production systems.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}