Technical University of Crete
  • Chaniá, Crete, Greece
Recent publications
Calcium looping and chemical looping technologies envisage advanced solutions for H2 production. This study compared the H2 and power co-production from biomass sorption enhanced gasification (SEG) and sorption enhanced chemical looping gasification (SECLG) under autothermal conditions with thermodynamic simulation. The thermal self-sufficiency of calcination was achieved by splitting biomass for combustion and oxidizing the reduced oxygen carrier, respectively. It was found that SECLG was able to achieve higher energy efficiency (64.6%) than SEG (55.7%) at the optimized carbonator temperature. In both processes, parametric analysis illustrates that under the autothermal-available carbonator temperature range, higher carbonator temperature and fixed carbon conversion are recommended to achieve higher H2 yields and energy efficiencies, owing to lower energy penalty leading to lower requirement of combusted biomass content or Ni/C molar ratio for thermal self-sufficiency. Elevating carbonator pressure slightly improved the energy performance. Regarding CO2 capture through oxyfuel combustion in SEG and SECLG processes, the energy penalty from higher calcination temperature greatly degraded the energy performance, which was even higher than the power consumption of air separation unit. According to exergy analysis, the main exergy destruction occurred at the syngas production section (∼49%). From the view of energy performance, SECLG is a promising autothermal strategy for SEG upgrade.
In this study a bamboo species, Moso Bamboo (MB) – Phyllostachys pubescens – has been selected for its heavy metal accumulation capacity and translocation potential to restore Cr-contaminated soil. Experiments have been conducted so to evaluate the capability of MB to remove Cr from soil, growing under Mediterranean conditions, irrigated with water containing 180 mgCr/L, at flow rate of 600 mm/year. The soil has been contaminated by the irrigation water. When the concentration of Cr in soil reached 300 mgCr/kg, Cr phytoextraction by MB from soil at the same irrigation rate of 600 mm/year with uncontaminated water has been evaluated. Cr removal from soil was approx. 42% after 6 weeks and 60.7% after 12 weeks, starting from a Cr content in soil of approximately 300 mg/kg. MB growing in Cr contaminated soil has shown Cr concentration per gram of dry biomass in aerial parts greater than the underground parts of the plants. After 12 weeks of cultivation, the quantity of Cr in roots and rhizome was measured as 1.79 mg/g, while in stems and leaves as 2.49 mg/g. Results shown a bioconcentration factor of 0.77, 0.65, 0.18, 0.08, after 6 weeks and 0.64, 0.98, 0.53, 0.26 after 12 weeks for roots, rhizomes, stems and leaves, respectively and a translocation factor equal to 0.23 and 0.11 after 6 weeks and 0.83 and 0.40 after 12 weeks, for stems and leaves, respectively.
In this paper, we apply a Control Lyapunov Function methodology to design two families of cruise controllers for the two-dimensional movement of autonomous vehicles on lane-free roads using the bicycle kinematic model. The control Lyapunov functions are based on measures of the energy of the system with the kinetic energy expressed in ways similar to Newtonian or relativistic mechanics. The derived feedback laws (cruise controllers) are decentralized, as each vehicle determines its control input based on its own speed and on the relative speeds and distances from adjacent vehicles and from the boundary of the road. Moreover, the corresponding macroscopic models are derived, obtaining fluid-like models that consist of a conservation equation and a momentum equation with pressure and viscous terms. Finally, we show that, by selecting appropriately the parameters of the feedback laws, we can determine the physical properties of the “traffic fluid”, i.e. we get free hand to create an artificial fluid that approximates the emerging traffic flow.
In the current research a holistic tool towards STEM education is introduced. The proposed method is implemented using an enhanced version of a previously introduced educational framework [5], namely HYDRA 2.0. The proposed system offers a set of hardware and software tools which allow the creation of working artefacts. An application using augmented reality has been developed allowing the users to interact and obtain information about the different building blocks. In order to adopt the aforementioned tools in a classroom environment, an educational procedure consisting of sequential tasks and actions has been introduced and modeled using Timed Petri nets, for representation, monitoring, what-if analysis and root cause analysis purposes. To highlight the applicability of the proposed approach a sample test case which results in a mobile robot with autonomous capabilities is presented and future extensions and conclusions are discussed.
Methane gas is emitted during both underground and surface coal mining. Underground coal mines need to monitor methane gas emissions to ensure adequate ventilation is provided to guarantee that methane concentrations remain low under different production and environmental conditions. Prediction of methane concentrations in underground mines can also contribute towards the successful management of methane gas emissions. The main objective of this research is to develop a forecasting methodology for methane gas emissions based on time series analysis. Methane time series data were retrieved from atmospheric monitoring systems (AMS) of three underground coal mines in the USA. The AMS data were stored and pre-processed using an Atmospheric Monitoring Analysis and Database Management system. Furthermore, different statistical dependence measures such as cross-correlation, autocorrelation, cross-covariance, and variograms were implemented to investigate the potential autocorrelations of methane gas as well as its association with auxiliary variables (barometric pressure and coal production). The autoregressive integrated moving average (ARIMA) time series model which is based on auto-correlations of the methane gas is investigated. It is established that ARIMA used in the one-step-ahead forecasting mode provides accurate estimates that match the direction (increase/decrease) of the methane gas emission data.
The main objective of this paper is to perform a comparative analysis between fuel consumption and CO2 emissions estimation and actual fuel consumption. Before some years detailed actual fuel consumption reports were collected from ship‐owners for determining the expenses on each trip and were not publically available. Nowadays ship‐owners report specific data including fuel consumption and CO2 emissions for the needs of EU MRV regulation. As a consequence EMSA/MRV‐THETIS database (EMSA, 2020) is publically available and provides annual reporting of fuel consumption and CO2 emissions. The current study follows the bottom‐up methodology presented in detail in a recent publication (Doundoulakis & Papaefthimiou, 2021) where the fuel ‐ energy consumption and air emissions (CO2, SOX, NOX, PM) of ships calculated and presented for previous years. A detailed comparative analysis between results from calculated methodology and reported emissions data from EMSA/MRV‐THETIS Database (MRV) was performed, which emerged that there was a small difference on the results (about 6–12%), proving in this way the reliability of the bottom‐up methodology for this geographic area and ships in study. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. This article is protected by copyright. All rights reserved
Mining activities depend significantly on water resources availability as it consists a major tool of the extraction, processing and the post closure mining operations. Especially, groundwater is the major water source in most mining areas. However, overexploitation, competition from the communities and climate change effects have caused significant stress on the groundwater resources in many areas of the Mediterranean basin. The sustainability of mining operations is threatened as well as the uninterrupted supply of raw materials to the industry. In this work spatial estimation and analysis of groundwater stress at hydrological basin-scale in the European part of the Mediterranean region is applied using local and global datasets. Aquifer productivity index and groundwater use information at monitoring sites are extracted from the River Basin Management Plans of the European Environment Agency, while groundwater recharge is considered from the World-wide Hydrogeological Mapping and Assessment Program (WHYMAP) after validation. The processing of these data using the Self Organized Maps technique and their integration within a novel function, provide the groundwater stress index. The output of this work can be used for governance and management decisions that will improve groundwater resources availability in vulnerable areas ensuring the sustainable use from the communities and the industry.
Impurities such as alkali metals (NaCl and KCl) and hydrogen chloride can limit downstream syngas utilization. In this study, a highly-active sorbent based on alumina containing active components for alkali metals and HCl sorption was synthesized for simultaneous removal of alkali metals and HCl from syngas at high temperatures of 750–850 °C in a reactor and compared with other sorbents (kaolin and γ-Al2O3). Results revealed that the removal efficiency of the developed sorbent for NaCl, KCl and HCl was the highest compared to kaolin and γ-Al2O3. At optimized conditions, the simultaneous alkali metal and HCl removal efficiencies were >80% and >70%, respectively (≤850 °C). Experimental data and thermodynamic calculations suggest that the removal of alkali metals was predominantly governed by physical sorption, while the removal of HCl was governed by chemical sorption. The physicochemical adsorption interactions between the sorbent and NaCl, KCl and HCl contributed to the simultaneous removal of alkali metals and HCl.
The eastern Mediterranean is a hotspot in terms of geomorphic hazards, but the activity of gravitational processes in mountainous areas is largely unexplored. We carried out dendrogeomorphic research in the Helmos Mountains (Northern Peloponnese, Greece) to determine the timing, spatial extent, and hydrometeorological triggers of debris flows and snow avalanches. Specifically, we sampled increment cores from 123 injured Greek firs (Abies cephalonica L.) growing on a debris flow cone and growing along a snow avalanche track. Tree rings were counted and cross-dated with the reference chronology using CooRecorder and CDendro software and the event years were determined on the basis of the location of scars and traumatic resin ducts. We compiled an 118-year chronology (1904–2021) with seven debris flow event years and only one severe debris flow occurring in the 1970/1971 dormant period (WIt = 148.0), followed by spatially limited records for 1986/1987 (WIt = 3.8) and 1993/1994 (WIt = 2.5). Similarly, seven snow avalanche event years were identified in the period 1854–2021, with one major event in 1997/1998 (WIt = 304.5) followed by the 1998/1999 event (WIt = 6.3). Extremely wet conditions in February–March 1971 followed by rain-on-snow precipitation were considered as the most likely trigger of the analysed debris flow event using data from nearby meteorological stations and the ERA5 reanalysis. The snow avalanche event was deciphered in the spring of 1998, when heavy snowfall over three days (62 cm) was followed by rapid snowmelt due to high average temperatures (6–11 °C). We conclude that the abundance of snow is a crucial factor in the geomorphic activity in the study region and that the temperature fluctuations and rain-to-snow transitions are the leading factors for the debris flows or snow avalanches to occur. Furthermore, the dendrogeomorphic approach used can be useful to clearly identify large-scale geomorphic events and excludes potential geomorphic noise caused by other ecological stresses.
Precision irrigation has been proposed as a key means towards a sustainable agriculture future. Many such techniques use infrared and/or visible-spectrum images to measure the canopy temperature. This, in turn, is utilized to calculate the crop water stress index (CWSI). Sunlit leaves are likely to get under stress sooner and to a higher extent compared to non-sunlit ones. As such, using only sunlit leaves for measuring canopy temperature can be beneficial for precision irrigation purposes. However, existing work generally does not separate sunlit from non-sunlit leaves. The works that do attempt to do so generally use empirical techniques and do not come with thorough evaluation results. In this work, we propose a novel generic method to identify sunlit leaves with high accuracy and high precision. The backbone of our approach is a convolutional neural network (CNN) technique for segmenting sunlit leaves in visible-spectrum images. This is the first work to propose a strictly supervised learning technique for sunlit-leaf segmentation. We release the first dataset for sunlit-leaf segmentation for pistachio trees. We evaluate four different CNN architectures for this task, namely FRRN-A, FC-DenseNet103, ResNet101-DeepLabV3, and SegNet. We show that CNNs can improve the accuracy and precision of sunlit-leaf segmentation by over 100% and 350%, respectively, when compared to the state of the art. Furthermore, we propose an expert system for measuring the CWSI of pistachio trees that incorporates CNN-based sunlit-leaf segmentation. We introduce the expert system to the public as a free-of-charge web-based tool.
Decision-making for cooperation between municipal entities involves elected members serving public interest who argue in both quantitative (e.g. financial performance), and qualitative (e.g. social acceptance) grounds. Policy support should consider conflicting objectives in a context of uncertainty and imprecision as well as in presence of organizational lock-ins that tend to favor incumbent arrangements. In search of appropriate algorithm to support decision making in such cases we opted for the PROMETHEE outranking method integrating novel findings of behavioral theory. Thus its preference functions are specified so that they reflect bounded rationality that shapes risk attitudes of decision makers within the uncertain environment of public management. Moreover alternative weighting procedures have been applied for group decisions. The prospect theory multi-criteria methodology, termed PT-PROMETHEE is implemented relating proposed options to observed behavior providing useful insights especially regarding status quo options also allowing for sensitivity analysis. Thus acceptance of MCDM support by the stakeholders is enhanced leading to solid compromise institutional arrangements.
Scientometric reviews, facilitated by computational and visual analytical approaches, allow researchers to gain a thorough understanding of research trends and areas of concentration from a large number of publications. With the fast development of satellite altimetry, which has been effectively applied to a wide range of research topics, it is timely to summarize the scientific achievements of the previous 50 years and identify future trends in this field. A comprehensive overview of satellite altimetry was presented using a total of 8541 publications from the Web of Science Core Collection covering the years from 1970 to 2021. We begin by presenting the fundamental statistical results of the publications, such as the annual number of papers, study categories, countries/regions, afflictions, journals, authors, and keywords, in order to provide a comprehensive picture of satellite altimetry research. We discuss the co-occurrence of the authors in order to reveal the global collaboration network of satellite altimetry research. Finally, we utilised co-citation networks to detect the development trend and associated crucial publications for various specific topics. The findings show that satellite altimetry research has been changed immensely during the last half-century. The United States, France, China, England, and Germany made the most significant contributions in the field of satellite altimetry. The analysis reveals a clear link between technology advancements and the trend in satellite altimetry research. As a result, wide swath altimetry, GNSS-reflectometry, laser altimetry, terrestrial hydrology, and deep learning are among the most frontier study subjects. The findings of this work could guide a thorough understanding of satellite altimetry’s overall development and research front.
Nowadays, plug-in electric vehicles (PEVs) have gained popularity because of their operational and environmental advantages. As a result, power systems must deal with new operation challenges from their integration. In this article, a method for the assessment of the effects of multi-objective optimal charging of PEVs at power system level is proposed. The proposed multi-objective optimization method takes into consideration the forecasts of power system load, Renewable Energy Sources (RES) and electricity price. Moreover, it is enhanced by the detailed modeling of the daily EV activity taking into consideration the characteristics of the area they are having activity, the type of the activity, the charging preferences of the driver as well as the technical characteristics of the EV. Moreover, Vehicle to Grid (V2G) operation can be modeled by the proposed method. Real-world data were used and the method was applied to the power system of Crete. The results obtained from the study of indicative application scenarios are presented and finally prove the efficiency of the proposed method.
The high rate of penetration of renewable energy sources leads to challenges in planning and controlling the production, transmission and distribution of energy. A possible solution lies within the change from traditional supply side management to demand side management. Buildings are good candidates for implementing a demand response model since they account for around 39% of global final energy use and are stably connected to all infrastructure networks. As a result, employing buildings as "players" in energy networks is considered now more than ever compelling. Recently, significant improvement has been denoted in the thermal efficiency of the building shell and the energy efficiency of the HVAC systems in new and renovated buildings. However, despite the reduction in energy demand regarding the space conditioning, buildings continue to be passive end users of the energy system. In order to ensure that they are capable of providing the necessary energy flexibility to balance intermittent energy production, a first step is to establish a formal, standard, and robust method of characterizing the energy flexibility provided on the demand side. Buildings can supply flexibility in a variety of ways, but there is currently no fixed and consistent method for quantifying the amount of flexibility a building can provide to future energy systems. In this paper, an overview of the literature on building energy flexibility will be offered, as well as an introduction to the concept of building energy flexibility and the methodologies used to define and evaluate it.
The concept of sustainability has gained importance over the last years and organizations worldwide are trying to adapt their strategies and their economic, environmental, and social goals in order to achieve what is called corporate sustainability. Despite its importance to organizations, there is no universally accepted approach for implementing and measuring corporate sustainability. Business Excellence Models (BEMs) are widely used all over the world as a means of achieving and sustaining outstanding levels of organizational performance by improving the quality and management of their operations, and have been regarded to promote sustainable development. However, they have often been criticized for focusing more on business and financial results, questioning the extent to which they can adequately promote corporate sustainability. The aim of this paper is to explore the adequacy of the latest versions of three major BEMs to address corporate sustainability, by analyzing their criteria, their core values, and the overall approach of these models. Although the latest versions of these BEMs have been evolved to take into account the growing importance of corporate sustainability, the extent to which this is achieved varies among them, and cannot yet be considered as standardized models for its implementation and measurement. BEMs should provide an extensive list of sustainability indicators, such as the ones described in the Global Reporting Initiative (GRI) standards, if they are to be regarded as frameworks that adequately address corporate sustainability.
A double waste stream problem arises from the increasing use of electrical and electronic equipment and their energy consumption: potentially toxic wastes from the equipment itself and potential acid mine drainage from the waste of the coal mines that provide the fuel to cover the energy demand. CEReS (Co-processing of Coal Mine & Electronic Wastes: Novel Resources for a Sustainable Future) is a novel method to co-process the coal mine and low-grade PCBs waste to reduce their environmental impacts while producing metals and other valuable products. The aim of this study is to investigate whether CEReS method is more environmentally friendly than the conventional practices of landfilling and incineration. Based on a Polish coal mine case study, our study found that the CEReS method could potentially eliminate the environmental impacts related to toxicity but increase the climate change impacts by ten times. A sensitivity analysis has shown that using a lower carbon electricity mix could reduce the climate change and fossil depletion impacts. It is also recommended to reduce water and energy requirements in some stages of the method.
The production of either CO or CH4 via the hydrogenation of CO2 is amongst the most promising routes for CO2 utilization. However, kinetic barriers necessitate the use of a catalyst, with Ni/CeO2 being one of the most investigated systems. Nevertheless, surface chemistry fine-tuning via appropriate promotional routes can induce significant modifications on the solid-state properties of catalysts and in turn on their activity/selectivity. In the present work, we originally report on the outstanding selectivity alteration of Ni/CeO2 by ZnO doping. Specifically, Ni-based catalysts supported on ZnO, CeO2 nanorods or a mixed ZnO-CeO2 oxide were synthesized by a modified hydrothermal method and characterized by various physicochemical methods. Notable changes in the reaction pathway were demonstrated, as the presence of ZnO largely favored CO production at T < 450 oC for both Ni/ZnO and Ni/ZnO-CeO2, whereas Ni/CeO2 was completely selective to CH4. These findings were interpreted on the basis of ZnO-induced inhibitory effects on key activity/selectivity descriptors like the redox and basic properties, as well as on the adsorption affinity of CO species, which are considered as intermediate species for CO2 methanation.
Air quality in Europe has been improving over the last decades. Notwithstanding, urban areas are still facing exceedances of the Air Quality Directive's limit and target values. In this study, we analyzed the effect of two mitigation measures on urban air quality: i) improvement of the biomass residential combustion appliances, and ii) electrification of passenger's cars fleet. Five European cities (Lisbon and Porto - Portugal, Athens - Greece, Kuopio - Finland, and Treviso - Italy) were used as case studies to evaluate the impact of the measures on the fine particle fraction (PM2.5) concentrations. To facilitate decision making and the quick test of new measures, the LIFE Index-Air tool was developed. In this tool, the air pollutant concentrations are predicted by Artificial Neural Networks trained using a set of air quality modelling simulations. The results indicate that the replacement of old biomass heating systems by new improved fireplaces can be more effective in Treviso. On the other hand, the replacement of gasoline and diesel passenger vehicles by electric ones seems to be more effective in reducing PM2.5 concentrations over Lisbon, Porto, and Athens. In Kuopio, both mitigation measures have an identical effect.
The main objective of this paper is to present an analytical methodological framework for the estimation of the external costs of air emissions from passenger ships. We used as a case study the two main ports of Crete (Souda and Heraklion) and studied all passenger ferries and cruise vessels that visited these ports in the last 5 years (2017–2021). A detailed inventory was created containing all technical details for 10 passenger ferries (owned by three different shipping companies) operating every day, following various itineraries all year around, and 88 different cruise vessels (which approached both ports mainly during the summer period). The estimated external costs due to air emissions cover health effects, materials and building damages, biodiversity and crop losses. Two levels of calculations for the total external costs per pollutant were implemented. At the first level, a bottom-up approach was applied to accurately calculate the total annual air emissions (CO2, SOX, NOX, PM2.5, PM10), while for the second level, the cost factors per pollutant were used as input values to estimate the annual total external costs. One of the most important findings is that externalities comprise a significant amount of shipping companies’ revenues (about 25–35%), thus, implying a substantial revenue loss in the case that they would be asked to bear these costs. Assuming that ship owners will pass these costs on to ticket fares, an attempt is made to allocate the “externalities surcharge” (i.e., the burden of external costs) to ticket fares per transportation category.
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2,012 members
Nektarios Moumoutzis
  • School of Electrical and Computer Engineering
Nikolaos Spanoudakis
  • School of Production Engineering and Management
Elefteria Psillakis
  • Department of Environmental Engineering
Georgios Eleftherios Stavroulakis
  • School of Production Engineering and Management
Akrotiri Campus, 73100, Chaniá, Crete, Greece