No abstract

This study presents the development and experimental assessment of novel, high strength, cementless binders that incorporate alkali-activated local waste. A silica-rich diabase mud (DM), currently considered as waste, was previously investigated for geopolymerization, signifying that the DM lacked the necessary reactivity to provide a stable geopolymer binder alone. Moreover, even after incorporation of small amounts of cement and metakaolin, the DM mixtures still did not yield adequate mechanical properties. In this study, the local DM was instead combined with another industrial byproduct known as Ground Granulated Blast-furnace Slag (GGBS) in varying mixtures. The mixture design trials enabled the development of three high strength cementless geopolymer mixtures with 28-day compressive strengths ranging between 60 and 100 MPa, comparable to conventional concrete compressive strengths. The results indicate that the innovative geopolymer material is very promising for the manufacturing of pavement tiles and other precast construction products. Most importantly, this study presents the first successful development of a construction material of adequate compressive strength that can absorb large quantities of the abundant quarry waste, following a course of 10 years of unsuccessful attempts to valorize the local DM. Although difficulties were encountered due to a high reactivity rate, especially for the mix that included the highest GGBS content, prototype pavement tiles were manufactured and assessed experimentally. The results reveal a promising potential of valorizing the local DM in the development of precast geopolymer products, despite the effects of shrinkage cracking on the experimental evaluation of the material mechanical properties.

The "EXCELSIOR" H2020 Widespread Teaming Phase 2 Project: ERATOSTHENES: EXcellence Research Centre for Earth SurveiLlance and Space-Based MonItoring Of the EnviRonment is supported from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 857510 for a 7 year project period to establish a Centre of Excellence in Cyprus. As well, the Government of the Republic of Cyprus is providing additional resources to support the establishment of the ERATOSTHENES Centre of Excellence (ECoE) in Cyprus. The ECoE seeks to fill the gap by assisting in the spaceborne Earth Observation activities in the Eastern Mediterranean and become a regional key player in the Earth Observation (EO) sector. There are distinct needs and opportunities that motivate the establishment of an Earth Observation Centre of Excellence in Cyprus, which are primarily related to the geostrategic location of the European Union member state of Cyprus to examine complex scientific problems and address user needs in the Eastern Mediterranean, Middle East and Northern Africa (EMMENA), as well as South-East Europe. An important objective of the ECoE is to be a Digital Innovation Hub and a Research Excellence Centre for EO in the EMMENA region, which will establish an ecosystem where state-of-the-art sensing technology, cutting-edge research, targeted education services, and entrepreneurship come together. It is based on the paradigm of Open Innovation 2.0 (OI2.0), which is founded on the Quadruple Helix Model, where Government, Industry, Academia and Society work together to drive change by taking full advantage of the cross-fertilization of ideas. The ECoE as a Digital Innovation Hub (DIH) adopts a two-axis model, where the vertical axis consists of three Thematic Clusters for sustained excellence in research of the ECoE in the domains of Atmosphere and Climate, Resilient Societies and Big Earth Data Management, while the horizontal axis is built around four functional areas, namely: Infrastructure, Research, Education, and Entrepreneurship. The ECoE will focus on five application areas, which include Climate Change Monitoring, Water Resource Management, Disaster Risk Reduction, Access to Energy and Big EO Data Analytics. This structure is expected to leverage the existing regional capacities and advance the excellence by creating new programs and research, thereby establishing the ECoE as a worldclass centre capable of enabling innovation and research competence in Earth Observation, actively participating in Europe, the EMMENA region and the global Earth Observation arena.

<p>Concrete is one of the most commonly used construction materials. However, the main drawbacks in the use of concrete are related to the use of cement and subsequently the high percentage of carbon dioxide emissions. The use of cement substitutes is an area where there is a lot of ongoing research. Geopolymer concrete is a concrete in which cement is replaced by waste materials such as Pulverised Fuel Ash (PFA), or Ground Granulated Blast furnace Slag (GGBS). To activate the geopolymerisation, an alkali activator is used. The procedure, which is used for the production of a geopolymer concrete, is normally a two-part procedure: Preparation of the alkali activator one day before the mixing and mixing of the aluminosilicate sources (PFA, GGBS) with the activator. To make the production of geopolymers more user friendly it needs to be converted to one part procedure where water will be added in a readymade mix. In the published literature, there is research on one- part geopolymers, but there are limited studies on the use of demolition waste materials as substitution of PFA and GGBS in this type of materials. With the current study, different sources of raw materials focusing on demolition waste materials such as red bricks and reclaimed concrete, which are commonly used in construction worldwide, will be examined for the production of one- part geopolymer. The major aim of this research proposal is to develop an innovative sustainable one-part cement free geopolymer concrete. The new concrete is a “green” concrete where cement is replaced by waste materials. Construction demolition materials such as red bricks can be used as raw materials in the geopolymer matrix. This project will focus on the selection, characterisation and development of the appropriate processing of these red bricks so as they can be used as raw materials in the geopolymer matrix. Also, the development of one part mix where the new concrete will be ready for use by adding only water in it, is another aim of the proposed project.</p>

&lt;div&gt; &lt;p&gt;&lt;span data-contrast=&quot;auto&quot;&gt;Landslides constitute a significant geohazard causing human losses and significantly affecting the economy worldwide. Earth Observation and the exploitation of the freely available Copernicus datasets, such as the Sentinel-1 and Sentinel-2 satellite images, can assist in the systematic monitoring of landslides overcoming the restrictions arising from in situ measurements. This study shows how the Google Earth Engine (GEE) platform can be utilised for the rapid mapping of landslides and effectively integrate both passive and active satellite data to enhance the results&amp;#8217; reliability. The GEE is a cloud computing platform designed to store and process huge datasets for scientific analysis and visualization of geospatial datasets where open-source images are acquired by several satellites.&lt;/span&gt;&lt;span data-ccp-props=&quot;{&amp;quot;201341983&amp;quot;:0,&amp;quot;335551550&amp;quot;:6,&amp;quot;335551620&amp;quot;:6,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}&quot;&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt; &lt;/div&gt; &lt;div&gt; &lt;p&gt;&lt;span data-contrast=&quot;auto&quot;&gt;For this study, Ground Range Detection (GRD) Sentinel-1 and multispectral Sentinel-2 satellite data were utilised for a time period between 2016 and 2021. Multitemporal SAR change detection was conducted to identify potential landslides using GRD Sentinel-1 satellite images. Moreover, the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Moisture Index (SMI) and Bare Soil Index (BSI) indices were used for the multispectral data. Multi-temporal image composites were created for the two periods. Furthermore, for all image collections, the calculated spectral indices were added as new bands to all images, and the maximum value for each pixel of the vegetation indices was taken. Following, the difference image for each spectral index was created based on two methods, i.e., the first method was based on subtracting the two time periods, and the second one on subtracting each year from the total average for the time period from 2016 until 2021. The possible events were then masked using the thresholding technique based on the trial-and-error procedure where the analyst adjusts manually the thresholds and evaluates the resulting image until satisfied. Based on the results derived from the abovementioned processing, the use of the second method, i.e., subtracting each year from the average, based on the NDVI spectral index provides better results. The proposed methodology was tested in Paphos city in Cyprus because of the occurrence of numerous landslide events in this area, based on the landslide inventory provided by the Geological Survey Department of the Ministry of Agriculture, Rural Development and Environment. The results of this study were validated using high-resolution images from Google Earth in combination with the data from the Geological Survey department.&lt;/span&gt;&lt;span data-ccp-props=&quot;{&amp;quot;201341983&amp;quot;:0,&amp;quot;335551550&amp;quot;:6,&amp;quot;335551620&amp;quot;:6,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}&quot;&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt; &lt;div&gt; &lt;p&gt;&lt;strong&gt;&lt;span data-contrast=&quot;none&quot;&gt;Acknowledgements&lt;/span&gt;&lt;/strong&gt;&lt;span data-ccp-props=&quot;{&amp;quot;134233117&amp;quot;:false,&amp;quot;134233118&amp;quot;:false,&amp;quot;201341983&amp;quot;:0,&amp;quot;335551550&amp;quot;:6,&amp;quot;335551620&amp;quot;:6,&amp;quot;335559738&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}&quot;&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt; &lt;/div&gt; &lt;div&gt; &lt;p&gt;&lt;span data-contrast=&quot;none&quot;&gt;The authors acknowledge the &#039;EXCELSIOR&#039;: ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The &#039;EXCELSIOR&#039; project has received funding from the European Union&#039;s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The authors would also like to thank the Geological Survey Department of the Ministry of Agriculture, Rural Development and Environment for the provision of the landslide inventory.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt; &lt;/div&gt;