• SDSN - Greece
• Open Access close

This deliverable contains the test report of the 3D sensor.

Design and deployment and the pilot use case of Cyprus in accordance with the deployment plans of the inteGRIDy project as defined in WP5 Furthermore the DR strategies and DSM techniques developed will be applied to all buildings within the campus and households with the support of the Cyprus DSO EAC The DR and DSM will be tested and verified in order to reach the optimal techniques fulfilling the goals set and creating a WINWIN situation between all involved stakeholders

AbstractIn this paper, we introduce and test a framework to qualitatively assess the environmental impact of climate adaptation innovations with the ambition to facilitate the implementation of these adaptations. The framework was designed to enable continuous environmentally conscious benchmarking based on three environmental performance indicators: sustainable design, environmental impact and ecological impact. It was pilot tested by uninvolved experts and key-persons for two large-scale nature-based flood adaptation innovations in the Netherlands and discussed with environmental assessment professionals. Our findings indicate how the inclusion of our framework helps to identify important knowledge gaps regarding environmental co-benefits and trade-offs, and can be beneficial to both those developing the innovation and the local authorities charged with assessing the suitability of innovations. We conclude by noting how the incorporation of environmental impact assessment from the design stage of adaptations could supplement existing environmental assessment regulations pre-empting concerns rather than reacting to them.

BackgroundElevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate.MethodsA case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM10, NO2, O3) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15 year period.ResultsSignificant interaction between maximum air temperature (Tamax) and PM10 was observed. During “summer smog” days (Tamax > 25 °C and PM10 > 50 μg/m3), the mortality risk at lag 2 was 7% higher compared to the reference (Tamax 15 °C and PM10 15 μg/m3). Persons above age 85 living alone were at highest risk.ConclusionWe found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%.

Discovery of novel viruses in host samples is a multidisciplinary process which relies increasingly on next-generation sequencing (NGS) followed by computational analysis. A crucial step in this analysis is to separate host sequence reads from the sequence reads of the virus to be discovered. This becomes especially difficult if no reference genome of the host is available. Furthermore, if the total number of viral reads in a sample is low, de novo assembly of a virus which is a requirement for most existing pipelines is hard to realize. We present a new modular, computational pipeline for discovery of novel viruses in host samples. While existing pipelines rely on the availability of the hosts reference genome for filtering sequence reads, our new pipeline can also cope with cases for which no reference genome is available. As a further novelty of our method a decoy module is used to assess false classification rates in the discovery process. Additionally, viruses with a low read coverage can be identified and visually reviewed. We validate our pipeline on simulated data as well as two experimental samples with known virus content. For the experimental samples, we were able to reproduce the laboratory findings. Our newly developed pipeline is applicable for virus detection in a wide range of host species. The three modules we present can either be incorporated individually in other pipelines or be used as a stand-alone pipeline. We are the first to present a decoy approach within a virus detection pipeline that can be used to assess error rates so that the quality of the final result can be judged. We provide an implementation of our modules via Github. However, the principle of the modules can easily be re-implemented by other researchers.

Livestock farming is the world’s largest land use sector and utilizes around 60% of the global biomass harvest. Over the coming decades, climate change will affect the natural resource base of livestock production, especially the productivity of rangeland and feed crops. Based on a comprehensive impact modeling chain, we assess implications of different climate projections for agricultural production costs and land use change and explore the effectiveness of livestock system transitions as an adaptation strategy. Simulated climate impacts on crop yields and rangeland productivity generate adaptation costs amounting to 3% of total agricultural production costs in 2045 (i.e. 145 billion US$). Shifts in livestock production towards mixed crop-livestock systems represent a resource- and cost-efficient adaptation option, reducing agricultural adaptation costs to 0.3% of total production costs and simultaneously abating deforestation by about 76 million ha globally. The relatively positive climate impacts on grass yields compared with crop yields favor grazing systems inter alia in South Asia and North America. Incomplete transitions in production systems already have a strong adaptive and cost reducing effect: a 50% shift to mixed systems lowers agricultural adaptation costs to 0.8%. General responses of production costs to system transitions are robust across different global climate and crop models as well as regarding assumptions on CO2 fertilization, but simulated values show a large variation. In the face of these uncertainties, public policy support for transforming livestock production systems provides an important lever to improve agricultural resource management and lower adaptation costs, possibly even contributing to emission reduction. European Union BMBF CGIAR Peer Reviewed

Europe is facing the challenge of increasing shares of energy from variable renewable sources. Furthermore, it is heading towards a fully integrated electricity market, i.e. a Europe-wide electricity system. The stable operation of this large-scale renewable power system requires detailed information on the amount of electricity being transmitted now and in the future. To estimate the actual amount of electricity, upscaling algorithms are applied. Those algorithms – until now – however, only exist for smaller regions (e.g. transmission zones and single wind farms). The aim of this study is to introduce a new approach to estimate Europe-wide wind power generation based on spatio-temporal clustering. We furthermore show that training the upscaling model for different prevailing weather situations allows to further reduce the number of reference sites without losing accuracy.

MedAID (Mediterranean Aquaculture Integrated Development) is a European H2020 Research and Innovation Project that started in 2017. The main objective was to increase the overall competitiveness and sustainability of the whole value chain of the Mediterranean marine aquaculture sector by improving its technical and business performance and by shifting to a sustainable market-oriented approach with a more positive social and consumer perception. In the field of disease control and welfare MedAID aims to provide essential components for a better health and welfare management system for the Mediterranean marine aquaculture industry overall and at company level. One of the gaps addressed by MedAID was the lack of reference methodologies for disease diagnostics for European seabass and Gilthead seabream, the main species produced in Mediterranean marine fish farming. The present Diagnostic Manual was conceived in the form of up-to-date guidelines providing current methodologies for a harmonised approach to the health challenges due to viral and bacterial pathogens in the farming of seabass and seabream. https://om.ciheam.org/option.php?IDOM=1037

Background. Epidemiological evidence on the association between ambient air pollution and brain tumor risk is sparse and inconsistent. Methods. In 12 cohorts from 6 European countries, individual estimates of annual mean air pollution levels at the baseline residence were estimated by standardized land-use regression models developed within the ESCAPE and TRANSPHORM projects: Particulate matter (PM) ≥2.5,≥10, and 2.5-10 FÊm in diameter (PM2.5, PM10, and PMcoarse), PM2.5 absorbance, nitrogen oxides (NO2 and NOx) and elemental composition of PM. We estimated cohort-specific associations of air pollutant concentrations and traffic intensity with total, malignant, and nonmalignant brain tumor, in separate Cox regression models, adjusting for risk factors, and pooled cohort-specific estimates using random-effects meta-analyses. Results. Of 282 194 subjects from 12 cohorts, 466 developed malignant brain tumors during 12 years of follow-up. Six of the cohorts also had data on nonmalignant brain tumor, where among 106 786 subjects, 366 developed brain tumor: 176 nonmalignant and 190 malignant. We found a positive, statistically nonsignificant association between malignant brain tumor and PM2.5 absorbance (hazard ratio and 95% CI: 1.67; 0.89.3.14 per 10.5/m3), and weak positive or null associations with the other pollutants. Hazard ratio for PM2.5 absorbance (1.01; 0.38.2.71 per 10-5/m3) and all other pollutants were lower for nonmalignant than for malignant brain tumors. Conclusion. We found suggestive evidence of an association between long-term exposure to PM2.5 absorbance indicating traffic-related air pollution and malignant brain tumors, and no association with overall or nonmalignant brain tumors. © 2018 The Author(s). Chemicals/CAS: nitric oxide, 10102-43-9; nitrogen dioxide, 10102-44-0