Suchergebnisse

Understanding the underlying processes and extracting detailed characteristics of rivers is critical and has not yet been fully developed. The purpose of this study was to examine the performance of non-linear time series methods on environmental data. Specifically, we performed an analysis of water level measurements, extracted from sensors, located on specified stations along the Nestos River (Greece), with Recurrence Plots (RP) and Recurrence Quantification Analysis (RQA) methods. A more detailed inspection with the sliding windows (epoqs) method was applied on the Recurrence Rate, Average Diagonal Line and Trapping Time parameters, with results showing phase transitions providing useful information about the dynamics of the system. The suggested method seems to be promising for the detection of the dynamical transitions that can characterize distinct time windows of the time series and reveals information about the changes in state within the whole time series. The results will be useful for designing the energy policy investments of producers and also will be helpful for dam management assessment as well as government energy policy.

AbstractSmart farming (SF) has emerged as a scientific approach exploiting technology advances for the management of agricultural practices, focusing on the control of resources and chemicals used. There is still limited evidence in the scientific literature in regard to the efficiency of SF, particularly for targeted environmental issues, such as air pollutant emissions from agricultural activities. The present paper expoits quantitative data collected from questionnaires to farmers of 6 pilot areas in Greece, participating in the LIFE GAIA Sense project. Emissions and pollutant levels were calculated for two consecutive years in these pilot areas, namely 2019 (baseline year) and 2020, which is the first SF application year. The methodology for calculating realistic emissions data, following a combined tier 1/tier2 approach is presented. To this purpose, detailed activity data of the specific SF application areas related to agricultural activities were acquired, based on the responses of participating farmers to targeted questionnaires. Calculated emissions were used as input data for air quality modeling simulations to examine the efficiency of SF in reducing local pollutant concentrations. The results show significant emissions and concentrations reductions in five out of the six pilot areas, for all pollutants and greenhouse gases studied, due to the decrease in fuel consumption and N fertilizer applied, as a result of the farmers following the SF advice. Particularly for NH3, which is an agricultural air pollutant of concern due to its health and environmental impacts, emission reductions of around 30% (and by up to almost 60%) were calculated.

The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) emerged in late 2019 and has caused a pandemic known as corona virus disease 2019 (COVID-19), responsible for the death of more than 2 million people worldwide. The outbreak of COVID-19 has posed an unprecedented threat on human lives and public safety. The aim of this review is to describe key aspects of the bio-pathology of the novel disease, and discuss aspects of its spread, as well as targeted protective strategies that can help shape the outcome of the present and future health crises. Greece is used as a model to inhibit SARS-COV-2 spread, since it is one of the countries with the lowest fatality rates among nations of the European Union (E.U.), following two consecutive waves of COVID-19 pandemic. Furthermore, niche research technological approaches and scientific recommendations that emerged during the COVID-19 era are discussed.