Light Pollution and Stargazing
This scientific poster was developed within the Erasmus+ KA210 project “Protect your Nature, Protect your Future,” coordinated by the 1st Gymasio Rafinas. Students of the Environmental Studies Club investigated light pollution in their city, exploring how artificial lighting affects the visibility of constellations and the night sky. Using citizen science tools such as the Globe at Night program, the Nightlights app, and Stellarium, they measured sky brightness, mapped observation points with GPS, and analyzed data from 108 questionnaires. Their results show that urban lighting strongly influences the ability to observe stars. The project raises awareness about energy efficiency and the beauty of the natural night sky as part of environmental education and sustainability.
School Bioclimatic Classroom with Robotics Applications
As part of the Erasmus+ KA210 project “Protect Your Nature, Protect Your Future,” we present the model of the School Bioclimatic Classroom with Robotics Applications.
This innovative creation aims to raise students’ awareness and educate them about the importance of sustainable development and climate change.
The classroom has been designed to promote energy efficiency and the use of renewable energy sources, while integrating robotic applications that allow real-time monitoring of energy consumption. Through these technologies, students develop digital skills and learn how to contribute to reducing their carbon footprint, supporting the goals of sustainable development.
The Bioclimatic Classroom is continuously improving and evolving, fostering collaboration and innovation among students from different countries. It encourages the exchange of ideas and good practices, empowering young people to become active citizens committed to protecting the environment and shaping a sustainable future.
">This video presents the bioclimatic classroom mode
Decoding Climate Change: 10 Years of Data from the School’s Weather Station in Rafina
A Decade of Meteorological Data: Understanding Local Climate Change
The ten-year dataset collected by our school’s weather station represents a valuable resource for understanding climate variations in our region. These data not only record daily weather conditions but also reflect the broader effects of climate change, providing crucial insights for future strategies in sustainable development.
This research is directly linked to the Erasmus+ KA210 project “Protect Your Nature, Protect Your Future”, as it enhances students’ knowledge and awareness of environmental challenges. The findings can be applied to our Bioclimatic Classroom, emphasizing the need for sustainable practices and the integration of technologies that reduce energy consumption.
Through this study, students develop digital competencies and are empowered to actively participate in environmental protection actions, promoting a culture of ecological awareness and social responsibility. The combination of data from the weather station and the bioclimatic classroom positions our school as a pioneer in promoting education for sustainability and innovation.
Climate change is one of the most pressing challenges facing our planet today. Human activities such as the release of greenhouse gases and deforestation have led to higher temperatures, shifts in climate patterns, and an increase in extreme weather events. The impacts include rising sea levels, destructive storms, biodiversity loss, and worsening living conditions for many species.
Analyzing a decade of meteorological data allows us to detect significant trends and variations that may be linked to climate change. The rise in average temperature, the increased frequency of extreme weather conditions, and the changing rainfall patterns provide evidence of the evolving climate.
For this reason, we collected data recorded by our school’s weather station from April 2014 to March 2024. Using Excel, we processed monthly mean temperatures for the entire decade, examined the frequency of extreme temperatures (maximum–minimum) during summer months, analyzed the variation of environmental parameters in autumn, and designed time series graphs, temperature anomaly charts, and rainfall frequency plots.
The study concluded with a statistical analysis of the data and the formulation of hypotheses regarding possible correlations with climate change
