Assessment of oceanographic services for the monitoring of highly anthropised coastal lagoons: The Mar Menor case study

Ocean monitoring systems are designed for continuous monitoring to track their evolution and anticipate environmental issues. However, they are often based on IoT systems that offer little spatial coverage and are hard to maintain. Satellite remote sensing offers good geographical coverage but they also face several challenges to become a monitoring system. This paper introduces an easy-to-use software tool to crawl water-quality data from up to 6 satellite instruments from the ESA and NASA. Particularly, Chl-a data is deeply analyzed in terms of reliability and data coverage for a highly anthropised coastal lagoon (Mar Menor, Spain), where serious socio-environmental issues are happening. Our results show a good linear correlation between in situ data and SRS data, reaching values close to 0.9, and stating the relevance of organic matter inputs from ephemeral streams in Chl-a concentrations. Moreover, temporal granularity is increased from 5 to 1.5 days by combining SRS sources.Preprin

Development of a Model to Estimate the Risk of Emission of Greenhouse Gases from Forest Fires

While the Mediterranean basin is foreseen to be highly affected by climate change (CC) and severe forest fires are expected to be more frequent, international efforts to fight against CC do not consider forest fires’ greenhouse gas (GHG) emissions risk and the possibility of its mitigation. This is partly due to a lack of a methodology for GHG risk spatial assessment and consideration of the high value of carbon stocks in forest ecosystems and their intrinsic risk. To revert this, an innovative GHG emission risk model has been developed and implemented in a pilot forest area. This model considers geospatial variables to build up emission vulnerability based on potential fire severity and resistance of a landscape, value at risk and the hazard of a fire occurrence. The results classify low, moderate and high emission risks in the analysed areas. This identification of hotspots allows the prioritisation of fire prevention measures in a region to maximise the reduction of GHG emissions in the case of a fire event. This constitutes the first step in a holistic and consistent CC mitigation that not only considers anthropic GHG sources but also possible GHG emissions by forest fires that can be actively prevented, managed and reduced