On a Holistic Modeling Approach for Managing Carbon Emission Ecosystems

Effective use of historical volumes of heterogeneous and multidimensional data is a major challenge, especially projects associated with potential applications of carbon emission ecosystems. Data science in these applications becomes tedious when such varied data are accumulated and or distributed in multiple domains. Design, development, and implementation of sustainable geological storages are crucial for managing carbon dioxide (CO₂) emissions and its modeling process. The purpose of the research is to address major challenges and how best a robust “ontology-based multidimensional data warehousing and mining” approach can resolve issues associated with carbon ecosystems. The conceptualized relationships deduced among multiple domains, integration of domain ontologies, data mining, visualization, and interpretation artefacts are highlights of the study. Several data, plot, and map views are extracted from metadata storage for interpreting new knowledge on carbon emissions. Statistical mining models describe data attributes’ correlations, patterns, and trends that can help in predicting future forecast of CO₂ emissions worldwide.     

Twenty years of elemental analysis of marine biota within the German Environmental Specimen Bank—a thorough look at the data

Purpose  

As one component of the German ecological environment observation, the Environmental Specimen Bank program was initiated in the mid-1980s. Under the program, representative specimens of marine, fresh water, and terrestrial ecosystems are sampled regularly and archived under chemically stable conditions. An initial characterization of the samples provides data regarding the status quo of the respective ecosystems. The aim of the present publication is to give insight into these real-time monitoring data, which have been generated for the last 10 to 20 years. This is done exemplarily for the heavy metals cadmium (Cd), mercury (Hg), and lead (Pb) in marine specimens of the Baltic and the North Sea.     

Targeting aquatic microcontaminants for monitoring: exposure categorization and application to the Swiss situation

Background, aim, and scope  

Aquatic microcontaminants (MCs) comprise diverse chemical classes, such as pesticides, biocides, pharmaceuticals, consumer products, and industrial chemicals. For water pollution control and the evaluation of water protection measures, it is crucial to screen for MCs. However, the selection and prioritization of which MCs to screen for is rather difficult and complex. Existing methods usually are strongly limited because of a lack of screening regulations or unavailability of required data.