Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks

This dataset contains the data that was used to model the spatial distribution of non-target screening data from the Joint Black Sea Surveys (JBSS) 2016 and 2017. The data is needed to reproduce and run the scripts that are contained in the following GitHub repository: https://github.com/nalygizakis/CECinBS The three zip files contain the three different splits of the training set that were used to train the models and evaluate their accuracy. The two excel files contain the chemical signals (component lists) of JBSS.

The data was generated in the context of the EU/UNDP Project: Improving Environmental Monitoring in the Black Sea—Selected Measures (EMBLAS-II), ENPI/2013/313-169.

Keywords

emerging contaminants, Dnieper river, Black Sea, Danube river, deep learning, convolutional neural network, riverine inputs, EMBLAS project, modeling spatial distribution

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