An approach for modeling and restructuring datasets concerning pollutant emissions in the air

• Main Author: Dimova, Delyana
• Format: Conference Proceeding
• Language: English
• Subjects: Agricultural wastes; Ammonia; Carbon dioxide; Columns (structural); Contaminants; Datasets; Methane; Nitrogen oxides; Pollutants; Pollution sources; Relational data bases; Tables (data); Variance analysis; VOCs; Volatile organic compounds; Wastewater treatment
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0208402

The examined pollution sources in the current paper include combustion and industrial processes; agriculture; household heating; waste and waste water treatment; road, rail and aviation transport. The investigated group of contaminants released from each of the listed pollution sources for the period 2011-2020 in Bulgaria are the following: sulphur and nitrogen oxides, non-methane volatile organic compounds, methane, carbon and dinitrogen oxide, carbon dioxide and ammonia. A hierarchical organization of the objects from the mentioned sets is built. This studied information from time series stored in xlsx files is structured in a relational database. In this connection, the values of contaminants from a certain pollution source in the relevant file are presented in matrix form. The variation of the number of columns in the formed rectangular matrix depends on the number of the examined years. The data are regrouped to obtain the transposed matrix. The components from each column of this matrix are entered into a selected field of a certain table from the database. The presented approach integrates the processes of searching the indicated data, restructuring and grouping separate datasets, and entering them in the built database. Certain criteria are defined in order to form and extract groups of elements from one or more tables of the database, as well as to establish the relevant dependencies for the studied objects. Analysis of variance and Tukey’s range test are used for statistical assessment of the data. The approach can also be applied to examine datasets on air pollutant emissions for other countries.