GIS-Based Identification and Representation of Particulate Matters Using Ontology and SPARQL

The cement industry is one of the industries that pollute the environment due to the micro-pollutants it releases. It has become necessary to use means and techniques to deposit and capture these pollutants and ensure that they do not leak into the atmosphere. Cement factories in Iraq are distributed among the Iraqi General Cement Company, the Southern General Cement Company, and the Northern General Cement Company, which includes the Badush cement factory, as a sample of our case study. This case study investigated the reality of air polluting industrial activities for ten sites in the Badush Cement Factory and analyzes the impact of cement production activities on the concentration of air pollutants such as pollution with particulate matter PM10 and PM2.5. The particulate matters are represented in the form of ontology which acts like a knowledge base for data analysis using geographic information systems (GIS). It is followed by execution of SPARQL query for retrieval of classes, properties and instances related to the domain ontology. During 2022–23, samples of coarse particles (PM10) and fine particles (PM2.5) were collected, and through GIS, the data obtained were analyzed and then compared to the standard rates of the Environmental Protection Organization. Through laboratory tests of the air, it was found that most of the pollutant concentrations of industrial activities were outside the permissible limits, which caused disruption to the ecosystem. The results revealed that during measuring the maximum concentration of PM10 and PM2.5 was respectively 1776 µg/m3 and 230 µg/m3, which exceed the maximum permissible concentration.