Specific features of air pollutant dispersion modeling at oil and gas production facilities

ABSTRACT

Background: Oil and gas production facilities represent complex industrial systems that impose a significant anthropogenic burden on ambient air quality. The simultaneous presence of organized and fugitive emission sources, high density of technological infrastructure, and adverse meteorological conditions complicate the processes of air pollutant dispersion. Therefore, the application of mathematical modeling techniques is of particular importance for predicting atmospheric pollution levels.

Aim: The aim of this study was to analyze the specific features of air pollutant dispersion modeling at oil and gas production facilities, identify the key factors affecting calculation accuracy, and assess the consistency between the results obtained from Maximum Permissible Emission (MPE) projects and verification calculations performed using the ERA software package.

Materials and methods: The study utilized data from Maximum Permissible Emission (MPE) projects, atmospheric dispersion calculations, and verification modeling results obtained using the ERA software package for production facilities of Enterprises No. 1 and No. 2. Comparative analysis, mathematical modeling, spatial interpretation, and expert evaluation of dispersion maps were employed as the primary research methods.

Results: The findings indicate that organized emission sources account for approximately 60–70% of total emissions at oil and gas production facilities, while the contribution of fugitive sources may reach 20–30%. At the same time, low-level fugitive emission sources were found to have a substantial influence on the formation of ground-level pollutant concentrations. The highest concentrations were observed for nitrogen dioxide, hydrogen sulfide, soot, and benzo(a)pyrene. The modeling results demonstrated the decisive role of meteorological factors, particularly wind speed and atmospheric stability conditions, in determining pollutant dispersion patterns. Verification calculations confirmed a generally satisfactory agreement between calculated and design concentration fields.

Conclusion: Air pollutant dispersion modeling is an effective tool for assessing the impact of oil and gas production facilities on ambient air quality. Comprehensive consideration of organized and fugitive emission sources, technological infrastructure density, and meteorological conditions significantly improves the reliability of modeling results. The obtained findings can be applied in the justification of sanitary protection zones, development of environmental protection measures, and improvement of industrial environmental monitoring systems.