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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" article-type="research-article" dtd-version="1.1d1" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher">Kazakhstan journal for oil &amp; gas industry</journal-id><journal-title-group><journal-title>Kazakhstan journal for oil &amp; gas industry</journal-title></journal-title-group><issn publication-format="print">2707-4226</issn><issn publication-format="electronic">2957-806X</issn><publisher><publisher-name>KMG Engineering</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">109017</article-id><article-id pub-id-type="doi">10.54859/kjogi109017</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>Specific features of air pollutant dispersion modeling at oil and gas production facilities</article-title></title-group><contrib-group><contrib contrib-type="author"><name name-style="western"><surname>Salimgereyev</surname><given-names>Malik Zh.</given-names></name><email>m.salimgereev@kmge.kz</email><uri content-type="orcid">https://orcid.org/0009-0003-0238-9574</uri><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Idrissova</surname><given-names>Elmira K.</given-names></name><email>e.idrissova@kmge.kz</email><uri content-type="orcid">https://orcid.org/0009-0000-2420-2350</uri><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Bassenova</surname><given-names>Marzhan B.</given-names></name><email>m.bassenova@kmge.kz</email><uri content-type="orcid">https://orcid.org/0009-0004-7974-3313</uri><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff id="aff-1">KMG Engineering</aff><pub-date date-type="epub" iso-8601-date="2026-09-30" publication-format="electronic"><day>30</day><month>09</month><year>2026</year></pub-date><volume>8</volume><issue>3</issue><fpage>129</fpage><lpage>140</lpage><history><pub-date date-type="received" iso-8601-date="2026-06-18"><day>18</day><month>06</month><year>2026</year></pub-date><pub-date date-type="accepted" iso-8601-date="2026-09-08"><day>08</day><month>09</month><year>2026</year></pub-date></history><permissions><copyright-statement>Copyright © 2026, Salimgereyev M.Z., Idrissova E.K., Bassenova M.B.</copyright-statement><copyright-year>2026</copyright-year></permissions><abstract>&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; Oil and gas production facilities represent complex industrial systems that exert a significant anthropogenic impact on ambient air quality. The simultaneous presence of organized and fugitive emission sources, high density of technological infrastructure, and adverse meteorological conditions considerably complicate the processes of air pollutant dispersion. Therefore, the application of mathematical modeling techniques is of particular importance for predicting ambient air pollution levels and assessing the environmental impacts of industrial facilities.&lt;/p&gt;&#13;
&lt;p&gt;&lt;strong&gt;Aim: &lt;/strong&gt;The s tudy aimed 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-Air software package.&lt;/p&gt;&#13;
&lt;p&gt;&lt;strong&gt;Materials and methods: &lt;/strong&gt;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. The principal research methods included comparative analysis, mathematical modeling, spatial interpretation, and expert assessment of pollutant dispersion maps.&lt;/p&gt;&#13;
&lt;p&gt;&lt;strong&gt;Results:&lt;/strong&gt; The findings indicate that organized emission sources account for 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. The verification calculations confirmed a generally satisfactory agreement between the calculated and project-based concentration fields .&lt;/p&gt;&#13;
&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Air pollutant dispersion modeling is an effective tool for assessing the impact of oil and gas production facilities on ambient air quality. A 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 to support the establishment of sanitary protection zones, develop environmental protection measures, and enhance industrial environmental monitoring.&lt;/p&gt;</abstract><kwd-group xml:lang="en"><kwd>ambient air</kwd><kwd>dispersion modeling</kwd><kwd>oil and gas production</kwd><kwd>ERA software package</kwd><kwd>permissible emission standards</kwd><kwd>maximum permissible emissions (MPE)</kwd><kwd>fugitive emissions</kwd><kwd>environmental safety</kwd><kwd>ground level concentrations</kwd></kwd-group><kwd-group xml:lang="kk"><kwd>атмосфералық ауа</kwd><kwd>таралуды модельдеу</kwd><kwd>мұнай-газ өндіру</kwd><kwd>ЭРА бағдарламалық кешені</kwd><kwd>РШН</kwd><kwd>ұйымдастырылмаған шығарындылар</kwd><kwd>экологиялық қауіпсіздік</kwd><kwd>жерүсті концентрациялары</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>атмосферный воздух</kwd><kwd>моделирование рассеивания</kwd><kwd>нефтегазодобыча</kwd><kwd>программный комплекс ЭРА</kwd><kwd>нормативы допустимых выбросов</kwd><kwd>предельно допустимые выбросы</kwd><kwd>неорганизованные выбросы</kwd><kwd>экологическая безопасность</kwd><kwd>приземные концентрации</kwd></kwd-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>OND-86. Method for Calculating Atmospheric Concentration of Hazardous Substances Contained in Industrial Emissions. Leningrad: Gidrometeoizdat; 1987.</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>U.S. Environmental Protection Agency. Guideline on Air Quality Models (Appendix W to 40 CFR Part 51). Washington, DC: U.S. EPA; 2024.</mixed-citation></ref><ref id="B3"><label>3.</label><mixed-citation>Sadykhov AB, Gasanov RE. Algorithm for Calculating Pollutant Dispersion at Industrial Sites. Transactions of The National Academy of Sciences of Azerbaijan. 2004;2:200–204. (In Russ).</mixed-citation></ref><ref id="B4"><label>4.</label><mixed-citation>Ryvkin DB. Modeling and Management Tasks of Environmental Safety at Oil and Gas Industry Enterprises [dissertation]. Moscow; 2010. Available from: www.dissercat.com/content/zadachi-modelirovaniya-i-upravleniya-ekologicheskoi-bezopasnostyu-predpriyatii-neftegazovogo. (In Russ).</mixed-citation></ref><ref id="B5"><label>5.</label><mixed-citation>Lauvaux T, Giron C, Mazzolini M, et al. Global Assessment of Oil and Gas Methane Ultra-Emitters. Science. 2021;375(6580):557–561. doi: 10.1126/science.abj4351.</mixed-citation></ref><ref id="B6"><label>6.</label><mixed-citation>Pasquill F, Smith FB. Atmospheric Diffusion: The Dispersion of Windborne Material from Industrial and Other Sources. 2nd ed. Chichester: Ellis Horwood; 1974. 429 p.</mixed-citation></ref><ref id="B7"><label>7.</label><mixed-citation>Seinfeld JH, Pandis SN. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. 3rd ed. Hoboken: John Wiley &amp; Sons; 2016. 1152 p.</mixed-citation></ref><ref id="B8"><label>8.</label><mixed-citation>Turner DB. Workbook of Atmospheric Dispersion Estimates: An Introduction to Dispersion Modeling. U.S. Department of Health, Education, and Welfare, National Center for Air Pollution Control; 1967. 84 p.</mixed-citation></ref><ref id="B9"><label>9.</label><mixed-citation>Schulman LL, Strimaitis DG, Scire JS. Development and Evaluation of the PRIME Plume Rise and Building Downwash Model. Journal of the Air &amp; Waste Management Association (In Press).</mixed-citation></ref><ref id="B10"><label>10.</label><mixed-citation>De Visscher A. Air Dispersion Modeling: Foundations and Applications. Hoboken: John Wiley &amp; Sons; 2014. 664 p.</mixed-citation></ref></ref-list></back></article>
