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Identifying and defining priority of obnoxious odor sources in ambient air in settlements using systematic hybrid analysis and fuzzy logic

https://doi.org/10.47470/0016-9900-2025-104-12-1589-1597

EDN: kankcl

Abstract

Introduction. Obnoxious odors in ambient air in industrial centers are a significant medical and social issue.

The aim of this study is to develop and test methodical approaches to identifying potential obnoxious odor sources in residential areas of regions with developed industries using fuzzy logic and systematic hybrid data analysis.

Materials and methods. We have developed and tested a complex eight-stage methodology for identifying priority obnoxious odor sources in the urban environment. The suggested approaches have been tested using actual data collected in a large industrial center. Fuzzy logic is used as a method for identifying areas where odor sources are likely to be located. Within the method, an odor is given as a linguistic variable that considers people’s complaints and meteorological conditions. We have analyzed one thousand nine hundred twenty seven people’s complaints about obnoxious odors and meteorological parameters (2022–2024), ambient air monitoring data (automated pollution control stations, readings taken at representative points (GC-MS)) and have accomplished computational simulation of 23 olfactory-active substances together with calculating source contributions, sensor estimates, GIS-modeling, and graphic spatial analysis.

Results. Testing of the developed universal algorithms has established 249 chemicals to be olfactory active out of total 375 ones emitted into ambient air. We have found a spatial-temporal correlation between complaints, meteorological conditions and time: 67% complaints are made when the wind speed is 0–1 m/sec; the peaks are reached in the evening (59.3%) and morning (22.4%). Chemical levels systematically higher than single maximum MPC have been confirmed by field observations: hydrogen sulfide (up to 17.5 MPC), formaldehyde (up to 3.2 MPC), and ammonia (up to 1.5 MPC). We have identified three zones where obnoxious odor sources are likely to be located in the analyzed area (15.85–31.8 km²); these zones correspond to industrial clusters. Ranking of 21 enterprises as potential pollutant sources has established 6 priority ones creating >80% of the total contribution to concentrations of odor chemicals in places where people’s complaints are usually made.

Limitations. The results are based on routine operation of obnoxious odor sources; emergency situations have not been analyzed.

Conclusion. The developed universal approach to identifying obnoxious odor pollution sources under uncertainty has been found to be effective in variable meteorological conditions and to be ready for testing in other areas with similar problems.

Compliance with ethical standards. The study does not require approval by an ethical committee or any other documents.

Contributions:
Zaitseva N.V. – study concept and design;
Patyashina М.А., Prokofyeva М.V.
– data collection, editing the text;
Kleyn S.V. – study concept and design, data collection, writing the text;
May I.V., Kiryanov D.А. – study concept and design, editing the text;
Klyachin А.А. – data collection and analysis, writing the text;
Chigvintsev V.М. – data collection and analysis.
All authors are responsible for the integrity of all parts of the manuscript and approval of the manuscript final version.

Conflict of interest. The authors declare no conflict of interest.

Funding. The study had no sponsorship.

Received: July 23, 2025 / Revised: November 19, 2025 / Accepted: December 2, 2025 / Published: January 15, 2026

About the Authors

Nina V. Zaitseva
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

DSc (Medicine), professor, academician of the RAS, scientific director of the Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 614045, Perm, Russian Federation

e-mail: znv@fcrisk.ru



Marina A. Patyashina
Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

Head, Office of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare of the Republic of Tatarstan (Tatarstan), Kazan, 420111, Russian Federation

e-mail: RPN.RT@tatar.ru



Svetlana V. Kleyn
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

DSc (Medicine), professor of the RAS, deputy director for research of the Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, Perm, 614045, Russian Federation

e-mail: kleyn@fcrisk.ru



Irina V. May
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

DSc (Biology)ical Science, professor, principal researcher-advisor to the Director of the Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 614045, Perm, Russian Federation

e-mail: may@fcrisk.ru



Marina V. Prokofyeva
Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

Deputy head, Office of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare of the Republic of Tatarstan (Tatarstan), Kazan, 420111, Russian Federation

e-mail: RPN.RT@tatar.ru 



Dmitrii A. Kiryanov
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

PhD (Engineering), head, Department of systems and processes mathematical modeling, Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, Perm, 614045, Russian Federation

e-mail: kda@fcrisk.ru



Aleksey A. Klyachin
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

Researcher, Department for systemic procedures of sanitary-hygienic analysis and monitoring of the Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, Perm, 614045, Russian Federation

e-mail: klyachin@fcrisk.ru



Vladimir M. Chigvintsev
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing
Россия

PhD (Physics and Mathematics), senior researcher, Situation modeling and expert and analytical management techniques laboratory, Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, Perm, 614045, Russian Federation

e-mail: cvm@fchisk.ru



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For citations:


Zaitseva N.V., Patyashina M.A., Kleyn S.V., May I.V., Prokofyeva M.V., Kiryanov D.A., Klyachin A.A., Chigvintsev V.M. Identifying and defining priority of obnoxious odor sources in ambient air in settlements using systematic hybrid analysis and fuzzy logic. Hygiene and Sanitation. 2025;104(12):1589-1597. (In Russ.) https://doi.org/10.47470/0016-9900-2025-104-12-1589-1597. EDN: kankcl

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ISSN 0016-9900 (Print)
ISSN 2412-0650 (Online)