Methodical approaches to spatial identification of probable sources of obnoxious odors in ambient air based on fuzzy logic
Authors:   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Zaitseva N.V. , May I.V. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Kiryanov D.А. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Kleyn S.V. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Chigvintsev V.М. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Klyachin А.А. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation
Published: January 2025

The article describes a task of searching for an unknown source of odor pollution. This task is classified as ‘considerably uncertain’, for which formal solution is proposed. The issue of obnoxious odor is relevant for many residential areas in large cities and industrial centers. Despite strict governmental control of emissions, including those from recycling facilities, undetermined pollution sources often become a reason for numerous people’s complaints. Odor pollution is known to affect human health including the respiratory, cardiovascular and nervous systems; to reduce life quality and adaptation capacity. Industrial enterprises, treatment and recycling facilities are the most frequent sources of odor pollution. Complexity of air quality control is caused by subjectivity typical for odor perception and their multicomponent structure.

The suggested approach to searching for obnoxious odor sources is based on using statistical data about complaints made by people and up-to-date methods of the fuzzy set theory. Statistical data on people’s complaints are subjective and emotional in their essence. In this method, an odor is represented as a linguistic variable that considers odor quality and intensity and weather and climatic conditions (wind speed and direction). The method assumes that an odor source is located in the direction opposite to the wind speed vector at the moment a complaint was registered. A possible location of an odor source was identified by superposing wind directions and considering impacts of a ‘pollution plume’, which had an area of dispersion of substances / a mixture of substances responsible for an odor. To perform more precise spatial searching for odor sources, the task was solved using fuzzy logic methods and a fuzzy conclusion considering a high level of uncertainty. The function of belonging was introduced to identify whether a point belonged to the multitude of probable locations of an odor source. Fuzzy model parameters were identified by using numeric experiments.

The suggested approached, which is based on analyzing statistical data about people’s complaints, has been shown to not only conform to up-to-date trends in applied use of the fuzzy set theory but also to be able to solve the relevant task of identifying sources of odor pollution in ambient air. The approaches outlined in the article expand a sphere where the fuzzy set theory can be used introducing a new application trend for it, which is to determine reasons for differences between data obtained by laboratory control of ambient air quality and calculated dispersion of chemical emissions from stationary and mobile pollution sources.