A fuzzy-based analysis of air particle pollution data: a magnetic index IMC Authors: Mauro A. E. Chaparro, Marcos A. E. Chaparro, Daniela Molinari Magnetic monitoring allows for assessing the particle pollution status in air, soils, and sediments. Airborne magnetic particles may be harmful because of their composition, morphology, and association with potentially toxic elements that may be observed through relationships between magnetic parameters and pollution indices such as the Tomlinson PLI. We present a fuzzy-based analysis of magnetic biomonitoring data from four Latin American cities, which allows us to construct a magnetic contamination index IMC. This IMC uses four magnetic parameters, i.e., magnetic susceptibility χ, saturation isothermal remanent magnetization SIRM, the coercivity of remanence Hcr, and SIRM/χ, and proposes summarizing the information to more easily assess an area of interest based exclusively on magnetic parameters. The fuzzy inference system membership functions are built from the standardization of the data to become independent of the values, and the index applies to other data sets. It should be noted that the proposed IMC is calculated using the baseline values for each case study, similar to the PLI. The IMC output values are between 0 (no contaminated) and 10 (contaminated). The highest IMC values were obtained in sites close to industrial areas, and on the contrary, the lowest ones were observed in residential areas far from avenues or highways. The linear regression model between modeled IMC and PLI data yielded robust correlations of R2 > 0.85. The proposed IMC index is a complementary tool for air particle pollution and is a cost-effective magnetic approach for monitoring areas.

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