Assessing heavy metal pollution load index (PLI) in biomonitors and road dust from vehicular emission by magnetic properties modeling.

Vehicular traffic occupies a significant place among the sources of air pollution, due to population and urban growth that has led to an excessive increase in the vehicle fleet worldwide, and in Costa Rica as well. Vehicle emissions generate greenhouse gases (GHGs), particulate matter (PM), and heavy metals (HMs), due to combustion products from fossil-fuel engines, tire wear, and brake linings. HMs are important because they cannot be degraded or destroyed naturally; however, they can be diluted by physicochemical agents and be incorporated into trophic chains where they can be bioaccumulated causing significant negative effects on human well-being and ecological quality. This study aimed to assess the HM pollution load in biomonitors and road dust from vehicular emissions by chemical analyses and magnetic properties modeling. For this purpose, chemical and magnetic property analyses were carried out on samples of road dust and leaves of Cupressus lusitanica Mill. and Casuarina equisetifolia L., which were sampled during 2 different years in the Greater Metropolitan Area of Costa Rica known as GAM. Contamination factor (CF) and pollution load index (PLI) results showed significant metal pollution in some of the study sites. Contamination by the metals V, Cr, and Zn was most commonly present in the biomonitors, and for road dust, they were Cr, Zn, and Pb. The PLI estimates obtained with the validated support vector machine (SVM) magnetic properties models were consistent (sensitivity, specificity, and precision) with those obtained by chemical analysis, demonstrating the feasibility of this method for the identification of this index of contamination.