Inhalation of particulate matter in industrial environments has been associated with respiratory symptoms and lung diseases, which continues to lead to long- and short-term hazardous health effects on exposed subjects. The main objectives of this study were (a) to determine the dust exposure of workers from the lead industry in different operations and (b) to evaluate if the Exhaled Breath Condensate (EBC) can be used as a non-invasive tool to evaluate this exposure. Therefore, this cross-sectional study not only measured the exposure to Airborne Particulate Matter (APM) and to the associated elements but also analysed the EBC elemental composition. APM was collected in Ind1, Ind2, Offices and outdoor with Gent samplers, which delivers two size fractions: fine particulate matter (< 2.5 µm), and coarse particulate matter (between 2.5 and 10 µm). EBC samples were collected from the workers and from a non-exposed group working in Offices. The techniques INAA and PIXE were used for the APM element characterization and ICP-MS for EBC elemental content. The PM2.5 and PM2.5-10 mass concentrations were significantly higher in the industries studied than in Offices and in the environment. At the industrial sites surveyed the coarse fraction dominated and both factories had different fingerprints: APM elements with higher expression were Pb, Sb, Na, Cl and Fe in Ind1 and Pb, Si, Br, Ca, Al, Cl and Na in Ind2. Most of these elements revealed a gradient of concentration where Ind.1 > Ind.2 > Offices and EBC revealed a clear translation of this exposure, suggesting the latter to be a potential good indicator of exposure to metals in occupational settings. Pb in EBC presented the most representative results. Even though EBC was found to reflect predominantly the inhaled coarser fraction it is more related to concentration levels of exposure than to the predominance of APM fraction. The present study demonstrated not only the ability of EBC to reflect environmental exposure to metals but also the importance of measuring and characterizing different fractions of APM for a correct assessment.