The genus Aspergillus is one of the most prevalent regarding fungi in several highly contaminated occupational environments. The goal of the current study was to assess the prevalence of Aspergillus spp. in different settings, focusing on those where a higher load of fungal contamination is expected according to the European Agency for Safety and Health at Work. A specific protocol to ensure a more accurate assessment of the exposure to Aspergillus spp. is proposed aimed at allowing a detailed risk characterization and management. Two wastewater treatment plants, one wastewater elevation plant, four waste treatment plants, three cork industries, five slaughter houses, four feed industries, one poultry pavilion, and two swineries, all located in the outskirts of Lisbon, were assessed. In total, 125 air samples and 125 surface samples were collected and analysed by culture-based methods. Real-time polymerase chain reaction was performed to detect fungal presence in 100 samples, targeting the Aspergillus sections Circumdati, Flavi, and Fumigati. The highest prevalence of Aspergillus spp. was found in wastewater treatment plants (69.3%; 31.1%), waste treatment plants (34.8%; 73.6%), and poultry feed industry (6.3%; 26.1%), in air and surfaces, respectively. Aspergillus spp. was also prevalent in cork industry (0.9%; 23.4%), slaughter houses (1.6%; 17.7%), and swineries (7.4%; 9.5%), in air and surfaces, respectively. The Aspergillus sections more prevalent in the air and surfaces of all the assessed settings were the Nigri section (47.46%; 44.71%, respectively), followed by Fumigati (22.28%; 27.97%, respectively) and Flavi (10.78%; 11.45%, respectively) sections. Aspergillus section Fumigati was successfully amplified by qPCR in 18 sampling sites where the presence of this fungal species had not been identified by conventional methods. It should be highlighted that the occupational exposure burden is due not only to the Aspergillus load, but also to the toxigenic potential of this genus. Based on our results, a protocol relied in the application of conventional and molecular methods in parallel is herein suggested aimed at allowing a better risk characterization and management.