Andrea Cattaneo1, Laura Campo2, Simona Iodice3, Andrea Spinazzè1, Luca Olgiati4, Francesca Borghi1, Elisa Polledri4, Laura Angelici5, Domenico Maria Cavallo1, Silvia Fustinoni6, Valentina Bollati3. 1. Department of Science and High Technology, Università degli Studi dell'Insubria, 22100 Como, Italy. 2. Environmental and Industrial Toxicology Unit Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy. Electronic address: laura.campo@policlinico.mi.it. 3. EPIGET Laboratory, Department of Clinical Sciences and Community Health, Università degli Studi di Milano, 20122 Milan, Italy. 4. Environmental and Industrial Toxicology Unit Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy. 5. EPIGET Laboratory, Department of Clinical Sciences and Community Health, Università degli Studi di Milano, 20122 Milan, Italy; Department of Epidemiology, Lazio Regional Health Service, ASL Roma 1, Roma, Italy. 6. Environmental and Industrial Toxicology Unit Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy; EPIGET Laboratory, Department of Clinical Sciences and Community Health, Università degli Studi di Milano, 20122 Milan, Italy.
Abstract
BACKGROUND: Human exposure to air pollutants, and specifically to particulate matter (PM) and volatile organic compounds (VOCs), may pose a relevant risk on human health. AIM: To evaluate the personal exposure of adults living and working in Milan (Italy) by environmental and biological monitoring. METHODS: Personal exposure of 51 volunteer adults to PM2.5, PM2.5-10 and selected VOCs, including benzene, toluene, ethylbenzene, o-xylene, m + p-xylene, methyl tert-butyl ether, naphthalene, hexane, cyclohexane, heptane, and limonene was assessed along a 24-h period via personal cascade impactors and radial diffusive samplers. Urine spot samples were collected to investigate the corresponding urinary biomarkers. Time-activity patterns were filled in by participants to explore the performed activities. Multiple regression models were applied to investigate the association between personal exposure, biomarker levels, and tobacco smoke, traffic exposure, commuting mode, cooking activities, and personal characteristics. RESULTS: Median personal exposure to PM2.5, PM2.5-10, benzene, toluene, ethylbenzene o-xylene, m + p-xylene, methyl tert-butyl ether, naphthalene, hexane, cyclohexane, heptane, and limonene were 36.1, 7.8, 2.3, 7.8, 2.1, 1.8, 4.7, 0.8, 0.3, 1.4, 2.5, 1.6, and 59.9 μg/m3, respectively. Median levels of urinary benzene, toluene, ethylbenzene o-xylene, m + p-xylene, naphthalene, hexane, and heptane were 78.0, 88.1, 21.5, 15.2, 43.9, 21.0, 11.0, and 22.5 ng/L, respectively. For personal exposure, multiple regression models explained up to 67% (PM2.5) and 61% (benzene) of variability, with major contribution from commuting mode and environmental exposure. For biological monitoring, multiple regression analysis explained up to 74% of urinary benzene, with a major contribution given by creatinine, and secondary contributions by commuting mode, personal exposure to airborne benzene and smoking. CONCLUSIONS: Personal exposure to air pollutants was lower than that measured in the past in Milan. Personal exposure was mainly driven by traffic variables, while internal dose was mainly driven by personal characteristics and smoking habit.
BACKGROUND:Human exposure to air pollutants, and specifically to particulate matter (PM) and volatile organic compounds (VOCs), may pose a relevant risk on human health. AIM: To evaluate the personal exposure of adults living and working in Milan (Italy) by environmental and biological monitoring. METHODS: Personal exposure of 51 volunteer adults to PM2.5, PM2.5-10 and selected VOCs, including benzene, toluene, ethylbenzene, o-xylene, m + p-xylene, methyl tert-butyl ether, naphthalene, hexane, cyclohexane, heptane, and limonene was assessed along a 24-h period via personal cascade impactors and radial diffusive samplers. Urine spot samples were collected to investigate the corresponding urinary biomarkers. Time-activity patterns were filled in by participants to explore the performed activities. Multiple regression models were applied to investigate the association between personal exposure, biomarker levels, and tobacco smoke, traffic exposure, commuting mode, cooking activities, and personal characteristics. RESULTS: Median personal exposure to PM2.5, PM2.5-10, benzene, toluene, ethylbenzeneo-xylene, m + p-xylene, methyl tert-butyl ether, naphthalene, hexane, cyclohexane, heptane, and limonene were 36.1, 7.8, 2.3, 7.8, 2.1, 1.8, 4.7, 0.8, 0.3, 1.4, 2.5, 1.6, and 59.9 μg/m3, respectively. Median levels of urinary benzene, toluene, ethylbenzeneo-xylene, m + p-xylene, naphthalene, hexane, and heptane were 78.0, 88.1, 21.5, 15.2, 43.9, 21.0, 11.0, and 22.5 ng/L, respectively. For personal exposure, multiple regression models explained up to 67% (PM2.5) and 61% (benzene) of variability, with major contribution from commuting mode and environmental exposure. For biological monitoring, multiple regression analysis explained up to 74% of urinary benzene, with a major contribution given by creatinine, and secondary contributions by commuting mode, personal exposure to airborne benzene and smoking. CONCLUSIONS: Personal exposure to air pollutants was lower than that measured in the past in Milan. Personal exposure was mainly driven by traffic variables, while internal dose was mainly driven by personal characteristics and smoking habit.