|Title||Inhalation intake of ambient air pollution in California's South Coast Air Basin|
|Publication Type||Journal Article|
|Year of Publication||2006|
|Authors||Marshall, Julian D., P. W. Granvold, A. S. Hoats, Thomas E. McKone, E. Deakin, and William W. Nazaroff|
|Keywords||diesel particulate matter, environmental chemistry, exposure & risk group, environmental justice, exposure analysis, exposure and health effects, geographic information system (gis), indoor environment department, mobility, ozone|
Reliable estimates of inhalation intake of air pollution and its distribution among a specified population are important for environmental epidemiology, health risk assessment, urban planning, and environmental policy. We computed distributional characteristics of the inhalation intake of five pollutants for a group of ~25,000 people (~29,000 person-days) living in California's South Coast Air Basin. Our approach incorporates four main inputs: temporally resolved information about people's location (latitude and longitude), microenvironment, and activity level; temporally and spatially explicit model determinations of ambient concentrations; stochastically determined microenvironmental adjustment factors relating the exposure concentration to the ambient concentration; and, age-, gender-, and activity-specific breathing rates. Our study is restricted to pollutants of outdoor origin, i.e. it does not incorporate intake in a microenvironment from direct emissions into that microenvironment. Median estimated inhalation intake rates ( g d-1) are 53 for benzene, 5.1 for 1,3-butadiene, 8.7 10-4 for hexavalent chromium in fine particulate matter (Cr-PM2.5), 30 for diesel fine particulate matter (DPM2.5), and 68 for ozone. For the four primary pollutants studied, estimated median intake rates are higher for non-whites and for individuals in low-income households than for the population as a whole. For ozone, a secondary pollutant, the reverse is true. Accounting for microenvironmental adjustment factors, population mobility, and temporal correlations between pollutant concentrations and breathing rates affects the estimated inhalation intake by 40% on average. The approach presented here could be extended to quantify the impact on intakes and intake distributions of proposed changes in emissions, air quality, and urban infrastructure.