Author/Authors :
Julian D. Marshall، نويسنده , , Patrick W. Granvold، نويسنده , , Abigail S. Hoats، نويسنده , , Thomas E. McKone، نويسنده , , Elizabeth Deakin، نويسنده , , William W Nazaroff، نويسنده ,
Abstract :
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 Californiaʹs South Coast Air Basin. Our approach incorporates four main inputs: temporally resolved information about peopleʹs 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 (μg 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.
Keywords :
Geographic Information System (GIS) , Diesel particulate matter , Mobility , Exposure analysis , ozone , environmental justice