Effect of geocoding errors on traffic-related air pollutant exposure and concentration estimates

Exposure to traffic-related air pollutants is highest very near roads, and thus exposure estimates are sensitive to positional errors. This study evaluates positional and PM(2.5) concentration errors that result from the use of automated geocoding methods and from linearized approximations of roads in link-based emission inventories. Two automated geocoders (Bing Map and ArcGIS) along with handheld GPS instruments were used to geocode 160 home locations of children enrolled in an air pollution study investigating effects of traffic-related pollutants in Detroit, Michigan. The average and maximum positional errors using the automated geocoders were 35 and 196 m, respectively. Comparing road edge and road centerline, differences in house-to-highway distances averaged 23 m and reached 82 m. These differences were attributable to road curvature, road width and the presence of ramps, factors that should be considered in proximity measures used either directly as an exposure metric or as inputs to dispersion or other models. Effects of positional errors for the 160 homes on PM(2.5) concentrations resulting from traffic-related emissions were predicted using a detailed road network and the RLINE dispersion model. Concentration errors averaged only 9%, but maximum errors reached 54% for annual averages and 87% for maximum 24-h averages. Whereas most geocoding errors appear modest in magnitude, 5% to 20% of residences are expected to have positional errors exceeding 100 m. Such errors can substantially alter exposure estimates near roads because of the dramatic spatial gradients of traffic-related pollutant concentrations. To ensure the accuracy of exposure estimates for traffic-related air pollutants, especially near roads, confirmation of geocoordinates is recommended

Geospatial relationships of air pollution and acute asthma events across the Detroit–Windsor international border: Study design and preliminary results

The Geospatial Determinants of Health Outcomes Consortium (GeoDHOC) study investigated ambient air quality across the international border between Detroit, Michigan, USA and Windsor, Ontario, Canada and its association with acute asthma events in 5- to 89-year-old residents of these cities. NO2, SO2, and volatile organic compounds (VOCs) were measured at 100 sites, and particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) at 50 sites during two 2-week sampling periods in 2008 and 2009. Acute asthma event rates across neighborhoods in each city were calculated using emergency room visits and hospitalizations and standardized to the overall age and gender distribution of the population in the two cities combined. Results demonstrate that intra-urban air quality variations are related to adverse respiratory events in both cities. Annual 2008 asthma rates exhibited statistically significant positive correlations with total VOCs and total benzene, toluene, ethylbenzene and xylene (BTEX) at 5-digit zip code scale spatial resolution in Detroit. In Windsor, NO2, VOCs, and PM10 concentrations correlated positively with 2008 asthma rates at a similar 3-digit postal forward sortation area scale. The study is limited by its coarse temporal resolution (comparing relatively short term air quality measurements to annual asthma health data) and interpretation of findings is complicated by contrasts in population demographics and health-care delivery systems in Detroit and Windsor