An accurate, economical and comparatively easy-to-use method for estimating traffic-related air pollution has been developed in Connecticut by a team of researchers from the Yale School of Public Health.
Epidemiologists routinely measure air quality in and around residential areas to determine how pollution levels from automobiles and other sources affect the health of people and contribute to conditions such as childhood asthma. But existing methods have drawbacks that limit their effectiveness.
The exposure model was devised by the Yale Center for Perinatal, Pediatric and Environmental Epidemiology and avoids the need for more expensive monitoring efforts. It also relies on readily available public information—such as census numbers, land-use records and traffic data—as the basis for a model that predicts residential nitrogen dioxide (NO2) levels. These statistics and other land-use data, elevation readings, wind speed and population density are all applied to a mathematical model that provides a final reading of NO2 concentrations.
“By using detailed spatial data that on some of the major sources of air pollution and factors affecting their dispersion we are able to estimate levels of environmental exposure at a site,” said Theodore R. Holford, the Susan Dwight Bliss Professor of Public Health in Biostatistics and one of the paper’s authors. “Our approach provides a cost-effective way of measuring exposure that can be used in environmental epidemiology. In addition, it provides a way of understanding the distribution of exposure, which can be important for developing public health policy.”
The research team tested and refined the model at 985 Connecticut residences from 2006 to 2009. The environmental and population variables were determined for each of the test sites and NO2 samples were collected using small air samplers placed outside the back door of each home and left in place for a month. A total of 3,140 samples were used to develop the model. Details of the research are published in the December issue of the journal Atmospheric Environment.
The researchers said that the model suggests that approximately 67 percent of the variation in NO2 levels can be explained by traffic volume and types of land use within two kilometers of a residence. Population density, the time of year and a home’s elevation are also factors.
The team’s model can be recalibrated and easily applied to residential locations in other states and, potentially, to other countries.
The team recently received funding from the National Children’s Study and hopes to work with investigators in other states to calibrate the model for use at their sites. In addition, they are studying the use of this approach for other traffic pollutants, such as elemental carbon.
Current scientific evidence links short-term NO2 exposures with a number of adverse effects, including airway inflammation in people who are healthy and increased respiratory symptoms in people with asthma. Also, nitrogen dioxide is a precursor to several other forms of air pollution, including ozone and nitric acid. In addition, studies show a connection between short-term exposure to elevated NO2 concentrations, and increased visits to emergency departments and hospital admissions for respiratory ailments, especially asthma, according the U.S. Environmental Protection Agency.
The principal author on the project was Katherine J. Skene, who earned her M.P.H. at Yale in 2009 and is now a Ph.D. student at the School of Public Health. Other authors on the paper include Brian P. Leaderer, deputy dean and the Susan Dwight Bliss Professor of Epidemiology in Environmental Health, Janneane F. Gent and Kathleen Belanger, both research scientists, and programmer/analyst Lisa A. McKay.