Photo credit: Diliff, via Wikipedia Commons
Reducing air pollution is vital for the protection of public health. Short-term effects of polluted air include, interfering with being able to breathe deeply during exercising and impairing visibility from haze. Long-term effects for individuals may be a lifetime burden of reduced lung function because they don’t fully develop due to pollution exposure during childhood. Air pollution has also been linked to premature death from heath attacks.
Robert Harley, professor in the Department of Civil and Environmental Engineering at the University of California, Berkley, spoke about a model use to understand the emissions and atmospheric formation processes for formaldehyde pollutants at the SOCAAR Seminar on March 28th.
Canada and the United States have established standards and routine monitoring and for measuring pollutants like PM2.5, ozone, nitrogen dioxide, and sulfur dioxide. But other types of pollutants like, formaldehyde, requires a risk-based management approach.
Research has shown that long-term exposure to formaldehyde results in an increase risk of cancer ranges from hundreds to thousands of cancer cases per year in the United States. While formaldehyde pollutants come from gas and diesel emissions, they’re also formed in secondary reactions in the atmospheres from natural precursors. There’s why Harley used the adjoint of an atmospheric chemistry and transport model to identify, quantify, and rank sources and processes responsible for formaldehyde pollutants. Formaldehyde is a pollutant that’s highly reactive and forming where emissions is not proportionally linked to concentration. A model that’s based on a linear assumption between emissions and concentrations is invalid.
The adjoint approach allows for better understanding of when, where and which species are relevant for formaldehyde emissions. Harley’s model tracked 72 reactive species and 211 reactions. It was observed that formaldehyde has both primary and secondary sources, from direct emissions and in-situ formation, respectively. Seasonal variations were also observed. In the summer time, formaldehyde emissions came from a balance between primary and other sources and were variable from site to site. The winter time, primary sources dominated formaldehyde emissions.
Harley’s model improves the understanding of where relevant formaldehyde emissions are coming from (i.e. local, regional or long-range transport). This will help researchers identify appropriately targeted solutions in the future.