According to a new study, considering new techniques of air quality testing and simulation is vital to enable policymakers to gain an exact understanding of the way emissions have an impact on air pollution levels.
In a review recently reported in the Journal of the Air & Waste Management Association, the researchers debate that existing air quality modeling systems employed in the United States to carry out simulations that help perceive how pollutants react in the atmosphere must strike a balance between adequate chemical detail and unnecessary speculation to generate accurate results to help enhance air quality.
The new study offers recommendations for ways to create more precise descriptions of atmospheric chemical reactions, and air quality simulations in turn, in the combat to minimize hazardous emissions.
Complex chemical reactions govern the synthesis of air pollution from industrial power plants, fossil fuel emissions, and motor vehicles. Air quality models precisely simulate air pollution by solving sets of equations mathematically explaining the chemical and physical processes that control the course of emissions in the atmosphere.
According to Professor William Stockwell, lead author of the study from the University of Texas at El Paso, to precisely simulate air pollutants, it is necessary to use accurate and updated descriptions of the chemical processes for the varying chemical regimes of the atmosphere and the contaminants of concern that emerge.
Existing methods employed to describe atmospheric chemical reactions were compared with more traditional methods. The focus of the comparison was on methods employed in a three-dimensional model that environmental agencies often use to simulate particulate matter, atmospheric acid concentrations, and ozone, as well as to come up with effective emission reduction approaches.
The review reports that during the early development (1970–2000) of methods for describing atmospheric chemical reactions, chemical reactions were added to the mathematical description one by one, where laboratory testing with an environmental chamber follows each one. Then, the simulations were compared with the results.
We consider this to be a ‘bottom-up’ approach.
William Stockwell, Study Lead Author and Professor, University of Texas at El Paso
By contrast, the existing methods for describing atmospheric reactions are termed as a “top-down” approach, where extremely complex mathematical descriptions of chemical reactions are first created before testing, which are then simplified later for use in an air quality model.
The researchers were not only concerned and surprised to discover that the top-down approach has largely been supported to exclude the “bottom-up” approach, to update the descriptions of the chemistry employed for modeling the air quality.
Stockwell claims that if the mathematical description of the chemistry is started to be developed with a huge number of reactions not tested well in the lab, this could add a needless amount of uncertainty to the description of the chemistry in the model. He added that this may, in turn, affect the effectiveness of a model in simulating air pollution.
Rather, the scientists propose that air quality models would be more precise if the atmospheric chemical reaction descriptions were created by combining bottom-up and top-down approaches, that is, by adding one reaction or a cluster of reactions to the mathematical description (bottom-up approach), and then testing against more complicated mathematical descriptions (top-down), with a final simplification for input of air quality model.
They also suggest that it is necessary to pay more attention to alternative approaches to create the sets of equations mathematically describing the chemical processes for air quality modeling, for example, using informatics and air quality modeling systems that better define the uncertainty in the simulations.