Response of Atmospheric Particulate Matter to Changes in Precursor Emissions: A Comparison of Three Air Quality Models

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• 作者：Betty K. Pun ; Christian Seigneur ; Elizabeth M. Bailey ; Larry L. Gautney ; Sharon G. Douglas ; Jay L. Haney ; Naresh Kumar
• 刊名：Environmental Science & Technology
• 出版年：2008
• 出版时间：February 1, 2008
• 年：2008
• 卷：42
• 期：3
• 页码：831 - 837
• 全文大小：1620K
• 年卷期：v.42,no.3(February 1, 2008)
• ISSN：1520-5851

文摘

Three mathematical models of air quality (CMAQ, CMAQ-MADRID, and REMSAD) are applied to simulate the response of atmospheric fine particulate matter (PM_2.5) concentrations to reductions in the emissions of gaseous precursors for a 10 day period of the July 1999 Southern Oxidants Study (SOS) in Nashville. The models are shown to predict similar directions of the changes in PM_2.5 mass and component (sulfate, nitrate, ammonium, and organic compounds) concentrations in response to changes in emissions of sulfur dioxide (SO₂), nitrogen oxides (NO_x), and volatile organic compounds (VOC), except for the effect of SO₂ reduction on nitrate and the effect of VOC reduction on PM_2.5 mass. Furthermore, in many cases where the directional changes are consistent, the magnitude of the changes are significantly different among models. Examples are the effects of SO₂ and NO_x reductions on nitrate and PM_2.5 mass and the effects of VOC reduction on organic compounds, sulfate and nitrate. The spatial resolution significantly influences the results in some cases. Operational model performance for a PM_2.5 component appears to provide some useful indication on the reliability of the relative response factors (RRFs) for a change in emissions of a direct precursor, as well as for a change in emissions of a compound that affects this component in an indirect manner, such as via oxidant formation. However, these results need to be confirmed for other conditions and caution is still needed when applying air quality models for the design of emission control strategies. It is advisable to use more than one air quality model (or more than one configuration of a single air quality model) to span the full range of plausible scientific representations of atmospheric processes when investigating future air quality scenarios.