Assessing Meteorological Variable and Process Relationships to Modeled PM2.5 Ammonium Nitrate and Ammonium Sulfate in the Central United States

Abstract

Abstract Many counties are required to submit an emissions control plan to the U.S. Environmental Protection Agency to reduce concentrations of particulate matter of less than 2.5 μm in diameter (PM2.5), which are dominated by ammonium sulfate and ammonium nitrate in the central United States. These control scenarios are simulated with photochemical models, which use emissions and meteorological variables to simulate PM2.5 formation, transport, and deposition. A monitor study was established in the central United States to measure simultaneously the PM2.5 sulfate ion, nitrate ion, ammonium ion, and chemical precursor species sulfur dioxide, nitric acid, and ammonia during 2004. These data, combined with nearby meteorological observations, provide an opportunity to assess whether meteorological variables or deposition processes may introduce systematic biases in PM2.5 ammonium sulfate and ammonium nitrate predictions. Skill in estimating total wet deposition is assessed by comparing model output with National Atmospheric Deposition Program monitors in the region. Meteorological variables that are important for mass transport (wind vector) and thermodynamic chemistry (temperature and relative humidity) compare well to observations. A model sensitivity, in which the temperatures in the inorganic chemistry module are adjusted to compensate for an underprediction bias, shows a minimal model response in predicted PM2.5 ammonium nitrate. The dry deposition of sulfur dioxide seems to have a systematic impact on ambient estimates of sulfur dioxide in the photochemical model. An attempt to correlate bias and error in meteorological variables to bias and error in PM2.5 species showed the most relationship between relative humidity and temperature and ammonium nitraite. Wet deposition of total sulfate, nitrate, and ammonium tend to be underpredicted in the winter months.