Evaluation of the reactive and optics model of emissions (ROME)

The reactive and optics model of emissions (ROME) is a reactive plume visibility model that simulates the potential atmospheric impacts of stack emissions. We present here an evaluation of the ability of ROME to simulate several plume physical and chemical variables, using an experimental data base that consists of a total of 40 case studies from four field programs. The evaluation variables include plume height, horizontal width, NO, and SO, maximum concentrations, NO2/NOx concentration ratio at the plume centerline, and plume-to-sky radiance ratios. Three algorithms used to simulate plume dispersion in ROME were compared: (1) the empirical Pasquill-Gifford-Turner (PGT) scheme, (2) a first-order closure (FOC) algorithm and (3) a second-order closure (SOC) algorithm that simulates the instantaneous plume dimensions. The plume height results show a correlation of 0.82 between simulated and measured values and a gross error that is 13% of the mean measured value. For plume horizontal dispersion, the second-order closure algorithm produces a moderate correlation (0.54) and a small bias (5% of the mean measured value) in comparison with the field data. Although the PGT scheme also demonstrates moderate correlation with the measurements, it produces a negative bias by significantly underestimating plume horizontal dispersion. The first-order closure algorithm overestimates plume width and shows the least correlation (with the measurements) of the three dispersion algorithms. For the NYSEG data set where coordinated measurements of stack emissions, meteorology at plume height and plume characteristics were available, the SOC algorithm provides better correlations for NOx concentrations, NO2/NOx ratios and plume visibility than the FOC and PGT algorithms. For plume visibility, the SOC algorithm shows a correlation of 0.96 at 405 nm, the wavelength where the plume was visible, and it simulates no visible plume at the other wavelengths (550 and 700 nm). A comparison of ROME simulations with those of the plume visibility model PLUVUE II shows that ROME, with the SOC algorithm, performs better for all variables. (C) 1998 Elsevier Science Ltd. All rights reserved.