Bonyoung Koo

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States.

Abstract Version 4.10s of the comprehensive air‐quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5–10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two‐section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36‐km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.

Source Apportionment of the Anthropogenic Increment to Ozone, Formaldehyde, and Nitrogen Dioxide by the Path-Integral Method in a 3D Model.

The anthropogenic increment of a species is the difference in concentration between a base-case simulation with all emissions included and a background simulation without the anthropogenic emissions. The Path-Integral Method (PIM) is a new technique that can determine the contributions of individual anthropogenic sources to this increment. The PIM was applied to a simulation of O3 formation in July 2030 in the U.S., using the Comprehensive Air Quality Model with Extensions and assuming advanced controls on light-duty vehicles (LDVs) and other sources. The PIM determines the source contributions by integrating first-order sensitivity coefficients over a range of emissions, a path, from the background case to the base case. There are many potential paths, with each representing a specific emission-control strategy leading to zero anthropogenic emissions, i.e., controlling all sources together versus controlling some source(s) preferentially are different paths. Three paths were considered, and the O3, formaldehyde, and NO2 anthropogenic increments were apportioned to five source categories. At rural and urban sites in the eastern U.S. and for all three paths, point sources typically have the largest contribution to the O3 and NO2 anthropogenic increments, and either LDVs or area sources, the smallest. Results for formaldehyde are more complex.

Constraining ozone‐precursor responsiveness using ambient measurements

This study develops probabilistic estimates of ozone (O3) sensitivities to precursor emissions by incorporating uncertainties in photochemical modeling and evaluating model performance based on ground-level observations of O3 and oxides of nitrogen (NOx). Uncertainties in model formulations and input parameters are jointly considered to identify factors that strongly influence O3 concentrations and sensitivities in the Dallas-Fort Worth region in Texas. Weightings based on a Bayesian inference technique and screenings based on model performance and statistical tests of significance are used to generate probabilistic representation of O3 response to emissions and model input parameters. Adjusted (observation-constrained) results favor simulations using the sixth version of the carbon bond chemical mechanism (CB6) and scaled-up emissions of NOx, dampening the overall sensitivity of O3 to NOx and increasing the sensitivity of O3 to volatile organic compounds in the study region. This approach of using observations to adjust and constrain model simulations can provide probabilistic representations of pollutant responsiveness to emission controls that complement the results obtained from deterministic air-quality modeling.

An Improved Volatility Basis Set for Modeling Organic Aerosol in Both CAMx and CMAQ

Atmospheric organic aerosol (OA) is highly complex and detailed mechanistic descriptions include hundreds or thousands of compounds and are impractical for use in photochemical grid models (PGMs). Therefore, PGMs adopt simplified OA modules where organic compounds with similar properties and/or origin are lumped together. The first generation volatility basis set (VBS) module grouped OA compounds by volatility and provided a unified framework for gas-aerosol partitioning of both primary and secondary OA and their chemical aging. However, a VBS approach with one dimension of variation (volatility) is unable to describe observed variations in OA oxidation state (i.e., O:C ratio) at a fixed volatility level. A two-dimensional VBS approach was introduced that tracks degree of oxidation in addition to volatility but further study is needed to fully parameterize 2-D VBS modules.