TY - JOUR
T1 - Evaluation of fine particle number concentrations in CMAQ
AU - Park, Sun Kyoung
AU - Marmur, Amit
AU - Kim, Seoung Bum
AU - Tian, Di
AU - Hu, Yongtao
AU - McMurry, Peter H.
AU - Russell, Armistead G.
N1 - Funding Information:
This research was supported by the U.S. Environmental Protection Agency under Agreements RD82897602, RD83107601, and RD83096001.
PY - 2006/11/1
Y1 - 2006/11/1
N2 - The Community Multiscale Air Quality (CMAQ) model is widely used in air quality management and scientific investigation. Numerous studies have been conducted investigating how well CMAQ simulates fine particle mass concentrations, but relatively few studies have addressed how well CMAQ simulates fine particle number distribution. Accurate simulation of particle number concentrations is important because particle number and surface area concentrations may be directly related to human health and visibility. Simulated fine particle number concentrations derived using CMAQ are compared to measurements to identify problems and to improve model performance. Evaluation is done using measured particle number concentrations in Atlanta, Georgia, from 1/1/1999 to 8/31/2000. While homogeneous binary nucleation mechanism used in CMAQ needs to be modified for better prediction of particle number concentrations, there are also other factors that affect the predicted particle level. Assumed particle size of the primary emissions in CMAQ causes number concentrations to be significantly underestimated, while particle density has a small impact. Assuming particle size distributions by three log-normal modes cannot accurately simulate particles with size less than 0.01 μm, particularly during nucleation events. An additional mode that accounts for particles smaller than 0.01 μm can improve the accuracy of the number concentration simulations. Though, the use of the Expectation-Maximization (EM) algorithm to estimate size distribution parameters of measured particles suggests that assumed parameters for the lognormal modes in CMAQ are generally reasonable.
AB - The Community Multiscale Air Quality (CMAQ) model is widely used in air quality management and scientific investigation. Numerous studies have been conducted investigating how well CMAQ simulates fine particle mass concentrations, but relatively few studies have addressed how well CMAQ simulates fine particle number distribution. Accurate simulation of particle number concentrations is important because particle number and surface area concentrations may be directly related to human health and visibility. Simulated fine particle number concentrations derived using CMAQ are compared to measurements to identify problems and to improve model performance. Evaluation is done using measured particle number concentrations in Atlanta, Georgia, from 1/1/1999 to 8/31/2000. While homogeneous binary nucleation mechanism used in CMAQ needs to be modified for better prediction of particle number concentrations, there are also other factors that affect the predicted particle level. Assumed particle size of the primary emissions in CMAQ causes number concentrations to be significantly underestimated, while particle density has a small impact. Assuming particle size distributions by three log-normal modes cannot accurately simulate particles with size less than 0.01 μm, particularly during nucleation events. An additional mode that accounts for particles smaller than 0.01 μm can improve the accuracy of the number concentration simulations. Though, the use of the Expectation-Maximization (EM) algorithm to estimate size distribution parameters of measured particles suggests that assumed parameters for the lognormal modes in CMAQ are generally reasonable.
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U2 - 10.1080/02786820600907353
DO - 10.1080/02786820600907353
M3 - Article
AN - SCOPUS:84862907883
SN - 0278-6826
VL - 40
SP - 985
EP - 996
JO - Aerosol Science and Technology
JF - Aerosol Science and Technology
IS - 11
ER -