Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains: Part II. Fine Particulate Matter and Visibility

Boylan, James W.; Odman, M. Talat; Wilkinson, James G.; Russell, Armistead G.

doi:10.1080/10473289.2006.10464431

Cited by 32 publications

(14 citation statements)

References 13 publications

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“…CMAQ was also used to investigate aerosol formation and transport in the Pacific Northwest during July 1-16, 19961-16, (O'Neill et al 2006. The mean fractional bias and error of PM 2.5 mass were within 30% and 50%, respectively, and those of PM 2.5 species concentrations were within the acceptable bound (Boylan et al 2006). Further, effects of spatial variability on CMAQ evaluation found that the uncertainties due to the different spatial scales between the point-observations and volume-averaged simulated concentrations did not significantly affect model errors .…”

mentioning

confidence: 72%

Evaluation of Fine Particle Number Concentrations in CMAQ

Park

Marmur

Kim

et al. 2006

Aerosol Science and Technology

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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 lognormal 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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confidence: 72%

Evaluation of Fine Particle Number Concentrations in CMAQ

Park

Marmur

Kim

et al. 2006

Aerosol Science and Technology

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“…Historical (24). Detailed information on the modeling system and performance can be found elsewhere (20).…”

Section: Methodsmentioning

confidence: 99%

Air Quality Impacts from Prescribed Forest Fires under Different Management Practices

Tian

Wang

Bergin

et al. 2008

Environ. Sci. Technol.

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Large amounts of air pollutants are emitted during prescribed forest fires. Such emissions and corresponding air quality impacts can be modulated by different forest management practices. The impacts of changing burning seasons and frequencies and of controlling emissions during smoldering on regional air quality in Georgia are quantified using source-oriented air quality modeling, with modified emissions from prescribed fires reflecting effects of each practice. Equivalent fires in the spring and winter are found to have a greater impact on PM 2.5 than those in summer, though ozone impacts are larger from spring and summer fires. If prescribed fires are less frequent, more biofuel is burnt in each fire, leading to larger emissions and air quality impacts per fire. For example, emissions from a fire with a 5-year fire return interval (FRI) are 72% larger than those from a fire of the same acreage with a 2-year FRI. However, corresponding long-term regional impacts are reduced with the longer FRI since the annual burned area is reduced. Total emissions for fires in Georgia with a 5-year FRI are 32% less than those with a 2-year FRI. Smoldering emissions can lead to approximately 1.0 or 1.9 µg/m 3 of PM 2.5 in the Atlanta PM 2.5 nonattainment area during March 2002.

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“…PM also contributes to impaired atmospheric visibility by scattering and absorbing light (Boylan et al, 2006), issues which are discussed in other article.…”

Section: Air Pollutantsmentioning

confidence: 99%