Important parameters for smoke plume rise simulation with Daysmoke

Liu, Yongqiang; Achtemeier, Gary L.; Goodrick, Scott L.; Jackson, W. A.

doi:10.5094/apr.2010.032

Cited by 32 publications

(26 citation statements)

References 12 publications

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“…A more sophisticated approach is taken by the 1-D plumerise models, such as the BUOYANT (Martin et al, 1997), BUO-FMI (Nikmo et al, 1999), FIREPLUME (Brown et al, 1997;Brown, 1997), model of Freitas et al (2007), DAYSMOKE (Liu et al, 2010), and others. These systems still assume the horizontal symmetry of the plume and use the formulations integrated across it.…”

Section: Existing Plume-rise Formulationsmentioning

confidence: 99%

Evaluation of the smoke-injection height from wild-land fires using remote-sensing data

2012

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Abstract.A new methodology for the estimation of smokeinjection height from wild-land fires is proposed and evaluated. It is demonstrated that the approaches developed for estimating the plume rise from stacks, such as the formulas of G. Briggs, can be formally written in terms characterising the wild-land fires: fire energy, size and temperature. However, these semi-empirical methods still perform quite poorly because the physical processes controlling the uplift of the wildfire plumes differ from those controlling the plume rise from stacks. The proposed new methodology considers wildfire plumes in a way similar to Convective Available Potential Energy (CAPE) computations. The new formulations are applied to a dataset collected within the MISR Plume Height Project for about 2000 fire plumes in North America and Siberia. The estimates of the new method are compared with remote-sensing observations of the plume top by the MISR instrument, with two versions of the Briggs' plume-rise formulas, with the 1-D plume-rise model BUOYANT, and with the prescribed plume-top position (the approach widely used in dispersion modelling). The new method has performed significantly better than all these approaches. For two-thirds of the cases, its predictions deviated from the MISR observations by less than 500 m, which is the uncertainty of the observations themselves. It is shown that the fraction of "good" predictions is much higher (>80 %) for the plumes reaching the free troposphere.

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Section: Existing Plume-rise Formulationsmentioning

confidence: 99%

Evaluation of the smoke-injection height from wild-land fires using remote-sensing data

2012

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“…Details of the FAST analysis for a prescribed burn can be found in [10]. FAST results are shown in Figure 5.…”

Section: Fast Analysismentioning

confidence: 99%

“…Forestry smoke in the southern United States contributes significantly to the budget of particulate matter in the atmosphere and efforts have been undertaken to include the smoke in regional air quality models [8][9][10][11][12]. Recent studies suggest that prescribed burning alone may be contributing up to 30% of the annual PM 2.5 mass in the Southeastern United States [13] and may be the leading cause of high PM 2.5 episodes in the region [14].…”

Section: Introductionmentioning

confidence: 99%

Modeling Smoke Plume-Rise and Dispersion from Southern United States Prescribed Burns with Daysmoke

et al. 2011

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Abstract:We present Daysmoke, an empirical-statistical plume rise and dispersion model for simulating smoke from prescribed burns. Prescribed fires are characterized by complex plume structure including multiple-core updrafts which makes modeling with simple plume models difficult. Daysmoke accounts for plume structure in a three-dimensional veering/sheering atmospheric environment, multiple-core updrafts, and detrainment of particulate matter. The number of empirical coefficients appearing in the model theory is reduced through a sensitivity analysis with the Fourier Amplitude Sensitivity Test (FAST). Daysmoke simulations for "bent-over" plumes compare closely with Briggs theory although the two-thirds law is not explicit in Daysmoke. However, the solutions for the "highly-tilted" plume characterized by weak buoyancy, low initial vertical velocity, and large initial plume diameter depart considerably from Briggs theory. Results from a study of weak plumes from prescribed burns at Fort Benning GA showed simulated ground-level PM 2.5 comparing favorably with observations taken within the first eight kilometers of eleven prescribed burns. Daysmoke placed plume tops near the lower end of the range of observed plume tops for six prescribed burns. Daysmoke provides the levels and amounts of smoke injected into regional scale air quality models. Results from CMAQ with and without an adaptive grid are presented. OPEN ACCESSAtmosphere 2011, 2 359

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“…The convective heat release can also be unevenly distributed across the landscape (e.g. Liu et al, 2010;Achtemeier et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Applicability of an integrated plume rise model for the dispersion from wild-land fires

et al. 2014

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Abstract.We have presented an overview of a mathematical model, BUOYANT, that was originally designed for the evaluation of the dispersion of buoyant plumes originated from major warehouse fires. The model addresses the variations of the cross-plume integrated properties of a buoyant plume in the presence of a vertically varying atmosphere. The model also includes a treatment for a rising buoyant plume interacting with an inversion layer. We have compared the model predictions with the data of two prescribed wild-land fire experiments. For the SCAR-C experiment in Quinault (US) in 1994, the predicted vertical extents of the plume at maximum plume rise were between 500 and 800 m and between 200 and 700 m, using two alternative meteorological data sets. The corresponding observed injection heights of the aerosol particles measured using an airborne lidar (light detection and ranging) ranged from 250 to 600 m. For the prescribed burning experiment in Hyytiälä (Finland) in 2009, the model predictions were compared with plume elevations and diameters, determined based on particulate matter number concentration measurements onboard an aeroplane. However, the agreement between modelled and measured results substantially depends on how the properties of the source term are evaluated, especially regarding the convective heat fluxes from the fire. The results demonstrate that in field experiments on wild-land fires, there are substantial uncertainties in estimating both (i) the source terms for the atmospheric dispersion computations and (ii) the relevant vertical meteorological profiles.

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Important parameters for smoke plume rise simulation with Daysmoke

Cited by 32 publications

References 12 publications

Evaluation of the smoke-injection height from wild-land fires using remote-sensing data

Evaluation of the smoke-injection height from wild-land fires using remote-sensing data

Modeling Smoke Plume-Rise and Dispersion from Southern United States Prescribed Burns with Daysmoke

Applicability of an integrated plume rise model for the dispersion from wild-land fires

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