Effects of Moisture Released during Forest Burning on Fog Formation and Implications for Visibility

Achtemeier, Gary L.

doi:10.1175/2007jamc1721.1

Cited by 15 publications

(12 citation statements)

References 26 publications

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“…Achtemeier (2008) modelled LWC from the smoke temperature and moisture measurements in the range from 0.07 to 5.1 g m −3 -up to 17 times larger than LWC found in fogs forming under natural conditions. Depending on the temperature sensor used, the range of LWC found in this study is from 1.24 to 28.19 g m −3 -almost 100 times larger than LWC found in natural fogs.…”

Section: Theoretical Analysis and Discussionmentioning

confidence: 92%

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On the formation and persistence of superfog in woodland smoke

Achtemeier

2009

Meteorological Applications

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Dense fogs, comparable to historical fogs in England, have been implicated in numerous roadway accidents in the southern United States. Many of the fogs have occurred in association with prescribed burning. Direct measurements of superfog (fog reducing visibility to less than 3 m) were taken during burning of forest litter on 22 March 2003. Visibility was measured at 0.1 m implying an extinction coefficient of 39 120 km −1 . The number of condensation nuclei required for fog to produce the observed visibility was about 1% of the number of particles released in wood smoke as reported in the literature. A recursive non-gradient mixing model shows (1) maximum excess liquid water (LWC) released was approximately 7.0 g kg −1 , 23 times the LWC in natural fog, (2) superfog can form at the site of combustion then continue to form as it drifts downwind, and (3) superfog can modify air mass stability near the ground and persist for hours until dispersed by changing wind conditions or by solar heating after sunrise. Published in

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Section: Theoretical Analysis and Discussionmentioning

confidence: 92%

“…Smokes measured by Achtemeier (2006Achtemeier ( , 2008 were not saturated. On 22 March 2003 the measurements were made for forest litter under ambient conditions more favourable for fog formation.…”

Section: Introductionmentioning

confidence: 86%

On the formation and persistence of superfog in woodland smoke

Achtemeier

2009

Meteorological Applications

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“…Smoke from these burns poses a threat-either as a nuisance, visibility, or transportation hazard [4,5], and/or as a health hazard [6]. The hazard can be local and/or regional depending on the number of prescribed burns being conducted on a given day.…”

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 role of rabbit longevity is described in reference to Rule FA1 below. Equations (1), (2), and (3) describe a simple CA model for "rabbits" hopping over a landscape. The relationship to fire spread rate (ROS) is analogous: fire spreads faster in stronger winds-rabbits hop farther in stronger winds; fire spreads faster uphill than downhill-rabbits prefer to hop uphill rather than downhill; fire spreads faster when embers fall farther from the fire line-rabbits jump higher, hence get carried farther by the wind, subject to food (fuel) characteristics.…”

Section: Fire Spread Modelmentioning

confidence: 99%

“…Most of this burning is accomplished during winter and early spring during days considered favorable for burning. Forestry smoke contributes significantly to the budget of particulate matter in the atmosphere and poses a threat-either as a nuisance, visibility, or transportation hazard [2,3], and/or as a health hazard [4]. The hazard can be local and/or regional depending on the area of the region subjected to burning, the amount of fuel burned, and the number of prescribed burns being conducted on a given day.…”

Section: Introductionmentioning

confidence: 99%

Modeling Multiple-Core Updraft Plume Rise for an Aerial Ignition Prescribed Burn by Coupling Daysmoke with a Cellular Automata Fire Model

2012

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Abstract:Smoke plume rise is critically dependent on plume updraft structure. Smoke plumes from landscape burns (forest and agricultural burns) are typically structured into "sub-plumes" or multiple-core updrafts with the number of updraft cores depending on characteristics of the landscape, fire, fuels, and weather. The number of updraft cores determines the efficiency of vertical transport of heat and particulate matter and therefore plume rise. Daysmoke, an empirical-stochastic plume rise model designed for simulating wildland fire plumes, requires updraft core number as an input. In this study, updraft core number was gained via a cellular automata fire model applied to an aerial ignition prescribed burn conducted at Eglin AFB on 6 February 2011. Typically four updraft cores were simulated in agreement with a photo-image of the plume showing three/four distinct sub-plumes. Other Daysmoke input variables were calculated including maximum initial updraft core diameter, updraft core vertical velocity, and relative emissions production. Daysmoke simulated a vertical tower that mushroomed 1,000 m above the mixing height. Plume rise was validated by ceilometer. Simulations with two temperature profiles found 89-93 percent of the PM 2.5 released during the flaming phase was transported into the free atmosphere above the mixing layer. The minimal ground-level smoke concentrations were verified by a small network of particulate samplers. Implications of these results for inclusion of wildland fire smoke in air quality models are discussed.

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Effects of Moisture Released during Forest Burning on Fog Formation and Implications for Visibility

Cited by 15 publications

References 26 publications

On the formation and persistence of superfog in woodland smoke

On the formation and persistence of superfog in woodland smoke

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

Modeling Multiple-Core Updraft Plume Rise for an Aerial Ignition Prescribed Burn by Coupling Daysmoke with a Cellular Automata Fire Model

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