Program VSMO Users Manua 

Leonidas G. Lavdas 
Contents Abstract ............................................ I 

Introduction ......................................... I 

Getting Started ...................................... 2 

About tkus Manual ................................. 2 

System Requirements ............................... 2 

Getting Help ...................................... 3 

Scientific Basis-Six Major Model Components ........... 6 

Smoke and Heat E~ssions and htial Smoke Distribution . 6 

Plume Rise and Vertical Smoke Distribution ............ 8 

Smoke Concenbrations ............................. 14 

Selecting a Dispersion Model ...................... 14 

Applicability of the VSMOKE Steady-State Gaussian 

Plume Dispersion Model ........................ 18 

Mathematical Basis of the VSMOKE Gaussian 

Plume Model ................................. 20 

VSMOKE Horizontal and Vertical Dispersion 

Coefficients .................................. 29 

Initial Dispersion Coefficients and Vlrtual Distances 

in VSMOKE ................................. 31 

Stability Class Determination in VSMOKE .......... 31 

VSMOKE Smoke Receptors ...................... 33 

Expected Accuracy of VSMOKE Concentration 

Estimates .................................... 37 

Crossplume Sightline Characteristics ................. 40 ' 

The VSMOKE Crossplume Sightline Characteristics 

Model ...................................... 40 

Sightline Modeling Concerns ...................... 45 

Dispersion Index ................................. 46 

Low Visibility Occurrence ksk Index ................ 50 

Installkg VSMOKE ................................. 53 

Installing ........................................ 53 

Testing ......................................... 53 

Test Prwedmes ................................... 53 

VSMOKE Program Charactenstics ..................... 56 

Program Files .................................... 56 

Source Cde-Characteristics and Stsuc~e ........... 57 

Visual Overview ................................ 58 

Subprogram Descriptions ......................... 58 

Source Code Revision .............................. 72 
VSMOm Input Req&emc=nts ...................... 73 

Input Overviw ................................. 74 

Input Variables ................................. 75 

VSMOM Outpul ................................ 82 

Output Overvim ............................... 82 

Interpretation .................................. 85 

Error Handlhg .................................. 85 

............................ 86 

Acknowledgments ................................... 89 

Litmame Cited ..................................... 90 

Appendix I-Input Hints .............................. 93 

Appendix 11-Input Examples ......................... 103 

Appendix 111-Ek-by-Eke Layout of VSMOm 

Output File. VSMOKE.OUT ....................... If1 

Appendix N-Index of Output Data ................... 122 

List of Figures ..................................... 139 

Tables ........................................... 140 

Index ............................................ 145 
Introduction 

This is a users mmud for VSMOm, a eompukr progm for predicting the smolce and dry weather 

visibaty hpzt of a single prescriw fm at severd downwind lwations. VSklOm is a 

F"IORTRA;".I 77 program that depends on the input in fik: VSEVI0E.m to generate output in file 

VSMOm,OUT, VSMOE is based on steady-state Gaussian plum mcldeting phciples 

compatible with those used by the U.S. Envkonmentat Protectim Agency. VSMOm is uniquely 

tailored as a plume model for a lcrtv to mderate htensiq pound fire as an emissions source. 

Keywords: Computer mdels, presc~M f~e, smoke, visibav, VSMOE. 

Fog, smoke from forest burning, or a combination of both can reduce visibility. 

Low visibility can increase the hazasds of road travel. Land managers must be 

able to assess the risk of a prescribed fire reducing visibility and increasing 

driving haz~ds. Two numerical indexes, the Dispersion Index (Lavdas 1986) and 

the hw Visibility Occunence Risk hdex (Lavdas and Hauck 199 1) were 

developed to help managers make this assessment. 

These indexes represent only part of VSMOB, a FBRTRM 77 computer 

program designed as an atmospheric dispersion model that estimates the effects of 

a prescribed forestry burn on air quality and visibility. Also usdul for evaluating 

similar emission sources, such as ag~cultural bums and wildfires, this dispersion 

model is a modularly designed algorith, from both an internal and external 

perspective. Gotnponents within VSMOKE are relatively easy to isolate, and the 

program can become a component within a more extensive family of programs, 

For example, VSMOm fits into a ly of programs when input data are 

derived from the results of computefized fire and emissions models and output 

data are used in post-processor programs, such as graphical display systems. 

VSMOE will help those responsible for forestry-prescribed burning assess the 

hazards associated with smoke, especially roadway hazards. As a "stand alone" 

program, VSMOm and this manual are designed to be used primily by air 

quality specialists with background in atmospheric dispersion modeling, This 

user group will be particularly intwsted in the techical development and overall 

pedomance of the model. Although the FORT list-directed input fomat 

should presmt ~nimal difficulty for these users, even the: most experienced 

should review the inputfoutput sections, paying close attention to unique input 

and output features, 

The structure and fomat of VSMOE and its associated inpulloutput files allow 

for development of pre- and post-processor programs to interface with other 

users, including those directly responsible for presrribed forest fires, A few 

sections in this manual are designed to help computer progra 

analysts develop these intedaces. As these specialists become more fafililiar with 

VSPCIOm, they will be able to provide fire managers with infomation pertinent 

to evaluating the visibility risks associated with a prescribed burn. 
Getting Started 

About this Mranual 

System Requirements 

a1 has been &vided into eight major sations to enmurage and 

facilitate user review. 

Getting Started da~bes topic mmgement, system req~ements, and help 

avdabifity . 

Overview provides essential backgound infomation. 

* Six Major Model Components thoroughly review the scientific basis of 

VSMOm. 

Installing VSMOm discussm how to obtain, install, and test the program, 

VSMOm Program Charact&stics presents general progradng infomtion, 

specifk input insh-uctions, and output organization and appfication. 

4 Literature Cited lists adational reference materials. 

Index provides quick amss to specific topics. 

Appendixes present input examples, output layout, and an output data index. 

VSMOm is written in the FORTRAN 77 progreng language and fully 

conforms to the standards of the American National Standards Institute (ANSI) 

X3.9.1978 (full language). (See ANSI 1978). VSMOKE was developed and 

tested on both the USDA Forest Service Data General MV4000 computer system, 

under IS-CLI, AOSNS F77 FORTRAN 77, Revision 04.02 Data General (DG); 

and on an 80386 IBM-compatible personal computer (PC), under MS-DOS, 

Version 5.0, using Microsoft FORTRAN, Version 5.0, and invoking the 80387 

math co-processor (PC). This release of VSMOE is supported on the PCmpatible envkoment only; however, its development on the Data General helps 

ensure that the program will work on a wide variety of systems. The near 

u~versality of the FORT language and the program's use of standard syntax 

also assure wide applicability. 

In the PC enviroment, version 19950128 of the VSMOm source code takes up 

246,909 bytes; the object code (compiled using the PC "4Yb" option) is contained 

in 3 segments of 6,373,73,486, and 69,459 bytes; and the exmutable code takes 

155,138 bytes. At least 3 Megabytes (MB) of storage should be available to hold 

the VSn/lOKE source, object, and ex-able code, while allowing some room for a 

modest library of input and output files. More extensive libraries will require 

additional space. Mlwating a directory for housing VSMOE and its associated 

is advised. 

VSMOm execution times were rapid in the tested environments. Program 

sing times averaged less than 1 second per analyzed period when crossplume 
Getting Help 

Overview 

sightline estimates were not calculated, and averaged about 3 seconds per period 

when sightline eshates were included. In the 80386 PC envkoment, a 

mathematical eo-processor (80387) is needed to attain rapid execution times. Such 

co-prmssors are integral to more recent PC systems such as the 486. The coprmssor is also requird to maktaFn program accuraq. 

The exact procedures for setting up and dg FORTRAN 77 programs will vary 

considerably among host system envkoments. Host system envkoment refers to 

the computer hardware and sohare systems that include the operating system, 

Foman compiler, lmker, libraries, mathematical co-processor, and other specifics 

involving the executable code, including its interaction with input and files--some 

of which cannot be directly specified by the Foman source code. These 

complexities prevent prediction of the exact behavior of VSMOKE wih an 

untested enviroment. Fortunately, both the hghly transportable nature of the 

FORTRAN 77 progreng language and VSMOKE's adherence to the ANSI 

Standard for the language meze the uniformity of the behavior of VSMOKE in 

a variety of computational envkoments. Thus, necessary adaptations to non-PC 

environments should be minimal. 

Users should be familiar with the behavior of FORTRAN 77 programs on the host 

system before setting up and g VSMOm. Users wanting more details on 

implementing VSMOm as a computer program than this manual provides should 

consult the FORTRAN 77 computer code. The code is accompanied by numerous 

comments that explain the mathematical and scientific aspects of the program, 

program structure, input/output procedures, etc. 

VSMOKE is primarily a tool for analyzing the effects of a single prescribed fire. 

Using an emissions source geomeehcally codgured to match that presented to the 

atmosphere by a prescribed fire, the program estimates smoke concentrations and 

crossplume sightline chaacteristics at specified downwind distances from the fire. 

Current scientific knowledge and data acquisition of the operational enviroment 

limit the applicability of VSMOKE sightline estimates to relative hwnidities less 

than 70 percent. VSMOME also caldates two indexes that further support the 

single fire analysis by providing a context for evaluating smoke from multiple fire 

activiq and the risk of smoke-related traftic hazards. These hvz, indexes are also 

applicable in humid conditions when VSMOm single fm sightline estimates tend 

to be meliable. 

VSMOKE uses a steady-state, period-by-period, Gaussian plume analysis to 

moke mncenkations and visual characteristics. The periodlows fire characteistics and the amospheric envir0men.t to 

undergo considerable change during the course of a run. As with many U. S. EPA 

(1986, 1987) dispersion models, each period is considered independently. 

VSMOKE stores each period's data for a worst-case s 
VSMOKE is designed to be used either alone or as a component with a system of 

automated prescribed fue management aids (e.g., as part of a batch prop 

job). Scientifically defmable processes ready calculable from available input data 

are represented ~b VSMOKE, However, some modeling cemprmises are 

necessarf. "Best estimates'' are provided when the physics of the problem are 

relatively well mderstood. "Consemative estimates" assume the worst and xe 

provided when the physics are poorly understood or their mathmatical 

representation is too complex or time consdg for rapid execution in an 

operational environment. To help account for uncertainty in current lolowledge, 

flexibly designed input variables allow preliminary or even speculative assessment. 

VSMOKE uses a single input file to obtain all required data. The input format has 

been kept as flexible as possible within the standard FORTRAN 77 programming 

language processing requirements. Extensive error detection procedwes are 

employed on the input data set, with provisions for immediate screen-based 

feedback and more permanent file output when problems arise with any input 

value. 

VSMOKE ou@ut goes primarily to a single file, with auxiliary end-of-pull and 

error messages also output to the screen. The VSMOME output format facilitates 

using automated post-processor programs (such as gaphical display progams) 

while mainlaining a presentable printout appearance. VSMOE output is listed in 

three sections: an "ecb-print" of all data successfully read into the program, a 

period-b-period analysis, and a worst-case s ar=y cmstructed from the periodby-period analysis. 

VSMOm consists of six major computationafly oriented components: 

1. Optional modeling of pollutant constihrents and heat missions, and the initial 

vertical and horizontal distribution of smoke; the user mw input the necessq data 

(perhaps from a forestv fuels emissions model), or use the simple missions model 

contained in VSMOE. 

2. A plme rise model, integrated TiVith tbe input specifications of the proportion of 

smoke subj& to plme rise and the vmical Bisli~bulion to be assimed due to 

plme rlse effects. 

3, A contientianal steady-state Gaussisln plume atmespheric &spersim mdel that 

yields estim&s of smoke cancent&ations at a nmber of bstmces Brrectlg; 

domwuld &om &e fire. 

4. A crosspluw~e sigbtliine characteristics msdel &at yields visibili@ md eonkast 

ratio eshates fsr fie plme at &e sme do~a~kd &stances; hese estimsrtes are 

valid mlg.. if t;k.e dient relalive &t5; is belokv 78 percent. 
6. A statistical model of the observed proportion of low visibility occurrences at 

Florida accident sites, which yields a Low Visibility Occusrence Risk Index 

(LVON). 

These components are intenelated as smoke hazard management aids and, in some 

cases, are closely related mathematically. The i~lterrelationships are s 

the followillg list: 

* Component 1 directly contributes to estimates yielded by components 2 and 3. 

* Component 2 directly contributes to estimates yielded by component 3. 

Component 3 directly contributes to estimates yielded by component 4. 

* Some matkematical association is present betureen output variables from 

components 2,3, and 4 and the indexes yielded by components 5 and 6. 

Component 5 directly contributes to the index yielded by component 6. 

VSMOKE procedures are relatively simple and computationally efPicient. The 

consewative nature of VSMOB estimates allows the model to be used as a 

screening system to point out the pot-Wial for smoke-related hazards. Where 

potential smolie problems are indicaled, more mathematically complete models can 

be run to better describe -tJhe naw of the "hazard. NWF, Version 2 (Petersen 

and Lavdas 1986) is a more complete dispersion model th& considers the effects 

of wind variations in space and time. The PLUVUE H model (Seimeur and others 

1984) provides more complek visibili~ analysis oriented to plumes from 

industrial stacks. These models demand more input requirements and computer 

resources thm VSMOKE, an8 may not adequately represent the geomem of a 

fosesm-prescribed fire smoke sowce. Although F, Version 2 cm 

a~wmmsdate prescribed fire emissions in most respec&, it does not account for 

"gadualf>1ume rise (i.e., rise as the smoke leaves the viciniv of the fire). 

VSMOE is based on weather conditions and smoke-related problems found in tke 

Eastern United States. VSMOME smoke concenrmion and sightline 

characteristics estimates cm be applied cautiously in the West, but the spatial 

variabiliq of windflow over rugged tenain will limit the plume model's 

effeaiveness, VSMOE;;IE BI estirn&s are: based on widely applicable physical 

principles and should be applicable to any location, Tkae WORZ is based on 

slatistics &om Florida and c ot be qplied indiscriminakly to sther locations. 

However, subjective evidence gained from expefience in Eoreesting md 

monitoring LVBN does suggest &at the risk pmem indicated by ae Florida cdah 

can be directly applied to &ose humid asem within a $ew h&ed miles ofthe Gulf 

Coast that are capable of sustaining a forest.' 

Lsersmal ccamunieation, G,W, Rip&"en. 1991. Meteorologist, Georgia Foresty Comission, Macon, GA. 

5 
Scientific ffasi ly, WMOm is an emission model; it is &I meteomlogically 

Six Major Model orienkd mdel that wes idomation from other available models that best 

describe the: emissions and plume behavior of a ground fire. Reseaseh in Components forest fiels, fire behavior, and the: chemise of smoke prdtletisn is reflected 

Smoke and Heat within VSMOKE primarily by its input requirements. Because research has not 

Emissions and In_ltial yet led to ubiquitous emissions models for all hels and burning conditions, a 

Smok Distlribufcion simple emissions calculation procedure has been incorporated within VSMOm as 

a "fall back" option. However, the option to input emissions data on a period-byperiod basis should be wed vvbenever the necessary data are available. VSMOm 

input requirements are based on the Sandberg and Peterson (1 984) Source Strengfu 

model for Coniferous Logging Slash in the Pacific North~est.~ This model yields 

particulate matter, carbon monoxide, and heat emissions estimates on a period-byperiod basis, simulating emissions behavior through the complete life of a fire, 

f?om i@tion to smoldering. Using other emissions models or assumptions is 

acceptable if all VSMOKE input requirements are met. 

If period-by-period emissions data are unavailable, VSMOW uses an extension of 

the method developed by Lavdas (1982) to estimate smoke and heat emission rates 

during the course of a fire. This method was also developed from forestryprescribed burning data in the Pacific Northwest-an analysis of burning activity 

near the Willamette Valley, Oregon and its effects on particulate matter 

concentrations within the valley. Figure 1 shows time dependence of fire 

characteristics assumed in VSMOlCEl. 

FW P-ER ASSUMP?TONS 

Smoke emissions rate Held constant for a given duration, TCONST, then undergoes exponential decay (as specified 

by the decay eomtant, TDECAY) 

Heat emission rate Held comtatlt for a given duration, TI.IOT, not to exceed TCONST, then msmed to be zero. 

Fiwe 1-Time dependence of fire charackristics wsmed in VSltlOm 

vwsion ofthe Somw S&en@ m&i is refemd to as tPle Edssion Produetion Mdel (IEPW. mis model yields pfiod-by-pe~d 

zuticulak mamr in &e 2.5 and 10 &~rom&r s as well B for particulak maer, cmbn monoxide, csbn dioxide, 

md hy&~)(:ertx,ns (Gf%). m&l alw provicies PoM Ireat e&h&s in BW8s mave~ mgawarn 

(mw) kfore &ey m - 1 .055 t * 10" mw). Verslifln 1.02 of EPM 

md WmgngtQn on both si wm~e&ian. 1991,199 rajeet bder, UST)A 

Fo~st Ss:miw9 Pacific Nofiwest Resemch Satioq %atle, WA.) 
Mathematially, the the dependency of smoke and heat emission. rates of the 

built-in VSMOKE model are expressed as follows: 

where 

SNIPEAK = peak smoke emission rate (during to TITRE + 

TCONST interval), 

SMDCAY = smoke e~ssion rate during smoke decay perid, 

AK = heat emission rate (during TFVRE to TFTRE + THOT 

inn tend), 

HRDCAY = heat emission rate thereafter (set to zero), 

TITRE = fire start time in hours as input, 

TCONST = period of constant emissions in hours as input, 

TSM = md shulation the in hours, 

TBGDCY = TFDtE! + TCONST, 

TDECAY = exponential decay coefficient in hours as input, and 

THOT = period of significant convective heat emission in hours as input. 

This technique as applied in VSMOI<E can yield period-by-period smoke 

emissions esthates that tend to follow those given by Sandberg and Peterson 

(1984). The applicability of the tecmque outside the Pacific Northwest has not 

been specifically verified. However, by using user input for the three time 

parameters in a time-dependent modeling context, VSMOKE time-dependent 

emissions estimates may be applied with a degree of confidence comparable to the 

input esthates themselves. 

Other user input data characterize the geometric codpation of the fie as an 

emissions source to the atwsphere. The initial geometriG configuration is defined 

by the following: 

1. Specification of the area of the smoke source (ACRES3). VSMOKE generally 

constructs its emissions source as a Iine at the downwind edge of a square of size 

matching the user input; a zero or negative input value directs the model to 

construct a point as an emissions source. 

names in parentheses correspond to the vatiable nmes discussed in "VSMOm Input," 

7 
2, Specification of any initial Gaussian dispenion of the pollubnb in the 

) and vertical (OZm)3) directions present at the source 

site, Tlhese i~tial coeBcients can be used to characterrize how tuTbufence md flow 

patterns near the fire affect the distribution of nearby smoke on a period-by-period 

lie, he& at a smoldering bm site might be expected to result in 

modest IiRing of some smoke within the site, bul might be too difficult ta calculate 

by using plme rise modeling techniques. Obsewed eEec& of low he& output on 

the vertical smoke distribution at the site can be accounted for by specifying an 

appropriate value for initial vertical dispersion. 

3. Specification of the distribution of smoke afEected by plme rise. This 

specification stron&y affects the initial vertical distribution of pollutanh when 

plume rise occurs. (For additional information, see Plume Rise and Vertical 

Smoke Distribution.) 

Specification (1) and the horizontal portion of specification (2) detemine the 

"initial" horizontal distribution of pollutants, while both the vertical portion of 

specification (2) and specification (3) detemine the "initial" vertical distribution. 

Specification (2) also yields initial Gaussian dispersion coeflicients for the fire at 

the fire site, which are applied to all subsequent model calculatisns. In contrast, 

specification (1) yields m initially horimnblly unifomn dis"ii.ibution along tfie 

complete length of the effective line source. Specification (3) can yield either a 

point somce at the calculated plume rise hi& or a veflically unifomly distdbuted 

source. Specification (3) also determines the proportion of smoke emissions 

affected by plume rise. Any remaining smoke is treated as ground-based 

emissions. These distributions are further acted upon by the transport-related 

dispersion processes in VSMOKE described in Smoke Concentrations. 

Plume Rise and Vertical In VSMOKE, plume rise is the height smoke emissions reach as a result of 

Smoke Dis~buCion convective effects from the fire's heat emissions. Smoke concentrations at ground 

level, especially those close to a fire, are extremely sensitive to plume rise effects. 

In particular, the presence of smoldering smoke sources, which lack the necessary 

heat to generate significmt plume rise, creates a potential for excessive nearby 

&round level concentrations (SFFLP 1976, Lavdas 1978). This ground smoke can 

be a major contributor to traffic accidents (National Wildfire Coordinating Group 

1985). Accordingly, VSMOm uses a pragmatic, concenbation-estimate-bwed9 

bottom-line philosophy with respect to plume rise estimates similar to that 

expressed by Brims (1975) who stated, "I prefer to define plume rise as [the value] 

one would need in the diffusion equation to correctly calculate the maximum 

ground concentration." VSMOKE includes unique descriptor input variables for 

plme rise and plme rise associated effects on the initial vertical distribution of 

smoke. These variables are designed to help the model correctly depict groundlevel concentrations as a function of domwind distanGe fiom a fire. 

VSE/IOm relies on plune rise equations developed for indmtrial stacks to 

detemine the potential height of smoke due to heat emissions (Briggs, 1969, 1972, 

1975). VSMOKE also includes an option for setting the vertical distribution of 
smoke resulting fiQm plrune rise effects. The verlicd distrtbution may be set to 

leave a portion of smoke on the ground to distribute smoke uniformly from the 

ground to the calmlatea plme hei&t? or ba&. 

Pfme rise, as estim&d by Briggs, is a hetion of buclj~ancy flux, atmospheric 

stabifit)., and domw+nd &stance. In VSMOE, buqancy flu, F, is a funetion of 

the .total he& mission r& of the fire, Q,. Q, is the pm&t of the totaf fuel mass 

loss rate FNitfiin ~e fire tims the heat value of the kt. Follo~~g SFFLP (1976), 

the heat value ofthe fuel is 0.01465 1 Joules per gram (or in SFFLP' writs, 3500 

calories per gram). Briggs (1975) developed the following equation4 for buoyancy 

flux: 

where 

F - buoymcy Rux (due to the heat emissions of &e pollulion sowcc) in. 

meters raised to the fob pa seeds raised to tlbe third, 

G - xceler&ion of ga-c.iQ, 

QH = total sensible he& evnission rate, 

6, - specific he& of atnnosphere, 

p - densiv of the atmosphere, and 

T - temperature of the amosphere. 

In VSMOKE, equation (5) is sirmplified by ass 

1. The ideal gas law, i.e., P = pRT, (where P is atmospheric pressure and R is the 

gas constant for dry air). 

2. The diatomic molecule ideal gas assumption that = 2 

G, 7' 

3. Standard atmosphere at sea level values for G and P; 9.80665 ms-' for G and 

101,325 pascals (i.e., 1013.25 mb) for P. 

These assmptions yeld the following app ate equation for F in VSMBKE: 

where 

Q, is expressed in mgmatts. 

Equation 1 1, page 63, of Briggs (7 975). 
proMate plwe rise 

, of the vertid potential 

chmgr: with re;spect to 

@ven on pagm 1 1 - 12.) 

Find plume rise equation for 2 0,001 K m-5 most 

Final plume rise equation for DTHETA 2 0.001 K m-' in very light winds is: 

where, in equations (7) and (8) 

An additional "candidate" final plume rise estimate is evaluated if the atmospheric 

conditions are regarded as stable. This same estimate produces the only 

"candidate" hal plume rise es if the vertical potential temperature gradient, 

DTHETA, is less than 0.001 K m'l, i.e., indicating a neutral or unstable 

atmosphere. The choice of equations to produce this estimate is based on the value 

of the esthted buoyancy flux, F (from equation (6), or more generally, equation 

(5)): 

For F r; 5 1.602 m4 s-~: 

For F > 5 1.602 m4 sm3: 
scheme is us& to sel- the " 

plume ~se, W, (i,e,, the plume rise as the plume mvm 

FS 51.602 m4 s'~, H, = the 

(from quation C7)), Hmw (hm equation 811, or Hms (froan. qmtion (10)). 

2. If DTmTA r: 0.001 K me' F > 5 1.602 mQs", HF = the of Hm 

(from quatjon (7)), H, (from equation (o), or HMs (&om equation (1 1)). 

3, 1Cf DTETA < 0.001 K rnml F 5 1.602 m4 s'~, HF = H, (from equation 

(10)). 

4. ED A < 0.001 K mm" F > 5 1.602 m4 s-$, H, = Hw, (from equation 

(1 111. 

5, An ad&tional restriction on the value of HF is p ardless of the value of 

DTmTA F: W, may not exceed the input v 

Generally, the plume rise used in subsequent model calculations in VSMOm is 

also dlowed to be a hnction of domind distance, That is, the model smoke 

plume usually cgmbs as it is transported donwind until final plume rise is 

att~d. For a strictly kt4 type of VSMOm application, including the effects 

of gadual plume rise with respect to domad distan~e may not be necessary. 

However, for mast operationdl applications of VSM[Om, the gradual plume rise 

optionS compares the final plume rise estimate, HF, to the partial plume rise 

estimate, H,,,, based on the Briggs (19'75) "213 distance dependent law." The 

lower of the two values is applied to subsequent model cdculations for that 

spaific dom*d distance. 

The Briggs "213 distmw dependent law" partial plme rise, W,,, estimate is 

independent of DTmTG i-e., it is used for all atmospheric stabilities. The 

fallowing equation estimates HPART: 

where sepwate es of HpmT are made for each down 

Defdtiam of vdables for plume rise equations (7) through (1 2) &How: 

HF = "'final" plume rise in meten, 

Hm, = "fa" plume rise generally in near neutral or unstable 

wn&tia~s, 
HB = '%finalt"lue rise for most stable conditions, 

Haw = "final" plme rise in sbble, very light wind conditions 

H, = "pmial" plme rise in meters, 

S = a stability pameter in inverse seconds sqwed, 

B erature gradient in degrees Kelvin per meter; in 

is assigned a zro value if the s&bility class is 

mtable, or near neut~al during the day; at night, DTETA is set to 

0.010 for near neutral stability, 0.020 for slight@ stable conditr'ons, 

and 0.035 for moderately or extremely stable conditions (stability 

class, itself, is either defined by input or determined from other input 

data within the model), 

TETA = represenative potential tempterahre in degrees Kelvin (defined by 

input>, 

U, = transport windspeed in meters per second for the period, as used in plume 

rise calculations (not allowed to be less than 0.5 meters per second) (defined 

by input), 

X, = domind distance in kilometers, and 

Am = mixing height in meters (defuned by input). 

Because the Briggs plume rise equations were developed 6or tall stacks, the 

modeling of plume rise from ground fires must be approached cautiously. In tall 

stacks, smoke and heat emissions are directly associaled with each okfier, Mrhile in 

gromd fire, eaensive areaf of smoldering (with hi& smoke emissions but little 

significant heat production) may be well removed lErom actively Baing meas, 

One relevant theoretical question was formulated: "Is direct and complete 

involvement within a single convedion colum observed Eor all smoke generated 

hm all possible geome&ic confipttions of gowd fires?" herous ink"omal 

an$ ha1 obsemtions (SFFLP 1976) yielded a "No" mswer, & lemt for low or 

moderate intensity prescribed fires (or for high intensity fires as they are dying). 

Accurately prediding groruad fire plume rise remains urnemin because estimates 

of plume rise based on stack data may not be applicable and the proportions of 

smoke that ultimately undergo complete, incomplete, or insignificant plume rise are 

The practical smoke management implication of the plwne rise prediction problem 

is that at least a fraction of the smoke from a ground fire may be close enough to 

the ground to result in potentially high ground-level smoke concentrations near the 

ously high smoke concentration values might not be picked up by 

dispersion model estimates unless suitable adjustments are made to the model's 

plume rise equations, dispersion equations, or both. Any dispersion model for a 

gaud fire: wing he sb;lGk plume 17;se equatiom is likely to 

peat1 y mdesestimate rfip Eom gounad level smoke ne~ &e 

s0uI"Ge. 

h the 6rst aBempt to qwntifiabl;); evaluate &is pss"raler%l, Lavdszs (1 9"78) tested tihe 

B~ggs eqradiom against vedical sm~kF: dist~bution daQ obtained gorn three lawintensity test fires by aircraft nephelometer sampling. Fire and amospheric 

parameters %"or the test. fires fe1l into the foll~~ng ranges: buoymy fiuxes (values 
of F as given by equation (6)) from about 300 to 1,000 m4 s", line lengths from 80 

to 200 meters (m) within areas of about 1.75 to 10 am@, fuel consumd mostly to 

totally by a single line of fire, and transport windsp from 5 to 12 ms"'. The 

Briggs fomulas excelfed in predicting maxdum observd height of smoke from 

these fies, However? signilficant amounts of smake were found well below the 

predicted height, some near the gound. Based on optimizing the perfomance of 

the Gaussian plume mdel in predicting smoke conmntrations near the gound 

using Pasquill-Cifford-Tmer dispersion coefficients (Turner 1970), Lavdas 

(1978) proposed allowing 60 percent of the smoke to rise to Briggs' height, while 

leaving 40 percent to disperse from ground level. This modification to the plume 

rise equations resulted in a good fit to observed ground-level conmntrations near a 

fourth test fie. A recent, unpublished analysis6 tested the effect of a curtain-like 

vertically uniform distribution of smoke from the ground to Briggs' plume height 

for 75 percent of the smoke, while leaving 25 percent to disperse from ground 

level. This distribution resulted in a slightly better fit for predicted ground level 

smoke concentrations and a much improved description of the observed vertical 

profiles of smoke. 

these limited findings and the he~stically reasonable 

extrapolations from available infomation and obsewations of plume behavior 

effects on ground-level concentrations, VSMBm adds the following user-inputdriven specifications: which greatly extend the Lavdas (1 978) formulation: 

1. Specification of the propofiion of smoke (i.e., from zero to one) subject to 

plume rise processes. 

2. Specification of whether the rising portion of smoke is to be dispersed solely 

from Briggs' height or as if from a uniform "curtain" extending from the ground to 

the Briggs height. 

Any smoke not subject to plume rise processes is left to disperse Erom ground 

level. 

The ability of the VSMOm model to acco e a single, initially vertically 

unifom source within a surface-based vertical layer is unique mong plume 

ctispersion models, Gaussian plume dispersion effects on the initially unifom 

vertical "curtain'kf smoke are calculated as the smoke is transported dom~nd 

with referenm to plume wncentrations at ground level. (See Smoke 

Concentrations for more infomation.) 

Lavda~ / 2 99 1) unpublished analysis. 

The tvvo sp~cations ase controUed by a single user input vdable. If period-by-perid emissions data are available (i.e., if WREBD is 

TRUE), the eon.trohg variable is EMTQR(T), which is spe~ified on a geriod-by-pfid basis. IE such data are not avdable (LQREAD =: FALSE), 

the conmhg v&able is RRG. Ln ei&er ease, the valid range of values is from - 1 to + 1. Its absolute vdue conCro1s the pmpftion of smoke 

subjat to pIum rise, wh3e its siv controls the verticai dis~bution assigned to plum I-ise assmiat& smoke. See the VSMOKE &put 

Rqukments, Input V&abtc;s for more hfomation. 
A third plume-rise-related specification determines whether the final plume height 

ately or gadually as the smoke travels down 

d distance-dependent plume rise value, H, 

the pjume rise estimate), Gradual plume rise effects nomdly should be calculated. 

The alternative option forces the fimal plume rise value, H,, to be used at all 

domwind distanm and i for occasions when benchark runs 

of VSMOm may be req do not include gradual plume rise in 

their calculations, For exmple, certain puff models ( ,2.0) (Petersen and 

Lavdas 1986) are desipedj to include the effects of varying wind flow on smoke 

transport and dispersion, but use the fiial plume rise value for the height of all 

puffs. Although such puff models are less physically realistic in terms of plume 

rise calculations near the source, they can depict changing wind conditions, 

g wind conditions, or both more realistically than VSMOKE can. 

Combining the various plume rise related specifications with the specification of 

initial vertical dispersion, gives VSMOm considerable flexibility in specifying the 

overall initial distribution of smoke in the vertical dimension (fig. 2). If all smoke 

undergoes "sidficant plume rise", little or no smoke is present at ground level for 

some distance downwind (fig. 2, pant A). In the split plume rise option ground 

smoke is present at all downwind distances (fig. 2, part B); however, the vertical 

profile of smoke near the fire is often umealistic. The smoke curtain option (fig. 2, 

part C) often improves the realism of the vertical smoke profile and can be used to 

approximate the effects of gravitational settling of larger smoke particles in the 

plume. This last option also may include ground smoke. 

VSMOm is designed to readily accomdate revisions in the methodology for 

calculating and, to some extent, utilizing plume rise. Cunent how1ede;e is scanty, 

and independent investigations may yield significantly different results. The 

sensitivity of VSMOW estimates to plume rise assumptions and model input 

values is very high, particularly near the fire in stable conditions (i.e,, under 

conditions in which potential hazard is greatest). Therefore, the effect of any 

plume rise revisions on the "bottom line" smoke concentration estimates of 

VSMOKE should be carefully considered before they are used in an operational 

enviroment . 

Smoke Concentrations The largest single computational component within the VSMOm computer 

code is its shgle-sow=, steady-state, Gaussian plume atmosphe~e dispersion 

Selecting a Dispersion mdel. To visuaZize such a model, imagine a u~fom air mss with steady wind 

Mode]. direction and speed. Any pollutant will be c~ed downu;lnd by this mean wind. 

The Gaussian plume m&l assumes that the uniform vvind flow is disturbed by 

small rmdom pemrbations (i.e., wind fluctuations such as gusts, lulls, and 

momentary wind shifts). The character of lftese perturbations causes 

measwements of pollutant concentrations along a cross-section at right angles to 

the mw vvind to assume a Gaussian shape. 
A ALL SMOKE RISES 

B. SPLIT PLUME RISE WITH RISE-NO RISE RATIO SET BY INPUT 

LY TO MIX VMTH 

WTIOMS 

@, SMOKE CURTAN WITH 9)P"TOt"SAL GFBOtlNC) SMOKE 

Figure 2-Effects of plum rise op~ons on smoke concentrations at the ground. 
and othem (1982) provide a generic desGription of the Gaussian plume 

model and compare this modeling approach to some of the more mathematically 

comprehemive and demandirzg dispersion modeling tecbiques. me following 

asize their msessment of the Gaussiarr! plume model: 

" . . . is still the basic wor&orse for dispersion cdculations; 

. . . produces resultf that agee wi& expeI.iime-l dizta as well as 

my model; . . . is a relatively easy work to mathematically 

solve; . . . is appealing conceptually; . . . is consistent with the 

random name of Wbulence; . . . is a solution to the FicEm 

diffusion equations . . . has found its way into most gove 

guidebooks, thus obtaining a 'blessed' status;" and [&though it 

contains much enrpiricism] ". . . other so-called tkeoretical 

fomulas contain large mounts of empiricism in their final 

stages. '" 

Traeed back to the work by Taylor (1921), the Gaussian plurne model hm been 

refined by many: Sutton (1 9471, Pasquill (1 96 1, 19'74, 13761, Gi%ford (1 96 11, 

Turner (1964, 19"766), and hin (1983). Continuing resexch tends to csnfjim that 

the Gaussian plme model is no longer "state of the art" ((Vekatrasn and 

Wyngmd 1988). Yet, the disculty in obkihg &e data required to m enore 

accurate models~asticularly on an operational, real tim basi4eaves 

significant gaps between theoretical representations of atmospheric motions and 

the best available means of operationally chmacterizing them bm available data 

in real time. Currently, for many air quality analyses needs, the Gaussian plume 

dispersion model is still a "workhorse." As recently as 1987, in the U.S. EPA's 

"Guideline to Air Quality Mode1s'T.S. EPA 1986, 1987) msly all U.S. EPA 

"preferred models'hd the majofiv of "alt-ive models" were bsed on the 

Gaussian plune model. 

Evaluating the input requirements of a dispe~ion model is a particularly relevant 

problem for foresb'y-prescribed burning. Prescribed fire is a relatively inexpensive 

land maagement tool usually conducted in remote locations. At any given 

location, a prescribed fire is a transient pollution source. Compared to what is 

often available for a large stationary pollution source for which specialized 

amospheric mo~to~ng is typically available and often mand&d, resomes for 

and knowledge about collecting and wing meteorological diata on site are limited. 

The atmospheric monitoring of large stationary pollution sources should gradually 

lead to increasing use of rather sophisticated dispersion models. These models will 

require and eEectively utilize data such as eontinuow measu~eanem of wind, 

temperawe, presswe, and moisture variations in ve&icd md small horimml 

scales; direct measurements of tusbulent parameters such as very short-time-scale 

fluctuations of horizontal and vertical wind; and various means of describing site 

' A vev simple fom ofthe Fickian diffusion eqwtion statc:s hat the Erst derivative of concen&ation with m~~t to tim is eqrlnl to t-be sec& 

derivative of conantration wifh ~spect to dim= times a diffusivity mnm& wdly denoted by "K." A more eomplc?x. but still ineomplek9 

fom uses diEer3.ng values of K in the domwind, korimnbl crosswind, and ve~ica directions. 
and sumoun~g v~ables that affe~t wind flow and turbulence, such as roughness 

pameters and sudaee hearing coefficients. Models with tkse data requkements 

will be of little practical value in ral-time operational analysis of smoke fm F~es 

at remote lmations unta teehnologicaf ;and thmretieal aadvmas provide the 

to monitor the rqukd input on a national scale. Even as data sources become 

mre compll=te, and more mmplerr mdels are implemented, the Gaussian plume 

mdet will probably continue to be used as a scrm~ng analysis tool. 

The limitations of currently available real time data include its hability to properly 

derme wind Buctuation statistics, characterize vegetative or terrtriin roughness 

except In a crude sense, or confidently des&be my meteorological variables in 

the vertical, The Gaussian plume mdel has several advantages in this type of 

operational environment, espr=cially when used as a conservative scrwning tool. It 

is rmdily understood by nometeorologists; its strengths and weaknesses are well 

know within the meteorological co nity and readily co nicated to foresters 

and ad~nistrators; its input rqukements are relatively well matched to the level 

of infomation available in real time at remote forest locations; and it is based on 

data sets that are particularly well suited for predicting ground-level concentrations 

nem a ground-bas& pollution source (Bdggs 1988). Tfis last advmtage is 

particularly significant, given the roadway safely hazd potential assmiat& with 

smoldering smoke a& the neecl! for a reasonably accurate system to chaacte~ze 

the risk and extent of potential hazad. 

VS1410m does not consider any changes in any of the pollutmts during the time 

smoke travels from soure to receptor. The simplest mathematical method of 

accounting for pollutant removal uses first order decay processes of pollutant 

constituents. Some Gaussian plume dispersion models use a pollutant exponential 

decay constant or half-life decay constant (hin and otkrs 1985). According to 

Hmna and others (1 982), first order decay can be utilized for some wet deposition 

(using a scavtsging coefficient), che~cal transfornation prwesses fusing a 

cherniGa1 decay rate coefficient), and radioactive pollutants. VSNIOm makes no 

allowance for first order decay, and no first order decay effects have been 

document& for forestry smoke to the author's knowledge, First order decay 

reduces pollutant concentrations, and if decay effects do omur within forestry 

smoke plums, VSMOE"LE concentration estimates my be too bigh. 

Overes-tinnating smoke effects bmause physical processes are poorly understood or 

accounted for introduces a depe of conservatism, a deskable tendency in the 

scrmning applications for which VS1410m is designd. 

Othes processes that may transfom or move pollutants within the atmosphere 

include settling and deposition. These prwesses cm be nndeled by using one or 

more velwity coefficients, which assume that paicles move domward at the 

given speed(s) as they are transported domwind. Gravitational settling efficiently 

removes large and dense (mssive) suspended pmiculates, but has no effect on 

carbon monoxide. Be~ause forestry particulates are relatively small they are less 

affmted by settling thm are particulates from urban sources. Aaording to 

Petersen and Rumsey (I 987), dry deposition includes a number of removal 

mechanisms, inclu&ng gravitational settling, turbulent and Brovvnian diffusion, 
che~cal absorption, inertial impaction, and 1 and elmtrial effects. Some 

particles my actuafiy be re-introduced into sphere by mwha~cal 

resuspension (e.g., a dust stom), The plume PAL 2.0 mdel (Petersen 

and Rume;y 19871, and Gaussian puff 2.0 mdel (Petersen and Lavdas 

1986) are U.S. EPA dispersion models that include the effects of settling and dry 

deposition. Both models include settling and deposition velocity as input 

parametem. 

The governing equations for deposition and settling ses within PAL 2.0 and 

2.0 are somewhat complex and time consu mpxd to remaifig 

mdel computalions. In 2.0, the inelusion of dry deposition and setthg 

effects considerably utational time. A test that ineluded settling and 

dry deposition velocities thought to be characteristic of fo 

others 1979, Buck 1981) did not have a decisive effect on 

concentration esthates. Deposition and settling computations are not included in 

VSMOm because: (1) they are relatively demanding, (2) their effect is to lower 

aggregate smoke effects at any given distance from the fire, and (3) any tendency 

they might have to increase smoke effects at ground level near the fire can be 

sirnuiiftext by simple adjustments of VSMOKE input parameters. 

0th pollutant transfamiltion and removal prmsses, such as wet deposition 

modeling, are more difficult or even impractical to include in a steady-state plume 

model. Some wet deposition modeling techniques use washout ratio which, in a 

limited way, can defie a wet deposition velocity analogous to dry deposition 

velocity. This type of wet deposition can be incorporated in a steady-state plume 

model. However, most photochemical transfornation modeling, used for urban 

area pollutants such as ozone, uses chemical kinetic relationships within the 

framework of gradient transfer models-a very different frame- from that used 

in VSMOE. 

The steady-state Gaussian plume mudel context is used in VSMOKlE because it 

has a good track record and is generally accepted, easily understood, adaptable, and 

compatible with the mnstraints of forestry field-level planning and real time 

agplieations. The Gaussian plume model is also an attractive ntlacrdology far 

"worst-case" andysis in "pre-planning" or "saeening" operational 

environments-such a model can efficiently identify scenasios rquiring the use of 

rimre prwise and demnding computational methodologies. Co~nputational 

demands preelude the use of setthg and depssitim adqlations of the Gaussian 

mdel, while the desirability of conservarive smke inngacl estimates precludes the 

use of poillutant decay coefficients asswiated with smoke travel distance. 

Applicability of the The steady-state Gaussian plume model used in VSMOECE is best suited for 

VSMOKE Steady-State g the effects of a single fire vvitbin periods of mnstant or slowly 

Gaussian Plume Dispersion changing fie, smoke emission, and weather conditions, during which the smoke 

Madel mncentsation field can be amwately depicted within a steady-state frmework. 

The period-by-period analysis employed by VSMOKE allow som consideration 

of changs in fire and weather conditions. Hovvever, VSMOME ~alculations for 
any given period are independent of those for any other period, i.e., the weather or 

emissions of past periods have little direct effect on concentration es 

cment period. 

The Gaussian plume model is based on the idea that while pollutants are sta&ly 

and bodily transported do transport vector" of the wind field, 

sma21-scale turbulenm disperses the pollutants in directions perpendjcular to the 

mean transport direction, This results in a Gaussian distribution of pollutants with 

respect to crossplume distance from the plume centerline. Because horizontal and 

vertical twbulent motions differ greatly, the model calculates two Gaussian 

coefficients to deal with horizontal and vertical pollutant displacemen-ts. The 

Gaussian plume model is used successfully when the following conditions are met: 

* Turbulent motions are of small space and time scale with respect to the mean 

flow. 

Turbulent motions are sufficiently random. 

Mean flow is unifom, linear, and invariant, or nearly so. 

* Mean flow and turbulent structure maintain a sufficient unifodty during the 

period and across the donrain within which pollutant transport and dispersion 

occurs. 

* Rmulting horizontal and vertical displacements are correctly characterized. 

Placed in a climatological and synoptic meteorology context, these rquirements 

mean that Gaussian plume modeling is generally suitable either within a well 

mixed "boundary layer" of the lower troposphere- e.g., within a well established 

surface thermal mixing layer typical of fair weather afternoon conditions in the 

lowest 1,000 to 1,500 m-or within a shallow, nominally uniform, nocturnal, 

ground-based, stable layer. The approach, as used in WMOKE, does not directly 

delineate mass exchange rates or turbulent processes between adjacent contrasting 

atmospheric layers (e.g., between a stable surface layer and an overl+g neutral or 

unstable layer). Generdy, uniform air masses with uniform flow are required to 

maintain reasonable model pefiormanm. This requirement typically matches the 

need for predictable and steady fire behavior in prescribed bu~ng operations 

(Wade and Lunsford 1989). Areas with fair weather within high pressure system, 

and locations within relatively linear fields of pressure gadient (e.g., isobars 

fonning nearly straight lines or slowly sweeping arcs on a national weather map), 

often found around the periphery of high pressure systems, are often well suited for 

both safe and predictable prescribed fie behavior and relatively accurate Gaussian 

plume model estimates. Complicating factors such as rough terrain, sea or large 

lake breezes, or changing weather patterns can cause mdel pedormmce to range 

from degraded accuracy to omp promised performance to a point where the model 

simply "does not work." 

Given an appropriate "weather map," the Gaussian model can be expected to often 

work well in flat or rolling teah in the Eastern United States. In the Western 

Unit& States, terrain driven effects the forms that VVJnd 

flow patterns. Considerable experti g regional and her 

patterns is required for any assurance that a plum model will work amptably for 
any gven location in the Western United States. However, VSMOKE fight be 

used in selected situations, perhaps to establish a basis of comparison in evaluating 

the performance of more mathematically comprehensive modeling approaches. 

The steady-state, period-by-period analysis techque used in VSMOKE allows 

limited model applicability to scenarios that include changing fire and smoke 

emissions behavior and chanpg weather conditions. Each analysis period of 

VSMOKE should be regarded as a "snapshot" scenario 

emissions, and weather parameters remain constant during the period. Because 

most input parameters are allowed to vary from period to period, VSMOKE can 

analyze a series of snapshots for several periods. The modeling approach used in 

VSMOKE is not suited for rapidly changing weather regmes unless the analysis 

interval is set short enough to effectively "freeze" the weather changes in time and 

space. 

How the period-by-period capability of VSMOKE can be applied may be 

appreciated by considering a rather typical case of a prescribed fire. Fire personnel 

ignite a fire in an early afternoon with moderate winds and a slightly unstable 

atmosphere (a normal "fair" weather afternoon conhtion). ARer the fire actively 

burns for an hour or two, the personnel (unwisely) allow the fire to smolder for 

several more hours. The smoldering could easily extend into the night hours, when 

the winds would drop and a ground-based stable inversion would form. Through 

the proper specification of input values, a single VSMOKE run can generate smoke 

concentration estimates during the active period of the fire in the afternoon and 

during smoldering the following night. The estimates for each of the periods 

would be identical to estimates generated by properly specified separate VSMOKE 

simulations for each of the two periods. 

Mathematical Basis Using Tmer's (1970) approach, VSMOKE concentration estimates are made at 

of the VSMOm receptor locations along the centerline of the plume trajectory, and are 

Gaussian Plume Model applicable at ground level. The equation for concentration resulting from a single 

pollutant source as given by the Gaussian plume model under these restrictions 

may be expressed as: 

where 

C = concentration due to the source in micrograms per cubic 

meter, 

Q = source seen@ emission rate in micrograms per second, 

0, = horizonbl dspersion c~fficimt in meters (a function of 

atm.ospherjic stabilirty and do &stmm), 

rsion coefficient in meters (a bction of atmospheric stabilit). 

d distance), 
U = trimsport windspeed in meters per second (as input), and 

N = plume height in meters (a function of heat emissions, atmospheric stability, 

and downwind distance), 

Figure 3 shows an idealized depiction of the geometric structure of the Gaussian 

plume model as described by equation (13). In this figwe, a horizontal 

cross-section with a Gaussian smok concentration is shown closest to the fie, 

while the more distant profile shows a vertical Gaussian profile. Please note that 

the horizontal and vertical dispersion coefficients, a, and a,, need not (indeed, 

generafly do not) have the same values at any given down 

Equation (13) precisely applies in VSMOKE only if (1) a point source is specified 

or may be assumed, (2) a single plume height exists, and (3) the vertical dispersion 

coefficient is small compared to the mixing height (i.e., "reflections" of pollutants 

from the top of the mixing layer have no appreciable effect on ground-level 

concentrations). Equation (13) is modified as necessary to accommodate the 

VSMOKE assumption that all pollutants are "trapped" within the surface-based 

mixing layer, i.e., all pollutants remain at and below the mixing height value, A,,. 

VSMOE concentrations within the mixing layer are assumed to undergo perfect 

and complete "reflections" both from the ground and from the mixing height. If the 

vertical dispersion coefficient, o,, is much larger than the mixing height, A, the 

resulting vertical distribution of pollutants is essentially uniform within the mixing 

layer. In VSMOKE, the plume is assumed to be vertically uniformly mixed 

whenever o, exceeds two times A,. The governing equation for a point source in 

this case may be expressed as: 

GRQSS PLUME 

ENTERLINE ARE GAUSSIAN, WITH THE 

BEING THE PLUME CENTERLINE AND SIGMAS EING FUNCTIONS OF: 

B DISTANGE AND ATWSPHERIG STNlLIR(; XQRIZONTAt AEJD 

SIGMA VALUES ME USUKlY DIFFERENT. 

Epre 3- d Gaussian Plume Model. 
For wes in wbich plwe trapping may be , but a vertially unifom 

plme has not yet been achieved, VSMOKE uses the plume trapping assmption to 

ammt for multiple eddy reflections. The governing equation used when 0, is no 

more than two thm Am may be expressed as: 

where 

M = an integer such that each value to be exponentiated in the series is 

-25 or less (i.e., all terms << lo-'*). 

In evaluating equation (IS), each exponentiation argument is included if it is no 

less than the criterion value of -25, and the summation process continues until all 

arguments are less than the dterion. Under VSMOm constrhts which restrict 

H from zero to A,, and the use of equation (15) only if a, is no more than two 

times Am, the su n is completed in eight p most and is usually 

completed in fewer than four passes. Men all th thin the summation are 

insi&icmt, equation (15) is equivalent to equat 

equation (15) more than many U.S. EPA models, which is a nominal disadvantage 

in execution time. Bwause tests on the design host system revealed that the 

ed the insignifreantly affected operations, the more complete use of 

equation (15) is executed iq VSMOm. 

Figure 4 depicts the effwts of multiple reflections from the gound and from the 

layer on concentrations 6t~n the ' * layer. The initially 

al smoke profile closest to the fire ally mdfied as the 

"tails" of the distribution in. upper and lower bounds. These tails are 

"folded" or "reflected'" b g layer, and their conmntration 

wntributions are added of the Gaussian plume. As the vertical 

dispersion mfficient, cr,, inawes to about the same value of the 
A, a number of such reflections takes place. As o, becomes substantially larger 

than A, a vertically uniform smoke distribution results. 

NEAR SOURCE INITIAL RE 

MIXING HEIOWnr ---------- 

ONS MANY 

Figure 4--Vertical "reflections" from ground and mixing height "lid" in a Gaussian plume model. 

When the area of the burn is greater than zero, VSMBD (in mst cases) replaces 

the applicable point source equation with a finite line source equation to estimate 

con~entrations. If the dowwind distance from the fznite line to the analysis point 

is sufficiently great, the line "looks like a point." Because the point sow 

equations (13) to (15) are sufficiently accurate, they are used for a finite line source 

if the effwtive line length of the source in (defind as the square root 

of the area of the bm in square mters), i 0.0 l 2 tha the 

horizontal dispersion coefficient, a,. If hw 0.012 times cry, the source is 

treated as a unifom finite line sous= of te line soure mdebg 

is used to estimate conmtratio~s. If plume trapphg impo~mt (i.e., if 

quation (13) would apply for a pokt source), the go g equation for a flnite 

line source may be expressed as: 
where 

= effective fine length in meters, 

P = the quantity, Y/o,, where Y is horizontal crossplume distance from 

the plume centerline in meters, 

P, = Y,/ay, where Y, is one of the finite line end points, and 

5 = Y2,uY, where Y2 is the other finite line end point. 

In VSMOm, aU concentration es are made diratly domwind of the 

central point of the source, therefore as used in equation (16): 

P ra~tges from -0.5- to +0.5---. Eum 

@Y OY 

The definite integal within equation (16) is the inverse no& distribution 

function with respect to P (or Y/ay). VSMOKE uses a polynonnial approximation, 

as described by Abromowitz and Stwn (1972), equation (26.2.17), to evaluate 

this integral. The raw mathemtical polynomial is accurate to within 7.5 * an 

ained within VSMOE(E thou& the use of DOUBLE PRlECISION 

computations as required. Additional information on this aspat of VSMOlKE 

computations is provided within the mputer code. 

Finite line source effects are also considered when vertically unifbmrly mixed 

plum or plume trapping computations are appropriate (i.e., when equations (14) 

or 05) would be appropriate for a point some). Because the VSMOliCE computer 

all mncen&ation cal~dations into hasizsntal and vatic 

uations of the form of equation (16) never appear in 

not inGluded in this discussion. The sonespding 

trapped pollutants fmm a finite line source would b 

equalion8 (14) and (15) as does equation (16) to quation (13). Figure 5 depicts 

the effmt of a fife line source on s tration estimates, Close to the 

sow=, mnmntrations aru: horizontally drop to backsound 

from either edge of the he, &stance increases, 

" begin to take on a " e" shape. As the 

eient, a,, continues to inaease with inamsing distanw, 

begin to affect the uniform central area. Ultimately, as 

o, bmmes much larger than the lengttr of the line sousce, the horizontal 

mss-section of smoke concentration becomes fiully Gaussian, as if a point source, 

rather than a f~te line sowce, were upvvind. 
MUCH 

'THAN 

UNE ENW 

Figure 5-Line sources in a Gaussim Plume Model. 
Egum &Effects of Gaussian dispemion on an initially unifom dis~bution. 

VSMOm also calculates ground-level mentrations dourtlwind from a source 

specified to have an initial vertical distribution of pollutants that is uniform from 

the gound to the predicted plume height. These estimates are made by allowing 

Gaussian dispersion ses to act upon the initially vertically uniform 

distribution. Figure 6 illustrates the effect of Gaussian turbulence on an initially 

vertically uniform distribution. The top portion of the figure shows the effect of 

gradual plume rise, with no vertical dispersion (i.e., a, = 0). However, in 

VSMOKE, the effect of gradual plume rise is mmbind with vertical mixing 

effects. The bottoln portion of the figure shows more ralistic vvith 

SIGMA-Z inmasing (left to right) as the plume is trmsported . At first, 

with SIGMA-Z = 10 m, the unifom vertical distribution is diluted only at the top 

of the layer, and ground concentration, C, is relatively high at 1OW pg mm3. Next, 

SIGMA-Z haeases to 100 m, causing ing to take effmt over an increasing 

depth of the plume, which dilutes ground-level concentration to 680 pg m3. 

Finally, SIGMA-Z hereases to 300 m, causing the vertical distribution to assume a 

"folded" Gaussian character, wbich dilutes C to 260 pg me3. Tbe effect illustrated 

in figure 6 is siml1ar to the horizontal dispersion effect depicted in figure 5, ex~ept 

only one "side" of the pEme is allowed to dispers othm is bounded by the 
ground. Not shown in figure 6, but accounted for in the VSMOKE model, is the 

effect of the upper (show for a shpler case in fig. 4). 

To ammphsh the conoputajlons rqukexl for aaa ini~dly vestiedly unifom sowce, 

VSMOKE generally follows the method outlined in Lavdas (1986).9 This method 

reexpresses the con~entration equation in terms of relative concentration, CUIQ, 

then integrates with respect to 21a, i.e., hei@t divided by vertical dispersion 

coefficient. The limits of integration zue defined by Z-0 to ZH, where H is the 

plume height applicable at the given downwind distance (i.e., the entire dispersion 

s that defines a, is applied for the complete transport distance, whether or 

not padud plume rise is assumed). When equation (13) is reexpressed in terms of 

relative concentration and Z is used in place of H within the exponential factor, the 

following equation results: 

-- cu 411 pz 

Q (a, a, H) 

where 

P, is the inverse Gaussian distribution function in terms of Za,. 

The equation for P, is expressed as: 

- H 

where 

0 and Wa, are the limits of integration, and the integration is with respect to the 

ratio, 270, (i.e., the ratio of height to vertical dispersion coefficient). 

Because equation (1 8) is the inverse Gaussian distribution in terms of the ratio, 

ZaZ, it is completely analogous to that found with respect to P (or Y/o,) within the 

finite line sowce relationshi 

For vertically well-mixed concentration estimates, equation (14) is reexpressed in 

of relative concentration, CU/Q; then, using an equivalent height, HE, in 

place of Am, the followhg expression is obtained: 
where 

HE = an equivalent height or depth of a &round-based smoke layer in meters, with 

respect to gomd-level concentrations, ass verticaf ly unifody 

distributed pollumts. 

Equation (1 8) and expression (19) are combined to calculate the effective depth of 

pollutants after subsequent Gaussian dispersion processes have affected the 

vertical Bistribution of an initially vertically uniform source. Ths yields: 

where 

H = the plume height as defmed in equation (13), but now interpreted as 

the top of the initially vertically uniform plume layer, and P, is 

obtained from equation ( 1 8). 

Like the ~fom finite line source equation, equation (26.2.17) of Abrmo~tz and 

Step (1972) is used to evaluate P,. Equation (20) is used to obtain HE, then 

expression (1 9) may be solved for concentration, yieldmg: 

In all cases where concentration fkom a single pollution source, C, is calculated, the 

background concentration, C,,is added before concentration is output to the 

user. For particulate matter, the calculation is straightfornard: C, is added to C, 

yielding the total concentration, C, for each receptor, or: 

where 

C, CBKa, and C are gven in mi per cub& meta for partiedate matter. 

In Ihe case of carbon monoxide, background md tatd concentratims are expressed 

in piuts per rnallion on a mass basis. VSMOm first s tke density (mass 

per unit volume) of the moist atmosphere, multiplies this value by the parts per 

million input for carbon monoxide to obtain a C,,, density, then uses equation 

(221, using the calculated density of C for carbon monoxide resulting &om the Em. 

C,, is then reexpressed as parts per million of total carbon monoxide ~~ the 

atmospheric ~xme. 
VSMOa Horizorttd To calculate the horizontal and vertical dispersion cmfficients, a, and o,, 

and Vertical Dispersion VSMOm uses the dl-bow Pasquill-Gifford-Tmer (P-G-T) system, 

coefficients This system is most applicable for a &round source over open camtry in 

mal =as wJrth smmth or gently rolling ten&airt, Both ctispersion mfficients are 

specifid as functions of dom d &st- and atmosph&c stability class. 

Graphs of o, and a, appar in mny references, e.g., Pasquill (1974), Turner 

(19701, and Hanna and others (1982). In VSMOm, domwhd distmee Fncludes 

the source-to-receptor distance and may also inGlude virtual distances to account 

for "initial" Gaussian dispersion at the source site. Stability class in VSMOKE 

generally follows the objective scheme described by Turner (1964) and Lavdas 

(1986). Like many of the more recent U.S. EPA mdels, VSMOm extends the 

Turner system to distinguish between day and night for the near neutral stability 

class. In VSMOm, "near neutral - day" stability reflects an adiabatically neutral 

lapse rate and "near neutral - night" reflects somewhat subadiabatic conditions, i.e., 

an approximately isothermal lapse rate. 

Formulas for calculating dispersion coefficients appew in many published 

Gaussian plume models. For example, in the US, EPA model, GDM 2.0, (Irwin 

and others 19851, using the "PGSIG" option invokes the P-G-T system. The CDM 

2.0, PGSIG fomulas are follod in VSEtlOm with one exception: the vertical 

dispersion cwfficient for the nm neutral stability class during daylight uses 

fomulas provided by Turner." The unpublished Turner fomulas yield results 

that, at very short &stan@es, we more consistent with those calculated for the other 

stability classes. Wle the differences are inconsequential in any individual 

VSMOE concentration estimate, prescribed fire smoke management p 

often use a meteorological case sensitive structure. This structure 

Fnternal consistency among estimates in the design of VSMOm. The effects of 

this consistency become apparent when virtual distance calculations are made and 

model runs with differing stability classes are compmd-an inappropriate 0, 

value at short range could lead a land manager to mdify a meteorological criterion 

for burning in the "wong" direction. The Turner-based VSMOE values for 0, in 

"near neutrd - day" conditions are slightly less than the CDM 2.0 PGSIG option 

values for the range of downwind distances displayed in VSMOm output, i.e., 

from 0,180 to 100.0 kilometers (h). This difference causes VSMOI(E 

concentration estimates for the "na neutral day" stability class to slightly ex 

those based on CDM 2.0 PGSIG coefficients, The greatest relative difference 

betw~n the two is about 1 1.6 permnt at 0.100 km. This difference lies we11 tvithin 

the factor of 2 range of uncertainty intrinsidy asswiated with Gmssiara plum 

model dispersion coefficients (Turner 1970). 

The equation us4 to cdculate horizontal dispersion cwfficient, a,, in VSMOm 

follows : 

a, = 465.116 X,, tan (4 + B h 

Persond comunication. 1975. D. E3. Turner, U.S. Envkonmental Protation Agency, Resewch Tkgle Bak NG. 
where 

distance, ineluding virtual &stance due to initial horizontd 

dispersion, in kilomekrs, 

465.1 16 = 1000 (meters to kilometers) divided by 2.15; is approximately the 0.1 

amplitude point of the Gamsian dishbution funetion, and 

A and B = constants set according to stability class (table 1). 

The tangent argument in brackets in equation (23) may be thought of as a nominal 

horizontal "spread angle" for the plume. This spread angle is that angle to the 

domhd centerline mjectory for wluch the concenh.ation from a point souree 

main& a value 0.1 times that at the centerline. Table 2 shows that the effect of 

A and B within equation (23) at various dom&d &stances affords app 

adherence to the spread angles. 

The vertical hspersion coefficient, o,, in VSMOKE is calculated by using the 

follohg power function: 

where 

C and D = stability class and distance dependent constants (table 3). 

Other techniques for dete-g dispersion coefficients are widely used. Some 

simply use different constants and formulas to obtain stability and distance 

dependent coefficients (Hanna and others 1 982"). Others may assume different 

dependencies such as substituting travel time for do-nvvind distance. One 

theoretically appealing method (Irwin 1983) relies on wind variability statistics to 

help define the ~~cients, el~ating some of the empiricism inherent when 

using stability classes. Unfortunately, obta&g wind fluchation data for routine, 

operational, prescribed fie applications seems unlikely in the near future. 

The flexible smcLw:e of the VSMOKE program 

using certain types of alternatives to the P-G-T sys 

heoreticallq. appeal* use of 

(1983). Smoke and visibility esthates are vely s 

of both Bispersion coefficients, a, and hl attention must be men to the 

eM"ects of any Bispersion coefficient scheme on the '"oottm lhe" 

ground-level concentration estimates before any revisions to VSMOKE are made 

in an operatliml envkoment. 

'"age 30 of &nna and others 1982. 
Initial Dispersion In VSMOKE, specification of "initial" horizontal and vertical Gaussian dispersion 

CoeEcien-ts md Vi coefficients accomb for any dispersing effects at the source other than those 

Dismces in VSMOm directly associated with source size and plune rise. hput by the: user on a periodby-period basis, the effect of these coefficients on concentration estimates is 

calculated by using the "virtual source" coneept often used in U. S. EPA 

models (e.g., Wackter and Foster 1986). source modeling calculates the 

appropriate value of a dispersion coeffi ox$ "as if' the source were 

located further upwind than its physical location. The extra downwind distance 

equals that needed for a point sowce to generate a dispersion coeEcient value 

equal to the specified "initial" value. Figure 7 illustrates the vi 

concept. Except for the 500-m translation, the concentration distributions in the 

top and bottom portions of the figure are identical. The 500 m is the downwind 

distance required in this illustration to attain a desired horizontal dispersion 

coefficient value of 30 m. That 500-m distanGe is added to all downwind receptors 

only to compute the horizontal dispersion coefficient, a, 

VSMOm virtual distances are calculated by inverting the relationships used to 

calculate the dispersion coefficients. The vertical dispersion coefficients are 

determined by simple power laws (see equation (24)); invefiing them is 

analytically straightfornard. The horizontal dispersion coefficients are calculated 

by a combination of trigonometric and logarithmic hctions (see equation (23)) 

not readily inverted. To approximate the inverse of these hctions, VSMOKE 

constructs an array of calculated horizontal dispersion coefficients for each 

stability class and a wide range of downwind distances. When a virtual distance is 

required for a specific coefficient and stability class, array references to and 

geometric interpolation between the two closest values are performed. This 

technique yields more consistent results than the approximation formulas used in 

most U. S. EPA Gaussian plume models, e.g. Petersen and Lavdas (1 986). The 

improved computational accuracy can be important in some VSMOKE 

applications. For example, several program runs may be made to compare fires of 

differing size in an aaempt to meet prescribed fire management criteria by reducing 

Stability Class Stability clziss detemination in VSMOME fsllow the objective scheme 

Determination in VSMOKE of Turner (1 964) and Lavdas (1986), based on the categorical system developed by 

Pasquill (1 961). This system essentially consists of seven stability categories with 

descriptors (table 2). Like Pasquill (1 974), Lavdas (19861, and many U.S. EPA 

models (e.g. bin and others 19851, VSMOME distinguishes between "day" and 

"ai@t" under the near neutral skbiliw class. VSMOKE has the calpabilily to either 

xcept input val-s for stability class and a day/nif=ht flag or calculate stability 

class and day vs. night from input location, date, time, and surface weather 

prameters. Tumefs (1 964) ~alculation procedure is followed with one additional 

step. Ephemeris determination of day or night is based on time of sunrise and 

smset according to procedures in the U.S. EM meteorolodcal pre-pmessor 

T, as given by Gablano (1987). Tllese s et times 

those published in almanacs, partly because wes a 

single standard year in some of its ephemeris equations anQ paPtly because almanac 
STEP 1. DETERMINE VIRTUAL DISTANCE 

(May vary for sigma-y 

and sigma-z) 

ACTUAL POINT L 

-- 'Wr? 

INITIAL SIGMA-Y 1% ( .r 

OF 30 METERS IS ,qv-L,,.&, , ~rr~~~ *' 

WANTED 

500 METERS SIGMA-Y-30 METERS AT DOWNWIND 

DISTANCE=500 METERS 

STEP 2. CONCENTRATION CALCULAmIONS 

VIRTUAL POINT 

FOR SIGMA-Y 

500 METERS I SIGMA-Y CONTINUES TO 

ACTUAL POlNT INCREASE 

SIGMA-\( IS ALREADY (As if source were 500 meters 

30 METERS AT SOURCE further upwind) 

Figure 'I-Vimd distance concept (point source illustrated). 
VSbfOm Smoke 

Receptors 

calculations account for re~action and the radius of the solar disk. T 

assumes no regaction and neglects the solar disk radius. With implementation 

peci fied interval bettveen analysis periods, VSMOW", 

T criterion that restria changes in stabiliv class to no 

more than one category per hour. 

Users with meteorological backgrounds may choose to use National Weather 

Service upper air and su&e observations to help specify stability class. These 

users should note the findings of hvdas (198 1) for the early moming (1200 UTC) 

soundings at Medford, OR. The extremely stable and moderately stable classes 

averaged a lapse rate of about 0.035 kelvin (K) per m near the ground; the slightly 

stable class averaged about 0.020 K per rn, Both these values equal those 

specified by U.S. EPA (e.g., Cablano 1987) in plume rise calculations. The near 

neutral class at night averaged about 0.010 K per m, which is close to isothermal. 

Because the Lavdas findings and the U.S. EPA slable class lapse rate values agree, 

the practice of basing stability class at nigbt on observed lapse rate is credible. 

Moreover, the daq. vs. night "adiabatic" iutd "subatliabatic" distinction made in 

VSMOIKE;: within the near neutral stabiliv class reflee& the distiwion made by 

Pasquill (1974). Therefore, an isothermal layer at the sudace layer of the 

atmosphere would tend to dictate the near neutal ni@t class, while an adiabatic 

lower atmosphere would tend to dicbte the near neutral day class regardless of 

time of day. 

Attemp@ to distinguish among the various daylibt stability classes by using near 

surface lapse rate have not been notably successful. Atmospheric turbulence in 

near neutral or unstable conditions tends to eficiently force the vertical 

temperature gradient to a value very close to a neutral lagse rate. How unstable a 

lapse rate the atmosphere can sustain seems to be tied more closely to surface 

heating and frictional characteristics than to the intensity of turbulence. This 

circumsbnce limits using the degree of instabiliw of the vertical potential 

temperature profile to specify Gaussian dispersion coefficients. 

VSMOECE concentration estimates are made along the centerline of the plume 

trajectory fi.om the fare at ground level. In atmospheric modeling terminology, 

VSMOm uses a Lagrangian fix., airborne particle following) modeling approach. 

Cowentration estimates are mde at logasithically spaced distanGes ranging &om 

0.100 to 100,000 km. (or abut 1/26 to just over 66 miles). Logasithie spacing 

cawes the receptors ts be closest to eiach oher new the fire, where variations in 

smoke effects are greatest. An interval of a factor of about 1.2589 (10"') is used. 

For sources with no plume rise, this spacing keeps the demease in concentr&ions 

&om a fire betvveen adjacent ireceptors to just under a EaGtor of 2. More rapid 

increases of concentration are possible with increasing distance when a smoke 

plme from a fire with nearly complete plme rise first intercepts the ~ound. The 

receptor spacing is dense enou& to allow suficient3ly accwate geometric 

intergolation of concentration estimates to intermediate dishnces, All smoke 

concerztration estimates given by VSMOKE include specified conslant background 

values for eaeh period; tb, relative changes in the ouQUt concentration values we 

generally less than those cited for concentralions solely 60m the source. 
The VSMOKE plume centerline approach uses receptors located dong the plume 

trajectory. By using the unifom flow assmpaion &om Gaussian plme mdels 

md oaem 1982) md aii a11 receptom directly on the plume 

centerline, VSMOE removes all mathemat;lical reference to wind direc~on @om 

the concentration equations. By removing wind direction dependency &om its 

calculations, VSMOm in effect employs comentric rings about the smoke source 

as receptors. The~fore, no explicit plume pathway exists in VSMOm. Instead, 

the model provides concentration estimates along the trajectov without attempting 

to spatially locate that trajectory, except by downwind distance frsm the emissions 

source. In this sense, VSMDKE may be regarded as a one-dimensional model. 

The VSMOKE methodology that locates all receptors along the downwind 

centerline plume transport trajectory (SFFLP 1976) represents a sipificant point 

from many U.S. EPA dispersio 1s. The receptor methodolo@ 

resembles the older U.S. EPA model than any of the 

d air quality models in the "Guideline to Air Quality Models" (U.S. 

EPA 1986,1987). However, the PLUVUE I1 model (Seigneur and others 1984) 

listed in the EPA Guideline is a specialized model that uses downwind distance to 

define receptor Iocatiens. 

Models that rely on fixed point secegtors are subject to large emrs in smoke 

concentration estimates caused by errors in wind flow specification. These errors 

are assoeiated with small displacements of relatively narrow smoke plumes, and 

are more likely to occur in the stable conditions characteristic of 

variable/drainage wind regimes. These conditions are associated with high smoke 

and visibility hazard. In these cases, the model plume is nmow and the 

uncertainty in the wind field is high. By using a "plume following" technique that 

assures the targeting of every receptur by the smoke plume, VSMOm avoids 

much of the error that "fixed point receptor" models are prone to. 

VSMOm is oriented toward short-tern avoidance near or in any direction 

domwind of a firegenerally an episodic event. Many U.S. EPA models using 

fixed receptors estimate average impact at a pint or over a geographic area during 

a period of time when a variety of weather regimes may occur (bin and others 

1985). 

Figure 8 illustrates the digerences beween the VSMOm plume centerfine and 

EPA fixed pint receptor modeling approaehes. This fiwe sbow the effect ofa 

smoke source upn a hpothetically "dean" backgomd. To compute the 

concentration values in the figure, a 1,000 gram per second smoke emission rate 

with no wompanying heat emission rate, a slightly unstable atglospheric 

environment, a 4 ms-I transport windspeed, and a 1,500-m mixing height are 

assumed. Initial horizontal and vertical dispersion coefficients of 5 m each are 

also assumed. The figure shows the 1,000 pg m" concentration isopleth resulting 

from a wind direction of 200". The resulting locations of the first 17 (total 3 1) 

VSMOW rmptors is show dong the plume centerline. "'Rwptor 17," at a 

distnm of 3,98 1 m Gust uder 2.5 ~les), is naly t0uchr:ng the 

isopleth, as would be expected from its tabular concentration value of 999 pg me3. 

The VSMOm receptors "apture" the extretnely high smoke con~enltrations close 

to the smoke source, with the highest tabular coneenmtion ex 

pg m3. 

Fiwe 8 also illustrates srnoke concen&ation values as they would be det 

from a cartaim grid of receptors with a spacing of 500 m, a north-south, east-west 

orientatjon, and the zero point of the grld assigned to the central smoke source 

location. Where the grid points fall well outside the 1,000 pg me3 isopleth 

boundaty, concentration values are shown near the applicable grid point location. 

Note that the grid of receptors is insufficiently dense to capture the very high 

concentrations charactefistic of the values given for the fust 10 to 12 VSMOm 

receptors. 

The first labeled grid point, A, is 500 m north of the source and very close (within 

20 m) to the 1,000 pg nx3 isopleth, yet its concentration value is only 360, or less 

than 1 percent of the enterbe value fox its dom~ndistan~ fom the source. 

The plume almost completely nnisses point A's "sister receptor" 500 m to its east. 

On the other hand, point B (1,000 m north and 500 m east of the source) scores a. 

"near hit"; its concentration value of 5,282 pg m-3 is almost one-half the value for a 

receptor directly on the centerline at its downwind distance. However, point B's 

"sister receptors" 500 m to the west and to the east give little or no hint of the 

magnitude of the plume's impact 1 km, north of the source. A "lucky hit" is scored 

at point C, which is only about 43 rn from the plume centerline while nearly 1,600 

m distant, The distance from the centerline of point C is only about 0.27 times the 

value of a, for its domwind distance, which means that it captures about 0.964 of 

the centerhe concentration at its dom distanw. Point C's conmntration 

value of 4,985 pg nf3 is close to the value for the nearby VSMOKE receptor 13 

value of 5,145 pg m3. However, if the plume isopleth undergoes a small rotation 

in either dhtion, detection of the maximum impact of the plume 1,500 m north of 

ly a mtter of luck. This assertion is supported by the mueh 

lowet concentration values 500 m to the east and west of point 6. 

PIme detmtion bmmes more reliable as distmm from the sour= hawse, 

Mjawnt points D and E both swre mu hits, and given tbe low wncenlritticzn 

values to the east and wat of th.ese points, some indication sf the shape and 

magitude of the plume at this distmm begins to emerge, At inaashg distances, 

points I; and C smre nearly &wt hits and are sunoundd by signiEicantly high 

griddd conentralion vdues, dong the tw no& st rows of Mddd 

rsxeptors (3300 m md 4,000 m noah sf tk source) the Gaussian shape of the 

plum becow quite obvious. At this distance, the VSMOZCE receptolr spachg 

bas inawed so that its adjam rqtors are 

raptors. Centerline eon%ntsation values at s 

sowm change sloubliy enough to aUow mntinuous haeaes in. VSMOm rmptor 

spacing. 
To produce reasonably accurate averaged concentration estimates, models with 

geometrically fixed receptors are dependent on a veq accurate averaged 

representation of plume widths, orientations, and locations over the period of 

simulation. Nmow plme models cam be expected to produce reliable shortterm concentration estimates at fixed locations in an episodically oriented 

operational enviroment. For example, in moderately stable conditions, a 

VSMOm-like model with fixed receptor locations must speci@ the effective 

plume transport direction within 5" or less (table 2) in order to maintain factor-of10 accuracy! Fox (198 1) also points out that errors of representativeness and 

variability associated with applying a single wind direction for the effective area 

between source and receptor tend to be large compared to the characteristic angular 

dimensions of the pollutant plume. This leads to large errors in estimates of shortterm single source impacts at fixed locations. 

In "real-world terms," the relatively large uncertainty in the direction of plume 

transport compared to its width means that a fixed-point receptor model is apt to 

depict a plume trajectory showing a given receptor to be fiee of smoke, when a 

small change in wind direction could have a heavy impact on that same receptor. 

The VSMOKE approach eliminates much of the sensitivity of Gaussian plume 

models to small errors in the specified horizontal direction of pollutant transport. 

Such errors can have a crucial effect on the analysis of an episodic and potentially 

hazardous event such as smoke intnrsion from a gr~und fire over a sensitive 

location. 

Expected Accuracy of The accuracy of VSMOE concentration estimates is inherently limited by the 

VSMOm Concentration scope of the dispersion model. Uniform steady-state fire, smoke and heat 

Estimates emissions, and meteorological conditions are assumed over the portions of the 

atmosphere containing smoke during the course of any single analysis period. 

Variations in dispersion rate and wind flow minor enough to retain a generally 

intact and uniform smoke plume are accomodated by this modeling approach, 

with minimal error introduced in the smoke concentration estimates for points 

centrally located within the plume. However, significant variations in imp0 

meteorological parmeters, particularly in the wind field, will seriously degrade 

model performance. Major complexities in wind flow, such as a wind field that 

causes the smoke plume to double back on itself, are completely beyond the 

model's scope, 

The accuracy of VSMOE smoke concentration estimates is affected by the 

accuracy of the emissions data supplied to the VSMOKE dispersion model. Any 

emr in a pollutant emission rate will result in a 1 : 1 proportionate error in the 

resulting smoke concentration estimate (equations 13 to 21). Concentration 

estimates near a fire are also extremely sensitive to plume rise assmptiom both 

within the model and as input. Smoke concentrations at the pound increase 

rapidly as an elevated plume first intercepts ground-level receptors. Therefore, a 

relatively small decrease in plume rise can result in a large increase in the estimated 

concentration at a given downwind distance. This sensitivity is most marked ifthe 

user input indicates that all or nearly all smoke attains full plrzrne bei&t. Similmly, 
if the proportion of smoke subject to plume rise is incon&ly specified, large 

errors in smoke concentration est can result, particularfy near the source. 

For example, if input indicates that 99 percent of smoke undergoes significant 

plume rise, but only 80 percent actually does so, the resulting smoke conantration 

estimates close to a fire can be too low by a factor of 20. 

VSMOm concenb.ation estimates are also highly dependent on the various 

wteorological input values supplied to the dispersion model. For example, if 

plume rise does not change, concentration estimates are inversely proportional to 

the transport windspeed; halving the ddspeed doubles the concentration 

estimates. However, transport windspeed also influences estimated plume height; 

in unstable or near neutral-day conditions, doubhg the transport windspeed halves 

the plume rise. In stable conditions (or near neutral at night, when an isothed 

atmosphere is assumed by VSMOm), an eightfold increase in transport 

windspeed is generally required to halve the plume rise. Any change in the input or 

calculated stability class value can also result in a large change in smoke 

concentration estimates . 

In pat, this sensitivity is a consequence of the categorical nature of atmospheric 

stability as used in VSMOKE. In the categorical system, a small change in an 

input value that specifies or influences stability class can cause a rather large step 

change in estimated concentrations. For a fire with no significant plume rise, a 

more stable class results in higher ground-level centerline concentration estimates. 

For a fire with all or nearly all smoke attaining a significant plume rise, a more 

stable class may sharply reduce VSMOm concentration estimates for nearby 

receptors-the higher concentrations remain above the ground. Mixing height 

usually exerts less influence on ground-level concentration estimates close to the 

fire than the other major meteorological parameters. However, once the plume is 

well mixed within the mixing layer, which occurs at longer distances and in more 

unstable conditions, halving mixing height can double concentration estimates. 

Internal calculations within the Gaussian plume dispersion model are affected by 

the VSMOm assumption that uniform "steady-state" conditions prevail during 

any given period. %%en all the variables affecting smoke concentrations 

downvvind have been determine& they are fixed in time and space for the full 

period and over the full geometsic domain from smoke generation to any downvvind 

point. Aithough VSMOKE can generate smoke concentration estimtes for several 

sequential perictds, the dispersion model calculations for each period are considered 

independently. 

The empficd mdehg techniques used in VSMOKE to specify dispersian 

mfficients are far from exact but, amrbg to Turner (1970), can give acceptable 

. Given a perfst specification of plume rise Wcb is 

easiest to obtain when little or no plume rise murs during smoldering conditions), 

the aawaey of the pollutant mncentration estimates due to the source is 

mpletely dependent on the accmacy of the dispersion coeffiGients and the 

validity of the Gaussian plunze assumption. The expected aGeuTacy of the 
Gaussian plume dispersion model is greatest closest to the pllution source. At the 

closest distaflces, estimates of the vertical dispersion coefficient may lie within a 

'"actor of 2,'hd the combined effect of errofs in the vertical and horizontal 

coeficients may result in estimates remaining within a "factor of 3" of actual 

values. Therefore, concentration estimates wihin 1 km (about 518 mile) of a 

perfectly specified smoldering burn site may fall within a factor of 3 of actual 

values. The expected accuracy of the dispersion model becomes much worse with 

increasing distance, especially beyond 10 km (about 6 miles) from the source. 

Pasquill (1974) characterizes the accuracy of the dispersion coefficients at such 

distances as "speculative." VSMOKE estimates at long distances might best be 

regarded as little more than hypotheses agreed to by experts in the absence of 

better idomation. 

The VSMOKE Lagrandan receptor location approach, in a sense, gives the model 

a measure of accuracy not possible in an equivalent Eulerian ("fixed grid") receptor 

model. An Eulerian model estimates that a smoke concentration, C,, will occur at 

a specific receptor point, (x,y), while VSMOKE only warns that a smoke 

concentration, C,, will occur at a downwind distance, X, from the fire. The 

location of occurrence of C, is not specified except by downwind distance from the 

fire; in VSMOKE that distance could be in any direction from the fire. 

Because VSMOKE does not locate the smoke trajectory, it must be independently 

determined. Not only the width of the plume, but uncertainties in smoke transport 

directions should be considered when determining areas of possible smoke impact. 

The user must allow for the variability and uncertainty always associated with the 

wind field, and the risk associated with an imperfect weather forecast. Variations 

in wind are nearly always present both in space and time. Winds aloft may 

transport smoke in directions not anticipated based on surface winds alone. Those 

experienced in prescribed fire know how much wind can vary within a burn site as 

well as during the course of a burn. For smoke, wind variations literally above and 

beyond the bum site are also crucial to prescribed burning decisions. 

When using VSMOKE smoke concentration estimates it is best to assume that the 

estimated concentrations will occur over a rather wide arc to either side of the 

nominal downwind direction. SFFLP (1976) recomends using a 30" angle to 

either side of an observed representative domwind direction. At least 45" to either 

side is required when a forecast downwind direction is used. National Weather 

Service public forecasts of wind do not spec@ direction more precisely than by 8 

compass points. When no consistent wind direction exists (e.g., near calm, light 

and variable, or stronger but highly variable winds), concentric circles about the 

fire site may be the only reasonable basis for seaing geometrically based criteria 

for smoke management decisions. A preliminary study of wind direction 

persistence and forecast accuracy (Lavdas 1993) indicates that the possible effect 

of smoke in all directions shouid be considered, regardless of the meteorological 

regime. 
Crossplume Sightline te plm visibility and contrast ratio along aossglume 

Gkiametehtic~ sightllnes at ground level centered along the downwind plume trajectory. The 

two pasmeters, visibility md eonmst mio, are dosely related. Visibility 

The VSMOKE Crossplume defmes how far one can see a "target" with a given clarity. Contrast ratio 

Sightline Characteristics defines the clarity with which one sees a target at a given distance. Because the 

Model atmosphere acts to scatter and absczrb light (a propensity geatly increilsed by 

impuri.t_iw such as smoke), clarity dmeases as distane increases. In other words, 

as distance increases dong a sightline, contrast ratio decreases. The visibility 

along a sightline is the length at which the contrast ratio falls to a critical value. 

The sightline estimates of visibility and contrast ratio are based on relationships 

that are valid only in dry conditions, i.e., when relative humidity is less than 70 

percent. Like smoke conatration estimates, the sightline estimates are given as a 

function of down~ndistance. Although it uses less wmputer code than the 

dispersion model, the sightline analysis is the most computationauy intensive and 

time-consuming VSMOKE component during progam. exwutbn, For this reason, 

sightline es thates are optional. 

es are calculated from the specified background part;iculate matter 

concentration value and from ~ariousmoke plume cha~aeteristics at each 

downwind distmce. The sightlines are constmctd in short piwewise segments 

(along which plume characteristics are assumd to be constant) at gfound level 

outward from and horizontally perpendicular to the plum centerline. Slghtlines 

start with a central segment for which the centerhe pat.lticul& matter 

concentration athate is assumed to apply. Segment pairs are then added as 

rquired to each end of the sightline, extending until the contrast ratio drops to the 

specified criterion threshold value and the sightline reaches a knglh Wchg the 

specified visibility criterion. 

Tbe following equation for contrast ratio, adapted from Middleton's (1968) 

equation (4.251, is used in all VSMOKE crossplume sightline calculations: 

where 

CRa = Apparent eontsast ratio (i.e., as seen dong tlre sightlhe) of an obja versus 

its background (unitless), 

GR, = Intrinsic wntrast ratio (i.e., wiaout any fight altenuation) of an ol?ject 

versus its backgound (unitlms), 

B, = Light extinction efficient of the atmosphere hcluding the effects of any 

pollutats in units of hverse meters, and 

= Sigbtline length in meters, 

Light extinctior, characteristics are expressed through the equation (25) v&abk, 

Bm BE, is detedned by a relationship given by Tangren (1982) and later 
modified by Tanm in 1985. In VSMOm, the Tan- qation Eor BE% 

applies to boh smoke md backgound pmiculak mager. It is 

that this equation Eor dl -nuation of light (e.g., effats due ta nibiG 

o~des, NOx, are neglwtd). "Te rrelatiombp as used bn VSMOm ma)J be 

expressed as follows: 

where 

XpM = particulate marter concenLration in micrograms per cubic meter. 

Equation (25) is valid if the light extinction coefficient, B, from equation (26) is 

regarded as constant for the MI len& of the sightlllle. Sialine segbnents dong 

which the concentrations vq only ally are used in VSMOKE. The 

consmction of the sightline begins outvvard fiom the centerline for a crossplwe 

djstmce for which the con~entration is app ately equal to the centerline value 

already calculated by the VSMOm model. For a pod sowe or a relatively shoa 

llfte sow["=, ~s cenaLra1 sepeni is set ts a lengh 0.2 thes the ho~zontal 

&spersion coefficient, a,. Tbe v~alion of cmcentration alow ~s line segment is 

less thm 0.005 thes the centerline value. For line somces much longer tksm a,, 

plume eoncentrations can be nearly constant for &stances much longer hm 0.2 

thes a,. If ths: effective source line lengtfa, Km, is mre than 10.3 thes a,, a 

central sightline segrnent of length [(Km /a,) + 10. If times a, is used. To 

computations of light attenuation in the plme to either horimtal 

ide of the cenbal plme segment, semen& of length 0.1 thes a, are 

added as needed. The "OR-centerline" concenLration at the midpoint of each line 

sepent is used in equation (26) to calculate the appropriate vdue of B,, for 

equation (25). In the Caussian plme model (figs. 4,6, and 8), concentration 

values wntinuously decrease with increasing &st= fiom the plume centerline. If 

light aaenuation calculations are required once the oB-centerline crossplume 

distance has reached the absolute value of 5.0 times a, plus one half of no 

additional "in plme'kalcdations are made. At these large crossplume distances, 

the effect of the smoke plume is considered negligrble and the baekg0un.d 

concentration value is used in equation (26). 

methcrdolo~ applies to these sightline calculations. XPM in equation 

(26) for the antrd sigktIirre segrnent is the sm of the eenterline pMidate matter 

wncenwalion resulting Grom the fie and the inp& backgouyltd value, BEm for the 

cen&al segment an$l an assumed CR, of 1 (i.e., perfect wbite against pedect black) 

are used in equation (25) to obtain 6% for the central segment. If Clt, is lugher 

than the user criterion, then visibiliw is longer than the central segment, and more 

contrast ratio calculations are req~ed toobtain a visibiliv esthate. If the 

sepent is shorter than the visibility criterion, more contrast ratio caldations are 

req~ed. In either case, as calcdations continue, the ~ntral se&n?.ent C$ becomes 

the new CR, for the next CR, calculation. In additim to the elltmts ofthe cenb.al 

sepent, this CR, inGludes the eEects of the hyo si&tlk sepents adjacent to 
both ends of the centube segment. A new value of XpM at the representative 

crossplume distance for the two new sightline segments is used to determine BE, 

for the new segments only. New segments are added to both ends of the sightline 

until the input criteria for both mtrast ratio and visibility are attained. Far each 

new sepent pair, the CR, of the last complete sightline calculated beeomes the 

CR, with respect to the new segment pair. When the sightline segments reach the 

criterion crossplume distance, plume calculations are ated. If the sighthe 

must be extended further, the bacwound con~entration as XpM in equation (26) 

and the resulting value of B, (equation 25) are used. The final visibility estimate 

co~esponds to the total sightline length for which the user-specified contrast ratio 

critedon can just be maintained, The final mntrast ratio estimate applies to a 

completely constructed sightline with a total length equal to the user-specified 

visibility criterion. 

Visibility calculations during sighthe construction are performed from a modified 

equation (25): 

where 

V = visibility in meters. 

Figure 9 illustrates the construction of sightlines for an ideal case. Within 300 m 

of the source and near the smoke plume centerline, visibility is near zero and does 

not register on the graph. At 450 m, a short sightline is shown in the "east-west" 

horizontal crossplume direction. Visibility conditions improve and the sightline 

extends outward to greater distances as domwind distance increases. At 1,050 m 

north of the plume, the plume "boundaries" are almost reached. At 1,200 m, 

gh" is achieved and an individual to one side of the plume can 

just see completely through the plume and distinguish objects at the far side of the 

plume. As the effect of the plume on visibility continues to decrease with 

increasing domwhd distance, one may see objects at the far side of the plum 

with hereasing clarity, and the ultimate crossplume visibility continues to inaease. 

VSMOKE crossplume visibility estimtes sometimes exhibit an abrupt increase 

with respect to downwhd distanee near the sighlline "b hrough" zone (fig. 9). 

This sudden increase wws when a sightline is constructed through a dense smoke 

plume of limited crossplurne extent within a mu& clearer background atmosphere. 

distance, the contrast ratio may be reduced to just below the 

the smoke plum+w%ch yields a low visibility esthate. At 

&s-ee, the sightline "just b through" into the 

clear atmospfiere. Amrding to the input contrast ratio criterion, the visibility is 

much greater, but the visual quality of objects within the clear atmosphere seen 

ratio criterion. The change in the 

hrough zone" is usually far less 
----*----- 

NOW CAN JUST SEE WROUUH PLUMQ 

UPDlTlOllAL YISIIIIUTT OLPENDS ON 

BRUK-THROUQH "HOW MUCH CwllTf i8 LEFP AND 

0ACKGROUND CONDITIONS 

t--%---.--. 

CAM MYOPT SEE WROUQH ?WME 

t * +++- 

BUILD SIUHTUNE OUT UNllL 

OBJECT TOO fAlNT 

t'-4-*--- 

.--c- *-- 

BUILD f ROY CLNTERLIWL 

OMlNM PLUME OUTLINE 

TUALLY IS QUITE "8LURRY 

ALMOST "DLiNDE 

-1 00 

-500 -250 0 250 500 

CROSSPLUME ISOPLETH DISTANCE 

Emre 94onstruction of horizontal crosspfume sighhes for VSMOME. 
2: 

g aoa 

drmstic, In these cases, the mntrast ratio est es may give a cfmrer picture of the 

plume's overall visual characteristics and its potential to contribute to a roadway 

hazard. 

Figure 10 illustrates the behavior of VSMOKE estimates near the "sightline 

gh me." A plme 400 m ($4 mile) wide at 1,050 m dowwind is set 

ckground* The sightline using a 0.02 contrast ratio criterion 

gfi. The computed visibility is about $4 mile, and the 

contrast ratio for a % mile sightline is perhaps 0.19. At a somewhat greater 

downwind distance (1,350 m), sightline breakthrough is achieved. Perhaps the 

contrast ratio for a % mile crossplume sightline central to the plume is still only 

0.25. However, because the background visibility is so good the contrast ratio 

does not drop to 0.20 until a sightline 10 miles long is constructed. The 10-mile 

visibility estimate seems to indicate good seeing conditions, but the marginally 

acceptable contrast ratio estimate of 0.25 is a much better indicator of the potential 

for visibility hazard. In this case, a person with slightly impaired vision that still 

meets driver's liensing requirements might not be able to see $4 mile across the 

central portion of the plume. 

CROSSPLUME lSOPLETH DISTANCE (meters) 

Egilre 1 &Sigh*e b ugh zane behavior with very clear bwkmund in VSMOm. 
Sightline Modeling 

Cornems 

The modeling of si&tline chafacteristics is suhect to more problematic 

asslunflions, uncertainties, and potential difficulties in ap~slicatim thm my otkr 

asgect of VSMOKE, However, sightline-related estimates are imluded in 

VSMOME, because available scientific Imswfedge must be used to characterize a 

smoke-related phenomenon that is potentially hnrdous to the general gubfic. 

Nevertheless, concerns associated with the use of VSMOU si&tline estimates do 

exist, 

The greatest potential for smoke-related visibility hazard exists when relative 

humidity is high. Unfomnately, methodology has not been developed for making 

reliable predictive qumtitative estimaks of visibili~ in smoke under conditions of 

high relative humidi-ty. Accordingly, sightline characteristics are not quantified 

hen relative humidity equals or exceeds 70 percent. Sightline estimates in 

VSMOm are valid only for lower hwnidities. These values are accompanied by 

aterisks when the specified r dity is 2 70 percent, Because sigl.ltline 

characteristics are likely to be than a VSMQU estimate when. relative 

hurnidity is too high, extreme caution is absolutely necessav when interpreting any 

sigktline value accompanied by an asterisk. A description of a @ index that 

characterizes ro well as in lower 

humidities is de 

More research is needed on the approp.ate inpub. criteria for critical contrast ratio 

and visibiliv criterion for public roadway safe@. A contrast ratio sf 0.02 

(Middleton 1968) has often been used to dehe mway visual range, beeme this 

value hs been found necessaq for an airera& pilot to make a positive 

identification of a target. A sornewl-r;aa higher value may be needed for roadvvay 

safety because legally operating motorists do not necessarily have the visual acuity 

required of aired pilolts. Factors associated with driver and vehicle response, 

such as rextion tim ad stopping distance, should be considered vvhera choosing a 

crirical value for visibility, Tbese factors vary simificmtly mong drivers and 

among vehicles and are also aEected by the nature of the roadway, traffic patterns, 

and other driving conditions. Tn any case, 500 feet (0.0947 miles) appears to be an 

absolute minirnuarr visibility requirement for safe use of public roadways. hdeed, 

a much higher value can be justified for maintaining safew on mmy roads, 

pwictrluly heavily traveled qressways such s long intersht.23 downgades used 

by mmy tandem tsailers, 

Anarher mea of coneern is that the li&t scatlering equation (26) applies $Qs a 

nmower range of conditions thm hose d"or which VSMOE, overall, is desiped, 

The relationship bemeen optical properties of smoke md pa~iculate maser 

concentration varies ssnsiderabb &om that @ven by equation (26). Backgowd 

polturn& may not shme the optical pmpellties of smoke. Optical pmy;tePgies of 

smoke md biackgound are subject to dratic chg: m relatiw krurnidiv imrewes, 

and non-hydrophcsbic particles will scaeter md absorb mre li&: rn humidiv 

approaches saturatim, llra addition, visibili&gr absenration?; in hi& hunnidiv exhibit 

a geat &al of va~abion, Because Pkte causes sCIkese v&atiions ase imomglekfgr 

mderstood and diaeult kQ spec=i@ in rn operational envimmenl, &e processes 

have not been ineluded in this version sf VSltllOm, FurCfaer discussion on the 
Dispersion Index 

limits and the extension of the light scattering equation are given within the 

VSDRYG and BEXnS subprogms of the VSMOKE computer code. 

VSMOKE sightline estimates are given for the horimntal crossplme direction 

only; si&tline charwteristics in other directions may vary sieficantly (fig. 11). 

Because sightiine quality ean vary with respect to orientation, VSMOU includes a 

calculation of a constant XpM value, CNTPM, that would result in a sightline that 

just meets the contrast ratio and visibility criteria. Any particulate matter 

concen&ation greater than C has the potential to result in ground-level 

sightlines oriented in another horizontal direction from the crossplume and not 

meeting the input sibtline criteria. Meeting the criteria depends on XpM values 

along a particular si&tline direction. For example, if centerline X;,, values drop 

very slowly as downwind distance increases and the plu~ne is very nmow, an 

upwind-downwind sightline may fail to meet the criteria at a downwind distance 

for which the crossplurne sightline does meet the criteria. To adopt a conservative 

approach to this problem, the user can consider any downwind distance with 

particulate matter concentraations greater than CmPM as a distance that has a 

potential roadway safety problem. 

It is uncertain whether all visual cues necessary for safe driving are adequately 

accounted for by the VSMOKE crossplume sightline model. VSMQm visibility 

and contrast ratio estimates should be interpreted very cautiously. Such estimates 

are far from "proof' that safe driving conditions are assured at a given distance 

fiom a fire. A safer, conservative approach would regard VSMOKE estimates as 

indicators of potential smoke-related low visibility problems at a given distance 

fiom a prescribed burn site. 

VSMOKE provides an estimate of the atmospheric capacity to disperse smoke 

emissions fiom prescribed bming activity over a given area to acceptably low 

average concentrations domwind of that activity. The Dispersion Index (DI), 

developed by Lavdas (1986), is used to provide this estimate. Dispersion Index 

combines the effects of transport windspeed, stability class, and mixing height on 

smoke concentrations fiom areawide forestry-prescribed burning. This index is 

closely related to ventilation factor (i,e., the prodwt of transgort windspeed times 

mixing height), a parameter widely used in making operational prescribed-fire 

smoke management decisions. Accounting for the rate of dispersion within the 

mixing layer by analyzing vertical dispersion coefficients as specified by stability 

class, DI provides a more ~omplete description sf atmospheric dispersion than 

vermtilation factor. Because stability class is wed, BI can be detemined in stable 

conditions when mixing heigfit and ventilation factor are undetined. Therefore, DI 

provides vdues that can be disedly conzpared between daytime and nighttime 

conditioms, wKle ventil ation factor c s capability is particularly 

when dealing wittt. blems associated with smoldering 

smoke sowces in high humidity conditiom wical of most nights in the Eastern 

U~&d States. 
DOWNWIND DISTANCE FROM FlRE (meters) 

TOWARD FIRE HAS 8 DIRECTLY AWAY FROM FIRE 
Dispersion Index is mathematically derived directly from widely used U.S. EPA 

dispersion models and measured or infend characteristics of plume rise from 

prescribed f"11;w of low to moderate intensity. A uniform area emission source 

reprasenting the aggregate effects of prescribed-fite activity as typically conducted 

in the Eastern United States is used within an adaptation of the U.S. EPA 

~Ihatological dispersion model (Busse and 1973), Tlre preser3bdfire activity source occupies a 50 by 50 km2 area (approximately 1,000 square 

miles), and the adapted dispersion model calculates smoke concentration for an 

"impact analysis point" at the downwind edge of the area (fig. 12). The model 

allocates presrribed-f~e smoke evenly between substantial plume rise and very 

limited plume rise. The plume rise smoke is assumed to be well mixed within its 

"effective depth." This unifom mixing is a result of vertical dispersion processes 

and the aggregate effect of a number of bums of varying intensity be 

within the area. The effective depth corresponds to the fit if 

phere is unstable or near neutral. If the atmosphere is stable, effective 

depth is determined from characteristic presnibed-fire heat emission rates and 

repmmtatiw atmospheric conditions. The 

EFFECTIVE PLUME 

. DEPTH MAY 

INCREASE DF NOT 

RESTRICTED BY 

MIXING HEIGHT 

112 OF SMOKE 

WELL MIXED 

If2 OF SMOKE 

MIXES FROM NEAR 

GROUND ONLY 

WIND 

DIRECTION 

(AT GROUND AND MIDPOINT 

OF DOWNWIND BOUNDARV) 

R&un 1%-Dispion index edssions model as used in VSMOm. 
plume rise represents smolde~ng. ms smke is &spas& from the geund with 

an initial vefiicaf djspersion cwffident of 30 m. Atmsphe~c dispmsion p 

xe integatd over all trampod distances from s+tEn the zea of prescGbed-f"u1e 

actic.ity to tk "imp;lct analpis point" to estimate a caamtration value firr tkal 

point (a. 12)- The inverse of the smoke concesrlPatisn at that pa-lnt is the value 

usd far Df, 

calculating smoke mn~entration resulting from plum-~se-associatd 

smoke, the effetilpe depth is assumecl to be mstant owr the mkke ma. men a 

~xing height is themaltgr &Fur& (i.e., in unstable or raeutral con&tions), tlais 

assumption is identical to that used in VSMOm plume calculations for smlre 

unifody nalxe$ wjttk the ing laym. Iln stable conditions (no themally 

ing height), calculk-tting tbe effect of dispersion prmesses over the 

entke area is descrjlbd by Lavdas (1986). By considering d;ispersion over the 

entire wea md using a single effective height, the calculation prmss is geatly 

shplifid and is malogeus to the pmss us4 for vertically well-mixed smoke. 

Values of effe~tive height are set by the folloGng schenne. When ~xing height is 

defined in unstable (IP" neutral - daflirne copldtions, eff~tive height is set to the 

~xing height but is rest~cled to a ~nimum vdue of 240 m. At night, when 

slable condidons often prevaiisresralthg in an bmdf"med ~xing height-the 

effwtiw height of tbe unifom smoke lap is dependent on stability class. I6 th 

stability class is netlr neutral- night, the depth matches tlhe ~xing height (or 

dqth of the isothemal lagfer), but is restrict& to a range between 240 and 600 m. 

If the stability class is slightly stable, the unifm smoke hyee depth is 180 rn. If 

the stability class is moderateXy or extremely stable, the depth is 150 m. 

The smoke that is very limited in plum rise in the DI mdel undergoes a Gaussian 

dispersion proGess (Lavdas 1986). The initial vefiical dispersion cwffircient for 

this smk is set at 30 m, regardless of atmosphe~c stability conditions--unstable, 

stable, or neutral4ay or night. The effxt of stability on the smoldening smoke 

causes it to disperse at the rate appropriate to the assigned stability class. The 

functional &penden= of tbis dispersion on domwind distame is accounted for by 

numerical inkgation of the appropriate functions for verti~al dispersion 

coefficient over the range of distances from witEn the: prescfibd-fire activity 

sour= area to the "ianpacl: arralysis point." 

With all other ktors equal, the unifom area source in figurn 12 may be thought of 

as prescribed burning activity. 'Fhe smoke coneenkration at the impact analysis 

pclirtt my be thought of as the averaged aggregate effmt of tbe burning activity 

As the simple inverse of that conentration, DI: can be used as a rneasuse of the 

buming activity possible without &verse efEeGts from add4 smke 

concentrations. In the absence of other sowces of atmospheric pollution, the 

relalionship between Df and amptable burning ~"civity ~ght- be ons side red 

dkwtly proportional. IIomver, the limitations of DI must be reeognjized. For 

instance, bwause the smoke e~ssion source is defined as unifom and covers a 

wide ma, DI is not an approp~ate analysis tool for smoke effwts from an 
Low Visibility 

Occurrence Risk 

Index 

individual plme (unless that plume hppns to be 50 h-about 3 1 miles wide!). 

The VSMOm plume model, not DI, should be used for single plume analysis. 

The direct relationship between DI and es~rnated smoke comentration at the 

impact malysis point (fig. 12) irnplies that any mauimum smoke comentration 

level set for that point would not be violated when burning activity is doubled on 

occasions when DI is doubled. Because DI is calculated only on a proportionate 

basis, the concentration criterion is never explicitly specified; therefore, DI does 

not directly specify an absolute acceptable level of burning activity. Designed to 

enable aea-wide dispersion comparisons among weather re@mes, DI is well suited 

as a basis for allocating smoke emissions from prescribed-fire activity over areas 

ranging from subcounty to multicounty sizes (about 25 to 10,000 square miles). 

Table 4 interprets DI values. The interpretations are based on climatology, criteria 

for air stagnation, and prescribed weather conditions for controlled burning. 

Although they have been used for several years, these intefpretations may be 

regarded as preliminary. With experience and expertise, the interpretations may be 

modified and the ranges redefined to best fit the fire and atmospheric patterns of a 

specific area. 

Dispersion Index does not account for high humidity effects on visibility in smoke. 

Dispersion Index strictly describes areawide atmospheric capacity to disperse 

pollutants to or below some acceptably low criterion value for smoke 

concentration. In high humidity, a smoke concentration sufficiently low from an 

air quality assessment standpoint may generate or worsen a hazardously low 

visibility in smoke and fog. However, when DI is combined with relative humidity, 

it appears to help characterize the frequency of low visibility occurrences resulting 

from fog, smoke, or both. 

VSMOKF, provides an estimate of risk of low visibility and smoke hazard on 

roadways by using the LVON (Lavdas and Hauck 1991). Low Visibility 

Occurrence Risk Index is a semi-quantitative, indexed variable that expresses the 

estimated level of risk for roadway visibility hazard with integer values from 1 to 

10. A value of 1 denotm the lowest (standard) risk category and a value of 10 

denotes the hi&est risk category. The 10 categories allow considerable flexibility 

ty for developing multiple management strategies. Low Visibility 

Occurrence Risk Index values are determined directly from DI and relative 

humidity (RH). Low values of DI combined with very humid conditions result in 

the highest LVORI values, while moderate to high DI values combined with 

moderate to dry humidity conditions yield low LVORI values. The top part of 

table 5 shows LVORI values as a function of DI and RH. The bottom part 

presents interpretations of these values. 

Low Visibility Occlfnrence Risk Index is derived &om an analysis of the observed 

proportions of low visibility in fog, smoke, or both as reported by the Florida 

Highway Patrol at over 400,000 roadway accident sites during 1979-8 1. The 
accident reports were statisticay stratified with respect to the estimated wathm at 

the time and place of each accident. The weather est were based on National 

Waer Service surface and upper air observations ns near or smounding 

each accident site. Twice daily, upper air reports were used to est 

height and transport windspeed at each sdam weather station at ch 

available observation (ranging hour to every 3 hours). The surface 

station data were weighted to tions appropriate for the county where 

each accident occd. V~ous weather parmeters in the accident sites data base, 

including estimates of windspeed, humidity, stability class, and DI, were correlated 

to the proportion of reports of low visibility in smoke ador fog found in the 

Florida Eghway Patrol data base. Relative humidity and DI showed the strongest 

and most physially coherent association. The s.tratification of the data matched 

expectations based on physical mwhanism (i.e., as RH increased, DI dmeased, or 

both, the proportion of low-visibility reports by the Florida Highway Patrol 

unifody and smoothly inaeased). In general, statistical proportionafity testing of 

the data showed very strong statistical significance. With the exception of 

categories 1 and 2, each LVORI category is statistically distinct from any other 

category. Tests involving DI as the sole indicator of risk were used as the basis for 

distinguis~ng betwwn category 1 and category 2. No need for any additional 

categories emerged from similar tests involving only RH. 

Table 5 shows the relationship between risk of visibility hazard on roadways and 

RH and DI. Only a small degree of smoothing was performed on the raw accident 

data to generate the tabular values shown, and this data smoothing was restricted 

to selecting values of DI and RH to group together. The smmtbness of response 

of LVORI with increasing RH and decreasing DI lends considerable credence to 

the asswiations found in the analysis. In the bottom portion of table 5, a low 

LVORI value indicates a relatively low proportion of accident reports with fog, 

smoke, or both; a higher number indicates an increased proportion and the 

likelihood of increased risk of roadway hazard resulting from low visibility in 

smoke. Lnw visibility in Florida is a relatively uncomon event. The highway 

patrol reported fog, smoke, or both in only 3,235 out of a total of 433,649 

analyzed accident reports during the 3-year period. In these reports, 604 included 

smoke, 2,972 includd fog, and 341 included both smoke and fog. This proportion 

can be as low as about 1 in 1,000 for LVORI = 1 (or 2) or about 150 times higher 

when LVORI = 10 (table 5). 

Udafiunatdy, data used to develop LVORI are scww, expensive, and tim 

eonsu~ng to proeess; LVORT has not been verified by an independent data set. 

Until verification, this index must be regadd as a statistically well-behaved, 

reasonable, worbg hypothesis that should be used cautiously when mhg fire 

management decisions, The literal use of the level of risk given in table 5 is not 

ended. 

Visibility studies using observational data at National Weather Servi~e and 

a1 sites have geld& eally &Berent proportions of low visibiGty 

risk. For example, much higher low-visibility proportions in very hu~d 
conditions were found by Lavdas (1974) in a study of fog in coastal Georgia. Part 

of this difference is attributed to scatter and uncertainty associated with probable 

enom in rhe weather %slimat= at aaident sires often gmgrap1bic;rlly remote front 

wather stations. 

hident &a sets m be inaccurate bmause law enforcement officials are not 

meteoro1ogical sbservations. The highway patrol &ta were 

saer:nd to remove reparts with obvious problems (e.g,, da\ilight conditions 

repond for a 1 :00 a.m. accident). Occasionally, fog would be reported with 

spuriousty low W estimtes. nese repol;ts wHe ampted under che assumption 

that fog-like conditions were present md perhags a result of maporalion after a 

show or generation i>lF a glum that appeared more like fog than smoke. 

mese reports received respect, bwause roadway safety is an wedding 

consideration in my report law edorcernent officers m&e. 

mted by VSMOm, LVOIRII is given as a 

ndex givling a risk category, somewhat in the sme 

fashion that an hsurmce risk category might be dete~ned and des~bd. Tbe 

hsurmce risk analogy even appfies to the sow= of tfie data: a lwge number of 

mident teports and the assmiation of cireumstanees sunounding the accibts. 

The user shoul$ cw the insurance risk analogy one step ful;ther: avoid the high 

risk categories and lower the risk as much as practicable. 

h additional degree of caution is rquked when using EVORI for prescribed fire 

applications with any regbe ~eatly &ssElar to that of Florida. 

Subjective experience in an operational forestry weatk forwasting enviroment 

indicates tlhal LVORE can be directly applied in the bunnid elirnates witEn a few 

hun&& ~ks of tbe: Gulf of Mexico (wpm, fmtnok 1, page 5)- However, tbe 

appfi7.cabiEty of DI and W rdationshirps &clad& in the cunent version of LVORI 

in 0th loeations is less main. Synoptic-scale weather patterns conducive to fog 

md low visibility in smoke ape lilre1y to have varying relations~ps ta locally 

&sewed vveather pametm in va~ous climatk regions. Hmardcrusly law 

visibiljty response h elhatic areas here t,he Erquency dist~butions of reldive 

humidity, slability, ~ndspd9 and perfraps cloud sow ae mmkdly different 

@roan thoise found in Rod& nay be somewhas: &fferent, Frquencies of low 

visibity with respmt to BI aJld REJ wuId vq, or muld be mare closely 

msohdiabd with other metwrologid pNameters. 

Sig~ficiirnt dif-ferenms in tihe relatiolrskps sk;: also mely on a much smaller spatial 

scale, For exmpie, fag prone mms dB probably expe~ena more h,7zwdorss 

conditions when the nearest BM &sewations iindic- "marginal" conditions or 

~sk, heas dam (or ""dmMt"")om water bdes 09: very wet ueas, such 

as svvmps sr &gHy ~gatd agrieulturd tracts, can expefience incrased md 

more se~oras visuzla obstmction, Smbtk ten&sa featllres cm hduee low visibiEty as 

nwIy saturatd & is ford to fise sljnd cwl, Vegetative arrd sea ciiafferenm earn 

cause si@f"reant &f erenss in atmosphe~c radiatbnal cmding rates and ioc=d& 

flow pagems that can be hpor&mt h low visibility events resulthg from fig, 
smoke, or both. In a very hu~d enviroment, 

slightly different chmteristics can trigger rap 

atmospheric pollutants can force widely varyin 

constituents in smoke and other sources contain nuclei capable of 

droplets in a process closely analogous to cloud fornation. The 

ture of atmospheric pollutants at a given lmation will 

determine whether conditions must be saturated with respect to a planar surface of 

pure water for such smoke and fog clouds to fon~ which is the rmon why LVORI 

risk levels (table 5) start to rise when RH is mnsiderably less than 100 percent. 

Installing VSMOKE NO installation steps are necessary prior to ru&g VSMOKE. VSMOW.E~ 

is run like any FORTRAN 77 program on the host system. However in the PC 

Ins taung environment, an appropriate library of mathematical fwtions and processes must 

be present. 

If VSMOKE.FOR (but not VSMOm.Em) has been supplied, the program must 

be compiled and linked like any other FORTRAN 77 source listing in the host 

envimment. h the PC environment, the source code must be brolcen into 

segments before compilation can take place. Compiling the main program, input 

§&ions, and output sections separately has given satisfactory results. 

Testing 

Test Procedures 

Running the test cases will help asmain whether the program is functioning 

properly on the host system. VSMOKE is a cumplex FORTRAN 77 algorithm 

that uses many routines from various software libraries. The exact nature of the 

executable instructions depends on the various interactions between the compiler, 

linker, math co-processor (if present), operating system, and computer hardware. 

1. Copy fiIe VSMOKE.111 onto file VSM0m.m. 

2. Run VSMOIE. 

3a. If a message indicating "END OF RUN FLAG = T" is displayed on the screen, 

compare output file VSMOKE.OUT to file VSMOKE.011. 

3b. If the message indicates "END OF RUN FLAG = F," or no message appears, 

a serious problem has oecmed. First check that VSMOW.DPT properly matches 

4. Note any discrepancies between the output files. 

5. Delete file VSM0KE.m. 

6. If you wish to save the output file, rename VSMOKE.OUT; otherwise delete it. 

7. Repeat steps 1 through 6, using files VSMOKE.122, VSMOQ.133, and 

VSMOKE.14. 
8a. If diserepmcies are nonexistent or inconsequential for the four input files, 

sfully passed the teisting p e on your host systenn. 

8b. If discrepmcies are large and cannot be resolved, notes of the exact natme of 

the &serepancia for the mmt test runs will help the authorized VSMOE 

Pro agent identify and correct the problem. 

The test cases are designed to test ranges of input values, exercise the various 

flags, md force the execution of all non-error pathway logic vvithin VSMOKE. 

The values assigned to the input variables in the test cases should not be 

considered re~ommen&tions for any operationd use. 

File VSMOm.111 contains the Fit test case: 

60 

'VSMOm.111 TEBT CASE 1 :' 

36.000 76.000 5.0 1994 3 26 8 15.5 1.0 T T T 0.02 

0.25 

40.0 240.0 40.0 250.0 14.0 4.0 4.0 2.0 T 0.60 

14 -500. -1. 30 T 11500. 2.0 0.0 0.0 30.0 2.5 

15 -500. -1. 40 T 2 1500. 4.0 0.0 0.0 40.0 3.0 

16 -500. -1. 50 T 3 1500. 6.0 0.0 0.0 40.0 3.5 

17 -500. -1. 60 T 4 1500. 8.0 0.0 0.0 40.0 4.6 

18 -500. -1. 70 F 4 500. 4.0 0.0 0.0 50.0 5.0 

19 -500. -1. 80 F 5 240. 2.0 0.0 0.0 40.0 5.0 

20 -500. -1. 90 F 6 240. 1.5 0.0 0.0 35.0 4.0 

21 -500. -1. 100 F 7 240. 1.0 0.0 0.0 30.0 3.5 

14 4.OE+01 l.OE+Ol 5.OE+01 +0.60 

15 4.OE+01 l.OE+Ol 5.OE+01 -1.00 

16 4.0E+01 l.OE+Ol 5.OE+02 -0.90 

17 2.OE+00 4.0E+01 1,OE+00 -0.75 

18 l.OE+OO l.OE+OO 1.OE-02 +0.50 

19 1.OE-01 l.OE+OO 1.03-03 0.00 

20 1.OE-02 1.OE-01 O.OE+OO +1.00 

21 1.OE-04 1.OE-02 1.OE-05 +0.80 
File VSMOm.f22 contains the second test case: 

62 

'VSMOKE.122 - VSM0KE"S SECOND TEST CASE SOmmEm BALF TO LX)m 

-35.067 -145.383 -9,25 2002 04 13 6 11,O 1.0 T F F 0.0 0.0 

640.0 1920.0 15.0 50.0 11.0 0.75 1.00 0.25 F -0.75 

2002041311 -46. 845.6 20 T 2 240, 0.5 0.0 30.0 0.0 0.0 

2002041312 +123. 992.3 25 T 2 7000. 10.0 0.0 30.0 0.0 0.0 

2002041313 +32. 1013.25 30 T 3 1500. 8.0 0.0 30.0 0.0 0.0 

2002041314 50. 1065.3 16 T 3 1500. 4.0 0.0 30.0 0.0 0.0 

2002041315 44. 888.0 9 T 4 500. 4.0 0.0 30.0 0.0 0.0 

2002041316 60. 700.0 37 T 4 5000. 4.0 0.0 30.0 0.0 0.0 

File VSNIOm.133 contains the third test case: 

60 

'VSMOKE.133 - TEST CASE 3:' 

30.000 90.000 6.0 1993 1 4 1 14.00 0.0 F T T 0.05 0.125 

0.0 0.0 0.0 0.0 13.50 0.0 0.0 0.0 T 2.0 

1993010414 59. 1014.0 55 7. 9 13000. 850. 3.5 0.0 0.0 125. 8.0 

1993010414 30.0 2.0 15.0 -0.95 

file VSMOm.Idl.4 contains the fourth case: 

66 

'VSNiOKE.I44 TEST CASE 4:' 

35.583 76.217 4.0 1996 5 4 21 12.75 1.0 F F T 0.25 0.25 

10.0 50.0 17.0 315.6 13.0 4.0 6.0 4.0 T +0.60 

1245 75. 1012.4 33 3. 0 99999. 1200, 3.6 0.0 0.0 30.0 2.5 

1345 79. 1012.4 29 5. 199999. 1500. 5.8 5.0 10.0 35.0 5.0 

1445 82. 1013.0 27 6, 4 99999. 1750. 4.7 30.0 40.0 100.0 20.0 

1545 90. 1011.9 18 5. 10 25000. 2645. 6.3 100.0 100.0 30.0 4.0 

1645 69. 1013.8 75 37. 10 600. 1000. 23.5 10.0 10.0 20.0 3.0 

1745 78. 1012.7 48 16. 10 15000. 1500. 8.0 0.0 0.0 40.0 3.0 

1845 81. 1010.5 39 6. 10 5000. 1700. 5.9 5.0 5.0 50.0 8.0 

1945 74. 1009.8 44 3. 10 15000. 700. 2.8 20.0 20.0 0.0 0.0 

2045 73. 1010.4 48 5. 10 7000. 500. 5.0 50.0 0.0 0.0 0.0 

2145 70. 1010.4 52 0. 10 4000. 300. 1.5 90.0 0.0 0.0 0.5 

2245 68. 1011.9 56 0. 7 4000. 240. 1.0 65.0 5.0 5.0 1.0 

2345 63. 1012.3 64 0. 8 4000. 240. 1.0 0.0 0.0 40.0 3.5 

0045 61. 1012.0 69 3. 5 99999. 240. 1.5 0.0 0.0 0.0 0.0 

0145 59. 1012.2 70 4. 4 99999. 240. 2.2 0.0 0.0 0.0 0.0 

0245 57. 1012,5 78 9- 2 99999, 240. 4.6 1.0 1.0 10.0 2.0 

0345 54 1011.8 85 10. 0 99999. 240. 5.1 5.0 3.0 20.0 3.0 

0445 53. 1011.5 89 7. 0 99999. 240. 5.7 5.0 3.0 20.0 3.5 

0545 52. 1011.7 93 6. 4 99999. 240. 6.1 0.0 0.0 40.0 4.0 

0645 53, 1011.6 100 0, 10 0. 400. 2.0 0.0 0.0 40.0 4.0 

0745 57. 1010.2 94 0. 6 500. 600, 5.5 0.0 0.0 30.0 3.0 

0845 68. 1009.0 76 0. 1 99999. 900. 7.1 0.0 0.0 30.0 3.0 
A brief des~p~oa of the files used in VSMOm follows: 

1. VSMOm, a docmentation file for progsm VSMOm, vvhich 

should be consdtd before VSMBm is run. 

2. VSMOm.FO ntains the VSMOKE EO 77 so- de tistkg 

for use in the Pe or saar mkoment. To mpik the progm, this sowce 

Listing is copied, then broken into three sections: the 

prog* the 

indirectly by 

(subroutines GMOW and VOW 

indirectly by subroutine CHOW). 

2%. VSMOmm,FOR-ntains the FOR 77 soww listing for the 

progm of VSMOW. 

2b. VSMOmW.FOR--contains the FOR 77 sow listing for the mut2c. VSMOmOT.FBR-aths the FORT '9'7 sow= listing for the 

output-related subp 

3. VSMOWMN.OBJ-ntains the object code generated by cornpiling the 

* propam of VSMOKE. 

4. VSMOBP.OBJ-nbins the object code generated by compiling the input 

related subprogam of VSMOKE. 

5. VSMOmOT.OBJ--contains the object code generated by compiling the 

output related subpro&ram of VSMOKE env 

6. VSMOm. ntains the executable code generated by linking the thee 

VSMOm object code files, VSMOKEMN.OBJ, VSMOEP.OBJ, and 

VSMO~OT.OBJ. 

7. VSM0KE.m-is the single input file for VSMOI(E; it must be present when 

VSMOm is run; tting and required data we describd in WMOm Input 

Requirements. 

8. VSMOm.OW-is the output file generated when VSMOm is run; any data 

hedidy present in this file at run tirne are lost. 

9. VSMOm,I**+where ** is a multiple of 1 I, up to $4) are sample kput files 

included for testing pqoses. 

10. VSMOm.O**+where ** is a multiple of 1 1, up to 44) are output files, 

wrnesgon&mg to eaeh sample input file, inGluded .for testing purposes. 
Source Cod 

Characteristics and 

Structure 

1 1, VSMOm.SCR-a pseudescratch output file generated during a VSMOm 

run; if the final ouQut file, VSMOU.OU?", c be successfirlly completed, this 

file may be kept at the end of the mn; othemise, it is deleted during the ntn aRer 

VSMB=,OfJT is generated. 

VSMOE uses FORT 77 "List-directed" input from file VSMOKIE.PT in all 

cases. List-directed output is used only to echo-print the contents of the input fife 

and diagnose some errors. The remaining output is formatted. 

All input required to ntn VSMOW is provided through file VSMOE.CPT. 

'Xist-directedt?ead statements input data to this file. The VSMOW.PT data 

must be given in the exact order and fomat described in hput Requirements. 

Nearly all output generated by VSMOKE is witten onto file VSMOKE.OUT. 

Formatted output sbtements assume that FO 77 fomatted output printing 

conventions are followed by the host system. When generated by formatted 

WMTE statements, the VSMOm.OUT output file consists of up to 127 printed 

characters per line. Up to 60 lines per individual page are generated within the 

period-by-period and worst-case analysis sections of the outpul. The output file 

begins with an echo-print section. The length and characteristics of this section 

depend on the length sf the VSMOE.PT input file and how host computer and 

sohare systems handle FO 77 list-directed ouqut. 

somce code for VSn/lOE is contained in file 

VSMOm.FOR. The source code hlly meets ANSI Standard X3.9.1978 

77 propamming lmpagekll langu Sf (1978). The code 

is thoroughly commented, both with respect to pro logic and underlying 

mathematical and scientific bases. 

VSMOm consists of 34 subprogram units, including 1 main, 1 3 subroutines, 19 

functions, and 1 blwk data unit. The main progm, VSMOKE, opens the input 

and output files, VSMOE.PT and VSMOKE.SCR, and calls the controlling 

ATA and CHIOUT. All input is handled in 

subprogram EMSPRI. Subprogram 

ility class is not available in the input file; 

ATA calls EMSPRl when period-by-period emissions related daw are imluded 

in the input file. With the exception of echo-printing of input data, any necessary 

enor diapstics, alnd an end-of-run message, all VSMOE-controlled output is 

initially Mled in CKIOUT or WOCOUT. Subpsogrm CH[EOUT calls 

WOCOUT to pracess worst cmditionf found among all ansllyzed periods. Galled 

by the main pmgam, subprogam VOUTPR generates final output. 

Double precision mathematical processing is invoked selectively within 

TI0 and EDEPTW and completely in subprogrm QNO 

Double precision is required within these subprogams unless at least roughly 60 

bits are available for amal single prwision real nurnber pmcessing on the host 
. Single precision p is used exclusively for floating point 

sing in dl other subprogr 

Fipe 13 provides a 12-page ovmiew of program VSMOm and nmes 

subpropam, identifies inputloutput points, and shows major loops and decision 

points of the proparn. 

Subprogram Descriptions A brief desdption of each subprogram follows: 

alizes program name and version number for the 

ns files VSM0m.m and VSMOm.SCR, calls 

W, and VOWPR, and stops the run. During a 

normal run, the only output generated by the main program is an end-of-run 

message to the screen. In case of errors, other messages may be generated. 

mATA-subroutine reads and enor checks fire and weather data, then directly 

or indirectly determinnes weather and emissions variables for each period; if needed, 

calls subroutine LSMKWX to determine stability class; calls either subroutine 

EMSPRI or EMSPRC, depending on whether period-by-period emission rate 

related values are to be read in or calculat&. This subroutine also generates echoprint output to VSMOm.SCR; in case of error, calls subroutine VOWPR. 

ILSMm-subroutine reads and error checks weather data when that data does 

not include stability class: dete~nes stability class from the data and solar 

ephemeris variables; calls subroutines ASTRO and SUNANC, and references 

function ITW; generates echo-print output to VSMOKE.SCR. In case of 

error, calls subroutine VOWPR. 

EMSPH-subroutine reads and enor checks period-by-period emission rate 

related data; generates echo-print output to VSMOm.SCR; in case of error, calls 

subroutine VOWR. 

EMSPRC-subroutine calculates period-by-period emission rate related data.'' 

DAm-finction determines day of year from year, month, and day. 

ASTRO-subroutine mmputes solar ephemeris vdables for a given day. 

SUNANG-subroutine computes solar elevation angle. 

function determines stability class from surface weather and solar 

elevation angle. 

l2 S MSPRC was by G. Lav& Meteorologist, USDA Forest Service, Juliette, GA, and Clay D. Gaespie, 

formerly a systems analyst with the Georgia I?omtry Co-sion, Dry Branch, GA, 
VSMOKE (MAIN) 

/ SET HEADER 1 

r OPEN VSMOKE.SCR 

a CALL CHIOUT (6A) 

Figure 13-Flowchart of FORW 77 Computer Code for VSMOKE, Version 1995012Wontinued on pages 60-70. 
I PRINT KTITLE 1 

Figure 13-Flowchm of FORTRAN 77 Computer Code for VSMOm, Version 19950 12&--Gontinued. 
I RETURN 1 (1) 

Figure 13-Flowchart of FORTRAN 77 Computer Code for VSMOKE, Version 19950128--Continued. 
LSMKWX 

/ SET CALENDAR & CLOCK 

RESET CALENDAR 

GET EPHEMERIS & 

SUN ANGLE 

+ 

( READ NUMDWX (I) . . . BKGCOA (I) I 

PRINT NUMDWX (I) . . . BKGCOA (I) 

/ SET ETABA (I) I (ITURNR) 

I RESET CLOCK I 

Figure 13-Flowchart of FORmN 77 Computer Code for VSMOKE, Version 19950128--Continued. 
Figure 13-Flowchart of FORTRAN 77 Computer Code for VSMOKE, Version 19950 1284ontinued. 
SET HOTFLX, 

FCSTDDY, FC2ER1, 

F62ER2, CLOCK 

SET DUMMY RATE 

NUMBER 

SET FCONSM, EMTQH (I), 

EMTQR (I) 

1 SET EMTQPM (I). EMTQCO (I) 

Figure 13-Flowchart of FO 77 Gompukr Code for VSMOm, Version 19950 128-xontinued. 
(SETSGV, 

SIGMAY) 

SET ATMOSPHERIC DENSITY I (RHOMIX) 

NWR, CRITGT, CRITLT, 

ORI, KDIADJ, KLVADJ) 

(XW, XVZ) 

SET BACKGROUND 

& SIGHTLINE 

VALUES 

WRIE HEADER, KTlf hE 

Figure 13-FIo~~ha of FO 77 computer code for VSMQm, Version 19950 128-<ontinued, 
ISTANCE LOO 

+ SET PLUME RISE (GABRIZ) 

.t 

SET SIGMAS (SIGMAY, SIGMAZ) 

(YFCTR, YRATIO, QNORML) 

I SET ZFACTR I (ZFCTR, OZREFL, EDEPTH, QNORML) 

I SET DLFCTR I 

DETERMINE SMOKE PM & CO 

M CONVERT CO TO PPM 

DETERMINE TOTAL PM & 

Figure 13-Flowchart of FO 77 CompuW Code for VSMOE, Version 19950 128-Xontinued. 
(VSDRYG, Y RATIO, 

QNORML, BEXTFS) 

$. I WRITE SHORT FORM 1 I BACKGROUND VALUES I 

RESET CLOCK / 

CALL WOCOUT 1 (7) 

Figure 13-Flowchart of FO 77 Computer Code for VSMOKE, Version 19950 12Wontinued. 
/ WORST \ 

I WRITE RH,WARNING 1 (NO WARNING I 

I WRITE END VSMOKE MESSAGE / 

Fipe 13-Flowchart of FO 77 Compukr Code for VSmE, Version 19950 12 
VOUTPR 

REWIND VSMOKE.SCR 

OPEN VSMOKE,OUT 

T 

EPEAT LINES . . . UNTl 

END VSMOKE.SCR 

I INCREMENT SCR COUNTER I 

CHECK FOR PAGE SKIP 1 

N 

Figure 13-Flowchart of FO 77 Computer Code for VSMOm, Version 19950128--Continued. 
SEARCH FOR LAST 

(DELETE) 

Figure 13-Flowhart of FORTRAN 77 Computer Code for VSMOE, Version 19950 1284ontinued. 

RETURN (1) 
CHOW-ubroutine con&ols calculations and output of selected input and 

intermediate variables, DI, LVORI, domwnd centerline particulate matter and 

carbon monoxide concenbations, and dry weather crossplume visibilities and 

contrmt raios, on a pefiod-by-period basis; calls subroutines SETSGY, UFCW 

DSPWR, and VSI>RUG, and references fun 

nVmJ, XVY, XVZ, BEXTFS, GABW, 

detemine period-by-period data; all period-by-period output is generated directly 

to file VSMOKE.SCR; and calls WOCOUT to generate vvorst-case output from all 

periods analyzed, 

function computes density of a moist atmosphere; vapor pressure is 

detemined following equation (8) of Buck (1 98 1). 

DSPNPR+Lavdas 1986) subroutine cornputes DI; references functions CRITGT 

and CRITLT. 

CmGT+Lavdas 1986) kction aids in calculating DI. 

CNTLT4Lavdas 1986) hction aids in calculating DI. 

DMDJ-_character function deternines DI adjective corresponding to its input DI 

value. 

WON-hction calculates LVORI. 

mVmJ-_chmacter function deternines LVORI adjective corresponding to the 

input LVORI value. 

GABmhction computes plume rise at a given downwind distance resulting 

from the sensible heat emissions from a fire (Briggs 1975); slightly modified as 

noted in coments within the code. 

SETSGY-subroutine presets values of horizontal dispersion coefficient for a 

wide range of downwind distances for later use in "virtual distance" calculations, 

and references function SI 

XVY-hction computes horizontal "vi 1 distance" associated with a given 

horizontal dispersion coefficient. 

SICMAY-hnction computes horizontal dispersion coeficient. 

YFCTR-subroutine computes the effects of all horizontal dispersion processes 

for a point or line sou= and references hction IT0 for a "significantly 

long" line sowce only. 

TI ction computes ratio of concentrations &om a fi 

those from an infinite line source, and references hnction 

under portions of the nomal distribution curve. 
XV ctim connptltes ve~ieal "vimal dis$tanceW msociated with a given 

vertical dispefsion coefficienl. 

SlG ction computes vertical dispmion coeEcient, 

ZFCm-hetion computes the eRec& of all vefiical dispersion processes for the 

variety of possible initial vertical plume configurations possible in VSMOKE, and 

references hctions OZWFL and EDERH, 

OZmFL-hction cornpules the eflects of vereical exponential terms in the 

Gaussim plme equation's "reflections" terns (earn the e;round md top of the 

mixing lwr) for a sowee md weepfor at aniy hei@ between the @ourad and tap of 

the mixing layer. 

IEDE ction computes the "effective depfi" of a some with emissions 

i~tidly uniformly dispersed to some dep& in &e veeical and then subsequently 

acted upon by Gaussian dispessiosl pmesses (tke "effective depeh" is relative to 

he ns & a ground-level receglor only), and references h&im 

bin asea mder po~ions of the nemal dis~bul;ion ewe. 

ubmuline compws dsy wealher horizon&1 crossplume visibiliw and 

csnhrwt rdio for a given downwind diswee resulting from a single smoke plme 

and consm backgowd, referewes hetion BEXTFS to abaihm extinction 

coeffiicient, md reerences function 

BEXTFSbction computes extinction coeficieml using the relationship 

aceording to Tan- (1982) as modified by Tangsen in 198% (fig. 14, fornote a, 

page 84). 

ouble precision diclnction that deternines the aea of lhe slandard 

normal distribution thrat lies behveen a point x and "qproaching infiniw," here 

the sign of x and "approaching infinity" are the same. 

BDSD lock data subprogram tbt sets all domwind dismces used in 

VSMOU; these range &om 1 m to 1000 km. 

routine processes and hdles olalput for worst relative humidity, 

cul- matter and cabon monoxide concentrations, and dry 

weaaer crossplme visibilities md contrast ratios; ~Eerences hctions IML) 

and UVAjDJ; and generates outgu'E to VSMOm'SCIR. 

&routine; opens and generates the final OU~W file, VSEVIO~,OUT, 

from data in the pseudo-scratch outpa file, VSMOE,SCfg; generates screen 

output only if it encounters an error. 

Source Code Revision r research or hare applications of VSM&)ti=E may evenmlly dictabe that 

alternatives to the Briggs (1975) relationsEps be med to estim* pluxne rise* Tbe 

curTed vesion of VSMOm is restricted to the Briggs fomtalas. However, 

VSMOm is desiped to make revisions to its plume rise ~alcul&ion procedwes a 

straiglltfo~vvard process, Plume rise calculations me pe~omed in one hetion, 
VSMOKE Input 

Requirements 

. 'Fhe sole referen= routine CHOW. Userdesign4 subprogram raltematiar be add4 ts tk existing de. 

A mntrol stmewre to seIwt the fise subprogam should also be 

added witk subroutine CHOW at the poht where Gm 

sele~tion among alternative plume fise subprograms can b 

by addkg a new user inpur: vafiak>lc. Ipl addition* if any of the user's plume rise 

routines @end on data not inclad& in the VSMOa input v&ables, pmvision 

tbr bcluding and prmssi~ the additional data would also be nmssary, 

hy eEf8t-t: to revise the methds used in rdSM8m to either &st~bute the smoke 

lhak rism or deteene its imp;.lct on dom~nd ground-level concentrations is not a 

si~lgk process, Any sig~fieant changes to the grogrm methodology wuld 

requke extensbe revision to and thorough testing of a number of subpm 

the VSMOB FORTIRM 77 code. 

To use alternatives to the Pasquill-Gifford-Turner systerra to detedne dispersjion 

coefficients in VSMOm wmld rquke a program revision, VSMOE is 

design& to m&e revisions to its dispersion cwffieieat calculation tec~ques 

(bcluding incoqoration sf a selection methdology) a straigh 

Alternative subprograms to the cunent $ispersion cmfficient 

SIGMAV and SIGMM, should be provided. Alternative sub 

inverse functions, WY and XVZ, wfiich calculate ""vi&rral dis 

rqukd. References to all four fundions should be revised by including a 

selmtion structure to control the subpmgram references. One reference to exh of 

the four functions is made in. subroutine CHIOW, One additional reference to 

SlGMAU is mrade in subroutine SETSGY, wkieh prms a, values used to obtain 

horizontal virtuat distmces. Revising tbg: melhod of obtaining a, would probabIy 

also involve an alternative to subroutine SETSG ne referenee to SETSGU is 

made in subroutine GMOW, Dynam3c control of the dispersion coefficient 

selection process can be a~Eevt=d by adding approp~ate user input vslriables. In 

addition, provision must be made for adding any input variables (such as wind 

variabiLity coefficienb) rquired by an alternative schem. 

Any user hoddgeable in pro@ ng scientigc models in the FORTIRM 77 

Impage should be able to m&e these revisions. However, careful attention 

should be given to tbe effeets of plume rise, dispersion coefficient, sr any other 

revisions to VSMOm on the model" '%attam line," Le., its gound-level 

emcentration and sightline related estimates, behrh: using any revision(s) in an 

olperational envkonment. 

Beeause all VSfLZOm data ;ape input through FORTRm 77 list-directed 

MAD statements, users must be pa~icufarly fa~lisrr with the quirements 

associated with T;1ORTRM 77 list-dk~te$ input on their system. 

kr;chnique allows considerable flexibility, system Mendent mtes not defined by 
Input Overview 

ANSI (1978) can dfwt the p of VSMOm. Moreova, care must be 

exercised to ensure that all variables appear proper order and according to 

ted ing is mntrolled by the input 

vs. AL vs. CmRBCmR). 

The input fie VSIMOIKE.m must be available to the executable progam at the 

VSMOm run. is free to generate the data vvithin 

by any conveni before VSMOm is run. htemdiate 

"worhg" files will be nmssw if automated pre-processing programs are to be 

used to generate a subset of the rquired data. That subset would then be merged 

g required data before VSMOm run time to meet all input 

ts. Althou& the intefity of the data within VSM0IKE.m is 

a VSMOm run, input Hes should be archived under unique 

names and copied to VSM0m.m when a VSMOKE run is to be rn 

VSM0m.m becomes a de facto working fie when these operating s 

are follow&. 

The input file contains variables that give processing instructions, describe the fire, 

specify its atmospheric envbment, and set criteria for acceptable fm~ke and 

roadway visibility nnanagement. A sig~cant proportion of the data are input on a 

period-by-period basis. To some extent, the layout of the data depends on the 

values of two LOGICAL variables: LSTBDY and LQREiAD. 

Because all user input to VSMOKE is through FORTRAN 77 list-directed read 

sktementts, the following rules of this input process are most likely to affect the 

VSMOKE user: 

1. Variables file must agree in type (REiAL, 

LOGICAL, or with the variable input list in t tatement. 

2. Generally in VSMOB, variables should be separated by a coma or one to a 

few blank spaces. 

3, An end-of-record mark (e.g., a new line in an input file would usually be 

detected as an end-of-record mark) is generally treated as a variable separator, 

unless it is part of a C CTER variable (enclosed within bracketing 

apos trop ha). 

point is optional within a variable that has a whole integer 

value. 

5. Powers of 10 exponen~d notation (e.g., 1.35E+05 or 0.135E+06, for 

135000.0; and 1.35E-04 or 0.135E-03, for 0.000 135) may be used to specify a 

le, Judicious use of this notation form my result in mare accurate 

representation of the REAL value wi& VSMOKE under certain conditions. 
6. A decimd point is illegal within an 

Input Variables 

7. A plus sign (+) is optional witkin either a REAL or 

8. A min~ sign (-) must be used as necessary within a or 

variable or within the exponent of a REAL variable. 

9. A LOGICAL variable is specified as T or F; TRUE or FALSE or .TRUE. or 

.FALSE. are also acceptable. 

10. AC CTER variable is delineated by apostrophes ('), which are not 

counted as part of the C TER variable; if an apostrophe is a part of the 

CmCTER variable adjacent apostrophes ('I); only one becomes part 

of the C CTEiR variable. 

11. The lengthofac CTER variable in the input file should not exceed the 

specified length of the corresponding CHARACTER variable in the input list of 

the REXI.3 statement (in VSMOKE, the only CllARACTER input variable is 

KTITLE which can be up to 72 characters long). 

22, The input file C CTER value may be shorter than the specified length of 

the corresponding CE-IARACTER variable in the input list; blanks are used to "fill" 

the unused positions of the CHARACTER variable (e.g., using '12' in 

VSMOKE.PT for KTITLE causes positions 3 to 72 of KTITLE to be blanks). 

Progming language FORTRAN Standard X3.9.1978 (ANSI 1978), as 

implemented on the host computer system, should be consulted if questions or 

problems arise associated with specifying a variable for the VSMOKE input 

process. 

The following input variables must be included in file VSMOKE.m. These 

variables are considered on a line-by-line basis, with each line corresponding to the 

execution of a READ statement in VSMOW. Input lines with multiple 

noncharacter data items may be broken into two or more shorter lines where the 

break between the lines serves as a variable separator within the input file. 

Input line #I-Read the number of lines per page to be used in the output file; in 

ATA, the READ statement appears as follows: 

where 

WAGE = INTEGER number of lines per page of output to be generated within 

final output fife, VSMOKE.OUT; must be within the range 60 to 66. 

Input line #2-Read title of run; in subprogrm ATA, the READ statement 

appears as follows: 
72, Title of run, up to 72 characters; apostrophes(") 

and after the title in order to codom to 

CTER data. 

input Eine #3-Rad place and time of fire, input weather data for 

emissions data, and sightline cr;itefia; unless othedse noted, v t as 

REAL variables; in subprogram ATA, the READ statement appws as 

f0Uows: 

where 

ALAT = htitude in decimal s north; valid range is -90.0 to +90.0. 

ALONG = Longitude in decimal degrees west; valid range is -240.0 to +240.0. 

N = Time zone in decimal hours behind UTC (i.e., Greenwich), EDT = 

4.0, EST = 5.0, CDT = 5.0, CST = 6.0, etc., with fractions allowed for locations 

such as Neurfotlndand; valid range is - 1 8.0 to +18.0. 

WFAR = INTEGER, year (leading 19- or 20- optional). 

ER, montfi of year (January = 1, 

day of month. 

ER, number of periods in simulation; valid range is 1 to 100. 

mSTRT = Start time of simulation in decimaf hours, relati 

and IDAY; any value is acceptable, but the usud range is 0 

f the intern& between adj 

haws; das WHOD = 1, VL must be at least 

0.0001 hm; if WNOD = 1, supply a d 

LSmDY = LOGE&, TRUE!, if stability dass and daylight data are to be input; 

E if progrm must Galculate these variables. 

y va3ue means any vdue legal for the type of vatiable in the inptlou@ut ht. The value is d into the 

used. 
LQmBL) = LOGICAL, mm if period-by-period total emission rates, total 

sensible heat emission rate, and proportion of emissions subject to plume rise for 

each NPRTOD are to be input; FaSE if program must calculate these varia6les. 

LSICm = LOCICAL, TRUE if crossplume sigfrtline variable estimates (visibility 

and contmt ratio) are needed; FALSE if not neede 

cdculatiom can save significant computational time. 

CCOCRT = Critical contrast ratio upon which crossplume visibility estimates are 

based; 0.02 is used for airport visual range; a somewhat higher value might be 

appropriate for the general population of licensed drivers; a much higher value is 

required for appreciating scenic vistas; not used if LSIGEFT is FALSE, but a 

value must still be provided; if LSIGHT is TRUE, the valid range of 

CCOCRT is 0.000001 to 0.999999. 

VISCRT = Visibility criterion for roadway safety or other intended purpose in 

miles; for roadway safety, set it to at least 0.0947 miles (500 feet); other 

reasonable values for roadway safety include 0.125, 0.25, 0.5, and 1.0 miles; not 

used if LSIGHT is FALSE, but a dummy value must still be provided; if LSIGHT 

is TRUE, VISCRT must be at least 1.OE-07, and no greater than 9999.99 miles. 

Input line M-Read fire and smoke characteristics data; unless otherwise noted, 

values are input as REAL variables; in subprogram INDATA, the READ 

statement appears as follows: 

where 

ACMS = Area of fire as a smoke source in acres; zero or negative specifies point 

source modeling. 

TONS = Total mass of fuel consumed in short tons; not used if LQREAD is 

value must still be provided; if LQREAD is FALSE, TONS 

must be non-negative. 

EFPM = Emission factor in pounds per ton for particulate matter; in the current 

version of VSMOKE, "particulate marter" may mem total or my size class, but the 

input value of EFPM must be consistent with the input value($) of BKGP 

see U.S. EPA (1 985-90) for appropriate values; not used if LQREAD is TRUE, 

y value must still be provided; if LQNkD is FALSE, EFPM must be 

non-negative. 

EFCO = Emission factor in pounds per ton for carbon monoxide; see U.S. EPA 

(1 985-90) for appropriate values; not used if LQmBD is TRUE, but a d 

value must still be provided; if LQNAD is FALSE, EFCO must be non-negative. 
= Sa~ time of fire in decimal hours; relative to U, MO, and DAY 

(usual rmge, 0.0000 to 23.9999). 

THOT = Duration of convective period of fire in decimal hours, beginnirzg at time 

; not used if LQmm is mw, but a value must still be provided; 

if LQWm is FALSE, mOT must be non-negative, md mOT must not exceed 

TCONST, 

TCONST = Dmtion of comtant emissions period in decimal hours, beginning at 

; not used if LQBEm is TRUE, but a value must still be 

provided; if LQmm is FALSE, TCONST must be non-negative, TCONST must 

be at least as great as THOT, and TCONST + TDECAU must exceed zero. 

TDIECAY = Exponential decay consmt for smoke emissions in decimal hours; the 

pplied beginning at time, ( + TCONST), as in: EXP 

+ TCONST)) / TDECAY), TSN is the cwent 

simulation time in VSMOKE; not used if LQMAD is TRUE, but a d 

must still be provided; if LQMm is FfiSE, TDECAV must be non-negative, 

and TCONST +TDECAY must exceed zero. 

LGMSE = LOGIC&, TRm if plume is =sued to rise @&ally to its final 

height as it travels downwind; FRLSE if plume is assumed to i 

its final rise. 

RFK - Proportion of emissions subject to plume rise; +I.O, denotes all emissions 

rise to the height predicted by plme rise equations for a stack (Brigs 1975) and 

undergo model dispersion prwesses initially from that height only; zero denotes no 

plurne rise and dispersim is initially Erom ground level only; a positive &tion 

denotes rhe plme is initially splil: between full plume height and ground level; a 

negcttive fiaction denotes thal the fising proportion of smoke (as expressed by the 

absolute value of WK) is initialiy unifomly distributed in the vertical Erom 

ground level to the Briggs (1975) height md then this unifom vertical distribution 

is subjected to model dispersion processes: as it moves downwind, the remaining 

smoke is dispmsed fiom ground level (if -1.0, all smoke is initidly unifomly 

distributed in the vefiieal, if -0.5, half is initidly unifom and the o&er half starts 

o om gomd le-vel); not used if LQWAID is TRE, but a d y value must still 

be pmvided; if LQmm is FUSE, &e valid range of WRC is -1,0 to +I -0; a 

value of H.6 is wed by SFFLP (1976) md described by Lavdw (1878); m 

unpublished mti1ysis ofthe L8vdm da& shows &at a wlue of --8-75 yields an 

improved fit. 

]Loop throu* pe~ds, ming Z as &e index vafiable, reading pefiod-by-period 

wea.clher dalta; he bp& dala list includes dayti&t md sabifiv elms; the data are 

kxssumed spehonow vvith the dues of %--EBSTRT and and must be 

syn~honous with fie optid period-by-pedod emissions dm; unless orhernisei 
not&, values are input as RlEAL variables; within the appropriate IF block and DO 

loop in subpropa ATA, the READ statement appews as follows: 

where 

ECER, this pesiod's weather data number to aid in 

file bm&eping. 

TTA(I) = Tgs perids temperature at the surEace in degrees Fahredeit (a value 

approaching or below absolute zero, is., less tban -459.0 F, is interpreted as 

defaulting to &e U.S. Standard Atmosphere value for sea level, 59.0 F). 

M(T) = Tlhis period's atmospheric pressure at the sudae in millibars (mb) (a 

value approac&ng or less than zero, i.e., Iess tban 0.1 mb, is bteqretd as. 

defaulting to the U.S. Standad Atmssphere value for sea level, LO 13.25 mb). 

EGER, this period's relative humidity in percent; valid range is 0 to 

100. 

LTOFDU(I) = LOGE&, set to TRW if this period is after sulnrise and before 

sunset; athewise, set to 

ISTABA(I) = ZPJTECER, this period's stability class (Tmer 1 964); valid range is 

1 to 7, 

where 

1 = extremely unstable 

2 = moderately unstable 

3 =r slightly unstable 

4 - nea neutral 

5 = slightly stable 

6 - mdmately stable 

7 = ext;remely stable 

ing height in meters; vdid range is 1.0 to 1W00.0 

m, 

UA(T) = This period's transport wbdspd in meters per se~ond ws); mst be at 

last 0.1 dse 
A@) = This pe~ds "initst' horizontal crosswind dispersion at the sou= 

in meters; must be non-negative, 

erids '"tialtl'hvertid dispersion at the source in meters (not 

TQR(T) plme rise related effmts); must be non-negative. 

BKGPMA(T) = This pepids backgound concentration of pahtjculate matter in 

per cubic meter (pg m3); in the current version of VSMOKE, 

"particulate matter" may tal or any size class, but the input value(s) of 

BKGPMA(I) must be the input value of EWM (if LQRIEAL) = 

E) or with the input value(s) of EMTQPM(T) (if LQREAD = TRm); must 

be non-negative. 

BKGCOA(I) = This petids background concentration of carbon monoxide in 

parts per miEon (ppm); must be non-negative. 

EME IF LSTBDY = S #5 to (NPMOD + 4): 

Loop though perisds, using I as the idex variabk, reading period-by-pepid 

weather data; the &put data list does not include daylight or stability class; the data 

are assumed sp~hronous with the values of mSTRT and VL and must be 

synchronous with the optional period-by-period emissions data; unless othemise 

noted, values are input as REAL variables; within the appropriate DO loop in 

subprogram LSM-, the FtEAD statement appears as follows: 

where 

DVVX(I) = INTEGER, this period's d-y weather data number to aid in 

file bm&mp&g. 

TTA(I) = This period's temperatwe at the surface in degrees F&e&eit (a value 

approacbing or below absolute zero, i.e., less than -459.0 F, is interpreted as 

defaulting to the 17.3. Stmdard Atmosphere value for sea level, 59.0 F). 

PPA(I) = This period's atmospheric pressure at the surface in dLibars (a value 

approacbg or less than zero, i.e., less than 0.1 mb, is interpret4 as defaulting to 

the U.S. Standasd Atmosphere value for sea level, 10 13.25 mb). 

ER, this period's relative humidity in percent; valid range is 0 to 

100. 

(Note: The next three values are used to help det this period's stability 

class, stored in array ISTABA.) 
WSSFG = This period" suf7Face windspeed in knots; must be non-negative. 

ICOWR = NTEGEK this period's opaque cloud cover in tenths; valid range is O 

to 10. 

CEIL = This period's cloud ceiling height in feet; if ceiling is unlimited, use 99999. 

feet; if sky is obscured, use vertical visibility; must be non-negative. 

A(1) = This period's mixing height in meters; valid range is 1.0 to 

10000.0 m. 

UA(1) = This period's transport windspeed in meters per second; must be at least 

0.1 Ids. 

TA(1) = This period's "initial" horizontal crosswind dispersion at the source 

in meters; must be non-negative. 

OZWTA(1) = This period's "initial" vertical dispersion at the source in meters (not 

including RFRCEMTQR(1) plume rise related effects); must be non-negative. 

(I) = This period's background concentration of particulate matter in 

micrograms per cubic meter; in the current version of VSMOKE, "particulate 

matter" may mean total or any size class, but the input value(s) of BKGPMA(1) 

must be consistent with the input value of EFPM (if LQREAD = FALSE) or with 

the input value(s) of EMTQPM(1) (if LQREAD = TRUE); must be non-negative. 

BKGCOA(1) = This period's background concentration of carbon monoxide in 

parts per million; must be non-negative. 

EP!D LSTBDY BLOCK IF.. .THEN.. .ELSE. 

IF LQREAD = TRUE; TmN IbPUT L S # WPERIOD + 5) to (2 * NPRIOD 

+ 4): 

Loop through periods, using I as the index variable, reading period-by-period 

emission rate related data; data are assumed synchronous with the values of 

HRSTRT and HWTVL and must be synchronous with the period-by-period 

weather data; unless otherwise noted, values are input as REAL variables; within 

the appropriate DO loop in subprogram EMSPRI, the READ statement appears as 

follows: 
where 

VSMOKE Output 

Output Overview 

CER, this pefiod"s d emission rate related daa number 

to aid in file bookkeeping. 

EMTQPM(1) = This period's Lotal some emission rate of particulate maller in 

gas per second; in the cunent version of VSMOm, "'particulate mal-ter'bmay 

mean total or any size class, but the input value(s) of EMTQPM(I) must be 

consistent with the input valw(s) of BKG (I); see U.S. EPA (1985-90) for 

fuler infomation; mwt be non-negative. 

EMTQCO(1) = Tbis period" total source emission rate of carbon monoxide in 

gas per second; see U.S. EPA (1985-90) for Mber idomation; mwt be nonnegative. 

EMTQH(1) = This period's total sensible heat emission rate in megawa'its; catz be 

determined by total rate of fuel comumption times sensible heat released per unit 

mass of kel conswed; must be non-negative, 

EMTQR(1) = Proportion of emissions subject to plunne rise; if c1.0, denotes all 

emissions rise to the height predicted by plume rise equsltions for a sbck (Briggs 

1375), sund undergo model dispersion processes initially from that. hei&t only; if 

zero, denotes no plume rise and dispersion is initially Erom ground level only; a 

positive fiaction denotes the plume is initially split betvveen hll plume ki&t and 

gound level; a negative fi'action denotes that the rising proportion of smoke (as 

expressed by the absolute value of Eh/lTQR(I)) is initially unifomly distributed in 

the vertical from ground level to the Briggs (1975) height, and then this unifom 

vertical distribution is subjected to model dispersion processes as it moves 

downwind, the remaining smoke is dispersed fiom ground level (e.g., if -1.0, all 

smoke is initially unifomly distributed in the vertical, if -0.5, half is initially 

u~fom and the other half s from gound level); the valid range is -1 '0 to i-1.0; 

a value of M.6 is used by SFFLP (1976) and described by Lavdas (1978); an 

unpublished analysis of the Lavdas data shows that a value of -0.75 yields an 

improved fit. 

Em LQWm BLOCK H". 

VSMOE output is primarily generated to one file, VSMOm,OUT. An end-ofm message ;and any error diagnostics are also output to the screen. Men 

VSMOMIE is mf any pre-existkg data within VSMOm,BUTT are lost. If the 

conten& of VSMOKE.OUT m of cmtinuing imp0 ce, archiving the output 

dala before mother VSMOKE aun is performed is necessary (e.g., by copying Ihe 

conlent& of VSMOm.OUT to anoIher file). 

In the environment, a "scratch'koutput file, VSMOm.SCR, holds VSMOKE 

resul& mti1 the model m is vi ly complete. At the end ofthe ma, 

VS1410ME.SCR results ase processed inw he ut Gle, "SSM[O~.O~= 

Tliis allows the program to we '"column 1 FO 
folfovved in the PC envhonment, rtn intemdiate scratch file is used. As a scratch 

file, VSMOD.SCR should be trwted as a "'resewed file rime." Any pre-existing 

file with that nae will or&arily be lost duhg a VSMOm run. 

The final output file layout is intended to fxilitate the design of post-prwssor 

progam while maintaj.ning an eas y-to-read 1 32-colum printout. Distinct 

delirniters, readily detwted either by eye or by automated post-processor, designate 

either a specific section of the output or a notice of an error condition. men a 

printout is generated, the delimiters double as page headers. 

The line and column placement of output values is as consistent as is practicable, 

depending on the values of only two LOGICAL input variables. A flag near the 

end of the output file indicates the proper ion of the VSMOm run. The flag 

should reduce the chance of error in job s that include VSMOm output as a 

component of further automated processing. 

The following discussion describes how the output data in file VSMOKE.OUT is 

organized (see fig. 14 for an outhe). Output consists of three sections: (1) an 

do-print of the input data read in by the model, (2) a period-by-period analysis, 

and (3) a worst-case sumq analysis constructed from the period-by-period 

output. The length of the output is dependent on the input data. The length of the 

do-print section (one or more pages) depends on. the amount of input data read 

by the program and the characteristics of the host computer system and software 

packages. The layout of the echo-print swtion is also processor dependent, but the 

layout of the period-by-period and worst-case s ons is controlled by 

the VSMOm program. Usually, the majority o .OUT data consists of 

the period-by-period analysis. Each analyzed one page of output, 

consisting of up to 6,800 characters. The worst-case su generates the ha1 

page, consisting of up to 4,200 characters. 

The most important factor in the length of the overall output file is the number of 

periods analyzed. AZthough this value is specified by the user, the number of 

periads actually anaZyzed depends on the number of perids with significant 

e~ssions (i.e., a pe~d with few or no smoke e~ssions generates no direct 

output), When mmhg the maximum nurnbw of periods p 

VSMOm has generated an output file of nearly 750,000 bpes. 

In a Eew unusual situations, the ouhplat bat may vary from the outline (Eig, 14). 

Wen VSMOE detwts ara enor, a new final gage is geaerated, givhg a Biagnosis 

of the emor mn&tion, Should the hput vaiues fczr , MRSmT, mWm, 

and WMOD result in m model sirnulation time oeeurr;ing vvhile tk kc: is 

ernirtting a sigkficattt mount of pollutant cmstituents, no gerjid-b y-pefiod 

nnalysis is generated. Should any individual pefid kk signi 

any pollu&nt, no autput is generated hr that pe~sd. bdly, in the PG 

envkament, sbuld problem mus in openjing or ~tiing the ha1 ouwt file, 

VSMOMLi.OW, thr: pseudo-scratch output file, VSMOME;.SGRB is saved for user 

inspeetion, 
I. Etial section: 

An "echo-print" section of the data suecessklly read frm bhe VSM0m.m input file. This seaion is at least one 

page in length and may be longer, depending on the amount of data read into the VSMOKE run. For example, if 

the input value for number of perids is high, the echo-print section will be lengthy. 

II. Period-by-period section, one page for each analyzed period: 

A. Emissions, weather, and other data used to determine the concentration and (optional) sightline estimates for 

the given period. 

B. Dispersion Index and associated adjective. 

C. Low Visibility Occumence Risk Index and associated interpretation. 

D. A table giving smoke impact variables with respect to 3 1 logaribicdly-spaced domwind distances; each line 

consists of data specifying the downwind distance, with other variables including: 

1. information about the rise or depth of the smoke plume. 

2. Information about the horizontal and vertical crosswind extent of the smoke. 

3. Pollutant constituent concenration estimates (pafticdate matter and carbon monoxide) resulting from the 

single fire plus background level. 

4. Optional single fire, dry weather crossplume visibility estimates, based on the input background particulate 

matter concentration, the input contrast ratio criterion, the estimated plume characteristics at particular 

downwind distances, and assumptions based on the work of Tangren (1 982; 1985"). 

5. Optional single fire dry weather contrast ratio estimates, detemined in a m er similar to crossplume 

visibilities and applicable for a sightline length equal to the input visibility criterion. 

UII. Worst-case smary section? one final page: 

A presentation of the wont-case RH, Dl, LVORI, pollutant constituent concentrations, and optional dry weather 

crossplume visibilities and contrast ratios found in the period-by-period analysis. This is followed by a "run OK" 

flag and an end-of-nut. message. 

" Pemnd wm~cation. 1985, C.D. T eal statiftician, USDA Forest Sewice, *-theastern Forest Expriment Sbtion, 320 

Green Street, Athem, GA 30602. 

Fiwe 1-utline; of VSk40m output file, VSMOE.OUT 

84 
Interpretation 

Error Handling 

Sect-iort I: Eeho-print-This section starts with Line 1 as a header which consists 

of a series of colons (:), follovved by program name and version number (e-g., 

SMOm - WRSION 19950128) wbere the version number is in 

mat, followed by a series of colons. The fomat of the rest of 

dependent on the host system, because it is prharily generated by 

77 List-directed output statements. 

Section 2: Analysis for each period with sig~ificant emissions-The first line 

of each page in Section 2 contains a header similar to Section 1; however, a series 

of plus signs (+) replace the colons. In general, NPRIOD periolilpages appear in 

Section 2. If the f~e does not generate at least 1 miGrogrm per second of either 

particulate matter or carbon monoxide emissions in a given period, that period is 

omitted. Therefore, Section 2 output may be entirely omitted for a VSMOE run 

(e.g., if TFlRE and/or HRSTRT are erroneously input, resulting in all periods 

occurring before the start of the fire). Barring such unusual circumstances, the 

line-by-line output of each period appears as described in Appendix III. 

Sec~on 3: Worst-case analysis for all periods with significant emissioras-The 

worst-case analysis is constructed entirely from the period-by-period analysis of 

Section 2. Each variable is individually considered. For example, the worst 

particulate matter concentration 1 .000 lun downwind is not necessarily from the 

same period as the worst carbon monoxide concentration 10.000 km downwind. 

The first line of the final page contains a header similar to the headers used in other 

sections, but a series of equals signs (=) replaces the colons or plus signs. 

Following the worst-case analysis, the final message in this section gives the value 

of the program's "run OK" flag and an end-of-run message. The value of the "run 

OK" flag is also output to the screen. When no errors are encountered, this 

message is the only VSMOf(E-controlled output to the screen. Barring unusual 

circumstances, the Line-by-line output of the worst-case andysis appears as 

described in Appendix III. 

In the case of errors with files or input data, the program will give diagnostic 

messages and kill the run. A final page of output, in effect an Error Section with a 

distinctive header line to signal an enor condition, is generated as described in 

Appendix III. A brief error message is also output to the screen. The scren 

message will also inform the user if the pseudo-saatch output file, 

VSMOICE.SCR, bas been saved for inspection. If possible, the final output file, 

VSMOE;E.OW, will be generated during the em handing process, &Gating thtt 

need to keep the pseudo-scratch file. 

Enor conditions detected and handled by the host system may also be encountered. 

In these cases, the output to the files and scren \;vill be host system dependent. fn 

case of processor-controlled errors, the pseudo-scratch output file, 

VSMOKE.SGR, will probably be available for inspection, wble the ha1 output 

file, VSMOKE.OUT, may not have been opened vvhen the mr condition 

OCGU~~. 
The resulb of a VSMOm nm are primarily intended to give an overview of the 

probable air quality impact from a single foresw-prescribed fire, The effects of a 

user-specified uniform backgound level of pl1ubn.t~ are included in the 

VSMOU estimates, Because the physics of sound fires in general are 

suEciently similar to that of forestry-prescribed fires, VSMOKE can be used to 

estimate air quality impact fkom sources such as wildfires, aacultural burns, and 

other ground-based open combustion sources. 

VSMOKE, smoke concentration estimates are applicable at ground level along the 

downwind centerline of the smoke trajectory. No attenngt is made in VSMOKE, to 

geometrically specifj the trajectory of the smoke. The direction of smoke transport 

must be detemined independently. Allowance must be made for both the 

horimntal width of the smoke plume and the variability and uncertainty associated 

with wind direction. The width of the smoke plume depends on both the area of 

the smoke source and the horizontal dispersion of smoke. 

Table 2 presents the horizontal "spread angles" of the plume for which the 

concentrations of a point source fall to 0.1 times the centerline value. The spread 

angles are a hnction of stability class and downwind distance. VSMOE output 

displays the stability class (ISTAB) used during each analysis period in the tabular 

infomation in the top one-fifth of each analysis period/page. The VSMOKE: 

downwind distance dependent tabular output in the lower two-thirds of each 

analysis periodlpage also includes estimates of the horizontal dispersion 

coefficient, a,, with respect to downwind distance for each analysis period. For a 

point source, smoke concentrations from a fire will fall to 0.1 times the centerline 

value at appro~mately 2.15 times the value of a, to either side of the centerline. 

The relationship for a finite line source is more complex but may be approximated 

as a horizontal displacement of 0.5 times RM plus 2.15 times a, to achieve a fall 

to 0.1 times the centerline value, where ELM is the effective line length of the 

pollution source. ELM is displayed in the tabular infomation in the top one-fifth 

of each analysis periodlpage. 

To account for wind vdations and fluctuations, the user must allow for the 

probability that concentrations and visibilities similar to VSMOKE centerline 

estimates will occur at considerable angles to the nominal smoke trajectory. At a 

minimum, an assumption that the centerline concentrations could occur 30" to 

eitfier side of an obsenred steady domwind direction is required, as has been 

d by SFFLP (1 976) and Wade and Lunsford (1989). A recent study 

of wind direction pmistence aJld forecast accura~y (Lavdas 1993) indicates that at 

Maicon, GA, the probability of the wind maintai~ng adirection within 30" on an 

hour-to-how basis is only 71 percent. Of course, wind direction is even less 

consistert.l wih forecastf. Because the National Weather Service forecasa are 

given to only ei&t compss pints (i.e., northeast, east, southeas%, sourb, 

southwesg west, no&west, md north), a fmast cm never be more precise than 

within plus or minus 22.5". Moreover, the Lzbvdas (1 993) sady found tbat early 

mo~ng Eore~ae were ""corn&" 'only 37 per~enl of& time md were '"off by onb 

one categsry" m additid 40 prcent of &e time. 
Frquently at night, wind heetion e inmnsistent, or a 

"near calm'hr "light and variable'" Smoke can still be 

distances by light h re@=. For instmm, an 

anemometa witl not turn until es about 3 knots - fast enough to 

transport smoke over 50 knz ( les) during a night. In these eases, 

eoncentric circles about the fire site are the only reasonable basis for setting 

geometrically based criteria for smoke mnagement decisions. Use of concentric 

circles is also required for stronger dspeeds with highly variable dlreetions and 

for any magement situation where wind &=tion behavior is unertah. 

VSMOKE smoke conmntration estimates are given for particulate matter and 

carbon monoxide at 3 1 logarithrnicdy spaced downwind distances, ranging from 

0.1 to 100 km (table 6). The conmntration estimates apply at ground level along 

the centerline of the smoke trajwtory and include the user input background 

concentration values. Particulate matter in VSMOKE is "generic," i.e., it may 

include all total suspended particulate matter or only a portion of the total (e.g., 

PM10 - particulate matter of 10 micrometers (pm) diameter or less, or PM2.5 - 

particulate matter of 2.5 pm diameter or less), as reflected by the user's input 

values for input background wncentration array, BKGPMA, and the eanission 

factor for the fire, EFPM, or the emission rate array, EMTQPM. Thus, the user 

determines whether the VSMOKE particulate matter concentration analysis applies 

to total suspended particulate matter, PM10, PM2.5, or some other fraction of 

particulate matter. 

VSMOKE particulate matter concentration estimates are given in micrograms per 

cubic meter, the same units currently used to define the National Ambient Air 

Quality Standards (NAAQS) for PM10. The short-term NAAQS standards are the 

most applicable to prescribed fire analyses using VSMOKE. The shortest term 

NAAQS standard for PMlO is 150 pg m-3, averaged over a 24-hour period, not to 

be exceeded more than once a year. Even if VSMOm estimates of PMlO 

conentrations are in excess of the NAAQS 24-hour average standard, that 

standard may still be met by the analyzed fire. The geometdc locations 

experiencing centerline smoke concentrations will often change during the course 

of a burn. Moreover, many, if not most, prescribed fires will not affect air quality 

for a full 24-hour period. 

However, NMQS values are not specifically designed to safeguard roadway 

safety. A smoke impact remining within the PMlO NAAQS limits may cause a 

relatively short-lived, but sevae, impact on roadway visibility, even if the relative 

humidity is less than 70 percent. For example, a fire causes a 6,000 pg m3 PMlO 

concentration for 30 minutes, but then the smoke goes elsewhae, the fire goes 

completely out, or both, leaving a background of 20 p g m-' for the rest of the day. 

The 24-hour average concentration would be less than 150 pg m-', but the peak 

eonentration muld be high enough to cause a signikmt visibility hazard, In 

hurnid conditions, hazardously low visibilities are higfily probable with much lower 

PM l 0 smoke concentrations. 
VSMOKE carbon monoxide (CO) concentration estimates are given in parts per 

million with respect to mass per unit volume of CO and the total atmospherethe 

same units currently used to define the NAAQS standards for CO. The shortest 

tern NAAQS standards for carbon monoxide are 9.0 ppm for an 8-hour average 

and 35 ppm for a 1-hour average. Near sea level, these values nominally 

correspond to 10,000 and 40,000 pg m3. These standards are designed to keep the 

proportion of GO ~thh the blood of exposed persons below 2 percent. 

Assuming that realistic background and emission factors for both particulate 

matter and carbon monoxide are input, concentration estimates for PMlO will more 

the NAAQS standards than GO estimates in most situations. Fires 

involving organic soils may be an exception. When most combustion in an organic 

soil fie is glowing or smoldering, the emission factor for CO may greatly exceed 

that for any of the regulated size classes of particulate matter. An organic soil fie 

can pose a threat as great or greater to the WQS CO standards than to the 

PMlO standard. 

The downwind dependent crossplume visibility and contrast ratio es tirnates, which 

optionally accompany the tabular smoke concentration estimates, are applicable 

only if the relative humidity is less than 70 persent, At higher humidities, the 

lkelihood of smoke particle size grswh resulting from condensation of water 

vapor increases-thus the scattering and extinction capabilities of individual 

smoke particles can greatly increase. As relative humidity values approach 

saturation (i.e., approach 100 percent), the probability of dense fog occurrence 

greatly increases. Such fogs can be triggered by the presence of only a relatively 

modest concentration of smoke. The LVON can be used as a measure of the 

overall likelihood of smoke problems on a roadway, but must be considered with 

sightline estimates to evaluate the potential hazard of an individual fire. 

Even in low humidity conditions, VSMOKE crossplume sightline estimates must 

be evaluated with care. The relationship between overall particulate matter 

concentrations and light scattering and extinction coefficients is subject to enough 

variation to cause errors in visual obscuration estimates of about a factor of 2. 

Therefore, a given VSMQE visibility estimate could occur with associated 

overall particulate matter concentrations as little as one-half (or as much as 2) 

times the given value. Moreover, VSMOKE visibility estimates are dependent on 

the input contrast ratio crite~on, CCOGRT. Under certain conditions, a small 

change in the input value of CCOCRT can result in a considerable change in the 

crossplume visibility estimate for a given downwind distance. For example, a 

smoke plume may be dense enough to reduce contrast to a value just above the 

criterion-i.e., an individual with eyesight matching the criterion will just be able 

to see though the plume. If the background atmosphere is very clean, objects 

beyond the plume will be dimly visible for a considerable distance beyond the 

plume boundaries. A less keen-eyed observer may not be quite able to see though 

the plume. A criterion contrast ratio set to match that obsemer's eyesight would 

result in a much lower visibility estimate. 
Acknowledgments 

The VSMOKE crossplume contrast ratio estimates are provided for two reasons. 

First, they are to alert the user to the sensitivity of visibility estimates. A contrast 

ratio estimate just above the criterion value should be weighted more heavily as a 

potential hazard indicator than an accompanying visibility estimate that falsely 

seems to provide an ample margin of safety. Second, roadway safety may be as 

comparably dependent on the ability to see the relevant portion of the roadway 

panorama clearly as the ability to dimly see an individual potential roadway 

hazard. In any case, the abiliw of the simple VSMOKE optical parameter 

calculations to characterize driving visibility appear limited, perhaps very limited 

at night. A conservative approach in specifying the input criteria for contrast ratio, 

CCOCRT, and visibility, VISCRT, and in interpreting the output visibility and 

contrast ratio tables is strongly recommended for all roadway-oriented VSMOKE 

applications. 

The DI estimates from VSMOKE have a wider application than most of the other 

output. As an areawide, multiple-prescribed fire smoke management tool, DI 

represents an area source of about 3 1 by 3 1 miles (or rougNy 1,000 square miles). 

However, it may be applied successfully to somewhat larger areas experiencing 

uniform weather conditions or to areas as small as 5 by 5 miles with little 

distortion in its description of the atmosphere's relative dispersive capacity. 

Dispersion Tndex does not apply to conditions within the plume of any one 

pollution source. Thus, DI should be used as a supplement to, not a substitue for, 

the single fire VSMOKE analysis. 

The LVORI estimates fiom VSMOK-E may be applied to either single or multiple 

fire air quality/tra%c hazard management problems. Low Visibility Occurrence 

Risk Index is the only VSMOKE visibility analysis tool that can be currently 

applied without modification in humidities greater than or equal to '70 percent. 

However, LVORI should be used with caution until it can be corroborated by an 

independent data set, particularly in areas with a climatic regime significantly 

different from that of Florida. 

VSMOKE is a computer progam that evolved over many years and is based on the 

work of many individuals. Contributions are acknowledged in references to 

publications and in footnotes. In addition, the author thanks Gary Achtemeier and 

William Jackson, both of the USDA Forest Service, for their helpful reviews of 

this document, and C. Wayne Adkins, also of the USDA Forest Sewice, for his 

assistance in preparing the figures. 
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Appendix IInput Hints 

Line 1. variable 

Line 2 variable 

Input hintsLine 3 variables 

VSMOKE requires values for numerous input variables. Some are quite 

specialized; a few are unique to this model. ;En addition, VSMOm estimates of 

wncentration and visibility can be sensitive to input values, sometimes in ways not 

obvious to my but the most experiend users. Finally, some VSMOIKE input 

variables are deliberately designed to allow running of multiple scenarios. This 

design allows for uncert~ties in the scientific knowledge of fire behavior and 

chemistry, fire interaction with the atmosphere, dispersion and other 

meteorological processes, optics, and psycho-physical perception. These model 

characteristics dictate that considerable thought be given to deteding input 

values. The following suggestions are not comprehensive but give the user a basis 

for determining appropriate input for and uses of VSMOm. 

In general: When the user believes a range of values is likely for any input 

variable, the sensitivity of VSMOKE output variables dictates that the user test for 

all extremes and representative mid-range values of each variable, thereby allowing 

the behavior of VSMOKE to be appropriately displayed. 

WAGE: INTEGER. Number of lines per page of output, restricted to the range 

60 to 66. Any value in this range that matches the host system parameters and 

restrictions may be used. 

KTITLE: CHARACTER*72. The input value need not fill all 72 positions; any 

remaining positions trailing the input value are blank filled. This variable is 

purposely left open-ended, allowing adaptation to a wide range of filing or 

bookkeeping systems. Files VSMOKE.IPT, VSMOIKE.SCR, and VSMOKE.OUT 

are intended to be used only as working files. The user who anticipates 

maintaining a library of input and output files should probably incorporate the 

library file name or other distinctive code within KTITLE to help identify and 

ensure the integrity of each file. 

ALAT, ALONG, TMZON: REAL. In addition to allowing the program 

to determine stability class if needed, these variables serve a useful boofieping 

function. If VSMOE is ever integrated into a system containing automated 

weather input data, these variables might be necessary to help det 

weather from a large data base, The user should be aware that limited error 

checking is pedomed on these variables. Because VSMOKE can be used at any 

location, including those with changing or unusual time zone conventions (e.g., 

near the international dateline or in areas with a fractional hour time zone), some 

values of UONC and TMZON that may appear enoneous at first glance are 

accepted into the program. The valid range for ALAT is -90.0 to +90.0; for 

ALONG, -240.0 to +240.0; and for TMZON, -18.0 to +18.0. 

IYEAR, MO, IDAY: NEGER, Used in detemrining stability class if needed, 

these variables are also useful for booMceeping purposes. No error checking is 

pedomed. Care should be taken to ensure consistency with input values of 

NPRIOD, HRSTRT, HRNTVL, and TFQE. tie the location items, these 
variables may also be required if VSMOKE is integrated with a larger weather data 

base. 

ER. Error checking is used to ensure a value from 1 to 100. A 

large value will result in longer execution times and a lengthier output file. Too 

smU a value may result in missing the period of greatest fire impact. 

HRSTRT: REAL. Input in decimal hours on a 24-hour clock basis (e.g., 12:01 

a.m. is 0.0167,7:30 a.m. is 7.5,2:45 p.m. is 14-75), KRSTRT is referenced to and 

linked with TYEAR, MO, and DAY. When NPMOD is set to 1, the only analysis 

s of , DAY, NPRIOD, HRSTRT, 

Pro . No error checking is pefiomd. 

Values should nomHy be with the range 0.0000 to 23.9999. 

mVL: REfi. hput in decimal hours, l3tNTVL is added to HRSTRT for 

period 2, and added again for each subsequent NPNOD. HlWTVL should be 

comtly linked with WEL4R, MO, DAY, NPRIOD, HRSTRT, and TFQW. 

VL should be small enough to allow analysis of the life cycle of the fire, 

emissions, and weather con&tions during each period of interest. Setting 

VL between 1 and 3 hours should yield satisfactory results from a 

meteorological starndpoi~t for most presc~bd fire situations in the Eastern United 

States. A shorter analysis interval (perhaps 0.1 hour) might be appropriate for 

short-lived or rapidly changing fires. mVL isnot used if NPRIOD is 1, 

although a value must be provided. For NPRIOD greater than 1, error checking 

ensures a value of at least 0.000 1 hours (i.e., 511 8 seconds). 

LSTBDY: LOGICAL. LSTBDY should be set to true only if stability class is 

included mong the period-by-period data in the input file. The value of LSTBDY 

has little effect on VSMOm run tbes. 

LQREAD: LOGICAL. LQREAD should be set to true only if particulde matter 

and carbon monoxide emission rates, total sensible heat emission rate, and 

proportion of emissions subje~t to plume rise are included in the peaid-by-perid 

data in the uut file. The value of LQWAD has fittle effect on VSMOKE run 

time. 

6XZGm: LOSICa* LSEGm should be set to true whenever mossglum 

sighthe mtiirnates are rqukd (i.e., when quantitative mossplume visibility md 

mnt_rwt ratio dl be estinzated). Setting TSICEjTT to false when suGh estimate are 

nsl rquired can shofien nzn. thes by about a factor of 3, 

CCOGRT: ma. A vdue of 0.02 hm hen usd fm 

rnay be too low a eonepast raGo 

Smtt&ng of Eght my dso prove tcs be more ~ticaI for kgItt 

y sitlaations fad by &ersaSt pilob, A value of at least 0.05 

md some &vhg situations hvolvhg glwe, v~ous Ends of 

e, e>s boob may rq&e a much Ggker value, pehhapls 0,25, An 
Input hintsLine 4 variables 

appropriate value of CCOCRT is best determined by specific research studies and 

consultation with such agencies as the National Hi&way Traffic Safety 

Adminisbation. To allow for mathematical testing and wrforeseen applications, 

VSMOKE permits a range of values from 0.000001 to 0.999999. Low values 

relate primarily to target identification; higher ones relate to the quality of view 

along the crossplume sightlines. The laner permits expe~mental use of VSMW 

for assessing smoke impact on scenic vistas. The user should ensure that the 

values of CCOCRT and WSCRT are in the proper relationshipacceptable 

visibility in VSMOKE is defined by maintenance of a contrast ratio of GCOCRT or 

more owr a sightline ten& of at least WSCRT. 

WSCRT: REAL. Values ranging from 1 OS7 miles (about 0.16 

miles are permitted in VSMOKE. Much of this range should be reserved for 

mathematically exercising the model. WSCRT should ordinarily be related to 

specific traffic safety variables such as safe stopping distance. State traffic safety 

agencies often cite a criterion value of 500 feet (0.0947 miles). Other reasonable 

values mi@t include 0.125,0.25,0.5, and 1.0 miles. Visual sightlines of more 

than a mile migfrt be required in some cases, including aircraft operations. 

Protecting scenic vistas would typically require values of several to many miles. 

The user should enswe that the values of CCOCRT and VISCRT are in the proper 

relationshig-accegtable visibility in VSh/ZOKE is defined by maintenance of a 

contrast ratio of CCOCRT or more over a sightline length of at least WSCRT. 

ACRES: REAL. VSMOKE assumes a square area of smoke emissions, 

but generates a line source of length equal to the square root of ACES at the 

downwind edge of the area. Implicitly, rotation of the area is performed by 

VSMOU in case of wind shift. ACRES should ordinarily be equal to the area 

generating smoke emissions during the period of interest-generally equal to the 

area burned during a given fire. A lower value of ACRES may be necessary to 

account for "trouble spots" within a large burn area if smoke-sensitive receptors 

are close. With a lower value of ACRES, TONS (if LQREAD=FALSE) or 

EMTQPM, EMTQCO, and EMTQH (if LQREm=TRIJE) should also be reduced 

correspondingly, and the effects from the remainder of the bum area should be 

deterrnined by adding the results of a second VSMOKE run. If the fire is to be 

evaluated as a point sowce, ACRES should be set to zero or a negative value. 

Point sourGe modeling generally results in the most consewative estimates of 

centerline plume characteristics. Domwind concentration estimates close to a fire 

in VSMOME are only moderately sensitive to AGMS and decrease with the 

square root of ACWS. 

TONS: REAL. Defined as the total mass of fuel consumed by the fire within the 

complete bum area during the toal pel.iod of analysis. TONS is used only if 

LQREAD is set to FALSE. If used, TONS must be non-negative. Past resources 

such as SFFLP (1975) perally used tons per acre to characterize he1 loading 

available for fire consumption. TONS is usually around three times ACRES for 

understory litter reduetion burns. TONS can mge as hi& as rou&ly f 00 times 

ACES for traGts with large piles of forest hels. 
EFPM: REAL. Docmented particulate matter emission faGtors for southern 

forest fbels range from about 15 pounds per ton for dry, highly aerated &el, such 

s, to as much as 200 pounds per ton for some poor combustion smoldering 

situations. The work of SFFLP (1976) was based on total suspended particulate 

matter (TSP), while the latest (1990) Clean Air Act defines particulates by particle 

size. For most forestry smoke analysis, emission factors for TSP may be regarded 

as rougNy equivalent to those for PMlO (i.e., particulate matter of diameter 10 

micrometers (pm) or less). EFPM is used only if LQWAD is set to FALSE. If 

used, EFPM must be non-negative. 

EFCO: REAL. Emission factors for carbon monoxide have been cited by SFFLP 

(1976) as ranging from 20 to 500 pounds per ton in southern forest fuels. Relative 

to the air quality standards in the Clean Air Act, carbon monoxide emissions are 

usually of secondary concern - PMlO standards will likely be broken before CO 

standards are approached. To illustrate, the current l-hour and 8-hour average CO 

NAAQS standards he nominally 40,000 and 10,000 pg mS3, respectively; the 

current 24-hour average PMlO NAAQS standard is 150 pg m-3. One exception is 

important: smoldering organic soils can emit very high amounts of CO and low 

amounts of gMiculates. Because organic soil combustion poses an extreme 

hazard, carbon monoxide analysis is provided in VSMOKE. EFCO is used only if 

LQWATl is set to FALSE. If used, EFCO must be non-negative. 

TFIRE: REAL. Linked to IYEAR, MO, and IDAY, TFlRE (like HRSTRT) is 

input in decimal hours. The user should ensure that linkage between NPRIOD, 

HRSTRT, HRNTVL, and TFIRE is correct. The model simulation clock time for 

any given period is determined by the relationship, TSIM = HRSTRT + (IPRIOD - 

1) * HRNTVL, where TSIM is current model time in decimal hours and IPRIOD is 

current model period under analysis, with IPRIOD ranging from 1 to NPRIOD. 

Any lack of precision in real arithmetic within the user's host system can cause 

unexpected results in the relationship between TSIM and TFIRE. The most 

striking of these occurs when TSIM is calculated to be just less than TFIRE while 

the user is expecting an exact match. For example, HRSTRT = 11 .O, HRNTVL = 

1.0, NPRIOD = 3, and TFIRE = 12.0 may result in concentration estimates for the 

last period only, because TSIM could be internally represented as 1 1.999 ... during 

IPRIOD = 2, when a value of 12.0 is intended. This problem did not occur when 

VSMOKE was run in environments that used the 80387 math co-processor or 

equivalent; however the problem has occurred on other systems. A small margin 

(perhaps 0.0001 hours) should be built into the input value of HRSTRT or TFIRE 

if this problem is encountered or anticipated. 

THOT: REAL. Input in decimal hours, THOT expresses the duration of the 

period begidng at time, TFIRE, when the heat of the fire causes an active 

convection column with significant plume rise for a substantial proportion of 

emissions. After time, TSIM = TFIRE + THOT, any continuing emissions of the 

fire are restricted to ground-level-based dispersion. For lines of fire, an estimate of 

THOT may be obtained by dividing the rate of spread into the distance that the line 

of fire must cover. For piled debris fires, THOT should probably be used to 
characterize the period of active flaming while RFRC or EMTQR should be used 

to help characterize any period when the appearance of the smoke column indicates 

both flaming and smoldering processes. Slight mathematical processor errors in 

model time calculations can came unexpected results in some systems. This 

problem occurs if the calculated model time, TSM, causes a given period to be 

just inside or outside of the convective period when the opposite result is expected. 

THOT is used only if LQREAD is set to FALSE. If used, THOT must be nonnegative and less than TCONST. 

TCONST: REAL. Input in decimal hours, TCONST expresses the duration of the 

period, beginning at time TFIRE, when the total emission rate of the fire may be 

regarded as constant. For lines of fire, TCONST will probably be equal to or 

slightly greater than THOT. For piled debris, emissions from smoldering can be 

high enough to cause TCONST to exceed THOT by a substantial amount (Lavdas 

1982). Slight mathematical processor errors in model time calculations can cause 

unexpected results in some systems. This problem is most likely to cause 

substantial errors at the end of the period of constant emissions and could be 

significant for a given period if TDECAY is set to zero or is much smaller than 

FlRNTVL. TCONST is used only if LQREAD is set to FALSE. If used, 

TCONST must be non-negative and greater than or equal to THOT; also, 

TCONST + TDECAY must exceed zero, 

TDECAY: REAL. Input in decimal hours, TDECAY expresses the decay 

constant for exponential decay of total emission rate of the fire, beginning at time, 

TBGDCY = TFIRE + TCONST. Emission rate at any time at and after TBGDCY 

is expressed as: ERDCAY = ERPEAIS * exp (-(TSIM - TBGDCY) / TDECAY), 

where ERPEAK is the "peak" emission rate of the fire which occurs at time 

TBGDCY, and TSIM is the current model time in decimal hours. For each 

TDECAY hours after time = TFIRE + TCONST, the total emission rate of the fire 

is reduced by a factor of e (becomes about 0.37 of its value at the start of the 

TDECAY period). TDECAY is closely related to the concept of "half-life." The 

half-life of emissions after time = TBGDCY is about 0.693 * TDECAY. 

TDECAY is probably no more than 1 hour (and can be much less) for light fuels 

such as pine needles, grass, and low brush. In aggregate, TDECAY has been 

found to be about 4 hours for buming activity near the Willamette Valley, Oregon 

in the late 1970's (Lavdas 1982). For organic soils, TDECAY can be large enough 

to make the decay concept moot. Such a fire is better characterized by daily runs 

of VSMOKE that assume constant emissions for each day. TDECAY is used only 

if LQREAD is set to FALSE. If used, TDECAY must be non-negative and 

TCONST + TDECAY must exceed zero. 

LGRISE: LOGICAL. LGRISE should be set to true in most cases. Setting it to 

false can cause underestimates of plume impact near the fire. This setting causes 

immediate attainment of final plume height, and is useful primarily when 

comparing VSMOKE results with models that do not use gradual plume rise, such 

as INPUFF, version 2.0 (Petersen and Lavdas 1 986). LGRISE has little effect on 

run time. 
: REAL. This is a rather complex and unique variable, with acceptable 

inpa mge from - 1.0 to + 1.0. The absolute valw of WRC expresses the 

proportion of emissions subject to plume rise. A positive value places the plume 

rise proportion at the Brigs ( 1975) plume height for each calsulated down.uvind 

distance in the model; a negaPive value unifomly dislributes the smoke fiorn the 

go& to the Briggs plume height. The remaining proportion is placed at the 

gaud. A value of + 1.0 or - I .0 mems all smoke is subject to plume rise; a value 

of 0.0 me= no smoke rises. Once the distribution due to WRC is set, bath 

propofiions are subject to initial dispersion (as input) and transport-related 

dispersion processes. By wing a positive input value, RFRG acco 

concept of "split plume rise" discussed in SFFLP (1976) and Lavdas (1 978). 

Setting RFRC to 0.6 causes VSMOKE to confom to the assumptions given by 

SFFLP (1 976). Setting RFRC to 1.0 causes complete plume rise, allowing 

VSMOKE to confom to industrial stack oriented models such as CRSmR W.S. 

EPA 1977). A value of zero i~bits all plume rise, resulting in very conservative 

estimates of plume impact. Negative values of WRC activate the initially 

vertically uniformly distributed approach, which implies that the smoke forms a 

n" &om gomd to plume height, and any remaining smoke is 

dispersed fiom gomd level. For low intensity prescribed forest fires, as described 

by Lavdas (1 978), either + 0.60 or - 0.75 is suggested for RFRG. The -0.75 value 

is based on an unpublished reanalysis of aircraft data (Lavdas 1978) which 

resulted in a slight improvement in concentration estimates nearest the ground and 

a considerably better match to the observed vertical smoke profiles. RFRC is used 

only if LQREAD is set to FALSE. 

Input hints- Unless otherwise indicated, each of these variables is stored in arrays: 

Meteorological period-byperiod variables JAR: GER. Neither stored in an array nor othenvise used after it is 

read into VSMOKE, NUMDWX helps in bookkeeping the weather input data. 

Only the host-system-dependent limitations for a list-directed read of an integer 

variable constrain its use. One convenient approach involve date and 

time for the weather data that follows on the same line, e.g., - 

199707 1 5 16 signifies 16 hours, 1 5 July 1997. The year-month-date-hour order is 

convenient when mathematical sorting is used to constmct the data set. 

?TA, PPA: REAL. These variables are used in VSMOKE only to perfom 

mathematical operations &Ween carbon monoxide emissions and concentrations. 

If CO concentrations are not significant, default values may be forced by inputting 

a value less thm - 459.0 F for 'I"I'A and less than 0.1 mb for PPA. For PPA, the 

actual (i.e. station) pressure rather than sea level pressure should be used. 

GER. This variable mwt be detemined fiom weather observations 

or forecasts applicable for the time and place of analysis. Values from 0 to 100 are 

accepted by the program. Because relative humidity is used to determine other 

variables in an may "look up" sense, to maintain consenrative 'fworst-cmeff 

estimates, any fractional value of relative humidity should be automatically 

rounded up (e.g., 48.23 percent should be input as 49). If variations in RH are 
expected witb the smoke impact area or g the the period represented, the 

"worst-case" (i.e,, highest) RH should be used. 

LT8m)Y: LOGIC&. This variable defines "day" vs. "night" for a given period. 

VSMOm defines "day" as the period mmencing just after sunrise and 

nating just before sunset. AU. other times are defmd as "~&t." U&e most 

published sunrise and sunset times, the apparent solar disk radius md effects of 

atmospheric refraction are not considered in VSMOa. merefo~, VSMOKE 

solar ephemeris determinations result in a slightly shorter daylengh for a given 

date and lwation than most bmacs. Although the value of LTOFDY can 

critically affect VSMOKE output, such large model output differenw may be 

t~ggered by data that refleet rather trivial differences in actual physical conditions. 

These VSMOm sensitivities demonstrate the need to use the model in the most 

conservative sense reasonable for a given situation. In general, VSMOE analysis 

should be extended into a period that the model regards as "night" if there is any 

indjcation that smoke could cause a potential problem from a little before sunset to 

a little after sunrise. LTOFDY is read and used in VSMOm only if LSTBIIY is 

set to TRm. 

ISTABA: mGER. With acceptable values from 1 to 7, this variable 

characterizes stability class. hvdas (1986) or Turner (1964) should be consulted 

if there is any question about determining or interpreting stability class. If stability 

class cannot be provided, the user should automatically estimate stability class 

(achieved by setting LSTBDY to false). VSMOKE output is rather sensitive to 

stability class in many situations, and the discrete nature of the stability 

classification system used in VSMOKE causes some "jumpiness" in model output 

results, Therefore, a conservative approach is suggested that accounts for the 

effects of both adjacent classes on smoke concentration estimates for sample 

burns. For example, if three is input, the effects of using two and four as inputs for 

the given bum geometry and dispersion situation should be known. ISTABA is 

read and used only if LSTBDY is set to TRUE. 

WSSFC, ICOWR, GEL: REAL,, EGER, ItFia. Not stored in mays, these 

va~ables are based on vveather observations. They are read and used only 

if LSTBDY is set to F . The "jumpy" response of VSMOE vvith resptxt to 

stability class can be triggered by small shifts in any of these three surface weather 

variables. A mnservative approach, such as "forcing'" more stable class in a 

borderline cae, is strongly . ICOWR is restricted to the range 0 to 

10; WSSFC and GEL must be non-negative. 

eight is straightfom~d. Mixing height can be estbated by (and usually 

st (or well-designed and tested melmro1ogid softwm 

data. The metmrolodst 

concept even under stable 

e sense, no longer exists (crr 

hg hei&t as asl hpenetrable 
"lid" that perfectly traps all smoke. Specifying too low a mixing height will result 

in unrealistically high smoke concentration and visibility impact because smoke in 

an invesion layer slowly disperses within the layer. In stable conditions, A 

values should be set to at least 100 m. These values may be set lower if a good 

reason, such as well defined subsidence, exists. However, the VSMOm 

dispersion coefficients are not designed to account for important dispersion effects 

when an inversion is extremely close to the surface. Because mixing height when 

used to determine DI at night is restricted to the range between 240 and 600 m, 

restricting the VSMOKE input for A in "night" conditions to this range is 

generally prudent. However, to allow for testing VSMOK_E mathematical 

performance on varying host computer systems, any value of 1.0 m to 10,000.0 m 

is accepted by the program. 

UA: REAL. This variable also requires a meteorologist (or appropriate software 

package) with access to surface and upper air weather data. UA is the average (or 

"net") windspeed for the layer of atmosphere within which significant smoke 

concentrations fiom the fire occur and are likely to affect roadways and other 

sensitive areas. Extra weight should be given to surface wind observations or 

forecasts, especially in the presence of a surface inversion. Dense layers of smoke 

near the ground in stable conditions are most likely to cause traffic hazards. A 

reasonable practice is to weigh the surface windspeed equally with the average of 

speeds aloft within any actual or assumed mixing (or smoke) layer. In operational 

conditions where the available surface data are more likely to be representative of 

conditions at the time and place of analysis than are the upper air data, the surface 

report may be given precedence when it exceeds the "raw" transport windspeed 

value. For example, if a remote morning raob is used to determine a transport 

windspeed of 4.0 meters per second (m/s), and an afternoon observation gives a 

surface windspeed of 10 knots, and that surface wind is regarded as representative 

of conditions in and near the burn area, then the appropriate value of UA would be 

no less than 10 knots, or about 5.1 m/s. UA must be at least 0.1 mls. 

OYINTA, OZINTA: REAL. These variables allow period-by-period input of 

"initial" dispersion in the horizontal (OYINTA) and vertical (OZINTA) 

crossplume directions. Any non-negative value is acceptable. The most 

conservative approach for estimating concentrations from ground-level smoke is to 

use zero for both OYINTA and OZINTA. This approach corresponds to the 

practice of SFFLP (1976). The most conservative approach for fires with 

complete plume rise (RFRC or EMTQR = + 1 .O) is to input the highest reasonable 

value for OZINTA and zero for OYINTA. Rigorously determining appropriate 

non-zero values requires rather sophisticated monitoring of smoke behavior near 

fires. Appropriate data are generally lacking. Selecting appropriate values in an 

operational environment requires a knowledge of the initial distribution and virtual 

distance concept a. used in VSMOKE. A Gaussian distribution of pollutants is 

applied at the source due to these coefficients. Domind calculations are hmdled 

by adding virtual distances to the source/receptor relationships. These must be 

equivalent to those necessary to generate the specified initial distributions from a 

point source by transport-related model dispersion processes. Other VSMOKE 
input variables also describe the of a ground fire as a 

quare root of which is the 

omontall dist.ribution of smoke at 

, if ILQWm is true) help 

net '"Gal'Ustribution 

resulting from the effect of 

the geonretry of the smoke 

: REAL. This is a "generic" background perid-by-period 

concentrat~on for particulate matter in micrograms per cubic meter (pg m3). 

as defined by the 1990 Clean Air Act (unless and 

ed if available. In any case, BKGPMA should 

correspond to the particular matter component specified for EFPM (if 

LQMAD---FALXE) or for EhrITQPM (if LQREAD=:mUE). For the foreseeable 

future, little or no monitoring of particulate matter is likely to be available at most 

prescribed bum field locations, therefore a value for BKGPMA will usually be 

assumed. The input value must be non-negative; a zero input causes VSMOKE to 

determine smoke concentrations only from the single fire under analysis. When 

LSIGHT is set to TRUE, a zm value for BKGPMA leads to unrealistic 

crossplume sightline estimates. If background visibility is the only basis for 

BIKGPMA, the following relationship should be used: 

BKGPUA = 3.0E+05 ( 2.4:;:i03 - 1.5E-05 

where 

VISM is the background visibility in miles. For example, VISM = 1 mile, 

BKGPMA = 725 pg m3; VISM = 7 miles, BKGPMA = 100 pg mm3. 

BKGCOA: REAL. This is perid-by-period background concentration for carbon 

monoxide in parts per million based on a density of CO per total density of air. 

Little or no monitoring data are likely to be available in most prescribed burn 

situations. The input value must be non- negative; a zero input yields smoke 

concentrations from only the single fire under analysis without adverse effects on 

subsequent model calculations. Unlike particulate matter concentrations, 

VSMOKE CO concentration estimates are influeneed by input values of ambient 

temperature, pressure, and moisture. 

Note: We variables are read and used by VSMOKE only if LQWm is set to 

related period-by-period TRUE, which indicates that period-by-period emissions related data are included 

variable in the input file. 

DRT: GER. This variable serves a "bookkeeping only" function with 

respect to the optional period-by-period emission rate related data. Any 

bookkeeping system within the limitations of the user's host system may be used. 

NUMDRT is not stored in an array or used in any other capacity. 
EMTQPM, EMTQCO: REAL. These variables would ordinarily be derived &om 

an emissions model for a prescribed fire. Both the particulate matter GMTQPM) 

and carbon monoxide (EMTQCO) emission rates in grams per second represent 

the total fire for the given period. Any non-negative value for either emission rate 

is acceptable. Because the values can be high, the use of the powers of 10 format 

(e.g., 1.5E+O6 for 1,500,000) may be more convenient and allow more exact 

represenation of the input values of EWQPM and EMTQCO within VSMOm. 

The cunent version of VSMOKE treats particulate matter "generically"; that is, 

emissions and concentrations may be for total particulate matter or for particulates 

within a given size class. Whichever component of particulate matter is used in a 

given VSMOKE run, the input value(s) of EMTQPM should match the component 

described by the input value(s) of BKGPMA. 

EMTQH: REAL. This variable would probably be derived from a model of a 

prescribed fire that tracks and outputs either sensible heat emission rate or the rate 

of mass loss of fiel. This variable is available %om some emission models for 

prescribed fire (Sandberg and Peterson 1984). As of December 3 1,199 1, heat 

emission estimates from this model (i-e., the EM model) were given in BTUts per 

second and must be converted to megawatts (by multiplying by 1.0551 * 1V3) 

before running in VSMOKE. EMTQH can be estimated %om a knowledge of the 

rate of fuel commption and the amount of sensible heat released to the 

atmosphere per unit mass of fuel consumed. Fuel consumption rate estimates are 

available within some emissions models, while sensible heat release per unit fuel 

can be assumed constant for many forest fiels. Any non-negative value is 

acceptable. Using powers of 10 notation may prove more convenient and allow 

more exact representation of EmQH within VSMOKE. 

EMTQR: REAL. This variable may be regarded as a period-by-period value of 

WRC. The absolute value of EMTQR specifies the proportion of smoke 

emissions subject to plume rise. The sign of EMTQR specifies the initial vertical 

distribution assigned to the plume rise associated smoke. If positive, all plume rise 

smoke is dispersed from the calculated plume height; if negative, the plume rise 

smoke is initially uniformly distributed from the ground to the calculated plume 

height. In either case, all remaining smoke is dispersed from the ground. EMTQR 

is more specialized than the three preceding emissions values, and may not be 

available fiom emissions model oulput. If no da& are wailable, the best available 

estimate of RFRC for the active combustion period should be used for each period 

with significant active flaming combustion. When heat emissions become low and 

the source of heat is widespread (e.g., smoldering smoke sources scattered 

setting EMTQR to zero yields rhe most consewalive 

estimates of smoke impact. Values from - 1.0 to + 1.0 are accepted by the 

program. SFFLP (19761, in eEecf assigned a value of + 0.6 to EmQR during 

the "convective lifi phase" of a fire, and 0.0 during the "no convective lift phase." 

Either a value of + 0.60 or - 0.75 can be justified fi.orn the low-intensity prescribed 

fire and smoke data analyzed by Lavdas (19781, and - 0.75 may be a better value, 

according to an mgub1ished analysis. 
Appendix I 

Input Examples 

The following examples are for illustration only and should not be construed 

endations for input values. 

Example 1-A quick check of day and night smoke conditions 

It is March 15,1996. A bum is scheduled to begin tomomw afiernoon 

at 2 p.m., on the Fictitious National Forest in South Carolina. The 

location of the bun site is 33.6" N. 79.7" W. The burn is a 40-acre series of 

bacHres that will reduce the he1 loading by 2.5 tons per acre. No emission rate 

data from modeling efforts are available, but consultations with experts indicate 

that the emission factor for particulates is 30 pounds per ton, the duration of both 

the convective and constanl emissions period of the fire is 2.5 hours, the 

appropriate value of the exponential decay constant is 0.5 hours; 75 percent of the 

smoke will rise to full plume height and 25 percent will remain on the ground. For 

this burn, carbon monoxide concentrations are not needed, but crossplme 

visibility estimates are--a contrast ratio of 0.10 or better is desired at a distance of 

1/8 mile. The smoke plume undergoes gradual rise. The weather forecast specifies 

tomorrow's stability class to be 3, mixing height of 1200 m, and transport 

windspeed of 7.0 ds. The following evening, a stability class of 6 and transport 

windspeed of 2.5 ds are expected, and an appropriate mixing height input would 

be 300 rn. Predicted l3.H is 45 percent for tomonow afternoon, rising to 80 percent 

by 8 p.m., and 95 percent by 2 a.m. the next day. The horizontal and vertical 

"initial" dispersion coefficients are to be set to zero throughout the life of the fire. 

The background concentration of particulate matter will be 40 pg m" throughout 

the period. The VSMOKE.PT file should contain the following information: 

NLPAGE - 66, appropriate for uncontrolled form fold line printers 

KTITLE - one can simply use the title of example 1 ; a numbering system 

enclosed in apostrophes could be devised for operational use 

ALAT - 33.6" N 

ALONG - 79.7" W 

TWON - in March in South Carolina would be EST, or 5.0 hours 

behind UTG 

ImPIW - 1996 

MO - March, or 3 

DAY - 16 

WOD - estimates for 2 p.m., 8 p.m., and 2 a.m. are desired; use 3 

mSTRT - use the fire start time; on a 24-how decimal clock, 2 p.m. is 

14.0 

'VL - the desired estimate times are every 6 hours, use 6.0 

LSTBDY - stability classes are a part of the input forecst; use T 

LQREAD - no period-by-period emission rate related data are available; 

use F 

LSIGm - crossplme sightline estimates are desired; use T 

GCOCRT - 0.10 

VISCRT - 0.125 

ACWS - 40.0 
TONS - 100.0 (2.5 tons per a~re times 40 acres) 

EFPM - 30.0 

EFCO - wbon monogde analysis is not needed; use 0.0 

- 2 p.m.; use 14.0 

- 2.5 

TCONST - 2.5 

mECAY - 0.5 

LORISE - grad& plme rise cdculation is desired; use T 

RFRC - 75 permnt of smoke rises fully and disperses from full plume 

- this particular user finds the numbers 14,20, and 26 to be 

way to keep track of times associated with the weather 

data; a more robust method would be 199603 1614, 199603 1620, and 

199603 1702 

TTA - used only in determining CO concentrations in parts per million; a 

defauIt is forced 

PPA - used only in deternlining CO concenbations in parts per million; a 

It is forced 

relative humidities are 45,80, and 95 percent 

LTOFDY - 2 p.m. is day, 8 p.m. is after sunset, and 2 a.m. is night; use 

T, F, and F 

ISTABA - stability classes are 3,6, and 6 

AMMjl, - mixing heights are 1200., 300., and 300. m 

UA - &=port windspeeds are 7.0,2.5, and 2.5 m/s 

OYBTTA - "initial" horimntal dispersion coefficients are 0.0,0.0, and 

0.0 

0DNTA - "initial" vertical dispersion coefficients are 0.0,0.0, and 0.0 

BKGPMA - background particulate matter concentrations are 40 

pg mJ for all periods, use 40.0,40.0, and 40.0 

BKGCOA - carbon monoxide is not considered in this example; zeros 

can be used 

The VSM0KE.m file for example 1 should appear as follows: 

66 

EMLE 1 - A QUICK CHECK OF DAY NGHT SWKE 

commoNst 

33.6 79.7 5.0 1996 3 16 3 14.0 6.0 T F T 0.10 0.125 

40.0 100.0 30.0 0.0 14.0 2.5 2.5 0.5 T 0.75 

14 -500, -1. 45 T 3 1200.7.0 0.0 0.0 40.0 0.0 

20 -500. -1. 80F 6 300. 2.5 0.0 0.0 40.0 0.0 

26 -500. -1. 95 F 6 300.2.5 0.0 0.0 40.0 0.0 

EmmpIe 2A and 254 more detailed look at a head fire at the same site 

Sme time, same place, different firing technique. A head fire takes less time to 

bum through the site (assume 1.75 hours); the experts say that the emission factor 
should be 60 pounds per ton, the constant emission period outlasts the convective 

period by a half hour, the decay constant should be "doubled, maybe tripled," and 

75 percent of smoke that rises will be unifody distributed between the ground 

and the prdcted plum height. No one has much to say about "initial" dispersion 

cients. The user decides hour-by- of smoke conmtrations and 

aossplume visibitities are: nded and con th a meteorologist about hawly 

weather input. The user is advised that "p e 1 " is acceptable. Assum: this 

uses the emmn wathm between noon and 2 horn before sunset and hmly 

interpolates relative humidity and stability class to evening and late night values. 

The night values of transp xing height are used all night. 

Wer sunrise, the stability er how to a &we value of 4 or 

less, but mixing height lag behind until miboeg. In 

the operational world, a little program &eady exists that handles this weather data 

generation automatically. The "initial" dispersion ients are handled by 

setting them to zero (generally the most conservative course of action, unless better 

information is available). Because the "doubled or maybe tripled" decay constant 

is vague, you decide to run the program twice. The VSM0KE.R for the fust run 

should contain the following infomation: 

WAGE - assume a system setup makes 63 most convenient 

KTITLE - merely need to distinguish between the two cases 

&AT, ALONG, TMZON, WEAR, MO, DAY - same as example 1 

NPRIOD - continue until 8 a.m. the following day; use 19 - HRSTRT - use the start time for the fire, 14.0 

- 1.0 

LSTBDY, LQREAD, LSIGHT, CCOCRT, VISCRT - same as example 1 

ACRES, TONS - same as example 1 

EF'PM - 60.0 

EFCO, TFDE - same as example 1 

THOT - 1.75 

TCOMST - half an hour longer than THOT, or 2.25 

TDECAY - "doubling" example 1 gives 1.0 

UNSE - still desired; use T 

C - 75 percent of smoke rises resulting in a uniform vertical 

tstribution; use -0.75 

- choose 14-23, then 00-08 

- use defaults, same as example 1 

- use 45 from 2 p.m. to 5 p.m., then work upward to 80 and 95 

percent 

LTOFDY - su~se is 6:20 a.m., sunset is 6:20 p.m. 

ISTABA - keep 3 from 2 p.m. to 5 p.m., go up 1 per hour until 8 p.m., 

hold to 6 a.m., then use 5 for 7 a.m., 4 for 8 a.m. 

- 1200. m through 6 p.m., then 300. m 

ds through 6 p.m., then 2.5 ds 

A, BE;GPMA, and BKGCOA - same as example 1 
The VSM0KE.m fie for exampie 2A should appear as follows: 

The run for example 2B changes only I(TITLE and TDECAY (from 1.0 to 1.5): 

63 

ANaYSIS mH TDECAY = 1.5 

Hornsf 

33.6 79.7 5.0 1996 3 16 19 14.0 1.0 T FT 0.10 0.125 

40.0 100.0 60.0 0.0 14.0 1.75 2.25 1.5 T -0.75 

14 -500. -1. 45 T 3 1200.7.0 0.0 0.0 40.0 0.0 

15 -500. -1. 45 T 3 1200.7.0 0.0 0.0 40.0 0.0 

16 -500. -1. 45 T 3 1200.7.00.0 0.040.0 0.0 

17 -500. -1. 45 T 3 1200.7.0 0.0 0.0 40.0 0.0 

18 -500. -1. 57 T 4 1201). 7.0 0.0 0.0 40.0 0.0 

19 -500. -1. 69 F 5 300.2.5 0.0 0.0 40.0 0.0 

20 -5W. -1, 80 F 6 300.2.5 0.0 0.0 40.0 0.0 

21 -500. -1. 83 F 6 300. 2.5 0.0 0.0 40.0 0.0 

22-500. -1. 85F6 300.2.50.00.040.00.0 

23 -500. -1. 88 F 6 300.2.5 0.0 0.0 40.0 0.0 

00 -500.. -1. 90 F 6 300.2.5 0.0 0.0 40.0 0.0 

01 -500. -1, 93 F 6 300.2.5 0.0 0.0 40.0 0.0 

02 -500. -1. 95 F 6 300.2.5 0.0 0.0 40.0 0.0 

03 -500. -1. 95 F6 300.2.5 0.0 0.0 40.0 0.0 
Example &Forecast stabifity class wn 

Assume the same condtions as example 1, except stabifity class is not given in the 

forecast and crossplume visibility estimates are not required. The weather 

is given as "clear tomorrow, with winds of 10 mph; fair tomorrow night with winds 

of 5 mph." For this example, VSMOKE.IPT should contain the following 

infomation: 

NLPAGE - set to the mi&um of 60 lines per page 

KTJTLE - use the above title 

ALAT through VL - same as example 1 

LSTBDY - stability class not available; use F 

LQREAD - period-by-period emission rate related data not available; 

use F 

LSIGHT - crossplume sightline estimates not required; use F 

CCOCRT, VISCRT - same as example 1 

gh RFRC - same as example 1 

although weather format is for LSTBDY = F, this is same 

A - same as example 1 

WSSFC - 10 mph tomorrow, 5 mph tomorrow night; these convert to 8.6 

and 4.3 knots; use 8.6,4.3, and 4.3 (the 5 mph forecast applies to both 8 p.m. 

and 2 a.m.) 

ICOWR - clear is 0 tenths, fair is generally under 5 tenths, the exact 

number vvith the 0 to 4 rage is not cfitical; use 0,0, and 0 

CEIL - there is no ceifing unless KOVER is 6 or more; use 99999. for all 

three periods 

A, BKGPMA and BKCGOA - sme as example 1 

The VSPAOm.m file for example 3 should appem as fallows: 
Exslmple 6Eam;pfe 3 with clouds 

Assme now the same conditions as e le 3, except the forecast is cloudy 

conditions tomorrow and tomorrow night. After consulting a meteorologist, you 

find that ICOVER inputs should be 6,9, and 10, and CEIL inputs should be 

12000., 6000., and 3000. VSM0m.m for e le 4 should appear as follows: 

60 

I LE 4 - FOmCAST STBILRY CLASS 

FOMCAST:' 

33.6 79.7 5.0 1996 3 16 3 14.0 6.0 F F F 0.10 0.125 

40,O 100,0 30.0 0.0 14.0 2.5 2.5 0.5 T 0.75 

14 -500. -1. 45 8.6 6 12000. 1200.7.0 0.0 0.0 40.0 0.0 

20 -500. -1. 80 4.3 9 6000. 300.2.5 0.0 0.040.0 0.0 

26-500. -1. 954.3 10 3000. 300.2.5 0.00.040.00.0 

Example -moldering organic soils scenario with convoys available 

Generally, carbon monoxide concentrations fiom a prescribed fire tend to be less 

critical than particulate matter. Carbon monoxide is invisible and does not directly 

affect visibility. Moreover, air quality emission factor compilations (US. EPA 

1985, 1988, 1990) set typical emission factors for CO relatively low compared to 

particulate matter with respect to air quality standards. An exception can occur 

when dealing with smoldering organic soils. These fires may often be relatively 

"clean" with respect to particulates, but "dirty" with respect to CO. Smoldering 

organic soil is a si-tion that should be 

operations. These emissions can last fo 

impossible to extinguish unless environmental conditions are unusually favorable, 

and the resulting smoke is both inherently dangerous for traffic safety and 

potentially highly aging to general air quality, Men used with care, 

VSMOKE can be applied for any ground-based emissions source, including a fire 

in organic soil cawed by a ligh~ng strike. VSMOm can be used to obtain a 

"snapshot" of atmospheric conditions during poor weather when the likelihood of 

safety problems is greatest. For this example, the fire has been ongoing as a 

smoldering source for several weeks. Assme that law enforcement officials are 

actively involved in convoying traffic tlrrotlgh affected roadways. Please note that 

consultations with experts are required for these conditions. The following input 

represents a hwthetical situation used for illustration only. 

le 5 that may require clarifi~ation are: 

ALAT, ALONG - have been moved to an area containing deep organic 

soils 

MO, DAY - changed to late s 

WHOD, mSmT, ario snapshot; only the 

4 a.m. conditions is not used 
CCOCRT - assume that consultation with law enforcement officials have 

resulted in an agreement to set the value to 0.02; patrols will lead all traBc 

through the area in low-speed convoys 

WSCRT - set by consultation, convoys will be nm at low speeds, with 

500 foot (0.0947 mile) visibility regarded as adequate 

ACRES - assumed to be 40.0, but many organic soils fires are much 

larger 

TONS - note that the tons per acre consumed during the snapshot period is low, 

only 0.1; this &el is consumed during the period specified by the sum of 

TCONST and TDECAY 

EFPM, EFCO - reflect the "clean" and "dirty" nature of the source with 

respect to particulate matter and carbon monoxide 

TFIRE - specified as 3:30 a.m.; this means only that the source emissions are 

"underway" when the model concentrations are calculated at 4 a.m. 

THOT - the source is "cool"; THOT is specified as zero 

TCONST, TDECAY - the smoldering soils are assumed to be in a 

"steady-state"; for the purposes of the snapshot, TCONST is set to 1.0 hour and 

TDECAY to 0.0; that is, 0.1 tons per acre (4 tons in the 40 acres) of fuel are 

consumed in the 1 hour specified by TCONST + TDECAY 

RFRC - a cool source is assumed; RFRC is set to zero, but is not used 

WX - a year/month/day/hour integer is used in this case 

IRHA though UA - reflect very poor atmospheric dispersion conditions 

OYINTA, OZINTA - assume these nonzero quantities are given by an expert; 

although OYINTA in this case is of limited practical importance, the nonzero 

OZINTA value acts to slightly reduce concentrations close to the source 

BKGPMA, BKGCOA - assume that 75 pg mW3 for particulates and 6.0 ppm for 

CO have been monitored as background levels 

The VSMOKE.IPT file for example 5 should appear as follows: 

Example &Example 5 with emission rate estimates available 

Close monitoring of smoke &om prescribed fires that permits rigorous estimates of 

the emissions input requirements of VSMOKE under the LQREAD = TRUE 

option may not occur in the near mre. However, the problems associated with 

the persistent smoke from burning organic soils may soon result in close 

monitoring of these types of fires. Progress in smoke models generating the 

necessary input data may also continue, e.g., work continues on such efforts 

pioneered by Sandberg and Peterson (1984). To illus&ixte the LQREAD = TRUE 

option, assume that the smoldering fire in e fe 5 continued for an 
additional week: dGng that time, its emission rates have been well established. 

The input elements in example 6 follow: 

G ORGANIC SOILS WITH mO 

N - same as exmple 5 

week later, i.e., 1997 8 29 

NPRIOD - assume three snapshot analyses are to be perfomed with worst-case 

memrology and three di missions scenarios developed from the 

monitoring program; thi artifact used instead of running the 

progm three times. an be taken safely once the mechanics 

of the model are thoroughly unders 

TVL - set for predawn analysis 

CCOCRT, VISCRT - same as example 5 

ACRES - same as example 5 

TONS, EFPM, EFCO - not used by the program, but must have dummy inputs 

(values that are normally invalid are used to avoid confusion) 

TFIRE - set to allow predawn analysis 

THOT, TCONST, TDECAY - not used, but must have dummy inputs (again, 

invalid values are used) 

LGRISE - since no plume rise is possible in this model nm, this value is irrelevant; 

in this example, set to T 

RFRC - not used, but need a dummy input (this example uses an invalid input) 

NUMDWX through BKGCOA - same as example 5, but now have three 

lines of identical weather related data 

WDRT - set to keep in synch with HRSTRT and HRNTVL 

EMTQPM, EMTQCO - set low, midrange, and high estimates 

EMTQH - although sensible heat emission rate might be no more 

difficult to estimate than emission rate, no plume rise is assumed; therefore, 

zero is used 

EMTQR - set to zero, forcing zero plume rise, enabling a worst-case analysis 

The VSMOKE.IPT file for example 6 should appear as follows: 

66 

PLE 6 - SMOLDE C ORGANIC SOILS WTH KNO 

EMISSIONS" 

34.6 77.8 4.0 1997 8 29 3 3.0 1.0 T T T 0B02 0,0947 

40.0 -1.0 -1.0 -1.0 2,s -1.0 -1.0 -1,0 T 10.0 

1997082903 72.0 1012.5 100 F 7 240, 1.0 5.0 5.0 75.0 6.0 

199"108204 72.0 1012.5 100 F' 7 240. 1.0 5.0 5.0 75.0 6.0 

1997082905 72.0 1012.5 100 F 7 240, 1.0 5.0 5.0 75.0 6.0 

1997082903 I ,OE+O2 4,0E+03 O.OEO0 0,0 

1997082904 2.0E-t-02 8.OE+03 0.0E00 0.0 

1997082905 4,0E+02 l.cSEt-04 O.0EOO 0.0 
Appendix 1x1-Line- This appendix presents a generic line-by-line description of the contents of 

by-line Layout of VSMOKE,Om and an example that shows outpt format for a specific test 

run. 

Part A4eneric Section 1 - Echo-print 

Line-by-Line Description 

Line 1 is the header, giving program name and version number, bracketed by a 

series of colons, ": : : : , etc.". The version nmber is referenced to date of last 

revision and is given in dd format. 

Lines 2 and 3 are skipped. 

Line 4 consists of the message, 

ECHO PRINT (LIST-DIRECTED OUTPUT) OF INPUT VALUES: 

Lines 5 to '7 are skipped. 

Line 8 consists of the control variable, NLPACE: 

Line 9 is skipped, 

Line 10 gives the value of WAGE as input. 

Lines 1 1 and 12 are skipped. 

Line 13 consists of the label, KTITLE: 

Line 14 is skipped. 

Line 15 gives the value of KTITLE, generally as it is represented in its output 

format. This means that apostrophe (') delimiters do not appear in KTITLE, and 

that single apostrophes appear where consecutive apostrophes are used within 

KTITLE. The methods used to process the output file may cause trailing blanks 

included within the input value of KTITLE to be eliminated as a part of the output 

file (e.g., the blanks following the colon in 'TEST CASE #I:' may be eliminated). 

Lines 16 and 1'7 are skipped. 

The following lines in this section continue the echo-print of the remaining 

contents of the input file. The input/output list of each line of input data is used as 

a header, which takes up at least one line of output. Where array variables appear, 

a second line is used to identi@ the my index value. The header line(s) are 

followed by a line skip, then by the values of each variable in the input/output list. 

The number of lines required by the list of values is dependent on the host system. 

The values appear in their proper order, but their format and layout are dependent 

upon the methodology used by the host system to process FORTRAN 77 

list-directed output. Two lines are skipped to separate the list of values from the 

header for the next line of input data. Lines are not necessarily skipped after the 

last list of values for the last line of input. Page processing is not used within 

section 1 but is used at the end of the section. Section 2 starts with a new page. 

- INTEGER set to 1 if this period is in daylight, set to 2 for darkness 

- INTEGER, this period's Turner (1964) stability class (input as 

mA(I), if LSTBDV = TRUE) 

- EAL, this period's mixing height in meters (input as 

U - REAL, this period's transport windspeed in meters per second (input as 

UA(1)) 

- REAL, this period's "initial" horizontal dispersion coefficient in meters, 

outing effects from non-point source modeling (input as 

- REAL, this period's "initial" vertical dispersion coeffici 

counting effects fiom the input value of RFRC and/or EMTQR(1) (input as 

OZNTA(1)) 

RHO - REAL, this period's ambient atmospheric density in kilograms per cubic 

meter 

Column 4 (lines 5 through 12): 

ELM - REAL, effective line source length in meters 

TFRE - REAL, start time of fire in decimal hours (input) 

THOT - REAL, duration of convective period of fire in decimal hours (input) 

TCONST - REAL, duration of constant emissions period of fire in decimal hours 

(input) 

TDECAY - REAL, exponential decay constant, a decay period duration 

parameter, in decimal hours (input) 

EFPM - REAL, emission factor for particulate matter in pounds per ton of he1 

consumed (input) 

EFCO - REAL, emission factor for carbon monoxide in pounds per ton of &el 

consumed (input) 

RFRC - REAL, proportion of emissions subject to plume rise, with vertical 

distribution controlled by the sign of RFRC (input) 

Column 5 (lines 4 to 12): 

ACRES - REAL, area of emissions source in acres (input) 

TONS - REAL, total mass of fuel consumed in short tons (input) 

CRITPM - REAL, particulate matter concentration in micrograms per cubic meter 

associated with the input sightline criteria, CCOCRT and VISCRT, valid only if 

conditions are dry (i.e., relative humidity less than 70 percent); CNTPM is 

calculated if LSIGHT = TRW, set to zero if LSIGHT = FALSE 

EMTQPM(I) - REAL, this period's total emission rate for particulate matter in 

grams per second (input if LQREAD = TRUE) 

EMTQCO(1) -REAL, this period's total emission rate for carbon monoxide in 

grams per second (input if LQmAD = TRUE) 

EMTQH(1) -REAL, this period's total sensible heat emission rate in megawatts 

(input if LQREAD = TRUE) 

F - REAL, this period's total buoyancy flux in meters4 per second3 

THETA - REAL, this period's ambient potential temperature in degrees kelvin 
EMTQR(I) - REAL, this perids proportion of emissions subject to plume rise, 

with veftieal distribution controlled by the sign of EMTQR(T) (input if 

LQmm = mw) 

Lines 13 and 14 are skipped. 

Line 15 gives Dispersion Index (DO and a descriptive adjective (see Table 4). 

Line 15 also displays Low Visibility Occurrence Risk Index (LVORI) with a brief 

explanation (see Table 5). 

Line 16 continues the des~ption of LVORI. 

Line 17 is skipped. 

Line 18 is used only if LSIGHT = TRUE; if so, line 18 is a table heading 

explanation, w~ch includes the input values for critical contrast ratio (CCOCRT) 

and critical crossplume horizontal visibility (VISCRT). 

Line 19 is an overall table heading, which includes the period number, simulation 

time, and time elapsed since the start of the fire. 

Line 20 is skipped. 

Lines 21 through 24 give the headings for each variable displayed in each column 

of the table. These variables include downwind distance in kilometers, plume 

height or depth in meters, horizontal and vertical dispersion coefficients in meters 

(including the effects of any initial dispersion), particulate matter centerline 

concentration including background in microgram per cubic meter, carbon 

monoxide centerline concentration including background in parts per million, 

optional crossplume visibility in miles (applicable if relative humidity (RH) is less 

than 70 percent), optional contrast ratio (for RH less than 70 percent) applicable 

for a crossplume sightline of length, VISCRT, and a repeat of downwind &stan= 

in kilometers to help in reading the table. The optional sightline parameters are 

calculated for a sightline constmted outward from the plume centerline in both 

ground-level horizontal crossplume directions. 

Line 25 is skipped, 

Lines 26 through 56 give the calculated values of the variables described in lines 

21 thou& 24 for each downwind distance (table 6). The distances range from 

0.100 to 100.000 km, using logarithmic spacing, with 10 tabular values per factor 

of 10 (i.e., imementing is by a factor of lo0-', resulting in an increase in downwind 

distanee slightly over 25 percent per increment). The optional sightline values are 

accompanied by an asterisk if this period's RH quais or ex 

Line 57 gives applicable values for background. Not applicable (N/A) is displayed 

for the plume height or depth and the horizontal and vertical dispersion 

coe=cients. The optional sightline values are accompanied by an asterisk if the 

Line 58 is skipped, 
Line 59 is used only if LSIGHT = TRUE and the RH equals or exceeds 70 percent; 

it consists of a wming message. 

Line 60 is used only if LSIGHT = TRUE; it gives the tabular downwind distance at 

md beyond which the estimated ground-level horizontal crossplume sightline 

parameters maintain acceptable characteristics, given an RH less than 70 percent. 

Section 3 - Worst-case analysis for all periods with significant emissions 

Line 1 is the header, giving program name and version number, bracketed by a 

series of equals signs, "= = = = , etc." The version nmber is referenced to date of 

last revision and is given in yyyymmdd fomat. 

Line 2 is skipped. 

Line 3 gives the title (KTITLE) as input in VSMOKE.IPT. The apostrophe 

delimiters are not show. At most, only the first 72 positions of line 3 are used. 

Line 4 is skipped. 

Line 5 gives the worst (highest) RH among all periods analyzed. 

Line 6 is skipped. 

Line 7 gives the worst (lowest) DI among all periods analyzed and the 

corresponding descriptive adjective (see Table 4). 

Line 8 is skipped. 

Lines 9 and 10 give the worst (highest) LWORI and the corresponding brief 

explanation (see table 5). 

Line 11 is skipped. 

Line 12 gives the smoke concentration (and optional sightline) table heading. 

Line 13 is used only if LSIGHT = TRUE; it gives critical contrast ratio, CCOCRT, 

and visibility criterion, VISCRT. 

Line 14 is skipped. 

Lines 15 through 18 give the headings for each variable displayed in each column 

of the table. These variables include downwind distance in kilometers, particulate 

matter concentration including background in micrograms per cubic meter, carbon 

monoxide concentration including backgound in parts per million, optional 

crossplume visibility in miles (applicable if RI-i is less than 70 percent), optional 

contrast ratio (for RH less than 70 percent) applicable for a crssspfume si&tline of 

length, VISCRT, and a repeat of dowwind distance in kilmeters, The optional 

sightline parameters are calculated for a sightline comtnteted ou-IWmd Erom the 

plume centerline in both pud-level horizontal crossplume directions. 

Line t 9 is skipped, 

Lines 20 thou& 50 give the calculated values of lhe v~ables described in lines 

11 5 through 1 8 fbr each domwind distance. The distan@es rmge from 0.100 to 
100.000 km, wing logarithmic spacing, with 10 tabular values per factor of 10 (i.e, 

incrementing is by a factor of lo0-', resulting in an increase in downwind distance 

of slightly over 25 percent per increment). The values displayed are for the worstcase (hi&est concenlration, lowest visibilig or contrast ratio) found among all 

malyzd periods for the specific vafiable at the specific domwind distance. The 

optional si&tline values are accompanied by an asterisk if the relative humidity for 

any period analyzed equals or exceeds 70 percent. 

Line 51 gives worst-case values for backe;round. The optional sightline values are 

accompanied by an asterisk if the relative humidity for any period analyzed equals 

or exceeds 70 percent. 

Line 52 is skipped. 

Line 53 is used only if LSIGHT = TRUE and the relative humidity for any period 

analyzed equals or exceeds 70 percent; if so, it consists of a warning message. 

Line 54 is used only if LSIGHT = TRUE; it gives the tabular domwind distance, 

at and beyond which the estimated ground-level horizontal crossplume sightline 

pwmeters maintain acceptable characteristics given a relative humidity less than 

30 percent. 

Lines 55 thou& 53 are skipl~ed. 

Line 58 gives a run OK flag message, which should appear as "LRUNOK = T," if 

no problems were diagnosed during the VSMOKE run. If problems, such as ID 

processing errors, are found and system control is retained by the VSMOKE 

FOR program, "LRUNOK = F" should appear in file VSMOKE.OUT near 

the end of the aborted ourput. 

Line 59 is skipped. 

Line 60 contains the end of VSMOKE: run message. 

In case of error with program VSMOKE-controfld termination: 

A new page is generated: The header line begins with a series of open parentheses, 

followd by progm name ancl version number, and ends witfr a sePies of closed 

parentheses. This line is followed by text that explains the nature of the error. A 

line is skipped followed by a nur not OK message, which appears as "LRUNOK = 

F." A line is skipped followed by the end of VSMOKE run message. The last 

three lines (LRUNOK ..., skipped line, and end of VSMOKE) follow the same endoEm format as a normal run. Therefore, an automatic post-processor, diagnosing 

file VSMOKE.OUT, can determine whether a given run executed normally by 

reading to the VSMOKE.OUT end-of-file, backspacing to the LRUNOK line, and 

reading lrhe valare sf LRWOK. 

In case of a host comparter sys;Qm-mutrolled error: 

Any output from errors not anticipated by program VSMOKE logic or controllable 

wi~n &e csnfmes sf a F 77 progm in fie host system will be 
dependent on the exact nature of the emor and the host system characteristics, 

given the specific error diagnosed. The generation of a new line or a new page of 

output under such conditions cannot be assured. The handling of output under 

such conditions must be left within the purview of the user or the user's host 

system. 

pecific Output This portion of Appendix III illustrates the layout of output file, 

File Example VSMOKE.OW, by means of a specific example. This example is used for 

illustration only and should not be construed as a recornendation for input values. 

For this example, VSMOKE.IPT appears as follows: 

VSMOKE.OUT output corresponding to the input example appears on the 

following four pages. 
ECWO PR11ST (LIST-DIRECTED 3 OF IUWT VALUES: 

ICC I TLE : 

.IPT OUTPUT FlLE LE: 

<I),TTA<I~,PPA(I~,IRHA<I),LTOFDY~I~,IST~<I~,MIW\I(I~,UA~I~,OY1NTA~I~,OZINTA<I),BKGPWA~I),BKGMM~I); 

FOR I = 2: 

T(I),~T~(I),~~<~),EW~PH(I ),BHTOR(I?; 

FOR I = 2: 
LW VISIBILITY EWWfi?E#GE RISK INDEX = 1 - CEULS BASE LIXE) 

(THE BASE LIBE RISK OF LW vnsIelLIfy ~WRREMCE IS I ig 1080) 

 fie F~LWOJG TABLE IS ~ASED C~M A CRITJML ~TRALT WTIO = oa~50~00, WIVN WOWIZWIAL CROSSPLUME VISIBILITY = .a00 MILES, 

PERIa t - E meEMfRII3lWiVISIBILEIV TABLE: XRSIIS = 14r000@ - - - THAT IS, 1,08b)O ItWRS AFTER FPWE SMART flHE, 

PLWE WmI ZOWTAL MR3 I aL P"FIEEXTERLIlJE CQ CEXTERLIXE CROSSPLWE 

b l SIIlMGE WEIGHT/ BESPERSi8011 DISPERSEOX aCEMTARATIW CBMGEITMIIOX VPbllBILlIV RClllO AT DISTANCE 

FRW FIRE DEPTH mFFlCIEMf eFlEFFlCIEWT (INCL, EOKGW) (IMGL. IlEGCO) leC11(, LClU RH ,2500 FRa FlRE 

(m3 [METERS) (IflETERS F (=TEARS) (IdCiM-3 3 (PW) [HOLES) MILES (Wf 

DRY EIIPIIER CBaSPL%RsgE VISfBiLITIES ARE AT LEAST .ZSQO MILES, AT AND BEYOND .100 W FRW THE FIRE- 
IRX 

IbVtlT 

I STaS 

MIX 

U 

OYllllB 

aI#l 

RHO 

*2400 RILES. 

PERlllD 2 - aGEXPRELTIOEIPVt SIB1 t ITV TABLE: HRSlPI = TXAI IS, 7,M)CIO HaS AFTER FIRE START TIME, 

ILlD PL- HQR I ZOWTAL VERf I CXt Pn -1ERtIXE CEWTERLIWE CRmSPEWE 

D I STME HEIGWIl DISPERSICIW DISPERSIOd3 mCEWTRAIlC)U aCEMTRATI(IM VlSfBlLlTV RATEOAT DISTAHGE 

FWW FIRE BWTH GOEFFIGIEUT mFFICIEWT (ItlCt. ItK:GPX) (flrlCL, BKGCO) Fa bCtM RH .(i?J00 FRCm FIRE 

tm3 ~MTERS~ ~FKTERSI CWTERS) tucln**3 3 CPWI (MILES) nl LES <K;w$ 

" - REUTIE MIOITV EeWALS 08 MGEEDS 831 PER CENT, ACTUaL VISIBILlTIES AIUD 6019TRASTS FIAV BE PtUGX LESS THAN ESTIFIATED. 

* DRY MTHER CROSSPtWE VISIBILITIES ARE AT LEI\ST .2500 HILES, AT AUD BEY- .251 Kn FR(3n THE FIRE, 
W5T (HIGHEST) LOU VISIIEIItfV VmRERE#a RISK fWI)EX = 7 - (20 10 46 TIMES BASE LI[XE) 

(THE 131\5E LIWE RISK OF LLWd VISIBILITV mCIPRRE19CE fS AefCKIT f IW 'l000) 

\rK)r;lS;f IWDfVIOUAt erZ:GURREWa aCEWPRATIW/VfSItliILIIV TMLE:: 

fWE FOLLlfaJlWG TABLE 1% MSEQ M A ACallICal aTRASI RAT80 s: Q,OSmCf, MlrN WMlZWTAL CRCM;SPLWE VISlBfLSTY .bOQ MILES, 

DWUlRO Pn GEMIERILI)OE QXf GEMTERLIHE CROISSPLME 

DISTBXS aCEXVRATIOIW GCIUGEMTffAlICtldl VISIBILITY RATEOAT DlSTAIS.wE 

FROllS FIRE (IWt, IBKW) (IICL, @KG603 FClrS LW RW ,25f)ff FRW FIRE 

(1811 (UG1V3 3 (PPMS (MI tES) HlLES (Kn) 

* - WELATIE XWIDITI EWLS OR EXCEEDS 70 PER GEWT, ACTUAL VISIBILITIES AWB C~IRASTS MY BE weH LESS TWAX ESTIMATED, 

* DRY WTHER CROSSQLWE VlSlBlLlfIES ARE AT LEAST -2500 MILES, AT AMD BEVOUD ,251 ICW FRW THE FIRE. 

LRUUC)I[ T 

EX@ OF VSME RUM. 
Appendix IV 

Index of Output Dab 

This appendix gives a detailed index of line and column position and 

for VSMOKE output variables and supposing textual information 

pws in the final output file, VSMOKE.OUT. Lncluded in the appendix are 

line number, column position(s), and (as applicable) input/ou 

appendix is intended to aid those developing automated postin the appendix are given by section and line number, following the order given in 

Appendix III. Even though text is delimited by quotation marks ("1 in this 

appendix, quotes do not appear in the output. Variable names are in capital letters, 

md bkef explanations follew in g n&d, Explanations ae separatd 

from tbe vhabk name by kwo or 

2. - denotes one or more (as specified by m) position "skips" (generally, 

used only for bids), 

3. Lnn - denotes LOGICAL data. where m is the number of spaces allowed for 

the data; generally, only the rightmost position is used to display T or F as 

approlpfiate. 

GER data, where m is the number of spaces allowed for the 

&ta. 

5. Pm.& - denotes WAk, data display4 in dwimal natation, where nn is tk total 

number of spaces allowed for the data; space for the decimal point and possible 

sign must be included; dd is number of places displayed to the right of the decimal 

poht. 

6. Em.dd - denotes MAL d&a displayed in exponential notation, where nn is tk 

total number of spaces allowed for the data, and dd is the number of places 

displayed to the right of the decimal point within the mantissa; nn must be at least 

seven spaces larger than dd to allow space for the decimal point and sign in the 

mantissa and space for the display of the exponent; exponent display is generally 

of the fom Espp, where s is the sign and pp is the positive or negative power of 

10, 

Should VSMOI(E generate a numerical value that "overflows" the space allowed, 

asterisks will occupy the complete field. An attempt has been made to design 

VSMOm so this problem will not occur under ordinary operations using 

physically rmEstic input v~ables. Howem, such behavior clan be "forcec8" kr 

output fields when the ede is mathematitsdIy exercisd. The user should 

note that asterisks cannot be successfully read by a FORTRAN 77 program 

&wtIy into a numerical data field. Because VSMOKE outputs asterisks within its 

t&le Irmdhgs and us@ k splay Egh hu~&t 

related variables, my F 

numerical data will need to test for asterisks within the various specific positions 

dwatd to mme~cd &ta lixnitb the output file, 
bding colons 

Bla& spacers for colons 

Blank spacers for colons 

.*. 

Blanks 

Text for section hader 

.a. 

Text - "mELE:" 

..' 

KTITLE (echo-print) 

1 odd, 1- 45 

1 even, 2- 46 

1 47 

1 48- 61 

1 62- 64 

1 65- 72 

1 73- 80 

1 81 

1 even, 82-126 

1 odd, 83-127 

Lines 2 and 3 are skipped. 

4 1- 30 

4 31- 80 

Lines 5-7 are skipped. 

8 1- 7 

Line 9 is skipped. 

10 1- 72 

... The f Section 1 consists of an echo-print of the data within the input file, 

VSMO length of the remainder of Section 1 and the appearance and location of echoprint data within the output fie, VSMOKE.OUT, depend upon both a within the input fie 

and the methods used by the host eomputer system to process FOR 7 fist-hectd output 

s tsttemnh. 

3.2 may be used. 
Section 2 - Period-byperiod Analysis 

h&g plus signs 1 &, 1- 45 

Blank spams for plus signs 1 even, 2- 46 

Bld leader vvithin 1 47 

ADR 1 48- 61 

1 62- 64 

1 65- 72 

1 73- 80 

Blank: trailer vvithin mmR 

Blank spacers for plus signs 

Trailing plus signs 

-ff - 

"UmDY =It 

LSIBDY (T/F value is on col. 13) 

Blaslks 

ttPEMOD =I1 

I (that is, the PENOD) 

B1& 

'IM 

IRH 

"TONS =It 

TONS 

'@LQMrn =" 

LQMm (TIF value is on cof. 13) 

B1 

I'WNOD 2='t 

WNOD 

- - 1' 

1 81 

1 even, 82- 126 

1 odd, 83-127 

Line 2 is skipped. 

3 1- 72 

4 1-102 

4 103-1 13 

4 114-127 

5 1- 8 

5 9- 13 

5 14- 21 

5 22- 29 

5 30- 34 

5 35- 47 

5 48- 55 

5 56- 60 

5 61- 74 

5 75- 82 

5 83- 93 

5 94- 102 

5 103- 113 

5 114- 127 

6 1- 8 

6 9- 13 

6 14- 21 

6 22- 29 

6 30- 34 

6 35- 47 

6 48- 55 

6 56- 60 

3I2 may tK used 

contintied 
Swtion 2 - Period-by-Period Anafysis (Continued) 

Blah -st - 

Blah 

"CmPM =" 

CRITPM 

"LSIGHT =I' 

LSIGW (TIE; value is on col. 13) 

Blanks 

"msm =" 

msm 

Blanks 

"l[STM =" 

ISTAB 

Blanks 

"THOT =" 

THOT 

Blanks 

"EMTQPM(1) =" 

EMTQPM(1) 

"LGRISE =" 

LGRISE (TIE; value is on col. 13) 

Blanks 

"rnSTRT =I' 

HRSTRT 

Blanks 

"AM* =" 

"TCONST =" 

TCONST 

Blanks 

"EMTQGO(T) ='" 

EMTQCO(f) 

"LTOrnY ='" 

LTOEDY (TIE; value is on eol. 13) 

"U 

U 
Section 2 - Period-by-Period Anatysis (Conhued) 

Variablnext 

B1 

"TDECAY =*' 

TDECAY 

H(I) =" 

EMTQH(0 $*gyF7M =,I 

mAR 

Blanks 

"ALAT =" 

ALAT 

Blanks "om =" 

om 

Blank3 

"EWM =" 

EWM 

Blanks 

"F =" 

F 

"MO =" 

MO 

Blanks 

"ALONG =*I 

ALONG 

Blank3 "om =" 

"EFCO ='" 

EFCO 

"'IDAY =" 

DAY 

"RHO ='" 

RHO 
Seetion 2 - Period-by -Period Amly sis (Continued) 

Blanks 

Bla& 

"EMTQR(I) =" 

ErnQR(? 

12 68- 74 

12 75- 82 

12 83- 93 

12 94- 102 

12 103-1 13 

12 114-127 

Line 13 is skipped. 

Line 14 is slripped. 

"DISPERSION INDEX =" 15 1- 18 

DSPNX (rounded DI value) 15 19- 22 $1 - st 15 23- 25 

KDSPNX(IDX) (DI adjective) 

Blanks 

I1 %KY OCC CE" It X --.I1 

ILVRT (value of LVORI) It - 11 

KLVORT(ILVRI) (describes LVORI) 

RISK OF LOW" 

" VISIBILnY OCCmNCE IS " 

"ABOUT 1 n\J 1000)~' 

15 

15 

15 

15 

15 

15 

15 

16 

16 

16 

16 

Line 17 is skipped. 

LSIGHT = TRUE, THEN: 

Line 18 appears as follows: 

"THE F8 TABLE IS BASED ON" 

"ACRIT RAST RATIO = 0" 

fl VVISLBLK'II = 

VISCRT 

" ME=." 

ELSE IF LSIGHT = FALSE, THEN: 

Line 18 is skippd 

P 

END Line 18 block E* 

Can use F8.6 for col. 6168 
Setton 2 - Period-by-Period Analysis (Continued) 

"PEMOD'" 19 1- 6 

I (that is, the PEHOD) 19 7- 10 

'" SMOm GONG ON'" 19 11- 34 

Line 19 (continud) 

WIGm = TRm9 

Line 19, Col. 35- 54 appears as follows: 

'WSBEEY TABLE " 19 35- 54 

Line 19, Col. 35- 54 appears as follows: 

Line 19, Col. 35-127 block 

tlm~m -." 19 55- 61 

mSM 19 62- 71 

" - - - TWT IS," 19 72- 88 

19 89- 98 

AFTER START TME." 19 99- 127 

Line 20 is skipped. 

LSIGHT = TRUE, THEN: 

Lines 2 1-24 appear as follows: 

I1 

't 

"ICCOmoW~ '* 

" mRTIG& " 

"DISTWCE '" 

'? rnIGHT/ I' 

"DISPERSION " 

"DISPERSION " 

"CONCEWWTION 
£21-PT T 

£T 1-901 

€01-06 

68 -EL 

ZL -SS 

PS -09 

6€ -92 

SZ -PT 

€1 -1 

BZf-PT f 

€1 T-POT 

£0 1 -06 

68 -EL 

ZL -5s 

PS -09 

6E -92 

SZ -PI 

£1 -1 

SZT-$1 ll 

€11-WT 

£0 1 -06 

68 -£L 
Section 2 - Period-by -Period Analysis (Continued) 

'CGOEmCEN '" 

'TOEmCEW " 

"(NCL, BKGPM) " 

"(WCL. BKGCO)'? O M tl 

(ES) If 

(ER) If 

" (METERS) " 

(G M3) It 

It (PPM) " 

ff (rn)'l 

Lines 2 1 to 24 block E. 

- IF LSIGHT = TRU-E, TJ3EN: 

Lines 26-56 appear as follows: 

XKM (downwind distance) 

H (plume heightldepth) 

OY (sigma-y) 

02: (sigma-z) 

CmM (particulate cone.) 

CmCO (carbon monoxide cone.) 

VXPLMI (sighthe visibsty) 

Blank 

Blank (or aste~sk, E RW GE.70%) 

CICOVCT (contrast ratio) 

Blanlc 

Bid (or asterisk, W.GE.70%) 

B1 

Xm (repeated for xadability) 

EWE IF WIGm = E, TmN: 

Lines 26-56 appear as follows: 

OU (sigma-y) 
Section 2 - Period-by-Period Analysis (Continued) 

CHICO (carbon monoxide conc.) 

Blanks 

XKM (repeated for readability) 

END Lies 26 to 56 block IF;. 

- If? LSIGHT = TRUE, THE5N: 

Line 57 appears as follows: 

"BACKGROUND" 

Blanks 

"Nf A" 

Blanks 

"Nllb" 

Blanks 

"N/A" 

Blanks 

CHIPM (particulate conc.) 

CHICO (carbon monoxide conc.) 

VXPLMI (sightline visibility) 

Blank 

Blank (or asterisk, RH.GE.70%) 

CCOVCT (contrast ratio) 

Blank 

Blank (or asterisk, IF; RH.GE 70%) 

Blanks 

"BACKGROUND" (repeated) 

IF LSIGHT = FALSE, THEN: 

Blanks 

"WA" 

Bl 

"NIA" 

Blanks 

"NIA'" 

Blanks 

CHIPM (particulate conmntration) 

CHICO (carbon monoxide concentration) 

Blanks 

Line 57 appears as follows: 
Section 2 - Period-by-Period Analysis (Continued) 

Line 57 block E. 

Line 58 is skipped. 

LSIGHT = TRUE, mLAm HUhrlDSUY EQUALS OR EXCEEDS 70 PERCENT, 

THEN: 

Line 59 appears as follows: 

"" - RELATM mUY " 59 1- 24 A 

"EQUALS OR EXCEEDS 70 PERCENT," 59 25- 54 A 

" ACTUAL WSIBEITES AN11 " 59 55- 79 A 

"CONTRAST RATIOS Y BE MCH " 59 80-101 A 

"LESS THAN ESWTED." 59 102-121 A 

LSIGHT = FALSE, Q& RELATIVE mUY IS LESS 70 PERCENT, THEN: 

Line 59 is skipped, 

Line 59 block E. 

LSIGW = TRUE, THEN: 

Line 60 appears as follows: 

Blank (or asterisk I;E RW.GE.70%) 

B1 

"DRY WAmR CROSSPLW " 

"WsIBEImS ARE " 

"AT LEAST", 'ZESS T 

VISCRT 

LSE If; LSTGHT = FALSE, TmN: 

Line 60 is skipped. 

Line 60 block E. 

' Line 60: First alternative applies if the crossplume visibility 100.000 lan dovrnvvind is at least VISCRT. 

' Line 60: DSm(SVSOK) is the sfio~test downwind distastce far which estimated visibiliv is at least VISCRT at this 

and all longer distances in the 

'" OK for both 
Seetiion 3 - Worst-Case Analysb 

Leading quds signs 1 

Blank spacers for equals sips 1 

Blank spacers for equals signs 1 

Trailing equals signs 1 

Line 2 is skipped. 

KTITLE 3 

Line 4 is slr;ippeQ. 11 5 t t 5 

rnH 5 

"PERCENT" 5 

Line 6 is skipped. 

"WORST (LOWST) " 7 

"DISPERSION INDEX =" 7 

m 7 1s It 7 

KVVDINX (D1 adjective) 7 

Line 8 is skipped. 

"WORST (mGHEST) LOW VISIBLITY " 9 

"OCCURRENCE RISK 9 

mvRI 9 

9 

VRI (LVORI class description) 9 

10 

"LOW V'ISTBILUY OCCmWNCE '" 10 

$'IS mom 1 IN 1000)" 10 

Line 11 is skipped. 

add, 1- 45 

even, 2- 46 

47 

48- 61 

62- 64 

65- 72 

73- 80 

81 

even, 82- 126 

odd, 83- 127 

- IF SIGHT = TRUE, TmN: 

Lies 12 and 13 appear as follows: 

312 may be used 

Continued 
Section 3 - Worst-Case Analysis (Continued) 

"WRST INP)IVDUfi OCCmNCE " 12 

'"Mom CONCENTRATION" 12 

"mSIBLnY TABLE:" 12 

"THI? FOLLOmG TABLE IS BASED ON" 13 

" A CRITICAL COWRAST RATIO = 0" 13 

CCOCRT 13 

", WITH HORII!OWAL CROSSPLME" 13 

" VISIBERY = " 13 

MSCRT 13 

I' MEW. " 13 

ELSE IF LSIGHT = FALSE, TmN: 

Lines 12 and 13 appear as follows: 

"WORST INDIVIDUAL OCCTJIUWNCE " 12 

"SMOKE CONCENTRATION" 12 

"TABLE: " 12 

Line 13 is skipped. 

- END Line 18 block IF. 

Line 14 is skipped. 

- IF LSIGHT = TRUE, TEEN: 

Lines 1 5- 1 8 appear as follows: 

"DO 

"PM It 

"COCEWE~N " 

"CROSSPLmE " 

" COWRAST" 

" DO 

"DISTANCE " 

"CONCEWUTION " 

"CONCE~TION " 

* Can use F8.6 for coL 61-68 
Section 3 - Worst-Case Analysis (Continued) 

Colum(s) Fomat 

"'VISBLLnU '" 

" RATIO AT'" 

" DISTANCE" 

'TROM F 11 

"(INCL. BKGPM) " 

"(INCL. BKGCO) " 

"FORLOW RH " 

VISCRT 

" FROMFm" 

'I (KM) " 

"(UGM')) 11 " 

11 

tt 

ELSE LSIGHT = FALSE, THEN: 

Lines 15-18 appear as follows: 

"DOWNW (I 

"PMCENTEmINE, " 

"CO CENTEUINE," 

" DOWNW" 

"DISTANCE " 

"CONCENTMTION " 

"CONCENTRATION" 

"(INCL. BKGCO)" 

" FROMFIlCE" 

EhV Lines 15 to 18 block E. 

Line 19 is skipped. 
Seetion 3 - Worst-Case Analysis (Continued) 

d distane) 

pm, eonc.) 

WCHCO(J) (worst 60 conc.) 

(J) (sightline visibiEty) 

Bl& (or asterisk, WN GE.70%) 

WCGO(J) (wors t contrm t ratio) 

Blaplk 

Blank (or asterisk, W.CE.70%) 

B1 

DSm(I) (rqedtte3td f;or readabil,) 

Lhes 20-50 appear as follows: 

20-50 

(J) (worst pm. wnc.) 20-50 

U"'GWCO(J) (worst CO m~.) 20-50 

Blah 20-50 

DSm(3) (repeated for readabil.) 20-50 

Line 20 to 50 block E. 

Line 5 1 appas as Collows: 

st bkg, PM cone.) 

WCHCO(2 1) (wrorst blirg. 68 cone.) 

S(2 1) (warst bkg. visibigty) 

B1& 

Blaulk. (or ast~sk, fF RH.GE.70%) 

WCCQ(2 I) (worst eon&ast ratio) 

BIe 

Bl& (or aste~sk, W.GE 70%) 
Sectian 3 - Worst-Case Artialysis (Co~tinaecf) 

Blanks 51 

51 

ELSE WICm -. FWSE, TmN: 

Line 5 1 qpeas as follows: 

'%BAG1KCROUNDf" 51 

WCHPM(2 1) (worst bkg. PM cone.) 51 

WCHICO(21) (wmst bkg. CO cone.) 51 

BfanIrs 51 

51 

Line 52 is shpped. 

If* - YgY It 53 

"'EQ 70 PERGEIV?"," 53 

" ACTUAL VISGEfLRES AND " 53 

"'CONRAST RATIOS MAY BE MKH '93 

"LESS TWPIPI(" ESTMATED." 53 

IS LaS 70 PERCEN'%, THEN: 

Line 53 is sEpged. 

Line 54 appeass as follows: 
Seetion 3 - Worst-Case Analysis (Continued) 

"AT LEAST", a "LESS 54 

VTSCRT 54 

54 

54 

54 

fIE LSIGHT = FALSE, TEN: 

Line 54 is skipped. 

Line 54 block E. 

Line 55 is sfiripped. 

Line 56 is skipped. 

Line 57 is skipped. 

'%RUNOK = " 58 

LRUNOK (LOGICAL, T vs. F, variable) 58 

Line 59 is skipped. 

"END OF VSMOKE RUN." 60 

Line 54: First alternative applies if the crossplume visibility 100.000 km downwind of the fire (i.e., Ule value of 

VXPLMI at line 50, cols. 45-58) is at least VISCRT; othenuise, the second alternative applies. 

Line 54: DSKM(NSOK) is the shortest downwind distvlce for which estimated visibility is at least VISCRT at this 

and all long= &stan- analyzed in the pro 

OK for bth. 
List of Figures 

1 . Time dependence of fire characteristics assumed in VSMOKE ............................. 6 

2 . EfGects of plume rise options on smoke concentrations at the ground ....................... 15 

3 . Idealized Gaussian Plume Model ................................................... 21 

4 . Vertical "reflections" from ground and mixing height "lid" in a Gaussian plume model ......... 23 

5 . Line sources in a Gaussian Plume Model ............................................. 25 

6 . Effects of Gaussian dispersion on an initially vertically uniform distribution .................. 26 

7 . Virtual distance concept .......................................................... 32 

8 . VSMOKE centerline vs . fixed grid point receptor ...................................... 35 

9 . Construction of horizontal crossplume sightlines for VSMOKE ........................... 43 

10 . Sightline breakthrough zone behavior with very clear background in VSMOKE ............... 44 

11 . Some sightline effects for directions not treated in VSMOKE ............................. 47 

12 . Dispersion index emissions model as used in VSMOKE ................................. 48 

13 . Flowchart of FORTRAN 77 computer code for VSMOKE, Version 19950128 ............... 59 

14 . Outline of VSMOKE output file, VSMOKE.OUT ...................................... 84 
Table IStabllity class dependent constsnts for dete 

equation 23 

Stabi2ity class Value of A blue of B 

1 - extremely unstable 

2 - moderately unstable; 

3 - slightly unstable 

4d - near neutral - day 

4n - near neutral - night 

5 - slightly stable 

6 - mod~ately stable 

7 - extremely stable 

Table GApproldmate horizontal spread angles in degrees as a function 

of downwind distance and stability class 

Downwind - - - - - .. - - - - - - - Stability class - - - - - - - - - - - - - .. - - 

distance 1 2 3 4(dln)" 5 6 or 7 

a Horizontal spread angles are the same for stability class 4--day or night. 
Table Htabitity class and downwind dishnee dependent corwltants for 

o, in equation 24 

Stability Dow~d 

class dis tam Value of C Value of D 

all 

4 day 

4 day 

4 night 

4 night 

4 night 

4 night 

4 night 

4 night 

Continued 
ability elass arnd downwind dist518aee dependeat constaab far 

determi~irtlg a, in equation 24 (coratiaaed) 

Shbilify Domwind 

class dismce Value oEC Value of D 

Table &Dispersion Index Interpretation, adapted from Lavdas (1986) 

DI value Interpretation Conditions 

> 100 Very Good May indicate hazardous burning conditions; 

check fire weather 

61 - 100 Good "Good burning weather" conditions (Southern Forest 

Fire Laboratory Personnel 1976) are typically in this range 

41 - 60 Fair to Good Climatological afternoon values in most inland forested 

areas of the United States are in this range 

21 - 40 Fair Stagnation may be indicated if accompanied by persistent 

low windspeeds 

13 - 20 Fair to Poor Stagnation if persistent, but better than average for a night 

value 

7- 12 Poor Stagnant at day, but near or above average at night 

1- 6 Very Poor Very frequent at night, occurs on a majority of nights in 

may locations 
IrtcJex based on the prapcrfiti~n af aceidem wigh fog alftdcVor smoks?, as repcsrW by the marfds 

mghway Patsol, 18879-1981, (Lavdas and Hauck l991) 

Dispersion hdex 

Reiative 

Hu~bif y 1 2 3-4 5-6 "1-8 9-10 11-12 13-16 17-20 21-25 26-30 31-40 340 

Key to 10-poinl scale: 

1 - Lowest proportion of accidents with fog andlor smoke reported (130 out of 127,604 accidents, or just over 

1 out of Z ,000 aeeidents in t&s category) 

2 - Physical or statistical reasons for not including as a part of category 1, but proportion of accidents with fog 

andor smb not signifiemtly Inigher 

3 - Higher proportion of accidents than category 1, by about 30 to 50 percent, marginally significant 

4 - Significantly higher proportion than category 1, by about a factor of 2 

5 - Significantly higher proportion than category 1, by a factor of 3 to 10 

6 - Significantly higher proportion than category 1, by a factor of 10 to 20 

7 - Significantly higher proportion than category 1, by a factor of 20 to 40 

8 - Significantly higher proportion than category 1, by a factor of 40 to 75 

9 - Significantly higher proportion than category 1, by a factor of 75 to 125 

10 - Significantly higher proportion than category 1, by about a factor of 150 

Note: The overall number of accidents with fog, smoke, or both reported is 3,235 out of a total of 433,649 

accident reports analyzed. Of these, 604 included smoke, 2,972 included fog, and 341 included both. 
Table &Index of downwind distances by Line number for 

concentration (/visibility) tables in output Sections 2 and 3 

Peridpage 

he number Line number 

from fire for Section 2 for Section 3 
Index (pages in boldface contain primary definitions or discussions for the given entry) 

Almanac, 3 1,99 

Best estimates, 4 

"Bottom line", 14, 30, 73 

Breakthrough sightline, 42-44, 139 

Carbon monoxide, 6, 17,28, 71, 72, 77, 80-82, 84, 85, 87, 88, 94, 96,98,101-102, 103-104, 108, 

109, 113-115, 130, 131 

CDM (US. EPA model), 29,90 

Centerline, 19, 20,24, 30, 33-36, 38,40-42,46, 71, 86, 87, 95, 114, 116, 128, 129, 134, 135, 139 

Conservative estimates, 4, 17, 18,95,98-100, 102 

Contrast ratio, 4,40-42,44-46,71,72, 77, 84, 88, 89, 94, 95, 103, 1 14- 1 16, 127, 130-1 32, 134, 

136,137 

CRSTER (U.S. EPA model), 40,42,98 

Dispersion Index, i, 1,4,46-50, 84, 89, 90, 1 14, 127, 133, 139, 142, 143 

Effective depth, 28, 48,49, 72 

Emissions model(s), 1, 4,6,48, 102, 139 

Emission rate, 6,7, 9,20, 34, 37,48, 58,77, 81, 82, 87, 94, 97, 101-103, 107, 109, 110, 113 

EmPM (USDA, Forest Service model), 6, 102 

(as Sandberg and Petersen), 6, 7, 9 1, 102, 109 

First order decay, 17 

Gaussian plume model, 1, 3,4, 13, 14, 16-39,41, 91, 139 

Gradual plume rise, 1 1, 14,26,27, 97, 104 

Graphical display programs, 1,4 

Heat emission rate, 4, 6, 7, 9,21, 34,48, 71, 77, 82, 94, 102, 110, 114 

High humidity, 45,46, 50, 122 

MPUFF (U.S. EPA model), 5, 14, 18, 96, 97 

Input variables (see end of index) 

Low Visibility Occurrence Risk Index (LVORI), 1 , 5,50-53,7 1,72, 84, 88, 89, 1 14, 127, 133, 

143, 

Mixing height (input as AMMA), 1 1, 12, 19,2 1-23,27, 34,38,46,48,49, 5 1, 72, 79, 81, 99-100, 

103-105, 113, 139 

Narrow plume models, 37 

Organic soil@), 88, 96, 97, 108-1 10 

PAL (U. S. EPA model), 1 8,9 1 

Particulate matter, 6,28,40,41,45,46, 71,72,77,80-82, 84, 85, 87, 88,91, 94, 96, 101, 102, 103, 

104, 108, 109, 113-115 

Plume rise, 4, 5, 8-14, 15,26,27, 31, 33, 37, 38,48,49,71-73, 77, 78, 80-82, 89, 90, 94, 96-98, 

100, 102,104, 110,113, 114,139 

PL (U.S. EPA model), 5, 34, 91 

Saturation, 45, 88 

Screening system, 5, 17, 18 

Sightline, 3-5,40-46,47, 73, 76, 77, 84, 88, 94, 95, 101, 103, 107, 112-116, 122, 130, 131, 

136, 139 

Smolder(ing), 6, 8, 12, 17, 20, 38, 39,46, 49, 88, 96, 97, 102, 108-110 

Snapshot, 20, 108-1 10 
Stability class (input as ISTABA), 12,20,21,29,30,31-33,38,46,49, 51, 52, 58,76, 79, 80, 

86,93,94,99, 103-185, 107, 108, 1 12, 113,140-142 

Transport windspeed (input as UA), 12, 13,21,34,38,46,51,79,81,100,103-105,113 

U,S.EPA, 1,3, 16, 18,22,29, 31,33,34,48,77, 82, 89-"a2,98, 108 

Ventilation factor, 46 

Vir@ual distaslce(s), 29,30-3%,32,71-73, 100, 139 

Visibility, 1,4, 5, 30, 34,40-42,44-46,50-53,72,74,77,81,84, 87-89,91,93,94,95, 100, 101, 

103, 107, 108, 114-116, 127-136, 138, 143, 144 

Visual obscuration, 88 

VSMOKE.IPT (computer file), 1, 53, 56-58,74,75,94,93-102, 103-1 10, 1 12, 1 15, 1 17, 123 

VSMOm.OJT (computer file), 1, 53, 56, 57,72,75,82-85, 93, 211-138, 139 

VSMOKE.SGR (computer file), 57, 58, 71, 82, 82, 83, 85, 93 

Weather map, 1 9 

Wind fluctuation(s), 14, 16, 17, 30, 86 

Wind variation(s), 5, 16, 37, 39, 86 

Worst-case, 3,4, 18, 57,71,83-85, 98,99, 110, 115, 116, 133-138 

70 percenl (relative humidiQ), 3,4,40,45,87,88, 113-1 15, 130-132, 136-137 

ay, 20-24,27,29-3 1, 36,4 1,73, 86, 140 

QZ ,20-22, 24,26, 27,29-3 1, 141, 142 

X, 41,42,46 

Input variables: 

ACmS, 7, 77,95, 101, 103-105, 107, 109, 110, 113, 124 

ALAT, 76,93,103, 105,107, 108,110, 112, 126 

ALONG, 76,93, 103, 105, 108, 110, 112, 126 

A, 79-8%,99-100, 104, 105, 107, 1 13 

BKGCOA, 79-81,101, 104, 105, 107, 109,110 

BKGPMA, 77,71)-81,82,87,101, 102,104, 105, 107, 109 

CCOCRT, 76, 77, 88, 89,94-95, 103, 105, 107, 109, 110, 113-115, 127, 134 

CEIL, 80,81,99, 107,108 

EFCO, 77-78,96, 104, 105, 109, 110, 113, 126 

EFPM, 77,80,81,87,96, 101, 104,105,109,110, 113,126 

EMTQCQ, 81,82,95,102, 1 liO, 113, 125 

EMaqH,8I982,95,102, 110,114,126 

EMTQPM, 80,81-82,87,95, 101,102, 1 10, 113, 125 

EMTQR, 80,81682, 96, 100, 101,102, 110, 113, 114, 127 

VL, 76,79-81, 83, 93,94, 96,97, 103, 105, 107, 108, 110, 112, 125 

HRSTRT, 76, 79-81,83,85,93,94,96, 103, 105, 108, 110, 112, 125 

ICOWK 80,81,99,107,108 

,76? 78,93-94,96, 103, 105, 108, 1 10, 112, 126 

,79,80,98-99, 104, 105, 107, 109, 112 

ISTmA, 79,80,99, 104, 105, 1 13 

IYEAR, 76,78,93-94,96, 103,105,108, 1 10,112, 126 

KTITLE, 75,76,93, 103, 105-107, 109, 110, 11 1, 112, 115, 123, 124, 133 
LGRISE, 11,77,78,97, 104, 105, 110, 112, 125 

LQREAD, 13,74,76-77,78,94,95-98, 101, 103, 105, 107, 109, 112-1 14, 124 

LSIGHT, 76, 77,94, 101, 103, 105, 107, 112-116, 125, 127-138 

LSTBDY,74,76,78,80,81,94,99,103,105,107,112,113,124 

LTOFDY, 79,99, 104, 105t 1 12, 125 

MO, 76,78,93-94,96, 103, 105, 108, 110, 112, 126 

NLPAGE, 75,93, 103, 105, 107, 1 1 1 

NPRIOD, 76,77,78, 80, 81, 83, 85, 93,94,96, 103, 105, 108, 110, 112, 124 

81,82,101, 110 

,79,80,98,104,105,1079 109,110 

,79-81,100-101, 104, 105, 107, 109, 113 

,79-81,100-101, 104, 105, 107, 109, 113 

PPA, 79,80,98,104, 105 

WRC, 13,77, 78, 80, 81, 96,98, 100-102, 104, 105, 107, 109, 110, 113, 127 

TCONST, 6,7,77,78,97, 104, 105, 109, 110, 113, 125 

TDECAY, 6,7,77,78,97, 104-106, 109, 110, 113, 126 

,7, 77, '78, 83, 85, 93, 94,96, 97, 104, 105, 109, 110, 113, 125 

,6, 7,77,78,96-97, 104, 105, 109, 110, 113, 125 

,76,93,103,105, 108,110, 112,126 

TONS, 77,95,104,105,109,110,113, 124 

TTA, 79,88,98,104,105 

UA, 79-81,100, 104, 105, 107, 109, 113 

VISCRT, 76,77,89,95,103, 105, 107, 109, 110, 113-115, 127, 129, 132, 134, 135, 138 

WSSFC, 80,81,99,107