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'''Biomass''', a source of [[renewable energy]], is [[biology|biological]] material such as wood, wood waste, municipal solid waste, straw, sugar cane, algae, and many other byproducts derived from agricultural and forestry production as well as other sources. Since biomass derives from plants generated by [[solar energy]] in the [[photosynthesis]] process, it can also be defined as the biological material on [[Earth]] that has stored solar energy in the chemical bonds of the organic material.
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[[File:Crude oil-fired power plant.jpg|thumb|right|225px|Industrial air pollution source]]
Atmospheric dispersion modeling is the mathematical simulation of how air pollutants disperse in the ambient atmosphere. It is performed with computer programs that solve the mathematical equations and algorithms which simulate the pollutant dispersion. The dispersion models are used to estimate or to predict the downwind concentration of air pollutants emitted from sources such as industrial plants, vehicular traffic or accidental chemical releases.  


The [[fossil fuels]] ([[coal]], [[petroleum crude oil]] and [[natural gas]]) are currently thought to have been formed from prehistoric, ancient biomass buried deeply underground over millions of years of [[geological time]]. Therefore, they are not considered to be renewable sources of energy
Such models are important to governmental agencies tasked with protecting and managing the ambient air quality. The models are typically employed to determine whether existing or proposed new industrial facilities are or will be in compliance with the National Ambient Air Quality Standards (NAAQS) in the United States or similar regulations in other nations. The models also serve to assist in the design of effective control strategies to reduce emissions of harmful air pollutants. During the late 1960's, the Air Pollution Control Office of the U.S. Environmental Protection Agency (U.S. EPA) initiated research projects to develop models for use by urban and transportation planners.<ref>J.C. Fensterstock et al, "Reduction of air pollution potential through environmental planning", ''JAPCA'', Vol. 21, No. 7, 1971.</ref>  


==Uses of biomass==
Air dispersion models are also used by emergency management personnel to develop emergency plans for accidental chemical releases. The results of dispersion modeling, using worst case accidental releases and meteorological conditions, can provide estimated locations of impacted areas and be used to determine appropriate protective actions. At industrial facilities in the United States, this type of consequence assessment or emergency planning is required under the Clean Air Act (CAA) codified in Part 68 of Title 40 of the Code of Federal Regulations.


===Biomass fuel for electric power production===
The dispersion models vary depending on the mathematics used to develop the model, but all require the input of data that may include:


The direct combustion of biomass for producing [[heat]] and [[electric power]] provides a ready disposal mechanism for municipal, agricultural, and industrial organic wastes. In 2009, about 11,350 [[megawatts]] (MW) of electric power, amounting to 1.1% of the summertime electrical supply in the [[United States]] was generated by burning biomass that included: wood, wood waste, [[municipal solid waste]] (MSW), [[landfill gas]], and agricultural byproducts and waste.<ref>[http://www.eia.doe.gov/cneaf/alternate/page/renew_energy_consump/table4.html U.S. Electric Net Summer Capacity] [[U.S. Energy Information Administration]] (EIA), part of the [[U.S. Department of Energy]]</ref>
* Meteorological conditions such as wind speed and direction, the amount of atmospheric turbulence (as characterized by what is called the "stability class"), the ambient air temperature, the height to the bottom of any inversion aloft that may be present, cloud cover and solar radiation.
* The emission parameters such the type of source (i.e., point, line or area), the mass flow rate, the source location and height, the source exit velocity, and the source exit temperature.
* Terrain elevations at the source location and at receptor locations, such as nearby homes, schools, businesses and hospitals.
* The location, height and width of any obstructions (such as buildings or other structures) in the path of the emitted gaseous plume as well as the terrain surface roughness (which may be characterized by the more generic parameters "rural" or "city" terrain).


The New Hope Power Partnership in [[Florida]] is the largest biomass power plant in [[North America]]. It generates 140 MW of power using uses sugar cane fiber ([[bagasse]]) and recycled wood as fuel.<ref>[http://www.psc.state.fl.us/utilities/electricgas/RenewableEnergy/Cepero-OCFC.pdf Agriculture & Renewable Energy: The Partnership for a New Frontier] Florida Power Service Commission (FPSC) Workshop, July 26, 2007.</ref> It has been in operation for more than 10 years.
Many of the modern, advanced dispersion modeling programs include a pre-processor module for the input of meteorological and other data, and many also include a post-processor module for graphing the output data and/or plotting the area impacted by the air pollutants on maps. The plots of areas impacted usually include isopleths showing areas of pollutant concentrations that define areas of the highest health risk. The isopleths plots are useful in determining protective actions for the public and first responders.


===Production of ethanol and biodiesel fuels===
The atmospheric dispersion models are also known as atmospheric diffusion models, air dispersion models, air quality models, and air pollution dispersion models.


There are several processes  available for converting the [[Energy (science)|chemical energy]] contained in biomass into liquid fuels such as [[biodiesel]] and [[ethanol]].
==Atmospheric layers==


====Ethanol fuel====
Discussion of the layers in the Earth's atmosphere is needed to understand where airborne pollutants disperse in the atmosphere. The layer closest to the Earth's surface is known as the ''troposphere''. It extends from sea-level up to a height of about 18 km and contains about 80 percent of the mass of the overall atmosphere. The ''stratosphere'' is the next layer and extends from 18 km up to about 50 km. The third layer is the ''mesosphere'' which extends from 50 km up to about 80 km. There are other layers above 80 km, but they are insignificant with respect to atmospheric dispersion modeling.


Ethanol fuel is [[ethyl alcohol]] (C<sub>2</sub>H<sub>5</sub>OH) and it is most often used as an automotive [[motor fuel]], mainly as an additive for [[gasoline]]. Ethanol can be produced by [[fermentation]] of [[sugar cane]], [[bagasse]], [[sugar beet]]s, [[barley]], [[potato]]es, [[corn]] and many other grains as well as many agricultural byproducts and wastes.
The lowest part of the troposphere is called the ''atmospheric boundary layer (ABL)'' or the ''planetary boundary layer (PBL)'' and extends from the Earth's surface up to about 1.5 to 2.0 km in height. The air temperature of the atmospheric boundary layer decreases with increasing altitude until it reaches what is called the ''inversion layer'' (where the temperature increases with increasing altitude) that caps the atmospheric boundary layer. The upper part of the troposphere (i.e., above the inversion layer) is called the ''free troposphere'' and it extends up to the 18 km height of the troposphere.


The worldwide production of ethanol for automotive fuel in 2007 was 52,000,000,000 [[litre]]s. From 2007 to 2008, the share of ethanol in global gasoline use increased from 3.7% to 5.4%.<ref name=UNEP>[http://www.unep.fr/scp/rpanel/pdf/Assessing_Biofuels_Full_Report.pdf Assessing Biofuels (2009)] From the website of the [[United Nations Environment Programme]] (UNEP)</ref> In 2009, worldwide ethanol fuel production reached 19.5 billion gallons (73.9  billion liters).<ref name=RFA2009>[http://www.ethanolrfa.org/page/-/objects/pdf/outlook/RFAoutlook2010_fin.pdf?nocdn=1 2010 Ethanol Industry Outlook] From the website of the Renewable Fuels Association (RFA).</ref>
The ABL is the most important layer with respect to the emission, transport and dispersion of airborne pollutants. The part of the ABL between the Earth's surface and the bottom of the inversion layer is known as the ''mixing layer''. Almost all of the airborne pollutants emitted into the ambient atmosphere are transported and dispersed within the mixing layer. Some of the emissions penetrate the inversion layer and enter the free troposphere above the ABL.


Ethanol fuel is widely used in [[Ethanol fuel in Brazil|Brazil]] and in the [[Ethanol fuel in the US|United States]], and together both countries were responsible for 86 percent of the world's ethanol fuel production in 2009.<ref name=RFAstats2009>{{cite web|url=http://www.ethanolrfa.org/page/-/objects/pdf/outlook/RFAoutlook2010_fin.pdf?nocdn=1|title=2009 Global Ethanol Production (Million Gallons)|publisher=[[F.O. Licht]], cited in [[Renewable Fuels Association]], Ethanol Industry Overlook 2010, pp. 2 and 22|year=2010|accessdate=2011-02-12}}</ref>  Most cars on the road today in the U.S. can run on [[Common ethanol fuel mixtures#E5, E7, E10|blends of up to 10% ethanol]],<ref>Worldwatch Institute and Center for American Progress (2006). [http://images1.americanprogress.org/il80web20037/americanenergynow/AmericanEnergy.pdf ''American energy: The renewable path to energy security'']</ref> and the use of 10% ethanol gasoline is mandated in some U.S. states and cities. Since 1976 the Brazilian government has made it mandatory to blend ethanol with gasoline, and since 2007 the legal blend is around [[Common ethanol fuel mixtures#E20, E25|25% ethanol and 75% gasoline]] (E25).<ref name="Portaria2007">{{cite web|url=http://extranet.agricultura.gov.br/sislegis-consulta/consultarLegislacao.do?operacao=visualizar&id=17886|title=Portaria Nº 143, de 27 de Junho de 2007|publisher=Ministério da Agricultura, Pecuária e Abastecimento|accessdate=2008-10-05|language=Portuguese}}</ref> In addition, by December 2010 Brazil had a fleet of 12 million [[flexible-fuel vehicle|flex-fuel automobiles and light trucks]] and over 500 thousand flex-fuel [[motorcycle]]s regularly using neat ethanol fuel (known as [[Neat alcohol fuel|E100]]).<ref name=ANFAVEA4/><ref name=ANFAVEA2/><ref name=MotoFlex10/><ref name=MotoFlex09/>
In summary, the layers of the Earth's atmosphere from the surface of the ground upwards are: the ABL made up of the mixing layer capped by the inversion layer; the free troposphere; the stratosphere; the mesosphere and others. Many atmospheric dispersion models are referred to as ''boundary layer models'' because they mainly model air pollutant dispersion within the ABL. To avoid confusion, models referred to as ''mesoscale models'' have dispersion modeling capabilities that can extend horizontally as much as  a few hundred kilometres. It does not mean that they model dispersion in the mesosphere.


==Gaussian air pollutant dispersion equation==


====Biodiesel fuel====
The technical literature on air pollution dispersion is quite extensive and dates back to the 1930s and earlier. One of the early air pollutant plume dispersion equations was derived by Bosanquet and Pearson.<ref>C.H. Bosanquet and J.L. Pearson, "The spread of smoke and gases from chimneys", ''Trans. Faraday Soc.'', 32:1249, 1936.</ref> Their equation did not assume Gaussian distribution nor did it include the effect of ground reflection of the pollutant plume.
Biodiesel refers to a [[Diesel oil|diesel fuel]] produced by chemically [[Chemical reaction|reacting]] [[lipids]] such as  vegetable oils or animal fats with an [[alcohol]] such as [[methyl alcohol]]. The resulting biodiesel consists of [[esters]] of long-chain [[fatty acid]]s. The process is known as "transesterification" and it may be carried out by several methods: the common batch process, supercritical processes and ultrasonic methods.


===Biomas gasification===
Sir Graham Sutton derived an air pollutant plume dispersion equation in 1947<ref>O.G. Sutton, "The problem of diffusion in the lower atmosphere", ''QJRMS'', 73:257, 1947.</ref><ref>O.G. Sutton, "The theoretical distribution of airborne pollution from factory chimneys", ''QJRMS'', 73:426, 1947.</ref> which did include the assumption of Gaussian distribution for the vertical and crosswind dispersion of the plume and also included the effect of ground reflection of the plume.
 
While there are many methods for processing biomass currently in use, the most important three are [[gasification]], [[syngas]] cleaning/processing, and [[Fischer-Tropsch synthesis]].<ref name=Damartzis>{{cite journal| author=T. Damartzis and A. Zabaniotou|title=Thermochemical conversion of biomass to second generation biofuels through integrated process design-A review|journal=Renewable & Sustainable Energy Reviews|volume=15|issue=1|pages=366-378|date=Jan. 2011|id=|url=}}</ref>


== Biomass gasification ==
Under the stimulus provided by the advent of stringent environmental control regulations, there was an immense growth in the use of air pollutant plume dispersion calculations between the late 1960s and today. A great many computer programs for calculating the dispersion of air pollutant emissions were developed during that period of time and they were commonly called "air dispersion models". The basis for most of those models was the '''Complete Equation For Gaussian Dispersion Modeling Of Continuous, Buoyant Air Pollution Plumes''' shown below:<ref name=Beychok>{{cite book|author=M.R. Beychok|title=Fundamentals Of Stack Gas Dispersion|edition=4th Edition| publisher=author-published|year=2005|isbn=0-9644588-0-2}}.</ref><ref>{{cite book|author=D. B. Turner| title=Workbook of atmospheric dispersion estimates: an introduction to dispersion modeling| edition=2nd Edition |publisher=CRC Press|year=1994|isbn=1-56670-023-X}}.</ref>


Gasification is a process of burning the biomass source at a relatively high temperature to release carbon monoxide and [[hydrogen]].  This process can occur through the use of [[oxygen]], [[air]], [[steam]], or mixtures similar to these.<ref>{{cite journal| author=S. Albertazzi et al|title=The technical feasibility of biomass gasification for hydrogen production|journal=Catalysis Today|volume=106|issue=1-4|pages=297-300|date=Oct. 15, 2005|id=|url=}}</ref> When air is used to carry out the gasification process the required amount of [[heat]] is a relatively low to medium heating value.  This process requires less thermal energy to complete but creates higher levels of unwanted by-products such as [[methanol]] and less of the useable hydrogen product.  The use of steam requires a higher amount of thermal energy to carry out the process but will yield higher amounts of actual hydrogen and lower amounts of by-products.  Gasification involves four main steps, drying, [[pyrolysis]], [[reduction]] and [[combustion]].  The drying process consists of taking the biomass source and removing all the moisture.  After the moisture is removed the resulting substance enters the pyrolysis zone.  This is where [[Volatility (chemistry)|volatiles]] are removed in the form of carbon monoxide and carbon dioxide and also where tar is produced.  After this process occurs the resulting substance goes over to the reduction zone where the raw materials are completely gasified in order to create a syngas product.  Finally in the combustion zone the left-over char material is burned which produces more gaseous product and also produces the necessary heat for the reactions in the previously mentioned reduction zone. The end product is known as syngas.  Syngas can be used as a fuel or it can be further processed to create [[synthetic natural gas]] (SNG) or synthetic [[Petroleum crude oil|petroleum]]. 


== Syngas purification ==
<math>C = \frac{\;Q}{u}\cdot\frac{\;f}{\sigma_y\sqrt{2\pi}}\;\cdot\frac{\;g_1 + g_2 + g_3}{\sigma_z\sqrt{2\pi}}</math>


When syngas is used for further processing it undergoes a cleaning and purification stage. The gas cleaning stage is the first stage of syngas purification.  This process involves the use of mechanical filters which remove [[particulate matter]], and [[Adsorption|adsorbents]] that remove the [[alkali]] and [[sulfur]] compounds in the gas.  The remaining tar in the gas is then broken down through the use of [[catalysis]] and steam.<ref name=Damartzis/> Syngas cleaning is a crucial step in preventing the fouling of machinery or contamination of catalysts when further processing the gas. 
{| border="0" cellpadding="2"
|-
|align=right|where:
|&nbsp;
|-
!align=right|<math>f</math>  
|align=left|= crosswind dispersion parameter
|-
!align=right|&nbsp;
|align=left|= <math>\exp\;[-\,y^2/\,(2\;\sigma_y^2\;)\;]</math>
|-
!align=right|<math>g</math>
|align=left|= vertical dispersion parameter = <math>\,g_1 + g_2 + g_3</math>
|-
!align=right|<math>g_1</math>
|align=left|= vertical dispersion with no reflections
|-
!align=right|&nbsp;
|align=left|= <math>\; \exp\;[-\,(z - H)^2/\,(2\;\sigma_z^2\;)\;]</math>
|-
!align=right|<math>g_2</math>
|align=left|= vertical dispersion for reflection from the ground
|-
!align=right|&nbsp;
|align=left|= <math>\;\exp\;[-\,(z + H)^2/\,(2\;\sigma_z^2\;)\;]</math>
|-
!align=right|<math>g_3</math>
|align=left|= vertical dispersion for reflection from an inversion aloft
|-
!align=right|&nbsp;
|align=left|= <math>\sum_{m=1}^\infty\;\big\{\exp\;[-\,(z - H - 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
|-
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z + H + 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
|-
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z + H - 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
|-
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z - H + 2mL)^2/\,(2\;\sigma_z^2\;)\;]\big\}</math>
|-
!align=right|<math>C</math>
|align=left|= concentration of emissions, in g/m³, at any receptor located:
|-
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; x meters downwind from the emission source point
|-
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; y meters crosswind from the emission plume centerline
|-
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; z meters above ground level
|-
!align=right|<math>Q</math>
|align=left|= source pollutant emission rate, in g/s
|-
!align=right|<math>u</math>
|align=left|= horizontal wind velocity along the plume centerline, m/s
|-
!align=right|<math>H</math>
|align=left|= height of emission plume centerline above ground level, in m
|-
!align=right|<math>\sigma_z</math>
|align=left|= vertical standard deviation of the emission distribution, in m
|-
!align=right|<math>\sigma_y</math>
|align=left|= horizontal standard deviation of the emission distribution, in m
|-
!align=right|<math>L</math>
|align=left|= height from ground level to bottom of the inversion aloft, in m
|-
!align=right|<math>\exp</math>
|align=left|= the exponential function
|}


== Fischer-Tropsch synthesis ==
The above equation not only includes upward reflection from the ground, it also includes downward reflection from the bottom of any inversion lid present in the atmosphere.


The last commonly used stage of processing biomass is known as Fischer-Tropsch synthesis.  Purified syngas will be processede through a series of catalytic steps which will eventually transform the gas into a liquid fuel.<Ref name=Damartzis/> This fuel can be used in standard piston engines and can substitute for the use of fossil fuels.  This process requires substantial thermal energy to carry out and is a relatively costly process. Efforts have been made to reduce the costs of this process to make it a reasonable competitor to the processing of oil for the creation of petroleum based fuels.
The sum of the four exponential terms in <math>g_3</math> converges to a final value quite rapidly. For most cases, the summation of the series with '''''m''''' = 1, '''''m''''' = 2 and '''''m''''' = 3 will provide an adequate solution.


==Risks of biomass processing==
<math>\sigma_z</math> and <math>\sigma_y</math> are functions of the atmospheric stability class (i.e., a measure of the turbulence in the ambient atmosphere) and of the downwind distance to the receptor. The two most important variables affecting the degree of pollutant emission dispersion obtained are the height of the emission source point and the degree of atmospheric turbulence. The more turbulence, the better the degree of dispersion.


The risk level of biomass processing depends largely on the inspection and maintenance standards of the processing facility.  From 2006 to 2010 there have been approximately 100 incidents in the United States regarding the processing of biomass to produce biofuels.  From 2006 to 2009 there have been 8 fires and 6 explosions on the basis of about 200 biodiesel facilities.  Some of these explosions were responsible for the complete destruction of their respective plants.  However, 50% of the incidental cases in the last 5 years have not involved the process under normal conditions and 22 % of the incidents have been related to tank storage (overfilling, leaks, etc.).<ref>{{cite journal| author=E. Salzano, M. Di Serio and E. Santacesaria|title=Emerging Risks in the Biodiesel Production by Transesterification of Virgin and Renewable Oils|journal=Energy & Fuels|volume=24|issue=| pages=6103-6109|date=Nov. 2010|id=|url=}}</ref> Given that maintenance is properly carried out, incidents such as these will rarely occur.  The unstable nature of the materials in addition to the poor plant regulation is the reason why incidents are so frequent.  As a result, improvement efforts on regulation, inspection, and maintenance of the processing plants have been carried out with the goal of drastically reducing the number of incidents.  
Whereas older models rely on stability classes for the determination of <math>\sigma_y</math> and <math>\sigma_z</math>, more recent models increasingly rely on Monin-Obukhov similarity theory to derive these parameters.


==Setbacks and the future of biomass==
==Briggs plume rise equations==


The cost of collecting and processing biomass is the current main concern for the energy and transportation industries.  Efforts are being made to expand the production and distribution of these fuels in order to lower costs to the consumer. However, costs of biofuels are still far higher than the costs of petroleum based fuelsThe environmental availability of biomass is not an issue because sources such as food waste and other forms of waste are constantly being renewed. As prices for petroleum based fuels continue to rise and more efficient technologies for processing biomass are developed, demand for these alternative fuels will begin to increase considerably. As a result, biomass may very well be the alternative fuel source of choice for the immediate future.
The Gaussian air pollutant dispersion equation (discussed above) requires the input of ''H'' which is the pollutant plume's centerline height above ground level. ''H'' is the sum of ''H''<sub>s</sub> (the actual physical height of the pollutant plume's emission source point) plus Δ''H'' (the plume rise due the plume's buoyancy).
 
[[File:Gaussian Plume.png|thumb|right|333px|Visualization of a buoyant Gaussian air pollutant dispersion plume]]
 
To determine Δ''H'', many if not most of the air dispersion models developed between the late 1960s and the early 2000s used what are known as "the Briggs equations." G.A. Briggs first published his plume rise observations and comparisons in 1965.<ref>G.A. Briggs, "A plume rise model compared with observations", ''JAPCA'', 15:433–438, 1965.</ref> In 1968, at a symposium sponsored by CONCAWE (a Dutch organization), he compared many of the plume rise models then available in the literature.<ref>G.A. Briggs, "CONCAWE meeting: discussion of the comparative consequences of different plume rise formulas", ''Atmos. Envir.'', 2:228–232, 1968.</ref> In that same year, Briggs also wrote the section of the publication edited by Slade<ref>D.H. Slade (editor), "Meteorology and atomic energy 1968", Air Resources Laboratory, U.S. Dept. of Commerce, 1968.</ref> dealing with the comparative analyses of plume rise modelsThat was followed in 1969 by his classical critical review of the entire plume rise literature,<ref>G.A. Briggs, "Plume Rise", ''USAEC Critical Review Series'', 1969.</ref> in which he proposed a set of plume rise equations which have become widely known as "the Briggs equations".  Subsequently, Briggs modified his 1969 plume rise equations in 1971 and in 1972.<ref>G.A. Briggs, "Some recent analyses of plume rise observation", ''Proc. Second Internat'l. Clean Air Congress'', Academic Press, New York, 1971.</ref><ref>G.A. Briggs, "Discussion: chimney plumes in neutral and stable surroundings", ''Atmos. Envir.'', 6:507–510, 1972.</ref>
 
Briggs divided air pollution plumes into these four general categories:
* Cold jet plumes in calm ambient air conditions
* Cold jet plumes in windy ambient air conditions
* Hot, buoyant plumes in calm ambient air conditions
* Hot, buoyant plumes in windy ambient air conditions
 
Briggs considered the trajectory of cold jet plumes to be dominated by their initial velocity momentum, and the trajectory of hot, buoyant plumes to be dominated by their buoyant momentum to the extent that their initial velocity momentum was relatively unimportant.  Although Briggs proposed plume rise equations for each of the above plume categories, '''''it is important to emphasize that "the Briggs equations" which become widely used are those that he proposed for bent-over, hot buoyant plumes'''''.
 
In general, Briggs's equations for bent-over, hot buoyant plumes are based on observations and data involving plumes from typical combustion sources such as the flue gas stacks from steam-generating boilers burning fossil fuels in large power plants.  Therefore the stack exit velocities were probably in the range of 20 to 100 ft/s (6 to 30 m/s) with exit temperatures ranging from 250 to 500 °F (120 to 260 °C).
 
A logic diagram for using the Briggs equations<ref name=Beychok/> to obtain the plume rise trajectory of bent-over buoyant plumes is presented below:
[[Image:BriggsLogic.png|none]]
:{| border="0" cellpadding="2"
|-
|align=right|where:
|&nbsp;
|-
!align=right| Δh
|align=left|= plume rise, in m
|-
!align=right| F<sup>&nbsp;</sup> <!-- The HTML is needed to line up characters. Do not remove.-->
|align=left|= buoyancy factor, in m<sup>4</sup>s<sup>−3</sup>
|-
!align=right| x
|align=left|= downwind distance from plume source, in m
|-
!align=right| x<sub>f</sub>
|align=left|= downwind distance from plume source to point of maximum plume rise, in m
|-
!align=right| u
|align=left|= windspeed at actual stack height, in m/s
|-
!align=right| s<sup>&nbsp;</sup> <!-- The HTML is needed to line up characters. Do not remove.-->
|align=left|= stability parameter, in s<sup>−2</sup>
|}
The above parameters used in the Briggs' equations are discussed in Beychok's book.<ref name=Beychok/>


==References==
==References==
{{reflist}}
{{reflist}}
== Further reading==
*{{cite book | author=M.R. Beychok| title=Fundamentals Of Stack Gas Dispersion | edition=4th Edition | publisher=author-published | year=2005 | isbn=0-9644588-0-2}}
*{{cite book | author=K.B. Schnelle and P.R. Dey| title=Atmospheric Dispersion Modeling Compliance Guide  | edition=1st Edition| publisher=McGraw-Hill Professional | year=1999 | isbn=0-07-058059-6}}
*{{cite book | author=D.B. Turner| title=Workbook of Atmospheric Dispersion Estimates: An Introduction to Dispersion Modeling | edition=2nd Edition | publisher=CRC Press | year=1994 | isbn=1-56670-023-X}}
*{{cite book | author= S.P. Arya| title=Air Pollution Meteorology and Dispersion | edition=1st Edition | publisher=Oxford University Press | year=1998 | isbn=0-19-507398-3}}
*{{cite book | author=R. Barrat| title=Atmospheric Dispersion Modelling | edition=1st Edition | publisher=Earthscan Publications | year=2001 | isbn=1-85383-642-7}}
*{{cite book | author=S.R. Hanna and R.E. Britter| title=Wind Flow and Vapor Cloud Dispersion at Industrial and Urban Sites  | edition=1st Edition | publisher=Wiley-American Institute of Chemical Engineers | year=2002 | isbn=0-8169-0863-X}}
*{{cite book | author=P. Zannetti| title=Air pollution modeling : theories, computational methods, and available software | edition= | publisher= Van Nostrand Reinhold | year=1990 | isbn=0-442-30805-1 }}

Latest revision as of 04:25, 22 November 2023


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Industrial air pollution source

Atmospheric dispersion modeling is the mathematical simulation of how air pollutants disperse in the ambient atmosphere. It is performed with computer programs that solve the mathematical equations and algorithms which simulate the pollutant dispersion. The dispersion models are used to estimate or to predict the downwind concentration of air pollutants emitted from sources such as industrial plants, vehicular traffic or accidental chemical releases.

Such models are important to governmental agencies tasked with protecting and managing the ambient air quality. The models are typically employed to determine whether existing or proposed new industrial facilities are or will be in compliance with the National Ambient Air Quality Standards (NAAQS) in the United States or similar regulations in other nations. The models also serve to assist in the design of effective control strategies to reduce emissions of harmful air pollutants. During the late 1960's, the Air Pollution Control Office of the U.S. Environmental Protection Agency (U.S. EPA) initiated research projects to develop models for use by urban and transportation planners.[1]

Air dispersion models are also used by emergency management personnel to develop emergency plans for accidental chemical releases. The results of dispersion modeling, using worst case accidental releases and meteorological conditions, can provide estimated locations of impacted areas and be used to determine appropriate protective actions. At industrial facilities in the United States, this type of consequence assessment or emergency planning is required under the Clean Air Act (CAA) codified in Part 68 of Title 40 of the Code of Federal Regulations.

The dispersion models vary depending on the mathematics used to develop the model, but all require the input of data that may include:

  • Meteorological conditions such as wind speed and direction, the amount of atmospheric turbulence (as characterized by what is called the "stability class"), the ambient air temperature, the height to the bottom of any inversion aloft that may be present, cloud cover and solar radiation.
  • The emission parameters such the type of source (i.e., point, line or area), the mass flow rate, the source location and height, the source exit velocity, and the source exit temperature.
  • Terrain elevations at the source location and at receptor locations, such as nearby homes, schools, businesses and hospitals.
  • The location, height and width of any obstructions (such as buildings or other structures) in the path of the emitted gaseous plume as well as the terrain surface roughness (which may be characterized by the more generic parameters "rural" or "city" terrain).

Many of the modern, advanced dispersion modeling programs include a pre-processor module for the input of meteorological and other data, and many also include a post-processor module for graphing the output data and/or plotting the area impacted by the air pollutants on maps. The plots of areas impacted usually include isopleths showing areas of pollutant concentrations that define areas of the highest health risk. The isopleths plots are useful in determining protective actions for the public and first responders.

The atmospheric dispersion models are also known as atmospheric diffusion models, air dispersion models, air quality models, and air pollution dispersion models.

Atmospheric layers

Discussion of the layers in the Earth's atmosphere is needed to understand where airborne pollutants disperse in the atmosphere. The layer closest to the Earth's surface is known as the troposphere. It extends from sea-level up to a height of about 18 km and contains about 80 percent of the mass of the overall atmosphere. The stratosphere is the next layer and extends from 18 km up to about 50 km. The third layer is the mesosphere which extends from 50 km up to about 80 km. There are other layers above 80 km, but they are insignificant with respect to atmospheric dispersion modeling.

The lowest part of the troposphere is called the atmospheric boundary layer (ABL) or the planetary boundary layer (PBL) and extends from the Earth's surface up to about 1.5 to 2.0 km in height. The air temperature of the atmospheric boundary layer decreases with increasing altitude until it reaches what is called the inversion layer (where the temperature increases with increasing altitude) that caps the atmospheric boundary layer. The upper part of the troposphere (i.e., above the inversion layer) is called the free troposphere and it extends up to the 18 km height of the troposphere.

The ABL is the most important layer with respect to the emission, transport and dispersion of airborne pollutants. The part of the ABL between the Earth's surface and the bottom of the inversion layer is known as the mixing layer. Almost all of the airborne pollutants emitted into the ambient atmosphere are transported and dispersed within the mixing layer. Some of the emissions penetrate the inversion layer and enter the free troposphere above the ABL.

In summary, the layers of the Earth's atmosphere from the surface of the ground upwards are: the ABL made up of the mixing layer capped by the inversion layer; the free troposphere; the stratosphere; the mesosphere and others. Many atmospheric dispersion models are referred to as boundary layer models because they mainly model air pollutant dispersion within the ABL. To avoid confusion, models referred to as mesoscale models have dispersion modeling capabilities that can extend horizontally as much as a few hundred kilometres. It does not mean that they model dispersion in the mesosphere.

Gaussian air pollutant dispersion equation

The technical literature on air pollution dispersion is quite extensive and dates back to the 1930s and earlier. One of the early air pollutant plume dispersion equations was derived by Bosanquet and Pearson.[2] Their equation did not assume Gaussian distribution nor did it include the effect of ground reflection of the pollutant plume.

Sir Graham Sutton derived an air pollutant plume dispersion equation in 1947[3][4] which did include the assumption of Gaussian distribution for the vertical and crosswind dispersion of the plume and also included the effect of ground reflection of the plume.

Under the stimulus provided by the advent of stringent environmental control regulations, there was an immense growth in the use of air pollutant plume dispersion calculations between the late 1960s and today. A great many computer programs for calculating the dispersion of air pollutant emissions were developed during that period of time and they were commonly called "air dispersion models". The basis for most of those models was the Complete Equation For Gaussian Dispersion Modeling Of Continuous, Buoyant Air Pollution Plumes shown below:[5][6]


where:  
= crosswind dispersion parameter
  =
= vertical dispersion parameter =
= vertical dispersion with no reflections
  =
= vertical dispersion for reflection from the ground
  =
= vertical dispersion for reflection from an inversion aloft
  =
           
           
           
= concentration of emissions, in g/m³, at any receptor located:
            x meters downwind from the emission source point
            y meters crosswind from the emission plume centerline
            z meters above ground level
= source pollutant emission rate, in g/s
= horizontal wind velocity along the plume centerline, m/s
= height of emission plume centerline above ground level, in m
= vertical standard deviation of the emission distribution, in m
= horizontal standard deviation of the emission distribution, in m
= height from ground level to bottom of the inversion aloft, in m
= the exponential function

The above equation not only includes upward reflection from the ground, it also includes downward reflection from the bottom of any inversion lid present in the atmosphere.

The sum of the four exponential terms in converges to a final value quite rapidly. For most cases, the summation of the series with m = 1, m = 2 and m = 3 will provide an adequate solution.

and are functions of the atmospheric stability class (i.e., a measure of the turbulence in the ambient atmosphere) and of the downwind distance to the receptor. The two most important variables affecting the degree of pollutant emission dispersion obtained are the height of the emission source point and the degree of atmospheric turbulence. The more turbulence, the better the degree of dispersion.

Whereas older models rely on stability classes for the determination of and , more recent models increasingly rely on Monin-Obukhov similarity theory to derive these parameters.

Briggs plume rise equations

The Gaussian air pollutant dispersion equation (discussed above) requires the input of H which is the pollutant plume's centerline height above ground level. H is the sum of Hs (the actual physical height of the pollutant plume's emission source point) plus ΔH (the plume rise due the plume's buoyancy).

Visualization of a buoyant Gaussian air pollutant dispersion plume

To determine ΔH, many if not most of the air dispersion models developed between the late 1960s and the early 2000s used what are known as "the Briggs equations." G.A. Briggs first published his plume rise observations and comparisons in 1965.[7] In 1968, at a symposium sponsored by CONCAWE (a Dutch organization), he compared many of the plume rise models then available in the literature.[8] In that same year, Briggs also wrote the section of the publication edited by Slade[9] dealing with the comparative analyses of plume rise models. That was followed in 1969 by his classical critical review of the entire plume rise literature,[10] in which he proposed a set of plume rise equations which have become widely known as "the Briggs equations". Subsequently, Briggs modified his 1969 plume rise equations in 1971 and in 1972.[11][12]

Briggs divided air pollution plumes into these four general categories:

  • Cold jet plumes in calm ambient air conditions
  • Cold jet plumes in windy ambient air conditions
  • Hot, buoyant plumes in calm ambient air conditions
  • Hot, buoyant plumes in windy ambient air conditions

Briggs considered the trajectory of cold jet plumes to be dominated by their initial velocity momentum, and the trajectory of hot, buoyant plumes to be dominated by their buoyant momentum to the extent that their initial velocity momentum was relatively unimportant. Although Briggs proposed plume rise equations for each of the above plume categories, it is important to emphasize that "the Briggs equations" which become widely used are those that he proposed for bent-over, hot buoyant plumes.

In general, Briggs's equations for bent-over, hot buoyant plumes are based on observations and data involving plumes from typical combustion sources such as the flue gas stacks from steam-generating boilers burning fossil fuels in large power plants. Therefore the stack exit velocities were probably in the range of 20 to 100 ft/s (6 to 30 m/s) with exit temperatures ranging from 250 to 500 °F (120 to 260 °C).

A logic diagram for using the Briggs equations[5] to obtain the plume rise trajectory of bent-over buoyant plumes is presented below:

BriggsLogic.png
where:  
Δh = plume rise, in m
F  = buoyancy factor, in m4s−3
x = downwind distance from plume source, in m
xf = downwind distance from plume source to point of maximum plume rise, in m
u = windspeed at actual stack height, in m/s
s  = stability parameter, in s−2

The above parameters used in the Briggs' equations are discussed in Beychok's book.[5]

References

  1. J.C. Fensterstock et al, "Reduction of air pollution potential through environmental planning", JAPCA, Vol. 21, No. 7, 1971.
  2. C.H. Bosanquet and J.L. Pearson, "The spread of smoke and gases from chimneys", Trans. Faraday Soc., 32:1249, 1936.
  3. O.G. Sutton, "The problem of diffusion in the lower atmosphere", QJRMS, 73:257, 1947.
  4. O.G. Sutton, "The theoretical distribution of airborne pollution from factory chimneys", QJRMS, 73:426, 1947.
  5. 5.0 5.1 5.2 M.R. Beychok (2005). Fundamentals Of Stack Gas Dispersion, 4th Edition. author-published. ISBN 0-9644588-0-2. .
  6. D. B. Turner (1994). Workbook of atmospheric dispersion estimates: an introduction to dispersion modeling, 2nd Edition. CRC Press. ISBN 1-56670-023-X. .
  7. G.A. Briggs, "A plume rise model compared with observations", JAPCA, 15:433–438, 1965.
  8. G.A. Briggs, "CONCAWE meeting: discussion of the comparative consequences of different plume rise formulas", Atmos. Envir., 2:228–232, 1968.
  9. D.H. Slade (editor), "Meteorology and atomic energy 1968", Air Resources Laboratory, U.S. Dept. of Commerce, 1968.
  10. G.A. Briggs, "Plume Rise", USAEC Critical Review Series, 1969.
  11. G.A. Briggs, "Some recent analyses of plume rise observation", Proc. Second Internat'l. Clean Air Congress, Academic Press, New York, 1971.
  12. G.A. Briggs, "Discussion: chimney plumes in neutral and stable surroundings", Atmos. Envir., 6:507–510, 1972.

Further reading

  • M.R. Beychok (2005). Fundamentals Of Stack Gas Dispersion, 4th Edition. author-published. ISBN 0-9644588-0-2. 
  • K.B. Schnelle and P.R. Dey (1999). Atmospheric Dispersion Modeling Compliance Guide, 1st Edition. McGraw-Hill Professional. ISBN 0-07-058059-6. 
  • D.B. Turner (1994). Workbook of Atmospheric Dispersion Estimates: An Introduction to Dispersion Modeling, 2nd Edition. CRC Press. ISBN 1-56670-023-X. 
  • S.P. Arya (1998). Air Pollution Meteorology and Dispersion, 1st Edition. Oxford University Press. ISBN 0-19-507398-3. 
  • R. Barrat (2001). Atmospheric Dispersion Modelling, 1st Edition. Earthscan Publications. ISBN 1-85383-642-7. 
  • S.R. Hanna and R.E. Britter (2002). Wind Flow and Vapor Cloud Dispersion at Industrial and Urban Sites, 1st Edition. Wiley-American Institute of Chemical Engineers. ISBN 0-8169-0863-X. 
  • P. Zannetti (1990). Air pollution modeling : theories, computational methods, and available software. Van Nostrand Reinhold. ISBN 0-442-30805-1.