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{{Image|LucasGusher SpindletopTexas.JPG|right|300px|The famous Lucas Gusher oil well of 1901 in Spindletop, Texas.}}
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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.  


'''Petroleum crude oil''', or simply '''crude oil''', is a naturally occurring, [[flammability|flammable]] liquid found primarily in underground [[Geology|geological]] formations and consists of a complex mixture of [[hydrocarbon]]s of various [[molecular weight]]s plus other [[Organic chemistry|organic compound]]s.
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> 


The [[Latin]] word '''''petroleum''''' was first used to describe petroleum crude oil  by the [[Germany|German]] mineralogist [[Georg Bauer]] (also known as Georgius Agricola) in the treatise ''De Natura Fossilium'', published in 1546<ref>{{cite book |author=Bauer Georg|title=De Natura Fossilium |year=1546}} Translated in 1955 by Mark C. Bandy and Jean A. Bandy </ref> The [[Greek language|Greek]] word for petroleum is ''πετρέλαιον'', meaning "rock oil".
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 first oil well drilled at [[Spindletop]] in southeast [[Texas]] , known as the "Lucas Gusher", was completed when petroleum crude oil gushed forth on January 10, 1901. The oil reservoir underneath Spindletop was formed by a salt dome (see the "Crude oil sources" section below) and become known as the oil well that started the birth of the oil industry in Texas. It initially produced about 100,000 [[U.S. customary units|barrel]]s per day (16,000 cubic [[metre]]s  per day), more than the combined production from all of the oil wells then existing in the United States.
The dispersion models vary depending on the mathematics used to develop the model, but all require the input of data that may include:


== Composition of crude oil ==
* 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.
{{main|Hydrocarbons}}
* 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.
{| border="0" width="400" align="right"  
* 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).
{| class = "wikitable" align="center"
|-
! Hydrocarbon !! Average<br />Weight %
|-
|[[Hydrocarbon|Paraffin]]s||align="center"|30
|-
|[[Hydrocarbon|Naphthene]]s||align="center"|49
|-
|[[Hydrocarbon|Aromatic]]s||align="center"|15
|-
|[[Asphalt (petroleum)|Asphaltics]]||align="center"|6
|}
|
{| class = "wikitable" align="center"
|-
! Element!!Weight %
|-
|[[Carbon]] ||align="center"|83 to 87
|-
|[[Hydrogen]] ||align="center"|10 to 14
|-
|[[Nitrogen]] ||align="center"|0.1 to 2.0
|-
|[[Oxygen]] ||align="center"|0.1 to 1.5
|-
|[[Sulfur]] ||align="center"|0.5 to 6.0
|-
|Metals ||align="center"|less than 1000 ppm
|}
|}
 
Both crude oil and [[natural gas]] are predominantly mixtures of [[hydrocarbons]]. At typical ambient conditions of pressure and temperature, the lower molecular weight hydrocarbons [[methane]], [[ethane]], [[propane]] and [[butane]] occur as gases, while the higher molecular weight ones ([[pentane]] and higher) are in the form of liquids or solids. However, in the underground [[oil reservoir]]s the proportion which is gas or liquid varies depending on the subsurface conditions, and on the [[phase diagram]] of the petroleum mixture.<ref name="Hyne 2001">{{cite book|author=Norman J. Hyne|title=Nontechnical Guide to Petroleum Geology, Exploration, Drilling, and Production|edition=|publisher=PennWell Corporation|date=2001|pages=pages 1-4|id=ISBN 087814823X}}</ref>
 
Crude oil consists mostly of hydrocarbons with small amounts of other [[Organic chemistry|organic chemical compounds]] that may contain [[nitrogen]], [[oxygen]] or [[sulfur]]. It may also contain trace amounts of metals such as [[iron]], [[nickel]], [[copper]] and [[vanadium]]. The exact [[Chemical element|elemental]] composition varies widely from formation to formation but the proportion of [[chemical element]]s vary over fairly narrow limits.<ref name="Speight"> {{Cite book|author=James G. Speight|title=The Chemistry and Technology of Petroleum|edition=|publisher=Marcel Dekker|year=1999|pages=pages 215-216|id=ISBN 0824702174}}</ref> The distribution of the different types of hydrocarbons in petroleum also varies considerably from one crude oil reservoir to another which means that the properties of the various crude oils are quite different.<ref name="Hyne 2001"/>


The average elemental composition of petroleum crude oil and the average distribution of the different hydrocarbons in the various crude oils are shown in the adjacent tables.
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.


{{Image|Example Cycloalkanes.png|right|225px}}
The atmospheric dispersion models are also known as atmospheric diffusion models, air dispersion models, air quality models, and air pollution dispersion models.
{{Image|Example Aromatics.png|right|325px}}
;The hydrocarbons in crude oil:
{{main|Hydrocarbons|Petroleum refining processes|Petrochemical}}
Petroleum is a mixture of a very large number of different [[hydrocarbon]]s. The most common hydrocarbons found in petroleum crude oil are linear or branched [[Hydrocarbons|alkane]]s (also called ''paraffins''), [[Hydrocarbons|cycloalkane]]s (also called ''cyclic paraffins'' or ''naphthenes''), [[Hydrocarbons|aromatic hydrocarbon]]s, or much more complicated chemicals like [[asphaltene]]s which may have a [[molecular weight]] of 800 to 500.<ref>{{cite book|author=Oliver Mullins and Eric Sheu (Editors)|title=Structure & Dynamics of Asphaltenes|edition=1st Edition|publisher=Springer|year=1999|id=ISBN 0-306-45930-2}} (See Chapter 1, page 17)</ref><ref>Note: There are many other values in the technical literature for the molecular weight of asphaltenes and there does not appear to be a concensus as to which values are more correct.</ref> .


The alkanes present in crude oil are [[saturation (chemistry)|saturated]] hydrocarbons, with linear or branched chains,  which contain only [[carbon]] and [[hydrogen]] atoms and have the general formula of C<sub>n</sub>H<sub>2n+2</sub>. They generally have from 4 to 40 carbon atoms per molecule, although some molecules may be present that have less than 5 or more than 40 carbon atoms.
==Atmospheric layers==


The cycloalkanes are also saturated hydrocarbons, but they which have one or more rings of carbon atoms to which hydrogen atoms are attached. The general formula for cycloalkane having a single ring of carbon atoms (with no side chains) is C<sub>n</sub>H<sub>2n</sub>. Cycloalkanes have similar properties to alkanes but have higher boiling points.  
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 upper adjacent diagram depicts the chemical structure of [[cyclopentane]] and [[cyclohexane]] as some examples of cycloalkanes having a single ring.
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 aromatic hydrocarbons have one or more rings of six carbons, called [[benzene ring]]s, to which<br /> hydrogen atoms are attached. The general formula of the aromatic hydrocarbons having a single ring (and having no side chains) is C<sub>n</sub>H<sub>n</sub>.  
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.


The lower adjacent diagram depicts the chemical structures of [[benzene]] as an example of an aromatic hydrocarbon having a single ring with no side chains, as well as the structures of [[toluene]] and [[o-Xylene]] as examples of aromatic hydrocarbons having a single benzene ring with one and with two side chains.
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.


==Formation of crude oil==
==Gaussian air pollutant dispersion equation==


According to generally accepted theory, petroleum is derived from ancient [[biomass]].<ref>Keith A. Kvenvolden (2006), ''Organic geochemistry – A retrospective of its first 70 years'', Organic Geochemistry, '''37''' pp. 1–11.</ref> The theory was initially based on the isolation of molecules from petroleum that closely resembled known biomolecules.
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.


More specifically, crude oil and [[natural gas]] are products of [[diagenesis|heating]] of ancient [[Organic  chemistry|organic materials]] (i.e. [[kerogen]]) over [[geologic time scale|geological time]]. Formation of petroleum occurs from [[hydrocarbon]] [[pyrolysis]], in a variety of mostly [[endothermic]] reactions at high temperature and/or pressure. Today's oil formed from the preserved remains of prehistoric [[zooplankton]] and [[algae]], which had settled to a sea or lake bottom in large quantities under [[anoxic waters|anoxic conditions]]. Over geological time, the organic matter mixed with mud, and was buried under heavy layers of [[sediment]] resulting in high levels of [[heat]] and [[pressure]]. This process caused the organic matter to change, first into the waxy material known as [[kerogen]], which is found in various [[oil shale]]s around the world, and then with more heat into liquid and gaseous hydrocarbons via a process known as [[catagenesis (geology)|catagenesis]].  
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.


Geologists often refer to the temperature range in which oil forms as an "oil window". Below the oil window minimum temperature oil remains trapped in the form of kerogen, and above the window maximum temperature the oil is converted to [[natural gas]] through the process of [[thermal cracking]]. Although this temperature range is found at different depths below the surface throughout the world, a typical depth for the oil window is 4 – 6 km. Sometimes, oil which is formed at extreme depths may migrate and become trapped at much shallower depths than where it was formed, as in the case of the [[Athabasca Oil Sands]].
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>


== Crude oil sources ==


{{Image|Crude Oil Traps.png|right|446px|The three basic forms of structural crude oil traps.}}  
<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>
;Conventional crude oil reservoirs:
Three conditions must be present for oil reservoirs to form, as depicted in the adjacent drawing:


:* A reservoir of hydrocarbon material must exist and must have been buried deep enough for subterranean heat and pressure to have transformed it over a long period of time into crude oil.
{| border="0" cellpadding="2"  
:* A [[porous]], [[permeability (fluid)|permeable]] reservoir rock for the crude oil to accumulate in.
:* A non-porous, non-permeable cap rock that acts to seal and to prevent the accumulated crude oil from migrating upward and escaping to the surface.
Because most hydrocarbons are lighter than rock or water, they often migrate upward by permeating through porous, permeable rock layers until either reaching the surface or becoming trapped by non-porous, impermeable rocks above. When hydrocarbons are accumulated in a such a trap, an oil reservoir forms from which the oil can be extracted by drilling and pumping as also shown in the adjacent drawing.
 
;Unconventional oil reservoirs:
Oil-eating bacteria [[biodegradation|biodegrades]] oil that has escaped to the surface. [[Oil sands]] are reservoirs of partially biodegraded oil still in the process of escaping and being biodegraded, but they contain so much migrating oil that, although most of it has escaped, vast amounts are still present—more than can be found in conventional oil reservoirs. The lighter fractions of the crude oil are destroyed first, resulting in reservoirs containing an extremely heavy form of crude oil, called crude bitumen in Canada, or extra-heavy crude oil in Venezuela. These two countries have the world's largest deposits of oil sands.
 
On the other hand, [[oil shale]]s are source rocks that have not been exposed to heat or pressure long enough to convert their trapped hydrocarbons into crude oil. Technically speaking, oil shales are not really shales and do not really contain oil, but are usually relatively hard rocks called [[marl]]s containing a waxy substance called [[kerogen]]. The kerogen trapped in the rock can be converted into crude oil using heat and pressure to simulate natural processes. The method has been known for centuries and was patented in 1694 under British Crown Patent No. 330 covering, "A way to extract and make great quantityes of pitch, tarr, and oyle out of a sort of stone." Although oil shales are found in many countries, the United States has the world's largest deposits.<ref name=Lambertson>{{cite news | title=Oil Shale: Ready to Unlock the Rock | first=Giles | last=Lambertson | publisher=Construction Equipment Guide | url=http://www.cegltd.com/story.asp?story=10092 | date=February 16, 2008}}</ref>
 
==Classification of crude oils==
 
The [[petroleum industry]] generally classifies crude oil by the geographic location of the reservoir from which it is produced (e.g. [[West Texas Intermediate]], [[Brent oilfield|Brent]], or [[Oman]]), its [[API gravity]] (an oil industry measure of density), and by its sulfur content. Crude oil may be considered ''light'' if it has a low density or ''heavy'' if it has a high density and it may be referred to as ''sweet'' if it contains relatively little sulfur or ''sour'' if it contains substantial amounts of sulfur.
 
''Light'' crude oil is more desirable than ''heavy'' oil since it provides a higher yield of gasoline and  ''sweet'' oil is more desirable than ''sour'' oil because it has fewer environmental problems and requires less refining to meet sulfur content standards of refined fuels. Each crude oil has a unique composition and set of physical properties which are delineated by [[crude oil assay]]s performed in petroleum laboratories.
 
Some of the common petroleum crude oils (many of which are known as ''benchmark crude oils'') are:
 
* '''''West Texas Intermediate''''' is a very high-quality, sweet, light oil. It is a [[North America|North American]] oil.
* '''''Brent Blend''''' is a blend of 15 oils from the [[Brent oilfield|Brent]] and [[Ninian]] oil fields in the [[East Shetland Basin]] of the [[North Sea]].
* '''''Dubai Crude''''' is a [[Middle East|Middle Eastern]], sour oil from [[Dubai]].
* '''''Arabian Crude''''' is a Middle Eastern oil from [[Saudi Arabia]].
* '''''Tapis Crude''''' is a [[Far East|Far Eastern]] oil from [[Malaysia]].
* '''''Minas Crude''''' is a Far Eastern oil from [[Indonesia]].
* Canada (to be added)
* Russia (to be added)
 
== Products produced from crude petroleum ==
 
{{main|Petroleum refining processes|Petrochemicals}}
The petroleum crude oil is refined in [[Petroleum refining processes|petroleum refineries]] to produce various fuels as well as a number of other products.
 
;Fuels:
* [[Liquified petroleum gas]], commonly referred to as LPG
* [[Gasoline]], also called [[petrol]], in various grades
* [[Jet fuel]] in various grades
* [[Kerosene]]
* [[Diesel fuel]]
* [[Fuel oil]]
 
;Other products:
* [[Solvents]] for various industrial and other uses
* [[Lubricant]]s such as [[motor oil]]s and [[Grease (lubricant)|greases]]
* [[Wax|Petroleum wax]]
* [[Sulfur]], a byproduct of [[Hydrodesulfurization|sulfur removal]] from fuels. 
* [[Asphalt (petroleum)|Asphalt]]
* [[Petroleum coke]], used in speciality carbon products or as a solid fuel.
* [[Petrochemical]] feed stocks:
** [[Benzene]], [[toluene]] and [[xylene]]s
** [[Petroleum naphtha]] and [[fuel oil]]s as feedstocks for steam-assisted [[thermal cracking]] plants referred to as ''[[steam cracker]]s'' that produce intermediate petrochemical feedstocks
 
== Crude oil statistics  ==
 
The three tables below provide the 20008 statistics for the production, consumption and proven reserves of petroleum crude oil of the top nations in each of those categories. The corresponding total world quantities of each category were (See table footnotes for measurement definitions and conversions):
 
* Production: 73,780,000 bbl/day (11,730,000 m<sup>3</sup>/day)
* Consumption: approximately 73,780,000 bbl/day (11,730,000 m<sup>3</sup>/day)
* Proven reserves: 1,332,000,000,000 bbl (211,790,000,000 m<sup>3</sup>)
 
As noted in the table footnotes, Canada's proven reserves include the petroleum in their [[Athabasca Oil Sands]]. The proven reserves of Venezuela probably include their oil sands also, but that is not explicitly stated in the referenced data sources.
 
{| border="0" align="center"
|
{| class="wikitable" align="center"
|+Crude Oil Producers (2008)<sup> </sup><ref name=EIATop15>[http://tonto.eia.doe.gov/country/index.cfm Country Energy Profiles] [[Energy Information Administration]], [[U.S. Department of Energy]]</ref>
!Producing Nation
!bbl/d !!m<sup>3</sup>/d
|-
|[[Saudi Arabia]]
|10,782,000
|1,729,000
|-
|-
|[[Russia]]
|align=right|where:
|9,790,000
|&nbsp;
|1,557,000
|-
|-
|[[United States]]
!align=right|<math>f</math> 
|8,514,000
|align=left|= crosswind dispersion parameter
|1,354,000
|-
|-
|[[Iran]]
!align=right|&nbsp;
|4,174,000
|align=left|= <math>\exp\;[-\,y^2/\,(2\;\sigma_y^2\;)\;]</math>
|663,700
|-
|-
|[[China]]
!align=right|<math>g</math>
|3,973,000
|align=left|= vertical dispersion parameter = <math>\,g_1 + g_2 + g_3</math>
|631,700
|-
|-
|[[Canada]]
!align=right|<math>g_1</math>
|3,350,000
|align=left|= vertical dispersion with no reflections
|532,700
|-
|-
|[[Mexico]]
!align=right|&nbsp;
|3,186,000
|align=left|= <math>\; \exp\;[-\,(z - H)^2/\,(2\;\sigma_z^2\;)\;]</math>
|506,600
|-
|-
|[[United Arab Emirates]]
!align=right|<math>g_2</math>
|3,046,000
|align=left|= vertical dispersion for reflection from the ground
|484,300
|-
|-
|[[Kuwait]]
!align=right|&nbsp;
|2,741,000
|align=left|= <math>\;\exp\;[-\,(z + H)^2/\,(2\;\sigma_z^2\;)\;]</math>
|435,800
|-
|-
|[[Venezuela]]
!align=right|<math>g_3</math>
|2,643,000
|align=left|= vertical dispersion for reflection from an inversion aloft
|420,200
|-
|-
|[[Norway]]
!align=right|&nbsp;
|2,466,000
|align=left|= <math>\sum_{m=1}^\infty\;\big\{\exp\;[-\,(z - H - 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
|392,100
|-
|-
|[[Brazil]]
!align=right|&nbsp;
|2,396,000
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z + H + 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
|381,000
|-
|-
|[[Iraq]]
!align=right|&nbsp;
|2,385,000
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z + H - 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
|379,200
|-
|-
|[[Algeria]]
!align=right|&nbsp;
|2,180,000
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z - H + 2mL)^2/\,(2\;\sigma_z^2\;)\;]\big\}</math>
|346,600
|-
|-
|[[Nigeria]]
!align=right|<math>C</math>
|2,169,000
|align=left|= concentration of emissions, in g/m³, at any receptor located:
|344,900
|}
|
{| class="wikitable" align="center"
|+Crude Oil Consumers (2008)<sup> </sup><ref name=EIATop15/>
!Producing Nation
!bbl/d !!m<sup>3</sup>/d
|-
|-
|[[United States]]
!align=right|&nbsp;
|19,498,000
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; x meters downwind from the emission source point
|3,100,000
|-
|-
|[[China]]
!align=right|&nbsp;
|7,850,000
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; y meters crosswind from the emission plume centerline
|1,248,000
|-
|-
|[[Japan]]
!align=right|&nbsp;
|4,785,000
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; z meters above ground level
|760,800
|-
|-
|[[India]]
!align=right|<math>Q</math>
|2,940,000
|align=left|= source pollutant emission rate, in g/s
|467,500
|-
|-
|[[Russia]]
!align=right|<math>u</math>
|2,900,000
|align=left|= horizontal wind velocity along the plume centerline, m/s
|461,100
|-
|-
|[[Germany]]
!align=right|<math>H</math>
|2,569,000
|align=left|= height of emission plume centerline above ground level, in m
|408,500
|-
|-
|[[Brazil]]
!align=right|<math>\sigma_z</math>
|2,520,000
|align=left|= vertical standard deviation of the emission distribution, in m
|400,700
|-
|-
|[[Saudi Arabia]]
!align=right|<math>\sigma_y</math>
|2,297,000
|align=left|= horizontal standard deviation of the emission distribution, in m
|365,200
|-
|-
|[[Canada]]
!align=right|<math>L</math>
|2,260,000
|align=left|= height from ground level to bottom of the inversion aloft, in m
|359,300
|-
|-
|[[Republic of Korea]]
!align=right|<math>\exp</math>
|2,175,000
|align=left|= the exponential function
|345,800
|-
|[[Mexico]]
|2,128,000
|338,400
|-
|[[France]]
|1,986,000
|315,800
|-
|[[Iran]]
|1,755,000
|279,000
|-
|[[United Kingdom]]
|1,710,000
|271,900
|-
|[[Italy]]
|1,639,000
|260,600
|}
|}
|
 
{| class="wikitable" align="center"
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.
|+Crude Oil Proven Reserves (2008)<sup> </sup><ref name=CIAWorldFactbook>[https://www.cia.gov/library/publications/the-world-factbook/fields/2178.html?countryName=World&countryCode=xx&regionCode=oc&#xx Proved Reserves of Oil by Country] CIA World Factbook</ref>
 
!Producing Nation
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.
!bbl!!m<sup>3</sup>
 
|-
<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.
|[[Saudi Arabia]]
 
|264,300,000,000
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.
|42,023,700,000
 
==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 ''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 models.  That 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"
|-
|-
|[[Canada]]
|align=right|where:
|178,600,000,000
|&nbsp;
|28,297,400,000
|-
|-
|[[Iran]]
!align=right| Δh
|136,200,000,000
|align=left|= plume rise, in m
|21,655,800,000
|-
|-
|[[Iraq]]
!align=right| F<sup>&nbsp;</sup> <!-- The HTML is needed to line up characters. Do not remove.-->
|112,500,000,000
|align=left|= buoyancy factor, in m<sup>4</sup>s<sup>−3</sup>
|17,887,500,000
|-
|-
|[[Kuwait]]
!align=right| x
|101,500,000,000
|align=left|= downwind distance from plume source, in m
|16,138,500,000
|-
|-
|[[United Arab Emirates]]
!align=right| x<sub>f</sub>
|97,800,000,000
|align=left|= downwind distance from plume source to point of maximum plume rise, in m
|17,887,500,000
|-
|-
|[[Russia]]
!align=right| u
|79,000,000,000
|align=left|= windspeed at actual stack height, in m/s
|12,561,000,000
|-
|-
|[[Venezuela]]
!align=right| s<sup>&nbsp;</sup> <!-- The HTML is needed to line up characters. Do not remove.-->
|78,270,000,000
|align=left|= stability parameter, in s<sup>−2</sup>
|12,444,900,000
|-
|[[Libya]]
|45,000,000,000
|7,155,000,000
|-
|[[Nigeria]]
|38,500,000,000
|6,121,500,000
|-
|[[Kazakhstan]]
|30,000,000,000
|4,770,000,000
|-
|[[Qatar]]
|27,090,000,000
|4,307,300,000
|-
|[[United States]]
|20,970,000,000
|3,334,200,000
|-
|[[China]]
|19,600,000,000
|3,116,400,000
|-
|[[Algeria]]
|14,790,000,000
|2,351,600,000
|}
|}
|}
The above parameters used in the Briggs' equations are discussed in Beychok's book.<ref name=Beychok/>
'''Footnotes for the above tables''':
#bbl/d and m<sup>3</sup>/d are the liquid volume measures of '''''barrels per day''''' and '''''cubic metres per day''''', respectively. 1 bbl = 0.1590 m<sup>3</sup> and 1 m<sup>3</sup> = 6.289 bbl
#Proved reserves are those quantities of petroleum crude oil, which, by analysis of geological and engineering data, can be estimated with a high degree of confidence to be commercially recoverable from a given date forward, from known reservoirs and under current economic conditions.
#Canada's crude from oil sands is included in its proven reserves. On that basis, it has the world's second largest oil reserves after Saudi Arabia.
#Canada's production of crude oil from conventional sources is declining, but its prodution from oil sands is increasing.
#In the terminology of the oil industry, ''production'' refers to the quantity of crude oil extracted from reserves, not the literal creation of the product.


==History==
==References==
(This section need more content between ancient Persia and today)
{{reflist}}
 
Petroleum, in one form or another, has been used since ancient times, and is now important across society, including in economy, politics and technology. The rise in importance was mostly due to the invention of the [[internal combustion engine]].
 
More than 4000 years ago, according to [[Herodotus]] and [[Diodorus Siculus]], [[asphalt]] was used in the construction of the walls and towers of [[Babylon]]; there were oil pits near [[Ardericca]] (near Babylon), and a pitch spring on [[Zacynthus]].<ref name=EB1911>[http://encyclopedia.jrank.org/PER_PIG/PETROLEUM_Lat_Petra_rock_and_ol.html Petroleum] Article originally appearing in Volume V21, Page 321 of the 1911 Encyclopedia Britannica (which is now in the public domain). </ref> Great quantities of it were found on the banks of the river [[Issus (river)|Issus]], one of the tributaries of the [[Euphrates]]. Ancient [[Persian Empire|Persian]] tablets indicate the medicinal and lighting uses of petroleum in the upper levels of their society.
 
Today, the petroleum industry is global in its scope. The largest volume products of the industry are [[fuel oil]]s and [[gasoline]] (petrol). Petroleum is also the raw material for many [[Petrochemical|chemical products]], including pharmaceuticals, solvents, fertilizers, pesticides, and plastics.
 
Petroleum is vital to many [[industries]], and is of importance to the maintenance of industrialized [[civilization]] itself.. Oil accounts for a large percentage of the world's energy consumption, ranging from a low of 32% for [[Europe]] and [[Asia]], up to a high of 53% for the [[Middle East]].  The consumption patterns of other geographic regions are: [[America|South and Central America]] (44%), [[Africa]] (41%), and [[North America]] (40%).  The world at large consumes 30 billion [[Barrel (unit)|barrels]] (4.8&nbsp;km³) of oil per year, and the top oil consumers largely consist of developed nations.


==Environmental effects==
== Further reading==


The presence of oil has significant [[society|social]] and [[environment (biophysical)|environment]]al impacts from accidents and routine activities such as [[seismology|seismic]] exploration, [[drilling]], and generation of [[pollution|polluting]] wastes and [[greenhouse gas]]es.
*{{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}}


;Extraction:
*{{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}}
Oil extraction is costly and sometimes environmentally damaging, although oceanographer Dr. John Hunt of the [[Woods Hole Oceanographic Institution]] pointed out in a 1981 paper that over 70% of the reserves in the world are associated with visible [[seep|macroseepage]]s, and many oil fields are found due to natural [[seep]]s. Offshore exploration and extraction of oil disturbs the surrounding marine environment.<ref>[http://www.offshore-environment.com/discharges.html Waste discharges during the offshore oil and gas activity] by Stanislave Patin, translated by Elena Cascio.</ref>  Extraction may involve [[dredging]], which stirs up the seabed and kills the sea plants that marine creatures need to survive. But at the same time, [[offshore platform]]s also form micro-habitats for marine creatures.


;Oil spills:
*{{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}}


Oil spills at sea are generally much more damaging than those on land, since they can spread for hundreds of [[nautical mile]]s in a thin [[oil slick]] which can cover beaches with a thin coating of oil. Such spills can kill sea birds, mammals, shellfish and other organisms it coats. Oil spills on land are more readily containable if a makeshift earthen [[dam]] can be rapidly [[bulldozer|bulldozed]] around the spill site before most of the oil escapes, and land animals can avoid the oil more easily.
*{{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}}


Crude oil and refined fuel [[Oil spill|spills]] from [[tanker (ship)|tanker ship]] accidents have damaged natural [[ecosystem]]s in [[Alaska]], the [[Galapagos Islands]], [[France]] and many other place. The quantity of oil spilled from tanker ships during accidents has ranged from a few hundred tons to several hundred thousand tons (e.g., the tankers [[Atlantic Empress]] and [[Amoco Cadiz]]). Smaller spills have already proven to have a great impact on ecosystems, such as the oil spill from the [[Exxon Valdez tanker]].
*{{cite book | author=R. Barrat| title=Atmospheric Dispersion Modelling | edition=1st Edition | publisher=Earthscan Publications | year=2001 | isbn=1-85383-642-7}}


Control of oil spills is difficult, requires ad hoc methods, and often a large amount of manpower. The dropping of bombs and incendiary devices from aircraft on the [[Torrey Canyon tanker]] wreck produced poor results.<ref>{{cite book |title=Oil and water - the Torrey Canyon disaster |author=Edward Cowan |year=1968 |publisher=Lippincott |id=}}</ref> Modern techniques would include pumping the oil from the wreck, like in the [[Prestige tanker]] oil spill or the oil spill from the [[Erika tanker]].<ref>[http://www.total.com/en/group/news/special_report_erika/erika_measures_total/erika_pumping_cargo_11379.htm Pumping of the Erika cargo]</ref>
*{{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}}


==References==
*{{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 }}
{{reflist}}

Latest revision as of 04:25, 22 November 2023


The account of this former contributor was not re-activated after the server upgrade of March 2022.


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.