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{{Image|Air Quality Monitoring Station.jpg|right|300px|An air quality monitoring station.}}
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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 '''Air Quality Index''' ('''AQI''') (also known as the '''Air Pollution Index''' ('''API''') or '''Pollutant Standard Index''' ('''PSI''') is a number used by government agencies to characterize the quality of the ambient air at a given location. As the AQI increases, the severity of probable adverse health effects increases as does the percentage of the population expected to be affected by the adverse health effects.  
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> 


To compute the AQI requires an air pollutant concentration to be obtained from an air quality monitoring station. The method used to convert from air pollutant concentrations to AQIs varies for each air pollutant, and is different in different countries.
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.


In many countries, air quality index values are divided into ranges, and each range is assigned a ''descriptor'' (i.e., a very few words describing the air quality or the health effects of the range) and often a color code as well. A government agency might also encourage members of the public to avoid strenuous activities, use public transportation rather than personal automobiles and work from home when AQI levels are high.
The dispersion models vary depending on the mathematics used to develop the model, but all require the input of data that may include:


Many countries monitor ground-level [[ozone]], [[Particulate matter|particulate matter]] (PM<sub>10</sub>), [[sulfur dioxide]] (S0<sub>2</sub>), [[carbon monoxide]] (CO) and [[nitrogen dioxide]] (NO<sub>2</sub>) and calculate air quality indices for these pollutants. Most other air contaminants do not have an associated AQI.
* 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).


==Air Quality Indices by country==
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.


{| border="0" width="330" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
The atmospheric dispersion models are also known as atmospheric diffusion models, air dispersion models, air quality models, and air pollution dispersion models.
|
 
{| class=wikitable cellpadding="5" align="right"
==Atmospheric layers==
|+ Canada's AQHI<ref name=EnvCanada>[http://www.ec.gc.ca/cas-aqhi/default.asp?Lang=En&n=065BE995-1 About the Air Quality Health Index] (From the website of [[Environment Canada]])</ref>
 
! Air Quality<br/>Health Index<br/>(AQHI)|| Health Risk<br/>Category|| Color<br/>Code
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.
|-
 
| 1 – 3|| Low||[[Image:ColorCode123.png]]
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.
|-
 
| 4 – 6|| Moderate||[[Image:ColorCode456.png]]
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.
|-
 
| 7 – 10|| High||[[Image:ColorCode78910.png]]
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.
|-
 
| 10+|| Very High||[[Image:ColorCode10+.png]]
==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.<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.
===Canada===


[[Environment Canada]], the national environmental protection agency of [[Canada]], uses Air Quality Health Index (AQHI) categories ranging from 1 to 10+ and each category has an assigned color code (see adjacent table) that enables members of the general public to easily identify their health risks as indicated in published air quality forecasts.<ref name=EnvCanada/>
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.


As shown in the adjacent table:
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>


* The three AQHI levels of 1, 2 and 3 are all in the '''''low''''' risk category.
* The three AQHI levels of 4, 5 and 6 are all in the '''''moderate''''' risk category.
* The four AQHI levels of 7, 8, 9 and 10 are all in the '''''high''''' risk category.
* The AQHI level of 10+ is the very high risk category.


As of 2009, many of the Canadian provinces, if not all, have adopted the AQHI categories implemented by Environment Canada.
<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>


{| border="0" width="330" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
{| border="0" cellpadding="2"  
|
|-
{| class=wikitable align="right" cellpadding="5"
|align=right|where:
|+ China's National API<ref name=AMFIC>[http://www.knmi.nl/samenw/amfic/bulletin/faq.php?lang=0 Air Quality Monitoring and Forecasting in China] Air Quality Monitoring & Forecasting in China (AMFIC). Published on [[KNMI]] website.</ref>
|&nbsp;
! Air Pollution<br/>Index<br/>(API)||Air Quality<br/>Level|| Air Quality<br/>Category
|-
|-  
!align=right|<math>f</math> 
| 0 – 50||align="center"| I || Excellent
|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>
|-
|-
| 51 – 100||align="center"| II || Good
!align=right|&nbsp;
|-
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z + H - 2mL)^2/\,(2\;\sigma_z^2\;)\;]</math>
| 101 – 200||align="center"| III || Slightly polluted
|-  
| 201 – 300||align="center"| IV || Moderately polluted
|-  
| 301+ ||align="center"| V ||Heavily polluted
|-
|-
|colspan="3" align="center"|'''Beijing's API<ref name=AMFIC/>'''
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>+\, \exp\;[-\,(z - H + 2mL)^2/\,(2\;\sigma_z^2\;)\;]\big\}</math>
|-
|-
|0 – 50||&nbsp;|| Good
!align=right|<math>C</math>
|align=left|= concentration of emissions, in g/m³, at any receptor located:
|-
|-
|51 – 100||&nbsp;|| Moderate
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; x meters downwind from the emission source point
|-
|-
|101 – 150||&nbsp;|| Unhealthy for<br/>sensitive groups
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; y meters crosswind from the emission plume centerline
|-
|-
|151 – 200||&nbsp;|| Unhealthy
!align=right|&nbsp;
|align=left|&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; z meters above ground level
|-
|-
|201 – 250||&nbsp;|| Very unhealthy
!align=right|<math>Q</math>
|align=left|= source pollutant emission rate, in g/s
|-
|-
|251 – 500||&nbsp;|| Hazardous
!align=right|<math>u</math>
|}
|align=left|= horizontal wind velocity along the plume centerline, m/s
|}
|-
 
!align=right|<math>H</math>
=== China ===
|align=left|= height of emission plume centerline above ground level, in m
[[China|China's]] [[Ministry of Environmental Protection]] (SEPA)<ref name=SEPA>[http://www.sepa.cn Ministry of Environmental Protection]] (in Chinese)</ref> is responsible for monitoring the level of air pollution in China.
 
As of August 2008, SEPA monitors daily pollution level in its major cities and develops an Air Pollution Index (API) level that is based on the ambient air concentrations sulfur dioxide, nitrogen dioxide, particulate matter (PM<sub>10</sub>), carbon monoxide, and ozone as measured at monitoring stations in each of those major cities.<ref name=SEPA/>
 
The adjacent table presents China's national API scale, which is not color coded and uses a scale 0 to more than 300, divided into five ranges of air quality categorized as ''excellent'', ''good'', ''slightly polluted'', ''heavily polluted'' and ''hazardous''.
 
=====API Mechanics=====
An individual score is assigned to the level of each pollutant and the final API is the highest of those 5 scores. The pollutant concentrations are obtained quite differently. Sulfur dioxide, nitrogen dioxide and PM<sub>10</sub> concentrations are obtained as daily averages. Carbon monoxide and ozone are more harmful and are obtained as an hourly averages. The final API value is calculated as a daily average.<ref name=SEPA/>
 
The scale for each pollutant is non-linear, as is the final daily API value. Thus, an API value of 100 does not mean it is twice the pollution of API at 50, nor does it mean it is twice as harmful.
 
=====Beijing's API=====
China's capitol city, [[Beijing]], has its own API scale, which was developed by the [[Beijing Municipal Environmental Protection Bureau]].<ref>[http://bjepb.gov.cn/air2008/olympic.aspx Beijing Municipal Environmental Protection Bureau] (predominantly in Chinese)</ref> As can be seen in the adjacent table, the API scale used by Beijing differs quite significantly from China's national scale in that:
 
* The Beijing scale ranges from 0 to 500 (rather than 0 to 300 as in the national scale)
 
* The Beijing scale is divided into six ranges of air quality (rather than five ranges as in the national scale).
 
{| border="0" width="210" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
|
{| class=wikitable align="right" cellpadding="0"
|+Hong Kong's API<ref name=HK>[http://www.epd-asg.gov.hk/english/backgd/healthe.php API and Air Monitoring Background Information] (From the website of the [[Hong Kong Environmental Protection Department]])</ref>
! Air Pollution<br/>Index<br/>(API)|| Health Effect<br/>Category|| Color<br/>Code
|-
| 0 – 25|| Low|| bgcolor="#009900"|&nbsp;
|-
|-
| 26 – 50|| Medium||  bgcolor="#00FFFF"|&nbsp;
!align=right|<math>\sigma_z</math>
|-
|align=left|= vertical standard deviation of the emission distribution, in m
| 51 – 100|| High|| bgcolor="#FFFF00"|&nbsp;
|-
| 101 – 200|| Very High||bgcolor="#FF0000"|&nbsp;
|-
| 201 – 500|| Severe|| bgcolor="#000000"|&nbsp;
|}
|}
 
===Hong Kong===
 
The [[Hong Kong Environmental Protection Department]] (Hong Kong EPD) has developed a color coded Air Pollution Index (API) based upon the measured concentrations of ambient particulate matter (PM<sub>10</sub>), sulfur dioxide, carbon monoxide, ozone and nitrogen dioxide over a 24-hour period. 
 
[[Hong Kong|Hong Kong's]] color coded Air Pollution Index (API) scale ranges from 0 to 500 corresponding to adverse health effects that range from '''''low''''' to '''''severe''''' as shown in the adjacent chart:<ref name=HK/>
 
*An API at or below 100 means that the pollutant levels are in the satisfactory range over 24 hour period and pose no acute or immediate health effects.
 
*Persistent '''''high''''' API values (51 to 100) in a year may mean that the annual Hong Kong ''Air Quality Objectives'' for protecting long-term health effects could be violated.
 
*API values in excess of 100 ('''''very high''''') mean that levels of one or more pollutant(s) is/are in the unhealthy range. The Hong Kong EPD provides advice to the public regarding precautionary actions to take for such levels.
 
Although Hong Kong is now part of China, it can be seen that Hong Kong's API scale differs from both China's scale and Beijing's scale.
 
{| border="0" width="225" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
|
{| class=wikitable align="right" cellpadding="5"
|+ Malaysia's API<ref name=DOP>[http://www.doe.gov.my/en/content/air-pollutant-index-api-reading-0 Air Pollutant Index (API)]Department of the Environment, [[Malaysian Ministry of Natural Resources and Environment.</ref>
! Air Pollution<br/>Index<br/>(API)|| Air Quality<br/>Category
|-
| 0 – 50|| Good
|-
|-
| 51 – 100|| Moderate
!align=right|<math>\sigma_y</math>
|-
|align=left|= horizontal standard deviation of the emission distribution, in m
| 101 – 200|| Unhealthy
|-
| 201 – 300|| Very Unhealthy
|-
| 301+ ||Hazardous
|}
|}
 
===Malaysia===
 
The air quality in [[Malaysia]] is described in terms of an Air Pollutant Index (API). The API is an indicator of air quality and was developed based on scientific assessment to indicate in an easily understood manner, the presence of pollutants and its impact on health. The API system of Malaysia closely follows the similar system developed by the [[U.S. Environmental Protection Agency]] (U.S. EPA). As shown in the adjacent table, Malaysia does not color code their air quality categories.
 
Monitoring stations measure the concentration of five major pollutants in the ambient air: PM<sub>10</sub>, sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone. These concentrations are measured continuously on an hourly basis. The hourly value is then averaged over a 24-hour period for PM1<sub>10</sub> and sulfur dioxide and an 8-hour period for carbon monoxide. The ozone and nitrogen dioxide are read hourly. An hourly index is then calculated for each pollutant. The highest hourly index value is then taken as the API for the hour.
 
When the API exceeds 500,  a state of emergency is declared in the reporting area. Usually, this means that non-essential government services are suspended, and all ports in the affected area closed. There may also be a prohibition on private sector commercial and industrial activities in the reporting area excluding the food sector.
 
{| border="0" width="275" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
|
{| class=wikitable cellpadding="5" align="right"
|+ Mexico's IMECA<ref>[http://www.sma.df.gob.mx/simat2/index.php?opcion=24 IMECA (Índice Metropolitano de la Calidad del Aire)]</ref>
! Air Quality<br/>Index<br/>(IMECA)|| Air Quality<br/>Category|| Color<br/>Code
|-
| 0 – 50|| Good|| bgcolor="#00CC00"|&nbsp;
|-
|-
| 51 – 100|| Moderate ||  bgcolor="#FFFF00"|&nbsp;
!align=right|<math>L</math>
|-
|align=left|= height from ground level to bottom of the inversion aloft, in m
| 101 – 200|| Unhealthy || bgcolor="#FF7E00"|&nbsp;
|-
| 201 – 300|| Very Unhealthy||bgcolor="#FF0000"|&nbsp;
|-
| 301+|| Extremely Unhealthy|| bgcolor="#99004C"|&nbsp;
|}
|}
 
===Mexico===
 
The air quality in [[Mexico]] is described and reported hourly in terms of a color coded [[Metropolitan Index of Air Quality]] (IMECA), developed by the [[Ministry of the Environment for the Government of the Federal District]].
 
The IMECA is calculated from the results of real-time monitoring of the ambient concentrations of ozone, sulfur dioxide, nitrogen dioxide, carbon monoxide and particulate matter (PM<sub>10</sub>).
 
The IMECA was developed specifically for the Federal District of Mexico which only encompasses Mexico City and its surrounding suburbs and adjacent municipalities. 
 
The real-time monitoring of the ambient atmosphere is performed by the Sistema de Monitoreo Atmosférico de la Ciudad de México (SIMAT or System of Atmospheric Monitoring for Mexico City).
 
SIMAT's real-time monitoring includes monitoring of the ultra-violet (UV) radiation from the sun and the results are also described and reported hourly as IUVs (Índice de Radiación Ultravioleta) in a manner that is similar to the reporting of the IMECAs.<ref>[http://www.sma.df.gob.mx/simat2/index.php?opcion=33 What is an Index of Ultraviolet Radiation?]</ref>
 
{| border="0" width="210" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
|
{| class=wikitable align="right" cellpadding="0"
|+ Singapore's PSI<ref name=NEA>[http://app.nea.gov.sg/cms/htdocs/article.asp?pid=1253 Frequently Asked Questions on the Haze (Q8)] (From the website of the National Environment Agency (NEA), Ministry of the Environment and Water Resources (MEWR).</ref>
! Pollution<br/>Standard <br/>Index<br/>(24-hour PSI)|| Air Quality<br/>Category
|-
| 0 – 50|| Good
|-
|-
| 51 – 100|| Moderate
!align=right|<math>\exp</math>
|-
|align=left|= the exponential function
| 101 – 200|| Unhealthy
|-
| 201 – 300|| Very Unhealthy
|-
| 301+ ||Hazardous
|}
|}
|}


===Singapore===
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.


[[Singapore|Singapore's]] National Environment Agency (NEA) in the [[Ministry of the Environment and Water Resources (MEWR)]] has the responsibility for the real-time monitoring of the concentrations of sulfur dioxide, nitrogen dioxide, carbon monoxide, ozone and PM<sub>10</sub> in the ambient air of Singapore.  
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.


The real-time monitoring of the ambient air quality is done by a telemetric network of air quality monitoring stations strategically located in different parts of Singapore.
<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 NEA uses the real-time monitoring data to obtain and report 24-hour Pollution Standard Index (PSI) levels  along with their corresponding air quality categories as shown in the adjacent table and which does not use color coding.<ref name=NEA/>
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.


The NEA states that the PSI scale developed for use in Singapore is very similar to the scale developed and used by the U.S. Environmental Protection Agency. The NEA also further states that the [[National Ambient Air Quality Standards]] (NAAQS) developed  by the U.S. Environmental Protection Agency are used to assess Singapore's air quality.
==Briggs plume rise equations==


Although the adjacent table indicates that the NEA categorizes a 24-hour PSI level that is higher than 300 as being ''hazardous'', the NEA also considers a 24-hour PSI level higher than 400 to be ''life-threatening to ill and elderly persons''.<ref name=NEA2>[http://app.nea.gov.sg/cms/htdocs/article.asp?pid=1251 Haze Action Plan] (From the website of the NEA)</ref>
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).


{| border="0" width="265" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
[[File:Gaussian Plume.png|thumb|right|333px|Visualization of a buoyant Gaussian air pollutant dispersion plume]]
|width=100%|
{| class=wikitable cellpadding="0" align="right"
|+ United Kingdom's API<ref name=AEA>[http://www.airquality.co.uk/standards.php#band Air Quality Standards] (From a website maintained by AEA Technology on behalf of DEFRA)</ref>
! Air Pollution<br/>Index<br/>(API)|| Health Effect<br/>Banding|| Color<br/>Code
|-
| 1 – 3 || Good || bgcolor="#00E400"|&nbsp;
|-
| 4 - 6 || Moderate || bgcolor="#FF9900"|&nbsp;
|-
| 7 – 9 || High || bgcolor="#FF0000"|&nbsp;
|-
| 10 || Very High || bgcolor="#99004C"|&nbsp;
|}
|}


===United Kingdom===
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>


[[AEA Technology]], a [[Great Britain|British]] environmental consulting company, issues air quality forecasts for the [[United Kingdom]] (UK) on behalf of the [[Department for Environment, Food and Rural Affairs]] (DEFRA).<ref name=AEA/> The scale used in the United Kingdom is an Air Pollution Index (API) with levels ranging from 1 to 10 as shown in the attached table and it is color coded.
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


The scale was thoroughly studied and approved by the United Kingdom's government advisory body, namely the "Committee on Medical Effects of Air Pollution Episodes" (COMEAP).<ref name=AEA/>
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'''''.


The scale is based on continuous monitoring, in locations throughout the United Kingdom, of the ambient air for the concentrations of the major air pollutants, namely sulfur dioxide, nitrogen dioxide, ozone, carbon monoxide and PM<sub>10</sub>. The forecasts issued by AEA Technology are based on the prediction of air pollution index for the worst-case of the five pollutants.
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).


As shown in the adjacent table, the health effect of each API range is referred to as its ''banding'' rather than as its ''category''. The health effect bandings for the API ranges are ''low'', ''moderate'', ''high'' and ''very high''.
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" width="265" align="right" cellpadding="0" cellspacing="0" style="wrap=no"
:{| border="0" cellpadding="2"
|width=100%|
|-
{| class=wikitable cellpadding="5" align="right"
|align=right|where:
|+ United States' AQI<ref>[http://airnow.gov/index.cfm?action=static.aqi Air Quality Index (AQI)] (From the website of AirNow created by the U.S. EPA, NOAA and other U.S. federal, tribal, state and local agencies)</ref>
|&nbsp;
! Air Quality<br/>Index<br/>(AQI)|| Air Quality<br/>Category|| Color<br/>Code
|-
|-  
!align=right| Δh
| 0 – 50|| Good|| bgcolor="#00E400"|&nbsp;
|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
|-
|-
| 51 – 100|| Moderate||  bgcolor="#FFFF00"|&nbsp;
!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>
| 101 – 150|| Unhealthy for<br/>Sensitive Groups|| bgcolor="#FF7E00"|&nbsp;
|-  
| 151 – 200|| Unhealthy||bgcolor="#FF0000"|&nbsp;
|-  
| 201 – 300|| Very Unhealthy|| bgcolor="#99004C"|&nbsp;
|-
| 301 – 500|| Hazardous||bgcolor="#7E0023"|&nbsp;
|}
|}
|}
The above parameters used in the Briggs' equations are discussed in Beychok's book.<ref name=Beychok/>


===United States===
==References==
{{reflist}}


The Air Quality Index (AQI) ranges used by the U.S. Environmental Protection Agency (U.S. EPA) and their  corresponding health effect categories and color codes are provided in the adjacent table. The U.S. EPA's AQI is also known as the Pollution Standards Index (PSI).
== Further reading==
 
If multiple pollutants are measured at a monitoring site, then the largest or "dominant" AQI value is reported for the location.


The U.S. EPA has developed conversion calculators, available online,<ref>[http://airnow.gov/index.cfm?action=aqi.aqi_conc_calc AQI Calculator: AQI to Concentration]</ref><ref>[http://airnow.gov/index.cfm?action=aqi.conc_aqi_calc AQI Calculator: Concentration to AQI]</ref> for the conversion of AQI values to [[concentration]] values and for the reverse conversion of concentrations to AQI values.
*{{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}}


A national map of the [[United States]] containing daily AQI forecasts across the nation, developed jointly by the U.S. EPA and [[NOAA]] is also available online.<ref>[http://www.airnow.gov/index.cfm?action=airnow.national Today's National Air Quality Forecast]</ref>
*{{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}}


The [[Clean Air Act of 1990]] requires the U.S. EPA to review its [[National Ambient Air Quality Standards]]<ref>[http://www.epa.gov/air/criteria.html National Ambient Air Quality Standards] (From the website of the U.S. EPA)</ref> every five years to reflect evolving health effects information.  The Air Quality Index is adjusted periodically to reflect these changes.
*{{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}}
 
=====Air pollutant concentration measurement units=====
In the United States, the concentrations of the air pollutants involved in the AQI are usually expressed as:
* Ozone and sulfur dioxides: ppbv = parts per billion (10 <sup>9</sup>) by volume = volume of pollutant gas per billion volumes of ambient air
* Carbon monoxide: ppmv = parts per million (10 <sup>6</sup>) by volume = volume of pollutant gas per million volumes of ambient air
*PM<sub>10</sub>, defined as particulate matter having an aerodynamic diameter of 10 μm (micrometer) or less: ug/m³ = micrograms of particulate matter per cubic metre of ambient air
*PM<sub>2.5</sub>, defined as particulate matter having an aerodynamic diameter of 2.5 μm (micrometer) or less: ug/m³ = micrograms of particulate matter per cubic metre of ambient air
 
==References==
{{reflist}}


_________________________________________________________
*{{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}}
==See also==
* [[Air pollution]]


* [[Atmospheric dispersion modeling]]
*{{cite book | author=R. Barrat| title=Atmospheric Dispersion Modelling | edition=1st Edition | publisher=Earthscan Publications | year=2001 | isbn=1-85383-642-7}}
* [[Emission standard]]
* [[European emission standards]]
* [[Smog]]
* [[U.S. National Ambient Air Quality Standards]]


==External links==
*{{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}}


* [http://www.pcd.go.th/info_serv/en_air_aqi.htm Thailand's AQI] (Predominantly in the Thai language)
*{{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


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.