OVERVIEW The problem of air pollution (i.e in cities ... · Stochastic Methods •Mathematical...

Methods for Atmospheric Dispersion EstimatesNTUA/Aerolab/GB

NTUA 1

••AirAir quality prediction methods in complex terrainsquality prediction methods in complex terrains

OVERVIEW The problem of air pollution (i.e in cities-

Athens) Methods for reducing air pollution impact Methods for predicting air pollution impact Results (Stochastic versus deterministic

models) The Future from the Professional Engineering

point of view


NTUA 2

••What is AIRWhat is AIR--POLLUTIONPOLLUTION

Introduction into the environment of substances or energy in such quantities that can cause damages to•living organisms•human health•ecological systems•constructions-monuments, or•restrictions in the legal use of the environment

Primary:CO, SO2, Smoke,Pb etc.

Secondary-Photochemical:ΝΟx (ΝΟ2, ΝΟ), Ο3.

MAJOR AIR POLLUTANTS


NTUA 3CAUSES OF AIRPOLLUTION in citiesCAUSES OF AIRPOLLUTION in cities

Concentration of millions of people and activities in the city

Traffic problems Not modern means of public transportation Bad fuel quality Inadequate maintanance of engines and furnaces Local industry Air-transport of pollutants from industrial area


NTUA 4

ACTIVITIES POLLUTANTS

Thermal power stations Smoke, particles, SO2,NOx,HC

Refineries HC,CO,SO2,NOx,H2S,particles

Cement factories TPM,SO2,NOx

Steel industry TPM, CO, SOx, NOx, HC

Fertiliser TPM, NH3, F or S or N compounds

Glass industry SOx, NOx,F compounds, TPM

Cars CO, HC,NOx, TPM, SO2

Sources and types of pollutants


NTUA 5

CAUSES AND CONSEQUENCES OF AIR POLLUTION IN CAUSES AND CONSEQUENCES OF AIR POLLUTION IN ATHENSATHENS

The high air pollution levels in Athens are due to a combination of :

High emission levels as a consequence of industrial and transportation activities.

Unfavourable topographical and meteorological features: leading to land breeze and sea breeze which have opposing effects .

Sun shine

CONSEQUENCES•A brown cloud over the city appeared in the 1970-Photochemical smog•Threat to the public health and damage to ancient monuments


NTUA 6

EmissionsEmissions

Interactions,Interactions,Chemical ReactionsChemical Reactions& Transformations.& Transformations.

Diffusion and TransportDiffusion and Transportof Air Pollutants of Air Pollutants

THE MECHANISMS OF AIR POLLUTION

Air QualityAir Quality


NTUA 7

SOURCES

Cars

Heating

Industry

Total

tn %. tn % tn % tn %

smoke 3.300 64 859 17 1.035 19 5.195 100

particles 90 0 0 0 21.206 100 21.296 100

SO2 1.410 7 3.690 21 12.696 72 17.796 100

NOx 17.400 67 1.391 5 7.181 28 25.972 100

CO 323.750 100 380 0 449 0 324.579 100

HC 46.200 68 190 0 21.747 32 68.137 100

Athens

Emissions of pollutants in big cities

Emission regulation limmitsnecessitate the installation of APCequipment, i.e E/P, catalytic cars


NTUA 8

••Present status of cars in GreecePresent status of cars in Greece

0

200000

400000

600000

800000

1000000

cars

1 2 3 4 5

age slo t

Cars vs age

Up to 5 years6-10

11-15

16-20

>20 years

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7

Catalyticnon-catalytic

20041998

Predictions without measures

0

50

100

150

200

250

1 2 3

Kt/a CO

NOx VOC

2004

%


NTUA 9

••Predictions mith measuresPredictions mith measures

0102030405060708090

1 2 3 4 5 6 7

-45

-40

-35

-30

-25

-20

-15

-10

-5

01 2 3

20041998

catalytic

Reduction in emissions

CO NOx VOC

By 2004-4-3-2-10123456

1 2 3

CONOx VOC

Change of Emissions without measures by 2004


NTUA 10Interactions,Chemical Reactions& Transformations.Interactions,Chemical Reactions& Transformations.

Intense sunshine many days during the year

• High temperatures(Increased speed of the chemical reactions)

• Great variety of air pollutantsand chemical reactions

Country Days ina year

µgr/m3

of O3

Durationin hours

Austria 8 224 1.7Belgium 11 230 2.9Germany 19 219 1.8Danemark 0 <180 -Spain 40 341 1.9Finland 0 <180 -France 42 277 2.2U.K 9 228 2.5Greece 53 304 2.2Ireland 0 <180 -Italy 68 339 3.3Lux 2 203 2.3Holland 7 251 1.9Portugal 10 242 2.2Sweden 0 <180 -Control of VOC and HC ( not of sunshine)


NTUA 11

Diffusion and Transport of Air Pollutants Diffusion and Transport of Air Pollutants

• Complex topography (Athens basin)• Influence by the sea (breeze)

0

10000

20000

30000

40000

50000

60000

70000

x-ax

is (

met

res)

0 10000 20000 30000 40000 50000 60000 70000

y-axis (metres)

14:00 LST/ Horizontal wind velocity at 10 m AGL.

10 m/s0

10000

20000

30000

40000

50000

60000

70000

x-ax

is (m

etre

s)

0 10000 20000 30000 40000 50000 60000 70000

y-axis (metres)

10 m/s



NTUA 12Air QualityAir Quality ««GoodGood» or «» or «BadBad»»

Regulation of air pollution concentrations of pollutants

•Allowable limmits

•1st stage measures

•2nd stage measures

•Values and severity of measuresdepend on the toxicity of the pollutant

O3: 200 µg/m3 in 1 hour

SO2: 300 µg/m3 in 24 hours

Pollution index ( good, medium, bad)


NTUA 13Methods for reducing air pollution impact in Athens

Industry• New combustion technologies• New production processes• Installation of equipment

• Electrostatic filters • Cyclones• Low NOx burners• Replacement of fuels • Better quality fuels

Transportation• Public transport• Metro• Better fuel• Catalytic cars• Exhaust emissioncertification

• Introduction of Natural gas into the energy system


NTUA 14

b.Photochemical oxidantsDramatic increase of

approximately 15% p.a.. After 1987 the concentrations of some cases started to exceed the health protection threshold of the European Union. O3 is a major pollutant in big cities

a. SO2 and smoke - 1974-1985 : the limitationsin the use of heavy oil , thereductions of diesel fuel sulfurcontent and periodic controls ofcombustions led to a reduction ofthese substances.

- 1985 onwards: sulfurdioxide emissions increaseddue to birth of newindustries. Smokeconcentration levels rosebut below allowable limits.

- Today allowable limmitsare not exceeded

Present state of air pollution in Athens


NTUA 15

First ApproachFirst ApproachDetermenistic (Physical)

Second ApproachSecond ApproachStochastic Methods

•Mathematical description ofthe phenomenon.•Numerical simulation of theair field.•Numerical calculation of thediffusion, transformation andtransportationof the air pollutants into the atmosphere

•Use is made of alreadymeasured concentration valuesin order to predict those whichwill be observed in the future.G

ener

al

Cha

ract

eris

tics

Inpu

t In

form

atio

n•Emission data•Meteorological data•The topography of the region

•Already measured concentration values•Differences between the predicted and the observedconcentration values•«Optionally»: meteorological data

APPROACHES FOR MODELLING AIR POLLUTION


NTUA 16

•Wind speeds all over the simulated area (flow field)

•Air pollutants concentrationvalues all over the simulated area

•Air pollutants concentration values in specific locations(where the air qualitymonitoringstations are installed)O

utpu

tIn

form

atio

n

APPROACHES FOR MODELLING AIR POLLUTION


NTUA 17

THE PHYSICAL MODEL

• Mass continuity equation :

∂∂

ρx

( j =1,2,3j

U j ) ,= 0

(1)

• Momentum equations

[

]

D UDt

Px x

Ux

Ux

u u g f U

U f U f U

i

i j

i

j

j

i

j i i i

i i i

( )

(

)

ρ ∂∂

∂∂

µ∂∂

∂

∂

ρ ρ δ

δ δ δ

= − + +

−

+ + −

− +

ΘΘ0

1 1 2

2 1 2 1 3 2 3 1

(2)

where f1 and f2 are the coriolis coefficients and are definedby :

f and f1 22 2= =Ω Ωsin cos ,φ φ

Ω being the angular velocity of the earth’s rotation and φthe latitude.

• Potential temperature and species concentrationequations :

DD t x x

u Q

D CD t x

Cx

u c Q

j jj

j c jj s

( )

( )

,

,

ρ ∂∂

µσ

∂∂

ρ θ

ρ ∂∂

µσ

∂∂

ρ

Θ Θ

Θ= −

+

= −

+

•

•

l

l

(3)

where Q•

and Qs

• represent respectively the surface

heat flux and pollutant emission rate.

The above set of equations is closed via the Boussinesqeddy viscosity approximation in conjunction with the k-εturbulence model :

025501002003004005006007008009001000

Deterministic approach


NTUA 18

( ) ( ) ( )u zXx y

K zXy z

K zXzy z

∂∂

∂∂

∂∂

∂∂

∂∂

~

+

+−= 2

2

2

2

21exp1

zyzy

zyQXu

σσσσπ

uxK

uxK z

zy

y22 22 == σσ

Gaussian Models of Dispersion

With the assumptions of •uniform velocity, •flat terrain and •introduction of empirical correlations σy and σz


NTUA 19•• EPA recommended methodologyEPA recommended methodology

UNAMAP series computer codes/www.epa.gov– Gaussian models

Mostly for flat terrains - extension to complex topography

Usually underestimate environmental impact Require detailed information not usually

available in most power station sites i.e mixing heights, turbulence level, etc

Gaussian models can simulate point, line and area sources of pollution


NTUA 20••The Engineering Problem The Engineering Problem -- LegislationLegislation

MINIMISE environmental impact of the new source– Find minimum stack height so as MGLC to comply with the legislation

Pollutants– SO2( Desulphurisation)– NOx ( Low NOx burners)– Particulates ( E/P)

Legislation– Clean Air Act– E.U legislation– Greek legislation


NTUA 21••Basic Design FactorsBasic Design Factors

Minimum height of stack– Hs=1.4 Hb

Minimum exit velocity– Vs=1.5 us(p>90%)

Xs-b> (3 to 5) Hb

Relative location of stack and cooling tower


NTUA 22

••Risk Analysis Methodology (1st stage analysis)Risk Analysis Methodology (1st stage analysis)

Let the computer programme run for “ hours” to find the worst meteorological conditions which lead to maximum GLC

– Parametric studies of» stack height» gas exit velocity, etc.

Design results will be on the safe side for the whole power station life

but overestimated


NTUA 23•• 1st stage results1st stage results

1 2 3 40

50

100

150

200

250

1h NO2

Stability classes

• 150 m stack•125 m stack• 100 m stack height

1 2 3 40

50100150200250300

Stability classes

24h SO2


NTUA 24

••2nd Stage Analysis / ENVIPOL2nd Stage Analysis / ENVIPOL

With the most detailed meteorological information available for one,two years etc and with the results of the 1st stage

– hourly,24h and yearly concentrations of pollutants are predicted and compared with the legislative values (design parameters are adjusted accordingly)

The results of the year indicate the meteorological conditions which led to maximum maximorum of GLC


NTUA 25

After examination of 10 years, year 1974 led to highest GLC After examination of 10 years, year 1974 led to highest GLC

0

5

10

15

20

40

60

80

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180

200

0

5

10

15

20

25

30

35

40

45

50

100

200

300

350

1h GLC NO2 98%, max=172µg/m3 24h GLC SO2 95%, max=48,7µg/m3

Mean annual values1h NOx 23 micro g/m324 h SO2 7.5 micro g/m3

2nd stage- Results / ENVIPOL


NTUA 26

••3rd Stage Analysis ( the POCART computer code)3rd Stage Analysis ( the POCART computer code)

POCART computer code – developed over years

Feartures– Collocated approach-porosity-nested grid

24 hour numerical simulation for the “ worst” meteorological conditions found in 2nd stage

The code requires at least 16 MB CPU memory and few days of CPU time on a HP workstation

Usually results are lower than those predicted by Gaussian models ( 2nd stage) as expected.


NTUA 27

THE PHYSICAL MODEL

• Mass continuity equation :

∂∂

ρx

( j =1,2,3j

U j ) ,= 0

(1)

• Momentum equations

[

]

D UDt

Px x

Ux

Ux

u u g f U

U f U f U

i

i j

i

j

j

i

j i i i

i i i

( )

(

)

ρ ∂∂

∂∂

µ∂∂

∂∂

ρ ρ δ

δ δ δ

= − + +

−

+ + −

− +

ΘΘ0

1 1 2

2 1 2 1 3 2 3 1

(2)

where f1 and f2 are the coriolis coefficients and are definedby :

f and f1 22 2= =Ω Ωsin cos ,φ φ

Ω being the angular velocity of the earth’s rotation and φthe latitude.

• Potential temperature and species concentrationequations :

DD t x x

u Q

D CD t x

Cx

u c Q

j jj

j c jj s

( )

( )

,

,

ρ ∂∂

µσ

∂∂

ρ θ

ρ ∂∂

µσ

∂∂

ρ

Θ Θ

Θ= −

+

= −

+

•

•

l

l

(3)

where Q•

and Qs

• represent respectively the surface

heat flux and pollutant emission rate.

The above set of equations is closed via the Boussinesqeddy viscosity approximation in conjunction with the k-εturbulence model :

025501002003004005006007008009001000

THE POCART SOFTWARE


NTUA 28

••FEATURES OF THE CODEFEATURES OF THE CODE

• The irregular boundary (terrain surface) is approximated by a broken oblique surface.

• Geometrical coefficients are introduced to take account of the fact that boundary cells are not composed totally of fluid.

• This is done by a preprocessor

Y

XReal Boundary

Approximated Boundary

Ground

• Cartesian velocities- Cartesian coordinates


NTUA 29

•• FEATURES OF THE CODEFEATURES OF THE CODE

• Local refinement was used in regions with high gradients of pollutants concentrations.

• Fine meshes were constructed by dividing the cells of the coarse grid in a number of smaller cells.

• Boundary conditions for the inner fine mesh were obtained by interpolation of the variables in the surrounding cells(adjacent to the interface) which belong to the coarse grid

• Boundary conditions for the coarse grid were calculated by volume-weighting of the variables of the fine grid. The fluxes through the interface were surface-weighted.

coarse grid refined grid

common boundary (interface)

coarse grid

refinedgrid

interface

P P1

E1

solved values interpolated values

E2P2

S


NTUA 30

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0.0010000.00

20000.0030000.00

40000.0050000.00

60000.0070000.00

0.00

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60000.00

70000.00

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0.10

0.50

1.00

9.00

10.00

30.00

50.00

100.00

200.00

300.00

WIND FIELD & SO2 Concentration in time

On 25.5.90


NTUA 31

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met

res)

0 10000 20000 30000 40000 50000 60000 70000

y-axis (metres)


10 m/s

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20000.0030000.00

40000.0050000.00

60000.0070000.00

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30000.00

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50.00

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200.00

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NTUA 32

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30000

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50000

60000

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x-ax

is (m

etre

s)

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y-axis (metres)

10 m/s


0.00

10000.00

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30000.00

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60000.00

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NTUA 33

0.0010000.00

20000.0030000.00

40000.0050000.00

60000.0070000.00

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40000.00

50000.00

60000.00

70000.00

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1.00

2.00

3.00

5.00

7.00

9.00

0.0010000.00

20000.0030000.00

40000.0050000.00

60000.0070000.00

0.00

0.05

0.10

0.20

0.50

1.00

2.00

3.00

5.00

7.00

9.00

CO concentration

At 1:00 At 14:00


NTUA 34

0.00

0.05

0.10

0.20

0.50

1.00

2.00

3.00

5.00

7.00

9.00

OBSERVATIONS

• The model predicts Theatmospheric stability changesduring the day.

• Downward wind currents aregenerated in mountains during thenight, due to cooling of theground.

• Pollutants are advected by thesecurrents from the basin towardsthe sea.

• Sea breeze then readvects thepollutants back to the basin duringthe day.

At 22:00

CO concentration


NTUA 35Conclusions I

• The 3 stage approach leads to conservative estimation of the environmental impact of power plant stacks.• Highly suitable for complex topographies where recirculation might be present.• The POCART code is reliable for engineering calculations but requires computer resources .• The described approach must be used in complex terrains or in coastal areas.


NTUA 36

The Time Series Stochastic Models’ Development Process Obtaining the Predictions Predictions Accuracy Criteria Predictions Confidence Limits

Stochastic Prediction Models

First ApproachFirst ApproachDetermenistic (Physical)

Second ApproachSecond ApproachStochastic

Adv

anta

ges

Adv

anta

ges

Dis

adva

ntag

esD

isad

vant

ages

•It takes into account thephysical mechanism of the phenomenon•It concerns the entireregion which is modelled

•Accurate emissions dataare required•High computer power anda lot of time are needed so that accurate predictionscan be obtained

•Emissions data are not needed•Reliable predictions areobtained on real time basis•High power computers arenot needed•User friendly•No specific knowledge isneeded

•Air quality monitoring networks are required•The physical mechanism ofthe phenomenon is not takeninto consideration•The predictions are forspecific locations only•The type of the stochastic model must be modified when the general conditions in the specific location change

APPROACHES FOR AIR POLLUTION MODELLING


NTUA 38

•The Stochastic Models (S.M.) do not describe the physical mechanism of the creation and evolution of air pollution.•The S.M. make use of information included in past concentration values to predict future values.•S.M. which use meteorological or other physical data as input information can be developed.

Already observed concentration values

Differences between predicted andobserved concentrations from the past

StochasticStochastic ModelModel

Future ConcentrationValues

OUTPUTOUTPUTOUTPUT

STOCHASTIC PREDICTION MODELS/ Introduction


NTUA 39

The concentration values for the n nexttime steps(hours, days, etc) are predicted as we are foundin time t-1 and we knowall the measured concen-trations until this time.

PredictionsPredictions

«One Step Ahead» «One Step Ahead» «With Time Horizon»«With Time Horizon»Time Horizon > 1 step (hour, day)

t-2

t-1

t

t+1

t+2

t+3

t+4

11stst Prediction: known until Prediction: known until tt--11

2nd Prediction: known untilknown until t

33rdrd Prediction: known until Prediction: known until t+1t+1

44thth Prediction: known until Prediction: known until t+2t+2etc.

The next time step (hour, day, etc.) concentration value is predicted as we know the observed concentration values until the current time step.

t-2

t-1

t

t+1

t+2

t+3

t+4

Here n=5

etc.

Present

Futu

re

Past

STOCHASTIC PREDICTION MODELS/ Predictions


NTUA 40

AI.PO.C.:1-Hour Aheadpredictions for the25th May 1990.

CO concentration at Patision str 1 hour ahead


NTUA 41

AI.PO.C.:Predictions with Horizon the 25th May 1990.

• For CO at Patision St.


NTUA 42

• For O3 at Amarousion.

Predictionswith horizon 2 days ahead(9 &10 May1992).

O3

(µgr

/m3 )


NTUA 43AI.PO.C. Program

More accurate More accurate predictionspredictions.

Predictions on a real on a real time basistime basis.

Emission data are notnotneededneeded.

Measurement stationsstations ornetworksnetworks are needed.

Doesn’t take into account the flow fieldflow field

aerodynamic characteristicsaerodynamic characteristics.

Stochastic Models mustmustbe modifiedbe modified whenever thegeneral conditions change.

Dispersion Model

Takes into account thephysical mechanismphysical mechanism and

the flow field aeroflow field aero--dynamic characteristicsdynamic characteristics. The predictions concern

the entire areaentire area.

Predictions are not onnot ona real time basisa real time basis.

It is impossible to knowwith the desirableaccuracy the air

pollutant emissionsemissions.

Adv

anta

ges

Dis

adva

ntag

es


NTUA 44

••SUMMARYSUMMARY

Three types of prediction models are available

Gaussian types ( suitable for engineering calculations and decision makers)

Differential ( suitable for research and engineering calculations)

Stochastic ( suitable for municipalities)


NTUA 45

••The Environmental engineeringThe Environmental engineering

Professional activity with a bright future– Design office for environmental impact studies– Design office for APC equipment selection-

installation– Construction of APC equipment– Monitoring equipment of Air Pollution

(construction-selection-installation)– Environmental impact auditors

OVERVIEW The problem of air pollution (i.e in cities ... · Stochastic Methods •Mathematical...

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