air quality applications - fmi

Air Quality applications(AQ modelers view)

Ari Karppinen

Ari Karppinen, HTB , 14/2/2007

?

BUOYANTbuoyant gases, fires

MATCH

ESCAPE,chem. accidents

OSPM (NERI),street canyon

MATCH

UDM-FMI, urban

CAR-FMI, traffic

EXPAND (+ YTV) exposure

METINPUT


Subset of measurements

Masts with 3 measurement heigths Ceilometers

+MALMIWindProfilerRASSDopplerLidarSODAR


z/h

z=zH

z=3zH

h/zH

Urban BL structureSketch of the urban boundary layer structure indicating the various (sub)layers and their names (from Rotach et al., 2004, modified after Oke, 1987). An unstable daytime urban boundary layer is shown. For a stable layer of height h ≅ 200m, h/zH ≅ 10 and z*/h ≅ 0.1 to 0.3.


The basics (valid only for the inertial sublayer ..in ideal conditions ! )

( )⎥⎥⎦

⎤

⎢⎢⎣

⎡Ψ−⎟⎟

⎠

⎞⎜⎜⎝

⎛ −= ζmz

dzku

zu0

* ln)(

( )⎥⎥⎦

⎤

⎢⎢⎣

⎡Ψ−⎟⎟

⎠

⎞⎜⎜⎝

⎛ −=− ζθ

θθ hr zdz

kz

0

* ln)(

Functional forms of universal functions from classical theory

Ldz −

=ζ

.

Where


Mast data : how to solve for turbulence parameters?

• measurements of T & u available at 2 levels => still too many unknowns u*, L , z0, d ?

• normally : z0, d determined by other/independent methods (like morphology/simple terrain type roughness classification,wind gust analyses) or profile based fitting/iteration/non-linear regression ( long time series of mast measurements a prequisite !)

Problem: z0 and d obviously strongly dependent on flow direction in heterogeneous environment


Practical example, Kumpula

0 50 100 150 200 250 300 350-140

-120

-100

-80

-60

-40

-20

0

20

40

Tuulen suunta ( °)

d (m

)

dd ± σd

100 190 270 360-10

-5

0

5

10

0 50 100 150 200 250 300 350-10

0

10

20

30

40

50

60

70

Tuulen suunta ( °)

z o (m

)

z0

z0 ± σz0

100 190 270 360-5

0

5

10

Displacement height & roughness length (Järvi , 2005)


Practical example ; Kivenlahti (1989-1998)

Displacement height determinedfrom neutral wind profiles

1.3

1.5

1.7

1.9

2.1

2.3

2.5

2.7

2.9

0 2 4 6 8 10 12

Displacement height (m)

Δu/Δ

ln(z

)

1

2

3

4

5

6

7

8

9

10

11

Rel

ativ

e er

ror(%

)

k21

k32

Rel.error (%)

Kivenlahti roughness length Neutral stratification

00.5

11.5

22.5

33.5

N

30

60

E

120

150

S

210

240

W

300

330

17503 observations at Kivenlahti during 1989-1998

Displacement height andwind direction

0

2

4

6

8N

30

60

E

120

150

S

210

240

W

300

330

Karppinen et al, 2002


The mixing height

Atmospheric boundary layer height, or the mixing height determine the volume

available for pollutant dispersion.

It depends on basic meteorological parameters, surface turbulent fluxes and physical

parameters, and follows a diurnal cycle.

The mixing height cannot be observed directly by standard

measurements, so that it must be parameterised or indirectly estimated from profile

measurements or simulations.


Appendix 5A: Some current formulations for estimating the mixing height:

Reference SBL height equations

1. Zilitinkevich (1972) 2/1*

2 ⎟⎟⎠

⎞⎜⎜⎝

⎛=

fLuch ,

c2 ≈ 0.4 (varies between 0.13 and 0.72 according to different authors)

2. Venkatram (1980)fN

uh 2*=

3. Arya (1981)

(after Zilitinkevich, 1972);

2/1* bfLuah +⎟⎟⎠

⎞⎜⎜⎝

⎛= 3.29,43.0 == ba

4. Nieuwstadt (1981)LhLf

uLh

9.10.10.13.0 *

+=

5. Zilitinkevich andMironov (1996)

fhu

hL

Nhu

h fu L

h Nfu0 5 10 20 17

12 1 2

1 2

1 2

. ( ) .* *

/

/

/⎛⎝⎜

⎞⎠⎟ + + + + =

∗ ∗

6. Zilitinkevich et al. (2002) ( )2/1

2**

2

*

* /111⎥⎥⎦

⎤

⎢⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛ ++⎟⎟

⎠

⎞⎜⎜⎝

⎛+=

fLCuNLCuC

uwC

fuCh

S

uNRhh

R

with: CR = 0.4, CS = 0.74, CuN = 0.25 and Ch = 0.3.

7. Zilitinkevich andBaklanov (2002) hKhhfCh

th

hCQEE2)(|| ∇+−−=∇⋅+

∂∂ V with CE ≈ 1

8. Joffre and Kangas (2002)NNN L

bma

abh

⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

⎥⎦

⎤⎢⎣

⎡ ++−= −2/1

22'

''411

'2' μμ

with a' =0.12, b' =2.85 and m' =24 (very rough surface)

where u10 is the wind speed at 10m height, V = (u,v) is the horizontal velocity vector, Kh

is the horizontal diffusivity, h is the equilibrium mixing height calculated from adiagnostic formulation (e.g. Zilitinkevich et al., 2002), μN = LN/L, LN = u*/N, and f is theCoriolis parameter.

Reference CBL height equations

9. Tennekes(1973);

Tennekes andDriedonks

(1981)

θΔ=

Sdtdh

; where h

uBwAS o βθ

3*)''( +=

hS

hwS

dtd o −−

Δ=

Δ )''( θθ

γθ ; where A = 0.2; B = 5.

10.Batchvarovaand Gryning

(1991)

( ) ( )2

3*2

''21

huB

hw

Ath o

βγγθ

++=∂∂

, where 2.0=A , 5.2=B

11. Gryningand

Batchvarova(1996)

( ) ( )[ ]( )γθ

∂∂

∂∂

∂∂

κβγκo

sw

wyhv

xhu

th

LBhAuC

LBhAh ''2

1221

2=⎟⎟

⎠

⎞⎜⎜⎝

⎛−++

⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

−++

−+∗ ,

with A = 0.2, B = 5, C = 1.3

12. Joffre andKangas (2002) NNN L

bma

abh

⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

⎥⎦⎤

⎢⎣⎡ ++= −

2/12

2"""411

"2" μμ with a´´= 0.1 ; b´´= - 0.85 ; m´´=12

R eferen ce N eu tra l A B L h e ig h t eq u atio n s

1 3 . R o ssb y an d M o n tgo m ery(1 9 3 5) ||

*

fu

ch N= , w h ere cN = 0 .0 4 - 0 .3 (S e ib e rt e t a l., 1 9 9 8 )

1 4 . A rya (1 9 8 1)1.85089.0 * +=

fuh

1 5 . M ahrt (1 9 82 )f

uh *06.0=

1 6 . B en k ley an d S ch u lm an(1 9 7 9) 10125 uh =

1 7 . N ieu w stad t (1 9 8 4) 2/31028 uh =

E q u atio n s (1 4 ) to 1 7 ) h av e b een d ev e lo p ed fo r n eu tra l co n d itio n s , b u t so m e au th o rs h av eu sed th em a lso fo r s tab le c o n d itio n s .

The ”equation-slide”


Wind profilers & RASS (Angevine)

Ideal case Residual layerSmooth gradient


Wind profilers & RASS (Angevine)

If the convective boundary layer is physically well defined , wind profilers can find the mixing height -but – simple automatic procedures are expected to work in only very simple situations.

The profiles gives very good information of the morning transition of the boundary layer but in the afternoon – the reverse transition is much more difficult to track with profilers – the residual inversion often shows stronger reflectivity maxima, leading easily to erroneous interpretation

Spectral width profiles can be used to distinguish between active turbulent region from developing residual layer.(for details see e.g.: Heo et al, 2003 –available from: http://ams.allenpress.com )

RASS together with surface data can be useful for nocturnal MH determination.


SODAR (Malmi , 21.8.2006 klo 8:30 UTC

Used (~20 years) for continuous monitoring of boundary layer conditions.

A good tool for monitoring the nocturnal, surface-based temperature inversion -although different from the mixing height, the nocturnal inversion is equally important for modeling nocturnal dispersion conditions.

The range of a sodar, however, is limited; estimates of the mixing height are possible only when the top of the mixed layer within the range of the sodar.


LIDARS

• For AQ-modeller by far the most interesting profilers

• Measuring directly aerosol profiles (also one of the most important pollutant!)

• Especially interesting for urban areas where modeling the mixing height is extremely difficult – and – the aerosol concentrations are high enough for utilizing the aerosol profiles for mixing height determination


Doppler lidar at Malmi (http://www.ties.salford.ac.uk/people/keb/ufamlidar.html)


Ceilometer(CL31): Nurmijärvi 27 08 2006


Ceilometer(CL31): Vallila 21 08 2006


Clear sky situations• MH estimated by fitting an

idealized profile to the measured backscatteringprofile by the formula

(Steyn et al., 1999)• Bm is the mean mixing layer

backscatter and Bu is the mean backscatter in the air above the mixing layer; Δh is related to the thickness of the entrainment zone

⎟⎠⎞

⎜⎝⎛

Δ−−

−+

=hMHzerf

BBBBzB umum

22)(

Figure 2. An idealizedbackscattering profile.


Reference mixing height

An example of the Richadsonnumber profile at Vantaa, 4 January 2002 07:17 UTC

. Illustration of the Holzworth-method. Temperature profileat Vantaa, 29 May 2002 08:56 UTC


Cloudy situations – methods• Fog: the idealized profile method• Cloud type 1: The critical value

(25% of the maximum value)• Cloud type 2:

• Minimum well-defined: the cloud removed and the idealized profile methodused

• Otherwise the minimum orthe critical value (10% of the maximum value) used

Figure 4. Example of the removed cloud at Vantaa, 3 April 2002 9:40 UTC


Results: Clear sky situations

)8947()10.080.0( ±+±= soundingceilometer hh

. Comparison between mixing heightsdetermined by the ceilometer and radiosoundings in convectivesituations.The regression line is

The correlation coefficient r = 0.90

Comparison between mixing heightsdetermined by the ceilometer and radiosoundings in stable situations.The regression line is

The correlation coefficient r = 0.80)34120()16.062.0( ±+±= soundingceilometer hh


Results: Cloudy situations

Comparison between mixing heights determined by the ceilometer and radiosoundings in cloudy situations.


MH and Testbed• 5 CL31 ceilometers• The 2-step algorithm

• MHSL corresponds to the lowermixing height (Step1); MHML to the upper one (Step2).

• The algorithm is tested with twodatasets (22 November 2005 and mid-April 2006

)(*22

)(*22

)(

ML

MLUMLUML

SL

SLMLSLMLSL

hMHz

erfBBBB

hMHz

erfBBBB

zB

Δ−−

−+

+

Δ−−

−−

=

An idealized backscattering profile(2-step algorithm)


2-step method - results

72-h period of ceilometer echo intensity observations at Vallila, 13-15 April 2006


Examples of longer observation periods

Mixing height as determined bydifferent methods or schemesduring a surface temperatureinversion (2-3 January 2002)

A 24-h period of ceilometer echointensity observations at Vantaa, 29 May 2002


”Next step” 3-step method

444444 3444444 214444444 34444444 21444444 3444444 213

2

222

2

22

1

1

111

222222)(

STEP

UU

STEP

ML

MLMLML

STEP

MLML

hMHzerfBBBB

hMHzerfBBBB

hMHzerfBBBBzB ⎟⎟

⎠

⎞⎜⎜⎝

⎛Δ−−

−+

+⎟⎟⎠

⎞⎜⎜⎝

⎛Δ−−

−−

+⎟⎟⎠

⎞⎜⎜⎝

⎛Δ−−

−−

=

First HTB-data basedevaluation in

Eresmaa et al, 2007

“The most promising methods in mixing height determination are ceilometer and lidar.

Both systems still face some problems. The biggest problem for ceilometer are the clouds, as the biggest problem for the lidar is the range of the data “


ConclusionsHTB offers an exceptionally rich database

(lidars,sodar,soundings,masts,wind profiler,RASS) for developing and evaluating turbulence and mixing height parameterizations

– and –for developing operative methods for mixing height

“measurements”The real work has just started :- finding out the efficient/reliable combination of

profilers for providing continuous MH-observations will be one of the main goals for AQ-modelers


references• Eresmaa, N, Karppinen, A, Joffre, S, Räsänen, J. and Talvitie, H., 2006. Mixing height

determination by ceilometer, Atmospheric Chemistry and Physics, 6, pp. 1485-1493, SRef-ID: 1680-7324/acp/2006-6-1485.

• Christoph Münkel, Noora Eresmaa, Janne Räsänen, Ari Karppinen, 2007. Retrieval of mixing height and dust concentration with lidar ceilometer. Boundary Layer Meteorology (in press). (doi: 10.1007/s10546-006-9103-3).

• N. Eresmaa, A. Karppinen, K. Bozier, M. Rantamäki, 2007. The mixing height determination in Testbed campaign in Helsinki , Finland, Accepted to 6th International Conference on Urban Air Quality, Limassol, Cyprus, 27-29 March, 2007 (4p abstract)

• Angevine : http://www.etl.noaa.gov/ams_measurement/2003SC_SMOI_8a.pdf• Heo et al,2003: http://ams.allenpress.com/perlserv/?request=get-abstract&doi=10.1175%2F1520-

0426(2003)020%3C0408%3AUOTDSW%3E2.0.CO%3B2• Pechinger, U.,Dittman, E., Erbes, G., Johansson, P.-E., Karppinen, A., Musson-Genon, L.,

Omstedt, G. and Tercier, P., 1997. The surface energy balance. COST action 710 “Harmonisation in the preprocessing of meteorological data for atmospheric dispersion models”, Report of Working Group 1, European Comission, Brussels, 64 p.

• Piringer, M., Kukkonen, J., Joffre, S., Baklanov, A., Vogt, R., Tombrou, M., Mestayer, P., Middleton, D., Karppinen, A., Burzynski, J., Deserti M., 2005. The mixing height and inversions in urban areas . In: Fisher, B., Joffre, S., Kukkonen, J., Piringer, M., Rotach, M., Schatzmann, M. (eds.): Meteorology applied to urban pollution problems, Final report COST Action 715, ISBN 954-9526-30-5, Demetra Ltd Publishers, Bulgaria , pp. 71-98.

• Piringer, M., Joffre., S. (eds.); Baklanov, A., Burzynski, J., Christen, A., Deserti, M., De Ridder, K., Emeis, S., Karppinen, A., Mestayer, P., Middleton, D., Tombrou, M. (lead authors), 2005.The urban surface energy budget and mixing height in European cities: data, models and challenges for urban meteorology and air quality. Final Report of Working Group 2 of COST-715 Action. ISBN 954-9526-29-1, Demetra Ltd Publishers, Bulgaria. 239 pp.

• Järvi, Leena, 2005. Alustan rosoisuus ja turbulenssin ominaisuudet kaupunkiympäristössa , ProGradu-turkielma, Helsingin yliopisto

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