modeling of wet deposition in chemical transport...
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MODELING OF WET DEPOSITION IN CHEMICAL TRANSPORT
SIMULATION
Toshihiro KITADA
National Institute of Technology,
Gifu College
Kamimakuwa, Motosu 441-8580, Japan
Transport/chemistry/deposition model for atmospheric trace chemical species
• An important tool:
(1) for understanding of the effects of various human activities, such as fuel combustion and deforestation, on human health, eco-system, and climate, and
(2) for planning of appropriate control of emission sources.
“Comprehensive” models such as RADM (Chang, et al., 1987); STEM-II (Carmichael, et al.,
1986); and CMAQ, WRF-Chem etc. for public
use
• “Comprehensive” models include not only gas/aerosol phase chemistry but also aqueous phase chemistry in cloud/rain water in addition to the processes of advection, diffusion, wet deposition (mass transfer between aqueous and gas/aerosol phases), and dry deposition.
Types of Modeling of Wet Deposition
1. Simple Modeling using Scavenging Coefficient.
2. Dynamic Modeling using One Dimensional Cloud Microphysics Model (Ex. RSM – RADOM scavenging module, Berkowitz et al. 1989; PLUVIUS, Hales 1981, CMAQ, WRF-Chem, others) → Hydrometeors themselves are not transported over horizontal grid cells.
3. Dynamic Modeling using Three/Two Dimensional Cloud Microphysics Model (Ex. Hegg et al. 1986, Rutledge et al. 1986, Kitada et al. 1993, others) → Allow transport of hydrometeors over horizontal grid cells.
One of the Important Factors: Wet Deposition Modeling:
Target for the “Comprehensive” Model Development
• the model which can correctly reproduce mass balance of various chemical species in the atmosphere with keeping adequate accuracy for calculated concentration distributions of chemical species.
• In the Fukushima case, radioactive species are the target.
Examples
• Cloud-Resolving Modeling
• Non Cloud-Resolving Modeling: Simple Modeling of Wet Deposition
MM5(NCAR Mesoscale
Model)
Out puts: Flow,
Temperature, Water
vapor,
Hydrometeors, Eddy
diffusivity.
Cloud Micro
Physics
Out put:
Cloud water/ice,
Rain, Snow,
Graupel
Turb. Model
k-εModel
Out put: k, ε,
Eddy
diffusivity
Boundary & Initial
GCM out puts 、 GPV 、 Obs.
Meteorol.
Surface Boundary
(Geography, Topo. )
Elevation, Land Use, etc.
Gas Phase Species
Process: Advec., Diffusion,
Chem. Rxns., Mass Transfer
between Gas and Hydro.
Phases, Dry Deposition
Chem. Species:NOx, HNO3,
NH3, Hydrocarbons, O3,
H2O2, DMS, SO2, H2SO4,
etc.
Aerosol : NH4NO3,
(NH4)2SO4, NaCl, BC, OC,
etc.
Species in Hydrometeors
( Hydrometeors : Cloud
Water, Cloud Ice, Rain Water,
Snow, Graupel) Process:Adv., Diff., Aqueous Phase
Chem. Rex, Mass Transfer between
gas and hydrometeor phases, Wet
Deposition
Chem. Species:S(IV), SO4=, NO3
-,
H2O2, O3, OH, HO2, Ca2+, K+, Na+,
Cl- , etc.
TRANPORT/CHEMISTRY/DEPOSITION MODEL
METEOROLOGICAL MODEL
Role of Cloud in Transport/Transformation of Trace Chemical
Species
Mass Conservation Eqs. of Chemical Species in hydrometeor Phases (Kitada et al., 1993)
𝑞𝑗 : water content of j th hydrometeor such as cloud
water, cloud ice, rain water, snow, and graupel. : concentration of i-th species in j-th hydrometeor. : chemical reaction rate of i-th species in j-th hydrometeor. : mass transfer rate of i-th species between j-th and k-th hydrometeors. : mass transfer rate of i-th species between gas/aerosol phase and j-th hydrometeor.
𝐸𝑥𝑎𝑚𝑝𝑙𝑒: 𝐺𝑗i for Gas Absorption/
Desorption of i-th species between Gas Phase and Cloud Water and Rain Water Phases
𝐺𝑗i =
Mass Conservation Eqs. for Chemical Species in Gas/Aerosol Phase
SO2-Sulfate
(used in Kitada et al.,1993)
Aqueous Phase Chemical Reactions
Examples
• Cloud-Resolving Modeling
• Non Cloud-Resolving Modeling: Simple Modeling of Wet Deposition
CTM Equations System for Large Scale
Below top of cloud layer: scavenging of gas/aerosol phase species by hydrometeors,
Simple Modeling of Wet Deposition: Ex. For Particulate Sulfate (derived and summarized in Kitada, 1994) Formulation by Scavenging Rate Coefficient Λ:
Λ: Capture rate of sulfate by rain with collection efficiency “η” of sulfate particle (radius R) by rain drop (radius, a)
Mass conc. of “sulfate in rain phase”.
Mass conc. of “sulfate in gas/aerosol phase”.
Simple Modeling of Wet Deposition: Ex. For Particulate Sulfate (derived and summarized in Kitada, 1994) (continued)
Simplified Expression of Λ using volume averaged radius of rain drop "𝑎𝑚" (Slinn, 1977) :
Precipitation intensity P:
Simplified form of Λ (C=3/4, constant):
If we choose, for example, η = 0.05,
Empirical relation of 𝑎𝑚 and P (Mason, 1971):
=6x10−4η𝑃0.75 (𝑠−1)
(C≡3
4, 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡)
(continued)
From semi-empirical expression by Slinn (1977), sample value of η for particle with its radius 0.1 ~ 3μm →
V(am)
Cloud
H
By a variable transformation of , Eq. 2.11 can be written as follows:
Integrating from z=0 ~H :
(continued)
dz
Wet Deposition at Ground Level, Fw, can be obtained by evaluating the right hand side of Eq. (2.20):
+
: Sulfate in rain at height of cloud base H; may not be zero at z= H.
: Sulfate mass in rain water phase at ground level.
H ≡
In gas absorption/desorption case, conc. in rain water must be considered in wet dep.:
(continued)
Calculated S and N Deposition for March 1 to 15, 1994
S-total Deposition N-total Deposition
25 Acid Rain Monitoring Sites, Environ. Agency, Japan in 1994:
S-total Dep.: Ob vs Cal at 25 Acid Rain Sites
N-total Dep.: Ob vs Cal at 25 Acid Rain Sites
S-Wet Dep.: Ob vs Cal at 25 Acid Rain Sites
N-Wet Dep.: Ob vs Cal at 25 Acid Rain Sites
S-total Dep.: Ob vs Cal
N-total Dep.: Ob. Vs Cal.
Observation Point in China
PM Simulation for March 1 to 31, 2001
Beijing & South or East of Beijing: 北京、斉南、青島、大連
20 済南のPM濃度変化 (rwdp621_rr-emrad)
0
200
400
600
800
1000
1200
3/1
3/2
3/3
3/4
3/5
3/6
3/7
3/8
3/9
3/10
3/11
3/12
3/13
3/14
3/15
3/16
3/17
3/18
3/19
3/20
3/21
3/22
3/23
3/24
3/25
3/26
3/27
3/28
3/29
3/30
3/31
Mas
s C
onc. (μ
g/m
3)
SOIL_Coarse
SOIL_Fine
OCV
BCB
OCB
BCF
OCF
NO3
SO4
TSP(OBS)
21青島のPM濃度変化 (rwdp621_rr-emrad)
0
200
400
600
800
1000
1200
3/1
3/2
3/3
3/4
3/5
3/6
3/7
3/8
3/9
3/10
3/11
3/12
3/13
3/14
3/15
3/16
3/17
3/18
3/19
3/20
3/21
3/22
3/23
3/24
3/25
3/26
3/27
3/28
3/29
3/30
3/31
Mas
s C
onc. (μ
g/m
3)
SOIL_Coarse
SOIL_Fine
OCV
BCB
OCB
BCF
OCF
NO3
SO4
TSP(OBS)
7 大連を含むグリッドののPM濃度変化 (rwdp821_rr-emrad)
0
100
200
300
400
500
600
700
3/1
3/2
3/3
3/4
3/5
3/6
3/7
3/8
3/9
3/10
3/11
3/12
3/13
3/14
3/15
3/16
3/17
3/18
3/19
3/20
3/21
3/22
3/23
3/24
3/25
3/26
3/27
3/28
3/29
3/30
3/31
Mas
s C
onc. (μ
g/m
3)
SOIL_Coarse
SOIL_Fine
OCV
BCB
OCB
BCF
OCF
NO3
SO4
TSP(Dalian OBS)
TSP(OBS Ave.)
(b) Jinang
(c) Qingdao (d) Dailian
0
200
400
600
800
1000
1200
1400M
ass
Conc. (
OB
S
μg/
m3)
北京を含むグリッドの濃度比較 (rwdp721_rr-emrad)
SOIL_Coarse
SOIL_Fine
OCV
BCB
OCB
BCF
OCF
HNO3
SO4
TSP (Ave. OBS)
TSP (Beijing OBS)
(a) Beijing
PM: Cal. Vs Obs. for March 1 to 31, 2001
Southeastern Mountainous Area: Kunming(昆明)
0
50
100
150
200
250
Mas
s C
onc. (
μg/
m3)
36 昆明のPM濃度変化 (rwdp821_rr-emrad)
SOIL_Co
arseSOIL_Fin
eOCV
BCB
OCB
BCF
OCF
HNO3
SO4
TSP(OB
S)
(a) KUNMING
0
50
100
150
200
250
300
350
400
450
Mas
s C
onc. (μ
g/m
3)
37 ラサのPM濃度変化 (rwdp721_rr-emrad) SOIL_Co
arseSOIL_Fin
eOCV
BCB
OCB*1.5
BCF
OCF
HNO3
SO4
TSP(OB
S)
(b) LHASA
Southern Highland Area (Tibet): Lhasa(ラサ)
PM: Cal. Vs Obs. for March 1 to 31, 2001
Japan: 東京、大阪
0
50
100
150
200
250
Mas
s C
onc. (μ
g/m
3)
大阪のPM濃度変化 (rwdp721_rr-emrad)
SOIL_Coarse
SOIL_Fine
OCV
BCB
OCB
BCF
OCF
HNO3
SO4
SPM10(OBS)
0
20
40
60
80
100
120
140
Mas
s C
onc
. (μ
g/m
3)
東京のPM濃度変化 (rwdp721_rr-emrad)
SOIL_Coars
eSOIL_Fine
OCV
BCB
OCB
BCF
OCF
HNO3
SO4
SPM10(OB
S)
(a) TOKYO
(b) OSAKA, Japan
SPM: Cal. Vs Obs. for March 1 to 31, 2001
Summary and concluding remarks • Introduced two examples of wet deposition modeling;
• (1) Cloud-resolving
• (2) Non Cloud-resolving simplified approach
• (3) Further investigation of the cloud-resolving study may be necessary for improvement of wet deposition prediction; the research will also improve parameterization in the non cloud-resolving approach.
• (4) Difficulty for mass balance study in the Fukushima case: Almost no information on atmospheric concentration fields of the discharged radioactive materials(?). Only deposition distribution is available. → Reduce other uncertainties such as met fields as much as possible.
One of the important factors: reliable Wet Deposition calculation. • Three types of modeling; (1) Dynamic Modeling using Three/Two
Dimensional Cloud Transport Model: Cloud-Resolving Method → Allow trans-horizontal-grids mass transport of hydrometeors and chemical species with PDEs (Ex. Hegg et al. 1986, Rutledge et al. 1986, Kitada et al. 1993, others)
(2) Dynamic Modeling using One Dimensional Cloud Transport Model: Semi-Cloud-Resolving Method → Hydrometeors themselves are not transported over horizontal grid cells. (Ex. RSM – RADOM scavenging module, Berkowitz et al. 1989; PLUVIUS, Hales 1981, others); completes cloud processes within each vertical column.
One of the important factors: reliable Wet Deposition calculation. (continued)
(3) Simple Modeling using Scavenging Coefficient.