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MODEL DISPERSI
PENCEMAR
UDARA
Abdu F. Assomadi
2
Main concepts in air quality modeling
Parameter-parameter dalam Model Sumber (Karakteristik emisi)
laju emisi (massa/waktu)lokasi sumber (koordinat)temperatur gas emisi (K)tinggi plume rise (m)
MeteorologyTemperatur AtmosferStabilitas Atmosfer (diperlukan untuk menentukan koefisien
dispersi) Kecepatan dan arah angin, turbulensi
Sifat Kimia AtmosferReaksi-reaksi kimia di atmosferDeposisi (basah / kering)
Parameter permukaangeometri permukaan, kekasaran/terrain, lautan, daerah kota atau
desa
4
Beberapa Model Kualitas Udara Model point source
Model at urban and large scale
Model Fotokimia
Model-model lain:
Model secara meteorologi
Model plume rise dan Model Dispersi
Model Statistik - Model Penerima/receptor di ambien
Model deposisi
Model bau/odor
Model partikulat
Model Point Source
Model pertama yang dikembangkan untuk
kualitas udara (contoh, Sutton, 1932,
Bosanquet, 1936) menjelaskan sifat dispersi
plume yang diemisikan dari cerobong industri.
Dalam sejarahnya dinilai sukses, dari sini
dikembangkan model dispersi sederhana –
Model Plume Gaussian.
Model ini telah diaplikasikan untuk menghitung
impact plume pada MGL (max ground level)
dan jarak maksimum dari sumber.
Plume Boundary
H
X
Y
Z
u
Q
7
The simplest dispersion modeling – Gaussian approximation for
the plume spread
Not applicable to regional scales – complex
terrain, convective conditions, and ground-level sources.
Gambaran Model Gaussian
Asumsi-asumsi pada Model
Dispersi Gauss
• Plume disebar mengikuti sebaran gauss normal baik dalam bidang horisontal maupun vertikal,dengan deviasi standar konsentrasi plume padaarah horisontal dan vertikal y, and z;
• Laju emisi polutan seragam, Q;
• Kondisi plume pada ground (z=0) dianggap secara total direfleksikan oleh permukaan; dan
Plume bergerak downstream (horisontal padaarah x) dengan rata-rata kecepatan angin, u,
10
Limitations of Gaussian-plume models Causality effects
Gaussian-plume models assume pollutant material is transported in a straight line instantly (like a beam of light) to receptors that may be several hours or more in transport time away from the source.
Low wind speeds
Gaussian-plume models 'break down' during low wind speed or calm conditions due to the inverse wind speed dependence of the steady-state plume equation, and this limits their application.
Straight-line trajectories
In moderate terrain areas, these models will typically overestimate terrain impingement effects during stable conditions because they do not account for turning or rising wind caused by the terrain itself. CTDM and SCREEN are designed to address this issue.
Spatially uniform meteorological conditions
Gaussian steady-state models have to assume that the atmosphere is uniform across the entire modelling domain, and that transport and dispersion conditions exist unchanged long enough for the material to reach the receptor.
Convective conditions are one example of a non-uniform meteorological state that Gaussian-plume models cannot emulate.
No memory of previous hour's emissions
In calculating each hour's ground-level concentration the plume model has no memory of the contaminants released during the previous hour(s).
Wark & Warner, “Air Pollution: Its Origin & Control”
Mixed layer
TRAPPED BY MIXED LAYER
Sistem Koordinat Model Dispersi
Gauss
Short term model, steady-state Gaussian plume equation untuk sumber kontinyu dan punya elevasi tertentu.
Koordinat asal (0,0) ditempatkan pada ground surface tepat di dasar stack.
Sumbu X positif pada arah angin (downwind direction), sumbu y tegak lurus arah angin (crosswind searah sumbu X) dan sumbu Z merupakan arah vertikal.
Lokasi penerima dikonversi dari sistem koordinat sumber, untuk perhitungan konsentrasi jangka waktu tertentu (sesuai arah angin dominan)
Sistem Koordinat Distribusi Gauss Arah
Horizontal dan Vertikal
Persamaan Model Dispersi Gauss
Model Gauss distribusi konsentrasi
Rumus menghitung C gas atau aerosol (<20 u) padapermukaan tanah arah downwind (x):
Di mana: C = konsentrasi polutan, g/m3
m = laju emisi polutan, g/s
= kecepatan angin rata-rata, m/s
z = standar deviasi konsentrasi flume arah orizontal
y = standar deviasi konsentrasi flume arah vertikal
He = tinggi efektif cerobonhg, m
X = jarak downwind sepanjang centerline flume darititik sumber, m
Y = jarak crosswind dari centerline flume, m
Model Gaussian
Diformulasikan dengan penentuan sebaran plume scr horisontal / vertikal dan distribusi konsentrasiplume dengan deviasi standar plume mengikutisebaran normal
Distribusi/sebaran polutan dihitung sebagai fungsistabilitas atmosfer dan jarak dari sumber searahangin
Stabilitas Atmosfer parameter karakteristikturbulensi atmosfer (Range F A; menyatakansanga stabil sangat tidak stabil; D netral)
Pengaruh Stabilitas Atmosfer pada
Plume
Typical Velocity, and Plume Shapes
The lateral dispersion coefficient function and, the vertical dispersioncoefficient functions depend on the downwind distance and the atmosphericstability class. These coefficients in meters can be obtained using Pasquill-Gifford-Turner estimates shown in the equations below
Gaussian Parameters
where ,
s = an integer [1-6] representing the atmospheric stability shown in Table 1
kx,x = empirical constants, values for each of the stability class can be obtained from Green et al. (1960)
Surface wind
speed at 10 m
(m/s)
Day Night
Incoming Solar radiation Cloud Cover
Strong Moderate Slight Thinly Overcast Mostly Cloudy
< 2 A (s = 1) A-B B (s = 2)
2-3 A-B B C (s = 3) E (s = 5) F (s = 6)
3-5 B B-C C D E
5-6 C C-D D (s = 4) D D
>6 C D D D D
Table 1. Constants a,b,c,d depend on Pasquill Stability categories defined by Turner (1995)
Horizontal Dispersion Coefficient as a Function of Downwind Distance from Source
Vertical Dispersion Coefficient as a Function of Downwind Distance from Source
11/20/2014 22
Gaussian Dispersion Equation
If the emission source is at ground level with no
effective plume rise then
2
2
2
2
2
1exp,,
zyzy
zy
u
QzyxC
• H is the sum of the physical stack height and
plume rise.
Plume Rise
stackactualriseplume hhH
11/20/2014 23
Plume Rise
For neutral and unstable atmospheric
conditions, buoyant rise can be calculated by
)/ 55F( 425.21 34
75.0
smu
Fh riseplume
)/ 55F( 71.38 34
6.0
smu
Fhplume rise
Sass TTTdgVF 4/)(2
where buoyancy flux isVs: Stack exit velocity, m/s
d: top inside stack diameter, m
Ts: stack gas temperature, K
Ta: ambient temperature, K
g: gravity, 9.8 m/s2
Buoyant plume: Initial buoyancy >> initial momentum
Forced plume: Initial buoyancy ~ initial momentum
Jet: Initial buoyancy << initial momentum
11/20/2014 24
Carson and Moses: vertical momentum & thermal
buoyancy, based on 615 observations involving 26 stacks.
(stable) 24.204.1
(neutral) 64.235.0
(unstable) 15.547.3
u
Q
u
dVh
u
Q
u
dVh
u
Q
u
dVh
hsriseplume
hsriseplume
hsriseplume
asph TTCmQ
MWRT
PV
dm
s
s4
2
(heat emission rate, kJ/s)
(stack gas mass flow rate. kg/s)
When pollutants are dispersed to the ground level,
how should we handle the situation?
11/20/2014 25
Wark & Warner, “Air Pollution: Its Origin & Control”
2
2
2
2
2
2
2exp
2exp
2exp
2,,
zzyzy
HzHzy
u
QzyxC
What if the surface is absorbing?
How should the concentration profile look like w/ reflection?
11/20/2014 26
Ground level concentration
2
2
2
2
2exp
2exp
zyzy
Hy
u
QC
11/20/2014 27
Maximum Ground Level Concentration
Under moderately stable to near neutral conditions,
zy k1
The ground level concentration at the center line is
2
2
2
1 2exp0,0,
zz
H
uk
QxC
The maximum occurs at
2 0/
HddC zz
Once z is determined, x can be known and subsequently C.
u
Q
u
QxC
zyzy
1171.01exp0,0,
11/20/2014 28
Example
An industrial boiler is burning at 12 tons (10.9
mton) of 2.5% sulfur coal/hr with an emission
rate of 151 g/s. The following exist : H = 120 m,
u = 2 m/s, y = 0. It is one hour before sunrise,
and the sky is clear. Determine downwind
ground level concentration at 10 km.
Stability class =
y =
z =
C(10 km, 0, 0) =
11/20/2014 29
If emissions are from a ground level source with H = 0, u = 4 m/s, Q = 100 g/s, and the stability class = B, what is downwind concentration at 200 m?
At 200 m:
y =
z =
C(200 m, 0, 0) =
Exercise
11/20/2014 30
Calculate H using plume rise equations for an 80 m high
source (h) with a stack diameter = 4 m, stack velocity =
14 m/s, stack gas temperature = 90o C (363 K), ambient
temperature = 25 oC (298 K), u at 10 m = 4m/s, and
stability class = B. Then determine MGLC at its location.
F =
h plume rise =
H =
z =
y =
Cmax =
Example
Residents around Florida Rock Cement Plant are complaining its emission
being violating its allowed level. The plant has its facility within 0.5 km
diameter. Its effective stack height is 60 m. You are a FLDEP environmental
specialist. Where are you going to locate your air quality monitors? Why?
Pengaruh Stabilitas Atmosfer pada
Konsentrasi Plume (A)parameter unit case 1
wind speed (from or to south west) m/s 2
stack height m 45
Δh m 90,602efective stack height (He) m 135,602
parameter polutan (gas) n
Nitrogen Oxides
beban (loading) g/s 19,834
stabilitas atmosfer a
Pengaruh Stabilitas Atmosfer pada
Konsentrasi Plume (B)parameter unit case 1
wind speed (from or to south west) m/s 3
stack height m 45
Δh m 60,401efective stack height (He) m 105,401
parameter polutan (gas) n
Nitrogen Oxides
beban (loading) g/s 19,834
stabilitas atmosfer b
Pengaruh Stabilitas Atmosfer pada
Konsentrasi Plume (C)parameter unit case 1
wind speed (from or to south west) m/s 5
stack height m 45
Δh m 36,241
efective stack height (He) m 81,241parameter polutan (gas) n
Nitrogen Oxides
beban (loading) g/s 19,834
stabilitas atmosfer c
Pengaruh Stabilitas Atmosfer pada
Konsentrasi Plume (D)parameter unit case 1
wind speed (from or to south west) m/s 7
stack height m 45
Δh m 25,886
efective stack height (He) m 70,886
parameter polutan (gas) n
Nitrogen Oxides
beban (loading) g/s 19,834
stabilitas atmosfer d
Pengaruh Stabilitas Atmosfer pada
Konsentrasi Plume (E)parameter unit case 1
wind speed (from or to south west) m/s 5
stack height m 45
Δh m 36,241
efective stack height (He) m 81,241
parameter polutan (gas) n
Nitrogen Oxides
beban (loading) g/s 19,834
stabilitas atmosfer e
Pengaruh Stabilitas Atmosfer pada
Konsentrasi Plume (F)parameter unit case 1
wind speed (from or to south west) m/s 3
stack height m 45
Δh m 60,401
efective stack height (He) m 105,401parameter polutan (gas) n
Nitrogen Oxides
beban (loading) g/s 19,834
stabilitas atmosfer f
Beberapa pengembang model
ini Högstrom (1964), Turner (1964), Briggs (1965) Moore
(1967), Klug (1968) Penggunaan dan aplikasi meluas danmenjadi teknik standar di berbagai negara untuk menghitungtinggi stack yang dibutuhkan untuk perijinan
Beryland (1975) telah mem-publis standar kerja di Rusia
Holzworth, (1967), Deardorff, (1975) pengaruh mixing height dalam memeperhitungkan konsentrasi MGL
Yamartino, (1977) teri refleksi distribusi ditambahkan padaModel Plume Gaussian
MODEL-MODEL LAIN
DALAM DISPERSI
PENCEMAR UDARA
Abdu F. Assomadi
Model pada skala urban dan luas
Sekitar 1970 diketahui bahwa polusi udara bukan hanyafenomena lokal (tidak cocok didekati dengan model gaussian) SOx dan Nox di eropa hujan asam di wilayah luas (antar
negara)
Ozon urban dan industri impact
Didekati dengan model Lagrangian dan Model Eulerian Lagrangian modeling parcel udara (atau ―puff‖) megikuti
lintasannya dan diasumsikan tetap identitasnya selama dalamperjalanan
Eulerian modeling area studi dibagi menjadi grid cell, dalamarah vertikal maupun horisontal
Lagrangian modeling
Diarahkan pada deskripsi transport sulfur jarak jauh (long-range), dimulai dengan penelitian Rohde (1972, 1974), Eliassen (1975) dan Fisher (1975).
Eliassen (1975) mulai dengan model well-known EMEP-trajectory digunakan beberapa tahun untuk menghitungpolusi udara trans-boundary spesies penyebab keasaman , dan kemudian foto-oksidan
Lagrangian modeling digunakan mencakup periode waktuyang lebih panjang bahkan sampai skala tahun
Secara umum dipakai di Eropa, fokus utama pada SO2 yang terdistribusi jauh dan waktu yang lama
Prinsip Perubahan Konsentrasi dideskripsikan relatifterhadap pergerakan fluida
Eulerian modeling
Dimulai dengan studi Reynolds (1973) untuk ozondi area urban; Shir and Shieh (1974) untuk SO2 diarea urban, Egan (1976) dan Carmichael (1979) untuk sulfur skala regional.
Reynolds (1973) Los Angeles, simulasifotokimia ―well-known Urban Airshed Model-UAM‖.
Pemodelan Eulerian grid secara luas diaplikasikandi US, meliputi area urban dengan fokus utamapada O3.
Prinsip Eulerian Model
Sifat/perubahan spesies dideskripsikan relatifterhadap sistem koordinat yang tetap (fixed)
Ada dua model yang dikembangkan:Single Box Model
Focus: Kimia Atmosfer Lack physical realism - horizontal and vertical transport,
etc
Multi-dimensional grid-based air quality model Potentially the most powerful Involving the least-restrictive assumption
Beberapa Pengembang Model
Lagrangian dan Eulerian Sklarew et al., (1971) pendekatan hybrid, seperti metode
particle-in-cell.
Paper mengenai pemodelan Eulerian and Lagrangianmodeling Friedlander and Seinfeld (1969), Eschenroeder -Martinez (1970) dan Liu and Seinfeld (1974).
A comprehensive overview of long-range transport modeling in the seventies Johnson (1980).
Selanjutnya, global modeling of earth’s troposphere. Model Global 2-D troposfer global dimodelkan dalam rata-rata
arah longitudinal (Isaksen, 1978).
model global 3-D dikembangkan Peters (1979) (dan jugaZimmermann, 1988).
Sekitar tahun 1980, konsep dasar modeling danperangkatnya sudah avalaible.
Pengembangan setelah 1980 difokuskan pada fine-tuningdari konsep dasar tersebut
Model Fotokimia
AQM dengan pendekatan Fotokimia dibuatsecara luas dan rutin digunakan sebagai alatanalisis regulasi dan menguji efektifitas strategipengendalian
Model fotokimiamodel kualitas udara skalabesar yang mensimulasikan perubahankonsentrasi polutan di atmosfer menggunakansederet persamaan matematik, karakteristik kimiadan proses fisika di atmosfer.
Model ini diaplikasikan pada skala multiple spatial mulai lokal, regional, nasional, dan global
Beberapa Model Foto kimia CMAQ Tujuan utama Models-3/Community Multiscale Air Quality
(CMAQ) untuk mengimprove 1) kemampuan environmental
management community untuk evaluasi impact pengelolaan kualitas
udara multi polutan pada multi skala, dan 2) kemempuan peneliti
untuk memahami dan mensimulasi lebih baik interaksi polutan
secara kimia-fisika di atmosfer
CAMX model kualitas udara komperehensif a publicly
available open-source computer modeling system untuk assesment
terintegrasi (pencemar udara gas-gas dan partikel)
Simulate air quality over many geographic scales
Treat a wide variety of inert and chemically active pollutants:
Ozone
Inorganic and organic PM2.5/PM10
Mercury and toxics
Provide source-receptor, sensitivity, and process analyses
Be computationally efficient and easy to use
Beberapa Model Foto kimia
UAM The Urban Airshed Model® (UAM®) mulai dikembangkan oleh ystems Applications International (SAI) sejak sekitar tahun 1970paling luas digunakan dalam photochemical air quality model saat ini
Model photochemical lain telah dikembangkannamun tidak ada model sampai saat ini yang lebihreliable dan superior secara teknik
CALGRID
Model-model Lain
Model Meteorologi CALMET
MM5
RAMS
Model Plume Rise dan Dispersi AERMOD termasuk PRIME sistem algoritma untuk
mensimulasi efek plume rise, termasuk downwash ketikaplume melintas diatas/melewati gedung-gedung
Model Statistik – Model Receptor Air Quality Forecast and Alarm Systems
Model Deposisi
Model Bau
Model Partikulat Kinematic Simulation Particle (KSP) Model in CALPUFF
MONTECARLO (Zannetti and Sire, 1999)
Model-model yang populer dalam
AQM Industrial Source Complex Short-Term Model (ISCST3)
American Meteorological Society- Environmental Protection Agency Regulatory Model (AERMOD)
Guideline on Air Quality Models (GAQM)
Office of Air Quality Planning and Support (OAQPS)
Support Center for Regulatory Air Models (SCRAM)
ISC-COMPDEP model (a merger of the ISCST2 and COMPLEX I model)
COMPLEX I, from which a new model—COMPDEP
Rough Terrain Diffusion Model (RTDM) RTDMDEP
California Puff Model (CALPUFF)
ISCST with the new downwash algorithm, ISC-PRIME
AERMOD dan CALPUFFRekomendasi US-EPA saat ini dua model komputasi untuk simulasi polutan
non reaktif (misal, SO2):
AERMOD: http://www.epa.gov/scram001/dispersion_prefrec.htm#aermod steady-state Gaussian plume model, menggunakan angin tunggal yang diturunkan dari permukaan lapisan atas, dan pengamatan meteorological onsite. AERMOD juga menggabungkan data geofisika (terrain, elevasi) untuk mendapatkan parameter boundary layer ( panjang monin-obukhov, mixing height, stabilitas, turbulrnsi , dsb) AERMOD saat ini menggantikan ISC models untuk sebagian besar regulasi di US
CALPUFF: http://www.epa.gov/scram001/dispersion_prefrec.htm#calpuff model dispersi puff non-steady state Lagrangian Dibanding dengan Gaussian-based model CALPUFF lebih realistik mensimulasi
transport polutan pada kondisi calm, stagnant, complex terrain, dan coastal regions with sea/land breezes.
CALPUFF direkomendasikan untuk long-range simulations (lebih dari 50 miles) danassesment visual impact plume.
Dengan VISTAS Version 6 model2, CALPUFF digunakan dengan data meteorological sub-hourly dan dijalankan dengan tahap waktu sub-hourly. CALPUFF versi ini juga didekati untuk kedua simulasi long-range and short-range.
ISCST3 modelSecara teknik mampu untuk menghitung dan evaluasi
Laju dispersi gaussian vertical dan horizontal plume cross-section;
Koefisien dispersi Urban dan rural;
Efek Terrain;
Karakteristik sumber point diskrit, area dua dimensi, volume 3-D;
Rerata Short-term dan long-term (1jam - tahunan);
Data meteorologi permukaan termasuk data pengamatan kecepatanangin tiap jam , arah angin, stabilitas (6 kelas), dan temperatur;
Interpolasi Data Mixing height dihubungkan dengan data kondisipermukaan;
Proses deposisi massa konservatif , wet /dry deposisi partikel danremoval
Laju peluruhan ekponensial order satu tunggal
Sumber dan referensi
Human Health Risk Assessment Protocol Chapter 3: Air Dispersion and Deposition Modeling, U.S. EPA Region 6 Multimedia Planning and Permitting Division Center for Combustion Science and Engineering, september 2005
Daly, A. and P. Zannetti. 2007. Air Pollution Modeling – An Overview. Chapter 2 of AMBIENT AIR POLLUTION (P. Zannetti, D. Al-Ajmi, and S. Al-Rashied, Editors). Published by The Arab School for Science and Technology (ASST) (http://www.arabschool.org.sy) and The EnviroCompInstitute (http://www.envirocomp.org/).