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The The Australian Air Quality Australian Air Quality Forecasting System (AAQFS)Forecasting System (AAQFS)
P.C. ManinsP.C. Manins11,, M.E.CopeM.E.Cope1,21,2, , G.D HessG.D Hess33, K.J. Tory, K.J. Tory33, ,
Sunhee LeeSunhee Lee11, K.Puri, K.Puri33, M.Young, M.Young44
11CSIRO Atmospheric Research, CSIRO Atmospheric Research, 22CSIRO Energy Technology, CSIRO Energy Technology, 33Bureau of Meteorology Bureau of Meteorology Research Centre Research Centre 44Environment Protection Authority of NSWEnvironment Protection Authority of NSW
GENERAL PROJECT OBJECTIVES
A project supported by A project supported by Environment Australia Environment Australia through the Natural through the Natural Heritage Trust.Heritage Trust.
SYDNEYSYDNEYMELBOURNEMELBOURNE
AUSTRALIAAUSTRALIA
Develop and implement a numerical air Develop and implement a numerical air quality forecasting system in Melbourne quality forecasting system in Melbourne and Sydney and Sydney –– AustraliaAustraliaDemonstrate the System in Sydney during Demonstrate the System in Sydney during the Olympics and Parathe Olympics and Para--Olympics (2000)Olympics (2000)
PORT PHILLIP BAY
260 280 300 320 340 360EASTING (km)
DND
BRI
FTSPSY
PTC
MTC ALP
PTHGLS
GVD
PLP BXH
5740
5760
5780
5800
5820
5840
NO
RTH
I NG
(km
)
LIGHT
MODERATE
HEAVY
AIR QUALITY FORECAST-MELBOURNE
AIR QUALITY FORECASTAIR QUALITY FORECAST--MELBOURNEMELBOURNE
NORTH EAST
HOUR
IND
EX
NORTH EAST
HOUR
IND
EX
Tomorrow will be fine and sunnyTomorrow will be fine and sunny--with moderate to heavy air pollutionwith moderate to heavy air pollution
Are spatial and temporal information Are spatial and temporal information needed from the forecast? needed from the forecast? (e.g. hour(e.g. hour--byby--hour, suburbhour, suburb--byby--suburb)suburb)
Support air quality management & policy Support air quality management & policy development? development? (e.g. VOC controls)(e.g. VOC controls)
Are monitoring data limited?Are monitoring data limited?(no extensive network)(no extensive network)??
Is a prognostic air pollution forecasting system worth the considerable effort?
Why not a use a statistical forecasting system? More…
Levels of Complexity More…
1.1. Embedded in a operational National Weather Embedded in a operational National Weather Forecasting System Forecasting System –– AAQFSAAQFS
2.2. Extension of Numerical Weather Forecasting Extension of Numerical Weather Forecasting Capability Capability –– e.g.e.g., Beijing, China, Beijing, China
3.3. NMHS seeking to develop both a national NMHS seeking to develop both a national numerical weather and pollution forecast numerical weather and pollution forecast –– Malaysia?Malaysia?
4.4. NMHS focussed on forecasting air pollution for NMHS focussed on forecasting air pollution for a limited region a limited region –– others?others?
AAQFS DESIGN FEATURES
Generate air quality forecasts twice per day for a Generate air quality forecasts twice per day for a period of 24period of 24––36 hours: 36 hours: (3 pm and 9 am).(3 pm and 9 am).Consider a range of air pollutants: Consider a range of air pollutants: NOxNOx, ROC, SO, ROC, SO22, O, O33, aerosol, air toxics., aerosol, air toxics.Resolve air quality at regional and suburb level Resolve air quality at regional and suburb level (5 km, 1 km).(5 km, 1 km).Generate a ‘business as usual’ forecast and a Generate a ‘business as usual’ forecast and a ‘greener emissions’ forecast.‘greener emissions’ forecast.
The Need for High Resolution More…
Leads to improved weather forecastsLeads to improved weather forecastsChanges in space and time importantChanges in space and time important
Necessary to resolve regional flowsNecessary to resolve regional flowsFor air pollution, wind For air pollution, wind trajectorytrajectory vitalvital
Boundary layer must be resolvedBoundary layer must be resolvedFor air pollution levels, For air pollution levels, mixing heightmixing height vitalvital
SYSTEM- FEATURES
MET ANALYSIS
EMISSIONSDATABASE
AQ + METOBS.
NWPGASP/LAPS
INVENTORY
CTM
AIR QUALITYFORECAST
EVALUATIONDATA
PACKAGE
Australian operationalAustralian operationalweather weather forecast modelsforecast models
EMSEMS--95 derivative95 derivative
CustomCustom--integrateintegrateinto NWPinto NWP
STUDY REGIONSVictoria-Melbourne
141.0 142.0 143.0 144.0 145.0 146.0 147.0
Longitude (deg. E)
-41.0
-40.0
-39.0
-38.0
-37.0
-36.0
-35.0
Latit
ude
(deg
. N)
MELBOURNE
WANGARATTA
BENDIGO
WARRAGULGEELONG
WODONGA
CASTLEMAINE
SWANHILL
HORSHAM
WARRNAMBOOL
KING IS
TASMANIA
BASS STRAIT
130 130 ×× 130; 130; ∆∆xx ~5 km ~5 km VICTORIAVICTORIA
SYDNEYSYDNEYMELBOURNEMELBOURNE
AUSTRALIAAUSTRALIA
144.2 144.4 144.6 144.8 145.0 145.2 145.4LONGITUDE (deg. E)
-38.4
-38.2
-38.0
-37.8
-37.6
LATI
TUD
E (d
eg. N
)
ALPH
BXHL MTCL
PTCK
PAIS
BRTN
RMIT
GSTH GRVD
PORT PHILLIPBAY
BASS STRAIT
MELBOURNE
GEELONG
130 130 ×× 96; 96; ∆∆xx ~1 km ~1 km
149.0 150.0 151.0 152.0 153.0
Longitude (deg. E)
-36.0
-35.0
-34.0
-33.0
-32.0
Latit
ude
(deg
. N)
NEWCASTLE
WOLLONGONG
MUSWELLBROOK
LITHGOW
SYDNEY
CANBERRA
ORANGE
PACIFIC OCEAN
STUDY REGIONSNew South Wales-Sydney
98 98 ×× 98; 98; ∆∆xx ~5 km ~5 km NSWNSW
SYDNEYSYDNEYMELBOURNEMELBOURNE
AUSTRALIAAUSTRALIA
150.5 150.6 150.7 150.8 150.9 151.0 151.1 151.2 151.3 151.4LONGITUDE (deg. E)
-34.1
-34.0
-33.9
-33.8
-33.7
-33.6
LATI
TUD
E (d
eg. N
)
BLAC
BRIN
CAMD CAMP
EARL LIDC
LIND
LIVE RAND
RICH
ROZE
ST.M
VYNE
WSTM
WOOL TASMAN
SEA
SYDNEY
MASCOT
PENRITH
SYDNEYSYDNEY 98 98 ×× 56; 56; ∆∆xx ~1 km ~1 km
Data Flows for AAQFS
GASP
CTMNSW
LAPS05VIC
CTMVIC
LAPS375
LAPS125
LAPS05NSW
SUPERCOMPUTERS
POST-PROCESSING,ARCHIVING,GRAPHICS,VERIFICATION
EPAVIC
EPANSW
ARCHIVE
WEBSITE
FTPSITE
EPANSW
EPAEPA--Victoria AAQFS Web PageVictoria AAQFS Web Page
http://www.epa.vic.gov.au/air/AAQFS
Daily Validation
15 March 200115 March 2001
OO33
NONOyy NONO22
VOCVOC
PERFORMANCE REVIEWPERFORMANCE REVIEW
Consider forecasts for some of 2000/2001 and all of 2001/2002 photochemical smog seasons
5 km forecasting domains
Assess the limit of predictability for forecasts of peak daily 1-hour ozone concentration
Verification- Air Quality modelling
Example: Sydney 7Example: Sydney 7--day ozone episode 21day ozone episode 21--27 January 200127 January 2001
149.0 150.0 151.0 152.0 153.0
EASTING
-36.0
-35.0
-34.0
-33.0
-32.0
NO
RTH
ING
NEWCASTLE
WOLLONGONG
MUSWELLBROOK
LITHGOW
SYDNEY
CANBERRA
ORANGE
PACIFIC OCEAN
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
OZONE- HOUR 16, 21/1/2001
149.0 150.0 151.0 152.0 153.0
EASTING
-36.0
-35.0
-34.0
-33.0
-32.0
NO
RTH
ING
NEWCASTLE
WOLLONGONG
MUSWELLBROOK
LITHGOW
SYDNEY
CANBERRA
ORANGE
PACIFIC OCEAN
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
OZONE- HOUR 16, 23/1/2001
149.0 150.0 151.0 152.0 153.0
EASTING
-36.0
-35.0
-34.0
-33.0
-32.0
NO
RTH
ING
NEWCASTLE
WOLLONGONG
MUSWELLBROOK
LITHGOW
SYDNEY
CANBERRA
ORANGE
PACIFIC OCEAN
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
OZONE- HOUR 16, 25/1/2001
149.0 150.0 151.0 152.0 153.0
EASTING
-36.0
-35.0
-34.0
-33.0
-32.0
NO
RTH
ING
NEWCASTLE
WOLLONGONG
MUSWELLBROOK
LITHGOW
SYDNEY
CANBERRA
ORANGE
PACIFIC OCEAN
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
OZONE- HOUR 16, 27/1/2001
(ppb)
260 270 280 290 300 310 320 330 340 350 360
EASTING (km)
6200
6210
6220
6230
6240
6250
6260
6270
6280
6290
6300
NO
RTH
ING
(km
)
ROZELLE
WOOLOOWARE
LIVERPOOL
LIDCOMBE
BLACKTOWN
RICHMOND
WESTMEAD
VINEYARD
BARGO
CAMPBELLTOWN
APPIN
LINDFIELD
RANDWICK
Example: Sydney 7Example: Sydney 7--day ozone episodeday ozone episode2121--27 January 2001.27 January 2001.
VINEYARD- O3
0
20
40
60
80
100
120
140
0 24 48 72 96 120 144 168
TIME (hours)
CONC
ENTR
ATIO
N (p
pb) OBS
CTM
LIDCOMBE- O3
0
20
40
60
80
100
120
140
0 24 48 72 96 120 144 168
TIME (hours)
CON
CENT
RATI
ON
(ppb
)
OBSCTM
LIVERPOOL- O3
0
20
40
60
80
100
120
140
0 24 48 72 96 120 144 168
TIME (hours)
CO
NCE
NTR
ATI
ON
(ppb
)
OBSCTM
WOOLOOWARE- O3
0
20
40
60
80
100
120
140
0 24 48 72 96 120 144 168
TIME (hours)
CONC
ENTR
ATI
ON
(ppb
)
OBSCTM
PERFORMANCE REVIEWPERFORMANCE REVIEW
149.0 150.0 151.0 152.0 153.0
Longitude (deg. E)
-36.0
-35.0
-34.0
-33.0
-32.0
Latit
ude
(deg
. N)
NEWCASTLE
WOLLONGONG
MUSWELLBROOK
LITHGOW
SYDNEY
CANBERRA
ORANGE
PACIFIC OCEAN
REGIONALREGIONALFORECASTINGFORECASTING
PEAK 1-HOUR OZONE (Regional)
0
50
100
150
200
0 50 100 150 200OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
SYDNEY SOUTH WEST
0
50
100
150
200
0 50 100 150 200OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
SYDNEY NORTH WEST
0
50
100
150
200
0 50 100 150 200OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
150.5 150.6 150.7 150.8 150.9 151.0 151.1 151.2 151.3 151.4LONGITUDE (deg. E)
-34.1
-34.0
-33.9
-33.8
-33.7
-33.6
LATI
TUD
E (d
eg. N
)
BLAC
BRIN
CAMD CAMP
EARL LIDC
LIND
LIVE RAND
RICH
ROZE
ST.M
VYNE
WSTM
WOOL TASMAN
SEA
SYDNEY
MASCOT
PENRITH
NW
SW
EAST
SYDNEYSYDNEY-- Daily 1Daily 1--hour Ohour O33 maxmaxSUBSUB--REGIONAL FORECASTINGREGIONAL FORECASTING
SYDNEY EAST
0
50
100
150
200
0 50 100 150 200OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
SYDNEYSYDNEY-- Daily 1Daily 1--hour Ohour O33 maxmax
SUBURBSUBURB--LEVEL LEVEL FORECASTINGFORECASTING
150.5 150.6 150.7 150.8 150.9 151.0 151.1 151.2 151.3 151.4LONGITUDE (deg. E)
-34.1
-34.0
-33.9
-33.8
-33.7
-33.6
LATI
TUD
E (d
eg. N
)
BLAC
BRIN
CAMD CAMP
EARL LIDC
LIND
LIVE RAND
RICH
ROZE
ST.M
VYNE
WSTM
WOOL TASMAN
SEA
SYDNEY
MASCOT
PENRITH
NW
SW
EAST
PEAK 1-HOUR OZONE (Suburb)
0
50
100
150
200
0 50 100 150 200OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
SYDNEYSYDNEY-- Daily 1Daily 1--hour Ohour O33 maxmax
STATIONSTATION--LEVEL LEVEL FORECASTINGFORECASTING
150.5 150.6 150.7 150.8 150.9 151.0 151.1 151.2 151.3 151.4LONGITUDE (deg. E)
-34.1
-34.0
-33.9
-33.8
-33.7
-33.6
LATI
TUD
E (d
eg. N
)
BLAC
BRIN
CAMD CAMP
EARL LIDC
LIND
LIVE RAND
RICH
ROZE
ST.M
VYNE
WSTM
WOOL TASMAN
SEA
SYDNEY
MASCOT
PENRITH
NW
SW
EAST
PEAK 1-HOUR OZONE (Monitoring station)
0
50
100
150
200
0 50 100 150 200OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
144.2 144.4 144.6 144.8 145.0 145.2 145.4LONGITUDE (deg. E)
-38.4
-38.2
-38.0
-37.8
-37.6
LATI
TUD
E (d
eg. N
)
ALPH
BXHL MTCL
PTCK
PAIS
BRTN
RMIT
GSTH GRVD
PORT PHILLIPBAY
BASS STRAIT
MELBOURNE
GEELONG
MELBOURNEMELBOURNE-- Daily 1Daily 1--hour Ohour O33 maxmax
REGIONAL FORECASTINGREGIONAL FORECASTING
REGIONAL
0
20
40
60
80
100
0 20 40 60 80 100OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
MELBOURNEMELBOURNE-- Daily 1Daily 1--hour Ohour O33 maxmax
SUBSUB--REGIONAL FORECASTINGREGIONAL FORECASTING
144.2 144.4 144.6 144.8 145.0 145.2 145.4LONGITUDE (deg. E)
-38.4
-38.2
-38.0
-37.8
-37.6
LATI
TUD
E (d
eg. N
)
ALPH
BXHL MTCL
PTCK
PAIS
BRTN
RMIT
GSTH GRVD
PORT PHILLIPBAY
BASS STRAIT
MELBOURNE
GEELONG
EASTWEST
GEELONG
EAST
0
20
40
60
80
100
0 20 40 60 80 100OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
WEST
0
20
40
60
80
100
0 20 40 60 80 100OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
GEELONG
0
20
40
60
80
100
0 20 40 60 80 100OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
MELBOURNEMELBOURNE-- Daily 1Daily 1--hour Ohour O33 maxmax
144.2 144.4 144.6 144.8 145.0 145.2 145.4LONGITUDE (deg. E)
-38.4
-38.2
-38.0
-37.8
-37.6
LATI
TUD
E (d
eg. N
)
ALPH
BXHL MTCL
PTCK
PAIS
BRTN
RMIT
GSTH GRVD
PORT PHILLIPBAY
BASS STRAIT
MELBOURNE
GEELONG
SUBURBSUBURB--LEVEL FORECASTINGLEVEL FORECASTING
PEAK 1-HOUR OZONE (Suburb)
0
20
40
60
80
100
0 20 40 60 80 100OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
PEAK 1-HOUR OZONE (Monitoring station)
0
20
40
60
80
100
0 20 40 60 80 100OBSERVED CONCENTRATION (ppb)
FOR
ECA
ST C
ON
CEN
TRA
TIO
N (p
pb)
MELBOURNEMELBOURNE-- Daily 1Daily 1--hour Ohour O33 maxmax
144.2 144.4 144.6 144.8 145.0 145.2 145.4LONGITUDE (deg. E)
-38.4
-38.2
-38.0
-37.8
-37.6
LATI
TUD
E (d
eg. N
)
ALPH
BXHL MTCL
PTCK
PAIS
BRTN
RMIT
GSTH GRVD
PORT PHILLIPBAY
BASS STRAIT
MELBOURNE
GEELONG
STATIONSTATION--LEVEL FORECASTINGLEVEL FORECASTING
OO33>50 ppb>50 ppb
PERFORMANCE INDICESPERFORMANCE INDICES ((OO33 >> 50 ppb50 ppb))SYDNEY- NORMALISED BIAS
-30
-15
0
15
Regional Sub-regional
Suburb Station
Perc
enta
ge
SYDNEY- NORMALISED GROSS ERROR
0
10
20
30
Regional Sub-regional
Suburb Station
Perc
enta
ge
MELBOURNE- NORMALISED BIAS
-30
-15
0
15
Regional Sub-regional
Suburb Station
Perc
enta
ge
MELBOURNE- NORMALISED GROSS ERROR
0
10
20
30
Regional Sub-regional
Suburb Station
Perc
enta
ge
Detected = Detected = d/(d+md/(d+m) ) —— correct forecastscorrect forecastsFalse alarm = False alarm = f/(f+df/(f+d) ) —— missed events missed events
M ≥ O Observed
Model Yes No Total
Yes d f f+d
No m b m+b
Total d+m f+b
AAQFSAAQFS-- PERFORMANCEPERFORMANCE
Contingency TableContingency Table
SYDNEYSYDNEYOZONE DETECTION RATE- SYDNEY
0
20
40
60
80
100
40 60 80 100Exceedance concentration (ppb)
Rat
e (%
)
RegionSub-regionSuburb
OZONE FALSE ALARM RATE- SYDNEY
0
20
40
60
80
100
40 60 80 100Exceedance concentration (ppb)
Rat
e (%
)
RegionSub-regionSuburb
OZONE DETECTION RATE- MELBOURNE
0
20
40
60
80
100
40 60 80 100Exceedance concentration (ppb)
Rat
e (%
)
RegionSub-regionSuburb
OZONE FALSE ALARM RATE- MELBOURNE
0
20
40
60
80
100
40 60 80 100Exceedance concentration (ppb)
Rat
e (%
)
RegionSub-regionSuburb
MELBOURNEMELBOURNE
AAQFS vs. PERSISTENCEAAQFS vs. PERSISTENCE(Sub(Sub--regional)regional)
DETECTION RATE
0
1
2
3
4
40 60 80 100Exceedance concentration (ppb)
AAQ
FS /
PER
SIST
ENC
E SydneyMelbourne
FALSE ALARM RATE
0.0
0.5
1.0
1.5
2.0
40 60 80 100Exceedance concentration (ppb)
AAQ
FS /
PER
SIST
ENC
E SydneyMelbourne
TIME
DO
SAG
E
TWOTWO--SCENARIO FORECASTSCENARIO FORECAST
Why is AAQFS special?
Provides twiceProvides twice--daily forecasts of AQI and daily forecasts of AQI and 18 pollutants for 18 pollutants for EPAsEPAsShows the daily development of pollution Shows the daily development of pollution (highly instructive/other applications)(highly instructive/other applications)Because prognostic, unusual events handledBecause prognostic, unusual events handledCan explore results with offCan explore results with off--line toolsline toolsAlternative scenarios, special locationsAlternative scenarios, special locations
Why is AAQFS unique?
Resolution: 5 km Met, 1 km AQResolution: 5 km Met, 1 km AQIntegral verification of yesterday’s forecastIntegral verification of yesterday’s forecastProven operational within a NMHSProven operational within a NMHSResponsive to daily changes in Responsive to daily changes in EPAEPA--supplied emissions datasupplied emissions dataMinimal demand on resources by Minimal demand on resources by EPAsEPAs‘Green’ scenarios can be run on special days‘Green’ scenarios can be run on special days
Experience with Generating Emissions Inventories More…
PopulationPopulation--based emissions can produce based emissions can produce quite acceptable results (no industry)quite acceptable results (no industry)Industry must be treated explicitlyIndustry must be treated explicitlySimple Simple biogenicsbiogenics scheme works wellscheme works wellPollution inflows may be much more Pollution inflows may be much more important in other national settingsimportant in other national settingsSeasonal, diurnal and weatherSeasonal, diurnal and weather--related related emissions changes should be done emissions changes should be done inin--line for simplicity and speed.line for simplicity and speed.
Prognostic Model + Emissions Inventory → Applications More…
StandStand--alone applications useful (TAPM)alone applications useful (TAPM)Air quality management planning/scenariosAir quality management planning/scenariosMonitoring network designingMonitoring network designingIndustrial complex emissions managementIndustrial complex emissions managementSurveillance of urban pollution emissionsSurveillance of urban pollution emissionsUrban design applicationsUrban design applicationsAssessments of transport options/technologiesAssessments of transport options/technologiesAirshed emissions taxes/tradingAirshed emissions taxes/tradingWindWind--Power prospecting!Power prospecting!
AAQFS Experiences More…
Emissions Inventories Emissions Inventories –– our biggest problemour biggest problemWindWind--blown dust, other particle sources, blown dust, other particle sources, difficult difficult –– effort by Met. Service of Canada effort by Met. Service of Canada commendablecommendableTimeliness and quality of air pollution Timeliness and quality of air pollution monitoring data is vital for warm starts monitoring data is vital for warm starts (assimilation)(assimilation)GRS chemistry adequacyGRS chemistry adequacyRoutine verification of forecastsRoutine verification of forecastsBackgrounds/domainBackgrounds/domain--size issuesize issueCooperation between Agencies is importantCooperation between Agencies is importantUptake by others is slow Uptake by others is slow –– patience!patience!