application of synoptic typing to an investigation of nocturnal ozone concentration at a maritime...
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Application of synoptic typing to an
investigation of nocturnal ozone concentration
at a maritime location, New Zealand
B. A. Khan1, C.R. de Freitas1* and D. Shooter1
1School of Geography, Geology and Environmental Science, The University of Auckland, New Zealand.
*Corresponding author: [email protected]
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The paper presented at a conference
Resource Management under stormy skies: Water Allocation @ the crossroads?
Held in
Christchurch, New Zealand
20-Nov-2006 to 23-Nov-2006
At University of Canterbury, ChCh
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- Ozone (O3) and NO2 are important components of photochemical smog
- Physical and chemical processes at night affect the photochemical oxidant’s concentration the following day
- Meteorological conditions and synoptic situations at night are important with respect to ...
• Dispersion• Destruction• Advection• Chemical reactions
… of pollutants
- Most of research on photochemical oxidants has focused on the day time
processes
BackgroundBackground
NOCTURNAL OZONENOCTURNAL OZONE
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Examine relationships between synoptic conditions and nocturnal ozone
ProcedureProcedure
- Define the prevailing weather types in winter at night
- Examine the effect of those weather types on O3 and NOx concentration
- Examine the contribution of background O3 at night time
MAIN AIMMAIN AIM
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- Study area: Auckland region
- Monitoring site: • Musick Point; east coast of Auckland region
- Data: • Winter, 19:00 to 06:00 hours for 2004 and 2005
- Variables measured
• Wind speed
• Wind direction
• Relative humidity
• Temperature
• NO
• NO2
• O3
STUDY SITESTUDY SITE
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STUDY SITE STUDY SITE Musick PointMusick Point
Musick Point
NN
NN
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Deposition
NO
NO2
NO3
N2O5
HNO3
Organic Nitrates
NO, hv
NOx
NO2
O3, RO2
O3
VOC
H2O (Het)
OH∆
hvO O3
O2
Atmospheric Chemistry Atmospheric Chemistry of NOof NOxx and O and O33
NOCTURNAL OZONENOCTURNAL OZONE
Adopted from Brown et al. (2004)
Red arrows indicate reactions that require sunlight while black
arrows indicate reactions that do not
NO + O3 NO2 + O2
NO2 + O3 NO3 + O2
NO2 + NO3 +(M) N2O5 +(M)
N2O5 +H2O(het) 2HNO3
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An integrated approach was adopted, addressing a weather condition/type
instead of individual meteorological parameters
Analysis approachAnalysis approach
- Principal Component Analysis (PCA)
- Principal Component Regression
- Weather maps for validation of synoptic regimes
Exploratory analysis methodExploratory analysis method
METHODMETHOD
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METHODMETHOD
Daily average night-timedata of winter 2004-2005
Preliminary Analysis
PCA
PCs accounting for highest variation in the
data
Regression AnalysisDominant weather
types
Synoptic Classes
Relationship between synoptic
classes and O3
Var. Transformation
O3 and NOx regressed on PCs
Reg with data allocated to WD
Analysis of PCs score
Verif. weather maps
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Variable Minimum Maximum Mean Std. Deviation
O3 (µg m-3) 2.93 95.66 50.64 18.72
NO (µg m-3) .00 66.36 2.60 6.96
NO2 (µg m-3) .33 47.55 12.40 10.47
Air temperature (oC) 6.7 20.10 12.28 2.81
Wind speed (m s-1) 1.00 13.05 3.81 1.96
Relative humidity (%) 62.49 96.34 82.82 6.42
Vapour pressure (hPa) 6.70 21.73 12.07 2.80
Descriptive statisticsDescriptive statistics
PRELIMINARY ANALYSISPRELIMINARY ANALYSIS
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Wind frequency in various quadrantsWind frequency in various quadrants
80% wind frequency from W, SW and S (Urban/land winds)
20% wind frequency from N, NE, E (Maritime winds)
PRELIMINARY ANALYSISPRELIMINARY ANALYSIS
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Northeast
EastSoutheast
South
Southwest
West
Northwest
WD Quadrants
40.0
50.0
60.0
70.0
Me
an
O3
µg
/m3
Northeast
EastSoutheast
South
Southwest
West
Northwest
WD Quadrants
0.0
5.0
10.0
15.0
20.0
Me
an
NO
2 µ
g/m
3
Ozone (OOzone (O33) and NO) and NO22 concentration in various wind concentration in various wind
quadrantsquadrants
PRELIMINARY ANALYSISPRELIMINARY ANALYSIS
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Variable
Component
PC1:Intermediate Cond.
PC2:Stable and
Unstable Cond.
v-component 0.829 0.260
u-component 0.712 -0.070
Relative humidity 0.767 -0.193
Temperature 0.572 0.506
Wind speed -0.121 0.915
Rotated component matrix (loading matrix) Rotated component matrix (loading matrix)
PRINCIPAL COMPONENT ANALYSIS (PCA)PRINCIPAL COMPONENT ANALYSIS (PCA)
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Synoptic classReference Weather type
Anticyclonic
1Weak south-westerlies flow with low temperature and moisture content.
2Weak easterly flow with average temperature and moisture content.
Cyclonic
3Strong south-westerlies with average temperature and moisture content.
4Strong north-easterly and easterlies with relatively high temperature and moisture content.
Intermediate
5Moderate southerly, south-westerly and westerly winds with relatively low temperature and moisture content.
6Moderate south-westerlies with average temperature and moisture content.
7Moderate north-easterlies with average temperature and moisture content.
PRINCIPAL COMPONENT ANALYSIS (PCA)PRINCIPAL COMPONENT ANALYSIS (PCA)
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Regression Model
Dependent variable R2
Adjusted R2
PC1: Intermediate condition
PC2: Calm/Unstable condition
R2
changeStandardized coefficients β
R2 change
Standardized coefficients β
1 O3 0.257 0.252 0.047 0.217 0.210 0.458
2 NO2 0.457 0.453 0.149 -0.386 0.308 -0.555
Regression models for ORegression models for O33 and NO and NO22
PRINCIPAL COMPONENT REGRESSION (PCR)PRINCIPAL COMPONENT REGRESSION (PCR)
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0.0 20.0 40.0 60.0 80.0 100.0
Dependent Variable: O3µg/m3
30.0
40.0
50.0
60.0
70.0
80.0
90.0
Pre
dic
ted
Va
lue
of
O3
µg
/m3
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0
Dependent Variable: t.NO2
-2.0
0.0
2.0
4.0
6.0
Pre
dic
ted
Va
lue
of
t.N
O2
Scatter plots of predicted and observed average daily Scatter plots of predicted and observed average daily concentration of Oconcentration of O3 3 and NOand NO22
PRINCIPAL COMPONENT REGRESSION (PCR)PRINCIPAL COMPONENT REGRESSION (PCR)
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Synoptic class
Weather type
Winddirection
Wind speed Temp. Humidity O3 NO2 NO
Anticyclonic1 SW Weak L L L H H
2 E Weak M M H L 0
Cyclonic 3 SW Strong M M H L 0
4 NE, E Strong H H H L 0
5 S, SW,W Moderate L L M H M
Intermediate 6 SW Moderate M M M M L
7 NE Moderate M M H L 0
Synoptic classes with corresponding Synoptic classes with corresponding descriptions of seven weather types. descriptions of seven weather types.
H = high or above average; L = low or below average; M = medium or above average. NO = 0 = less than 1μgm-3.
SYNOPTIC TYPINGSYNOPTIC TYPING
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- Main process is titration of O3 by NO
- Dry deposition
NONOxx destruction processes destruction processes
Ozone destruction processesOzone destruction processes
Important meteorological variablesImportant meteorological variables
- O3: Wind speed and wind direction
- NOx: Wind speed, wind direction and temperature
- Hydrolysis of N2O5 (dinitrogen pentodxide) by heterogeneous gas phase reaction
SYNOPTIC TYPINGSYNOPTIC TYPING
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Sources of human induced O3
- Traffic
- Industry
- Home heating
Sources of background O3
- Maritime winds
- Wind gusts
- Thunderstorms
SOURCES OF OSOURCES OF O33
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Study identified three synoptic classes consisting of seven weather types.
Most of the variation in O3 and NOx was observed during cyclonic and anticyclonic conditions.
Ozone was high in maritime wind flows and cyclonic condition while NOx was high in anticyclonic weather types related to urban wind flows
Effect of weather types varied with pollutant: greater effect on NOx than O3.
Background O3 is an important contributor to total O3 in Auckland region
Temperature and humidity had no effect on nocturnal O3 concentration, but contribute to NOx concentration at night
Thunderstorms and wind gusts appears to be important processes for down welling of O3 from upper boundary layer.
CONCLUSIONCONCLUSION
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It is difficult to characterise NOx and O3 chemistry using a single
measurement site. A more comprehensive study is required
using data from several sites.
Future WorkFuture Work
CONCLUSIONCONCLUSION
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AcknowledgementAcknowledgement
We are grateful to the Auckland Regional Council and
Janet Peterson for providing meteorological and air
pollutants data from Musick Point monitoring station.
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