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1
Understanding Relationships Between Changes in Ambient Ozone and
Precursor Concentrations and Changes in VOC and NOx Emissions
from 1990 to 2004 in Central California
Envair – C. Blanchard and S. Tanenbaum
DRI – E. Fujita and D. Campbell
Alpine Geophysics – J. Wilkinson
Phase I Findings and Proposed Phase II ApproachMay 31, 2007
2
Acknowledgements
CARB
Dar Mims, Dwight Oda, Don Johnson, Martin Johnson, Larry Larsen, Cheryl Taylor
BAAQMD
Jim Cordova, Saffet Tanrikulu
SJVAPCD
Evan Shipp
… plus everyone else for review and assistance
3
Today’s TopicsI. Project overviewII. Trend analysis summary III. Trends in ozone precursors IV. Trends in precursors compared with county-
level emissionsV. Spatial variations of ozone precursors
=> Questions
VI. Ozone trendsVII. Meteorological classificationVIII. Do met classes shed light on ozone trends?
=> Questions
IX. Phase II analyses and schedule
4
I. Project Overview• Phase I
– Develop databases and methods– Characterize ozone and precursor trends by site,
subregion – compare precursor trends to county-level emission trends – characterize ozone trends by meteorological class
– Evaluate prospects for success in Phase II
• Phase II– Grid emissions and relate ambient primary-pollutant
trends to zone-of-influence emission trends– Relate ozone trends to ambient and emission trends of
precursors, and to meteorological conditions– Submit final report
5
II. Trends Summary
6
Sub-Region
N orthern S ierra Footh ills
Southern S ierra Footh ills
Sacram ento Valley
N orthern SF Bay A rea
Eastern SF Bay A reaSouthern SF Bay A reaN orthern San Joaquin
C entra l San Joaquin
Southern San Joaquin
AQ Sites and Subregions
7
AQ Metrics – Annual Averages• Ozone
– Annual 4th-highest daily 8-hour max, each site– Annual mean of top-60 peak 8-hour days, each site
(the top-60 days are determined for each subregion)
• CO and NOx– Annual means from top-60 days, each site– Morning (start hours 5 am – 10 am)– Time of peak 8-hour ozone maxima (“mid-day”)
• NMOC – Annual means from all days, by site– Early morning - 5 am PST (most complete sampling)
8
1990 – 2004 AQ Trends Summary Results
• No trends significantly upward*• NOx sig* down at 22 of 28 sites**• CO sig* down at 21 of 25 sites**• NMOC sig* down at 5 of 7 sites***• Ozone sig* down at 7 of 42 sites**• Annual mean top-60 ozone trends similar
to trends in annual 4th-highest 8-hour max
* p < 0.05** At least 10 years data. One or both metrics.*** 7 - 10 years data
9
III. Trends in Ozone Precursors
10Morning NOx decline: 0.66 ppbv/year (~10 ppbv over period)Mid-day NOx decline: 0.31 ppbv/year (~5 ppbv over period)
Fresno First Street - Mean Morning ( 5 am - 11 am) and Mid-day (Time of 8-hour O3 Max) NOx on Top 60 Subregional Days
0
10
20
30
40
50
60
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
NO
x (p
pb
v)
11
Parlier - Mean NOx on Top 60 Subregional High-Ozone DaysMorning ( 5 am - 11 am) and Mid-day (Time of 8-hour Ozone Max)
0
5
10
15
20
25
30
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
NO
x (p
pb
v)
Morning NOx decline: 0.39 ppbv/year (~4 ppbv over period)Mid-day NOx decline: 0.21 ppbv/year (~2 ppbv over period)
12
Morning NMOC - Fresno First Street
0
50
100
150
200
250
300
350
400
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
NM
OC
(p
pb
C)
Morning NMOC decline: 8.2 ppbC/year (~66 ppbv over period)
13
Mean Morning NMOC - Clovis
0
100
200
300
400
500
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
NM
OC
(p
pb
C)
Morning NMOC decline: 11.5 ppbC/year (~115 ppbv over period)
14
Mean Morning NMOC Parlier
0
50
100
150
200
250
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
NM
OC
(p
pb
C)
Morning NMOC decline: 5.1 ppbC/year (~51 ppbv over period)
15
Morning CO decline: 43 ppbv/year (~650 ppbv over period)Mid-day CO decline: 20 ppbv/year (~300 ppbv over period)
(1990 data suspect)
Fresno First Street - Mean CO on Top 60 Subregional High-Ozone DaysMorning ( 5 am - 11 am) and Mid-day (Time of 8-hour Ozone Max)
0
200
400
600
800
1000
1200
1400
1600
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
CO
(p
pb
v)
16
FRESNO
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
YEAR
NM
OC
/CO
Similar results for Bakersfield and Sacramento Del Paso: ~0.3 ppbC NMOC per ppbv CO (some years differed)
NMOC/CO from regression of NMOC against CO, by year.Annual r2 ranged from 0.65 to 0.94 (5 am samples)
NMOC vs. CO Fresno First Street, 5 am Samples, Summer 2000
0
100
200
300
400
500
600
700
0 500 1000 1500 2000 2500
CO (ppbv)
NM
OC
(p
pb
C)
17CO/NOx declines so does NMOC/NOx
Fresno First Street Morning CO/NOx
0
5
10
15
20
25
30
35
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
CO
/NO
x (d
imen
sion
less
)
18
FRESNO
0
3
6
9
12
15
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
YEAR
BE
NZ
EN
E/C
O
Benzene/CO from regression of benzene against CO, by year.Annual r2 ranged from 0.68 to 0.94, except 1998 (5 am samples)
19
IV. Comparison of AQ Trends to County-Level Emission Trends
20
Fresno County NOx Emissions Compared With Morning NOx Concentrations at Fresno First Street
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
No
rmal
ized
An
nu
al V
alu
e
NOx Emissions Morning NOx Linear (NOx Emissions) Linear (Morning NOx)
Emission trend (0.40) exceeds ambient trend (0.20)
21Ambient trend (0.80) exceeds emission trend (0.60)
Fresno County CO Emissions Compared With Morning CO Concentrations at Fresno First Street
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
2.00
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
No
rmal
ized
An
nu
al V
alu
e
CO Emissions Morning CO Linear (CO Emissions) Linear (Morning CO)
22
Ambient vs. Emissions Decrease for CO
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
Emissions Decrease (normalized difference)
Am
bie
nt
Dec
reas
e (n
orm
aliz
ed d
iffe
ren
ce)
Ambient decrease exceeds emissions decrease (13 sites)
Ambient decrease less than emissions decrease (12 sites)
23
Ambient vs. Emissions Decrease for NOx
-0.2
0
0.2
0.4
0.6
0.8
1
-0.2 0 0.2 0.4 0.6 0.8 1
Emissions Decrease (normalized difference)
Am
bie
nt
Dec
reas
e (n
orm
aliz
ed d
iffe
ren
ce)
Ambient decrease exceeds emissions decrease (15 sites)
Ambient decrease less than emissions decrease (13 sites)
24
Ambient and Emissions Decreases for CO
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Fremont-Chapel W
ay
Livermore
Jackson-Clinton Road
San Andreas-Gold Strike
Pittsburg-10th Street
Bethel Island Road
Concord-2975 Treat Blvd
Placerville-Gold Nugget
Fresno-Drumm
ond Street
Parlier
Fresno-Sierra Skypark #2
Fresno-1st Street
Clovis-N Villa Avenue
Edison
Oildale-3311 Manor Stree
Arvin-Bear Mountain Blvd
Bakersfield-Golden State
Bakersfield-5558 Califor
Merced-S Coffee Avenue
Roseville-N Sunrise Blvd
North Highlands-Blackfoo
Sacramento-Del Paso M
ano
Elk Grove-Bruceville Roa
Sacramento-T Street
Folsom
Stockton-Hazelton Street
Gilroy-9th Street
San Jose-4th Street
Vallejo-304 Tuolumne Str
Modesto-14th Street
Turlock-S Minaret Street
Visalia-N Church Street
Sonora-Barretta Street
Site
Dec
reas
e (N
orm
aliz
ed V
alu
es)
Ambient CO Decrease at Sites Emissions CO Decrease in County
25
Ambient and Emissions Decreases for NOx
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Fremont-Chapel W
ay
Livermore
Jackson-Clinton Road
San Andreas-Gold Strike
Pittsburg-10th Street
Bethel Island Road
Concord-2975 Treat Blvd
Placerville-Gold Nugget
Fresno-Drumm
ond Street
Parlier
Fresno-Sierra Skypark #2
Fresno-1st Street
Clovis-N Villa Avenue
Edison
Oildale-3311 Manor Stree
Arvin-Bear Mountain Blvd
Bakersfield-Golden State
Bakersfield-5558 Califor
Merced-S Coffee Avenue
Roseville-N Sunrise Blvd
North Highlands-Blackfoo
Sacramento-Del Paso M
ano
Elk Grove-Bruceville Roa
Sacramento-T Street
Folsom
Stockton-Hazelton Street
Gilroy-9th Street
San Jose-4th Street
Vallejo-304 Tuolumne Str
Modesto-14th Street
Turlock-S Minaret Street
Visalia-N Church Street
Sonora-Barretta Street
Site
Dec
reas
e (N
orm
aliz
ed V
alu
es)
Ambient NOx Decrease at Sites Emissions NOx Decrease in County
26
What Did We Learn?
• On average, ambient precursor decreases are comparable to county-level emissions decreases
• There is a possibility that emission decreases are overestimated or underestimated for some counties
• Confirmation requires comparison of site trends to spatially-resolved emission trends (Phase II)
27
V. Spatial Variations of Ozone Precursors
28
Sacramento Del Paso Mean Morning Concentrations
CO NOx
29
Roseville Mean Morning Concentrations
CO NOx
30
Fresno 1st St Mean Morning Concentrations
CO NOx
31
Fresno Sierra Skypark Mean Morning Concentrations
CO NOx
32
Phase II AQ vs. Emissions• Directional variations of primary species AQ
concentrations imply significant local influences• Comparison of site primary species AQ trends to
emission inventory trends can be improved by using gridded inventories
• The Phase II comparisons will permit more robust conclusions about the differences between site and emission trends – eliminate the mismatch between spatial scales (replace county-level emissions with emissions from local zones of influence)
• Potential limitation is accuracy of gridding
33
Questions and Comments on Primary Species Phase I Findings and
Phase II Objectives
34
VI. What Are the Ozone Trends?
35Annual 4th max decline: 0.58 ppbv/year (~9 ppbv over period)Mean Top 60 decline: 0.38 ppbv/year (~6 ppbv over period)
Fresno First Street -- Annual 4th-Highest 8-Hour Ozone and Mean of Top 60 Subregional Days
0
20
40
60
80
100
120
140
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
Ozo
ne
(pp
bv)
36
Parlier -- Annual 4th-Highest 8-Hour Ozone and Mean of Top 60 Subregional Days
0
20
40
60
80
100
120
140
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
Ozo
ne
(pp
bv)
37
Livermore Annual 4th-Highest 8-Hour Ozone and Mean of Top 60 Subregional Days
0
10
20
30
40
50
60
70
80
90
100
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2000 2001 2002 2003 2004
Year
Ozo
ne
(pp
bv)
First Street | Rincon
38* Livermore 1st St only
Ozone Trends in Subregions - Medians of Site Trends
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
EasternSFB*
NorthernSFB
SouthernSFB
NorthernSJV
Central SJV
SouthernSJV
Sacra- mentoValley
NorthernSierra
Foothills
SouthernSierra
Foothills
Subregion
Ozo
ne
Tre
nd
(p
pb
v p
er y
ear)
4th Highest 8-hour maximum Top 60 8-hour maximum
39
VII. Meteorological Classification
40
Why Examine Meteorological Data?
Meteorological information may permit more complete reconciliation of ambient ozone trends with precursor and emissions trends.
Phase I. Uses meteorological information to split days into groups with different meteorological characteristics. Initial evidence indicates that ozone trends vary by site, subregion, met type.
Phase II. More detailed analyses.
41
Met Classification*:
1. Principal component analysis (PCA) of regional-scale met variables
2. K-means clustering of PCs
* Trend adjustment Forecasting Interbasin transport
PCA applied to all daysof all years from
1990 to 2004(n = 5480** days)
Clustering applied to allozone-season days
(n = 2790 days)
** 5441 with pressure gradient data; 4202 with 850 mb data
42
PCA of Regional-Scale Variables
San Francisco-to-Medford sea-level pressure gradient, daily averageSan Francisco-to-Reno sea-level pressure gradient, daily averageSan Francisco-to-Fresno sea-level pressure gradient, daily averageSan Francisco-to-Las Vegas sea-level pressure gradient, daily average
Oakland 850 mb vector component (u) wind speed and direction at 4 amOakland 850 mb vector component (v) wind speed and direction at 4 amOakland 850 mb vector component (u) wind speed and direction at 4 pmOakland 850 mb vector component (v) wind speed and direction at 4 pm
Oakland 850 mb temperature and height at 4 amOakland 850 mb temperature and height at 4 pm
43
Three PCs explain 80% of variance of eight variablesPC1 is westerly wind – PC2 is northerly wind – what is PC3?
PCA - Regional Scale Meteorological Variables
-1.5
-1
-0.5
0
0.5
1
1.5
SanFrancisco-Medfordpressuregradient
SanFrancisco-
Renopressuregradient
SanFrancisco-
Fresnopressuregradient
SanFrancisco-Las Vegaspressuregradient
Oakland850 mb u-vector windspeed anddirection, 4
am
Oakland850 mb v-
vector windspeed anddirection, 4
am
Oakland850 mb u-vector windspeed anddirection, 4
pm
Oakland850 mb v-
vector windspeed anddirection, 4
pm
Variable
Pri
nci
pal
Co
mp
on
ent
(dim
ensi
on
less
)
PC1 PC2 PC3
44
0
1
2
3
4
5
6
Res
ulta
nt W
ind
Spe
ed (
m s
-1)
-2.5 -1.5 -.5 .5 1.5 2.5Principal Component 3 (dimensionless)
d. Bakersfield California Avenue
0
1
2
3
4
5
6
Res
ulta
nt W
ind
Spe
ed (
m s
-1)
-2.5 -1.5 -.5 .5 1.5 2.5Principal Component 3 (dimensionless)
c. Clovis
0
1
2
3
4
5
6
Res
ulta
nt W
ind
Spe
ed (
m s
-1)
-2.5 -1.5 -.5 .5 1.5 2.5Principal Component 3 (dimensionless)
b. Livermore Rincon
0
1
2
3
4
5
6
Res
ulta
nt W
ind
Spe
ed (
m s
-1)
-2.5 -1.5 -.5 .5 1.5 2.5Principal Component 3 (dimensionless)
a. Sacramento Del Paso
PC3 correlates with surface wind speeds – interpret as ventilation
45
Split days into four groups using K-means clustering
46
Clusters separate days into groups with different pressure gradients
47
Clusters separate days into groups with different 850 mb wind directions
48
Clusters separate days into groups with different 850 mb T
49
12
34
S1
S2
S3
S4
0
50
100
150
200
250
300
350
400
450
Number of Days
Previous Day Cluster
Current Day Cluster
Met Clusters Compared With Previous-Day Cluster
Clusters exhibit persistence and preferred transitions(especially 4-to-1, 2-to-3, and 3-to-4)
50
SBANBA & EBA
SAC NSJV
CSJV SSJV
Daily-average surface wind speeds, all sites
51
52
What Can We Learn From Met Clusters?
• Splitting days into groups having similar meteorological conditions is useful for reducing meteorological “noise”
• Potentially may reveal differences in response of ozone to precursor changes under different source-receptor conditions or different degrees of photochemical activity and “aging”
53
VIII. Do Met Classes Shed Light on Ozone Trends?
54
Mean peak 8-hour ozone concentrations varied among sites, subregions, and met types – these days are all top-60 peak 8-hour days
55
The change in mean peak 8-hour ozone concentrations from 1995-1999 to 2000-2004 varied among sites, subregions, and met types
56
Change in Mean Peak Daily 8-Hour Ozone, 1995-99 to 2000-04
(by Meteorological Class and Subregion)
-15
-10
-5
0
5
10
15
Subregion
Ozo
ne
(p
pb
v)
SBA NBA EBA NSJ SAC NSF CSJ SSJ
Change in Mean Peak Daily 8-Hour Ozone, 1995-99 to 2000-04(by Meteorological Class and Subregion)
-15
-10
-5
0
5
10
15
Subregion
Ozo
ne
(p
pb
v)
SBA NBA EBA NSJ SAC NSF CSJ SSJSBA NBA EBA NSJ SAC NSF CSJ SSJ
57
Change in Mean Peak Daily 8-Hour Ozone, 1995-99 to 2000-04(by Meteorological Class and Subregion)
-15
-10
-5
0
5
10
15
Ozo
ne
Ch
ang
e (p
pb
v)
Type 1 Type 2 Type 3 Type 4
Change in Mean Peak Daily 8-Hour Ozone, 1995-99 to 2000-04(by Meteorological Class and Subregion)
-15
-10
-5
0
5
10
15
Ozo
ne
Ch
ang
e (p
pb
v)
Type 1 Type 2 Type 3 Type 4Type 1 Type 2 Type 3 Type 4
(Order is SBA, NBA, EBA, NSJ, SAC, NSF, CSJ, SSJ)
58
For all met classes, top-60 mean peak 8-hour ozone is down at Clovis but up at Parlier … the differences in ozone trends at Clovis and Parlier do not appear to be due to changes in meteorology or in the frequencies of occurrence of different meteorological types
59
Mean Top-60 Peak 8-hour Ozone - Cluster 1
0
20
40
60
80
100
120
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
Ozo
ne (p
pb
v)
Clovis Parlier Linear (Clovis) Linear (Parlier)
60
Mean Top-60 Peak 8-hour Ozone - Cluster 2
0
20
40
60
80
100
120
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
Ozo
ne (p
pb
v)
Clovis Parlier Linear (Clovis) Linear (Parlier)
61
Mean Top-60 8-hour Ozone - Cluster 3
0
20
40
60
80
100
120
1994 1995 1996 1997 1998 1999 2000 2001 2002 2004
Year
Ozo
ne (p
pb
v)
Clovis Parlier Linear (Clovis) Linear (Parlier)
62
Mean Top-60 Peak 8-hour Ozone - Cluster 4
0
20
40
60
80
100
120
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
Ozo
ne (p
pb
v)
Clovis Parlier Linear (Clovis) Linear (Parlier)
63
Next Steps – Phase II Ozone Analyses
• Phase I analyses demonstrate variations of ozone and of ozone trends but do not explain them
• Site-to-site variations and directional variations of mean concentrations imply significant local ozone formation
• Need to analyze ozone formation rates
• Potential limitation is signal-to-noise
64
Questions and Comments on
Ozone Phase I Findings and
Phase II Objectives
65
Phase II
• Phase II schedule – complete by December 2007 with final report and draft manuscript
• Why would Phase II be useful?– Identify zones of emission influence - more
accurate comparison of sites’ AQ trends with “zone-of-influence” emission trends
– Better understanding of ozone trends at sites within each subregion and the relation of ozone to precursor trends, differentiated by met class and subclass
66
Task 5
• Generate gridded inventories from county-level inventories and historical surrogate files
• Develop monitor-specific “zone-of-influence” emission trends using 3x3 to 7x7 arrays of grid cells around each long-term monitor
67
Task 6
• Compare “zone-of-influence” emission trends to ambient primary-pollutant trends. Identify consistencies and discrepancies. Evaluate evidence for inaccuracies in emission estimates.
• Subdivide met classes. Determine peak ozone changes by site, met class and subclass, and (if warranted) month and day of week. Relate ozone changes to precursor trends and meteorology.
68
Reporting
• Task 7: Prepare final report and draft manuscript
• Task 8: Provide data, documentation, and software
• Task 9: Present findings at meetings