climate change extremes and air pollution in california michael j. kleeman department of civil and...
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![Page 1: Climate Change Extremes and Air Pollution in California Michael J. Kleeman Department of Civil and Environmental Engineering UC Davis](https://reader035.vdocument.in/reader035/viewer/2022062407/56649ce65503460f949b40bd/html5/thumbnails/1.jpg)
Climate Change Extremes and Air Pollution in California
Michael J. KleemanDepartment of Civil and Environmental
EngineeringUC Davis
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Air Pollution Taxonomy
Primary Pollutants• Emitted directly from a source to
the atmosphere
• Concentration determined by emissions rate, wind speed, PBL height, and precipitation
Secondary Pollutants• Produced by chemical reactions in
the atmosphere
• Concentration determined by emissions, wind speed, PBL height, precipitation, temperature, humidity, UV, etc.
wind(m/sec)
emissions (kg/sec)
Conc = emissions / (wind * height) height (m)
http://acmg.seas.harvard.edu/people/faculty/djj/book/bookchap11.html
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Major Air Pollutants: Ozone and Particles
• Ozone (O3) is a chemical oxidant (reactive!)– Produced by CxHyOz + NOx -> O3
– inflammation of lung tissue, pulmonary and nasal congestion, coughing and wheezing, aggravates asthma, decreases resistance to pneumonia and bronchitis
• Airborne Particles (PM10, PM2.5)– Emitted directly or formed by chemical reaction– Associated with increased death rate even at low
concentrations (15 µg m-3)
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Early Extreme Air Pollution Event: The London Fog
Source: http://www.portfolio.mvm.ed.ac.uk/studentwebs/session4/27/greatsmog52.htm
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Source: DOCKERY DW, POPE CA, XU XP, et al. “AN ASSOCIATION BETWEEN AIR-POLLUTION AND MORTALITY IN 6 UNITED-STATES CITIES”, NEW ENGLAND JOURNAL OF MEDICINE 329 (24): 1753-1759 DEC 9 1993.
More Recent Health Effects Data for Airborne Particles: The Six Cities Study
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PM2.5 Concentrations in the US:30,000 – 50,000 deaths each year
Source: US EPA (http://www.epa.gov/air/airtrends/2007/report/particlepollution.pdf).
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California’s Major Air
Basins
San Joaquin Valley
South Coast Air Basin
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PM10 Time Trends 1980-2003 Riverside (Southern California)
Emissions changes make this a “non-stationary” signal.
We spend a lot of money to purchase this decrease over time.
Will climate change reduce the effectiveness of our emissions control programs?
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Parallel Climate Model (PCM) - provides initial and boundary conditions for the Weather
Research and Forecasting (WRF) model.
CIT-UCD 3D Photochemical Model - calculates transport and chemistry of gas- and particle-phase
species, and uses dry and wet deposition schemes
WRF Preprocessing System (WPS) - processes PCM outputs into the format used by WRF
Weather Research and Forecasting (WRF) version 2.2 - generates hourly fields for a 264x264x10 grid-cell domain
with 4-km horizontal resolution, and variable vertical spacing extending to 5000 m above the ground
WRF Output Processing -extracts and processes 2D
and 3D meteorological fields for the air quality
model
Emissions Processing - processes source oriented typed emissions for area,
point, mobile and biogenic sources
Initial conditions, seasonal boundary conditions, and
land use data
- hourly mixing ratios of gas-phase and concentrations of particle-phase species using SAPRC chemical mechanism
Source: A. Mahmud, M. Hixson, J. Hu, Z. Zhao, S.H. Chen, M.J. Kleeman, “Climate impact on airborne particulate matter concentrations in California using seven year analysis periods”, Atmos. Chem. Phys. Discuss., 10, 1–35, 2010.
Over-view of Climate Air Quality Modeling System
Statistical downscaling for PM doesn’t work well in California.
Dynamic downscaling studies are expensive. How well do they work?
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Seven-year Average PM2.5 Concentrations in California
PM2.5 Organic Compounds PM2.5 Nitrate
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0.00
5.00
10.00
15.00
20.00
25.00
CELA SJ4 FSF M14 VCS S13
Site
To
tal M
ass
(mg
m-3
)
Mod
Obs
Observed data obtained from the California Air Resources Board (CARB )
Six sites in California: Central Los Angeles (CELA), San Jose (SJ4), Fresno (FSF), Modesto (M14), Visalia (VCS), and Sacramento (S13)
Comparison: Modeled vs Observed (2000-06)
PM2.5 Total Mass Comparison
Source: A. Mahmud, M. Hixson, J. Hu, Z. Zhao, S.H. Chen, M.J. Kleeman, “Climate impact on airborne particulate matter concentrations in California using seven year analysis periods”, Atmos. Chem. Phys. Discuss., 10, 1–35, 2010.
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WRF Over-predicts Wind Speed During Pollution Events in California
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Are WRF Predictions for Wind Speed Too “Noisy” During Pollution Events?
Simulation with PCM
Simulation with GFS
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Are WRF PBL Height Predictions Reliable Enough?
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Change in Annual Average Airborne Particle Concentrations Due to Climate is Smaller than Inter-Annual Variability
Change in 7-Year Average Airborne Particle Concentrations Due to Climate
Red=IncreasedBlue=Decreased
Probability that Calculations show a Statistically Significant Change
Green=Less CertainBlue=More Certain
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Analysis of Extreme Events: 99th Percentile Days in 2000-06 vs. 2047-53
0
20
40
60
80
100
120
0.35 3.13 5.91 8.69 11.48 14.26 17.04 19.82
Bin mid-point (ug/m3)
2000-2006Sample (n) = 1008Mean (m ) = 8.06Std (s) = ±2.87
0
20
40
60
80
100
120
0.35
1.74
3.13
4.52
5.91
7.30
8.69
10.0
911
.4812
.8714
.2615
.6517
.0418
.4319
.8221
.21
Bin mid-point (mgm-3)
2047-2053Sample (n) = 1008Mean (m) = 7.92Std (s) =±3.08
(b)
Fre
qu
en
cy (
#)
(a)
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Increase in Airborne Particle Concentrations During Future Extreme Events Due to Climate
99th Percentile PM2.52000-06 (max=46µg/m3)
99th Percentile PM2.5 2047-53 (max=58 µg/m3)
Difference in 99th Percentile PM2.5 Caused by Climate
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Changing Population Exposure During Extreme Events
6
-6-10
-32816
-31
8812
-28
2671910
-200-150
-100-50
0
50100
150200
CA
25
-14
8153540
-54
444739
-27
56354538
-200-150-100-50
050
100150200
SV
391624305753
-37
474949
-30
68475550
-200-150-100-50
050
100150200
SJVF
utu
re c
ha
ng
e fr
om
pre
sen
t-d
ay
(%)
-7-23-13-9
20-2
-34-5-5-6
-36
3
-7
4
-6
-200-150-100-50
050
100150200
TO
T M
AS
S
EC
OC
N(V
)
S(V
I)
N(-
III)
ME
TL
Dus
t
Shi
ppin
g
Woo
d S
mok
e
Die
sel
Com
bust
ion
Gas
olin
eC
ombu
stio
n
Mea
t Coo
king
Hig
h S
ulfu
rC
onte
nt F
uels
Mis
cella
neou
s
SoCAB
PM2.5 category/species
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Wildfires Cause Extreme Air Quality Events
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Ozone Concentrations in the US
Source: US EPA (http://www.epa.gov/air/airtrends/2007/report/groundlevelozone.pdf).
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Ozone Time Trends 1980-2003
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Ozone Formation Increases at Warmer Temperatures
Statistical Evidence from Measurements
Predictions from Reactive Chemical Transport Models
0
50
100
150
200
250
300
275 280 285 290 295 300 305 310Daily max T850 (K)
Dai
ly 1
-hr
max
ozo
ne (
ppb)
1980-1989: Slope=8.55 ppb/K
1990-1999: Slope=5.96 ppb/K
2000-2004: Slope=3.24 ppb/K
Los Angeles
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Decreasing Ozone Climate Penalty Can Be Understood Using An “Isopleth” Diagram
Solid black lines mark contours of constant ozone concentrations
43ppb
75ppb
Dashed line shows our emissions trajectory between 1990 - 2020
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Do Extreme Temperatures
Always Produce Extreme Ozone Concentrations?
Source: A. Steiner, A. Davis, S. Sillman, R. Owen, A. Michalak, and A. Fiore, “Observed Suppression of Ozone Formation at Extremely High Temperatures Due to Chemical and Biophysical Feedbacks”, PNAS, 107, P 19685-19690, 2010.
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Conclusions• Air pollution events driven by emissions as well as
meteorology – we don’t have emissions models that can predict extreme events (traffic jams, factory upsets, etc)
• Regional climate models must accurately predict wind speed and PBL height during low wind speed “extreme events” – either summer or winter events
• Regional climate models must accurately predict high and low extreme temperatures – either summer or winter events
• Ozone “Climate-Penalty” is shrinking over time, but it likely won’t go to zero and it may rebound
• Climate does not strongly affect annual-average PM, but effects on extreme events may be stronger
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EXTRA SLIDES
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Temperature Changes2000-06 vs. 2047-53
ΔTemperature Summer (oC) Δ Temperature Winter (oC)
Source: Z. Zhao, S. Chen, and M. Kleeman, “The Impact of Climate Change on Air Quality Related Meteorological Conditions in California – Part II: Present versus Future Time Simulation Analysis”, Climate Change, submitted, 2010.
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Humidity Changes (%)2000-06 vs. 2047-53
Source: A. Mahmud, M. Hixson, J. Hu, Z. Zhao, S.H. Chen, M.J. Kleeman, “Climate impact on airborne particulate matter concentrations in California using seven year analysis periods”, Atmos. Chem. Phys. Discuss., 10, 1–35, 2010.
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Ozone Climate Penalty Is Decreasing Over Time
0
2
4
6
8
10
1980 1990 2000 2010
ΔO3
/ Δ
Tem
pera
ture
(ppb
/K)
Emissions Year
Ozone Response to Temperature in the SoCAB (1980-2010)
Statistical Downscaling (Mahmud et al., 2008)
Model Perturbation (Kleeman, 2008)
Model Perturbation (Millsteinand Harley, 2009)
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Ozone Climate Penalty Doesn’t Go to Zero In the Future
0
1
2
3
4
5
6
1985 1990 1995 2000 2005 2010 2015 2020
ΔO3
/ ΔTe
mpe
ratu
re (p
pb/K
)
Emissions Year
Azusa
Claremont
Central LA
Long Beach
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Change in Population-Weighted PM Caused
by Climate
-2 -2 -4
2
-2 -1 -2 -2 -6 -5 -2 -3 -4 -5 -3
-50
-30
-10
10
30
50CA
0 0 -111
-5
4
-2 -2
0 -1 1 0 0 0 -1
-50
-30
-10
10
30
50SV
0 0
-2
5
-5
-1 0 0 1
-2
0
-1
-1
-2 -1
-50
-30
-10
10
30
50SJV
-2 -3 -3
2
-2
-1
-3 -2 -6 -4 -3 -3 -4 -6 -4
-50
-30
-10
10
30
50
TO
T M
AS
S
EC
OC
N(V
)
S(V
I)
N(-
III)
ME
TL
Dus
t
Shi
ppin
g
Woo
d S
mok
e
Die
sel
Com
bust
ion
Gas
olin
eC
ombu
stio
n
Mea
t Coo
king
Hig
h S
ulfu
rC
onte
nt F
uels
Mis
cella
neou
s
SoCAB
Fut
ure
chan
ge fr
om p
rese
nt-d
ay (
%)
PM2.5 category/species
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Climate Impact May Be Stronger on Severe Airborne Particle Events
Increase in Airborne Particle Concentrations During Future Extreme Events Due to Climate
Population Exposure During Extreme Events
6
-6-10
-32816
-31
8812
-28
2671910
-200-150
-100-50
0
50100
150200
CA
25
-14
8153540
-54
444739
-27
56354538
-200-150-100-50
050
100150200
SV
391624305753
-37
474949
-30
68475550
-200-150-100-50
050
100150200
SJV
Fu
ture
ch
an
ge
fro
m p
rese
nt-
da
y (%
)
-7-23-13-9
20-2
-34-5-5-6
-36
3
-7
4
-6
-200-150-100-50
050
100150200
TO
T M
AS
S
EC
OC
N(V
)
S(V
I)
N(-
III)
ME
TL
Dus
t
Shi
ppin
g
Woo
d S
mok
e
Die
sel
Com
bust
ion
Gas
olin
eC
ombu
stio
n
Mea
t Coo
king
Hig
h S
ulfu
rC
onte
nt F
uels
Mis
cella
neou
s
SoCAB
PM2.5 category/species
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Criteria Pollutant Emissions Reductions Associated With Climate Mitigation: AB32
Level 1 – Industrial
Level 2 – Electric Utilities & Natural Gas
Level 3 – Agricultural
Level 4 – On-road vehicles
Level 5 – Off-road vehicles
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AB32 Has Different Impact on Each Criteria Pollutant Emissions Rate
-18.0%
-16.0%
-14.0%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
PM EC OC NOx SOx ROG NH3
Perc
enta
ge Em
issio
n Ch
ange
from
BAU
Lvl 1: Industry
Lvl 2: Elec. & NG
Lvl 3: Agriculture
Lvl 4: On-road Mobile
Lvl 5: Other Mobile
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AB32 Reduces Population Exposure to PM2.5 as a Co-Benefit of GHG Mitigation
(a) Change in population-weighted PM2.5 in California
(b) Change in population-weighted PM2.5 in Los Angeles
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S-3-05: More Aggressive GHG Mitigation Strategies Have Bigger Co-Benefits
(a) Change in population-weighted PM2.5 in California
(b) Change in population-weighted PM2.5 in Los Angeles
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Climate Predictions For 2001 vs. 2050 Using 36 km Resolution
Source:: Tagaris E, Liao KJ, Delucia AJ, Deck L, Amar P, Russell AG, “Potential Impact of Climate Change on Air Pollution-Related Human Health Effects”, Environ. Sci. Technol., 43, 4979-4988, 2009.
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Source:: Millstein, D.E., and Harley, R.A. “Impact of Climate Change on Photochemical Air Pollution in southern California”, Atmos. Chem. Phys., 9, 3745-3754, 2009.
Climate Predictions For 2001 vs. 2050 Using Averaged Meteorology