internal variability in projections of climate change ......internal variability in projections of...
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Internal variability in projections of climate change impacts on air quality and health
NCAR Large Ensembles WorkshopJuly 26, 2019
Fernando Garcia Menendez, James East, Bret Pienkosz –North Carolina State UniversityRebecca Saari- University of WaterlooErwan Monier - University of California, Davis
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Climate change impacts on air quality
Projected changes in 2100
Air Surface Temperature:
Precipitation:
Climate change impacts air quality through many coupled mechanisms:
→ Atmospheric chemistry→ Atmospheric ventilation→ Natural emissions→ Deposition rates
“Climate penalty” on air quality
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Climate change impacts on air quality
Climate change impacts air quality through many coupled mechanisms:
→ Atmospheric chemistry→ Atmospheric ventilation→ Natural emissions→ Deposition rates
“Climate penalty” on air quality
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Fourth National Climate Assessment
[1] Nolte, et al., 2018, Air Quality. In Impacts, Risks, and Adaptation in the US: NCA2018
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Projecting climate penalty on air quality
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Focus on climate-induced impact: Δ Climate + Δ Emissions → Δ Air Quality-------------------------------------------------------
Modeling framework:U.S. EPA CIRA projections[1]
MIT IGSM: Policy and climate projections[2]
CAM-Chem: Global atmospheric chemistryBenMAP: Health and economic impacts -------------------------------------------------------
Emissions held at start-of-century levelsSimulated periods: start (2000), middle (2050), and end (2100) of 21st century
Ensemble simulations:
1. Emissions-scenario uncertainty: Reference: No policy
2100 RF = 9.7 W/m2
Policy 4.5: Stabilization2100 RF = 4.5 W/m2
Policy 3.7: Stringent stabilization2100 RF = 3.7 W/m2
2. Natural variability 30-year simulations 5 different initializations
3. Climate model response Climate sensitivity =
2.0°C, 3.0°C or 4.5°C
[1] Waldhoff et al., 2015, Climatic Change[2] Monier et al., 2015, Climatic Change
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Ensemble-mean projections
2100 Climate Penalty
∆ PM2.5 (µg/m3)
No Policy Climate Policy
5[1] Garcia-Menendez et al., 2015, ES&T
∆ O3 (ppb)
U.S. population-weighted annual PM2.5
Avoided U.S. deaths under climate policy:2050: > 10,000 (4,000 - 22,000)2100: > 50,000 (19,000 - 95,000)
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Ensemble-mean projections
6[1] Garcia-Menendez et al., 2015, ES&T
U.S. population-weighted annual PM2.5
Avoided U.S. deaths under climate policy:2050: > 10,000 (4,000 - 22,000)2100: > 50,000 (19,000 - 95,000)
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[1] Garcia-Menendez et al., 2017, GRL
2100 Reference scenario O3 season climate penalty (Δ 8h-max ppb)
Natural variability
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[1] Garcia-Menendez et al., 2017, GRL
2100 Reference scenario O3 season climate penalty (Δ 8h-max ppb)
Natural variability
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[1] Garcia-Menendez et al., 2017, GRL
2100 Reference scenario O3 season climate penalty (Δ 8h-max ppb)
Natural variability
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Natural variability in O3 penalty projections
Averaging period (years)
2100 Reference scenario O3 season climate penalty (Δ 8h-max ppb)
[1] Garcia-Menendez et al., 2017, GRL
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Natural variability in PM2.5 penalty projections
11[1] Pienkosz et al., 2019, Earth’s Future
2100 REF-scenario annual PM2.5 climate penalty (Δ µg m-3)
5 10 15 20 25 30-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4 Northeast
Number of years
5 10 15 20 25 30-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3 Population-weighted
Number of years
∆ O3
∆ PM2.5
Relative change with respect to start-of-century mean
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Projections of climate penalty on air quality
12[1] Garcia-Menendez, et al., 2017, GRL[2] Pienkosz et al., 2019, Earth’s Future
2100 REF-scenario climate penalty on population-weighted concentrations in this ensemble:
O3: • + 3.2 ppb• 15 years for ± 1.0 ppb margin of error
(95% confidence)
PM2.5: • + 1.5 μg/m3
• 10 years for ± 0.5 μg/m3 margin of error (95% confidence)
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2100 REF-scenario climate penalty on population-weighted concentrations in this ensemble:
O3: • + 3.2 μg/m3
• 15 years for ± 1.0 ppb margin of error (95% confidence)
PM2.5: • + 1.5 μg/m3
• 10 years for ± 0.5 μg/m3 margin of error (95% confidence)
2100 REF
[1] Garcia-Menendez, et al., 2017, GRL[2] Pienkosz et al., 2019, Earth’s Future
Projections of climate penalty on air quality
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2100 REF-scenario climate penalty on population-weighted concentrations in this ensemble:
O3: • + 3.2 μg/m3
• 15 years for ± 1.0 ppb margin of error (95% confidence)
PM2.5: • + 1.5 μg/m3
• 10 years for ± 0.5 μg/m3 margin of error (95% confidence)
2050 REF
[1] Garcia-Menendez, et al., 2017, GRL[2] Pienkosz et al., 2019, Earth’s Future
Projections of climate penalty on air quality
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2100 REF-scenario climate penalty on population-weighted concentrations in this ensemble:
O3: • + 3.2 μg/m3
• 15 years for ± 1.0 ppb margin of error (95% confidence)
PM2.5: • + 1.5 μg/m3
• 10 years for ± 0.5 μg/m3 margin of error (95% confidence)
2100 P45
[1] Garcia-Menendez, et al., 2017, GRL[2] Pienkosz et al., 2019, Earth’s Future
Projections of climate penalty on air quality
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Ensemble-mean projections
16[1] Brown-Steiner et al., 2018, ACP
Increasing temporal averaging scales
1 year 5 years 10 years 20 years
Likelihood (%) that ozone estimate exceeds 0.5 ppb threshold due to meteorological variability in the present-day simulation:
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Ensemble-mean projections
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Increasing temporal averaging scales
1 year 5 years 10 years 20 years
Increasing spatial averaging scales
Increasing threshold
9 × 9 grid box
1 ppb threshold
Likelihood (%) that ozone estimate exceeds 0.5 ppb threshold due to meteorological variability in the present-day simulation:
[1] Brown-Steiner et al., 2018, ACP
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[1] Saari et al., 2019, ES&T
Projections of health and economic impacts
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End of century
Midcentury
Annual mortalities avoided by reducing climate penalty on PM2.5 under policy
Annual benefits from reducing climate penalty on PM2.5 and O3 under policy
Econ
omic
impa
cts
Hea
lth im
pact
s
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[1] Saari et al., 2019, ES&T
Projections of co-benefits of climate policy
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Effect of uncertainties on percent of policy costs offset by reducing health risks from climate penalty
2050 2100
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Range of climate penalty projections
Climate Sensitivity Emissions Scenario Natural Variability
2050
2100
ppb
Mean range of climate-induced O3 change for each source of uncertainty
20[1] East et al., in prep.
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Range of climate penalty projections
Climate Sensitivity Emissions Scenario Natural Variability
2050
2100
µg/m3
Mean range of climate-induced PM2.5 change for each source of uncertainty
21[1] East et al., in prep.
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Projections of climate change impacts on air quality
Examining natural variability can inform projections of air quality under climate change, related health impacts, and climate policy assessments
Air quality considerations:• Location and period of interest• High concentrations and extreme air pollution• Varying emissions and chemical composition• Structural uncertainty in climate and chemistry models• Simulations with interactive chemistry• PM2.5 composition• Complex treatment of SOA chemistry• Natural emission sources (wildfires and dust)• Increased resolution
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Thank youAcknowledgements:
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James East, Bret Pienkosz
Rebecca Saari
Erwan Monier
Noelle Selin, Benjamin Brown-Steiner
Simone Tilmes, Louisa Emmons