The Intersection of Climate, Air Quality, and Vegetation

Harvard Climate SeminarApril 10, 2014

Colette L. HealdXuan Wang, David A. Ridley, Amos P.K. Tai, Maria Val Martin

Climate Forcing

Climate Feedbacks

Altering Ecosystem Health (Nutrients, Toxics)

Emissions, Removal

AIR QUALITY

VEGETATION CLIMATE

Lots of interesting

stuff I won’t talk about

Air Pollution is a Significant Public Health Concern(more premature deaths per year from PM than car accident fatalities in the US)

Particulate Matter (PM) is estimated to be the leading environmental cause of premature mortality. Overall , PM is the 3rd and 9th most deadly risk factor.

Ozone is a risk factor for aging populations (i.e. Europe)

3.5M deaths/yr

3.1M deaths/yr

[Lim et al., 2012]

Ozone and PM Warm and Cool the ClimatePM is the Leading Source of Uncertainty in Global Climate

Forcing

[IPCC, 2013]

Ozone and PM also Alter Ecosystem Health

ACID RAINCROP DAMAGE FERTILIZATION

Mahowald et al., (2011) suggests biogeochemical feedbacks from aerosols

constitute a large climate cooling

Climate Forcing

Climate Feedbacks

Altering Ecosystem Health (Nutrients, Toxics)

Emissions, Removal

AIR QUALITY

VEGETATION CLIMATE

BC

Crops

DustOzone

IPCC AR5 Estimates that Black Carbon is the 2nd Largest Warming Agent in the Atmosphere.

(but that’s not what models say)

How can these be

reconciled?

Absorption ↑Lifetime ↓

Aging

Emission

Observations Suggest That Models Overestimate BC

[Koch et al., 2009]

AeroCom models overestimate BC over Americas by factor ~8, overestimate remote HIPPO BC by factor ~5.

[Schwarz et al., 2010]

AeroCom means in black, HIPPO obs in colourObs in black, AeroCom models in colour

New Model Aging Processes for BC

Hydro-phobic

Hydro-philic

Old Assumptions

1.15 days

Hydro-phobic

Hydro-phobic

New Assumptions

Anthropogenic

Biomass burning

Hydro-philic

Hydro-philic

Sulfate, etc.

Organic components

4 hours(also increase fraction emitted as

hydrophillic to 70%)

(Moteki et al., 2007; Moffet et al., 2009; Friedman et al.,2009; Liu et al., 2010; Akage et al.,2012; Lack et al.,2012; Shamjad et al., 2012; Schwarz et al.,2008, Moteki et al., 2007; Moffet and Prather, 2009),

k = 1/τ = a [SO2] [OH] + b

Impact of New Model Aging Processes on Simulation of BC

Good simulation near source (with or without new aging).Modified aging scheme results in shorter lifetime and better simulation of low concentrations in remote locations. Vastly

better than AeroCom. Generally within a factor of 2.

HIPPO Continental (Near-Source)

Good

Better

Still Bad

Considering Absorption Enhancement and Brown CarbonSmaller size, wider size range

Absorption CoefficientMie calculation

Absorption enhancement from

coating (AE=1.1)

Absorption Coefficient

Absorption enhancement from

coating (AE=1.5)

Larger size, narrower size range

Mie calculation

Brown Carbon

Aromatic SOA

50% of POA Biomass/biofuel

Absorption Coefficient

Get RI from field measurements

Mie calculation

Anth BC

BB BC

(Akage et al., 2012; Schwarz et al., 2006; 2007; 2008; Lack et al., 2012; Dubovik et al., 2002; Shamjad et al., 2012; Moffet et al., 2009; Knox et al., 2009; Kondo et al., 2011; Lack et al., 2012; Moffet and Prather, 2009; Bond et al., 2006; Cappa et al., 2012)

Also “Most Absorbing” Simulation : Set AE=2 and standard aging mechanism (longer lifetime)

Measurements Still Suggest Absorption is Underestimated

Better able to capture the spectral AAOD with our “best” simulation (including BrC), but still biased low (especially in biomass burning regions).

Can “scale up” our model to match observations (Bond et al., 2013) – emissions or optics?

*AAOD product here using lev2 SSA with lev1.5 AOD

Our Work Suggests Smaller BC DRF Required to Match All Observational Constraints

Brown Carbon contributes 35% of the warming from carbonaceous aerosols.BC DRF is less than methane and tropospheric ozone.

Suggests that controlling BC is less effective for climate mitigation.[Wang, et al., in prep]

Dust From North Africa

Air Quality (local & Americas)

Ocean Fertilization (C cycle)

Nutrient Supply(terrestrial productivity)

Relationship is breaking down?

Observations from Barbados suggest that increasing trend in dust from 1960s to 1980s may have reversed. Impact of greening of the Sahel on productivity of the Amazon?

Tropical Cyclone Genesis

[Mahowald et al., 2009]

Dust @ BarbadosNegative Sahel Precip Anomaly

Previous year’s Precip. Index

Sum

mer

dus

t con

c.

[Prospero and Lamb, 2003]

North African Dust Driven by Sahelian Precipitation

Why is Dust From North Africa Decreasing?

African dust has been decreasing year-round at both source and down-wind by ~10%/decade from 1982-2008, with

substantial interannual variability. Model captures this! Use model to assess that trends & variability largely from surface

winds NOT vegetation changes.

Fixed meteorologyFixed vegetationFixed surface winds

Vegetation Changes Are NOT Responsible for the Recent Trend in Dust From Africa

Vegetation(AVHRR NDVI)

Surface Winds(MERRA)

(2002-2006) – (1982-1986)

Regions of substantial

dust decrease

(black contours)

[Ridley et al., ACPD, 2014]

Possible Mechanism: Aerosols Changing Aerosols (via Climate)?

Suggests that this may be a short-term trend. Let’s wait and see!

↓ anthropogenic aerosols ↑ SST

Northward shift of ITCZ

↓surface winds↓ dust emission

[Booth et al., 2012; Ackerley et al., 2011; Evan et al., 2009; Folland et al., 1986; Broccoli et al, 2006; Doherty et al., 2012]

↑precipitation↑greening Sahel

Considering the Impact of Air Pollution and Climate on Global Food Security (in an era of rising food demand)

tolerant

sensitive

AIR POLLUTION(Snap peas damage due to ozone exposure)

CLIMATE(Illinois heat wave summer 2012)

Estimating the Climate and Air Quality Impacts on Global Crop Productivity From Historical Record

Rel

ativ

e Y

ield

[Mills et al. 2007]

Wheat

Ozone exposure (ppm-hour)

Tmax

Tmean

Thigh

Tbase

Day since 1 June

°C

based on Butler and Huybers

[2013]

climate ozone(2050) (2000)P P

Estimate yield-O3 relationship from literature estimate of O3 exposure

indices

Estimate yield-climate relationship from a MLR of 1961-2010 FAO crop yields and NCEP/NCAR

reanalysis

How Will Drivers Change in the Future?

2000-2050 changes in maximum daily 8-h average (MDA8) O3 (ppbv)

2000-2050 changes in surface air temperature (K)

Community Earth System Model (CESM 1.1) Simulation

Warming climate, similar in both scenarios. Ozone projections reflect regional pollution control, but RCP8.5 includes large increases in methane (increases O3 background)

stippling=significant

Impacts of Climate Change and Ozone Pollution on Total Crop Production

Future crop productivity very sensitive to ozone pollution & climate change. Uncertainty associated largely with future air quality.

Pollution effect: +0.22 ×1015 kcal

Climate effect: -0.80 ×1015 kcalCombined effect: -0.64 ×1015 kcal

Pollution effect: -0.26 ×1015 kcal

Climate effect: -0.81 ×1015 kcal Combined effect: -1.07 ×1015 kcal

RCP4.5

RCP8.5

106 kcal ha-1-50 -20 -10 -5 -2 -1 0 1 2 5 10 20 50

The rate of undernourishment

in developing countries in 2050

nearly doubles due to climate and

ozone.

Impact of Ozone Pollution and Climate Change on Crop Production Around the World

[Tai, val Martin and Heald, submitted]

But Wait, There are Known Large Summertime Biases in the Simulation of Surface Ozone in Eastern US and Europe

[Lamarque et al., 2012]

[Fiore et al., 2009]

[Lapina et al., 2014]

EMEP

The Importance of Getting Dry Deposition of Ozone Right

Correcting bugs in dry deposition parameterization in land model significantly reduces some the surface O3 bias…. So we thought about whether there might be other issues…

[val Martin et al., GRL, in press]

CLM (and MOZART) dry deposition schemes fail to account for leaf area density in calculation of leaf cuticular resistance and stomatal resistance

Reducing stomatal conductance drastically improves simulation of dry deposition velocity and surface concentrations of ozone. Realistic? Implications for carbon and hydrological cycle?

How Vegetation Phenology Is Controlling Predictions of Surface O3

Observations (ppb)

Harvard Forest

RMNPOriginal SchemeCorrected SchemeOptimized SchemeObservations

CONCLUSIONS

AQ → climate: Warming from BC overestimated in AR5. Not as effective a mitigation strategy for climate change.

AQ → climate → AQ: Recent decrease in North African dust due to stilling of winds (not vegetation), that we speculate is

due to decreasing anthropogenic aerosols from the U.S.

AQ + climate → vegetation: Together AQ & climate substantially threaten global food security

Vegetation → AQ: Vegetation seasonality & density controls surface O3 in Eastern U.S. and Europe (and

Amazon)