The Intersection of Climate, Air Quality, and Vegetation Harvard Climate Seminar April 10, 2014 Colette L. Heald Xuan 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 3 rd and 9 th 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 Climate PM is the Leading Source of Uncertainty in Global Climate Forcing [IPCC, 2013]

Ozone and PM also Alter Ecosystem Health ACID RAIN CROP 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 Dust Ozone

IPCC AR5 Estimates that Black Carbon is the 2 nd 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 colour Obs in black, AeroCom models in colour

New Model Aging Processes for BC Hydro- phobic Hydro- philic Old Assumptions 1.15 days Hydro- phobic New Assumptions Anthropogenic Biomass burning 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 [SO 2 ] [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 Carbon Smaller size, wider size range Absorption Coefficient Mie 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] Barbados Negative Sahel Precip Anomaly Previous year’s Precip. Index Summer dust conc. [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 , with substantial interannual variability. Model captures this! Use model to assess that trends & variability largely from surface winds NOT vegetation changes. Fixed meteorology Fixed vegetation Fixed surface winds

Vegetation Changes Are NOT Responsible for the Recent Trend in Dust From Africa Vegetation (AVHRR NDVI) Surface Winds (MERRA) ( ) – ( ) 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 Relative Yield [Mills et al. 2007] Wheat Ozone exposure (ppm-hour) T max T mean T high T base Day since 1 June °C°C based on Butler and Huybers [2013] Estimate yield-O 3 relationship from literature estimate of O 3 exposure indices Estimate yield-climate relationship from a MLR of FAO crop yields and NCEP/NCAR reanalysis

How Will Drivers Change in the Future? changes in maximum daily 8-h average (MDA8) O 3 (ppbv) 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 O 3 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: ×10 15 kcal Climate effect: ×10 15 kcal Combined effect: ×10 15 kcal Pollution effect: ×10 15 kcal Climate effect: ×10 15 kcal Combined effect: ×10 15 kcal RCP4.5 RCP kcal ha

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] [Murazaki and Hess, 2006] [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 O 3 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 O 3 Observations (ppb) Harvard Forest RMNP Original Scheme Corrected Scheme Optimized Scheme Observations

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 O 3 in Eastern U.S. and Europe (and Amazon)