Direct Observations of Aerosol Effects on Carbon and Water Cycles Over Different Landscapes Hsin-I Chang Ph D student Department of Atmospheric Sciences Advisor: Dr. Dev Niyogi Department of Atmospheric Sciences/Agronomy Purdue University

Kiran Alapaty, UNC Chapel Hill, currently with National Science Foundation Fitz Booker, USDA/ ARS, Air Quality-Plant Growth and Development Unit, NC Fei Chen, National Center for Atmospheric Research, Boulder Ken Davis, Department of Meteorology, Penn State University, University Park, PA Lianhong Gu, Oak Ridge National Laboratory, TN Brent Holben, GSFC, NASA, Greenbelt, MD Teddy Holt, N. C. State Univ and Naval Research Laboratory, Monterey, CA Tilden Meyers, ATDD/NOAA, Oak Ridge, TN Walter C. Oechel, San Diego State University Roger A. Pielke Sr. and Toshi Matsui Colorado State University Randy Wells, Department of Crop Science, N. C. State University, Raleigh, NC Kell Wilson, ATDD/NOAA, Oak Ridge, TN Yongkang Xue, Department of Geography, UCLA, Los Angeles, CA Collaborators:

Outline: Introduction Importance and Hypothesis Data and Methodology Results and Discussion Summary Future Work

- AEROSOLS AFFECT THE RADIATIVE FEEDBACK OF THE ENVIRONMENT -Majority of the studies have focused on the ‘temperature effects’ =>whether aerosols cause cooling or warming effect in the regional climate. -In this study we propose that: Aerosols also have a significant biogeochemical feedback on the regional landscapes, and should be considered in both carbon and water cycle studies

Why would aerosols affect biogeochemical pathways? Total solar radiation = (Diffuse + Direct) solar radiation For increased Cloud Cover or Increased Aerosol Loading, Diffuse Component Increases => changes the DDR (Diffuse to Direct Radiation Ratio) Hypothesis: Increase in DDR will impact the Terrestrial Carbon and Water Cycles through Transpiration and Photosynthesis changes (Transpiration is the most efficient means of water loss from land surface; Photosynthesis is the dominant mechanism for terrestrial carbon cycle)

Data : Need simultaneous observations of carbon and water vapor fluxes, radiation (including DDR), and aerosol loading. Carbon, Water vapor flux and plant information – Ameriflux Carbon, Water vapor flux and plant information – Ameriflux Radiation (including DDR) information from Ameriflux or NOAA Surface Radiation (SURFRAD) sites Radiation (including DDR) information from Ameriflux or NOAA Surface Radiation (SURFRAD) sites Aerosol loading information from NASA Aerosol Robotic Network (AERONET) Aerosol loading information from NASA Aerosol Robotic Network (AERONET)

Study sites Six sites available across the U.S. that have information on the required variables for our study (AOD,diffuse radiation and latent heat flux). Walker Branch, TN (mixed forest 2000) Barrow, AK (grassland 99) Bondville, IL (agriculture, C3 / C4, ) Willow Creek, WI Lost Creek, WI (mixed forest,00,01) Ponca, OK (wheat 98,99)

Hypothesis to be tested from the observational analysis : Increase in the aerosol loading could increase CO2 and latent heat flux at field scales This would indicate a more vigorous terrestrial carbon cycle because of aerosol interactions This would indicate a more vigorous terrestrial carbon cycle because of aerosol interactions This would also indicate potential for changes in the terrestrial water cycle because of aerosol loading This would also indicate potential for changes in the terrestrial water cycle because of aerosol loading

Does DDR Change Cause Changes in the CO2 Flux at Field Scale? Walker Branch Forest Site -CO2 flux into the vegetation (due to photosynthesis) increases with increasing radiation -For a given radiation, CO2 flux is larger for higher DDR Rg-total radiation Rd-diffuse radiation negative values indicate CO2 sink (into the vegetation)

Effect of DDR on field scale CO2 Flux Increase in DDR appears to increase the observed CO2 flux in the field measurements. Does DDR Change Cause Changes in the CO2 Flux at Field Scale? Yes! Changes in CO2 flux Normalized for changes in global Radiation versus Diffuse Fraction

Do clouds affect CO2 flux at Field Scale? - Yes, clouds appear to affect field scale CO2 fluxes significantly. -CO2 flux into the vegetation (due to photosynthesis) is larger for cloudy conditions

Do Aerosols affect field scale CO2 Flux? - Increase in AOD (no cloud conditions) causes increase in DDR (diffuse fraction) - CO2 flux into the vegetation (due to photosynthesis) is larger for higher AOD conditions - Aerosol loading appears to cause field scale changes in the CO2 flux

Forests Are these results true for different landscapes? CroplandsGrasslands For Forests and Croplands, aerosol loading has a positive effect on CO2 flux, where there shows a CO2 flux source at Grassland sites.

Hypothesis for LHF-aerosol relation: At high vegetation LAI (leaf area index): LHF is mainly due to transpiration; LHF is mainly due to transpiration; with increasing aerosols,diffuse radiation increases and air / leaf temperature decreases, with increasing aerosols,diffuse radiation increases and air / leaf temperature decreases, => increase in transpiration and thereby increase LHF => increase in transpiration and thereby increase LHF At low vegetation LAI: At low vegetation LAI: LHF is mainly due to evaporation ; LHF is mainly due to evaporation ; with increasing aerosols,diffuse radiation increases, and air / leaf temperature decreases, => reduce the evaporation and therefore LHF decreases. => reduce the evaporation and therefore LHF decreases.

Clustering AOD-LHF relation into different landscapes. Forest site CroplandGrassland (LHF values opposite in sign) Latent heat flux appears to generally decrease with increasing Aerosol Optical Depths for most of the studied sites.

Low LAI case (LAI < 2.5) LHF decrease with aerosol loading High LAI case (LAI >3) LHF increase with aerosol loading Walker Branch (Forest site): Observed data analyses:

Low LAI caseHigh LAI case Bondville (soy bean site(C3)): However, analyzed results vary for different landscapes For higher LAI, the AOD –ve dependence seems to be decreasing

Summary for water cycle study: Forest: - High LAI: LHF increase with AOD - Low LAI: LHF decrease with AOD - Low LAI: LHF decrease with AOD need to consider Leaf effect for the flux change. Corn: LHF decrease with AOD; Leaf area changes have more influence on LHF compare to Air Temperature and Soil Moisture. Soybean: LHF decrease with AOD; analyses found that Soil Moisture may have influence on the decreasing trend of Latent Heat Flux- without Soil Moisture effect, LHF increase with aerosol loading. Grassland: LHF increase with AOD; not considering leaf effect. (Soil Moisture data not available)

Conclusions: Aerosols affect land surface processes Results confirmed for different canopy conditions (mixed forests, corns, soybeans, winter wheat and grasslands). Results confirmed for different canopy conditions (mixed forests, corns, soybeans, winter wheat and grasslands). CO 2 sink increases with increasing aerosol loading over forests and croplands (both C3 and C4) CO 2 source increases with increasing aerosol loading over grasslands Water Vapor Flux generally decreases with increasing aerosol loading Exceptions were one grassland, and high LAI forest sites Exceptions were one grassland, and high LAI forest sites

Design of experiments Design configuration: Need to design confounding Environmental Confounding: (1) crop site: USDA Raleigh, Purdue AG Center (2) forest site: ChEAS (?) Radiation decreases in quantity, changing quality and spectral changes and higher DDR. Changes in temperature will change in VPD, evaporation/transpiration, soil moisture, emmisivity and albedo, etc. Experiments: (1) for crops: use high/low diffuse radiation shed; change soil moisture stress and stress from temperature and humidity => need to design special chambers. (2) for forest: repeat similar experiments for crops and need to examine vertical profiles => responses in different vertical levels may be important.

Related work: Analysis for AOD – LHF effects is still underway. (need to consider interaction terms such as LAI, soil moisture) Leaf and Canopy scale measurements of CO2 and Water Vapor Flux for plants grown under different soil moisture conditions at USDA Facility in Raleigh. LI6400 CO2 / H2O Flux system

Related work: Effect of Diffuse Radiation (Clouds and Aerosols) on Plant Scale Response Modeling of the plant scale response for changes in Diffuse Radiation (with Dr. Booker and Dr. Wells) Potted plants were grown in 2 sheds with different diffuse radiation screens and CO2 / H2O Exchange Measured

Direct and diffuse radiation shed

Ongoing and Future work: Regional Analysis of DDR Changes on Latent Heat Fluxes using satellite (MODIS) dataset. Regional Analysis of DDR Changes on Latent Heat Fluxes using satellite (MODIS) dataset. Continue on GEM-RAMS Modeling Systemfor isolating the effects of different variables in understanding the aerosol feedbacks on the land surface response. Continue on GEM-RAMS Modeling System for isolating the effects of different variables in understanding the aerosol feedbacks on the land surface response.

Thank you

Bondville (corn site(C4)): Low LAI case High LAI case LHF increase with aerosol loading up to certain level.

AOD-LHF relation after accounting for both leaf and air temperature effects: soy bean site corn site Compare with previous slides, Latent heat fluxes still decrease with aerosol loading without leaf and temperature effects.

Accounting for Soil Moisture effect: Corn SiteSoybean Site  For both high and low SM conditions, LHF decreases with aerosol loading for agricultural sites (not shown).  With no Soil Moisture effect, Latent Heat Flux increases with aerosol at Soybean site.

Glazing material treatment effects on average photosynthetic photon flux density (PPDF) at upper canopy height between h (EST) during the experimental period. The ratio of diffuse PPFD radiation to total PPDF radiation is also shown. Values are means ± SE. Values followed by a different letter were statistically significantly different (P ≤ 0.05). Glazing Material ParameterAmbientClearDiffusing PPFD (µmol m -2 s -1 )958 ± 6 a840 ± 6 b755 ± 5 c Diffuse: Total0.389 ± a0.415 ± b

Soybean biomass and yield responses to growth under Clear and Diffusing glazing materials (mean ± SE). Plants were harvested for determination of biomass (Biomass) at 88 days after planting (DAP), and for determination of seed yield (Yield) at 153 DAP. Values in parenthesis indicate percent change from the Clear treatment. Statistics: P ≤ 0.1 (†). Glazing Material HarvestParameterClearDiffusing Biomass Height (cm)55.6 ± ± 1.4 Branch number (plant -1 )17.3 ± ± 1.4 Leaf dry mass (g plant -1 )45.4 ± ± 3.0 Main stem dry mass (g plant -1 )19.2 ± ± 1.5 Branch dry mass (g plant -1 )51.7 ± ± 3.9 (+22%) † Pod dry mass (g plant -1 )67.3 ± ± 8.0 Root mass (g plant -1 )30.1 ± ± 2.6 Total dry mass (g plant -1 )213.7 ± ± 15.2 Main stem leaf area (m 2 plant -1 )0.19 ± ± 0.01 Branch leaf area (m 2 plant -1 )1.21 ± ± 0.08 (+16%) † Total leaf area (m 2 plant -1 )1.40 ± ± 0.08 (+15%) † Yield Pod number (plant -1 )397 ± ± 32 Seed mass (g plant -1 )173 ± ± 15 Mass per seed (g)0.20 ± ± 0.01 Stem mass (g plant -1 )43 ± 449 ± 4

Net photosynthesis (A) of upper canopy leaves and whole-plants treated with either Clear or Diffusing glazing materials (mean ± SE). Net photosynthesis of upper canopy leaves on four plants per treatment was measured weekly between 48 and 105 DAP (seven occasions). In addition, whole-plant A of three sets of three plants was measured on 56 DAP. Treatment effects on A were not statistically significant. Glazing Material ClearDiffusing Upper canopy leaves (µmol m -2 s -1 ) 28.4 ± ± 2.6 Whole-plant (µmol plant s -1 ) 14.7 ± ± 0.7