Direct observations of aerosol effects on carbon and water cycles over different landscapes
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Direct Observations of Aerosol Effects on Carbon and Water Cycles Over Different Landscapes. Hsin-I Chang Ph D student Department of Atmospheric Sciences Email: Advisor: Dr. Dev Niyogi Department of Atmospheric Sciences/Agronomy Email:

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Direct Observations of Aerosol Effects on Carbon and Water Cycles Over Different Landscapes

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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, TNWalter C. Oechel, San Diego State University

Roger A. Pielke Sr. and Toshi Matsui Colorado State UniversityRandy 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


  • Introduction

  • Importance and Hypothesis

  • Data and Methodology

  • Results and Discussion

  • Summary

  • Future Work


  • 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)


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

  • Radiation (including DDR) information from Ameriflux or NOAA Surface Radiation (SURFRAD) sites

  • 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).

Willow Creek, WI

Lost Creek, WI

(mixed forest,00,01)

Bondville, IL (agriculture, C3 / C4, 98-02)

Ponca, OK

(wheat 98,99)

Walker Branch, TN (mixed forest 2000)

Barrow, AK (grassland 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 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

Does DDR Change Cause Changes in the CO2 Flux at Field Scale?


Increase in DDR appears to increase the observed CO2 flux in the field measurements.

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


Are these results true for different landscapes?



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;

    with increasing aerosols,diffuse radiation increases and air / leaf temperature decreases,

    => increase in transpiration and thereby increase LHF

At low vegetation LAI:

LHF is mainly due to evaporation;

with increasing aerosols,diffuse radiation increases, and air / leaf temperature decreases,

=> reduce the evaporation and therefore LHF decreases.

Clustering AOD-LHF relation into different landscapes.

Forest site



(LHF values opposite in sign)

Latent heat flux appears to generally decrease with increasing Aerosol Optical Depths for most of the studied sites.

Observed data analyses:

Walker Branch (Forest site):

Low LAI case (LAI < 2.5)

LHF decrease with aerosol loading

High LAI case (LAI >3)

LHF increase with aerosol loading

However, analyzed results vary for different landscapes

Bondville(soy bean site(C3)):

Low LAI case

High LAI case

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

    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)


  • Aerosols affect land surface processes

    • Results confirmed for different canopy conditions (mixed forests, corns, soybeans, winter wheat and grasslands).

  • CO2sink increases with increasing aerosol loading over forests and croplands (both C3 and C4)

  • CO2 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

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:

LI6400 CO2 / H2O Flux system

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.

Related work:

Potted plants were grown in 2 sheds with different diffuse radiation screens and CO2 / H2O Exchange Measured

  • 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)

Direct and diffuse radiation shed

Ongoing and Future work:

  • 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.

Thank you

Bondville (corn site(C4)):

High LAI case

LHF increase with aerosol loading up to certain level.

Low LAI case

AOD-LHF relation after accounting for both leaf and air temperature effects:

corn site

soy bean site

Compare with previous slides, Latent heat fluxes still decrease with aerosol loading without leaf and temperature effects.

Accounting for Soil Moisture effect:

Corn Site

Soybean 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 0800-1600 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).

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 (†).

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.

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