Characterization of Aerosol Physical, Optical and Chemical Properties During the Big Bend Regional Aerosol and Visibility Observational Study (BRAVO) Jenny.

Slides:



Advertisements
Similar presentations
Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.
Advertisements

Optical Properties of Aerosol Particles Introduction Atmospheric aerosol particles play a significant role in determining Earth's climate, through their.
A Dictionary of Aerosol Remote Sensing Terms Richard Kleidman SSAI/NASA Goddard Lorraine Remer UMBC / JCET Short.
Multiwavelength Photoacoustic Measurements of Light Absorption and Scattering by Wood Smoke More Specific Title: Evidence for light absorption by organic.
1 Recent PM 2.5 Trends in Georgia André J. Butler Mercer University EVE 290L 14 April, 2008.
Xuan Wang and Colette L. Heald 7th International GEOS-Chem User’s Meeting, May 5, 2015 This work is funded by U.S. EPA Simulating Brown Carbon and its.
Regional Air Quality Modeling Patrick Barickman, Air Quality Modeler Tyler Cruickshank, Meteorologist/Modeler Utah Department of Environmental Quality.
BRAVO - Results Big Bend Regional Aerosol & Visibility Observational Study Bret Schichtel National Park Service,
Ben Kravitz Tuesday, November 10, 2009 AERONET. What is AERONET? AErosol RObotic NETwork Worldwide collection of sun photometers.
Radiative Effects of Atmospheric Aerosols and Regional Haze Jin Xu DAS Science Talk February 17, 2004.
IMPROVE Report 2006 L. Debell, K. Gebhart, B. Schichtel and W. Malm.
Presented At AMS Meeting, Long Beach, CA, 2003 Aerosol Phase Function And Size Distributions From Polar Nephelometer Measurements During The SEAS Experiment.
Aerosols and climate Rob Wood, Atmospheric Sciences.
Typically have a higher organic content than coarse particles Also contain soluble inorganics: NH 4 +, NO 3 -, SO 4 2- A bimodal peak is often observed.
Black Carbon:Global Budget and Impacts on Climate.
References: Acidic Deposition:State of Science and Technology (report 24) 1990 Visibility: Existing and Historical.
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.
Assessing Air Quality Using USDA Shadow-band Radiometers James Slusser USDA UV-B Monitoring and Research Program Natural Resource Ecology Laboratory Colorado.
Investigation of Decadal Changes in Aerosol and Asthma Sponsors: National Aeronautics and Space Administration (NASA) NASA Goddard Space Flight Center.
Accent Plus Symposium, Urbino, Italy, Sep2013 Observations of Enhanced Black Carbon radiative forcing over an Urban Environment A.S.Panicker, G.
Application of Satellite Data to Particulate, Smoke and Dust Monitoring Spring 2015 ARSET - AQ Applied Remote Sensing Education and Training – Air Quality.
Now That I Know That… What Do I Do? (Analyzing your Microtop Solar Radiometry Data)
Effects of Pollution on Visibility and the Earth’s Radiation Balance John G. Watson Judith C. Chow Desert Research Institute Reno,
Reason for Doing Cluster Analysis Identify similar and dissimilar aerosol monitoring sites so that we can test the ability of the Causes of Haze Assessment.
A Modeling Investigation of the Climate Effects of Air Pollutants Aijun Xiu 1, Rohit Mathur 2, Adel Hanna 1, Uma Shankar 1, Frank Binkowski 1, Carlie Coats.

Mixing State of Aerosols: Excess Atmospheric Absorption Paradox Shekhar Chandra Graduate Student, EAS Term Paper Presentation for EAS-6410.
Aerosol Extinction Assessment and Impact on Regional Haze Rule Implementation Douglas Lowenthal Desert Research Institute Pat Ryan Sonoma Technology, Inc.
CHARACTERIZATION OF AEROSOLS BASED ON THE SIMULTANEOUS MEASUREMENTS M. Nakata, T. Yokomae, T. Fujito, I. Sano & Sonoyo Mukai Kinki University, Higashi-Osaka,
Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 A study of range resolution effects on accuracy and precision of velocity.
Determination of aerosol components from multiwavelength/depolarization measurements Nobuo SUGIMOTO, Tomoaki Nishizawa, and Atsushi Shimizu National Institute.
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.
Causes of Haze Update Prepared by Marc Pitchford for the 5/24/05 AoH conference call.
Application of Combined Mathematical and Meteorological Receptor Models (UNMIX & Residence Time Analysis) to IMPROVE Aerosol Data from Brigantine.
Evaluation of the CMAQ Model for Size-Resolved PM Composition Prakash V. Bhave, K. Wyat Appel U.S. EPA, Office of Research & Development, National Exposure.
Online measurements of chemical composition and size distribution of submicron aerosol particles in east Baltic region Inga Rimšelytė Institute of Physics.
In Situ and Remote Sensing Characterization of Spectral Absorption by Black Carbon and other Aerosols J. Vanderlei Martins, Paulo Artaxo, Yoram Kaufman,
Aerosol Optical Depth during the Northern CA Fires of 2008 In situ aerosol light scattering and absorption measurements in Reno Nevada, 2008, indicated.
Page 1© Crown copyright Aircraft observations of mineral dust.
The Use of Optical Methods to Study Aerosols in the Paso del Norte Region Rosa M. Fitzgerald, Javier Polanco, Angel Esparza, Richard Medina Physics Department,
Measuring UV aerosol absorption. Why is aerosol UV absorption important ? Change in boundary layer ozone mixing ratios as a result of direct aerosol forcing.
Model Evaluation Comparing Model Output to Ambient Data Christian Seigneur AER San Ramon, California.
The Second TEMPO Science Team Meeting Physical Basis of the Near-UV Aerosol Algorithm Omar Torres NASA Goddard Space Flight Center Atmospheric Chemistry.
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote SEnsing Training A project of NASA Applied Sciences Pawan Gupta Satellite.
AoH Conference Call October 8, 2004 Air Resource Specialists, Inc.
1 NOAA-UPRM COOP Program in Atmospheric Sciences and Meteorology, Department of Physics, University of Puerto Rico at Mayagüez, Mayagüez, PR Yaítza.
Fog- and cloud-induced aerosol modification observed by the Aerosol Robotic Network (AERONET) Thomas F. Eck (Code 618 NASA GSFC) and Brent N. Holben (Code.
Numerical simulations of optical properties of nonspherical dust aerosols using the T-matrix method Hyung-Jin Choi School.
NATURAL AND TRANSBOUNDARY POLLUTION INFLUENCES ON AEROSOL CONCENTRATIONS AND VISIBILITY DEGRADATION IN THE UNITED STATES Rokjin J. Park, Daniel J. Jacob,
Timothy Logan University of North Dakota Department of Atmospheric Science.
1 Objective Finish with PM measurements Discuss Friday’s filed measurements 1.
Ground-based infrared retrievals of atmospheric dust properties over Niamey, Niger A case study: dust storm event (7-10 March 2006)* ATMS 790 R- Graduate.
Chemical Data Assimilation: Aerosols - Data Sources, availability and needs Raymond Hoff Physics Department/JCET UMBC.
Ambient Monitoring & Reporting Forum Plans for 2005 Prepared by Marc Pitchford for the WRAP Planning Team Meeting (3/9 – 3/10/05)
Introduction Instruments designed and fabricated at the Desert Research Institute, Reno Emphasis on the Integrating Nephelometer for scattering measurements.
The Use of Spectral and Angular Information In Remote Sensing
What Are the Implications of Optical Closure Using Measurements from the Two Column Aerosol Project? J.D. Fast 1, L.K. Berg 1, E. Kassianov 1, D. Chand.
Office of Research and Development Atmospheric Modeling Division, National Exposure Research Laboratory WRF-CMAQ 2-way Coupled System: Part II Jonathan.
University of Hawai`i, Hawai`i Group for Environments Aerosol Research School of Ocean and Earth Science and Technology A. Clarke, S. Howell, C. M c Naughton,
Fourth TEMPO Science Team Meeting
Remote Sensing of Aerosols
Aerosol chemistry studies at the SMEARIII station in Kumpula
Contribution of Dust to Regional Haze Based on Available IMPROVE Data From (Provided by Marc Pitchford (NOAA) and Jin Xu (DRI), 01/14/04) Mean.
Multiwavelength Photoacoustic Measurements of Light Absorption and Scattering by Wood Smoke More Specific Title: Evidence for light absorption by organic.
Continuous measurement of airborne particles and gases
Measuring microphysical, chemical and optical properties of aerosols aboard the NCAR/NSF C-130 during VOCALS Studying size-resolved aerosol cloud interactions.
Particle Size and Size Distributions
First use of satellite AOD data for EMEP model validation for PM
Contribution of Dust to Regional Haze Based on Available IMPROVE Data From (Provided by Marc Pitchford (NOAA) and Jin Xu (DRI), 01/14/04) Mean.
Presentation transcript:

Characterization of Aerosol Physical, Optical and Chemical Properties During the Big Bend Regional Aerosol and Visibility Observational Study (BRAVO) Jenny Hand* Eli Sherman*, Sonia Kreidenweis*, Jeff Collett, Jr.*, Taehyoung Lee*, Derek Day  and Bill Malm  Colorado State University *Atmospheric Science  CIRA/National Park Service Funding by National Park Service

OUTLINE Motivation for participating in BRAVO Chemical measurements and preliminary results Fine (PM 2.5 ) and Coarse (PM 10 - PM 2.5 ) species Size distribution measurements Experimental set-up and instrument calibration Alignment method: retrieved refractive index and density Comparisons between chemical and physical properties Optical properties: column and point measurements b sp (fine and coarse),  aer, Ångstrom exponent Summary

BRAVO STUDY July - October 1999 Big Bend NP has some of the poorest visibility of any monitored Class 1 area in the western U.S. Seasonal trends Sulfates: highest in summer Organic carbon: highest in spring Blowing soil: highest in July (Saharan dust episodes) (Gebhart et al., 2000) Recent work in Grand Canyon NP demonstrated that discrepancies of up to 50% or more exist between measured and reconstructed extinction (Malm and Day, 2000) Particle absorption or coarse scattering?

Aerosol Chemistry Measurements PM 2.5 composition CSU: daily samples, on-site analyses of major ionic species and particle acidity IMPROVE: daily samples: major ionic species, plus soil, organic and elemental carbon PM 10 composition IMPROVE: daily samples: major ionic species, plus soil, organic and elemental carbon  Coarse composition (PM 10 - PM 2.5 ) Ionic species’ particle size distribution: MOUDI samples Aethalometer- black carbon

BRAVO PM 2.5 Aerosol Acidity

BRAVO Soil Composition

Aerosol Size Distribution Measurements Dry size distributions were measured continuously ranging from 0.05< D p < 20 µm Instruments: TSI Differential Mobility Analyzer (DMA): 0.05 < D p < 0.87 µm (21 bins) PMS Optical Particle Counter (OPC): 0.1 < D p < 2 µm (8 bins) TSI Aerodynamic Particle Sizer 3320 (APS): 0.5 < D p < 20 µm (51 bins) Pre-, during-, and post-study calibration were performed using PSL, ammonium sulfate and oleic acid.

Instrument Calibration Empirical equations determined from instrument calibration relate real refractive index to OPC channel diameter (D opt  D p ) Channel collection efficiencies were determined Effective density (  e ) was related to APS channel diameter (D ae  D p ) by the following equation: where

Examples of Aligned and Unaligned DMA and OPC Volume Distributions Unaligned Aligned

Example of Combined Volume Distribution BRAVO

BRAVO Volume Distributions

Comparisons between chemical and physical properties Refractive index and density: retrieved from alignment method and calculated from chemical composition Total (PM 10 ) reconstructed mass and M =  V tot from size distributions, assuming X=1.2 MOUDI mass size distributions and volume distributions EC and aethalometer measurements

Accumulation Mode Parameters D gv gg

Coarse Mode Parameters D gv gg

Refractive Index and Density Real refractive index and effective density were retrieved from size distribution alignment method Values based on chemistry were calculated using a volume weighted method: and Species included: (NH 4 ) 2 SO 4 : m = 1.53,  = 1.76 g cm -3 OC: m = 1.55,  = 1.4 g cm -3 EC: m = i,  = 2.0 g cm -3 NH 4 NO 3 : m = 1.554,  = g cm -3 Soil: SiO 2, Al 2 O 3, Fe 2 O 3, CaO, TiO 2 (IMPROVE)

Aerosol Refractive Index and Density

Total Mass Comparisons PM 10 total mass concentration M =  V tot, assuming X = 1.2

MOUDI Mass and Volume Distributions

Calculations of Light Scattering Coefficient (b sp ) b sp was calculated using combined volume distributions and converged values of refractive index Q sp is the Mie scattering efficiency assuming spherical particles. b sp was calculated for the accumulation and coarse particle modes

BRAVO scattering distribution

Comparisons of NPS and CSU Dry b sp

Dry Mass Scattering Efficiency Accumulation ModeCoarse Mode

Calculation of Aerosol Optical Depth (  aer ) USDA UV-B radiation monitoring program has a fully instrumented site approximately 30 miles from BRAVO site in Big Bend National Park YES visible Multi-Filter Rotating Shadowband Radiometer measures irradiance with seven wavelength channels: 415, 500, 610, 665, 860, and 940 nm (Bigelow et al., 1998) Rayleigh and ozone optical depths were removed from column measurements of total optical depth Clouds and high sun angle measurements were removed Point measurements of  aer were determined by assuming a well-mixed layer and estimates of boundary layer heights

Two days were chosen for comparison:

Aerosol Optical Depth at 500 nm August 15, 1999 October 12, 1999

Ångstrom Wavelength Exponent (  ) Calculated for both point and column measurements over the wavelength range from 415 nm nm (Eck et al., 1999 & Reid et al., 1999) Two days were chosen for comparison, demonstrating very different aerosol physical, chemical and optical properties Column:Point:

Ångstrom wavelength exponent ( nm) August 15, 1999October 12, 1999

Correlations between b sp and  aer were found for several days:

Correlations between b ext and  aer were found for all months:

Correlations between  CSU and  UVB were found for all months:

Summary Sulfate was typically the major chemical species in the fine mode, although soil and OC were important during certain events Size distributions suggested that high coarse mode volume contributed significantly to total volume, especially during suspected Saharan dust events A new alignment method allowed for retrieving refractive index and effective density, in agreement with calculated values Calculated light scattering coefficients agreed well with measured values, and demonstrated periods when coarse scattering was important, often during suspected Saharan dust events

Summary, continued Time resolved sulfate measurements were observed to trend with light scattering coefficients, suggesting sulfate was the major contributor to visibility degradation during the study MOUDI mass distributions compared well with measured volume distributions Column and point measurements of aerosol optical depth were observed to be correlated for several days investigated Angstrom wavelength exponents agreed well between the two methods, and reflected the different aerosol types observed