Models and Measurements for Photothermal Spectrometry of Collected Aerosols

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Models and Measurements for Photothermal Spectrometry of Collected Aerosols IR EXCITATION SOURCE VISIBLE PROBE LASER Stephen E Bialkowski Department of Chemistry and Biochemistry Utah State University Logan, Utah 84322-0300

Outline Photothermal Spectrometry for Chemical Analysis Aerosol Problems and Laws (USA) Infrared Photothermal Deflection from Condensed Aerosols Experiment Details and Results Heat Transfer Solutions and Random Aerosol Collection Model Implications Conclusions and Future Work

Chemical Analysis Perspective of Photothermal Spectrometry Spectroscopy measures light absorption in order to quantitatively identify substances of interest The photothermal effect heats a sample upon absorption of electromagnetic radiation Refractive index change from the photothermal temperature change produces an optical signals High irradiance sources produce large temperature changes, thus large signals Is an ultrasensitive technique used to measure optical absorbance to 10-7 AU in fluids

Principles Optical energy absorbed and not lost through emission results in sample heating. For pulsed excitation αhy H δ T = ρc The temperature change alters the sample s s refractive index. dn δn = δt dt P The complex transmission produces a phase shift that is converted d to a power change by a variety of optical techniques. Photothermal detection techniques are all ultimately diffraction-based. P

Apparatuses to Detect Photothermal Heating Photothermal Reflection Lens (Photothermal Bump Detection) THERMAL LENS DETECTOR HEATING BEAM LENS VISIBLE PROBE LASER Photothermal Deflection (Mirage Effect) SAMPLE VISIBLE PROBE LASER POSITION SENSING DETECTOR LENS

Photothermal Detection: Apparatuses Continuous Excitation Homogeneous Sample e.g. continuous-wave laser excited photothermal lens Heterogeneous Sample or Experiment Geometry e.g. photothermal deflection from arc-lamp excited surface Pulsed Excitation Homogeneous Sample e.g. pulsed-laser laser excited Brillion scattering (PT gratings) Heterogeneous Sample or Experiment Geometry e.g. pulsed-laser laser excited cylindrical sample cell and surface excitation

Photothermal Detection: Comparison Continuous Excitation: Homogeneous Sample Very sensitive non-aqueous Convection & flow noise Requires laser source Signal loss with flow Solid Sample or Heterogeneous Geometry Can use regular light sources Good fluid heat transfer May reduce convection Pulsed Excitation: Homogeneous Sample Most sensitive for gases Nonlinear effects common Requires laser source Best for flowing samples Solid Sample or Heterogeneous Geometry Highest temperature change Sample damage Nonlinear effects Use laser sources

Considerations for Chemical Analysis Trace analysis needs low detection limits Dynamic range is important for practical samples Precision is equally important in mixtures Analysis should be standardized Measurements and reports should be comparable between all laboratories Need for stable calibration methods and materials Suitable instrument calibration standards are needed for each phase and experiment type Standard Reference Materials (SRM) seem to be lacking in the analytical chemical community using photothermal spectroscopy

Further Considerations for Chemical Analysis Chemical analysis requires well-behaved techniques Measurements need to be reproducible and stable Reproducible light source, alignments, sample measurement diagnostics. No changes in chemical state No thermal decomposition No optical bleaching and other nonlinear effects Minimize convective cooling turbulence flicker noise

Aerosol Air Pollution Agriculture Waste Logan, Utah Vehicle Emissions Industrial Emissions Land-Use Change

Photothermal Detection of Condensed Aerosols* Why aerosols? Increasing awareness of health risks due to PM 2.5 or less Increasing amounts with anthropogenic origin Implications in public health and safety Environmental regulations What aerosols? Natural Smoke, Salts (NaCl( NaCl), Clay Minerals (dust, clay) Anthropogenic Ammonium Nitrate, Pesticide Sprays, Exhaust Smoke, Smog Why photothermal? Sensitivity Complex matrix Difficult analysis In Situ analysis more accurate * Initial collaboration with James Amonette, Tom Autrey and Nancy y Foster-Mills, Pacific Northwest Laboratory

PM 2.5 Effects PM 2.5 refers to Particulate Matter 2.5 μm m or less in diameter Aerosols are technically liquids though are often grouped as PM 2.5 A PM 2.5 weighs about 1 pg. The health effects associated with exposure to fine particles are significant. Scientific studies have shown significant associations between elevated e fine particle levels and premature mortality. Effects associated with fine particle exposure include aggravation of respiratory and cardiovascular disease, lung disease, decreased lung function, asthma attacks, and certain cardiovascular problems such as heart attacks and cardiac arrhythmia. It is estimated that 44,000 persons die prematurely each year in the USA due to particulates

PM Updated Rules US EPA Fine Particle National Air Quality Standards policy was put p into effect September, 2006 Larger Particulate Matter inhalable coarse particles (PM 10 50 μg/m 3 Annual Mean (Annual arithmetic mean not to exceed) 150 μg/m 3 24-hour (Not to be exceeded more than once per year) Smaller Particulate Matter fine particles (PM 15.0 μg/m 3 Annual Mean 35 μg/m 3 24-hour (25 ppb w/w) (PM 2.5 ) http://www.epa.gov/air/particlepollution/pdfs/20060921_factsheet.pdf.pdf 10 )

Logan, Utah USA Elevation 4535 feet (1382 m) Population 42,670 (91,391 total valley) 80 miles from nearest population center - Salt Lake City ~ 250,000 pop Industry: Agriculture Up-wind: deserts- no industry Air Quality: Worst PM 2.5 in USA! (Winter 2004/2005) Reason: Cars + Cows (NH 3 + HNO 3 NH 4 NO 3 ) Some carbonaceous and sulfate aerosols Current Analysis Particle counting (laser scattering) Particle collection and analysis USA Today Posted 3/8/2005 4:04 PM Northern Utah residents choke on bad air LOGAN, Utah (AP) In the summer, Cache Valley's verdant parks and riverside trails in the Wasatch Range are a haven for outdoor enthusiasts who describe this northern Utah mountain basin as a kind of Shangri-La. For about 40 days since November, at-risk residents like Koerner, 54 who make up 30% of the valley's population have choked on an unrelenting pea soup of smoky haze, much of it belched by the engines of the area's estimated 75,000 automobiles.

Laboratory-Based Condensed Phase Aerosol Measurements Aerosol Generation and Collection Ammonium nitrate and Malathion (pesticide) Germanium collection plate (2.5 cm diameter) Free aerosol generator, no particle sizing/reforming Average aerosol ~ 2.0 μm m each with mass ~ 1.0 pg Surface coverage under 25% Photothermal Deflection Measurement Pulsed infrared laser excitation (carbon dioxide 9.56 μm) Helium-Neon probe laser with bi-cell position sensing electronics

Aerosol Particle Generation and Sampling

Aerosol / Particle Generation Nebulizer mist generation Drying (3-stages) Maturation with time/distance in flow Filtering/Thermal conditioning (~4 m with dry air) Impinger deposition Carrier Conditioning Solution e.g., NH 4 NO 3

Aerosols Generation and Sampling Method 5 1. Air source 2. Valve 1 2 3 6 3. Air filter 1 4 4. Atomizer 11 12 5. Pressure gauge 6. Drier 7 7. Mixer (0.1524m X 4 m cylindrical tube) 8 8. Slow Flow tube 9. MOUDI 10 9 10. Vacuum 11. Valve 2 12. Air filter

Aerosols Generation and Sampling Atomizer MOUDI* Impaction plate * MOUDI is Micro-Orifice Uniform-Deposit Impactor

Rotating and Stationary Impaction Deposit pattern for nonrotating impaction plate 250 200 Pixel Intensity 150 100 50 0 0 100 200 300 400 500 600 Cross Section [um] Distribution for individual impactor spot Uniform deposit pattern for rotating impactor plate

Size and Number Calibration Aerosols are collected at different MOUDI stages for different times t (MOUDI flow rate = 5 L/min) Plates are inspected with an optical microscope The average size and number surface density are measured The differential plate mass are measured with a microbalance Mass is used to calculate particle density and to scale photothermal signals to mass loading 20 seconds 120 seconds 100 μm 100 μm

Simple IR Laser-Excited Photothermal Deflection Apparatus Position Sensing Detector CO 2 Laser Excitation Lens He-Ne Probe Laser Ge Substrate Ammoniun Nitrate Aerosol Excitation Fluence = 12 J m -2 Malathion Aerosol PDS Excitation Fluence = 45 J m -2 0.5 1.2 0.4 1.0 Signal (V) 0.3 0.2 0.1 0.0-0.1 0.000 0.002 0.004 0.006 0.008 0.010 Signal (V) 0.8 0.6 0.4 0.2 0.0-0.2 0 0.002 0.004 0.006 0.008 0.01 Time (s) Time (s)

IR Laser-Excited Photothermal Deflection Apparatus for Aerosol Detection Aerosol samples collected on Ge or ZnSe blanks. Pulsed 9.56 μm m CO 2 laser for excitation HeNe or diode laser probe in Mirage configuration. Bi-cell/operational divider deflection detection Adaptive matched filter signal analysis

Summary of Aerosol Data Analysis No detected loss of signal with time No detected damage to sample at the relative low fluence Actively probed area ~ 10-5 m 2 Number of aerosol spots ~1000 for ammonium nitrate ~ 100 for Malathion SNR indicates single aerosol detection possible with unimproved apparatus Substrate results in negligible signal

Aerosols Number Concentration 100 90 80 Signal increases with number of particles and coverage area Number of Particles 70 60 50 40 30 20 10 R 2 = 0.9815 0 0 20 40 60 80 100 120 140 Loading Time [s] 0.5 Linear calibration within the loading time range. Photothermal Signal 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 R 2 = 0.9875 0 0 20 40 60 80 100 Predicted Counts

Photothermal Signal Photothermal Signal 0.07 0.06 0.05 0.04 0.03 0.02 0.01 Photothermal Signal 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 5 10 15 20 25 30 35 Collection Time [min.] 0 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 Average Mass of Individual Spot [μg] Detection limit from signal-mass curve is 7.31 ng Aerosol mass concentration is calculated from MOUDI flow rate and collection time. A detection limit of 0.65 μg/m 3 for 30 L/min flow rate and 30 min collection time.

So why are the detection limits so high for these photothermal signals? The problem is not one of sensitivity but one of variability Single aerosols can be detected with this apparatus The problem appears to be the irreproducibility of the collection stage or the aerosols themselves The MOUDI produces heterogeneous spots There is an intrinsic variance due to the probability distribution. There may be chemical differences in the aerosols used for calibration. Laboratory-generated aerosols may not be at equilibrium Water content may be a large variable

Potential Interpretation Problems The goal is to have more sensitive real-time detection for mass concentration but photothermal deflection measures optical absorption. Particulate matter do not follow Beer s s Law if they are stacked in layers. Data analysis should account for surface coverage. Particulate mass will not follow Beer s s Law if they are optically thick. Data analysis should account for varying optical extinction. As with most other types of photothermal spectrometry, signal may be a function of particulate heat capacity and thermal diffusivity

MOUDI Calibration Curve Stage 6 (0.56 um) Stage 5 (1 um) Average Mass per Spot [ μ g] 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 0 10 20 30 40 50 60 Collection Time [min] Nonlinearity is due to surface saturation

Aerosol Loading Effects Evolution aerosol deposition can follow a Poisson function 100 90 80 P (n,λat)) = ( (λat) n exp(-λat)/ )/n! Where t is loading time, A is surface area, λ is deposition rate Number of particles 70 60 50 40 30 20 10 Corrected count Real count" Probability that pile-up occurs is P o = 1 - exp(-ga) 0 0 50 100 150 Loading Time [s] Where g is a surface extinction coefficient, and a is the surface particle density. 0.12 0.1 0.08 Corrected count is given as RSD 0.06 0.04 n = n 0 exp(-ga) 0.02 Where n is the real number and n 0 the measured count. 0 0 20 40 60 80 100 120 140 Loading Time [s]

Finite Element Analysis Modeling Finite Element Analysis is a tool for numerical solutions to complex differential equations Comsol Multiphysics v. 3.3 Steps Define sample geometry Specify materials, boundary conditions, heat sources and sinks Solve problem with rough finite element definitions Obtain δt time series Calculate relative photothermal element Comparison to standard approximate results

Finite Element Analysis Calculations The experiments are modeled as functions of Aerosol size Aerosol optical absorbance Aerosol heat capacity and thermal conductivity Arrangements of aerosols on surface Substrate heat capacity and thermal conductivity

Particle Crowding Effect Does inter-particle contact affect the photothermal signal? Modeled as three 2 μm m diameter particles with variable distance between them The total time-dependent photothermal deflection signal is calculated Conclusion: inter-particle heat transfer affects signal magnitude and shape Photothermal Deflection 1.2 1 0.8 0.6 0.4 0.2 0 4um 2m 1um no interval 0 0.5 1 1.5 2 2.5 3 Time [μs]

Substrate Thermal Conductivity Effect How does substrate heat transport affect particulate signals? Modeled as three 2 μm m diameter (NH 4 NO 3 ) particles with high and low optical absorption. Low Optical Absorption Coefficient Particle Substrate thermal conductivity : Air thermal conductivity ratio 1.8 Photothermal Deflection 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 10000 1000 100 10 5 1 0.5 0.1 0 0 5 10 15 20 25 30 Time [μs]

Results for Substrate Thermal Conductivity Low Optical Absorption Coefficient Particle Substrate thermal conductivity : Air thermal conductivity ratio 1.8 Increasing substrate thermal conductivity decreases signal decay time For the high absorbance case, the decay time changes in a complex fashion due to the coupling between the particle to surface through the air. Photothermal Deflection Photothermal Deflection 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 2.5 1.5 0.5 0 5 10 15 20 25 30 Time [μs] 3 2 1 High Optical Absorbance Particle Substrate thermal conductivity : Air thermal conductivity ratio 0.1 1 10 100 1000 10000 0.1 1 10 100 1000 10000 0 0 5 10 15 20 25 30 Time [μs]

Substrate Heat Capacity Effect How does substrate heat capacity affect particulate signals? Modeled as three 2 μm m diameter (NH 4 NO 3 ) particles with high and low optical absorption. No significant changes for high optical absorbance aerosols 2.5 Substrate heat capacity : Air heat capacity ratio 10 5 3 Photothermal Deflection 2 1.5 1 0.5 0 0 5 10 15 20 25 30 Time [μs]

Inference from Heat Transport and Signal Modeling Predicted signals show large changes with thermal conductivity, optical absorption coefficients, and proximity to other aerosols. Signals are relatively stable with respect to heat capacity, especially ecially for high absorbance samples. As might be expected, predicted signals are dependent on probe beam b geometry and aerosol layering (vertical stacking). The big problem with FEM is deriving working numerical models for processing data.

Summary and Conclusions Summary and Conclusions Aerosol photothermal deflection spectroscopy is a sensitive method that may be used to perform in situ atmospheric analysis The detection limit from the signal-mass curve was 7.3 ng Aerosol mass concentration is calculated from these experiments demonstrated a detection limit of 0.65 μg/m 3 for 30 L/min flow over a 30 min collection time This is much better than the current technology using sample and weigh. As with most aerosol analysis methods, knowledge of the particle composition is needed to calculate μg/m 3 from signal.

Future Aerosol Work We need to us an in situ apparatus to measure aerosol concentrations side-by by-side with conventional equipment. In terms of understanding the signals, we need to answer How cooperative heat transfer effects in high-sample surface density Can we use the time-dependent signals to determine aerosol thermal and absorbance properties? Finally, can we obtain multiple aerosol signals that are as precise as the individual aerosol measurements?

Stephen Bialkowski s s Laboratory Matt Jorgenson Agnes Chartier Oluwatosin Dada Stan Wellard

Acknowledgements Several persons worked on experiments and contributed discussions: Oluwatosin Dada (graduate) obtained most aerosol and glass measurements Matt Jorgensen (undergraduate) FEM finite element analysis calculations Dr. Agnès Chartier (Valspar) Spiricon, Inc. (Logan UT) for pyroelectric camera and video interfaces This research has been supported by the state of Utah, NASA, USDA, DARPA and National Institutes of Health. PNL for summer support (2003 and 2004) and use of Environmental Spectroscopy Laboratory equipment at EMSL