IMPROVE Carbon AnalysisJohn G. Watson (john.watson@dri.edu)

Judith C. ChowXiaoliang WangDana L. TrimbleSteven D. Kohl

L.-W. Antony Chen

Desert Research Institute, Reno, NVPresented at

the IMPROVE Steering Committee MeetingPark City, UtahOctober 8, 2013

Objectives

• Report status and improvements of IMPROVE carbon analyses

• Update progress on enhancing thermal/optical analyses

Carbon Laboratory Operations(July 2012 to June 2013)

• Received ~1,790 samples per month (between 1,200–2,400)

• Maintained 24 hours per day/6-7 days per week operation with six staff

• Analyzed ~25,200 IMPROVE samples (1,400 to 2,932 per month)

• Averaged ~2,500 samples per month in the queue (200 to 5,395)

IMPROVE Carbon Analysis following the IMPROVE_Aa Protocol

(July 2012 to June 2013)

Sampling Period Samples Received

Analysis Completion Date

7/1/12-12/31/12 10,789 February 2013

1/1/13-6/30/13 10,282 September 2013

a Chow et al. (2007) JAWMA

Pre-baked filters yield values within blank tolerances

(Acceptance testing, July 2012 – June 2013)

Acceptable OC (1.5 µgC/cm2)

Average OC (0.18 µgC/cm2)

Acceptable EC (0.5 µgC/cm2)

Average EC (0.004 µgC/cm2)

Oxygen performance tests show values within the 100 ppm tolerance

Performance tests are within the ±5% tolerance(Sucrose; thrice per week between 7/1/2012 and 6/30/2013)

Acceptable limit (between 17.1 and 18.9 µg C)

Thermal/Optical Analysis Research Efforts(supported by NSF grant, Antony Chen sabbatical leave, Fulbright Fellowships, and DAS graduate

student fellowship)

• Multi-wavelength retrofit for DRI Model 2001 for radiation balance and source apportionment

• Thermal analysis for carbon, hydrogen, oxygen, nitrogen and sulfur (CHONS) for non-refractory mass balance

• Detailed organic compositions to optimize carbon fractions, identify source of black and brown carbon, and better understand the analytical process

• Design and test Model 2014 to increase interchangeability of detectors, improve reliability, lower costs of expendables (gases), more precise control of operating parameters

Extending from single to multiple wavelengths can distinguish pollution sources

0

10

20

30

40

50

60

70

200 400 600 800 1000 1200

EC Absorption Efficiency (M

m‐1/

g/m

3 )

Wavelength (nm)

Smoldering Biomass Diesel Flaming Biomass

Smoldering

Diesel

Flaming

(EC absorption efficiency varies by source and wavelength)

Sandraweji et al., 2008, EST p. 3316-3324. Atmos. Env. p. 101-112

Absorption at different wavelengths affects radiativetransfer (visibility and climate)

Emissions (above) and radiative transfer as a function of wavelength for funeral pyres in India

Chakrabarty, R.K.; Pervez, S.; Chow, J.C.; Dewangan, S.; Robles, J.A.; Tian, G.X.; Watson, J.G. (2013). Funeral pyres in south Asia: Large-scale brown carbon emissions and associated warming. Environmental Science & Technology Letters, online.

Multiple wavelengths may improve the EC char correction

BC (AAE ≈ 0.75) and char (AAE ≈ 5)

Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W. (2008). Modified thermal-optical analysis using spectral absorption selectivity to distinguish black carbon from pyrolized organic carbon. Environ. Sci. Technol., 42(22):8459-8464.

A 7-wavelength optical system is practical to implement on the existing Model 2001 TOR/TOT IMPROVE_A

carbon analysis system

405, 445, 532, 635, 780, 808, and 980 nm laser diodesShorter wavelengths will become available in the future

Retrofit hardware can be installed where the HeNelaser was located

Fiber Optic Assembly

Power Supplies

Laser Control andSignal Conditioning PCB

Lasers

National InstrumentsDAQ (underneath PCB)

Old laser (for comparison)

Each laser diode fires sequentially with timing keyed to the detector.

Fiber Optic Assembly

Power Supplies Laser Control and Signal Conditioning PCB

Lasers

National InstrumentsDAQ (underneath PCB)

A small microcontroller coordinates the signal creation and detection

DAQ Connectivity

Laser Indicators

Sensor Input

Microcontroller

Power supply

Signal Conditioning and Amplification

Example 7-Wavelength Thermogram showing Laser Reflectance

Example 7-Wavelength Thermogram showing Laser Transmittance

Characteristic patterns are found in wavelength/analysis time (temperature) space

Initial comparisons with HeNe 633 nm show comparable OC measurements

635 vs 633 nm OC comparison for Fresno, dust, diesel, and fire

samples

633 vs 633 nm OC replicate comparison for IMPROVE

samples

Initial comparisons with HeNe 633 nm show comparable EC measurements, except for some of the high fire values

635 vs 633 nm EC comparison for Fresno, dust, diesel, and fire

samples

633 vs 633 nm EC replicate comparison for IMPROVE

samples

Follow-up• Specify reporting parameters• Complete software interfaces• Compare 635 and 633 nm OC and EC for

IMPROVE samples (as replicates)• Replace HeNe lasers with diode lasers in

routine units• Modify reporting format to include

additional information

C, H, N, S, and O are major PM2.5components

OC EC H N S O

Emission Sources

Gasoline Diesel Wood Smoke FGD Stack

Elem

enta

l Abu

ndan

ces

(% o

f PM

2.5)

0

20

40

60

80

100

120Source Samples

IMPROVE Sites

BLISS,CA Fresno, CA GRSM,TN Washington, DC

Elem

enta

l Abu

ndan

ces

(% o

f PM

2.5)

(201

2)0

20

40

60

80

100

120Ambient Samples

• Sum of C, H, N, S, and O accounts for ~>80% of PM2.5 mass for many source and ambient samples

• Remaining mass is mostly associated with minerals, which may also contain CHNSO that does not decompose with moderate heating

• Relative abundances indicate different particle source/properties

C, H, N, S, and O can be obtained with thermal/optical techniques currently used for

only for C analysis

Mass spectrometer signals are linear with C, H, N, and S quantities for model compounds

Sulfanilamide: C6H8N2O2S; L-Cystine: C6H12N2O4S2

NDIR signal is linear with calibration chemical quantities

Benzoic acid: C7H6O2;Nonadecanol: C19H40OPentadecanoic acid: C15H30O2

• H2O bound to filters and particles. Need to pre-heat sample before analysis

• O2 in the carrier gas needs further reduction. Heaver gas (Ar) and higher pressure needed

Oxygen is converted to CO and then CO2 and detected by NDIR

Mating thermal/optical carbon analysis to more specific detectors yields specific organic compounds in thermal fractions

Grabowsky, J. et al. (2011) Hyphenation of a carbon analyzer to photo-1 ionization mass spectrometry to unravel the organic composition of particulate matter on a molecular level. Anal. Bioanal. Chem., 401(10):3153-3164.

DRI Model 2001 carbon analyzer with advanced resonance-enhanced multiphoton ionization (REMPI) single-photon ionization (SPI) detectors

y-scale x 0.25 !

y-scale x 0.25 !

y-scale x 1

OC I

OC II

OC III

IP

Sn

S0REMPI Zimmermann, 2011

Mass spectra of thermal carbon

fractions from Model 2001 with Resonance

Enhanced Multi-Photon Ionization-

Time-of-Flight/Mass Spectrometry (REMPI-

TOF/MS)

Charge to mass (m/z) patterns in temperature fractions indicate origins, including secondary organic aerosol

Grabowsky, J. et al. (2011) Hyphenation of a carbon analyzer to photo-1 ionization mass spectrometry to unravel the organic composition of particulate matter on a molecular level. Anal. Bioanal. Chem., 401(10):3153-3164.

Two-dimensional time temperature REMPI/TOF-MS-spectra of PM loaded filter from engine emissions using gasoline (left) and diesel (10% biodiesel) (right). Can be extended to the study of aged emissions

Concept for Model 2014 thermal/optical analysis system

98%

He,

2% O

2

He

He,

CH

4

He,

O2,

NO

, SO

2

Model 2014 will change components, but will retain sample presentation and heating system to retain OC/EC consistency

Component Model 2001 Model 2014Light Source 633 nm HeNe 405, 445, 532, 635,

780, 808, and 980nm laser diodes

Fiber optic Fiber bundle Single fiberFlow control Rotameters Mass flow metersPower supply 110 V AC DCData acquisition Keithley National InstrumentsCircuit boards Custom made Generic/ProgrammableDetector FID (CH4) detection

(requires ultrapure H2)NDIR (CO2) detection(no H2)

Software Visual Basic/C+ LabViewConversion zones after thermal evolution

Oxidization (to CO2) and reduction (to CH4) catalysts

Oxidation (to CO2) catalyst only for C-only analysis.Additional reactors for CHONS

Outlook• Emerging technologies allow more

information to be obtained from existing samples for comparable costs

• Additional information for each sample will enhance data analysis and modeling opportunities for radiation balance and source apportionment

• Changes must retain the OC/EC consistency of the IMPROVE long-term data base

DRI reports and publications using the IMPROVE protocol(2012 and 2013)

Bell, S.W.; Hansell, R.A.; Chow, J.C.; Tsay, S.C.; Wang, S.H.; Ji, Q.; Li, C.; Watson, J.G.; Khlystov, A. (2013). Constraining aerosol optical models using ground-based, collocated particle size and mass measurements in variable air mass regimes during the 7-SEAS/Dongsha experiment. Atmos. Environ., 78:163-173. Cao, J.J.; Wang, Q.Y.; Chow, J.C.; Watson, J.G.; Tie, X.X.; Shen, Z.X.; An, Z.S. (2012). Impacts of aerosol compositions on visibility impairment in Xi'an, China. Atmos. Environ., 59:559-566. Cao, J.J.; Huang, H.; Lee, S.C.; Chow, J.C.; Zou, C.W.; Ho, K.F.; Watson, J.G. (2012). Indoor/outdoor relationships for organic and elemental carbon in PM2.5 at residential homes in Guangzhou, China. AAQR, 12(5):902-910. http://aaqr.org/VOL12_No5_October2012/18_AAQR-12-02-OA-0026_902-910.pdf.Cao, J.J.; Shen, Z.X.; Chow, J.C.; Lee, S.C.; Watson, J.G.; Tie, X.X.; Ho, K.F.; Wang, G.H.; Han, Y.M. (2012). Winter and summer PM2.5 chemical compositions in 14 Chinese cities. J. Air Waste Manage. Assoc., 62(10):1214-1226. DOI: 10.1080/10962247.2012.701193. http://www.tandfonline.com/doi/pdf/10.1080/10962247.2012.7011933 .Chakrabarty, R.K.; Pervez, S.; Chow, J.C.; Dewangan, S.; Robles, J.A.; Tian, G.X.; Watson, J.G. (2013). Funeral pyres in south Asia: Large-scale brown carbon emissions and associated warming. Environmental Science & Technology Letters, online. http://pubs.acs.org/doi/pdf/10.1021/ez4000669.Chen, L.-W.A.; Tropp, R.J.; Li, W.-W.; Zhu, D.Z.; Chow, J.C.; Watson, J.G.; Zielinska, B. (2012). Aerosol and air toxics exposure in El Paso, Texas: A pilot study. AAQR, 12(2):169-189. http://aaqr.org/VOL12_No2_April2012/3_AAQR-11-10-OA-0169_169-179.pdf.Chen, L.-W.A.; Watson, J.G.; Chow, J.C.; DuBois, D.W.; Herschberger, L. (2012). Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks (vol 44, pg4908, 2010). Atmos. Environ., 51:335. Chen, L.-W.A.; Chow, J.C.; Watson, J.G.; Schichtel, B.A. (2012). Consistency of long-term elemental carbon trends from thermal and optical measurements in the IMPROVE network. Atmos. Meas. Tech., 5:2329-2338. http://www.atmos-meas-tech.net/5/2329/2012/amt-5-2329-2012.pdf.Chen, L.-W.A.; Watson, J.G.; Chow, J.C.; Green, M.C.; Inouye, D.; Dick, K. (2012). Wintertime particulate pollution episodes in an urban valley of the western U.S.: A case study. Atmos. Chem. Phys., 12(21):10051-10064. http://www.atmos-chem-phys.net/12/10051/2012/acp-12-10051-2012.pdf.Chow, J.C.; Watson, J.G. (2012). Chemical analyses of particle filter deposits. In Aerosols Handbook : Measurement, Dosimetry, and Health Effects, 2; Ruzer, L., Harley, N. H., Eds.; CRC Press/Taylor & Francis: New York, NY, 179-204..

DRI reports and publications using the IMPROVE protocol(2012 and 2013)

Chow, J.C.; Lowenthal, D.H.; Watson, J.G.; Chen, L.W.A. (2013). Source apportionment of SEARCH PM2.5 measurements with organic markers. prepared by Desert Research Institute, Reno, NV, for EPRI, Palo Alto, CA.Fujita, E.M.; Campbell, D.E.; Zielinska, B.; Chow, J.C.; Lindhjem, C.E.; DenBleyker, A.; Bishop, G.A.; Schuchmann, B.G.; Stedman, D.H.; Lawson, D.R. (2012). Comparison of the MOVES2010a, MOBILE6.2 and EMFAC2007 mobile source emissions models with on-road traffic tunnel and remote sensing measurements. J. Air Waste Manage. Assoc., 62(10):1134-1149. http://www.tandfonline.com/doi/pdf/10.1080/10962247.2012.699016.Green, M.C.; Chen, L.W.A.; DuBois, D.W.; Molenar, J.V. (2012). Fine particulate matter and visibility in the Lake Tahoe Basin: Chemical characterization, trends, and source apportionment. J. Air Waste Manage. Assoc., 62(8):953-965. Green, M.C.; Chow, J.C.; Chang, M.C.O.; Chen, L.-W.A.; Kuhns, H.D.; Etyemezian, V.R.; Watson, J.G. (2013). Source apportionment of atmospheric particulate carbon in Las Vegas, Nevada, USA. Particuology , 11:110-118. Hand, J.L.; Schichtel, B.A.; Malm, W.C.; Pitchford, M.L. (2012). Particulate sulfate ion concentration and SO2 emission trends in the United States from the early 1990s through 2010. Atmos. Chem. Phys. , 12(21):10353-10365. Hand, J.L.; Schichtel, B.A.; Pitchford, M.L.; Malm, W.C.; Frank, N.H. (2012). Seasonal composition of remote and urban fine particulate matter in the United States. J. Geophys Res. - Atmospheres, 117Ho, S.S.H.; Ho, K.F.; Liu, S.X.; Liu, W.D.; Lee, S.C.; Fung, K.K.; Cao, J.J.; Zhang, R.J.; Huang, Y.; Feng, N.S.Y.; Cheng, Y. (2012). Quantification of carbonate carbon in aerosol filter samples using a modified thermal/optical carbon analyzer (M-TOCA). Analytical Methods, 4(8):2578-2584. Kavouras, I.G.; Nikolich, G.; Etyemezian, V.; DuBois, D.W.; King, J.; Shafer, D. (2012). In situ observations of soil minerals and organic matter in the early phases of prescribed fires. J. Geophys Res. - Atmospheres, 117McDonald, J.D.; White, R.K.; Holmes, T.; Mauderly, J.L.; Zielinska, B.; Chow, J.C. (2012). Simulated downwind coal combustion emissions for laboratory inhalation exposure atmospheres. Inhal. Toxicol., 24(5):310-319. Orasche, J.; Seidel, T.; Hartmann, H.; Schnelle-Kreis, J.; Chow, J.C.; Ruppert, H.; Zimmermann, R. (2012). Comparison of emissions from wood combustion. Part 1: Emission factors and characteristics from different small-scale residential heating appliances considering particulate matter and polycyclic aromatic hydrocarbon (PAH)-related toxicological potential of particle-bound organic species. Energy & Fuels, 26(11):6695-6704. Qadir, R.M.; Abbaszade, G.; Schnelle-Kreis, J.; Chow, J.C.; Zimmermann, R. (2013). Concentrations and source contributions of particulate organic matter before and after implementation of a low emission zone in Munich, Germany. Environ. Poll., 175:158-167.

DRI reports and publications using the IMPROVE protocol(2012 and 2013)

Schichtel, B.A.; RodriguezB, M.A.; Barna, M.G.; Gebhart, K.A.; Pitchford, M.L.; Malm, W.C. (2012). A semi-empirical, receptor-oriented Lagrangian model for simulating fine particulate carbon at rural sites. Atmos. Environ., 61:361-370. Wang, X.L.; Watson, J.G.; Chow, J.C.; Kohl, S.D.; Chen, L.-W.A.; Sodeman, D.A.; Legge, A.H.; Percy, K.E. (2012). Measurement of real-world stack emissions with a dilution sampling system. In Alberta Oil Sands: Energy, Industry, and the Environment, Percy, K. E., Ed.; Elsevier Press: Amsterdam, The Netherlands, 171-192.Watson, J.G.; Chow, J.C.; Lowenthal, D.H.; Chen, L.-W.A.; Wang, X.L. (2012). Reformulation of PM2.5 mass reconstruction assumptions for the San Joaquin Valley: Literature review. prepared by Desert Research Institute, Reno, NV, for San Joaquin Valley Air Pollution Study Agency, Fresno, CA.Watson, J.G.; Chow, J.C.; Wang, X.L.; Lowenthal, D.H.; Kohl, S.D.; Gronstal, S. (2013). Characterization of real-world emissions from nonroad mining trucks in the Athabasca Oil Sands Region during October, 2010. prepared by Desert Research Institute, Reno, NV, for Ft. McMurray, AB, Canada, Wood Buffalo Environmental Association.Watson, J.G.; Chow, J.C.; Wang, X.L.; Zielinska, B.; Kohl, S.D.; Gronstal, S. (2013). Characterization of real-world emissions from nonroad mining trucks in the Athabasca Oil Sands Region during September, 2009. prepared by Desert Research Institute, Reno, NV, for Ft. McMurray, AB, Canada, Wood Buffalo Environmental Association.Watson, J.G.; Chow, J.C.; Wang, X.L.; Kohl, S.D.; Sodeman, D.A. (2013). Measurement of real-world stack emissions in the Athabasca Oil Sands Region with a dilution sampling system during August, 2008. prepared by Desert Research Institute, Reno, NV USA.Watson, J.G.; Chow, J.C.; Wang, X.L.; Kohl, S.D.; Gronstal, S.; Zielinska, B. (2013). Measurement of real-world stack emissions in the Athabasca Oil Sands Region with a dilution sampling system during March, 2011. prepared by Desert Research Institute, Reno, NV USA.White, W.H.; Farber, R.J.; Malm, W.C.; Nuttall, M.; Pitchford, M.L.; Schichtel, B.A. (2012). Comment on "Effect of coal-fired power generation on visibility in a nearby National Park (Terhorst and Berkman, 2010)". Atmos. Environ., 55:173-178. Xu, H.M.; Tao, J.; Ho, S.S.H.; Ho, K.F.; Cao, J.J.; Li, N.; Chow, J.C.; Wang, G.H.; Han, Y.M.; Zhang, R.J.; Watson, J.G.; Zhang, J.Q. (2013). Characteristics of fine particulate non-polar organic compounds in Guangzhou during the 16th Asian Games: Effectiveness of air pollution controls. Atmos. Environ., 76:94-101. j.atmosenv.2012.12.037. Zhou, J.M.; Cao, J.J.; Zhang, R.J.; Chow, J.C.; Watson, J.G. (2012). Carbonaceous and ionic components of atmospheric fine particles in Beijing and their impact on atmospheric visibility. AAQR, 12(4):492-502. http://aaqr.org/VOL12_No4_August2012/4_AAQR-11-11-OA-0218_492-502.pdf.