Articles | Volume 14, issue 7
https://doi.org/10.5194/amt-14-4805-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-4805-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jul 2021
Research article |
| 08 Jul 2021
| 08 Jul 2021
Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network
Amir Yazdani
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
Ann M. Dillner
Air Quality Research Center, University of California Davis, Davis, CA, USA
Satoshi Takahama
CORRESPONDING AUTHOR
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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Cited articles
Aiken, A. C., DeCarlo, P. F., Kroll, J. H., Worsnop, D. R., Huffman, J. A.,
Docherty, K. S., Ulbrich, I. M., Mohr, C., Kimmel, J. R., Sueper, D., Sun,
Y., Zhang, Q., Trimborn, A., Northway, M., Ziemann, P. J., Canagaratna,
M. R., Onasch, T. B., Alfarra, M. R., Prevot, A. S. H., Dommen, J., Duplissy,
J., Metzger, A., Baltensperger, U., and Jimenez, J. L.: O/C and
OM/OC Ratios of Primary, Secondary, and Ambient Organic
Aerosols with High-Resolution Time-of-Flight Aerosol Mass
Spectrometry, Environ. Sci. Technol., 42, 4478–4485,
https://doi.org/10.1021/es703009q, 2008. a
Atkins, P., de Paula, J., and Keeler, J.: Atkins' Physical Chemistry,
Oxford University Press, Oxford, New York, 11th Edn., 2017. a
Boris, A. J., Takahama, S., Weakley, A. T., Debus, B. M., Fredrickson, C. D., Esparza-Sanchez, M., Burki, C., Reggente, M., Shaw, S. L., Edgerton, E. S., and Dillner, A. M.: Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 1: Methods, Atmos. Meas. Tech., 12, 5391–5415, https://doi.org/10.5194/amt-12-5391-2019, 2019. a, b
Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J.: Classification and Regression Trees, Biometrics, 40, 874–874, https://doi.org/10.2307/2530946, 1983. a
Bürki, C., Reggente, M., Dillner, A. M., Hand, J. L., Shaw, S. L., and Takahama, S.: Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations, Atmos. Meas. Tech., 13, 1517–1538, https://doi.org/10.5194/amt-13-1517-2020, 2020. a, b, c, d, e, f, g, h, i, j
Canagaratna, M. R., Jayne, J. T., Jimenez, J. L., Allan, J. D., Alfarra, M. R.,
Zhang, Q., Onasch, T. B., Drewnick, F., Coe, H., Middlebrook, A., Delia, A.,
Williams, L. R., Trimborn, A. M., Northway, M. J., DeCarlo, P. F., Kolb,
C. E., Davidovits, P., and Worsnop, D. R.: Chemical and Microphysical
Characterization of Ambient Aerosols with the Aerodyne Aerosol Mass
Spectrometer, Mass Spectrom. Rev., 26, 185–222, https://doi.org/10.1002/mas.20115,
2007. a
Cocker III, D. R., Mader, B. T., Kalberer, M., Flagan, R. C., and Seinfeld,
J. H.: The Effect of Water on Gas-Particle Partitioning of
Secondary Organic Aerosol: II. m-Xylene and 1,3,5-Trimethylbenzene
Photooxidation Systems, Atmos. Environ., 35, 6073–6085,
https://doi.org/10.1016/S1352-2310(01)00405-8, 2001. a
Corsetti, S., Rabl, T., McGloin, D., and Kiefer, J.: Intermediate Phases during
Solid to Liquid Transitions in Long-Chain n-Alkanes, Phys. Chem. Chem. Phys.,
19, 13941–13950, https://doi.org/10.1039/C7CP01468F, 2017. a, b
Coury, C. and Dillner, A. M.: A Method to Quantify Organic Functional Groups
and Inorganic Compounds in Ambient Aerosols Using Attenuated Total
Reflectance FTIR Spectroscopy and Multivariate Chemometric Techniques,
Atmos. Environ., 42, 5923–5932, https://doi.org/10.1016/j.atmosenv.2008.03.026, 2008. a
Decesari, S., Facchini, M. C., Fuzzi, S., and Tagliavini, E.: Characterization
of Water-Soluble Organic Compounds in Atmospheric Aerosol: A New
Approach, J. Geophys. Res.-Atmos., 105, 1481–1489,
https://doi.org/10.1029/1999JD900950, 2000. a
DeRieux, W.-S. W., Li, Y., Lin, P., Laskin, J., Laskin, A., Bertram, A. K., Nizkorodov, S. A., and Shiraiwa, M.: Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition, Atmos. Chem. Phys., 18, 6331–6351, https://doi.org/10.5194/acp-18-6331-2018, 2018. a
Desiraju, G. R. and Steiner, T.: The Weak Hydrogen Bond: In Structural
Chemistry and Biology, Oxford University Press, 2001. a
Donahue, N. M., Epstein, S. A., Pandis, S. N., and Robinson, A. L.: A two-dimensional volatility basis set: 1. organic-aerosol mixing thermodynamics, Atmos. Chem. Phys., 11, 3303–3318, https://doi.org/10.5194/acp-11-3303-2011, 2011. a, b
Faber, P., Drewnick, F., Bierl, R., and Borrmann, S.: Complementary Online
Aerosol Mass Spectrometry and Offline FT-IR Spectroscopy
Measurements: Prospects and Challenges for the Analysis of Anthropogenic
Aerosol Particle Emissions, Atmos. Environ., 166, 92–98,
https://doi.org/10.1016/j.atmosenv.2017.07.014, 2017. a
Fornaro, T., Burini, D., Biczysko, M., and Barone, V.: Hydrogen-Bonding
Effects on Infrared Spectra from Anharmonic Computations:
Uracil–Water Complexes and Uracil Dimers, J. Phys.
Chem. A, 119, 4224–4236, https://doi.org/10.1021/acs.jpca.5b01561, 2015. a
Gentner, D. R., Isaacman, G., Worton, D. R., Chan, A. W. H., Dallmann, T. R.,
Davis, L., Liu, S., Day, D. A., Russell, L. M., Wilson, K. R., Weber, R.,
Guha, A., Harley, R. A., and Goldstein, A. H.: Elucidating Secondary Organic
Aerosol from Diesel and Gasoline Vehicles through Detailed Characterization
of Organic Carbon Emissions, P. Natl. Acad. Sci. USA, 109, 18318–18323,
https://doi.org/10.1073/pnas.1212272109, 2012. a, b, c, d
Graber, E. R. and Rudich, Y.: Atmospheric HULIS: How humic-like are they? A comprehensive and critical review, Atmos. Chem. Phys., 6, 729–753, https://doi.org/10.5194/acp-6-729-2006, 2006. a, b
Hähner, G., Zwahlen, M., and Caseri, W.: Chain-Length Dependence of the
Conformational Order in Self-Assembled Dialkylammonium Monolayers
on Mica Studied with Soft X-Ray Absorption, Langmuir, 21,
1424–1427, https://doi.org/10.1021/la047841u, 2005. a
Hallquist, M., Wenger, J. C., Baltensperger, U., Rudich, Y., Simpson, D., Claeys, M., Dommen, J., Donahue, N. M., George, C., Goldstein, A. H., Hamilton, J. F., Herrmann, H., Hoffmann, T., Iinuma, Y., Jang, M., Jenkin, M. E., Jimenez, J. L., Kiendler-Scharr, A., Maenhaut, W., McFiggans, G., Mentel, Th. F., Monod, A., Prévôt, A. S. H., Seinfeld, J. H., Surratt, J. D., Szmigielski, R., and Wildt, J.: The formation, properties and impact of secondary organic aerosol: current and emerging issues, Atmos. Chem. Phys., 9, 5155–5236, https://doi.org/10.5194/acp-9-5155-2009, 2009. a, b, c, d
Hand, J. L., Prenni, A. J., Schichtel, B. A., Malm, W. C., and Chow, J. C.:
Trends in Remote PM2.5 Residual Mass across the United States:
Implications for Aerosol Mass Reconstruction in the IMPROVE Network,
Atmos. Environ., 203, 141–152, https://doi.org/10.1016/j.atmosenv.2019.01.049, 2019. a, b
Hastie, T., Tibshirani, R., and Friedman, J.: The Elements of Statistical
Learning: Data Mining, Inference, and Prediction, Second
Edition, Springer Series in Statistics, Springer-Verlag, New
York, 2nd Edn., 2009. a
Hastings, S. H., Watson, A. T., Williams, R. B., and Anderson, J. A.:
Determination of Hydrocarbon Functional Groups by Infrared
Spectroscopy, Anal. Chem., 24, 612–618, https://doi.org/10.1021/ac60064a002, 1952. a
Hawkins, L. N. and Russell, L. M.: Oxidation of Ketone Groups in Transported
Biomass Burning Aerosol from the 2008 Northern California Lightning
Series Fires, Atmos. Environ., 44, 4142–4154,
https://doi.org/10.1016/j.atmosenv.2010.07.036, 2010. a
Hermans, J., Ongay, S., Markov, V., and Bischoff, R.: Physicochemical
Parameters Affecting the Electrospray Ionization Efficiency of
Amino Acids after Acylation, Anal. Chem., 89, 9159–9166,
https://doi.org/10.1021/acs.analchem.7b01899, 2017. a
Iyer, S., Lopez-Hilfiker, F., Lee, B. H., Thornton, J. A., and Kurtén,
T.: Modeling the Detection of Organic and Inorganic Compounds Using
Iodide-Based Chemical Ionization, J. Phys. Chem. A, 120, 576–587,
https://doi.org/10.1021/acs.jpca.5b09837, 2016. a
Jang, M. and Kamens, R. M.: Atmospheric Secondary Aerosol Formation by
Heterogeneous Reactions of Aldehydes in the Presence of a
Sulfuric Acid Aerosol Catalyst, Environ. Sci. Technol., 35, 4758–4766,
https://doi.org/10.1021/es010790s, 2001a. a
Jang, M. and Kamens, R. M.: Characterization of Secondary Aerosol from the
Photooxidation of Toluene in the Presence of NOx and
1-Propene, Environ. Sci. Technol., 35, 3626–3639,
https://doi.org/10.1021/es010676, 2001b. a
Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang,
Q., Kroll, J. H., DeCarlo, P. F., Allan, J. D., Coe, H., Ng, N. L., Aiken,
A. C., Docherty, K. S., Ulbrich, I. M., Grieshop, A. P., Robinson, A. L.,
Duplissy, J., Smith, J. D., Wilson, K. R., Lanz, V. A., Hueglin, C., Sun,
Y. L., Tian, J., Laaksonen, A., Raatikainen, T., Rautiainen, J., Vaattovaara,
P., Ehn, M., Kulmala, M., Tomlinson, J. M., Collins, D. R., Cubison, M. J.,
E, Dunlea, J., Huffman, J. A., Onasch, T. B., Alfarra, M. R., Williams,
P. I., Bower, K., Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S.,
Weimer, S., Demerjian, K., Salcedo, D., Cottrell, L., Griffin, R., Takami,
A., Miyoshi, T., Hatakeyama, S., Shimono, A., Sun, J. Y., Zhang, Y. M.,
Dzepina, K., Kimmel, J. R., Sueper, D., Jayne, J. T., Herndon, S. C.,
Trimborn, A. M., Williams, L. R., Wood, E. C., Middlebrook, A. M., Kolb,
C. E., Baltensperger, U., and Worsnop, D. R.: Evolution of Organic
Aerosols in the Atmosphere, Science, 326, 1525–1529,
https://doi.org/10.1126/science.1180353, 2009. a
Kalberer, M.: Identification of Polymers as Major Components of
Atmospheric Organic Aerosols, Science, 303, 1659–1662,
https://doi.org/10.1126/science.1092185, 2004. a, b
Kalberer, M., Sax, M., and Samburova, V.: Molecular Size Evolution of
Oligomers in Organic Aerosols Collected in Urban Atmospheres and
Generated in a Smog Chamber, Environ. Sci. Technol., 40, 5917–5922,
https://doi.org/10.1021/es0525760, 2006. a, b
Kanakidou, M., Seinfeld, J. H., Pandis, S. N., Barnes, I., Dentener, F. J., Facchini, M. C., Van Dingenen, R., Ervens, B., Nenes, A., Nielsen, C. J., Swietlicki, E., Putaud, J. P., Balkanski, Y., Fuzzi, S., Horth, J., Moortgat, G. K., Winterhalter, R., Myhre, C. E. L., Tsigaridis, K., Vignati, E., Stephanou, E. G., and Wilson, J.: Organic aerosol and global climate modelling: a review, Atmos. Chem. Phys., 5, 1053–1123, https://doi.org/10.5194/acp-5-1053-2005, 2005. a
Kroll, J. H. and Seinfeld, J. H.: Chemistry of Secondary Organic Aerosol:
Formation and Evolution of Low-Volatility Organics in the Atmosphere,
Atmos. Environ., 42, 3593–3624, https://doi.org/10.1016/j.atmosenv.2008.01.003, 2008. a, b, c
Kroll, J. H., Donahue, N. M., Jimenez, J. L., Kessler, S. H., Canagaratna,
M. R., Wilson, K. R., Altieri, K. E., Mazzoleni, L. R., Wozniak, A. S.,
Bluhm, H., Mysak, E. R., Smith, J. D., Kolb, C. E., and Worsnop, D. R.:
Carbon Oxidation State as a Metric for Describing the Chemistry of
Atmospheric Organic Aerosol, Nat. Chem., 3, 133–139,
https://doi.org/10.1038/nchem.948, 2011. a, b
Kuzmiakova, A., Dillner, A. M., and Takahama, S.: An automated baseline correction protocol for infrared spectra of atmospheric aerosols collected on polytetrafluoroethylene (Teflon) filters, Atmos. Meas. Tech., 9, 2615–2631, https://doi.org/10.5194/amt-9-2615-2016, 2016. a, b, c
Li, X., Han, J., Hopke, P. K., Hu, J., Shu, Q., Chang, Q., and Ying, Q.: Quantifying primary and secondary humic-like substances in urban aerosol based on emission source characterization and a source-oriented air quality model, Atmos. Chem. Phys., 19, 2327–2341, https://doi.org/10.5194/acp-19-2327-2019, 2019. a
Li, Y., Pöschl, U., and Shiraiwa, M.: Molecular corridors and parameterizations of volatility in the chemical evolution of organic aerosols, Atmos. Chem. Phys., 16, 3327–3344, https://doi.org/10.5194/acp-16-3327-2016, 2016. a, b
Li, Y., Day, D. A., Stark, H., Jimenez, J. L., and Shiraiwa, M.: Predictions of the glass transition temperature and viscosity of organic aerosols from volatility distributions, Atmos. Chem. Phys., 20, 8103–8122, https://doi.org/10.5194/acp-20-8103-2020, 2020. a
Lii, J.-H., Chen, K.-H., and Allinger, N. L.: Alcohols, Ethers,
Carbohydrates, and Related Compounds Part V. The Bohlmann Torsional
Effect, The J. Phys. Chem. A, 108, 3006–3015,
https://doi.org/10.1021/jp031063h, 2004. a
Lipp, E. D.: Application of Fourier Self-Deconvolution to the
FT-IR Spectra of Polydimethylsiloxane Oligomers for Determining
Chain Length, Appl. Spectrosc., 40, 1009–1011, 1986. a
Lopez-Hilfiker, F. D., Pospisilova, V., Huang, W., Kalberer, M., Mohr, C., Stefenelli, G., Thornton, J. A., Baltensperger, U., Prevot, A. S. H., and Slowik, J. G.: An extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) for online measurement of atmospheric aerosol particles, Atmos. Meas. Tech., 12, 4867–4886, https://doi.org/10.5194/amt-12-4867-2019, 2019. a
Mcclenny, W. A., Childers, J. W., Rōhl, R., and Palmer, R. A.: FTIR
Transmission Spectrometry for the Nondestructive Determination of Ammonium
and Sulfate in Ambient Aerosols Collected on Teflon Filters, Atmos.
Environ. (1967), 19, 1891–1898, https://doi.org/10.1016/0004-6981(85)90014-9, 1985. a
McHale, J. L.: Molecular Spectroscopy, CRC Press, Boca Raton, FL, 2017. a
Murphy, B. N., Donahue, N. M., Fountoukis, C., Dall'Osto, M., O'Dowd, C., Kiendler-Scharr, A., and Pandis, S. N.: Functionalization and fragmentation during ambient organic aerosol aging: application of the 2-D volatility basis set to field studies, Atmos. Chem. Phys., 12, 10797–10816, https://doi.org/10.5194/acp-12-10797-2012, 2012. a, b
Nozière, B., Kalberer, M., Claeys, M., Allan, J., D'Anna, B., Decesari, S.,
Finessi, E., Glasius, M., Grgić, I., Hamilton, J. F., Hoffmann, T.,
Iinuma, Y., Jaoui, M., Kahnt, A., Kampf, C. J., Kourtchev, I., Maenhaut, W.,
Marsden, N., Saarikoski, S., Schnelle-Kreis, J., Surratt, J. D., Szidat,
S., Szmigielski, R., and Wisthaler, A.: The Molecular Identification of
Organic Compounds in the Atmosphere: State of the Art and
Challenges, Chem. Rev., 115, 3919–3983, https://doi.org/10.1021/cr5003485, 2015. a
Orendorff, C. J., Ducey, M. W., and Pemberton, J. E.: Quantitative
Correlation of Raman Spectral Indicators in Determining
Conformational Order in Alkyl Chains, J. Phys. Chem. A, 106,
6991–6998, https://doi.org/10.1021/jp014311n, 2002. a
Orthous-Daunay, F. R., Quirico, E., Beck, P., Brissaud, O., Dartois, E.,
Pino, T., and Schmitt, B.: Mid-Infrared Study of the Molecular Structure
Variability of Insoluble Organic Matter from Primitive Chondrites, Icarus,
223, 534–543, https://doi.org/10.1016/j.icarus.2013.01.003, 2013. a
Pankow, J. F. and Barsanti, K. C.: The Carbon Number-Polarity Grid: A Means
to Manage the Complexity of the Mix of Organic Compounds When Modeling
Atmospheric Organic Particulate Matter, Atmos. Environ., 43, 2829–2835,
https://doi.org/10.1016/j.atmosenv.2008.12.050, 2009. a, b
Parks, D. A., Raj, K. V., Berry, C. A., Weakley, A. T., Griffiths, P. R., and
Miller, A. L.: Towards a Field-Portable Real-Time Organic and
Elemental Carbon Monitor, Mining, Metall. Explor., 36,
765–772, https://doi.org/10.1007/s42461-019-0064-8, 2019. a
Pope, R., Stanley, K. M., Domsky, I., Yip, F., Nohre, L., and Mirabelli, M. C.:
The Relationship of High PM2.5 Days and Subsequent Asthma-Related
Hospital Encounters during the Fireplace Season in Phoenix, AZ,
2008–2012, Air Qual. Atmos. Hlth., 10, 161–169,
https://doi.org/10.1007/s11869-016-0431-2, 2017. a
Price, D. J., Chen, C.-L., Russell, L. M., Lamjiri, M. A., Betha, R., Sanchez,
K., Liu, J., Lee, A. K. Y., and Cocker, D. R.: More Unsaturated, Cooking-Type
Hydrocarbon-like Organic Aerosol Particle Emissions from Renewable Diesel
Compared to Ultra Low Sulfur Diesel in at-Sea Operations of a Research
Vessel, Aerosol Sci. Technol., 51, 135–146,
https://doi.org/10.1080/02786826.2016.1238033, 2017. a, b, c
Reggente, M., Dillner, A. M., and Takahama, S.: Predicting ambient aerosol thermal–optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites, Atmos. Meas. Tech., 9, 441–454, https://doi.org/10.5194/amt-9-441-2016, 2016. a
Russell, L. M.: Aerosol Organic-Mass-to-Organic-Carbon Ratio
Measurements, Environ. Sci. Technol., 37, 2982–2987,
https://doi.org/10.1021/es026123w, 2003. a
Russell, L. M., Takahama, S., Liu, S., Hawkins, L. N., Covert, D. S., Quinn,
P. K., and Bates, T. S.: Oxygenated Fraction and Mass of Organic Aerosol from
Direct Emission and Atmospheric Processing Measured on the R/V Ronald
Brown during TEXAQS/GoMACCS 2006, J. Geophys. Res.-Atmos., 114, D00F05,
https://doi.org/10.1029/2008JD011275, 2009. a, b
Russell, L. M., Bahadur, R., and Ziemann, P. J.: Identifying Organic Aerosol
Sources by Comparing Functional Group Composition in Chamber and Atmospheric
Particles, P. Natl. Acad. Sci. USA, 108, 3516–3521, https://doi.org/10.1073/pnas.1006461108, 2011. a
Russo, C., Stanzione, F., Tregrossi, A., and Ciajolo, A.: Infrared Spectroscopy
of Some Carbon-Based Materials Relevant in Combustion: Qualitative and
Quantitative Analysis of Hydrogen, Carbon, 74, 127–138,
https://doi.org/10.1016/j.carbon.2014.03.014, 2014. a
Ruthenburg, T. C., Perlin, P. C., Liu, V., McDade, C. E., and Dillner, A. M.:
Determination of Organic Matter and Organic Matter to Organic Carbon Ratios
by Infrared Spectroscopy with Application to Selected Sites in the
IMPROVE Network, Atmos. Environ., 86, 47–57,
https://doi.org/10.1016/j.atmosenv.2013.12.034, 2014. a, b, c, d, e, f, g, h
Shiraiwa, M., Berkemeier, T., Schilling-Fahnestock, K. A., Seinfeld, J. H., and Pöschl, U.: Molecular corridors and kinetic regimes in the multiphase chemical evolution of secondary organic aerosol, Atmos. Chem. Phys., 14, 8323–8341, https://doi.org/10.5194/acp-14-8323-2014, 2014. a
Shiraiwa, M., Li, Y., Tsimpidi, A. P., Karydis, V. A., Berkemeier, T., Pandis,
S. N., Lelieveld, J., Koop, T., and Pöschl, U.: Global Distribution of
Particle Phase State in Atmospheric Secondary Organic Aerosols, Nat. Commun.,
8, 15002, https://doi.org/10.1038/ncomms15002, 2017a. a, b, c
Shiraiwa, M., Ueda, K., Pozzer, A., Lammel, G., Kampf, C. J., Fushimi, A.,
Enami, S., Arangio, A. M., Fröhlich-Nowoisky, J., Fujitani, Y.,
Furuyama, A., Lakey, P. S. J., Lelieveld, J., Lucas, K., Morino, Y.,
Pöschl, U., Takahama, S., Takami, A., Tong, H., Weber, B., Yoshino, A.,
and Sato, K.: Aerosol Health Effects from Molecular to Global
Scales, Environ. Sci. Technol., 51, 13545–13567,
https://doi.org/10.1021/acs.est.7b04417, 2017b. a
Simon, H., Bhave, P. V., Swall, J. L., Frank, N. H., and Malm, W. C.: Determining the spatial and seasonal variability in OM/OC ratios across the US using multiple regression, Atmos. Chem. Phys., 11, 2933–2949, https://doi.org/10.5194/acp-11-2933-2011, 2011. a, b
Takahama, S., Schwartz, R. E., Russell, L. M., Macdonald, A. M., Sharma, S., and Leaitch, W. R.: Organic functional groups in aerosol particles from burning and non-burning forest emissions at a high-elevation mountain site, Atmos. Chem. Phys., 11, 6367–6386, https://doi.org/10.5194/acp-11-6367-2011, 2011. a
Takahama, S., Johnson, A., and Russell, L. M.: Quantification of Carboxylic
and Carbonyl Functional Groups in Organic Aerosol Infrared Absorbance
Spectra, Aerosol Sci. Technol., 47, 310–325,
https://doi.org/10.1080/02786826.2012.752065, 2013. a, b
Takahama, S., Ruggeri, G., and Dillner, A. M.: Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: sparse methods for statistical selection of relevant absorption bands, Atmos. Meas. Tech., 9, 3429–3454, https://doi.org/10.5194/amt-9-3429-2016, 2016. a
Thomas, M.: Theoretical Modeling of Vibrational Spectra in the Liquid Phase,
Ph.D. thesis, Springer International Publishing, Cham,
https://doi.org/10.1007/978-3-319-49628-3, 2017. a
Thomas, M., Brehm, M., Fligg, R., Vöhringer, P., and Kirchner, B.:
Computing Vibrational Spectra from Ab Initio Molecular Dynamics, Phys.
Chem. Chem. Phys., 15, 6608, https://doi.org/10.1039/c3cp44302g, 2013.
a
Tolocka, M. P., Jang, M., Ginter, J. M., Cox, F. J., Kamens, R. M., and
Johnston, M. V.: Formation of Oligomers in Secondary Organic Aerosol,
Environ. Sci. Technol., 38, 1428–1434, https://doi.org/10.1021/es035030r, 2004. a
Trump, E. R. and Donahue, N. M.: Oligomer formation within secondary organic aerosols: equilibrium and dynamic considerations, Atmos. Chem. Phys., 14, 3691–3701, https://doi.org/10.5194/acp-14-3691-2014, 2014. a
Turpin, B. J., Saxena, P., and Andrews, E.: Measuring and Simulating
Particulate Organics in the Atmosphere: Problems and Prospects, Atmos.
Environ., 34, 2983–3013, https://doi.org/10.1016/S1352-2310(99)00501-4, 2000. a
Wold, S., Martens, H., and Wold, H.: The Multivariate Calibration Problem in
Chemistry Solved by the PLS Method, in: Matrix Pencils, edited by
Kågström, B. and Ruhe, A., Lect. Notes Math., 286–293,
Springer Berlin Heidelberg, 1983. a
Xie, Q., Li, Y., Yue, S., Su, S., Cao, D., Xu, Y., Chen, J., Tong, H., Su, H., Cheng, Y., Zhao, W., Hu, W., Wang, Z., Yang, T., Pan, X., Sun, Y., Wang, Z., Liu, C.-Q., Kawamura, K., Jiang, G., Shiraiwa, M., and Fu, P.: Increase of High Molecular Weight Organosulfate With Intensifying Urban Air Pollution in the Megacity Beijing, J. Geophys. Res.-Atmos., 125, e2019JD032200,
https://doi.org/10.1029/2019JD032200, 2020. a
Yazdani, A., Dillner, A. M., and Takahama, S.: Baseline-Corrected Aliphatic CH Peaks in the FTIR Spectra of Laboratory Standards and Atmospheric Aerosols, Zenodo [data set], https://doi.org/10.5281/zenodo.4882120, 2021. a
Yuan, Q., Lai, S., Song, J., Ding, X., Zheng, L., Wang, X., Zhao, Y., Zheng,
J., Yue, D., Zhong, L., Niu, X., and Zhang, Y.: Seasonal Cycles of Secondary
Organic Aerosol Tracers in Rural Guangzhou, Southern China: The
Importance of Atmospheric Oxidants, Environ. Pollut., 240, 884–893,
https://doi.org/10.1016/j.envpol.2018.05.009, 2018. a
Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Allan, J. D., Coe, H., Ulbrich,
I., Alfarra, M. R., Takami, A., Middlebrook, A. M., Sun, Y. L., Dzepina, K.,
Dunlea, E., Docherty, K., DeCarlo, P. F., Salcedo, D., Onasch, T., Jayne,
J. T., Miyoshi, T., Shimono, A., Hatakeyama, S., Takegawa, N., Kondo, Y.,
Schneider, J., Drewnick, F., Borrmann, S., Weimer, S., Demerjian, K.,
Williams, P., Bower, K., Bahreini, R., Cottrell, L., Griffin, R. J.,
Rautiainen, J., Sun, J. Y., Zhang, Y. M., and Worsnop, D. R.: Ubiquity and
Dominance of Oxygenated Species in Organic Aerosols in
Anthropogenically-Influenced Northern Hemisphere Midlatitudes, Geophys.
Res. Lett., 34, L13801, https://doi.org/10.1029/2007GL029979, 2007. a, b
Short summary
We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM2.5 currently collected in existing air pollution monitoring networks and field campaigns.
We propose a spectroscopic method for estimating several mixture-averaged molecular properties...
