Ambient aerosol composition by infrared spectroscopy and partial least-squares in the chemical speciation network: Organic carbon with functional group identification

References

• Abdi, H., and Williams, L. J. (2010). Principal Component Analysis. Wiley Interdisciplinary Rev.: Comput. Statist., 2:433–459.
   Google Scholar
• Allen, D. T., Palen, E. J., Haimov, M. I., Hering, S. V., and Young, J. R. (1994). Fourier Transform Infrared Spectroscopy of Aerosol Collected in a Low Pressure Impactor (LPI/FTIR): Method Development and Field Calibration. Aerosol Sci. Technol., 21:325–342.
   Web of Science ®Google Scholar
• Baumann, K., Jayanty, R. K. M., and Flanagan, J. B. (2008). Fine Particulate Matter Source Apportionment for the Chemical Speciation Trends Network Site at Birmingham, Alabama, Using Positive Matrix Factorization. J. Air Waste Manag. Assoc., 58:27–44.
   PubMedGoogle Scholar
• Blando, J. D., Porcja, R. J., and Turpin, B. J. (2001). Issues in the Quantitation of Functional Groups by FTIR Spectroscopic Analysis of Impactor-Collected Aerosol Samples. Aerosol Sci. Technol., 35:899–908.
   Web of Science ®Google Scholar
• Bocklitz, T., Walter, A., Hartmann, K., Rosch, P., and Popp, J. (2011). How to Pre-Process Raman Spectra for Reliable and Stable Models? Anal. Chim. Acta, 704:47–56.
   PubMed Web of Science ®Google Scholar
• Boer, G. J., Sokolik, I. N., and Martin, S. T. (2007). Infrared Optical Constants of Aqueous Sulfate–Nitrate–Ammonium Multi-Component Tropospheric Aerosols from Attenuated Total Reflectance Measurements—Part I: Results and Analysis of Spectral Absorbing Features. J. Quant. Spectrosc. Radiat. Transfer, 108:17–38.
   Web of Science ®Google Scholar
• Cai, W., Li, Y., and Shao, X. (2008). A Variable Selection Method Based on Uninformative Variable Elimination for Multivariate Calibration of Near-Infrared Spectra. Chemom. Intell. Lab. Syst. 90:188–194.
   Google Scholar
• Carlton, A. G., Turpin, B. J., Altieri, K. E., Seitzinger, S. P., Mathur, R., Roselle, S. J., and Weber, R. J. (2008). CMAQ Model Performance Enhanced When in-Cloud Secondary Organic Aerosol is Included: Comparisons of Organic Carbon Predictions with Measurements. Environ. Sci. Technol., 42:8798–8802.
   PubMed Web of Science ®Google Scholar
• Centner, V., Massart, D.-L., de Noord, O. E., de Jong, S., Vandeginste, B. M., and Sterna, C. (1996). Elimination of Uninformative Variables for Multivariate Calibration. Anal. Chem., 68:3851–3858.
   PubMed Web of Science ®Google Scholar
• Chen, Z.-P., Li, L.-M., Yu, R.-Q., Littlejohn, D., Nordon, A., Morris, J., Dann, A. S., Jeffkins, P. A., Richardson, M. D., and Stimpson, S. L. (2011). Systematic Prediction Error Correction: A Novel Strategy for Maintaining the Predictive Abilities of Multivariate Calibration Models. Analyst, 136:98–106.
   PubMed Web of Science ®Google Scholar
• Chen, L.-W. A., Watson, J. G., Chow, J. C., DuBois, D. W., and Herschberger, L. (2010). Chemical Mass Balance Source Apportionment for Combined PM 2.5 Measurements from US Non-Urban and Urban Long-Term Networks. Atmos. Environ., 44:4908–4918.
   Web of Science ®Google Scholar
• Chong, I.-G., and Jun, C.-H. (2005a). Performance of Some Variable Selection Methods When Multicollinearity is Present. Chem. Intel. Laboratory Syst., 78:103–112.
   Web of Science ®Google Scholar
• Chong, I.-G., and Jun, C.-H. (2005b). Performance of Some Variable Selection Methods When Multicollinearity is Present. Chemometr. Intelligent Laboratory Syst., 78:103–112.
   Web of Science ®Google Scholar
• Chow, J., Lowenthal, D., Chen, L. W. A., Wang, X., and Watson, J. (2015). Mass Reconstruction Methods for PM2.5: A Review. Air Qual. Atmos. Health, 8:243–263.
   PubMed Web of Science ®Google Scholar
• Chow, J. C., Watson, J. G., Chen, L.-W. A., Chang, M. O., Robinson, N. F., Trimble, D., and Kohl, S. (2007). The IMPROVE_A Temperature Protocol for Thermal/Optical Carbon Analysis: Maintaining Consistency with a Long-Term Database. J. Air Waste Manag. Assoc., 57:1014–1023.
   PubMedGoogle Scholar
• Chow, J. C., Watson, J. G., Pritchett, L. C., Pierson, W. R., Frazier, C. A., and Purcell, R. G. (1993). The DRI Thermal/Optical Reflectance Carbon Analysis System: Description, Evaluation and Applications in US Air Quality Studies. Atmos. Environ. Part A. General Topics, 27:1185–1201.
   Web of Science ®Google Scholar
• Cowe, I. A., and McNicol, J. W. (1985). The Use of Principal Components in the Analysis of Near-Infrared Spectra. Appl. Spectrosc., 39:257–266.
   Web of Science ®Google Scholar
• Dillner, A. M., Phuah, C. H., and Turner, J. R. (2009). Effects of Post-Sampling Conditions on Ambient Carbon Aerosol Filter Measurements. Atmos. Environ., 43:5937–5943.
   Web of Science ®Google Scholar
• Dillner, A. M., and Takahama, S. (2015a). Predicting Ambient Aerosol Thermal-Optical Reflectance (TOR) Measurements from Infrared Spectra: Organic Carbon. Atmos. Measur. Tech., 8:1097–1109.
   Web of Science ®Google Scholar
• Dillner, A. M., and Takahama, S. (2015b). Predicting Ambient Aerosol Thermal-Optical Reflectance Measurements from Infrared Spectra: Elemental Carbon. Atmos. Measur. Techn., 8:4013–4023.
   Web of Science ®Google Scholar
• Dixon, S. J., and Brereton, R. G. (2009). Comparison of Performance of Five Common Classifiers Represented as Boundary Methods: Euclidean Distance to Centroids, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Learning Vector Quantization and Support Vector Machines, as Dependent on Data Structure. Chemometr. Intell. Lab. Syst., 95:1–17.
   Web of Science ®Google Scholar
• Duarte, R. M. B. O., Santos, E. B. H., Pio, C. A., and Duarte, A. C. (2007). Comparison of Structural Features of Water-Soluble Organic Matter from Atmospheric Aerosols with Those of Aquatic Humic Substances. Atmos. Environ., 41:8100–8113.
   Web of Science ®Google Scholar
• Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I. (2002). Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations. J. Atmos. Sci., 59:590–608.
   Web of Science ®Google Scholar
• Efron, B., and Tibshirani, R. (1993). An Introduction to the Bootstrap. Chapman & Hall, Boca Raton, Florida.
   Google Scholar
• Feudale, R. N., Woody, N. A., Tan, H., Myles, A. J., Brown, S. D., and Ferré, J. (2002). Transfer of Multivariate Calibration Models: A Review. Chemometr. Intell. Lab. Syst., 64:181–192.
   Web of Science ®Google Scholar
• Fiegland, L. R., McCorn Saint Fleur, M., and Morris, J. R. (2005). Reactions of C C-Terminated Self-Assembled Monolayers with Gas-Phase Ozone. Langmuir, 21:2660–2661.
   PubMed Web of Science ®Google Scholar
• Gardner, M. J., and Altman, D. G. (1986). Confidence Intervals Rather Than P Values: Estimation Rather Than Hypothesis Testing. BMJ, 292:746–750.
   PubMed Web of Science ®Google Scholar
• Geladi, P., and Kowalski, B. R. (1986). Partial Least-Squares Regression: A Tutorial. Anal. Chim. Acta, 185:1–17.
   Web of Science ®Google Scholar
• George, K. M., Ruthenburg, T. C., Smith, J., Yu, L., Zhang, Q., Anastasio, C., and Dillner, A. M. (2015). FT-IR Quantification of the Carbonyl Functional Group in Aqueous-Phase Secondary Organic Aerosol from Phenols. Atmos. Environ., 100:230–237.
   Web of Science ®Google Scholar
• Graber, E., and Rudich, Y. (2006). Atmospheric HULIS: How Humic-Like are They? A Comprehensive and Critical Review. Atmos. Chem. Phys., 6:729–753.
   Web of Science ®Google Scholar
• Griffiths, P. R., and De Haseth, J. A. (2007). Fourier Transform Infrared Spectrometry. John Wiley & Sons, Hoboken, New Jersey.
   Google Scholar
• Havers, N., Burba, P., Lambert, J., and Klockow, D. (1998). Spectroscopic Characterization of Humic-Like Substances in Airborne Particulate Matter. J. Atmos. Chem., 29:45–54.
   Web of Science ®Google Scholar
• Hay, M. B., and Myneni, S. C. (2007). Structural Environments of Carboxyl Groups in Natural Organic Molecules from Terrestrial Systems. Part 1: Infrared Spectroscopy. Geochim. Cosmochim. Acta, 71:3518–3532.
   Web of Science ®Google Scholar
• Helland, I. S. (1988). On the Structure of Partial Least Squares Regression. Commun. Stat. Simulat. Comput., 17:581–607.
   Web of Science ®Google Scholar
• Ingle Jr, J. D., and Crouch, S. R. (1988). Spectrochemical Analysis. Prentice Hall College Book Division, Old Tappan, New Jersey.
   Google Scholar
• Isaksson, T., and Næs, T. (1988). The Effect of Multiplicative Scatter Correction (MSC) and Linearity Improvement in NIR Spectroscopy. Appl. Spectrosc., 42:1273–1284.
   Web of Science ®Google Scholar
• Jimenez, J., Canagaratna, M., Donahue, N., Prevot, A., Zhang, Q., Kroll, J., DeCarlo, P., Allan, J., Coe, H., and Ng, N. (2009a). Evolution of Organic Aerosols in the Atmosphere. Science, 326:1525–1529.
   PubMed Web of Science ®Google Scholar
• 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., 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. (2009b). Evolution of Organic Aerosols in the Atmosphere. Science, 326:1525–1529.
   PubMed Web of Science ®Google Scholar
• Kim, E., Hopke, P. K., and Edgerton, E. S. (2003). Source Identification of Atlanta Aerosol by Positive Matrix Factorization. J. Air Waste Manag. Assoc., 53:731–739.
   PubMedGoogle Scholar
• Kroll, J. H., and Seinfeld, J. H. (2008). Chemistry of Secondary Organic Aerosol: Formation and Evolution of Low-Volatility Organics in the Atmosphere. Atmos. Environ., 42:3593–3624.
   Web of Science ®Google Scholar
• Krzanowski, W. J. (1983). Cross-Validatory Choice in Principal Component Analysis; Some Sampling Results. J. Statist. Comput. Simulat., 18:299–314.
   Web of Science ®Google Scholar
• Krämer, N., and Sugiyama, M. (2011). The Degrees of Freedom of Partial Least Squares Regression. J. Amer. Statist. Assoc., 106:697–705.
   Web of Science ®Google Scholar
• Lee, E., Chan, C. K., and Paatero, P. (1999). Application of Positive Matrix Factorization in Source Apportionment of Particulate Pollutants in Hong Kong. Atmos. Environ., 33:3201–3212.
   Web of Science ®Google Scholar
• Liang, C., and Krimm, S. (1956). Infrared Spectra of High Polymers. III. Polytetrafluoroethylene and Polychlorotrifluoroethylene. J. Chem. Phys., 25:563–571.
   Web of Science ®Google Scholar
• Li, B., Morris, J., and Martin, E. B. (2002). Model Selection for Partial Least Squares Regression. Chemometr. Intell. Lab. Syst., 64:79–89.
   Web of Science ®Google Scholar
• Liu, S., Shilling, J. E., Song, C., Hiranuma, N., Zaveri, R. A., and Russell, L. M. (2012). Hydrolysis of Organonitrate Functional Groups in Aerosol Particles. Aerosol Sci. Technol., 46:1359–1369.
   Web of Science ®Google Scholar
• Malm, W. C., and Hand, J. L. (2007). An Examination of the Physical and Optical Properties of Aerosols Collected in the IMPROVE Program. Atmos. Environ., 41:3407–3427.
   Web of Science ®Google Scholar
• Malm, W. C., Schichtel, B. A., and Pitchford, M. L. (2011). Uncertainties in PM2.5 Gravimetric and Speciation Measurements and What We Can Learn from Them. J. Air Waste Manag. Assoc., 61:1131–1149.
   PubMedGoogle Scholar
• Maria, S. F., Russell, L. M., Turpin, B. J., and Porcja, R. J. (2002). FTIR Measurements of Functional Groups and Organic Mass in Aerosol Samples Over the Caribbean. Atmos. Environ., 36:5185–5196.
   Web of Science ®Google Scholar
• Mayo, D. W., Miller, F. A., and Hannah, R. W. (2004). Course Notes on the Interpretation of Infrared and Raman Spectra. John Wiley & Sons, Hoboken, New Jersey.
   Google Scholar
• McDade, C. E., Dillner, A. M., and Indresand, H. (2009). Particulate Matter Sample Deposit Geometry and Effective Filter Face Velocities. J. Air Waste Manag. Assoc., 59:1045–1048.
   PubMedGoogle Scholar
• McDow, S. R., and Huntzicker, J. J. (1990). Vapor Adsorption Artifact in the Sampling of Organic Aerosol: Face Velocity Effects. Atmos. Environ. Part A. General Topics, 24:2563–2571.
   Web of Science ®Google Scholar
• Mehmood, T., Liland, K. H., Snipen, L., and Sæbø, S. (2012). A Review of Variable Selection Methods in Partial Least Squares Regression. Chemometr. Intell. Lab. Syst., 118:62–69.
   Web of Science ®Google Scholar
• Miller, F. A., and Wilkins, C. H. (1952). Infrared Spectra and Characteristic Frequencies of Inorganic Ions. Anal. Chem., 24:1253–1294.
   Web of Science ®Google Scholar
• Nieuwoudt, H. H., Prior, B. A., Pretorius, I. S., Manley, M., and Bauer, F. F. (2004). Principal Component Analysis Applied to Fourier Transform Infrared Spectroscopy for the Design of Calibration Sets for Glycerol Prediction Models in Wine and for the Detection and Classification of Outlier Samples. J. Agric. Food. Chem., 52:3726–3735.
   PubMed Web of Science ®Google Scholar
• Næs, T., Isaksson, T., Fearn, T., and Davies, T. (2002). An User-friendly Guide to Multivariate Calibration and Classification. Nir Publications, Chichester, West Sussex.
   Google Scholar
• Polidori, A., Turpin, B. J., Davidson, C. I., Rodenburg, L. A., and Maimone, F. (2008). Organic PM 2.5: Fractionation by Polarity, FTIR Spectroscopy, and OM/OC Ratio for the Pittsburgh Aerosol. Aerosol Sci. Technol., 42:233–246.
   Web of Science ®Google Scholar
• Pope III, C. A., and Dockery, D. W. (2006). Health Effects of Fine Particulate Air Pollution: Lines That Connect. J. Air Waste Manag. Assoc., 56:709–742.
   PubMed Web of Science ®Google Scholar
• Presser, C., Conny, J. M., and Nazarian, A. (2014). Filter Material Effects on Particle Absorption Optical Properties. Aerosol Sci. Technol., 48:515–529.
   Web of Science ®Google Scholar
• Presto, A. A., Huff Hartz, K. E., and Donahue, N. M. (2005). Secondary Organic Aerosol Production from Terpene Ozonolysis. 2. Effect of NO x Concentration. Environ. Sci. Technol., 39:7046–7054.
   PubMed Web of Science ®Google Scholar
• Pöschl, U. (2005). Atmospheric Aerosols: Composition, Transformation, Climate and Health Effects. Angew. Chem. Int. Ed., 44:7520–7540.
   PubMed Web of Science ®Google Scholar
• Quarti, C., Milani, A., and Castiglioni, C. (2013). Ab Initio Calculation of the IR Spectrum of PTFE: Helical Symmetry and Defects. J. Phys. Chem. B, 117:706–718.
   PubMed Web of Science ®Google Scholar
• Rattigan, O. V., Felton, H. D., Bae, M.-S., Schwab, J. J., and Demerjian, K. L. (2011). Comparison of Long-Term PM 2.5 Carbon Measurements at an Urban and Rural Location in New York. Atmos. Environ., 45:3228–3236.
   Web of Science ®Google Scholar
• Reemtsma, T., These, A., Venkatachari, P., Xia, X., Hopke, P. K., Springer, A., and Linscheid, M. (2006). Identification of Fulvic Acids and Sulfated and Nitrated Analogues in Atmospheric Aerosol by Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Anal. Chem., 78:8299–8304.
   PubMed Web of Science ®Google Scholar
• Reggente, M., Dillner, A. M., and Takahama, S. (2015). Predicting Ambient Aerosol Thermal-Optical Reflectance (TOR) Measurements from Infrared Spectra: Extending the Predictions to Different Years and Different Sites. Atmos. Measur. Techn. Discuss., 8:12433–12474.
   Web of Science ®Google Scholar
• Rogge, W. F., Mazurek, M. A., Hildemann, L. M., Cass, G. R., and Simoneit, B. R. T. (1993). Quantification of Urban Organic Aerosols at a Molecular Level: Identification, Abundance and Seasonal Variation. Atmos. Environ. Part A. General Topics, 27:1309–1330.
   Web of Science ®Google Scholar
• Rosipal, R., and Krämer, N. (2006). Overview and Recent Advances in Partial Least Squares, in Subspace, Latent Structure and Feature Selection, Springer, Berlin, Heidelberg, 34–51.
   Google Scholar
• Russell, L. M. (2003). Aerosol Organic-Mass-to-Organic-Carbon Ratio Measurements. Environ. Sci. Technol., 37:2982–2987.
   PubMed Web of Science ®Google Scholar
• Russell, L. M., Bahadur, R., and Ziemann, P. J. (2011). Identifying Organic Aerosol Sources by Comparing Functional Group Composition in Chamber and Atmospheric Particles. Proc. Natl. Acad. Sci. U.S.A., 108:3516–3521.
   PubMed Web of Science ®Google Scholar
• Ruthenburg, T. C., Perlin, P. C., Liu, V., McDade, C. E., and Dillner, A. M. (2014). 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.
   Web of Science ®Google Scholar
• Saeys, Y., Inza, I., and Larrañaga, P. (2007). A Review of Feature Selection Techniques in Bioinformatics. Bioinformatics, 23:2507–2517.
   PubMed Web of Science ®Google Scholar
• Savitzky, A., and Golay, M. J. E. (1964). Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Anal. Chem., 36:1627–1639.
   Web of Science ®Google Scholar
• Shurvell, H. (2002). Spectra–Structure Correlations in the Mid-and Far-Infrared. Handbook of Vibrational Spectroscopy, 3:1783–1816.
   Google Scholar
• Solomon, P. A., Crumpler, D., Flanagan, J. B., Jayanty, R. K. M., Rickman, E. E., and McDade, C. E. (2014). U.S. National PM2.5 Chemical Speciation Monitoring Networks—CSN and IMPROVE: Description of networks. J. Air Waste Manag. Assoc., 64:1410–1438.
   PubMedGoogle Scholar
• Starkweather Jr, H. W., Ferguson, R. C., Chase, D. B., and Minor, J. M. (1985). Infrared Spectra of Amorphous and Crystalline Poly (tetrafluoroethylene). Macromolecules, 18:1684–1686.
   Web of Science ®Google Scholar
• Takahama, S., Johnson, A., and Russell, L. M. (2013). Quantification of Carboxylic and Carbonyl Functional Groups in Organic Aerosol Infrared Absorbance Spectra. Aerosol Sci. Technol., 47:310–325.
   Web of Science ®Google Scholar
• Takahama, S., Ruggeri, G., and Dillner, A. M. (2016). Analysis of Functional Groups in Atmospheric Aerosols by Infrared Spectroscopy: Sparse Methods for Statistical Selection of Relevant Absorption Bands. Atmos. Meas. Tech. Discuss., 2016:1–42.
   Google Scholar
• Trygg, J., and Wold, S. (2002). Orthogonal Projections to Latent Structures (O-PLS). J. Chemom., 16:119–128.
   Web of Science ®Google Scholar
• Turpin, B. J., Saxena, P., and Andrews, E. (2000). Measuring and Simulating Particulate Organics in the Atmosphere: Problems and Prospects. Atmos. Environ., 34:2983–3013.
   Web of Science ®Google Scholar
• Watson, J. G. (2002). Visibility: Science and Regulation. J. Air Waste Manag. Assoc., 52:628–713.
   PubMedGoogle Scholar
• Weakley, A., Miller, A., Griffiths, P., and Bayman, S. (2014). Quantifying Silica in Filter-Deposited Mine Dusts using Infrared Spectra and Partial Least Squares Regression. Anal. Bioanal. Chem., 406:4715–4724.
   PubMed Web of Science ®Google Scholar
• Weakley, A. T., Warwick, P. C., Bitterwolf, T. E., and Aston, D. E. (2012). Multivariate Analysis of Micro-Raman Spectra of Thermoplastic Polyurethane Blends using Principal Component Analysis and Principal Component Regression. Appl. Spectrosc., 66:1269–1278.
   PubMed Web of Science ®Google Scholar
• Williams, M. N., Grajales, C. A. G., and Kurkiewicz, D. (2013). Assumptions of Multiple Regression: Correcting Two Misconceptions. Pract. Assessment, Res. Evaluat.on, 18:2.
   Google Scholar
• Wold, S., Martens, H., and Wold, H. (1983). The Multivariate Calibration Problem in Chemistry Solved by the PLS Method, in Matrix Pencils, B. Kågström and A. Ruhe, eds., Springer, Berlin Heidelberg, pp. 286–293.
   Google Scholar
• Wold, S., Sjöström, M., and Eriksson, L. (2001). PLS-Regression: A Basic Tool of Chemometrics. Chemometr. Intell. Lab. Syst., 58:109–130.
   Web of Science ®Google Scholar
• Yamamoto, H., Yamaji, H., Abe, Y., Harada, K., Waluyo, D., Fukusaki, E., Kondo, A., Ohno, H., and Fukuda, H. (2009). Dimensionality Reduction for Metabolome Data using PCA, PLS, OPLS, and RFDA with Differential Penalties to Latent Variables. Chemometr. Intell. Lab. Syst., 98:136–142.
   Web of Science ®Google Scholar
• Zappoli, S., Andracchio, A., Fuzzi, S., Facchini, M., Gelencser, A., Kiss, G., Krivacsy, Z., Molnar, A., Meszaros, E., and Hansson, H.-C. (1999). Inorganic, Organic and Macromolecular Components of Fine Aerosol in Different Areas of Europe in Relation to Their Water Solubility. Atmos. Environ., 33:2733–2743.
   Web of Science ®Google Scholar
• Zhang, L., and Garcia-Munoz, S. (2009). A Comparison of Different Methods to Estimate Prediction Uncertainty using Partial Least Squares (PLS): A practitioner's Perspective. Chemometr. Intell. Lab. Syst., 97:152–158.
   Web of Science ®Google Scholar
• Zhang, R., Wang, G., Guo, S., Zamora, M. L., Ying, Q., Lin, Y., Wang, W., Hu, M., and Wang, Y. (2015). Formation of Urban Fine Particulate Matter. Chem. Rev., 115:3803–3855.
   PubMed Web of Science ®Google Scholar