Sequential SEM-EDS, PLM, and MRS Microanalysis of Individual Atmospheric Particles: A Useful Tool for Assigning Emission Sources
Abstract
1. Introduction
2. Materials and Methods
2.1. Monitoring Stations and Total Suspended Particulates (TSP) Sampling
2.2. Elemental Mapping of TSP Samples Subject to SEM-EDS and PLM
2.3. SEM-EDS/PLM/MRS Characterization of Individual Microparticles
3. Results and Discussion
3.1. Elemental Mapping of TSP Samples Subject to SEM-EDS and PLM
3.2. SEM-EDS/PLM/MRS Characterization of Individual Microparticles
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Xing, Y.-F.; Xu, Y.-H.; Shi, M.-H.; Lian, Y.-X. The impact of PM2.5 on the human respiratory system. J. Thorac. Dis. 2016, 8, E69–E74. [Google Scholar] [PubMed]
- Grahame, T.J.; Klemm, R.; Schlesinger, R.B. Public health and components of particulate matter: The changing assessment of black carbon. J. Air Waste Manag. Assoc. 2014, 64, 620–660. [Google Scholar] [CrossRef] [PubMed]
- Betha, R.; Behera, S.N.; Balasubramanian, R. 2013 Southeast Asian Smoke Haze: Fractionation of Particulate-Bound Elements and Associated Health Risk. Environ. Sci. Technol. 2014, 48, 4327–4335. [Google Scholar] [CrossRef]
- Ostro, B.; Broadwin, R.; Green, S.; Feng, W.-Y.; Lipsett, M. Fine Particulate Air Pollution and Mortality in Nine California Counties: Results from CALFINE. Environ. Health Perspect. 2006, 114, 29–33. [Google Scholar] [CrossRef] [PubMed]
- Samoli, E.; Analitis, A.; Touloumi, G.; Schwartz, J.; Anderson, H.R.; Sunyer, J.; Bisanti, L.; Zmirou, D.; Vonk, J.M.; Pek-kanen, J.; et al. Estimating the exposure-response relationships between particulate matter and mortality within the AP-HEA multicity project. Environ. Health Perspect. 2005, 113, 88–95. [Google Scholar] [CrossRef]
- López-Feldman, A.; Heres, D.; Marquez-Padilla, F. Air pollution exposure and COVID-19: A look at mortality in Mexico City using individual-level data. Sci. Total Environ. 2021, 756, 143929. [Google Scholar] [CrossRef]
- Travaglio, M.; Yu, Y.; Popovic, R.; Selley, L.; Leal, N.S.; Martins, L.M. Links between air pollution and COVID-19 in England. Environ. Pollut. 2021, 268, 115859. [Google Scholar] [CrossRef] [PubMed]
- Zoran, M.A.; Savastru, R.S.; Savastru, D.M.; Tautan, M.N. Assessing the relationship between surface levels of PM2.5 and PM10 particulate matter impact on COVID-19 in Milan, Italy. Sci. Total Environ. 2020, 738, 139825. [Google Scholar] [CrossRef]
- Hopke, P.K.; Dai, Q.; Li, L.; Feng, Y. Global review of recent source apportionments for airborne particulate matter. Sci. Total Environ. 2020, 740, 140091. [Google Scholar] [CrossRef]
- Boldo, E.; Linares, C.; Lumbreras, J.; Borge, R.; Narros, A.; García-Pérez, J.; Fernández-Navarro, P.; Pérez-Gómez, B.; Aragonés, N.; Ramis, R. Health impact assessment of a reduction in ambient PM2.5 levels in Spain. Environ. Int. 2011, 37, 342–348. [Google Scholar] [CrossRef]
- Hopke, P.K. Review of receptor modeling methods for source apportionment. J. Air Waste Manag. Assoc. 2016, 66, 237–259. [Google Scholar] [CrossRef]
- Coulter, C.T. Users Manual. Office of Air Quality Planning & Standards; EPA-452/R-04-011; U.S. Environmental Protection Agency, USEPA: Raleigh, NC, USA, 2004. [Google Scholar]
- Paatero, P. Least squares formulation of robust non-negative factor analysis. Chemom. Intell. Lab. Syst. 1997, 37, 23–35. [Google Scholar] [CrossRef]
- Shi, G.-L.; Feng, Y.-C.; Zeng, F.; Li, X.; Zhang, Y.-F.; Wang, Y.-Q.; Zhu, T. Use of a Nonnegative Constrained Principal Component Regression Chemical Mass Balance Model to Study the Contributions of Nearly Collinear Sources. Environ. Sci. Technol. 2009, 43, 8867–8873. [Google Scholar] [CrossRef] [PubMed]
- Reff, A.; Eberly, S.I.; Bhave, P.V. Receptor modeling of ambient particulate matter data using positive matrix factoriza-tion: Review of existing methods. J. Air Waste Manag. Assoc. 2007, 57, 146–154. [Google Scholar] [CrossRef] [PubMed]
- Utsunomiya, S.; Jensen, K.A.; Keeler, G.J.; Ewing, R.C. Direct Identification of Trace Metals in Fine and Ultrafine Particles in the Detroit Urban Atmosphere. Environ. Sci. Technol. 2004, 38, 2289–2297. [Google Scholar] [CrossRef]
- Geng, H.; Cheng, F.; Ro, C.U. Single-Particle Characterization of Atmospheric Aerosols Collected at Gosan, Korea, dur-ing the Asian Pacific Regional Aerosol Characterization Experiment Field Campaign Using Low-Z (Atomic Number) Particle Electron Probe X-ray Microanalysis. J. Air Waste Manag. Assoc. 2011, 61, 1183–1191. [Google Scholar] [CrossRef][Green Version]
- Zeb, B.B.; Alam, K.K.; Sorooshian, A.A.; Blaschke, T.; Ahmad, I.; Shahid, I. On the Morphology and Composition of Particulate Matter in an Urban Environment. Aerosol Air Qual. Res. 2018, 18, 1431–1447. [Google Scholar] [CrossRef]
- Ji, Z.; Dai, R.; Zhang, Z. Characterization of fine particulate matter in ambient air by combining TEM and multiple spectroscopic techniques – NMR, FTIR and Raman spectroscopy. Environ. Sci. Process. Impacts 2014, 17, 552–560. [Google Scholar] [CrossRef]
- Salma, I.; Maenhaut, W.; Zemplén-Papp, É.; Záray, G. Comprehensive characterisation of atmospheric aerosols in Buda-pest, Hungary: Physicochemical properties of inorganic species. Atmos. Environ. 2001, 35, 4367–4378. [Google Scholar] [CrossRef]
- Casuccio, G.S.; Schlaegle, S.F.; Lersch, T.L.; Huffman, G.P.; Chen, Y.; Shah, N. Measurement of fine particulate matter using electron microscopy techniques. Fuel Process. Technol. 2004, 85, 763–779. [Google Scholar] [CrossRef]
- Gokhale, S.; Patil, R. Uncertainty in modelling PM10 and PM2.5 at a non-signalized traffic roundabout. Atmos. Pollut. Res. 2010, 1, 59–70. [Google Scholar] [CrossRef][Green Version]
- Adachi, K.; Chung, S.H.; Buseck, P.R. Shapes of soot aerosol particles and implications for their effects on climate. J. Geophys. Res. Space Phys. 2010, 115, 1–9. [Google Scholar] [CrossRef]
- Ghio, A.J.; Devlin, R.B. Inflammatory Lung Injury after Bronchial Instillation of Air Pollution Particles. Am. J. Respir. Crit. Care Med. 2001, 164, 704–708. [Google Scholar] [CrossRef] [PubMed]
- Craig, R.L.; Bondy, A.L.; Ault, A.P.; Craig, R.L.; Bondy, A.L.; Computer-, A.P.A. Computer-controlled Raman microspec-troscopy (CC-Raman): A method for the rapid characterization of individual atmospheric aerosol particles. Aerosol Sci. Technol. 2017, 51, 1099–1112. [Google Scholar] [CrossRef]
- Doughty, D.C.; Hill, S.C. Raman spectra of atmospheric particles measured in Maryland, USA over 22.5 h using an automated aerosol Raman spectrometer. J. Quant. Spectrosc. Radiat. Transf. 2020, 244, 106839. [Google Scholar] [CrossRef]
- Jentzsch, P.V.; Kampe, B.; Ciobotă, V.; Rösch, P.; Popp, J. Inorganic salts in atmospheric particulate matter: Raman spectroscopy as an analytical tool. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2013, 115, 697–708. [Google Scholar] [CrossRef]
- Ghosal, S.; Macher, J.M.; Ahmed, K. Raman Microspectroscopy-Based Identification of Individual Fungal Spores as Poten-tial Indicators of Indoor Contamination and Moisture-Related Building Damage. Environ. Sci. Technol. 2012, 46, 6088–6095. [Google Scholar] [CrossRef]
- Bondy, A.L.; Craig, R.L.; Zhang, Z.; Gold, A.; Surratt, J.D.; Ault, A.P. Isoprene-Derived Organosulfates: Vibrational Mode Analysis by Raman Spectroscopy, Acidity-Dependent Spectral Modes, and Observation in Individual Atmospheric Particles. J. Phys. Chem. A 2017, 122, 303–315. [Google Scholar] [CrossRef]
- Sobanska, S.; Hwang, H.; Choël, M.; Jung, H.-J.; Eom, H.-J.; Kim, H.; Barbillat, J.; Ro, C.-U. Investigation of the Chemical Mixing State of Individual Asian Dust Particles by the Combined Use of Electron Probe X-ray Microanalysis and Raman Microspectrometry. Anal. Chem. 2012, 84, 3145–3154. [Google Scholar] [CrossRef]
- Tóth, Á.; Hoffer, A.; Pósfai, M.; Ajtai, T.; Kónya, Z.; Blazsó, M.; Czégény, Z.; Kiss, G.; Bozóki, Z.; Gelencsér, A. Chemical characterization of laboratory-generated tar ball particles. Atmos. Chem. Phys. 2018, 18, 10407–10418. [Google Scholar] [CrossRef]
- Petean, I.; Mocanu, A.; Păltinean, G.A.; Ţărcan, R.; Muntean, D.F.; Mureşan, L.; Arghir, G.; Tomoaia-Cotişel, M. Physi-co-chemical study concerning atmospheric particulate matter hazard. Stud. Univ. Babes-Bolyai Chem. 2017, 62, 33–46. [Google Scholar]
- Hindy, K.T.; Baghdady, A.R.; Howari, F.M.; Abdelmaksoud, A.S. A Qualitative Study of Airborne Minerals and Associated Organic Compounds in Southeast of Cairo, Egypt. Int. J. Environ. Res. Public Health 2018, 15, 568. [Google Scholar] [CrossRef]
- Comite, V.; Pozo-Antonio, J.S.; Cardell, C.; Randazzo, L.; La Russa, M.F.; Fermo, P. A multi-analytical approach for the characterization of black crusts on the facade of an historical cathedral. Microchem. J. 2020, 158, 105121. [Google Scholar] [CrossRef]
- Morillas, H.; Marcaida, I.; García-Florentino, C.; Maguregui, M.; Arana, G.; Madariaga, J.M. Micro-Raman and SEM-EDS analyses to evaluate the nature of salt clusters present in secondary marine aerosol. Sci. Total Environ. 2018, 615, 691–697. [Google Scholar] [CrossRef] [PubMed]
- Fermo, P.; Mearini, A.; Bonomi, R.; Arrighetti, E.; Comite, V. An integrated analytical approach for the characterization of repainted wooden statues dated to the fifteenth century. Microchem. J. 2020, 157, 105072. [Google Scholar] [CrossRef]
- Fermo, P.; Comite, V.; Ciantelli, C.; Sardella, A.; Bonazza, A. A multi-analytical approach to study the chemical composi-tion of total suspended particulate matter (TSP) to assess the impact on urban monumental heritage in Florence. Sci. Total Environ. 2020, 740, 140055. [Google Scholar] [CrossRef]
- INEGI/Instituto Nacional de Estadística y Geografía Anuario estadístico y geográfico de Nuevo León 2017. Gob. Del Estado Nuevo León 2017, 1, 9–53.
- Green, J.; Sánchez, S. Air Quality in Latin America: An Overview—2012 Edition. Clean Air Institute. Updated version May 2013. Available online: https://www.yumpu.com/en/document/view/41258091/air-quality-in-latin-america-an-overview-clean-air-institute (accessed on 23 January 2021).
- Centro Mario Molina Análisis de la Contaminación por PM2.5 en la Ciudad de Monterrey, Nuevo León, Enfocado a la Identificación de Medidas Estratégicas de Control. 2019, p. 8. Available online: https://centromariomolina.org/wp-content/uploads/2019/05/3.-ResumenEjecutivo_CalidadAire_2018.pdf (accessed on 17 February 2021).
- Informe nacional de la calidad de aire México. Inst. Nac. Ecol. Cambio Climático 2018, 53, 1689–1699.
- Mancilla, Y.; Paniagua, I.Y.H.; Mendoza, A. Spatial differences in ambient coarse and fine particles in the Monterrey metropolitan area, Mexico: Implications for source contribution. J. Air Waste Manag. Assoc. 2019, 69, 548–564. [Google Scholar] [CrossRef] [PubMed]
- de Monterrey, S.D.S. Programa de Gestión para Mejorar la Calidad del Aire del Estado de Nuevo León ProAire 2016–2025. p. 634. Available online: https://www.google.com.hk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjn9aOv9fLuAhXG7WEKHU8iDLgQFjABegQIAhAD&url=https%3A%2F%2Fwww.gob.mx%2Fsemarnat%2Facciones-y-programas%2Fprogramas-de-gestion-para-mejorar-la-calidad-del-aire&usg=AOvVaw1o4d1gjUfhPtqngbG8FYHh (accessed on 17 February 2021).
- INAFED, Plan Municipal de Desarrollo de Cadereyta 2018–2021. Periódico Of. del Estado. 2018. Available online: http://cadereyta.gob.mx/wp-content/uploads/2019/05/PLAN-MUNICIPAL-DE-DESARROLLO-2018-2021.pdf (accessed on 17 February 2021).
- U.S. EPA. Environmental Protection Agency Methods Compendium Method IO-2.1; US Environmental Protection Agency: Cincinnati, OH, USA, 1999; 30p. [Google Scholar]
- Li, W.; Shao, L. Transmission electron microscopy study of aerosol particles from the brown hazes in northern China. J. Geophys. Res. Space Phys. 2009, 114, 1–10. [Google Scholar] [CrossRef]
- Aragon-Piña, A. ¿Cómo son las Partículas Atmosféricas Antropogénicas y Cuál es su Relación con los Diversos Tipos de Fuentes Contam-Inantes? Palibrio: Bloomington, IN, USA, 2011; ISBN 978-1-4633-0202-3. [Google Scholar]
- González, L.T.; Rodríguez, F.; Sánchez-Domínguez, M.; Leyva-Porras, C.; Silva-Vidaurri, L.; Acuna-Askar, K.; Kharisov, B.; Chiu, J.V.; Barbosa, J.A. Chemical and morphological characterization of TSP and PM2.5 by SEM-EDS, XPS and XRD collected in the metropolitan area of Monterrey, Mexico. Atmos. Environ. 2016, 143, 249–260. [Google Scholar] [CrossRef]
- Cabadas-Báez, H.V.; Sedov, S.; Jiménez-Álvarez, S.D.P.; Léonard, D.; Ancona-Aragón, I.I.; Hernández-Velázquez, M.L. Soils as a source of raw materials for ancient ceramic production in the Maya region of Mexico: Micromorphological insight. Boletín Soc. Geológica Mex. 2018, 70, 21–48. [Google Scholar] [CrossRef]
- Anthony, J.W.; Bideaux, R.A.; Bladh, K.W.; Nichols, M.C. (Eds.) Handbook of Mineralogy; Mineralogical Society of America: Chantilly, VA, USA; Available online: http://www.handbookofmineralogy.org/ (accessed on 17 February 2021).
- Delly, J.G. Essentials of Polarized Light Microscopy and Ancillary Techniques; The McCrone Group: Westmont, IL, USA, 2007; pp. 1–602. [Google Scholar]
- Pallarés, S.; Gómez, E.T.; Jordán, M.M. Typological characterisation of mineral and combustion airborne particles in-doors in primary schools. Atmosphere 2019, 10, 209. [Google Scholar] [CrossRef]
- Iglesias, J.C.A.; Gomes, O.D.F.M.; Paciornik, S. Automatic recognition of hematite grains under polarized reflected light microscopy through image analysis. Miner. Eng. 2011, 24, 1264–1270. [Google Scholar] [CrossRef]
- González, L.T.; Rodríguez, F.L.; Sánchez-Domínguez, M.; Cavazos, A.; Leyva-Porras, C.; Silva-Vidaurri, L.G.; Askar, K.A.; Kharissov, B.I.; Chiu, J.V.; Barbosa, J.A. Determination of trace metals in TSP and PM 2.5 materials collected in the Metropolitan Area of Monterrey, Mexico: A characterization study by XPS, ICP-AES and SEM-EDS. Atmos. Res. 2017, 196, 8–22. [Google Scholar] [CrossRef]
- Centro Mario Molina. PROYECTO: Propuestas Para el Desarrollo Sustentable de una Ciudad Mexicana. 2019. Available online: https://centromariomolina.org/wp-content/uploads/2019/05/2.-Resumen-Ejecutivo-Monterrey_218.pdf (accessed on 17 February 2021).
- González, L.T.; Longoria-Rodríguez, F.E.; Sánchez-Domínguez, M.; Leyva-Porras, C.; Acuña-Askar, K.; Kharissov, B.I.; Arizpe-Zapata, A.; Alfaro-Barbosa, J.M. Seasonal variation and chemical composition of particulate matter: A study by XPS, ICP-AES and sequential microanalysis using Raman with SEM/EDS. J. Environ. Sci. 2018, 74, 32–49. [Google Scholar] [CrossRef]
- Worobiec, A.; Potgieter-Vermaak, S.; Brooker, A.; Darchuk, L.; Stefaniak, E.; Grieken, R. Van Interfaced SEM/EDX and micro-Raman Spectrometry for characterisation of heterogeneous environmental particles—Fundamental and practical challenges. Microchem. J. 2010, 94, 65–72. [Google Scholar] [CrossRef]
- Longoria-Rodríguez, F.E.; González, L.T.; Mendoza, A.; Leyva-Porras, C.; Arizpe-Zapata, A.; Esneider-Alcalá, M.; Acu-ña-Askar, K.; Gaspar-Ramirez, O.; López-Ayala, O.; Alfaro-Barbosa, J.M.; et al. Environmental Levels, Sources, and Can-cer Risk Assessment of PAHs Associated with PM2.5 and TSP in Monterrey Metropolitan Area. Arch. Environ. Contam. Toxicol. 2020, 78, 377–391. [Google Scholar] [CrossRef] [PubMed]
- López-Ayala, O.; González-Hernández, L.T.; Alcantar-Rosales, V.M.; Elizarragaz-de la Rosa, D.; Heras-Ramírez, M.E.; Silva-Vidaurri, L.G.; Alfaro-Barbosa, J.M.; Gaspar-Ramírez, O. Levels of polycyclic aromatic hydrocarbons associated with particulate matter in a highly urbanized and industrialized region in northeastern Mexico. Atmos. Pollut. Res. 2019, 10, 1655–1662. [Google Scholar] [CrossRef]
- Sze, S.K.; Siddique, N.; Sloan, J.J.; Escribano, R. Raman spectroscopic characterization of carbonaceous aerosols. Atmos. Environ. 2001, 35, 561–568. [Google Scholar] [CrossRef]
- Ivleva, N.P.; McKeon, U.; Niessner, R.; Pöschl, U. Raman Microspectroscopic Analysis of Size-Resolved Atmospheric Aerosol Particle Samples Collected with an ELPI: Soot, Humic-Like Substances, and Inorganic Compounds. Aerosol Sci. Technol. 2007, 41, 655–671. [Google Scholar] [CrossRef]
- Michaelian, K.H. The Raman spectrum of kaolinite #9 at 21 °C. Can. J. Chem. 1986, 64, 285–294. [Google Scholar] [CrossRef]
- Yadav, A.K.; Singh, P. A review of the structures of oxide glasses by Raman spectroscopy. RSC Adv. 2015, 5, 67583–67609. [Google Scholar] [CrossRef]
- Rivera, B.H.; Rodriguez, M.G. Characterization of Airborne Particles Collected from Car Engine Air Filters Using SEM and EDX Techniques. Int. J. Environ. Res. Public Health 2016, 13, 985. [Google Scholar] [CrossRef] [PubMed]
- Wu, Z.; Liu, F.; Fan, W. Characteristics of PM10 and PM2.5 at Mount Wutai Buddhism Scenic Spot, Shanxi, China. Atmosphere 2015, 6, 1195–1210. [Google Scholar] [CrossRef]
- Micic, M.; Leblanc, R.M.; Markovic, D.; Stamatovic, A.; Vukelic, N.; Polic, P. Atlas of the tropospheric aerosols from Bel-grade troposphere. Fresenius Environ. Bull. 2003, 12, 1015–1024. [Google Scholar]
- Inoue, J.; Yoshie, A.; Tanaka, T.; Onji, T.; Inoue, Y. Disappearance and alteration process of charcoal fragments in cumula-tive soils studied using Raman spectroscopy. Geoderma 2017, 285, 164–172. [Google Scholar] [CrossRef]
- Smith, M.W.; Dallmeyer, I.; Johnson, T.J.; Brauer, C.S.; McEwen, J.-S.; Espinal, J.F.; Garcia-Perez, M. Structural analysis of char by Raman spectroscopy: Improving band assignments through computational calculations from first principles. Carbon 2016, 100, 678–692. [Google Scholar] [CrossRef]
- Mancilla, Y.; Mendoza, A.; Fraser, M.P.; Herckes, P. Organic composition and source apportionment of fine aerosol at Monterrey, Mexico, based on organic markers. Atmos. Chem. Phys. Discuss. 2016, 16, 953–970. [Google Scholar] [CrossRef]
- Chacón, D.; Giner, M.; Vázquez, M.; Roe, S.; Maldonado, J.; Lindquist, H.; Strode, B.; Anderson, R.; Quiroz, C.; Scheiber, J. Emisión de Gases de Efecto Invernadero en Nuevo León y Proyecciones de Referencia 1990–2025; Banco de Desarrollo del América del Norte: San Antonioc, TX, USA, 2010; ISBN 9786078021109. [Google Scholar]
- Hanesch, M. Raman spectroscopy of iron oxides and (oxy)hydroxides at low laser power and possible applications in environmental magnetic studies. Geophys. J. Int. 2009, 177, 941–948. [Google Scholar] [CrossRef]
- Thorpe, A.; Harrison, R.M. Sources and properties of non-exhaust particulate matter from road traffic: A review. Sci. Total Environ. 2008, 400, 270–282. [Google Scholar] [CrossRef] [PubMed]
- Gonet, T.; Maher, B.A. Airborne, Vehicle-Derived Fe-Bearing Nanoparticles in the Urban Environment: A Review. Environ. Sci. Technol. 2019, 53, 9970–9991. [Google Scholar] [CrossRef] [PubMed]
- Walker, D.; Dasgupta, R.; Li, J.; Buono, A. Nonstoichiometry and growth of some Fe carbides. Contrib. Miner. Pet. 2013, 166, 935–957. [Google Scholar] [CrossRef]
- Urbonaite, S.; Hälldahl, L.; Svensson, G. Raman spectroscopy studies of carbide derived carbons. Carbon 2008, 46, 1942–1947. [Google Scholar] [CrossRef]
- Rantitsch, G.; Bhattacharyya, A.; Schenk, J.; Lünsdorf, N.K. Assessing the quality of metallurgical coke by Raman spec-troscopy. Int. J. Coal Geol. 2014, 130, 1–7. [Google Scholar] [CrossRef]
- Osacky, M.; Geramian, M.; Dyar, M.D.; Sklute, E.C.; Valter, M.; Ivey, D.G.; Liu, Q.; Etsell, T.H. Characterisation of petrologic end members of oil sands from the athabasca region, Alberta, Canada. Can. J. Chem. Eng. 2013, 91, 1402–1415. [Google Scholar] [CrossRef]
- Iglesias, J.C. Álvarez; Augusto, K.S.; Gomes, O.D.F.M.; Domingues, A.L.A.; Vieira, M.B.; Casagrande, C.; Paciornik, S. Automatic characterization of iron ore by digital microscopy and image analysis. J. Mater. Res. Technol. 2018, 7, 376–380. [Google Scholar] [CrossRef]
- Labrada-Delgado, G.; Aragon-Pina, A.; Campos-Ramos, A.; Castro-Romero, T.; Amador-Munoz, O.; Villalobos-Pietrini, R. Chemical and morphological characterization of PM2.5 collected during MILAGRO campaign using scanning electron microscopy. Atmos. Pollut. Res. 2012, 3, 289–300. [Google Scholar] [CrossRef]
- Doughty, D.C.; Hill, S.C. Journal of Quantitative Spectroscopy & Radiative Transfer Automated aerosol Raman spec-trometer for semi-continuous sampling of atmospheric aerosol. J. Quant. Spectrosc. Radiat. Transf. 2017, 188, 103–117. [Google Scholar]
% Phases | Monitoring Station | ||
---|---|---|---|
Obispado | Santa Catarina | Cadereyta | |
Calcite | 72.3 ± 1.6 | 77.9 ± 2.1 | 71 ± 1.9 |
Quartz | 11.7 ± 1.2 | 10.3 ± 1.6 | 15.0 ± 1.3 |
Gypsum | 11.1 ± 0.9 | 7.3 ± 1.1 | 10.4 ± 0.8 |
Aluminosilicates | 3.0 ± 0.8 | 3.2 ± 1.0 | 1.7 ± 0.7 |
Hematite | 1.8 ± 0.4 | 1.3 ± 0.7 | 1.9 ± 0.6 |
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Longoria-Rodríguez, F.E.; González, L.T.; Mancilla, Y.; Acuña-Askar, K.; Arizpe-Zapata, J.A.; González, J.; Kharissova, O.V.; Mendoza, A. Sequential SEM-EDS, PLM, and MRS Microanalysis of Individual Atmospheric Particles: A Useful Tool for Assigning Emission Sources. Toxics 2021, 9, 37. https://doi.org/10.3390/toxics9020037
Longoria-Rodríguez FE, González LT, Mancilla Y, Acuña-Askar K, Arizpe-Zapata JA, González J, Kharissova OV, Mendoza A. Sequential SEM-EDS, PLM, and MRS Microanalysis of Individual Atmospheric Particles: A Useful Tool for Assigning Emission Sources. Toxics. 2021; 9(2):37. https://doi.org/10.3390/toxics9020037
Chicago/Turabian StyleLongoria-Rodríguez, Francisco E., Lucy T. González, Yasmany Mancilla, Karim Acuña-Askar, Jesús Alejandro Arizpe-Zapata, Jessica González, Oxana V. Kharissova, and Alberto Mendoza. 2021. "Sequential SEM-EDS, PLM, and MRS Microanalysis of Individual Atmospheric Particles: A Useful Tool for Assigning Emission Sources" Toxics 9, no. 2: 37. https://doi.org/10.3390/toxics9020037
APA StyleLongoria-Rodríguez, F. E., González, L. T., Mancilla, Y., Acuña-Askar, K., Arizpe-Zapata, J. A., González, J., Kharissova, O. V., & Mendoza, A. (2021). Sequential SEM-EDS, PLM, and MRS Microanalysis of Individual Atmospheric Particles: A Useful Tool for Assigning Emission Sources. Toxics, 9(2), 37. https://doi.org/10.3390/toxics9020037