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Chemical Characteristics and Identification of PM10 Sources in Two Lima Districts, Peru
Caracterizaciòn Química e identificación de fuente para PM10 en dos distritos de Lima-Perú
DOI:
https://doi.org/10.15446/dyna.v87n215.83688Palabras clave:
air quality, chemical species, identification of source, PMF, PCA (en)calidad del aire, especies químicas, identificación de fuentes, FMP, ACP (es)
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This study evaluates the concentration of PM10 and PM2.5 and identification of source in the districts of San Juan de Lurigancho and Puente Piedra (PPD) in Lima-Peru. The samples were collected from April to May 2017 by the National Meteorology and Hydrology Service of Peru (Senamhi). The concentration of PM10 and PM2.5, measured by gravimetric techniques, exceeded the international (WHO) and national standards; with maximum values for PM10 and PM2.5 of 160 and 121.56 µg/ m3 in PPD and 295.06 and 154.58 µg/ m3 in SJL. Identification of sources by the Positive Matrix Factorization Model (PMF 5.0) and Principal Component Analysis (ACP), showed similar sources for both districts. In SJL, the combination of vehicular traffic and resuspension of soil dust, marine aerosol and iron and steel industry was determined, while in PPD the resuspension of soil dust, vehicular source, industrial activity and marine aerosol.
El presente estudio evalúa la concentración de PM10 y PM2.5 e identifica las fuentes contaminantes en los distritos de San Juan de Lurigancho (SJL) y Puente Piedra (PPD), Lima-Perú. Las muestras fueron colectadas por el servicio nacional de Meteorología e Hidrología del Perú en Abril a mayo del 2017. La concentración de PM10 y PM2.5, registradas a través de técnicas gravimétricas, excedieron el estándar internacional (OMS) y nacional; encontrándose valores máximos para PM10 y PM2.5 de 160 y 121.56 µg/ m3 en PPD y 295.06 y 154.58 µg/ m3 en SJL. La identificación de fuentes contaminantes para PM10 y PM2.5, obtenidas mediante el Modelo de Factorización de Matriz Positiva (PMF v. 5.0) y análisis por componentes principales (ACP), mostraron fuentes similares para ambos. En SJL se determinó la combinación de tráfico vehicular + resuspensión de polvo de suelo, aerosol marino e industria de hierro y acero; mientras que, en PPD se logró identificar la resuspensión de polvo del suelo, fuente vehicular, actividad industrial y aerosol marino.
Referencias
Bhuyan, P., Deka, P., Prakash, A., Balachandran, S. and Hoque, R.R., Chemical characterization and source apportionment of aerosol over mid Brahmaputra Valley, India. Environmental Pollution, (234), pp. 997-1010, 2018. DOI: 10.1016/j.envpol.2017.12.009
Alleman, L.Y., Lamaison, L., Perdrix, E., Robache, A. and Galloo, J.C., PM10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone. Atmospheric Research, 96(4), pp. 612-625, 2010. DOI: 10.1016/j.atmosres.2010.02.008
Organización Mundial de la Salud (OMS)., Calidad del aire ambiente (exterior) y salud. 2018a [Online]. [date of reference Octuber 20th of 2019]. Available at: https://www.who.int/es/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health#.Xa3WxFFqdl 0.link
Organización Mundial de la Salud (OMS)., Contaminación atmosférica y salud infantil: prescribir aire limpio. Resumen. Ginebra: 2018b (WHO/CED/ PHE/18.01). Licencia: CC BY-NC-SA 3.0 IGO [Online]. [date of reference Octuber 28th of 2019] Available at: https://apps.who.int/iris/bitstream/handle/10665/275548/WHO-CED-PHE-18.01-spa.pdf?ua=1
Gonzales, G. and Steenland K., La salud ambiental en el Perú. Revista Peruana de Medicina Experimental y Salud Pública, 31(2), pp.393-401, 2014. DOI: 10.17843/rpmesp.2014.312.71
Reiss, R., Anderson, E.L., Cross, C.E., Hidy, G., Hoel, D., McClellan, R. and Moolgavkar, S., Evidence of health impacts of sulfate-and nitrate-containing particles in ambient air. Inhalation Toxicology. 19(5), pp. 419-449, 2007. DOI: 10.1080/08958370601174941
Stanek, L.W., Brown, J.S., Stanek, J., Gift, J. and Costa, D.L., Air pollution toxicology—a brief review of the role of the science in shaping the current understanding of air pollution health risks. Toxicological Sciences 120(1), pp. S8-S27, 2010. DOI: 10.1093/toxsci/kfq367
Valavanidis, A., Vlachogianni, T., Fiotakis, K. and Loridas, S., Pulmonary oxidative stress, inflammation and cancer: respirable particulate matter, fibrous dusts and ozone as major causes of lung carcinogenesis through reactive oxygen species mechanisms. International Journal of Environmental Research and Public Health. 10(9), pp. 3886-3907, 2013. DOI: 10.3390/ijerph10093886
Ruzer, L and Harley, N., Health effects of aerosols: mechanism and epidemiology in aerosols Handbook, second Ed., Press. Taylor & Francis Group, Charper 23, 2013, 565 P.
Ministerio de Ambiente (MINAM)., Aprueban Estándares de Calidad Ambiental (ECA) para Aire y establecen disposiciones complementarias. Normas legales. 2017 [Online]. [Consulta, 28 de Diciembre 2018]. Available at: http://www.minam.gob.pe/wp-content/uploads/2017/06/DS-003-2017-MINAM.pdf
Ministerio de Ambiente (MINAM)., Informe nacional de calidad del aire 2013-2014. 2014. [Online]. [Consulta, 20 de Diciembre 2018]. Available at: http://www.minam.gob.pe/calidadambiental/wp-content/uploads/sites/22/2014/07/Informe-Nacional-de-Calidad-del-Aire-2013-2014.pdf
Silva, J., Rojas, J.S., Norabuena, M., Molina, C., Toro, R.O. and Leiva, G.M., Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao, Peru. Environmental Monitoring and Assessment, 189, art. 635, 2017. DOI: 10.1007/s10661-017-6327-2
Instituto Nacional de Estadística e Informática de Peru. (INEI) Estadisticas ambientales. 2018. [Online]. [date of reference November 21th of 2019] Available at: https://www.inei.gob.pe/biblioteca-virtual/boletines/estadisticas-ambientales/1/
Instituto Nacional de Estadística e Informática (INEI). Lima alberga 9 millones 320 mil habitantes al 2018. 2018. [en línea]. [consultado en: Noviembre 29 de 2019]. Disponible en: https://www.inei.gob.pe/prensa/noticias/lima-alberga-9-millones-320-mil-habitantes-al-2018-10521/
Sánchez, C.O.R. y Ordoñez, A.C.C., Evaluación de la calidad en Lima Metropolitana 2015. [en línea]. [consultado en: noviembre 27 de 2019] Disponible en: https://www.senamhi.gob.pe/load/file/01403SENA-7.pdf
Paatero, P., Least squares formulation of robust non-negative factor analysis. Chemometrics and Intelligent Laboratory Systems. 37(1), pp. 23-35, 1997. DOI: 10.1016/S0169-7439(96)00044-5
Paatero, P., The multilinear engine—A table-driven, least squares program for solving multilinear problems, including the n-Way parallel factor analysis mode. Journal of Computational and Graphical Statistics. 8(4), pp. 854-888, 1999. DOI: 10.1080/10618600.1999.10474853
United States Environmental Protection Agency (EPA). EPA Positive Matrix Factorization (PMF) 5.0 Fundamentals and User Guide, 2014. [en línea]. [date of reference May 20th of 2019]. Available at: https://www.epa.gov/sites/production/files/2015-02/documents/pmf_ 5.0_user_guide.pdf, (accessed November 20, 2018).
Hopke, P.K., Review of receptor modeling methods for source apportionment. Journal of the Air & Waste Management Association, 66(3), pp. 237-259, 2016. DOI: 10.1080/10962247.2016.1140693
Pandolfi, M., Gonzalez-Castanedo, Y., Alastuey, A. et al., Source apportionment of PM10 and PM2.5 at multiple sites in the strait of Gibraltar by PMF: impact of shipping emissions. Environmental Science and Pollution Research. 18(2), pp. 260-269, 2011. DOI: 10.1007/s11356-010-0373-4
Ito, K., Xue, N. and Thurstona, G., Spatial variation of PM2.5 chemical species and source-apportioned mass concentrations in New York City. Atmospheric Environment, 38(31), pp 5269-5282, 2004. DOI: 10.1016/j.atmosenv.2004.02.063
Camero, S., Source identification of environmental pollutants using chemical analysis and Positive Matrix Factorization. PhD dissertation. Facoltà di Scienze Matematiche, Fisiche e Naturali Dipartimento di Scienze della Terra “Ardito Desio”, Milan University, Milan, Italy, 2011.
Zhang, H., Cheng, S., Li, H., Fu, K. and Xu, Y., Groundwater pollution source identification and apportionment using PMF and PCA-APCA-MLR receptor models in a typical mixed land-use area in Southwestern China. Science of the total environment, 741, 2020, 140383. DOI: 10.1016/j.scitotenv.2020.140383.
Salim, I., Sajjad, R.U., Paule-Mercado, M.C., Memon, S.A., Lee, B.-Y., Sukhbaatar, C. and Lee, C.-H., Comparison of two receptor models PCA-MLR and PMF for source identification and apportionment of pollution carried by runoff from catchment and sub-watershed areas with mixed land cover in South Korea. Science of The Total Environment, 663, pp. 764-775, 2019. DOI: 10.1016/j.scitotenv.2019.01.377
Jain, S., Sharma, S.K., Vijayan, N. and Mandal, T.K., Seasonal characteristics of aerosols (PM2.5 and PM10) and their source apportionment using PMF: a four year study over Delhi, India. Environmental Pollution, 262, art. 114337. 2020. DOI: 10.1016/j.envpol.2020.114337
Padoan, S., Zappi, A., Adam, T., Melucci, D., Gambaro, A., Formenton, G. and Zimmermann, R., Organic molecular markers and source contributions in a polluted municipality of north-east Italy: extended PCA-PMF statistical approach. Environmental Research, 186, art. 109587, 2020. DOI: 10.1016/j.envres.2020.109587
Gupta, S., Gadi, R., Sharma, S. K. and Mandal, T. K..Characterization and source apportionment of organic compounds in PM10 using PCA and PMF at a traffic hotspot of Delhi. Sustainable Cities and Society, 39, pp. 52-67.2018. DOI: 10.1016/j.scs.2018.01.051
Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI). Boletín Mensual Vigilancia de la Calidad del Aire Lima Metropolitana MAYO 2017: [en línea]. [date of reference November 20th of 2019] Available at : https://www.senamhi.gob.pe/load/file/03201SENA-48.pdf
United States Environmental Protection, (EPA) Agency. Criteria Air Pollutants. 2014b [Online]. [date of reference October 29th of 2019] Available at : https://www.epa.gov/criteria-air-pollutants
World Health organization Regional Office for Europe Copenhagen. WHO. Air Quality Guidelines for Europe Second Edition. [Online]. [date of reference July 28th of 2019] Available at : http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf
Gao, Y; , Nelson, E. D; Field, M. .; Ding,Q; Li, H.; Sherrell, R.M; Gigliotti, C.l; Van Ry, D.A; Glenn, T.R; Eisereich, S.J. Characterization of atmospheric trace elements on PM2.5 particulate matter over the New York–New Jersey harbor estuary. Atmospheric Environment. 36(6), pp.1077-1086, 2002. DOI: 10.1016/S1352-2310(01)00381-8
Amato, F; Pandolfi, M; Viana, M.; Querol,X; Alasteuy, A.; Moreno, T. Spatial and chemical patterns of PM10 in road dust deposited in urban environment. Atmospheric Environment. 43(9), pp. 1650-1659, 2009. DOI: 10.1016/j.atmosenv.2008.12.009
Jorquera, G.H. Introducción a la contaminación atmosférica. 1st ed; Santiago de Chile. Ediciones UC. 2015.
Ho, K. F; Lee S .C; Chan, C. K; Yu, C.J; Chow, C. J; Yao, X.H. Characterization of chemical species in PM2.5 and PM10 aerosols in Hong Kong. Atmospheric Environment. 37(1), pp. 31-39, 2003. DOI: 10.1016/S1352-2310(02)00804-X
Esmaeilirad, S., Lai, A., Abbaszade, G., Schnelle-Kreis, J., Zimmermann, R., Uzu, G. and El Haddad, I., Source apportionment of fine particulate matter in a middle eastern metropolis, Tehran-Iran, using PMF with organic and inorganic markers. Science of the Total Environment, 705, art. 135330, 2019. DOI: 10.1016/j.scitotenv.2019.135330
Salvi, S., Blomberg, A., Rudell, B., Kelly, F., Sandström, T., Holgate, S.T. and Frew, A., Acute inflammatory responses in the airways and peripheral blood after short-term exposure to diesel exhaust in healthy human volunteers. American Journal of Respiratory and Critical Care Medicine. 159, pp. 702-709, 1999. DOI: 10.1164/ajrccm.159.3.9709083
Lee, J.Y., Leem, J.H., Kim, H.C., et al., Effects of traffic-related air pollution on susceptibility to infantile bronchiolitis and childhood asthma: a cohort study in Korea. Journal of Asthma 55, pp. 223-230, 2018. DOI: 10.1080/02770903.2017.1313270.
Posada, C., Aumento continuo del parque automotor, un problema que urge solucionar. Cámara de Comercio de Lima, Comercio exterior. 2018. [en línea]. [Consultado en: junio 29 de 2019] Disponible en: https://www.camaralima.org.pe/repositorioaps/0/0/par/posada_816/posada%20816_final_aumento%20continuo%20del%20parque%20automotor.pdf
Ministerio de Transporte y Comunicaciones (MTC). Plan estratégico nacional de seguridad vial Perú 2017-2021. 2017. [en línea]. Diario el Peruano. [Consultado en: julio 30 de 2019] Disponible en: https://www.mtc.gob.pe/cnsv/documentos/PlanEstrategico.PDF
Instituto Nacional de Estadística e Informática (INEI.). Instituto Nacional de Estadística 2019. [en línea]. [Consultado en: julio 30 de 2019] Disponible en: https://www.inei.gob.pe/buscador/?tbusqueda=PARQUE+AUTOMOTOR+NACIONAL.
Ramadan, Z., Song, X.-H. and Hopke, P.K., Identification of sources of Phoenix aerosol by positive matrix factorization. Air & Waste Management Association. 50(8), pp. 1308-1320, 2000. DOI: 10.1080/10473289.2000.10464173
Minguillón, B.M., Composición y fuentes del material particulado atmosférico en la zona cerámica de Castellón. Impacto de la introducción de las mejores técnicas. PhD Tesis, Departament d'Enginyeria Química.Universitat Jaume I., Spain, 2007.
Alolayan, M.A., Brown, K.W., Evans, J.S., Bouhamra, W.S. and Koutrakis, P., Source apportionment of fine particles in Kuwait City. Science of the Total Environment. 448(15), pp. 14-25, 2013. DOI: 10.1016/j.scitotenv.2012.11.090
Owoade, K.O., Hopke, P. Olise, F.S., et al., Chemical compositions and source identification of particulate matter (PM2.5 and PM2.5–10) from a scrap iron and steel smelting industry along the Ife–Ibadan highway, Nigeria. Atmospheric Pollution Research. 6(1), pp. 107-119, 2015. DOI: 10.5094/APR.2015.013
Satsangi, G.P., Chavan, S.P., Rao, P.S.P. and Safai, P.D., Chemical characterization of particulate matter at Sinhagad, a high altitude station in Pune, India. Indian Journal of Radio and Space Physics [Online]. 43(4-5), pp. 284-292, 2014. [date of reference July 25th of 2018]. Available at: https://pdfs.semanticscholar.org/8322/ 2061dbd1dc2bca8bc41192b2eae64cdda095.pdf
International Finance Corporation (IFC), (Grupo del Banco Mundial). Guías sobre medio ambiente, salud y seguridad para fundiciones 2007. [en línea]. [consultado en: junio 28 de 2019] Disponible en: https://www.ifc.org/wps/wcm/connect/47cf767d-cb80-4799-b0b4-8905b03e2cf2/0000199659ESes+Foundries.pdf?MOD=AJPERES&CVID=jkD2zCX
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