Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla
Air pollution has become a critical issue in urban areas, so a broad understanding of its spatiotemporal characteristics is required. In the present study, continuous measurements in real time of atmospheric pollutants of particulate matter (PM10 and PM2.5) and ozone (O3), were carried out between M...
- Autores:
-
Duarte González, Ana Lucía
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7079
- Acceso en línea:
- https://hdl.handle.net/11323/7079
https://repositorio.cuc.edu.co/
- Palabra clave:
- Particulate matter
Ozone
Colombian Caribbean
Coastal urban area
Material particulado
Ozono
Caribe Colombiano
Área urbana costera
- Rights
- openAccess
- License
- Attribution-NonCommercial-ShareAlike 4.0 International
id |
RCUC2_bb059620c71a780d331b3012bcec0e36 |
---|---|
oai_identifier_str |
oai:repositorio.cuc.edu.co:11323/7079 |
network_acronym_str |
RCUC2 |
network_name_str |
REDICUC - Repositorio CUC |
repository_id_str |
|
dc.title.spa.fl_str_mv |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
title |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
spellingShingle |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla Particulate matter Ozone Colombian Caribbean Coastal urban area Material particulado Ozono Caribe Colombiano Área urbana costera |
title_short |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
title_full |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
title_fullStr |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
title_full_unstemmed |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
title_sort |
Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla |
dc.creator.fl_str_mv |
Duarte González, Ana Lucía |
dc.contributor.advisor.spa.fl_str_mv |
Schneider, Ismael Luis |
dc.contributor.author.spa.fl_str_mv |
Duarte González, Ana Lucía |
dc.subject.spa.fl_str_mv |
Particulate matter Ozone Colombian Caribbean Coastal urban area Material particulado Ozono Caribe Colombiano Área urbana costera |
topic |
Particulate matter Ozone Colombian Caribbean Coastal urban area Material particulado Ozono Caribe Colombiano Área urbana costera |
description |
Air pollution has become a critical issue in urban areas, so a broad understanding of its spatiotemporal characteristics is required. In the present study, continuous measurements in real time of atmospheric pollutants of particulate matter (PM10 and PM2.5) and ozone (O3), were carried out between March 2018 and June 2019, in three (3) monitoring stations localized in Barranquilla city. The Móvil station is located in the north area near the sea, Policía located in the south and influenced by high vehicular traffic and Tres Avemarías in the north-historic center in a residential area were evaluated. The average concentrations observed for Móvil, Policía and Tres Avemarías stations, respectively, for PM10 were: 46.37, 51.37 and 39.68 µg/m3; PM2.5: 15.95, 18.12 and 15.10µg/m3 and O3: 34.99, 26.56 and 33.63 µg/m3. The results indicated the existence of spatial and temporal variations between the stations and the pollutants evaluated. The highest PM concentrations were observed in the south of the city, while for ozone in the north. These variations are mainly associated with the influence of local sources in the environment of each site evaluated as well as the meteorological conditions of the study area. This research will help to establish the air quality baseline for Barranquilla, as well as enable the development of more effective Environmental Management plans. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-09-09T14:55:16Z |
dc.date.available.none.fl_str_mv |
2020-09-09T14:55:16Z |
dc.date.issued.none.fl_str_mv |
2020 |
dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
status_str |
acceptedVersion |
dc.identifier.citation.spa.fl_str_mv |
Duarte, A. (2020). Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de barranquilla. Trabajo de Maestría, Recuperado de https://hdl.handle.net/113 |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/7079 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
identifier_str_mv |
Duarte, A. (2020). Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de barranquilla. Trabajo de Maestría, Recuperado de https://hdl.handle.net/113 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
url |
https://hdl.handle.net/11323/7079 https://repositorio.cuc.edu.co/ |
dc.language.iso.none.fl_str_mv |
spa |
language |
spa |
dc.relation.references.spa.fl_str_mv |
Achilleos, S., Kioumourtzoglou, M. A., Wu, C. Da, Schwartz, J. D., Koutrakis, P., & Papatheodorou, S. I. (2017). Acute effects of fine particulate matter constituents on mortality: A systematic review and meta-regression analysis. Environment International, 109(December 2016), 89–100. https://doi.org/10.1016/j.envint.2017.09.010 Adhikari, A. (2020a). Introduction to spatiotemporal variations of ambient air pollutants and related public health impacts. In Spatiotemporal Analysis of Air Pollution and Its Application in Public Health (pp. 1–34). Elsevier. https://doi.org/10.1016/b978-0-12- 815822-7.00001-7 Agudelo-Castañeda, D., De Paoli, F., Morgado-Gamero, W. B., Mendoza, M., Parody, A., Maturana, A. Y., & Teixeira, E. C. (2020). Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city. Science of the Total Environment, 720. https://doi.org/10.1016/j.scitotenv.2020.137675 Agudelo-Castañeda, D. M., Teixeira, E. C., Schneider, I. L., Pereira, F. N., Oliveira, M. L. S., Taffarel, S. R., Sehn, J. L., Ramos, C. G., & Silva, L. F. O. (2016). Potential utilization for the evaluation of particulate and gaseous pollutants at an urban site near a major highway. Science of the Total Environment, 543, 161–170. https://doi.org/10.1016/j.scitotenv.2015.11.030 Ahmed, S. O., Mazloum, R., & Abou-Ali, H. (2018). Spatiotemporal interpolation of air pollutants in the Greater Cairo and the Delta, Egypt. Environmental Research, 160, 27–34. https://doi.org/10.1016/j.envres.2017.09.005 Alizadeh-Choobari, O., Bidokhti, A. A., Ghafarian, P., & Najafi, M. S. (2016). Temporal and spatial variations of particulate matter and gaseous pollutants in the urban area of Tehran. Atmospheric Environment, 141, 443–453. https://doi.org/10.1016/j.atmosenv.2016.07.003 Amoatey, P., Omidvarborna, H., Baawain, M. S., & Al-Mamun, A. (2019). Emissions and exposure assessments of SOX, NOX, PM10/2.5 and trace metals from oil industries: A review study (2000–2018). In Process Safety and Environmental Protection (Vol. 123, pp. 215–228). Institution of Chemical Engineers. https://doi.org/10.1016/j.psep.2019.01.014 Andreae, M. O. (2019). Emission of trace gases and aerosols from biomass burning – An updated assessment. Atmospheric Chemistry and Physics Discussions, 1–27. https://doi.org/10.5194/acp-2019-303 Andrée, B. P. J., Chamorro, A., Spencer, P., Koomen, E., & Dogo, H. (2019). Revisiting the relation between economic growth and the environment; a global assessment of deforestation, pollution and carbon emission. Renewable and Sustainable Energy Reviews, 114(December 2018), 109221. https://doi.org/10.1016/j.rser.2019.06.028 Armenta, S., & de la Guardia, M. (2016). Pollutants and Air Pollution. In Comprehensive Analytical Chemistry (Vol. 73). Elsevier Ltd. https://doi.org/10.1016/bs.coac.2016.03.002 Austin, E., Zanobetti, A., Coull, B., Schwartz, J., Gold, D. R., & Koutrakis, P. (2015). Ozone trends and their relationship to characteristic weather patterns. Journal of Exposure Science and Environmental Epidemiology, 25(5), 535–542. https://doi.org/10.1038/jes.2014.45 Jiao, J., Han, X., Li, F., Bai, Y., & Yu, Y. (2017). Contribution of demand shifts to industrial SO2 emissions in a transition economy: Evidence from China. Journal of Cleaner Production, 164, 1455–1466. https://doi.org/10.1016/j.jclepro.2017.07.060 Kambezidis, H. D., & Kalliampakos, G. (2013). Mapping atmospheric corrosion on modern materials in the greater Athens area. Water, Air, and Soil Pollution, 224(3), 1463. https://doi.org/10.1007/s11270-013-1463-y Karl, T. G., Christian, T. J., Yokelson, R. J., Artaxo, P., Hao, W. M., & Guenther, A. (2007). The tropical forest and fire emissions experiment: Method evaluation of volatile organic compound emissions measured by PTR-MS, FTIR, and GC from tropical biomass burning. Atmospheric Chemistry and Physics, 7(22), 5883–5897. https://doi.org/10.5194/acp-7-5883- 2007 Kavassalis, S. C., & Murphy, J. G. (2017). Understanding ozone-meteorology correlations: A role for dry deposition. Geophysical Research Letters, 44(6), 2922–2931. https://doi.org/10.1002/2016GL071791 Koppmann, R., von Czapiewski, K., & Reid, J. S. (2005). A review of biomass burning emissions, part I: gaseous emissions of carbon monoxide, methane, volatile organic compounds, and nitrogen containing compounds. Atmospheric Chemistry and Physics Discussions, 5(5), 10455–10516. https://doi.org/10.5194/acpd-5-10455-2005 Koren, I., Kaufman, Y. J., Washington, R., Todd, M. C., Rudich, Y., Martins, J. V., & Rosenfeld, D. (2006). The Bodélé depression: A single spot in the Sahara that provides most of the mineral dust to the Amazon forest. Environmental Research Letters, 1(1). https://doi.org/10.1088/1748-9326/1/1/014005 Kumar, A., Singh, D., Singh, B. P., Singh, M., Anandam, K., Kumar, K., & Jain, V. K. (2015). Spatial and temporal variability of surface ozone and nitrogen oxides in urban and rural ambient air of Delhi-NCR, India. Air Quality, Atmosphere and Health, 8(4), 391–399. https://doi.org/10.1007/s11869-014-0309-0 Kwak, H. Y., Ko, J., Lee, S., & Joh, C. H. (2017). Identifying the correlation between rainfall, traffic flow performance and air pollution concentration in Seoul using a path analysis. Transportation Research Procedia, 25, 3552–3563. https://doi.org/10.1016/j.trpro.2017.05.288 Lawrence, M. G., & Lelieveld, J. (2010). Atmospheric pollutant outflow from southern Asia: A review. Atmospheric Chemistry and Physics, 10(22), 11017–11096. https://doi.org/10.5194/acp-10-11017-2010 Lazaridis, M. (2011). Fisrt Principles of Meteorology and Air Pollution (J. T. Brian Alloway (ed.); 19th ed.). Springer. Lazaridis, M., Katsivela, E., Kopanakis, I., Raisi, L., Mihalopoulos, N., & Panagiaris, G. (2018). Characterization of airborne particulate matter and microbes inside cultural heritage collections. Journal of Cultural Heritage, 30, 136–146. https://doi.org/10.1016/j.culher.2017.09.018 Lee, S., Ho, C. H., & Choi, Y. S. (2011). High-PM10 concentration episodes in Seoul, Korea: Background sources and related meteorological conditions. Atmospheric Environment, 45(39), 7240–7247. https://doi.org/10.1016/j.atmosenv.2011.08.071 Li, L., Wu, A. H., Cheng, I., Chen, J. C., & Wu, J. (2017). Spatiotemporal estimation of historical PM2.5concentrations using PM10, meteorological variables, and spatial effect. Atmospheric Environment, 166, 182–191. https://doi.org/10.1016/j.atmosenv.2017.07.023 Li, L., Wu, J., Ghosh, J. K., & Ritz, B. (2013). Estimating spatiotemporal variability of ambient air pollutant concentrations with a hierarchical model. Atmospheric Environment, 71, 54– 63. https://doi.org/10.1016/j.atmosenv.2013.01.038 Li, Q., Gabay, M., Rubin, Y., Raveh-Rubin, S., Rohatyn, S., Tatarinov, F., Rotenberg, E., Ramati, E., Dicken, U., Preisler, Y., Fredj, E., Yakir, D., & Tas, E. (2019). Investigation of ozone deposition to vegetation under warm and dry conditions near the Eastern Mediterranean coast. Science of the Total Environment, 658, 1316–1333. https://doi.org/10.1016/j.scitotenv.2018.12.272 Li, Xiangyu, Huang, S., Jiao, A., Yang, X., Yun, J., Wang, Y., Xue, X., Chu, Y., Liu, F., Liu, Y., Ren, M., Chen, X., Li, N., Lu, Y., Mao, Z., Tian, L., & Xiang, H. (2017). Association between ambient fine particulate matter and preterm birth or term low birth weight: An updated systematic review and meta-analysis. Environmental Pollution, 227, 596–605. https://doi.org/10.1016/j.envpol.2017.03.055 Li, Xiaolan, Ma, Y., Wang, Y., Liu, N., & Hong, Y. (2017). Temporal and spatial analyses of particulate matter (PM10and PM2.5) and its relationship with meteorological parameters over an urban city in northeast China. Atmospheric Research, 198(September 2016), 185– 193. https://doi.org/10.1016/j.atmosres.2017.08.023 Limon–Sanchez, M. T., Carbajal–Romero, P., Hernandez–Mena, L., Saldarriaga–Norena, H., Lopez–Lopez, A., Cosio–Ramirez, R., Arriaga–Colina, J. L., & Smith, W. (2011). Black carbon in PM2.5, data from two urban sites in Guadalajara, Mexico during 2008. Atmospheric Pollution Research, 2(3), 358–365. https://doi.org/10.5094/APR.2011.040 Ling, H., Schäfer, K., Xin, J., Qin, M., Suppan, P., & Wang, Y. (2014). Small-scale spatial variations of gaseous air pollutants e A comparison of path-integrated and in situ measurement methods. Atmospheric Environment, 92, 566–575. https://doi.org/10.1016/j.atmosenv.2014.01.062 Liu, C., Sun, J., Liu, Y., Liang, H., Wang, M., Wang, C., & Shi, T. (2017). Different exposure levels of fine particulate matter and preterm birth: a meta-analysis based on cohort studies. Environmental Science and Pollution Research, 24(22), 17976–17984. https://doi.org/10.1007/s11356-017-9363-0 Liu, Y., Gao, Y., Yu, N., Zhang, C., Wang, S., Ma, L., Zhao, J., & Lohmann, R. (2015). Particulate matter, gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) in an urban traffic tunnel of China: Emission from on-road vehicles and gas-particle partitioning. Chemosphere, 134, 52–59. https://doi.org/10.1016/j.chemosphere.2015.03.065 Luben, T. J., Nichols, J. L., Dutton, S. J., Kirrane, E., Owens, E. O., Datko-Williams, L., Madden, M., & Sacks, J. D. (2017). A systematic review of cardiovascular emergency department visits, hospital admissions and mortality associated with ambient black carbon. Environment International, 107(January), 154–162. https://doi.org/10.1016/j.envint.2017.07.005 Maji, K. J., Ye, W. F., Arora, M., & Nagendra, S. M. S. (2019). Ozone pollution in Chinese cities: Assessment of seasonal variation, health effects and economic burden. Environmental Pollution, 247(x), 792–801. https://doi.org/10.1016/j.envpol.2019.01.049 Manahan, S. (2013). Fundamentak of environmental and toxicological chemestry: Sustainable Science (C. Press (ed.); Fourth Edi). CRC press. Mason, P. J., & Thomson, D. J. (2015). Boundary Layer (Atmospheric) and Air Pollution: Overview. Encyclopedia of Atmospheric Sciences: Second Edition, 1, 220–226. https://doi.org/10.1016/B978-0-12-382225-3.00081-5 Ministerio de Ambiente Vivienda y Desarrollo Territorial. (2008). Manual de Operación de Sistemas de Vigilancia de la Calidad del aire. Monks, P. S. (2005). Gas-phase radical chemistry in the troposphere. In Chemical Society Reviews (Vol. 34, Issue 5, pp. 376–395). https://doi.org/10.1039/b307982c Montañez, D. P. (2019). ESTIMACIÓN DE LAS EMISIONES ATMOSFÉRICAS DE BUQUES EN EL PUERTO DE BARRANQUILLA. In Universidad del Norte (Vol. 1, Issue 1). https://doi.org/10.1017/CBO9781107415324.004 Motallebi, N., Tran, H., Croes, B. E., & Larsen, L. C. (2003). Day-of-week patterns of particulate matter and its chemical components at selected sites in california? Journal of the Air and Waste Management Association, 53(7), 876–888. https://doi.org/10.1080/10473289.2003.10466229 Muñoz, R. C. (2012). Relative roles of emissions and meteorology in the diurnal pattern of urban PM10: Analysis of the daylight saving time effect. Journal of the Air and Waste Management Association, 62(6), 642–650. https://doi.org/10.1080/10962247.2012.665147 Naciones Unidas. (2020). Población urbana (% del total) (Issue i). https://datos.bancomundial.org/indicator/SP.URB.TOTL.IN.ZS Nadadur, Srikanth S, Hollingsworth, J. W. (2015). Air Pollution and Health Effects (Springer- Verlag London (ed.)). https://doi.org/DOI 10.1007/978-1-4471-6669-6 News, G. (2020). O que é a ’ nuvem de poeira Godzilla ’, que viaja 10 mil km do Saara para as Américas. https://g1.globo.com/natureza/noticia/2020/06/24/o-que-e-a-nuvem-de-poeiragodzilla-que-viaja-10-mil-km-do-saara-para-as-americas.ghtml Núñez, Y. (2019). ESTIMACIÓN DE FUENTES DE MATERIAL PARTICULADO ATMOSFÉRICO (PM 10 y PM 2.5 ) EN LA CIUDAD DE BARRANQUILLA, COLOMBIA [Universidad de la Costa]. https://repositorio.cuc.edu.co/bitstream/handle/11323/6017/Estimación de fuentes de material particulado atmosférico %28PM10 y PM2.5%29 en la ciudad de Barranquilla%2C Colombia.pdf?sequence=1&isAllowed=y O’Leary, B., Reiners, J. J., Xu, X., & Lemke, L. D. (2016). Identification and influence of spatiotemporal outliers in urban air quality measurements. Science of the Total Environment, 573, 55–65. https://doi.org/10.1016/j.scitotenv.2016.08.031 Ohara, T. (2019). Long-range transport and deposition of air pollution. Encyclopedia of Environmental Health, 126–130. https://doi.org/10.1016/B978-0-12-409548-9.11352-1 ONS. (2018). Carga de enfermedad ambiental en Colombia - Informe Técnico Especial 10. In Observatorio Nacional de Salud. https://www.ins.gov.co/Direcciones/ONS/Informes/10 Carga de enfermedad ambiental en Colombia.pdf Ouyang, W., Guo, B., Cai, G., Li, Q., Han, S., Liu, B., & Liu, X. (2015). The washing effect of precipitation on particulate matter and the pollution dynamics of rainwater in downtown Beijing. Science of the Total Environment, 505, 306–314. https://doi.org/10.1016/j.scitotenv.2014.09.062 Owens, E. O., Patel, M. M., Kirrane, E., Long, T. C., Brown, J., Cote, I., Ross, M. A., & Dutton, S. J. (2017). Framework for assessing causality of air pollution-related health effects for reviews of the National Ambient Air Quality Standards. Regulatory Toxicology and Pharmacology, 88, 332–337. https://doi.org/10.1016/j.yrtph.2017.05.014 Pachón, J. E., Galvis, B., Lombana, O., Carmona, L. G., Fajardo, S., Rincón, A., Meneses, S., Chaparro, R., Nedbor-Gross, R., & Henderson, B. (2018). Development and evaluation of a comprehensive atmospheric emission inventory for air quality modeling in the megacity of Bogotá. Atmosphere, 9(2), 1–17. https://doi.org/10.3390/atmos9020049 Pateraki, S., Asimakopoulos, D. N., Flocas, H. A., Maggos, T., & Vasilakos, C. (2012). The role of meteorology on different sized aerosol fractions (PM10, PM2.5, PM2.5-10). Science of the Total Environment, 419, 124–135. https://doi.org/10.1016/j.scitotenv.2011.12.064 Peshin, S. K., Sharma, A., Sharma, S. K., Naja, M., & Mandal, T. K. (2017). Spatio-temporal variation of air pollutants and the impact of anthropogenic effects on the photochemical buildup of ozone across Delhi-NCR. Sustainable Cities and Society, 35, 740–751. https://doi.org/10.1016/j.scs.2017.09.024 Petit, R. H., Legrand, M., Jankowiak, I., Molinié, J., Asselin de Beauville, C., Marion, G., & Mansot, J. L. (2005). Transport of Saharan dust over the Caribbean Islands: Study of an event. Journal of Geophysical Research D: Atmospheres, 110(18), 1–19. https://doi.org/10.1029/2004JD004748 Qu, W., Zhang, X., Wang, Y., & Fu, G. (2020). Atmospheric visibility variation over global land surface during 1973–2012: Influence of meteorological factors and effect of aerosol, cloud on ABL evolution. Atmospheric Pollution Research, 11(4), 730–743. https://doi.org/10.1016/j.apr.2020.01.002 R.E., H., Harrison, R. M., & Querol, X. (2016). Airborne Particulate Matter: Sources, Atmospheric Processes and Health. The Royal Society of Chemistry. www.rsc.org Raherison, C., & Filleul, L. (2002). Asthma in exercising children exposed to ozone [3]. Lancet, 360(9330), 411. https://doi.org/10.1016/S0140-6736(02)09580-6 Ramírez, O., da Boit, K., Blanco, E., & Silva, L. F. O. (2020). Hazardous thoracic and ultrafine particles from road dust in a Caribbean industrial city. Urban Climate, 33(October 2019), 100655. https://doi.org/10.1016/j.uclim.2020.100655 Ramírez, O., Sánchez de la Campa, A. M., & de la Rosa, J. (2018). Characteristics and temporal variations of organic and elemental carbon aerosols in a high–altitude, tropical Latin American megacity. Atmospheric Research, 210(April), 110–122. https://doi.org/10.1016/j.atmosres.2018.04.006 Ramsey, N. R., Klein, P. M., & Moore, B. (2014). The impact of meteorological parameters on urban air qualityThe impact of meteorological parameters on urban air quality. Atmospheric Environment, 86, 58–67. https://doi.org/10.1016/j.atmosenv.2013.12.006 Reche, C., Moreno, T., Amato, F., Pandolfi, M., Pérez, J., de la Paz, D., Diaz, E., GómezMoreno, F. J., Pujadas, M., Artíñano, B., Reina, F., Orio, A., Pallarés, M., Escudero, M., Tapia, O., Crespo, E., Vargas, R., Alastuey, A., & Querol, X. (2018). Spatio-temporal patterns of high summer ozone events in the Madrid Basin, Central Spain. Atmospheric Environment, 185(November 2017), 207–220. https://doi.org/10.1016/j.atmosenv.2018.05.002 Richmond-Bryant, J., Saganich, C., Bukiewicz, L., & Kalin, R. (2009). Associations of PM2.5 and black carbon concentrations with traffic, idling, background pollution, and meteorology during school dismissals. Science of the Total Environment, 407(10), 3357–3364. https://doi.org/10.1016/j.scitotenv.2009.01.046 Riggs, D. W., Zafar, N., Krishnasamy, S., Yeager, R., Rai, S. N., Bhatnagar, A., & O’Toole, T. E. (2020). Exposure to airborne fine particulate matter is associated with impaired endothelial function and biomarkers of oxidative stress and inflammation. Environmental Research, 180(November 2019), 108890. https://doi.org/10.1016/j.envres.2019.108890 Rodríguez-Villamizar, L. A., Rojas-Roa, N. Y., Blanco-Becerra, L. C., Herrera-Galindo, V. M., & Fernández-Niño, J. A. (2018). Short-term effects of air pollution on respiratory and circulatory morbidity in colombia 2011–2014: A multi-city, time-series analysis. International Journal of Environmental Research and Public Health, 15(8). https://doi.org/10.3390/ijerph15081610 Rodríguez-Villamizar, L. A., Rojas-Roa, N. Y., & Fernández-Niño, J. A. (2019). Short-term joint effects of ambient air pollutants on emergency department visits for respiratory and circulatory diseases in Colombia, 2011–2014. Environmental Pollution, 248, 380–387. https://doi.org/10.1016/j.envpol.2019.02.028 Rohr, A. C., & Wyzga, R. E. (2012). Attributing health effects to individual particulate matter constituents. Atmospheric Environment, 62, 130–152. https://doi.org/10.1016/j.atmosenv.2012.07.036 Russo, A., Gouveia, C., Levy, I., Dayan, U., Jerez, S., Mendes, M., & Trigo, R. (2016). Coastal recirculation potential affecting air pollutants in Portugal: The role of circulation weather types. Atmospheric Environment, 135, 9–19. https://doi.org/10.1016/j.atmosenv.2016.03.039 Sandeep, A., Rao, T. N., Ramkiran, C. N., & Rao, S. V. B. (2014). Differences in Atmospheric Boundary-Layer Characteristics Between Wet and Dry Episodes of the Indian Summer Monsoon. Boundary-Layer Meteorology, 153(2), 217–236. https://doi.org/10.1007/s10546- 014-9945-z Schaller, B. (2010). New York City’s congestion pricing experience and implications for road pricing acceptance in the United States. Transport Policy, 17(4), 266–273. https://doi.org/10.1016/j.tranpol.2010.01.013 Seinfeld, J. H., & Pandis, S. N. (2006). Atmospheric Chemistry: From Air Pollution to Climate Change (I. John Wiley & Sons (ed.); Second Edi). Seinfeld, J., & Pandis, S. N. (2016). Atmospheric Chemistry and Physics: From air pollution to climate change (WILEY (ed.); third edit). Shaddick, G., Thomas, M. L., Mudu, P., Ruggeri, G., & Gumy, S. (2020). Half the world’s population are exposed to increasing air pollution. Npj Climate and Atmospheric Science, 3(1), 1–5. https://doi.org/10.1038/s41612-020-0124-2 Shahid, I., Kistler, M., Mukhtar, A., Ghauri, B. M., Ramirez-Santa Cruz, C., Bauer, H., & Puxbaum, H. (2016). Chemical characterization and mass closure of PM10 and PM2.5 at an urban site in Karachi - Pakistan. Atmospheric Environment, 128, 114–123. https://doi.org/10.1016/j.atmosenv.2015.12.005 Shi, S., Chen, C., & Zhao, B. (2017). Modifications of exposure to ambient particulate matter: Tackling bias in using ambient concentration as surrogate with particle infiltration factor and ambient exposure factor. Environmental Pollution, 220, 337–347. https://doi.org/10.1016/j.envpol.2016.09.069 SIAC. (2020). Fenómenos del Niño y la Niña. http://www.siac.gov.co/ninoynina Simon, H., Reff, A., Wells, B., Xing, J., & Frank, N. (2015). Ozone trends across the United States over a period of decreasing NOx and VOC emissions. Environmental Science and Technology, 49(1), 186–195. https://doi.org/10.1021/es504514z Sippo, J. Z., Maher, D. T., Tait, D. R., Ruiz-Halpern, S., Sanders, C. J., & Santos, I. R. (2017). Mangrove outwelling is a significant source of oceanic exchangeable organic carbon. Limnology and Oceanography Letters, 2(1), 1–8. https://doi.org/10.1002/lol2.10031 Stanek, L. W., & Brown, J. S. (2019). Air Pollution: Sources, Regulation, and Health Effects. In Reference Module in Biomedical Sciences (Issue June, pp. 1–10). Elsevier Inc. https://doi.org/10.1016/b978-0-12-801238-3.11384-4 Stanek, L. W., Sacks, J. D., Dutton, S. J., & Dubois, J. J. B. (2011). Attributing health effects to apportioned components and sources of particulate matter: An evaluation of collective results. Atmospheric Environment, 45(32), 5655–5663. https://doi.org/10.1016/j.atmosenv.2011.07.023 Suh, H. H., Bahadori, T., Vallarino, J., & Spengler, J. D. (2018). Criteria Air Pollutants and Toxic Air Pollutants. 108, 625–633. https://doi.org/10.2307/3454398 Tang, J., McNabola, A., Misstear, B., Pilla, F., & Alam, M. S. (2019). Assessing the impact of vehicle speed limits and fleet composition on air quality near a school. International Journal of Environmental Research and Public Health, 16(1). https://doi.org/10.3390/ijerph16010149 Thurston, G. D. (2016a). Outdoor Air Pollution: Sources, Atmospheric Transport, and Human Health Effects. In International Encyclopedia of Public Health (Second Edi, Vol. 5, Issue 69). Elsevier. https://doi.org/10.1016/B978-0-12-803678-5.00320-9 Tian, Ye, Yao, X., & Chen, L. (2019). Analysis of spatial and seasonal distributions of air pollutants by incorporating urban morphological characteristics. Computers, Environment and Urban Systems, 75(April 2018), 35–48. https://doi.org/10.1016/j.compenvurbsys.2019.01.003 Tian, Yulu, Jiang, Y., Liu, Q., Xu, D., Zhao, S., He, L., Liu, H., & Xu, H. (2019). Temporal and spatial trends in air quality in Beijing. Landscape and Urban Planning, 185(October 2018), 35–43. https://doi.org/10.1016/j.landurbplan.2019.01.006 Tiwari, S., Dumka, U. C., Gautam, A. S., Kaskaoutis, D. G., Srivastava, A. K., Bisht, D. S., Chakrabarty, R. K., Sumlin, B. J., & Solmon, F. (2017). Assessment of PM2.5and PM10over Guwahati in Brahmaputra River Valley: Temporal evolution, source apportionment and meteorological dependence. Atmospheric Pollution Research, 8(1), 13– 28. https://doi.org/10.1016/j.apr.2016.07.008 Toro A., R., Morales S., R. G. E., Canales, M., Gonzalez-Rojas, C., & Leiva G., M. A. (2014). Inhaled and inspired particulates in Metropolitan Santiago Chile exceed air quality standards. Building and Environment, 79, 115–123. https://doi.org/10.1016/j.buildenv.2014.05.004 Triantafyllou, E., Diapouli, E., Korras-Carraca, Manousakas, M., Psanis, C., Floutsi, A. A., Spyrou, C., Eleftheriadis, K., & Biskos, G. (2020). Contribution of locally-produced and transported air pollution to particulate matter in a small insular coastal city. Atmospheric Pollution Research, 11(4), 667–678. https://doi.org/10.1016/j.apr.2019.12.015 Tzortziou, M., Parker, O., Lamb, B., Herman, J. R., Lamsal, L., Stauffer, R., & Abuhassan, N. (2018). Atmospheric trace gas (NO2 and O3) variability in south Korean coastal waters, and implications for remote sensing of coastal ocean color dynamics. Remote Sensing, 10(10), 1–20. https://doi.org/10.3390/rs10101587 Vallero, D. A. (2014). Fundamentals of air pollution (5th editio). Elsevier. https://doi.org/https://doi.org/10.1016/C2012-0-01172-6 van der Zee, S. C., Fischer, P. H., & Hoek, G. (2016). Air pollution in perspective: Health risks of air pollution expressed in equivalent numbers of passively smoked cigarettes. Environmental Research, 148, 475–483. https://doi.org/10.1016/j.envres.2016.04.001 Vellingiri, K., Kim, K. H., Ma, C. J., Kang, C. H., Lee, J. H., Kim, I. S., & Brown, R. J. C. (2015). Ambient particulate matter in a central urban area of Seoul, Korea. Chemosphere, 119, 812–819. https://doi.org/10.1016/j.chemosphere.2014.08.049 Viana, M., Pérez, C., Querol, X., Alastuey, A., Nickovic, S., & Baldasano, J. M. (2005). Spatial and temporal variability of PM levels and composition in a complex summer atmospheric scenario in Barcelona (NE Spain). Atmospheric Environment, 39(29), 5343–5361. https://doi.org/10.1016/j.atmosenv.2005.05.039 Vicedo-Cabrera, A. M., Sera, F., Liu, C., Armstrong, B., Milojevic, A., Guo, Y., Tong, S., Lavigne, E., Kyselý, J., Urban, A., Orru, H., Indermitte, E., Pascal, M., Huber, V., Schneider, A., Katsouyanni, K., Samoli, E., Stafoggia, M., Scortichini, M., … Gasparrini, A. (2020). Short term association between ozone and mortality: global two stage time series study in 406 locations in 20 countries. The BMJ, 368, 1–10. https://doi.org/10.1136/bmj.m108 Vitolo, C., Scutari, M., Ghalaieny, M., Tucker, A., & Russell, A. (2018). Modeling Air Pollution, Climate, and Health Data Using Bayesian Networks: A Case Study of the English Regions. Earth and Space Science, 5(4), 76–88. https://doi.org/10.1002/2017EA000326 Wang, T., Xue, L., Brimblecombe, P., Lam, Y. F., Li, L., & Zhang, L. (2017a). Ozone pollution in China: A review of concentrations, meteorological influences, chemical precursors, and effects. Science of the Total Environment, 575, 1582–1596. https://doi.org/10.1016/j.scitotenv.2016.10.081 Wang, Yan, Shi, L., Lee, M., Liu, P., Di, Q., Zanobetti, A., & Schwartz, J. D. (2017). Long-term Exposure to PM 2.5 and Mortality among Older Adults in the Southeastern US. Epidemiology, 28(2), 207–214. https://doi.org/10.1097/EDE.0000000000000614 Wang, Yungang, Ying, Q., Hu, J., & Zhang, H. (2014). Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013-2014. Environment International, 73, 413–422. https://doi.org/10.1016/j.envint.2014.08.016 Watson, J. G., & Chow, J. C. (2015). Receptor Models and Measurements for Identifying and Quantifying Air Pollution Sources. In Introduction to Environmental Forensics: Third Edition (Third Edit). Elsevier Ltd. https://doi.org/10.1016/B978-0-12-404696-2.00020-5 WHO. (2018). Global Ambient Air Quality Database (update 2018). In World Health Organization (Issue update 2018). https://www.who.int/airpollution/data/cities/en/ WHO, Health Organization, W., & Office for Europe, R. (2013). Review of evidence on health aspects of air pollution-REVIHAAP Project Technical Report. World Health Organization. (2016). Ambient (outdoor) air pollution. https://www.who.int/newsroom/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health World Health Organization WHO. (2016). Urban Ambient Air Pollution database ‐ Update 2016. WHO. https://doi.org//entity/phe/health_topics/outdoorair/databases/cities/en/index.html Xian, J., Sun, D., Xu, W., Han, Y., Zheng, J., Peng, J., & Yang, S. (2020). Urban air pollution monitoring using scanning Lidar. Environmental Pollution, 258. https://doi.org/10.1016/j.envpol.2019.113696 Xie, Y., Zhao, B., Zhang, L., & Luo, R. (2015a). Spatiotemporal variations of PM2.5 and PM10 concentrations between 31 Chinese cities and their relationships with SO2, NO2, CO and O3. Particuology, 20, 141–149. https://doi.org/10.1016/j.partic.2015.01.003 Xu, F., Shi, X., Qiu, X., Jiang, X., Fang, Y., Wang, J., Hu, D., & Zhu, T. (2020). Investigation of the chemical components of ambient fine particulate matter (PM2.5) associated with in vitro cellular responses to oxidative stress and inflammation. Environment International, 136(January). https://doi.org/10.1016/j.envint.2020.105475 Yang, J., Ji, Z., Kang, S., Zhang, Q., Chen, X., & Lee, S. Y. (2019). Spatiotemporal variations of air pollutants in western China and their relationship to meteorological factors and emission sources. Environmental Pollution, 254, 112952. https://doi.org/10.1016/j.envpol.2019.07.120 Yang, L., Liu, Z., Guan, Q., Wang, L., & Wang, F. (2018a). Association between heating seasons and criteria air pollutants in three provincial capitals in northern China: Spatiotemporal variation and sources contribution. Building and Environment, 132(November 2017), 233–244. https://doi.org/10.1016/j.buildenv.2018.01.034 Yu, J., Mi, N., Yu, Q., Li, S., He, C., Yin, L., Li, S., Zhang, Y., Yao, Y., Ma, W., & Wang, W. (2019). Properties of particulate matter and gaseous pollutants in Shandong, China: Daily fluctuation, influencing factors, and spatiotemporal distribution. Science of The Total Environment, 660, 384–394. https://doi.org/10.1016/j.scitotenv.2019.01.026 Yu, J., Mi, N., Yu, Q., Li, S. S., He, C., Yin, L., Li, S. S., Zhang, Y., Yao, Y., Ma, W., Wang, W., Mi, K., Zhuang, R., Zhang, Z., Gao, J., Pei, Q., Li, R., Wang, Z., Cui, L., … Chen, L. (2019). Spatiotemporal characteristics of PM2.5 and its associated gas pollutants, a case in China. Sustainable Cities and Society, 648(April 2018), 35–48. https://doi.org/10.1016/j.scitotenv.2018.08.181 Zeri, M., Oliveira-Júnior, J. F., & Lyra, G. B. (2011). Spatiotemporal analysis of particulate matter, sulfur dioxide and carbon monoxide concentrations over the city of Rio de Janeiro, Brazil. Meteorology and Atmospheric Physics, 113(3), 139–152. https://doi.org/10.1007/s00703-011-0153-9 Zhan, Y., Luo, Y., Deng, X., Grieneisen, M. L., Zhang, M., & Di, B. (2018). Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment. Environmental Pollution, 233, 464–473. https://doi.org/10.1016/j.envpol.2017.10.029 Zhang, B. N., & Kim Oanh, N. T. (2002). Photochemical smog pollution in the Bangkok Metropolitan Region of Thailand in relation to O3 precursor concentrations and meteorological conditions. Atmospheric Environment, 36(26), 4211–4222. https://doi.org/10.1016/S1352-2310(02)00348-5 Zhang, H., Wang, Y., Hu, J., Ying, Q., & Hu, X. M. (2015). Relationships between meteorological parameters and criteria air pollutants in three megacities in China. Environmental Research, 140, 242–254. https://doi.org/10.1016/j.envres.2015.04.004 Zhang, K., & Batterman, S. (2013). Air pollution and health risks due to vehicle traffic. Science of the Total Environment, 450–451, 307–316. https://doi.org/10.1016/j.scitotenv.2013.01.074 Zhao, H., Che, H., Ma, Y., Xia, X., Wang, Y., Wang, P., & Wu, X. (2015). Temporal variability of the visibility, particulate matter mass concentration and aerosol optical properties over an urban site in Northeast China. Atmospheric Research, 166, 204–212. https://doi.org/10.1016/j.atmosres.2015.07.003 Zhao, H., Che, H., Zhang, X., Ma, Y., Wang, Y., Wang, H., & Wang, Y. (2013). Characteristics of visibility and particulate matter (PM) in an urban area of Northeast China. Atmospheric Pollution Research, 4(4), 427–434. https://doi.org/10.5094/APR.2013.049 Zhao, S., Yu, Y., Yin, D., Qin, D., He, J., & Dong, L. (2018). Spatial patterns and temporal variations of six criteria air pollutants during 2015 to 2017 in the city clusters of Sichuan Basin, China. Science of the Total Environment, 624, 540–557. https://doi.org/10.1016/j.scitotenv.2017.12.172 |
dc.rights.spa.fl_str_mv |
Attribution-NonCommercial-ShareAlike 4.0 International |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
Attribution-NonCommercial-ShareAlike 4.0 International http://creativecommons.org/licenses/by-nc-sa/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.publisher.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.publisher.program.spa.fl_str_mv |
Maestría de Investigación en Desarrollo Sostenible Mides |
institution |
Corporación Universidad de la Costa |
bitstream.url.fl_str_mv |
https://repositorio.cuc.edu.co/bitstreams/12025781-9786-465b-8837-6ce943c23577/download https://repositorio.cuc.edu.co/bitstreams/34bb9741-15c1-47cf-b9e1-43b4be0653d0/download https://repositorio.cuc.edu.co/bitstreams/3a0d5ea1-a276-4b9f-b6be-26bef72307e9/download https://repositorio.cuc.edu.co/bitstreams/9103e27a-4f36-40cd-8452-36274381ab86/download https://repositorio.cuc.edu.co/bitstreams/a8a04dc4-07d4-43d9-8520-b57267cb450e/download https://repositorio.cuc.edu.co/bitstreams/8cab8360-46ab-4a2f-9032-fbd224b8615a/download |
bitstream.checksum.fl_str_mv |
823dc66363436fd70f134179bdf7e11c 934f4ca17e109e0a05eaeaba504d7ce4 e30e9215131d99561d40d6b0abbe9bad 63cee4b016c13c60fe260f887ac94b1e 63cee4b016c13c60fe260f887ac94b1e 63af7cf2ce4ce8c06e54a72045db6d75 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositorio de la Universidad de la Costa CUC |
repository.mail.fl_str_mv |
repdigital@cuc.edu.co |
_version_ |
1811760676499095552 |
spelling |
Schneider, Ismael LuisDuarte González, Ana Lucía2020-09-09T14:55:16Z2020-09-09T14:55:16Z2020Duarte, A. (2020). Evaluación espaciotemporal de contaminantes atmosféricos en la ciudad de barranquilla. Trabajo de Maestría, Recuperado de https://hdl.handle.net/113https://hdl.handle.net/11323/7079Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Air pollution has become a critical issue in urban areas, so a broad understanding of its spatiotemporal characteristics is required. In the present study, continuous measurements in real time of atmospheric pollutants of particulate matter (PM10 and PM2.5) and ozone (O3), were carried out between March 2018 and June 2019, in three (3) monitoring stations localized in Barranquilla city. The Móvil station is located in the north area near the sea, Policía located in the south and influenced by high vehicular traffic and Tres Avemarías in the north-historic center in a residential area were evaluated. The average concentrations observed for Móvil, Policía and Tres Avemarías stations, respectively, for PM10 were: 46.37, 51.37 and 39.68 µg/m3; PM2.5: 15.95, 18.12 and 15.10µg/m3 and O3: 34.99, 26.56 and 33.63 µg/m3. The results indicated the existence of spatial and temporal variations between the stations and the pollutants evaluated. The highest PM concentrations were observed in the south of the city, while for ozone in the north. These variations are mainly associated with the influence of local sources in the environment of each site evaluated as well as the meteorological conditions of the study area. This research will help to establish the air quality baseline for Barranquilla, as well as enable the development of more effective Environmental Management plans.La contaminación atmosférica se ha convertido en un tema crítico en áreas urbanas, por lo que se requiere una comprensión amplia de las características espaciotemporales de esta. En el presente estudio, mediciones continuas en tiempo real de contaminantes atmosféricos de material particulado (PM10 y PM2.5) y ozono (O3), se llevaron a cabo entre marzo de 2018 y junio de 2019, en tres (3) estaciones de monitoreo localizadas en la ciudad de Barranquilla. Fueron evaluadas las estaciones Móvil ubicada en la zona norte cerca al mar, Policía localizada en el sur y con influencia de alto tráfico vehicular y Tres Avemarías en el norte-centro histórico, zona residencial. El promedio de las concentraciones observadas para las estaciones Móvil, Policía y Tres Avemarías, respectivamente, para PM10 fueron: 46,37, 51,37 y 39,68 µg/m3; PM2.5: 15,95, 18,12 y 15,10 µg/m3 y O3: 34,99, 26,56 y 33,63 µg/m3. Los resultados indicaron la existencia de variaciones espaciales y temporales entre las estaciones y los contaminantes evaluados. Para el PM las mayores concentraciones fueron observadas en el sur de la ciudad, mientras que para el ozono en el norte. Estas variaciones están asociadas principalmente con la influencia de fuentes puntuales en el entorno de cada sitio evaluado así como de las condiciones meteorológicas del área de estudio. Esta investigación ayudará a establecer la línea base de calidad de aire para Barranquilla, así como permitirá el desarrollo de planes de Gestión Ambiental más efectivos.Duarte González, Ana LucíaspaCorporación Universidad de la CostaMaestría de Investigación en Desarrollo Sostenible MidesAttribution-NonCommercial-ShareAlike 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Particulate matterOzoneColombian CaribbeanCoastal urban areaMaterial particuladoOzonoCaribe ColombianoÁrea urbana costeraEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de BarranquillaTrabajo de grado - MaestríaTextinfo:eu-repo/semantics/masterThesishttp://purl.org/redcol/resource_type/TMinfo:eu-repo/semantics/acceptedVersionAchilleos, S., Kioumourtzoglou, M. A., Wu, C. Da, Schwartz, J. D., Koutrakis, P., & Papatheodorou, S. I. (2017). Acute effects of fine particulate matter constituents on mortality: A systematic review and meta-regression analysis. Environment International, 109(December 2016), 89–100. https://doi.org/10.1016/j.envint.2017.09.010Adhikari, A. (2020a). Introduction to spatiotemporal variations of ambient air pollutants and related public health impacts. In Spatiotemporal Analysis of Air Pollution and Its Application in Public Health (pp. 1–34). Elsevier. https://doi.org/10.1016/b978-0-12- 815822-7.00001-7Agudelo-Castañeda, D., De Paoli, F., Morgado-Gamero, W. B., Mendoza, M., Parody, A., Maturana, A. Y., & Teixeira, E. C. (2020). Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city. Science of the Total Environment, 720. https://doi.org/10.1016/j.scitotenv.2020.137675Agudelo-Castañeda, D. M., Teixeira, E. C., Schneider, I. L., Pereira, F. N., Oliveira, M. L. S., Taffarel, S. R., Sehn, J. L., Ramos, C. G., & Silva, L. F. O. (2016). Potential utilization for the evaluation of particulate and gaseous pollutants at an urban site near a major highway. Science of the Total Environment, 543, 161–170. https://doi.org/10.1016/j.scitotenv.2015.11.030Ahmed, S. O., Mazloum, R., & Abou-Ali, H. (2018). Spatiotemporal interpolation of air pollutants in the Greater Cairo and the Delta, Egypt. Environmental Research, 160, 27–34. https://doi.org/10.1016/j.envres.2017.09.005Alizadeh-Choobari, O., Bidokhti, A. A., Ghafarian, P., & Najafi, M. S. (2016). Temporal and spatial variations of particulate matter and gaseous pollutants in the urban area of Tehran. Atmospheric Environment, 141, 443–453. https://doi.org/10.1016/j.atmosenv.2016.07.003Amoatey, P., Omidvarborna, H., Baawain, M. S., & Al-Mamun, A. (2019). Emissions and exposure assessments of SOX, NOX, PM10/2.5 and trace metals from oil industries: A review study (2000–2018). In Process Safety and Environmental Protection (Vol. 123, pp. 215–228). Institution of Chemical Engineers. https://doi.org/10.1016/j.psep.2019.01.014Andreae, M. O. (2019). Emission of trace gases and aerosols from biomass burning – An updated assessment. Atmospheric Chemistry and Physics Discussions, 1–27. https://doi.org/10.5194/acp-2019-303Andrée, B. P. J., Chamorro, A., Spencer, P., Koomen, E., & Dogo, H. (2019). Revisiting the relation between economic growth and the environment; a global assessment of deforestation, pollution and carbon emission. Renewable and Sustainable Energy Reviews, 114(December 2018), 109221. https://doi.org/10.1016/j.rser.2019.06.028Armenta, S., & de la Guardia, M. (2016). Pollutants and Air Pollution. In Comprehensive Analytical Chemistry (Vol. 73). Elsevier Ltd. https://doi.org/10.1016/bs.coac.2016.03.002Austin, E., Zanobetti, A., Coull, B., Schwartz, J., Gold, D. R., & Koutrakis, P. (2015). Ozone trends and their relationship to characteristic weather patterns. Journal of Exposure Science and Environmental Epidemiology, 25(5), 535–542. https://doi.org/10.1038/jes.2014.45Jiao, J., Han, X., Li, F., Bai, Y., & Yu, Y. (2017). Contribution of demand shifts to industrial SO2 emissions in a transition economy: Evidence from China. Journal of Cleaner Production, 164, 1455–1466. https://doi.org/10.1016/j.jclepro.2017.07.060Kambezidis, H. D., & Kalliampakos, G. (2013). Mapping atmospheric corrosion on modern materials in the greater Athens area. Water, Air, and Soil Pollution, 224(3), 1463. https://doi.org/10.1007/s11270-013-1463-yKarl, T. G., Christian, T. J., Yokelson, R. J., Artaxo, P., Hao, W. M., & Guenther, A. (2007). The tropical forest and fire emissions experiment: Method evaluation of volatile organic compound emissions measured by PTR-MS, FTIR, and GC from tropical biomass burning. Atmospheric Chemistry and Physics, 7(22), 5883–5897. https://doi.org/10.5194/acp-7-5883- 2007Kavassalis, S. C., & Murphy, J. G. (2017). Understanding ozone-meteorology correlations: A role for dry deposition. Geophysical Research Letters, 44(6), 2922–2931. https://doi.org/10.1002/2016GL071791Koppmann, R., von Czapiewski, K., & Reid, J. S. (2005). A review of biomass burning emissions, part I: gaseous emissions of carbon monoxide, methane, volatile organic compounds, and nitrogen containing compounds. Atmospheric Chemistry and Physics Discussions, 5(5), 10455–10516. https://doi.org/10.5194/acpd-5-10455-2005Koren, I., Kaufman, Y. J., Washington, R., Todd, M. C., Rudich, Y., Martins, J. V., & Rosenfeld, D. (2006). The Bodélé depression: A single spot in the Sahara that provides most of the mineral dust to the Amazon forest. Environmental Research Letters, 1(1). https://doi.org/10.1088/1748-9326/1/1/014005Kumar, A., Singh, D., Singh, B. P., Singh, M., Anandam, K., Kumar, K., & Jain, V. K. (2015). Spatial and temporal variability of surface ozone and nitrogen oxides in urban and rural ambient air of Delhi-NCR, India. Air Quality, Atmosphere and Health, 8(4), 391–399. https://doi.org/10.1007/s11869-014-0309-0Kwak, H. Y., Ko, J., Lee, S., & Joh, C. H. (2017). Identifying the correlation between rainfall, traffic flow performance and air pollution concentration in Seoul using a path analysis. Transportation Research Procedia, 25, 3552–3563. https://doi.org/10.1016/j.trpro.2017.05.288Lawrence, M. G., & Lelieveld, J. (2010). Atmospheric pollutant outflow from southern Asia: A review. Atmospheric Chemistry and Physics, 10(22), 11017–11096. https://doi.org/10.5194/acp-10-11017-2010Lazaridis, M. (2011). Fisrt Principles of Meteorology and Air Pollution (J. T. Brian Alloway (ed.); 19th ed.). Springer.Lazaridis, M., Katsivela, E., Kopanakis, I., Raisi, L., Mihalopoulos, N., & Panagiaris, G. (2018). Characterization of airborne particulate matter and microbes inside cultural heritage collections. Journal of Cultural Heritage, 30, 136–146. https://doi.org/10.1016/j.culher.2017.09.018Lee, S., Ho, C. H., & Choi, Y. S. (2011). High-PM10 concentration episodes in Seoul, Korea: Background sources and related meteorological conditions. Atmospheric Environment, 45(39), 7240–7247. https://doi.org/10.1016/j.atmosenv.2011.08.071Li, L., Wu, A. H., Cheng, I., Chen, J. C., & Wu, J. (2017). Spatiotemporal estimation of historical PM2.5concentrations using PM10, meteorological variables, and spatial effect. Atmospheric Environment, 166, 182–191. https://doi.org/10.1016/j.atmosenv.2017.07.023Li, L., Wu, J., Ghosh, J. K., & Ritz, B. (2013). Estimating spatiotemporal variability of ambient air pollutant concentrations with a hierarchical model. Atmospheric Environment, 71, 54– 63. https://doi.org/10.1016/j.atmosenv.2013.01.038Li, Q., Gabay, M., Rubin, Y., Raveh-Rubin, S., Rohatyn, S., Tatarinov, F., Rotenberg, E., Ramati, E., Dicken, U., Preisler, Y., Fredj, E., Yakir, D., & Tas, E. (2019). Investigation of ozone deposition to vegetation under warm and dry conditions near the Eastern Mediterranean coast. Science of the Total Environment, 658, 1316–1333. https://doi.org/10.1016/j.scitotenv.2018.12.272Li, Xiangyu, Huang, S., Jiao, A., Yang, X., Yun, J., Wang, Y., Xue, X., Chu, Y., Liu, F., Liu, Y., Ren, M., Chen, X., Li, N., Lu, Y., Mao, Z., Tian, L., & Xiang, H. (2017). Association between ambient fine particulate matter and preterm birth or term low birth weight: An updated systematic review and meta-analysis. Environmental Pollution, 227, 596–605. https://doi.org/10.1016/j.envpol.2017.03.055Li, Xiaolan, Ma, Y., Wang, Y., Liu, N., & Hong, Y. (2017). Temporal and spatial analyses of particulate matter (PM10and PM2.5) and its relationship with meteorological parameters over an urban city in northeast China. Atmospheric Research, 198(September 2016), 185– 193. https://doi.org/10.1016/j.atmosres.2017.08.023Limon–Sanchez, M. T., Carbajal–Romero, P., Hernandez–Mena, L., Saldarriaga–Norena, H., Lopez–Lopez, A., Cosio–Ramirez, R., Arriaga–Colina, J. L., & Smith, W. (2011). Black carbon in PM2.5, data from two urban sites in Guadalajara, Mexico during 2008. Atmospheric Pollution Research, 2(3), 358–365. https://doi.org/10.5094/APR.2011.040Ling, H., Schäfer, K., Xin, J., Qin, M., Suppan, P., & Wang, Y. (2014). Small-scale spatial variations of gaseous air pollutants e A comparison of path-integrated and in situ measurement methods. Atmospheric Environment, 92, 566–575. https://doi.org/10.1016/j.atmosenv.2014.01.062Liu, C., Sun, J., Liu, Y., Liang, H., Wang, M., Wang, C., & Shi, T. (2017). Different exposure levels of fine particulate matter and preterm birth: a meta-analysis based on cohort studies. Environmental Science and Pollution Research, 24(22), 17976–17984. https://doi.org/10.1007/s11356-017-9363-0Liu, Y., Gao, Y., Yu, N., Zhang, C., Wang, S., Ma, L., Zhao, J., & Lohmann, R. (2015). Particulate matter, gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) in an urban traffic tunnel of China: Emission from on-road vehicles and gas-particle partitioning. Chemosphere, 134, 52–59. https://doi.org/10.1016/j.chemosphere.2015.03.065Luben, T. J., Nichols, J. L., Dutton, S. J., Kirrane, E., Owens, E. O., Datko-Williams, L., Madden, M., & Sacks, J. D. (2017). A systematic review of cardiovascular emergency department visits, hospital admissions and mortality associated with ambient black carbon. Environment International, 107(January), 154–162. https://doi.org/10.1016/j.envint.2017.07.005Maji, K. J., Ye, W. F., Arora, M., & Nagendra, S. M. S. (2019). Ozone pollution in Chinese cities: Assessment of seasonal variation, health effects and economic burden. Environmental Pollution, 247(x), 792–801. https://doi.org/10.1016/j.envpol.2019.01.049Manahan, S. (2013). Fundamentak of environmental and toxicological chemestry: Sustainable Science (C. Press (ed.); Fourth Edi). CRC press.Mason, P. J., & Thomson, D. J. (2015). Boundary Layer (Atmospheric) and Air Pollution: Overview. Encyclopedia of Atmospheric Sciences: Second Edition, 1, 220–226. https://doi.org/10.1016/B978-0-12-382225-3.00081-5Ministerio de Ambiente Vivienda y Desarrollo Territorial. (2008). Manual de Operación de Sistemas de Vigilancia de la Calidad del aire.Monks, P. S. (2005). Gas-phase radical chemistry in the troposphere. In Chemical Society Reviews (Vol. 34, Issue 5, pp. 376–395). https://doi.org/10.1039/b307982cMontañez, D. P. (2019). ESTIMACIÓN DE LAS EMISIONES ATMOSFÉRICAS DE BUQUES EN EL PUERTO DE BARRANQUILLA. In Universidad del Norte (Vol. 1, Issue 1). https://doi.org/10.1017/CBO9781107415324.004Motallebi, N., Tran, H., Croes, B. E., & Larsen, L. C. (2003). Day-of-week patterns of particulate matter and its chemical components at selected sites in california? Journal of the Air and Waste Management Association, 53(7), 876–888. https://doi.org/10.1080/10473289.2003.10466229Muñoz, R. C. (2012). Relative roles of emissions and meteorology in the diurnal pattern of urban PM10: Analysis of the daylight saving time effect. Journal of the Air and Waste Management Association, 62(6), 642–650. https://doi.org/10.1080/10962247.2012.665147Naciones Unidas. (2020). Población urbana (% del total) (Issue i). https://datos.bancomundial.org/indicator/SP.URB.TOTL.IN.ZSNadadur, Srikanth S, Hollingsworth, J. W. (2015). Air Pollution and Health Effects (Springer- Verlag London (ed.)). https://doi.org/DOI 10.1007/978-1-4471-6669-6News, G. (2020). O que é a ’ nuvem de poeira Godzilla ’, que viaja 10 mil km do Saara para as Américas. https://g1.globo.com/natureza/noticia/2020/06/24/o-que-e-a-nuvem-de-poeiragodzilla-que-viaja-10-mil-km-do-saara-para-as-americas.ghtmlNúñez, Y. (2019). ESTIMACIÓN DE FUENTES DE MATERIAL PARTICULADO ATMOSFÉRICO (PM 10 y PM 2.5 ) EN LA CIUDAD DE BARRANQUILLA, COLOMBIA [Universidad de la Costa]. https://repositorio.cuc.edu.co/bitstream/handle/11323/6017/Estimación de fuentes de material particulado atmosférico %28PM10 y PM2.5%29 en la ciudad de Barranquilla%2C Colombia.pdf?sequence=1&isAllowed=yO’Leary, B., Reiners, J. J., Xu, X., & Lemke, L. D. (2016). Identification and influence of spatiotemporal outliers in urban air quality measurements. Science of the Total Environment, 573, 55–65. https://doi.org/10.1016/j.scitotenv.2016.08.031Ohara, T. (2019). Long-range transport and deposition of air pollution. Encyclopedia of Environmental Health, 126–130. https://doi.org/10.1016/B978-0-12-409548-9.11352-1ONS. (2018). Carga de enfermedad ambiental en Colombia - Informe Técnico Especial 10. In Observatorio Nacional de Salud. https://www.ins.gov.co/Direcciones/ONS/Informes/10 Carga de enfermedad ambiental en Colombia.pdfOuyang, W., Guo, B., Cai, G., Li, Q., Han, S., Liu, B., & Liu, X. (2015). The washing effect of precipitation on particulate matter and the pollution dynamics of rainwater in downtown Beijing. Science of the Total Environment, 505, 306–314. https://doi.org/10.1016/j.scitotenv.2014.09.062Owens, E. O., Patel, M. M., Kirrane, E., Long, T. C., Brown, J., Cote, I., Ross, M. A., & Dutton, S. J. (2017). Framework for assessing causality of air pollution-related health effects for reviews of the National Ambient Air Quality Standards. Regulatory Toxicology and Pharmacology, 88, 332–337. https://doi.org/10.1016/j.yrtph.2017.05.014Pachón, J. E., Galvis, B., Lombana, O., Carmona, L. G., Fajardo, S., Rincón, A., Meneses, S., Chaparro, R., Nedbor-Gross, R., & Henderson, B. (2018). Development and evaluation of a comprehensive atmospheric emission inventory for air quality modeling in the megacity of Bogotá. Atmosphere, 9(2), 1–17. https://doi.org/10.3390/atmos9020049Pateraki, S., Asimakopoulos, D. N., Flocas, H. A., Maggos, T., & Vasilakos, C. (2012). The role of meteorology on different sized aerosol fractions (PM10, PM2.5, PM2.5-10). Science of the Total Environment, 419, 124–135. https://doi.org/10.1016/j.scitotenv.2011.12.064Peshin, S. K., Sharma, A., Sharma, S. K., Naja, M., & Mandal, T. K. (2017). Spatio-temporal variation of air pollutants and the impact of anthropogenic effects on the photochemical buildup of ozone across Delhi-NCR. Sustainable Cities and Society, 35, 740–751. https://doi.org/10.1016/j.scs.2017.09.024Petit, R. H., Legrand, M., Jankowiak, I., Molinié, J., Asselin de Beauville, C., Marion, G., & Mansot, J. L. (2005). Transport of Saharan dust over the Caribbean Islands: Study of an event. Journal of Geophysical Research D: Atmospheres, 110(18), 1–19. https://doi.org/10.1029/2004JD004748Qu, W., Zhang, X., Wang, Y., & Fu, G. (2020). Atmospheric visibility variation over global land surface during 1973–2012: Influence of meteorological factors and effect of aerosol, cloud on ABL evolution. Atmospheric Pollution Research, 11(4), 730–743. https://doi.org/10.1016/j.apr.2020.01.002R.E., H., Harrison, R. M., & Querol, X. (2016). Airborne Particulate Matter: Sources, Atmospheric Processes and Health. The Royal Society of Chemistry. www.rsc.orgRaherison, C., & Filleul, L. (2002). Asthma in exercising children exposed to ozone [3]. Lancet, 360(9330), 411. https://doi.org/10.1016/S0140-6736(02)09580-6Ramírez, O., da Boit, K., Blanco, E., & Silva, L. F. O. (2020). Hazardous thoracic and ultrafine particles from road dust in a Caribbean industrial city. Urban Climate, 33(October 2019), 100655. https://doi.org/10.1016/j.uclim.2020.100655Ramírez, O., Sánchez de la Campa, A. M., & de la Rosa, J. (2018). Characteristics and temporal variations of organic and elemental carbon aerosols in a high–altitude, tropical Latin American megacity. Atmospheric Research, 210(April), 110–122. https://doi.org/10.1016/j.atmosres.2018.04.006Ramsey, N. R., Klein, P. M., & Moore, B. (2014). The impact of meteorological parameters on urban air qualityThe impact of meteorological parameters on urban air quality. Atmospheric Environment, 86, 58–67. https://doi.org/10.1016/j.atmosenv.2013.12.006Reche, C., Moreno, T., Amato, F., Pandolfi, M., Pérez, J., de la Paz, D., Diaz, E., GómezMoreno, F. J., Pujadas, M., Artíñano, B., Reina, F., Orio, A., Pallarés, M., Escudero, M., Tapia, O., Crespo, E., Vargas, R., Alastuey, A., & Querol, X. (2018). Spatio-temporal patterns of high summer ozone events in the Madrid Basin, Central Spain. Atmospheric Environment, 185(November 2017), 207–220. https://doi.org/10.1016/j.atmosenv.2018.05.002Richmond-Bryant, J., Saganich, C., Bukiewicz, L., & Kalin, R. (2009). Associations of PM2.5 and black carbon concentrations with traffic, idling, background pollution, and meteorology during school dismissals. Science of the Total Environment, 407(10), 3357–3364. https://doi.org/10.1016/j.scitotenv.2009.01.046Riggs, D. W., Zafar, N., Krishnasamy, S., Yeager, R., Rai, S. N., Bhatnagar, A., & O’Toole, T. E. (2020). Exposure to airborne fine particulate matter is associated with impaired endothelial function and biomarkers of oxidative stress and inflammation. Environmental Research, 180(November 2019), 108890. https://doi.org/10.1016/j.envres.2019.108890Rodríguez-Villamizar, L. A., Rojas-Roa, N. Y., Blanco-Becerra, L. C., Herrera-Galindo, V. M., & Fernández-Niño, J. A. (2018). Short-term effects of air pollution on respiratory and circulatory morbidity in colombia 2011–2014: A multi-city, time-series analysis. International Journal of Environmental Research and Public Health, 15(8). https://doi.org/10.3390/ijerph15081610Rodríguez-Villamizar, L. A., Rojas-Roa, N. Y., & Fernández-Niño, J. A. (2019). Short-term joint effects of ambient air pollutants on emergency department visits for respiratory and circulatory diseases in Colombia, 2011–2014. Environmental Pollution, 248, 380–387. https://doi.org/10.1016/j.envpol.2019.02.028Rohr, A. C., & Wyzga, R. E. (2012). Attributing health effects to individual particulate matter constituents. Atmospheric Environment, 62, 130–152. https://doi.org/10.1016/j.atmosenv.2012.07.036Russo, A., Gouveia, C., Levy, I., Dayan, U., Jerez, S., Mendes, M., & Trigo, R. (2016). Coastal recirculation potential affecting air pollutants in Portugal: The role of circulation weather types. Atmospheric Environment, 135, 9–19. https://doi.org/10.1016/j.atmosenv.2016.03.039Sandeep, A., Rao, T. N., Ramkiran, C. N., & Rao, S. V. B. (2014). Differences in Atmospheric Boundary-Layer Characteristics Between Wet and Dry Episodes of the Indian Summer Monsoon. Boundary-Layer Meteorology, 153(2), 217–236. https://doi.org/10.1007/s10546- 014-9945-zSchaller, B. (2010). New York City’s congestion pricing experience and implications for road pricing acceptance in the United States. Transport Policy, 17(4), 266–273. https://doi.org/10.1016/j.tranpol.2010.01.013Seinfeld, J. H., & Pandis, S. N. (2006). Atmospheric Chemistry: From Air Pollution to Climate Change (I. John Wiley & Sons (ed.); Second Edi).Seinfeld, J., & Pandis, S. N. (2016). Atmospheric Chemistry and Physics: From air pollution to climate change (WILEY (ed.); third edit).Shaddick, G., Thomas, M. L., Mudu, P., Ruggeri, G., & Gumy, S. (2020). Half the world’s population are exposed to increasing air pollution. Npj Climate and Atmospheric Science, 3(1), 1–5. https://doi.org/10.1038/s41612-020-0124-2Shahid, I., Kistler, M., Mukhtar, A., Ghauri, B. M., Ramirez-Santa Cruz, C., Bauer, H., & Puxbaum, H. (2016). Chemical characterization and mass closure of PM10 and PM2.5 at an urban site in Karachi - Pakistan. Atmospheric Environment, 128, 114–123. https://doi.org/10.1016/j.atmosenv.2015.12.005Shi, S., Chen, C., & Zhao, B. (2017). Modifications of exposure to ambient particulate matter: Tackling bias in using ambient concentration as surrogate with particle infiltration factor and ambient exposure factor. Environmental Pollution, 220, 337–347. https://doi.org/10.1016/j.envpol.2016.09.069SIAC. (2020). Fenómenos del Niño y la Niña. http://www.siac.gov.co/ninoyninaSimon, H., Reff, A., Wells, B., Xing, J., & Frank, N. (2015). Ozone trends across the United States over a period of decreasing NOx and VOC emissions. Environmental Science and Technology, 49(1), 186–195. https://doi.org/10.1021/es504514zSippo, J. Z., Maher, D. T., Tait, D. R., Ruiz-Halpern, S., Sanders, C. J., & Santos, I. R. (2017). Mangrove outwelling is a significant source of oceanic exchangeable organic carbon. Limnology and Oceanography Letters, 2(1), 1–8. https://doi.org/10.1002/lol2.10031Stanek, L. W., & Brown, J. S. (2019). Air Pollution: Sources, Regulation, and Health Effects. In Reference Module in Biomedical Sciences (Issue June, pp. 1–10). Elsevier Inc. https://doi.org/10.1016/b978-0-12-801238-3.11384-4Stanek, L. W., Sacks, J. D., Dutton, S. J., & Dubois, J. J. B. (2011). Attributing health effects to apportioned components and sources of particulate matter: An evaluation of collective results. Atmospheric Environment, 45(32), 5655–5663. https://doi.org/10.1016/j.atmosenv.2011.07.023Suh, H. H., Bahadori, T., Vallarino, J., & Spengler, J. D. (2018). Criteria Air Pollutants and Toxic Air Pollutants. 108, 625–633. https://doi.org/10.2307/3454398Tang, J., McNabola, A., Misstear, B., Pilla, F., & Alam, M. S. (2019). Assessing the impact of vehicle speed limits and fleet composition on air quality near a school. International Journal of Environmental Research and Public Health, 16(1). https://doi.org/10.3390/ijerph16010149Thurston, G. D. (2016a). Outdoor Air Pollution: Sources, Atmospheric Transport, and Human Health Effects. In International Encyclopedia of Public Health (Second Edi, Vol. 5, Issue 69). Elsevier. https://doi.org/10.1016/B978-0-12-803678-5.00320-9Tian, Ye, Yao, X., & Chen, L. (2019). Analysis of spatial and seasonal distributions of air pollutants by incorporating urban morphological characteristics. Computers, Environment and Urban Systems, 75(April 2018), 35–48. https://doi.org/10.1016/j.compenvurbsys.2019.01.003Tian, Yulu, Jiang, Y., Liu, Q., Xu, D., Zhao, S., He, L., Liu, H., & Xu, H. (2019). Temporal and spatial trends in air quality in Beijing. Landscape and Urban Planning, 185(October 2018), 35–43. https://doi.org/10.1016/j.landurbplan.2019.01.006Tiwari, S., Dumka, U. C., Gautam, A. S., Kaskaoutis, D. G., Srivastava, A. K., Bisht, D. S., Chakrabarty, R. K., Sumlin, B. J., & Solmon, F. (2017). Assessment of PM2.5and PM10over Guwahati in Brahmaputra River Valley: Temporal evolution, source apportionment and meteorological dependence. Atmospheric Pollution Research, 8(1), 13– 28. https://doi.org/10.1016/j.apr.2016.07.008Toro A., R., Morales S., R. G. E., Canales, M., Gonzalez-Rojas, C., & Leiva G., M. A. (2014). Inhaled and inspired particulates in Metropolitan Santiago Chile exceed air quality standards. Building and Environment, 79, 115–123. https://doi.org/10.1016/j.buildenv.2014.05.004Triantafyllou, E., Diapouli, E., Korras-Carraca, Manousakas, M., Psanis, C., Floutsi, A. A., Spyrou, C., Eleftheriadis, K., & Biskos, G. (2020). Contribution of locally-produced and transported air pollution to particulate matter in a small insular coastal city. Atmospheric Pollution Research, 11(4), 667–678. https://doi.org/10.1016/j.apr.2019.12.015Tzortziou, M., Parker, O., Lamb, B., Herman, J. R., Lamsal, L., Stauffer, R., & Abuhassan, N. (2018). Atmospheric trace gas (NO2 and O3) variability in south Korean coastal waters, and implications for remote sensing of coastal ocean color dynamics. Remote Sensing, 10(10), 1–20. https://doi.org/10.3390/rs10101587Vallero, D. A. (2014). Fundamentals of air pollution (5th editio). Elsevier. https://doi.org/https://doi.org/10.1016/C2012-0-01172-6 van der Zee, S. C., Fischer, P. H., & Hoek, G. (2016). Air pollution in perspective: Health risks of air pollution expressed in equivalent numbers of passively smoked cigarettes. Environmental Research, 148, 475–483. https://doi.org/10.1016/j.envres.2016.04.001Vellingiri, K., Kim, K. H., Ma, C. J., Kang, C. H., Lee, J. H., Kim, I. S., & Brown, R. J. C. (2015). Ambient particulate matter in a central urban area of Seoul, Korea. Chemosphere, 119, 812–819. https://doi.org/10.1016/j.chemosphere.2014.08.049Viana, M., Pérez, C., Querol, X., Alastuey, A., Nickovic, S., & Baldasano, J. M. (2005). Spatial and temporal variability of PM levels and composition in a complex summer atmospheric scenario in Barcelona (NE Spain). Atmospheric Environment, 39(29), 5343–5361. https://doi.org/10.1016/j.atmosenv.2005.05.039Vicedo-Cabrera, A. M., Sera, F., Liu, C., Armstrong, B., Milojevic, A., Guo, Y., Tong, S., Lavigne, E., Kyselý, J., Urban, A., Orru, H., Indermitte, E., Pascal, M., Huber, V., Schneider, A., Katsouyanni, K., Samoli, E., Stafoggia, M., Scortichini, M., … Gasparrini, A. (2020). Short term association between ozone and mortality: global two stage time series study in 406 locations in 20 countries. The BMJ, 368, 1–10. https://doi.org/10.1136/bmj.m108Vitolo, C., Scutari, M., Ghalaieny, M., Tucker, A., & Russell, A. (2018). Modeling Air Pollution, Climate, and Health Data Using Bayesian Networks: A Case Study of the English Regions. Earth and Space Science, 5(4), 76–88. https://doi.org/10.1002/2017EA000326Wang, T., Xue, L., Brimblecombe, P., Lam, Y. F., Li, L., & Zhang, L. (2017a). Ozone pollution in China: A review of concentrations, meteorological influences, chemical precursors, and effects. Science of the Total Environment, 575, 1582–1596. https://doi.org/10.1016/j.scitotenv.2016.10.081Wang, Yan, Shi, L., Lee, M., Liu, P., Di, Q., Zanobetti, A., & Schwartz, J. D. (2017). Long-term Exposure to PM 2.5 and Mortality among Older Adults in the Southeastern US. Epidemiology, 28(2), 207–214. https://doi.org/10.1097/EDE.0000000000000614Wang, Yungang, Ying, Q., Hu, J., & Zhang, H. (2014). Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013-2014. Environment International, 73, 413–422. https://doi.org/10.1016/j.envint.2014.08.016Watson, J. G., & Chow, J. C. (2015). Receptor Models and Measurements for Identifying and Quantifying Air Pollution Sources. In Introduction to Environmental Forensics: Third Edition (Third Edit). Elsevier Ltd. https://doi.org/10.1016/B978-0-12-404696-2.00020-5WHO. (2018). Global Ambient Air Quality Database (update 2018). In World Health Organization (Issue update 2018). https://www.who.int/airpollution/data/cities/en/WHO, Health Organization, W., & Office for Europe, R. (2013). Review of evidence on health aspects of air pollution-REVIHAAP Project Technical Report.World Health Organization. (2016). Ambient (outdoor) air pollution. https://www.who.int/newsroom/fact-sheets/detail/ambient-(outdoor)-air-quality-and-healthWorld Health Organization WHO. (2016). Urban Ambient Air Pollution database ‐ Update 2016. WHO. https://doi.org//entity/phe/health_topics/outdoorair/databases/cities/en/index.htmlXian, J., Sun, D., Xu, W., Han, Y., Zheng, J., Peng, J., & Yang, S. (2020). Urban air pollution monitoring using scanning Lidar. Environmental Pollution, 258. https://doi.org/10.1016/j.envpol.2019.113696Xie, Y., Zhao, B., Zhang, L., & Luo, R. (2015a). Spatiotemporal variations of PM2.5 and PM10 concentrations between 31 Chinese cities and their relationships with SO2, NO2, CO and O3. Particuology, 20, 141–149. https://doi.org/10.1016/j.partic.2015.01.003Xu, F., Shi, X., Qiu, X., Jiang, X., Fang, Y., Wang, J., Hu, D., & Zhu, T. (2020). Investigation of the chemical components of ambient fine particulate matter (PM2.5) associated with in vitro cellular responses to oxidative stress and inflammation. Environment International, 136(January). https://doi.org/10.1016/j.envint.2020.105475Yang, J., Ji, Z., Kang, S., Zhang, Q., Chen, X., & Lee, S. Y. (2019). Spatiotemporal variations of air pollutants in western China and their relationship to meteorological factors and emission sources. Environmental Pollution, 254, 112952. https://doi.org/10.1016/j.envpol.2019.07.120Yang, L., Liu, Z., Guan, Q., Wang, L., & Wang, F. (2018a). Association between heating seasons and criteria air pollutants in three provincial capitals in northern China: Spatiotemporal variation and sources contribution. Building and Environment, 132(November 2017), 233–244. https://doi.org/10.1016/j.buildenv.2018.01.034Yu, J., Mi, N., Yu, Q., Li, S., He, C., Yin, L., Li, S., Zhang, Y., Yao, Y., Ma, W., & Wang, W. (2019). Properties of particulate matter and gaseous pollutants in Shandong, China: Daily fluctuation, influencing factors, and spatiotemporal distribution. Science of The Total Environment, 660, 384–394. https://doi.org/10.1016/j.scitotenv.2019.01.026Yu, J., Mi, N., Yu, Q., Li, S. S., He, C., Yin, L., Li, S. S., Zhang, Y., Yao, Y., Ma, W., Wang, W., Mi, K., Zhuang, R., Zhang, Z., Gao, J., Pei, Q., Li, R., Wang, Z., Cui, L., … Chen, L. (2019). Spatiotemporal characteristics of PM2.5 and its associated gas pollutants, a case in China. Sustainable Cities and Society, 648(April 2018), 35–48. https://doi.org/10.1016/j.scitotenv.2018.08.181Zeri, M., Oliveira-Júnior, J. F., & Lyra, G. B. (2011). Spatiotemporal analysis of particulate matter, sulfur dioxide and carbon monoxide concentrations over the city of Rio de Janeiro, Brazil. Meteorology and Atmospheric Physics, 113(3), 139–152. https://doi.org/10.1007/s00703-011-0153-9Zhan, Y., Luo, Y., Deng, X., Grieneisen, M. L., Zhang, M., & Di, B. (2018). Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment. Environmental Pollution, 233, 464–473. https://doi.org/10.1016/j.envpol.2017.10.029Zhang, B. N., & Kim Oanh, N. T. (2002). Photochemical smog pollution in the Bangkok Metropolitan Region of Thailand in relation to O3 precursor concentrations and meteorological conditions. Atmospheric Environment, 36(26), 4211–4222. https://doi.org/10.1016/S1352-2310(02)00348-5Zhang, H., Wang, Y., Hu, J., Ying, Q., & Hu, X. M. (2015). Relationships between meteorological parameters and criteria air pollutants in three megacities in China. Environmental Research, 140, 242–254. https://doi.org/10.1016/j.envres.2015.04.004Zhang, K., & Batterman, S. (2013). Air pollution and health risks due to vehicle traffic. Science of the Total Environment, 450–451, 307–316. https://doi.org/10.1016/j.scitotenv.2013.01.074Zhao, H., Che, H., Ma, Y., Xia, X., Wang, Y., Wang, P., & Wu, X. (2015). Temporal variability of the visibility, particulate matter mass concentration and aerosol optical properties over an urban site in Northeast China. Atmospheric Research, 166, 204–212. https://doi.org/10.1016/j.atmosres.2015.07.003Zhao, H., Che, H., Zhang, X., Ma, Y., Wang, Y., Wang, H., & Wang, Y. (2013). Characteristics of visibility and particulate matter (PM) in an urban area of Northeast China. Atmospheric Pollution Research, 4(4), 427–434. https://doi.org/10.5094/APR.2013.049Zhao, S., Yu, Y., Yin, D., Qin, D., He, J., & Dong, L. (2018). Spatial patterns and temporal variations of six criteria air pollutants during 2015 to 2017 in the city clusters of Sichuan Basin, China. Science of the Total Environment, 624, 540–557. https://doi.org/10.1016/j.scitotenv.2017.12.172PublicationORIGINALEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdfEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdfapplication/pdf2289373https://repositorio.cuc.edu.co/bitstreams/12025781-9786-465b-8837-6ce943c23577/download823dc66363436fd70f134179bdf7e11cMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81031https://repositorio.cuc.edu.co/bitstreams/34bb9741-15c1-47cf-b9e1-43b4be0653d0/download934f4ca17e109e0a05eaeaba504d7ce4MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/3a0d5ea1-a276-4b9f-b6be-26bef72307e9/downloade30e9215131d99561d40d6b0abbe9badMD53THUMBNAILEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdf.jpgEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdf.jpgimage/jpeg25667https://repositorio.cuc.edu.co/bitstreams/9103e27a-4f36-40cd-8452-36274381ab86/download63cee4b016c13c60fe260f887ac94b1eMD54THUMBNAILEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdf.jpgEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdf.jpgimage/jpeg25667https://repositorio.cuc.edu.co/bitstreams/a8a04dc4-07d4-43d9-8520-b57267cb450e/download63cee4b016c13c60fe260f887ac94b1eMD54TEXTEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdf.txtEvaluación espaciotemporal de contaminantes atmosféricos en la ciudad de Barranquilla.pdf.txttext/plain198485https://repositorio.cuc.edu.co/bitstreams/8cab8360-46ab-4a2f-9032-fbd224b8615a/download63af7cf2ce4ce8c06e54a72045db6d75MD5511323/7079oai:repositorio.cuc.edu.co:11323/70792024-09-16 16:43:39.538http://creativecommons.org/licenses/by-nc-sa/4.0/Attribution-NonCommercial-ShareAlike 4.0 Internationalopen.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |