Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city

NO2 ambient concentrations were measured in a coastal Caribbean city. Barranquilla is a Caribbean city located in the North of Colombia that has approximately 1.200.000 inhabitants and possesses a warm, humid climate. In order to obtain the concentration of the contaminant in an adequate resolution,...

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Autores:
Agudelo-Castañeda, Dayana Milena
De Paoli, Fabrício
MORGADO GAMERO, WENDY BEATRIZ
Mendoza Hernandez, Martha
Parody, Alexander
Maturana, Aymer
Calesso Teixeira, Elba
Tipo de recurso:
http://purl.org/coar/resource_type/c_816b
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/6157
Acceso en línea:
https://hdl.handle.net/11323/6157
https://repositorio.cuc.edu.co/
Palabra clave:
NO2
Spatial variability
Regression model
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_a93710f01acc74c47edc0a564ce6fa71
oai_identifier_str oai:repositorio.cuc.edu.co:11323/6157
network_acronym_str RCUC2
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dc.title.spa.fl_str_mv Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
title Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
spellingShingle Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
NO2
Spatial variability
Regression model
title_short Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
title_full Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
title_fullStr Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
title_full_unstemmed Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
title_sort Assessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal city
dc.creator.fl_str_mv Agudelo-Castañeda, Dayana Milena
De Paoli, Fabrício
MORGADO GAMERO, WENDY BEATRIZ
Mendoza Hernandez, Martha
Parody, Alexander
Maturana, Aymer
Calesso Teixeira, Elba
dc.contributor.author.spa.fl_str_mv Agudelo-Castañeda, Dayana Milena
De Paoli, Fabrício
MORGADO GAMERO, WENDY BEATRIZ
Mendoza Hernandez, Martha
Parody, Alexander
Maturana, Aymer
Calesso Teixeira, Elba
dc.subject.spa.fl_str_mv NO2
Spatial variability
Regression model
topic NO2
Spatial variability
Regression model
description NO2 ambient concentrations were measured in a coastal Caribbean city. Barranquilla is a Caribbean city located in the North of Colombia that has approximately 1.200.000 inhabitants and possesses a warm, humid climate. In order to obtain the concentration of the contaminant in an adequate resolution, 137 passive diffusion tubes from Gradko© were installed. Diffusion passive tubes prepared with 20% TEA/water were located at the roadside between 1 and 5 m from the kerb edge. The sampling period was two weeks, from 3/16/2019 to 3/30/2019. Samples were analyzed on the UV CARY1 spectrophotometer by Gradko©. Results showed an average of 19.92 ±11.50 µg/m3 , with a maximum and minimum value of 70.27 and 0.57 µg/m3 , respectively. Spatial NO2 correlation with low traffic load was higher than with maximum traffic. The expected results include analyzing the areas of the city with high concentrations of this pollutant that exceed the WHO guidelines in six (6) points. Overall, the multiregression analysis is a very effective method to enrich the understanding of NO2 distributions. It can provide scientific evidence for the relationship between NO2 and traffic, beneficial for developing the targeted policies and measures to reduce NO2 pollution levels in hot spots. This research may subsidize knowledge to serve as a tool for environmental and health authorities.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-04-09T19:44:48Z
dc.date.available.none.fl_str_mv 2020-04-09T19:44:48Z
dc.date.issued.none.fl_str_mv 2020
dc.type.spa.fl_str_mv Pre-Publicación
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dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
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url https://hdl.handle.net/11323/6157
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identifier_str_mv Corporación Universidad de la Costa
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language eng
dc.relation.references.spa.fl_str_mv Achakulwisut, P., Brauer, M., Hystad, P., Anenberg, S.C., 2019. Global, national, and urban burdens of pediatric asthma incidence attributable to ambient NO2 pollution: estimates from global datasets. Lancet Planet. Heal. 3, e166–e178. https://doi.org/10.1016/S25425196(19)30046-4
Adame, J.A., Serrano, E., Bolívar, J.P., de la Morena, B.A., 2010. On the tropospheric ozone variations in a coastal area of Southwestern Europe under a mesoscale circulation. J. Appl. Meteorol. Climatol. 49, 748–759. https://doi.org/10.1175/2009JAMC2097.1
Coughlin, J.G., Yu, Z., Elliott, E.M., 2017. Efficacy of passive sampler collection for atmospheric NO2 isotopes under simulated environmental conditions. Rapid Commun. Mass Spectrom. 31, 1211–1220. https://doi.org/10.1002/rcm.7885
Cyrys, J., Eeftens, M., Heinrich, J., Ampe, C., Armengaud, A., Beelen, R., Bellander, T., Beregszaszi, T., Birk, M., Cesaroni, G., Cirach, M., de Hoogh, K., De Nazelle, A., de Vocht, F., Declercq, C., Dedele, A., Dimakopoulou, K., Eriksen, K., Galassi, C., Graulevičiene, R., Grivas, G., Gruzieva, O., Gustafsson, A.H., Hoffmann, B., Iakovides, M., Ineichen, A., Krämer, U., Lanki, T., Lozano, P., Madsen, C., Meliefste, K., Modig, L., Mölter, A., Mosler, G., Nieuwenhuijsen, M., Nonnemacher, M., Oldenwening, M., Peters, A., Pontet, S., ProbstHensch, N., Quass, U., Raaschou-Nielsen, O., Ranzi, A., Sugiri, D., Stephanou, E.G., Taimisto, P., Tsai, M.Y., Vaskövi, É., Villani, S., Wang, M., Brunekreef, B., Hoek, G., 2012. Variation of NO2 and NOx concentrations between and within 36 European study areas: Results from the ESCAPE study. Atmos. Environ. 62, 374–390. https://doi.org/10.1016/j.atmosenv.2012.07.080
Felix, E., Gidhagen, L., Alonso, M.F., Nahirny, E.P., Alves, B.L., Segersson, D., Amorim, J.H., 2019. Passive sampling as a feasible tool for mapping and model evaluation of the spatial distribution of nitrogen oxides in the city of Curitiba, Brazil. Air Qual. Atmos. Heal. 12, 837– 846. https://doi.org/10.1007/s11869-019-00701-z
Geddes, J.A., Martin, R. V., Boys, B.L., van Donkelaar, A., 2016. Long-term trends worldwide in ambient NO2 concentrations inferred from satellite observations. Environ. Health Perspect. 124, 281–289. https://doi.org/10.1289/ehp.1409567
Kimbrough, S., Chris Owen, R., Snyder, M., Richmond-Bryant, J., 2017. NO to NO2 conversion rate analysis and implications for dispersion model chemistry methods using Las Vegas, Nevada near-road field measurements. Atmos. Environ. 165, 23–34. https://doi.org/10.1016/j.atmosenv.2017.06.027
Lanzafame, R., Monforte, P., Scandura Pier, F., 2016. Comparative Analyses of Urban Air Quality Monitoring Systems: Passive Sampling and Continuous Monitoring Stations. Energy Procedia 101, 321–328. https://doi.org/10.1016/j.egypro.2016.11.041 ul-Haq, Z., Tariq, S., Ali, M., Mahmood, K., Batool, S.A., Rana, A.D., 2014. A study of tropospheric NO2 variability over Pakistan using OMI data. Atmos. Pollut. Res. 5, 709–720. https://doi.org/10.5094/APR.2014.080
Zhang, L., Lee, C.S., Zhang, R., Chen, L., 2017. Spatial and temporal evaluation of long term trend (2005–2014) of OMI retrieved NO2and SO2concentrations in Henan Province, China. Atmos. Environ. 154, 151–166. https://doi.org/10.1016/j.atmosenv.2016.11.067
IDEAM. Atlas climatológico de Colombia. http://atlas.ideam.gov.co/visorAtlasClimatologico.html
Barranquilla, 2018. Alcaldía de Barranquilla. [WWW Document]. URL http://www.barranquilla.gov.co/index.php?option=com_content&view=article&id=27&Ite mid=118. (accessed 7.31.18).
Morgado Gamero W.B., Ramírez M.C., Parody A., Viloria A., López M.H.A., Kamatkar S.J. (2018) Concentrations and Size Distributions of Fungal Bioaerosols in a Municipal Landfill. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham
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spelling Agudelo-Castañeda, Dayana MilenaDe Paoli, FabrícioMORGADO GAMERO, WENDY BEATRIZMendoza Hernandez, MarthaParody, AlexanderMaturana, AymerCalesso Teixeira, Elba2020-04-09T19:44:48Z2020-04-09T19:44:48Z2020https://hdl.handle.net/11323/6157Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/NO2 ambient concentrations were measured in a coastal Caribbean city. Barranquilla is a Caribbean city located in the North of Colombia that has approximately 1.200.000 inhabitants and possesses a warm, humid climate. In order to obtain the concentration of the contaminant in an adequate resolution, 137 passive diffusion tubes from Gradko© were installed. Diffusion passive tubes prepared with 20% TEA/water were located at the roadside between 1 and 5 m from the kerb edge. The sampling period was two weeks, from 3/16/2019 to 3/30/2019. Samples were analyzed on the UV CARY1 spectrophotometer by Gradko©. Results showed an average of 19.92 ±11.50 µg/m3 , with a maximum and minimum value of 70.27 and 0.57 µg/m3 , respectively. Spatial NO2 correlation with low traffic load was higher than with maximum traffic. The expected results include analyzing the areas of the city with high concentrations of this pollutant that exceed the WHO guidelines in six (6) points. Overall, the multiregression analysis is a very effective method to enrich the understanding of NO2 distributions. It can provide scientific evidence for the relationship between NO2 and traffic, beneficial for developing the targeted policies and measures to reduce NO2 pollution levels in hot spots. This research may subsidize knowledge to serve as a tool for environmental and health authorities.Agudelo-Castañeda, Dayana Milena-will be generated-orcid-0000-0002-6589-6835-600De Paoli, Fabrício-will be generated-orcid-0000-0003-4322-6416-600MORGADO GAMERO, WENDY BEATRIZ-will be generated-orcid-0000-0003-2394-2589-600Mendoza Hernandez, MarthaParody, AlexanderMaturana, AymerCalesso Teixeira, Elba-will be generated-orcid-0000-0002-0382-5898-600engUniversidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2NO2Spatial variabilityRegression modelAssessment of the NO2 distribution and relationship with traffic load in the Caribbean coastal cityPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionAchakulwisut, P., Brauer, M., Hystad, P., Anenberg, S.C., 2019. Global, national, and urban burdens of pediatric asthma incidence attributable to ambient NO2 pollution: estimates from global datasets. Lancet Planet. Heal. 3, e166–e178. https://doi.org/10.1016/S25425196(19)30046-4Adame, J.A., Serrano, E., Bolívar, J.P., de la Morena, B.A., 2010. On the tropospheric ozone variations in a coastal area of Southwestern Europe under a mesoscale circulation. J. Appl. Meteorol. Climatol. 49, 748–759. https://doi.org/10.1175/2009JAMC2097.1Coughlin, J.G., Yu, Z., Elliott, E.M., 2017. Efficacy of passive sampler collection for atmospheric NO2 isotopes under simulated environmental conditions. Rapid Commun. Mass Spectrom. 31, 1211–1220. https://doi.org/10.1002/rcm.7885Cyrys, J., Eeftens, M., Heinrich, J., Ampe, C., Armengaud, A., Beelen, R., Bellander, T., Beregszaszi, T., Birk, M., Cesaroni, G., Cirach, M., de Hoogh, K., De Nazelle, A., de Vocht, F., Declercq, C., Dedele, A., Dimakopoulou, K., Eriksen, K., Galassi, C., Graulevičiene, R., Grivas, G., Gruzieva, O., Gustafsson, A.H., Hoffmann, B., Iakovides, M., Ineichen, A., Krämer, U., Lanki, T., Lozano, P., Madsen, C., Meliefste, K., Modig, L., Mölter, A., Mosler, G., Nieuwenhuijsen, M., Nonnemacher, M., Oldenwening, M., Peters, A., Pontet, S., ProbstHensch, N., Quass, U., Raaschou-Nielsen, O., Ranzi, A., Sugiri, D., Stephanou, E.G., Taimisto, P., Tsai, M.Y., Vaskövi, É., Villani, S., Wang, M., Brunekreef, B., Hoek, G., 2012. Variation of NO2 and NOx concentrations between and within 36 European study areas: Results from the ESCAPE study. Atmos. Environ. 62, 374–390. https://doi.org/10.1016/j.atmosenv.2012.07.080Felix, E., Gidhagen, L., Alonso, M.F., Nahirny, E.P., Alves, B.L., Segersson, D., Amorim, J.H., 2019. Passive sampling as a feasible tool for mapping and model evaluation of the spatial distribution of nitrogen oxides in the city of Curitiba, Brazil. Air Qual. Atmos. Heal. 12, 837– 846. https://doi.org/10.1007/s11869-019-00701-zGeddes, J.A., Martin, R. V., Boys, B.L., van Donkelaar, A., 2016. Long-term trends worldwide in ambient NO2 concentrations inferred from satellite observations. Environ. Health Perspect. 124, 281–289. https://doi.org/10.1289/ehp.1409567Kimbrough, S., Chris Owen, R., Snyder, M., Richmond-Bryant, J., 2017. NO to NO2 conversion rate analysis and implications for dispersion model chemistry methods using Las Vegas, Nevada near-road field measurements. Atmos. Environ. 165, 23–34. https://doi.org/10.1016/j.atmosenv.2017.06.027Lanzafame, R., Monforte, P., Scandura Pier, F., 2016. Comparative Analyses of Urban Air Quality Monitoring Systems: Passive Sampling and Continuous Monitoring Stations. Energy Procedia 101, 321–328. https://doi.org/10.1016/j.egypro.2016.11.041 ul-Haq, Z., Tariq, S., Ali, M., Mahmood, K., Batool, S.A., Rana, A.D., 2014. A study of tropospheric NO2 variability over Pakistan using OMI data. Atmos. Pollut. Res. 5, 709–720. https://doi.org/10.5094/APR.2014.080Zhang, L., Lee, C.S., Zhang, R., Chen, L., 2017. Spatial and temporal evaluation of long term trend (2005–2014) of OMI retrieved NO2and SO2concentrations in Henan Province, China. Atmos. Environ. 154, 151–166. https://doi.org/10.1016/j.atmosenv.2016.11.067IDEAM. Atlas climatológico de Colombia. http://atlas.ideam.gov.co/visorAtlasClimatologico.htmlBarranquilla, 2018. Alcaldía de Barranquilla. [WWW Document]. URL http://www.barranquilla.gov.co/index.php?option=com_content&view=article&id=27&Ite mid=118. (accessed 7.31.18).Morgado Gamero W.B., Ramírez M.C., Parody A., Viloria A., López M.H.A., Kamatkar S.J. (2018) Concentrations and Size Distributions of Fungal Bioaerosols in a Municipal Landfill. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. 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