Estimation of the impact of biomass burning based on regional transport of PM2.5 in the Colombian Caribbean

dc.creatorBolaño-Truyol, Jehison
dc.creatorSchneider, Ismael
dc.creatorCANO CUADRO, HEIDIS PATRICIA
dc.creatorBolaño Truyol, Jorge Daniel
dc.creatorL.S. Oliveira, Marcos
dc.date2021-05-31T17:10:41Z
dc.date2021-05-31T17:10:41Z
dc.date2021-01-31
dc.date.accessioned2023-10-03T19:54:10Z
dc.date.available2023-10-03T19:54:10Z
dc.identifier1674-9871
dc.identifierhttps://hdl.handle.net/11323/8302
dc.identifierhttps://doi.org/10.1016/j.gsf.2021.101152
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9173141
dc.descriptionDeterioration of air quality due to the increase in atmospheric emissions from biomass burning (BB) is one of the major environmental problems worldwide. In this study, we estimated the contributions of BB to PM2.5 concentrations in the municipalities of Soledad and Malambo located in the Colombian Caribbean. The evaluation period ranged from February 24 to March 30, 2018, a period with a high number of BB events recorded in the surroundings of the evaluated sites. The contribution of BB to the two sampling sites was estimated using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) dispersion model with forwarding trajectories from each of the burning points identified by satellite images (n = 1089). The PM2.5 emissions were determined using the fire radiative power (FRP), obtained by remote-sensing data, and corresponded to the radiant energy released per time unit by burning vegetation. The average PM2.5 concentrations during the evaluation period were 19.91 μg/m3 for Soledad and 22.44 μg/m3 for Malambo. The average contribution of BB to these municipalities was 22.8% and 28.8%, respectively. The methodology used in this study allowed to estimate the contribution of this important source without knowledge of a previous tracer of BB, thereby increasing the use of the proposed procedure worldwide. This information would enable the implementation of effective mitigation, thereby diminishing the adverse impact of PM2.5 on the health of the population.
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dc.formatapplication/pdf
dc.languageeng
dc.relationAmegah, A.K., 2018. Proliferation of low-cost sensors. What prospects for air pollution epidemiologic research in Sub-Saharan Africa? Environ. Pollut. 241, 1132–1137.
dc.relationBarranquilla, 2016. Plan de Ordenamiento Territorial. https://www.barranquilla.gov.co/ transparencia/planeacion/politicas-lineamientos-y-manuales/planes-estrategicos/ plan-de-ordenamiento-territorial
dc.relationDANE – Departamento Administrativo Nacional de Estadística, 2018. Censo Nacional de Población y Vivienda. https://www.dane.gov.co/files/censo2018/informaciontecnica/CNPV-2018-VIHOPE-v2.xls.
dc.relationGuo, L., Chen, B., Zhang, H., Xu, G., Lu, L., Lin, X., Kong, Y., Wang, F., Li, Y., 2018. Improving PM2.5 forecasting and emission estimation based on the Bayesian Optimization Method and the coupled FLEXPART-WRF model. Atmosphere 9 (11), 428.
dc.relationHoyos, N., Correa-Metrio, A., Sisa, A., Ramos-Fabiel, M.A., Espinosa, J.M., Restrepo, J.C., Escobar, J., 2017. The environmental envelope of fires in the Colombian Caribbean. Appl. Geogr. 84, 42–54
dc.relationHuang, X.H.H., Bian, Q., Ng, W.M., Louie, P.K.K., Yu, J.Z., 2014. Characterization of PM2.5 major components and source investigation in suburban Hong Kong: a one year monitoring study. Aerosol Air Qual. Res. 14 (1), 237–250.
dc.relationIslam, M.R., Jayarathne, T., Simpson, I.J., Werden, B., Maben, J., Gilbert, A., Praveen, P.S., Adhikari, S., Panday, A.K., Rupakheti, M., Blake, D.R., Yokelson, R.J., DeCarlo, P.F., Keene, W.C., Stone, E.A., 2019. Ambient air quality in the Kathmandu Valley, Nepal during the pre-monsoon: concentrations and sources of particulate matter and trace gases. Atmos. Chem. Phys. 20 (5), 2927–2951.
dc.relationIUFRO – International Union of Forest Research Organizations, 2018. Global Fire Challenges in a Warming World. In: Robinne, F.-N., Burns, J., Kant, P., de Groot, B., Flannigan, M.D., Kleine, M., Wotton, D.M. (Eds.), Occasional Paper No. 32. 2018. IUFRO, Vienna.
dc.relationKota, S.H., Guo, H., Myllyvirta, L., Hu, J., Sahu, S.K., Garaga, R., Ying, Q., Gao, A., Dahiya, S., Wang, Y., Zhang, H., 2018. Year-long simulation of gaseous and particulate air pollutants in India. Atmos. Environ. 180, 244–255.
dc.relationLai, H.-C., Ma, H.-W., Chen, C.-R., Hsiao, M.-C., Pan, B.-H., 2019. Design and application of a hybrid assessment of air quality models for the source apportionment of PM2.5. Atmos. Environ. 212, 116–127.
dc.relationLi, F., Zhang, X., Kondragunta, S., Roy, D.P., 2018. Investigation of the fire radiative energy biomass combustion coefficient: A comparison of polar and geostationary satellite retrievals over the conterminous United States. J. Geophys. Res.–Biogeo 123 (2), 722–739.
dc.relationLi, F., Val Martin, M., Andreae, M.O., Arneth, A., Hantson, S., Kaiser, J.W., Lasslop, G., Yue, C., Bachelet, D., Forrest, M., Kluzek, E., Liu, X., Mangeon, S., Melton, J.R., Ward, D.S., Darmenov, A., Hickler, T., Ichoku, C., Magi, B.I., Sitch, S., van der Werf, G.R., Wiedinmyer, C., Rabin, S.S., 2019. Historical (1700–2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP). Atmos. Chem. Phys. 19, 12545–12567.
dc.relationMalamakal, T., Chen, L.-W.A., Wang, X., Green, M.C., Gronstal, S., Chow, J.C., Watson, J.G., 2013. Prescribed burn smoke impact in the Lake Tahoe Basin: model simulation and field verification. Int. J. Environ. Pollut. 52 (3/4), 225–243.
dc.relationMasiol, M., Squizzato, S., Rich, D.Q., Hopke, P.K., 2019. Long-term trends (2005–2016) of source apportioned PM2.5 across New York State. Atmos. Environ. 201, 110–120
dc.relationNoda, J., Bergström, R., Kong, X., Gustafsson, T.L., Kovacevik, B., Svane, M., Pettersson, J.B.C., 2019. Aerosol from biomass combustion in Northern Europe: Influence of meteorological conditions and air mass history. Atmosphere 10 (12), 789.
dc.relationOliveira, M.L.S., Tutikian, B.F., Milanes, C., Silva, L.F.O., 2020. Atmospheric contaminations and bad conservation effects in Roman mosaics and mortars of Italica. J. Clean. Prod. 248, 119250.
dc.relationPereira, A.A., Pereira, J.M.C., Libonati, R., Oom, D., Setzer, A.W., Morelli, F., Machado-Silva, F., de Carvalho, L.M.T., 2017. Burned area mapping in the Brazilian Savanna using a one-class support vector machine trained by active fires. Remote Sens. 9 (11), 1161.
dc.relationPrato, D.F., Huertas, J.I., 2019. Determination of the area affected by agricultural burning. Atmosphere 10 (6), 312.
dc.relationQuerol, X., Viana, M., Alastuey, A., Amato, F., Moreno, T., Castillo, S., Pey, J., de la Rosa, J., Sánchez de la Campa, A., Artíñano, B., Salvador, P., García dos Santos, S., FernándezPatier, R., Moreno-Grau, S., Negral, L., Minguillón, M.C., Monfort, E., Gil, J.I., Zabalza, J., 2007. Source origin of trace elements in PM from regional background, urban and industrial sites of Spain. Atmos. Environ. 41 (34), 7219–7231.
dc.relationRamírez, O., Sánchez de la Campa, A.M., Amato, F., Moreno, T., Silva, L.F., de la Rosa, J.D., 2019. Physicochemical characterization and sources of the thoracic fraction of road dust in a Latin American megacity. Sci. Total Environ. 652, 434–446.
dc.relationRamírez, 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 Clim. 33, 100655.
dc.relationRojas, J.C., Sánchez, N.E., Schneider, I., Oliveira, M.L.S., Teixeira, E.C., Silva, L.F.O., 2019. Exposure to nanometric pollutants in primary schools: Environmental implications. Urban Clim. 27, 412–419.
dc.relationRönkkö, T.J., Hirvonen, M.R., Happo, M.S., Leskinen, A., Koponen, H., Mikkonen, S., Bauer, S., Ihantola, T., Hakkarainen, H., Miettinen, M., Orasche, J., Gu, C., Wang, Q., Jokiniemi, J., Sippula, O., Komppula, M., Jalava, P.I., 2020. Air quality intervention during the Nanjing youth olympic games altered PM sources, chemical composition, and toxicological responses. Environ. Res. 185, 109360.
dc.relationSchneider, I.L., Teixeira, E.C., Oliveira, L.F.S., Wiegand, F., 2015. Atmospheric particle number concentration and size distribution in a traffic–impacted area. Atmos. Pollution Res. 6 (5), 877–885
dc.relationShe, H., Cheng, P.-H., Yuan, C.-S., Yang, Z.-M., Hung, C.-M., Ie, I.-R., 2020. Chemical characteristics, spatiotemporal distribution, and source apportionment of PM2.5 surrounding industrial complexes in Southern Kaohsiung. Aerosol Air Qual. Res. 20 (3), 557–575
dc.relationSilva, P.S., Bastos, A., Libonati, R., Rodrigues, J.A., DaCamara, C.C., 2019. Impacts of the 1.5 °C global warming target on future burned area in the Brazilian Cerrado. Forest Ecol. Manag. 446, 193–203.
dc.relationSilva, L.F.O., Pinto, D., Lima, B.D., 2020a. Implications of iron nanoparticles in spontaneous coal combustion and the effects on climatic variables. Chemosphere 254, 126814.
dc.relationSilva, L.F.O., Milanes, C., Pinto, D., Ramirez, O., Lima, B.D., 2020b. Multiple hazardous elements in nanoparticulate matter from a Caribbean industrialized atmosphere. Chemosphere 239, 124776.
dc.relationSilva, L.F.O., Pinto, D., Neckel, A., Oliveira, M.L.S., Sampaio, C.H., 2020c. Atmospheric nanocompounds on Lanzarote Island: Vehicular exhaust and igneous geologic formation interactions. Chemosphere 254, 126822.
dc.relationTurap, Y., Rekefu, S., Wang, G., Talifu, D., Gao, B., Aierken, T., Hao, S., Wang, X., Tursun, Y., Maihemuti, M., Nuerla, A., 2019. Chemical characteristics and source apportionment of PM2.5 during winter in the southern part of Urumqi, China. Aerosol Air Qual. Res. 19 (6), 1325–1337
dc.relationVermote, E., Ellicott, E., Dubovik, O., Lapyonok, T., Chin, M., Giglio, L., Roberts, G.J., 2009. An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power. J. Geophys. Res. 114, D18205
dc.relationWang, S.-C., Wang, Y., Estes, M., Lei, R., Talbot, R., Zhu, L., Hou, P., 2018. Transport of central American fire emissions to the U.S. Gulf Coast: climatological pathways and impacts on Ozone and PM2.5. J. Geophys. Res.-Atmos. 123 (15), 8344–8361
dc.relationWooster, M.J., 2002. Small-scale experimental testing of fire radiative energy for quantifying mass combusted in natural vegetation fires. Geophys. Res. Lett. 29 (21), 2027.
dc.relationJ. Bolaño-Truyol, I.L. Schneider, H.C. Cuadro et al
dc.relationWooster, M.J., Roberts, G., Perry, G.L.W., Kaufman, Y.J., 2005. Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release. J. Geophys. Res.-Atmos. 110 D24311
dc.relationWu, Y., Arapi, A., Huang, J., Gross, B., Moshary, F., 2018. Intra-continental wildfire smoke transport and impact on local air quality observed by ground-based and satellite remote sensing in New York City. Atmos. Environ. 187, 266–281.
dc.relationYin, L., Du, P., Zhang, M., Liu, M., Xu, T., Song, Y., 2019. Estimation of emissions from biomass burning in China (2003-2017) based on MODIS fire radiative energy data. Biogeosciences 16 (7), 1629–1640
dc.relationZhang, X., Kondragunta, S., Quayle, B., 2011. Estimation of biomass burned areas using multiple-satellite-observed active fires. IEEE Trans. Geosci. Remote Sensing 49 (11), 4469–4482.
dc.relationZhang, X., Kondragunta, S., Ram, J., Schmidt, C., Huang, H.-C., 2012. Near-real-time global biomass burning emissions product from geostationary satellite constellation. J. Geophys. Res.-Atmos. 117 (D14).
dc.relationZhou, Y., Han, Z., Liu, R., Zhu, B., Li, J., Zhang, R., 2018. A modeling study of the impact of crop residue burning on PM2.5 concentration in Beijing and Tianjin during a severe autumn haze event. Aerosol Air Qual. Res. 18 (7), 1558–1572
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourceGeoscience Frontiers
dc.sourcehttps://www.sciencedirect.com/science/article/pii/S1674987121000165
dc.subjectBiomass burning
dc.subjectParticulate matter
dc.subjectHYSPLIT
dc.subjectDispersion model
dc.subjectRemote sensing
dc.titleEstimation of the impact of biomass burning based on regional transport of PM2.5 in the Colombian Caribbean
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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