Estimation of the impact of biomass burning based on regional transport of PM2.5 in the Colombian Caribbean
Tài liệu tham khảo
Amegah, 2018, Proliferation of low-cost sensors. What prospects for air pollution epidemiologic research in Sub-Saharan Africa?, Environ. Pollut., 241, 1132, 10.1016/j.envpol.2018.06.044
Barranquilla, 2016
DANE – Departamento Administrativo Nacional de Estadística, 2018
Guo, 2018, Improving PM2.5 forecasting and emission estimation based on the Bayesian Optimization Method and the coupled FLEXPART-WRF model, Atmosphere, 9, 428, 10.3390/atmos9110428
Hoyos, 2017, The environmental envelope of fires in the Colombian Caribbean, Appl. Geogr., 84, 42, 10.1016/j.apgeog.2017.05.001
Huang, 2014, Characterization of PM2.5 major components and source investigation in suburban Hong Kong: a one year monitoring study, Aerosol Air Qual. Res., 14, 237, 10.4209/aaqr.2013.01.0020
Islam, 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, 2927, 10.5194/acp-20-2927-2020
IUFRO – International Union of Forest Research Organizations, 2018, Global Fire Challenges in a Warming World, 2018
Kota, 2018, Year-long simulation of gaseous and particulate air pollutants in India, Atmos. Environ., 180, 244, 10.1016/j.atmosenv.2018.03.003
Lai, 2019, Design and application of a hybrid assessment of air quality models for the source apportionment of PM2.5, Atmos. Environ., 212, 116, 10.1016/j.atmosenv.2019.05.038
Li, 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, 722, 10.1002/2017JG004279
Li, 2019, Historical (1700–2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP), Atmos. Chem. Phys., 19, 12545, 10.5194/acp-19-12545-2019
Malamakal, 2013, Prescribed burn smoke impact in the Lake Tahoe Basin: model simulation and field verification, Int. J. Environ. Pollut., 52, 225, 10.1504/IJEP.2013.058457
Masiol, 2019, Long-term trends (2005–2016) of source apportioned PM2.5 across New York State, Atmos. Environ., 201, 110, 10.1016/j.atmosenv.2018.12.038
Noda, 2019, Aerosol from biomass combustion in Northern Europe: Influence of meteorological conditions and air mass history, Atmosphere, 10, 789, 10.3390/atmos10120789
Oliveira, 2020, Atmospheric contaminations and bad conservation effects in Roman mosaics and mortars of Italica, J. Clean. Prod., 248, 119250, 10.1016/j.jclepro.2019.119250
Pereira, 2017, Burned area mapping in the Brazilian Savanna using a one-class support vector machine trained by active fires, Remote Sens., 9, 1161, 10.3390/rs9111161
Prato, 2019, Determination of the area affected by agricultural burning, Atmosphere, 10, 312, 10.3390/atmos10060312
Querol, 2007, Source origin of trace elements in PM from regional background, urban and industrial sites of Spain, Atmos. Environ., 41, 7219, 10.1016/j.atmosenv.2007.05.022
Ramírez, 2019, Physicochemical characterization and sources of the thoracic fraction of road dust in a Latin American megacity, Sci. Total Environ., 652, 434, 10.1016/j.scitotenv.2018.10.214
Ramírez, 2020, Hazardous thoracic and ultrafine particles from road dust in a Caribbean industrial city, Urban Clim., 33, 100655, 10.1016/j.uclim.2020.100655
Rojas, 2019, Exposure to nanometric pollutants in primary schools: Environmental implications, Urban Clim., 27, 412, 10.1016/j.uclim.2018.12.011
Rönkkö, 2020, Air quality intervention during the Nanjing youth olympic games altered PM sources, chemical composition, and toxicological responses, Environ. Res., 185, 109360, 10.1016/j.envres.2020.109360
Schneider, 2015, Atmospheric particle number concentration and size distribution in a traffic–impacted area, Atmos. Pollution Res., 6, 877, 10.5094/APR.2015.097
She, 2020, Chemical characteristics, spatiotemporal distribution, and source apportionment of PM2.5 surrounding industrial complexes in Southern Kaohsiung, Aerosol Air Qual. Res., 20, 557, 10.4209/aaqr.2020.01.0007
Silva, 2019, Impacts of the 1.5 °C global warming target on future burned area in the Brazilian Cerrado, Forest Ecol. Manag., 446, 193, 10.1016/j.foreco.2019.05.047
Silva, 2020, Implications of iron nanoparticles in spontaneous coal combustion and the effects on climatic variables, Chemosphere, 254, 126814, 10.1016/j.chemosphere.2020.126814
Silva, 2020, Multiple hazardous elements in nanoparticulate matter from a Caribbean industrialized atmosphere, Chemosphere, 239, 124776, 10.1016/j.chemosphere.2019.124776
Silva, 2020, Atmospheric nanocompounds on Lanzarote Island: Vehicular exhaust and igneous geologic formation interactions, Chemosphere, 254, 126822, 10.1016/j.chemosphere.2020.126822
Turap, 2019, Chemical characteristics and source apportionment of PM2.5 during winter in the southern part of Urumqi, China, Aerosol Air Qual. Res., 19, 1325, 10.4209/aaqr.2018.12.0454
Vermote, 2009, An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power, J. Geophys. Res., 114, 10.1029/2008JD011188
Wang, 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, 8344, 10.1029/2018JD028684
Wooster, 2002, Small-scale experimental testing of fire radiative energy for quantifying mass combusted in natural vegetation fires, Geophys. Res. Lett., 29, 2027, 10.1029/2002GL015487
Wooster, 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, 10.1029/2005JD006318
Wu, 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, 10.1016/j.atmosenv.2018.06.006
Yin, 2019, Estimation of emissions from biomass burning in China (2003-2017) based on MODIS fire radiative energy data, Biogeosciences, 16, 1629, 10.5194/bg-16-1629-2019
Zhang, 2011, Estimation of biomass burned areas using multiple-satellite-observed active fires, IEEE Trans. Geosci. Remote Sensing, 49, 4469, 10.1109/TGRS.2011.2149535
Zhang, 2012, Near-real-time global biomass burning emissions product from geostationary satellite constellation, J. Geophys. Res.-Atmos., 117, 10.1029/2012JD017459
Zhou, 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, 1558, 10.4209/aaqr.2017.09.0334