Bottom-up estimates of atmospheric emissions of CO₂, NO₂, CO, NH₃, and Black Carbon, generated by biomass burning in the north of South America




Bottom-up, burned area, atmospheric emissions, Aboveground biomass validation, greenhouse gases, atmospheric pollutants, uncertainty


Biomass burning is an important source of greenhouse gases (GHG) and air pollutants (AP) in developing countries. In this research, a bottom-up method was implemented for the estimation of emissions, emphasizing the validation process of aerial biomass products (AGB), which it has not been sufficiently approached from the point of view of the quantification of emissions. The most recent results on the validation of burned area (AQ) products and the analysis of uncertainty were also incorporated into the process of estimating the emissions of gases that directly or indirectly promote the greenhouse effect, such as COâ‚‚, NOâ‚‚, CO, NH₃, and Black Carbon (BC). In total, 87.60 Mha were burned in the region between 2001 and 2016, represented in a 57% by pasture lands a 23% by savannas, an 8% by savanna woodlands, an 8% by mixed soils with crops and natural vegetation, a 3% by evergreen broadleaf forests, and a 1 % in the region´s remaining types of land cover. With 35480 reference polygons, a model based on the uncertainty of AQ was generated, which served to find the calibration factor of the FireCCI5.0 in all the studied species. The total emissions (minimum and maximum) and the average of the same in the study period were the following: 1760 Tg COâ‚‚ (765.07-2552.88; average 110 Tg), 68.12 Tg of CO (27.11-98.87; average 4.26 Tg), 3.05 Tg of NOâ‚‚ (1.27-4.40; average 0.19 Tg), 0.76 Tg of NH₃ (0.33-1.12; average 0.05 Tg), and 0.44 Tg of Black Carbon (0.015-0.64; average 0.03 Tg).


Download data is not yet available.

Author Biographies

Germán M. Valencia, Universidad de San Buenaventura

Director de Investigaciones y Posgrados

Jesús A. Anaya, Universidad de Medellín

Facultad de IngenieríasDocente titular

Francisco J. Caro-Lopera, Universidad de Medellín

Docente titular Director del Doctorado Modelamiento y ciencia computacionalDepartamento de Ciencias Básicas


Abril-Salcedo, D. S., Melo-Velandia, L. F., ParraAmado, D. 2020. Nonlinear relationship between the weather phenomenon El niño and Colombian food prices. Australian Journal of Agricultural and Resource Economics, 64(4), 1059-1086.

Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., … Wennberg, P. O. 2011. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmospheric Chemistry and Physics, 11(9), 4039-4072.

Anaya, J. A., Chuvieco, E. 2010. Accuracy assessment of burned area products in the Orinoco basin. American Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies, 1(1), 8-17

Anaya, J. A., Chuvieco, E., Palacios-Orueta, A. 2009. Aboveground biomass assessment in Colombia: A remote sensing approach. Forest Ecology and Management, 257(4), 1237-1246.

Anaya, J. A., Colditz, R. R., Valencia, G. 2015. Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series. Remote Sensing, 7(12), 16274-16292.

Anderson, B. E., Grant, W. B., Gregory, G. L., Browell, E. V., Collins, J. E., Sachse, G. W., … Blake, N. J. 1996. Aerosols from biomass burning over the tropical South Atlantic region: Distributions and impacts. Journal of Geophysical Research: Atmospheres, 101(D19), 24117-24137.

Andreae, M. 1991. Biomass burning: its history, use, and distribution and its impact on environmental quality and global climate. In J. Levine (Ed.), MIT Press (pp. 3-21). Cambridge.

Avitabile, V, Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L., Asner, G. P., … Willcock, S. 2015. An integrated pan-tropical biomass map using multiple reference datasets. Global Change Biology, n/a-n/a.

Avitabile, Valerio, Camia, A. 2018. An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots. Forest Ecology and Management, 409(November 2017), 489-498.

Baccini, a., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., … Houghton, R. a. 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbondensity maps. Nature Clim. Change, 2(3), 182-185.

Bastarrika, A., Alvarado, M., Artano, K., Martinez, M. P., Mesanza, A., Torre, L., … Chuvieco, E. 2014. BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data. Remote Sensing, 6, 12360-12380.

Bauduin, S., Clarisse, L., Theunissen, M., George, M., Hurtmans, D., Clerbaux, C., Coheur, P. F. 2017. IASI's sensitivity to near-surface carbon monoxide (CO): Theoretical analyses and retrievals on test cases. Journal of Quantitative Spectroscopy and Radiative Transfer, 189, 428-440.

BBC. 2019. Amazon fires increase by 84% in one year - space agency - BBC News. BBC. Retrieved from

Boschetti, L., Roy, D. P., Giglio, L., Huang, H., Zubkova, M., Humber, M. L. 2019. Global validation of the collection 6 MODIS burned area product. Remote Sensing of Environment, 235(October), 111490.

Brown, K. 2017. NASA Pinpoints Cause of Earth's Recent Record Carbon Dioxide Spike. National Aeronotics and Space Administration (NASA). Retrieved from nasa-pinpoints-cause-of-earth-s-recent-recordcarbon-dioxide-spike

Buis, A. 2019. The Atmosphere: Getting a Handle on Carbon Dioxide - Climate Change: Vital Signs of the Planet. Retrieved December 6, 2020, from

Chave, J., Davies, S. J., Phillips, O. L., Lewis, S. L., Sist, P., Schepaschenko, D., … Saatchi, S. 2019. Ground Data are Essential for Biomass Remote Sensing Missions. Surveys in Geophysics, 40(4), 863-880.

Chuvieco, E., Mouillot, F., van der Werf, G. R., San Miguel, J., Tanasse, M., Koutsias, N., … Giglio, L. 2019. Historical background and current developments for mapping burned area from satellite Earth observation. Remote Sensing of Environment, 225(November 2018), 45-64.

Chuvieco, E., Opazo, S., Sione, W., Del Valle, H., Anaya, J., Di Bella, C., … Libonati, R. 2008. Global burned-land estimation in Latin America using MODIS composite data. Ecological Applications, 18(1), 64-79.

Clerbaux, C., Hadji-Lazaro, J., Turquety, S., George, M., Boynard, A., Pommier, M., … Van Damme, M. 2015. Tracking pollutants from space: Eight years of IASI satellite observation. Comptes Rendus - Geoscience, 347(3), 134-144.

Crutzen, P. J., Andreae, M. O. 1990. Biomass Burning in the Tropics: Impact on Atmospheric Chemistry and Biogeochemical Cycles. Science, 250(4988), 1669-1678.

Dammers, E., Palm, M., Van Damme, M., Vigouroux, C., Smale, D., Conway, S., … Erisman, J. W. 2016. An evaluation of IASI-NH3 with ground-based Fourier transform infrared spectroscopy measurements. Atmospheric Chemistry and Physics, 16(16), 10351-10368.

Edwards, D. P., Emmons, L. K., Hauglustaine, D. a., Chu, D. a., Gille, J. C., Kaufman, Y. J., … Drummond, J. R. 2004. Observations of carbon monoxide and aerosols from the Terra satellite: Northern Hemisphere variability. Journal of Geophysical Research D: Atmospheres, 109(24), 1-17.

EPA. 2019a. Basic Information of Air Emissions Factors and Quantification.

EPA. 2019b. Basic Information of Air EmissionsFactors and Quantification, 2017-2019. Retrieved from

Evangeliou, N., Balkanski, Y., Eckhardt, S., Cozic, A., Van Damme, M., Coheur, P. F., … Hauglustaine, Di. 2021. 10-Year Satellite-Constrained Fluxes of Ammonia Improve Performance of Chemistry Transport Models. Atmospheric Chemistry and Physics, 21(6), 4431-4451.

Freitas, S. R., Longo, K. M., Alonso, M. F., Pirre, M., Marecal, V., Grell, G., … Sánchez Gácita, M. 2011. PREP-CHEM-SRC - 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models. Geoscientific Model Development, 4(2), 419-433.

Fry, M. M., Naik, V., West, J. J., Schwarzkopf, M. D., Fiore, A. M., Collins, W. J., … Zeng, G. 2012. The influence of ozone precursor emissions from four world regions on tropospheric composition and radiative climate forcing. Journal of Geophysical Research Atmospheres, 117(7), 1-16.

Galloway, J. N., Aber, J. D., Erisman, J. W., Seitzinger, S. P., Howarth, R. W., Cowling, E. B., Cosby, B. J. 2003. The Nitrogen Cascade. BioScience, 53(4), 341.[0341:TNC]2.0.CO;2

Ghasemi, A., Zahediasl, S. 2012. Normality tests for statistical analysis: A guide for non-statisticians. International Journal of Endocrinology and Metabolism, 10(2), 486-489.

Giglio, L., Csiszar, I., Justice, C. O. 2006. Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Journal of Geophysical Research, 111(July 1996), 1-12.

Giglio, L., Randerson, J. T., Van Der Werf, G. R. 2013. Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). Journal of Geophysical Research: Biogeosciences, 118(1), 317-328.

Gray, E. 2019. Satellite Data Record Shows Climate Change's Impact on Fires. Retrieved December 6, 2020, from

Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., Stahel, W. A. 1986. Robust Statistics: The Approach Based on Influence Functions. (J. W. & Sons, Ed.). New York.

Huber, P. J., Ronchetti, E. M. 2009. Robust Statistics. (Wiley, Ed.) (2nd ed.).

IPCC. 2018. IPCC Special Report on the impacts of global warming of 1.5°C. Ipcc - Sr15. Retrieved from

Jaffe, L. S. 1968. Ambient carbon monoxide and its fate in the atmosphere. Journal of the Air Pollution Control Association, 18(8), 534-540.

Janssens-Maenhout, G., Dentener, F., Aardenne, J. Van, Monni, S., Pagliari, V., Orlandini, L., … Keating, T. 2012. EDGAR-HTAP: a harmonized gridded air pollution emission dataset based on national inventories. … Office, Ispra (Italy).

Janssens-Maenhout, G., Petrescu, A. M. R., Muntean, M., Blujdea, V. 2011. Verifying Greenhouse Gas Emissions: Methods to Support International Climate Agreements. Greenhouse Gas Measurement and Management, 1(2), 132-133.

Jones, M. W., Smith, A., Betts, R., Canadell, J. G., Prentice, I. C., Le Quéré, C. 2020. Climate change increases the risk of wildfires. Rapid Response Review, (March 2013), 2013-2015. Retrieved from

Kaiser, J. W., Heil, a., Andreae, M. O., Benedetti, a., Chubarova, N., Jones, L., … Van Der Werf, G. R. 2012. Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power. Biogeosciences, 9(1), 527-554.

Koenker, R. 1994. Confidence Intervals for Regression Quantiles. In P. Mandl & M. Hušková (Eds.), Asymptotic Statistics (pp. 349-359).

Koenker, R. W. 2005. Quantile Regression. (Cambridge University Press, Ed.).

Kumar, S. S., Hult, J., Picotte, J., Peterson, B. 2020. Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires. Remote Sensing, 12(2), 10-14.

Lamarque, J. F., Bond, T. C., Eyring, V., Granier, C., Heil, a., Klimont, Z., … Van Vuuren, D. P. 2010. Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application. Atmospheric Chemistry and Physics, 10(15), 7017-7039.

Langmann, B., Duncan, B., Textor, C., Trentmann, J., van der Werf, G. R. 2009. Vegetation fire emissions and their impact on air pollution and climate. Atmospheric Environment, 43(1), 107-116.

Lees, K. J., Quaife, T., Artz, R. R. E., Khomik, M., Clark, J. M. 2018. Potential for using remote sensing to estimate carbon fluxes across northern peatlands - A review. Science of the Total Environment, 615, 857-874.

Levine, J. S., Cofer III, W. R., Pinto, J. P. 2001. Chapter 14. Biomass Burning. In Atmospheric methane: source, sinks, and role in Global Change (Vol. 113, pp. 299-313). NATO ASI series. Retrieved from

Libonati, R., DaCamara, C., Setzer, A. W., Morelli, F., Melchiori, A. E., Cândido, P. de A., Jesús, S. C. de. 2015. Validating MODIS burned area products over Cerrado region. In XVII Simpósio Brasileiro de Sensoriamento Remoto - SBSR (pp. 6381-6388).

Limpert, E., Stahel, W. A. 2011. Problems with using the normal distribution - and ways to improve quality and efficiency of data analysis. PLoS ONE, 6(7).

Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. a M., Canadell, J. G., McCabe, M. F., Evans, J. P., Wang, G. 2015. Recent reversal in loss of global terrestrial biomass. Nature Climate Change, 5(May), 1-5.

Löndahl, J., Swietlicki, E., Lindgren, E., Loft, S. 2010. Aerosol exposure versus aerosol cooling of climate: What is the optimal emission reduction strategy for human health? Atmospheric Chemistry and Physics, 10(19), 9441-9449.

Longo, K. M., Freitas, S. R., Andreae, M. O., Setzer, a., Prins, E., Artaxo, P. 2010. The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 2: Model sensitivity to the biomass burning inventories. Atmospheric Chemistry and Physics, 10(13), 5785-5795.

Malhi, Y., Rowland, L., Aragão, L. E. O. C., Fisher, R. A. 2018. New insights into the variability of the tropical land carbon cycle from the El Niño of 2015/2016. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1760).

Masek, J.., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., … Lim, T. 2006. A Landsat Surface Reflectance Dataset for North America, 1990-2000. IEEE Geoscience and Remote Sensing Letters, 3(1), 68-72.

Masek, J.., Vermote, E. F., Saleous, N., Wolfe, R., Hall, F. G., Huemmrich, F., … Lim, T. K. 2013. LEDAPS Calibration, Reflectance, Atmospheric Correction Preprocessing Code. Oak Ridge National Laboratory Distributed Active Archive Center. Tennessee, U.S.A.

Mavroidis, I., Chaloulakou, a. 2011. Long-term trends of primary and secondary NO2 production in the Athens area. Variation of the NO2/NOx ratio. Atmospheric Environment, 45(38), 6872-6879.

Mieville, a., Granier, C., Liousse, C., Guillaume, B., Mouillot, F., Lamarque, J.-F., … Pétron, G. 2010. Emissions of gases and particles from biomass burning during the 20th century using satellite data and an historical reconstruction. Atmospheric Environment, 44(11), 1469-1477.

Monks, P. S., Granier, C., Fuzzi, S., Stohl, A., Williams, M. L., Akimoto, H., … von Glasow, R. 2009. Atmospheric composition change - global and regional air quality. Atmospheric Environment, 43(33), 5268-5350.

Moreira, D. S., Freitas, S. R., Bonatti, J. P., Mercado, L. M., Rosário, N. M. É., Longo, K. M., …Gatti, L. V. 2013. Coupling between the JULES land-surface scheme and the CCATT-BRAMS atmospheric chemistry model (JULES-CCATTBRAMS1.0): applications to numerical weather forecasting and the CO2 budget in South America. Geoscientific Model Development, 6(4), 1243-1259.

Mouillot, F., Schultz, M. G., Yue, C., Cadule, P., Tansey, K., Ciais, P., Chuvieco, E. 2014. Ten years of global burned area products from spaceborne remote sensing-A review: Analysis of user needs and recommendations for future developments. International Journal of Applied Earth Observation and Geoinformation, 26(1), 64-79.

Opazo, S., Chuvieco, E. 2013. Análisis geográfico de áreas quemadas en Sudamérica. Geofocus, 13(2), 1-24.

Padilla, M., Olofsson, P., Stehman, S. V, Tansey, K., Chuvieco, E. 2017. Stratification and sample allocation for reference burned area data. Remote Sensing of Environment, 203, 240-255.

Padilla, M., Stehman, S. V., Chuvieco, E. 2014. Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling. Remote Sensing of Environment, 144, 187-196.

Padilla, M., Stehman, S. V., Ramo, R., Corti, D., Hantson, S., Oliva, P., … Chuvieco, E. 2015. Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation. Remote Sensing of Environment, 160(April), 114-121.

Palmer, P. I., Feng, L., Baker, D., Chevallier, F., Bösch, H., Somkuti, P. 2019. Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal. Nature Communications, 10(1), 1-9.

Palomino, S., Anaya, J. A. 2012. Evaluation of the Causes of Error in the Mcd45 Burned-Area Product for the Savannas of Northern South America. DynaColombia, 79(176), 35-44.

Pierre-Louis, K. 2019. The Amazon, Siberia, Indonesia: A World of Fire. The New York Times. Retrieved from

Portnoy, S., Koenker, R. 1997. The Gaussian hare and the Laplacian tortoise: computability of squarederror versus absolute-error estimators, 279-300.

Prosperi, P., Bloise, M., Tubiello, F. N., Conchedda, G., Rossi, S., Boschetti, L., … Bernoux, M. 2020. New estimates of greenhouse gas emissions from biomass burning and peat fires using MODIS Collection 6 burned areas. Climatic Change, 161(3), 415-432.

Rodriguez-Montellano, A., Libonati, R., Melchiori, E. 2015. Sensibilidad en la detección de áreas quemadas en tres ecosistemas vegetales de Bolivia, utilizando tres productos regionales. In XVII Simpósio Brasileiro de Sensoriamento Remoto - SBSR (Vol. 1, pp. 1663-1670).

Rodríguez-Veiga, P., Wheeler, J., Louis, V., Tansey, K., Balzter, H. 2017. Quantifying Forest Biomass Carbon Stocks From Space. Current Forestry Reports, 3, 1-18.

Rousseeuw, P. J., Huber, M. 1997. Recent developments in PROGRESS. In L1-Statistical Procedures and Related Topics. Dodge, IMS Lecture Notes, 31, 201-214.

Rousseeuw, P. J., Leroy, A. M. 2005. Robust Regression and Outlier Detection. (John Wiley & Sons, Ed.). Wiley. Retrieved from

Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T. A., Salas, W., … Morel, A. 2011. Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences of the United States of America, 108(24), 9899-904.

Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J. E. S., Hall, R. J., … Wegmüller, U. 2015. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sensing of Environment, 168, 316-334.

Seiler, W., Crutzen, P. J. 1980. Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning. Climatic Change, 2(3), 207-247.

Shi, Y., Matsunaga, T., Saito, M., Yamaguchi, Y., Chen, X. 2015. Comparison of global inventories of CO2 emissions from biomass burning during 2002-2011 derived from multiple satellite products. Environmental Pollution, 206, 479-487.

Shi, Y., Matsunaga, T., Yamaguchi, Y. 2015. HighResolution Mapping of Biomass Burning Emissions in Three Tropical Regions. Environmental Science and Technology, 49(18), 10806-10814.

Simões Amaral, S., Andrade de Carvalho, J., Martins Costa, M., Pinheiro, C. 2016. Particulate Matter Emission Factors for Biomass Combustion. Atmosphere, 7(11), 141.

Solaun, K., Sopelana, A., Arraibi, E., Pérez, M. 2014. Series CO2: Black Carbon y sus efectos en el clima. Factor CO2, 52. Retrieved from

Stahl, S. 2014. Evolution of the Normal Distribution. In Mathematics magazine (pp. 96-113). Retrieved from

Tie, X., Chandra, S., Ziemke, J. R., Granier, C., Brasseur, G. P. 2007. Satellite measurements of tropospheric column O3 and NO 2 in eastern and southeastern asia: Comparison with a global model (MOZART-2). Journal of Atmospheric Chemistry, 56(2), 105-125.

Urbanski, S. P., Hao, W. M., Nordgren, B. 2011. The wildland fire emission inventory: Western United States emission estimates and an evaluation of uncertainty. Atmospheric Chemistry and Physics, 11(24), 12973-13000.

Valencia, G. M., Anaya, J. A., Caro-Lopera, F. J. 2016. Implementación y evaluación del modelo Landsat Ecosystem Disturbance Adaptive Processing System ( LEDAPS ): estudio de caso en los Andes colombianos. Revista de Teledetección, 46(46), 83-101.

Valencia, G. M., Anaya, J. A., Ramo, R., Velásquez, É. A., Francisco, J. 2020a. About ValidationComparison of Burned Area Products. Remote Sensing, 12(2018), 1-39.

van der Werf, G. R., Randerson, J. T., Giglio, L., Leeuwen, T. T. Van, Chen, Y., Collatz, G. J., … Kasibhatla, P. S. 2017. Global fire emissions estimates during 1997 - 2016. Earth System Science Data, 9, 697-720.

Vasconcelos, S. S. De, Fearnside, P. M., Graça, P. M. L. D. A., Nogueira, E. M., Oliveira, L. C. De, Figueiredo, E. O. 2013. Forest fires in southwestern Brazilian Amazonia: Estimates of area and potential carbon emissions. Forest Ecology and Management, 291, 199-208.

Voiland, A. 2015. Fourteen years of carbon monoxide from MOPITT - Climate Change: Vital Signs of the Planet. Retrieved December 6, 2020, from

von Bobrutzki, K., Braban, C., Famulari, D., Jones, S., Blackall, T., Smith, T. E. L., … Nemitz, E. 2010. Field inter-comparison of eleven atmospheric ammonia measurement techniques, 91-112.

Whitburn, S., Van Damme, M., Kaiser, J. W. W., Van Der Werf, G. R. R., Turquety, S., Hurtmans, D., … Coheur, P.-F. F. 2014. Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories. Atmospheric Environment, 121, 42-54.

Whitburn, Simon, Van Damme, M., Clarisse, L., Hurtmans, D., Clerbaux, C., Coheur, P. F. 2017. IASIderived NH3 enhancement ratios relative to CO for the tropical biomass burning regions. Atmospheric Chemistry and Physics, 17(19), 12239-12252.

Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., Soja, A. J. 2011. The Fire INventory from NCAR (FINN) - a high resolution global model to estimate the emissions from open burning. Geoscientific Model Development Discussions, 3(4), 2439-2476.

Williams, A. P., Abatzoglou, J. T., Gershunov, A., Guzman-Morales, J., Bishop, D. A., Balch, J. K., Lettenmaier, D. P. 2019. Observed Impacts of Anthropogenic Climate Change on Wildfire in California. Earth's Future, 7(8), 892-910.

Yang, J., Gong, P., Fu, R., Zhang, M., Chen, J., Liang, S., … Dickinson, R. 2013. The role of satellite remote sensing in climate change studies. Nature Climate Change, 3(10), 875-883.

YuSheng, S., Matsunaga, T., Yamaguchi, Y. 2015. High-resolution mapping of biomass burning emissions in three tropical regions. Environmental Science & Technology, 49(18), 10806-10814.

Zuluaga, O., Patiño, J. E., Valencia, G. M. 2021. Modelos implementados en el análisis de series de tiempo de temperatura superficial e índices de vegetación: una propuesta taxonómica en el contexto de cambio climático global. Revista de Geografía Norte Grande, 78, 323-344.





Research articles