Forest wildfire air pollution plume dispersion
A case study in Southern Argentina
DOI:
https://doi.org/10.59471/raia2026235Keywords:
Forest fire, Source estimation, Air pollution, Atmospheric Dispersion, HYSPLITAbstract
Forest fires pose significant threats to ecosystems, biodiversity, and human health, highlighting the importance of accurate tracking and assessment of their impact. The sources and levels of wildfire contamination were determined using HYSPLIT simulations and NASA MODIS satellite imagery. The forest fire that started in January 2024 in Los Alerces National Park, located in Chubut Province, Argentina, is presented as a case study. By adjusting the simulation with observed data, the biomass was estimated to be 650 Mg/ha, a value consistent with estimates reported in the literature. The distribution and concentration of airborne particulate matter in the affected areas were estimated. Thus, this study assessed contamination levels in nearby areas, revealing significant air quality impacts, with pollution levels exceeding 100 µg/m³. This research adopts a multidisciplinary approach to deepen our understanding of the ecological and human health impacts of forest fires in sensitive ecosystems, with the goal of contributing to more effective conservation strategies and enabling future prevention and mitigation efforts.
Downloads
References
Aguilera, R., Corringham, T., Gershunov, A., & Benmarhnia, T. (2021). Wildfire smoke impacts respiratory health more than fine particles from other sources: Observational evidence from Southern California. Nature Communications, 12(1), 1493. https://doi.org/10.1038/s41467-021-21708-0
Alebić-Juretić, A., Mifka, B., & Kuzmić, J. (2024). Airborne desert dust in the Northern Adriatic area (Croatia): Different sources. Science of the Total Environment, 912, 169320. https://doi.org/10.1016/j.scitotenv.2023.169320
Bertolin, M. L., Urretavizcaya, M. F., & Defossé, G. E. (2015). Fire emissions and carbon uptake in severely burned lenga beech (Nothofagus pumilio) forests of Patagonia, Argentina. Fire Ecology, 11(1), 32–54. https://doi.org/10.4996/fireecology.1101032
Besteiro, A., Kurtz, M., Masci, I., Bonetto, J., Zitto, M., Piotrkowski, R., & Tasat, D. (2024). Dinámica de plumas en incendios forestales: Simulación y análisis. In Grupo Argentino de Bioestadística, Libro de resúmenes de la XXVII Reunión Científica del Grupo Argentino de Bioestadística (p. 50). Grupo Argentino de Bioestadística. ISBN 978-631-90133-1-3
Blundo, C., Malizia, A., Malizia, L. R., & Lichstein, J. W. (2021). Forest biomass stocks and dynamics across the subtropical Andes. Biotropica, 53(1), 170–178. https://doi.org/10.1111/btp.12858
Brode, R. W. (2006). AERMOD Technical Forum. EPA R/S/L Modelers Workshop, San Diego, CA, United States.
Cao, C., Xiong, J., Blonski, S., Liu, Q., Uprety, S., Shao, X., Bai, Y., & Weng, F. (2013). Suomi NPP VIIRS sensor data record verification, validation, and long-term performance monitoring. Journal of Geophysical Research: Atmospheres, 118(20), 11,664–11,678. https://doi.org/10.1002/2013JD020418
Choi, Y., Kanaya, Y., Park, S.-M., Matsuki, A., Sadanaga, Y., Kim, S.-W., Uno, I., Pan, X., Lee, M., Kim, H., & Jung, D. H. (2020). Regional variability in black carbon and carbon monoxide ratio from long-term observations over East Asia: Assessment of representativeness for black carbon (BC) and carbon monoxide (CO) emission inventories. Atmospheric Chemistry and Physics, 20(1), 83–98. https://doi.org/10.5194/acp-20-83-2020
Copernicus Atmosphere Monitoring Service. (2022, December 12). CAMS: Monitoring extreme wildfire emissions in 2022. https://atmosphere.copernicus.eu/cams-monitoring-extreme-wildfire-emissions-2022
Davies, D., Ederer, G., Olsina, O., Wong, M., Cechini, M., & Boller, R. (2019). NASA’s Fire Information for Resource Management System (FIRMS): Near real-time global fire monitoring using data from MODIS and VIIRS. EARSeL Forest Fires SIG Workshop. https://cnrfire2019.eu/wp-content/uploads/2019/10/Davies_Earsel_2019.pdf
Defossé, G. E., Godoy, M. M., & Bertolin, M. L. (2020). Carbon balance and fire emissions in Andean cypress (Austrocedrus chilensis) forests of Patagonia, Argentina. International Journal of Wildland Fire, 29(8), 661–674. https://doi.org/10.1071/WF19183
Dirección General de Estadística y Censos. (2009). Cantidad de habitantes por localidad. https://web.archive.org/web/20090831211301/http://www.estadistica.chubut.gov.ar/index.php?option=com_content&task=view&id=19&Itemid=63
Draxler, R. R., & Hess, G. D. (1997). Description of the HYSPLIT4 modeling system. NOAA Technical Memorandum ERL ARL-224. NOAA Air Resources Laboratory. https://repository.library.noaa.gov/view/noaa/31133
El Chubut. (2024, February 6). El fuego arrasó con casi 7000 hectáreas en Los Alerces y está cerca de Esquel. https://www.elchubut.com.ar/chubut/2024-2-6-8-48-0-el-fuego-arraso-con-casi-7000-hectareas-en-los-alerces-y-esta-cerca-de-esquel
Fearnside, P. M. (1997). Wood density for estimating forest biomass in Brazilian Amazonia. Forest Ecology and Management, 90(1), 59–87. https://doi.org/10.1016/S0378-1127(96)03840-6
Feldpausch, T. R., Lloyd, J., Lewis, S. L., Brienen, R. J. W., Gloor, M., Monteagudo Mendoza, A., Lopez-Gonzalez, G., et al. (2012). Tree height integrated into pantropical forest biomass estimates. Biogeosciences, 9(8), 3381–3403. https://doi.org/10.5194/bg-9-3381-2012
Franzi, L. M., Bratt, J. M., Williams, K. M., & Last, J. A. (2011). Why is particulate matter produced by wildfires toxic to lung macrophages? Toxicology and Applied Pharmacology, 257(2), 182–188. https://doi.org/10.1016/j.taap.2011.09.003
Grant, E., & Runkle, J. D. (2022). Long-term health effects of wildfire exposure: A scoping review. The Journal of Climate Change and Health, 6, 100110. https://doi.org/10.1016/j.joclim.2021.100110
Infobae. (2024, January 28). El incendio forestal en el Parque Nacional Los Alerces consumió más de 500 hectáreas y advierten que está fuera de control. https://www.infobae.com/sociedad/2024/01/28/el-incendio-forestal-en-el-parque-nacional-los-alerces-consumio-mas-de-500-hectareas-y-advierten-que-esta-fuera-de-control/
Johnston, F. H., Henderson, S. B., Chen, Y., Randerson, J. T., Marlier, M., DeFries, R. S., Kinney, P., Bowman, D. M. J. S., & Brauer, M. (2012). Estimated global mortality attributable to smoke from landscape fires. Environmental Health Perspectives, 120(5), 695–701. https://pmc.ncbi.nlm.nih.gov/articles/PMC3346787/
Jones, M. W., Abatzoglou, J. T., Veraverbeke, S., Andela, N., Lasslop, G., Forkel, M., Smith, A. J. P., Burton, C., Betts, R. A., van der Werf, G. R., Sitch, S., Canadell, J. G., Santín, C., Kolden, C., Doerr, S. H., & Le Quéré, C. (2022). Global and regional trends and drivers of fire under climate change. Reviews of Geophysics, 60(3), e2020RG000726. https://doi.org/10.1029/2020RG000726
Justice, C. O., Townshend, J. R. G., Vermote, E. F., Masuoka, E., Wolfe, R. E., Saleous, N., Roy, D. P., & Morisette, J. T. (2002). An overview of MODIS Land data processing and product status. Remote Sensing of Environment, 83(1–2), 3–15. https://doi.org/10.1016/S0034-4257(02)00084-6
Keywood, M., Cope, M., Meyer, C. P. M., Iinuma, Y., & Emmerson, K. (2015). When smoke comes to town: The impact of biomass burning smoke on air quality. Atmospheric Environment, 121, 13–21. https://doi.org/10.1016/j.atmosenv.2015.03.050
Kurtz, M., Lezón, C., Masci, I., Boyer, P., Brites, F., Bonetto, J., Bozal, C., Álvarez, L., & Tasat, D. (2024). Air pollution induces morpho-functional, biochemical and biomechanical vascular dysfunction in undernourished rats. Food and Chemical Toxicology, 188, 114777. https://doi.org/10.1016/j.fct.2024.114777
Lang, N., Jetz, W., Schindler, K., & Wegner, J. D. (2023). A high-resolution canopy height model of the Earth. Nature Ecology & Evolution, 7(11), 1778–1789. https://doi.org/10.1038/s41559-023-02206-6
Li, L., Liu, Y., & Wang, Y. (2017). Monitoring an air pollution episode in Shenzhen by combining MODIS satellite images and the HYSPLIT model. IOP Conference Series: Earth and Environmental Science, 74(1), 012010. https://doi.org/10.1088/1755-1315/74/1/012010
McKenzie, D., Gedalof, Z., Peterson, D. L., & Mote, P. (2004). Climatic change, wildfire, and conservation. Conservation Biology, 18(4), 890–902. https://doi.org/10.1111/j.1523-1739.2004.00492.x
NOAA Air Resources Laboratory. (2024). HYSPLIT tutorials. https://www.ready.noaa.gov/HYSPLIT_Tutorials.php
Orona, N. S., Astort, F., Maglione, G. A., Ferraro, S. A., Martin, M., Morales, C., Mandalunis, P. M., Brites, F., & Tasat, D. R. (2020). Hazardous effects of urban air particulate matter acute exposure on lung and extrapulmonary organs in mice. Ecotoxicology and Environmental Safety, 190, 110120. https://doi.org/10.1016/j.ecoenv.2019.110120
Pérez, A., Caracotche, S., Izquierdo, M., Chehebar, C., & Tagliorette, A. (2016). Inscripción Parque Nacional Los Alerces como Sitio del Patrimonio Mundial de UNESCO. https://sib.gob.ar/archivos/sitio_de_Patrimonio.pdf
Reisen, F., Duran, S. M., Flannigan, M., Elliott, C., & Rideout, K. (2015). Wildfire smoke and public health risk. International Journal of Wildland Fire, 24(8), 1029–1044. https://doi.org/10.1071/WF15034
Rolph, G. D., Ngan, F., & Draxler, R. R. (2014). Modeling the fallout from stabilized nuclear clouds using the HYSPLIT atmospheric dispersion model. Journal of Environmental Radioactivity, 136, 41–55. https://doi.org/10.1016/j.jenvrad.2014.05.006
Singh, S. (2016). Implications of forest fires on air quality: A perspective. Bulletin of Environmental and Scientific Research, 5(3–4), 1–4. https://www.researchgate.net/publication/317357743_Implications_of_forest_fires_on_air_quality_-_a_perspective
Souto-Oliveira, C. E., Marques, M. T. A., Nogueira, T., Lopes, F. J. S., Medeiros, J. A. G., Medeiros, I. M. A., Moreira, G. A., da Silva Dias, P. L., Landulfo, E., & Andrade, M. F. (2023). Impact of extreme wildfires from the Brazilian forests and sugarcane burning on the air quality of the biggest megacity in South America. Science of the Total Environment, 888, 163439. https://doi.org/10.1016/j.scitotenv.2023.163439
Stunder, B. (2004). Global Data Assimilation System (GDAS1) archive information. NOAA Air Resources Laboratory. https://www.ready.noaa.gov/gdas1.php
Su, L., Yuan, Z., Fung, J. C. H., & Lau, A. K. H. (2015). A comparison of HYSPLIT backward trajectories generated from two GDAS datasets. Science of the Total Environment, 506–507, 527–537. https://doi.org/10.1016/j.scitotenv.2014.11.072
Tesone, A. I., Vitar, R. M. L., Tau, J., Maglione, G. A., Llesuy, S., Tasat, D. R., & Berra, A. (2018). Volcanic ash from Puyehue-Cordón Caulle Volcanic Complex and Calbuco promote a differential response of pro-inflammatory and oxidative stress mediators on human conjunctival epithelial cells. Environmental Research, 167, 87–97. https://doi.org/10.1016/j.envres.2018.07.013
Troparevsky, M. I., Muszkats, J. P., Seminara, S. A., Zitto, M. E., & Piotrkowski, R. (2022). Modeling particulate pollutants dispersed in the atmosphere using fractional turbulent diffusion. Physica A: Statistical Mechanics and its Applications, 599, 127478. https://doi.org/10.1016/j.physa.2022.127478
UNESCO World Heritage Centre. (2017). Los Alerces National Park. https://whc.unesco.org/en/list/1526/
U.S. Environmental Protection Agency. (2009). Integrated Science Assessment for Particulate Matter (Final Report No. EPA/600/R-08/139F). U.S. Environmental Protection Agency. https://assessments.epa.gov/isa/document/&deid=216546
U.S. Environmental Protection Agency. (2024). CMAQ: The Community Multiscale Air Quality Modeling System. https://www.epa.gov/cmaq
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
