Rising Thermal Extremes and Seasonal Particulate Exposure in Western Mato Grosso, Brazil (2000-2025): An Environmental Exposure Profile and the Case for Health Surveillance
DOI:
https://doi.org/10.12974/2311-8741.2026.14.05Keywords:
Pantanal, Thermal extremes, Heat index, Fine particulate matter, Environmental exposure, Health surveillanceAbstract
The western margin of the Pantanal meets the southern edge of the Amazonian deforestation arc, and each dry season its population breathes what the fires leave behind. Yet the small municipalities along this margin are among the least monitored in Brazil, and the exposure their residents carry has never been quantified. We characterised thermal and particulate exposure across 21 municipalities of western Mato Grosso between 2000 and 2025, counting days rather than months above health-relevant thresholds. Daily air temperature, dew point and precipitation came from ERA5-Land; the heat index was computed daily from maximum temperature and the relative humidity concurrent with it, derived from dew point. Fine particulate matter was characterised independently from two validated products, the ACAG satellite-derived estimate (2000-2022) and the NASA GEOS-CF composition reanalysis (2018-2025), and burned area from MODIS MCD64A1. Trends were tested with a Mann-Kendall test modified for serial correlation and the Theil-Sen estimator, with false discovery rate correction across municipalities. Days with a heat index above 39 °C, the NOAA danger level, rose from 8.4 per year in 2000-2009 to 21.4 in 2016-2025; days with maximum temperature above 36 °C rose from 6.5 to 23.1; days with afternoon relative humidity below 30 per cent, the Brazilian meteorological service attention level, rose from 14.1 to 28.7. Maximum temperature rose by 0.394 °C per decade and was significant in all 21 municipalities after correction. Particulate matter showed no trend in either product, but a pronounced seasonal cycle peaking in September at 47.7 and 47.1 µg m⁻³ respectively, closely tracking burned area. Thermal danger and particulate load therefore diverge in direction and are offset in timing, the smoke maximum falling in September and the thermal maximum in October. This is an exposure profile rather than evidence of harm. Even so, a population whose days of thermal danger have more than doubled in a quarter century, and whose dry-season air remains heavily loaded, warrants systematic surveillance of respiratory and cardiovascular outcomes.
References
Anderson, G. B., Bell, M. L., & Peng, R. D. (2013). Methods to calculate the heat index as an exposure metric in environmental health research. Environmental Health Perspectives, 121(10), 1111-1119. https://doi.org/10.1289/ehp.1206273
Bonnett, N. L., & Birchall, S. J. (2023). The influence of regional strategic policy on municipal climate adaptation planning. Regional Studies, 57(1), 141-152. https://doi.org/10.1080/00343404.2022.2049224
Buzási, A., Simões, S. G., Salvia, M., Eckersley, P., Geneletti, D., Olazabal, M., Wejs, A., Heidrich, O., Church, J. M., Pietrapertosa, F., De Gregorio Hurtado, S., Rivas, S., Fokaides, P., Ioannou, B. I., Feliu, E., Vasilie, S., Rekevičius, M., Matosović, M., Flamos, A., … Reckien, D. (2024). European patterns of local adaptation planning: A regional analysis. Regional Environmental Change, 24, 59. https://doi.org/10.1007/s10113-024-02211-w
Caumo, S., Schramm, A., Oliveira Júnior, E. S., Girotto de Almeida Pina, C. S., Ignotti, E., Gioda, A., Massone, C. G., Pequeno de Araújo, L., Carreira, R., & Hacon, S. (2026). Background exposure to smoke-related pollutants among firefighters during training in the Pantanal biome. Revista Brasileira de Saúde Ocupacional, 51, e12. https://doi.org/10.1590/2317-6369/12024en2026v51e12
Gasparrini, A., Guo, Y., Hashizume, M., Lavigne, E., Zanobetti, A., Schwartz, J., Tobias, A., Tong, S., Rocklöv, J., Forsberg, B., Leone, M., De Sario, M., Bell, M. L., Guo, Y.-L. L., Wu, C.-F., Kan, H., Yi, S.-M., de Sousa Zanotti Stagliorio Coelho, M., Saldiva, P. H. N., … Armstrong, B. (2015). Mortality risk attributable to high and low ambient temperature: A multicountry observational study. The Lancet, 386(9991), 369-375. https://doi.org/10.1016/S0140-6736(14)62114-0
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., & Justice, C. O. (2018). The Collection 6 MODIS burned area mapping algorithm and product. Remote Sensing of Environment, 217, 72-85. https://doi.org/10.1016/j.rse.2018.08.005
Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of Hydrology, 204(1-4), 182-196. https://doi.org/10.1016/S0022-1694(97)00125-X
Lawrence, M. G. (2005). The relationship between relative humidity and the dewpoint temperature in moist air: A simple conversion and applications. Bulletin of the American Meteorological Society, 86(2), 225-234. https://doi.org/10.1175/BAMS-86-2-225
Lazaro, W. L., Oliveira-Júnior, E. S., Silva, C. J., Castrillon, S. K. I., & Muniz, C. C. (2020). Climate change reflected in one of the largest wetlands in the world: An overview of the Northern Pantanal water regime. Acta Limnologica Brasiliensia, 32, e104. https://doi.org/10.1590/s2179-975x7619
MapBiomas Project. (2025). Annual land cover and land use maps of Brazil. https://brasil.mapbiomas.org
Marengo, J. A., Alves, L. M., & Torres, R. R. (2016). Regional climate change scenarios in the Brazilian Pantanal watershed. Climate Research, 68(2-3), 201-213. https://doi.org/10.3354/cr01324
Morin, C. W., Semenza, J. C., Trtanj, J. M., Glass, G. E., Boyer, C., & Ebi, K. L. (2018). Unexplored opportunities: Use of climate- and weather-driven early warning systems to reduce the burden of infectious diseases. Current Environmental Health Reports, 5(4), 430-438. https://doi.org/10.1007/s40572-018-0221-0
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., & Thépaut, J.-N. (2021). ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13(9), 4349-4383. https://doi.org/10.5194/essd-13-4349-2021
Rahman, M. M., McConnell, R., Schlaerth, H., Ko, J., Silva, S., Lurmann, F. W., Palinkas, L., Johnston, J., Hurlburt, M., Yin, H., Ban-Weiss, G., & Garcia, E. (2022). The effects of coexposure to extremes of heat and particulate air pollution on mortality in California: Implications for climate change. American Journal of Respiratory and Critical Care Medicine, 206(9), 1117-1127. https://doi.org/10.1164/rccm.202204-0657OC
Requia, W. J., Amini, H., Mukherjee, R., Gold, D. R., & Schwartz, J. D. (2021). Health impacts of wildfire-related air pollution in Brazil: A nationwide study of more than 2 million hospital admissions between 2008 and 2018. Nature Communications, 12, 6555. https://doi.org/10.1038/s41467-021-26822-7
Rocha, R., & Sant’Anna, A. A. (2022). Winds of fire and smoke: Air pollution and health in the Brazilian Amazon. World Development, 151, 105722. https://doi.org/10.1016/j.worlddev.2021.105722
Sheehan, D., Mullan, K., West, T. A. P., & Semmens, E. O. (2024). Protecting life and lung: Protected areas affect fine particulate matter and respiratory hospitalizations in the Brazilian Amazon biome. Environmental and Resource Economics, 87(1), 45-87. https://doi.org/10.1007/s10640-023-00813-2
Shen, S., Li, C., van Donkelaar, A., Jacobs, N., Wang, C., & Martin, R. V. (2024). Enhancing global estimation of fine particulate matter concentrations by including geophysical a priori information in deep learning. ACS ES&T Air, 1(5), 332-345. https://doi.org/10.1021/acsestair.3c00054
Silveira, G. O., Brum, R. L., Tavella, R. A., Bonifácio, A. S., Fernandes, R. C., & Silva Júnior, F. M. R. (2026). Impact of PM2.5 on cardiorespiratory mortality: A study in the capitals of Brazilian Amazon rainforest. Toxicology, 521, 154401. https://doi.org/10.1016/j.tox.2026.154401
Sobreira, E., Pereira, T. F., Dias, D. F., Viana, C. R. S., de Paula, J. S. B. C., Barbosa, A. P. D., de Souza, A. R., da Rocha Pedra, T., dos Santos, M. C., de Souza Campos, D. V., Romano, A. M., Kosten, S., Muniz, C. C., Ikeda-Castrillon, S. K., & Lázaro, W. L. (2025). Human pressure on the Pantanal: A four-decade analysis of land cover changes, ecological degradation, and future prospects. In T. Pullaiah (Ed.), Wetlands of Tropical and Subtropical South and Central America. Wiley. https://doi.org/10.1002/9781394307166.ch05
Thielen, D., Schuchmann, K.-L., Ramírez-Ramírez, P., Marquez, M., Rojas, W., Quintero, J. I., & Marques, M. I. (2020). Quo vadis Pantanal? Expected precipitation extremes and drought dynamics from changing sea surface temperature. PLOS ONE, 15(1), e0227437. https://doi.org/10.1371/journal.pone.0227437
World Health Organization. (2021). WHO global air quality guidelines: Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. World Health Organization. https://iris.who.int/handle/10665/345329