@article{21311,
  abstract     = {Air pollution is a critical public health issue worldwide, South America faces unique challenges due to rapid urban growth, industrial expansion, and recurrent biomass burning. Existing studies have largely focused on regional or national scales, overlooking detailed spatio-temporal dynamics in cities. This study provides a comprehensive assessment of air pollution spatio-temporal trends from 2013 to 2023 in six major South American cities: Bogotá, Buenos Aires, Montevideo, Quito, Santiago de Chile, and São Paulo. We evaluated four key pollutants, NO2, O3, PM10, and PM2.5, using in situ monitoring networks complemented with reanalysis (boundary layer and pollution dynamics), and fire detections datasets (biomass burning). A key innovation is the use of a Lagrangian Tracker, which identifies persistent hotspots and transport pathways of pollutants, offering new insights into transboundary pollution. Results show that nearly all cities experienced reductions in particulate matter concentrations, while three of the six cities exhibited rising O3 levels, reflecting complex interactions between emissions, meteorology, and atmospheric chemistry. Santiago de Chile recorded the highest levels of NO2 and PM, strongly influenced by topography and biomass burning in JJA. Bogotá and Quito were notably impacted by regional fire emissions, whereas coastal cities such as Buenos Aires and Montevideo benefited from greater pollutant dispersion but still exceeded the World Health Organization guidelines. By integrating ground-based, satellite, and reanalysis data with advanced trajectory modeling, this research provides detailed spatio-temporal evaluations of air pollution in South America and highlights the urgent need for coordinated regional strategies to reduce health and economic burdens.},
  author       = {González, Yuri and Malagón, Nicolás and Benavides, Kevin and Belalcázar, Luis Carlos and Lopez-Barrera, Ellie Anne and Casallas Garcia, Alejandro},
  issn         = {2509-9434},
  journal      = {Earth Systems and Environment},
  publisher    = {Springer Nature},
  title        = {{Spatio-temporal trends of air pollution in six South American cities}},
  doi          = {10.1007/s41748-026-01068-9},
  year         = {2026},
}

@article{21344,
  abstract     = {Tropospheric ozone has the potential to become an increasingly pressing public health issue in Bogotá, Colombia, due to rising concentrations across the city driven by complex interactions among emissions, meteorology, and urban structure. This study presents a comprehensive spatiotemporal analysis of ozone levels from 2013 to 2023 and assesses the associated health burden using mortality data from the same period. Results reveal a consistent upward trend in ozone concentrations, particularly in northern, western, and southern localities, with seasonal peaks linked to biomass burning and photochemical conditions. Mortality analysis, based on the Global Exposure Mortality Model, estimates that 18.3% of all deaths among individuals aged 25 and older are attributable to long-term ozone exposure. The highest burdens are found in densely populated and socioeconomically vulnerable areas such as Kennedy, Suba, and Ciudad Bolívar, with the elderly being the most affected. Building on these findings, we developed a machine learning prediction model for ozone using a convolutional merge with a long-short term memory network architecture trained on air quality and meteorological variables. The model demonstrated strong predictive performance (mean Rho=0.86, RMSE=3.5 μg/m3) across monitoring stations (17 with at least 35000 data points), supporting its potential application in real-time early warning systems across Bogotá. This integrated approach highlights the importance of localized air quality management, combining epidemiological assessment with predictive modeling. The findings underscore the urgency of implementing region-specific mitigation strategies and improving monitoring infrastructure to reduce health risks from ozone exposure in Bogotá’s rapidly growing urban environment.},
  author       = {Bustos, Daniela and Garcia, Diana and Rojas, Nestor Y. and Lopez-Barrera, Ellie A. and Peña-Rincon, Carlos and Casallas Garcia, Alejandro},
  issn         = {2509-9434},
  journal      = {Earth Systems and Environment},
  publisher    = {Springer Nature},
  title        = {{Ozone trends and mortality risk: The growing need for machine learning predictions in Bogotá, Colombia}},
  doi          = {10.1007/s41748-026-01052-3},
  year         = {2026},
}