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G. Mariano

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Review Open access Aug 2026

Air Pollution in the Context of Climate Challenges: Toward an Integrated Research and Policy Agenda in Brazil

Brazil presents a distinctive convergence of continental-scale climatic diversity, extensive urbanization, large-scale biomass burning, rapid land-use change, persistent air-quality monitoring gaps, and deep social inequalities, producing highly heterogeneous and compound environmental health risks. In this context, treating air pollution and climate change as parallel environmental crises obscures their structural interconnections through shared emission sources, mutually reinforcing exposure pathways, and overlapping health and social consequences. In this narrative review, we critically synthesize scientific and institutional lines of evidence and argue that air pollution and climate risks can be more effectively addressed in Brazil through a single strategic agenda for science, public health, and governance. We first discuss why these challenges cannot be managed in isolation, emphasizing the effects of heat, drought, stagnation events, biomass burning, and extreme weather on pollutant formation, dispersion, and health burden. We then examine Brazil as a critical case where recent regulatory advances coexist with structural limitations in monitoring, data integration, and territorial coverage. Based on this diagnosis, we propose an integrated national agenda organized around five mutually reinforcing priorities: monitoring through hybrid networks; predictive science through climate-informed modeling and early warning; public health through the convergence of epidemiology, toxicology, and mechanistic research; equity-oriented research and action through the explicit incorporation of vulnerability, inequality, and climate justice; and policy appraisal through the assessment of disease burden, economic costs, mitigation co-benefits, and trade-offs. We further discuss the governance mechanisms needed to connect these priorities and translate evidence into coordinated action and adaptive public policies. We also argue that the Amazon should be approached not as an isolated ecological exception but as a central component of a broader Brazilian and Global South discussion on environmental health, land-use change, and climate justice. In this scenario, Brazil has the scientific capacity and regulatory momentum to become a reference in the integrated management of air pollution and climate risks, but this will depend on replacing fragmented approaches with a coordinated framework capable of linking exposure, mechanism, burden, inequality, and action.

R. Tavella, F. R. de Moura, A. da Silva Bonifácio et al. · 0 citations
Open access Aug 2026

Age-specific climate sensitivity of respiratory hospitalizations in a tropical coastal city: 20-year Random Forest forecasts

Respiratory diseases remain a major public health challenge in tropical coastal cities, where persistent heat-humidity interactions and climate variability shape population vulnerability. This study quantified associations between atmospheric conditions and respiratory hospitalizations in Maceió, Brazil, using a 20-years time series (2000–2019). Weekly hospitalization rates stratified by age (children 0–4 years, adults 5–59 years, elderly ≥ 60 years), were modeled against meteorological variables—including temperature, relative humidity, precipitation, atmospheric pressure, and solar radiation—considering lag structure of 0, 1, and 2 weeks. Random Forest regression models were applied to capture nonlinear relationships and forecast hospitalization rates. Minimum temperature was the dominant predictor, exhibiting strong inverse associations across all age groups (ρ = − 0.65, p < 0.001), with effects persisting up to two weeks. Age-specific patterns were observed: children showed immediate sensitivity to thermal and precipitation variables, whereas elderly populations exhibited delayed responses to barometric pressure and evaporation. Model performance was high for children and adults (R2 = 0.83–0.90) and moderate for the elderly, with Symmetric Mean Absolute Percentage Error ranging from 13 to 25% across groups. Long-term trends revealed declining hospitalization rates among children and adults, contrasted by stabilization and subsequent increases in the elderly after 2010, consistent with demographic aging and increased climate sensitivity. These findings demonstrate the value of machine learning approaches for modeling complex climate-health relationships and provide a transferable framework for climate-informed respiratory risk assessment and early warning systems in tropical coastal environments.

Marcos Paulo Santos Pereira, R. L. Costa, Fabrício Daniel dos Santos Silva et al. · 0 citations

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