Artigos Acadêmicos e Noticiosos
URI permanente desta comunidadehttps://repositorio.insper.edu.br/handle/11224/3226
Navegar
3 resultados
Resultados da Pesquisa
Artigo Científico Wildfire-sourced fine particulate matter and preterm birth risks in Brazil: A nationwide population-based cohort study(2024) Zhang, Yiwen; Huang, Wenzhong; Xu, Rongbin; Ye, Tingting; Chen, Gongbo; Yue, Xu; Coêl , Micheline de Sousa Zanotti Stagliorio; Saldiva, Paulo Hilario Nascimento; Song, Jiangning; Guo, Yuming; Li, ShanshanWildfire-specific particulate matter with diameters ≤ 2.5 µm (PM2.5) is the key component of wildfire smoke, with potentially higher toxicity than PM2.5 from other sources. In this nationwide population-based cohort study, we included 22,163,195 births from Brazil during 2010–2019. Daily wildfire-specific PM2.5 was estimated through the chemical transport model. Time-varying Cox proportional hazards models were used to characterize the exposure-time-response (E-T-R) relationship between weekly wildfire-specific PM2.5 exposure and preterm birth (PTB) risks, followed by subgroup analyses. A 10 µg/m3 increment in wildfire-specific PM2.5 was associated with a hazard ratio of 1.047 (95 % confidence interval [CI]: 1.032–1.063) for PTB. Stronger associations between wildfire-specific PM2.5 and PTB were observed during earlier pregnancy, among female infants, and pregnant women < 18 years old, in ethnic minorities, with a length of education ≥ 11 years, from low-income or high temperature municipalities, and residing in North/Northeast regions. An estimated 1.47 % (95 % CI: 1.01 %–1.94 %) of PTBs were attributable to wildfire-specific PM2.5 in Brazil, increasing from 2010 to 2019. The PTBs attributable to wildfire-specific PM2.5 surpassed those attributed to non-wildfire PM2.5 (0.31 %, 95% CI: 0.09 %–0.57 %). Wildfire emerged as a critical source contributing to the PM2.5-linked PTBs. Prioritized fire management and emission control strategies are warranted for PTB prevention.Artigo Científico Modeling sea-level processes on the U.S. Atlantic Coast(2020) Berrett, Candace; Christensen, William F.; Sain, Stephan R.; Sandholtz, Nathan; Coats, David W.; Tebaldi, Claudia; HEDIBERT FREITAS LOPESOne of the major concerns engendered by a warming climate are changing sea levels and their lasting effects on coastal populations, infrastructures, and natural habitats. Sea levels are now monitored by satellites, but long-term records are only available at discrete locations along the coasts. Sea levels and sea-level processes must be better understood at the local level to best inform real-world adaptation decisions. We propose a statistical model that facilitates the characterization of known sea-level processes, which jointly govern the observed sea level along the United States Atlantic Coast. Our model not only incorporates long-term sea level rise and seasonal cycles but also accurately accounts for residual spatiotemporal processes. By combining a spatially varying coefficient modeling approach with spatiotemporal factor analysis methods in a Bayesian framework, the method represents the contribution of each of these processes and accounts for corresponding dependencies and uncertainties in a coherent way. Additionally, the model provides a consistent way to estimate these processes and sea level values at unmonitored locations along the coast. We show the outcome of the proposed model using thirty years of sea level data from 38 stations along the Atlantic (east) Coast of the United States. Among other results, our method estimates the rate of sea level rise to range from roughly 1 mm/year in the northern and southern regions of the Atlantic coast to 5.4 mm/year in the middle region.Artigo CientíficoGEOLOGIA Comparison of weather station and climate reanalysis data for modelling temperature‑related mortality(2022) Mistry, Malcolm N.; Schneider, Rochelle; Masselot, Pierre; Royé, Dominic; Armstrong, Ben; Kyselý, Jan; Orru, Hans; Sera, Francesco; ShiluTong1; Lavigne, Éric; Urban, Aleš; Madureira, Joana; García‑León, David; Ibarreta, Dolores; Ciscar, Juan‑Carlos; Feyen, Luc; Schrijver, Evan de; Coelho, Micheline de Sousa Zanotti Stagliorio; Pascal, Mathilde; Tobias, Aurelio; Multi-Country Multi-City (MCC) Collaborative Research Network; Guo, Yuming; Vicedo‑Cabrera, Ana M.; Gasparrini, AntonioEpidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk.