Oil Spill Modeling in Sea Ice Covered Ocean

The ongoing reduction in extent and thickness of sea ice in the Arctic allows the expansion of shipping activity and oil exploration in the high north, and with that a potential increased risk of oil spill in ice covered areas. This thesis asses the response of two oil-in-ice surface drift models implemented in an open-source Lagrangian framework and forced by four dif- ferent ice-ocean products (RIOPS, TOPAZ4 real-time forecast system, TOPAZ4 reanalysis and SVIM). Both approaches were evaluated over three sets of simulations: (I) a field experiment conducted in the Barents Sea marginal ice zone in 2009; (II) observed trajectories of buoys in the ice pack and in the Barents Sea marginal ice zone; and (III) stochastic simulations (960 runs, from 1998 to 2017) to reproduce a hypothetical oil spill in the Kara Sea. Results from experiments (I) and (II) indicate that the two drift models provide similar response both in the ice pack and the marginal ice zone under the same forcing. It was also found that finer horizontal resolution ice-ocean products (RIOPS and SVIM) did not reproduce better the ob- served drifts. The experiment (III) revealed that the sea ice concentration (%) field dictates the spread, the predominant direction of trajectories and the distance (km) traveled by the cloud of particles (SVIM: -1.41 km/% and TOPAZ4 reanalysis: -1.24 km/%).Master's Thesis in Meteorology and OceanographyGEOF399MAMN-GEO

Assessing ocean ensemble drift predictions by comparison with observed oil slicks

Geophysical models are cornerstone pieces in marine forecasting of floating objects and pollution, such as marine surface oil slicks. Trajectory forecasts of oil spills inherit the uncertainties from the underlying geophysical forcing. In this work we compare the forecast capabilities of an ocean ensemble prediction system (EPS) to those from a higher resolution deterministic model on the representation of oil slick drift. As reference, we use produced water (PW) slicks detected and delineated from 41 C–band Sentinel-1A/B satellite synthetic aperture radar images between April and December, 2021. We found that the EPS provided at least equivalent member-wise results relative to simulations forced with the deterministic model. Ensemble verification through rank histograms and spread-error relationship showed that including the ocean fields is necessary to address model uncertainties. Whether considering the ocean field or not, the modeled slicks were counterclockwise rotated between 20° and 30° relative to the ones observed in the satellite images, and these were deflected about 45° to the right of the observed wind direction

Quantitative assessment of two oil-in-ice surface drift algorithms

The ongoing reduction in extent and thickness of sea ice in the Arctic might result in an increase of oil spill risk due to the expansion of shipping activity and oil exploration shift towards higher latitudes. This work assessed the response of two oil-in-ice surface drift models implemented in an open-source Lagrangian framework. By considering two numerical modeling experiments, our main finding indicates that the drift models provide fairly similar outputs when forced by the same input. It was also found that using higher resolution ice-ocean model does not imply better results. We highlight the role of sea ice in the spread, direction and distance traveled by the oil. The skill metric seems to be sensitive to the drift location, and drift model re-initialization is required to avoid forecast deterioration and ensure the accurate tracking of oil slicks in real operations.publishedVersio

Estimating a mean transport velocity in the marginal ice zone using ice-ocean prediction systems

Understanding the transport of objects and material in the marginal ice zone (MIZ) is critical for human operations in polar regions. This can be the transport of pollutants, such as spilled oil, or the transport of objects, such as drifting ships and search and rescue operations. For emergency response, the use of environmental prediction systems are required which predict ice and ocean parameters and are run operationally by many centres in the world. As these prediction systems predict both ice and ocean velocities, as well as ice concentration, it must be chosen how to combine these data to best predict the mean transport velocities. In this paper we present a case study of four drifting buoys in the MIZ deployed at four distinct ice concentrations. We compare short-term trajectories, i.e. up to 48 h lead times, with standard transport models using ice and ocean velocities from two operational prediction systems. A new transport model for the MIZ is developed with two key features aimed to help mitigate uncertainties in ice–ocean prediction systems: first, including both ice and ocean velocities and linearly weighting them by ice concentration, and second, allowing for a non-zero leeway to be added to the ice velocity component. This new transport model is found to reduce the error by a factor of 2 to 3 for drifters furthest in the MIZ using ice-based transport models in trajectory location after 48 h.publishedVersio

Utilização de imagens sensor oli landsat 8 no mapeamento dos usos e cobertura do solo em Brejinho de Nazaré (TO)

O Tocantins é um dos estados brasileiros com maior área coberta pelo bioma Cerrado. Com a preocupação em preservar o meio ambiente, o sensoriamento remoto é utilizado como tecnologia aliada, facilitando a identificação dos tipos de cobertura, natural ou artificial, presentes na imagem captada pelos sensores. Diante do exposto, objetivou-se com o presente trabalho caracterizar o uso e cobertura do solo em Brejinho de Nazaré (TO), por meio de imagens do sensor OLI Landsat 8. Foram escolhidas cinco classes para a caracterização do uso e cobertura do solo da imagem (corpo hídrico, pastagem, cerrado, formação florestal e áreas agrícolas). Através da análise da imagem de sensor OLI Landsat 8, classificadas de forma supervisionadas, verificou-se que as áreas antropizadas (áreas agrícolas e pastagem) somaram 115.780,8 ha, representando 67% da área total do município de Brejinho de Nazaré, seguidas por cerrado (19,7%), formação florestal (10,6%) e corpo hídrico (2,7%). Pela classificação supervisionada que a classe menos representativa foram as classes corpo hídrico, formações florestais e cerrado. A classe pastagem foi a mais representada em Brejinho de Nazaré, pois o solo do município é classificado como Latossolo, e o relevo é plano a levemente suave, o que proporciona um melhor resultado no cultivo de pastagem e criação de bovinos

Uma revisão integrativa sobre a Colangite Biliar Primária

A colangite biliar primária, um novo nome para a cirrose biliar primária, é uma doença colestática de etiologia autoimune e representa a primeira causa de colestase intra-hepática. Caracteriza-se pela destruição de pequenos dutos biliares ligados à infiltração de linfócitos, com prevalência de 10 a 40 por 100.000 habitantes no mundo. Este estudo teve como objetivo refletir sobre novas informações a respeito da colangite biliar primária. Para isso, foi realizada uma revisão integrativa de literatura, selecionando artigos publicados nas bases de dados Medical Literature Analysis and Retrieval System Online e Literatura Latino-americana e do Caribe em Ciências da Saúde. A partir da análise qualitativa dos dados, obteve-se como conclusão as seguintes descobertas: A PBC é um problema de saúde raro e mal diagnosticado; não há conhecimento ainda sobre as razões da predominância dessa da CBP em mulheres, resposta à terapêutica, distribuição geográfica e mortalidade entre sexos; os casos dessa doença são assintomáticos; a qualidade de vida dos pacientes é comprometida com o agravamento dos casos, onde apresentam inicialmente sinais de prurido (20 a 70% dos casos) e fadiga (entre 50% a 78% dos pacientes); exames de biópsica hepática podem ser tranquilamente substituídos por testes não-invasivos, em análises de rotina de bioquímica hepática; a possiblidade de diagnosticar a PBC pode ser diagnosticada partindo de fatores biológicos exclusivos que indicam a presença de anticorpos anti-mitocondriais e uma elevação da fosfatase alcalina. No entanto é quase possível que o PBC seja soronegativo; a etiologia da CBP não sendo encontra clara, sendo o tratamento difícil; em caso de tratamento, utiliza-se mais ursodesoxicólico, ácido biliar hidrofílico natural que bloqueia a síntese hepática do colesterol, estimulando a síntese de ácidos biliares e restaurando o equilíbrio entre esses

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030