Reator Eletrolìtico Para Tratamento De Efluentes Têxteis

Este desenvolvimento refere-se a um equipamento destinado à utilização como pré-tratamento, tratamento ou pós-tratamento de efluentes de indústria têxteis contendo corantes reativos e dispersivos, sendo expansível ao tratamento de diversos tipos de efluentes domésticos e/ou industriais. O reator possui uma estrutura compacta, e consiste de um sistema tubular concêntrico de eletrodos de titânio revestido por TiO2/RuO2, fechado nas extremidades por tampas de polipropileno irradiado e com um tubo de quartzo central. O reator utiliza o processo eletrolítico, onde a aplicação de diferença de potencial via fonte externa entre eletrodos desencadeia reações químicas na superfície destes levando à formação de radicais capazes de degradar espécies químicas recalcitrantes presentes em efluentes. Oferece ainda, a possibilidade de tratamento fotoquímico, por meio de colocação de lâmpada ultravioleta dentro do tubo de quartzo. O sistema se mostrou eficiente no tratamento de corantes, pois permitiu uma rápida degradação da solução contendo corante Preto Remazol, verificados por reduções da cor superiores a 88% a partir de 90 minutos de tratamento e reduções no teor de Carbono Orgânico Total. Quando aplicado no efluente da indústria têxtil, foram obtidas reduções da cor da ordem de 99% em 45 minutos de processamento. Houve também, redução superior a 39% no teor de Carbono Orgânico Total em 180 minutos, enquanto que foi obtida redução superior a 74% na Demanda Química de Oxigênio. As reduções da cor, do COT e da DQO podem estabelecer relação com a degradabilidade e recalcitrância do corante e, consequentemente, pode-se esperar um aumento da biodegradabilidade desses corantes após o tratamento com o reator proposto.BR0201465C02F1/46C02F1/46BR20020201465C02F1/46C02F1/4

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

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Treatment of landfill leachate by photo-assisted electrolysis

Orientador: Rodnei BertazzoliTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia MecanicaResumo: Em aterros, quando o lixo depositado entra em decomposição, se forma o chorume, um líquido escuro e de odor desagradável, potencial patogênico e toxicológico que pode conter compostos orgânicos, metais pesados e outros íons e que se não adequadamente tratado pode causar problemas de caráter sanitário e ambiental. Métodos de oxidação química ou biológica habitualmente utilizados apresentam dificuldade para tratar chorume de aterros antigos. Visando a obtenção de um método de tratamento complementar ou alternativo, neste trabalho utilizou-se um sistema fotoeletroquímico em escala piloto de 18 L operando em modo contínuo com reciclo, composto por reator tubular com eletrodos comerciais ADE de Ti/70TiO2-30RuO2 e lâmpada ultravioleta para degradar chorume bruto de um aterro sanitário municipal. Esta configuração possui o diferencial de utilizar um sistema compacto, com eletrodo não-solúvel de longo tempo de vida útil e eliminar a necessidade de separação do semicondutor da solução após o tratamento. Foram comparados os processos fotocatalítico, eletrolítico e eletrolítico assistido por fotocatálise heterogênea com e sem a adição de fotocatalisador TiO2, determinando-se a eficiência do sistema por meio de análises de cor, DBO, DQO, toxicidade aguda, Carbono Orgânico Total, pH, temperatura, amônia e cloreto. O sistema foi otimizado em termos de densidade de corrente de eletrólise, tempo de tratamento e vazão da solução. Foram testados os valores 300, 1000,2000 e 3000 L h-1 nas densidades de corrente de 13,25, 39, 48, 78, 90 e 116 mA cm-2. No tratamento eletrolítico, em 180 min de processamento a 116,0 mA cm-2 e 2000 L h-1 foi possível remover de 86 a 1 00% da cor, 33 a 73% do COT, 31 a 90% da DQO e 31 a 100% da amônia do chorume. O comportamento cinético para remoção da cor, COT e DQO foi de segunda ordem, com constantes aparentes de velocidade de remoção variando entre 1,58.10-4 e 3,79.10-5 ma-1m s-1 2,13.10-8 e 2,92.10-9 m4s-1g-1 e 1,40.10-8 e 2,07.10-9 m4s-1g-l respectivamente. As remoções de amônia e cloreto seguiram comportamento cinético de primeira ordem, sendo que a constante média de velocidade de remoção de amônia variou entre 6,87.10-5 e 3,46.10-6 m s-1. Também, foram observadas reduções da DBO, da toxicidade e remoção de metais. Esta forma de tratamento não apresenta problemas posteriores em relação à geração de lodo ou subprodutos tóxicos, sendo indicada como complementar ao tratamento biológicoAbstract: Sanitary landfills are the major method used today for the disposal and management of municipal solid waste. Decomposition of waste and rainfall generate leachate at the bottom of landfills, causing groundwater contamination. The leachate is a dark grey, foul smelling solution and it can be considered a complex effluent, often containing organic compounds, heavy metals, and many other soluble compounds. Furthermore, leachate presents high values of biological oxygen demand (BOD), chemical oxygen demand (COD) and, because of its toxic potential, it may represent an environmental problem. Biological and chemica1 oxidation commonly used in the treatment have not entirely efficient in degrading old landfill leachate. Moreover, the process is sensitive to variable organic 10008 and different flow rates. In this study, leachate from an old age municipal landfill site was treated by photo-electrochemical oxidation in a pilot scale flow reactor (18 L), using DSA anode and UV radiation. The adopted system is small, compact, long service-life electrodes and separation between of cata1yst from solution is not necessary. By using photocatalytic, electrolytic and photo-assisted electrolytic processes, the effect of current density and flow rate on COD, BOD, total organic carbon, color, ammonia and toxicity removal was investigated. At a current density of 116.0 mA cm-l, flow rate of 2000 L h-1 and 180 min of processing, removal of 86-100% of color, 33-73% of TOC, 31-90% of COD and 31-100% of ammonia were achieved. Removal rates for color, TOC and COD presented a second-order kinetic, with apparent kinetic constants among 1,58.10-4 - 3,79.10-5 ma-lm s-l, 2,13.10-8 - 2,92.10-9 m4s-1g-1 and 1,40.10-8 - 2,07.10-9 m4s-1g-1 respectively. The ammonia and chloride removal followed a first-order kinetic, with apparent kinetic constants ranging from 6,87.10-5 to 3,46.10-6 m s-1. Furthermore, BOD, toxicity and metallic ions were also removed. This process of treatment doesn't show further problems related to sludge production or toxic by-products, been appointed as complementary to traditional biological systems. Besides the high energy consumption, the process proved effectiveness in degrading leachate, despite this effluent' s usual refractoriness to treatmentDoutoradoMateriais e Processos de FabricaçãoDoutor em Engenharia Mecânic