Análise de sílico-fitólitos de eudicotiledôneas em área de mineração e seu potencial na fitorremediação de solos contendo metais pesados

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Heloiza Márcia Fernandes Horn
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/NCAP-AETF9M
Resumo: Anthropogenic activities such as industry and agriculture use in large-scale metals activities classified as heavy metals. In nature, these metals occur normally in small quantities and in a distributed form and therefore they are called trace elements.By being concentrated on processes in anthropogenic activities, the quantities released into the environment may be significant. These metals are not biodegradable and can accumulate in the environment. Even at low concentrations, they are able to cause metabolic disorders and chronic diseases in living beings. When these elements enter the tropic chain, their concentrations may be magnified as they pass from lower to upper tropic levels (biomagnification). Metals such as Pb, Cd and Hg are classified as non-essential and others, such as Fe, Zn, Mn, Cu, B, Mo, Ni, Co, Cr, Se and Sn are indispensable to animals and/or plants. Phytoremediation techniques are well known and often employed, but studies using Si-Phytoliths are limited to a few plants of the Poaceae family. The present work was developed in the Cerrado in an area located in the North of the Minas Gerais State, in the surroundings of the gold mine of Carpathian Gold Company, in the municipality of Riacho dos Machados. In this region occurred during the Precambrian intense hydrothermalism impregnating the rocks with high concentrations of heavy metals distributed in disseminated form or concentrated in specific zones, exceeding locally the values established by Brazilian current environmental legislation. The aim of this work was to select plants that have the potential to form Si-Phytoliths and the capacity to absorb heavy metals and contain them in these bio minerals. They were identified five species of Eudicots Class typical of the Cerrado biome, quote: Rollinialeptopetala, Piptadeniagonoacantha, Sidasp, Senna obtusifolia and Solanum capsicoides. Two of these collected species were excluded: Senna obtusifolia and Solanum capsicoides, due to leaf mass loss in the dry period. The species selected that were investigated: Piptadeniagonoacantha, Rollinialeptopetala and Sida sp. 18 soil and 45 plants samples were collected for later extraction of Si-Phytoliths and chemical analysis of selected metals in them. Soil samples collected around the location of plants sampled (number 1-9) at a depth between 3-10 cm were analyzed for total and available metals, and from them were also extracted Si-Phytoliths. The results revealed that the studied species have concentrated the selected metals in the Si-Phytoliths. The concentrations varied for the different organs of the plant (root, stem and leaves). The organs of the three studies species concentrated the elements in different quantities. The highest concentration in the soil coincided with the highest concentrations in Si-Phytoliths (from plants or soil). The plants investigated therefore can be used for the decontamination of metals in soils. The best effect was obtained with the species Rollinialeptopetala and Piptadeniagonoacantha with higher levels. The largest concentrations of metals occurred in Si-Phytoliths of sheets then stems and roots. The Si-Phytoliths extracted from the soil (with small amounts of other compounds like oxides, clays >1-3%) show average concentrations comparable to the average values of studied plants. Some abnormal changes of metals concentrations in Si-Phytoliths, not correlated to the investigated parameters, can be assigned to the extreme weather conditions in the year of study.