2 resultados para Indicadores ambientais
em Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT)
Resumo:
The faunal inventory of the macroinvertebrate community is important to the environmental assessment, since this biota is sensitive to human disturbance. The reservoir of Rio Verde, located on the first plateau of Paraná, is inserted into an agricultural region with several forest fragments Araucaria. The aim of this study was to evaluate the environmental integrity of the reservoir through ecological indexes of macroinvertebrate community benthic and associated with macrophytes. Five sampling points were defined in the study area, which comprise distinct microhabitats in the basin. There were four sampling campaigns, each by weather station: Spring (2014); Summer (2015); Autumn (2015) and Winter (2015). In each sample were measured abiotic various parameters in the field and be collected water samples for nutrient analysis in the laboratory. The macroinvertebrates were collected in triplicate at adapted Macan method using mesh sieve 1 mm and CPUE (catch per unit effort) for 20 minutes. In order to pellet sample was used a dredger model Petersen 2L. Still in the field, by season, samples were collected from macrophytes Myriophyllum aquaticum (Vell) Verdc. and Potamogeton montevidensis A. Benn. in triplicates in the fluvial region of the reservoir, to analyze the associated fractal dimension and macrofauna. For this we used a PVC sampler specific volume 0.025 m3. the following ecological descriptors were calculated in each case: abundance, wealth tax, wealth Margalef, Shannon-Wiener diversity, evenness evenness through the Past software. The index Biological Monitoring Working Party (BMWP) for monitoring sampling points was also calculated. Regarding the statistical analysis, we used the analysis of PERMANOVA to compare points and seasons and canonical correspondence analysis (CCoA) for variables. Regarding M. aquaticum and P. montevidensis it was not verified difference to the average associated macroinvertebrates. However there was a difference for abundance of organisms in the fractal dimension and biomass of specimens. M. aquaticum is more complex and took more macrofauna in relation to P. montevidensis. Regarding the monitoring of the reservoir, it showed up mesotrophic with moderate nutrient concentrations and within the regulatory limits. Benthic macrofauna showed statistical differences in relation to the reservoir region, sample point and temporal variation. The BMWP index showed that the river region has the highest biotic integrity (in all samples above 70 points), and the ecological descriptors of wealth and Margalef diversity of Shannon- Wiener higher. In point 4 (dam downstream) were recorded evidence of possible impacts due to lower wealth and BMWP index which resulted in a questionable quality water. New approaches are needed to focus on the aquatic community in the best understanding of this ecosystem and also with a view to environmental preservation of the Green River Basin.
Resumo:
Energy indicators are tools to support decision-making on energy. The growing debate on sustainable development, contributed to the energy indicators began to incorporate, besides the traditional economic, social and environmental information. Therefore, taking sustainable development into account, it is important to know contributions and limitations of these tools. The overall goal of this study is to analyze the contributions and limitations of the energy indicators as assets to support sustainable development.This study can be classified as descriptive because it relies on bibliographical and documental material. As a result of documental analysis, 55 energy indicators for sustainable development (EISD) were selected. The selection took place by identification of those indicators through the institutions International Atomic Energy Agency (IAEA), Helio International and World Energy Council (WEC), among 19 institutions involved in research on energy identified in the survey. The study stresses that most of the selected indicators focuses on the economic dimension, 19 EISDs (34.54%), followed by 10 EISDs (18.18%) focused on the environmental dimension, 9 EISDs (16.36%) focused on the social issues, 7 EISDs (12.45%) are classified as resilience, 4 EISDs (7.27%) is about governance, 3 EISDs (5.45%) focused on vulnerability and 3 EISDs (5.45%) is about policy. Despite the inclusion of indicators associated with other dimensions than economy, information provided by those indicators emerges as their own limitation. Because, recently, indicators’ information were used to promote sustainable development as well as the opposite. Additionally, the study identified EISDs whose components were not specified. They may enable generation of information far from the real scenario, if components dissociated EISD would be taking into consideration or even the non-consideration of relevant components. Despite limitations, EISDs assisting decision-makers contributes to the pursuit of sustainable development. But they may be improved through information about environmental issues, such as emission of atmospheric pollutants, soil and water, resulting from energy sources, helps identifying which sources are more or less harmful for sustainable development. However, difficulty in collecting data, identifying the components for calculation of each indicator and even interpretation of this, as analyzed, may not only fail to contribute to sustainable development, as can delay taking corrective or preventive decisions.