Detalhes bibliográficos
Ano de defesa: |
2010 |
Autor(a) principal: |
Silva, Fernando José Araújo da |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Tese
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Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Não Informado pela instituição
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Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: |
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Link de acesso: |
http://www.repositorio.ufc.br/handle/riufc/16844
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Resumo: |
In the present study fuzzy arithmetic via triangular fuzzy numbers (TFNs) was applied to compute Fuzzy Agreement Index (FAI) and Fuzzy Risk (FR) for the evaluation of operational aspects, performance and effluent quality in 14 full-scale waste stabilization pond plants (6 primary facultative ponds – PFPs and 8 pond series- PSs) treating domestic sewage. Findings showed that fuzzy logic is an attractive approach for the evaluation of the performance of wastewater treatment plants and their environmental compatibilities. The study also provided a better understanding of operational aspects of waste stabilization ponds. Except for two pond systems (PFP4 and PS8) the FAI in PFPs and PSs showed that they operated on average 81.3 and 86.3% of the time below the value stipulated in their original designs. Results indicated average potential increments of 74.7 and 84.5% in influent flow rates to PFPs and PSs, respectively. With respect to organic load () FAI numbers indicated possible increases of 91.8 and 71.9% in PSs and PFPs respectively. In the case of the regulatory standards the FAI applied to effluent quality had best results for DO (PSs = 0.945 and PFPs = 0.867). In general pond series had higher numbers for FAI than PFPs. The fuzzy risk regarded to overloading (organic and hydraulic) was higher in pond series. Comparatively, systems PFP4 and PS8 showed higher fuzzy risk of overloading because these plants operated close to the design numbers. The FR on performance analysis showed that all ponds plants had actual performance slightly below that expected and reported by the literature. The lowest FR values were observed in pond series. On the performance analysis the highest fuzzy risk numbers were for TSS (0.929 in PFPs and 0.903 in PSs), followed by unfiltered COD (0.846 in PFPs and 0.677 in PSs). As expected, fuzzy risk regarded to the violation of environmental standards was higher in PFPs. In pond series by increasing number of cells FR was lower. Positive linear correlations (at a significance level of 95%) showed that lower content of BOD and COD (unfiltered samples), and TSS implied in lower FR with respect to termotolerant coliform concentrations (TTFC). Correlations between FR of pH and TTFC were negative. A Fuzzy Performance Index (FPI) was proposed to compare effluent quality with respect to the environmental standard regulation. The model considered a scale (1-18) based on the following parameters: BODf, CODf, TSS, TAN, DO and TTFC. The results showed the following order: FPI PFP3 (2.09) < FPI PFP2 (2.15) < FPI PFP4 (2.30) < FPI PFP5 (3.49) < FPI PFP1 (3.62) < FPI PFP6 (4.96) < FPI PS5 (9.59) < FPI PS8 (9.67) < FPI PS4 (9.72) < FPI PS3 (10.01) < FPI PS1 (10.38) < FPI PS2 (13. 57) < FPI PS6 (15.49) < FPI PS7 (15.69). The analysis of FR for helminth eggs showed that for a marginal fuzzy risk of 10% pond systems would require a HRT of 28.8 days for oH ≤ 1.0 egg/L, and 38.0 days for oH ≤ 0.1 egg/L. In two series (LS5 and LS8) the FAI and FR with respect to effluent quality from each pond component provided distinctions imposed by the configuration and operational status in each of these plants. Along pond cells in these series BOD and TAN surface removal rates (r) were represent by TFNs. These fuzzy numbers showed negative surface removal rates. They offered an anomalous interpretation for pollutant generation via physical or biotic means. The probable and reasonable cause was the asynchrony between affluent and effluent concentrations, associated with fluctuations in flow rates. Climatic factors and hydraulic behavior of ponds might also influence this. |