Assessment of water quality based on statistical analysis of physical-chemical, biomonitoring and land use data: Manso River supply reservoir.

Preserving the quality of surface water has become increasingly difficult due to the intensification of human activities in watersheds. This study assessed the water quality of the Manso River reservoir, which supplies water to Brazil's third largest metropolitan region. The integration of >10,000 secondary data, comprising physico-chemical parameters, metals and microbiological indicators, together with biomonitoring and land use and occupation data, were analyzed by using statistical tools, the Water Quality Index (WQI) and the Trophic State Index (TSI). The results showed higher concentrations for solids and metals (Fe and Mn) characteristic of local geochemistry and also related to the mining activity in the region. Parameters associated with organic pollution, such as total phosphorus and Escherichia coli, were also elevated, probably due to contamination by untreated or insufficiently treated domestic sewage. The water at the tributary watercourses presented worse quality, predominantly medium WQI, compared with the stations inside the reservoir (predominantly good WQI). The TSI indicated a predominance of ultra-oligotrophic conditions for stations located in the lotic environment and mesotrophic conditions for those located in the lentic environment. In general, the same pattern was observed for the occurrence of the phytoplankton and zooplankton classes, indicating the relationship between the degree of trophy and the composition of these groups. In quantitative terms, for phytoplankton, the Euchlorophyceae and Cyanophyceae classes stood out, mainly in the rainy period (summer), whereas for zooplankton, the Crustacea and Monogonta classes were dominant. Regarding land use and occupation in the reservoir sub-basin, the positive impact of the surrounding forest cover was observed. It was also identified the effect of seasonality on the quality of aquatic environments. The integrated evaluation of the results proved to be efficient in assessing the environmental conditions of the reservoir and the tributaries, providing information for better management of these water resources.

Artificial neural networks for performance prediction of full-scale wastewater treatment plants: a systematic review.

Wastewater treatment plants (WWTPs) are complex systems that must maintain high levels of performance to achieve adequate effluent quality to protect the environment and public health. Artificial intelligence and machine learning methods have gained attention in recent years for modeling complex problems, such as wastewater treatment. Although artificial neural networks (ANNs) have been identified as the most common of these methods, no study has investigated the development and configuration of these models. We conducted a systematic literature review on the use of ANNs to predict the effluent quality and removal efficiencies of full-scale WWTPs. Three databases were searched, and 44 records of the 667 identified were selected based on the eligibility criteria. The data extracted from the papers showed that the majority of studies used the feedforward neural network model with a backpropagation training algorithm to predict the effluent quality of plants, particularly in terms of organic matter indicators. The findings of this research may help in the search for an optimum design modeling process for future studies of similar prediction problems.

Municipal wastewater discharge standards for ammonia nitrogen in Brazil: technical elements to guide decisions.

In Brazil, domestic effluents represent the primary source of pressure on water resources. Water pollution can be controlled by defining, applying, and enforcing the effluent standards for wastewater discharge. Discussions are ongoing in Minas Gerais State regarding the possibility of setting a discharge standard for ammonia nitrogen in municipal wastewater, which is currently not required. However, providing technical support for decision-making is challenging because of the difficulties in accessing monitoring data from sewage treatment plants. This study aimed to analyze the monitoring data from 49 sewage treatment plants operating in Minas Gerais to offer guidance for decision making. High concentrations of ammonia nitrogen in the effluents of the treatment plants were found, reinforcing the need for better control and the adoption of more advanced technologies. Furthermore, it was observed an increase in concentrations downstream of the discharges in the receiving water bodies. Adopting a progressive and adaptable discharge standard can be a solution for better control of treatment systems.

Spatial variability of surface water quality in a large Brazilian semiarid reservoir and its main tributaries.

Brazil has one of the greatest hydroelectric potential in the world with high number of reservoirs for the electricity generation. However, little is known about the influence of these environments on the water quality. The water quality monitoring data from 14 stations distributed throughout the Irapé HPP reservoir (lentic environment), and its main tributaries (lotic environment), between the years 2008 and 2018, were evaluated and compared to assess the spatial variability of water quality. The analyzed parameters included total alkalinity, thermotolerant coliforms, electric conductivity, biochemical oxygen demand, dissolved iron, total phosphorus, nitrate, total ammoniacal nitrogen, dissolved oxygen, pH, total dissolved solids, sulfate, water temperature, and turbidity. Cluster analysis (CA), Kruskal-Wallis (KW) tests, Spearman rank-order correlation, and principal component analysis (PCA) were applied to identify and compare the relationship between the main parameters in the lotic and lentic environments. The CA resulted in four clusters according to proximity and the environment type (lotic or lentic). In general, the water quality showed better conditions in the reservoir and in the lotic stations on the immediate surround. The results may be associated with the greater sedimentation in the lentic environment. The analyses indicated that agricultural activities and the geochemical characteristics of the region are the main responsible for changes in the water quality.

Applicability of statistical analysis for performance and reliability evaluation of large-scale water treatment plants with direct filtration systems.

Water treatment plants (WTPs) are extremely important in basic sanitation services because of their association with human health by producing safe drinking water. Thus, their proper operation is of utmost relevance and has led to the development of distinct performance evaluation methodologies. Direct filtration is a leading technology applied in WTPs. However, although it costs less than conventional treatment, it might also be less flexible and robust. To evaluate performance with data from real-scale WTPs with direct filtration systems, the use of a statistical analysis methodology for turbidity, apparent color, and pH data from raw and effluent water is proposed. Reliability analysis, a probabilistic-based methodology, was applied for turbidity alongside evaluating the compliance of the treated water with different potability standards. The parameters pH (between 6.0 and 8.0) and apparent color (< 15 HU) showed almost complete compliance (> 99%). Reliability analysis could not be applied for apparent color and pH, while apparent color did not adhere to the lognormal distribution frequency. The turbidity results show high variability in the coefficients of variation and reliability among various plants and a general difficulty in complying with stricter standards, such as the 0.1 and 0.3 NTU defined by the United States Environmental Protection Agency. All WTP studies show a 95% compliance with the World Health Organization standard of 5.0 NTU. A higher value for the coefficient of reliability and a lower value for the variation coefficient could indicate a more stable process, regardless of the treated water quality, highlighting the relevance of applying combined methods for performance evaluation, such as compliance with established standards.

Impacts of anthropogenic activities and calculation of the relative risk of violating surface water quality standards established by environmental legislation: a case study from the Piracicaba and Paraopeba river basins, Brazil.

The nonparametric test of Kruskal-Wallis and relative risk were used to evaluate surface water quality allowed to an identification of the most degraded water bodies in Piracicaba River and Paraopeba River basins, two important hydrographic basins in Brazil. Total manganese, dissolved iron, and fecal contamination indicator were considered the most relevant parameters for the characterization of water quality in the basins. The Peixe River, in Nova Era, and Pedras Creek, in Betim, were considered the most impacted water bodies in the Piracicaba River and Paraopeba River basins, respectively. The analysis of violations and the relative risk confirmed that both basins are subject to impacts resulting from economic activities. On comparing the relative risks, the Paraopeba River basin showed a higher risk of violation for 5-day biological oxygen demand (BOD5), total manganese, total phosphorus, total suspended solids, and turbidity, while the Piracicaba River basin showed a higher risk of violation for fecal contamination indicator. The release of domestic sewage and industrial effluents, mining activities, and diffuse pollution from agriculture and pasture areas were responsible for the surface water quality deterioration in these basins. The results show the need for investment in basic sanitation, improved treatment efficiency for industrial effluents, adequate soil management, riparian vegetation preservation, and environmental education actions.

Adequacy analysis of drinking water treatment technologies in regard to the parameter turbidity, considering the quality of natural waters treated by large-scale WTPs in Brazil.

This paper seeks to present a performance evaluation of large-scale water treatment plants and verify the adjustment of the treatment to the parameter turbidity of natural waters. Nonparametric and multivariate statistical tools were used to analyze raw water and treated water turbidity of a large on-line monitoring databank for the period from 2013 to 2015, from six large-scale treatment plants utilizing different technologies. Cluster analysis was able to differentiate adequately groups of treatment plants with similar raw and treated water quality. Considering the effluent turbidity as a marker parameter, the results indicated that selection of the technology to be applied must be well studied to always seek the best solution, and that other factors than only the raw water characteristics should be evaluated. It was also demonstrated that utilization of the same treatment technology does not always result in the same effluent quality, since there are many factors related to operation, maintenance, raw water variability, climatic interferences, and others.

Assessment of spatial variations in the surface water quality of the Velhas River Basin, Brazil, using multivariate statistical analysis and nonparametric statistics.

The Velhas River sub-basin, which is located in the third-largest river basin in Brazil (São Francisco), is in an advanced state of degradation. In this work, the surface water quality of the Velhas River Basin was studied at 65 monitoring sites; 16 water quality parameters were sampled quarterly for 11 years (2008 to 2013). Cluster analysis (CA) and a nonparametric Kruskal-Wallis test were associated with the analysis of violations to water quality standards to interpret the water quality data set from the Velhas River Basin and assess its spatial variations. The CA grouped the 65 monitoring sites into four groups. The Kruskal-Wallis test identified significant differences (p < 0.05) between the groups formed by CA. The results show that watercourses located in the upper region of the Velhas River Basin are more affected by the release of industrial effluent and domestic sewage, and the lower region is more affected by diffuse pollution and erosion. This association between multivariate statistical techniques and nonparametric tests was effective for the classification and processing of large water quality datasets and the identification of major differences between water pollution sources in the basin. Therefore, these results provide an understanding of the factors affecting water quality in the Velhas River Basin. The results can aid in decision-making by water managers and these methods can be applied to other river basins.

Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin, Brazil.

Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.

Correction to: The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin, Brazil.

Unfortunately, the original version of this article was published online with error. The Tables 3 and 4 data was mixed up. The corrected Tables 3 and 4 are shown in the next page. The original article has been corrected.

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin, Brazil.

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008-2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.

Qualidade das águas superficiais do Médio São Francisco após a implantação dos perímetros irrigados de Gorutuba/Lagoa Grande e Jaíba / Surface water quality of the Middle San Francisco river basin after the implementation of irrigated perimeters of Gorutuba/Lagoa Grande and Jaíba

RESUMO Os perímetros irrigados de Gorutuba/Lagoa Grande e Jaíba localizam-se na porção mineira do Médio São Francisco, totalizando cerca de 31.493 ha. Essa região possui potencial de contaminar os recursos hídricos em decorrência da urbanização, do desmatamento e da utilização de fertilizantes e de agrotóxicos nas atividades agrícolas. O objetivo desta pesquisa foi investigar o impacto da irrigação na qualidade das águas superficiais da região, utilizando fontes de dados secundários de monitoramento. Foram selecionadas nove estações de monitoramento da qualidade da água superficial na região, que representavam diferentes usos e ocupação do solo. A análise de cluster e o teste não paramétrico de Kruskal-Wallis, seguido do teste de comparações múltiplas, foram utilizados para avaliar comparativamente as estações de amostragem, bem como identificar os parâmetros que apresentaram comportamentos diferenciados entre essas estações. Apesar de não ter sido possível observar um padrão de contaminação em função da localização das estações, detectou-se que as estações localizadas ao longo do Rio São Francisco não apresentaram diferenças significativas entre si, ainda que o uso e ocupação do solo fossem diferentes. A tendência temporal dos constituintes foi verificada através da aplicação do teste de hipótese de estacionariedade de Spearman, o qual detectou que a maioria dos dados analisados foram não estacionários, apresentando tendência de elevação ou redução ao longo do período analisado. Após a aplicação desses testes estatísticos, concluiu-se que, de maneira geral, a implantação de perímetros irrigados causou baixo impacto na qualidade das águas na região, no período estudado, considerando os parâmetros analisados neste trabalho.

ABSTRACT The irrigation perimeters of Jaíba and Gorutuba/Lagoa Grande are located in the Minas Gerais portion of the Middle São Francisco river basin, Brazil, occupying an area of approximately 31,493 ha. This region has the potential to contaminate water resources as a result of urbanization, deforestation and the application of fertilizers and pesticides in agricultural activities. The aim of this research was to investigate the impact of irrigation on surface water quality in the region, using secondary monitoring. Nine monitoring stations were selected in the region, which represent the diferente uses and occupation of land. The cluster analysis and the nonparametric Kruskal-Wallis test, followed by multiple comparisons, were used to comparatively evaluate the sampling stations and to identify which parameters showed different behavior among these stations. Although it was not possible to observe a pattern of contamination due to the location of the stations, it was found that the stations located along the São Francisco river showed no significant differences, although the use and occupation of land were different. The temporal trend of the constituents was verified by applying the test of the hypothesis of stationarity Spearmant, which found that most of the data analyzed were not stationary, with a tendency of increase or decrease over the analysis period. After the application of these statistical tests, it was concluded that, in general, the implementation of irrigated perimeters caused low impact in water quality in the region, in the period studied, considering the parameters analyzed in this study.

Application of solar photo-Fenton toward toxicity removal and textile wastewater reuse.

Solar photo-Fenton represents an innovative and low-cost option for the treatment of recalcitrant industrial wastewater, such as the textile wastewater. Textile wastewater usually shows high acute toxic and variability and may be composed of many different chemical compounds. This study aimed at optimizing and validating solar photo-Fenton treatment of textile wastewater in a semi-pilot compound parabolic collector (CPC) for toxicity removal and wastewater reclamation. In addition, treated wastewater reuse feasibility was investigated through pilot tests. Experimental design performed in this study indicated optimum condition for solar photo-Fenton reaction (20 mg L-1 of Fe2+ and 500 mg L-1 of H2O2; pH 2.8), which achieved 96 % removal of dissolved organic carbon (DOC) and 99 % absorbance removal. A toxicity peak was detected during treatment, suggesting that highly toxic transformation products were formed during reaction. Toxic intermediates were properly removed during solar photo-Fenton (SPF) treatment along with the generation of oxalic acid as an ultimate product of degradation and COS increase. Different samples of real textile wastewater were treated in order to validate optimized treatment condition with regard to wastewater variability. Results showed median organic carbon removal near 90 %. Finally, reuse of treated textile wastewater in both dyeing and washing stages of production was successful. These results confirm that solar photo-Fenton, as a single treatment, enables wastewater reclamation in the textile industry. Graphical abstract Solar photo-Fenton as a revolutionary treatment technology for "closing-the-loop" in the textile industry.

Operação de filtros biológicos percoladores pós-reatores UASB sem a etapa de decantação secundária / Operation of trickling filters post-UASB reactors without the secondary sedimentation stage

A pesquisa teve por objetivo avaliar filtros biológicos percoladores (FBP) pós-reatores UASB operando sem a etapa de decantação secundária, em termos da remoção da demanda bioquímica e química de oxigênio (DBO e DQO) e sólidos suspensos totais (SST). O aparato experimental consistia em um reator UASB que alimentava quatro FBP em paralelo, preenchidos com diferentes materiais suporte. O reator UASB operou em regime hidráulico permanente, e três condições operacionais foram impostas aos FBP durante o período experimental. Em geral, os sistemas UASB/FBP foram capazes de promover o atendimento aos padrões de lançamento. Em condições de baixas cargas orgânicas volumétricas (COV), o uso de materiais de enchimento de maior área superficial específica não proporcionou ganhos expressivos em termos de desempenho. Contudo, o uso de meio suporte baseado em espumas de poliuretano propiciou melhoria significativa na qualidade do efluente final. O uso de sistemas UASB/FBP sem decantadores secundários parece ser uma promissora alternativa para a simplificação operacional da tecnologia, e uma importante estratégia para o tratamento de efluentes domésticos em países em desenvolvimento. No entanto, o sucesso do emprego desta tecnologia fica condicionado ao correto gerenciamento do lodo anaeróbio do reator UASB, a fim de que sejam evitadas sobrecargas nos FBP.

The research aimed at evaluating the operation of trickling filters (TF) post-UASB reactors without the secondary sedimentation stage, in terms of biochemical and chemical oxygen demand (BOD and COD) and total suspended solids (TSS) removal. The experimental apparatus consisted of one UASB reactor followed by four TF in parallel, each one filled with a different packing media. The UASB reactor was operated at a permanent hydraulic regime, while three operational conditions were imposed to the TF during the experimental period. In general, the UASB/TF systems were able to comply with the discharge standards. At low organic loading rates (OLR), no improvements in terms of organic matter removal, with the use of higher surface area packing media were observed. However, the use of a sponge-based packing media provided significant improvements on final effluent quality. The use of UASB/TF systems without secondary sedimentation can constitute an attractive alternative in terms of operational simplification of this technology, and an important strategy for domestic wastewater treatment in developing countries. However, the success of this technology is strictly connected to the correct anaerobic sludge management of the UASB reactor, in order to avoid overloads on the TF.

Análise da confiabilidade de estações de tratamento de esgotos / Reliability analysis of wastewater treatment plants

Este artigo apresenta uma análise da confiabilidade de 166 estações de tratamento de esgotos em operação no Brasil, considerando seis processos de tratamento mais usualmente adotados. Foi utilizada uma metodologia desenvolvida por Niku et al (1979) para determinação de coeficientes de confiabilidade (CDC), considerando o alcance a metas de lançamento para concentrações efluentes de DBO, DQO, SST, NT, PT e CF. A partir dos CDC obtidos, foram calculadas as concentrações de projeto necessárias para o cumprimento das metas de lançamento e os percentuais de atendimento esperados. Os resultados mostraram que poucas ETEs, nas condições de operação observadas, conseguiriam apresentar desempenhos confiáveis, em termos de cumprimento dos padrões. Para todos os constituintes e sistemas de tratamento, a variabilidade da qualidade do efluente foi muito grande.

This article presents a reliability analysis of 166 full-scale wastewater treatment plants operating in Brazil, comprising six different treatment processes usually adopted. A methodology developed by Niku et al (1979) is used for the determination of the coefficients of reliability (COR), in terms of the compliance of effluent BOD, COD, TSS, TN, TP and FC to discharge standards. The design concentrations necessary to meet the prevailing discharge standards and the expected compliance percentages have been calculated from the coefficients of reliability obtained. The results showed that few plants, under the observed operating conditions, would be able to present reliable performances in terms of compliance with the analyzed standards. For all constituents and systems, the variability of the effluent quality was very large.