Behavior simulation of nitrogen compounds in rivers with uncertainty  analysis

Fortunato, Tatiana Candeia da Silva; Reis, José Antônio Tosta dos; Mendonça, Antônio Sérgio Ferreira; Silva, Fernando das Graças Braga da

doi:10.4136/ambi-agua.2449

Cited by 3 publications

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In most surface water and soil deposits, there are many contaminants, which implies that the water is not suitable for drinking, which, in general, is the main reason for water quality (Yaraghi et al, 2020) studies. Some studies indicate that some chemical factors can be considered as quality indicators, such as the concentration of ammonia nitrogen (NH 3− N) in rivers (Che et al, 2019; da Silva Fortunato, Tosta dos Reis, Sérgio Mendonça, & Braga da Silva, 2020; Frazier, Naimo, & Sandheinrich, 1996; Jing & Lin, 2004; Sun, Wang, Wang, & Zhang, 2020; Wang et al, 2020; Xu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Identifying water factors that are related to ammonia nitrogen concentrations in Columbia River using a reversed hazard exponential model

Santos

Martins

Silva

et al. 2021

River Research & Apps

View full text Add to dashboard Cite

Ammonia nitrogen is a compound that in its abundance is related to the inadequate discharge of industrial and domestic effluents. Since high concentrations of ammonia nitrogen can directly affect the water quality or disturb the marine environment, this study examined the ammonia nitrogen concentrations in Columbia River, USA in a fixed period (from January, 2014 to January, 2020) related to some water factors. Some interesting conclusions were obtained in this study as the identification of dissolved oxygen (in mg/L), pH, specific conductivity (in umhos/cm), and temperature (in °C) as potential factors affecting the ammonia nitrogen concentrations in Columbia River which may alert authorities to keep restrictive strategies to control the advance of this kind of water pollution. The results of this study could be extended to other regions of the world, especially in more impoverished countries usually with precarious water pollution control systems with implications for public health.

show abstract

Section: Introductionmentioning

confidence: 99%

Identifying water factors that are related to ammonia nitrogen concentrations in Columbia River using a reversed hazard exponential model

Santos

Martins

Silva

et al. 2021

River Research & Apps

View full text Add to dashboard Cite

show abstract

Simulação da qualidade da água do rio Pardo com incorporação de análise de incerteza

Poton

Reis

Almeida

et al. 2023

Eng. Sanit. Ambient.

Self Cite

View full text Add to dashboard Cite

Resumo A principal perspectiva do presente trabalho é a simulação matemática de transformações de oxigênio dissolvido e demanda bioquímica de oxigênio no rio Pardo (Espírito Santo, Brasil), considerando a incorporação de análise de incerteza pelo Método de Monte Carlo. Para a aplicação do Método de Monte Carlo, as variáveis hidrodinâmicas, condições iniciais de qualidade do rio Pardo e efluentes e constantes cinéticas do modelo de qualidade de água foram gerados aleatoriamente com auxílio das distribuições de probabilidade Normal e Uniforme. O emprego de cada distribuição de probabilidade envolveu a realização de mil simulações dos perfis de oxigênio dissolvido e demanda bioquímica de oxigênio. Os resultados das simulações indicaram que, para o curso d’água estudado, as concentrações mínimas de oxigênio dissolvido variaram predominantemente entre 6,0 e 6,5 mg∙L-1 e, em nenhuma das simulações, apresentaram valores inferiores ao padrão de qualidade ambiental. As concentrações de demanda bioquímica de oxigênio, por sua vez, permaneceram acima do padrão de qualidade ambiental na maior porção intermediária do rio Pardo, com valores máximos entre 16,0 e 17,75 mg∙L-1. No entanto o emprego de diferentes distribuições de probabilidade para a geração aleatória de variáveis hidrodinâmicas, constantes cinéticas e concentrações dos parâmetros de qualidade de água não produziu variações consideradas relevantes quando da análise de frequência das concentrações críticas dos parâmetros de qualidade de água simulados.

show abstract

Sewage treatment efficiencies estimation for urban areas located in the River Pardo’s watershed by associating nonlinear programming and water quality modeling

Rocha

Almeida

Reis

et al. 2020

Rev. Bras. Ciênc. Ambient. (Online)

Self Cite

View full text Add to dashboard Cite

Estimating efficiencies required for sewage treatment plants within a river watershed, where there are usually multiple sewage discharges and water withdrawals points in watercourses, presenting different quality conditions and sewage assimilation capacities, is a complex task. In this context, combined optimization techniques and water quality modeling can be important tools to support sewage treatment efficiencies appropriation processes. In the present paper, QUAL-UFMG water quality model and Nonlinear Programming (NLP) are jointly applied to sewage treatment levels selection for the river Pardo’s (watercourse located in Espírito Santo State, Southern region, Brazil) watershed different urban areas. Four different optimization models were tested for estimating the minimum organic matter removal efficiencies. The results indicate strong dependence between the estimated minimum organic matter removal efficiencies within the watershed and equity measures incorporated in the optimization models.

show abstract

Behavior simulation of nitrogen compounds in rivers with uncertainty analysis

Cited by 3 publications

References 24 publications

Identifying water factors that are related to ammonia nitrogen concentrations in Columbia River using a reversed hazard exponential model

Identifying water factors that are related to ammonia nitrogen concentrations in Columbia River using a reversed hazard exponential model

Simulação da qualidade da água do rio Pardo com incorporação de análise de incerteza

Sewage treatment efficiencies estimation for urban areas located in the River Pardo’s watershed by associating nonlinear programming and water quality modeling

Contact Info

Product

Resources

About