Exploring the influence of meteorological conditions on the performance of a waste stabilization pond at high altitude with structural equation modeling

Ho, Long; Pham, Duy Tan; Echelpoel, Wout Van; Alvarado, Andrés; Espinoza-Palacios, Juan; Arevalo-Durazno, Maria; Goethals, Peter

doi:10.2166/wst.2018.254

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…Consequently, there was no large difference on the average temperature between the dry and wet seasons. However, the daily fluctuations in temperature over 24-h periods are much more pronounced, meaning that temperature stratification can occur during daytime [38,40]. However, this was not the case in this study as no large difference and variability of water temperature between the surface and the bottom was observed in the ponds.…”

Section: Variability Of the Physicochemical And Biological Parameterscontrasting

confidence: 52%

“…However, it was also interesting to note that the maximum concentration observed in the WSP was 500 µg L −1 , which was considered to be low, according to Mara [1], as the chlorophyll a concentration in "healthy" WSPs is usually in the range of 500-2000 µg L −1 . Therefore, more samplings and long-term data collection should be done to figure out whether this low concentration of chlorophyll a was related to short-term data collection, or this could be a characteristic of a WSP operating at a high altitude [34][35][36][37][38].…”

Section: Variability Of the Physicochemical And Biological Parametersmentioning

confidence: 99%

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Generalised Linear Models for Prediction of Dissolved Oxygen in a Waste Stabilisation Pond

Pham

Espinoza-Palacios

et al. 2020

Water

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Due to simplicity and low costs, waste stabilisation ponds (WSPs) have become one of the most popular biological wastewater treatment systems that are applied in many places around the globe. Increasingly, pond modelling has become an interesting tool to improve and optimise their performance. Unlike process-driven models, generalised linear models (GLMs) can deliver considerable practical values in specific case studies with limited resources of time, data and mechanistic understanding, especially in the case of pond systems containing vast complexity of many unknown processes. This study aimed to investigate the key driving factors of dissolved oxygen variability in Ucubamba WSP (Ecuador), by applying and comparing numerous GLMs. Particularly, using different data partitioning and cross-validation strategies, we compared the predictive accuracy of 83 GLMs. The obtained results showed that chlorophyll a had a strong impact on the dissolved oxygen (DO) level near the water surface, while organic matter could be the most influential factor on the DO variability at the bottom of the pond. Among the 83 models, the optimal models were pond- and depth-specific. Specifically, among the ponds, the models of MPs predicted DO more precisely than those of facultative ponds; while within a pond, the models of the surface performed better than those of the bottom. Using mean absolute error (MAE) and symmetric mean absolute percentage error (SMAPE) to represent model predictive performance, it was found that MAEs varied in the range of 0.22–2.75 mg L−1 in the training period and 0.74–3.54 mg L−1 in the validation period; while SMAPEs were in the range of 2.35–38.70% in the training period and 10.88–71.62% in the validation period. By providing insights into the oxygen-related processes, the findings could be valuable for future pond operation and monitoring.

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Section: Variability Of the Physicochemical And Biological Parameterscontrasting

confidence: 52%

Section: Variability Of the Physicochemical And Biological Parametersmentioning

confidence: 99%

Generalised Linear Models for Prediction of Dissolved Oxygen in a Waste Stabilisation Pond

Pham

Espinoza-Palacios

et al. 2020

Water

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“…Plus, the values of suggest a higher diurnal variation of the CO2 and CH4 emissions compared to the stable N2O emissions across the sampling days since the variance of the random diurnal effect explained only 4% of the total variation in the case of the N2O emissions. This contrast can be explained by substantial temporal variation of DO level observed in Cuenca in the previous studies (Ho et al, 2018a;Ho et al, 2018b). In particular, the production of CO2 and CH4 might depend stronger on the prevalence of DO as it controls the efficiency of anaerobic/anoxic processes, which are mainly responsible for releasing CH4, and highly correlated to the amount of CO2…”

Section: Spatiotemporal Variation Of the Ghg Emissionsmentioning

confidence: 89%

Effects of land use and water quality on greenhouse gas emissions from an urban river system

Jerves-Cobo

Barthel

et al. 2020

Preprint

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Abstract. Rivers act as a natural source of greenhouse gases (GHGs) that can be released from the metabolisms of aquatic organisms. Anthropogenic activities can largely alter the chemical composition and microbial communities of rivers, consequently affecting their GHG emissions. To investigate these impacts, we assessed the emissions of CO2, CH4, and N2O from Cuenca urban river system (Ecuador). High variation of the emissions was found among river tributaries that mainly depended on water quality and neighboring landscapes. By using Prati and Oregon Indexes, a clear pattern was observed between water quality and GHG emissions in which the more polluted the sites were, the higher were their emissions. When river water quality deteriorated from acceptable to very heavily polluted, their global warming potential (GWP) increased by ten times. Compared to the average estimated emissions from global streams, rivers with polluted water released almost double the estimated GWP while the proportion increased to ten times for very heavily polluted rivers. Conversely, the GWP of good-water-quality rivers was half of the estimated GWP. Furthermore, surrounding land-use types, i.e. urban, roads, and agriculture, significantly affected the river emissions. The GWP of the sites close to urban areas was four time higher than the GWP of the nature sites while this proportion for the sites close to roads or agricultural areas was triple and double, respectively. Lastly, by applying random forests, we identified dissolved oxygen, ammonium, and flow characteristics as the main important factors to the emissions. Conversely, low impact of organic matter and nitrate concentration suggested a higher role of nitrification than denitrification in producing N2O. These results highlighted the impacts of land-use types on the river emissions via water contamination by sewage discharges and surface runoff. Hence, to estimate of the emissions from global streams, both their quantity and water quality should be included.

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“…A WSP model with three different compartments was simulated within the plug flow module, with each compartment containing different microorganisms, processes, and variables, hence increasing significantly the model complexity compared to the AS model. Within the plug-flow module, its assumption of a homogenous depth profile of variables is valid since the photosynthesis activity in facultative (FPs) and maturation ponds (MPs) can extend down to a depth of 20-30 cm, creating a homogenous aerobic condition in these oxidation ponds whose height is 20 cm [19,20]. Regarding the processes in the WSP model, following the Constructed Wetland Model No.1 of Langergraber, et al [21], the anaerobic processes in the anaerobic compartment included the hydrolysis process of slowly biodegradable COD and the metabolism of anaerobic bacteria.…”

Section: Model Descriptionmentioning

confidence: 99%

Model-Based Analysis of Increased Loads on the Performance of Activated Sludge and Waste Stabilization Ponds

Pompeu

Echelpoel

et al. 2018

Water

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In a way to counter criticism on low cost-effective conventional activated sludge (AS) technology, waste stabilization ponds (WSPs) offer a valid alternative for wastewater treatment due to their simple and inexpensive operation. To evaluate this alternative with respect to its robustness and resilience capacity, we perform in silico experiments of different peak-load scenarios in two mathematical models representing the two systems. A systematic process of quality assurance for these virtual experiments is implemented, including sensitivity and identifiability analysis, with non-linear error propagation. Moreover, model calibration of a 210-day real experiment with 31 days of increased load was added to the evaluation. Generally speaking, increased-load scenarios run in silico showed that WSP systems are more resilient towards intermediate disturbances, hence, are suitable to treat not only municipal wastewater, but also industrial wastewater, such as poultry wastewater, and paperboard wastewater. However, when disturbances are extreme (over 7000 mg COD·L−1), the common design of the natural system fails to perform better than AS. Besides, the application of sensitivity analysis reveals the most influential parameters on the performance of the two systems. In the AS system, parameters related to autotrophic bacteria have the highest influence on the dynamics of particulate organic matter, while nitrogen removal is largely driven by nitrification and denitrification. Conversely, with an insignificant contribution of heterotrophs, the nutrient removal in the pond system is mostly done by algal assimilation. Furthermore, this systematic model-based analysis proved to be a suitable means for investigating the maximum load of wastewater treatment systems, and from that avoiding environmental problems and high economic costs for cleaning surface waters after severe overload events.

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Exploring the influence of meteorological conditions on the performance of a waste stabilization pond at high altitude with structural equation modeling

Cited by 10 publications

References 26 publications

Generalised Linear Models for Prediction of Dissolved Oxygen in a Waste Stabilisation Pond

Generalised Linear Models for Prediction of Dissolved Oxygen in a Waste Stabilisation Pond

Effects of land use and water quality on greenhouse gas emissions from an urban river system

Model-Based Analysis of Increased Loads on the Performance of Activated Sludge and Waste Stabilization Ponds

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