Mass Balance Models of Phosphorus and Nitrogen in Sediments and Water of the Lower Reaches of Tamiraparani River System

Abstract Determination of the mass output through the St. Lawrence River outflow system is an important component in computing mass balance of chemical loadings to Lake Ontario. The total flow rate in the St. Lawrence River System at the Wolfe Island area was calculated from detailed time series current meter measurements from a network of current meters and Lagrangian drifter experiments. This flow is roughly distributed in the ratio of 55% to 45% in the South and North channel, respectively. Loading estimates of selected chemicals have been made by combining the above transport calculations with the ongoing chemical monitoring data at the St. Lawrence outflow. A vertical gradient in the concentration of some organic and inorganic chemicals was observed. The measured concentration for some of the chemicals was higher during the summer months and also is higher in the South Channel than in the North Channel of the St. Lawrence River. These loading estimates are useful not only for modelling the mass balance of chemicals in Lake Ontario but also for serving as input loadings to the St. Lawrence River system from Lake Ontario.

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The role of multimedia mass balance models for assessing the effects of volatile organic compound emissions on urban air quality

Atmospheric Environment ◽

10.1016/j.atmosenv.2005.11.067 ◽

2006 ◽

Vol 40 (16) ◽

pp. 2986-2994 ◽

Cited By ~ 8

Author(s):

Karen L. Foster ◽

Steven Sharpe ◽

Eva Webster ◽

Donald Mackay ◽

Randy Maddalena

Keyword(s):

Air Quality ◽

Organic Compound ◽

Mass Balance ◽

Volatile Organic Compound ◽

Urban Air Quality ◽

Urban Air ◽

Mass Balance Models ◽

Volatile Organic ◽

Volatile Organic Compound Emissions

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Comparison between energy balance and mass balance models for actual evapotranspiration assessment

10.1117/12.830229 ◽

2009 ◽

Author(s):

A. Gentile ◽

L. Pierce ◽

G. Ciraolo ◽

G. Zhang ◽

G. La Loggia ◽

...

Keyword(s):

Energy Balance ◽

Mass Balance ◽

Actual Evapotranspiration ◽

Mass Balance Models

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Investigating Fast- and Slow-settling Phosphorus Fractions in Lakes using Steady-state Modeling

10.5194/egusphere-egu21-13910 ◽

2021 ◽

Author(s):

Hamed Khorasani ◽

Zhenduo Zhu

Keyword(s):

Steady State ◽

Mass Balance ◽

Large Scale ◽

Hydraulic Residence Time ◽

Simple Method ◽

Retention Models ◽

Mass Balance Models ◽

Limiting Nutrient ◽

Fast Settling ◽

P Retention

<p>Phosphorus (P) is the key and limiting nutrient in the eutrophication of freshwater resources. Modeling P retention in lakes using steady-state mass balance models (i.e. Vollenweider-type models) provides insights into the lake P management and a simple method for large-scale assessments of P in lakes. One of the basic problems in the mass balance modeling of P in lakes is the removal of P from the lake water column by settling. A fraction of the incoming P into the lake from the watershed is associated with fast-settling particles (e.g. sediment particles) that result in the removal of that fraction of P quickly at the lake entrance. However, existing models considering a constant fraction of fast-settling TP for all lakes are shown to result in overestimation of the retention of P in lakes with short hydraulic residence time. In this study, we combine a hypothesis of the fast- and slow-settling P fractions into the steady-state mass balance models of P retention in lakes. We use a large database of lakes to calibrate the model and evaluate the hypothesis. The results of this work can be used for the improvement of the prediction power of P retention models in lakes and help to better understand the processes of P cycling in lakes.</p>

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Impact of the choice of surface mass balance models and their calibration on large-scale glacier change projections

10.5194/egusphere-egu21-1391 ◽

2021 ◽

Author(s):

Lilian Schuster ◽

David Rounce ◽

Fabien Maussion

Keyword(s):

Mass Balance ◽

Large Scale ◽

Model Complexity ◽

Model Parameters ◽

Glacier Change ◽

Surface Mass Balance ◽

Ice Dynamics ◽

Surface Mass ◽

Mass Balance Models ◽

Intercomparison Study

<p>A recent large model intercomparison study (GlacierMIP) showed that differences between the glacier models is a dominant source of uncertainty for future glacier change projections, in particular in the first half of the century.&#160; Each glacier model has their own unique set of process representations and climate forcing methodology, which makes it impossible to determine the model components that contribute most to the projection uncertainty. This study aims to improve our understanding of the sources of large scale glacier model uncertainty using the Open Global Glacier Model (OGGM), focussing on the surface mass balance (SMB) in a first step. We calibrate and run a set of interchangeable SMB model parameterizations (e.g. monthly vs. daily, constant vs. variable lapse rates, albedo, snowpack evolution and refreezing) under controlled boundary conditions. Based on ensemble approaches, we explore the influence of (i) the parameter calibration strategy and (ii) SMB model complexity on regional to global glacier change. These uncertainties are then put in relation to a qualitative selection of other model design choices, such as the forcing climate dataset and ice dynamics model parameters.&#160;</p>

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Computational Techniques Application in Environmental Exposure Assessment

Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment - Advances in Chemical and Materials Engineering ◽

10.4018/978-1-4666-8136-1.ch012 ◽

2015 ◽

pp. 471-505

Author(s):

Karolina Jagiello ◽

Tomasz Puzyn

Keyword(s):

Mass Balance ◽

Exposure Assessment ◽

Environmental Exposure ◽

Chemical Properties ◽

Computational Techniques ◽

Structure Property ◽

Mass Balance Models ◽

Modelling Methodology ◽

Environmental Exposure Assessment ◽

Input Variables

In this chapter, the application of computational techniques in environmental exposure assessment was described. The most important groups of these techniques are Multimedia Mass-balance (MM) modelling and Quantitative Structure-Activity/Structure-Property Relationships (QSAR/QSPR) modelling. Multimedia Mass-balance models have been widely utilized for studying Long-Range Transport Potential (LRTP) and overall persistence (POV) of Persistent Organic Pollutants (POPs), regulated by many national and international acts, including the Stockholm Convention on POPs. Recently, a novel modelling methodology that links QSPR and MM has been implemented. According to this approach, the physical/chemical properties required as the input variables for multimedia modelling can be calculated directly from appropriate QSPR models. QSPR models must be previously developed based on the relationships between the chemical structure and the modelled properties (QSPR).

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Mathematical Modeling of a Domestic Wastewater Treatment System Combining a Septic Tank, an Up Flow Anaerobic Filter, and a Constructed Wetland

Water ◽

10.3390/w12113019 ◽

2020 ◽

Vol 12 (11) ◽

pp. 3019

Author(s):

Alberto Fernández del Castillo ◽

Marycarmen Verduzco Garibay ◽

Carolina Senés-Guerrero ◽

Carlos Yebra-Montes ◽

José de Anda ◽

...

Keyword(s):

Mathematical Modeling ◽

Wastewater Treatment ◽

Linear Regression ◽

Multiple Linear Regression ◽

Mass Balance ◽

Constructed Wetland ◽

Oxygen Demand ◽

Septic Tank ◽

First Order ◽

Mass Balance Models

Systems combining anaerobic bioreactors with constructed wetlands (CW) have proven to be adequate and efficient for wastewater treatment. Detailed knowledge of removal dynamics of contaminants can ensure positive results for engineering and design. Mathematical modeling is a useful approach to studying the dynamics of contaminant removal in wastewater. In this study, water quality monitoring was performed in a system composed of a septic tank (ST), an up flow anaerobic filter (UAF), and a horizontal flow constructed wetland (HFCW). Biological oxygen demand (BOD5), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), NH3, organic nitrogen (ON), total suspended solids (TSS), NO2−, and NO3− were measured biweekly during a 3-month period. First-order kinetics, multiple linear regression, and mass balance models were applied for data adjustment. First-order models were useful to predict the outlet concentration of pollutants (R2 > 0.87). Relevant multiple linear regression models were found, which could be applied to facilitate the system’s monitoring and provide valuable information to control and improve biological and physical processes necessary for wastewater treatment. Finally, the values of important parameters (μmax, Ks, and Yx/s) in mass-balance models were determined with the aid of a differential neural network (DNN) and an optimization algorithm. The estimated parameters indicated the high robustness of the treatment system since performance stability was found despite variations in wastewater composition.

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