Mass Balance Equations Research Articles

Optimizing Brown Stock Washing in the Pulp and Paper Industry: A System Dynamics Approach

The process of pulping and papermaking is a complicated, resource-demanding operation that requires energy, water, and chemicals. When not managed properly, the process can also contribute significantly to pollution. The washing process is one critical operation that impacts the process’s economics and environmental footprint. Most mills utilize rotary vacuum washers to separate black liquor from pulp, ensuring clean pulp for further processing downstream. Numerous factors influence the efficiency of a brown stock washer, and the washing operation itself is intricate. This study employs the system dynamics modeling approach to examine the critical role of brown stock washing in the pulp and paper industry, emphasizing optimizing process parameters for improved efficiency and sustainability. In the first part of the paper, a single stage of the washer system is modeled by establishing mass balance equations for key streams, including pulp, liquor, and dissolved solids. Within the system dynamics environment, separate models are developed for each stream, allowing for a detailed analysis of their behavior. To enhance modeling efficiency, the brown stock washing process is divided into four distinct operations: dilution, pulp formation, washing, and filtration. Breaking down the process into these operations makes it possible to focus on optimizing each step for improved overall performance. Furthermore, a control strategy is implemented to ensure stability in critical areas such as dilution vat level, discharged pulp consistency, and filtration tank level. In the final phase of the research, a multistage countercurrent brown stock washing line comprising three washers is modeled. Researchers can gain insights into how different components interact and influence overall performance by evaluating various parameters and analyzing the line’s efficiency. This comprehensive analysis enables them to identify potential improvements and optimize the washing process for enhanced productivity and quality output. The conclusions drawn from this work offer valuable guidance for optimizing water management practices in the pulp and paper sector, contributing to the industry’s sustainability goals and regulatory compliance.

A multimedia fugacity model for assessing the environmental fate of typical antibiotics in Lake Taihu with emphasis on the biomechanical characteristics of drug delivery systems

The extensive use of antibiotics in the Taihu Lake Basin has led to a significant threat to human and environmental health. In this context, the QWASI model is developed to simulate the fate of typical antibiotics in Lake Taihu. Through this model, real-time tracking of the dynamic changes in antibiotic content is possible. The study primarily focuses on evaluating the fate and transfer of antibiotics in the water and sediment phases of the lake. The model results indicate that most of the simulated concentrations and mass fluxes are within the same order of magnitude as the measured values, demonstrating a good simulation effect. However, an underestimation of the simulated output value occurs in some cases. The sediment layer serves as the main accumulation site for antibiotics, and the mass balance equation is a crucial tool for simulating the environmental distribution of antibiotics. Sulfamethoxazole (SMX) exhibits a relatively high concentration in water due to its large model input. The sensitivity analysis reveals that for ATM, SMX, and OFX, the five input parameters with the most significant impact are the half-life in water, sediment-water partition coefficient, sediment solids concentration, sediment particle density, and sediment-water diffusion MTC. For OTC, the impact of lake water depth is more prominent than the sediment-water mass transfer rate. The uncertainty analysis effectively showcases the model’s stability, with the water phase concentration showing better stability. In this process, each factor is assigned a correlation coefficient to represent its influence on the original content. The sediment phase antibiotic concentration has a relatively high uncertainty. The source intensity assessment in this study utilizes direct monitoring data of the Taihu Lake water body, ensuring higher accuracy. The major factor contributing to prediction errors is the ambiguity of the sediment phase, which is affected by numerous environmental factors. Importantly, when considering the fate of antibiotics in the lake, the biomechanical characteristics of potential drug delivery systems play a vital role. The movement and dispersion of antibiotics within the water and sediment are influenced by biomechanical forces. In the sediment, the porosity and permeability, which are related to biomechanical properties, can determine the rate at which antibiotics penetrate and accumulate. Understanding these biomechanical aspects of drug delivery systems can help in devising more effective strategies for antibiotic remediation. It can also provide insights into how the physical environment interacts with the chemical behavior of antibiotics, ultimately contributing to a more comprehensive understanding of the environmental fate of antibiotics in Lake Taihu. This is the first study to explore the fate of antibiotics in Lake Taihu and offers valuable recommendations for the restoration of antibiotic-contaminated lakes. It enriches the research perspectives on water management, especially in relation to addressing water pollution caused by antibiotic abuse.

Mapping Spatiotemporal Solvent Velocity from Measured Concentration Gradients in a Polarized Electrolyte

Abstract The electric-field induced motion of neutral species impedes the efficacy of electrochemical devices. By combining operando X-ray transmission measurements with continuum mechanics, we have developed a methodology for determining the velocity of neutral solvent molecules under an applied field. The X-ray transmission experiments were used to determine ion concentration profiles as a function of space and time in a polymer electrolyte. The unsteady state solvent mass balance equation was solved numerically with experimental concentration profiles to map spatiotemporal solvent velocities. We compare our experimentally derived results with predictions made with concentrated solution theory. We use the cation transference number as the only adjustable parameter to match experimental measurements of both concentration and solvent velocity. Our approach may be used to determine solvent velocity with any operando technique used to measure time-dependent ion concentration profiles.

Dynamic modeling and optimization of methanol partial oxidation to formaldehyde over Mo–Fe catalyst in an industrial isothermal reactor

Abstract In this research, a one-dimensional heterogeneous model is developed to simulate the partial oxidation of methanol to formaldehyde over a molybdenum-iron catalyst in an industrial isothermal reactor at dynamic condition. The considered isothermal reactor is modelled based on the mass and energy balance equations considering catalyst deactivation. Based on the simulation results, decline in the catalyst activity from 1.0 to 0.73 decreases the rate of formaldehyde production rate from 94.9 kmol h−1 to 89.63 kmol h−1 during process run time. Subsequently, a multi-objective optimization problem is programmed to enhance formaldehyde productivity and minimize the production decline during process run time. To select the effective decision variables, a sensitivity analysis is performed based on the developed dynamic model. Then, the programmed multi-objective optimization problem is replaced with a single objective by the weighted sum method, and the problem is handled by the genetic algorithm method to determine the optimal trajectory of coolant temperature. The simulation results showed that the average formaldehyde production rate increases from 92.11 kmol h−1 to 95.22 kmol h−1 when the optimal conditions are applied to the reactor.

Exergo-environmental sustainability assessments of organic Rankine cycle plants powered by a typical abandoned oil well

Economic and technical factors often force players in the oil and gas sectors to abandon oil wells with significant but minimal energy contents. To promote energy efficiency, efforts are ongoing to explore viable means of recovering such residual energy, basically as geotherms, for power generation. However, there are sparse studies in the literature that assess the exergo-environmental sustainability potentials of power generation from ORC using abandoned oil wells as the primary energy source, thereby necessitating this study. The exergetic sustainability and exergo-environmental performance of non-recuperative and recuperative organic Rankine cycle (ORC) plants were assessed in this study for the production of electricity from abandoned oil wells. The geomechanical properties of a typical oil well in Nigeria were employed as inputs into an established COMSOL model to determine the thermal profile of the heat source. For the ORC plant, the mass, energy, and exergy balance equations defined by the Thermodynamics laws were implemented in MATLAB. Also, MATLAB was adopted for computing the exergetic sustainability and exergo-environmental metrics for the individual components and the entire system. Results showed that the condenser exhibited the least exergo-environmental sustainability for both ORC schemes assessed, meaning that it contributed the most to energy wastages among the system components. Furthermore, results showed that the exergo-environmental impact rates of the condenser are highest in both cases. Generally, results showed that the inclusion of a recuperator would improve the exergy-based environmental sustainability of the ORC plant. Specifically, the overall rate of exergo-environmental impact would decrease from around 86 Pt/h to about 76 Pt/h, amounting to approximately 13% decrease.

Theory of Gas Purification by Liquid Absorber in Small Rotating Channels with Application to the Patented Rotational Absorber Device

A new design for absorbing vapour-phase impurities from gases is presented. It consists of small channels packed in a rotating vertical cylinder. Gas flows through the channels adjacent to a thin film of absorber liquid. The liquid film is pressed to the radially outward side of each channel by the centrifugal force and flows downwards by gravity. Formulae are presented which describe the concentration distributions of gaseous impurities subject to absorption in gas and liquid. Results include expressions for laminar and turbulent diffusion coefficients to be used in mass balance equations. The role of rotation is quantified including the effect on wavy motion and enhanced diffusion in the liquid layer. Application in design is indicated for the case of separation of the greenhouse gas CO2 from flue gases of fossil fuel combustion processes. At other equal dimensions, the height of the Rotational Absorber Device is calculated to be 25 times shorter than the enormous heights of conventional tray and packed columns.

Characterization and Modeling of Gravity-Driven Flashing of Superheated Water in a Pool Heated from Below

Gravity-driven flashing of superheated water, the topic of this paper, is a phase change phenomenon that is tightly linked with some of the safety issues of a spent-fuel-pool loss-of-cooling accident. As detailed in this article, the phenomenon has been empirically studied and characterized within the Aquarius laboratory-scale experimental device. Primarily, the performed tests unveil the occurrence conditions of the gravity-driven flashing phenomenon in a pool heated from below and its coupling with the degassing of dissolved gases that may take place within the liquid. Next, a set of dimensionless correlations describing the studied heat and mass transfers is derived from the data and presented for both the single-phase and the two-phase regimes of any conducted test. Then, a lumped-parameter model, relying on those correlations and describing the studied physics, is introduced. The model resolves the coupled mass and energy balance equations of the heated liquid pool. Last, this model is used to simulate a selected reference test. The performed simulations are successfully compared with the available empirical data, with moderate discrepancies, thereby verifying the adequateness of the proposed model.

Bayesian predictive modeling of indoor ultrafine particles to enhance mid-cost monitoring

Monitoring airborne nanoparticles has a vital role in indoor air quality control due to their hazardous effects on human health. Detecting particles becomes more challenging as their sizes decrease. While research-grade instruments like the scanning mobility particle sizer (SMPS) can provide detailed and useful information, they are not practical for personal use due to their size and cost. This study aims to provide a comparable prediction of the temporal size distribution of ultrafine particles (UFPs, <100nm) using mid-cost measurements from a handheld particle sizer, which is more economical but has a narrower detectable size range. To achieve this, the study builds upon a computational modeling approach based on a mass-balance equation to estimate the time-varying particle size distribution, while accounting for particle evolution processes such as coagulation, deposition, and ventilation. The analytical model for indoor UFPs requires prior information regarding particle dynamic behavior, such as the size-resolved deposition rate and source emission rate. This study estimates, rather than pre-determines, the model parameters required for the temporal prediction of indoor UFP size distribution by applying Bayesian parameter inference with the analytical model of indoor aerosol. The results indicate that the present model reasonably predicts the temporal evolution of particle distributions, comparable to that of the SMPS. Furthermore, this study demonstrates the identifiability of model parameters, considering both the entire and detectable size ranges, through variance-based global sensitivity analysis.

Artificial Neural Networks-based models for an internally cooled liquid desiccant dehumidifier

Abstract Air-conditioning systems condense air water vapor to achieve dehumidification. This process entails excessive cooling followed by reheating, resulting in high energy usage. As a more energy-efficient alternative, liquid desiccant-based dehumidification eliminates the need for excess cooling by dehumidifying through an absorption process. Advanced internally cooled liquid-desiccant dehumidifiers enhance overall air conditioning efficiency by incorporating internal cooling mechanisms. These devices are three-stream heat and mass exchangers, involving air, liquid desiccant, and cooling water. Simulating them involves discretization and solving comprehensive partial differential mass and energy balance equations to capture the interconnected heat and mass transfer phenomena. The models require detailed dehumidifier information, are computationally expensive, and pose challenges in convergence. These requirements make them unsuitable for integration into Building Energy Simulation software or inclusion within a comprehensive air-conditioning system model. This study aims to generate models with less computational demands during simulation using artificial neural networks. A comprehensive finite difference model was used to generate training data for developing the neural network. Various network configurations were explored to assess their impact on prediction precision. The trained network, integrated into an independent code, underwent evaluation for prediction accuracy using a distinct dataset from the training stage, proving accurate to simulate the internally cooled dehumidifier, reaching R-values up to 0.96 for the 5 predicted outlet variables. This is the initial step towards incorporating neural network models into specialized Building Energy Simulation software, as the foundation for conducting system-level, transient, and long-term simulations.

Origin of Intercrystalline Brine Formation in the Balun Mahai Basin, Qaidam: Constraints from Geochemistry and H-O-Sr Isotopes

The Balun Mahai Basin (BLMH), located in the northern Qaidam Basin (QB), is endowed with substantial brine resources; however, the genetic mechanisms and potential of these brine resources remain inadequately understood. This study investigated the intercrystalline brine (inter-brine) in BLMH, performing a comprehensive geochemical analysis of elemental compositions and H-O-Sr isotopes. It evaluated the water source, solute origin, evolutionary process, and genetic model associated with this brine. Moreover, a mass balance equation based on the 87Sr/86Sr isotopic ratio was developed to quantitatively evaluate the contributions of Ca-Cl water and river water to the inter-brine in the study area. The results suggest that the hydrochemical type of inter-brine in the north part of BLMH is Cl-SO4-type and in the south part is Ca-Cl-type. The solutes in brine are mainly derived from the dissolution of minerals such as halite, sylvite, and gypsum. The hydrochemical process of brine is controlled by evaporation concentration, water–rock interaction, and ion exchange interaction. Hydrogen and oxygen isotopes suggest that the inter-brine originates from atmospheric precipitation or ice melt water and has experienced intense evaporation concentration and water–rock interaction. The strontium isotopes suggest that the inter-brine was affected by the recharge and mixing of Ca-Cl water and river water, which controlled the spatial distribution and formation of brine hydrochemical types. The analysis of ionic ratios suggest that the inter-brine is derived from salt dissolution and filtration, characterized by poor sealing and short sealing time in the salt-bearing formation. The differences in hydrochemical types and spatial distribution between the north and the south are fundamentally related to the replenishment and mixing of these two sources, which can be summarized as mixed origin model of “dissolution and filtration replenishment + deep replenishment” in BLMH.

Building a model of oil tank water cooling in the case of fire

The object of this study is the process of liquid combustion in spillage, and the subject is the temperature distribution along the wall of a vertical steel tank when it is heated under the thermal influence of fire and cooled by water. A system of equations describing the water cooling of the wall of a vertical steel tank under the conditions of the thermal effect of a fire spilling a flammable liquid has been constructed. The system consists of a heat balance equation for the tank wall, a heat balance equation for the water film flowing over the wall, and a mass balance equation for the water film. The equations take into account the radiative heat exchange with the flame, the environment, the internal space of the tank, as well as the convective heat exchange with the surrounding air, the vapor-air mixture, and the liquid inside the tank, as well as between the water film and the wall. The joint solution to the system of equations makes it possible to determine the temperature distribution along the tank wall and the water film at an arbitrary time point, as well as to determine the thickness and flow rate of the water film at a certain point. The finite difference method was used to solve the system of heat and mass balance equations. It is shown that the insufficient intensity of water supply for cooling leads to boiling of water from the film, as a result of which the wall temperature in such areas can reach 300 °C. A delay in the supply of water, even with sufficient intensity, could lead to the establishment of a film-like mode of boiling. In such a situation, the water film is thrown away from the wall, as a result of which the part of the wall below the film boiling zone remains without cooling. The practical significance of the built model is the possibility of determining the necessary intensity of water supply for cooling the tank and the limit time for the start of cooling

Part-load performance analysis of a modular biomass boiler with a combined heat and power industrial Rankine cycle and supplementary sCO2 Brayton cycle

Abstract The addition of a supplementary high efficiency cycle integrated with an existing steam power cycle may increase energy efficiency and net generation. In this paper, part load performance and operation of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and supplementary supercritical CO2 (sCO2) Brayton cycle is analysed. The aim is to leverage the high efficiency of the sCO2 cycle by retrofitting sCO2 heaters in the existing biomass boiler, increasing net power output and thermal efficiency. With nominal load performance previously investigated, understanding part-load performance and operation is vital to determine cycle feasibility. A quasi-steady-state one dimensional thermofluid network model was used to simulate the integrated cycle performance for loads ranging from 100% to 60%. The model solves the mass, energy, momentum, and species balance equations, capturing detailed component characteristics. Two control methodologies are explored for the sCO2 Brayton cycle, namely inventory control and inventory control combined with throttling valve control. Inventory control is selected as the better performing control strategy for load following, maintaining high thermal efficiency across partial loads. At 60% load, the sCO2 compressor operates near the pseudo-critical point, leading to a sharp decrease in sCO2 cycle capacity, which requires careful management of inventory control. Two sCO2 heater configurations are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. The single heater configuration is preferred to minimise adverse impacts on the Rankine cycle superheaters.

Coating flow of a liquid film with colloidal particles on a vertical fiber

A thin liquid film of colloidal suspension is considered which is spreading down on a vertical cylinder under the effect of gravity. A precursor film model is employed at the three-phase contact line to relieve the stress singularity. The curvature pressure leads to the formation of a capillary ridge at the contact-line. Bulk and surface colloids are assumed to be present in the liquid film. The interfacial pattern is governed by the film evolution equation, obtained by simplifying mass and momentum balance equations within the lubrication assumption, while rapid vertical diffusion is assumed for the advection–diffusion equation of the bulk concentration. Fluid viscosity and diffusivity are considered to be functions of the particle volume fraction. The effects of the bulk and surface colloids on the spreading film dynamics are systematically studied. The presence of bulk colloids leads to the thinning of the capillary ridge for smaller inlet bulk colloid concentrations. On the other hand, a larger inlet bulk concentration leads to the formation of a secondary advancing front behind the capillary ridge in the film profile. A reduced contact point velocity is observed with an increase in the upstream bulk concentration. Surface concentration is found to result in a hump-like structure behind the capillary ridge in the upstream direction due to solutal Marangoni stress. The Marangoni stress also hinders the surface-tension-driven spreading, resulting in a smaller contact line velocity. Reducing the Bond number results in unstable film profiles, which lead to a wave-like structure in the region with no bulk concentration gradients.

Estimating Air Change Rate in Mechanically Ventilated Classrooms Using a Single CO2 Sensor and Automated Data Segmentation.

With a growing emphasis on indoor air quality (IAQ) in educational environments, CO2 monitoring in classrooms has become commonplace. CO2 data can be used to estimate outdoor air change rate (ACH) based on the mass balance principle, which can be further linked to human health, performance, and building energy consumption. This study used a novel machine learning method to automatically segment CO2 concentration time series data into build-up, equilibrium, and decay periods, and then estimated classroom ACH using the corresponding CO2 mass balance equations. This method, applied to 40 classrooms in two mechanically ventilated K-6 schools, generated up to ten ACH estimates per day per classroom. A comparison with ACH calculated using the mechanical ventilation rates with 100% outdoor air reported by the building automation system during the study period reveals a slight underestimation by the decay and build-up methods, while the equilibrium method produced closer estimates. These differences may be attributed to uncertainties in occupancy, activity, CO2 emission rates, and air mixing. This research underscores the potential of leveraging CO2 data for more comprehensive IAQ assessments and highlights the challenges associated with accurately estimating ACH in real-world settings.

Fimbriimonadales performed dissimilatory nitrate reduction to ammonium (DNRA) in an anammox reactor

Bacteria belonging to the order Fimbriimonadales are frequently detected in anammox reactors. However, the principal functions of these bacteria and their potential contribution to nitrogen removal remain unclear. In this study, we aimed to systematically validate the roles of Fimbriimonadales in an anammox reactor fed with synthetic wastewater. High-throughput 16S rRNA gene sequencing analysis revealed that heterotrophic denitrifying bacteria (HDB) were the most abundant bacterial group at the initial stage of reactor operation and the abundance of Fimbriimonadales members gradually increased to reach 38.8 % (day 196). At the end of reactor operation, Fimbriimonadales decreased to 0.9 % with an increase in anammox bacteria. Correlation analysis demonstrated nitrate competition between Fimbriimonadales and HDB during reactor operation. Based on the phylogenetic analysis, the Fimbriimonadales sequences acquired from the reactor were clustered into three distinct groups, which included the sequences obtained from other anammox reactors. Metagenome-assembled genome analysis of Fimbriimonadales allowed the identification of the genes narGHI and nrfAH, responsible for dissimilatory nitrate reduction to ammonium (DNRA), and nrt and nasA, responsible for nitrate and nitrite transport. In a simulation based on mass balance equations and quantified bacterial groups, the total nitrogen concentrations in the effluent were best predicted when Fimbriimonadales was assumed to perform DNRA (R2 = 0.70 and RMSE = 18.9). Moreover, mass balance analysis demonstrated the potential contribution of DNRA in enriching anammox bacteria and promoting nitrogen removal. These results prove that Fimbriimonadales compete with HDB for nitrate utilization through DNRA in the anammox reactor under non-exogenous carbon supply conditions. Overall, our findings suggest that the DNRA pathway in Fimbriimonadales could enhance anammox enrichment and nitrogen removal by providing substrates (nitrite and/or ammonium) for anammox bacteria.

Dynamic Thermomechanical Modeling of Rock‐Ice Avalanches: Understanding Flow Transitions, Water Dynamics, and Uncertainties

AbstractThe rapid melting of glaciers and thawing of permafrost in mountainous regions have heightened the danger of rock‐ice avalanches. These avalanches pose a severe threat due to their potential to transform into water‐saturated debris flows. The catastrophic event in Chamoli, India, on 7 February 2021, illustrates the devastating consequences of such processes. Developing a model capable of predicting the dynamics and extent of these events is imperative for natural hazard science and disaster mitigation. In response, we propose a depth‐averaged rock‐ice avalanche model encompassing four distinct materials: rock, ice, snow, and water. The model integrates crucial physical processes, including frictional heating, phase changes, ground material entrainment, and air‐blast hazards. Through a system of mass and momentum balance equations extended with grain flow and internal energy equations, the model captures heat exchanges and resulting phase changes as the fragmented material flows. Focusing on identifying the primary water source in the flow and testing the model on the 2021 Chamoli event, we quantify water's influence on flow dynamics and regime transitions. However, uncertainties persist in heat transfer physics and quantifying the hydro‐meteorological state of the flow path. Our thermo‐mechanical model enables the simulation of complex avalanches and identifies key flow transitions: powder cloud formation and potential debris flow transformation. The study underscores the pivotal role of water in avalanche dynamics and the challenge of accurately quantifying water content within the flow, necessitating comprehensive ground assessments for effective disaster management.

Estimation of gas diffusion coefficient for gas/oil-saturated porous media systems by use of early-time pressure-decay data: An experimental/numerical approach

This paper presented a novel numerical method for estimating the gas diffusion coefficient based on the early-time pressure-decay data. Experimentally, “flooding–soaking” procedures were developed to perform the gas diffusion in an oil-saturated tight core under different gas phase volume conditions. After flooding, the capillary bundle model was used to calculate the oil–gas contact area. The early-time pressure-decay data of the gas phase were monitored and recorded during the soaking process. Theoretically, a non-equilibrium inner boundary condition coupled with the characteristics of experimental early-time pressure had been incorporated to develop a diffusion model for a gas/oil-saturated tight core system. Based on gas-phase mass balance equations and gas equation of state, the diffusion coefficients were optimized once the discrepancy between experimental data and numerical solutions was minimized. According to the estimated results in this study, the CH4 diffusion coefficients were 3.74 × 10−11 and 3.86 × 10−11 m2/s in tight core saturated with crude oil, respectively. Moreover, the oil–gas contact area significantly impacts the diffusion flux in oil-saturated porous media. Specifically, an additional 10% contact area results in a 75% increase in CH4 diffusion mass. In addition, with the application of our proposed model to CH4/bitumen and CO2/bitumen systems, the diffusion coefficients were in close agreement with the results reported in previous literature, indicating that the proposed model was applicable to both gas/liquid and gas/liquid-saturated porous media systems.

Non-linear biphasic mixture model: Existence and uniqueness results

Abstract This paper is concerned with the development and analysis of a mathematical model that is motivated by interstitial hydrodynamics and tissue deformation mechanics (poro-elasto-hydrodynamics) within an in-vitro solid tumour. The classical mixture theory is adopted for mass and momentum balance equations for a two-phase system. A main contribution of this study is we treat the physiological transport parameter (i.e., hydraulic resistivity) as anisotropic and heterogeneous, thus the governing system is strongly coupled and non-linear. We derived a weak formulation and then formulated the equivalent fixed-point problem. This enabled us to use the Galerkin method, and the classical results on monotone operators combined with the well-known Schauder and Banach fixed-point theorems to prove the existence and uniqueness of results.

Identification and quantitative estimates of groundwater transfers to formerly charophyte dominated marl lakes with radon-222

Interaction with groundwater determines many processes in marl lakes. Net transfer of inorganic carbon helps define their chemical characteristics and determines their unique benthic flora. Nutrient enrichment weakens the biogeochemical buffering mechanisms which help maintain a clear-water state and many small, shallow marl lakes are prone to siltation. Despite hydrological processes being recognised as important for the complex interactions between plants, nutrient availability and physical sediment properties which shape marl lake ecology, groundwater discharge to many of these lakes has never been quantified. The aim of this study was to locate and quantify groundwater transfers to degraded marl lakes in a Special Area of Conservation on the island of Ireland. A RAD7 radon detector identified and measured elevated concentrations of 222Rn in three lakes for quantifying their groundwater influx with a 222Rn mass-balance equation. Conservative estimates of mean daily groundwater discharge to Kilroosky Lough, Drumacrittin Lough, and Dummy's Lough were 143 m3, 502 m3, and 269 m3 respectively. With extrapolation to the entire hydrological year, annual groundwater recharge contributed approximately 47 %, 155 %, and 50 % of the respective lake volumes. The areas within the lakes which were found to have the highest groundwater influence also closely matched the locations where substantial charophyte communities persist suggesting that the two are linked. These findings underline the importance of groundwater transfers for the water budget in small marl lakes and will inform management efforts to mitigate their eutrophication.

Modeling, parameter estimation and optimization of fluidized bed-based alternative ironmaking process for CO2 emission reduction

This study presents the development of a comprehensive process model for simulating and optimizing the FINEX process consists of the multi-stage fluidized beds, the melter-gasifier unit, and a gas recycling system. The model is developed using Pyomo, a Python-based open-source software package that provides extensive capabilities for formulating, solving, and analyzing optimization models. It incorporates heat and mass balance equations and captures a wide range of chemical reactions, including the reduction of iron ore by hydrogen and carbon monoxide, the calcination of carbonate materials, the water–gas shift reaction, and coal gasification and combustion. Unknown parameters in the model, such as heat loss in each reactor, the extent of the calcination reaction, and the outlet gas temperature from the melter-gasifier, were estimated to calibrate the model. These parameters were estimated by solving an optimization problem that minimizes the gap between the model and real plant data. The optimized model was employed to investigate various scenarios for minimizing CO2 emissions in the FINEX process. This included assessing the impact of HBI charging rates, iron ore quality, and the integration of a CCUS unit. For each scenario, an optimization problem was formulated to minimize production costs across a range of CO2 tax levels. The optimal solutions revealed the relationships between process economics and CO2 emissions for each variable.