Search Results (18)

Societies are aiming to have a higher ecological consciousness in wastewater treatment operations and achieve a more sustainable future. With this said, global demands for larger quantities of resources and the consequent waste generated will inevitably lead to the exhaustion of current municipal wastewater treatment works. The utilization of biosolids (particularly microbial proteins) from wastewater treatment operations could generate a sustainable bio-adhesive for the wood industry, reduce carbon footprint, mitigate health concerns related to the use of carcinogenic components, and support a more circular economic option for wastewater treatment. A techno-economic analysis for three 10 MGD wastewater treatment operations producing roughly 11,300 dry pounds of biosolids per day, in conjunction with co-feedstock defatted soy flour protein at varying ratios (i.e., 0%, 15%, and 50% wet weight), was conducted. Aspen Capital Cost Estimator V12 was used to design and estimate installed equipment additions for wastewater treatment plant integration into an urban biorefinery process. Due to the mechanical attributes and market competition, the chosen selling prices of each adhesive per pound were set for analysis as USD 0.75 for Plant Option P1, USD 0.85 for Plant Option P2, and USD 1.00 for Plant Option P3. Over a 20-year life, each plant option demonstrated economic viability with high NPVs of USD 107.9M, USD 178.7M, and USD 502.2M and internal rates of return (IRRs) of 24.0%, 29.0%, and 44.2% respectively. The options examined have low production costs of USD 0.14 and USD 0.19 per pound, minimum selling prices of USD 0.42–USD 0.51 per pound, resulting in between 2- and 4-year payback periods. Sensitivity analysis shows the effects biosolid production fluctuations, raw material market price, and adhesive selling price have on economics. The results proved profitable even with large variations in the feedstock and raw material prices, requiring low market selling prices to reach the hurdle rate of examination. This technology is economically enticing, and the positive environmental impact of waste utilization encourages further development and analysis of the bio-adhesive process. Full article

Amid the advancements in computer-based chemical process modeling and simulation packages used in commercial applications aimed at accelerating chemical process design and analysis, there are still certain tasks in design optimization, such as distillation column internals design, that become bottlenecks due to inherent limitations in such software packages. This work demonstrates the use of soft actor-critic (SAC) reinforcement learning (RL) in automating the task of determining the optimal design of trayed multistage distillation columns. The design environment was created using the AspenPlus^® software (version 12, Aspen Technology Inc., Bedford, Massachusetts, USA) with its RadFrac module for the required rigorous modeling of the column internals. The RL computational work was achieved by developing a Python package that allows interfacing with AspenPlus^® and by implementing in OpenAI’s Gymnasium module (version 1.0.0, OpenAI Inc., San Francisco, California, USA) the learning space for the state and action variables. The results evidently show that (1) SAC RL works as an automation approach for the design of distillation column internals, (2) the reward scheme in the SAC model significantly affects SAC performance, (3) column diameter is a significant constraint in achieving column internals design specifications in flooding, and (4) SAC hyperparameters have varying effects on SAC performance. SAC RL can be implemented as a one-shot learning model that can significantly improve the design of multistage distillation column internals by automating the optimization process. Full article

Methyl mercaptan is a sulfur-based chemical found as a co-product in produced natural gas and it causes corrosion in pipelines, storage tanks, catalysts, and solid adsorption beds. To improve the quality of methane produced, researchers have studied the use of metal oxides and aluminum silicates as catalysts for removing mercaptan. However, there are restrictive limitations on the efficiency of metal oxides or aluminum silicates as adsorbents for this application. Therefore, this study investigated the performance of these materials in a fixed-bed reactor with simulated natural gas streams under various operating conditions. The testing procedure includes a detailed assessment of the adsorbent/catalysts by several techniques, such as Braeuer–Emmett–Teller (BET), Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectrometry (EDS), and X-ray Photoelectron Spectroscopy. The results revealed that metal oxides such as copper, manganese, and zinc performed well in methyl mercaptan elimination. The addition of manganese, copper, and zinc oxides to the aluminum silicate surface resulted in a sulfur capacity of 1226 mg S/g of catalyst. These findings provide critical insights for the development of catalysts that combine metal oxides to increase adsorption while reducing the production of byproducts like dimethyl sulfide (DMS) and dimethyl disulfide (DMDS) during methyl mercaptan removal. Full article

This work focused on demonstrating the use of dynamic time warping (DTW) as a metric for the elementary effects computation in Morris-based global sensitivity analysis (GSA) of model parameters in multivariate dynamical systems. One of the challenges of GSA on multivariate time-dependent dynamics is the modeling of parameter perturbation effects propagated to all model outputs while capturing time-dependent patterns. The study establishes and demonstrates the use of DTW as a metric of elementary effects across the time domain and the multivariate output domain, which are all aggregated together via the DTW cost function into a single metric value. Unlike the commonly studied coefficient-based functional approximation and covariance decomposition methods, this new DTW-based Morris GSA algorithm implements curve alignment via dynamic programing for cost computation in every parameter perturbation trajectory, which captures the essence of “elementary effect” in the original Morris formulation. This new algorithm eliminates approximations and assumptions about the model outputs while achieving the objective of capturing perturbations across time and the array of model outputs. The technique was demonstrated using an ordinary differential equation (ODE) system of mixed-order adsorption kinetics, Monod-type microbial kinetics, and the Lorenz attractor for chaotic solutions. DTW as a Morris-based GSA metric enables the modeling of parameter sensitivity effects on the entire array of model output variables evolving in the time domain, resulting in parameter rankings attributed to the entire model dynamics. Full article

Adhesive formulations derived from sustainable feedstocks, like waste-activated sludge and biosolids from wastewater treatment plants, are developed due to protein-based adhesives receiving attention for their low-cost, resourcefulness, and minimal ecological footprint. The protein composition and associated dynamic changes of the adhesive formulations were studied via gel permeation chromatography, which detailed a molecular size distribution of 8.72 × 10⁵ g/mol for the adhesive formulation and 6.89 × 10³ g/mol for the dewatered biosolid base fraction, which confirms the formation of multiple protein functional groups combining to form the larger adhesive molecules. Further analysis determined the types of proteins present in the dewatered biosolids as glutelin, prolamin, globulin, and albumin proteins, with the glutelin proteins as the most prevalent, as thus likely responsible for adhesive formation. The rheological properties of the novel protein adhesive were also studied to interpret the structure of the adhesives, which detailed the findings of viscoelastic properties and flow behaviors of each adhesive in relation to the wastewater treatment plant sample location, which yielded higher flow points, storage moduli, and loss moduli for the dewatered biosolids in comparison to the waste-activated sludge and biosolid adhesives, which correlates with the higher solids content of the dewatered biosolids and potentially cell rupturing when exposed to filtration stress. Full article

Historically, there has been little success with the captive breeding of American alligators (Alligator mississippiensis) for both commercial and conservative purposes. This study, conducted at Golden Ranch in Gheens, LA, between 2016 and 2022, utilized a newly formulated commercial feed and practical dietary supplementation (crawfish waste products) to enhance egg production, fertility, and hatch rates. The primary focus of this study was to compare the outcome of this captive breeding program at Golden Ranch with a program conducted at Rockefeller Refuge (RR) between 1979 and 1984. Notable success was achieved in terms of reproductive performance in comparison to the captive breeding program conducted at Rockefeller Refuge. In this study, 16.1 hatchlings were produced per nest on Golden Ranch from captive breeders. Additionally, when wild nests from Golden Ranch were incubated in the same controlled environmental chambers, they produced an average of 16.3 hatchlings per nest. This comparison emphasizes the similarity in egg production between captive-bred A. mississippiensis and their wild counterparts. The findings of this study suggest that a closed farming system for A. mississippiensis can be established by employing captive breeders derived from artificially incubated wild eggs. Furthermore, American alligators raised in controlled environmental chambers during their initial three years of life demonstrated adaptability to captive conditions and tolerated stocking rates associated with farming conditions and served as breeding stock. Full article

The health risks associated with formaldehyde have propelled relevant stakeholders to push for the production of non-toxic wood adhesives. Several countries including the USA, Japan, and Germany have implemented policies mandating manufacturers to reduce the emissions of formaldehyde to lower levels. Protein adhesives stand out due to their sustainability, renewable sources, and biodegradability. However, they are limited by poor wet strength and water resistance, which affect their wide acceptability in the marketplace. Researchers have developed multiple strategies to mitigate these issues to advance protein adhesives so they may compete more favorably with their petroleum-based counterparts. This review paper explores these strategies including cross-linking, modified fillers, and the removal of hydrophilic content while providing insights into the methodological approaches utilized in recent literature with a comparison of the resultant protein adhesives. Full article

Wastewater (WW) analysis is a critical step in various operations, such as the control of a WW treatment facility, and speeding up the analysis of WW quality can significantly improve such operations. This work demonstrates the capability of neural network (NN) regression models to estimate WW characteristic properties such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia (NH₃-N), total dissolved substances (TDS), total alkalinity (TA), and total hardness (TH) by training on WW spectral reflectance in the visible to near-infrared spectrum (400–2000 nm). The dataset contains samples of spectral reflectance intensity, which were the inputs, and the WW parameter levels (BOD, COD, NH₃-N, TDS, TA, and TH), which were the outputs. Various NN model configurations were evaluated in terms of regression model fitness. The mean-absolute-error (MAE) was used as the metric for training and testing the NN models, and the coefficient of determination (R²) between the model predictions and true values was also computed to measure how well the NN models predict the true values. The highest R² (0.994 for training set and 0.973 for testing set) and lowest MAE (0.573 mg/L BOD, 6.258 mg/L COD, 0.369 mg/L NH₃-N, 6.98 mg/L TDS, 2.586 m/L TA, and 0.014 mmol/L TH) were achieved when NN models were configured for single-variable output compared to multiple-variables output. Hyperparameter grid-search and k-fold cross-validation improved the NN model prediction performance. With online spectral measurements, the trained neural network model can provide non-contact and real-time estimation of WW quality at minimum estimation error. Full article

Biomass is an excellent sustainable carbon neutral energy source, however its use as a coal/petroleum coke substitute in thermal applications poses several challenges. Several inherent properties of biomass including higher heating value (HHV), bulk density, and its hydrophilic and fibrous nature, all contribute to challenges for it to be used as a solid fuel. Torrefaction or mild pyrolysis is a well-accepted thermal pretreatment technology that solves most of the above-mentioned challenges and results in a product with superior coal-like properties. Torrefaction involves the heating of biomass to moderate temperatures typically between 200 °C and 300 °C in a non-oxidizing atmosphere. This study focused on evaluating the influence of torrefaction operating temperature (204–304 °C) and residence time (10–40 min) on properties of pine. Tests were performed on a continuous 0.3 ton/day indirectly heated rotary reactor. The influence of torrefaction operational conditions on pine was evaluated in terms of the composition of torrefied solids, mass yield, energy yield, and HHV using a simulated model developed in Aspen Plus™ software. A kinetic model was established based on the experimental data generated. An increase in torrefaction severity (increasing temperature and residence time) resulted in an increase in carbon content, accompanied with a decrease in oxygen and hydrogen. Results from the simulated model suggest that the solid and energy yields decreased with an increase in temperature and residence time. Solid yield varied from 80% at 204 °C to 68% at 304 °C, and energy yield varied from 99% at 204 °C to 70% at 304 °C, respectively. On the other hand, HHV improved from 22.8 to 25.1 MJ/kg with an increase in temperature at 20 min residence time. Over the range of 10 to 40 min residence time at 260 °C, solid and energy yields varied from 77% to 59% and 79% to 63%, respectively; however the HHV increased by only 3%. Solid yield, energy yield, and HHV simulated data were within the 5% error margin when compared to the experimental data. Validation of the simulation parameters was achieved by the conformance of the experimental and simulation data obtained under the same testing conditions. These simulated parameters can be utilized to study other operating conditions fundamental for the commercialization of these processes. Desirable torrefaction temperature to achieve the highest solid fuel yield can be determined using the energy yield and mass loss data. Full article

The prospect of humans inhabiting planetary bodies is gaining interest among research and development communities, with the moon being considered as a transitory base camp and Mars the next planet humans will inhabit. NASA’s Mission to Mars program is set to have humans inhabiting Mars within on-planet space camps by the Year 2030, which has tremendously increased research and development for space exploration—including research oriented toward human life support in long-term planetary lodging camps. The sustenance of human life on Mars will not be trivial due to the unavailability of an appropriate atmosphere and usable water. This situation requires a self-sustaining human life support system that can provide the basic needs such are breathable air, potable water, food, and energy. The feasibility of sending a payload with resources adequate to support long-term human inhabitation is not reasonable, which means every resource within a Mars space camp is valuable, including human-produced wastes. A biorefinery system that treats wastewater and can also produce valuable products such as oxygen, food, and energy offers a form of circular utilization of valuable resources. To conduct research for such systems requires a wastewater influent that is representative of the wastewater to be generated by the space crew within this isolated, confined environment, which is different from what is generated on Earth due to limited variability in diet, human activity, and lifestyle in this confined area. Collection of actual wastewater influent from an isolated environment supporting humans is challenging. Additionally, to ensure a safe working environment in the laboratory and avoid the imposed threat of handling actual human feces, the proposed synthetic, non-human feces containing wastewater influent formulation offers an easy-to-produce and safer-to-handle option. This paper reviews several synthetic wastewater compositions that have been formulated for space exploration purposes. None of the formulations were found to be realistic nor adequate for a space-camp-type scenario. Thus, the formulation of a synthetic wastewater for simulating a wastewater influent from a human space-based camp is proposed in this paper. In addition, the physical, chemical, and biodegradation characteristics of the final formulation designed are presented to illustrate the value of the proposed influent formulation. Full article

Methanotrophs are bacteria that can consume methane as their sole carbon and energy source to produce a wide variety of high-value products such as lipids, biopolymers, ectoine, and single cell proteins (SCPs). Collected samples from various sources were subjected to DNA extraction followed by 16S rRNA analysis to determine the identity and relative abundance of their microbial population. Several taxa of methanotrophs were detected in the samples including Type I (Methylobacter), Type X (Methylocaldum), Type II (Methylocystis, Methylosinus, and Beijerinckia), and Type III (Verrucomicrobium). This paper expounds the effects of environmental/cultivation conditions on the growth and population of different types of methanotrophs. The results could be used to systematically identify source(s) of natural consortia that can be enriched and developed to produce specific target product(s) under a given cultivation conditions/limitations. Full article

Microalgae are multi-purpose microbial agents due to their capability to efficiently sequester carbon dioxide and produce valuable biomass such as protein and single-cell oils. Formulation and tuning of microalgae kinetics models can significantly contribute to the successful design and operation of microalgae reactors. This work aimed to demonstrate the capability of self-organizing map (SOM) algorithm to elucidate the patterns of parameter rankings in microalgae models subject to stochastic variations of input forcing functions–bioprocess influent component concentration levels. These stochastic variations were implemented on a modeled chemostat with a deterministic microalgae kinetic model consists of ten time-dependent variables and eighteen model parameters. The methodology consists of two major stages: (1) global sensitivity analysis (GSA) on the importance of model parameters with stochastic sampling of bioreactor influent component concentrations, and (2) training of self-organizing maps on the datasets of model parameter rankings derived from the GSA indices. Results reveal that functional principal components analysis can project at least 99% of the time-dependent dynamic patterns of the model variables on B-splines basis functions. The component planes for hexagonal lattice SOMs reveal that the sensitivity rankings some parameters in the algae model tested can be stable over a wide range of variations in the levels of influent component concentrations. Therefore, SOM can be used to reveal the trends in multi-dimensional data arrays arising from the implementation of GSA of kinetic models under stochastic perturbation of input forcing functions. Full article

The rapid increase in the population is expected to result in the approaching of design capacity for many US wastewater treatment plants (WWTPs) over the next decade. WWTPs treat both municipal and industrial wastewater influents, resulting in the production of biosolids after digestion. Biogas, a potential recovered alternative energy source, is also produced as an output from successful anaerobic digestion. More than 7M of dry tons/year of biosolids produced in the US are most often disposed in either landfills or land-applied (~80%). These options are becoming more challenging to implement due to increases in transportation costs and tipping fees, decreases in the availability of landfill/landfarm space, and most importantly, increased regulations. This situation is strongly encouraging WWTPs to find alternatives for the disposal of biosolids. Developing alternative management/disposal options for biosolids are evolving. One of the most attractive alternative option from a sustainability perspective are biorefineries (converts waste to commercial products), which are a fast-growing option given the push toward circular urban source economies (little to no waste generation). Anaerobic digestion has been widely applied in WWTPs to reduce the volume of activated sludge due to its low energy requirements, effective handling of fluctuations due to organic loading rate, relative flexibility with temperature and pH changes, and since biogas is produced that can be transformed into energy. Various pretreatment methods for waste sludges prior to digestion that have been studied to reduce solids production and increase the energetic content of the biogas are presented and discussed. Solids handling and management, which comprises ~60% of the operational cost of a WWTP, is estimated to save more than $100 M annually by achieving at least 20% reduction in the annual production of biosolids within the US. This review incorporates an assessment of various pretreatment methods to optimize the anaerobic digestion of waste sludges with a focus on maximizing both biosolids reduction and biogas quality. Full article

Lactic acid, an important commodity chemical for various applications, is mainly produced through fermentation. In this study, the potential of non-ionic surfactants (an alcohol ethoxylate (AE) and two alcohol alkoxylates (AAs)) as solvents for the extraction of lactic acid from aqueous solutions is reported for the first time. Ternary mixtures containing lactic acid, water, and surfactants were prepared for the assessment. The results indicated that for all the systems, the water–surfactant binary pair exhibits partial immiscibility. Furthermore, the results suggested that with respect to the size of the two-phase region and stability of phases developed, the AE is the suitable solvent for the targeted extraction process. Thus, tie-lines for the system lactic acid + water + AE were then determined to establish the phase diagram of the system at 308.15 K. From the tie-lines, distribution coefficients and separation factors were estimated, which indicated that a compromise between the size and number of extraction units is necessary if AE is to be used as a solvent for lactic acid extraction. The extraction efficiency was estimated to be only about 37–48%. Nevertheless, the biodegradability and non-toxicity of AE makes it a viable solvent for the development of the extractive lactic acid fermentation process. Full article