Integrating the three E’s in wastewater treatment

Water is often the most mispriced and misused component in domestic, industrial and agricultural sectors. The rise in world population and industrialization in developing nations has tremendously increased the demand for water and has resulted in the generation of wastewater which is contaminated with dangerous pollutants and unknown contaminants. Furthermore, if the wastewater is not treated properly the toxic pollutants will leach back into the ground ultimately contaminating the groundwater resources. Thus, wastewater treatment, reuse, and safe disposal have become crucial for sustainable existence. In this review, the different aspects involved in designing efficient and sustainable wastewater treatment systems such as wastewater characterization, stage-wise treatment approach, technology features, modeling methodologies, cost evaluations, and environmental impact assessment are presented and future need for information exchange, interdisciplinary collaborations and convergent research are emphasized

Synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions

Recent advances in metabolic engineering have enabled the production of chemicals via bio-conversion using microbes. However, downstream separation accounts for 60–80% of the total production cost in many cases. Previous work on microbial production of extracellular chemicals has been mainly restricted to microbiology, biochemistry, metabolomics, or techno-economic analysis for specific product examples such as succinic acid, xanthan gum, lycopene, etc. In these studies, microbial production and separation technologies were selected apriori without considering any competing alternatives. However, technology selection in downstream separation and purification processes can have a major impact on the overall costs, product recovery, and purity. To this end, we apply a superstructure optimization based framework that enables the identification of critical technologies and their associated parameters in the synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions. We divide extracellular chemicals into three categories based on their physical properties, such as water solubility, physical state, relative density, volatility, etc. We analyze three major extracellular product categories (insoluble light, insoluble heavy and soluble) in detail and provide suggestions for additional product categories through extension of our analysis framework. The proposed analysis and results provide significant insights for technology selection and enable streamlined decision making when faced with any microbial product that is released extracellularly. The parameter variability analysis for the product as well as the associated technologies and comparison with novel alternatives is a key feature which forms the basis for designing better bioseparation strategies that have potential for commercial scalability and can compete with traditional chemical production methods

Integrating Design Thinking in Chemical Engineering Coursework for Enhanced Student Learning

In the engineering discipline, it is of utmost importance to give value to applied learning because as engineers, we are expected to innovate, and innovations happen when theoretical ideas are implemented successfully. Design thinking is one such approach that can enhance the value of theoretical concepts and motivate the students to visualize their ideas in more meaningful ways. The five stages of design thinking include: (i) Empathize, (ii) Define, (iii) Ideate, (iv) Prototype, and (v) Test. The traditional engineering curriculum focuses on the last four stages and thus leads to a skewed perspective among students with regards to problem definition, formulation, and solution. In this proposed curricular modification, we have developed computational modules as part of the Process Optimization and Experimental Methods in Chemical Engineering courses offered to seniors in the chemical engineering department as electives, which encompass all five stages of design thinking

Systems level roadmap for solvent recovery and reuse in industries

Recovering waste solvent for reuse presents an excellent alternative to improving the greenness of industrial processes. Implementing solvent recovery practices in the chemical industry is necessary, given the increasing focus on sustainability to promote a circular economy. However, the systematic design of recovery processes is a daunting task due to the complexities associated with waste stream composition, techno-economic analysis, and environmental assessment. Furthermore, the challenges to satisfy the desired product specifications, particularly in pharmaceuticals and specialty chemical industries, may also deter solvent recovery and reuse practices. To this end, this review presents a systems-level approach including various methodologies that can be implemented to design and evaluate efficient solvent recovery pathways

A COMPARATIVE STUDY ON PHOTO DEGRADATION OF METHYLENE BLUE DYE EFFLUENT BY ADVANCED OXIDATION PROCESS BY USING TiO 2 /ZnO PHOTO CATALYST

ABSTRACT The effluent from the textile, paper, and food industries containing dye is strongly colored & reveals very harmful effects on living things. In order to reduce water pollution, the degradation of dye into non-toxic form is desirable. The photo catalytic degradation of methylene blue is reported in the present paper. The irradiation of aqueous solution of methylene blue (MB) dye in presence of photo catalyst & UV light were carried out in the batch photo reactor. Titanium dioxide (TiO 2 ) & zinc oxide (ZnO) were used as photo catalyst for the study. The rate decolorisation was estimated from residual concentration spectrophotometrically. Effects of some operating parameters such as the initial P H , H 2 O 2 /COD ratio, & the amounts of catalyst on the degradation of the dyes were investigated. Results show that ZnO is a better alternative photo catalyst compared to TiO 2 in terms of percentage degradation of MB. The maximum decolorizing efficiency was occurred in less than 90min with 50mg/750ml of ZnO catalyst dose

Systematic Design, Optimization, and Sustainability Assessment for Generation of Efficient Wastewater Treatment Networks

Due to population growth and economic development, there has been an increase in global wastewater (WW) generation footprint. There are different technologies associated with the wastewater treatment (WWT) process. The challenge is to select technologies that minimize the cost of treatment, as well as meet purity requirements. Further, there is a need to integrate sustainability analysis to facilitate a holistic decision. With the application of systems engineering, sustainable and cost-effective solutions can be achieved. In this work, we apply systems engineering to generate a sustainable and cost-effective solution. A superstructure was generated by categorizing technologies into four treatment stages. After modeling all functional equations for each technology, an optimization problem was formulated to determine the best path for the treatment process. Mixed-integer non-linear programming (MINLP), which implements a 0–1 binary integer constraint for active/inactive technologies at each stage was used. Sustainability analysis was performed for each representative case study (municipal and pharmaceutical WWT) using the sustainable process index (SPI). The total cost of municipal WWT is 1.92 USD/m3, while that for the pharmaceutical WWT is 3.44 USD/m3. With the treatment of WW, there is a reduction of over 90% ecological burden based on the SPI metric

Design of solvent-assisted plastics recycling: Integrated economics and environmental impacts analysis

In 2018, the United States generated over 35. 7 million tons of plastic waste, with only 8.4% being recycled and the other 91.6% incinerated or disposed of in a landfill. The continued growth of the polymer market has raised concerns over the end of life of plastics. Currently, the waste management system is faced with issues of inefficient sorting methods and low-efficiency recycling methods when it comes to plastics recycling. Mechanical recycling is the commonest recycling method but presents a lower-valued recycled material due to the material incompatibilities introduced via the inefficient sorting methods. Chemical recycling offers a promising alternative as it potentially allows for plastics to maintain their original properties. To that end, there is the need to investigate feasible chemical recycling methods to help mitigate the challenging problem posed by plastics at the end-of-life stage. This work proposes a conceptual solvent-assisted plastics recycling framework based on a superstructure optimization approach. This framework is evaluated using a representative case study to recover Polyethylene Terephthalate (PET). In this case study, it is found that polymer recovery is both economically and environmentally favorable when compared to traditional methods of disposal such as incineration

Teaching sustainable design through simultaneous evaluation of economics and environmental impacts

The ever-increasing human population and industrial growth have posed a considerable burden on existing resources and have led to an increase in environmental pollution and climate change. The Engineering Clinics offered at the Henry M. Rowan College of Engineering at Rowan University is the hallmark of our program that enables our undergraduate students to actively participate in solving real-world problems through collaborative activities. Our graduate students get an opportunity to engage in stakeholder (i.e., industries, federal and regional funding agencies) interactions and student mentoring in conjunction with developing their research ability. Thus, through these synergistic undergraduate-graduate-faculty- stakeholder collaborations this work envisions to develop awareness about sustainable design and environmental impact in the community. The clinic problems include; (i) solvent recovery in process industries, and (ii) systematic synthesis of wastewater treatment (WWT) networks. These problems are important because imprudent use of industrial solvents and water resources have exacerbated the challenges relating to availability, quality as well as safe disposal of harmful solvents and wastewater. Through these challenging and relevant problems, we can teach our students multiple skills such as information collection, selective extraction of valuable content, economic and sustainability evaluation of multiple pathways through mathematical modeling, computer programming, technical writing, and presentation. The overall impact of these efforts is evident in the peer-reviewed conference and journal publications, oral and poster presentations at regional and national conferences, as well as our students choosing careers which value sustainability

Comprehensive review of models and methods for inferences in bio-chemical reaction networks

The key processes in biological and chemical systems are described by networks of chemical reactions. From molecular biology to biotechnology applications, computational models of reaction networks are used extensively to elucidate their non-linear dynamics. The model dynamics are crucially dependent on the parameter values which are often estimated from observations. Over the past decade, the interest in parameter and state estimation in models of (bio-) chemical reaction networks (BRNs) grew considerably. The related inference problems are also encountered in many other tasks including model calibration, discrimination, identifiability, and checking, and optimum experiment design, sensitivity analysis, and bifurcation analysis. The aim of this review paper is to examine the developments in literature to understand what BRN models are commonly used, and for what inference tasks and inference methods. The initial collection of about 700 documents concerning estimation problems in BRNs excluding books and textbooks in computational biology and chemistry were screened to select over 270 research papers and 20 graduate research theses. The paper selection was facilitated by text mining scripts to automate the search for relevant keywords and terms. The outcomes are presented in tables revealing the levels of interest in different inference tasks and methods for given models in the literature as well as the research trends are uncovered. Our findings indicate that many combinations of models, tasks and methods are still relatively unexplored, and there are many new research opportunities to explore combinations that have not been considered—perhaps for good reasons. The most common models of BRNs in literature involve differential equations, Markov processes, mass action kinetics, and state space representations whereas the most common tasks are the parameter inference and model identification. The most common methods in literature are Bayesian analysis, Monte Carlo sampling strategies, and model fitting to data using evolutionary algorithms. The new research problems which cannot be directly deduced from the text mining data are also discussed