RESEARCH
Advanced Radioactive Waste Treatment using Nanostructured Hybrid Composites
Effective and safe management of wastes are primary requirements for the nuclear industry per se. These wastes whether solid, liquid or gaseous arise from every stage of the nuclear fuel cycle and are treated to ensure they comply with stringent regulatory standards before final disposal into the environment. In the early period of nuclear energy the emphasis was largely on the treatment of operational wastes but over the past two decades the need to accommodate wastes arising from the decommissioning of nuclear installations has gradually increased and in the next two decades will become the prime focus. Significant components of decommissioning are post operation clean out (POCO) and the decontamination of plants/equipment to minimise dose uptake to operatives. It is crucial now and in the future that an integrated approach to waste management has been/is developed to ensure the overall decommissioning process produces an end product that can be disposed of safely with the minimal impact on the environment and is acceptable to all stakeholders. It is imperative that effective treatments of liquors arising from POCO, decontamination and even operational activities are developed and employed. These treatments will require a solid matrix as the final product that is stable, resistant to environment pressures for many centuries. Our approach is to develop low cost nanostructured hybrid materials that can be employed in-situ that have high capacities for a variety of radionuclides from various aqueous matrices that are stable and capable of being incorporated without conditioning into encapsulants such as glass or cement for disposal.
Two-dimensional MXenes and Their Applications in wastewater treatment
MXenes are a new family of 2D transition metal carbide/nitride nanosheets analogous to graphene. MXenes are produced by etching of ‘‘A’’ layer from MAX phases. MAX phases (Mn+1AXn; n = 1, 2, or 3) are ternary carbides and nitrides composed of early transition metals (M), group IIIA and IVA elements (A) in the periodic table, and a carbon and/or nitrogen component (X). Unique structural, electrical, chemical properties, hydrophilic behavior, and tunable chemistry, MXenes has number of potential applications in environmental pollution remediation specifically wastewater treatment process. MXene are highly desirable in decontamination of wastewater heavy metals polluted due to large surface area, hydrophilicity and easily available active binding sites.
Ti3C2Tx MXenes exhibited reductive properties for copper during adsorption process. Upon liquid/liquid phase interaction with Cu2+ partial reduction of Cu2+ into Cu+ was observed. We recently synthesized MXene composite (MGMX) with magnetic properties and applied for the removal mercuric ions. MGMX unveiled unprecedented ultrahigh removal capability for mercury in aqueous solutions. Due to conductive properties and self-restructure ability, a heterostructural 001-TiO2/MXene was synthesized via control oxidation. We have explored catalytic behaviors of 001-TiO2-Ti3C2 heterostructure for the adsorption coupled with photodegradation of antiepileptic drug Carbamazepine.
Photocatalytic degradation of emerging micropollutants
Photocatalysis is the occurrence of a reaction in presence of light and the suitable catalyst that stimulates the photochemical reaction. The catalyst is activated by the incident light and carries on the chemical reaction producing highly reactive oxidative radicals which attack the pollutant molecules by bond formation and bond breaking triggering the degradation of the harmful parent molecule. Photocatalysis is the promising approach for water purification. The basic research includes the application of this technology in developing a new understanding of the complex heterogeneous photochemical process of the catalytic systems in aqueous environment.
Bioelectrochemical systems
Bioelectrochemical systems (BESs), such as microbial fuel cells (MFCs) and microbial electrolysis cells (MECs), have been widely investigated for their novel aspects and potential environmental advantages. The basic principal of such systems is the oxidation of organics from wastewater by electrochemically active microorganisms, and, consequently, the microorganisms transport electrons resulting from this oxidation to the anode via extracellular electron transfer. Then, the electrons are transported to the cathode through an external circuit, where they are used for oxygen reduction and electricity generation (in MFCs) or other useful product formation, such as hydrogen (H2), caustics (NaOH/KOH), and hydrogen peroxide (H2O2) (with additional power supply in MECs). Overpotential can be substantially brought down with electrochemically active bacteria (EAB) at the anode/cathode, hence inexpensive materials (such as graphite and carbon) can be employed as electrodes in BESs. A number of valuable oxidation or reduction reactions demonstrating the versatility of BESs have been described. Bioelectricity generation can be achieved by using a large range of biodegradable fuels, including substrates such as acetate and organics in wastewater. Meanwhile, some studies have reported that BESs could greatly promote the removal of refractory organics such as pyridine, quinoline, indole, furfural, and phenol. At the BES’s anode, co-substrates provide electrons for the degradation of biorefractory compounds at higher rates, along with electricity production (in MFC) or useful product formation (in MEC); therefore, both electricity production/useful product formation and the degradation of biorefractory compounds are major focuses of BESs.
In one of our recent studies, a bioelectrochemical system (BES) enriched with sulfate-reducing bacteria (SRB) in the anodic chamber was proposed and evaluated for the biodegradation of recalcitrant chlorinated phenol, electricity generation, and production of hydrogen peroxide (H2O2), which is a very strong oxidizing agent and often used for the degradation of complex organics.
Our focus is the photodegradation of organic pollutants under both solar and UV-light. We improve catalytic property of the metal oxide nanomaterials by structural modification, perform their characterizations and apply them to degrade pollutants. The design of cost-effective and reusable photocatalyst and optimization of the process parameters are other goals of our research group. Our accomplished work includes the synthesis of 3D porous reduced graphene/TiO2 aerogel for the photocatalytic degradation of persistent organic pollutant where incorporation of polymer in this aerogel was proved to be very effective for enhanced reusability of the hybrid composite. Besides, heterogeneous Fenton-like Fe3O4 catalyst was also synthesized with graphene loading in a controlled way to obtain higher degradation performance for persistent volatile compounds. Moreover, the TiO2/MXene catalyst synthesized in an in-situ hydrothermal process discovered a potential way for the application of MXenes in photocatalytic wastewater treatment.
Multivariate Statistical Process Control
Traditionally, WWTPs have been monitored by using time series charts where operators can view the different variables as historical trends and judge deviation from the norm. However, as the number of variables increases from modern industrial plants with well-equipped computerized measurement devices, it becomes difficult or impossible to interpret all measurement data simultaneously. Therefore, a more systematic way to handle and analyze data is needed to effectively extract relevant information for monitoring and supervision. In recent years, multivariate statistical process control such as principal component analysis (PCA) and partial least squares (PLS) have become increasingly useful in many industrial fields. Those techniques can be used to extract the state of the system from the huge volume of the stored data via applications of statistical methods. Primary objectives of PCA and PLS are data summarization, classification of variables, outlier detection, early warning of potential malfunctions and fault identification.
In the previous research, when PCA was applied to a full-scale industrial wastewater treatment process a gradual deterioration of process performance was very effectively monitored. In addition, adaptive multiblock MPCA has been proposed. The method combines elements of adaptive MPCA and multiblock PCA in order to monitor non-stationary batch processes. Dividing the process data into meaningful blocks based on process knowledge makes it possible to localize the cause of a detected fault and disturbance in a decentralized manner and allows to clearly indicate the faulty variables. The proposed adaptive multiblock monitoring method was successfully applied to a pilot-scale sequencing batch reactor for biological wastewater treatment. The use of multivariate statistical approaches by applying PCA methods will be an increasingly stringent operational requirement for water/wastewater treatment works in the near future.
Dynamic Modeling and Simulation of Wastewater Treatment Plants
As demands on water quality become more and more stringent, more advanced treatment systems will be required to comply with (lowering) standards not only for organic carbon, but also for nitrogen and phosphorus (nutrient) levels. With biological nutrient removal typically being the most economic treatment technology, rather complex process configurations have resulted. Hence the increased complexity due to this process integration has become a major driving force for the use of mathematical models. The need to make the best use of previous investments by upgrading existing plants for handling increased loads or extension with nutrient removal capability is another incentive for the use of models.
A carefully calibrated activated sludge model, based on Activated Sludge Model (ASM1, ASM2, ASM2d and ASM3) proposed by the IWA (formerly IAWPRC, then IAWQ) task group, can be very useful to increase the understanding about the complex interactions that occur between the different microbial communities in an activated sludge plant and to examine influence of process modifications on treatment process efficiency. Dynamic models are therefore used for scenario evaluations aiming at the optimization of activated sludge process and used to exploit the possibility for a treatment plant renovation that aims at a minimization of the renovation cost.
Recently, I participated, in collaboration with Prof. Vanrolleghem’s group at Gent Univ., developing and applying a calibration protocol to full-scale WWTPs in the Netherlands to propose operational modifications. Model-based scenarios were applied to evaluate the influence of treatment plant design modifications on treatment plant performance. From this experience, model-based scenario analysis could lead to an efficient reuse of existing treatment plant components, resulting in reduced renovation costs.