Defect engineering on electrocatalysts for sustainable nitrate reduction to ammonia: Fundamentals and regulations.

Electrocatalytic nitrate (NO3 -) reduction to ammonia (NH3) is a "two birds-one stone" method that targets remediation of NO3 --containing sewage and production of valuable NH3. The exploitation of advanced catalysts with high activity, selectivity, and durability is a key issue for the efficient catalytic performance. Among various strategies for catalyst design, defect engineering has gained increasing attention due to its ability to modulate the electronic properties of electrocatalysts and optimize the adsorption energy of reactive species, thereby enhancing the catalytic performance. Despite previous progress, there remains a lack of mechanistic insights into the regulation of catalyst defects for NO3 - reduction. Herein, this review presents insightful understanding of defect engineering for NO3 - reduction, covering its background, definition, classification, construction, and underlying mechanisms. Moreover, the relationships between regulation of catalyst defects and their catalytic activities are illustrated by investigating the properties of electrocatalysts through the analysis of electronic band structure, charge density distribution, and controllable adsorption energy. Furthermore, challenges and perspectives for future development of defects in NO3RR are also discussed, which can help researchers to better understand the defect engineering in catalysts, and also inspire scientists entering into this promising field.

Electrochemical Acid-Base Transport Limitation Principle for Low Electroactive Analyte Sensing in Wastewater Monitoring.

Electrochemical sensing (ES) is crucial for improving data acquisition in wastewater treatment, but obtaining the signal for a low electroactive analyte is challenging. Here, we propose an electrochemical acid-base transport limitation (eABTL) principle for inertness-based sensing, offering a new insight into generating ES signals from an interfacial transport process rather than electron transfer. This principle enables potential ES application for various weak acids and bases (WABs) without reactions themselves. We established an eABTLP method for detecting orthophosphate in solutions as a proof of concept, demonstrating commendable accuracy and precision, and a wide detection range from 10 µM to over 300 mM. Endogenous interferences were identified using 23 weak acids, indicating no significant endogenous interfering factors in typical wastewaters. Of them, volatile fatty acids are the main interference, but their effect can be eliminated by adjusting pH above 6.0. Exogenous factors like anions, cations, ion strength, temperature, organic load, and dissolved oxygen were examined, and most of their effects can be ignored by maintaining consistent analytical procedures between calibration curve and sample. Furthermore, measurement of wastewater samples confirmed the applicability toward domestic wastewater and demonstrated its wide applicability when combined with digestion pretreatment. Given the merits of inertness-based sensing, the eABTL-based methods have the potential to be a crucial part of ES techniques for environmental and industrial monitoring.

Enhancing sensitivity of microbial fuel cell sensors for low concentration biodegradable organic matter detection: Regulation of substrate concentration, anode area and external resistance.

The relatively low sensitivity is an important reason for restricting the microbial fuel cell (MFC) sensors' application in low concentration biodegradable organic matter (BOM) detection. The startup parameters, including substrate concentration, anode area and external resistance, were regulated to enhance the sensitivity of MFC sensors. The results demonstrated that both the substrate concentration and anode area were positively correlated with the sensitivity of MFC sensors, and an external resistance of 210 Ω was found to be optimal in terms of sensitivity of MFC sensors. Optimized MFC sensors had lower detection limit (1 mg/L) and higher sensitivity (Slope value of the linear regression curve was 1.02), which effectively overcome the limitation of low concentration BOM detection. The essential reason is that optimized MFC sensors had higher coulombic efficiency, which was beneficial to improve the sensitivity of MFC sensors. The main impact of the substrate concentration and anode area was to regulate the proportion between electrogens and nonelectrogens, biomass and living cells of the anode biofilm. The external resistance mainly affected the morphology structure and the proportion of living cells of the anode. This study demonstrated an effective way to improve the sensitivity of MFC sensors for low concentration BOM detection.

Assessing the electron transfer and oxygen mass transfer of the oxygen reduction reaction using a new electrode kinetic equation.

The oxygen reduction reaction (ORR), which is widely employed for energy harvesting and environmental purification, requires an electrode kinetic equation for assessing the electron transfer (ET) and oxygen mass transfer (OMT). Herein, we establish a new kinetic equation in conjunction with the ET kinetics and OMT flux, creating a parameter (kO2) characterizing the effect of OMT. This equation allows for the nonlinear fitting of polarizations in full scale and outputs reliable parameters, including α (ET coefficient), j0 (exchange current density) and kO2. The performance is superior to the Tafel equation by outputting reliable values of α and j0, and covers the function of the Koutecky-Levich equation to calculate the electron transfer number (n) as well. Furthermore, by means of kO2, the assessment of OMT becomes available, disclosing the facilitating effect brought about by the porous structure on the ORR rate. Consequently, the new equation provides a reliable and facile approach for assessing the performance of electrode reaction systems and electrocatalysts.

Reactive and microbial inhibitory mechanisms depicting the panoramic view of pH stress effect on common biological nitrification.

pH is a crucial factor of microbial nitrification, which often combines with high-strength ammonium to influence nitrogen removal pathway in wastewater treatment. However, the detailed inhibitory mechanisms of pH stress are not sufficiently disclosed yet. In this study, the pH stress effect on nitrification was comprehensively studied by a set of experiments which identified the reactivity of nitrification processes and activity of nitrifiers, the time dependence of inhibition effect and the hybrid pH stress effect with ammonium. The results revealed two distinct inhibitory mechanisms dominating in alkaline and acid ranges. In alkaline range (pH > 8), pH stress causes physiological damages on microorganisms which is named as microbial inhibition. It has the features of less recoverability of nitrifiers, time-dependent inhibition effect and low pH-tolerance of nitrite oxidation bacteria. Free ammonia enhanced microbial inhibition and greatly promoted nitrite accumulation. A novel reactive inhibition mechanism dominated in acid range (pH < 7) was disclosed. It only impedes ammonia oxidation process (AOP) but not impair microbial activity obviously and the effect is time-independent. The mechanism was clarified from H+ transport because AOP involved H+ production. The H+ transport was impeded under acid stress owing to the decrease of pH gradient across cell membrane. The two mechanisms formed a panoramic view of pH stress effect on nitrification advancing the understanding of nitrifier adaptability and nitritation regulation in wastewater treatment processes.

Tailoring the draw solution chemistry in the integrated electro-Fenton and forward osmosis for enhancing emerging contaminants removal: Performance, DFT calculation and degradation pathway.

Integrated electro-Fenton and forward osmosis is capable to simultaneously separate emerging contaminants and degrade accumulated ones. Thus, an understanding of how draw solution chemistry in forward osmosis influences electro-Fenton is vital for maximizing overall treatment. Therefore, this study aimed to determine the transport behavior of four trace organic contaminants (TrOCs) including Diuron, Atrazine, DEET and Sulfamethoxazole under several influencing factors. Alkalic NaCl severely deteriorated degradation because of the less generation of OH caused by the interfered iron redox cycle. pH-neutral NaCl resulted in the highest reverse salt flux, namely possible largest production of active chlorine, therefore leading to the highest degradation. Compared to NaCl, Na2SO4 presented a significant lower reverse diffusion due to the larger hydrated radius of SO42- than Cl-. Meanwhile, the large consumption of OH by SO42- decreased degradation. Dissolved organic matters in the secondary effluent acted as the scavenger for OH and resulted in a degradation decline. Water extraction resulted from forward osmosis deteriorated degradation kinetics of all compounds except Sulfamethoxazole. On the other hand, Density functional theory calculations and identified intermediates contributed to propose the possible degradation pathways for each TrOC in terms of understanding TrOCs removal mechanism.

Pulse-opencircuit voltammetry: A novel method characterizes bioanode performance from microbe-electrode interfacial processes.

Bioanode is a key component of bioelectrochemical systems, but the methods characterizing its resistance distribution are lacked. We propose a novel pulse-opencircuit voltammetry (POV) based on the analytical principle clarified from the electron flow pathways of microbe-electrode interfacial processes (MEIPs). A dual-cathode cell is designed to provide an experimental platform for ensuring precise data acquisition of bioanodes. This POV method enables to measure steady state polarization curves and ohmic potential loss curves by integrating potentiostatic discharge and current interruption techniques. They determines reaction resistance (RB,act) and ohmic resistance (RB,ohm) of biofilm with the assistance of impedance spectroscopy measuring material resistance. The results of various bioanodes demonstrate that RB,act is the principal limiting factor and its value relies on catabolism state. Whilst RB,ohm is relevant to extracellular electron transfer behaviors. They are two useful indicators of the dynamic evaluation of biofilm. We anticipate that this method together with the cell platform is accessible to users and has wide applications in bioanode construction and electroactive bacteria investigation.

Rapid detection of biodegradable organic matter in polluted water with microbial fuel cell sensor: Method of partial coulombic yield.

The quantification of biodegradable organic matter (BOM) in polluted water plays an essential role for biodegradation-based processing of wastewater and management of water environment. Compared with the traditional detection of five-day biochemical oxygen demand (BOD5), microbial fuel cell (MFC) sensors have shown an advantage for rapid and more accurate BOM assessment in several hours using coulombic yield of MFC as the signal. In this study, we propose a new calculation method that relies on the partial coulombic yield (P-CY) to further shorten the duration of the measurement. The P-CY is the cumulative coulomb at the point at which the voltage acquisition reaches a maximum voltage drop rate. The detection results with the standard GGA solution (a mixture of glucose and glutamic acid) show an enhanced linear relationship ranging from 37.5 mg L-1 to 375 mg L-1 in comparison to conventional methods. Notably, the response time for P-CY is remarkably shortened (0.99 ± 0.18-18.08 ± 0.58 h). The cutoff point for P-CY has more stable electrochemical characteristics, which enhances the accuracy of BOM detection. Furthermore, the validity of our determination of the cutoff point for P-CY is demonstrated by a mathematical model based on the Michaelis-Menten equation. Thus, the P-CY method is viable for the rapid detection of BOM in polluted water.

Characterizing the removal routes of seven pharmaceuticals in the activated sludge process.

The removal routes of pharmaceuticals especially biodegradation routes in the activated sludge process are still unclear. Some studies indicated pharmaceuticals were mainly removed via nitrification process (autotrophic biodegradation), while others suggested pharmaceuticals were mainly removed via COD degradation process (heterotrophic biodegradation). These unclear problems limited the improvements of pharmaceuticals removal. In this study, in order to elucidate three biodegradation routes (nitrification, COD degradation, or both nitrification and COD degradation), autotrophic and heterotrophic reactors were individually developed to separate nitrification and COD degradation form the activated sludge process (mix-trophic process including nitrification and COD degradation). Furthermore, the pharmaceuticals removal routes of adsorption, hydrolysis, and oxidation were also studied. Among six degradable pharmaceuticals, heterotrophic biodegradation and adsorption were the major removal routes. Two sulfonamides of five antibiotics were predominantly removed by COD degradation process, while nitrification and adsorption had no contributions. Adsorption, hydrolysis, nitrification, and COD degradation were the main elimination routes of cefalexin. COD degradation and adsorption were the dominant removal routes of norfloxacin. Tetracycline was mainly removed by the adsorption route, and hydrolysis and oxidation also played a role. For two drugs, ibuprofen was removed mainly via nitrification and COD degradation, and no adsorption occurred. Diclofenac could not be removed at all and was persistent in the aerobic conditions. Kinetic studies showed that biodegradation of the two sulfonamides, cefalexin, norfloxacin, and ibuprofen followed first-order kinetics rather than zero-order or second-order kinetics.

A force-based mechanistic model for describing activated sludge settling process.

Sludge settling as the last step in the biological wastewater treatment process substantially affects the system performance, and thus the design and control optimization of the sludge settling process has been frequently investigated with mathematical modeling tools. So far, these models are developed on the basis of the solid flux theory with numerous parameters and complicated boundary conditions, and their prediction results are often unsatisfactory. In this work, a new force-based mechanical model with five parameters was developed, in which five forces were adopted and Newton's law, rather than the flux theory, was used to describe the sludge settling process. In such a model, the phase interactions were taken into account. New functions of hydrodynamic drag, solids pressure and shear stress were developed. Model validation results demonstrate that both batch and continuous sludge settling processes could be accurately described by this model. The predictions of this model were more accurate than those of flux theory-based models, suggesting its advantages in understanding sludge settling behaviors. In addition, this mechanistic model needed to input 5 parameters and set 1 boundary condition only, and could be directly executed by commercial computational fluid dynamics software. Thus, this force-based model provides a more convenient and useful tool to improve the activated sludge settling design and operation optimization.

Supercritical water oxidation of oil-based drill cuttings.

Oil-based drill cuttings (OBDC) are a typical hazardous solid waste that arises from drilling operations in oil and gas fields. The supercritical water oxidation (SCWO) of OBDC was comprehensively investigated in a batch reactor under the conditions of various oxygen coefficients (OC, 1.5-3.5), temperatures (T, 400-500°C) and reaction times (t, 0.5-10min). Preheating experiments indicated that most of the organic compounds in the initial OBDC sample were distributed within gaseous, oil, aqueous and solid phases, with no more than 9.8% of organic compounds converted into inorganic carbon. All tested variables, i.e., OC, T and t, positively affect the transformation of carbon compounds from the oil and solid phases to the aqueous phase and, ultimately, to CO2. Carbon monoxide is the primary stable intermediate. The total organic carbon (TOC) removal efficiency can reach up to 89.2% within 10min at 500°C. Analysis of the reaction pathways suggests both homogeneous and heterogeneous reactions exist in the reactor. The homogeneous reaction is a typical SCWO reaction that is governed by a free radical mechanism, and the heterogeneous reaction is dominated by mass transfer. The information obtained in this study is useful for further investigation and development of hydrothermal treatment procedures for OBDC.

Mathematical modeling of autotrophic denitrification (AD) process with sulphide as electron donor.

Autotrophic denitrification (AD) plays a critical role in nitrate removal from organic carbon-deficient wastewaters with a high level of nitrogen oxides. However, the AD process is not included in the current denitrification models, which limits the application of AD technology for wastewater treatment. In this work, a kinetic model for AD process involved 4 processes and 5 components with 9 parameters is established to describe the sulphide biooxidation and nitrite removal process. In this model, 4 oxidation-reduction reactions using sulphide as electronic donor in the AD process are taken into account. The model parameters are optimized by fitting data from the experiments with different combinations of sulphide, sulphur, sulphate, nitrate and nitrite at various concentrations. Model calibration and validation results demonstrate that the developed model is able to reasonably describe the removal rates of nitrate, nitrite, sulphide and sulphur in the AD process. The model simulation results also show that the sulphur term (η(S)) in the kinetic equations of nitrate, nitrite, sulphur and sulphate remains constant, rather than being controlled by its own concentration. Furthermore, with this model the products of sulphide biooxidation in the AD process, sulphur and sulphate, and their concentrations can be accurately predicted. Therefore, this model provides a strategy to control the sulphate concentration below the discharge limits or recover sulphur as the main end product from sulphide biooxidation.

A detailed kinetic model for the hydrothermal decomposition process of sewage sludge.

A detailed kinetic model for the hydrothermal decomposition (HTD) of sewage sludge was developed based on an explicit reaction scheme considering exact intermediates including protein, saccharide, NH4(+)-N and acetic acid. The parameters were estimated by a series of kinetic data at a temperature range of 180-300°C. This modeling framework is capable of revealing stoichiometric relationships between different components by determining the conversion coefficients and identifying the reaction behaviors by determining rate constants and activation energies. The modeling work shows that protein and saccharide are the primary intermediates in the initial stage of HTD resulting from the fast reduction of biomass. The oxidation processes of macromolecular products to acetic acid are highly dependent on reaction temperature and dramatically restrained when temperature is below 220°C. Overall, this detailed model is meaningful for process simulation and kinetic analysis.

Modeling the commuting travel activities within historic districts in Chinese cities.

The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters' travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well.