Karel J. Keesman

Resource management as a key factor for sustainable urban planning

Due to fast urbanization and increasing living standards, the environmental sustainability of our global society becomes more and more questionable. In this historical review we investigate the role of resources management (RM) and urban planning (UP) and propose ways for integration in sustainable development (SD). RM follows the principle of circular causation, and we reflect on to what extent RM has been an element for urban planning. Since the existence of the first settlements, a close relationship between RM, urbanization and technological development has been present. RM followed the demand for urban resources like water, energy, and food. In history, RM has been fostered by innovation and technology developments and has driven population growth and urbanization. Recent massive resource demand, especially in relation to energy and material flows, has altered natural ecosystems and has resulted in environmental degradation. UP has developed separately in response to different questions. UP followed the demand for improved living conditions, often associated to safety, good manufacturing and trading conditions and appropriate sanitation and waste management. In history UP has been a developing research area, especially since the industrial era and the related strong urbanization at the end of the 18th century. UP responded to new emerging problems in urban areas and became increasingly complex. Nowadays, UP has to address many objectives that are often conflicting, including, the urban sustainability. Our current urban un-sustainability is rooted in massive resource consumption and waste production beyond natural limits, and the absence of flows from waste to resources. Therefore, sustainable urban development requires integration of RM into UP. We propose new ways to this integration.

State and parameter estimation in biotechnical batch reactors

Abstract In this paper the problem of state and parameter estimation in biotechnical batch reactors is considered. Models describing the biotechnical process behaviour are usually non-linear with time-varying parameters. Hence, the resulting large dimensions of the augmented state vector, roughly >7, in recursive estimation is a crucial problem. However, by decomposition techniques on the basis of singular perturbation analysis or batch phase analysis one is able to reduce the dimension of the augmented state vector. Furthermore, prior knowledge of parameters and initial states is essential. It is therefore shown how these initial values can be effectively obtained from the data. The approach will be demonstrated by two examples, a wastewater sludge treatment and a beer fermentation process, using real data.

Kinetic models for detection of toxicity in a microbial fuel cell based biosensor

Currently available models describing microbial fuel cell (MFC) polarization curves, do not describe the effect of the presence of toxic components. A bioelectrochemical model combined with enzyme inhibition kinetics, that describes the polarization curve of an MFC-based biosensor, was modified to describe four types of toxicity. To get a stable and sensitive sensor, the overpotential has to be controlled. Simulations with the four modified models were performed to predict the overpotential that gives the most sensitive sensor. These simulations were based on data and parameter values from experimental results under non-toxic conditions. Given the parameter values from experimental results, controlling the overpotential at 250 mV leads to a sensor that is most sensitive to components that influence the whole bacterial metabolism or that influence the substrate affinity constant (Km). Controlling the overpotential at 105 mV is the most sensitive setting for components influencing the ratio of biochemical over electrochemical reaction rate constants (K1), while an overpotential of 76 mV gives the most sensitive setting for components that influence the ratio of the forward over backward biochemical rate constants (K2). The sensitivity of the biosensor was also analyzed for robustness against changes in the model parameters other than toxicity. As an example, the tradeoff between sensitivity and robustness for the model describing changes on K1 (IK1) is presented. The biosensor is sensitive for toxic components and robust for changes in model parameter K2 when overpotential is controlled between 118 and 140 mV under the simulated conditions.

Technical Communique: Optimal parametric sensitivity control of a fed-batch reactor

The paper presents a method to derive an optimal parametric sensitivity controller for optimal estimation of a set of parameters in an experiment. The method is demonstrated for a fed batch bio-reactor case study for optimal estimation of the saturation constant Ks and, albeit intuitively, the parameter combination μmaxX/Y where μmax is the maximum growth rate [g/min], Y is the yield coefficient [g/g], and X is the (constant) biomass [g].

Energy and nutrient recovery for municipal wastewater treatment

Activated sludge systems are commonly used for robust and efficient treatment of municipal wastewater. However, these systems cannot achieve their maximum potential to recover valuable resources from wastewater. This study demonstrates a procedure to design a feasible novel configuration for maximizing energy and nutrient recovery. A simulation model was developed based on literature data and recent experimental research using steady-state energy and mass balances with conversions. The analysis showed that in the Netherlands, proposed configuration consists of four technologies: bioflocculation, cold partial nitritation/Anammox, P recovery, and anaerobic digestion. Results indicate the possibility to increase net energy yield up to 0.24?kWh/m3 of wastewater, while reducing carbon emissions by 35%. Moreover, sensitivity analysis points out the dominant influence of wastewater organic matter on energy production and consumption. This study provides a good starting point for the design of promising layouts that will improve sustainability of municipal wastewater management in the future. We demonstrate a five-step procedure to develop future sewage treatment plants.Steady-state energy and mass balances with conversions help to select scenarios.A promising scenario to treat and recover resources is proposed for Dutch case.Model shows recovery of energy yield of 0.24?kWh/m3 or 39% of organic carbon load.

Pathways of sulfide oxidation by haloalkaliphilic bacteria in limited-oxygen gas lift bioreactors

Physicochemical processes, such as the Lo-cat and Amine-Claus process, are commonly used to remove hydrogen sulfide from hydrocarbon gas streams such as landfill gas, natural gas, and synthesis gas. Biodesulfurization offers environmental advantages, but still requires optimization and more insight in the reaction pathways and kinetics. We carried out experiments with gas lift bioreactors inoculated with haloalkaliphilic sulfide-oxidizing bacteria. At oxygen-limiting levels, that is, below an O(2)/H(2)S mole ratio of 1, sulfide was oxidized to elemental sulfur and sulfate. We propose that the bacteria reduce NAD(+) without direct transfer of electrons to oxygen and that this is most likely the main route for oxidizing sulfide to elemental sulfur which is subsequently oxidized to sulfate in oxygen-limited bioreactors. We call this pathway the limited oxygen route (LOR). Biomass growth under these conditions is significantly lower than at higher oxygen levels. These findings emphasize the importance of accurate process control. This work also identifies a need for studies exploring similar pathways in other sulfide oxidizers such as Thiobacillus bacteria.

Optimal climate control of a storage facility using local weather forecasts

Abstract In this paper, the problem of optimal climate control of a potato storage facility exploiting favourable weather conditions is considered. A receding horizon optimal controller, allowing incorporation of real-time weather forecasts and input/state constraints and based on a reduced-order model, is chosen to evaluate the strategy in simulation. From the results, given the real-time weather forecasts from the Dutch weather office HWS, it appears that a significant reduction of ventilation costs and costs related to the constraint violation is possible when anticipating on future weather conditions.

A recursively identified model for short-term predictions of NH4/NO3 – concentrations in alternating activated sludge processes

Abstract One of the stumbling blocks in the operation of alternatingly aerated activated sludge processes (ASPs) for nitrogen removal is the limited knowledge of both the varying influent composition and the complex dynamics of the biological process. This paper presents a simple physical N-removal model for alternatingly aerated, continuously mixed ASPs. The simplicity is achieved by capturing the slower process dynamics in recursively estimated time-varying model parameters. Both seasonal and diurnal parameter variations are tracked. Also the influent ammonium concentration is treated as a recursively estimated model parameter. The method performs excellently on real data collected from an alternatingly aerated pilot scale ASP fed with municipal wastewater. Simulation of the resulting time-varying model yields accurate and computationally cheap predictions of ammonium and nitrate concentrations in the specific plant under operation over the next hours. Simulation for different control input scenarios can be used to optimize process performance, either manually by operators or automatically by model based optimizing controllers. Another possible application is optimization of the sludge (biomass) concentration, as the estimated parameters contain information regarding process load and concentrations and activities of the N-removing biomass. From this information it can be computed whether there is an excess/shortage of sludge in the reactor.

Theory of pH changes in water desalination by capacitive deionization

In electrochemical water desalination, a large difference in pH can develop between feed and effluent water. These pH changes can affect the long-term stability of membranes and electrodes. Often Faradaic reactions are implicated to explain these pH changes. However, quantitative theory has not been developed yet to underpin these considerations. We develop a theory for electrochemical water desalination which includes not only Faradaic reactions but also the fact that all ions in the water have different mobilities (diffusion coefficients). We quantify the latter effect by microscopic physics-based modeling of pH changes in Membrane Capacitive Deionization (MCDI), a water desalination technology employing porous carbon electrodes and ion-exchange membranes. We derive a dynamic model and include the following phenomena: I) different mobilities of various ions, combined with acid-base equilibrium reactions; II) chemical surface charge groups in the micropores of the porous carbon electrodes, where electrical double layers are formed; and III) Faradaic reactions in the micropores. The theory predicts small pH changes during desalination cycles in MCDI if we only consider phenomena I) and II), but predicts that these pH changes can be much stronger if we consider phenomenon III) as well, which is in line with earlier statements in the literature on the relevance of Faradaic reactions to explain pH fluctuations.

The Urban Harvest Approach as an Aid for Sustainable Urban Resource Planning

Now that more than half of the worlds population lives in cities, improving urban resource cycles is crucial for sustainable urban development. Currently cities are highly dependent on external supplies of water, energy, nutrients, and other materials, while local possibilities of self‐production of such resources are generally overlooked. This article describes a novel method, the urban harvest approach (UHA), its rationale, and the steps toward sustainable urban resource planning. The UHA is based on the urban metabolism concept. Herein, a city is regarded to have multiple potentials in the form of untapped primary and secondary (already used) resources that can be utilized. The UHA works on the principle that urban systems and their direct peri‐urban surroundings can become self‐sufficient by applying three strategies: minimizing demand, minimizing outputs, and multisourcing. An elaboration of the UHA for the resource “water” at the building scale is also presented in this article. A freestanding house in the Netherlands and a similar house in Australia were studied, with a focus on indoor consumption. Results showed a 40% demand reduction when water‐saving technologies were implemented. In both cases, after demand minimization, local resources were sufficient to cover the demand by recycling grey water and harvesting rainwater. These findings confirm that a multimeasure implementation according to the three different strategies is needed to achieve sustainable urban water systems. The UHA helps to structure large influences of urban context on water and other resource cycles as an aid to urban planners and water managers in designing sustainable urban areas.