Abstract: Intensive livestock farming cannot be uncoupled from the massive production of manure, requiring adequate management to avoid environmental damage. The high carbon, nitrogen and phosphorus content of pig manure enables targeted resource recovery. Here, fifteen integrated scenarios for recovery of water, nutrients and energy are compared in terms of technical feasibility and economic viability. The recovery of refined nutrients with a higher market value and quality, i.e., (NH4)2SO4 for N and struvite for P, coincided with higher net costs, compared to basic composting. The inclusion of anaerobic digestion promoted nutrient recovery efficiency, and enabled energy recovery through electricity production. Co-digestion of the manure with carbon-rich waste streams increased electricity production, but did not result in lower process costs. Overall, key drivers for the selection of the optimal manure treatment scenario will include the market demand for more refined (vs. separated or concentrated) products, and the need for renewable electricity production.

Abstract: Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot directly be adapted to Gielis curves. Indeed, the different nature of their parameters forbids the use of a unified gradient descent approach, which requires initial pre-processings, such as the symmetry detection, and a reliable pose and scale estimation. Furthermore, even the most recent algorithms in the literature remain extremely sensitive to initialization and often fall into local minima in the presence of large missing data. We present a simple evolutionary algorithm which overcomes most of these issues and unifies all of the required operations into a single though efficient approach. The key ideas in this paper are the replacement of the potential fields used for the cost function (closed form) by the shortest Euclidean distance (SED, iterative approach), the construction of cost functions which minimize the shortest distance as well as the curve length using R-functions, and slight modifications of the evolutionary operators. We show that the proposed cost function based on SED and R-function offers the best compromise in terms of accuracy, robustness to noise, and missing data.

Abstract: Deammonification systems are being implemented as cost- and resource-efficient nitrogen removal processes. However, their complexity is a major hurdle towards successful transposition from side- to mainstream application. Merely out-selecting nitrite oxidizing bacteria (NOB) or retaining anammox bacteria (AnAOB) does not guarantee efficient mainstream deammonification. This paper presents for the first time the interactions and synergies between kinetic selection, through management of residual substrates, and physical selection, through separation of solid retention times (SRTs). This allowed the formulation of tangible operational recommendations for successful deammonification. Activity measurements were used to establish retention efficiencies (η) for AnAOB for full-scale cyclones and rotating drum screens installed at a sidestream and mainstream deammonification reactor (Strass, Austria). In the sidestream reactor, using a screen (η = 91%) instead of a cyclone (η = 88%) may increase the capacity by up to 29%. For the mainstream reactor, higher AnAOB retention efficiencies achieved by the screen (η = 72%) compared to the cyclone (η = 42%) induced a prospective increase in capacity by 80–90%. In addition, the switch in combination with bioaugmentation from the sidestream made the process less dependent on nitrite availability, thus aiding in the outselection of NOB. This allowed for a more flexible (intermittent) aeration strategy and a reduced need for tight SRT control for NOB washout. A sensitivity analysis explored expected trends to provide possible operational windows for further calibration. In essence, characterization of the physical selectors at full scale allowed a deeper understanding of operational windows of the process and quantification of capacity, ultimately leading to a more space and energy conservation process.

Abstract: Selective chromium (Cr) leaching from stainless steel slag (SS slag) by alkali roasting followed by water leaching was investigated. The efficiency of the alkali roasting process for Cr leaching was increased by optimizing the mass ratio of alkaline agents (NaOH, and NaOH-NaNO3) to the slag, roasting temperature and time. At the optimum condition (0.67 mass ratio of NaOH to SS slag, 400 degrees C, 2 h) of NaOH roasting, chromium leaching was around 83%, while the matrix material was dissolved only to a limited extent (Si 8.0%). Mechanical activation of the SS slag prior to roasting reduced the optimum NaOH to SS slag mass ratio to 0.4. The addition of NaNO3 as an oxidant to the NaOH salt increased Cr leaching to 89% after roasting at 400 degrees C for 2 h. The remaining Cr phases in the residue were almost exclusively FeCr alloys. Further chromium dissolution from these alloys is prevented by a passivation layer of Fe oxides as shown by SEM/EDS images. Based on these results, a SS slag recycling process is suggested in which roasting-water leaching followed by water washing to remove Cr yields a residue which has potential for application as a construction material. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Monitoring and modelling tools may improve irrigation strategies in precision agriculture. We used non-invasive soil moisture monitoring, a crop growth and a soil hydrological model to predict soil water content fluctuations and crop yield in a heterogeneous sandy grassland soil under supplementary irrigation. The sensitivity of the soil hydrological model to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed after integrating models. Free drainage and incremental constant head conditions were implemented in a lower boundary sensitivity analysis. A time-dependent sensitivity analysis of the hydraulic parameters showed that changes in soil water content are mainly affected by the soil saturated hydraulic conductivity K-s and the Mualem-van Genuchten retention curve shape parameters n and alpha. Results further showed that different parameter optimization strategies (two-, three-, four- or six-parameter optimizations) did not affect the calculated water stress and water content as significantly as does the bottom boundary. In this case, a two-parameter scenario, where K-s was optimized for each layer under the condition of a constant groundwater depth at 135-140 cm, performed best. A larger yield reduction, and a larger number and longer duration of stress conditions occurred in the free drainage condition as compared to constant boundary conditions. Numerical results showed that optimal irrigation scheduling using the aforementioned water stress calculations can save up to 12-22 % irrigation water as compared to the current irrigation regime. This resulted in a yield increase of 4.5-6.5 %, simulated by the crop growth model.

Abstract: This study investigates the impact of lower temperature on short term and long term (down to 10 degrees C) on a completely anoxic anammox granular sludge process. This is the first time granular sludge Anammox is operated in pure anoxic condition in SBR and at low temperature. Conversion performance, kinetic parameters, sludge characteristics and microbial community were analyzed.

Abstract: A new parameterization for size resolved ultrafine particles (UFP) traffic emissions is proposed based on the results of PARTICULATES project (Samaras et al., 2005). It includes the emission factors from the Emission Inventory Guidebook (2006) (total number of particles, #/km/veh), the shape of the corresponding particle size distribution given in PARTICULATES and data for the traffic activity. The output of the model UFPEM (UltraFine Particle Emission Model) is a sum of continuous distributions of ultrafine particles emissions per vehicle type (passenger cars and heavy duty vehicles), fuel (petrol and diesel) and average speed representative for urban, rural and highway driving. The results from the parameterization are compared with measured total number of ultrafine particles and size distributions in a tunnel in Antwerp (Belgium). The measured UFP concentration over the entire campaign shows a close relation to the traffic activity. The modelled concentration is found to be lower than the measured in the campaign. The average emission factor from the measurement is 4.29E + 14 #/km/veh whereas the calculated is around 30% lower. A comparison of emission factors with literature is done as well and in overall a good agreement is found. For the size distributions it is found that the measured distributions consist of three modes Nucleation, Aitken and accumulation and most of the ultrafine particles belong to the Nucleation and the Aitken modes. The modelled Aitken mode (peak around 0.040.05 μm) is found in a good agreement both as amplitude of the peak and the number of particles whereas the modelled Nucleation mode is shifted to smaller diameters and the peak is much lower that the observed. Time scale analysis shows that at 300 m in the tunnel coagulation and deposition are slow and therefore neglected. The UFPEM emission model can be used as a source term in dispersion models.

Abstract: By 2050, the world population will have considerably expanded and the life standard of many will increase, yielding a 50% higher demand in protein (FAO, 2011), and even increases of 82 and 102% for diary and meat products, respectively (Boland et al., 2013). To provide in this increasing demand we are highly dependent on our classical fertilizer to food chain which has a high environmental impact and lacks efficiency. Nutrient losses cause eutrophication and biodiversity loss and the input of resources is already beyond the boundaries of environmental sustainability (Steffen et al., 2015). Phosphate fertilizers are made from phosphate rock (apatite), of which the reserves are predicted to be depleted within 50 100 years if we continue business as usual (Cordell et al., 2009). Next to problems related to the unbalanced geopolitical distribution with dominance in China and Morocco, the decreasing quality of the remaining apatite will result in an increasing environmental impact of fertilizer production. Finally, our traditional food production model requires 30% of all ice-free land, 70% of all available freshwater and produces up to one third of the global greenhouse gas emission, of which 80 to 86% is linked to agricultural production (Vermeulen et al., 2012). To ensure food security, nutrient recovery from waste streams can provide an important strategy. In this context, struvite ( ) crystallisation may be applied to recover phosphorus, along with some nitrogen. Reusing these nutrients as agricultural fertilizer on the field will lead to considerable losses to the environment. In contrast, their use to cultivate micro-organisms, e.g. for single cell protein (SCP), offers to potential of a near perfect conversion efficiency (Moed et al., 2015). At this moment, microalgae represent the most developed type of SCP, and are a promising protein source due to their growth rate, high nutritional quality and extremely high nutrient usage efficiency (Becker, 2007). Reliable solubilisation data are essential to design a technological strategy for struvite dosage in bioreactors for SCP production. The effect on solubility and solubilisation rate of relevant physicochemical parameters was studied experimentally in aqueous solutions. Because pH and temperature greatly affect solubilisation kinetics they were set at a constant value of 7 and 20°C respectively. The effect of some parameters on struvite solubility was already studied (Bhuiyan et al., 2007; Ariyanto et al., 2014; Roncal-Herrero and Oelkers, 2011), but solubilisation rates were not yet considered and pH was not controlled at a constant value. The chemical parameters considered in this study include the concentration of different common ions ( and ), foreign ions ( and the chelating agent ethylenediaminetetraacetic acid, EDTA) present in micro-algal cultivation media as well as ionic strength (as set by NaCl). The main physical parameter included was contact surface, through variation in initial particle size and as well as in struvite dosage concentration.

Abstract: In the present paper, we consider the bulky knots and bulky links that appear after cutting of generalized MöbiusListing GML 4 n bodies (with corresponding radial cross sections square) along different generalized MöbiusListing surfaces GML 2 n situated in it. The aim of this article is to examine the number and geometric structure of independent objects that appear after such a cutting process of GML 4 n bodies. In most cases, we are able to count the indices of the resulting mathematical objects according to the known tabulation for knots and links of small complexity.

Abstract: The research presented here examined at which spatial and temporal resolution urban metabolism should be analysed to generate results that are useful for implementation of urban planning and design interventions aiming at optimization of resource flows. Moreover, it was researched whether a lack of data currently hampers analysing resource flows at this desired level of detail. To facilitate a stakeholder based research approach, the SIRUP tool Space-time Information analysis for Resource-conscious Urban Planning was developed. The tool was applied in a case study of Amsterdam, focused on the investigation of energy and water flows. Results show that most urban planning and design interventions envisioned in Amsterdam require information on a higher spatiotemporal resolution than the resolution of current urban metabolism analyses, i.e., more detailed than the city level and at time steps smaller than a year. Energy-related interventions generally require information on a higher resolution than water-related interventions. Moreover, for the majority of interventions information is needed on a higher resolution than currently available. For energy, the temporal resolution of existing data proved inadequate, for water, data with both a higher spatial and temporal resolution is required. Modelling and monitoring techniques are advancing for both water and energy and these advancements are likely to contribute to closing these data gaps in the future. These advancements can also prove useful in developing new sorts of urban metabolism analyses that can provide a systemic understanding of urban resource flows and that are tailored to urban planning and design.

Abstract: Twenty years ago, mainstream partial nitritation/anammox (PN/A) was conceptually proposed as pivotal for a more sustainable treatment of municipal wastewater. Its economic potential spurred research, yet practice awaits a comprehensive recipe for microbial resource management. Implementing mainstream PN/A requires transferable and operable ways to steer microbial competition as to meet discharge requirements on a year-round basis at satisfactory conversion rates. In essence, the competition for nitrogen, organic carbon and oxygen is grouped into ON/OFF (suppression/promotion) and IN/OUT (wash-out/retention and seeding) strategies, selecting for desirable conversions and microbes. Some insights need mechanistic understanding, while empirical observations suffice elsewhere. The provided methodological R&D framework integrates insights in engineering, microbiome and modeling. Such synergism should catalyze the implementation of energy-positive sewage treatment.