Modelling gas-liquid mass transfer in wastewater treatment : when current knowledge needs to encounter engineering practice and vice versa

Abstract Gas–liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas–liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid–base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas–liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas–liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas–liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas–liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners

Perfil Epidemiológico de mães de pacientes com transtorno do Espectro Autista da Associação de Pais de Autistas do Município de São João Del Rei / Epidemiological profile of mothers of patients with autistic spectrum disorder of the Association of Parents of Autism of the Municipality of São João Del Rei

O autismo hoje é definido como TEA (Transtorno do Espectro Autista) e é conhecido como um estado ou uma condição em que o indivíduo parece estar recluso a si próprio. Pouco se conhece sobre a patogenia do autismo e, com isso, os sintomas ainda são pouco claros. Alguns fatores de riscos podem estar envolvidos como: aspiração de mecônio, lesão ou traumatismo no nascimento, malformação congênita, anemia no lactente e incompatibilidade ABO ou Rh também estão entre os fatores relacionados. Além disso, sabe-se que há um componente genético envolvido para que o transtorno se manifeste. O aumento da prevalência do autismo está possivelmente relacionado às mudanças na conscientização, critérios diagnósticos mais apurados, maior acesso a instrumentos de diagnóstico ou triagem. Este trabalho teve por objetivo analisar a frequência das etiologias para a predição do TEA na ASPAS (Associação de Pais de Autistas de São João del Rei-MG), indicando os fatores de riscos que podem estar associados ao TEA. Foi realizado um estudo envolvendo 16 pacientes de ambos os sexos assistidos pela ASPAS. Os dados coletados foram:sexo, idade materna no parto, idade gestacional no parto, uso de medicação no decorrer da gestação, traumas obstétricos ou complicações periparto, incompatibilidade do sistema ABO(Rh), diabetes mellitus gestacional, doença autoimune na história familiar, infecções no período gestacional, exposição a poluentes atmosféricos, carência de vitamina D no período gestacional, tabagismo no período gestacional, . A análise foi realizada através das distribuições de frequências e porcentagem. Foi possível delinear o perfil epidemiológico dos pacientes, observando os fatores de risco e as características demográficas.Estes resultados poderão auxiliar nas condutas de assistência aos pacientes com TEA de São João del Rei - MG

Performance of algorithms that reconstruct missing transverse momentum in √s= 8 TeV proton-proton collisions in the ATLAS detector

The reconstruction and calibration algorithms used to calculate missing transverse momentum (EmissT ) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton–proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the EmissT reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton–proton collisions at a centre-of-mass energy of 8 TeV during 2012, and results are shown for a data sample corresponding to an integrated luminosity of 20.3fb−1. The simulation and modelling of EmissT in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for EmissT , and estimates of the systematic uncertainties in the EmissT measurements are presented.ATLAS Collaboration, for complete list of authors see dx.doi.org/10.1140/epjc/s10052-017-4780-2Funding: We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [58].</p

Towards a detailed understanding of oxygen transfer in wastewater treatment: the effect of bubble size distribution

Approximately 50 to 80% of the energy cost in biological wastewater treatment is accounted for by the aeration system that provides air to the bioreactor hosting the microorganisms of the activated sludge. These microorganisms require air to convert organic carbon and inorganic nitrogen into waste gasses. In order to reduce the costs associated with wastewater treatment it is therefore crucial to optimise the operation and design of aeration systems. To achieve this, the mechanisms driving the aeration processes need to be understood at a fundamental level. The objective of this doctoral research is to improve the general understanding of oxygen transfer by taking into account the effect of bubble size. In a first part, it is illustrated how computational fluid dynamics can be used to predict the spatial distribution of dissolved oxygen in an aerated river stretch subjected to different scenarios. Next an experimental study was conducted to investigate the effect of activated sludge process conditions, more specifically liquid viscosity and air flow rate, on the spatial dynamics of the bubble size distribution (BSD). A high-speed camera together with appropriate image analysis tools were used to obtain the size distribution of bubbles generated in a cylindrical bubble column under different process conditions and at different heights. These measurement data were subsequently used for the development of a population balance model that predicts the BSD dynamics. Finally, a new modelling approach was suggested that takes into account the BSD to estimate the spatial distribution of the volumetric oxygen transfer coefficient or KLa. Based on the results presented in this doctoral dissertation, it should be concluded that more advanced monitoring and modelling approaches, which take into account the spatial distribution of bubble size, are valuable tools to more accurately estimate aeration efficiency

Detailed off-gas measurements for improved modelling of the aeration performance at the WWTP of Eindhoven

At wastewater treatment plants (WWTPs), the aerobic conversion processes in the bioreactor are driven by the presence of dissolved oxygen (DO). Within these conversion processes, the oxygen transfer is a rate limiting step as well as being the largest energy consumer. Despite this high importance, WWTP models often lack detail on the aeration part. An extensive measurement campaign with off-gas tests was performed at the WWTP of Eindhoven to provide more information on the performance and behaviour of the aeration system. A high spatial and temporal variability in the oxygen transfer efficiency was observed. Applying this gathered system knowledge in the aeration model resulted in an improved prediction of the DO concentrations. Moreover, an important consequence of this was that ammonium predictions could be improved by resetting the ammonium half-saturation index for autotrophs to its default value. This again proves the importance of balancing sub-models with respect to the need for model calibration as well as model predictive power

Towards advanced aeration modelling: from blower to bubbles to bulk

Aeration is an essential component of aerobic biological wastewater treatment and is the largest energy consumer at most water resource recovery facilities. Most modelling studies neglect the inherent complexity of the aeration systems used. Typically, the blowers, air piping, and diffusers are not modelled in detail, completely mixed reactors in a series are used to represent plug-flow reactors, and empirical correlations are used to describe the impact of operating conditions on bubble formation and transport, and oxygen transfer from the bubbles to the bulk liquid. However, the mechanisms involved are very complex in nature and require significant research efforts. This contribution highlights why and where there is a need for more detail in the different aspects of the aeration system and compiles recent efforts to develop physical models of the entire aeration system (blower, valves, air piping and diffusers), as well as adding rigour to the oxygen transfer efficiency modelling (impact of viscosity, bubble size distribution, shear and hydrodynamics). As a result of these model extensions, more realistic predictions of dissolved oxygen profiles and energy consumption have been achieved. Finally, the current needs for further model development are highlighted