Development of quantitative methods for sustainability assessment in process industry

The increasing aversion to technological risks of the society requires the development of inherently safer and environmentally friendlier processes, besides assuring the economic competitiveness of the industrial activities. The different forms of impact (e.g. environmental, economic and societal) are frequently characterized by conflicting reduction strategies and must be holistically taken into account in order to identify the optimal solutions in process design. Though the literature reports an extensive discussion of strategies and specific principles, quantitative assessment tools are required to identify the marginal improvements in alternative design options, to allow the trade-off among contradictory aspects and to prevent the “risk shift”. In the present work a set of integrated quantitative tools for design assessment (i.e. design support system) was developed. The tools were specifically dedicated to the implementation of sustainability and inherent safety in process and plant design activities, with respect to chemical and industrial processes in which substances dangerous for humans and environment are used or stored. The tools were mainly devoted to the application in the stages of “conceptual” and “basic design”, when the project is still open to changes (due to the large number of degrees of freedom) which may comprise of strategies to improve sustainability and inherent safety. The set of developed tools includes different phases of the design activities, all through the lifecycle of a project (inventories, process flow diagrams, preliminary plant lay-out plans). The development of such tools gives a substantial contribution to fill the present gap in the availability of sound supports for implementing safety and sustainability in early phases of process design. The proposed decision support system was based on the development of a set of leading key performance indicators (KPIs), which ensure the assessment of economic, societal and environmental impacts of a process (i.e. sustainability profile). The KPIs were based on impact models (also complex), but are easy and swift in the practical application. Their full evaluation is possible also starting from the limited data available during early process design. Innovative reference criteria were developed to compare and aggregate the KPIs on the basis of the actual sitespecific impact burden and the sustainability policy. Particular attention was devoted to the development of reliable criteria and tools for the assessment of inherent safety in different stages of the project lifecycle. The assessment follows an innovative approach in the analysis of inherent safety, based on both the calculation of the expected consequences of potential accidents and the evaluation of the hazards related to equipment. The methodology overrides several problems present in the previous methods proposed for quantitative inherent safety assessment (use of arbitrary indexes, subjective judgement, build-in assumptions, etc.). A specific procedure was defined for the assessment of the hazards related to the formations of undesired substances in chemical systems undergoing “out of control” conditions. In the assessment of layout plans, “ad hoc” tools were developed to account for the hazard of domino escalations and the safety economics. The effectiveness and value of the tools were demonstrated by the application to a large number of case studies concerning different kinds of design activities (choice of materials, design of the process, of the plant, of the layout) and different types of processes/plants (chemical industry, storage facilities, waste disposal). An experimental survey (analysis of the thermal stability of isomers of nitrobenzaldehyde) provided the input data necessary to demonstrate the method for inherent safety assessment of materials.

Anaerobic oxidation of ethanol over spinel mixed oxides: the first step in the steam-iron process for H2 production

The future hydrogen demand is expected to increase, both in existing industries (including upgrading of fossil fuels or ammonia production) and in new technologies, like fuel cells. Nowadays, hydrogen is obtained predominantly by steam reforming of methane, but it is well known that hydrocarbon based routes result in environmental problems and besides the market is dependent on the availability of this finite resource which is suffering of rapid depletion. Therefore, alternative processes using renewable sources like wind, solar energy and biomass, are now being considered for the production of hydrogen. One of those alternative methods is the so-called “steam-iron process��� which consists in the reduction of a metal-oxide by hydrogen-containing feedstock, like ethanol for instance, and then the reduced material is reoxidized with water to produce “clean” hydrogen (water splitting). This kind of thermochemical cycles have been studied before but currently some important facts like the development of more active catalysts, the flexibility of the feedstock (including renewable bio-alcohols) and the fact that the purification of hydrogen could be avoided, have significantly increased the interest for this research topic. With the aim of increasing the understanding of the reactions that govern the steam-iron route to produce hydrogen, it is necessary to go into the molecular level. Spectroscopic methods are an important tool to extract information that could help in the development of more efficient materials and processes. In this research, ethanol was chosen as a reducing fuel and the main goal was to study its interaction with different catalysts having similar structure (spinels), to make a correlation with the composition and the mechanism of the anaerobic oxidation of the ethanol which is the first step of the steam-iron cycle. To accomplish this, diffuse reflectance spectroscopy (DRIFTS) was used to study the surface composition of the catalysts during the adsorption of ethanol and its transformation during the temperature program. Furthermore, mass spectrometry was used to monitor the desorbed products. The set of studied materials include Cu, Co and Ni ferrites which were also characterized by means of X-ray diffraction, surface area measurements, Raman spectroscopy, and temperature programmed reduction.

Geometrical optimization of a short-stem hip implant for the reduction of proximal stress shielding (ottimizzazione geometrica di uno stelo corto di protesi d?anca per la riduzione della schermatura del carico prossimale)

Nowadays the number of hip joints arthroplasty operations continues to increase because the elderly population is growing. Moreover, the global life expectancy is increasing and people adopt a more active way of life. For this reasons, the demand of implant revision operations is becoming more frequent. The operation procedure includes the surgical removal of the old implant and its substitution with a new one. Every time a new implant is inserted, it generates an alteration in the internal femur strain distribution, jeopardizing the remodeling process with the possibility of bone tissue loss. This is of major concern, particularly in the proximal Gruen zones, which are considered critical for implant stability and longevity. Today, different implant designs exist in the market; however there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. The aim of the study is to investigate the stress shielding effect generated by different implant design parameters on proximal femur, evaluating which ranges of those parameters lead to the most physiological conditions.

Reduction of inappropriate medications among older nursing-home residents: a nurse-led, pre/post-design, intervention study

Background: Medication-related problems are common in the growing population of older adults and inappropriate prescribing is a preventable risk factor. Explicit criteria such as the Beers criteria provide a valid instrument for describing the rate of inappropriate medication (IM) prescriptions among older adults. Objective: To reduce IM prescriptions based on explicit Beers criteria using a nurse-led intervention in a nursing-home (NH) setting. Study Design: The pre/post-design included IM assessment at study start (pre-intervention), a 4-month intervention period, IM assessment after the intervention period (post-intervention) and a further IM assessment at 1-year follow-up. Setting: 204-bed inpatient NH in Bern, Switzerland. Participants: NH residents aged ≥60 years. Intervention: The intervention included four key intervention elements: (i) adaptation of Beers criteria to the Swiss setting; (ii) IM identification; (iii) IM discontinuation; and (iv) staff training. Main Outcome Measure: IM prescription at study start, after the 4-month intervention period and at 1-year follow-up. Results: The mean±SD resident age was 80.3±8.8 years. Residents were prescribed a mean±SD 7.8±4.0 medications. The prescription rate of IMs decreased from 14.5% pre-intervention to 2.8% post-intervention (relative risk [RR] = 0.2; 95% CI 0.06, 0.5). The risk of IM prescription increased nonstatistically significantly in the 1-year follow-up period compared with post-intervention (RR = 1.6; 95% CI 0.5, 6.1). Conclusions: This intervention to reduce IM prescriptions based on explicit Beers criteria was feasible, easy to implement in an NH setting, and resulted in a substantial decrease in IMs. These results underscore the importance of involving nursing staff in the medication prescription process in a long-term care setting.

Role of catechol in the radical reduction of B-alkylcatecholboranes in presence of methanol

Mechanistic investigations on the previously reported reduction of B-alkylcatecholboranes in the presence of methanol led to the disclosure of a new mechanism involving catechol as a reducing agent. More than just revising the mechanism of this reaction, we disclose here the surprising role of catechol, a chain breaking antioxidant, which becomes a source of hydrogen atoms in an efficient radical chain process

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Solar thermal decoupled water electrolysis process I: Proof of concept

A new concept for a solar thermal electrolytic process was developed for the production of H-2 from water. A metal oxide is reduced to a lower oxidation state in air with concentrated solar energy. The reduced oxide is then used either as an anode or solute for the electrolytic production of H-2 in either an aqueous acid or base solution. The presence of the reduced metal oxide as part of the electrolytic cell decreases the potential required for water electrolysis below the ideal 1.23 V required when H-2 and O-2 evolve at 1 bar and 298 K. During electrolysis, H-2 evolves at the cathode at 1 bar while the reduced metal oxide is returned to its original oxidation state, thus completing the H-2 production cycle. Ideal sunlight-to-hydrogen thermal efficiencies were established for three oxide systems: Fe2O3-Fe3O4, Co3O4-CoO, and Mn2O3-Mn3O4. The ideal efficiencies that include radiation heat loss are as high or higher than corresponding ideal values reported in the solar thermal chemistry literature. An exploratory experimental study for the iron oxide system confirmed that the electrolytic and thermal reduction steps occur in a laboratory scale environment.

Diagnostic criteria for hematopoietic stem cell transplant-associated microangiopathy: results of a consensus process by an International Working Group

BACKGROUND AND OBJECTIVES: There are no widely accepted criteria for the definition of hematopoietic stem cell transplant -associated microangiopathy (TAM). An International Working Group was formed to develop a consensus formulation of criteria for diagnosing clinically significant TAM. DESIGN AND METHODS: The participants proposed a list of candidate criteria, selected those considered necessary, and ranked those considered optional to identify a core set of criteria. Three obligatory criteria and four optional criteria that ranked highest formed a core set. In an appropriateness panel process, the participants scored the diagnosis of 16 patient profiles as appropriate or not appropriate for TAM. Using the experts' ratings on the patient profiles as a gold standard, the sensitivity and specificity of 24 candidate definitions of the disorder developed from the core set of criteria were evaluated. A nominal group technique was used to facilitate consensus formation. The definition of TAM with the highest score formed the final PROPOSAL. RESULTS: The Working Group proposes that the diagnosis of TAM requires fulfilment of all of the following criteria: (i) >4% schistocytes in blood; (ii) de novo, prolonged or progressive thrombocytopenia (platelet count <50 x 109/L or 50% or greater reduction from previous counts); (iii) sudden and persistent increase in lactate dehydrogenase concentration; (iv) decrease in hemoglobin concentration or increased transfusion requirement; and (v) decrease in serum haptoglobin. The sensitivity and specificity of this definition exceed 80%. INTERPRETATION AND CONCLUSIONS: The Working Group recommends that the presented criteria of TAM be adopted in clinical use, especially in scientific trials.

Limited open reduction and internal fixation of displaced intra-articular fractures of the calcaneum

The extended lateral L-shaped approach for the treatment of displaced intra-articular fractures of the calcaneum may be complicated by wound infection, haematoma, dehiscence and injury to the sural nerve. In an effort to reduce the risk of problems with wound healing a technique was developed that combined open reduction and fixation of the joint fragments and of the anterior process with percutaneous reduction and screw fixation of the tuberosity. A group of 24 patients with unilateral isolated closed Sanders type II and III fractures was treated using this technique and compared to a similar group of 26 patients managed by the extended approach and lateral plating. The operation was significantly shorter (p < 0.001) in the first group, but more minor secondary procedures and removal of heel screws were necessary. There were no wound complications in this group, whereas four minor complications occurred in the second group. The accuracy and maintenance of reduction, and ultimate function were equivalent.

Sediment yield reduction in an agricultural watershed

With proper application of Best Management Practices (BMPs), the impact from the sediment to the water bodies could be minimized. However, finding the optimal allocation of BMP can be difficult, since there are numerous possible options. Also, economics plays an important role in BMP affordability and, therefore, the number of BMPs able to be placed in a given budget year. In this study, two methodologies are presented to determine the optimal cost-effective BMP allocation, by coupling a watershed-level model, Soil and Water Assessment Tool (SWAT), with two different methods, targeting and a multi-objective genetic algorithm (Non-dominated Sorting Genetic Algorithm II, NSGA-II). For demonstration, these two methodologies were applied to an agriculture-dominant watershed located in Lower Michigan to find the optimal allocation of filter strips and grassed waterways. For targeting, three different criteria were investigated for sediment yield minimization, during the process of which it was found that the grassed waterways near the watershed outlet reduced the watershed outlet sediment yield the most under this study condition, and cost minimization was also included as a second objective during the cost-effective BMP allocation selection. NSGA-II was used to find the optimal BMP allocation for both sediment yield reduction and cost minimization. By comparing the results and computational time of both methodologies, targeting was determined to be a better method for finding optimal cost-effective BMP allocation under this study condition, since it provided more than 13 times the amount of solutions with better fitness for the objective functions while using less than one eighth of the SWAT computational time than the NSGA-II with 150 generations did.

Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set

Stepwise uncertainty reduction (SUR) strategies aim at constructing a sequence of points for evaluating a function  f in such a way that the residual uncertainty about a quantity of interest progressively decreases to zero. Using such strategies in the framework of Gaussian process modeling has been shown to be efficient for estimating the volume of excursion of f above a fixed threshold. However, SUR strategies remain cumbersome to use in practice because of their high computational complexity, and the fact that they deliver a single point at each iteration. In this article we introduce several multipoint sampling criteria, allowing the selection of batches of points at which f can be evaluated in parallel. Such criteria are of particular interest when f is costly to evaluate and several CPUs are simultaneously available. We also manage to drastically reduce the computational cost of these strategies through the use of closed form formulas. We illustrate their performances in various numerical experiments, including a nuclear safety test case. Basic notions about kriging, auxiliary problems, complexity calculations, R code, and data are available online as supplementary materials.

Mindfulness-based cognitive therapie for depression (MBCT) in clinical practice - baseline patient characteristics, process and outcome

Introduction: Mindfulness based cognitive therapy for depression (MBCT) has shown to be effective for the reduction of depressive relapse. However, additional information regarding baseline patient characteristics and process features related to positive response could be helpful both for the provision of MBCT in clinical practice, as well as for its further development. Method: Baseline characteristics, process data, and immediate outcome (symptom change, change in attitudes and trait mindfulness) of 108 patients receiving MBCT in routine care were recorded. A newly developed self-report measure (Daily Mindfulness Scale, DMS) was applied daily during the MBCT program. Additionally, patients filed daily reports on their mindfulness practice. There was no control group available. Results: Patients with more severe initial symptoms indicated greater amounts of symptom improvement, but did not show great rates of dropout from the MBCT intervention. Younger age was related to higher rates of dropout. Contradictory to some previous data, patients with lower levels of initial trait mindfulness showed greater improvement in symptoms, even after controlling for initial levels of symptoms. Adherence to daily mindfulness practice was high. Consistent with this result, the duration of daily mindfulness practice was not related to immediate outcome. Process studies using multivariate time series analysis revealed a specific role of daily mindfulness in reducing subsequent negative mood. Conclusions: Within the range of patient present in this study and the given study design, results support the use of MBCT in more heterogeneous groups. This demanding intervention was well tolerated by patients with higher levels of symptoms, and resulted in significant improvements regarding residual symptoms. Process-outcome analyses of initial trait mindfulness and daily mindfulness both support the crucial role of changes in mindfulness for the effects of MBCT.

Predicting Physical Activity in Adolescents: The Role of Compensatory Health Beliefs within the Health Action Process Approach

Objective: Compensatory health beliefs (CHBs), defined as beliefs that healthy behaviours can compensate for unhealthy behaviours, may be one possible factor hindering people in adopting a healthier lifestyle. This study examined the contribution of CHBs to the prediction of adolescents’ physical activity within the theoretical framework of the Health Action Process Approach (HAPA). Design: The study followed a prospective survey design with assessments at baseline (T1) and two weeks later (T2). Method: Questionnaire data on physical activity, HAPA variables and CHBs were obtained twice from 430 adolescents of four different Swiss schools. Multilevel modelling was applied. Results: CHBs added significantly to the prediction of intentions and change in intentions, in that higher CHBs were associated with lower intentions to be physically active at T2 and a reduction in intentions from T1 to T2. No effect of CHBs emerged for the prediction of self-reported levels of physical activity at T2 and change in physical activity from T1 to T2. Conclusion: Findings emphasise the relevance of examining CHBs in the context of an established health behaviour change model and suggest that CHBs are of particular importance in the process of intention formation.

The Process-Outcome Mindfulness Effects in Trainees (PrOMET) study: protocol of a pragmatic randomized controlled trial

Background Mindfulness has its origins in an Eastern Buddhist tradition that is over 2500 years old and can be defined as a specific form of attention that is non-judgmental, purposeful, and focused on the present moment. It has been well established in cognitive-behavior therapy in the last decades, while it has been investigated in manualized group settings such as mindfulness-based stress reduction and mindfulness-based cognitive therapy. However, there is scarce research evidence on the effects of mindfulness as a treatment element in individual therapy. Consequently, the demand to investigate mindfulness under effectiveness conditions in trainee therapists has been highlighted. Methods/Design To fill in this research gap, we designed the PrOMET Study. In our study, we will investigate the effects of brief, audiotape-presented, session-introducing interventions with mindfulness elements conducted by trainee therapists and their patients at the beginning of individual therapy sessions in a prospective, randomized, controlled design under naturalistic conditions with a total of 30 trainee therapists and 150 patients with depression and anxiety disorders in a large outpatient training center. We hypothesize that the primary outcomes of the session-introducing intervention with mindfulness elements will be positive effects on therapeutic alliance (Working Alliance Inventory) and general clinical symptomatology (Brief Symptom Checklist) in contrast to the session-introducing progressive muscle relaxation and treatment-as-usual control conditions. Treatment duration is 25 therapy sessions. Therapeutic alliance will be assessed on a session-to-session basis. Clinical symptomatology will be assessed at baseline, session 5, 15 and 25. We will conduct multilevel modeling to address the nested data structure. The secondary outcome measures include depression, anxiety, interpersonal functioning, mindful awareness, and mindfulness during the sessions. Discussion The study results could provide important practical implications because they could inform ideas on how to improve the clinical training of psychotherapists that could be implemented very easily; this is because there is no need for complex infrastructures or additional time concerning these brief session-introducing interventions with mindfulness elements that are directly implemented in the treatment sessions.

Bench-scale evaluation of the activated sludge process for treatment of a high -strength chemical plant wastewater

A bench-scale treatability study was conducted on a high-strength wastewater from a chemical plant to develop an alternative for the existing waste stabilization pond treatment system. The objective of this study was to determine the treatability of the wastewater by the activated sludge process and, if treatable, to determine appropriate operating conditions, and to evaluate the degradability of bis(2-chloroethyl)ether (Chlorex) and benzene in the activated sludge system. Four 4-L Plexi-glass, complete mixing, continuous flow activated sludge reactors were operated in parallel under different operating conditions over a 6-month period. The operating conditions examined were hydraulic retention time (HRT), sludge retention time (SRT), nutrient supplement, and Chlorex/benzene spikes. Generally the activated sludge system treating high-strength wastewater was stable under large variations of organic loading and operating conditions. At an HRT of 2 days, more than 90% removal efficiency with good sludge settleability was achieved when the organic loading was less than 0.4 g BOD$\sb5$/g MLVSS/d or 0.8 g COD/g MLVSS/d. At least 20 days of SRT was required to maintain steady operation. Phosphorus addition enhanced the performance of the system especially during stressed operation. On the average, removals of benzene and Chlorex were 73-86% and 37-65%, respectively. In addition, the low-strength wastewater was treatable by activated sludge process, showing more than 90% BOD removal at a HRT of 0.5 days. In general, the sludge had poor settling characteristics. The aerated lagoon process treating high-strength wastewater also provided significant organic reduction, but did not produce an acceptable effluent concentration. ^