Approche pour l'identification des causes de la mauvaise décantation des solides biologiques

Les procédés d'épuration biologique à culture libre (boues activées) comprennent habituellement un décanteur qui permet de concentrer les solides biologiques en vue de leur recirculation en tête du réacteur biologique. Lorsque ce décanteur fonctionne mal on observe une perte de solides biologiques (SB), ce qui se traduit par une augmentation de la concentration des matières en suspension (MES) dans l'effluent du décanteur secondaire et par une baisse des performances du procédé d'épuration. Lorsque la concentration de MES dans l'effluent du décanteur secondaire est trop élevée on mesure l'indice de volume des boues (IVB). Un IVB faible indique que les solides biologiques ont de bonnes caractéristiques de décantation de sorte que la cause de la mauvaise efficacité du décanteur est d'ordre physique et peut être identifiée facilement. Lorsque l'IVB est élevé, la mauvaise décantation est alors causée par un désordre de l'écosystème qui se traduit le plus souvent par une croissance excessive d'organismes filamenteux. Les causes et les solutions d'un tel problème sont alors difficiles à identifier. Pour ce travail, les auteurs ont réalisé une importante revue bibliographique dont les résultats sont présentés sous la forme d'un cheminement critique (fig. 1). Dans cette figure, les cases numérotées de 1 à 48 sont liées par des énoncés logiques. Ainsi, en répondant à des questions simples, il est possible de cheminer dans la figure 1 et d'identifier les causes les plus probables du déséquilibre microbiologique ainsi que les solutions qui ont déjà été apportées avec succès. De plus les auteurs ont associé à chaque case une fiche technique (portant le même numéro que la case) sur laquelle sont présentées des explications et la liste des références consultées.Activated sludge is a microbiological aerated sewage treatment process which includes a secondary clarifier to separate the treated effluent from the biological solids. Part of the concentrated solids is recirculated to maintain an adequate concentration of mixed liquor suspended solids (MLSS) In the aerated basin. When the secondary clarifier malfunctions, some biological solids are lost to the effluent : the process efficiency drops and the concentration of suspended solids (SS) increases. When the SS in the effluent is too high the sludge volume index (SVI) must be measured. A low SVI means that the biological solids have good sedimentation characteristics : the problem is thon physical in nature and is easily identified. When the SVI is high, the problem is due to a disturbance of the microbiological ecosystem, which is at the origin of excessive filamentous organism growth. The origins and solutions of such a problem are much harder to find. To this end the authors proceeded with an important review of the literature, the results of which are summarized through a critical path, in figure 1. Files from 1 to 48 are linked by logical statements in such a way that by answering simple questions, one can proceed through the files and identify the must probable cause of the biological disturbance as well as the solution which has already proven successful. Furthermore, the authors have linked each file to a technical file which bears the same number and on which an explanation and references are found.Before proceeding with figure 1 to identify a problem in real life, one must obtain information, resulting from an analysis and observations, with regard to plant effluent, primary clarifier effluent and activated sludge characteristics, including the MLSS concentration. One must also know the chemical oxygen demand (COD), the soluble and total biochemical oxygen demand (BOD5), as well as the nitrogen and phosphorus concentrations in the plant influent. Furthermore, one must also be told of the presence of toxic material or industrial wastes in the sewage and of the fraction of pollution load which is in the form of particulates. Whether sudden changes in the quality of the plant influent have occurred is worth knowing. The concentration of oxygen or hydrogen sulfide in the primary clarifier is also important. One must also gather data related to the activated sludge treatment itself : type of reactor (completely mixed or plug flow), mixed liquor volatile suspended solids (MLVSS) concentration, dissolved oxygen concentration, rate of oxygen uptake and pH. Finally, the results of a microbiological analysis of the sludge are very useful.To illustrate the use of figure 1, let us say that we have the following data :a) Many filamentous microorganisms are present in the MLSS, in particular Microthrix parvicella, type 0092, and Thiothrix sp;b) The rate of dissolved oxygen uptake is 12 mg O2/g of SS - h;c) The rate of COD removal is 0,48 Kg/Kg of SS -d;d) There are no toxic substances in the plant influent;e) There are no abrupt changes in plant influent quality;f) The pHs of the plant influent and of the MLSS are 7,0 and 6,8 respectively;g) The ammonia nitrogen concentration of the plant influent is 1,2 mg/L (N);h) The phosphorus concentration of the plant influent is 4,4 mg/L (P);i) The total and soluble BOD5 concentrations of the plant influent are 400 and 80 mg/L respectively.With this information, we are ready to proceed through figure 1. From file one, one goes to file 2, since the rate of oxygen uptake is sufficient. Otherwise, we would have proceeded to file 32. The reactor being completely mixed, the next step is file 3, where it is said that, because of the low soluble BOD5 concentration one must go to file 9, where we find a fast of filamentous microarganisms which may be responsible for the disturbance. Since two of these microorganisms are effectively present in the mixed liquor suspended solids (MLSS), Microthrox parvicella and type 0092, we are invited to go to file 35, where it is stated that someone has already solved a similar problem by creating a modified contact zone to increase the substrats (organic matter) concentration around the microbiological flocs. The third filamentous microorganism is not identified in file 9. As a second possibility one may assume, in file 2. That the mixing is not complete, which is often the case. With the help of information and results of analyses already available, we proceed, through file 4, 14, 15 and 16, to file 20 where Thiothrixsp is included in the microorganisms listed. File 20 is linked to file 41, where it is said that the controlled addition of nitrogen in the plant influent has already been used to solve this type of problem.The critical path presented in this article is the result of an elaborate study. It may be used as a tool to identify the causes of bad biological flocs sedimentation in the secondary clarifier and select solutions that have already been used successfully

An examination of the temporal and geographical patterns of psychiatric emergency service use by multiple visit patients as a means for their early detection

<p>Abstract</p> <p>Background:</p> <p>Frequent users of the psychiatric emergency service (PES) place a heavy burden upon the mental health care delivery system. The aim of this study was to identify distinct temporal or geographical patterns of PES use by these patients as potential markers for their early detection.</p> <p>Methods:</p> <p>Diagnostic profiles were obtained for patients making an intermediate (4 to 10) or a high (11 or more) number of visits to a general hospital PES in Montreal (Canada) between 1985 and 2004. Between-group comparisons were made with regards to several parameters. These included the time intervals between consecutive visits, visit clustering (single, repeating, and the time interval to the first cluster) and visits made to three other services where data was similarly acquired from 2002 to 2004.</p> <p>Results:</p> <p>The two multiple visit groups differed with regards to diagnostic profiles and actual time between consecutive visits (significantly shorter in patients with 11 or more visits). Patients with 11 or more visits were more likely to have a single cluster (3 or more visits/3 months) or repeating clusters (4 visits/3 months) in their patterns of use. Personality disorders were more prevalent in patients with single clusters as they were, along with schizophrenia, in those with repeating clusters. In addition, clusters were found to occur sufficiently early so as to be potentially useful as markers for early detection. Ten percent of those with 11 or more visits and 16% of those with an intermediate number of visits frequented at least one other PES. A small number of patients, primarily those with substance abuse, made over 50% of their visits to other services.</p> <p>Conclusion:</p> <p>Temporal and geographical patterns of use differed significantly between the multiple visit groups. These patterns, combined with distinct diagnostic profiles, could potentially lead to the more rapid identification and treatment of specific sub-groups of multiple visit patients.</p

Regulatory Constructivism: Application of Q Methodology in Italy and China

Conventional view holds that beliefs play an important role in the development of regulations but there is little evidence to support this claim. We use Comparative Q Methodology to systematically map out and compare the beliefs of public officers in China and Italy, two countries with contrasting sets of institutions but have both adopted similar ideas about integrated water resource management. We find some similarities and differences in the beliefs of public officers in both countries. In particular, we find that in both countries beliefs on the regulation of water utilities are diverse and fragmented on issues such as ownership structure of water utilities, how water infrastructure development should be funded, and how tariffs should be regulated. Our findings have two implications for theory, methods and practice. First, the Q methodology is a useful tool for systematically mapping out the beliefs of regulators and managers. Second, systematically mapping out beliefs will help facilitate the development of an alternative regime of regulation such as negotiated rule making. This alternative regime can provide substantial benefits such as more efficient rule making, more cost effective enforcement and compliance, and more equitable in terms of balancing the interests of stakeholders

A multidisciplinary systematic literature review on frailty: Overview of the methodology used by the Canadian Initiative on Frailty and Aging

<p>Abstract</p> <p>Background</p> <p>Over the past two decades, there has been a substantial growth in the body of literature on frailty in older persons. However, there is no consensus on its definition or the criteria used to identify frailty. In response to this lack of consensus, the Canadian Initiative on Frailty and Aging carried out a set of systematic reviews of the literature in ten areas of frailty research: biological basis; social basis; prevalence; risk factors; impact; identification; prevention and management; environment and technology; health services; health and social policy. This paper describes the methodology that was developed for the systematic reviews.</p> <p>Methods</p> <p>A Central Coordination Group (CCG) was responsible for developing the methodology. This involved the development of search strategies and keywords, article selection processes, quality assessment tools, and guidelines for the synthesis of results. Each review was conducted by two experts in the content area, with the assistance of methodologists and statisticians from the CCG.</p> <p>Results</p> <p>Conducting a series of systematic literature reviews involving a range of disciplines on a concept that does not have a universally accepted definition posed several conceptual and methodological challenges. The most important conceptual challenge was determining what would qualify as literature on frailty. The methodological challenges arose from our goal of structuring a consistent methodology for reviewing literature from diverse fields of research. At the outset, certain methodological guidelines were deemed essential to ensure the validity of all the reviews. Nevertheless, it was equally important to permit flexibility in the application of the proposed methodology to capture the essence of frailty research within the given fields.</p> <p>Conclusion</p> <p>The results of these reviews allowed us to establish the status of current knowledge on frailty and promote collaboration between disciplines. Conducting systematic literature reviews in health science that involve multiple disciplines is a mechanism to facilitate interdisciplinary collaboration and a more integrated understanding of health. This initiative highlighted the need for further methodological development in the performance of multidisciplinary systematic reviews.</p

Deriving utility scores for co-morbid conditions: a test of the multiplicative model for combining individual condition scores

BACKGROUND: The co-morbidity of health conditions is becoming a significant health issue, particularly as populations age, and presents important methodological challenges for population health research. For example, the calculation of summary measures of population health (SMPH) can be compromised if co-morbidity is not taken into account. One popular co-morbidity adjustment used in SMPH computations relies on a straightforward multiplicative combination of the severity weights for the individual conditions involved. While the convenience and simplicity of the multiplicative model are attractive, its appropriateness has yet to be formally tested. The primary objective of the current study was therefore to examine the empirical evidence in support of this approach. METHODS: The present study drew on information on the prevalence of chronic conditions and a utility-based measure of health-related quality of life (HRQoL), namely the Health Utilities Index Mark 3 (HUI3), available from Cycle 1.1 of the Canadian Community Health Survey (CCHS; 2000–01). Average HUI3 scores were computed for both single and co-morbid conditions, and were also purified by statistically removing the loss of functional health due to health problems other than the chronic conditions reported. The co-morbidity rule was specified as a multiplicative combination of the purified average observed HUI3 utility scores for the individual conditions involved, with the addition of a synergy coefficient s for capturing any interaction between the conditions not explained by the product of their utilities. The fit of the model to the purified average observed utilities for the co-morbid conditions was optimized using ordinary least squares regression to estimate s. Replicability of the results was assessed by applying the method to triple co-morbidities from the CCHS cycle 1.1 database, as well as to double and triple co-morbidities from cycle 2.1 of the CCHS (2003–04). RESULTS: Model fit was optimized at s = .99 (i.e., essentially a straightforward multiplicative model). These results were closely replicated with triple co-morbidities reported on CCHS 2000–01, as well as with double and triple co-morbidities reported on CCHS 2003–04. CONCLUSION: The findings support the simple multiplicative model for computing utilities for co-morbid conditions from the utilities for the individual conditions involved. Future work using a wider variety of conditions and data sources could serve to further evaluate and refine the approach