Combining sampling, profiling, remote sensing and modelling to efficiently monitoring estuarine and coastal water quality

Monitoring of coastal and estuarine water quality has been traditionally performed by sampling with subsequent laboratory analysis. This has the disadvantages of low spatial and temporal resolution and high cost. In the last decades two alternative techniques have emerged to overcome this drawback: profiling and remote sensing. Profiling using multi-parameter sensors is now in a commercial stage. It can be used, tied to a boat, to obtain a quick “picture” of the system. The spatial resolution thus increases from single points to a line coincident with the boat track. The temporal resolution however remains unchanged since campaigns and resources involved are basically the same. The need for laboratory analysis was reduced but not eliminated because parameters like nutrients, microbiology or metals are still difficult to obtain with sensors and validation measurements are still needed. In the last years the improvement in satellite resolution has enabled its use for coastal and estuarine water monitoring. Although spatial coverage and resolution of satellite images in the present is already suitable to coastal and estuarine monitoring, temporal resolution is naturally limited to satellite passages and cloud cover. With this panorama the best approach to water monitoring is to integrate and combine data from all these sources. The natural tools to perform this integration are numerical models. Models benefit from the different sources of data to obtain a better calibration. After calibration they can be used to extend spatially and temporally the methods resolution. In Algarve (South of Portugal) a monitoring effort using this approach is being undertaken. The monitoring effort comprises five different locations including coastal waters, estuaries and coastal lagoons. The objective is to establish the base line situation to evaluate the impact of Waste Water Treatment Plants design and retrofitting. The field campaigns include monthly synoptic profiling, using an YSI 6600 multi-parameter system, laboratory analysis and fixed stations. The remote sensing uses ENVISAT\MERIS Level 2 Full Resolution data. This data is combined and used with the MOHID modelling system to obtain an integrate description of the systems. The results show the limitations of each method and the ability of the modelling system to integrate the results and to produce a comprehensive picture of the system.

Fungal contamination in two Portuguese wastewater treatment plants

The presence of filamentous fungi was detected in wastewater and air collected at wastewater treatment plants (WWTP) from several European countries. The aim of the present study was to assess fungal contamination in two WWTP operating in Lisbon. In addition, particulate matter (PM) contamination data was analyzed. To apply conventional methods, air samples from the two plants were collected through impaction using an air sampler with a velocity air rate of 140 L/min. Surfaces samples were collected by swabbing the surfaces of the same indoor sites. All collected samples were incubated at 27°C for 5 to 7 d. After lab processing and incubation of collected samples, quantitative and qualitative results were obtained with identification of the isolated fungal species. For molecular methods, air samples of 250 L were also collected using the impinger method at 300 L/min airflow rate. Samples were collected into 10 ml sterile phosphate-buffered saline with 0.05% Triton X-100, and the collection liquid was subsequently used for DNA extraction. Molecular identification of Aspergillus fumigatus and Stachybotrys chartarum was achieved by real-time polymerase chain reaction (RT-PCR) using the Rotor-Gene 6000 qPCR Detection System (Corbett). Assessment of PM was also conducted with portable direct-reading equipment (Lighthouse, model 3016 IAQ). Particles concentration measurement was performed at five different sizes: PM0.5, PM1, PM2.5, PM5, and PM10. Sixteen different fungal species were detected in indoor air in a total of 5400 isolates in both plants. Penicillium sp. was the most frequently isolated fungal genus (58.9%), followed by Aspergillus sp. (21.2%) and Acremonium sp. (8.2%), in the total underground area. In a partially underground plant, Penicillium sp. (39.5%) was also the most frequently isolated, also followed by Aspergillus sp. (38.7%) and Acremonium sp. (9.7%). Using RT-PCR, only A. fumigatus was detected in air samples collected, and only from partial underground plant. Stachybotrys chartarum was not detected in any of the samples analyzed. The distribution of particle sizes showed the same tendency in both plants; however, the partially underground plant presented higher levels of contamination, except for PM2.5. Fungal contamination assessment is crucial to evaluating the potential health risks to exposed workers in these settings. In order to achieve an evaluation of potential health risks to exposed workers, it is essential to combine conventional and molecular methods for fungal detection. Protective measures to minimize worker exposure to fungi need to be adopted since wastewater is the predominant internal fungal source in this setting.

Biodiversity of amoebae and amoebae-resisting bacteria in a drinking water treatment plant

The complex ecology of free-living amoebae (FLA) and their role in spreading pathogenic microorganisms through water systems have recently raised considerable interest. In this study, we investigated the presence of FLA and amoebae-resisting bacteria (ARB) at various stages of a drinking water plant fed with river water. We isolated various amoebal species from the river and from several points within the plant, mostly at early steps of water treatment. Echinamoeba- and Hartmannella-related amoebae were mainly recovered in the drinking water plant whereas Acanthamoeba- and Naegleria-related amoebae were recovered from the river water and the sand filtration units. Some FLA isolates were recovered immediately after the ozonation step, thus suggesting resistance of these microorganisms to this disinfection procedure. A bacterial isolate related to Mycobacterium mucogenicum was recovered from an Echinamoeba-related amoeba isolated from ozone-treated water. Various other ARB were recovered using co-culture with axenic Acanthamoeba castellanii, including mycobacteria, legionella, Chlamydia-like organisms and various proteobacteria. Noteworthy, a new Parachlamydia acanthamoebae strain was recovered from river water and from granular activated carbon (GAC) biofilm. As amoebae mainly multiply in sand and GAC filters, optimization of filter backwash procedures probably offers a possibility to better control these protists and the risk associated with their intracellular hosts

Water Quality Variation, its Influence on Drinking Water Treatment and Remedial Measures - A Case Study of Peechi reservoir, Thrissur, Kerala

The Kerala Water Authority requested the School of Environmental Studies to carry out investigations on the mechanism of sporadic mobilization of iron and odour in the raw water drawn to the drinking water treatment plant. The currently used treatment process failed to remove iron completely. This led to problems in the filter and complaints of taste and colour due to iron in the finished water. The sporadic nature of the problem itself made the trouble shooting difficult. The problem was looked in from three points of view. 1. Influence of environmental (climatic) conditions on the dynamics of the relevant basin of the reservoir. 2. Influence of the physical dynamics on the physico — chemical quality of water. 3. Identification of cost-effective treatment processes to suit the existing plant. Since the problem emerged only during the post- monsoon to pre-monsoon months, a related problem was investigated, namely, influence of anions on the oxidation of Fe(II) in natural waters by air. This is presented in Part II of the dissertation.

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelation between variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically the compliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process

DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied to wastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take the necessary actions to restore the system’s performance. These decisions are often based both on physical, chemical, microbiological principles (suitable to be modelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AI architecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

Conceptual design of wastewater treatment plants using multiple objectives

La implementació de la Directiva Europea 91/271/CEE referent a tractament d'aigües residuals urbanes va promoure la construcció de noves instal·lacions al mateix temps que la introducció de noves tecnologies per tractar nutrients en àrees designades com a sensibles. Tant el disseny d'aquestes noves infraestructures com el redisseny de les ja existents es va portar a terme a partir d'aproximacions basades fonamentalment en objectius econòmics degut a la necessitat d'acabar les obres en un període de temps relativament curt. Aquests estudis estaven basats en coneixement heurístic o correlacions numèriques provinents de models determinístics simplificats. Així doncs, moltes de les estacions depuradores d'aigües residuals (EDARs) resultants van estar caracteritzades per una manca de robustesa i flexibilitat, poca controlabilitat, amb freqüents problemes microbiològics de separació de sòlids en el decantador secundari, elevats costos d'operació i eliminació parcial de nutrients allunyant-les de l'òptim de funcionament. Molts d'aquestes problemes van sorgir degut a un disseny inadequat, de manera que la comunitat científica es va adonar de la importància de les etapes inicials de disseny conceptual. Precisament per aquesta raó, els mètodes tradicionals de disseny han d'evolucionar cap a sistemes d'avaluació mes complexos, que tinguin en compte múltiples objectius, assegurant així un millor funcionament de la planta. Tot i la importància del disseny conceptual tenint en compte múltiples objectius, encara hi ha un buit important en la literatura científica tractant aquest camp d'investigació. L'objectiu que persegueix aquesta tesi és el de desenvolupar un mètode de disseny conceptual d'EDARs considerant múltiples objectius, de manera que serveixi d'eina de suport a la presa de decisions al seleccionar la millor alternativa entre diferents opcions de disseny. Aquest treball de recerca contribueix amb un mètode de disseny modular i evolutiu que combina diferent tècniques com: el procés de decisió jeràrquic, anàlisi multicriteri, optimació preliminar multiobjectiu basada en anàlisi de sensibilitat, tècniques d'extracció de coneixement i mineria de dades, anàlisi multivariant i anàlisi d'incertesa a partir de simulacions de Monte Carlo. Això s'ha aconseguit subdividint el mètode de disseny desenvolupat en aquesta tesis en quatre blocs principals: (1) generació jeràrquica i anàlisi multicriteri d'alternatives, (2) anàlisi de decisions crítiques, (3) anàlisi multivariant i (4) anàlisi d'incertesa. El primer dels blocs combina un procés de decisió jeràrquic amb anàlisi multicriteri. El procés de decisió jeràrquic subdivideix el disseny conceptual en una sèrie de qüestions mes fàcilment analitzables i avaluables mentre que l'anàlisi multicriteri permet la consideració de diferent objectius al mateix temps. D'aquesta manera es redueix el nombre d'alternatives a avaluar i fa que el futur disseny i operació de la planta estigui influenciat per aspectes ambientals, econòmics, tècnics i legals. Finalment aquest bloc inclou una anàlisi de sensibilitat dels pesos que proporciona informació de com varien les diferents alternatives al mateix temps que canvia la importància relativa del objectius de disseny. El segon bloc engloba tècniques d'anàlisi de sensibilitat, optimització preliminar multiobjectiu i extracció de coneixement per donar suport al disseny conceptual d'EDAR, seleccionant la millor alternativa un cop s'han identificat decisions crítiques. Les decisions crítiques són aquelles en les que s'ha de seleccionar entre alternatives que compleixen de forma similar els objectius de disseny però amb diferents implicacions pel que respecte a la futura estructura i operació de la planta. Aquest tipus d'anàlisi proporciona una visió més àmplia de l'espai de disseny i permet identificar direccions desitjables (o indesitjables) cap on el procés de disseny pot derivar. El tercer bloc de la tesi proporciona l'anàlisi multivariant de les matrius multicriteri obtingudes durant l'avaluació de les alternatives de disseny. Específicament, les tècniques utilitzades en aquest treball de recerca engloben: 1) anàlisi de conglomerats, 2) anàlisi de components principals/anàlisi factorial i 3) anàlisi discriminant. Com a resultat és possible un millor accés a les dades per realitzar la selecció de les alternatives, proporcionant més informació per a una avaluació mes efectiva, i finalment incrementant el coneixement del procés d'avaluació de les alternatives de disseny generades. En el quart i últim bloc desenvolupat en aquesta tesi, les diferents alternatives de disseny són avaluades amb incertesa. L'objectiu d'aquest bloc és el d'estudiar el canvi en la presa de decisions quan una alternativa és avaluada incloent o no incertesa en els paràmetres dels models que descriuen el seu comportament. La incertesa en el paràmetres del model s'introdueix a partir de funcions de probabilitat. Desprès es porten a terme simulacions Monte Carlo, on d'aquestes distribucions se n'extrauen números aleatoris que es subsisteixen pels paràmetres del model i permeten estudiar com la incertesa es propaga a través del model. Així és possible analitzar la variació en l'acompliment global dels objectius de disseny per a cada una de les alternatives, quines són les contribucions en aquesta variació que hi tenen els aspectes ambientals, legals, econòmics i tècnics, i finalment el canvi en la selecció d'alternatives quan hi ha una variació de la importància relativa dels objectius de disseny. En comparació amb les aproximacions tradicionals de disseny, el mètode desenvolupat en aquesta tesi adreça problemes de disseny/redisseny tenint en compte múltiples objectius i múltiples criteris. Al mateix temps, el procés de presa de decisions mostra de forma objectiva, transparent i sistemàtica el perquè una alternativa és seleccionada en front de les altres, proporcionant l'opció que més bé acompleix els objectius marcats, mostrant els punts forts i febles, les principals correlacions entre objectius i alternatives, i finalment tenint en compte la possible incertesa inherent en els paràmetres del model que es fan servir durant les anàlisis. Les possibilitats del mètode desenvolupat es demostren en aquesta tesi a partir de diferents casos d'estudi: selecció del tipus d'eliminació biològica de nitrogen (cas d'estudi # 1), optimització d'una estratègia de control (cas d'estudi # 2), redisseny d'una planta per aconseguir eliminació simultània de carboni, nitrogen i fòsfor (cas d'estudi # 3) i finalment anàlisi d'estratègies control a nivell de planta (casos d'estudi # 4 i # 5).

Knowledge-based modelling and simulation of operational problems of microbiological origin in wastewater treatment plants

The activated sludge and anaerobic digestion processes have been modelled in widely accepted models. Nevertheless, these models still have limitations when describing operational problems of microbiological origin. The aim of this thesis is to develop a knowledge-based model to simulate risk of plant-wide operational problems of microbiological origin.For the risk model heuristic knowledge from experts and literature was implemented in a rule-based system. Using fuzzy logic, the system can infer a risk index for the main operational problems of microbiological origin (i.e. filamentous bulking, biological foaming, rising sludge and deflocculation). To show the results of the risk model, it was implemented in the Benchmark Simulation Models. This allowed to study the risk model's response in different scenarios and control strategies. The risk model has shown to be really useful providing a third criterion to evaluate control strategies apart from the economical and environmental criteria.

Noise levels and hearing conservation in a water treatment facility

This paper describes a study assessing the sound levels and noise exposures of a municipal water treatment plant to determine the level of employee noise exposure dosages and to make any necessary recommendations regarding reducing the risk of noise induced hearing loss in employees.

A review of the potential impacts of climate change on surface water quality

It is now accepted that some human-induced climate change is unavoidable. Potential impacts on water supply have received much attention, but relatively little is known about the concomitant changes in water quality. Projected changes in air temperature and rainfall could affect river flows and, hence, the mobility and dilution of contaminants. Increased water temperatures will affect chemical reaction kinetics and, combined with deteriorations in quality, freshwater ecological status. With increased flows there will be changes in stream power and, hence, sediment loads with the potential to alter the morphology of rivers and the transfer of sediments to lakes, thereby impacting freshwater habitats in both lake and stream systems. This paper reviews such impacts through the lens of UK surface water quality. Widely accepted climate change scenarios suggest more frequent droughts in summer, as well as flash-flooding, leading to uncontrolled discharges from urban areas to receiving water courses and estuaries. Invasion by alien species is highly likely, as is migration of species within the UK adapting to changing temperatures and flow regimes. Lower flows, reduced velocities and, hence, higher water residence times in rivers and lakes will enhance the potential for toxic algal blooms and reduce dissolved oxygen levels. Upland streams could experience increased dissolved organic carbon and colour levels, requiring action at water treatment plants to prevent toxic by-products entering public water supplies. Storms that terminate drought periods will flush nutrients from urban and rural areas or generate acid pulses in acidified upland catchments. Policy responses to climate change, such as the growth of bio-fuels or emission controls, will further impact freshwater quality.

Speciation and variation in the occurrence of haloacetic acids in three water supply systems in England

An investigation into the speciation and occurrence of nine haloacetic acids (HAAs) was conducted during the period of April 2007 to March 2008 and involved three drinking water supply systems in England, which were chosen to represent a range of source water conditions; these were an upland surface water, a lowland surface water and a groundwater. Samples were collected seasonally from the water treatment plants and at different locations in the distribution systems. The highest HAA concentrations occurred in the upland surface water system, with an average total HAA concentration of 21.3 μg/L. The lowest HAA levels were observed in the groundwater source, with a mean concentration of 0.6 μg/L. Seasonal variations were significant in the HAA concentrations; the highest total HAA concentrations were found during the autumn, when the concentrations were approximately two times higher than in winter and spring. HAA speciation varied among the water sources, with dichloroacetic acid and trichloroacetic acid dominant in the lowland surface water system and brominated species dominant in the upland surface water system. There was a strong correlation between trihalomethanes and HAAs when considering all samples from the three systems in the same data set (r2=0.88); however, the correlation was poor/moderate when considering each system independently.

Assessment of potential climate change impacts on peatland dissolved organic carbon release and drinking water treatment from laboratory experiments

Catchments draining peat soils provide the majority of drinking water in the UK. Over the past decades, concentrations of dissolved organic carbon (DOC) have increased in surface waters. Residual DOC can cause harmful carcinogenic disinfection by-products to form during water treatment processes. Increased frequency and severity of droughts combined with and increased temperatures expected as the climate changes, have potentials to change water quality. We used a novel approach to investigate links between climate change, DOC release and subsequent effects on drinking water treatment. We designed a climate manipulation experiment to simulate projected climate changes and monitored releases from peat soil and litter, then simulated coagulation used in water treatment. We showed that the ‘drought’ simulation was the dominant factor altering DOC release and affected the ability to remove DOC. Our results imply that future short-term drought events could have a greater impact than increased temperature on DOC treatability.

Simulated climate change impact on summer dissolved organic carbon release from peat and surface vegetation: implications for drinking water treatment

Uncertainty regarding changes in dissolved organic carbon (DOC) quantity and quality has created interest in managing peatlands for their ecosystem services such as drinking water provision. The evidence base for such interventions is, however, sometimes contradictory. We performed a laboratory climate manipulation using a factorial design on two dominant peatland vegetation types (Calluna vulgaris and Sphagnum Spp.) and a peat soil collected from a drinking water catchment in Exmoor National Park, UK. Temperature and rainfall were set to represent baseline and future conditions under the UKCP09 2080s high emissions scenario for July and August. DOC leachate then underwent standard water treatment of coagulation/flocculation before chlorination. C. vulgaris leached more DOC than Sphagnum Spp. (7.17 versus 3.00 mg g−1) with higher specific ultraviolet (SUVA) values and a greater sensitivity to climate, leaching more DOC under simulated future conditions. The peat soil leached less DOC (0.37 mg g−1) than the vegetation and was less sensitive to climate. Differences in coagulation removal efficiency between the DOC sources appears to be driven by relative solubilisation of protein-like DOC, observed through the fluorescence peak C/T. Post-coagulation only differences between vegetation types were detected for the regulated disinfection by-products (DBPs), suggesting climate change influence at this scale can be removed via coagulation. Our results suggest current biodiversity restoration programmes to encourage Sphagnum Spp. will result in lower DOC concentrations and SUVA values, particularly with warmer and drier summers.