Monitoring and quantifying the treatment performance of on-site wastewater treatment plants
Motivation. On-site wastewater treatment plants (OSTs) treat wastewater from a single household or dwelling directly on site. Because of the low initial investment costs, high flexibility, and resource recovery potential, they are used worldwide. Their core problem is that they are mostly operated without constant supervision. To keep costs low, common practice is to have one to four annual inspections. But with no online monitoring in place, treatment performance of such plants is low. Furthermore, failures are not noticed promptly after their occurrence, but only during the next inspection, if at all. This leads to reduced overall treatment performance and reinforces the widespread prejudice that OSTs are a makeshift solution.
Aim. The overall goal of this work is to see if OST systems can achieve treatment performances that are comparable to conventional centralised systems. The vision is that treatment performance should no longer be a criterion to rule out OSTs in the future any more. To get closer to this overall objective, two main objectives were defined:
• To identify a performance sensor that only requires maintenance annually or less frequent. This could greatly reduce maintenance costs, therefore enabling large-scale monitoring of OSTs.
• To investigate how such a nominally inaccurate sensor influences the treatment performance of a single OST unit as well as a system of OSTs and its quantification.
A specific hurdle when monitoring individual OSTs is sensor accuracy. In a nutrient-rich wet environment such as wastewater, biofilm grows everywhere within a few days. Therefore, manufacturers usually recommend monthly or even weekly sensor maintenance routines. Our idea was to use established, but unmaintained sensors for monitoring. [...]
Generation and evaluation of sanitation options for urban planning. Systematic consideration of technology innovations and sustainability criteria
Motivation. It is particularly challenging to reach SDG 6.2, access to sanitation for all, in urban areas of developing countries, where most of the current global population growth is taking place. Traditionally, urban sanitation planning is based on top-down, one-size-fits-all approaches. This has often led to inappropriate technology choices and failing projects worldwide, particularly in urban areas of developing countries. Conventional centralized sanitation is often inappropriate in these areas because it depends on capital-intensive sewer networks, large quantities of water, stable institutions with adequate capacities, and long planning horizons. Increasing investments in the development of novel technologies (e.g. urine separation) and system configurations (e.g. container-based sanitation) have been the result. These innovations can be more appropriate (independent from sewers, water and energy) and sustainable (adaptable to changing environmental and socio-demographic conditions, and saving/recovering water, nutrients, and energy).
Research need. While novel technologies and system configurations potentially enhance sustainability, they also increase planning complexity. Structured decision-making (SDM) has been found to assist the planning process, by combining decision analysis with engineering, and balancing opposing interests in a facilitated framework that embraces all relevant steps. To support the application of SDM, several frameworks were developed over the past decades (e.g. Community-led Urban Environmental Sanitation, CLUES, or Sanitation21). Yet, they are rarely used in practice. Recent research focuses on developing tools that operationalize the different planning steps, but these tend to prioritize methods for understanding the problems (e.g. Shit Flow Diagrams, SFDs), or for the selection of preferred options (e.g. multi-criteria decision analysis), assuming that the options to choose from are given. However, the currently available technologies result in an unmanageable number of possible system configurations (>100’000). The present technological development requires methods that generate a manageable number of locally appropriate sanitation decision options and that are systematic and can deal with the growing portfolio of technologies and sustainability criteria. Moreover, there is a lack of generic methods to quantify the performance of novel sanitation system configurations at the scale of an entire city. The identification of options and their comparison is further hampered by the lack of knowledge or data, particularly for novel options.
Research objectives. The objective of this thesis is to develop systematic and generic methods to identify locally appropriate sanitation system options and to evaluate their performance in terms of resource efficiency. The aim is to use these results as an input into the decision-making process. The methods shall: (i) consider entire sanitation systems from the toilet to reuse or disposal; (ii) be applicable to a large and diverse range of technologies and system configurations; and (iii) integrate criteria from all sustainability dimensions. Given the context of expanding urban areas and the focus on novel technologies, the methods should also be able to deal with uncertainties. The thesis covers three specific objectives: (I) methods for sanitation system options generation; (II) methods to quantify resource recovery potentials of entire systems as a performance indicator for the evaluation of their sustainability; and (III) a procedure for the integration of the methods in SDM and their practical application. The third objective also includes the analysis of the implementation of practical applications in Nepal, Ethiopia, South Africa, and Peru. [...]
Public surveillance and the future of urban pluvial flood modelling
Motivation and objective
Urban pluvial flooding is an issue of increasingly critical importance due to climate change and urbanization. However, the numerical models used for flood forecasting and risk mitigation suffer from a pronounced lack of monitoring data, which affects model accuracy. Monitoring data are necessary so the models, which contain undefined parameters, can be calibrated and validated against real flood events. In particular, it is important that the models are able to reproduce flood behavior in and around buildings, where the most damage is caused. However, conventional flow and water level sensors reach their limits in public spaces like streets due to irregular topography, moving obstacles, and the risk of vandalism. It has been suggested that surveillance cameras and social media could provide the necessary surface flooding data at a fraction of the cost of conventional sensors. The objective of this thesis is to explore how trend-like data can be extracted from surveillance footage and assimilated to boost the reliability of urban pluvial flood models. [...]
Motivation und Zielsetzung
Urbane regenbedingte Überschwemmungen sind aufgrund des Klimawandels und der Urbanisierung von immer größerer Bedeutung, aber den numerischen Modellen zur Hochwasservorhersage und Risikominderung mangelt es an Überwachungsdaten, was die Modellgenauigkeit einschränkt. Überwachungsdaten sind notwendig, damit die Modelle, welche unsichere Parameter enthalten, gegen echte Hochwasserereignisse kalibriert und validiert werden können. Insbesondere ist es wichtig, dass die Modelle das Überschwemmungsverhalten in und um Gebäude herum nachbilden können, wo die meisten Schäden verursacht werden. Herkömmliche Strömungs- und Wasserstandsensoren stoßen jedoch im öffentlichen Raum, wie Straßen, aufgrund unregelmäßiger Topographie, beweglicher Hindernisse und der Gefahr von Vandalismus an ihre Grenzen. Deswegen gibt es Interesse für alternative Datenquellen wie Überwachungskameras und soziale Medien, aus denen Oberflächenabflussdaten zu einem Bruchteil der Kosten herkömmlicher Sensoren gewonnen werden könnte. Das Ziel dieser Arbeit ist es, zu untersuchen, wie trendartige Daten aus Überwachungsbildern extrahiert und assimiliert werden können, um die Zuverlässigkeit von Überschwemmungsmodellen zu erhöhen. [...]
Advancing decision analysis methods for environmental management. Including stakeholder values in wastewater infrastructure planning and river assessment
Good decision-making requires the joint consideration of two aspects: knowledge about consequences of decision alternatives and knowledge about values, which can be expressed as decision objectives and preferences. Obtaining information on potential consequences and on stakeholder values, structuring this information, and integrating it in a meaningful way presents challenges for environmental decisions. Traditionally, natural and engineering sciences are concerned with improving the prediction of potential consequences. In this dissertation, the focus is on values, with the aim of a better integration of both aspects: How can we improve the inclusion of subjective values, expressed as objectives and preferences, in decision-making? [...]
Um gute Entscheidungen zu treffen, müssen zwei Aspekte betrachtet werden: Zum einen braucht es Wissen über die Konsequenzen der Entscheidungsalternativen, zum anderen müssen Werte, die in Form von Zielen und Präferenzen ausgedrückt werden können, einbezogen werden. Informationen zu den möglichen Konsequenzen und zu den Werten von Akteuren zu sammeln, sie zu strukturieren und schlussendlich zusammenzuführen, sind Herausforderungen für die Entscheidungsfindung im Umweltbereich. Natur- und Ingenieurswissenschaften bemühen sich traditionellerweise vor- wiegend darum, die Abschätzung von Konsequenzen zu verbessern. In dieser Dissertation liegt der Fokus auf den Werten, mit dem Ziel einer besseren Integration dieser beiden Aspekte für die Entscheidungsfindung: Wie können wir den Einbezug subjektiver Werte - Ziele und Präferenzen - in Entscheidungen verbessern? [...]
Spatiotemporal variability of micropollutants in sewer overflows
Motivation. Our surface water is impacted by a wide variety of contaminants released through human activities. One contaminant group of concern is micropollutants, which can have eco-toxicological effects in trace concentrations. Micropollutants, for example, include plant protection products and biocides, which are specifically designed to harm organisms. An important input pathway of micropollutants to surface water can be untreated sewer overflows (combined sewer overflows and stormwater outlets). However, the understanding of factors influencing the occurrence and levels of micropollutants is limited and challenged by: i) high spatial differences among sites, ii) a large number of discharge sites and iii) high temporal fluctuating discharge events.
Research objective. This thesis intends to enhance our understanding of micropollutants in sewer overflows. It aims to investigate efficient methods to prioritize sewer overflow sites, which can be potentially harmful for receiving waters. The presented work focuses on the development of model prediction and efficient monitoring approaches and includes the following: i) a Swiss-wide model to assess how many discharge sites may be critical (Chapter 2), ii) fundamentals to develop passive sampling as an alternative monitoring method for short duration sewer overflows (Chapter 3 and 4) and iii) an extended monitoring study covering 20 combined sewer overflows (CSOs) to explore spatial differences among sites (Chapter 5). The main findings of this thesis are presented in the following.
Model-based screening. A dynamic substance flow modeling approach was applied to 2,500 Swiss municipalities, considering micropollutant accumulation and wash-off on urban surfaces. The approach is based on the simplification, that there is one CSO and one stormwater outlet per municipality. The model allows for an estimation of the micropollutant concentration fluctuations in sewer overflows in 10-min resolution. The results show the importance of untreated discharges from sewer overflows as emission into receiving waters. The load contribution to sewer overflows of micropollutants in stormwater (e.g. plant protection products and biocides) is estimated to be considerably higher than of micropollutants in municipal wastewater (e.g. pharmaceuticals and other household chemicals). In addition, the results indicate that up to 83% of all urban catchments have sewer overflows that need to rely on upstream dilution in order to not exceed substance-specific environmental quality standards (EQS). Thus, this nationwide screening approach clearly highlights the need for a more detailed assessment of micropollutants in sewer overflows, and especially, the need for more measured data to allow the development of validated micropollutant prediction models.
Measuring. Difficulties of monitoring sewer overflows with traditional methods are i) high concentration fluctuations with unknown event durations which require a high temporal sampling resolution, ii) many discharge sites and iii) placement, operation, and maintenance of equipment. Hence, passive samplers for polar organic micropollutants are analyzed systematically as a viable alternative to monitor short duration sewer overflows. The main advantage of passive samplers is the continuous accumulation of contaminants from the water phase, with no need for external energy sources nor for immense water sample storage volume. In a first step, the impact of fluctuating concentrations on deviations from true time-weighted average (TWA) concentrations was studied. The results highlight that the deviations induced by fluctuating concentrations are similar or smaller than uncertainties arising from chemical analysis and environmental factors. Understanding the uptake mechanism of micropollutants is one of the most important issues that needs to be resolved to reduce uncertainties in passive sampling data. The uptake experiments in sewer conditions for short duration events (<36h) indicate that the mass transfer is either dominated by the sorbent, or, by a multi-step mechanism. Therefore, a new semi-empirical mixed rate control model is proposed, which can be directly used for future studies under similar conditions. A field validation (3 locations, 10 events) shows that TWA concentration estimates measured by passive samplers are within a factor of 0.4 to 3.1 compared to composite water samples. Hence, the use of upper limit TWA concentration estimates is recommended for compliance checking with EQS. The findings clearly show that passive samplers are suitable to estimate TWA concentration ranges in sewer overflows and, thus facilitate identification of potentially critical discharge sites.
Occurrence of micropollutants. Unique monitoring data from 20 CSO sites was collected with passive samplers. In total 13 polar organic micropollutants were analysed in 95 events (2-7 events per site). The results highlight indicator micropollutants, which were often found in the monitored CSOs and could be used in future monitoring studies: diclofenac, benzotriazole, carbamazepine, diazinon, diuron, carbendazim, mecoprop, metolachlor and terbutryn. Further, our results reveal that the spatial differences among CSO sites are bigger than the inter-event differences within a site for all studied micropollutants. Nevertheless, no significant correlation with land use data could be identified. The results, therefore, suggest that additional factors, most likely the contaminant usage pattern, have a considerable influence on the observed spatial differences. Both municipal wastewater and stormwater contributed to concentrations above the EQS in CSOs (not in the receiving water). In addition, the monitoring with passive samplers indicates that at least 13 out of 20 CSOs show concentrations above EQS in CSOs, and would rely on dilution by receiving waters to not exceed EQS.
Outlook. Overall, the thesis shows the relevance of sewer overflows as a source of micropollutants entering receiving water bodies. The findings can serve as a basis for the development of a systematic and stepwise approach to efficiently identify critical sites. The development of such an approach would require joint efforts by eco-toxicologists, analytical chemists, regulators and wastewater engineers. This approach could be based on a simplified modeling approach as a first indicator, followed by passive sampling to assess micropollutant levels. To enable the widespread application of passive samplers in monitoring programs, regulators’ and operators’ confidence in passive sampling needs to be strengthened with more field validation studies and common guidelines.
Statistical methods for better hydrologic predictions. Improving parameter and uncertainty estimation
Hydrologic systems are complex - constituting spatially distributed and temporally variable properties and processes. Such systems are generally modelled mathematically after some simplifying assumptions, for example, by aggregating certain variable properties and neglecting many subprocesses. These model structure deficits result in a mismatch between the real and the modelled system response, which entails uncertain predictions. In addition to model structure deficits, the presence of errors in model inputs and in the observations of system response contributes to the uncertainty in the estimation of model parameters. For risk-based decision making and for statistical hypothesis testing using these models, their uncertainties need to be adequately and explicitly stated. Furthermore, attempts need to be made to reduce these uncertainties. [...]
Hydrologische Systeme sind komplex - sie bilden räumlich verteilte und zeitlich veränderliche Eigenschaften und Prozesse ab. Solche Systeme werden mathematisch unter einigen vereinfachenden Annahmen modelliert, beispielsweise durch das Aggregieren bestimmter Variableneigenschaften und das Vernachlässigen einiger Teilprozesse. Diese Defizite in der Modellstruktur führen zu einer Diskrepanz zwischen realem und modelliertem System, was zu Vorhersagen mit grösserer Unsicherheiten führt. Weiterhin trägt das Auftreten von Fehlern in den Input-Parametern sowie in den simulierten Resultaten zu Unsicherheiten bei der Schätzung von Modellparametern bei. Für eine risikobasierte Entscheidungsfindung sowie für statistische Hypothesentests unter Verwendung der Modelle müssen Unsicherheiten angemessen und explizit angegeben und langfristig reduziert werden.
The optimal degree of centralisation for wastewater infrastructures. A model-based geospatial economic analysis
Efficient infrastructure planning is essential to achieve a more sustainable future. This includes aiming for optimal and economically more efficient infrastructures in the field of urban water management (UWM). Especially network-based infrastructures need special attention as they are generally very cost intensive and have distinctly demanding planning characteristics. Today’s historically evolved UWM practices tend to be network-based as in the last century enormous investments have been made to build-up vast sewer networks and large central wastewater treatment plants which centrally connect very high population percentages in many countries. The construction of large network infrastructures has resulted in a dominant centralised planning paradigm and heavily centralised wastewater management systems (WMS). However, this strong central planning paradigm is increasingly being questioned with respect to sustainability challenges and the call is becoming louder for innovative and radical approaches to address future challenges in the field of UWM. One such innovative approach is the decentralised treatment of wastewater by decentralised WMS, although in countries with high central connection rates this has so far been seen mainly as a stopgap solution. Today, connection rates differ significantly across countries: Great differences exist not only between high-income and low-income countries but also within OECD countries. It is unclear to what degree centralised or decentralised WMS should be installed in a region from the point of view of economic efficiency. Whereas the UWM literature presents specific cost assessments, there is a paucity of tools and methods to assess the costs of WMS consisting of centralised and decentralised systems (hybrid WMS). There are also few cost assessments of decentralised WMS with respect to their operation and maintenance costs. This dissertation uses an economic geospatial model-based approach to address the challenging research question of the optimal degree of centralisation. Conceptually, especially the spatially explicit full-cost modelling and the socio-technical conceptualisation of WMS are of special relevance. The basic trade-off between wastewater transportation and treatment is modelled in a geographically explicit way, economies of density for decentralised systems are assessed and a framework is presented to assess different optimal connection rates for hybrid systems. This framework is then used to assess economically sustainable connection rates in order to promote the economic argumentation for a possible sustainability transition in UWM. [...]
Multi-criteria decision analysis for water supply infrastructure planning under uncertainty
Our centralized water supply systems are aging. Despite their success in reliably providing high quality drinking water, nowadays especially small utilities (e.g. less than 10’000 inhabitants supplied) are illprepared to face possible future challenges. The fragmented structure of the water supply sector leads to a lack of institutional, financial and personnel resources for professional management and planning of water supply systems. Current planning is furthermore challenged by insufficient knowledge and data about the prevailing water infrastructure condition and future rehabilitation demand. It usually ignores future dynamics and planning uncertainties, as well as alternatives to the perpetuation of the status quo. Infrastructure decision making is usually not transparent and only few stakeholders are included into the decision process.
This thesis presents an approach to overcome these shortcomings and support long-term water supply infrastructure planning under uncertainty in a multi-stakeholder context. Thereto, methods from multicriteria decision analysis (MCDA), strategic asset management (SAM), pipe failure modeling, and scenario planning were combined, adapted, and further developed. The suitability of the approach was validated in a case study in Switzerland.
To improve the prediction of pipe service life in view of data scarcity, it was shown how the knowledge of experts can be quantitatively assessed and integrated into the calibration of pipe survival models by means of Bayesian inference. Similarly, knowledge gained from three mid-size to large Swiss water networks was used to improve calibration of a novel pipe failure model. It is demonstrated that this failure model is able to deal with the common data situation, and mitigate overestimation of the time to failure caused by the absence of data from already replaced pipes. The failure model was combined with a rehabilitation model to assess the performance of 18 rehabilitation strategies under four future scenarios for a small water utility. MCDA was used to compare these alternatives under different preferences concerning three objectives. The analysis revealed that the common strategy, purely reactive rehabilitation, is not recommendable in most cases and that annual replacement of 1–2 % of the network by condition might be a good strategy for the utility in question.
These findings were considered during the definition of alternatives for a second MCDA study aiming at identifying ‘good water supply infrastructure’ alternatives. Eleven alternatives and an objectives hierarchy consisting of 44 fundamental objectives and 30 attributes were developed together with stakeholders. The alternatives differ not only with regard to rehabilitation management, but also technical, managerial, and organizational aspects. The outcomes of all alternatives regarding these attributes were predicted under four future scenarios to account for uncertainties about the future development. The approach for the elicitation and modeling of preferences includes the imprecision of the stated preferences as well as uncertainties of preference parameters which were not elicited (the aggregation model, marginal value functions, risk attitude, and scaling factors). Preferences of ten selected stakeholders were then elicited and probability distributions of the ranking of alternatives based on these preferences were obtained. Despite differences in the individual rankings, a potential compromise solution could be proposed and ways for potential adaptation and improvement of other alternatives be indicated. In general, alternatives with good outcomes regarding groundwater protection, water quality, supply reliability, and realization of the rehabilitation demand received the highest ranks, as these were also among the most important objectives for the majority of the stakeholders. As operation and management do considerably contribute to the performance regarding the latter three objectives, the importance of a thorough infrastructure and rehabilitation management cannot be neglected. In view of the possible ranges of the outcomes, the objectives of ‘high social acceptance’ (e.g. disturbance by unnecessary road works, resources autonomy), and to some extent also ‘low costs’ were judged less important.
Multi-criteria decision analysis proved useful to support the long-term planning of water infrastructures under uncertainty and in a multi-stakeholder framework. The usual extrapolation of the status quo was overcome. Future dynamics and uncertainties could be incorporated by combining decision making and modeling with scenario planning, besides the quantitative consideration of uncertainties in making predictions, and evaluating the results. With the presented approaches for the modeling of pipe failures and rehabilitation, the methods and tools for the assessment of the current condition and future rehabilitation demand of small water networks despite a difficult data situation are now available.