Angered, Sweden
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Malm A.,Gothenburg Water | Malm A.,Chalmers University of Technology | Svensson G.,Lulea University of Technology | Backman H.,Swedish Water and Wastewater Association | Morrison G.M.,Chalmers University of Technology
Water Science and Technology: Water Supply | Year: 2013

Ageing drinking water, stormwater and sewer pipe networks imply an increased degree of rehabilitation. The need for rehabilitation can be predicted using lifetime distribution functions together with current network age and material distribution. In Sweden, current age and material distribution is neither documented on a national level, nor for many water utilities on a local level. In this study, current network age and material distribution was provided through a questionnaire sent to Swedish water and wastewater utilities and the data provided were extrapolated to cover the whole of Sweden. The data were then combined with lifetime distribution functions to provide predictions. One limitation is that for newer materials the lifetime is still uncertain. Predictions were made for different scenarios to reflect local differences and the medium scenario shows that while the Swedish rehabilitation rate is stable, investments in monetary terms need to double in the next 60 years. The rehabilitation rate is also dependent on the extent to which the network is expanded. This method can be used to calculate national investment needs, and the results can also provide a basis for estimates for Swedish utilities with data scarcity. © IWA Publishing 2013.

Sokolova E.,Chalmers University of Technology | Astrom J.,Chalmers University of Technology | Pettersson T.J.R.,Chalmers University of Technology | Bergstedt O.,Gothenburg Water | Hermansson M.,Gothenburg University
Environmental Science and Technology | Year: 2012

The implementation of microbial fecal source tracking (MST) methods in drinking water management is limited by the lack of knowledge on the transport and decay of host-specific genetic markers in water sources. To address these limitations, the decay and transport of human (BacH) and ruminant (BacR) fecal Bacteroidales 16S rRNA genetic markers in a drinking water source (Lake Rådasjön in Sweden) were simulated using a microbiological model coupled to a three-dimensional hydrodynamic model. The microbiological model was calibrated using data from outdoor microcosm trials performed in March, August, and November 2010 to determine the decay of BacH and BacR markers in relation to traditional fecal indicators. The microcosm trials indicated that the persistence of BacH and BacR in the microcosms was not significantly different from the persistence of traditional fecal indicators. The modeling of BacH and BacR transport within the lake illustrated that the highest levels of genetic markers at the raw water intakes were associated with human fecal sources (on-site sewers and emergency sewer overflow). This novel modeling approach improves the interpretation of MST data, especially when fecal pollution from the same host group is released into the water source from different sites in the catchment. © 2011 American Chemical Society.

Malm A.,Gothenburg Water | Malm A.,Chalmers University of Technology | Ljunggren O.,Gothenburg Water | Bergstedt O.,Gothenburg Water | And 3 more authors.
Water Research | Year: 2012

Lifetime distribution functions and current network age data can be combined to provide an assessment of the future replacement needs for drinking water distribution networks. Reliable lifetime predictions are limited by a lack of understanding of deterioration processes for different pipe materials under varied conditions. An alternative approach is the use of real historical data for replacement over an extended time series. In this paper, future replacement needs are predicted through historical data representing more than one hundred years of drinking water pipe replacement in Gothenburg, Sweden. The verified data fits well with commonly used lifetime distribution curves. Predictions for the future are discussed in the context of path dependence theory. © 2012 Elsevier Ltd.

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