Current Projects
Cost-benefit analysis of micropollutant reduction through upgrading of wastewater treatment plants in Switzerland
The main objective of this research is to conduct a cost-benefit analysis of water quality improvement that would be achieved through upgrading of wastewater treatment plants in Switzerland with the aim of reducing the levels of micropollutants. This project will identify the total costs of investments in terms of their net present value, which are needed for the planned upgrading of wastewater treatment plants. In the second step, the benefits of enhanced water quality that would result from these investments will be estimated based on a survey. The choice experiment will be applied in order to elicit the willingness to pay of Swiss residents for higher water quality resulting from reduced levels of micropollutants. The experimental design will consist of defining an increase in water quality, measured by a change in the levels of different micropollutants. Those changes will be translated into effects on human health and ecosystems in order to make them easily understandable to survey respondents. The respondents will also be carefully informed about uncertainties associated with the effects of micropollutants. Furthermore, the survey will examine the perceptions and awareness of Swiss residents about the current water quality, micropollutants, and the price they are presently paying for drinking water and wastewater services. Based on a comparison of costs and benefits of upgrading wastewater treatment plants, the project will conclude whether or not the investment is justified from an economic point of view.
Collaborators: Max Maurer
Cost-effectiveness and cost-benefit analyses of measures for water quality improvement in Mönchaltorfer Aa (iWaQa project)
This research forms part of iWaQa project and has three main objectives. The first one is to conduct a cost-effectiveness analysis of different measures for reducing chemical water pollution in Mönchaltorfer Aa (Canton of Zürich). This part of the analysis will consist of two steps: 1) cost assessment of different measures that can be undertaken with the purpose of reducing pollution levels and 2) determining water pollution reduction that would be achieved by implementing each of these measures (with the help of collaborators in the project). This information will enable comparing costs and effects of each measure for water pollution reduction and find out which would be the most cost-effective one. The second objective of the research is to estimate the benefits that would be generated by implementing pollution reduction measures, i.e. the consequent water quality improvement. This will be done by applying a choice experiment in order to elicit both use and non-use values of the enhancement of ecosystem services provided by water resources in the area (in particular water quality improvement). Finally, based on this information, a cost-benefits analysis of implementing various measures for water pollution reduction will be performed.
Collaborators: Christian Stamm, Peter Reichert, Nele Schuwirth
Creating a GIS-based water services value map for Switzerland
The ultimate objective of this project is to assess willingness to pay for different water services in Switzerland. This will be done by applying meta-analysis value transfer function based on a GIS map. The first step in this process will be identifying key services provided by water resources, such as drinking water provision, hydropower production, recreation activities (bathing, fishing, boating, walking), commercial transportation by ships, cooling down of nuclear power plants, and non-use ecological services. This will be followed by assessing the availability of a) biophysical data, such as water quality indicators across the country and b) spatial data that will allow identifying geographical locations of different water services and the intensity of their use on the map of Switzerland. GIS maps for ecosystem services provided by water resources will then be created based on the available data. In the next step, meta-analysis of valuation studies that estimate willingness to pay for different water services will be used along with socio-economic data for Switzerland (e.g., GDP per capita, population density, distance from the nearest water resource) in order to construct value transfer functions for various water services. Finally, value transfer functions will be applied. They will enable estimating the willingness to pay (i.e. the value) of different water services in Switzerland based on GIS maps.