Co-benefit valuation of urban and peri-urban nature in high resolution on continental scale

Abstract

Space is a highly valued asset in cities. This is a key reason why nature-based solutions (NBS) for water management are often perceived to be more expensive than traditional greysolutions. Promoting NBS implementation requires methods for quantifying their non-market benefits that are widely accepted and easy-to-apply in early planning and brainstorming stages. In this work, we develop a predictive metamodel for the total economic value of urban and peri-urban nature, based on 114 stated-preference valuation studies of nature in (peri-)urban areas and openly available geographic data from across the world. The dataset covers the entire range of NBS types with sizes from 0.5 to 900.000 ha. We employ a mixed-effects modelling approach and use a cross-validation procedure to determine which factors affect the willingness to pay for (peri-)urban nature. We consider the predictive performance of 8.4 million model permutations that consider different combinations of site properties and topographic and socio-economic characteristics of the surroundings as input. We find that the total economic value is determined by the size of the nature areas and population densities in their surroundings. There is clear evidence for substitution effects where available nature areas reduce the willingness to pay for new nature. Beyond the dependency on area, there is little evidence for making distinctions between nature types. Economic values do depend on the average income at a site, but these variations are entirely captured by purchase power corrections. Our value estimates are aligned with related literature and range between 150 and 400,000 USD/ha/year. We have implemented our metamodel into a freely available Python program, which generates maps of the predicted values for any location in Europe in a spatial resolution of 100m.