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Here the models used for deriving the co-benefits of increases in vegetation and water due to climate adaptation measures are described. It is important to know that the individual model results can not directly be summed up due to potential double-counting. The model inputs and results have a resolution of 10x10 meters meaning that one cell has a surface area of one square decameter (dam2)

 

Table of Contents
minLevel3

Reduction of healthcare and labour costs due to vegetation (adapted from Remme et al. 2018)

Vegetation provides health benefits to people in their living environments and reduces the number of people that need to visit a doctor (Maas, 2008). Vegetation has a positive effect on air quality, stress reduction, urban cooling, concentration and physical activity, among other things (e.g. Maas, 2008 and KPMG, 2012). Vegetation in the surroundings of people’s homes reduces the prevalence of multiple health risks and diseases, including respiratory diseases, migraine, diabetes, depression, neck and back pain, depression and coronary heart disease (KPMG, 2012). For this model, an aggregated methodology has been applied to assess the effect of vegetation on nine health risks (cf. the TEEB-Stad tool, see www.teebstad.nl). Table 1 and Table 2 provide an overview of the input and output maps of the co-benefit: ‘reduction of healthcare and labour costs due to vegetation’.

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  • KPMG, 2012. ‘Groen, gezond en productief. The Economics of Ecosystems & Biodiversity (TEEB NL): natuur en gezondheid’.
  • Maas J., 2008. Vitamin G: Green environments, healthy. environments, Proefschrift ter verkrijging van de graad van docoraat Universiteit Utrecht, Utrecht, 2008.
  • Remme, R., De Nijs, T., Paulin, M., 2008. Natural Capital Model, Technical documentation of the quantification, mapping and monetary valuation of urban ecosystem services, RIVM, RIVM Report 2017-0040.
  • RIVM, 2003 onwards. Cijfertool kosten van ziekten met cijfers uit de ‘kosten van ziektestudie’.
  • RVO 2013. Basisregistratie Gewaspercelen (BRP), 2013. Available at http://www.nationaalgeoregister.nl/geonetwork/srv/dut/catalog.search#/metadata/%7B25943e6e-bb27-4b7a-b240-150ffeaa582e%7D
  • Steenbeek R., Hooftman W., Geuskens G., Wevers C., 2010. Objectiveren van gezondheidsgerelateerde non-participatie en de vermijdbare bijdrage van de gezondheidszorg hieraan. TNO, TNO-rapport 2010.171/13738.01.01.


Reduction of particulate matter (PM10) by vegetation (Adapted from Remme et al. 2018)

In industrialized countries like the Netherlands, the soil, water and air are often polluted. One of the main forms of air pollution is particulate material (PM₁₀), which comes from sources such as traffic, industry and intensive livestock farming. Particulates can cause respiratory conditions, including some serious diseases. There are major scientific differences in the influence of vegetation on air quality. Recent reviews (Janhall, 2015; Abhijith et al., 2017; Baldauf, 2017) show that the impact of green infrastructure on air quality depends on the local situation. These studies show that ecosystems including trees, shrubs, lawns, and other vegetation can be of assistance in catching and retaining fine particulate matter and the purification of the air. Tables 1 and 3 provide an overview of the input and output maps of the co-benefit: ‘reduction of particulate matter (PM10) by vegetation’.

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  • Abhijith, K.V., Kumar, P., Gallagher, J., McNabola, A., Baldauf, R., Pilla, R., Broderick, B., Di Sabatino, S., Pulvirenti, B., 2017. Air pollution abatement performances of green infrastructure in open road and built-up street canyon environments - A review. Atmospheric Environment 162, p71-86.
  • Baldauf, R., 2017. Roadside vegetation design characteristics that can improve local, near-road air quality. Transportation Research Part D 52 p354–361.
  • CE-Delft, 2017. Handboek Milieuprijzen 2017. Methodische onderbouwing van kengetallen gebruikt voor waardering van emissies en milieu-impact. Publicatienummer: 17.7A76.64, Delft.
  • CE-Delft, 2014. Externe en infrastructuurkosten van verkeer. Een overzicht voor Nederland in 2010. Publicatienummer: 14.4485.35, Delft.
  • De Nocker L en Viaene P., 2016. Methode ecosysteemdienst fijn stof afvang, ECOPLAN. VITO.
  • HEATCO, 2006. Developing Harmonised European Approaches for Transport Costing and Project Assessment (HEATCO). Deliverable D5: Proposal for Harmonised Guidelines, Stuttgart: IER, University of Stuttgart.
  • Janhall, S., 2015. Review on urban vegetation and particle air pollution – Deposition and dispersion. Atmospheric Environment 105, p130-137.
  • Remme, R., De Nijs, T., Paulin, M., 2008. Natural Capital Model, Technical documentation of the quantification, mapping and monetary valuation of urban ecosystem services, RIVM, RIVM Report 2017-0040.
  • RIVM, 2017. Grootschalige concentratie- en depositiekaarten Nederland. Rapportage 2016. RIVM Rapport 2016-0068. RIVM, Bilthoven, the Netherlands.

 

Influence of vegetation & water on residential property values (Adapted from Remme et al. 2018)

Trees, parks, gardens and water increase the amenity of residential areas, which is reflected in property values (Czembrowski & Kronenberg 2016; Franco & MacDonald, 2017). In the Netherlands, multiple studies have been done to quantify the influence of vegetation and water on property values, for example Daams et al. 2016 and for an overview Ruijgrok et al. (2006). This model uses Luttik & Zijlstra (1997) as a main data source. The studies in the Netherlands make a distinction between two aspects, i.e. the view on green elements, parks and water, and the proximity to these elements. Tables 1 and 3 provide an overview of the input and output maps used to model the co-benefit: ‘influence of vegetation and water on residential property values’.

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  • CBS, 2017. Ecosystem Unit map, 2013. Available at https://www.cbs.nl/en-gb/background/2017/12/ecosystem-unit- map.
  • CBS, 2016. Gemeente, wijk- en buurtenkaart 2015. Available at http://www.cbsinuwbuurt.nl/#sub- buurten2015_gemiddelde_WOZwoningwaarde.
  • Czembrowski P. & Kronenberg J., 2016. Hedonic pricing and different urban green space types and sizes: Insights into the discussion on valuing ecosystem services. Landscape and Urban Planning 146, 11-19.
  • Daams M.N., Sijtsma, F.J., van der Vlist, A.J., 2016. The effect of natural space on nearby property prices; accounting for perceived attractiveness. Land Economics 92:3 389-410.
  • Franco S.F. & Macdonald J.L., 2017. Measurement and valuation of urban greenness: Remote sensing and hedonic applications to Lisbon, Portugal. Regional Science and Urban Economics 76, 156-180.
  • Luttik J. & Zijlstra M., 1997. Woongenot heeft een prijs; Het waardeverhogend effect van een groene en waterrijke omgeving op huizenprijzen. Wageningen SC-DLO (Rapport 562).
  • Remme, R., De Nijs, T., Paulin, M., 2008. Natural Capital Model, Technical documentation of the quantification, mapping and monetary valuation of urban ecosystem services, RIVM, RIVM Report 2017-0040.
  • Ruijgrok E.C.M., Smale A.J., Zijlstra R., Abma R., Berkers R.F.A., Németh A.A., Asselman N., de Kluiver P.P., de Groot D., Kirchholtes U., Todd P.G., Buter E., Hellegers P.J.G.J. and Rosenberg F.A., 2006. Kentallen Waardering Natuur, Water, Bodem en Landschap, Hulpmiddel voor de MKBA. Witteveen+Bos, commissioned by Ministerie van Landbouw Natuurbeheer en Voedselkwaliteit, The Hague.

 

Increase in physical activity due to vegetation (Adapted from Paulin et al. 2019)

A study conducted by Klompmaker et al. (2018) found a positive relationship between green space and outdoor physical activity within the Netherlands. The study was based on a national health survey (Public Health Monitor 2012, PHM; CBS, 2015) with 387,195 adults. Outdoor physical activity was defined as all moderate and vigorous physical activities that can be done outdoors (physical activity for commuting purposes, leisure time physical activity (walking, cycling, gardening) and outdoor sports). To measure green space. the Normalized Difference Vegetation Index (NDVI) was used. NDVI captures the density of green vegetation at a spatial resolution of 30m. Surrounding greenness was measured as the average NDVI within a circular buffer of the participant's residential address. The study found a positive relationship between green space within a buffer of 300m and the change in minutes adults engage in outdoor physical activities. Table 1 and Table 3 provide an overview of the input and output maps model for the co-benefit of ‘increase in physical activity due to vegetation’.

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Benefits of increased cycling for commuting purposes due to vegetation (adapted from Paulin et al., 2019)

A study conducted by Maas et al. (2008) studied the relationship between green space and cycling within the Netherlands. The study was based on a national health survey (Second Dutch National Survey of General Practice, DNSGP-2) with 4,899 people. To measure green space, the National Land Cover Classification database (LGN4) was used. LGN4 contains the dominant type of land use of each 25×25m grid cell in the Netherlands in 2001. Surrounding greenness was measured  as the percentage of vegetation cover within a circular buffer of the participant's address. The study found a positive relationship between the percentage of vegetation cover within a buffer of one km and the number of minutes cycled for commuting purposes. It was found that, for every percentage increase  in vegetation cover, people who cycle to work for commuting purposes will cycle 0.83 additional minutes on average (Figure 1). Moreover, people with 20% green space  within a one km radius around their home cycle 120 minutes per week for commuting purposes, whereas people with 80% green space within a one km radius cycle approximately 170 minutes per week for commuting purposes. Based on this information, the intercept is estimated at 103.4 minutes per week per person (Figure 1). Table 1 and Table 2 provide an overview of the input and output maps model for the co-benefit of ‘increase in cycling for commuting purposes due to vegetation’.

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  • Kahlmeier S., Götschi T., Cavill N., Castro Fernandez A., Brand, David Rojas Rueda C., Woodcock J., Kelly P., Lieb C., Oja P., Foster, Harry Rutter C., Racioppi F., 2017. Health economic assessment tool (HEAT) for walking and for cycling. Methods and user guide on physical activity, air pollution, injuries and carbon impact assessments. World Health Organization.
  • Kelly P., Kahlmeier S., Götschi T., Orsini N., Richards J., Roberts N., Scarborough, P., Foster C., 2014. Systematic review and meta-analysis of reduction in all-cause mortality from walking and cycling and shape of dose response relationship. International journal of behavioral nutrition and physical activity. 11(1). 132.
  • Maas J., Verheij. R. A., Spreeuwenberg. P., & Groenewegen. P.P., 2008. Physical activity as a possible mechanism behind the relationship between green space and health: a multilevel analysis. BMC public health. 8(1). 206.

 

Carbon sequestration by vegetation (adapted from Remme et al. 2019)

Vegetation provides an important climate regulating service by sequestering carbon from the atmosphere and converting it into biomass. Carbon sequestration in biomass decreases the amount of carbon in the atmosphere and therefore helps to mitigate further climate change. The models indicate the potential and actual carbon sequestration in biomass and the avoided monetary damage costs based on carbon sequestration in forests and trees. Table 1 and 6 provide an overview of the input and output maps for the ecosystem service model ‘carbon sequestration’.

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