Urban agriculture as a city planning adaption measure to climate change

Transkript

1 Urban agriculture as a city planning adaption measure to climate change Jakob Köhler 1 Felicitas Bechstein 1, Torsten Lipp² 1 IASP ²Universität Potsdam ECBCC Nature-Based Solutions to Climate Change in Urban Areas and their Rural Surroundings - Linkages between Science, Policy and Practice November 2015, Bonn, Germany

2 Urban agriculture has to be considered as an significant measure within city planning procedures Many functions and potentials with particular regard to climate issues Agricultural land use in European cities [%] Berlin 4,3 London 8,6 Munich 17,2 Wien 13,5 Düsseldorf 21,6 Mannheim 23,8 Hamburg 25 (municipal statistic offices )

3 The study In a co-operation between University of Potsdam and IASP Berlin (HU Berlin), the effect of urban farmland on city climate in Berlin was investigated (KÖHLER 2013) The impact on temperature and Predicted Mean Vote (PMV) were estimated in order to detect the effects of agricultural areas on the urban climate Based on the results, recommendations for action can be deduced

4 Starting point Generally, agricultural areas are known to lower the temperature in urban areas Mainly intensive cold-air production is mentioned in the literature (BONGARDT 2006, DANNERT 2011, GÄLZER 2001, LOHRBERG 2001) Until now, only little accurate data has been collected about this phenomenon. (BURST 2010, REUTER, U. & KAPP, R. 2012)

5 Cold-air production at night in Berlin Figure 1: Green and agriculture area with cold air production in proportion to the city area. Cold air production of agricultural land differentiated by intensity (according to: BERLIN SENATE ADMINISTRATION FOR CITY DEVELOPMENT / SENATSVERWALTUNG FÜR STADTENTWICKLUNG o.j.) 90% of agricultural land produces high to medium levels cold-air

6 The simulation with ENVI-Met Simulation of Air-Temperature and thermal comfort (PMV) from selected Berlin farm areas (compared to an asphalted area) The microclimatic simulations are performed using the three-dimensional model ENVI-Met V3.1 ( designed to simulate the surface-plant-air interactions in urban environments and to measure effects for urban green Is used for climate adaption strategies in practice and in research projects (u.a. REGIONALVERBAND RUHR 2010, REGKLAM-KONSORTIUM 2013) Input data: building structure, soil and plants, defined by: Leaf Area Index (LEA), height, root depth Asphalted reference area without vegetation Meteorological data, start time and duration

7 Simulation Rural-Urban Linkages Extensiv-emultifunctional farming Extensive-multifunctional farming Intensive-multifunctional farming Agricultural farm Intensive-multifunctional farming Figure 2: Location of selected farms in Berlin city area and type of farming Figure 3: 4: Spatial Bioclimate Distribution of Berlin. of Felt air Temperature in at height a summer of 2 m day at (DWD) at 12 a.m. CET in Berlin (Helbig 1999, according to Reichenbächer 1978) Selected Farms located intra- and peri-urban different types of farming Urban heat island (UHI) changes with city structure from center to the fringe important for planning

8 Results of Simulation Air Temperature Area (4) with highest green volume is coldest at 14:00 From 19:00 area with best aeration the coldest > Area (2) Figure 5: Modeling results Air Temperature of asphalted reference area (0) and the study areas (1-5) at a hot summer day

9 Area (2) Landschaftspark Herzberge Trees 4.5m 9m Grassland 0.15m Grassland 0.20m Grassland 0.15m Grassland 0.10m Building 4m Figure 6: aerial view of the selected area of Landschaftspark Herzberge [Area 2] (Google Inc. 2013)

10 Results of Simulation PMV PMV Value Under trees 0,3-0,6 neutral Short grassland 0,9-1,5 slightly warm Pavements > 2,1 warm Figure 7: Modelling result PMV distribution of Landschaftspark Herzberge [Area 2] at 14:00 at hot summer day

11 Results of Simulation PMV PMV Value Asphalt 2,5 - > 3 hot Figure 8: Modelling Result PMV distribution of asphalted Area [Reference Area 0] at 14:00 at hot summer day

12 Summary of simulations Cooling effect is determined by occurring use (Intensity of Green Volume) and structure (treetop cover and aeration) Configuration of the agricultural area determines the climatic target effects

13 Recommendations for action Planning Integrative, collaborative and multidisciplinary planning Integration in formal planning instruments (MATHEY et al. 2011) Intelligent use of agricultural design Implementation Use of support programs Binding lease to conditions (BRINK 2004) Maintenance Cooperation with Citizens and Farmers (BOCK et al. 2013) Extensive care strategies extensive multifunctional agriculture

14 Advantages of multifunctional urban agriculture Biodiversity Education Recreation Local Economy Feeding the Cities Resilience of Cities

15 The End Thank you for your attention Dipl.-Geoecologist Jakob Köhler

16 References BOCK, S., LIBBE, J., PREUß, T., ZWICKER-SCHWARM, D. (2013): Urbanes Landmanagement in Stadt und Region: Urbane Landwirtschaft, urbanes Gärtnern und Agrobusiness. Difu-Impulse, 2 (2013). Dt. Inst. für Urbanistik. Berlin. BONGARDT, B. (2006): Stadtklimatologische Bedeutung kleiner Parkanlagen: Dargestellt am Beispiel des Dortmunder Westparks. Bd. 24. Essener Ökologische Schriften. Hohenwarsleben: Westarp-Wissenschaftsverlag. BRINK, A. (2004): Landwirtschaft in urbanen Regionen: Ziele des GALK-Arbeitskreises "Umweltgerechte Landwirtschaft in Ballungsräumen". Stadt + Grün, 53 (11), BURST, A., BURST, S. & LÄHNE, W. (2010): Stadtklimaanalyse Mannheim Erstellt durch die Fa. Ökoplana, Mannheim. Im Auftrag der Stadtverwaltung Mannheim, FB Städtebau. Mannheim. DANNERT, H.-G. (2011): Frankfurts Antwort auf den Klimawandel. Anpassungsstrategien erfordern gesteuerte Eingriffe. In: Garten + Landschaft, Jg. 121, Nr. 5, S GÄLZER, R. (2001): Grünplanung für Städte: Planung, Entwurf, Bau und Erhaltung. Stuttgart (Hohenheim): Ulmer. GOOGLE INC. (Hrsg.) (2013): Google Earth. Version HELBIG, A. (1999): Stadtklima und Luftreinhaltung: Mit 79 Tabellen. 2. Au. Berlin: Springer. LOHRBERG, F. (2001): Stadtnahe Landwirtschaft in der Stadt- und Freiraumplanung: Ideengeschichte, Kategorisierung von Konzepten und Hinweise für die zukünftige Planung, Books on Demand, Norderstedt. KÖHLER, J. (2013): Urbane Landwirtschaft und ihre Auswirkungen auf das Stadtklima am Beispiel Berlins. Diplomarbeit, Universität Potsdam, Potsdam. MATHEY, J., RÖSLER, S., LEHMANN, I. (2011): Noch wärmer, noch trockener? Stadtnatur und Freiraumstrukturen im Klimawandel: Abschlussbericht zum F+E-Vorhaben (FKZ ) "Noch wärmer, noch trockener? Stadtnatur und Freiraumstrukturen im Klimawandel", Bd. 111, Naturschutz und biologische Vielfalt, Bundesamt für Naturschutz, Bonn-Bad Godesberg. REGIONALVERBAND RUHR (2010): Handbuch Stadtklima: Maßnahmen und Handlungskonzepte für Städte und Ballungsräume zur Anpassung an den Klimawandel (Langfassung), Hrsg. Von Ministerium für Umwelt und Naturschutz, Landwirtschaft und Verbraucherschutz des Landes Nordrhein-Westfalen, Düsseldorf. REGKLAM-KONSORTIUM (Hrsg.) (2013): Integriertes Regionales Klimaanpassungsprogramm für die Region Dresden. Grundlagen, Ziele und Maßnahmen, REGKLAM Publikationsreihe, Heft 7, Rhombos-Verlag, Berlin. REUTER, U. & KAPP, R. (2012): Städtebauliche Klimabel - Hinweise für die Bauleitplanung. Hrsg. von Ministerium für Verkehr und Infrastruktur Baden-Württemberg. Stuttgart. SENATSVERWALTUNG FÜR STADTENTWICKLUNG (Hrsg.) (o.j.): Digitaler Umweltatlas Berlin. Online Publikation.

17 Picture Credits Title: CC BY-SA 3.0 Slide 1: Stefan Lübke, Agrarbörse Ost e.v. / CC BY-SA 3.0 / CC BY-SA 3.0, Arnoldius / Stefan Lübke, Agrarbörse Ost e.v. (From Left to Right) Slide 11: Bernd Pölling, Fachhochschule Südwestfalen Slide 13: Salvör Jonsdottir, EU COST-Action Urban Agriculture Europe & Esther Veen, EU COST-Action Urban Agriculture Europe (From Left to Right) Slide 14: Bernd Pölling, Fachhochschule Südwestfalen

18 More about the Input data Size of Area: 4 ha and surrounding use free edge of 20m. Resolution of 1m x 1m For use-related comparison uniform surface (clay) Vegetation structure of each area are determined by aerial photos, the Berlin enviromental atlas and due to local inspection Vegetation specific parameters based on existing literature values Meteorological Inputdata see Table 1 Parameter Value Wind speed [m/s] 3 Wind direction West Roughness length 0.1 Start temperature [K] 293 Specific humidity in 2500 m [g water/kg air] 7 Relatic humidity in 2 m [%] 50 Table 1: Meteorological Input data