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Climate Model Berlin - Planning Advices Urban Climate 2015

Figures / Tables

Figures

Fig. 1: Percentage distribution of evaluation classes for the overall thermal situation in the settlement areas (linking of day and night situation) of Berlin.

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Fig. 1: Percentage distribution of evaluation classes for the overall thermal situation in the settlement areas (linking of day and night situation) of Berlin.

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Fig. 2: Spatial distribution of evaluation classes for the overall thermal situation in the settlement areas (linking of day and night situation ) of Berlin.

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Fig. 3: Balancing of the overall thermal situation in the settlement area of 12 districts of Berlin

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Fig. 3: Balancing of the overall thermal situation in the settlement area of 12 districts of Berlin

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Fig. 4: Percentage distribution of the evaluation classes for overall thermal situation on public roads, paths and places in Berlin.

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Fig. 4: Percentage distribution of the evaluation classes for overall thermal situation on public roads, paths and places in Berlin.

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Fig. 5: Overall evaluation of the thermal situation on public roads, paths and places in Berlin.

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Fig. 6: Balancing of the overall thermal situation on public roads, paths and places of the 12 districts of Berlin.

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Fig. 6: Balancing of the overall thermal situation on public roads, paths and places of the 12 districts of Berlin.

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Fig. 7: Core zones of cold air pathways ("pathway corridors") in Berlin

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Fig. 8: Summary effective area of the components of Berlin's air-exchange system in case of autochthonous weather conditions.

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Fig. 9: Balancing of cold air effect on the settlement area in Berlin according to districts

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Fig. 9: Balancing of cold air effect on the settlement area in Berlin according to districts

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Fig. 10: Percentage distribution of evaluation classes for climate-ecological worthiness of protection of open/green spaces in Berlin

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Fig. 10: Percentage distribution of evaluation classes for climate-ecological worthiness of protection of open/green spaces in Berlin

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Fig. 11: Spatial distribution of evaluation classes for climate-ecological worthiness of protection of open/green spaces in Berlin

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Fig. 12: Percentage distribution of the area categories with special urban-climatic drawbacks in Berlin.

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Fig. 12: Percentage distribution of the area categories with special urban-climatic drawbacks in Berlin.

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Fig. 13: Balancing of areas with special urban-climatic drawbacks for the 12 districts of Berlin

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Fig. 13: Balancing of areas with special urban-climatic drawbacks for the 12 districts of Berlin

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Fig. 14: Areas with special urban-climatic drawbacks in Berlin

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Fig. 15: Demographic vulnerability as compared to thermal stress - Spatial analysis at the level of block areas in Berlin

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Fig. 16: Demographic vulnerability as compared to thermal stress - Balancing at the level of Berlin's districts

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Fig. 16: Demographic vulnerability as compared to thermal stress - Balancing at the level of Berlin's districts

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Fig. 17: Absolute number and relative percentage of aggregated sensitive uses in thermally stressed environment in the 12 districts of Berlin.

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Fig. 17: Absolute number and relative percentage of aggregated sensitive uses in thermally stressed environment in the 12 districts of Berlin.

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Fig. 18: Absolute number and relative percentage of sensitive use types in thermally stressed environment in Berlin.

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Fig. 18: Absolute number and relative percentage of sensitive use types in thermally stressed environment in Berlin.

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Fig. 19: Spatial representation of areas with a special vulnerability as compared to the urban climate based on a shortage of green areas in Berlin

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Fig. 20: Balancing of the vulnerability as compared to the urban climate based on a shortage of green areas in the 12 districts of Berlin.

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Fig. 20: Balancing of the vulnerability as compared to the urban climate based on a shortage of green areas in the 12 districts of Berlin.

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Fig. 21: Schematic representation of the air-temperature-mortality relationship

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Fig. 22: Daily deaths (all causes) and daily maxima of the Universal Thermal Climate Index (UTCI) in Berlin in 2010 compared to mean values based on 2000-2010

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Fig. 23: Connection between thermal load (Universal Thermal Climate Index (UTCI), 2-day mean) and PM10 (2-day mean) as well as the total mortality (logarithmised relative risk) in Berlin. The bivariate response surface model has been adapted for trend, year and day of the week. A logarithmised relative risk of 0.2 corresponds to 22% more deaths

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Fig. 24: Connection between thermal load (Universal Thermal Climate Index (UTCI), 2-day mean) and PM10 (2-day mean) as well as the total mortality (logarithmised relative risk) in Berlin. The bivariate response surface model has been adapted for trend, year and day of the week. A logarithmised relative risk of 0.2 corresponds to 22% more deaths

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Fig. 25: Total mortality (all causes), represented as deaths per 1 million inhabitants per day, and daily mean temperatures in the period of 2001-2010. The blue/red line represents the best fit line for the days with low/high air temperatures. The intersection of these lines marks the mean minimum of the mortality rate (21.5 deaths per 1 million inhabitants per day) under conditions of a daily mean temperature of 21 °C

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Fig. 26: Representation of the number of (a) hot days (Tmax ≥ 30 °C) and (b) tropical nights (Tmin ≥ 20 °C) per year for selected measurement stations in Berlin in the period of 2001-2010. The dashed coloured lines show the arithmetic mean value of the years 2001-2010 of the respective station. The black hatching shows the number of days on which hot days and tropical nights occurred in combination. Stations: DAHF - Dahlemer Feld, DESS - Dessauer Straße, TGL - Berlin-Tegel, THF - Berlin-Tempelhof. In August 2004, there were measurement failures at the DAHF station. The DAHF and DESS stations are part of the Urban Climate Observation Network of the Chair of Climatology, Ecology Department, Technical University Berlin. The TGL and THF stations are operated by the German Meteorological Service

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Fig. 27: Ratio of the monthly mean of the daily maximum of the air temperature (meteorological stations Tegel, Tempelhof, Schönefeld) to the monthly sum of the deaths (all causes) in Berlin for the month of July in the period of 2001-2010

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Fig. 28: Spatial pattern of the age-standardised heat-related excess mortality, calculated as relative risk (hot Julys of 2006 and 2010 compared to the cooler Julys of 2007-2009). Values greater than 1 indicate an increased risk. A value of 1.5 means that the risk in the respective planning area (PLA) is 1.5 times higher in proportion to the average of the relative risk of all PLAs

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Fig. 29: Relative risks for patient admissions in hospitals for ≥ 65-year-olds with diseases of the respiratory system during the summer months of 2000-2009 in Berlin for the patients' places of residence (postcode areas). The red dots indicate the significant clusters with increased risk. Values greater than 1 indicate an increased risk. A value of 1.5 means that the risk in the corresponding cluster is 1.5 times higher than outside of the cluster. In addition, the risks of the postcode areas within the clusters are shown in quartiles

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Tables

Tab. 1: Categories and methods for identifying the areas having special urban-climatic drawbacks

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Tab. 2: Recommendations for measures specific to spatial units as the third main level of the planning advice map for the urban climate of Berlin 2015

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Tab. 3: Overview table of studies investigating the impacts of thermal load and air pollution on health in Berlin (as of 2015, sample)

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Tab. 3: Overview table of studies investigating the impacts of thermal load and air pollution on health in Berlin (as of 2015, sample)

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Tab. 4: Annual overview regarding the heat-related excess mortality based on the heat-event-based risk model by Scherer et al. (2013). The number of heat waves (heat events) per year (N), the sum of heat wave days per year (days), the mean daily rate of the excess mortality (rate) and the number of excess deaths per year are listed

XLSX-Document Document: Scherer et al. 2015

Tab. 5: Expected cases on day basis for fully inpatient admissions (PA) of the total of all age groups and for ≥ 65-year-olds as well as deaths (D) in hospitals for diseases of the cardiovascular (CVS) and respiratory system (RS) in Berlin in the mean of the summer periods (June-September) of 2001-2010 and 2021-2030, taking the influence factors population prognosis, air temperature projections and air temperature effects into account

XLSX-Document Document: Scherber 2014