Bioclimatic potential of European locations: GIS supported study of proposed passive building design strategies

According to the Köppen-Geiger climate classification, Europe is under the influence of at least ten different climate types. Thus, various climates can be found, from the polar tundra and cold climate in the Alps and northern European regions, to hot-arid climate in southern parts of Spain. This level of climate diversity makes the European territory interesting for the analysis from the bioclimatic building design perspective. Therefore, the purpose of the research was to assess the bioclimatic potential of selected European locations. The calculation of bioclimatic potential was done by acquiring the typical meteorological year (TMY) data comprised of climate characteristics, such as air temperature, air relative humidity and received solar irradiance, which was later processed by BcChart tool. In order to make bioclimatic potential maps of Europe, the points with uniform point sampling were generated. Furthermore, several additional locations of great interest were selected based on population density. The bioclimatic potential was used to define the prevailing passive building design strategies and measures at the analysed locations. At the same time, the in-depth analysis was conducted using the geospatial data and GIS tools, where the bioclimatic potential results at the selected locations were additionally analysed in relation to Köppen-Geiger climate types. The resulting bioclimatic potential maps can be used as a relevant onset for the policy makers in order to improve regional development strategies for building design.


Introduction
For building performance, the climate of a specific location represents both a limitation as well as a potential for increased indoor occupant comfort and wellbeing.Consequentially, climatic conditions also determine to a substantial degree the energy efficiency of buildings, which is particularly prominent in the case of envelope dominated buildings [1] [2].Therefore, taking into account the opportunities and limitations of a particular climate at an early (i.e.conceptual) stage of building design can contribute to the overall higher efficiency of the building.The described process is commonly referred to as bioclimatic or climate adapted design, where the climatic conditions are the basis for the design of passive building envelope elements that enable environmental modulation between the exterior and interior without relying on the provision of energy through active systems (e.g.heating and/or cooling systems) [3] [4].In its essence, the bioclimatic building design strives to increase the portion of a year when a building is in free-run operation, which means that indoor comfortable conditions are provided exclusively by the external environmental conditions modulated via the building envelope.
Because of the above-mentioned reliance of bioclimatic buildings on the climatic conditions of a location for their performance, the determination of bioclimatic potential (i.e.duration of time when indoor comfort can be facilitated by passive building design strategies) at a specific location is an essential step of the design process [5] [6].Calculation of bioclimatic potential can be achieved using bioclimatic charts [6] [8] relating selected climatic variables, usually dry bulb temperature and relative humidity, to the indoor occupant comfort demands (i.e.comfort zone).Simultaneously, the bioclimatic charts can also be used to determine the potential effect of the selected passive strategies for the increase of the achieved duration when a building under specified climatic conditions can be in free-run operation.However, the process of determining the resulting bioclimatic potential through climate analysis is usually omitted at early design stages, as it is often viewed as unnecessary by designers, who rely on generic solutions presumed for a specific climate type or region.For example, it is commonly supposed that buildings designed in the geopolitical region of Central Europe [9] should be optimised for a heating season, while overheating does not represent a potential concern for the provision of indoor occupant comfort [10].Such generalisation by the professional design community is unusual, as the mentioned region is comprised of 1,036,380 km 2 , nine countries (i.e.Austria, Czech Republic, Germany, Hungary, Lichtenstein, Poland, Slovakia, Slovenia and Switzerland) [9] and five different Köppen-Geiger climate types (i.e.Cfa -temperate humid with hot summer, Cfb -temperate humid with warm summer, Dfb -cold humid with warm summer, Dfc -cold humid with cool summer and ET -polar tundra) [11].Furthermore, the latitudes of locations in the Central European region vary substantially (i.e.45° N to 55° N), affecting the amount of received solar irradiance [12], which is one of the most influential climate factors determining the thermal response of buildings [5].Based on the above example it becomes evident that climate conditions, defining the performance and design of bioclimatic buildings, cannot be treated as discrete values demarcated by political or geographical constructs, but should be viewed as a geospatial continuum with one climate type slowly morphing into another.In this respect, even the well-established climate classification schemes (e.g.Köppen-Geiger, Thornthwaite, etc.) devised by climatologist are to some degree misleading, because different climate types are presented as discrete categories due to practical reasons of exposing distinct climatic characteristics and general patterns [11][13] [14].It should also be mentioned that as these climatological classifications are based on climate parameters not directly relatable to the design of buildings (e.g.temperature and precipitation in the instance of Köppen-Geiger classification [11] [14]), their applicability in the bioclimatic building design process is limited.
Determination of bioclimatic potentials over selected regions and/or countries has been the subject of numerous previous studies [5][6] [15][16] [17][18] [19].However, these were predominantly focused on the analysis of bioclimatic potentials at specific locations.This means that variance of geospatial distribution of bioclimatic potentials was reduced to conditions representing a specific geographic location, limiting the spatial resolution of the conducted analysis to a series of points.Moreover, because these studies have been executed either for specific countries (e.g.China [15], Mexico [16], Cyprus [18]) or smaller regions covering parts of a country or countries (e.g.north-east India [19], Alpine-Adriatic region [5]), their scope is limited to a specific state or region.Therefore, the main objective of the present study is to interpret climatic conditions of the European continent through the lens of bioclimatic potentials calculated by BcChart tool developed by Košir and Pajek [20] and to present their geospatial distribution using a geographic information system (GIS) and its data processing tools.The obtained results using recent geospatial and climatic data will give a clear indication of the potential for providing indoor occupant comfort using solely passive bioclimatic strategies.Furthermore, an additional investigation was conducted for selected most densely populated European locations indicating specific bioclimatic potentials at areas of greatest interest to designers, policy makers and other interested stakeholders.Overall, the results of the presented analysis can be used as design guidelines for selecting appropriate passive bioclimatic strategies, as well as a basis for the formation of building codes that would promote the use of passive building envelope integrated technologies.

Determination of bioclimatic potential
The bioclimatic potential of the selected locations was determined by BcChart tool [20] [21].The tool is based on Olgyay's theory of bioclimatic charts, which can be a starting point for the bioclimatic design of buildings.To use bioclimatic charts as such, two locational climate characteristics are needed -temperature (T) and relative humidity (RH) of air.Although these two attributes are far from being enough to accurately calculate the building thermal or energy performance, they can be used for a quick and general overview of the effective passive building design measures, making the bioclimatic chart useful in the early stages of building design.However, Pajek and Košir [5] stressed that solar radiation is nevertheless so important that its impact cannot be ignored even in the first stages of building design.Therefore, the BcChart tool is adapted to take into account global solar irradiance (G) data as well as the air temperature and relative humidity.For the purpose of this study, BcChart v2.1 was used [20].The entire required climate data (i.e.T, RH, G) were attained from the Photovoltaic Geographical Information System (PVGIS 5) [12].In particular, the typical meteorological year (TMY) data for the period between 2006 and 2015 were used.The idea of the BcChart tool is to draw a bioclimatic chart for a selected location and then determine on its basis the bioclimatic potential of that location.The yielded bioclimatic potential represents a fraction of year, when the combinations of temperature, relative humidity and solar irradiance fall in or out of the thermal comfort zone.Additionally, the combinations define if specific passive building design solutions can be used to achieve thermal comfort or if active measures (e.g.mechanical cooling, conventional heating) are needed [21].The comfort zone is defined roughly between 21 and 27 °C (lower at higher RH values).Definitions of each bioclimatic potential corresponding to certain passive measure suggested by BcChart are explained in Table 1.In the cases where the conditions fall inside the comfort zone, comfort can be achieved either by shading (Csh) or by using solar energy (Csn) (Table 1).Further on, the segments presented in Table 1 may also be combined into three main categories: comfort zone (Cz = Csh + Csn), shading needed (Sh = Q + A + M + V + Csh) and sun needed (Sn = Csn + R + H).If values A, M and V are combined into AMV, they represent a share of year, when passive measures for heat exclusion and heat dissipation are recommended (e.g.shading, high thermal mass, etc.).

Geospatial analysis
The BcChart tool is designed to calculate the bioclimatic potential of a selected location.The selection of the location can yield various insights into the spatial characteristics of the calculated data.In this study, the geospatial, i.e.GIS tools in the open source environment QGIS [22] were used to provide referenced spatial coordinates of locations for bioclimatic potential calculation and for the visualisation of calculated parameters.
Firstly, the values of bioclimatic potential for the whole territory of the European continent were analysed.We decided to analyse the spatial aspect of bioclimatic potential in the selected area.Thus, a spatial interpolation based on the known values of bioclimatic potential was used.In order to perform interpolation, point sampling covering the majority of the study was generated.Using GIS tools in QGIS, we derived a vector layer of points having uniform geospatial distribution with a 100 km grid.This uniform grid of points was calculated for the rectangular extent of Europe and then clipped by the actual shape of the continent, which in the end resulted in 908 points for the calculation of bioclimatic potential values (Figure 1).Next, the BcChart tool was used to calculate bioclimatic potential parameters for all 908 points.After obtaining the parameters (e.g.H, R, Cz, etc.; see section 2.1), we performed the interpolation of the selected parameters to obtain interpolated surfaces over the entire continent.The interpolation was implemented using Inverse Distance Weighted (IDW) algorithm in GIS software QGIS, in which the sampled points are weighted according to the distance from a point at an unknown location.We decided to provide interpolated surfaces only for the selected bioclimatic potential parameters, namely H, Cz, Sh, and a summed value of A, M and V (see section 2.1, Table 1).In the end, each interpolated surface was clipped to the extent of vector geospatial layer of Europe with the area of approx.10 million km 2 , which was acquired from the ArcGIS webpage [23].Finally, for the visualisation of results, the interpolated raster surfaces of the selected bioclimatic potential parameters were smoothed using Gaussian filter in order to obtain continuous presentations of results.
In the second part of the research, the spatial aspect of the study is focused on the analysis of the bioclimatic potential parameters with respect to the population density and spatial distribution of various climate types considering the extent of the European continent.As the population density layer, we used the open and freely available Global Human Settlement Layer (GHSL), provided by EU Science hub [24].It is a raster layer with 1 km resolution containing the number of people living in each 1 km 2 raster cell.The third used spatial layer containing climate type polygons was sourced from World maps of Köppen-Geiger climate classification (Figure 2) with the resolution of 5 arc minutes for the period 1986-2010 [25].The main aim of the location selection was to extract locations of the most densely populated areas in Europe.The simplest method is to use locations of the raster cells with the highest values.The results are locations concentrated in a few very densely populated areas in Europe.Our method uses the population density raster layer as the initial dataset.It consists of several steps that were implemented using GIS software QGIS: 1. Raster reclassification; 2. Applying the majority filter; 3. Vectorisation; 4. Calculating centroids; 5. Iterative removal of neighbour points; 6. Extracting climate properties of each point.
The input raster layer was firstly reclassified to a binary raster with cell values of 0 or 1. Setting different thresholds for reclassification allows for manual optimisation of the number of selected points.We selected the threshold to be 4000 people per cell.The result was a relatively "noisy" binary raster, with values set to 1 where population density exceeds the value of 4000.The next operation is the application of the majority filter to exclude the small groups of cells with value 1 that do not represent significantly large densely populated areas.The modification of the radius for the majority filter is another option to modify and optimise the selection of the points.The radius of four cells was selected.Each group of the cells with value 1 should then be selected as one location.The optimal GIS solution for this task is to automatically convert these groups of raster cells to polygons with the vectorisation tool.Once we have polygons, the centroids can be determined per each polygon, representing the location of each group of cells.In the end, we used the spatial overlay operation using the selected points and climate type layer.For each point, the climate properties were extracted, depending on the corresponding climate type polygon.
To evaluate the selection of the locations, two ratios were calculated.For the first one, we calculated 50 km buffer polygons around the selected points and calculated the sum of these areas, removing the parts that stretch into the sea.The selected points with 50 km buffer occupy approx.6 % of the total area of the European continent.The second ratio is focused on comparing the population on the same buffered areas, compared to the total European population calculated by summing all the raster values.The result shows that approx.35 % of the total population in Europe live in buffered areas.This means that we selected locations where 35 % of Europeans live in the circle with 50 km radius, representing only 6 % of the total area of Europe.After the points of interest had been obtained, which correspond to the most densely populated areas in Europe, we used BcChart to calculate the bioclimatic potential for these points.

Bioclimatic potential of Europe
With respect to evenly distributed sample points with calculated values of bioclimatic potential, the interpolation operations for selected parameters using IDW algorithm was performed.Firstly, we calculated the surface for parameter H, which describes the share of year when conventional heating and heat retention bioclimatic strategy are necessary.The results can be seen in Figure 3. Higher H values describe locations where there is no potential for passive solar heating, so the indoor comfort must be achieved by conventional heating and heat retention.The third parameter selected for the interpolation was parameter Sh, which represents the share of year when shading should be applied in order to achieve comfortable conditions.The interpolated values of Sh can be seen in Figure 5, which shows the duration of a year when effective shading of transparent building envelope elements has to be applied in order to facilitate indoor comfort and prevent overheating.In the end, we calculated the composite values of three bioclimatic potential parameters, namely A, M and V.The summed values of the selected parameters, which were interpolated across Europe, represent the potential for using passive building design measures for hot-arid and hot-humid climates, such as high thermal mass, night-time ventilation, etc.The interpolated values are shown in Figure 6. and demarcate the areas of the European continent where in addition to effective shading (Figure 5) also other design measures are necessary to passively control overheating of buildings.

Bioclimatic potential of the most populated areas
The second part of the study focuses on the analysis of bioclimatic potential at the most densely populated areas of Europe.Bioclimatic potential values of Q, A, M, V, Csn, Csh, R, and H were calculated and later visualised using pie charts, which can be seen in Figure 7.Each of the pie charts is positioned at one of the 85 most densely populated areas, cumulatively representing 35 % of the European population.Individual pie chart slices illustrate the portion of the entire year when a particular passive building design measure should be used in order to achieve or maintain thermal comfort in a building.In its essence, each individual pie chart clearly defines what should be the focus of building designed at a specific location.that, as expected, in most of the cases the resulting bioclimatic potential overlaps to a large extent the climate type distribution over Europe.In particular, as described above, similarities can be drawn between bioclimatic parameters H, Cz, Sh and AMV and the Köppen-Geiger (K-G) climate classification.Observing Figures 2 and 3 we can conclude that there is an evident relation between the H value and the K-G climate types.To be precise, cold climates (i.e.D) are all characterised by an H value above 50 %.Similar relation can also be found for other parameters, as presented in Figure 8.However, the observed parameters of bioclimatic potential are scattered most in the Cfb climate type (i.e.temperate climate with warm summers), especially the H value (Figure 8a), the Sh value (Figure 8c) and the AMV value (Figure 8d).The stated could be a consequence of using the Köppen-Geiger climate classification map with not high enough resolution, so that some locations with Dfb and Cfa climates might be labelled as Cfb climate.Another possible cause of the large distribution of results (Figure 8) may also be that bioclimatic potential calculation with BcChart was made with TMY data for the period between 2006 and 2015, unlike the utilized Köppen-Geiger classification, where climate data from 1986 to 2010 were used.Nevertheless, it could be claimed that bioclimatic potential parameters are quite typical for each of the four most represented climate types (Figure 8).The stated was expected because both methods -the K-G climate classification as well as bioclimatic potential calculation method -use air temperature as one of the input parameters.However, in the instance of the K-G classification the amount of precipitation is taken into account besides the air temperature, while in the case of bioclimatic potential, additional parameters used in the calculation are relative humidity and incident global solar irradiance.This results in relatively large variance of the observed bioclimatic parameters for the Cfb climate (Figure 8), where the solar irradiance can have the largest impact on the calculated results.Contrary, the hotter the climate, the more the K-G climate type of a location is comparable to its bioclimatic potential, because in this case the impact of solar radiation on the calculated bioclimatic potential is smaller (e.g. received solar irradiation marginally influences the achieved values of Cz and H).The same goes for the extremely cold climates.
In the end, the findings of the conducted study have significant importance for (bioclimatic) building design, as they show that certain design presumptions do not stand in line with observed bioclimatic potentials of a particular climate.For example, it was demonstrated that even at specific locations, which are believed to be cold (i.e.Dfb) or have a temperate climate (i.e.Cfb), the Sh and AMV values can significantly deviate from the median value (Figure 8c,d).In this context, the proposed passive building design measures based on the calculated bioclimatic potentials (i.e.Sh and AMV) deviate from the general presumptions of bioclimatic building design.For instance, parts of Eastern Europe (e.g.Ukraine) have very high H values (i.e.extensive conventional heating is needed, see Figure 3), while at the same time they have for their high latitude an unexpectedly high Sh value (i.e. a lot of shading is needed during summer, see Figure 5).The latter parameter significantly affects the resulting Cz value (i.e.achieved comfort, see Figure 4).The opposite situation was identified in the southern part of Great Britain, where the bioclimatic potential analysis exposed that this region is characterised by low H values (i.e.conventional heating of moderate intensity is needed) and pleasant duration of Cz.Considering the combination of the two values it may be expected that also the Sh value (i.e.shading needed) should be high, which, however, was not the case.Therefore, it can be learnt that in this region bioclimatic design strategies and interventions are not strongly emphasized in either way -neither cooling nor heating.

Conclusion
The presented bioclimatic analysis of the European continent can represent an efficient starting point for building designers.Particularly, the results of this paper represent a relevant starting point for policy makers in order to improve regional development and building design strategies and regulations.Furthermore, the bioclimatic potential maps may support designers with suggested bioclimatic strategies and measures at a specific location in far greater detail than is attainable from general distribution of climate types or by using rules of a thumb.As an illustration, the results showed that even in some parts of Europe, where it is not intuitive to shade the transparent parts of a building envelope, it should, nevertheless, be applied in order to avoid overheating during summer.Our future work will be focused on preparing a more elaborate and user-friendly bioclimatic potential atlas of Europe.
BcChart adapted from Košir and Pajek [21].Label Colour Bioclimatic potential Suggested bioclimatic measures Q mechanical cooling and/or dehumidification needed A potential for passive solutions for hot arid climates M natural ventilation and/or high thermal mass needed V natural ventilation needed Csh comfort achieved by shading Csn comfort achieved by utilizing solar irradiation R potential for passive solar heating H conventional heating needed, focus on heat retention Sh shading needed (Sh = Q + A + M + V + Csh)

Figure 1 .
Figure 1.Uniform grid of 908 points with 100 km spacing, where bioclimatic potential was calculated.Note: Due to the used cartographic projection, the points appear unevenly distributed.

Figure 2 :
Figure 2: Climate types of Europe as defined by Köppen-Geiger [25].BWk = cold arid desert, BSh = hot arid steppe, BSk = cold arid steppe, Cfa = temperate humid with hot summer, Cfb = temperate humid with warm summer; Cfc = temperate humid with cool summer, Csa = temperate with dry hot summer (Mediterranean), Csb = temperate with dry warm summer (Mediterranean), Csc = temperate with dry cool summer (Mediterranean), Dfa = cold humid with hot summer, Dfb = cold humid with warm summer, Dfc = cold humid with cool summer, Dsb = cold with dry warm summer, Dsc = cold with dry cool summer, ET = polar tundra, EF = polar frost.

Figure 3 :
Figure 3: Values of parameter H.The higher is the H value, the longer part of the year conventional heating must be used.Secondly, the interpolated surface for bioclimatic potential parameter Cz was calculated, which represents the achieved thermal comfort by shading and/or by utilizing solar irradiation.The interpolated values for Europe are shown in Figure4.Higher Cz values represent locations, where a higher level of comfort can be achieved solely by controlling the impact of solar radiation on a building.

Figure 4 :
Figure 4: Values of parameter Cz.The higher the Cz value, the more important is the regulation of solar radiation in order to achieve comfort.

Figure 5 :
Figure 5: Values of parameter Sh, which represents the share of year when shading should be applied.

Figure 6 :
Figure 6: Values of composite parameter AMV show the amount of year when various building design measures for hot climates should be applied in order to achieve comfort.

Figure 7 :
Figure 7: Bioclimatic potential calculated with BcChart tool at 85 most densely populated locations in Europe.Pie charts represent the share of year when a distinct passive building design measure should be used in order to achieve comfort.For the explanation of the legend see section 2.1.

Figure 8 :
Figure 8: Box plot of the selected four parameters of bioclimatic potential, i.e.H (a), Cz (b), Sh (c) and AMV (d), presented for the four most represented climate types in Europe, namely Dfb, Cfb, Cfa and Csa.White line depicts the median value, coloured area represents the extent of the 2 nd and the 3 rd quartiles.