A total of 125 questionnaires were completed via face-to-face interviews in Potsdam. This generated the data base for the analysis and the results presented below.

The following three questions were selected and combined to formulate the factor “acceptance”:

• Q4.7: “In your opinion, how important should wind energy be for the energy production in Germany?”,
• Q5: “In general, what do you think about renewable energies, such as biomass, solar or wind energy?“,
• Q12: “Would you accept more wind turbines in the surroundings of Potsdam?“

As we had high expectations from the dwellers from Potsdam, only positive answers for all of the three questions were counted as having a “high acceptance” of wind energy. Then the level of acceptance of wind energy was linked to various factors to test the corresponding hypotheses, introduced in the methodology before.

Respondents came from 20 different districts of Potsdam. The majority of respondents lived in the city centre (19,2%) and in Babelsberg (16,8%).

Table 1: Number of respondents from the different districts of Potsdam.

Figure 1 shows for how long respondents had lived in their place of residence at the time of the interview. As one interviewee was not willing to share his/her place of residence, 124 answers were collected. A total of 48 respondents (38.7%) indicated that they have lived in Potsdam for more than 10 years. A further 38 respondents (30.6%) have lived in Potsdam between 1 and 5 years. Respondence rates were almost evenly distributed between the respondents who had lived in Potsdam for 6 to 10 years (16.1%), and those who had lived in Potsdam for less than one year (14.5%).

Fig. 1: Time designation for current residence (n=124)

Figure 2 describes the perceived level of knowledge of the different energy sources, i.e. gas; oil; coal; nuclear; biomass; solar; and wind energy. Respondents rated their feeling on how informed they were for each of the above listed energy sources. The rating system included the following categories: “very bad”; “rather bad”; “rather good”; and “very good”.

Fig. 2: Knowledge about the different energy sources (n=125)

Solar energy was selected as the highest response for “rather good” informed as perceived by the survey respondents. Solar and wind energy were selected most often by respondents for the categories of “very good” and “rather good” in the respondents' perception of how informed they felt.

Conversely, solar and wind energy were selected the fewest number of times for being “rather bad” and “very bad” in the respondents' perception of how informed they felt. On this basis we can state, that dwellers of Potsdam feel well informed about the non-combustible renewable energy resources, compared to the other surveyed sources of energy.

Figure 3 indicates the level of importance as perceived by the respondents of the different energy production methods. Importance was ranked into the three categories of “high”, “medium”, and “low” for the various energy sources, namely natural gas; oil; nuclear; biomass; solar; and wind energy.

Fig. 3: Level of importance of different energy sources

The bar graph shows an increasing level of importance from nuclear energy over natural gas to wind and solar energy. Solar energy was selected by respondents the most often with “high importance” with 105 answers (84%) in this category. Moreover, only 18 respondents (14.4%) claimed that solar energy is of “middle importance “and only 2 respondents (1.6%) indicated a rather “low importance” for solar energy. Wind energy has almost the same preference as solar energy. A total of 91 (72.8%) responses indicated the “high importance” for wind energy. “Middle importance” received slightly more responses, 12 responses (9.6%), in the case of wind energy than in the case of solar energy. The category of “low importance” received 2 responses (1.6%) more for wind than in the case of solar energy (2 responses).

Biomass, in comparison to wind and solar energy, shows a lower importance with 52 responses for the category of “high importance” (41.9%), and 57 responses for the “middle importance” (46%) category. In contrast, nuclear energy received 90 responses (72%) for the category of “low importance”, 27 responses (21.6%) for “middle importance” category, and 8 responses (6.4%) for the category of “high importance“. A similar trend was found for coal and oil. In general, renewable energies, such as solar and wind energy have a higher importance than nuclear energy or coal, according to the respondents. It can be concluded that dwellers of Potsdam do not only feel more informed about solar and wind energy than about other energy resources but also consider them the most important sources of energy production.

As Figure 4 displays, the overall opinion on renewable energies is very good in Potsdam. 109 respondents (87.2%) think “a lot” or “rather a lot” of biomass, solar, and wind energy. Only 1 respondent (0.8%) thinks “rather less” of renewables and no one indicated that they do “not much” value renewables.

Fig. 4: General opinion of renewable energies

In question 6, two sub-questions were applied (Q6.1, Q6.2). Respondents were asked to indicate whether they consider price (Q6.1) and/or renewable energies (Q6.2) when choosing their energy provider. Respondents were allowed to pick any combinations when answering the sub-questions. The results are as follows (Table 2):

Table 2: Number and percentage of respondents who do or do not consider price or renewable energy utilization when choosing their energy provider

According to our results, both price and renewable energy sources are considered by numerous respondents when they choose their energy provider. 85 respondents (68%) consider price as an important factor while 40 of them (32%) pay no particular attention to the price of energy. 96 respondents (77%) do consider renewable energy sources when choosing energy provider while 29 (23%) do not deliberate using green energy.

The applied questionnaire provided the opportunity to assess the spatial differences of the attitude towards renewable energy utilization within Potsdam. According to their responses, almost all respondents support renewable energy production to a certain extent (Q5). We found the spatial pattern of the intention of using green energy an interesting field of research. For this purpose, 123 questionnaires provided valid and useful information. Two questionnaires were omitted as these respondents were not willing to tell the exact place of their residence within Potsdam.

In question one (Q1), respondents were asked to name the district where they lived when filling out the questionnaire. The districts named by respondents were aggregated and as a result Potsdam was divided into five units. These units do not have any kind of administrative role, as they were formed by our project group based on their location and rent indices (“Mietspiegel”). Rent indices of units were based on the 6/2016 and 7/2016 “Mietspiegel” of Wohnungsboerse.net. The prices in those districts unmarked by respondents were not taken into consideration when calculating the rent indices of the five units. Additionally, forming similarly-sized subsamples (with a number of responses between 20 and 30 in each unit) was a primary consideration. After establishing subsamples, the number of responses per units was as follows (Table 3):

Table 3: Number and percentage of responses per units

In 4 out of 5 subsamples (“Babelsberg”, “Innenstadt”, “Nord”, and “Nördliche und Westliche Vorstädte”), more than 80% of the respondents answered “yes” Q6.1 (“Do you consider renewable energy utilization when choosing energy provider?”), while in one subsample (“Süd und Südost”) slightly more than 50% did so. Figure 5 is a visual representation of the answers received.

Fig. 5: Proportion of respondents who consider renewable energy when choosing their energy provider (figure: B. Dienes)

For question seven (Q7), interviewees were given a set of 14 statements to which they could indicate if they agreed with the statements, if they disagreed, or if they were unsure/had no opinion. The statements reflected positive or negative attitudes towards wind energy and wind power plants. The statements were randomly ordered and did not allow an inference on a general flow or direction of the matrix answers.

Fig. 6: Agreement or disagreement of interviewees to statements about wind energy

A large majority of interviewees in Potsdam (79%) agreed that wind energy is a (suitable) alternative to nuclear energy (cf. Figure 5). Respondents perceived wind power plants to be a technical innovation (77.6%) and acknowledged the potential of wind power plants to reduce environmental pollution; including greenhouse gases (74.4%). More interviewees agreed (62.4%) than disagreed (21.6%) to the statements that wind energy usage secures development options for future generations by creating employment and economic growth (53.6%).

The negative effects were analyzed and the topics “destruction of landscape” and “noise emissions” showed the smallest differences in agreement or disagreement. More people agreed that wind turbines produce noise (44% agreed, 37.6% disagreed) and destroy the landscape (48% agreed, 42.4% disagreed) than disagreed. Including interviewees that were unsure/had no opinion with those who disagreed, this combination of responses is larger than those who agreed. This picture looks different for other negative impacts of wind power plants. The majority agreed (60.8%) that wind turbines endanger wildlife, especially birds and bats. There are other negative impacts which are either not present in the people’s minds (“I don’t know”) or controversial and (potentially) perceived as false claims (“disagree”). This applies to the reflection of sunlight on the turbines and the effect of ice shedding. Both of these statements were only “agreed” within a range of 5%-15% of all questionnaires. The majority of interviewees in Potsdam either did not know about them or disagreed with them.

For three of the statements a clear trend in either direction could not be determined. Almost equal numbers of respondents agreed that wind turbines generate shadow flicker (36%) or did not know that the wind turbines generated shadow flicker (36.8%). Fewer respondents disagreed with this statement (27.2%). We have a somewhat similar picture when it comes to the statement regarding wind turbines as investment opportunities, however more respondents agreed (44%) with this statement. A combined 56% of respondents did not agree i.e. 28% disagreed and 28% were unsure. The same applies for the third statement that “Energy saving is better than the promotion of wind turbines”: 46.4% of the respondents agreed with this statement, whereas 24.8% disagreed and 28.8% were unsure.

The statement that received the highest consensus throughout the whole statement list, 89.6% of interviewees, had the common view that wind energy conserves non-renewable resources.

Figure 7 shows that most of the respondents (45.6%) think that people from their social environment have a positive opinion of wind energy. A total of 10 respondents (8%) think that their social environment has a negative opinion towards wind energy, whereas 48 respondents (38.4%) think that the people in their social environment are neutral, and 10 respondents (8%) could not estimate the general opinion on wind energy at all.

Fig. 7: Opinion poll of the respondents social environment about wind energy

The applied questionnaire provided opportunity to assess respondents’ perception regarding the location of wind turbines around Potsdam. For this purpose, a map was attached to the questionnaires. Each respondent was asked to show on the attached map the location of wind turbines that can be found in the proximity of Potsdam. Respondents were not asked to show the location of wind turbines located the closest to Potsdam in order to have a better understanding of the factors modifying the respondents’ perception. The attached map was supplemented by a grid in order to facilitate clear answers and to simplify the analysis. Some respondents marked areas that were not covered by the attached map, while others used vague terms to describe the supposed location of wind turbines. In these cases possible corresponding cells were considered and used where suitable. However, some answers had to be removed due to indeterminable locations. Some respondent decided to mark more than one cell; in these cases all answers have been considered.

Out of 125 respondents, 50 decided to show the location of wind turbines around Potsdam on the attached map. After the above introduced disambiguation procedure, 75 responses could be involved in the analysis. The most selected cell was B1 with 18 responses, representing the close proximity of the town of Nauen. In addition, cell C2 (motorway exit to Nauen) and D8 (close proximity of the municipality of Michendorf) were popular answers, both were selected 5 times each. G7 (close proximity of the municipality of Großbeeren) received 4, while B4 (close proximity of the town of Ketzin/Havel) and D2 (close proximity of the town of Falkensee) received 3 guesses. All other cells received 0, 1, or 2 guesses (cf. figure 8).

Fig. 8: Actual distribution of wind turbines in the surroundings of Potsdam (blue dots) and the number of guesses by respondents regarding where these wind turbines are located (squares in shades of red) (figure: R. Camargo & B. Dienes).

Figure 8 is based on the map that had been attached to the questionnaires. As explained before, during the interviews, respondents were asked to mark cells in which they believed wind turbines were located. Afterwards, the number of guesses were summarized on a cell-by-cell basis and visualized by different shades of red. In order to check the exactness of the guesses received, actual location of wind turbines in operation and wind turbines under construction was added to the map from the website of MetadatenVerbund and visualized by blue dots. The relationship between the perception of respondents and the actual location of wind turbines is discussed here.

Fig. 9: Number of days respondents spend their leisure time in the surroundings of Potsdam (n=125)

A total of 110 (88%) respondents (cf. figure 9) spend their leisure time at least once per month in the surroundings of Potsdam. With 42 respondents (33.6%), the largest group, spending 1 to 3 days per month in the surroundings of Potsdam. The next largest group of respondents spend 4 to 6 days in the surroundings of Potsdam (33 respondents, 26.4%). One fifth of all interviewees (25) stated that they spend more than 10 days per month outside of Potsdam in their free time.

Fig. 10: Absolute frequency of the feeling of disturbance while spending recreation time in the surroundings of the city (n=125)

With a total of 116 (92.8%), the vast majority of all respondents do not feel disturbed by wind turbines while being in the surroundings of Potsdam, spending leisure time there, and pursuing leisure time activities (cf. Figure 10). A total of 8 people (6.4%) felt disturbed by wind turbines outside of Potsdam. One person (8%) was not sure if they felt disturbed or not by the wind turbines.

To determine whether this evaluation of disturbance was dependent upon the chance that people actually come in contact with wind turbines, we correlated the statements of disturbance in leisure time to the leisure time spent outside of Potsdam. We assumed that the chances of getting in contact with wind turbines, and consequently being disturbed by wind turbines, is higher the more time one spends in the surroundings of the city.

Fig. 11: Relative frequency of the feeling of disturbance while spending leisure time to the amount of days spent in the surroundings of the city (n=125)

The results in figure 11 show that there is no correlation between spending more time in the surroundings of the city and feeling more disturbed by turbines. In 4 of 5 categories, between 5% and 10% of the interviewees felt disturbed. There was no visible increase in this value if they spent more days in the surrounding areas. In the category with the second highest amount of days spent outside of the city, no one reported feeling disturbed by the wind turbines. Possible hints for these findings are discussed in the corresponding section of the urban discussion.

A total of 63.2% of the surveyed respondents (n=79, cf. Figure 12) reported that they would accept more wind turbines in the surroundings of Potsdam. A total of 19.2% (n=24) reported that they would not agree with the installation of additional wind turbines around Potsdam and 17.6% (n=22) did not know whether they would accept it or not. Fig. 12: Number of respondents, who would accept or would not accept more wind turbines in the surroundings of Potsdam (n=125)

In this question the interviewees could choose between distances of 800m, 1000m, 1600m, 3000m and further than 3000m as the appropriate distance for situating wind turbines away from residential areas. Approximately a third of the respondents (36,8%, n=46, cf. Figure 13) responded that wind turbines should be installed 3000m from residential areas. Whereas 23% (n=29) agree upon a 1600m distance; 18.4% prefer a distance further than 3000m; 16.8% (n=21) think that a distance of 1000 is sufficient; and 4% (n=5) of respondents agree upon a distance of 800m.

Fig. 13: Number of respondents who agreed with a certain distance (800, 1000, 1600, 3000 or more than 3000 meter) between wind turbines and residential areas (n=125)

In order to simplify our analysis, age of respondents has been grouped. The age categories were “under 20 years,” “20-30 years,” “31-40 years,” “41-50 years,” “51-60 years,” “61-70 years,” “71-80 years,” and “over 80 years old”.

Fig. 14: Number of respondents within a certain age class (n=125)

As displayed in figure 14, the majority of respondents are in the group of “20-30 years” with 44 responses (35.2%); these interviewees were mainly students. The second largest group is the group of “31-40 years” with 25 respondents (20%), the third one is the group of “51-60 years” with 15 respondents (12%), and the fourth is the group of “41-50 years” with 14 respondents (11.2%). Nine respondents (7.2%-7.2%) are both in the group of “under 20 years” and the group of “61-70 years”. The group of “71-80 years” consists of seven respondents (5.6%) and two respondents are over 80 years (1.6%).

Fig. 15: Social acceptance within age groups (n=125)

Within the age category of “31-40” a total of 72% of these respondents held a positive attitude towards wind energy (cf. Figure 15). The age groups “under 20” and “20-30” were 67% positive and 64% positive respectively. The two respondents in the age group “over 80” were 50% positive and therefore 50% negative in their attitudes toward wind energy. In the remaining age groups, the majority of respondents did not report a positive attitude towards wind energy.

Correlation between age and social acceptance was tested statistically. Due to the low number of responses in the age group “over 80” (<5), a new group was formed for the correlation analysis by merging the age groups “71-80” and “over 80”. This new group represents respondents in the age group “over 70”. The resulting correlation coefficient was -0.88 which shows a very good correlation.

As it can be seen in figure 16, majority of respondents (44.8%) have a university degree. A similar number of respondents have completed a vocational training (20.8%) and acquired A-levels (18.4%). The fewest respondents finished secondary school (6.4%) or junior high school (4%) only. 5.6% of respondents provided other, previously not categorized, answers or were not willing to answer this question. Citizens with university degree (highest rank) and vocational training (2nd highest rank) were determined as respondents with the highest level of education; followed by interviewees with A-levels (3rd highest rank); and then respondents finishing secondary school (4th rank) and junior high school (5th rank) exclusively. It is important to note that a number of the responses were not equal in the assessed groups. However, a minimum number of 5 respondents per group fulfilled the minimum requirement for a statistical analysis with the exception of the uncategorized answers. Our approach is admittedly not completely prudent as, inter alia, no further information about the field of education was required from respondents at this question.

Fig. 16: Level of education among respondents (n=125)

Figure 17 represents the level of acceptance within the groups introduced above. The highest level of acceptance of wind energy was found within those reporting secondary school education as their highest level of education (63%); followed by university degree (59%). The groups of respondents with vocational training (54%) and A-levels (52%) have only a slightly lower level of acceptance towards wind energy. The “junior high school” group had a lower acceptance (20%). In order to test the relationship between the highest level of education and attitude towards wind energy, a correlation analysis was performed. The resulting correlation coefficient (0.638123425) shows a “good” correlation between these factors.

Fig. 17: Social acceptance within education level (n=125)

Fig. 18: Social acceptance linked to occupation (n=125)

To analyse whether social acceptance is linked to occupation, every answer towards occupation was categorized according to the 10 main classifications of occupations 2012 (KldB 2010) provided by the “Bundesargentur für Arbeit”. As unemployed and retired people also answered the questionnaire, an 11th group named “without occupation” was created.

The largest occupation group, with over a third of the people interviewed, formed the category “health, social issues and education.”. This was also linked to the large number of people in the age category “21-30,” which were very often students. The second largest occupation group (13%) was “commodity trading, commodities brokerage, tourism, and sales.” The following three occupation groups were underrepresented: “agriculture, forestry, livestock and horticulture,” the group of “extraction, material production, manufacturing and product use”, and the group of “logistics, transport, safety and security”. The occupation group “military” was not represented at all in the responses received.

At a first glance (cf. Figure 18) there is no significant difference in the social acceptance that can be observed within the higher represented occupation groups (ranging from 70% to 91%). However, in the occupation group “architecture, building, technologies, surveying and construction”, which is quite well represented (6% of total), there is a lack of acceptance as only 43% of the group responded positively to all the questions used for this analysis (Q4.7, Q5, and Q12).

In order to test the significance of the differences in social acceptance within occupation categories, the Chi-squared test was applied. To avoid inaccuracies that could derive from the low number of responses in some response groups, only occupations with greater than 5 responses were included in the statistical analysis. The resultant p-value (0.212763179) shows that the difference is greater than 0.05; on this basis we can state that significant differences can be observed between the responses provided by different occupation groups.

The aim of question 17 was to make people think about how cities could contribute to energy transition. A total of 56% of the citizens interviewed answered this question. The citizens of Potsdam submitted 37 different ideas (cf. Table 3).

The most common ideas were as follows: 9.6% of the citizens believed that the expansion of solar energy by installing solar panels on inner-city roofs is a possibility to contribute to the energy transition. It was followed by the idea of financially supporting renewable energy projects, which was mentioned by 8.8% of respondents. The supply of information on energy transition was considered to be an important factor by 8% of the respondents. Saving energy at home is considered to be a contributing factor by 7.2% of respondents, and 4.8% stated that saving energy by a reduction in lighting at night (e.g. in streets, of shop windows) contributes to the energy transition. Promotion of electro-mobility was also stated by 4.8% of respondents.

Table 5: Ideas on how cities could contribute to the energy transition

In the applied questionnaire, gender of respondents was recorded in order to compare the attitude towards wind energy among female (53.6% of total) and male (46.4% of total) respondents.

As figure 19 indicates, 51% of the interviewed female and 59% of the interviewed male respondents had a high acceptance of wind energy. Here, men have a slightly higher acceptance of wind energy than the female respondents. Chi-square test was used to check whether the difference is statistically significant. As the chi-square statistic was 0.7771, the p-value was 0.378035 at p < 0.05, this result is not significant statistically.

Fig. 19: Social acceptance to wind energy due to gender (n=125)

As shown in figure 20, positive attitude towards renewable energies is almost equal for both male and female respondents. The female respondents, however, tend to be neutral more often than men.

Fig. 20: What is your general opinion about renewable energy e.g. bio-, sun-, windenergy? (n=125)

The majority of all respondents (cf. Figure 21) would accept more wind turbines around Potsdam. The female respondents tended to have a more positive attitude towards new wind energy developments within the area.

Fig. 21: Would you accept more wind turbines in surroundings of Potsdam? (n=125)

References

• Bundesagentur für Arbeit, 2015, Klassifikation der Berufe 2010 - KldB 2010. [online] Available at: https://statistik.arbeitsagentur.de/Navigation/Statistik/Grundlagen/Klassifikation-der-Berufe/KldB2010/KldB2010-Nav.html. Last accessed: 07th January, 2017.
• MetadatenVerbund, 2016, Windkraftanlagen im Land Brandenburg. [online] Available at: http://www.metaver.de/kartendienste;jsessionid=BAA5C7BCFAF72E5F466FA18B1C6805C0?wms_url=http%3A%2F%2Fmaps.brandenburg.de%2Fservices%2Fwms%2Fwka%3FREQUEST%3DGetCapabilities%26SERVICE%3DWMS&ID=http%3A%2F%2Fmetaver.de%2Figc_bb%2Flfu%2345C506E5-3E9D-4DE2-9073-C3DB636CE7CF. Last accessed: 13th September, 2016.