Measurement locations
The urban spaces of which the thermal conditions were assessed are all located in Amsterdam. Amsterdam is the capital and the most populous city of the Netherlands. The number of inhabitants is nearly 850,000 (CBS 2017). The climate of Amsterdam is a temperate marine climate (Köppen climate classification Cfb) and summers are normally moderately cool.
Nearly all measurement sites are located in the centre of Amsterdam (Fig. 1). They were selected because they are well-known and well-visited spaces. Well-visited locations are useful to collect a considerable number of surveys. The reason to select also well-known spaces is to enable the dissemination of the results to urban professionals, which is easier if they know the spaces and recognise the characteristics.
We assessed the thermal conditions of three types of urban spaces: (1) grey locations—impervious areas such as streets and squares, (2) green locations—green spaces such as parks existing of grass, shrubs and trees, and (3) blue locations—urban areas close to water bodies such as canals, rivers, ponds and fountains. Each location was either sunlit or in the shade of trees or buildings. On the basis of visual observations, we determined if a location was in the sun or in the shade. Locations were sunlit or shaded during the total measurement period. The measurement locations at the blue locations were always at the downwind direction of the water body and within a distance of 8 m from the water body. In total, 13 impervious urban spaces, 2 green urban spaces and 6 spaces near urban water bodies were assessed.
Table 1 gives an overview of the measured sites in Amsterdam, including the measurement date and period, the location type, the situation: sunlit or shaded, a description of the site and the Local Climate Zone (Stewart and Oke 2012) that we identified for each site. We always conducted measurements and surveys at two different locations at the same time and compared the thermal situations between the two sites to evaluate the thermal effects of green, water, and shading. The thermal effect was assessed by considering the differences in the average air temperature and physiological equivalent temperature (PET) over the entire measurement period, which is mostly from noon until the late afternoon, and the difference in the thermal experience of the respondents.
Table 1 Date of measurements, maximum air temperature measured at Schiphol airport (Ta,max), name and type of location, situation with respect to sun or shade and description of the measured urban spaces, including tree species and dimensions of the water bodies and the Local Climate Zone (Stewart and Oke 2012). The colour indicates the type of location: grey are impervious urban spaces, green are parks with grass or shrubs and blue are spaces near urban water. It is indicated if measurements were done in the sun (yellow), in the shade of trees (green) or in the shade of buildings (red). Also listed is the measured time period, the number of interviews in shade and sun, the average meteorological conditions—air temperature (Ta) and physiological equivalent temperature (PET) in the shade and in the sun, relative humidity (RH) and wind speed (u). *Measurements done at Oosterdok are not used in this paper During some days in the first measurement year 2015, we moved the weather station each hour between a sunlit and a shaded location (see Table 1). By doing so, we could in addition assess the thermal difference between a sunlit and a shaded area for one type of location, apart from the thermal difference between two types of locations. For example, from the measurements at the locations Leidseplein (impervious location E) and Vondelpark (green location O) on 30-6-2015 (Table 1), we could estimate the thermal effect of a green urban space (Vondelpark) with respect to an impervious urban location (Leidseplein) for sunny as well as shaded conditions. In addition, we could assess the shading effect of trees for a green space (i.e. Vondelpark), and the shading effect of trees for an impervious urban space (i.e. Leideplein). However, moving a weather station each hour between two locations also turned out to complicate the analyses considerably. Therefore, in the second season (2016), we measured with each mobile weather station at only one location throughout the day.
Measurement days and meteorological conditions
The dates in Table 1 show that measurements were carried out on 12 different days in the summer months (June, July and August) of 2015 and 2016. All days were weekdays. The measurements were taken during the hottest part of the day, starting from around noon until late afternoon. In 2015, four measurement days were part of a heat wave period in the Netherlands lasting from 30th of June to 5th of July 2015. A heatwave period in the Netherlands is defined by the Netherlands Royal Meteorological Institute as a period of five consecutive days with a maximum temperature above 25 °C including at least three on which the maximum temperature exceeds 30 °C. Days for which air temperatures above 25 °C and clear skies were forecasted, were chosen to carry out the measurements and the surveys. For this reason, most air temperatures measured at the urban sites reached maximum temperatures well above 25 °C. However, on some days, air temperatures remained lower than forecasted (e.g. 26 August 2016), but PET values always exceeded 33 °C in the sun, indicating a situation of at least moderate heat stress (Matzarakis and Mayer 1996). Table 1 also lists the maximum air temperature measured at Schiphol airport, a rural reference station of the Netherlands Royal Meteorological Institute 10 km from the centre of Amsterdam. Also at this site, air temperatures did not always exceed 25 °C.
The meteorological measurements listed in Table 1 indicate that the average humidity on the measurement days was low, between 33 and 68%, and wind speeds measured were calm up to light breeze. These values reflect a typical situation for an urban environment on a hot summer day.
Micrometeorological measurements and assessment of PET
To measure the meteorological conditions and estimate the PET, we equipped two-wheel hand carts with a Davis Vantage Pro2 weather station (see Fig. 2). This instrument includes sensors that measure air temperature, air humidity, wind speed, wind direction, and global radiation and uses a fan-aspirated radiation shield. The accuracy of the sensors are 0.5 °C for air temperature, 3% for air humidity, 5% for wind speed, 3° for wind direction and 5% for global radiation. The globe temperature was measured using an additional 38-mm flat grey globe thermometer, made of a grey painted table tennis ball using a flat grey paint (RAL 7001) following Thorsson et al. (2007). A temperature probe of Davis (type 6372) was used inside the table tennis ball. The accuracy of this sensor is 0.5 °C. The time interval of the recorded meteorological variables was 1 min. The height at which the sensors were installed is 1.1 m, corresponding to the average height of an adult’s centre of gravity (Mayer and Hoeppe 1987).
From the globe temperature, the wind speed and the air temperature, the mean radiant temperature (Tmrt; Mayer and Hoeppe 1987) could be obtained using the method as suggested by Thorsson et al. (2007):
$$ {T}_{\mathrm{mrt}}={\left[{\left({T}_{\mathrm{g}}+273.15\right)}^4+\frac{1.335\times {10}^8{u}^6}{\varepsilon {D}^4}\times \left({T}_{\mathrm{g}}-{T}_{\mathrm{a}}\right)\right]}^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$4$}\right.}-273.15 $$
(1)
where Tg is the globe temperature (°C), u is wind speed (m/s), Ta is air temperature (°C), ε is the globe emissivity (0.95) and D is the globe diameter (m).
Tmrt is the most important variable in assessing the thermal comfort situation and calculating the PET. It sums the human body exposure to all short- and long-wave radiation fluxes (direct, diffuse, reflected and emitted) in a given environment (Johansson et al. 2014). Since the method used to assess Tmrt is very sensitive to variations in wind speed, we used 10-min running averages of the meteorological variables as input for calculating Tmrt.
The PET was calculated using Rayman software (Matzarakis et al. 2007). Air temperature, relative humidity, wind speed and Tmrt were used as input and the default settings of Rayman were used: gender—male, age—35 years of age, weight —75 kg, length—1.75 m, standing, moderate clothing (clo = 0.9) and doing light work (80.0 W).
Field surveys
In order to gain insight into the perception of the thermal environment of the urban spaces, we conducted interviews and surveyed people in the near environment of the weather stations, ensuring that the interviewees were in the same thermal environment as the measurement devices. We questioned people walking or sitting in this area. A structured interview form was prepared for the interviews (Table 2). People were asked to give some personal information related to the individual factors that determine thermal sensation (part 2 of the form) and their opinion on the thermal environment (part 3 of the form). Note that some slight differences exist between the surveys used in 2015 and 2016. We based the questions of the surveys on studies of Johansson et al. (2014), Klemm et al. (2015a), Lenzholzer and Van der Wulp (2010) and Nikolopoulou and Lykoudis (2006). Filling in a questionnaire took 2 to 3 min and was supported by a researcher.
Table 2 Overview of the questions in the survey The total number of surveys that were completed and could be used in this study is 1928. Table 1 lists the number of people that were interviewed at each location. The average gender division of the respondents is 55% male, 42% female and of 3% unknown. The personal characteristics of the respondents with respect to age and origin are presented in Tables 3 and 4. Since most of the measured urban spaces are situated in touristic areas, the number of respondents from countries other than the Netherlands is relatively high (nearly 50%).
Table 3 Age of the respondents Table 4 Origin of the respondents The dataset that we created by doing this questionnaire survey is extensive and can be used to answer a wide range of research questions on thermal experience and its relationship with individual factors such as clothing, age and cultural background. In this study, we especially focused on the answers to the first 4 questions concerning thermal experience (questions 3a, b, c and d). We also checked for some relationships with individual factors. Chi-square tests performed on the dataset of 2015 showed however that experienced thermal comfort (question 3b: Do you find this environment thermally comfortable/slightly uncomfortable/uncomfortable/very uncomfortable) does not have a significant (p < 0.05) relationship with any of the individual factors age, gender, clothing, activity level, cultural background or thermal history. In other words, the influence of individual factors on how people experience and value the thermal conditions of the urban spaces was not found in the dataset.
Methodology to assess the thermal effect
The key results of this study are the thermal effects of green, water and shading in urban spaces. The thermal effects are evaluated in terms of differences in air temperature, PET and thermal experience.
Table 5 shows which locations (L1 and L2) were compared with each other to estimate the thermal effects. Each time L1 is the expected cooler situation (green, water, shade) and L2 is the reference location. First, the thermal effects of water and urban green (grass and shrubs in parks) were assessed. This was done separately for shaded and sunlit locations. Second, the thermal effects of shading by buildings and shading by trees were assessed. The effect of shading by buildings could be assessed for impervious urban spaces only, while the effect of shading by trees could be assessed for two situations: trees in green (parks) and trees in impervious urban spaces. Note that each time only measurements from the same day were compared.
Table 5 Thermal effects of water, green (grass and shrubs) and shading measured as the difference in air temperature, PET and thermal experience between two locations (L1 and L2). The colours of L1 and L2 indicate the type of location: impervious (grey), grass or shrubs (green) and near urban water (blue). n.s. means that the difference in temperature or thermal comfort is not significant (p = 0.05). Bold numbers indicate that the location L2 is cooler—which is counterintuitive. The yellow and dark grey cells for thermal perception, comfort, preference and acceptation indicate a significant difference in thermal experience between L1 and L2. The significance level (p value) is given. Yellow indicates that L1 is perceived cooler, more comfortable or acceptable. Grey indicates that L2 is perceived cooler—which is counterintuitive. Concerning preference, yellow indicates that people at L2 prefer a cooler environment than at L1. The thermal effects are numbered from 1 to 19 in line with Fig. 3. The thermal effects of water and green urban spaces are always based on measurements and surveys at two locations with two weather stations at the same time. The differences in air temperature and PET listed in Table 5 were therefore calculated as the average of the differences between the two time series (1-min time intervals). A paired sample t-test was used to determine whether the mean difference between the two series is significant (p < 0.05). The thermal effects of shaded locations are mostly based on measurements from a weather station that was moved each hour between a sunlit and a shaded location. The differences in air temperature and PET listed in Table 5 were therefore calculated as the difference in the average air temperature and PET measured at the two locations. An unpaired sample t-test was used to determine whether this difference is significant (p < 0.05).
For assessing the differences in thermal experience, we compared interviewed thermal perception, thermal comfort, thermal preference and thermal acceptation between the locations. This corresponds to the four questions of the survey:
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3a.
Thermal perception—How are you feeling now? cold/cool/slightly cool/neutral/slightly warm/warm/hot
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3b.
Thermal comfort—Do you find this environment thermally: comfortable/slightly uncomfortable/uncomfortable/very uncomfortable
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3c.
Thermal preference—How would you prefer it to be now: cooler/no change/warmer
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3d.
Thermal acceptation—On thermal level, this environment is for me: acceptable/unacceptable
A chi-square test of independence was used to test the difference in perception, comfort, preference and acceptation between two locations. This test is applicable, since we compare two categorical data sets: thermal experience versus the type of urban space. Kendall’s Tau-test was applied for thermal acceptation when the sample size of the group ‘unacceptable’ was too small for applying a chi-square test. Chi-square examines the difference in distribution of two groups and Kendall’s tau-test examines the difference in ranking of the two groups.