Reducing the urban heat island effect; an assessment
on the vulnerability and resilience of Amsterdam
Course: Interdisciplinary Project
Students: Lorenzo Turk 10326774
Pieter Zuiderveld 10292691 Raphael Reinegger 10193731 Stijn van der Slot 10624805 Expert Supervisor: Dr. Kenneth Rijsdijk
Tutor: Tamara Jonkman
Date: 18-12-2015 Number of words: 9351
Abstract
The Urban Heat Island Effect (UHIE), the phenomenon that urban areas are warmer than their surrounding rural areas, is present in every city. The UHIE has several bad
consequences, both environmental and health related. The UHIE in Amsterdam is one of the strongest of Europe and causes heat stress on warm days. This research was conducted to find mitigation measures in order to decrease the UHI in Amsterdam. To do this, first the causes were investigated. The sky view factor, green areas and building materials are the most important controllable factors in generating UHI. Next, the heat stress on humans was investigated to assess the effect of high urban temperatures on labour productivity and public health. However, the heat index that was used (approximate wet bulb globe
temperature) failed to indicate any heat stress during the summer of 2014. This is most likely due to the tendency of the index to over or underestimate environmental warmth, thus providing an unreliable measure for heat stress. Even though the index failed to quantify the impact of the UHI, high urban temperatures remain a significant problem especially for vulnerable groups. In terms of mitigation measures, local vegetation and green areas are important in reducing the UHI, because vegetation cools both the urban area and buildings and therefore less energy is needed to cool buildings. A calculation about the possible energy savings and a cost-benefit analyses of several mitigation measures has been made in order to give a better representation about the costs and benefits involved, which can guide the decision making process. Besides, a case study about plans of the municipality of Amsterdam to build a, with vegetation covered, office building on the Zuidas is done. This research shows that there are several ways to mitigate the UHI, of which especially planting of trees, green roofs and other forms of green urban design are of significant value. The case study also shows the possibilities and willingness to make the city and its buildings more sustainable and less vulnerable to the UHIE.
Index Page
Abstract 1
Introduction & research questions 4
Theoretical framework 6
Urban heat island effect 6
Factors causing the urban heat island 6
Urban heat island in relation to heat stress 8
The role of urban planning in urban heat islands 8
Green urbanism 9
Creating common ground 9
Methods 11 Literature review 11 Heat index 11 Discount rate 12 Cost-benefit analysis 12 Case study 13 Results 14 Causing factors 14 Heat index 15 Cost-benefit analyses 16 Energy savings 19 Casus 20 Discussion 22 Conclusions 24 Literature 25
Introduction & research question
Although the ongoing urbanization around the world provides many comforts and benefits such as job opportunities and a great variety of markets and goods, it also causes adverse environmental effects such as air pollution, waste products and environmental degradation. Due to the increasing human population, a growing number of people are both causing and being confronted with the downside of these developments. The Urban Heat Island (UHI), which means that an urban area has an increased temperature compared with its
surroundings, is one of the adverse effects, predominantly caused by (anthropogenic) heat sources such as vehicles and air conditioners, and storage and re-radiation of significant amounts of solar radiations by complex urban structures due to massive construction material and decreased sky view factor (Rizwan, Dennis & Chunho, 2008). Moreover, because of the urbanization, urban areas consist of less vegetation to absorb and store solar
radiation. The factors causing the UHI can be divided in controllable and uncontrollable ones. This means measures can be taken to reduce the UHI. In this paper, the causes and
consequences are reviewed. Furthermore, benefits of measures and their cost to reduce the urban heat island effect (UHIE) are researched. The city of Amsterdam will be used as a case study because it is susceptible to the UHIE and it has one of the most severe urban heat islands in Europe (Van der Hoeven & Wandl, 2013). In the summer of 2006, daytime surface temperatures in the city were 10 to 20 °C higher than in the area surrounding the city (Van der Hoeven & Wandl, 2013). With the projected global increase in air temperature,
temperatures are likely to become higher and heat waves are likely to occur more frequently. The heatwave in 2003 proves the accompanied risks: it claimed 1700 lives in the Netherlands (Van der Hoeven and Wandl, 2014). To prevent such casualties in the future, the UHIE needs to be mitigated.
This research was conducted in order to understand the processes behind UHI and its consequences. This knowledge was then used to come up with mitigation measures. The costs and benefits of these measures are influential since it is important to know to what extent the solutions are realizable.
In order to answer our research- and sub questions it is important to first of all understand the problem and all the variables that have an effect on UHIE. Hereafter we need to investigate measures that reduce this problem and determine which measures have the most impact. To help with the decision making process, a cost-benefit analyses of several mitigation strategies will be made. Because this cannot be resolved by one discipline we have to adapt an interdisciplinary approach. Our group consists of four students, two of which study earth sciences, who will investigate the most important causes of UHI and the consequences of UHIE in their field of work. One of our group members studies urban planning and will focus on the extent to which urban planning adds to the generation of the UHIE, but also on the extent to which urban planning can contribute to combat the UHIE. Our last group member studies business administration and he will look into the costs of the consequences of UHIE and make a cost-benefit analysis of the measures that could be taken to reduce UHIE. Besides, the group members combine their knowledge in the case study about the building plans on the Zuidas.
In order to fulfil the objectives written down in the introduction, the following main research question was formulated:
How can urban planning be utilized in combating the Urban Heat Island Effect in the city of Amsterdam?
To answer our main research question, the following sub questions are answered:
To what extent do the most important causes of the urban heat island effect contribute to the generation process?
What are the current and (possible) future implications of the urban heat island effect?
What are the spatial and climatological characteristics of the urban heat island effect in Amsterdam?
Theoretical framework
Urban Heat Island EffectAs this research project primarily focus on the UHIE, it is important to first get a clear definition of this theory as a fundament that can be expanded to an holistic approach on mitigating the problems associated with the UHIE by urban planning and design. Although there are several phrasings of the definition of the UHIE, there is not much debate about which definition is most comprehensive, as the definitions given in several articles do not differ significantly from each other. For example, Kleerekoper et al. (2012) described UHIE as ‘the phenomenon that the urban air temperature is higher than that of the surrounding rural environment’, while Stone & Rodgers (2001) described it as ‘elevated temperatures in cities relative to rural areas at their surroundings’ and Rizwan, Dennis & Chunho (2008) described it as an urban area that has higher temperatures than its surroundings.
The UHIE is an often-documented topic. In 1833, the first scientific observations concerning urban heat islands were documented by Luke Howard, who portrayed a city distinctly warmer than its countryside (Stewart, 2011). In the two decades that followed, hundreds of studies on UHI’s in different cities around the world have been published.
Oke (1973) wrote that the ability of a town or city to generate an urban heat island was already a well-accepted fact and was ‘one of the most widely documented climatological effects of man’s modification of the atmospheric environment’. He was trying to find generalizations in the relation between the size of a city and the magnitude of the urban heat island it produces (focused on similarities in urban heat islands, in contrast with the majority of the studies on UHIE’s that focused on investigating the UHIE in a particular city) that could be of value for climate modeling and urban planning. His focus on finding
generalizations demonstrates that, although there was already much literature on UHI, there was still a need for expanding theories on UHI. This emphasizes that the debate concerning UHIE is focused on the differences in methodologies that are used to investigate UHI’s rather than the effect itself.
In 1982, Oke stated that urban heat island was ‘well described but rather poorly understood’, because there was still a need for simple methods to estimate UHI intensity under different circumstances. In 2011, Stewart criticized the methodologies used in observational heat island literature because it was compromised by ‘poor scientific practice’. He emphasized that there is a need for standardized guidelines for site reporting and more discretion in the use of terminology. It can be concluded that although UHI is an often-documented topic, there is still a need for further research to generalize methodologies in order to find a simple method that can be used as a standard under different circumstances.
Factors causing the UHI
With use of earth scientific knowledge the causes of the UHI and their contribution to the UHI are researched. Oke (1982 & 1987) was the first to describe the causes and underlying processes of the UHI. Some additions to these papers followed. Rizwan et al. (2008) divided them in controllable and uncontrollable causes (figure 1). This graphic was used as a guideline in our research project, because it emphasizes the importance of an
interdisciplinary approach for investigating the different factors causing the urban heat island.
These categories can be categorized further in temporary effects, permanent effects and cyclic effects. The temporary effects are weather related and uncontrollable: anticyclone conditions, season, diurnal conditions, wind speed and cloud cover. The permanent factors are city design related and controllable: sky view factor, green areas and building materials.
Cyclic effect variables are dependent on the difference between daily and nightly activities and are more or less controllable: anthropogenic heat, air pollutants and solar radiation.
Figure 1: Categorised generation factors (Rizwan, Dennis & Chunho, 2008)
Some factors directly heat up the environment (i.e. anthropogenic), others (partly) indirectly (i.e. solar radiation) (Rizwan et al., 2008). Urban structures take up heat from the sun and release it when the sun goes down. To what extent this happens is dependent on the sky view factor and the building materials. The sky view factor is the amount of sky that can be seen. The sky view factor is depending on both the building height and the width of the road (Svensson, 2004).
Different views exist in papers about the influence that factors have on the generation progress. Giridharan et al. (2004) state that the albedo and sky view factors are two important factors in generating UHI. The motivation for this statement is that buildings capture solar radiation and reflect it back partly because of the decreased sky view. The street canyon configuration is the reason that the albedo (i.e. reflection power of the surface) is very small. The “large thermal inertia” of impenetrable surfaces and small surface cover of natural vegetation in urban areas are the two most important factors contributing to UHI according to Velazquez-Lozada et al. (2006).
The influence of the city population size on the generation process is still a point of
discussion. Hung et al. (2006) found a positive correlation between population size and UHI, but Kim & Baik (2004) did not. Steeneveld et al. (2011) found a positive correlation on population density in Dutch cities, but no correlation on population size: whether the population density has a direct (more metabolism per km²) or indirect (more/higher buildings per km²) influence is yet unsure (Steeneveld et al., 2011; Rizwan et al., 2008). Steenveld et al. (2011) states that the effect of open waters on UHI remains unclear. Van der Hoeve & Wandl (2013) argue that surface waters have a cooling effect during daytime due to evaporation. During nighttime, the surface waters would have a heating effect. This is due to the low albedo of surface waters; they take up a relative large amount of solar radiation. Wind speed in urban areas can be lower than in rural areas (Oke, 1987), but the degree of influence that wind has on the generation of UHI is yet unclear. Measurements of Kim and Baik (2002) showed a disappearing urban heat island intensity of 0.3°C at a wind speed of 7.0 m/s and a decreased UHI at 0.8 m/s. Klysik and Fortuniak (1999) showed that a UHI of 1°C was still present at both day- and night time, at an wind speed of respectively 4 m/s and 2 m/s. Morris et al. (2001) estimated that the UHI is roughly the fourth root of wind speed and cloud cover.
The quantification of the influence of different factors is a topic that has not been the subject of many publications. The most detailed analysis is from Ryu & Baik (2012). Here, both the
different factors and day- and nighttime UHI were separated and the interaction between factors was analysed. Other papers that quantify factors were found not detailed enough to review in this paper, because the factors were not separated (Martilli, 2002; Tokairin, 2006) or factors were excluded from the calculation (Kusaka & Kimura, 2004). However, it is possible to quantify thermal comfort (heat stress) which is influenced by the urban heat island and will be discussed in the next section.
UHI in relation to heat stress
To create a better understanding of the possible effects of the urban heat island in Amsterdam and to determine to what extent the UHIE needs to be mitigated in the near future, an assessment is needed on the impact of higher urban temperatures on public health (heat stress). This impact can best be assessed with thermal comfort (Steeneveld et al., 2011), which is the condition of mind that expresses the satisfaction with the thermal environment. Studies have shown (Fisk & Rosenfeld, 1997; Wargocki & Djukanovic, 2003; Lan et al., 2011) that improving the thermal environment in offices, and therefore improving thermal comfort, resulted in a direct increase in productivity and that the net productivity gain reduced by improving indoor air quality could exceed the investment costs by a factor of 60 with a turnover period of about 2.1 years. To maintain and improve labor productivity in a city, a thermal comfort assessment is needed (Lan et al., 2011). After quantifying the effects of the UHI, the costs of the consequences of the UHI and the costs and benefits of the actions to mitigate the UHI can be investigated. This information can then be used for strategic urban planning and help in answering the main research question: How can urban planning be utilized in combating the Urban Heat Island Effect in Amsterdam? Thermal comfort can be assessed with the Wet Bulb Globe Temperature (WBGT). This will be discussed in the methods.
The role of urban planning and design in UHI
Since the spatial characteristics of a city influence its climate, urban planning design can be held responsible for the combined effects of UHIs. In this way, UHIs are often investigated by relating planning to climatological factors. However, Kleerekoper et al. (2012) emphasized that urban design can also be deployed to mitigate these effects. In this way, the urban design and structure add significantly to the generation of the UHI, but can also be used in the mitigation of this problem. A review of relevant literature learned that urban planning is more often used for measuring the causes and consequences of UHIs, while urban design is more often cited in articles that focus on mitigation of UHIs. An example of this can be found in the article ‘Urban form and thermal efficiency: how the design of cities influences the Urban Heat Island Effect’ (Stone & Rodgers, 2001). In this article, the magnitudes of UHIs were determined through an environmental urban planning perspective, which focus on the relation between urban development patterns (e.g. land use patterns) and regional climate change. The next section of their research concentrated on mitigation of UHI through an environmental urban design perspective, which means that specific urban forms (e.g. pervious surface areas) are used to achieve an environmental objective. Their article gave two relevant insights, namely that heat islands might be more a product of urban design than (as commonly assumed) the density of development and population, and that the imposition of restrictions on urban development and the introduction of area-based tree canopy requirements are applicable urban design principles for mitigation of UHI.
Kleerekooper et al. (2012) also provided tools for urban design to mitigate UHI effects in the complexity of urban areas. They concluded that climate adaptation plans could only be successful when they also address social, economic and spatial aspects. In the article
Amsterwarm: Mapping the landuse, health and energy-efficiency implications of the Amsterdam urban heat island (Van der Hoeven & Wandl, 2014) specific conditions of
planning authorities to prioritize adaptation actions. This emphasizes the need to also focus on how to adopt mitigation options in (local) policies.
Green Urbanism
Because of the adverse effects on the environment caused by phenomena like UHIs,
concepts such as Green Urbanism arose. Green Urbanism is a conceptual model that arose in the 1990s that promotes the development of social and environmental sustainable cities. Green urbanism believes that urban modernization can only be achieved by using clearly formulated sustainable urban design principles, which have to be clearly defined and adjusted to a period of growing urbanization. Green urbanism is an interdisciplinary concept, because in order to design a sustainable city, people from different disciplines have to work together (Lehmann, 2010).
A city that integrates landscapes, urban gardens and green roofs will not only protect and maximize biodiversity, but also ensure urban cooling (Lehmann, 2010). The city needs to enlarge the resilience of the eco-system by using urban landscapes that mitigate UHIE; plants can be used for air purification and urban cooling.
Creating common ground
The interdisciplinary approach is visualized in figure 2. Common ground between the different disciplines is found by appointing each discipline to a specific aspect of the Urban Heat Island Effect. By dissecting the problem, some disciplines turn out to be more suitable for a specific aspect than others. For example in the causes that need to be analyzed in order to find suitable mitigation strategies. Moreover, a large amount of information on the consequences of the UHI is needed in order to quantify the negative effects on the
environment and humans. This is necessary to assess the impact of the UHIE and to create a better understanding of how the UHIE should be mitigated. The earth-science discipline shows to be the most suitable discipline for quantification of both the causes and
consequences of UHIE. The next step in finding common ground is to look into the measures for mitigation. Because most of the causes of the urban heat island are related to urban structures and design, this aspect was assigned to Urban Planning. The quantitative information obtained by the other disciplines, business studies and earth-sciences, should act as a foundation for this urban design assessment. This is helpful for the next step, to analyze to what extent the measures were realistic, efficient and cost-effective in order to find the most suitable mitigation strategies. This aspect is assigned to Business Studies, which provides the tools to conduct a cost-benefit analysis and conclude this research. It shows that an interdisciplinary approach to UHI-related problems is very helpful because it makes way for possibilities to tackle the problem by a combination of both quantitative and qualitative factors, and to get a more holistic overview of the complex UHI-problem.
Methods
Literature reviewThis study is primarily literature based. By using literature from different sources, knowledge of different academic disciplines can be combined. This is the most effective way to fulfill our research objectives of understanding the different processes and how urban areas have to be adapted to reduce the UHI. In order to quantify thermal comfort and the effects of the UHI a heat index was used. Additionally, a cost benefit analysis was made to determine and quantify the costs and benefits of the different urban design strategies.
Heat index
Thermal comfort can be assessed with the Wet Bulb Globe Temperature (WBGT). However, in order to calculate the WBGT the black globe temperature is needed. This variable is not routinely observed and therefore an approximation of the WBGT is used: The approximate wet bulb globe temperature (AWBGT) (Steeneveld et al., 2011; Budd, 2008). The AWBGT excludes solar radiation and wind. Therefore, it is only useful for determining heat stress in individuals that are not constrained in their behavioral responses (Budd, 2008). It is not suitable for predicting heat stress in people who engage in strenuous exercise. Furthermore, it is not a very accurate in predicting heat stress in an indoor environment, because it provides no information about the influence of the infrared radiation of objects and building materials on the human body (black globe temperature). Due to the lack of black globe temperature measurements, the methods will be limited to the AWBGT.
Equation 1: AWBGT = 0.567Ta + 0.393e + 3.94
Ta: Air temperature
e: Vapor pressure
Air temperature data is widely available (GGD) and vapor pressure (e) can be calculated when relative humidity (RH) is known. Relative humidity is often included in climate datasets (e.g. KNMI weather observations).
Equation 2.1: RH = 100% x (e/es)
The saturated vapor pressure (es) can be calculated with equation 4.
Equation 2.2: es = 6.11 exp ( ( 7.5 × Ta)/ (237.3 + Ta)) Now e can be calculated with:
Equation 2.3: e = (RH/100) * (6.11 exp ( ( 7.5 × Ta)/ (237.3 + Ta)))
Now this equation can act as a substitute for e in the equation for AWBGT, which results in the following equation.
Equation 3: AWBGT = 0.567Ta + 0.393((RH/100) * (6.11 exp ( ( 7.5 × Ta)/ (237.3 + Ta)))) +
3.94
For 27.7°C < AWBGT < 32.2°C the heat stress increases, and for AWBGT > 32.2°C great heat stress danger occurs (Steeneveld et al., 2011). Because it is likely that these temperatures only occur in summer, the AWBGT was measured during the summer months (July – September) in 2014.
The air temperature data was obtained from the GGD weather stations at Nieuwendammerdijk, Einsteinweg, Van Diemenstraat, Overtoom, Westerpark,
Stadhouderskade and Jan van Galenstraat. Because the measurements are taken on an hourly basis, only the daytime measurements were extracted from the dataset (sunrise approx. 06:00 – sunset approx. 21:00). Because morning temperatures (06:00- 10:00) often
deviate strongly from the noon and evening temperatures (12:00 – 21:00), the median air temperature was used to calculate the AWBGT.
The relative humidity measurements were obtained from weather station Holendrecht and weather station Westerpark. However, Holendrecht was the only weather station that offered complete relative humidity data for 2014. Moreover, the difference in relative humidity measurements from these two weather stations was very small (maximum 4%). A two sample t-test can help in determining if the difference is significant. Nonetheless, a difference of 4% in relative humidity barely affects the outcome of the AWBGT calculation. Discount rate
The UK government indicates in the Green Book, Appraisal and Evaluation in Central Government (HM Treasury, 2003) that a rate of 3.5% should be used to discount future benefits and costs of public projects with a lifespan below 30 years. In Europe, the social discount rates are between 3% and 6% (Zhuang, Liang, Lin & De Guzman, 2007). If a project has a long lifespan the discount rate tends to be lower. The California Energy Commission has adopted a 3% discount rate for energy efficient buildings and other long range
investments trying to save fossil fuel. (Rosenfeld, Akbari & Romm, 1998). We will use a rate between 3%-6% in our calculations to see the effects on the benefits and costs.
Cost-Benefit analyses (CBA)
In order to determine the costs and benefits of the actions to mitigate the UHI, a cost benefit analysis has to be made. Since the 1960s it has been usual to analyse benefits and costs of different projects to help with the decision making process (Hanley & Spash, 1993). The general theory and approach for conducting a cost benefit analysis was obtained from Berk and DeMarzo (2007), Hanley and Spash (1993) and Rosenfeld, Akbari, Romm and Pomerantz (1998).The different stages of a cost-benefit analyses will be discussed below;
Stage one & two: Definition of the project and identifying the project impacts
Determining what is going to be analyzed and what is taking into account in the calculations. When this is done, the relevant impacts that result from the implementation of the project have to be identified. Two important concepts, additionality and displacement. Additionality stands for the net impacts of the project and displacement means that the implementation of a project can have negative effects on other entities (Hanley & Spash, 1993).
Stage three: Which impacts are economically relevant?
When the impacts of the project are identified, the impacts that are economically relevant have to be determined. Positive impacts are benefits and negative impacts are referred to as costs. With environmental projects the concept of externalities, which are unpriced impacts that can be either positive or negative have to be taken into account if possible. Externalities can be the use of plants, which give people enjoyment, or the occurrence of acid rains. With both examples it is difficult to determine the total benefits or costs of these externalities (Hanley & Spash, 1993).
Stage four & five: Physical quantification of relevant impacts and monetary evaluation of relevant effects
Determining the costs and benefits of a project and when these costs or benefits will occur. Because most calculations will be subjected to uncertainty, probabilities can be used to calculate the expected value. In order for all impacts to be measurable, they must be valued in the same unit and mostly the unit is money because it is convenient for the analyses. Hereafter the prices for future value flows have to be predicted; the market prices have to be adapted where necessary and prices have to be calculated where no prices yet exist. When
adjusting market prices a couple of things have to be considered, namely the assumptions of a perfectly competitive market, no government interventions and the existence of a market. When these assumptions are not the case in reality, shadow prices have to be assumed in order to give a more realistic representation of the situation.
In order to determine the prices of future value flows, inflation has to be taken into account. One example is adjusting the prices with inflation if the projects takes longer than one year, the real adjusted value in this case is B(1+P)^-t, where B is the nominal value which is not adjusted, P the inflation rate and t the number of years, in the first year t is always zero (Hanley & Spash, 1993).
Stage six: Discounting of costs and benefit flows
When all the relevant impacts are converted into costs and benefits that can be expressed in the same unit, they have to be converted into present value terms. This is needed because of the time value of money, risk and uncertainties. If someone receives €100 now, the money can be invested directly; this is not possible if someone were to receive €100 after one year. In order to make cost and benefit flows more comparable even if they occur in different time periods, they have to be discounted with a certain rate. The present value (PV) of a cost or benefit (X) received in time t, where i is the discount rate is calculated as follows: PV (X) = X * (1+i)^t when going forward in time and PV(X) = X /(1+i)^t when going backwards. (Berk & DeMarzo, 2007), (Hanley & Spash, 1993). According to Rosenfeld et al. (1998) the PV of future savings can be calculated with: PV = A * ((1-(1+i)^-t)/i) where A stands for the annual savings, i for the discount rate and t for the time in years.
Stage seven: Applying the net present value test
The net present value test is a calculation to determine whether the sum of discounted gains is larger than the sum of discounted losses. The net present value (NPV) is the sum of all the beneficial PV’s minus the sum of all the costs PV’s. The project can be accepted if the NPV is larger than zero and this means that the project should increase social welfare (Berk & DeMarzo, 2007), (Hanley & Spash, 1993).
Stage eight: Sensitivity analysis
Recalculating stage seven with different values for the key parameters, this is an important part of CBA because most values are predictions and are not certain, due to this large uncertainty the NPV has to be recalculated several times with different values for the following parameters:
- The discount rate
- Input & output of benefits and costs - Shadow prices
- Project time span
When this is done it is possible to see which parameter has the largest influence on the NPV. The NPV of project with a relatively long time span will be largely dependent on the discount rate, as is the case with tree planting for example (Hanley & Spash, 1993).
Case study
In order to make the link between theories of mitigation efforts and implementation of such measures in the focus area, a case study is set up to see how the council of Amsterdam tries to make the business district ‘Zuidas’ more climate-proof by building a vertical forest.
Results
Results causing factors of UHI
Contribution of different factorsIn table 1, the results of the analysis of Ryu & Baik (2012) can be seen. The G-classes are subclasses from class F3. Therefore, the daytime contribution of class G1 is a negative influence on UHI. The interactions between factors are omitted from this table, considering the size of this paper. Therefore, the net sum of the percentages does not equal 0. Notable interactions will be discussed later in this review.
Clas s
Factor Daytime contribution
(%) Nighttime contribution (%) F1 Anthropogenic 36 86 F2 Impervious surfaces 98 47 F3 3D urban geometry -24 28
G1 Additional heat stored in vertical walls
163 89
G2 Radiation trapping -37 36
G3 Wind speed reduction 151 74
Table 1: The contribution of different factors on the generation of UHI during both daytime and nighttime
As far as the factors are concerned, some remarkable results can be found in table 1. At first, there is a large difference between daytime and nighttime influence. Anthropogenic heat is the largest factor in generation nighttime UHI, while in daytime the impervious surfaces are. 3D urban geometry is slowing down the process during daytime and stimulating it during nighttime. As far as the sub factors of the 3D urban geometry goes, the heat stored in vertical walls is together with wind speed reduction a large influence. A lot of heat is stored into vertical walls during daytime, while reduced wind speed causes a smaller cooling down effect of an urban area; this is slowing down the process. In contrary, at nighttime when the temperature drops, the heat is released and warming up the environment.
The interaction between different factors can in some cases also be a relevant influence. During daytime, the interaction between class G1 and G3, and between G2 and G3 have a strong positive effect on the UHII, while G1 and G3 individually have a negative effect. In contrary, during nighttime the interactions are all negative while the individual factors have a positive effect.
Results heat index
Figure 3: Plot of the AWBGT during the period 01/06/2014 – 28/09/2014. Series 1 until 6 represent these different weather stations (from top to bottom): Nieuwendammerdijk, Einsteinweg, Van Diemenstraat, Overtoom, Westerpark, Stadhouderskade and Jan van Galenstraat.
The peak AWBGT is reached during July, but the threshold for heat stress (27.7°C) is not exceeded. Even the peak AWBGT remains about 3-4 °C beneath the threshold. Furthermore, the AWBGT variation between the weather stations is very small. This is most likely due to the small variation in the measured air temperature between the weather stations. However, in June the temperatures measured by the weather station in Nieuwendammerdijk strongly deviate from those measured by the other weather stations. This could be caused by the cooling influence of the water bodies and green spaces surrounding the weather station. Options for mitigation of UHI by urban design and planning
Theories on the role of urban planning and design in mitigation of UHI (see theoretical framework) provide specific insights that can be of value for answering this research question. The articles by Stone & Rodgers (2001) and Kleerekoper et al. (2012) give both quantitative data on the magnitude of the impact that different factors contribute to UHI’s and theories on mitigation options with an estimation of their possible impact. For example, the article by Stone & Rodgers provides insights that, contrary to intuitive assumptions, lower density sprawl patterns of urban development contribute more radiant heat energy to the formation of UHI than do higher density compact forms. Due to that insight, they argued that the imposition of restrictions on the zone of urban development and the introduction of
area-based tree canopy requirements are applicable urban design principles for mitigation of UHI. Therefore, infill and higher-density development must be stimulated as strategies for thermal efficiency, because it reduces deforestation and the size of the area needed for development.
Lehmann (2010) argued that a city should focus on green urbanism for mitigation of adverse environmental effects. He gives several examples that could be of value for mitigation of UHIE: the narrowing of roads not only slows traffic, it also lowers the UHIE and provides space for more tree planting. In our own houses, we need to de-pave the driveway or tear up parking lots.
Kleerekoper et al. (2012) provide tools for urban design to mitigate UHI effects in the complexity of urban areas with two case studies on neighbourhoods in the Dutch city of Utrecht. According to them, types of application of vegetation within urban areas (urban forests (parks), trees along streets, green in private garden and green roofs or facades) could have an average cooling effect of 1-4,7◦ C spread over 100-1000 meters, depending on airflow and other climatological circumstances. In this way, vegetated areas could act as Park Cool Islands, because of their lower air and surface temperature (ibid.). Shashua-Bar & Hoffman (2000) concluded that a cooling effect could already be generated in small areas, because their study showed that a park with a size of 0,15 ha already had an average cooling effect of 1.5 ◦ C at day and 3 ◦ C at night.
Rosenfeld et al. (1998) and Kleerekoper et al. (2012) also state that light-colored or green roofs can be of significant value. Green roofs (covering roofs or facades with vegetation) do not only cool the surroundings, it also has indoor climatological advantages. It cools the building itself in summer due to the cooling effect of the leaves (evapotranspiration,
conversion of heat into latent heat, shading and insulation), while in winter the vegetation is transparent and permeable to solar radiations (Kleerekoper et al.). Yukihiro et al. (2006) found out that green roofs can cause a decrease in temperature up to 0.2–1.2 ◦ C in its close surroundings and a energy saving of 4-40% (optimal results can be achieved when west-facing windows and walls are shaded).
From the types of vegetation in urbanized areas, street trees seem to have to lowest impact for mitigation of the UHI because of their dispersion, but due to the quantity of trees they actually have the biggest cooling power, namely up to 20-30 kW per tree on sunny days (comparable to ten air conditioners) (Kravcík et al., 2007). In comparison with other mitigation options, planting of trees in combination with covering the dark surface of
pavements with a thin coating can be relative simple methods of UHI-reduction (Rosenfeld et al., 1998).
Although more difficult to implement in high-density urban environments, other measures to reduce the UHIE include cooling effects of flowing water. Dispersed water has the biggest cooling effect and therefore fountains can be of value, but their magnitude may be smaller than cooling effects of rivers etc.
Previously mentioned mitigation measures may differ in impact and the impact of mitigation measures can be enhanced when policy programmes are set up to stimulate the use of such measures in private spaces, but what becomes most evident is that application of green urban design in high-density cities can be of significant use to mitigate UHI effects.
Results cost-benefit analyses
The previous section proves that there are several options for UHI-mitigation, but it can also be of great value to compare the costs and benefits of such strategies. Rosenfeld et al. (1998) calculated how much benefit could be attributed to three different strategies to reduce UHI. The three different strategies were tree planting, light colored roofs and light colored pavements. The results were that 50% of the temperature decrease was due to tree planting,
29% came from light colored roofs and 21% was because of light colored pavements. The costs and benefits of these strategies will be discussed below.
Tree planting
The present value (PV) of savings has to be calculated in order to find out how much a homeowner can afford to pay for shade trees. Akbari et al. (2001) estimated that the direct savings to a homeowner who plants three shade trees would have a present value of about $200/home ($68/ tree). The present value of indirect savings is smaller, $72/home ($24/ tree). The PV of smog savings was about $120/tree. The total PV of all benefits from trees is then $212/tree. According to Rosenfeld et al. (1998) the costs of a tree-planting program depends on the type of program and the type of trees. A tree planting program of trees between 2-3 meters cost about US$10 per tree, whereas a professional tree-planting program using large trees could cost from US$150 to US$470 per tree. In a program of the Sacramento Municipal Utility District and the Sacramento Tree Foundation between 1992-1996 they planted 6 meter high trees at an average cost of US$45 per tree. With the planting of trees we also have to take into account all the costs related to tree maintenance such as pruning, removal of dead trees and removal of stump of dead trees, repair of damages to roads and administration costs. The PV of all costs, including maintenance costs are assumed to be twice the additional costs of planting the trees (Rosenfeld et al., 1998). According to Kravcík et al. (2007) trees have a cooling power of 20-30 kW per tree on sunny days. Ennos (2011) calculated that at midday on sunny days, trees in Amsterdam have a cooling power between 1.5 and 7 kW per tree. If the 49 days above a threshold of 20 degrees celsius are used from the weather data mentioned earlier and assume that in Amsterdam trees have a cooling power of 1.0 kW/tree/hour for 14 hours per day on these 49 days, the total benefits per tree per year because of their cooling power would be;
1 kW * 14 hours * 49 days * €0.22(according to Milieu Centraal) = €150.92
This seems to be a relatively high benefit compared to the benefits mentioned earlier, but here the cooling power of mature trees is calculated. If it takes ten years for a tree to mature and discount that back with a rate of 3% and 6%, respectively, the PV`of benefits would be;
€150.92/(1.0310) = €112.30 and €226.38/(1.0610) = €84.27
If it only takes 5 years for these trees to grow mature and discount that back with a rate of 3% and 6%, respectively, the PV of benefits would be;
€150.92/(1.035) = €130.18 and €150.92/(1.065) = €112.77
With these calculations it is shown that the time to mature and the discount rate, which are prone to large uncertainties, both have a large influence on the PV of benefits of the cooling power of trees. The average of the four PV’s is;
€112.30 + €84.27 + €130.18 + €112.77 = 439.52/4 = €109.88
With the assumption that the total PV of all direct and indirect effects of trees, which includes the benefits on smog savings and carbon sequestration, are twice the PV of benefits of cooling power, the PV of total benefits would be €219.76. This assumption is based on
articles where the PV’s of smog savings and other indirect effects were larger than the PV of energy savings (Rosenfeld et al.,1998; Akbari et al., 2001). The total costs per tree are assumed to be €200, which means that the NPV of the project would be slightly positive, but because it is difficult to determine the exact total costs of trees, it is possible that the costs are actually higher, which could result in a negative NPV.
NPV = €219.76 - €200 = €19.76 per tree
Green and white roofs
The best time for people to make the switch to cool surfaces is when their roofs or
pavements need maintenance, which is mostly every 20 years for residential shingles and 5-10 years for a flat roof, parking lot or road. At this point the extra costs are as little as
possible. The extra cost of manufacturing white instead of brown or green roofing shingles is estimated to be around US$22/ 100 m2 of roof (Rosenfeld et al., 1998). The extra cost at retail will be decided by the market and possibly by the government. In order to keep the albedo at a high level, roofs need to be recoated or rewashed on a regular basis, the possible costs of doing this could be large if people do not do this themselves. Although white and green roofing membranes compared to dark roofing membranes have a one time extra cost of about US$100/ 100 m2, they have a continuing savings of US$65 per 100 m2 per year in a hot dry climate as in Los Angeles according to Rosenfeld et al. (1998). These savings are assumed to be less in Amsterdam, because it is a different climate and less air-conditioning is used in Amsterdam compared to Los Angeles. The continuing savings in the Netherlands are therefore assumed to be twice as low as the continuing savings in Los Angeles, $32.5/100m2. With a service life of 15 years and a discount rate of 3% and 6%, the PV would be;
32.5 *( (1-(1+3%)-15)/3%) = $387,98/100m2 and 32.5*((1-(1+6%)-15)/6%)=$315.64/100m2
With a one time extra cost of $100/ 100m2 and even with the extra costs of $22/100m2 for white roofing shingles the NPV of this project seems to be positive and therefore a good investment.
The initial costs of a roof are higher, but because it is assumed that people switch to cool roofs when their old roof needs maintenance, we have not taken this into account in these calculations. So as long as people switch to cool roofs when their old roof needs
maintenance it is a positive investment. With a discount rate of 3% and 6%, a service life of ten years and the assumption that the continuing savings are $25 dollars/100m2 in
Amsterdam, the PV of benefits would be;
25*((1-(1+3%)-10)/3%) = $213.25/100m2 and 25*((1-(1+6%)-10)/6%) = $184/100m2
The average of the four PV’s are;
$387.98 + $315.64 + $213.25 + $184 = $1100.87 / 4 = $275.21
With the assumption that the total costs of the roofing shingles are $175 in Amsterdam, due to higher additional and shipping costs, the NPV of the project is
This gives a positive NPV and therefore seems like a good investment that improves social welfare.
Pavements
According to Rosenfeld et al. (1998), the most economical way to make cool pavements is to lay a thin coating over the existing dark surface. The additional cost of materials for a 6 mm thick layer in US$/100 m2, can be shown with the following formula; Total costs
=1.45A+29.4B, where A is the additional cost (in US$/ton) of white aggregate and B is the additional cost of binder (in US$/gal). The price of white aggregates depends on the price of limestone and the shipping costs. If the white aggregate is not locally available, the cost of aggregate may increase with 50% (Bretz, Akbari & Rosenfeld, 1998). In the San Francisco Bay Area, the additional cost of white aggregate is about US$20/ton (Rosenfeld et al., 1998). By using this value and by using asphalt as the binder, which is normally used and gives B = 0, we found the total costs to be US$29/100 m2. This is less than the PV of benefits calculated by Rosenfeld et al. (1998), which is US$36/100m2.
They also state that if companies are able to recycle aggregates, the benefits will be 3 times higher which means that the PV of total benefits would be US$108/100m2. This results in a positive NPV for this investment in the San Francisco Bay Area. Whether or not these aggregates can be recycled in Amsterdam has the largest effect on the NPV of the project. The binder costs are not taking into account, because this measure will be implemented when the pavement needs maintenance and therefore already needs asphalt as a binder.
Results energy savings
According to Van der Hoeven and Wandl (2014), land use does affect the surface temperature.
The difference between the areas in the city of Amsterdam with the least and the greatest impervious surface coverage accounts for an average Land Surface Temperature (LST) difference of 11.6 degrees Celsius per hectare and an increase of the albedo from 0.3 to 0.5 would result in an average LST decrease in the range of 4.0–4.6 degrees Celsius per hectare. Akbari, Pomerantz, & Taha (2001) calculated that the electricity demand in cities rises between 2-4% for each degree increase in temperature above a threshold level between 15-20 degrees celsius based on an analyses of several large U.S. cities. For the calculations it is assumed that by implementing the mitigation strategies it is possible to lower the
temperature in Amsterdam with at least one degree celsius. A percentage of 1% for each degree celsius is assumed for the city of Amsterdam, because most of the cities used in the analyses are hotter in summer and therefore use more air conditioning which raises the potential savings. With the weather data obtained it is possible to see how many days there were in 2014 with temperatures above the threshold level of 20 degrees. According to the weather data there were 49 days in 2014 where the average day temperature was higher than 20 degrees celsius. The total electricity use in Amsterdam is 4,6*109 KWh/year according to a report of the gemeente Amsterdam conducted in 2014 (Den Boogert et al, 2014). On an annualized basis 1 GWh(1.000.000 KWh) of electricity emits 167 metric tons of carbon in the United States(Konopacki & Akbari, 2002). This will not be exactly the same in Amsterdam, due to differences in the way countries and cities generate energy. Lowering the average temperature will therefore not only save money, because less electricity is needed, it will also lower the total emission of carbon, which is better for the environment. An analyses conducted by Essent (2013), one of the largest energy providers in the Netherlands, reported that the amount of electricity use is 30% larger in winter.
This results in an energy use of 1.9*109 KWh in the warmer half of the year compared to 2.6*109 KWh in the colder half of the year, because of the larger use in winter.
With this information we can calculate the potential savings of electricity for 2014 if we would be able to lower the electricity demand of the city with 1% for the 49 where the
average day temperature was higher than 20 degrees and we assume that these days were in the warmer half of the year.
365 days/2 = 182.5 days/half year
1.9*109/182.5 = 10*106 (average) KWh/day in warmer half of the year 10*106 * 49 days = 49*107 KWh/49 days
49*107 * 1% = 49*105 KWh which can be saved
Milieu Centraal (2015) calculated the average price per KWh in the Netherlands, which is €0.22, so the potential savings in Amsterdam if it is possible to reduce the electricity use with 1% by planting trees and increasing the albedo are;
49*105 * €0.22 = €1.078.000/year
Casus: Implementation of UHI mitigation measures in Amsterdam
The population of Amsterdam grows every year and therefore urban density is also increasing, what causes different climatological effects. The project ‘Amsterwarm’ (van der Hoeven & Wandl, 2015) did research into the urban heat island in Amsterdam and concluded that the growth in suburban areas raises more concerns than the increasing density in existing urban areas. They also stated that mitigation efforts to reduce the UHI should focus on effective urban design at local level, increasing the quality of life in neighbourhoods and improving energy efficiency of buildings.The ecological impact of the growth in population (and the consequential increase in built area) in the cities like Amsterdam caused debate among urban planners. Different
approaches on urban design originated from this debate. The model of green urbanism by Lehmann (2011) focused on density and compactness in the sustainable development of cities while preserving green areas. He stated that bioclimatic urban design could be of great value to combat the UHIs. Another approach is the design philosophy of biodiversity, what attempts to redress the balance of nature in a polluted city by including animal, bird and plant life in architecture (Flannery & Smith, 2015).
A striking example of this new approach on green urban design is the phenomenon of vertical forest buildings, of which the first is constructed in Milan (‘Bosco Verticale’, designed by Stefano Boeri)(Flannery & Smith, 2015). The apartment skyscrapers are designed in such a way that they equal 2.5 acres of forest extending to the sky by making use of cantilevered balconies with 730 trees and 11,000 cover plants, and feature wind and solar systems for energy-efficiency (Vodenova & Angelova). Because this building can be build without expanding the city upon the territory, the building fits in results from Stone & Rodgers (2001) who mentioned that urban development must focus on compact, higher-density forms. In this way, vertical forest apartment buildings with green roofs and vertically vegetated surfaces can be seen as efficient option for the increase in population and for the mitigation of UHIE.
In the business district of Amsterdam, the ‘Zuidas’, a new plan to construct such a Vertical Forest is set up (see figure 4). The building will be placed between railways, highways and offices buildings, and will host a mix of functions such as offices, housing and public services (Council of Amsterdam, 2015). The council of Amsterdam choose the green building
designed by MVRDV and OVG as winner in a tender-procedure (Architectenweb, 2015). Personal communication with Sandra Gritti (November 26, 2015), development manager at
OVG , and Gijs Rikken (November 28, 2015), project manager and architect at MVRDV, learned that the building will consist of 50,000 to 75,000 square meters and have similar characteristics as the Bosco Vertical in Milan (e.g. large balconies, a green roof and many trees and plants). Gritti emphasized that the ‘Zuidas’ area is known for its large offices and other massive buildings and therefore, the architects also focused on physiological effects, such as an increase in the quality of life due to the better view for people in the direct neighbourhood of the building. Also, parts of the building will be publicly accessible. The building must add to efforts to counteract adverse climatological effects and to make the area more liveable via the mixing of functions (housing, working and recreating). This shows that Amsterdam is able and willing to mitigate UHI-related issues.
Discussion
The unlikely results of the heat index can be explained by different causes. An important restriction of the AWBGT is that it ignores the sun and the wind by excluding black globe temperature (Steeneveld et al., 2011; Budd, 2008). This means that this index is an unreliable guide for the prevention of heat illness from strenuous exercise that constrains people’s behavioral responses in warm weather (Budd, 2008). It leads to over or underestimation of environmental warmth. However, it is a convenient measure for predicting heat stress in people whose behavioral responses are unconstrained (Budd, 2008).
This could explain the results for the AWBGT in Amsterdam for the summer months of 2014. Even though air temperatures sometimes exceed 30°C and relative humidity exceeds 80%, the threshold of AWBGT > 27.7 °C is never exceeded and no heat stress occurs. During the summer of 2014 the KNMI warned about a persisting heat wave, with air temperatures exceeding 20 degrees during the night. According to the KNMI, measures were necessary to reduce the risk of vulnerable groups experiencing heat related illnesses (RIVM, 2014). Therefore, it is unlikely that no heat stress occurred during the summer of 2014. A heat index that includes black globe temperature might provide a better indication of heat stress.[T1]
Furthermore, the relative humidity and air temperatures were measured at different weather stations. Because of the small differences in relative humidity between the East (Holendrecht) and West (Westerpark) of Amsterdam (a maximum difference of 4%), and because of the lack of measurements by the Westerpark weather station and other weather stations, the relative humidity values from weather station Holendrecht were used for the AWBGT calculations throughout Amsterdam. A difference of 4% barely affects the outcome of the AWBGT. However, this does not rule out the possibility that bigger variations of relative humidity occur in other parts of Amsterdam. Measurements of relative humidity and temperature should be obtained from the same weather station to improve the validity of the methodological design.
The large costs of trees should maybe be justified with the concept of externalities, because trees not only mitigate the use of air conditioning and the amount of smog, but also give people enjoyment and enhance the quality of life within the city. Urban trees also play a role in sequestering CO2, which delays global warming. According to Ennos(2011), trees can sequester up to 90 KG of carbon per year at their peak, but this depends on the size, age, type of tree and on the climate. In order to take all these effects into account, the specific tree species, their characteristics and related costs have to be determined. When this is done a more accurate cost-benefit analyses can be made, which will result in a different NPV. All in all, we think that investing in trees is a good investment, because they have an influence on temperature reduction and other direct and indirect effects which improve the quality of life within the city. (Rosenfeld et al., 1998).
The different cost-benefit analyses were accompanied by several assumptions and
uncertainties, this can be improved in further research. The tree planting program could be improved by investigating which tree species should be implemented, determining what the actual and maintenance costs would be and by taking more of the indirect effects of these specific trees into account in our calculations. The analyses on pavements could be enhanced by closely analysing the local prices of white aggregate, shipping costs and the costs of binder in Amsterdam. The same holds for the cost-benefit analyses on roofing shingles. The results of the energy savings only represent the potential savings on electricity use and the calculations are based on certain assumptions and will therefore differ from reality, still it gives us a broad overview about the amount of money which can be saved if the electricity use of Amsterdam would decrease.
Conclusions
Despite of the results of the heat index that was used (AWBGT) to predict heat stress, Amsterdam is affected by one of the most severe heat islands in Europe (Van der Hoeven and Wandl, 2014). With the projected global increase in air temperature (KNMI, all climate scenarios), temperatures are likely to become higher and heat waves are likely to occur more frequently. The heat wave in 2003 claimed 1700 lives in the Netherlands (Van der Hoeven and Wandl, 2014). This means that by reducing the effects of the urban heat island, the amount of casualties could possibly be reduced in the future. Furthermore, studies have shown that improving the thermal environment leads to a direct increase in labor productivity (Lan et al., 2011). Therefore it is important that the effects of the urban heat island are assessed and mitigated. Literature research showed that there are several ways to mitigate the UHI, of which especially planting of trees, green roofs and other forms of green urban design are of significant value. The ‘Bosco Verticale’-building in de Zuidas is a striking example of this and shows that Amsterdam is already focusing on the use of green urban design.
According to Van der Hoeven and Wandl (2014) an increase of the albedo from 0.3 to 0.5 would result in an average LST decrease in the range of 4.0–4.6 degrees Celsius per hectare in Amsterdam. A cost-benefit analyses of several mitigation strategies was conducted. The results suggest that both a tree planting program and switching roof shingles are investments with a positive NPV. This means that the present values of all the benefits exceeds the present values of all the costs and should therefore be used to tackle the UHIE. The
investment of switching roof shingles has the largest NPV, as long as they are switched when the old roof needs to be replaced. The analyses on pavements also suggests a positive NPV, but this calculation is subjected to more uncertainties, which would first have to be
determined before making conclusions. Our calculations on energy savings suggest that only a 1% decrease of the amount of electricity used in summer, due to these mitigation
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