# Study on Surface Heat Budget of Various Pavements for Urban Heat Island Mitigation

Authors: Hideki Takebayashi; Masakazu Moriyama
Journal: Advances in Materials Science and Engineering
 (2012)

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## Abstract

The surface heat budgets of various pavement surfaces are studied with the aim of mitigating the urban heat island effect. In this study, the thermal characteristics of pavements are examined using data from observations. The net radiation, surface temperature, temperature under the surface, conduction heat flux, and core weight for each experimental surface are recorded, together with the weather conditions at the time of observation. The latent heat flux is estimated from the observed weight of the cores. The surface heat budget under the same weather conditions is examined, and the sensible heat flux from each target surface is calculated. The parameters that influence the surface heat budget, for example, solar reflectance (albedo), evaporative efficiency, heat conductivity, and heat capacity, are examined. On a typical summer day, the maximum reduction in the sensible heat flux from that on a normal asphalt surface is about 150 W/m2 for an asphalt surface with water-retaining material and about 100 W/m2 for a cement concrete surface with water-retaining material, depending on the albedo of each surface.


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## Body

## 1. Introduction

The purpose of this study is to investigate the urban heat island mitigation effect achieved by conversion from an asphalt pavement surface to another pavement surface for ground surface improvement, which is an established urban heat island mitigation technique. Various kinds of pavements were constructed experimentally for the purpose of investigating their effect on urban heat island mitigation by analyzing the surface heat budget. The urban heat island mitigation effect is discussed from the viewpoint of the sensible heat flux reduction for each pavement.Urban heat island mitigation technologies focus on the improvement of urban surface materials on roads, roofs, and walls. For example, roads and roofs coated with high-reflectance paint are called cool roofs and cool pavements by Akbari et al. [1]. According to their estimates, the annual balances in the saving in cooling cost and the increase in heating cost obtained by introducing cool roofs are $35 million in Los Angeles, $16 million in New York, and $10 million in Chicago. However, fewer studies have been carried out on roads as compared to those on green roofs [2–7], green parks [8–12], and green plantings [13–15].In Japan, several studies have been carried out to evaluate the performance of pavements designed to have a beneficial environmental impact [16–20]. However, those studies have evaluated each technology separately and discussed only the reduction in surface temperature as compared with that in the case of a normal pavement. They have not compared the surface heat budget for each pavement. In this study, the surface heat budget for each pavement surface is examined under the same weather conditions; further, the sensible heat flux for each pavement surface is evaluated, and the urban heat island mitigation effect of that pavement is discussed.


## 2. Observation Method

The observation site is located in Taisho Ward, Osaka, Japan. Sixteen experimental surfaces are constructed. The dimensions of each surface are 2 m × 2 m. A plan, a photo, and different cross-sections of the observation site are given in Figures1, 2, and 3, respectively, and an outline of the site is described in Table 1. In these figures, A refers to asphalt, B to interlocking block; and C to cement concrete. The south side of the observation site is open, and low-rise plant facilities are located on the north, west, and east sides. The distance from the observation site to the plant facilities on those three sides is about 20 m. Asphalts, cement concretes, and interlocking blocks are included in the surfaces studied. They are classified as “normal,” “porous,” and “with water-retaining material.” Each surface is referred to as As-N (asphalt-normal), As-P (asphalt-porous), As-W (asphalt-water retaining), Con-N (concrete-normal), Con-P (concrete-porous), Con-W (concrete-water retaining), Ilb-P (interlocking block-porous), and Ilb-W (interlocking block-water retaining). Grass and bare soil provide reference sites. These surfaces are fairly representative of the various kinds of pavement technologies proposed in Japan.Table 1
Outline of observation site.
PavementCharacteristicCodePhotoNormalAs-NAsphaltPorous (porosity: 13.6%)As-PWith water-retaining material (porosity: 13.6%, cement water-retention agent A)As-WWith water-retaining material (porosity: 13.6%, cement water-retention agent B)As-W′NormalCon-NCementPorous (porosity: 20.0%)Con-PWith water-retaining material (porosity: 20.0%, liquid water-retention agent A)Con-WWith water-retaining material (porosity: 20.0%, liquid water-retention agent B)Con-W′Interlocking blockPorousIlb-PWith water-retaining material (liquid water-retention agent)Ilb-WBare soilGranite soilBare soilGrassGrassFigure 1
Plan of observation site.Figure 2
Photo of observation site (position as shown in Figure1).Cross-sections of observation site.
(a)
A-A′ section(b)
B-B′ section(c)
C-C′ sectionAn outline of observation instrument is shown in Table2. The quantities observed are the surface and inner temperatures and conduction heat flux of each pavement and the weather conditions such as air temperature, relative humidity, global solar radiation, infrared radiation, precipitation, and wind direction and velocity. T-type thermocouples are placed at the boundaries of the pavement layers, and a conduction heat sensor is located 10 mm below the surface. These sensors were installed during pavement construction. The surface temperature is observed by an infrared thermometer set on the center of each surface. Weather conditions are observed near the observation site. The solar reflectance and weights of the test core, box, and block for each pavement surface, the net radiation for several pavement surfaces, and the surface temperature distribution of the observation site are observed for specific periods. The solar reflectance and net radiation are observed by a net radiation meter. The surface temperature distribution is observed by an infrared thermal camera. It was confirmed that data around the center of each surface is representative of each target, based on the observation results of the surface temperature distribution.Table 2
Outline of observation instrument.
ElementInstrument and accuracyGlobal solar radiation and infrared radiationEko, MR-50, 6%Wind direction and velocityPrede, O34S, 0.1 m/s (WS), 1% (WD)Air temperature and relative humidityEspec, RS-12, ±0.3°C, ±5%PrecipitationEko, NW-010, 0.5 mmSurface temperatureExergen, IRt/c.1X, ±2%Surface and inner temperatureT-type thermocoupleHeat flowEko, MF-180MWeightWeightingDownward/upward and short-wave/long-wave radiationKipp & Zonen, CPR-CNR1, ±10%Surface temperature distributionAvio, TVS-600


## 3. Observations

Observations were carried out in the summers of 2004 and 2005. In this study, the observed values from August 3 to 5, 2005, are analyzed to provide the surface heat budget for each pavement surface. The weights of the test core, box, and block are recorded during this period. The weather conditions during the observation period are shown in Figure4. It was mostly sunny during this period, but precipitation was observed at around 15:00 LST on August 5. The sudden drop in global solar radiation at around 12:00 on August 3 was due to cloud.Weather conditions on August 3 to 5, 2005.
(a)
Global solar radiation and infrared radiation near the observation site(b)
Wind direction and velocity at a height of 2.0 m near the observation site(c)
Air temperature and relative humidity at a height of 1.5 m near the observation site


### 3.1. Surface Temperature

The surface temperature is recorded by an infrared thermometer (Exergen, IRt/c.1X) and T-type thermocouple. The infrared thermometer is set on the north side of the target area at a height of 15 cm and at 30° from the horizontal surface. The target area is an ellipse with a long-axis radius of about 24 cm and a short-axis radius of about 9 cm. The T-type thermocouple is fastened to the surface by tape. The emissivity of each pavement surface in the nighttime is calculated using the values recorded by the infrared thermometer and T-type thermocouple. It was calculated using the following equation:ε=L/σTs4. The emissivity of each surface ranges from around 0.97 to 1.0. In the daytime, the values recorded by the infrared thermometer are lower than those recorded by the thermocouple. The thermocouple may be directly affected by solar radiation, but the infrared thermometer is not, as it is installed only in low-temperature areas included in the targeted ellipse. The amount of solar radiation differs depending on the distribution of the aggregate, especially on porous material surfaces. The infrared sensor can capture the average surface temperature. The observed values of the surface temperature for each pavement surface are shown in Figure 5. The surface temperature for As-N is the highest and that for grass is the lowest. The maximum difference in the daytime temperature between As-N and grass is about 20°C and that in the nighttime is less than about 4°.Figure 5
Observed values of surface temperature for each pavement surface on August 3 to 5, 2005.


### 3.2. Solar Reflectance

The net radiation meter, which records the downward and upward short-wave radiation and the downward and upward long-wave radiation, is set at a height of 30 cm above the center of each target surface. The shape factor between the target surface (2 m × 2 m) and radiation sensor is over 95%.For each surface, observations are carried out for 10 min with sampling every 10 s from 10:00 to 14:00 on July 27, 2005, when the solar altitude is high and the downward short-wave radiation is stable. This is a dry surface condition for reflectance. The solar reflectance on each pavement surface is shown in Table3. The solar reflectance on Con-N is larger than that on the other cement concrete surfaces because the presence of voids increases the dark area on Con-P and Con-W. The solar reflectance on As-W is larger than that on the other asphalt surface because the liquid water-retention agent injected into the voids of As-W is white. The solar reflectance on the interlocking blocks is relatively large because the material has a bright color.Table 3
Solar reflectance on each pavement surface (dry surface condition).
PavementAs-NAs-PAs-WAs-W′Con-NCon-PCon-WCon-W′Ilb-PIlb-WSoilGrassReflectance0.0820.0740.1720.2670.2940.1410.2020.1500.3970.3940.2250.210


### 3.3. Latent Heat Flux

Irrigation corresponding to 10 mm/h rainfall was carried out from 17:00 to 18:00 on August 2, 2005, the day before the observations. Then, the weights of the cores, boxes, and blocks were recorded every hour in the morning and every two hours in the afternoon on the first day (August 3), every two hours on the second day (August 4), and at 8:00 and 13:00 on the third day (August 5). Three cores, boxes, and blocks for each experimental surface were weighed for estimating the evaporative flux. The cores and boxes used for recording the weight are shown in Figures6 and 7. The core diameter was 15 cm, and the core depth was 5 cm for the asphalt surface and 15 cm for the cement concrete surface, as determined by the depth of each surface layer. Blocks (20 cm × 10 cm × 8 cm) were picked up and weighed. An electronic balance was used for recording the weight. Because it was measured in the field, moisture content in the material was not measured.Figure 6
Core for recording the weight (15 cm diameter).Figure 7
Box for recording the weight of grass and bare soil.The estimated values of evaporative flux obtained from the observed weights for August 3 to 5, 2005, are shown in Figure8. Because it rained at around 15:00 on August 5, the observation period was considered to be over at that time. On the first day after the irrigation, a difference in the amount of evaporative flux for each pavement surface was confirmed, but on the second day, the evaporative flux was quite small for all the pavement surfaces, except for grass and bare soil. We conducted the same experiments three times in August 2005 and 2004. The estimation results of the latent heat flux were quite similar for each experiment.Figure 8
Values of evaporative flux estimated from the observed weights on August 3 to 5, 2005.


## 3.1. Surface Temperature

The surface temperature is recorded by an infrared thermometer (Exergen, IRt/c.1X) and T-type thermocouple. The infrared thermometer is set on the north side of the target area at a height of 15 cm and at 30° from the horizontal surface. The target area is an ellipse with a long-axis radius of about 24 cm and a short-axis radius of about 9 cm. The T-type thermocouple is fastened to the surface by tape. The emissivity of each pavement surface in the nighttime is calculated using the values recorded by the infrared thermometer and T-type thermocouple. It was calculated using the following equation:ε=L/σTs4. The emissivity of each surface ranges from around 0.97 to 1.0. In the daytime, the values recorded by the infrared thermometer are lower than those recorded by the thermocouple. The thermocouple may be directly affected by solar radiation, but the infrared thermometer is not, as it is installed only in low-temperature areas included in the targeted ellipse. The amount of solar radiation differs depending on the distribution of the aggregate, especially on porous material surfaces. The infrared sensor can capture the average surface temperature. The observed values of the surface temperature for each pavement surface are shown in Figure 5. The surface temperature for As-N is the highest and that for grass is the lowest. The maximum difference in the daytime temperature between As-N and grass is about 20°C and that in the nighttime is less than about 4°.Figure 5
Observed values of surface temperature for each pavement surface on August 3 to 5, 2005.


## 3.2. Solar Reflectance

The net radiation meter, which records the downward and upward short-wave radiation and the downward and upward long-wave radiation, is set at a height of 30 cm above the center of each target surface. The shape factor between the target surface (2 m × 2 m) and radiation sensor is over 95%.For each surface, observations are carried out for 10 min with sampling every 10 s from 10:00 to 14:00 on July 27, 2005, when the solar altitude is high and the downward short-wave radiation is stable. This is a dry surface condition for reflectance. The solar reflectance on each pavement surface is shown in Table3. The solar reflectance on Con-N is larger than that on the other cement concrete surfaces because the presence of voids increases the dark area on Con-P and Con-W. The solar reflectance on As-W is larger than that on the other asphalt surface because the liquid water-retention agent injected into the voids of As-W is white. The solar reflectance on the interlocking blocks is relatively large because the material has a bright color.Table 3
Solar reflectance on each pavement surface (dry surface condition).
PavementAs-NAs-PAs-WAs-W′Con-NCon-PCon-WCon-W′Ilb-PIlb-WSoilGrassReflectance0.0820.0740.1720.2670.2940.1410.2020.1500.3970.3940.2250.210


## 3.3. Latent Heat Flux

Irrigation corresponding to 10 mm/h rainfall was carried out from 17:00 to 18:00 on August 2, 2005, the day before the observations. Then, the weights of the cores, boxes, and blocks were recorded every hour in the morning and every two hours in the afternoon on the first day (August 3), every two hours on the second day (August 4), and at 8:00 and 13:00 on the third day (August 5). Three cores, boxes, and blocks for each experimental surface were weighed for estimating the evaporative flux. The cores and boxes used for recording the weight are shown in Figures6 and 7. The core diameter was 15 cm, and the core depth was 5 cm for the asphalt surface and 15 cm for the cement concrete surface, as determined by the depth of each surface layer. Blocks (20 cm × 10 cm × 8 cm) were picked up and weighed. An electronic balance was used for recording the weight. Because it was measured in the field, moisture content in the material was not measured.Figure 6
Core for recording the weight (15 cm diameter).Figure 7
Box for recording the weight of grass and bare soil.The estimated values of evaporative flux obtained from the observed weights for August 3 to 5, 2005, are shown in Figure8. Because it rained at around 15:00 on August 5, the observation period was considered to be over at that time. On the first day after the irrigation, a difference in the amount of evaporative flux for each pavement surface was confirmed, but on the second day, the evaporative flux was quite small for all the pavement surfaces, except for grass and bare soil. We conducted the same experiments three times in August 2005 and 2004. The estimation results of the latent heat flux were quite similar for each experiment.Figure 8
Values of evaporative flux estimated from the observed weights on August 3 to 5, 2005.


## 4. Analysis of Surface Heat Budget

### 4.1. Surface Heat Budget Equation

The surface heat budget is represented as follows, by assuming that evaporation occurs at the surface:(1)Rn=A+V+lE,(2)A=-λ∂T∂z|z=0,(3)V=α(Ts-Ta),(4)lE=l⋅β⋅αw(Xs-Xa)=l⋅β⋅α(Xs-Xa)Cp,
where Rn is the net radiation (W/m2), A the conduction heat flux (W/m2), V the sensible heat flux (W/m2), lE the latent heat flux (W/m2), λ the heat conductivity (W/(mK)), α the sensible heat transfer coefficient (W/(m2K)), Ts the surface temperature (°C), Ta the air temperature (°C), l the latent heat of water (J/kg), β the evaporative efficiency (−), αw the evaporative transfer coefficient (kg/(m2h(kg/kg′))), Cp the specific heat (J/(kgK)), Xs the saturated absolute humidity of the surface (kg/kg′), and Xa the absolute humidity of air (kg/kg′).


### 4.2. Estimation of Heat Conductivity and Heat Capacity

The temperature profile in the material is calculated by the following one-dimensional unsteady heat conduction equation:(5)∂T∂t|m=λc∂T2∂z2,
where c is the heat capacity (J/(m3K)).In this study,λ and c are estimated on the basis of the observed heat flux and temperature data in each pavement. The differential equations for (2) and (5) are expressed as follows:(6)A=-λΔTΔz=λΔz(Ts-T1),(7)λ1(Δz1/2)+(Δz2/2)(Tm-1-TmΔz1-Tm-Tm+1Δz2)=c(Tm-Tm*)Δt,
where Δz is the distance between Ts and T1 (m), Δz1 the distance between Tm-1 and Tm(m), and Δz2 the distance between Tmand Tm+1 (m). When the observed values are substituted in (6), a relationship graph for estimating λ is obtained, as shown in Figure 9. The slope of the linear approximation is interpreted as λ. Then, when the estimated λ and the observed values are substituted in (7), a relationship graph for estimating c is obtained, as shown in Figure 10. The slope of the linear approximation is interpreted as c. The estimated values of λ and c for each pavement surface are shown in Table 4. Only those values near the surface are estimated.Table 4
Estimated values of heat conductivity (W/(mK)) and heat capacity (MJ/(Km3)) for each pavement surface.
PavementAs-NAs-PAs-WAs-W′Con-NCon-PCon-WCon-W′Ilb-PIlb-WSoilGrassConductivity1.030.901.031.432.211.211.190.901.471.160.740.72Capacity5.10.96.30.97.21.01.51.22.91.610.08.1Figure 9
Relationship graph for estimation of heat conductivity in the case of As-N.Figure 10
Relationship graph for estimation of heat capacity in the case of As-N.


### 4.3. Estimation of Evaporative Efficiency

The evaporation efficiencyβ is required for determining the latent heat flux from (4). The following equation is obtained by integrating and transforming (1), (3), and (4):(8)Rn-A=α{(Ts-Ta)+l⋅β⋅1Cp(Xs-Xa)}
Since Rn, A, Ts, Ta, and Xa are obtained by observation, the only unknowns are α and β. The following two cases for determining α and β are assumed.(1) Using the Jurges Formula [21] to Determine the Sensible Heat Transfer Coefficient α
By comparing the daily integrated latent heat flux obtained from the observed weight of cores with that from (4), the daily averaged βis estimated. In this study, β is assumed to be constant over one day because the moisture condition in the material may not change significantly in one day. The values of β estimated using the α value calculated by the Jurges formula are shown in Table 5.Table 5
Values of evaporative efficiency estimated using the sensible heat transfer coefficient calculated by the Jurges formula.
PavementAs-PAs-WAs-W′Con-PCon-WCon-W′Ilb-PIlb-WSoilGrass1st day (Aug. 3)0.010.110.030.040.040.040.070.080.310.932nd day (Aug. 4)0.010.040.020.020.030.020.040.040.160.793rd day (Aug. 5)0.010.030.030.030.030.020.050.050.030.69(2) Using (8) to Determine α
In (8), if β is known, α is obtained by comparing the daily integrated latent heat flux obtained from the observed core weights with that from (4). The values of β estimated using the α value calculated from (8) are shown in Table 6.Table 6
Values of evaporative efficiency estimated using the sensible heat transfer coefficient calculated by (8).
PavementAs-PAs-WAs-W′Con-PCon-WCon-W′Ilb-PIlb-WSoilGrass1st day (Aug. 3)0.010.090.060.040.040.050.050.071.001.002nd day (Aug. 4)0.000.030.030.020.020.020.030.020.201.003rd day (Aug. 5)0.000.020.030.010.020.010.030.020.091.00The values ofα determined by methods (1) and (2) are shown in Figure 11. The values for As-N, Con-N, and grass are shown as representative values. The diurnal variation is similar for the other surfaces. The α value estimated from method (1) has a peak in the afternoon, while that estimated from method (2) has a peak in the morning. This difference is considered to be influenced by the residues of the surface heat budget, because the estimated conduction heat flux in the morning is relatively small owing to the lower surface temperature recorded by the thermometer. Therefore, the surface temperature should be treated more carefully.Figure 11
Estimated values of sensible heat transfer coefficient on August 4, 2005.


## 4.1. Surface Heat Budget Equation

The surface heat budget is represented as follows, by assuming that evaporation occurs at the surface:(1)Rn=A+V+lE,(2)A=-λ∂T∂z|z=0,(3)V=α(Ts-Ta),(4)lE=l⋅β⋅αw(Xs-Xa)=l⋅β⋅α(Xs-Xa)Cp,
where Rn is the net radiation (W/m2), A the conduction heat flux (W/m2), V the sensible heat flux (W/m2), lE the latent heat flux (W/m2), λ the heat conductivity (W/(mK)), α the sensible heat transfer coefficient (W/(m2K)), Ts the surface temperature (°C), Ta the air temperature (°C), l the latent heat of water (J/kg), β the evaporative efficiency (−), αw the evaporative transfer coefficient (kg/(m2h(kg/kg′))), Cp the specific heat (J/(kgK)), Xs the saturated absolute humidity of the surface (kg/kg′), and Xa the absolute humidity of air (kg/kg′).


## 4.2. Estimation of Heat Conductivity and Heat Capacity

The temperature profile in the material is calculated by the following one-dimensional unsteady heat conduction equation:(5)∂T∂t|m=λc∂T2∂z2,
where c is the heat capacity (J/(m3K)).In this study,λ and c are estimated on the basis of the observed heat flux and temperature data in each pavement. The differential equations for (2) and (5) are expressed as follows:(6)A=-λΔTΔz=λΔz(Ts-T1),(7)λ1(Δz1/2)+(Δz2/2)(Tm-1-TmΔz1-Tm-Tm+1Δz2)=c(Tm-Tm*)Δt,
where Δz is the distance between Ts and T1 (m), Δz1 the distance between Tm-1 and Tm(m), and Δz2 the distance between Tmand Tm+1 (m). When the observed values are substituted in (6), a relationship graph for estimating λ is obtained, as shown in Figure 9. The slope of the linear approximation is interpreted as λ. Then, when the estimated λ and the observed values are substituted in (7), a relationship graph for estimating c is obtained, as shown in Figure 10. The slope of the linear approximation is interpreted as c. The estimated values of λ and c for each pavement surface are shown in Table 4. Only those values near the surface are estimated.Table 4
Estimated values of heat conductivity (W/(mK)) and heat capacity (MJ/(Km3)) for each pavement surface.
PavementAs-NAs-PAs-WAs-W′Con-NCon-PCon-WCon-W′Ilb-PIlb-WSoilGrassConductivity1.030.901.031.432.211.211.190.901.471.160.740.72Capacity5.10.96.30.97.21.01.51.22.91.610.08.1Figure 9
Relationship graph for estimation of heat conductivity in the case of As-N.Figure 10
Relationship graph for estimation of heat capacity in the case of As-N.


## 4.3. Estimation of Evaporative Efficiency

The evaporation efficiencyβ is required for determining the latent heat flux from (4). The following equation is obtained by integrating and transforming (1), (3), and (4):(8)Rn-A=α{(Ts-Ta)+l⋅β⋅1Cp(Xs-Xa)}
Since Rn, A, Ts, Ta, and Xa are obtained by observation, the only unknowns are α and β. The following two cases for determining α and β are assumed.(1) Using the Jurges Formula [21] to Determine the Sensible Heat Transfer Coefficient α
By comparing the daily integrated latent heat flux obtained from the observed weight of cores with that from (4), the daily averaged βis estimated. In this study, β is assumed to be constant over one day because the moisture condition in the material may not change significantly in one day. The values of β estimated using the α value calculated by the Jurges formula are shown in Table 5.Table 5
Values of evaporative efficiency estimated using the sensible heat transfer coefficient calculated by the Jurges formula.
PavementAs-PAs-WAs-W′Con-PCon-WCon-W′Ilb-PIlb-WSoilGrass1st day (Aug. 3)0.010.110.030.040.040.040.070.080.310.932nd day (Aug. 4)0.010.040.020.020.030.020.040.040.160.793rd day (Aug. 5)0.010.030.030.030.030.020.050.050.030.69(2) Using (8) to Determine α
In (8), if β is known, α is obtained by comparing the daily integrated latent heat flux obtained from the observed core weights with that from (4). The values of β estimated using the α value calculated from (8) are shown in Table 6.Table 6
Values of evaporative efficiency estimated using the sensible heat transfer coefficient calculated by (8).
PavementAs-PAs-WAs-W′Con-PCon-WCon-W′Ilb-PIlb-WSoilGrass1st day (Aug. 3)0.010.090.060.040.040.050.050.071.001.002nd day (Aug. 4)0.000.030.030.020.020.020.030.020.201.003rd day (Aug. 5)0.000.020.030.010.020.010.030.020.091.00The values ofα determined by methods (1) and (2) are shown in Figure 11. The values for As-N, Con-N, and grass are shown as representative values. The diurnal variation is similar for the other surfaces. The α value estimated from method (1) has a peak in the afternoon, while that estimated from method (2) has a peak in the morning. This difference is considered to be influenced by the residues of the surface heat budget, because the estimated conduction heat flux in the morning is relatively small owing to the lower surface temperature recorded by the thermometer. Therefore, the surface temperature should be treated more carefully.Figure 11
Estimated values of sensible heat transfer coefficient on August 4, 2005.


## 5. Calculation of Surface Heat Budget

### 5.1. Calculation Method

The following equation [3] is obtained by integrating and transforming (1), (3), and (6):(9)Ts=Rn-lE+α⋅Ta+(λ/Δz)⋅T1α+(λ/Δz).
Since Ts is required for calculating Rn and lE, it is calculated using the convergence method. By comparing the daily integrated latent heat flux obtained from the observed core weights, the daily averaged β is estimated using the Jurges formula for α. The values of β estimated using the α value calculated by (9) are shown in Table 7.Table 7
Values of evaporative efficiency estimated using the sensible heat transfer coefficient calculated by (9).
PavementAs-PAs-WAs-W′Con-PCon-WCon-W′Ilb-PIlb-WSoilGrass1st day (Aug. 3)0.0090.1150.0300.0440.0440.0510.0790.0950.4560.5082nd day (Aug. 4)0.0050.0400.0180.0260.0270.0230.0460.0400.2040.5133rd day (Aug. 5)0.0050.0310.0290.0270.0300.0240.0680.0580.1220.502


### 5.2. Calculation Results

The estimated values of the surface heat budget for each pavement surface on August 3 to 5, 2005, are shown in Figure12. The calculated and observed values for several pavement surfaces on August 3 to 5, 2005, are shown in Figure 13, and these values are approximately consistent.Values of surface heat budget estimated for each pavement surface on August 3 to 5, 2005.
(a)
As-N(b)
As-W(c)
Con-N(d)
Con-W(e)
Ilb-W(f)
Bare soil(g)
GrassCalculated and observed values of surface temperature for several pavement surfaces on August 3 to 5, 2005.
(a)
As-N(b)
As-W(c)
Con-N(d)
Con-W(e)
Ilb-W(f)
Bare soilThe estimated values of the sensible heat flux from each pavement surface on August 3 to 5, 2005, are shown in Table8. The maximum and mean values are also listed. At the maximum value, the reduction in the heat flux from that on As-N is about 180 W/m2 for Con-N and about 270 W/m2 for Ilb-P and Ilb-W. The heat flux reduction is considered to be influenced by albedo for Con-N and by both albedo and evaporation for Ilb-P and Ilb-W. The reduction in the heat flux from that on As-N is small for As-P and As-W because of the small differences in albedo and evaporation. The reduction values for Con-P and Con-W are also small because of the small albedo, despite some evaporation. The reduction on bare soil and grass is large owing to evaporation.Table 8
Values of sensible heat flux (W/m2) estimated for each pavement surface on August 3 to 5, 2005.
PavementAs-NAs-PAs-WAs-W′Con-NCon-PCon-WCon-W′Ilb-PIlb-WSoilGrassMaximum446.4465.3327.3313.7262.4358.1337.1365.9163.9172.6169.990.9Mean128.1117.975.372.679.984.279.085.639.941.320.02.9


## 5.1. Calculation Method

The following equation [3] is obtained by integrating and transforming (1), (3), and (6):(9)Ts=Rn-lE+α⋅Ta+(λ/Δz)⋅T1α+(λ/Δz).
Since Ts is required for calculating Rn and lE, it is calculated using the convergence method. By comparing the daily integrated latent heat flux obtained from the observed core weights, the daily averaged β is estimated using the Jurges formula for α. The values of β estimated using the α value calculated by (9) are shown in Table 7.Table 7
Values of evaporative efficiency estimated using the sensible heat transfer coefficient calculated by (9).
PavementAs-PAs-WAs-W′Con-PCon-WCon-W′Ilb-PIlb-WSoilGrass1st day (Aug. 3)0.0090.1150.0300.0440.0440.0510.0790.0950.4560.5082nd day (Aug. 4)0.0050.0400.0180.0260.0270.0230.0460.0400.2040.5133rd day (Aug. 5)0.0050.0310.0290.0270.0300.0240.0680.0580.1220.502


## 5.2. Calculation Results

The estimated values of the surface heat budget for each pavement surface on August 3 to 5, 2005, are shown in Figure12. The calculated and observed values for several pavement surfaces on August 3 to 5, 2005, are shown in Figure 13, and these values are approximately consistent.Values of surface heat budget estimated for each pavement surface on August 3 to 5, 2005.
(a)
As-N(b)
As-W(c)
Con-N(d)
Con-W(e)
Ilb-W(f)
Bare soil(g)
GrassCalculated and observed values of surface temperature for several pavement surfaces on August 3 to 5, 2005.
(a)
As-N(b)
As-W(c)
Con-N(d)
Con-W(e)
Ilb-W(f)
Bare soilThe estimated values of the sensible heat flux from each pavement surface on August 3 to 5, 2005, are shown in Table8. The maximum and mean values are also listed. At the maximum value, the reduction in the heat flux from that on As-N is about 180 W/m2 for Con-N and about 270 W/m2 for Ilb-P and Ilb-W. The heat flux reduction is considered to be influenced by albedo for Con-N and by both albedo and evaporation for Ilb-P and Ilb-W. The reduction in the heat flux from that on As-N is small for As-P and As-W because of the small differences in albedo and evaporation. The reduction values for Con-P and Con-W are also small because of the small albedo, despite some evaporation. The reduction on bare soil and grass is large owing to evaporation.Table 8
Values of sensible heat flux (W/m2) estimated for each pavement surface on August 3 to 5, 2005.
PavementAs-NAs-PAs-WAs-W′Con-NCon-PCon-WCon-W′Ilb-PIlb-WSoilGrassMaximum446.4465.3327.3313.7262.4358.1337.1365.9163.9172.6169.990.9Mean128.1117.975.372.679.984.279.085.639.941.320.02.9


## 6. Conclusions

In this study, the thermal characteristics of pavements for urban heat island mitigation are examined on the basis of observations and analysis of the surface heat budget. The surface heat budget for different surfaces under the same weather conditions is examined, and the sensible heat flux from each target surface is calculated. The parameters affecting the surface heat budget, for example, solar reflectance (albedo), evaporative efficiency, heat conductivity, and heat capacity, are examined.The following points are discussed on the basis of the results of the surface heat budget analysis for each pavement.(i)
Sensible heat flux is greatly reduced by evaporation on bare soil and grass surfaces. The reduction in the sensible heat flux compared with that on a normal asphalt surface in the daytime and nighttime is about 270 and 40 W/m2 on bare soil and about 350 and 60 W/m2 on grass.(ii)
The reduction in the sensible heat flux by interlocking blocks compared with that on a normal asphalt surface is relatively large, about 280 and 20 W/m2 in the daytime and nighttime, respectively.(iii)
The reduction in the sensible heat flux for a normal cement concrete surface as compared to that on a normal asphalt surface is about 180 W/m2 in the daytime, because of a slightly higher albedo. However, the reduction in the nighttime is small owing to a slightly larger thermal mass.(iv)
The reduction in the sensible heat flux by porous and water-retaining concrete surfaces compared with that on a normal asphalt surface is about 100 W/m2 in the daytime, which is lower than that for the normal cement concrete surface, because the albedo of these surfaces is a little lower than that of the normal cement concrete surface. However, the sensible heat flux reduction in the nighttime is about 20 W/m2 because of a slightly smaller thermal mass.(v)
The reduction in the sensible heat flux by a water-retaining asphalt surface as compared with that on a normal asphalt surface is about 140 W/m2 in the daytime, owing to evaporation and albedo. However, the heat flux reduction by a porous asphalt surface is almost 0, because there is no evaporation.The pavements targeted in this study do not represent all the pavements used for mitigating the urban heat island effect. However, the heat budget for each surface shown in this paper is generally representative of that for several kinds of pavements used for urban heat island mitigation. The results of this study may act as a guide for the future development of pavement materials.



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*Source: 523051-2012-05-17.xml*