1.1 Novelty and Gaps in Knowledge

Based on the review, previous studies focused on various methods for minimising the UHI phenomena. Numerous studies (Daniels et al., 2019, Bobes-Jesus et al., 2013) focused on the influential factors and parameters for improving the asphalt solar collectors heat collection efficiency. The work (Nasir et al., 2017a) investigated the influence of pipe layout, embedded pipe depth, pipe spacing, pipe diameter, the flow rate of the medium used for the heat transfer, thermal conductivity, etc. The impact of building geometry (Nasir et al., 2015) and street canyon aspect ratio (Nasir et al., 2017c, Nasir et al., 2017b) on the PSC system performance were also analysed using a decoupled approach. The decoupled approach simulates the urban canyon and PSC system separately and cannot predict the PSC’s direct influence on the urban air temperature. In addition, it has limitations when it comes to transferring the temperature data from the urban canyon model to the PSC system model. The study (Guldentops et al., 2016) focused on model development and validation of the pavement solar collector system. However, no study evaluated the integration of urban street canyon and the PSC system in a computational domain or using a coupled approach for analysing the impact of the PSC systems on the surface-air temperature reduction and thermal collection. This is mainly due to the high requirements for computing power and resource to carry out such simulations which were not available previously. The building cooling energy demand will also decrease because of the lower air temperature. Therefore, to fully optimise the system, the heat transfer processes from the sun to the pavement, pavement to air and air to the building must be taken into account. It is envisaged that the proposed approach will also help the development of future models to assess the influence of the PSC on the energy demand of the neighbouring buildings i.e. in terms of affecting the local air temperature and providing heat to the buildings. It is necessary to combine the canyon, pavement and PSC system to simulate the temperature reductions and thermal collection at the same time. This has not been explored in previous research (Daniels et al., 2019, Bobes-Jesus et al., 2013, Nasir et al., 2017a) and the limitation of existing models. Little research discussed the influence of the urban environment on the thermal performance of pavement solar collectors. Furthermore, there is no research on the pavement solar collector system’s influence and the urban environment conditions and vice versa.

1.2 Aim and Objectives

This work investigates the combined effect of the PSC system on building, air and road temperatures by modelling the heat transfer between the urban street canyon and pavement solar collectors using a coupled computational approach. A basic urban surface unit can be recognised as the urban canyon, the canyon includes walls and ground between two adjacent buildings, which can be used as the basic unit of urban areas in the built environment (M. Nunez and T. R. Oke, 1976). An array of pipes was embedded under the pavement located in the middle of an urban canyon to evaluate how the PSC system can affect the pavement surface temperature and surrounding air temperature. Computational Fluid Dynamics (CFD) simulation was used for this research which is widely used for analysing the aero-thermal environment of urban street canyons and pavement solar collectors (Ai and Mak, 2017). The weather data of Milan, Italy, was selected for this study and 20% of the road was embedded with the pipes. The study will compare the influence on the surface temperature and the ambient environment of pavement with and without the PSC system, also, assess the potential thermal collection. Six different water inlet velocities and temperatures were compared to show how it affects the PSC system’s thermal performance. The asphalt slab prototype of PSC was built and tested in a laboratory setup to obtain the real-time temperature distribution across an asphalt pavement and validate the CFD modelling approach.

2.1 Geometry and computational domain

2.1.1 Urban domain

To understand the local atmospheric flow and other related processes, a street canyon can be used as the basic unit of urban areas in the built environment (Ai and Mak, 2017, Oke, 1987). The microclimate of the urban street canyon includes temperature, wind flow, pollutants, noise and other outdoor environmental parameters, which are associated with the indoor environmental quality of the nearby buildings (Ai and Mak, 2015). It is suggested by Zhu et al. (2007) and Bouyer et al. (2011) that the microclimate of street canyons influences the pedestrian thermal comfort and building energy performance.

According to Table 2.1 (Murphy, 2011), the principle road’s width should be wider than 8.8 m, which includes the cycle lane. In the urban street canyon, the dimensions of the road between two buildings were 10.0 m with (W) and 100.0 m length (L). Building’s height was 10.0 m (H), which the canyon aspect ratio (H/W) was 1. The urban street canyon domain is illustrated in Figure 3.

Figure 3 

(a) Integration of PSC into an urban canyon (b) geometry of the whole domain and (c) location of the pipes (section from Figure 3 (a), not to scale).

Side and top walls are set to symmetry walls, the distance between inflow and outflow were set to 5H, which was 50.0 m. The 3H height was selected for the distance between the ground and domain top lane to provide enough space for airflow circulating. The wind came from the inlet, which is perpendicular to the pavement direction (y-direction).

The whole domain was divided into two regions: (1). 0.3 m thickness solid pavement region and (2). air-fluid region (wind). This model’s total macro domain was defined as 100.0 m length × 80.0 m width × 30.3 m height.

2.2 Mesh and sensitivity analysis

Mesh size impacts the result accuracy; the smaller mesh can provide higher quality simulation results as there will be more nodes and elements of the object, which needs longer simulation time. However, the mesh size for the whole domain was not uniform in order to achieve faster computational times (Fluent, 2011).

The patch conforming method was applied to canyon sections, including building walls, building roofs and ground road surfaces. The mesh sizing for the PSC area was set to High, which can calculate a more accurate output value than Coarse and Medium. Mesh details are shown in Table 1 and Figure 4.

2.3 Boundary conditions

Base on the previous studies (Nasir et al., 2015, Nasir et al., 2017b, Nasir et al., 2017c, Nasir et al., 2017a), in this research, the urban street canyon was located in Milan, Italy, for result validation, the latitude is 45.47°, and longitude is 9.18°. The selected time and date are 14:00 on 26^th June, on that day the sunshine factor is 0.25. The wind came from the south direction with a temperature of 303K (29.85°C) and velocity of 2 m/s.

Water at a lower temperature was circulated through the copper pipes and brought away the pavement slab’s heat. According to (Weather and Climate), the annual water temperature range is between 287K and 299K in Italy. Therefore, the initial inlet water temperature was set to 293K (19.85°C) (Bobes-Jesus et al., 2013). Copper was used as the pipe material. The top slab of the pavement was made of asphalt. The surface properties for pipes and asphalt pavement are shown in Table 2.

Asphalt pavement can be heated up after absorbing a large amount of solar radiation, the sun position and air temperature are changing with time. So eight different times of 26^th June 2016 in Milan, Italy were selected for analysing the PSC system performance under different environmental conditions. The water velocity was 0.25 m/s with a temperature of 293K.

2.4 CFD Theory

The energy model was set to investigate the temperatures and wind flow pattern, and the viscous model was set to k-epsilon (2 equations). The steady RANS equations simulated urban turbulent airflow with the standard k-ε model based on the principle of heat conversion, continuity and momentum. In this model, the transport equation for turbulence kinetic energy (k) and dissipation rate (ε) allows the airflow to be fully turbulent solved (Fluent, 2011). Discrete ordinate (DO) and solar ray tracing were used as the radiation model for evaluating the impact of solar radiation on the surface temperature and PSC system performance. The governing equations can be written as follows:

Momentum equation:

Continuity equation:

Heat conservation equation:

Where $\overline{u_i}$M4 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ \overline {{u_i}} \] \end{document} represent the mean speed of the airflow; ρ is the air density; μ the dynamic viscosity of the fluid; $\overline{{u^{\prime }}_i}\overline{{u^{\prime }}_j}$M5 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ \overline {{{u^\prime}_i}} \ \overline {{{u^\prime}_j}} \] \end{document} is the Reynolds stress; f_i is the thermal-induced buoyant force; $\overline{T}$M6 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ \bar T \] \end{document} is the potential temperature; K_t is the heat diffusivity

Transport equations:

Where k is the turbulence kinetic energy; ε the rate of dissipation; G_K is the generation of turbulence kinetic energy due to changes in velocity; G_b is the generation of turbulence kinetic energy due to the buoyancy force; C_1ε, C_2ε and C_3ε are constant; σ_K and σ_ε represent the turbulent Prandtl numbers for k and ε respectively. The discrete ordinate (DO) model solves the radiate transfer equation (6) for a finite number of discrete solid angles each associated with a vector direction fixed in the global Cartesian system (x, y, z) (Fluent, 2011). Hence,

Where $\overrightarrow{r}$M10 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ \vec r \] \end{document} is the position vector; $\overrightarrow{s}$M11 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ \vec s \] \end{document} is the direction vector; ${\overrightarrow{s}}_t$M12 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ {\vec s_t} \] \end{document} is the scattering direction vector; s is the path length; a is the absorption coefficient; n is the refractive index; σ_s is the scattering coefficient; σ is the Stefan-Boltzmann constant (5.669 × 10^–8 W/m²K⁴); T is the local temperature; Φ is the phase function; Ω’ represents the solid angle and I is the radiation intensity which depends on the position of the and vectors.

2.5 Numerical model validation

For the validation of the PSC numerical model, a laboratory experiment was conducted in the Energy Technologies Building, University of Nottingham, UK. A 600 mm length × 400 mm width × 130 mm depth PSC asphalt slab specimen sealed within an insulated box (Figure 4) was made of Bitumen Macadam with the properties of ρ = 2300 kg/m³, c_p = 920 J/kgK and k = 1.73 W/mK. A 6.1 m length copper pipe with a diameter, ∅ of 8 mm, with a thickness of 1 mm and with a thermal conductivity value, k_c of 413 W/mK was embedded at the slab specimen. The pipe was bent to replicate a serpentine U-PSC pipe with one water inlet nearby the side wall named Side A and one water outlet nearby the adjacent side wall, named Side B (Figure 6 (a)). The distance between each pass was maintained at 60 mm (Figure 5). The controlled water flow is expected to reduce the slab and surface temperature by extracting heat from the pavement. For heating up the asphalt specimen, 2 halogen lamps of 400W each were used with beam angle, ϕ of 60° from Side A and the lamp is 160 mm away from the specimen topmost surface.

The temperature at both Side A and Side B of the specimen surface, top layer, middle layer and bottom layer was measured using K-type thermocouples, see Figure 6. Calibration test of the thermocouples and water leakage test of the asphalt specimen was initially conducted before the specimen temperature was measured. The data was transferred and uploaded in PicoLog 6, a PC software which recorded the measurement at the specified locations.

The surface was heated up to 80.5°C and a total of 2 hours and 10 minutes was required to heat the asphalt specimen. The data logger began to record the temperature value at each thermocouple during the heating of the slab. After the temperature reached 80.5°C, water with ambient temperature 20–22°C began to flow into the serpentine pipe by using a pump with 240 litres/h maximum flow rate, 8.4W power, 12V DC voltage and 3 m maximum head. The water flow continued within 1-hour duration before the pump was switched off. Using FLIRthermal infrared camera, the topmost asphalt specimen surface temperature was taken every 2 minutes during the specified duration. The validation of the urban canyon modelling was carried out and fully detailed in previous works (Nasir et al., 2015).

3.1 Experimental validation for software modelling

The temperature field was validated by comparing the obtained temperature from the simulation with the temperature based on the experimental results. The comparison was carried out by measuring a similar location where the thermocouples were placed in the PSC prototype, see the validation results in Figure 7. The temperature results at three positions according to the asphalt depth (top, middle and bottom of side A and side B) between experiment and simulation were compared. Based on Figure 7, the simulation results were underestimated up to 5°C at the top position; however, the variance became nominal at the middle and bottom positions, by 1–3°C. Overall, the temperature distribution profile across the pavement depth of the simulation was compatible with the temperature profile across the pavement depth of the experiment. It implies from the validation that the temperature field of the constructed model in this study can be used for further analysis.

3.2 Effect of mesh sizing on results accuracy

Mesh size is one factor that influences the simulation result; Figure 8 shows the temperature difference among three different mesh sizes. The result for pipe 1, pipe 5 and 6 were almost the same; the maximum temperature difference was between pipe 4 and pipe 8, which was 0.21°C. The outlet water temperatures were in the range of 20.94°C to 22.01°C, which means the temperature differences among these 9 pipes were up to 1.07°C. Therefore, the percentage difference (19.53%) was not negligible. In order to obtain high accuracy results, the Fine mesh size was selected for future simulation and analysis.

3.3 Effect of the PSC system on urban canyon temperature

Figure 9 (a) shows the temperature distribution of the urban canyon ground and building surfaces. Due to the shadowing effect caused by the windward building, the lower surface temperature was (45–50°C) was observed near the windward building. It can also be observed that the pavement had about 10°C higher temperature than the building sidewalls and air. It can be clearly observed that the PSC system reduced the temperature of the pavement surface in the middle of the canyon (20% of the canyon). The temperature of the urban street canyon cross-section is shown in Figure 9 (b). Section 1 is the area above the pipe-embedded-pavement and section 2 is the area without the PSC system. The near-ground-air in section 2 had about 10°C higher than that of section 1, which means the PSC system could reduce air temperature. It also shows that the air near the building surface had a higher temperature than the air because of solar radiation. When the PSC cooled down the pavement temperature and air temperature, there would be less convective heat transfer between walls and air because of the smaller temperature differences. In this way, the building cooling energy demand would decrease. The detailed analytical results of the PSC’s temperatures and performance are presented in the following five sub-sections.

The most notable differences after adding the PSC system are the pavement surface temperature, and adjacent wall temperature of Building A. Figure 10 shows the pipe-embedded-pavement section’s temperature was about 28% lower than the areas without pipes. According to the figure, without the PSC system, the temperature of the unshaded pavement area was heated up to about 65°C, the maximum value can reach 71°C. With the PSC system, the temperature was about 47°C to 67°C. Although the temperature reduction was not significant in the shadowed area, the minimum pavement temperature dropped to about 28°C, which is even lower than the ambient air temperature (29.85°C). The pavement surface temperature was not uniform in the pipe-embedded area; it shows that the temperature distribution had the same pattern as the pipe locations and hence in further studies, we will attempt to improve the temperature distribution.

For the simulated period, four pipes were located in the shaded area or near Building B. Due to the shadowing effect, the pavement surface close to Building A had a higher temperature (60°C to 70°C) than the surface close to Building B (about 47°C). The building obstructed some solar radiation because Building B was located south of the pavement. The shadow effect prevented the pavement from being heated at a higher temperature; Figure 10 illustrated that the temperature difference between shaded and unshaded area was about 15°C. The central pavement area embedded with the cooling pipes had a much lower surface temperature in both shaded and unshaded areas; the cooling effect was more significant especially in the unshaded area, the temperature was reduced up to 20°C. The ambient air would have a lower temperature when it was close to the cool surfaces, improving the thermal environment for pedestrians in summer. As building energy demand is related to the ambient temperature, the cool pavement could reduce the cooling energy demand. Another advantage of cooling the surface is reducing the high-temperature damage to car tyres. It is stated by (DKT, 2020) that the higher temperature will increase the tyre pressure, which may cause the tyres to blow out. The tyre pressure drops by approximately 0.19 pounds per square inch (psi) for every decrease of 1°C. The result indicates that the PSC system can reduce the surface temperature, particularly the areas with very high temperature and exposed road surfaces. It also shows the importance of carrying out a detailed analysis which will help position the PSC system and maximise its performance.

3.4 Effect of the PSC system on building and air temperature

The previous section shows that when pipes were embedded under the road, the pavement surface temperature was much lower than that without the pipes. As the air temperature was always lower than the pavement surface temperature, the direction of convection heat transfer should always come from the pavement to the air. It can be indicated that there would be less heat transfer between air and pavement surface, because of smaller surface temperature difference. Therefore, low pavement surface temperature can decrease the surrounding air temperature and would be necessary to minimise the UHI effect.

Figure 11 shows the wall temperature contours of building surfaces, the wall section, which was close to the pipe area had much lower temperature than other sections. The wall surface of Building A shows clearly that the temperature reduction was significant in lower height areas. With the PSC system, the unshaded wall surface temperature ranged between 44°C to 48°C. At the pedestrian level, the wall surface temperature reduction was up to 10°C.

It can be observed that the PSC system had a more significant influence on the temperature of wall surfaces which were closer to the ground. From the figure of Building A, it shows the PSC system can reduce the near-ground-wall temperature about 10°C to 15°C. Figure 12 shows horizontal cross-section contours of the air temperatures at different heights (0.1 m, 0.5 m, 1.0 m, 1.5 m and 2.0 m). Without the PSC system, the overall air temperature decreased with the height increasing, which indicates that high-temperature pavement mainly affected the air temperature at a low height.

As observed in Figure 12, the air temperature near the ground surface (0.1 m) can be as high as 67°C and reduces with the height. The cooling effect provided by the PSC system was significant at the lower height areas; the air temperature can be cooled down up to about 30°C. The building wall surfaces had a higher temperature because of direct solar radiation and indirect radiation, so the walls emitted heat to the surrounding air and increased the air temperature up to 51°C. According to the temperature contours at five heights, it can be predicted that at the height of 2.0 m and above, the PSC system’s influence was minimal. For the spaces which were lower than 1.5 m, the air above the pipe-embedded-pavement section had a lower temperature than other areas; the temperature reduction was about 5°C to 10°C. Human average height is lower than 2.0 m so that the PSC system can provide a more comfortable thermal environment for pedestrians.

Six points were selected to investigate the relationship among the air temperature, location and height for the positions point a, b, c, d, e and f as shown in Figure 13 (a) and the air temperatures profiles from 0.0 m to 2.0 m height were plotted in Figure 13 (b). For this analysis, the case of the inlet water velocity of 0.25 m/s was chosen, and the pavement material was asphalt.

The six points were selected symmetrically, point a, c and e were close to the unshaded wall, and point b, d and f were close to the shaded wall. Compared to point a, c and e, point b, d and f had much lower air temperature, which was as same as discussed in section 4.1. At the height of 0.4 m, the temperature difference was 11°C, and at the height of 0.8 m, the temperature difference was 9°C, the air temperature difference between shaded and unshaded area.

Below the height of 0.88 m, the air temperatures at point c and d were much lower than those at point a, b, e and f. The gradients show that the temperature decreased much faster at point c and d than other points. The figure shows the cooling effect by the PSC system was notable at the low height spaces. In the unshaded area, with the PSC system, the air temperature can decrease up to 33.9°C at a height of 0.2 m. However, at this height without the PSC system, the air temperature was up to 57.5°C. Although below the 0.9 m height, air temperatures in the shaded area were lower than the unshaded area, they were even higher than that at point c, which is the unshaded area above pipe-embedded-pavement. Data collected from the six points confirmed that the PSC system significantly impacted the street canyon thermal environment and could reduce the air temperature near the pavement surface. It can cool down the air temperature at the pedestrian level effectively.

3.5 Effect of varying air temperature and solar radiation on pipe outlet water temperature/potential thermal energy collection

According to the above analysis, the pipes under shaded area dissipated less heat from the pavement than the pipes located in the unshaded area. The selected date for this work was 26^th June 2016 (Timeanddate.com). In this section, assuming that the initial inlet water temperature (19.85°C), inlet water velocity (0.25 m/s) and wind speed (2 m/s) were the same. Table 3 shows the ambient air temperature at different time of the day; the air temperatures are always higher than the circulating water temperature.

Building A is located in the north of the urban street canyon, and Building B is located in the south. The shadow area on the pavement changes with the sun position changing. The sun was in the north of the urban street canyon in the morning, as shown in Figure 14, the shadow is caused by Building A before 12 am. The figure clearly showed that in the unshaded area, the pavement temperature is related to the air temperature. When the ait temperature is higher, the pavement surface would have a higher temperature. It shows a significant difference between the pavement surface temperatures of 2 pm and 6 pm. Although the air temperatures were the same at 2 pm and 6 pm, the shaded area at 6 pm had much lower surface temperature than at 2 pm. Therefore, both air temperature and solar radiation patterns can influence the pavement surface temperature. The CFD results showed that at all selected times, the pipe-embedded areas have lower temperatures. The PSC system can provide cooling effect at all selected times, which means when there is no direct solar radiation coming to the surface, the cold water pipes could still reduce the pavement surface temperature.

The outlet water temperatures of the nine pipes are plotted in Figure 15, which are used to show the cooling effect provided by the PSC system. It showed that at noon the PSC system has a better cooling effect. The PSC system at 8 am and 6 pm showed low cooling effect than other times. There was no direct solar radiation to the pavement surface at 8 am, 4 pm and 6 pm, the asphalt surface cannot absorb a large amount of heat, the pavement was not heated up to a high temperature. Therefore, although the air temperature was high at 6 pm, the outlet water temperature can only increase by about 3.4°C in the late afternoon. In the morning, the air temperature was low, and there was no direct solar radiation, so the increment of outlet water temperature was also not significant.

When there was direct solar radiation coming to the pavement, the outlet water temperatures were much higher than the inlet temperatures. At 12 am, the water temperature average increment of the nine pipes was 7.02°C, while at 8am the average increment was 3.05°C. At 2 pm, the temperature maximum of increment was 7.8°C. For the pipes in the unshaded area, the inlet and outlet temperature differences are about 7°C, which means the circulating water temperature increased by 35%. The results showed that it is necessary to consider the PSC system operating time to obtain higher efficiency.