Radiative cooling improvement by retro-reflective materials

Radiative cooling improvement by retro-reflective materials

1. Introduction

Urbanization and climate change have contributed to rising temperatures in cities, significantly affecting energy consumption and human thermal comfort. One of the primary drivers of this issue is the Urban Heat Island (UHI) phenomenon, where urban areas experience significantly higher temperatures compared to their rural counterparts [[1], [2], [3]]. This temperature difference arises due to the prevalence of heat absorbing materials such as asphalt and concrete, high urban density, limited vegetation, and anthropogenic heat emission from vehicles, industries, and air conditioning (AC) systems [4,5]. Traditional urban materials, such as concrete, asphalt, and dark coloured roofing, have low solar reflectance and high thermal storage capacities, absorbing large amounts of solar radiation during the day and re-emitting it at night [6]. The reduction in vegetation further exacerbates this effect, as natural landscapes providing evaporative cooling and shading that are absent in urban settings [7]. Traditional AC systems, especially those using vapor compression, contribute to this problem by releasing latent waste heat into the environment [8]. In densely populated areas, UHI can increase local temperatures by 2–7 °C, exacerbating the need for cooling solutions that further contribute to energy demand and emissions [9]. The consequences of UHI phenomenon include increased energy demand for cooling in buildings, which currently accounts for nearly 30 % of global energy consumption [10,11], deteriorated outdoor and indoor thermal comfort, higher greenhouse gas emissions, and negative health effects, particularly for vulnerable populations [10,12].

To address these issues, a variety of strategies have been proposed, broadly categorized into passive [13] and active cooling methods [6]. Passive cooling, which relies on natural heat dissipation, is preferred for its cost-effectiveness and energy efficiency, making it ideal for widespread implementation [14]. Passive cooling techniques include cool coatings, shading, natural ventilation, insulation, double glazing, and green roofing [15]. Such technologies significantly reduce energy use and emissions within the building sector. Moreover, passive strategies, particularly radiative cooling, further alleviate UHI effects, resulting in even lower overall cooling demand [[16], [17], [18]]. Unlike conventional cooling methods, radiative cooling utilizes the atmospheric transparency window (8–13 µm) to allow heat to escape directly into the upper atmosphere, effectively reducing surface temperatures without consuming electricity [16]. According to Pirvaram et al. [19], adopting a radiative cooling system can lower electricity usage for cooling by 45–68 % compared to a conventional forced-air system.

Cool coatings, as a technology for passive radiative cooling, include those materials with specific optic and thermal properties, characterized by high reflection and high emissivity. There is a subgroup of cool materials which is characterized also by the capacity to reflect incident radiation directionally. Specifically, retro-reflective (RR) materials mostly reflect radiation backwards to the incoming direction. With respect to traditional diffusive materials, they are able to reduce the amount of reflected radiation onto adjacent surfaces, reducing local warming in dense urban environments [[20], [21], [22]]. A visual representation of conventional Diffusive and RR materials working mechanism is sketched in Fig. 1.

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Fig. 1. Paths of solar radiation due to conventional and RR skins in built environment.

As shown in Fig. 1, traditional diffusive coatings diffuse solar radiation in multiple directions, leading to reabsorption by nearby structures, thereby intensifying localized heating rather than reducing it [23,24]. This effect is particularly evident in dense urban areas where buildings are closely packed, forming urban canyons that trap heat [25]. Therefore, there is a pressing need for materials with directional reflectivity and emissivity that can control radiation more effectively and reduce inter-building heat exchange [26,27]. RR materials, originally developed for safety purposes, have undergone significant evolution over the years, transitioning from enhancing visibility in road signs and safety gears to improving the properties of building skins.

A proper design of an RR materials application introduces the following benefits for UHI mitigation: i) reduction of the interbuilding effect by reducing the energy trapped into the canyon; ii) reduction of the façades temperature and the outdoor air temperature; iii) reduction of the building energy demand for cooling.

In [20], the authors evaluated the albedo distribution at the canyon’s lid level and found that with RR paving there is an improvement of the radiation reflected out of the canyon (1–4 %) with respect to white and colored diffusive pavements. The same result was obtained in [25] with RR façade, which showed a higher percentage of the energy sent outside the canyon (maximum difference equal to 2.5 %). When RR materials are used in windows as in [28], they reflected 13 % more solar radiation into the sky compared to windows with heat-shading films. Yuan et al. [29] simulated the impact of different reflective building surfaces on the albedo of two-dimensional urban canyons and observed that albedo increases up to 10 % in summer and 33 % in winter when wall surfaces were coated with RR material with 81 % reflectivity, compared to diffuse and specular materials. Morini et al. [30] constructed two building group models—a block pattern and a canyon pattern—and found that RR materials increased the equivalent albedo by 3 % and 7 %, respectively, compared to conventional construction materials with similar solar reflectance.

As far as thermal evaluation is concerned, several studies show that the use of RR materials on building envelopes and urban pavements generally reduces the superficial temperature. For example, Inoue et al. [31] measured a reduction in the pavement temperature in the range from 1 °C to 8 °C when windows with RR films are applied to building façade. Qin et al. [32] constructed two small-scale building blocks using RR wall. The results showed that the outer surface temperatures of the RR wall were 5 °C to 10 °C lower than those of the diffuse wall during the daytime, while the temperature reduction was 1 °C at night. A thermal image in [33] show the same result comparing a diffusive wall with a RR wall (temperature difference equal to about 10 °C). This demonstrates that the RR wall can effectively keep the building blocks cooler than the diffuse-reflective wall under sunny conditions. The same paper [33] calculated the daily Glare probability during the day, taking into account the different incidence angles, for both walls and found that RR wall has a lower glare probability (−6% at 3.30 pm for middle latitudes).

Also, air temperature was reduced by RR materials thanks to the higher amount of solar radiation reflected outside the canyon, as described in detail in [34].

RR materials also lead to an annual cooling load reduction. For example Han et al. [34] modeled a bio-inspired RR envelope applied to a three-story building and found that it reduced total energy consumption by up to 8.2 % and cooling energy consumption by up to 9.8 % across various metropolitan areas in the United States. Mauri et al. [35] simulated cooling and heating energy consumption of a three-story building and similarly found that RR materials applied to the building façades reduced the yearly cooling demand of 15 % in Milan, 8 % in Rome and 7 % in Palermo, compared to diffusive materials with the same reflectivity. This is in line with the results in [36], consisting in more effectiveness of RR materials in mid to high latitude cities with cooling energy savings of 8–12 % in higher-latitude cities, varying by orientation and climate [36].

All the papers in literature analyzing the impact of RR materials refer to their behavior in the reflection of the incident radiation, mainly in the Vis range. To the best of our knowledge, previous research has not examined the RR materials in terms of directional emissivity and none has verified if the directional behaviour is maintained also in the thermal infrared range. Since emissivity is one of the parameters, together with reflectance, used in the calculation of the Cooling Power Potential (CPP) [37], there remains a critical knowledge gap regarding the CCP of RR coatings at varying orientations. To address this limitation, this work pioneers the application of directional emissivity analysis to RR materials, offering a robust framework for optimizing these coatings based on façade orientation and local environmental conditions.

This study examines the cooling performance of RR materials applied to vertical surfaces, addressing the following innovative aspects: i) evaluation of the directional emissivity RR materials under various surface temperatures and solar incidence angles; ii) quantification of the CCP of RR façades compared with conventional diffusive materials in urban environments.

2. Materials and methods

The materials and methodology used in this study are presented in this section. RR materials’ properties as well as solar reflectance and concentration n factor [25], may be designed by a proper combination of size and density of beads which confers RR properties to diffusive materials [38]. This paragraph provides a step-by-step explanation of the sample preparation process and the testing methodology, which includes spectrophotometric analysis, angular distribution of the reflected light, and angular emissivity measurements. Additionally, it details the instrumentation used, highlighting its key features and capabilities.

2.1. RR materials preparation

RR samples were prepared in a controlled laboratory environment. The base for each sample consisted of a circular steel plate with a surface area of 200 cm2. The steel plates were firstly coated with a highly reflective white diffusive paint (see Table 1), which is used as a substrate for hosting glass beads. Glass beads, made of hardened soda-lime glass, are widely used for cleaning, deburring, peening, and descaling due to their uniform composition and chemical stability. Their spherical shape ensures controlled surface finishes, while their durability minimizes equipment wear. Being chemically inert, they leave no residue on treated surfaces. In Table 2 the physical properties of glass beads are presented. Glass beads have been provided by Prochima® S.r.l. [39]. A reference diffusive (DIFF) sample was also created by applying the same highly reflective white diffusive paint to a steel plate, without the addition of glass beads. DIFF sample exhibits a diffusive reflectance which follows the Lambert’s cosine law, as shown in previous works [25,27,40,41]. In Table 1, the technical features of the highly reflective white paint [42] are presented. The white paint for building exterior applications has been supplied by INDEX Construction Systems and Products S.p.A. [42].

Table 1. Technical features of the highly reflective white paint.

Features Details
Model White Reflex Ultra
Solar reflectance (ASTM E-903) 0.86 [42]
Emissivity (ASTM C-1371) 0.91
Solar Reflectance Index (SRI) 110
Mass Density 1.35 ± 0.10 kg/L
Shelf-Life before and after opening 12 Months
Application Manual or Spray Technic
Water vapor permeability (EN7783) Sd < 5 m-class I
Adhesion Test (EN1542) ≥ 1.0 MPa
Water Absorption by capillary action (EN1062-3) w < 0.1 kg/m2·h0.5

Table 2. Physical properties of glass beads.

Features Details
Minimum hardness HRC 46 ± 48
Specific weight 2.45 ÷ 2.49 kg/dm3
Bulk Density ±1.6 g/cm3
Shape Spherical
Granulometry 40/70, 70/110, 100/200, 200/300, 400/800 μm
Colour Clear

The production of RR samples entailed manually dispersing glass beads over the freshly applied paint while it remained wet. Glass beads which are tiny spherical glass balls with a distinct refractive index compared to air, were evenly spread using a sieving technique to achieve a uniform distribution across the surface. After the paint had dried, any surplus beads that accumulated in overlapping layers and failed to adhere were systematically removed. The superficial density of the embedded glass beads was determined from the difference in glass beads weight measured before and after paint drying. Fig. 2 illustrates the main phases of the RR sample production process, which include:

  • 1.

    Application of the highly reflective white paint onto a steel plate;

  • 2.

    Manual deposition of glass beads over the wet paint using a sieving technique;

  • 3.

    Paint drying phase;

  • 4.

    Removal of excess glass beads after drying.

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Fig. 2. Stages of the manual RR sample production process: 1) Application of highly reflective white paint to a steel plate; 2) Manual deposition of glass beads onto the wet paint; 3) Drying of the painted surface; 4) Removal of excess glass beads after drying.

In previous studies conducted by the authors on RR materials, different substrates, glass bead diameters, and superficial densities were explored to understand their impact on RR optical properties [[43], [44], [45], [46]]. These studies provided a comprehensive understanding of how different parameters influence RR properties. Building on this research, five specific glass bead diameter ranges were chosen for this study: 40 ÷ 70 μm, 70 ÷ 110 μm, 100 ÷ 200 μm, 200 ÷ 300 μm, and 400 ÷ 800 μm. The selected glass beads diameter ranges are particularly relevant for assessing whether RR materials, in addition to their well-known angular distribution of the reflected light, also exhibit a directional emissivity. Understanding this relationship could provide new perspectives on the thermal-radiative properties of RR surfaces through the calculation of the CPP. The density of the glass beads varied based on the amount that adhered to each sample after removing the excess glass beads that did not integrate with the surface. As a result, the superficial density of the glass beads ranged from 0.10 to 0.20 g/cm2. In Table 3, the characteristics of the RR samples are shown.

Table 3. Characteristics of the RR samples.

Sample Glass beads’ size (μm) Glass beads’ density (g/cm2)
RR1 40 ÷ 70 0.17
RR2 70 ÷ 110 0.15
RR3 100 ÷ 200 0.11
RR4 200 ÷ 300 0.15
RR5 400 ÷ 800 0.10

Fig. 3 shows the stereo microscopic images of the five RR samples. As evidenced by these images, the distribution homogeneity of the glass beads improves as their diameter decreases.

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Fig. 3. Microscopic images of the investigated samples: a) RR sample with glass beads diameter range from 40 to 70 μm (RR1); b) RR sample with glass beads diameter range from 70 to 110 μm (RR2); c) RR sample with glass beads diameter range from 100 to 200 μm (RR3); d) RR sample with glass beads diameter range from 200 to 300 μm (RR4); e) RR sample with glass beads diameter range from 400 to 800 μm (RR5).

2.2. Methodology for RR samples characterization

To comprehensively characterize the RR samples, a combination of spectrophotometric analysis, angular distribution analysis of the reflected light, and directional emissivity measurements was conducted. The methodology ensures accurate and reliable data acquisition by detailing the instruments, calibration procedures, measurement conditions, and repetition trials to enhance reproducibility.

2.2.1. Spectrophotometric analysis

The spectral reflectance measurements were performed using a PerkinElmer UV/Vis/NIR Spectrophotometer LAMBDA™ 1050+, equipped with a 150 mm InGaAs integrating sphere [47,48]. The spectrophotometer was calibrated using a certified reflectance standard made of Spectralon™ from Labsphere [49], which also serves as the inner coating material of the integrating sphere. Compared to BaSO4 white reference, Spectralon™ provides higher reflectance accuracy over the entire wavelength range, particularly in the near-infrared spectrum [50]. Spectral reflectance measurements were conducted within the 300–2500 nm wavelength range, with a data interval of 5 nm. To ensure measurement accuracy and reduce potential errors, each sample was measured three times, and the mean value was calculated. The solar reflectance (R) values were directly computed by the spectrophotometer UV WinLab software using the ASTM E 892–87 “Terrestrial Solar Irradiance” method, which standardizes the spectral solar irradiance under air mass 1.5 conditions to assess the energy distribution across different wavelengths. The technical specifications of the PerkinElmer UV/Vis/NIR Spectrophotometer LAMBDA™ 1050 + are listed in Table 4 below. Measurements were carried out in laboratory at ambient temperature.

Table 4. Technical specifications of PerkinElmer UV/Vis/NIR Spectrophotometer LAMBDA™ 1050+ [51,52].

Feature Technical specifications
Light source Deuterium and Tungsten Halogen
Wavelenght operating range 175 ÷ 3300 nm
Integrating sphere 150 mm InGaAs
Wavelenght accuracy UV/Vis (656.1 nm): ±0,025 nm
NIR (1312.7 nm): ±0,200 nm

In Fig. 4, two pictures of the PerkinElmer LAMBDA™ 1050 + Spectrophotometer are shown: an outside view of the instrument, with details of the integrating sphere compartment, the sample holder and the software interface (Fig. 4a) and an inside view of the integrating sphere compartment (Fig. 4b), with the indication of the incident rays path.

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Fig. 4. PerkinElmer UV/Vis/NIR Spectrophotometer LAMBDA™ 1050+: a) outside view of the instrument; b) inside view of the integrating sphere compartment, with the main elements and the path of the incident rays.

2.2.2. Angular distribution of reflected light

To analyse the angular distribution of the reflected light, a custom gonio-reflectometer was developed at the Applied Physics Laboratories of the University of Perugia [47,48].

The system utilizes an Essenzialed® SpottOne lamp, incorporating SunLike® LED technology (Seoul Semiconductor Co., Ltd.) powered by Toshiba Materials Co., Ltd. [53,54]. This LED technology closely replicates natural sunlight in terms of both spectrum and color in the Vis range (see Fig. 5). The lamp specifications include: Color Rendering Index (CRI) = 97; Correlated Color Temperature (CCT) = 5000 K. A custom optical reducer was installed on the lamp, ensuring that the light beam is focused solely on the sample surface with minimal stray light affecting surrounding surfaces. Additionally, to eliminate unwanted reflections, the measurement surface was covered with a black, highly absorptive material in the Vis range. Fig. 6 illustrates the custom gonio-reflectometer setup, highlighting the LED lamp, the custom optical reducer, and the black, highly absorptive material used to control the measurement environment.

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Fig. 5. Spectrum of the LED lamp SpottOne by Essenzialed® with SunLike® TRI-R® technology by Seoul Semiconductor Co., Ltd. and Toshiba Materials Co., Ltd [54], for a CCT of 5000 K. []

Adapted from 55.

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Fig. 6. The custom experimental facility for angular distribution of the reflected light.

Measurements were conducted at ambient temperature under dark conditions. The angular distribution analysis was recorded using a Delta OHM HD2302.0 photo-radiometer, equipped with an LP471RAD irradiance probe. The instrument measures the irradiance in W/m2 for each angular position of the semi-circular array facility, by moving the probe along the arch i.e. with an interval of 10°. To ensure measurement consistency, two irradiance readings were taken at the light source position (one to the right and one to the left), and the average value was used for analysis. The technical specifications of the LP471RAD irradiance probe are provided in Table 5. The angular distribution measurements are conducted for incident light angles ranging from 0° to −60°, as these angles correspond to the most common solar elevation angles at mid latitudes. The duration of each test was determined based on the stability of the photo-radiometer readings at each measurement angle along the arc. Once the reading stabilized, the value was recorded.

Table 5. Technical specifications of the LP471RAD irradiance probe of Delta OHM HD2302.0 photo radiometer [56].

Feature Specifications
Description of the probe Radiometric probe for irradiance measurements with cosine correction diffuser
Spectral range of sensitivity 400 ÷ 1050 nm
Measurement range 1.0·10-3 ÷ 2000 W/m2
Calibration uncertainty <5%
Response according to the cosine law <6%
Linearity <1%
Instrument reading error ±1 digit
Fatigue <0.5 %
Drift after 1 year <1%
Working temperature 0 ÷ 50°C

2.2.3. Angular emissivity

Emissivity measurements were conducted in a thermal box set at 0 °C under dark conditions to minimize measurement errors and ensure a controlled and stable environment. Emissivity properties are represented in terms of RR/DIFF emissivity ratio (see paragraph 3.4) in order to simply compare RR materials with the DIFF reference sample.

The sample surface temperature was carefully controlled using a PID-regulated electric heater, which was monitored by a class 1 thermocouple. For each set temperature of 35 °C, 45 °C, and 55 °C, the thermocouple ensured precise temperature control, maintaining the sample within the target temperature range. To further enhance measurement accuracy:

  • 1.

    The PID controller continuously adjusted the heater power to maintain a stable surface temperature, with a maximum deviation of ± 0.05 °C after reaching steady-state conditions.

  • 2.

    This temperature variation is lower than the accuracy limit of the thermal camera, ensuring precise emissivity readings.

  • 3.

    The thermal camera readings were cross-checked with the thermocouple measurements to verify consistency.

To ensure reliable and repeatable results, the following measurement protocol was adopted:

  • Emissivity measurements are performed by a thermal camera [57] which can properly zoom the sample (technical details are reported in Table 6).

    Table 6. Data sheet of FLIR Systems B360 thermal camera [57].

    Specification Description
    Temperature Range −20 °C to 120 °C
    IR Image Resolution 76,800 pixels (320 × 240) Infrared resolution
    Thermal sensitivity <0.05 °C at 30 °C
    Spectral range 7.5 to 13 μm
    Lens Configuration 25°

  • For each sample, emissivity measurements were conducted at multiple angles, corresponding to the semi-circular structure’s graduated values (from 0° to 90° in 10° increments) (see Fig. 8 below). For each angle, the camera is properly repositioned by a mechanical graduated rail.

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    Fig. 8. Graphical representation of the custom angular emissivity experimental apparatus.

  • At each angle and for each surface temperature, emissivity measurements were performed three times, and the mean value was considered to reduce random errors.

  • The entire experimental campaign was repeated three times, further enhancing measurement reliability and ensuring reproducibility of the results.

  • The measurements duration was determined by how long it took for the emissivity value measured by the thermal camera to match the temperature reading from the thermocouple.

2.3. Parameters

In this paragraph, the parameters used in the paper are introduced.

Angular distribution of the reflected light is defined by Equation (1) [25] which may be derived from R values (see Table 7), concentration n factor (see Table 9) and incident radiation power:(1)The concentration factor n was already introduced in [25] and represents how the angular distribution of the reflected light is concentrated around the incidence direction. For a diffusive surface that follows the Lambert’s law, n is equal to 1, whereas for RR materials n is higher than 1, depending on the kind of RR material.

Table 7. Solar reflectance [%] of the tested samples in accordance with ASTM E 892–87 “Terrestrial Solar Irradiance” method.

Samples Solar reflectance [%]
DIFF 80
RR1 77
RR2 76
RR3 77
RR4 76
RR5 77

The RR/DIFF ratio (ρ) is introduced in Equation (2) to compare the emissivity of the RR sample with that of the DIFF sample:(2)Radiative cooling performances are characterized in terms of CPP which is defined as [37]:(3)In order to calculate CPP for RR materials, a proper modification of Eq. (3) is made by considering Eq. (1). In this way, an angular CPP is introduced as follows:(4)The measurement campaign (see paragraph 2.2) has characterized different RR materials in terms of both angular emissivity () and angular distribution of the reflected light; thus, Eq. (4) may be calculated for each direction and for different sample temperatures. In this way, a proper material may be selected for specific application conditions: incident light angle, surface temperature, inter-building effect.

3. Results and discussions

3.1. Solar reflectance (R)

In Table 7, the samples’ R values are reported. As confirmed by the literature [38,47,48], each RR sample exhibits overall lower reflectance with respect to the DIFF sample; this fact is primarily due to the incorporation of glass beads into the highly reflective paint, which diminishes its Vis reflectance [38,47,48]. However, in the NIR, the difference in spectral reflectance between RR and DIFF samples becomes lower. Among the RR samples, the greatest differences are observed in the NIR spectral region, with reflectance decreasing as the microsphere diameter increases. This fact is due to the interaction between wavelength and glass beads size, which affects surface roughness and potentially results in scattering effects in the IR region [58].

The DIFF sample showed the highest R value at 80 %. The embedding of glass microspheres in the highly reflective paint results in a decrease in R values. Among the RR samples, similar R values were found, ranging from 76 % to 77 %.

3.2. Angular distribution of the reflected light

For each sample, results are shown as angular distribution of the reflected light () defined as follows:(5)In Fig. 9, parameter is reported when incident source is at 0° (Fig. 9a), −30° (Fig. 9b), and − 60° (Fig. 9c). Specifically, in Fig. 9a the angular distribution of reflected energy is sketched on a polar representation. Each line corresponds to the directional reflectance of a specific sample which differs by colour. The top arrow represents the direction of incoming radiation (0°): let’s note that the reflected patterns come oriented towards incoming radiation. Such a property is called retro-reflectivity which is given by the glass beads mixed into the painting. The painting without glass beads produces a diffusive reflection ruled by Lambert’s law. Retro-reflective properties are ruled by Equation (1). In Fig. 9b and 9c, the reflected patterns are sketched for − 30° and − 60° incident direction: let’s note that the shape of the reflected patterns slightly changes as the angle of incident radiation varies.

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Fig. 9. parameter, i.e. angular distribution of the reflected light (see Eq. (5) for 0° (Fig. 9a), −30° (Fig. 9b) and − 60° (Fig. 9c).

RR4 exhibits the highest values for all investigated incident angles (see Table 8). The best performance of RR4 agrees with literature results [38,47,48].

Table 8. values of the investigated samples.

Empty Cell Empty Cell Direction of incident radiation [°]
Empty Cell Empty Cell 10° 20° 30° 40° 50° 60°
Angular distribution [%] DIFF 8.2 7.3 7.6 7.1 6.9 5.2 4.7
RR1 14.2 14.1 14.5 13.8 13.7 12.9 11.7
RR2 15.3 14.9 15.5 15.6 15.5 14.4 13.1
RR3 14.9 14.9 14.2 13.8 13.5 12.9 10.4
RR4 18.4 17.9 16.9 19.5 18.3 16.9 13.9
RR5 17.3 16.9 16.8 17.6 17.8 16.0 12.1

Table 9. Concentration factor n for each RR sample, calculated for an incidence angle of 0°.

Sample Concentration factor n
RR1 n = 14
RR2 n = 15
RR3 n = 15
RR4 n = 18
RR5 n = 17

In Table 8, values are numerically shown for each RR sample.

σ parameter depends only on declination angle and is symmetric with respect to the other angular coordinates which are consequently neglected.

In Fig. 10 (10a, 10b, 10c, 10d, 10e), the reflection patterns for 0° incident radiation of five samples are shown (Fig. 10a for sample RR1, Fig. 10b for sample RR2, Fig. 10c for sample RR3, Fig. 10d for sample RR4, Fig. 10e for sample RR5). In each figure, the angular distribution, represented by dotted lines, is also shown according to the theoretical model reported in [42], where n factor is introduced.

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Fig. 10. Comparison between the measured angular distribution and the theoretical distribution, for the RR samples: 10a) sample RR1; 10b) sample RR2; 10c) sample RR3; 10d) sample RR4; 10e) sample RR5.

In Table 9, the concentration factor n is shown for the RR samples.

3.3. Angular emissivity (εα)

By the procedure and instrumentation described in paragraphs 2.2 and 2.3, angular emissivity (εα) of each RR sample has been measured. In Fig. 11 (11a-RR1, 11b-RR2, 11c-RR3, 11d-RR4, 11e-RR5, 11f-DIFF), εα is shown for each RR sample and for the following surface temperatures: 55 °C, 45 °C and 35 °C. RR samples show higher emissivity than diffusive sample since for any condition. Specifically, for the 55 °C surface temperature (Fig. 11c), sample RR3 shows the best performance at all angles. For the 45 °C condition (Fig. 11e), sample RR5 performs the best, and for the 35 °C condition (Fig. 11d), sample RR4 exhibits the best performance across all angles.

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Fig. 11. Angular emissivity (εα) of RR and DIFF samples at 55°C, 45 °C, and 35 °C: a)RR1; b)RR2; c)RR3; d)RR4; e)RR5; f) DIFF.

εα parameter depends only on declination angle and is symmetric with respect to the other angular coordinates which are consequently neglected.

Fig. 11 shows that RR samples do not present angular variation in the emissivity. The value of emissivity for each sample varies with temperature.

Furthermore, despite R value for RR materials is lower than that for the same substrate diffusive ones, directional benefits may be achieved by RR materials. Emissivity and angular distribution can be optimized by adjusting the size and density of embedded beads which confer directional properties to materials. By that, the surface materials CPP may be improved. Such a property is particularly beneficial for vertical surfaces as well façades, where the angle of incident solar radiation is generally inclined. For a vertical surface (façade), it is here calculated the directional CPP (see Eq. (4) using proper RR material at different incident angles. The following hypotheses have been considered:

  • 1.

    Surface temperature is assumed 55 °C which is the typical temperature of urban façades during summertime [37,59];

  • 2.

    The average vertical surface solar irradiance has been set at 400 W/m2 which comes from the following Equation (6):

(6)

assuming, by a conservative approach,  = 800 W/m2 as the average horizontal solar irradiance for summertime on Cooling Dominant Zones (CDZs) [60];

  • 3.

    Ambient temperature is assumed 35 °C which is in thermal equilibrium with surrounding bodies not directly hit by the solar irradiance [59]

By considering Table 10, it may be argued that:

  • 1.

    Directional CPP produced by RR material is higher than DIFF one for each incident angle.

  • 2.

    Overall CPP (Eq. (3) which is the average CPP across all directions is also higher for RR material compared to DIFF one.

  • 3.

    CPP produced by RR applied on vertical surfaces is coherent with high performance cooling material used for flat surfaces (roof) [59].

This result corresponds to an important reduction of building energy demand and an important contribution to tackle UHI phenomenon. It is worth reiterating that the use of RR materials is particularly convenient since they may be properly designed for each specific application.

Finally, the increase of the cooling energy saving due to RR materials has been demonstrated and estimated by several papers [[61], [62], [63]]. A comparison between the reduction of absorbed solar radiation by RR materials versus conventional diffusive materials ranges between 2 to 100 W/m2 [64]. It deals to a reduction on energy consumption which depends on vertical surface area, on building orientation and on building thermal properties as well as heat transmission, thermal inertia and so on. However, an energy saving also produces a CO2 saving which depends on specific energy mix; for instance, in Italy, the equivalence between the CO2 and KWh is 0.33 kgCO2/KWh [65].

5. Conclusion

Based on the existing literature and the extensive experimental research conducted by the Authors—who have carried out multiple optical characterization campaigns on RR materials—this study builds upon previous findings that highlighted the directional properties of RR materials. Within this context, the aim of the present study was to determine whether RR materials with strong directional angular distribution of the reflected light properties also exhibit directional emissivity characteristics. To investigate this, five RR samples with different glass beads diameter were fabricated and systematically characterized in the laboratory. Their performance was assessed in terms of solar reflectance, angular distribution of reflected light, and angular emissivity. The key findings from this study can be summarized as follows:

  • 1.

    Emissivity of RR materials varies with surface temperature but does not show angular variations; the value is the same in all the emission angles.

  • 2.

    The size and density of embedded glass beads significantly influence the angular distribution of the reflected light and emissivity;

  • 3.

    RR materials significantly enhance CPP compared to conventional diffusive surfaces. At a typical façade temperature of 55 °C, RR materials increased CPP by an average of 20 %, demonstrating their superior cooling capability.

  • 4.

    The increased cooling energy saving due to RR materials contributes to lowering building energy demand, offering a practical solution for reducing urban overheating (UHI effect) in densely built environments.

Given that, the study directly addresses the research objectives outlined in the introduction:

  • 1.

    Demonstrating the viability of RR materials for façade cooling;

  • 2.

    Quantifying the cooling benefits of RR coatings;

  • 3.

    Establishing a groundwork for designing more effective RR materials optimized for radiative cooling applications.

Further research should focus on the long-term durability and environmental impact of RR materials to ensure their effectiveness over time. Additionally, integrating RR properties with spectrally selective coatings could further enhance cooling efficiency. It is also crucial to conduct regional and climate-specific validation by testing RR materials under different climate conditions, solar exposure patterns, and urban geometries to assess their adaptability and optimize their implementation. Lastly, a comprehensive economic analysis of production and implementation costs is essential to evaluate their feasibility for large-scale adoption. Thus, this study shows how RR materials can help cities stay cooler while reducing energy use, making them a valuable tool for urban planners, architects, and policymakers. To encourage their adoption, researchers, governments, and industry should work together to integrate them into building standards, provide incentives for large-scale use, and run real-world pilot projects to test their long-term benefits.

CRediT authorship contribution statement

Federico Rossi: Validation, Project administration, Funding acquisition, Conceptualization. Alessia Di Giuseppe: Writing – original draft, Visualization, Formal analysis, Data curation. Abdul Rehman Soomro: Writing – original draft, Data curation. Andrea Nicolini: Writing – review & editing, Validation, Supervision. Mirko Filipponi: Writing – review & editing, Resources. Beatrice Castellani: Writing – review & editing, Validation, Supervision, Methodology.

March 14, 2025 at 06:54PM
https://www.sciencedirect.com/science/article/pii/S0378778825003275?dgcid=rss_sd_all

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