Urban Climate 29 (2019) 100495

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Urban Climate

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Potential energy and climate benefts of super-cool materials as a rooftop strategy T ⁎ Amir Baniassadia, David J. Sailorb, , George A. Ban-Weissc a School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, United States of America b School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, United States of America c Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA, United States of America

ARTICLE INFO ABSTRACT

Keywords: For decades, refective rooftops have been used and advocated as cost-efective measures to Refective roofs mitigate the urban heat and reduce building cooling loads. However, their efectiveness has al- White roofs ways been limited by shortwave refectivity and long-wave of commercially available Urban heat mitigation technologies. Recent advances in coating materials with engineered spectral properties have Building energy consumption resulted in inexpensive “super-cool” technologies that can be applied to most surfaces and have fux and emissivity values greater than 0.96 and 0.97, respectively. This study is an efort to Passive daytime radiative cooling quantify the potential benefts of applying the newly developed materials on building rooftops. To do so, we conducted whole-building energy simulations of archetypical residential and commercial buildings to calculate rooftop surface temperature, sensible heat fux to the ambient, cooling energy saving, and heating energy penalty in 8 U.S. cities with urban heat mitigation plans that include use of high albedo materials. Our results suggest that in all climates, the surface temperature of the super-cool rooftop remains below the ambient air temperature throughout the year, resulting in a negative average daily sensible heat fux of 30–40 W.m−2. In addition, we found that the new technology can double the cooling energy saving (and heating energy penalty) compared to typical white roofs.

1. Introduction

Urban areas tend to experience higher ambient temperatures than their surroundings, a phenomenon commonly referred to as “Urban Heat Islands (UHI)” (Landsberg, 1981). Given the numerous negative impacts of urban heat, there is a large body of research on mitigation strategies that can reduce its negative impacts on energy and water demand (Touchaei and Akbari, 2015), air quality (Epstein et al., 2017), public health (Jandaghian and Akbari, 2018), and an overall reduction in quality of life for citizens. Refective surfaces (mostly applied on exterior surfaces of buildings) and urban vegetation are the two most studied methods of fghting urban heat. By reducing the absorbed solar radiation, the former has the potential to cool the near surface air (Morini et al., 2018). Because of their practicality, refective rooftops are the most studied (and applied) type of refective surfaces in the urban context (Aleksandrowicz et al., 2017), with a literature that dates back to early 90's (Rosenfeld et al., 1995). In addition, through building energy codes or other initiatives, many states around the world (especially, in mid-latitudes) already have established policies to promote (or mandate) the use of refective rooftops. For example, commercial buildings in many U.S. cities are required to implement white roofs (EPA, 2018).

⁎ Corresponding author. E-mail address: [email protected] (D.J. Sailor). https://doi.org/10.1016/j.uclim.2019.100495 Received 21 January 2019; Received in revised form 9 May 2019; Accepted 27 June 2019 2212-0955/ © 2019 Elsevier B.V. All rights reserved. A. Baniassadi, et al. Urban Climate 29 (2019) 100495

Studies on the efect of refective rooftops encompass a large range of scales. At the broadest level, Zhang et al. (2016) studied the potential impact of widespread cool roof implementation on continental and global scales and reported statistically signifcant (−0.0021 K) reductions in global mean temperature. At regional or metropolis-wide scales, examples include the work of Sailor (1995) and Vahmani et al. (2016) whose simulations suggest that wide adaptation of cool surfaces in the Los Angeles metro area can reduce daytime urban heat by 1 to 1.5 K in summer. Similarly, Li et al. (2014) showed that if 95% of rooftops in Washington- Baltimore area implement cool roofs, a 0.5 K reduction in near-surface UHI can be expected during a summertime heatwave. Based on a sensitivity analysis, Li and Norford (2016) report that in Singapore, city-wide deployment of cool roofs can reduce near-surface air temperature by up to 2 K. After reviewing the peer-reviewed literature, Santamouris (2014) concluded that the decrease in peak ambient temperature across all reliable studies is around 0.9 K per 0.1 increase in average surface albedo. At fner scales (e.g., neighborhood or a single street canyon), recent examples of studies include the work by Botham-Myint et al. (2015) who quantifed the variation of pedestrian-level efects of white roofs with respect to the arrangement and heights of buildings. Their computational fuid dynamics simulations showed that white roofs can potentially cause a near-surface air temperature reduction of 0.75 K. In another study, Taleghani et al. (2016) used micrometeorological simulations to show that, compared to cool pavements, cool roofs have a relatively low impact on thermal comfort of nearby pedestrians. In addition to the mentioned scales, there is another line of investigation that focuses on impacts at the building level. Specifcally, through measurements or whole-building energy simulations, researchers study the impacts of refective rooftops on the energy balance of buildings, and the consequent change in energy demand, thermal comfort, and heat fux into the ambient. For example, Baniassadi et al. (2018b) used EnergyPlus, a validated whole-building energy simulator, to study direct and indirect benefts of cool roofs for energy efciency and thermal comfort in residential buildings. Their work suggested that depending on the construction quality, the direct energy consumption beneft of shifting from a typical dark roof (albedo = 0.2) to a cool roof (albedo = 0.6) for a residential building in California could be up to 30%. Scherba et al. (2011) also used EnergyPlus in conjunction with a set of experimental measurements and reported that depending on the climate, a white roof can reduce total daily fux to the ambient by 75–80% compared to the baseline dark roof. While this summary covers few examples of a much larger body of work, the magnitude of benefts (regardless of the reported metric) in all previous studies is limited by the properties of commercially available products (Mastrapostoli et al., 2016). However, recent developments in Passive Daytime Radiative Cooling (PDRC) technology show the potential of a substantially diferent type of cool-roofs (Santamouris and Feng, 2018). The very recent development of an inexpensive and practical method for producing hierarchically porous poly (vinylidene fuoride-co-hexafuoropropene) coatings is one promising example. In particular, the work by Mandal et al. (2018) resulted in a coating with a substrate-independent albedo of 0.96 and emissivity of 0.97. Notably, they observed a surface temperature drop of up to 6 K below ambient air temperatures under solar intensity of 890 W/m2. This was only achievable through the extremely high albedo combined with the very high emissivity inside the atmospheric window that allow for surface cooling even in the afternoon hours. More importantly, while Mandal et al. did not scope the benefts of this coating as a rooftop strategy, they reported that the coating can be easily applied to any substrate (including rooftops). While this is the most recent and promising example, other research groups (Bhatia et al., 2018; Gentle and Smith, 2010; Gentle and Smith, 2015; Raman et al., 2014; Zhai et al., 2017) have also been working on this topic over the past few years, and achieved similar properies. Although, most are substrate-dependent and expensive solutions. There are several studies on applications of PDRC as a “free” source of cooling in buildings. Most of these studies consider the use of these materials in rooftop heat exchangers integrated within hydronic cooling and heating loops (Goldstein et al., 2017; Wang et al., 2018). For example, Fernandez et al. (2015) simulated this hybrid system (based on the coating proposed by (Raman et al., 2014)) in an ofce building in 5 US cities and reported 45–68% savings in cooling electricity demand. If this technology shows the same sub-ambient temperature performance on rooftops, it can result in a major paradigm shift in how refective rooftops interact with urban environments and individual buildings. While commonly referred to as “cool-roofs”, in reality, typical refective rooftops only reduce the daytime heat fux to the ambient (and into buildings) as opposed to actually cooling them. Hence, while they mitigate urban heat and reduce building cooling demand in comparison to dark roofs, they do not result in an actual cooling efect. In contrast, if the extremely high albedo and emissivity of the mentioned technology results in consistent sub-ambient surface temperatures, it can be considered as an actual urban cooling strategy. In addition, instead of simply reducing building heat gains, super cool roofs can passively cool the building interiors and thus, reduce the demand for mechanical cooling. To study these potential benefts, we used simulations at the building level to scope the benefts of the newly developed coating as a potential rooftop strategy (henceforth, super cool roofs). Through whole-building energy simulations, we compared roof surface temperatures and heat fuxes from super cool roofs in residential and commercial building archetypes to those of typical white (albedo of 0.7 and emissivity of 0.9) and dark (albedo of 0.2 and emissivity of 0.9) roofs. In addition, we calculated energy benefts for summertime cooling and the associated penalty in heating energy demand during winter. Then, we calculated net avoided CO2 emissions and net reduction in energy expenditures as two metrics that include both the cooling benefts and heating penalties. We conducted this analysis for eight U.S. cities with distinct climate characterisitcs, all of which already have policies aiming to promote the use of white roofs.

2. Methodology

To compare the three rooftop strategies, we ran a series of parametric runs in which we changed the roof properties (albedo and emissivity) of archetypical residential and commercial buildings in each location. The baseline building and the one with a “typical white roof” had a rooftop emissivity of 0.9 with of 0.2 and 0.7, respectively. For the “super cool roof” scenario, we increased rooftop albedo and emissivity to those reported by Mandal et al. (2018). The performance of all refective roofs deteriorates over time

2 A. Baniassadi, et al. Urban Climate 29 (2019) 100495 because of weathering (Mastrapostoli et al., 2016). Mandal et al. (2018) tested their technology through accelerated thermal and wet aging tests as well as a month-long exposure test under sky in New York, NY and observed no deterioration in its properties. However, currently, there is no long-term data on weatherization rate of passive daytime radiative technologies (Santamouris and Feng, 2018). Therefore, to control for this efect, we assumed new roof properties in all runs. This refects the performance during the frst few years, or for rooftops that are regularly maintained. This approach is the only option until further information is available for degradation rate of super cool roof properties.

2.1. Whole-building energy model (EnergyPlus)

EnergyPlus, a state of the art and widely used whole-building energy model in the building science literature, dynamically solves the mass and energy balance of all spaces in a building in response to outdoor conditions, internal loads, and occupant behavior. To do so, it represents phenomena on exterior surfaces with a high accuracy. EnergyPlus' global heat balance algorithm has been validated in compliance to ASHRAE/ANSI standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs (Witte et al., 2001). In addition, numerous studies in the building science literature have validated EnergyPlus's performance for special purposes. In particular, Scherba et al. (2011) showed that EnergyPlus can accurately replicate roof surface temperature of white roofs. In contrast to some of the older whole-building energy simulators, EnergyPlus directly outputs surface temperatures and heat fuxes. Therefore, similar to previously published research on refective rooftops (Gentle et al., 2011; Virk et al., 2014; Zinzi and Agnoli, 2012), we used EnergyPlus to simulate the impact of diferent technologies on roof energy balance and the associated changes in heating and cooling energy demands.

2.2. Archetype buildings

As a common strategy in the building science literature (Baniassadi et al., 2018a; Caputo et al., 2013; Swan and Ugursal, 2009), instead of modelling an individual building with specifc properties, we modelled archetypes with design and properties that re- present typical buildings in each city's building stock. For residential archetypes, we selected single-family residential buildings as well as the top foor units in multi-family apartments based on the data in (EIA, 2015). We did not consider lower foors of the multi- family unit because the impacts of rooftop on their energy demand is negligible. Fig. 1a shows the modelled single-family residential building which had a living area of 140 m2. The size was selected based on U.S. DOE data that suggests the majority of U.S. residential buildings are in the 100–180 m2 range. The model was set up following the procedures set by the Building America House Simulation Protocols (Hendron and Engebrecht, 2010) which is a standard fra- mework for energy modelling of residential buildings in the U.S. This included all assumptions regarding occupancy and internal load

Fig. 1. Modelled Building Archetypes of (a) Single Family Residential Building (b) Multi-family residential building (c) Stand-Alone Retail Store. Scales are not consistent across sub-fgures.

3 A. Baniassadi, et al. Urban Climate 29 (2019) 100495 schedules, window operation, and ventilation rates. For specifc climate-dependent envelope properties that are regulated by building energy codes (e.g., wall and roof insulation levels, glazing properties, airtightness), we used the 2003 International Energy Con- servation Code (IECC 2003). Since there are potential non-technical limitations (glare issues) to implementing refective coatings with albedos of 0.96 on top of sloped roofs, our archetype had a fat roof, despite the fact that around 46% of detached homes in U.S. have unfnished attics (EIA, 2015). Model buildings in all locations had the same type of cooling system, a direct expansion central air conditioning unit, which is the most common type of cooling system in the U.S. residential building stock (EIA, 2015). The heating system type was a natural gas furnace in all climates except Phoenix and Miami. In these two southern cities, we used electric heating which is far more common than natural gas heating. For the apartment building (Fig. 1b), we used the prototypes developed by Building Technology Ofce of U.S. Department of Energy. We downloaded the “multi-family mid-rise” model compliant to IECC 2006 and had to manually change the insulation properties to IECC2003 because it was not readily available to download. The energy benefts reported in this paper are the average of the top foor units (there was a small variation among units because of their orientation). In the model each unit had its own heating and cooling system (with efciencies set by 2003 code). Based on survey data in (EIA, 2015), the cooling and heating thermostat setpoints in both residential archetypes were 23 and 20 °C, respectively. In addition, per (Hendron and Engebrecht, 2010), these buildings did not include a natural ventilation strategy. Since commercial buildings have envelope properties and operation schemes that are distinctly diferent from residential units, we also modelled an archetypical mid-size single-story retail store, which is one of the most common non-residential building types in U.S. cities (EIA, 2012). The EnergyPlus input fle for this archetype was directly obtained from Commercial Prototype Building Models set provided by the Building Technology Ofce of U.S. Department of Energy. From this set, we downloaded the “stand-alone retail” model (Fig. 1c) compliant to ASHRAE standard 90.12004 which is climate-specifc. The only modifcation we made was changing the rooftop albedo for diferent cases. The cooling and heating thermostat setpoints of the main space in this archetype were 23 and 20 °C during working hours, and 30 and 15 °C during holidays and night hours. Since there is a considerable lag in code implementation in all states and counties in the U.S. (BECP, 2017), our selection (ASHRAE 90.12004 and IECC 2003) is representative of an average building constructed in the 21st century. Fig. 1 shows the outline of the three modelled archetypes. An important assumption is that no exterior object is shading the roof of model buildings.

2.3. Spectral emissivity considerations

While common refective materials have an almost uniform emissivity in the entire long wave spectrum, most super-cool ma- terials present a spectral variation in emissivity. On the other hand, the current version of EnergyPlus does not allow for inputting wavelength-dependent emissivity (although, the software developers have stated that this feature might be added in future releases). This can cause errors in calculation of roof surface temperature and sensible heat fux. To assess the error caused by this limitation, frst, we digitized the refectance data of the sample from the graphs presented in (Mandal et al., 2018). Our rendering of the spectral refectance of the material is shown in Fig. 2 (the solid black bar). In addition, we plotted a constant refectance of 0.03 (emissivity of 0.97) that is the reported averaged emissivity inside the atmospheric window by Mandal et al. (2018), and our input to EnergyPlus (the solid red line). It should be noted that in EnergyPlus, emissivity applies to wavelengths higher than 2.5 μm, which is a valid assumption considering the temperature range of building surfaces. As the data shows, the constant emissivity assumption is

Fig. 2. The potential errors from assuming a constant emissivity value.

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Table 1 Climate information for selected U.S. cities.

City Name Dry-Bulb Temperature (°C) Lat. (°N) Long. (°W) ASHRAE Climate Zone Airport Code

Avg. Max. Min.

Albuquerque 13.7 38.7 −8.4 35.1 106.7 4B (Mixed-Dry) ABQ Atlanta 16.7 36.7 −12.6 33.7 84.4 3A (Warm-Humid) ATL Chicago 10.0 34.8 −22.6 41.9 87.6 5A (Cool-Humid) ORD Houston 20.4 39.4 −6.1 29.8 95.4 2A (Hot-Humid) IAH Lost Angeles 17.5 38.9 1.7 34.1 118.2 3B (Mixed-Dry) CZ9a Miami 24.5 35.4 5.2 25.8 80.2 1A (Very Hot-Humid MIA Philadelphia 12.7 36.5 −13.9 40.0 75.2 4A (Mixed-Humid) PHL Phoenix 23.8 44.4 2.4 33.4 112.1 2B (Hot-Dry) PHX

a California Climate Zone 9 as defned by California Energy Commission. We did not select LAX since it was not a good representative of inland locations.

Table 2 Emission factors and unit price of energy for each location. Data from Energy Information Administration (https://www.eia.gov) for the year 2017.

City Emission factor Unit Price

Electricity (kg CO2/kWh) Natural Gas (kg CO2/MJ) Electricity ($/kWh) Natural Gas ($/MJ)

Commercial Residential Commercial Residential

Albuquerque 0.703 0.050 (National Average) 0.103 0.131 0.006 0.009 Atlanta 0.450 0.097 0.121 0.008 0.016 Chicago 0.385 0.089 0.122 0.007 0.008 Houston 0.520 0.079 0.116 0.007 0.013 Los Angeles 0.238 0.176 0.194 0.008 0.012 Miami 0.462 0.089 0.113 0.010 0.020 Philadelphia 0.395 0.087 0.138 0.009 0.011 Phoenix 0.409 0.110 0.129 0.008 0.015 reasonable for the super cool roof material at wavelengths higher than 7 μm, which includes the atmospheric window. This shows another important characteristic of the newly developed material by Mandal et al. (2018), which in contrast to previous materials, has a signifcantly consistent emissivity over a large range. This was not the case for previously developed materials such as the ones proposed by (Bhatia et al., 2018) and (Raman et al., 2014). Nevertheless, between 2.5 and 7 μm, there is a considerable diference between the actual emissivity of the sample and our input to EnergyPlus. However, according to the Planck distribution, only a small portion of radiative power of the roof is associated with this wavelength range. The two surfaces in Fig. 2 show this concept. The grey curve is the spectral radiation of the sample that we calculated by applying the wavelength-dependent emissivity to the Planck distribution. The red curve shows the spectral radiation of the sample that we calculated using a constant emissivity of 0.97. Both curves were obtained at a surface temperature of 290 K based on the distribution of temperatures we obtained from the running the models (see the result section). Although, the same principles apply to any surface temperature within a realistic range. As can be seen in the fgure, the two curves are almost identical across most of the spectrum except for 2.5–7 μm range. By calculating the area underneath these curves, we calculated the diference in total long-wave radiative output from the surface across the entire wave- length range for which the sample refectivity was reported by Mandal et al. (2.5–20 μm). The diference between the two areas was around 3.6%. We tested the sensitivity of our results to this issue found out that while this can result in a 2% error in sensible heat fuxes (Fig. 4 in the result section), the impacts on building energy demand, CO2 emission, and electricity costs are negligible. Therefore, for this particular material, the limitation in EnergyPlus does not have considerable impact on the main fndings of this study. Nevertheless, we acknowledge the importance and necessity of adding spectral emissivity in whole-building energy models to account for dynamic variations in atmospheric conditions and surface temperature (and the associated shift in Planck distribution), especially considering the need for modelling emerging technologies such as super cool roofs.

2.4. Selected locations and weather data

We selected eight cities (listed in Table 1) that are located in diferent ASHRAE climate zones to include a variety of underlying climates and the associated building envelope characteristics. In addition, using U.S. Environmental Protection Agency's Heat Island Community Actions Database, we confrmed that all selected locations have some type of local government programs or policy for promoting the implementation of refective rooftops. To force EnergyPlus simulations, 15 weather variables including dry-bulb temperature and direct horizonal radiation are required at hourly resolution. In the building science literature, the Typical Meteorological Year (TMY) is often used to run whole-building energy simulations. These data are generated using 15–30 years of recorded meteorological variables and represents a typical year. In

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Fig. 3. Roof-ambient temperature diference for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail. this study, we used the latest version of this data set (TMY3) generated by the U.S. Department of Energy (https://energyplus.net/ weather). While TMY3 is representative of typical conditions in each city, two main limitations of this approach are the exclusion of historic extremes and spatial variations within a city. Nevertheless, the commonly used TMY3 is the most reliable source of weather data to run whole-building simulations for purposes similar to our study. Table 1 lists the eight cities, their latitude and longitude, average dry-bulb temperature (from TMY3), ASHRAE climate zone, and airport code of the weather station.

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Fig. 4. Average daily heat fux for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail.

2.5. Emission and cost factors

It is well documented that refective roofs result in a heating energy penalty during the winter (Synnefa et al., 2007). Since in our archetypes, heating and cooling are provided from diferent energy sources (natural gas vs electricity), we calculated two metrics, net energy cost saving ($/year) and net avoided CO2 emission (kg CO2/year), to assess benefts of rooftop modifcations. In addition, this enabled us to capture diferences in fuel mix and energy cost in diferent locations. These two metrics cover the two main motives behind most building retroft eforts—environmental (buildings are responsible for 39% of global CO2 emissions (Masanet, 2017)), or economic. Table 2 lists the emission factors and per-unit energy cost that were obtained from publicly available datasets provided by Energy Information Agency (EIA) of U.S. DOE (https://www.eia.gov). All values in this table are annual averages for the year 2017. We used these factors to convert cooling and heating energy impacts to net avoided CO2 and costs. We also calculated a third metric—the source energy consumption. However, in all our selected locations, this metric was highly correlated with CO2 emission, and so, is not reported separately.

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Fig. 5. Hourly profle of sensible heat fux from the roof on June 21 and December 21 for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail. The shaded area includes all climates.

3. Results and discussions

After all building models were set up in EnergyPlus, we created a Matlab script to run simulations of baseline (dark roof), typical white roof, and super cool roof cases for both archetypes in all eight locations (a total of 48 simulations) and post-process the output. All simulations were run annually with a 15-minute time step.

3.1. Roof surface temperature

Fig. 3 is a histogram of hourly temperature diference between the rooftop surface and the ambient for the entire simulation year (averaged across climates). In addition, we have included separate graphs for each city in the supplemental materials (Fig. S1). These data confrm that super cool roofs could represent a paradigm shift in urban cooling technologies. Despite minor diferences between the two building types and the variability across diferent climates (see Fig. S1), the super cool roof remains below the ambient air temperature for more than 99% of the times, which is signifcantly higher than typical white roofs (60%) and the baseline roof (55%) that only remain below the ambient temperature at night and early morning hours. While the typical white roof mitigates

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Fig. 6. Cooling energy benefts for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail. urban heat in comparison to a dark roof (by reducing the duration and intensity of ambient warming), they are still generally warming the ambient air during the day. On the other hand, the super cool roof temperature remains below the ambient air tem- perature even during the day, meaning that it is almost always cooling the near-surface air.

3.2. Sensible heat fux

To analyze the impacts on sensible heat fuxes, we plotted average daily sensible heat fuxes for all cases in Fig. 4. In these graphs, a positive heat fux corresponds to heat transfer from the rooftop to the ambient. Henceforth, SF and MF in fgure legends refer to single-family and multi-family archetypes. The baseline heat fux and the mitigating impact of the typical white roof presented here are generally in-line with previous studies such as that of Scherba et al. (2011). Compared to the dark roof, the white roof has a considerably smaller heat fux to the ambient. However, the super cool roof has a negative heat fux with the same order of magnitude as the positive heat fux of the baseline dark roof. Notably, this is consistent across diferent climates and archetypes. This considerable cooling potential can play a signifcant role in urban cooling. As an example, in Phoenix, two buildings with a super cool roof can provide enough ambient cooling to compensate for one dark roof (or four white roofs) of the same size. This trend is consistent between the three archetypes (residential and commercial).

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Fig. 7. Heating energy penalty for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail. Residential building archetypes in Miami and Phoenix are excluded because they had a diferent heating system type (electric instead of natural gas).

To understand the diurnal pattern of this cooling, in Fig. 5, we plotted an example of hourly heat fux profle at summer and winter solstices. As this data suggests, the sensible heat fux of the super cool roof shows little diurnal variability compared to the other two options. Hence, the potential cooling beneft from this technology is consistent throughout the day. In addition, unlike the dark and white roof, the super cool roof does not show considerable seasonal variation.

3.3. Impacts on building energy demand

Figs. 6 and 7 show the cooling energy beneft and heating energy penalty of super cool roofs and typical white roofs. To make the cooling and heating energy demands (that are from diferent sources) comparable, we calculated annual CO2 emissions and energy costs as two metrics that include both the cooling benefts and heating penalties. Fig. 8 shows the net avoided

CO2 emssion of the modelled residential and commercial archetypes. This data highlights the importance of underlying climates and fuel mix on net benefts of refective technologies. In the shell-dominated residential building archetype, avoided CO2 is higher in three hot southern locations with hot climates (Phoenix, Houston, and Miami). Milder summers, colder winters (e.g., Chicago and Philadelphia), and clean electricity fuel mixes (e.g., Los Angeles) cause buildings in other locations to show negligible decrease, or even an increase in annual CO2 emission. Moreover, in relative (percentage) terms,benefts are larger in the top foors of multi-family

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Fig. 8. Net avoided emission of refective rooftops for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail. buildings. This was expected because their foor is essentially adiabatic, making the heat transfer from the roof more important in the zone energy balance. In commercial buildings (that have signifcant internal sources of heat and a larger roof surface to building volume ratio) the net impacts are generally positive and relatively larger than residential buildings. Considering the diferences between the super cool roof and the typical white roof, our simulations suggest that the efect of the super cool roof on CO2 emission is around twice that of the typical white roof. Remarkably, this is consistent across all climates and building types. Fig. 9 shows the net saving for the super cool roof and typical white roof across all climates. Based on the data presented here, impacts of refective rooftops on CO2 emissions and their economic benefts are inherently diferent as there is almost no case of negative impact on energy expenditure. An extreme example of this diference is the residential building archetype in Los Angeles, CA. This is due to the lower emissions associated with electricity generation and its higher costs in California (Table 2) and highlights the impacts of fuel mix and cost on relative benefts of refective rooftops. Considering the net energy expenditure savings alone, the super cool roof almost doubles the savings (and penalties) across all locations and archetypes. In locations with warm summers and/or high electricity prices, this provides a signifcant incentive to encourage building owners to implement super cool roofs.

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Fig. 9. Net saving in HVAC energy expenditure of refective rooftops for (a) single-family residential building (b) multi-family residential building (c) stand-alone retail.

3.4. The role of ceiling insulation

Based on the previous studies (Baniassadi et al., 2018b; Synnefa et al., 2007), ceiling insulation level is the main determinant of the efectiveness of refective rooftops on building energy use. In general, the more insulated the ceiling, the more thermally isolated indoor and outdoor environments, and the smaller the impacts of refective rooftops on building energy use. This isolation can potentially enhance the impact of roof albedo on outside surface temperature of the roof and the associated heat fux because it decouples the temperature of the outside surface from that of indoor air. To identify the impact of roof insulation on the efectiveness of super cool roofs, we ran a separate set of simulations, in which the rooftop insulation was changed to that required by the newest versions of IECC. To isolate the impacts from insulation, we kept other building properties constant. Fig. 10 shows the result for all building types. The vertical axis of this fgure is “insulation impact ratio” for each variable (v) - CO2 emission, energy costs, and average daily sensible heat fux - and is defned as follows:

change in V from applying super cool roofs withnew code insulation (%) Insulation impact ratio (v) = change in V from applying super cool roofs withold code insulation (%)

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Fig. 10. The impact of insulation on the efectiveness of super cool roofs in (a) single-family residential building (b) multi-family residential building (c) stand-alone retail. See the above defnition for the vertical axis. Chicago and Philadelphia are excluded from this fgure.

The closer the impact ratio of a variable to a 100%, the more similar the efectiveness between the two insulation levels. This means that performance metrics are not sensitive to insulation levels and can be generalized to future building stock that is going to have higher levels of roof insulation. As the data suggest, across all building types and climates, impact ratio is close to 100% for mean daily sensible heat fux. Hence, the fndings regarding the impacts of super cool roof on outside roof surface temperature and sensible heat fux to the ambient air can be generalized to newer buildings with higher levels of insulation. On the other hand, insulation impact ratio is signifcantly lower for energy benefts, suggesting that newer building codes can reduce the benefts of super cool roof (and in general, any roofng technology that is based on controlling the roof surface temperature). However, it is important to note that the building stock changes slowly. It usually takes a few years for jurisdictions and states to implement the newest version of each code. Therefore, realistically, the new code insulation level used here will not be mandated by early to mid- 2020's. Hence, in near to mid future, super cool roof can be a highly efective measure to reduce cooling energy demand in new buildings. In addition, since energy codes only apply to new constructions, a large portion of the building stock can beneft from super cool roofs as an energy retroft strategy.

4. Limitations and areas for future research

Several factors limited the scope of this study. Future research should expand upon this paper by addressing these limitations.

13 A. Baniassadi, et al. Urban Climate 29 (2019) 100495

First, the lack of spectral emissivity input in EnergyPlus needs to be addressed. Considering the recent interest in developing materials with selective properties, researchers and engineers need robust simulation tools to assess their performance under diferent climates and scenarios. Therefore, including the ability to model spectral variations in emissivity is a necessary next step. Second, while the newly proposed material shows a great potential, its feasibility as a competitive rooftop strategy can only be verifed after an economic analysis. This paper lacks such analysis due to unavailability of reliable cost estimates. Therefore, it is important to assess the required raw material and manufacturing process of producing super cool roof coatings at commercial scale to arrive at a reliable cost estimate. Third, deposition of dust, black carbon and other atmospheric constituents can alter the properties of the coating and thus; reduce its efectiveness. We could not account for these efects due to the lack of data. Therefore, a series of pilot tests are needed to gather data on long-term performance of these materials on actual rooftops. Fourth, while the sensible heat fux data presented clearly shows that super cool roofs have a high potential for urban heat mitigation, the actual end-impacts on ambient temperature can only be derived from micro or meso-scale climate simulations (that were outside the scope of this study). Therefore, we suggest that future studies expand upon this work by conducting climate simulations to investigate the heat mitigation impacts of large-scale deployment of super cool roofs in a city or neighborhood. Finally, it should be noted that increasing albedo and selective emissivity of rooftops is not the only rooftop strategy that has market potential. In specifc, there continues to be a growing interest in rooftop PV, that has a complex dynamic with the underlying roof. While it provides shade (and thus, renders the albedo of the roof irrelevant), it blocks the longwave radiation exchange with the sky. Moreover, by doubling the heat transfer surface, it increases the sensible heat fux to the ambient. On the other hand, it produces a considerable amount of energy at the point of consumption. Studies in the literature (with the exception of (Scherba et al., 2011)) often consider these two options exclusively. This should be addressed in future studies by integrating detailed building analysis with climate models and assessing these rooftop strategies side by side.

5. Conclusions

In this study, we used whole-building energy simulations to scope the benefts of a newly developed “super-cool” coating material with signifcantly improved properties as an alternative to conventional white roofs. Our simulations show that the super cool roof has the potential of a signifcant paradigm shift in fghting urban heat because it remains below ambient temperature at almost all times and provides a considerable cooling beneft. Therefore, it can be applied to virtually “cool” the urban climates as opposed to typical white roofs that simply reduce the positive heat fux to the ambient. Our calculations of net CO2 emissions show that this technology can almost double the benefts of conventional white roofs and is most suitable for environments with warm summers, moderate winters, and/or a CO2 intensive electricity fuel mix. Based on results from our simulations, compared to expensive deep- retroft options, super cool roofs can feasibly become a cost-efective strategy to reduce overall emissions under the mentioned scenarios. With respect to the net economic benefts, the super cool roof showed twice the cost saving potential of a conventional white roof. It reduced overall energy expenditure by 4–19% in commercial buildings and up to 28% in residential buildings, which can be an investment incentive for building owners. These benefts were most signifcant in locations with warm summers, moderate winters, and high electricity costs.

Acknowledgment

This research was supported in part by the National Science Foundation (NSF), US under grants 1512429 and 1623948. Co-author GB-W also received support from NSF grant 1752522. Any opinions, fndings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily refect the views of the National Science Foundation. Additional funding and support were provided by Urban Climate Research Center of Arizona State University.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.uclim.2019.100495.

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