Haider Taha

Many airports now consider implementing urban-cooling measures as proven strategies to reduce energy use and improve environmental conditions. Studies have also shown that reflective surfaces on roofs and grounds can have beneficial effects on thermal environment and airport workers’ productivity. To date, no studies have been undertaken to specifically assess whether any effects on aircraft performance would also result from implementing these measures. In this exploratory study, high-resolution micrometeorological modeling and remote-sensing analysis were undertaken to quantify the potential reductions in fuel use and, thus, emissions from aircraft taxiing on cooler surfaces. The results suggest small but non-zero benefits in terms of emissions and takeoff-roll distances. Using the Dallas–Ft. Worth International Airport (DFW) as a case study and Boeing 737 aircraft type as an example, it is found that if taxiways and shoulders albedo is increased to 0.35, an average of 2.3 kg CO₂ can be saved per single taxi-out or taxi-in operation around midday and about 1.5 kg CO₂ earlier in the morning or later in the evening. It is also found that even though runways albedo remains unchanged, cooler air advected over runways from modified taxiways can reduce the takeoff-roll distance by an average of 3% around midday that tapers off to an average of 1% early in the morning or late evening. Indeed, these are small effects per single taxi-in or taxi-out operation but when scaled by some 2000 arrivals and departures per day at DFW, saving 4000–5000 kg CO₂ per day, and if further scaled by the number of eligible airports, the impacts become significant. Furthermore, the effects reported here are from taxiway and shoulder modifications alone; if combined with the effects from cool roofs and other cool ground surfaces at terminals, tarmacs, ramps, and parking areas, the benefits will add up significantly. Limitations in this study, that would be addressed in future work, include simplifying assumptions regarding aircraft-engine performance, specifications, and aircraft types mix and operations.

Heat exposure in outdoor work environments poses risks to worker health and productivity. Engineering solutions like cool surfaces that increase surface albedo and reduce temperatures may help mitigate these impacts. We conducted detailed micrometeorological modeling to analyze surface characteristics and heat exposure for outdoor workers at San Francisco International Airport (SFO) under current conditions and three hypothetical albedo-increase scenarios. Wet bulb globe temperature (WBGT) was used to estimate potential productivity loss based on established relationships between heat stress and loss in physical work capacity. For the month of August 2020, we quantified possible gained hours of productivity per worker per month under each hypothetical albedo-increase scenario. Across the entire area of SFO, the average campus albedo was 0.20 (range: 0.08–0.85). Adopting low, moderate, and high albedo modifications for SFO would reduce peak midday WBGT by 0.89, 1.25, and 1.59 °C, respectively. The largest temperature reductions occurred during the morning shift (7 AM–3 PM). In one shift, we found a potential of 5.20, 7.16, and 8.95 h gained per worker over the entire month in the low, moderate, and high albedo modification scenarios, respectively.

Cool pavements represent one of several strategies that can mitigate the effects of urban overheating by increasing albedo. By definition, this means increasing reflected and potentially re-absorbed short-wave radiation but also decreased surface and air temperatures and longwave upwelling, thus reducing radiant temperatures. So far, real-world studies have been inconclusive as to net effects from cool pavements. A project by GAF installed reflective pavements in Pacoima, California, in summer of 2022. This study set out to perform detailed, high spatiotemporal resolution, multi-platform observations to quantify micrometeorological benefits of the cool pavements and address concerns regarding glare, chemistry/air quality, and pedestrian thermal comfort. Results indicated large variability, as expected, but that the dominant effects were beneficial both in direct side-by-side, real-time comparisons (RT) between test and reference areas, as well as in difference-of-difference (DofD) to quantify local changes in test areas. During a heatwave in September 2022, maximum air-temperature differences (averaged over individual street segments) reached up to −1.9 °C RT in the afternoon. During non-heatwave, hot summer days, the largest street-segment-averaged afternoon air-temperature differences reached up to −1.4 °C RT or −2.8 °C DofD, and surface temperature up to −9.2 °C RT or −12.2 °C DofD. Whereas above values represent maximum effects, more typical street-segment averages also showed statistically significant benefits. In the afternoon, the mean of air-temperature differences was −0.2 °C RT and −1.2 °C DofD. The mean of surface-temperature differences was −2.6 °C RT and −4.9 °C DofD. Indicators of pedestrian thermal comfort also showed variability but predominantly a cooling effect. The mean of differences in mean radiant temperature was between −0.9 and −1.3 °C RT, and for physiological equivalent temperature, between −0.2 °C and −0.6 °C RT and −1.7 °C DofD. In terms of predicted mean vote, the mean of differences was −0.09 RT and −0.32 DofD.

An urban atmospheric modeling study was undertaken with the goal of informing the development of a heat-mitigation plan for the greater Sacramento Valley, California. Realistic levels of mitigation measures were characterized and ranked in terms of their effectiveness in producing urban cooling under current conditions and future climate and land use. An urban heat-island index was computed for current and future climates based on each location’s time-varying upwind temperature reference points and its hourly temperatures per coincident wind direction. For instance, the UHII for the period 16–31 July 2015, for all-hours averaged temperature equivalent (i.e., °C · h hr⁻¹), ranged from 1.5 to 4.7 °C across the urban areas in the region. The changes in local microclimates corresponding to future conditions were then quantified by applying a modified high-resolution urban meteorology model in dynamically downscaling a climate model along with future urbanization and land use change projections for each area. It was found that the effects of urbanization were of the same magnitude as that of the local climate change. Considering the urban areas in the region and the selected emissions scenarios, the all-hours temperature equivalent of the UHII (°C · h hr⁻¹) increased by between 0.24 and 0.80 °C, representing an increase of between 17% and 13% of their respective values in the current climate. Locally, instantaneous (e.g., hourly) temperatures could increase by up to ~3 °C because of climate effects and up to ~5 °C because of both climate and urbanization changes. The efficacies of urban heat mitigation measures were ranked both at the county level and at local project scales. It was found that urban cooling measures could help decrease or offset exceedances in the National Weather Service heat index (NWS HI) above several warning thresholds and reduce the number of heatwave or excessive heat event days. For example, measures that combine increased albedo and urban forests can reduce the exceedances above NWS HI Danger level by between 50% and 100% and the exceedances above Extreme Caution level by between 18% and 36%. UHII offsets from each mitigation measure were quantified for two situations: (1) a scenario where a community implements cooling measures and no other nearby communities take any action and (2) a scenario where both the community and its upwind neighbors implement cooling measures. In this second situation, the community benefits from cooler air transported from upwind areas in addition to the local cooling resulting from implementation of its own heat mitigation strategies. The modeling of future climates showed that except for a number of instances, the ranking of measures in each respective urban area remains unchanged into the future.

The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo and tree fraction. High spatial density meteorological observations are obtained from 76 personal weather-stations. Observed air temperatures were then related to the spatial mean of each LULC parameter within a 500 m radius “neighborhood” of each weather station, using robust regression for each hour of July 2015. For the neighborhoods under investigation, increases in roof albedo are associated with decreases in air temperature, with the strongest sensitivities occurring in the afternoon. Air temperatures at 14:00–15:00 local daylight time are reduced by 0.31 °C and 0.49 °C per 1 MW increase in daily average solar power reflected from roofs per neighborhood in SFV and Central Los Angeles, respectively. Per 0.10 increase in neighborhood average albedo, daily average air temperatures were reduced by 0.25 °C and 1.84 °C. While roof albedo effects on air temperature seem to exceed tree fraction effects during the day in these two regions, increases in tree fraction are associated with reduced air temperatures at night.

To identify and characterize localized urban heat- and cool-island signals embedded within the temperature field of a large urban-climate archipelago, fine-resolution simulations with a modified urbanized version of the WRF meteorological model were carried out as basis for siting fixed weather monitors and designing mobile-observation transects. The goal was to characterize variations in urban heat during summer in Los Angeles, California. Air temperatures measured with a shielded sensor mounted atop an automobile in the summers of 2016 and 2017 were compared to model output and also correlated to surface physical properties focusing on neighborhood-scale albedo and vegetation canopy cover. The study modeled and measured the temperature response to variations in surface properties that already exist in the real world, i.e., realistic variations in albedo and canopy cover that are attainable through current building and urban design practices. The simulated along-transect temperature from a modified urbanized WRF model was compared to the along-transect observed temperature from 15 mobile traverses in one area near downtown Los Angeles and another in an inland basin (San Fernando Valley). The observed transect temperature was also correlated to surface physical properties characterizations that were developed for input to the model. Both comparisons were favorable, suggesting that (1) the model can reliably be used in siting fixed weather stations and designing mobile-transect routes to characterize urban heat and (2) that except for a few cases with opposite co-varying influences, the correlations between observed temperature and albedo and between observed temperature and canopy cover were each negative, ranging from −1.0 to −9.0 °C per 0.1 increase in albedo and from −0.1 to −2.2 °C per 0.1 increase in canopy cover. Observational data from the analysis domains pointed to a wind speed threshold of 3 m/s. Below this threshold the variations in air temperature could be explained by land use and surface properties within a 500-m radius of each observation point. Above the threshold, air temperature was influenced by the properties of the surface within a 1-km upwind fetch. Of relevance to policy recommendations, the study demonstrates the significant real-world cooling effects of increasing urban albedo and vegetation canopy cover. Based on correlations between the observed temperature (from mobile transects) and surface physical properties in the study domains, the analysis shows that neighborhood-scale (500-m) cooling of up to 2.8 °C during the daytime can be achieved by increasing albedo. A neighborhood can also be cooled by up to 2.3 °C during the day and up to 3.3 °C at night by increasing canopy cover. The analysis also demonstrates the suitability of using fine-resolution meteorological models to design mobile-transect routes or site-fixed weather monitors in order to quantify urban heat and the efficacy of albedo and canopy cover countermeasures. The results also show that the model is capable of accurately predicting the geographical locations and the magnitudes of localized urban heat and cool islands. Thus the model results can also be used to devise urban-heat mitigation measures.

To further evaluate the factors influencing public heat and air-quality health, a characterization of how urban areas affect the thermal environment, particularly in terms of the air temperature, is necessary. To assist public health agencies in ranking urban areas in terms of heat stress and developing mitigation plans or allocating various resources, this study characterized urban heat in California and quantified an urban heat island index (UHII) at the census-tract level (~1 km²). Multi-scale atmospheric modeling was carried out and a practical UHII definition was developed. The UHII was diagnosed with different metrics and its spatial patterns were characterized for small, large, urban-climate archipelago, inland, and coastal areas. It was found that within each region, wide ranges of urban heat and UHII exist. At the lower end of the scale (in smaller urban areas), the UHII reaches up to 20 degree-hours per day (DH/day; °C.hr/day), whereas at the higher end (in larger areas), it reaches up to 125 DH/day or greater. The average largest temperature difference (urban heat island) within each region ranges from 0.5–1.0 °C in smaller areas to up to 5 °C or more at the higher end, such as in urban-climate archipelagos. Furthermore, urban heat is exacerbated during warmer weather and that, in turn, can worsen the health impacts of heat events presently and in the future, for which it is expected that both the frequency and duration of heat waves will increase.

There exists a number of environmental and energy measures that, when deployed at urban scale, can directly impact energy use and emissions from power generation and indirectly affect the atmospheric environment which, in turn, impacts energy demand, emissions of greenhouse gas and ozone precursors and photochemical production of ozone. Atmospheric modeling is an important tool in evaluating the indirect effects, both beneficial and inadvertent, of urban heat-island mitigation. In this article, we provide a brief background discussion of heat-island research and modeling and present findings from three recent projects we have completed for California.