Phoenix Regional Heat and Air Quality Knowledge Repository

Given increasing utility of numerical models to examine urban impacts on meteorology and climate, there exists an urgent need for accurate representation of seasonally and diurnally varying anthropogenic heating data, an important component of the urban energy budget for cities across the world. Incorporation of anthropogenic heating data as inputs to existing climate modeling systems has direct societal implications ranging from improved prediction of energy demand to health assessment, but such data are lacking for most cities. To address this deficiency we have applied a standardized procedure to develop a national database of seasonally and diurnally varying anthropogenic heating profiles for 61 of the largest cities in the United Stated (U.S.). Recognizing the importance of spatial scale, the anthropogenic heating database developed includes the city scale and the accompanying greater metropolitan area.

Our analysis reveals that a single profile function can adequately represent anthropogenic heating during summer but two profile functions are required in winter, one for warm climate cities and another for cold climate cities. On average, although anthropogenic heating is 40% larger in winter than summer, the electricity sector contribution peaks during summer and is smallest in winter. Because such data are similarly required for international cities where urban climate assessments are also ongoing, we have made a simple adjustment accounting for different international energy consumption rates relative to the U.S. to generate seasonally and diurnally varying anthropogenic heating profiles for a range of global cities. The methodological approach presented here is flexible and straightforwardly applicable to cities not modeled because of presently unavailable data. Because of the anticipated increase in global urban populations for many decades to come, characterizing this fundamental aspect of the urban environment – anthropogenic heating – is an essential element toward continued progress in urban climate assessment.

We conducted microclimate simulations in ENVI-Met 3.1 to evaluate the impact of vegetation in lowering temperatures during an extreme heat event in an urban core neighborhood park in Phoenix, Arizona. We predicted air and surface temperatures under two different vegetation regimes: existing conditions representative of Phoenix urban core neighborhoods, and a proposed scenario informed by principles of landscape design and architecture and Urban Heat Island mitigation strategies. We found significant potential air and surface temperature reductions between representative and proposed vegetation scenarios:

1. A Park Cool Island effect that extended to non-vegetated surfaces.
2. A net cooling of air underneath or around canopied vegetation ranging from 0.9 °C to 1.9 °C during the warmest time of the day.
3. Potential reductions in surface temperatures from 0.8 °C to 8.4 °C in areas underneath or around vegetation.

We examined the horizontal and vertical nocturnal cooling influence of a small park with irrigated lawn and xeric surfaces (∼3 ha) within a university campus of a hot arid city. Temperature data from 0.01- to 3-m heights observed during a bicycle traverse of the campus were combined with modeled spatial temperature data simulated from a three-dimensional microclimate model (ENVI-met 3.1). A distinct park cool island, with mean observed magnitudes of 0.7–3.6°C, was documented for both traverse and model data with larger cooling intensities measured closer to surface level. Modeled results possessed varying but generally reasonable accuracy in simulating both spatial and temporal temperature data, although some systematic errors exist. A combination of several factors, such as variations in surface thermal properties, urban geometry, building orientation, and soil moisture, was likely responsible for influencing differential urban and non-urban near-surface temperatures. A strong inversion layer up to 1 m over non-urban surfaces was detected, contrasting with near-neutral lapse rates over urban surfaces. A key factor in the spatial expansion of the park cool island was the advection of cooler park air to adjacent urban surfaces, although this effect was mostly concentrated from 0- to 1-m heights over urban surfaces that were more exposed to the atmosphere.

Field observations were carried out to determine the influence of a park on the urban summer climate in the nearby areas. The possibilities of reduction in air conditioning energy were investigated. Air temperature, relative humidity and other meteorological factors were measured at many locations inside a park and in the surrounding areas in the Tama New Town, a city in the west of the Tokyo Metropolitan Area, Japan. The observations indicated that vegetation could significantly alter the climate in the town. At noon, the highest temperature of the ground surface of the grass field in the park was 40.3 °C, which was 19 °C lower than that of the asphalt surface or 15 °C lower than that of the concrete surface in the parking or commercial areas. At the same time, air temperature measured at 1.2 m above the ground at the grass field inside the park was more than 2 °C lower than that measured at the same height in the surrounding commercial and parking areas. Soon after sunset, the temperature of the ground surface at the grass field in the park became lower than that of the air, and the park became a cool island whereas paved asphalt or concrete surfaces in the town remained hotter than the overlying air even late at night. With a size of about 0.6 km2, at noon, the park can reduce by up to 1.5 °C the air temperature in a busy commercial area 1 km downwind. This can lead to a significant decrease of in air conditioning energy in the commercial area.