Arboriculture & Urban Forestry 36(3): March 2010 Arboriculture & Urban Forestry 2010. 36(2): 73–80 73 A Hedonic Analysis of the Impact of Tree Shade on Summertime Residential Energy Consumption Ram Pandit and David N. Laband Abstract. Trees cast shade on homes and buildings, lowering the inside temperatures and thus reducing the demand for power to cool these buildings during hot times of the year. Drawing from a large sample of residences in Auburn, Alabama, U.S., a statistical model was developed to produce specific estimates of the electricity savings generated by shade-producing trees in a suburban environment. This empirical model links residential energy consumption to hedonic characteristics of the structures, characteristics/behaviors of the occupants, and the extent and density of shade cast on the structures at different times of the day. Key Words: Electricity Usage; Economic Value; Shade Density; Shading Time; Tree Shade. Trees cast shade on homes and buildings, lowering the inside temperatures and thus reducing the demand for power to cool these buildings during hotter times of the year. The savings may be sizable because electricity usage for cooling houses in summer months is costly for those who live in hot climates. Particularly in the Sun Belt area of the U.S. (the southern states stretching from South Carolina to Florida, along the Gulf of Mexico, across to southern California), the energy used for air conditioning makes up a large fraction of the peak electrical utility loads dur- ing the warmest period of summer (Rudie and Dewers 1984). As the cost of electricity has increased in recent years, the amount and cost of electricity usage for cooling homes has become a significant expense to residents and industries in these areas. With respect to the value of using tree shade to help cool dwell- ings, with the exception of Rudie and Dewers (1984), there is little to no scientific guidance for hard estimates using real data from a large number of sample households. The cooling effect of trees is most important during the period of maximum temperature and solar radiation (Parker 1983). Therefore, shade trees are consid- ered as a possible demand-side management resource to provide cost-effective energy saving benefits to home and business own- ers (McPherson and Simpson 1995). In addition, the extent, tim- ing, and density of shade cast by trees surely are important factors in reducing the demand for power. However, the available sci- entific literature provides very limited empirical information on the impact of the extent, density, duration, and/or timing of tree shade on energy used to cool houses during hot summer months. Most of the available analyses of empirical link between tree shade and residential energy usage are based on simulation exercises. For example, the simulation results of Simpson and McPherson (1996) indicated that two trees shading the west- facing exposure of a house and one tree shading the east-facing exposure reduced annual energy use for cooling by 10% to 50% and peak electrical use up to 23%. Huang et al. (1987) conducted a simulation study of the potential role of vegetation in reduc- ing summer cooling energy in residential houses across 4 U.S. cities. Their results suggested that an additional 25% increase in tree cover would reduce annual cooling energy use by 40%, 25%, and 25% for an average house in Sacramento, Phoenix, and Lake Charles, respectively. However, the fourth city, Los Angeles, had minimal calculated savings. Similarly, another simulation study by McPherson et al. (1997) in Chicago indi- cated that three 7.6 m tall trees around a well-insulated new house would reduce annual heating and cooling costs by 8% as compared to otherwise identical houses without trees. However, conclusions drawn from these tightly controlled simulation exer- cises may not accurately reflect the savings realized by consum- ers, who lead lives that are considerably more complicated, in terms of energy consumption, than simulation exercises admit. There are a few empirical studies of shade trees and residential energy consumption based on real-world data, but the usefulness of the findings generated by these studies (Akbari et al. 1992; Ak- bari et al. 1997; Carver et al. 2004) is limited due to small samples, except Rudie and Dewers (1984), or the absence of rigorous con- trols for confounding effects (Clark and Berry 1995; Laverne and Lewis 1996). For example, Akbari et al. (1997) analyzed the im- pact of shade trees on peak power and cooling energy use in two houses in Sacramento, CA and found a 30% reduction in energy use and 0.6 to 0.8 kilowatt peak demand savings due to shade trees. Rudie and Dewers (1984), an exception to the small sample size limitation, examined the impact of shade cast in different coverage categories on energy consumption by 113 residents in College Station, TX. They evaluated tree shade on roofs for three years (1977–1979) from June to September, using mea- sured tree height to estimate the amount of shade cast based on hourly solar position on the twenty-first day of each month. They developed a shade score for each home ranging from 1 to 4 based on the shaded roof perimeter and wall space, and clas- sified each homes into one of four shade categories [category 1 with 4.27 m or greater depth of shade and category four homes ©2010 International Society of Arboriculture
March 2010
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