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Reference Publication: Vieira, R., Parker, D., "Energy Use in Attached and Detached Residential Developments: Survey Results", Condensed from FSEC-CR-381-91, Proceedings of the 3rd Visions of Quality Developments, Winter Park, FL., June 1991. Disclaimer: The views and opinions expressed in this article are solely those of the authors and are not intended to represent the views and opinions of the Florida Solar Energy Center.

Energy Use in Attached and Detached
Residential Developments: Survey Results

Robin K. Vieira and Danny S. Parker
Florida Solar Energy Center (FSEC)

FSEC-CR-381-91

Executive Summary

The relationship between land use, density, dwelling types and energy use in Florida has never been comprehensively examined. Few people consider both energy used in housing and energy used for local transportation. Florida state officials and some land planners have called for compact urban growth to reduce traffic congestion and travel distances. However, energy is rarely mentioned in these arguments. Local governments are trying to respond to the state's concern for compact growth. Developers, on the other hand, are concerned with meeting the local regulations. Unfortunately, energy use is seldom considered and there is little data available to guide decision makers.

To meet this deficiency, the Governor's Energy Office funded the Florida Solar Energy Center to study energy use in ten Florida developments built during the 1980s. In order to obtain reasonably sized samples of respondents for a survey, only two distinctly different development types were selected:

1) attached low-rise multifamily housing
2) golf-course community, single-family, executive homes.

Households in ten selected East Central Florida developments were sent the questionnaire; 384 households responded. Matching annual electricity use was obtained for 292 of the respondents. Respondents estimated the total yearly miles driven for each household vehicle. Because this data was collected from only a small number of selected, new developments, the results may not be generalized into representing all detached versus attached dwellings in Florida.

By converting electricity use (for all-electric household respondents) and mileage to fuel energy consumed, it was found that the detached household respondents used an estimated average of 2.4 times as much total energy as attached households. The detached households averaged one more occupant than the attached households.

The figure below illustrates total estimated energy use by household size for the attached and detached households. From it we may conclude that:

1. Increased occupancy increases household energy use
2. Energy-use-per-occupant decreases with increasing occupancy
3. Detached households consumed 150 to 220 million Btus more than attached households of equal occupancy (this represents 85% to 99% greater energy use)
4. Detached households consume substantially more electricity that attached households of equal occupancy
5. Detached househoulds consume slightly more gasoline than attached households of equal occupancy.

Other highlights of the differences between households include:

• Distances to work, schools and most errand trips were shorter for attached households.
• Forty-seven percent of attached households reported that someone in the household walked or biked to a store or recreation area as opposed to just 17% of detached households.
• Food stores were easily accessible by walking or bicycling according to 42% of attached households as compared to only 4% of detached households.
• Over 25% of attached respondents listed inadequate breezes as a factor in preventing them from opening windows more often as opposed to 10% of detached respondents.
• Noise from traffic was a greater reason for not ventilating attached households as compared to detached households (4.1% to 0%).
• Detached households were more likely to use a clothesline for drying laundry, to have more energy using appliances and more likely to use an electric dishwasher.
• Attached households were more active in managing their thermostats.

Responses to demographic, energy use, transportation and landscaping questions were analyzed through statistical techniques to determine their relationship to estimated miles driven and annual electricity use.

Analysis consistently revealed the following significant relationships to total electricity use:

• Increased floor area strongly relates to increased electricity consumption. Over 70% of the differences in electricity use among respondents were related to conditioned dwelling square footage.
• Households with pool/spa heat pumps showed much higher levels of electricity use.
• The number of hours that households report using pool or spa circulation pumps related to large increases in electricity use.
• Heated water beds were associated with large increases in electricity use.
• Increasing heating thermostat set points corresponded to a moderate increase in electricity use for all-electric homes.
• Increasing cooling thermostat set points correlated to a moderate decrease in electricity use.
• The number of months respondents ventilated related to a large decrease in electricity use.
• Respondents with heat recovery units related to significantly less electricity use.
• Respondents who only occupied households on a seasonal basis had much lower annual electricity use.
• Homes with natural gas used significantly less electricity.

Regression analysis of the transportation data did not show good explanation of the total miles driven. However, the variables which showed a statistically significant relationnship were:

• The number of drivers (the more drivers, the more miles driven).
• School trip miles (the more miles traveled to school, the more miles driven).
• Work trip miles (the more miles traveled to work, the more miles driven).
• College trip miles (the more miles traveled to college, the more miles driven).
• Income; as income increases so do miles driven.
• Households responding that someone walks or bicycles to a park or store corresponded to significantly fewer miles driven.
• Age of household drivers; as age increases, mileage decreases.

The results indicate that per person electricity and transportation use may be reduced by greater household occupancy. In terms of development patterns and zoning laws, it may be energy conserving to allow households to rent out bedrooms, and to have co-housing arrangements where some appliances, e.g., water heaters and refrigerators, could be shared. Transportation energy can be saved by combining erand or school trips by household occupants.

Based on the results, the authors also recommend that municipalities and developments:

• Avoid restrictions calling for minimum floor area
• Allow and encourage solar devices for heating swimming pools and spas
• Provide community pools as an option instead of individual pools and spas
• Allow and encourage the use of clotheslines
• Design homes to make use of natural ventilation
• Provide heat recovery water heater units or other efficient water heating devices
• Locate the development near destinations, particularly schools, colleges and places of work.

Additionally, new land developments should:

• Reduce grass areas; 88% of respondents said they never used their lawns for social or recreational activities, but spent 4 hours per week maintaining them
• Plan for non-drivers. Only one out of 89 children travelled to school independent of an automobile or bus. Only 25% of detached households with non-drivers had someone travel to a store or recreation area on a regular basis without the use of an automobile.

Questions raised by the analysis include:

• How do these results relate to other new Florida developements?
• How do trip distances change over time as new commercial areas follow residential developments?
• How can legal barriers to energy-efficiency, such as seperate zoning and minimum square-footages be removed or improved?
• How can bicycling and walking be encouraged as alternative transportation modes?
• What is the social cost of our present car-dependent transportation system on children and others who do not drive?
• What quantity of energy do residential heat recovery units (desuperheaters) save?
• How much electricity do different pool/spa devices use and what is their impact on the state's total residential energy use?
• What are some acceptable alternatives to turfed lawns for households?

1.0 Background

The relationship between land use, density, dwelling types and energy use has long been an issue of speculation. However, little data has been collected to substantiate these relationships based on measured energy use. Building energy use in four studies was compared by Hanson. They showed a modest decrease in building energy use per square foot of conditioned floor area for larger buildings. All studies were done for northern U.S. climates and only one involved collection of empirical data.

In a theoretical study by Calthorpe and Benson, energy use of a 200 acre townhouse community was calculated at only 56% of the energy use of a 500 acre sprawling single family development. Over half of the savings were due to expected transportation savings. Michael Corbett suggests ideal densities are seven to eight dwelling units per acre for strictly residential areas, five dwelling units per acre for a neighborhood and three to four dwelling units per acre for a town. Corbett argues that although multi-unit dwellings save building materials and reduce building energy use from reduced surfaces for heat loss and heat gain, the savings may be offset by the energy required to transport food into and waste out of highly populated areas. He recommends community gardens interspersed with housing, and using land treatment/enrichment for wastes; solutions unavailable in highly urbanized areas.

There are also other factors influencing energy use, such as land available for shade trees. Shade not only reduces air conditioning use in buildings, but can ameliorate the heat island effect that has been documented to cause as much as a 6oF increase in summer afternoon temperatures in large urban cities.

Another factor is the energy that is embodied in buildings and site development. By reducing pavement area by 15%, 15.2 x 106 Btu of energy had been calculated as an annual potential savings for a 2,300-unit development. Energy embodied in a building has been estimated as ten to fifty percent the amount of energy used directly in the building over an eighty-year life.

2.0 Developments

To fully describe the relationship of energy use to housing density or type of housing is a complex task. As a beginning, the Florida Solar Energy Center has conducted a written survey and collected one year's worth of electric utility bill from residents of ten East-Central Florida sites developed during the 1980's. The development fit into two distinct categories:

1) Attached low-rise multifamily housing developments, and
2) Golf-course-community, single-family, executive homes.

In the latter case, most of the developments were actually part of planned unit developments that consisted of other building types also, but for this study only single family subdivisions within the planned unit developments were mailed the questionnaire. The extreme disparity of the two residential community types was intentional. We wished to see if significant differences in energy use existed between very divergent community types. The developments were not randomly selected, they were arbitrarily chosen by FSEC to obtain the housing types desired. A description of each development will be presented in the future paper.

3.0 Data Collection

A total of 1,617 surveys were sent out to those residents in each development listed by Donnerly in their 1990 phone directories. Two hundred-fifty were returned because of change of address or insufficient address for delivery. This high return was likely due to the large number of rented multifamily units. Three hundred eighty-four were completed and returned, with an overall return rate of those people receiving the survey of 28.1%. Three hundred forty-two of the respondents gave FSEC permission to obtain electric bills for the past twelve months (September 1989 - August 1990). Two hundred ninety-two respondents had a complete year of electricity use data. The utility data covered the twelve months preceding the survey; September 1989 to August 1990. The values reported for each month represent the billing month. Thus, on average, the November value should represent electricity use from mid October to mid November. A complete year's water data was collected from 214 respondents that were billed individually. Water was metered collectively for most multifamily complexes and FSEC was able to obtain that consumption data as well. Approximate per household water use in the development was developed from this data. This report will focus on the energy use; a future paper will discuss the water use results.

A copy of the survey questionnaire and a more detailed report are available from the authors.

4.0 Statistical Significance of Data

The response rates of the questionnaire were 31% for detached units and 16% for attached units that were sent the survey instrument. Of those respondents who received the questionnaire, the response rate was 32% for detached households and 22% for attached households. Whether the respondents are representative of the non-respondents is unknown. Since the information was collected from only a small number of selected, new developments, this information may not be generalized into representing all detached versus attached dwellings.

The limitations of the data presented in this report should be understood when interpreting the reported results. An obvious limitation is the geographical homogenitity of the data source; it comes from the Central Florida area, which may be uncharacteristic of other areas within the state and particularly of other geographical areas in the United States where climatic differences could be expected to make significant differences in the described conclusions.

Because the survey data is self reported and the empirical values (kWh use and water use) are for monthly time periods, lack of correlation between a response and resulting usage does not imply there is no actual effect. In particular, the large variations on energy use makes it statistically difficult to establish significance for factors that result in little systematic change in energy use from one household to another. This problem is even more pronounced when correlating answers to the self-reported mileage data since the data source is necessarily imprecise (estimated mileage vs. actual odometer readings). Moveover, those survey responses that do correlate with the resource use data may show even stronger association if the data sources were improved such as with more households, and more precise measurements.

5.0 Demographics

Table 1 presents the demographics of the respondents. The age category includes every occupant. Although the difference in average is small, the distribution is extremely different as illustrated in Figure 1 and 2. The attached households have a far greater proportion of occupants in the 20 to 35 age group, but a much smaller proportion of occupants under age 20. The average number of occupants was 1.635 for the attached dwellings and was 2.706 for the detached dwellings.

There is a large disparity in the annual household income between the two housing types. Thirty-nine percent of the detached households had incomes in excess of $75,000, whereas only five percent of the attached households fell in that category. The median income fell in the $65,000 - 74,999 category for detached households and only $25,000 - 34,999 for attached households. In comparison, median Florida income for 1988 was $25,000 - 34,999 for all households and only 25.2% had incomes greater than $45,000.

6.0 Electricity Usage

Two developments had natural gas. Respondents using natural gas appliances were seperated from those that had all-electric homes for the purposes of analysis. Seasonal occupants were also eliminated for the attached versus detached analysis since we expected that their inclusion might bias the various estimates.

Table 1. Demographics of Respondents
	Total Respondents		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Age
Total Occupants	826		206		690
0-5 years	42	4.7	5	2.4	37	5.4
6-12 years	65	7.3	4	1.9	61	8.8
13-17 years	44	4.9	5	2.4	39	5.7
18-24 years	56	6.3	15	7.3	41	5.9
25-34 years	104	11.6	57	27.7	47	6.8
35-44 years	174	19.4	25	12.1	149	21.6
45-54 years	94	10.5	14	6.8	80	11.6
55-64 years	163	18.2	40	19.4	123	17.8
65 years and over	154	17.2	41	19.9	113	16.4
Average age	42.3		44.2		41.7
Household size
Total Respondents	381		126		255
One person	68	17.8	58	46.0	10	3.9
Two people	197	51.7	58	46.0	139	54.5
Three people	52	13.6	8	6.3	44	17.3
Four people	47	12.3	2	1.6	45	17.6
Five or more people	17	4.5	0	0	17	6.7
Average occupancy	2.352		1.635		2.706
Family income
Total Respondents	366		126		240
Less than $15,000	16	43.7	15	11.9	1	0.4
$15,000-24,999	33	9.0	27	21.4	6	2.5
$25,000-34,999	50	13.7	30	23.8	20	8.3
$35,000-44,999	55	15.0	28	22.2	27	11.3
$45,000-54,999	52	14.2	12	9.5	40	16.7
$55,000-64,999	30	8.2	6	4.8	24	10.0
$65,000-74,999	31	8.5	3	2.4	28	11.7
$75,000 or over	99	27.0	5	4.0	94	39.2
Median Range	$45,000-54,999		$25,000-34,999		$65,000-74,999

All electric homes

Average monthly electricity usage per household in the detached dwellings was 2,000 kWh, while only 684 kWh in the attached units. Average monthly electricity usage per occupant was 668 kWh in the detached units and 458 kWh in the attached units. Average monthly electricity usage per square foot was 0.744 kWh and 0.701 kWh respectively in the detached and attached dwellings. Average monthly electricity use per person per square foot was 0.253 kWh and 0.482 kWh in the detached and attached dwellings respectively. These relationships are illustrated in Figures 3 through 6. As shown in Figure 4, there is little difference in electricity use on a per square-foot basis between the two building types. However, because the attached units had fewer square feet per person, the electricity usage per occupant was substantially lower for the attached units as shown in Figure 5. If electricity usage is normalized by both occupancy and floor area, detached households use substantially less than attached dwellings, as shown in Figure 6. This can be explained by the larger household size of detached dwellings as shown in Figure 7. The relationship of electricity use to floor area basis is shown in Figure 8. Analysis indicates that floor area alone may explain over 70% in the variation in annual electricity consumption from one home to another.

Table 2 provides respondents answers to questions on square footage and other dwelling characteristics. The average square footage for attached dwellings is 1,031, whereas the average detached dwelling has 2,396 square feet.

A summary of total annual electricity use by building types is given in Table 3. Figures 9 and 10 show the distinct disparity between attached and detached households. The average usage for all respondents was 16548 kWh/year of 1379 kWh per month. At current electric rates ($0.08/kWh), this indicates an average monthly utility bill of approximately $120. The average per area usage was 8.7 kWh/ft2.

By way of comparison, a 1981 study of 25 existing Palm Beach County houses showed an annual average usage of 24,661 kWh, or 13.04 kWh/ft2, an average occupancy of 4.1, and an average age of 16.1 years[9]. A Florida Power and Light study of 165 customers with an average of 1466 square feet and 2.7 occupants per household had an average annual usage of 13,983 kWh from September 1978 to August 1979 or 9.54 kWh/ft2[10]. Therefore, the present study of new homes represents reduced electricity use per square foot than the studies on older homes.

Most of the differences in electricity use relates to differences in floor area. There is little difference on a kWh/ft2 basis in the frequency of respondents between attached and detached households.

Of particular interest to utilities is how the different types of dwellings affect peak demand. Collecting monthly electrical data does not provide a definitive answer to this question. However, Figure 11 shows that the detached units require more electricity during the peak heating (late December 1989 had the only real cold weather and is represented by the January 1990 billing) and cooling months on a per square foot basis. The differences between attached and detached electrical use disappears during the swing months.

Table 4 shows the distribution of answers to energy related questions. Highlights of differences between dwelling types follow.

• Similar proportions of respondents in each category claimed to open windows some during the various months. However, 26% of attached respondents as opposed to only 10% of detached respondents, listed inadequate breezes as a factor in preventing them from opening windows more often. The relationship of venting and annual electricity use per square foot is shown in Figure 12.
• Noise from traffic was a greater reason for not ventilating in the attached dwellings (4.1% to 0%).
• Attached households were more active in managing their thermostats; 78.7% of attached households turned off their air conditioner/heater or adjusted the thermostat when the dwelling was unoccupied. Only 49.6 % of detached households adjusted their thermostats.
• Fan use varied with housing type. 19.8% of attached households reported never using fans with the air conditioner in use, compared to only 5.6% of detached households. This may, however, be due to fan availability.
• Detached households had more energy using appliances. 26.7% of detached households have more than one refrigerator relative to 3.9% of attached households. 28.7% of detached households have a separate freezer compared to 10.2% of attached households.
• Detached households were more likely to use a clothesline for drying laundry. 21.3% of detached households used a clothesline compared to only 11.8% of attached households.
• Automatic dishwashers were chosen for the dish washing chore much more frequently in the detached dwellings.

Pools and spas are responsible for significant energy use. The distribution of answers on pools and spas are given in Table 5. Over 60% of detached households had a pool, spa or both.

Table 2. Dwelling Characteristics
	Total Respondents		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Ownership
Own	291	76.0	39	30.5	252	98.8
Rent	92	24.0	89	69.5	3	1.2
Total	383		128		255
Time in home
Less than 1 year	45	11.7	19	14.8	26	10.2
1 to 3 years	200	52.1	73	57.0	127	49.6
3 to 7 years	126	32.8	35	27.3	91	35.5
More than 7 years	13	3.4	1	0.8	12	4.7
Residence
Year-round	360	94.7	118	93.7	242	95.3
Seasonal	20	5.3	8	6.3	12	4.7
Type of residence
Single family - one story	229	59.6	0	0	229	89.5
Single family - two story	26	6.8	0	0	26	10.2
Townhouse (2-story attached)	33	8.6	32	25.0	1*	0.4
Top Floor of condominium/apartment	52	13.5	52	40.6	0	0
Other (lower) floor of condominium/apartment	44	11.5	44	34.4	0	0
Sides having windows
1	30	8.0	30	24.2	0	0
2	85	22.5	76	61.3	9	3.6
3	55	14.6	16	12.9	39	15.4
4	207	54.9	2	1.6	205	81.0
Direction home fronts
North	58	15.4	19	15.2	39	15.5
South	81	21.5	30	24.0	51	20.3
East	87	23.1	31	24.8	56	22.3
West	76	20.2	22	17.6	54	21.5
Northeast	22	5.9	8	6.4	14	5.6
Southeast	13	3.5	5	4.0	8	3.2
Northwest	14	3.7	2	1.6	12	4.8
Southwest	25	6.6	8	6.4	17	6.8
Construction
Concrete Block	186	51.1	69	62.2	117	46.2
Wood Frame	152	41.8	30	27.0	122	48.2
Other	26	7.1	12	10.8	14	5.5
Wall color
White	90	23.9	52	41.6	38	15.1
Other	287	76.1	73	58.4	214	84.9
Roofing material
Shingle	301	86.7	89	91.8	212	84.8
Metal	0	0	0	0	0	0
Built-up	6	1.7	1	1.0	5	2.0
Tile	40	11.5	7	7.2	33	13.2
Roof color
White	10	2.7	1	0.9	9	3.6
Other	357	97.3	116	99.1	241	96.4
Square footage
<750	11	3.1	11	10.9	0	0
750-1249	78	2.2	77	76.2	1	0.4
1250-1749	32	9.1	10	9.9	22	8.8
1750-2249	90	25.6	3	3.0	87	34.8
2250-2749	79	22.5	0	0	79	31.6
2750-3249	41	11.6	0	0	41	16.4
3250-3749	9	2.6	0	0	9	3.6
>3750	11	3.1	0	0	11	4.4
Average	2003.2		1031.1		2395.9
*Respondent had moved to townhouse from single family home. Water and electrical data was for previous residence and so respondent was classified as detached.

Table 3. Electricity Use of Non-seasonal Respondents
	Total		Attached		Detached		Total
	All-electric Households		All-electric Households		All-electric Households		Natural Gas (1) Households
	Respondents	%	Respondents	%	Respondents	%	Respondents	%
Annual Electricity Use
<3000 kWh	0	0	0	0	0	0	0	0
3000-5999 kWh	23	13.5	22	27.2	1	1.1	0	0
6000-8999 kWh	28	16.5	28	34.6	0	0	9	8.7
9000-11999 kWh	27	15.9	23	28.4	4	4.5	28	26.9
12000-14999 kWh	15	8.8	7	8.6	8	9.0	24	23.1
15000-17999 kWh	9	5.3	1	1.2	8	9.0	18	17.3
18000-20999 kWh	16	9.4	0	0	16	18.0	15	14.4
21000-23999 kWh	12	7.1	0	0	12	13.5	4	3.8
24000-26999 kWh	11	6.5	0	0	11	12.4	3	2.9
27000-29999 kWh	8	4.7	0	0	8	9.0	0	0
>30000 kWh	21	12.4	0	0	21	23.6	3	2.9
Total Respondents	170		81		89		104
Average annual kWh	16,548		8,211		24,136		14,715
kWh/month	1379		684		2000		1226
kWh/occupant/month	568		458		668		559
kWh/ft2/month	0.726		0.701		0.744		0.567
kWh/ft2/occupant/month	0.349		0.482		0.253		0.260
(1) only four natural gas households were attached units (2) respondents with a complete year of electricity use

Table 4. Distribution of Answers to Energy Use Questions
	Total		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Energy source
All electricity	235	61.8	124	97.6	111	43.9
Electricity & LP or natural gas	145	38.2	3	2.4	142	56.1
Heating source
Gas	133	35.4	2	1.6	131	51.8
Electricity	243	64.6	121	98.4	122	48.2
Electricity Heat Type
Forced air electric resistance heat	101	45.9	69	68.3	32	26.9
Heat pump	119	54.1	32	31.7	87	73.1
Heating temperature
<70	96	25.8	24	19.7	72	28.7
70-72	167	44.8	52	42.6	115	45.8
73-75	64	17.2	26	21.3	38	15.1
>75	46	12.3	20	16.4	26	10.4
Average reported set point	71.43		71.95		71.18
Air conditioning (which months)
January	28	7.4	13	10.3	15	5.9
February	36	9.5	17	13.5	19	7.5
March	73	19.3	35	27.8	38	15.0
April	157	41.4	56	44.4	101	39.9
May	280	73.9	93	73.8	187	73.9
June	352	92.9	109	86.5	243	96.0
July	369	97.4	119	94.4	250	98.8
August	371	97.9	121	96.0	250	98.8
September	365	96.3	120	95.2	245	96.8
October	243	64.1	72	57.1	171	67.6
November	68	17.9	27	21.4	41	16.2
December	32	8.4	16	12.7	16	6.3
Average number of months	6.22		6.27		6.19
Natural ventilation (which months)
January	266	77.1	94	79.7	172	75.8
February	268	77.1	93	78.8	175	77.1
March	273	79.1	87	73.7	186	81.9
April	226	65.5	70	59.3	156	68.7
May	122	35.4	44	37.3	78	34.4
June	45	13.0	22	18.6	23	10.1
July	28	8.1	14	11.9	14	6.2
August	26	7.5	12	10.2	14	6.2
September	45	13.0	22	18.6	23	10.1
October	192	55.7	72	61.0	120	52.9
November	301	87.2	99	83.9	202	89.0
December	277	80.3	92	78.0	185	81.5
Average number of months	5.44		5.68		5.32
Preventive factors
No adequate breeze	57	15.4	32	26.0	25	10.1
Lack of security	39	10.5	10	8.1	29	11.7
Too hot/cold/humid	234	63.2	68	55.3	166	67.2
Windows hard to operate/ inoperable	2	0.5	0	0	2	0.8
Excessive noise from traffic	5	1.4	5	4.1	0	0
Allergies	32	8.6	8	6.5	24	9.7
Other (dog barking)	1	0.3	0	0	1	0.4
Cooling temperature (F)
<75	43	11.4	20	16.0	23	9.1
75-77	75	19.9	24	19.2	51	20.2
78-80	237	62.8	74	59.3	163	64.7
>80	22	5.8	7	5.6	15	6.0
Average reported set point	77.70		77.47		77.80
Set back behavior
Turn off air conditioner/heating	58	15.2	32	25.2	26	10.2
Thermostat to higher setting	168	44.1	68	53.5	100	39.4
Don't change the setting	155	40.7	27	21.3	128	50.4
Set back
Automatically	14	8.3	6	8.8	8	7.9
Manually	155	91.7	62	91.2	93	92.1
Ceiling & portable fans
None	18	4.8	13	10.7	5	2.0
One	23	6.1	21	17.4	2	0.8
Two	49	13.0	33	27.3	16	6.3
Three	37	9.8	24	19.8	13	5.1
Four	62	16.5	20	16.5	42	16.5
Five	61	16.2	4	3.3	57	22.4
Six	60	16.0	3	2.5	57	22.4
Seven or more	66	17.6	3	2.5	63	24.7
Average number of fans	4.46		2.50		5.39
Fan usage to reduce a/c use
Always	196	52.3	60	48.8	136	54.0
Frequently	122	32.5	33	26.8	89	35.3
Occasionally	34	9.1	13	10.6	21	8.3
Never	23	6.1	17	13.8	6	2.4
Use fans with air conditioner
Yes	333	89.8	97	80.2	236	94.4
No	38	10.2	24	19.8	14	5.6
Water heater
Electric	216	57.9	115	96.6	101	39.8
Air conditioner heat exchanger	14	3.8	2	1.7	12	4.7
Gas	138	37.0	2	1.7	136	53.5
Heat pump	5	1.3	0	0	5	2.0
More than one refrigerator
Yes	73	19.1	5	3.9	68	26.7
No	309	80.9	122	96.1	187	73.3
Seperate freezer
Yes	86	22.6	13	10.2	73	28.7
No	295	77.4	114	89.8	181	71.3
Clothes washer
Inside the house	347	90.8	115	90.6	232	91.0
In the garage/porch	24	6.3	3	2.4	21	8.2
No clothes washer	11	2.9	9	7.1	2	0.8
Loads per week (average)	5.04		4.01		5.54
Clothes dryer
Electric	290	75.5	116	90.6	174	68.0
Gas	82	21.4	3	2.3	79	30.9
No dryer	12	3.1	9	7.0	3	1.2
Do you use a clothesline
Always	7	1.8	1	0.8	6	2.4
Frequently	18	4.7	7	5.5	11	4.3
Occasionally	44	11.5	7	5.5	37	14.6
Never	312	81.9	112	88.2	200	78.7
Do you use a dish water
Always	190	49.5	44	34.4	146	57.0
Frequently	85	22.1	21	16.4	64	25.0
Occasionally	88	22.9	48	37.5	40	15.6
Never	21	5.5	15	11.7	6	2.3
Heated water beds
None	337	90.1	111	88.1	226	91.1
One	30	8.0	12	9.5	18	7.3
Two or more	7	1.9	3	2.4	4	1.6
Do trees help shade your house
Almost totally	11	2.9	3	2.4	8	3.1
Partially	153	40.1	52	40.9	101	39.3
None	218	57.1	72	56.7	146	57.3

Natural gas homes

One hundred forty-nine homes had natural gas. One hundred forty-five (97%) of these homes were detached. The natural gas homes averaged 2,179 square feet. As illustrated in Figure 13, the annual electricity use per square foot of floor area in the homes with gas is 23% less. Figure 14 shows the month by month relationship. During the winter peak, electricity use in the gas homes was just 47% the electricity use in the all electric homes on a per square foot basis. This indicates that about half of the electricity consumption in the all-electric group of houses or 840 kWh, was associated with monthly space or water heating. The summer peak represented a mere 4% difference.

7.0 Transportation Energy Use

The transportation analysis results are more subject to error since they are based on the respondents' estimates as to miles each car they owned was driven in the past year rather than on actual odometer readings. Distances and frequencies of trips were likely roughly estimated by most respondents.

Table 6 presents responses to the questions regarding convenience and safety of walking and bicycle use. Highlights are:

• A considerable majority of the respondents in the attached developments thought it was easy to get around without a car inside the development and to access recreational facilities. About 50% of the detached households answered similarly.
• Food stores were easily accessible by walking or bicycling according to 42% of attached households as compared to only 4% of detached households.
• Each group answered overwhelmingly (95%) that it was safe to ride a bicycle in the development. However, 57% of the attached households thought it was also safe outside the development compared to only 16% of the detached households.
• In responding to the question if anyone in the household rides a bicycle or walks to the store or a recreational area such as a beach or a park on a regular basis, 47% of attached households indicated they did, compared to only 17% of the detached households. In households with non-drivers, 30% of the respondents said they walked or biked regularly, with 64% of the attached households and only 25% of the detached households answering to the affirmative. This may be a more reliable indicator as to the true convenience of these facilities.

Table 5. Distribution of Answers to Pool/Spa Use Questions
	Total		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Do you own spa/pool
Pool only	115	31.6	2	1.8	113	45.2
Spa only	10	2.7	3	2.6	7	2.8
Both	34	9.3	1	0.9	33	13.2
Neither	205	56.3	108	94.7	97	38.8
Spa/pool heat
Electric heat pump	16	10.4	3	75.0	13	8.7
Gas/propane	40	26.0	0	0	40	26.7
Solar	19	12.3	0	0	19	12.7
None	79	51.3	1	25.0	78	52.0
Spa/pool cover
Yes	44	28.4	3	50.0	41	27.5
No	111	71.6	3	50.0	108	72.5
Spa/pool pump hours per day
3 or less	15	9.8	1	33.3	14	9.3
4 to 6	52	34.0	2	66.7	50	33.3
7 to 9	64	41.8	0	0	64	42.6
10 or more	22	14.4	0	0	22	14.7
Average	7.67		4.00		7.74

Table 6. Transportation Perception and Activities
	Total		Attached	Detached
	#	%
Is it easy to get around without a car
Yes	251	66	89 %	54 %
No	132	34	11 %	46 %
Recreational facilities
Easily accessible	208	55	66 %	49 %
Car necessary	173	45	34 %	51 %
Stores accessible on foot/bicycle
Easily accessible	64	17	42 %	4 %
Car necessary	319	83	58 %	96 %
Is it safe to ride a bicycle in your development
Yes	363	95	95 %	95 %
No	19	5	5 %	5 %
Outside your development
Yes	112	30	57 %	16 %
No	262	70	43 %	84 %
Does anyone in your household ride a bicycle or walk to store or a recreational area (all households)
Yes	102	27	47 %	17 %
No	280	73	53 %	83 %
Does anyone in your household ride a bicycle or walk to store or a recreational area (households with non-drivers)
Yes	25	30.1	63.6 %	25.0 %
No	58	69.9	36.4 %	75.0 %

Table 9 presents characteristics of the households that relate to transportation use and the miles driven. The average total household distance driven for attached dwellings was 15,615 miles, against 23,121 miles per year for the detached units as illustrated in Figure 15. On a per driver basis it was 11,028 miles for attached dwellings and 10,636 miles for detached group (Figure 16). On the basis of automobiles, the total distance driven represented 11,409 miles per car for the attached group and 11,763 miles for the detached households. Thus, on a per driver or per automobile basis the reported mileage was almost equal between attached and detached households.

On a per occupant basis Table 7 shows attached households as driving 10,621 miles per occupant compared to only 9133 for detached households as shown in Figure 17. Because the mileage per driver is almost equal this indicates that there are more non-drivers (young children) in the detached households. A more accurate depiction of driving mileage per occupant is shown in Figure 18. For the same occupancy level, attached households have the same or fewer average miles than detached households, but the differences are not large. Figure 19 demonstrates that as household size increases, miles per occupant decreases, resulting in a lower overall mileage per occupant for the detached households (demographic data on occupants is shown in Table 1).

By comparison, in 1988 the U.S. average household drove 18,595 miles, owned 1.8 vehicles, for 10,246 miles driven per motor vehicle. Per vehicle fuel consumption was 559 gallons and per household vehicle fuel consumption was 1014 gallons with an overall on-road vehicle miles-per-gallon of 18.3. Average occupancy exceeded 2.85 persons per household. These results are based on a national survey with respondents recording odometer readings throughout the year.

Table 8 shows average trip length, frequency of trips and miles per month per household for selected errand-type trips. Trips to shopping malls were made an average of 3.72 times per month, and represented the longest average distance, 10.75 miles. College, home improvement centers, and theater trips were all over eight miles on average, but individually do not represent the miles per month per average household as shopping malls or grocery stores.

Attached households reported average trip lengths that were closer to every listed designation except for recreational/golf trips. The detached households were pre-selected as being part of golf course developments, so this exception is well understood, although all of the attached households have a recreational facility as well. In Table 8, it should be noted that respondents were asked to list the distance and frequency of trips to the designation they visited the most. In many situations a respondent may regularly visit a grocery store twice the distance from home to another grocery store because they perceive better value at that store. Respondents' errand mileage (the sum of all these individual trips) averaged to 474 miles per household per month. Detached households had about twice the errand trip mileage of attached households.

Table 7. Mileage and Household Transportation Characteristics
		Total Respondents		Attached		Detached
Annual Household Mileage	Average # of cars per household	Resp.	%	Resp.	%	Resp.	%
<3,000	1.125	8	2.3	7	6.2	1	0.4
3,000-6,000	1.143	14	4.0	11	9.7	3	1.3
6,001-9,000	1.280	25	7.1	10	8.8	15	6.3
9,001-12,000	1.231	52	14.7	23	20.4	29	12.1
12,001-15,000	1.587	46	13.0	16	14.2	30	12.5
15,001-18,000	1.870	23	6.5	4	3.5	19	7.9
18,001-21,000	1.846	39	11.0	16	14.2	23	9.6
21,001-24,000	2.053	38	10.8	7	6.2	31	12.9
24,001-27,000	2.174	23	6.5	6	5.3	17	7.1
27,001-30,000	2.095	21	5.9	5	4.4	16	6.7
30,001-33,000	2.182	11	3.1	3	2.7	8	3.3
33,001-36,000	2.500	14	4.0	1	0.9	13	5.4
36,001-39,000	2.375	8	2.3	0	0	8	3.3
39,001-42,000	2.286	14	4.0	2	1.8	12	5.0
42,001-45,000	2.500	4	1.1	0	0	4	1.7
45,001-48,000	4.000	1	0.3	0	0	1	0.4
48,001-51,000	2.875	8	2.3	1	0.9	7	2.9
>51,000	3.667	3	0.8	0	0	3	1.3
Total Respondents		353		113		240
		Total Respondents		Attached		Detached
Average annual miles driven		20,718		15,615		23,121
Miles per occupant		9,605		10,621		9,133
Miles per driver		10,761		11,028		10,636
Miles per automobile		11,650		11,409		11,763
Number of automobiles per household		1.81		1.389		2.01
Number of workers per household		1.00		0.95		1.02
Number of drivers* per household		1.98		1.51		2.21
School per household		0.37		0.08		0.52
Average length of trip to school (miles)		6.85		4.60		7.02
*Drivers were assumed to be anyone age 16 or older except for occupants of households that listed zero as car mileage (three elderly households). Any non-drivers age 16 or older that live with drivers are erronously counted as drivers.

Table 8. Errand Trips
	Total Respodents
	Resp.	Trip Length (Miles)	Frequency (Trips/Month)	Miles per House per Month
Grocery Store	375	5.57	8.64	93.99
Drug Store	355	5.64	3.18	33.16
Convenience Store	327	2.02	6.59	22.67
College	131	9.20	6.52	40.93
Restaurant	316	7.06	5.20	60.42
Shopping Mall	354	10.75	3.72	73.73
Place of Worship	269	6.05	4.89	57.53
Recreation/Golf	258	4.78	8.59	55.17
Movies/Theater	285	8.13	2.01	24.26
Laundromat	73	3.45	0.78	1.02
Home Improvement Center	246	8.99	2.36	27.18
Average trip length	6.05 miles
Average miles per month	474
	Attached
	Resp.	Trip Length (Miles)	Frequency (Trips/Month)	Miles per House per Month
Grocery Store	125	3.22	6.95	43.71
Drug Store	115	3.23	2.84	16.48
Convenience Store	107	1.42	6.13	14.55
College	45	6.20	6.71	29.25
Restaurant	102	4.98	5.02	39.84
Shopping Mall	114	7.69	3.37	46.16
Place of Worship	75	4.40	4.35	22.43
Recreation/Golf	71	5.63	6.55	40.91
Movies/Theater	94	6.19	2.09	19.00
Laundromat	31	1.48	1.00	0.71
Home Improvement Center	63	5.73	2.82	15.91
Average trip length	4.36 miles
Average miles per month	289
	Detached
	Resp.	Trip Length (Miles)	Frequency (Trips/Month)	Miles per House per Month
Grocery Store	250	6.75	9.46	124.72
Drug Store	24	6.80	3.34	42.58
Convenience Store	220	2.30	6.80	26.88
College	86	10.77	6.44	46.60
Restaurant	214	8.06	5.28	71.15
Shopping Mall	240	12.20	3.89	88.98
Place of Worship	194	6.69	5.09	51.61
Recreation/Golf	187	4.45	9.34	60.72
Movies/Theater	191	9.08	1.97	26.69
Laundromat	42	4.90	0.66	1.06
Home Improvement Center	183	10.11	2.21	31.94
Average trip length	6.78 miles
Average miles per month	573

Table 9 presents reported work trip characteristics. Distance to work has been grouped although respondents answers were given numerically. On average there is one worker per household, although some households had four workers and many had none. The average length of a trip to work was 16 miles. Only 3.1% lived within one mile of work, possibly the longest distance one would regularly walk. Almost one in four workers lives within five miles of work, possibly the maximum bicycling distance for most people. 37.2% of attached household workers lived within five miles of work whereas only 18.5% of detached household workers lived that close. The average length of a trip to work was 13.9 miles for workers in attached households and 16.9 miles for workers in detached households. Attached household workers went to work 6.0 times per week on average compared to only 5.7 times for detached household workers. Average miles traveled to work and back each week was 8.6% greater for a worker living in a detached household.

Not surprisingly, transport mode choice for work trips was overwhelmingly dominated by use of personal automobiles. Three workers' primary mode was by bicycle, five by walking, and one by bus. Fifteen workers claimed they car-pooled (not one of the provided questionnaire choices). Three hundred sixty-nine of the 386 workers responded that they usually drove to work (some car-poolers may have said both). This represents 95.6% of the workers. Only 2.3% did not use private motor vehicles for their primary mode (4 attached household workers, 5 detached household workers).

Table 10 shows mode choice, mileage and school types for the 139 school children that responded. This data is not divided by attached and detached because only ten school children live in the attached households. None of the school children walk to school as their typical mode choice. One child (from a detached household) bicycles to school. One in three school children take the bus and 66.2% drive or are driven. One respondent wrote that a child is car-pooled (not a provided choice).

Only 25 of the 89 elementary, middle and high school children live within two miles of the school they attend (typical maximum school bicycling distance). However, only one of those school children bicycled. Average mileage is 4.7 to elementary school, 8.2 to middle school and 8.2 to high school. Average mileage to preschool is 7.2 miles, for an overall average of 6.9 miles. Those school trips that are driven are 8.3 miles on average. As with errand trips, school trips may be part of the trip to or back from work for some drivers. Questions regarding combining trips were not posed, nor were questions regarding school type (i.e., private or public).

Table 9. Work Trips
	Total			Attached			Detached
	Workers	%	Frequency	Workers	%	Frequency	Workers	%	Frequency
Work Distance (miles)
0-1	12	3.1	6.18	6	5.0	6.83	6	2.3	5.40
2	22	5.7	6.09	10	10.7	6.20	12	4.5	6.00
3-5	57	14.8	6.05	26	21.5	5.50	31	11.7	6.53
6-10	86	22.3	5.85	29	24.0	6.60	57	21.5	5.42
11-15	85	22.0	5.21	18	14.9	5.44	67	25.3	5.24
16-20	36	9.3	5.20	6	5.0	5.00	30	11.3	5.24
21-25	23	6.0	5.22	8	6.6	6.63	15	5.7	4.47
26-30	13	3.4	5.42	6	5.0	5.00	7	2.6	5.71
>30	52	13.5	6.75	12	9.9	6.75	40	15.1	5.65
Total	386			121			265
Average	15.95 miles		5.79	13.92 miles		6.00	16.88 miles		5.69
Weekly average miles	178.2			167.4			183.2
Weekly average miles if driving	183.1			171.0			188.8

Table 10. School Trips
	School Children	Bus %	Bicycles %	Driven %	Walks %	Other %
Miles to School
Preschool
0-1	2	0 %	0 %	100 %	0 %	0 %
2	9	0 %	0 %	100 %	0 %	0 %
3-5	11	0 %	0 %	100 %	0 %	0 %
6-10	17	0 %	0 %	100 %	0 %	0 %
>10	11	0 %	0 %	100 %	0 %	0 %
Average = 7.16
Elementary
0-1	6	67 %	0 %	33 %	0 %	0 %
2	9	67 %	0 %	33 %	0 %	0 %
3-5	12	67 %	0 %	33 %	0 %	0 %
6-10	8	50 %	0 %	50 %	0 %	0 %
>10	4	0 %	0 %	100 %	0 %	0 %
Average = 4.74
Middle
0-1	1	0 %	100 %	0 %	0 %	0 %
2	2	0 %	0 %	100 %	0 %	0 %
3-5	8	100 %	0 %	0 %	0 %	0 %
6-10	6	100 %	0 %	0 %	0 %	0 %
>10	4	0 %	0 %	100 %	0 %	0 %
Average = 8.19
High
0-1	1	0 %	0 %	100 %	0 %	0 %
2	6	33 %	0 %	50 %	0 %	17 %*
3-5	13	54 %	0 %	46 %	0 %	0 %
6-10	1	0 %	0 %	100 %	0 %	0 %
>10	8	0 %	0 %	100 %	0 %	0 %
Average = 8.17
Total	100.0 %	32.3 %	0.7 %	66.2 %	0 %	0.7 %
Total School Children	139	45	1	92	0	1
Average Mileage	6.85	4.22	2.00	8.28	---	2.00
*Carpool

Figure 20 shows the relationship of average trip lengths for work, errands and school for attached and detached households. In each case, the average trip length was shorter for the attached households. Figure 21 shows the monthly miles contributed by work, errand and school trips for attached and detached households. The detached dwelling occupants drive consistently more miles to school, work and errands each month. Figure 22 shows the proportional relationship of these trips to the overall reported average mileage for attached household residents. Note that about 28% of the mileage is unaccounted for by the questionnaire. Figure 23 shows the same information for the detached households, with 24% remaining undetermined by the questionnaire. There are many trips which respondents may have taken but were not asked to report. In addition to little errands, there could be music lessons for children, weekend and night trips to school, trips to friends and relatives that live locally, trips to artistic or sports events and longer vacation or business trips. In regard to energy use, long distance trips may include air and rail modes. Since air travel is significantly less efficient than driving (particularly if there is more than one person in the automobile), those that travel by air would use more fuel despite having fewer motor vehicle miles.

Actual fuel use was not collected. Makes and models of automobiles were collected and the relationship between distance travelled and estimated fuel consumption of vehicle can be explored by using Environmental Protection Agency miles per gallon figures. However that represents effort is reserved for the future as it does not represent a strong impact on the detached versus attached dwelling development patterns. For all vehicles on Florida's roads in 1990, gasoline mileage may be approximated as 20 miles per gallon.

8.0 Combined Transportation and Electricity Use

In order to estimate differences in total annual energy used for transportation and electricity, certain simplifying assumptions were made:

• an electric power plant efficiency of 33% and transmission losses of 7.5%[13]
• an automobile fuel efficiency of 20 miles per gallon for all vehicles.

The resulting conversions into million Btus of energy are:

10_6Btu_e = kWh * 0.003413/0.305
10_6Btu_t = miles * 0.125/20

For readers more comfortable with metric units, one million Btu's are equal to 1,055 MJ. Only non-seasonal, all-electric households are used for this analysis.

There were 75 attached households and 83 detached households that were non-seasonal, all-electric respondents having answered total mileage questions, and having all year electricity data. Figure 24 illustrates the estimated energy use for each component by household type. Attached households use an average of 177 million Btus total, with 88 million Btus for transportation and 89 million Btus for electricity. By our estimates detached household respondents used 2.4 times as much total energy as attached households. The detached households use an average of 432 million Btus, with 164 million Btus being used for transportation and 268 Btus being used for electricity. The average respondent (of the 158 attached and detached respondents) used 311 million Btus total, 128 million Btus for transportation, and 183 million Btus for electricity.

Electricity and transportation energy use was about equal for the attached households, but electricity use was 63% larger than transportation energy use for the detached households. Over all respondents, the electricity energy use was 43% higher than for transportation.

Figure 25 illustrates total estimated energy use by household size for the attached and detached households. It clearly shows that:

1) as occupancy increases household energy use increases
2) the ratio of energy use to occupants decreases with increasing occupancy
3) detached households consumed 150 to 220 million Btus more than attached households of equal occupancy. This represents 85% to 99% greater energy use.

Because there are more occupants per household in the detached households there is not as much difference on an overall energy-use-per-occupant basis between the two building types. Detached households averaged 145 million Btus per occupant and attached households averaged 120 million Btus per occupant. Thus, energy use per occupant was 20% higher for detached households. In households of equal size, detached households used 21% (4-person) to 99% (1-person) more energy per occupant than attached households. However, only five attached households of more than two occupants are included in the comparison sample. The overall average value was 133 million Btus per occupant.

By way of comparison, in 1988 total per capita energy consumption in Florida was 239 million Btus. Per capita electricity consumption was 116 million Btus. These values include non-residential energy use as well. Residential building energy use is 25.8% of total Florida energy use, and total transportation energy use is 35.8%. Seventy-one percent of transportation energy use is for motor gasoline. Some of this motor gasoline is for commercial uses. If we assume 50% of Florida's transportation energy use is by household vehicles, then 43.7% of the 239 million Btus per person, or 104 million Btus per person should be used as a comparison number to the data in the previous paragraph.

Nationally, 44.5 MBtu's per person are used for household vehicle fuel. Households that are air-conditioned and heated by electricity use 52.5 MBtu's of electricity. Converting this into raw fuel used at the power plant equates to 169.4 MBtu per household or approximately 65 MBtu/person. Therefore, nationally, about 110 MBtu's are consumed per occupant for household electricity and vehicle fuel.

9.0 Water and Landscape Responses

Full analysis of water and landscape responses will be left for a future report. Because water use for most of the attached dwellings is group billed it is difficult to characterize water use to respondents in those categories. Only a few attached households have private yards or gardens.

Table 11 shows the responses to interior water use questions. Although the number of baths (includes showers) per week was significantly higher for the detached households it proved to be slightly smaller on a per occupant basis than attached households. 23% of the attached households had an occasional or more frequently, leaky faucet or running toilet compared to just 8% of the detached households (this may relate to the attached households not being billed directly for water use or unresponsiveness of landlords to such problems).

Table 12 shows the tally of respondents answers to landscaping questions. Highlights of the responses include:

• 88% of respondents never use their lawn for any social or recreational activities.
• The average respondent waters their lawn or garden 11 times per month.
• A slight majority (55.7%) of detached respondents use well water for landscape irrigation.
• 96% of the households have automatic sprinkling systems.
• 98% of respondents use fertilizers, herbicides, or pesticides on their landscape.
• Detached households spend 4.3 hours a week maintaining their yard.
• 49% of attached household respondents thought more than 10% of their landscape was native compared to just 26.6% of detached household respondents.
• 22% of respondests grow fruit, vegetables or both.
  

10.0 Applying Results to New Land Development Design

Certain recommendations can be made directly from the questionnaire results. An energy-efficient development should:

• avoid restrictions calling for minimum floor area
• allow and encourage solar devices for heating swimming pools and spas
• provide community pools as an option instead of individual pools and spas
• allow and encourage the use of clotheslines
• design homes to make use of natural ventilation (this may include allowing screen doors, providing windows front and back in attached dwellings, and implementing noise ordinances)
• provide heat recovery water heater units or other efficient water heating devices
• locate the development near destinations, particularly schools, colleges and places of work.

Table 11. Distribution of Answers on Interior Water Use
	Total		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Low-flow showerheads
Yes	219	59.0	68	55.3	151	60.9
No	152	41.0	55	44.7	97	39.1
Drippy faucet or running toilet
Always	1	0.3	0	0	1	0.4
Frequently	3	0.8	1	0.8	2	0.8
Occasionally	47	12.3	29	22.7	18	7.1
Never	332	86.7	98	76.6	234	91.8
Number of baths
Per household per week average	16.21		11.92		18.35
Per occupant per week average	7.20		7.61		7.00

Table 12. Distribution of Answers on Landscaping and Exterior Water Use
	Total		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Native landscape
0 to 10 %	230	66.7	53	51.0	177	73.4
10 % to 25 %	50	14.5	17	16.3	33	13.7
25 % to 50 %	32	9.3	14	13.5	18	7.5
Over 50 %	33	9.6	20	19.2	13	5.4
Lot size
No lot	16	5.9	15	62.5	1	0.4
Under 1/4 acre	81	29.7	8	33.3	73	29.3
1/4 to 1/2 acre	137	50.2	1	4.2	136	54.6
Over 1/2 acre	39	14.3	0	0	39	15.7
Average hours/week spent maintaining yard	4.14		1.00		4.30
Those that use
Pest control chemicals	223	58.1	10	7.8	213	83.2
Chemical fertilizers	221	57.6	9	7.0	212	82.8
Weed control chemicals	181	47.1	4	3.1	177	69.1
No chemicals	8	2.1	2	1.6	6	2.3
Do you grow
Fruits	36	13.5	2	10.5	34	13.8
Vegetables	8	3.0	0	0	8	3.2
Both	15	5.6	1	5.3	14	5.7
Neither	207	77.8	16	84.2	191	77.3
Water source for yard/garden
City/municipality	115	43.2	9	45.0	106	43.1
Ground water well	147	55.3	10	50.0	137	55.7
Both	4	1.5	1	5.0	3	1.2
Times a month water average	11.0		9.0		11.1
Type of water system
Automatic sprinklers	257	95.9	14	77.8	243	97.2
Manual sprinklers	10	3.7	4	22.2	6	2.4
Both	1	0.4	0	0	1	0.4
Use lawn for social / recreational activities
Yes	32	11.8	1	4.8	31	12.4
No	240	88.2	20	95.2	220	87.6

From a marketing viewpoint many of the respondents answers, including these shown in Table 13 may suggest certain qualities that should be improved upon:

• Reduce grass areas, 88% of lawns do not get used. One option may be a common area instead of many individually maintained areas in detached households. This would result in both maintenance and resource savings. Nineteen percent of respondents said they would like to have a park in the neighborhood.
• Improve local conveniences. Over 20% of respondents liked the convenience of their location the most about their community, and 25% liked it the least. Over 50% wanted a grocery store in the neighborhoood and over 40% wanted a restaurant.
• Offer popular community characteristics such as good facilities, low crime, attractive landscaping, quiet, and well maintained areas.
• Avoid excess traffic, over-development, high cost, and poor construction. These were problems listed by 10% or more of the respondents.
• More social activities and locations for such functions are desirable. Only 10% of respondents listed nice neighbors as the best feature of the community. Twelve percent want a social building in the neighborhood.
• Plan for non-drivers. Results indicate only 25% of detached households with non-drivers had someone who went to a recreational or store on a regular basis by walking or bicycling. Detached respondents also tended to desire more children in the neighborhood (13.6% versus 2.6% wanting fewer children). With only one out of 143 school children getting school and back independently of polluting vehicles, developers should look into possible planned pedestrian/bicycle short-cuts.

Many of these suggestions cannot be easily implemented within most Florida city and county regulations. Areas are zoned separately, not allowing commercial and residential areas nearby, and certainly not within walking distance. Areas are also zoned or deed rstricted based on a minimum square footage (often conditioned-square footage) of floor area of the homes. The state encourages large schools at the expense of having students travel further distances. More small schools would be desirable. Traffic corridors are planned and changed by state, regional, county and city groups. Rarely is the pedestrian or bicyclist given equal consideration.

Table 13. Community Preferences
	Total		Attached		Detached
	Respondents	%	Respondents	%	Respondents	%
Like most about development*
Clean, well maintained	133	37.7	38	32.8	95	40.1
Restrictive	35	9.9	3	2.6	32	13.5
Convenient location	76	21.5	33	28.4	43	18.1
Landscaping, views	117	33.1	40	34.5	77	32.5
Quiet, uncrowded	109	30.9	30	25.9	79	33.3
Safe, low crime	67	19.0	29	25.0	38	16.0
Facilities	83	23.5	31	26.7	52	21.9
Nice neighbors	35	9.9	7	6	28	11.8
Resale value	9	2.5	0	0	9	3.8
Others	7	2.0	2	1.7	5	2.1
Like least about development**
Not convenient	63	25.5	8	9.6	55	33.5
Poor maintained	16	6.5	7	8.4	9	5.5
No trees	19	7.7	6	7.2	13	7.9
Association needs power	20	8.1	10	12.0	10	6.1
Noise, crowd	14	5.7	10	12.0	4	2.4
Bad traffic, no lights	32	13.0	10	12.0	22	13.4
Size too small	5	2.0	5	6.0	0	0
Poor security	14	5.7	6	7.2	8	4.9
Over developed, new	49	19.8	12	14.5	37	22.6
High cost, high rent	29	11.7	13	15.7	16	9.8
Poorly constructed, other	32	13.0	13	15.7	19	11.6
Features you would like to see***
Community swimming pool	17	7.5	4	5.6	13	8.4
Community entertainment/social bldg.	27	11.9	9	12.5	18	11.7
Church/Synagogue or other	14	6.2	3	4.2	11	7.1
Restaurant	93	41.2	27	37.5	66	42.9
Laundromat	4	1.8	0	0	4	2.6
Neighborhood park	43	19.0	18	25.0	25	16.2
More children	24	10.6	3	4.2	21	13.6
Fewer children	9	4.0	5	6.9	4	2.6
Golf course	16	7.1	8	11.1	8	5.2
Tennis courts	15	6.6	3	4.2	12	7.8
Grocery store	122	54.0	25	34.7	97	63.0
Others	44	19.5	17	23.6	27	17.5
Other features you would like (write-ins)
Wide streets	6	1.6	4	3.1	2	0.8
Shopping center	24	6.3	5	3.9	19	7.4
Parking lot	1	0.3	1	0.8	0	0
Fitness, playground	7	1.8	3	2.3	4	1.6
School, others	13	3.4	5	3.9	8	3.1
* More than one response per person, 353 respondents ** More than one response per person, 247 respondents *** More than one response per person, 226 respondents

11.0 Implications for Respondents

The results indicate that respondents may not be fully aware of no-cost, energy saving methods available to them. The most significant of these are:

• Reduce pool pump hours. The respondents reported an average use of 7.67 hours per day. A study done in 1984 indicated that a majority of residents were satisfied with pool pumps only running 3 hours per day. Pump timers can be set to run 1-1/2 hours two times per day, or 1 hour three times a day, so that the skimmer maintains a clean pool surface. Savings of 1,500 to 2,000 kWh ($140 at $.08) have been estimated.
• Thermostat setback behavior. Experiments have shown that setting back thermostats saves energy, yet only 59% of the respondents set back or turn off their air conditioners when they leave their home.
• Water bed heating. By using covers on the water bed, under the sheets, water beds may be kept at lower temperatures, saving energy. By covering the bed with a quilt during the daytime, heat may also be conserved.
• The cost of spa/pool heating. Our analysis indicated large increases in electricity use by heating a pool or spa with a heat pump (6,841 (+-2,505) kWh). At $0.08 an hour this is $547 a year. FSEC is presently measuring pool heat pump energy use in a monitoring project. Solar heating of pools is an economically viable option for Florida residents. Spas should only be heated when needed; timers which pre-heat daily when there is no spa use watste considerable quantities of energy. It is also noteworthy that the effectiveness of all pool and spa heating options are strongly affected by use of nighttime covers; heating without a cover can more than double energy consumption.

12.0 Conclusions

Surveyed detached households used significantly more electricity than attached households. Larger house size (square footage) and greater occupancy in the detached households accounts for most of the differences. The detached households used less electricity on a per square foot per occupant basis than attached households. However part of the result is from decreasing electricity use per square foot per person as occupancy increases. Comparing households with equal number of occupants showed that attached households use about equal amounts of electricity on the basis of floor area and occupancy.

Results indicate electricity use can be reduced by greater levels of occupancy for a given floor area -- exactly the opposite of current demographic trends. For example, less energy would typically be used by having 4 occupants in one household, than to have one household with 3 occupants and one household with one occupant. In terms of development patterns and zoning laws, the results indicate it may be energy conserving to allow households to rent out bedrooms, and to have co-housing arrangements where some appliances, e.g., water heaters and refrigerators, could be shared. Minimum floor area requirements should be eliminated as additional floor area directly relates to greater electricity use.

Monthly electricity use data revealed that detached households had higher electricity use per unit floor area in the cooling and heating seasons but about the same during the swing seasons. The percent change from average monthly electricity use to the peak winter month electricity use was much higher in the detached households than in the attached households.

Detached households drove 48% more miles than attached households, however the differences are largely due to increased occupancy in detached households. As occupancy increases, miles per occupant decreases. Comparing households with equal number of occupants showed that attached households drive slightly fewer miles per year. On a per driver or per automobile basis the reported mileage was almost equal between attached and detached households.

Averaged distances to work, schools and all but one errand trip were shorter for attached households. A large majority of all trips were accomplished by automobile. Less than 1% of school children bicycled or walked to school. Only 27% of the school children live within two miles of the school they attend.

Twice as many attached household workers lived within five miles of work as detached household workers. Average miles traveled to work and back each week was 8.6% greater for a worker living in a detached household. Forty-nine percent of the reported miles driven in attached households were due to work trips, relative to 39% for detached households.

Forty-seven percent of attached households as opposed to 17% of detached households have someone who rides a bicycle or walks to a store or recreational area.

13.0 Further Research and Analysis

The collected data is for a small group of land developments built in the 1980's in central Florida. To generalize conclusions reached in this study, more households need to be analyzed. This might include:

∙ non-responding households in the ten developments;
∙ randomly selected households of all 1980s East-Central Florida residential land developments;
∙ similar households in a larger region of the state or throughout the entire state;
∙ older attached and detached households;
∙ reexamination of the same developments in ten years (e.g., transportation distances may be reduced with time as new commercial areas follow residential development).

A number of questions were raised by our analysis. They include:

∙ How can legal barriers to energy-efficiency, such as separate zoning and minimum square-footages be removed or improved?
∙ How can we encourage bicycling and walking as alternative transportation modes?
∙ What is the social cost of our present car-dependent transportation system on children and others who do not drive?
∙ What quantity of energy do residential heat recovery units (desuperheaters) save? [FSEC is being funded by the Governor's Energy Office through the Department of Community Affairs to investigate]. How would such savings compare to other efficient hot water heating methods?
∙ How much electricity do different pool/spa-heating devices use and what is the impact on the state's total residential energy use?
∙ What are some acceptable alternatives to turfed lawns for households?

14.0 Acknowledgements

FSEC is thankful of the Governor's Energy Office for funding the study and permitting the use of their envelopes for conducting the survey. Questionnaire mailing, receiving and coding was performed by Behavioral Science Research in Coral Gables, Florida, under the direction of Dr. Robert Ladner and Rohit Vaidya. Special thanks to Florida Power and Light, and Florida Power Corporation, for contributing time and effort in obtaining the utility data for each of twelve months for respondents in their territory. Assistance in developing the survey was provided by Larry Maxwell of FSEC. Wanda Dutton of FSEC helped collect water information and type many drafts of the survey and this report. Junaid Alim and Nick Drake of FSEC helped with research, data coding and report preparation.

Check out: Appendix A