7

- i CHAPTER 7 . ENERGY USE ANALYSIS

TABLE OF CONTENTS

7.1 INTRODUCTION

................................ ................................ ................................ ........... 7

- 1
7.2 SURVEY SAMPLES

................................ ................................ ................................ ....... 7

- 2
7.2.1 Sample for Residential Applications

................................ ................................ ............... 7

- 2
7.2.2 Sample for Commercial Applications

................................ ................................ .............. 7

- 3 7.3 ESTIMATES OF ENERGY USE

................................ ................................ .................... 7

- 3 7.3.1 Weather Station Assignment

................................ ................................ ............................ 7

- 5
7.3.2 Baseline Operating Hours

................................ ................................ ................................ 7

- 5
7.3.2.1 Residential Applications

................................ ................................ ................ 7

- 5
7.3.2.2 Commercial Applications

................................ ................................ .............. 7

- 6 7.3.3 Operating Hours at a Higher Efficiency Level

................................ ................................ 7

- 8 7.3.4 Upper Limit on Total Operating Hours

................................ ................................ ........... 7

- 9 7.3.5 Variability in Annual Energy Consumption

................................ ................................ .... 7

- 9 7.3.6 Average Annual Energy Consumption by Efficiency Level

................................ ......... 7

- 11 7.3.7 Estimating Energy Use by Month

................................ ................................ .................. 7

- 11

LIST OF TABLES

Table 7.2.1 RECS 2009 Records Used for Residential Portable AC Sample

......................... 7

- 2 Table 7.2.2 CBECS 2003 Records Used for Commercial Portable AC Sample

.................... 7

- 3 Table 7.3.1 Regression Equations

................................ ................................ ........................... 7

- 8 Table 7.3.2 Portable Air Conditioners: Average Annual Energy Use

................................ .. 7

- 11

LIST OF FIGURES

Figure 7.3.1 Number of Hours that Exceed ANSI/ASHRAE Standard 55 as a Function

of Cooling Degree

- Days

................................ ................................ ...................... 7

- 7 Figure 7.3.2 Range of Annual Energy Use for Portable Air Conditioners in the

Residential Sector

................................ ................................ .............................. 7

- 10 Figure 7.3.3 Range o f Annual Energy Use for Portable Air Conditioners in the

Commercial Sector

................................ ................................ ............................. 7

- 107-1 CHAPTER 7. ENERGY USE ANALYSIS

7.1 INTRODUCTION

When the U.S. Department of Energy (DOE) carries out a life

- cycle cost (LCC) and payback period (PBP ) analysis

, it must determine the operating cost savings consumers will derive from more efficient products

. This chapter describes how DOE ca lculated the annual energy consumption of portable AC s for use in the LCC and PBP analysis, which is described in chapter 8

.

The engineering analysis summarized in c hapter 5 reports portable AC energy use based on the proposed DOE test procedure. The test procedure provides standardized results that help

compare the performance of various units operating under the same conditions

. A unit ’ s u sage in the field , however, will differ from the test procedure results depending on the conditions in which the appliance i s operated. T o establish a reasonable range of real

- world energy consumption for portable AC s in residential applications

, DOE relied largely on data from the Energy Information Administration (EIA) ’ s 200 9 Residential Energy Consumption Survey (RECS 200 9 ). 1 The RECS survey i s a national sample of housing units to collect statistical information on residential energy consumption and expenditures across the nation

, along with data on energy

- related characteristics of the housing units and occupan ts. The EIA constructed
RECS 200 9 , which collected energy

- related data for 12

, 083 housing unit s, to represent the household population of the U nited States.

Although almost all p ortable AC s are used in residences

, a few are use d in commercial settings

. To calculate the energy use patterns of portable AC s in commercial applications, DOE relied largely on data from the EIA ’ s 2003 Commercial Building Energy Consumption Survey (CBECS 2003 )

. 2 The E I A constructed CBECS 2003

, which collected energy

- related data for
5

, 215 buildings

, to represent the commercial building stock in the United States.

Although RECS 2009 and CBECS 2003 collect ed no data on portable AC s, both surveys collect ed data on room air

- conditioners . For this preliminary analysis, DOE assumed that the subsample of users who own and operate room ACs are representative of owners of portable air conditioning units

. The details of each survey samp le are described in the following section s

.7-2

7.2 SURVEY SAMPLES

The following sections describe the data D OE examined to develop an understanding of portable AC usage and energy use in both residential and commercial applications . The data represent window

- or wall

- mounted room ACs, which DOE assumes are used in the same way as are portable ACs

.

7.2.1 Sample for Res idential Applications

DOE assumed that the ownership of a window

- or wall

- mounted AC in RECS 2009 could be used to approximate ownership of a portable AC . DOE selected the subset of RECS 2009 records that met the following criteria

.

 A t least one room AC was present in the household.

 The e nergy consumption of the room AC was greater than zero.

 The capacity of the room AC was less than 14,000 Btu /hr (a cooling capacity comparable to portable ACs as measured by industry test methods)

.

 The room being cooled measured no more than 1

, 000 square feet

.

0 provides details about the RECS 2009 records used to represent portable ACs

. DOE used EIA ’ s weightings for each RECS 2009 household in the sample

. The weightings indicate how frequent ly each household configuration occurs in the general population

. Although the total number of households and portable ACs presented in 0 correspond to room ACs in RECS 2009, DOE believes the weightings associated with each household represent the relative frequency of a household with a potential po rtable AC installation.

0 RECS 2009 Records Used for Residential Portable AC Sample

No. of
Records No. of U.S.

Households Represented million No. of P ortable

ACs Represented million

2

, 378 2 3.2 46.4

S izing charts provided by vendors indicate that portable ACs are intend ed to cool rooms having an area as large as approximately 525 to 600 square feet. 3

, 4 A review of retail websites, however, indicate d portable ACs may be used in rooms as large as 1,000 square feet. DOE assumed 1,000 square feet to be the maximum room size a use r would attempt to cool using a portable AC. In practice, only 60 records in the RECS 2009 sample (about 2 percent) represent rooms between 600 and 1,000 square feet.7-3

7.2.2 Sample for Commercial Appl ications

DOE assumed that the ownership of a window

- or wall

- mounted room AC in CBECS 2003 could be used to approximate ownership of a portable AC

. DOE selected t he subset of CBECS 2003 records that met all of the following criteria

.

 A room AC served as a source of air conditioning. a

 The building was not vacant.

 A room AC was used as the primary equipment to cool at least part of the building.

 The area being cooled measured less than 1

, 000 square feet

.

CBECS 2003 provides the total air conditioned square footage and the fraction of conditioning provided by a room AC for each building record, but it does not provide the number of room AC s in a given building . DOE therefore used the total conditioned square footage to determine its sample

. DOE assumed that a residential room AC would be used only in room s measuring less than 1

, 000 square feet. 0 shows the number of CBECS 200 3 records DOE used in its sample. DOE used EIA ’ s weightings for each CBECS 2003 building in the sample

. The weightings indicate how frequently each building configuration occurs throughout the United
States

.

0 CBECS 2003 Records Used for Commercial Portable AC Sample

No. of
Records No. of U.S. Buildings

Represented million

91 0.12

7.3 ESTIMATES OF ENERGY USE

DOE calculated the annual energy consumption of a portable AC using the following equation

.

PA C ENERGY = ( Total Hours of Use

Year ) × [ ( Capacity × X COOL EER ) ( 1

1000 ) + ( X

Fan × k W

Fan ) + ( X

Stby × k W

stby ) ]

W here:

a Packaged terminal air condition ing (PTAC) systems also could be listed as room AC s, so DOE focused on selecting buildings having only room ACs. A building was considered to have a room AC if it did not have a PTAC type of heating system.7-4

P AC ENERGY = annual energy consumption of portable AC (kWh/year),

Total Hours of Use

Year = number of hours the portable AC is used per year (at > 0 W)

, Capacity = r ated capac ity in Btu/h r as measured by the test procedure for

portable AC s , EER = energy efficiency ratio (Btu/h r /W),
X Cool = fraction of time in cooling mode,
X Fan = f raction of time in fan

- only mode,
X Stby = fractio n of time in standby mode

, k W Fan = power consumption (in kW) of fan

- on ly mode, and k W Stby = power consumption (in kW ) of standby/off mode.

For this preliminary analysis, DOE lacked data on operating hours associated with portable ACs

. To estimate those operating hours, DOE utilized data for room AC s as presented
in its Final Rule for Room Air Conditioner s (2011). 5 Furthermore, DOE made the following assumptions for its energy use analysis

.

 The portable AC was installed according to manufacturer instructions (for example, a dual

- duct unit would have both ducts proper ly installed and insulated).

 The number of operating hours spent in cooling mode for a window

- or wall

- mounted room AC in a RECS household or a CBECS enterprise could be used to approximate the hours a baseline portable AC spends in cooling mode.

 The upper limit of total hours in either cooling or fan

- only mode was estimated assuming that a portable AC would be operated only in months having 5 or more cooling

- degree days that exceed 65 °F.

 For rooms measuring less than 250 square feet, the portable AC setpo int can be reached (the cooling load is constant)

, and operating hours would decrease with a higher

- capacity portable AC.

 For rooms measuring 250 square feet or more, the cooling load could not be met by increasing the capacity of the portable AC and, ther efore, cooling operation would continue until the user turned off the unit. The operating hours spent in cooling mode would remain constant for any portable AC operating at any efficiency level.

 The average capacity at a given efficiency level can be used to re present the full range of capacities at that efficiency level.

CBECS 2003 does not report annual energy consumption of portable air conditioners

, so DOE estimated the energy consumption using (1) variables specific to each building in the sample and (2) data on cooling degree

- days . DOE used the calculation methodology described in its Final Rule for Room AC s (2011)

. 5

An additional factor in DOE ’ s energy use analysis was the square footage of the room the portable AC attempts to cool. In cases where the baseline portable AC adequately meets the cooling load of a room, a higher

- capacity unit will reduce th e hours of operation in cooling7-5

mode. If the baseline unit cannot handle the cooling load, however, field

- metering data indicate the compressor will remain running u ntil a user turns the unit off (Burke, et al.

, 2014 ). 6

Below, DOE describes in greater detail the method used to calculate annual en ergy
consump tion of portable AC s

.

7.3.1 Weather Station Assignment

DOE began by assigning each RECS household or CBECS enterprise that used a room AC to one of the 321 weather stations operated by the National Oceanic and Atmospheric Administration (NOAA). 7 DOE identified the weather station that best matched the heating and cooling degree

- days (CDD) of the RECS 2009 household or the CBECS 2003 building (see appendix 7

- A for more details)

. The weather data were used to constrain the hours of AC operation . In addition, regional energy prices were weighted to summer months , when portable
ACs likely would be used

.

7.3.2 Baseline Operating Hours

This section describes DOE ’ s estimate of operating hours for baseline portable ACs used in both residential and commercial applications.

7.3.2.1 Residential Applications

DOE estimated the number of hours a baseline portable AC operates in cooling mode based on data for room AC s operating in cooling mode. DOE began with the data reported by RECS 2009 on the annual energy consumption ( field energy consumption ) for room air conditioning , referred to as FEC (all) RECS

. The reported end

- use quantities were not based on metering of individual appliances; rather, EIA used a regression technique to estimate how much of each household ’ s total annual electricity consumption was attribut able to each end

- use category. b

RECS 2 009 reports the number of room AC s in each household

. Of all homes that use a

room AC , 3 2 percent have two room AC s , and 20 percent have three or more units

. To estimate the energy consumption of a single room AC

, referred to as FEC RECS

, DOE divided FEC (al l) RECS by the reported number of room AC s. For houses having both central air conditioning and room AC , DOE scaled FEC (all) RECS using a re lative use factor. Although each portable AC in a home may be utilized for a different amount of time , DOE has no way to estimate such differences

.

DOE calculated the annual cooling

- mode operating hours for each portable AC in each residential sample using the following formula based on room AC methodology

.

b The desire to use numerous independent variables without using a large number of interaction terms and the desire to adapt the regression procedures to account for heteroscedastic error terms led EIA to use a nonlinear regr ession technique. For more information, see: http://www.eia.doe.gov/pub/consumption/residential/append_c.pdf

.7-6

Where:

OH = o per ating hours per year

, FEC RECS = estimated field energy consumption for the room AC

, EER RECS = estimated EER of the room AC

, Ca pacity = capacity of the room AC in Btu/h r , BldgShellAdj = adjustment for building shell efficiency in 201 9 (%)

, and CDDAdj = adjustment for coolin g degree days ( Btu/h r )

.

The derivation of FEC RECS was discussed above. The capacity of the room AC is given by the representative product class analyzed in the Room AC Final Rule (2011)

. 5 So that the estimated operating hours c ould represent future conditions, DOE used the 2019 building shell index factor of 0.97 for space cooling in all residences from the EIA ’ s Annual Energy Outlook
201 4. 8 DOE also used the 115

- year historical average cooling degree

- days ( CDD ) by census division. Applying t he building shell index factor decreased energy use by 3 percent ; the CDD adjustment factor decreased energy use by 10 percent on average.

DOE estimated the EER of the room AC in each sample household by matc hing the reported age of the unit with the average EER for the reported product class in the year of its vintage

. DOE assumed a uniform distribution within each vintage bin

, and assigned an age to the

room AC in each RECS 2009 household

. DOE calculated scalars for each year based on the ratio of the total shipment s

- weighted EER for that year to the calculated EER, then applied th os e scalars to the minimum efficien cy required in each year

.

Based on an initial analysis of field

- metering data, DOE assumed that hours of portable AC operation in f

an

- only mode were 30 percent of hours spent in cooling mode. 6 The sum of the cooling

- mode and fan

- only mode hours of operation give the total hours a portable AC is in use

. The estimated mean operating hours for a portable AC is 586 in co oling mode and 176 in fan

only mod e , f

or 762 total operating hours

.

7.3.2.2 Commercial Applications

DOE calculat ed annual operating hours for portable ACs in the commercial sector using the method presented in the Room AC Final Rule (2011). 5 DOE calculated the annual operating hours for each commercial

- sector portable AC in its sample by establishing a relationship between CDD and operating hours for various combinations of building type and building schedule. DOE assumed that a portable AC is operated when outdoor air conditions exceed the comfort zone described by ANSI/ASHRAE Standard 55

- 2004. 9 To estimate how often those outdoor conditions are exceeded , DO E us ed the following equation

.

OH 55 = (a * CDD) + b7-7

Where:

OH 55 = a verage annual hours when outdo or air conditions exceed the ASHRAE Standard 55 comfort zone

, CDD = number of annual cooling d egree

- days ( in excess of 65 ° F) for a given

location , and

a and b = linear fit parameters.

DOE used data on CDDs from the National Solar Radiation Database (NSRDB) for 1991

– 2010

. 10 This data base is an hourly ground

- based set of solar and meteorological fields for
1

, 45 4 stations (see appendix 7

- B for more details)

. There is a complete 15

- year for 8 58 of the 1,454 s tations . After removing the NSRDB sites in Hawaii, Guam, and the Caribbean islands, DOE performed regressions to predict the hours per year that exceed ASHRAE Standard 55 based on the number of CDDs for each year. The data points and regre ssion lines are shown in Figure 7.3.1 for all hours of the year. Each data point represent s 15 years ’ of data for 842
NSRDB sites in the continental United States.

Figure 7.3.1 Number of Hours that Exceed ANSI/ASHRAE

Standard 55 as a Function of Cooling Degree

- Days

As Figure 7.3.1 illustrates , the data patterns differ for desert locations

, where humidity does not affect comfort. The regression equations developed from the data are presented in 0

.7-8

0 Regression Equations Region E quation R 2 No. of S ites
Non

- desert OH55 = 2.759 x CLDD + 127.99 0.9224 809
Desert OH55 = 1.153 x CLDD + 574.04 0.8714 33

For a given location, t he annual number of hours that exceed the ASHR AE Standard 55 comfort zone varies by building schedule , which indicates the time that a building is open or in

use

. DOE performed the regression for many combinations of building type and schedule

, yielding somewhat different equations for each combination

. The building types included were

a ssembly, education, food s ervice, office, retail, and warehouse

. For e ach building type , DOE estimated operating hours for the following schedule s : (1) open 24 hours a day and 7 days a week; (2) open business hours Monday through Friday; (3) open business hours Monday through
Satur day; (4) open business hours Monday through Friday and Sunday; (5) open business hours all week. Each schedule yielded a variation of the above equations

.

To estimate the operating hours of room ACs for each building in the CBECS 2003 sample having a room AC , DOE identified the building type and schedule using information provided by CBECS

, then used the appropriate equation (non

- desert or desert) combined with the number of CDDs for the location of the building

. DOE used a scaling fact or to adjust the result s to account for the difference between the number of building operating hours assumed for deriving the equations and the building operating hours reported by the CBECS 2003

.

The above approach provide s a ‘ best guess ’ of the operating hours for the portable AC in a particular CBECS building

. O perating hours are affected by some factors not included in the analysis, however, such as interior heat gains from equipment or people and solar gains . To develop a range for the number of operating hours for the portable AC in each sample building

, DOE added an error band to the value derived using a regression equation. The error band includes values that are ± 10 percent from the regression line for the appropriate combination of build ing type and schedule. Operating hours for portable ACs in t he commercial sector were estimated based on the cooling climate in 2003. To match the 115

- year average CDD values, DOE decreased the estimated operating hours in the commercial sector by 2 percent on average.

Based on an initial analysis of field

- metering data , hours of operation of portable ACs in
f an

- only mode were assumed to be 30 percent of the hours of operation in cooling mode ( Burke et al. )

. 6 DOE calculated t he mean number of operating hours as 1,3 8 8 in cooling mode and 400 in fan

- mode only , for a total of 1,7 88 operating hours

.

7.3.3 Operating Hours at a Higher Efficiency Level

DOE determined that a portable AC ’ s operating hours by mode at a higher efficiency level will depend on whether the baseline portable AC adequately cools the room in which it is located . If the baseline portable AC does not meet the cooli ng demand of the room, a higher

capacity portable AC will not reduce the hours spent in cooling mode. A study conducted by Consumer Report s 11 found that portable ACs tested in a 250

- square

- foot room labored to provide adequate cooling. Based on th at study

, DOE assumed that households using a higher

- efficiency7-9

(and thus higher

- capacity) portable AC in a room measuring less than 250 square feet would experience a reduction in hours of operation in cooling mode, assuming a fixed cooling load. In areas that meas ure 250 square feet or more , the hours spent in each mode would not change at any efficiency level , because no portable AC could cool the room adequately.

In cases where a baseline portable AC is cooling a space adequately ( i.e. , installations in

rooms smaller than 250 square feet) , DOE assumed that a higher

- capacity unit would operate in cooling mode for a reduced number of hours based on the ratios of cooling capacity:

O H Cooling

, STD = O H Cooling

, BASE ( Capacit y BASE Capacit y

STD )

The hours of operation not spent in cooling mode were assigned to fan

- only mode :

O H Fan mode

, STD = O H Fan mode

, BASE + ( O H Cooling

, BASE − O H Cooling

, STD )

In cases where a baseline portab le AC cannot cool a room adequately ( i.e. , installations in

rooms measuring 250 square feet or more ) , DOE assumed that the hours of operation in all modes would remain the same no matter the capacity of the portable AC

.

7.3.4 Upper Limit on Total Operating Hours

The climate data obtained from NOAA ’ s National Climatic Data Center helped DOE determine the maximum amount of time a portable AC would be operated annually . The data also helped DOE apportion the annual electricity use for porta ble ACs operating in various geographic areas among the months of the year. DOE assumed that a portable AC would be operated only in months having 5 or more cooling

- degree days that exceed 65 °F. DOE confirmed that the calculated combined hours of operatio n in cooling and fan

- only mode were less than the upper limit derived from months having 5 or more CDDs

. In cases where the hours of operation exceeded the upper limit, DOE set the hours of operation equal to the upper limit.

7.3.5 Variability in Annual Energy C onsumption

Error! Reference source not found. and Figure 7.3.3 sh ow the range of average annual energy consumption by efficiency level for portable ACs within DOE ’ s residential and commercial samples. In the figures, the blue box represents values within 25 percent to 75 percent of the distribution

, and the " whiskers " extend from 5 percent to 95 percent of the distribution. The red line indicates the median value

, and the red circle indicates the average. The figures illustrate the greater utilization of portable AC s in the commercial sector.7-10 Figure 7.3.2 Range of Annua l Energy Use for Portable Air

Conditioners in the Residential Sector

Figure 7.3.3 Range of Ann ual Energy Use for Portable Air

Conditioner s in the Commercial Sector7-11

7.3.6 Average Annual Energy Consumption by Efficiency Level

0 show s the efficiency levels of baseline portable ACs and the levels DOE is conside ring for potential standards. The considered efficiency levels are in terms of cooling energy e fficiency ratio (EER cm )

. Also shown are the corresponding average annual energy consumption s calculated for both the residential and commercial sector s

.

0 Portable Air Conditioner s : Average Annual Energy Use

E fficiency
Level Efficiency

EER cm Residential

Sector kWh Commercial

Sector kWh

Baseline 2.08 724 1,713

1 3.53 525 1,411

2 4.32 473 1,330

3 5.28 434 1,274

4 5.82 400 1,173

7.3.7 Estimating Energy Use by Month

Portable AC use occurs primarily in the warm months of the year. In conducting the LCC analysis for portable AC s (see chapter 8), DOE used monthly electricity prices because electricity tariffs show seasonal variation in many areas of the country. Therefore, to properly calculate operating costs for portable AC s , DOE needed to estimate how the annual portable AC ele ctricity use for each sample household or business is apportioned over the year.

To estimate portable AC ele ctricity use by month, DOE utilized data on seasonal climate variation , as measured by cooling degree

- days . RECS 2009 provides data on yearly heat ing and cooling degree

- days for each household in the sample, but does not break down the information by month. To estimate monthly CDDs for the households in the RECS sample, DOE match ed each household with the NOAA weather station that had the most simil ar climate based on cooling and heating degree

- days . After matching a household to a weather station, DOE utilized the monthly CDD data from the weather station to estimate the relative number of cooling

degree days by month (see appendix 7

- B for more details ). DOE divided the number of cooling

degree days in each month by the total number of CDDs in the year for that weather station. DOE assumed that each month ’ s percentage of cooling

- degree days reflect s the appropriate weigh t ing of electricity usage and price for that month

.7-12

REFERENCES

1 U.S. Department of Energy

– Energy Information Administration

. Residential Energy Consumption Survey:2009 RECS Survey Data

. 2009. (Last accessed September 8, 2014.)

< http://www.eia.gov/consumption/residential/data/2009/ >

2 U.S. Department of En ergy

– Energy Information Administration

. Commercial Buildings Energy Consumption Survey

. 2003. (Last accessed September 8, 2014.)

< http://www.eia.gov/consumption/commercial/data/2003/ >

3 Air & Water, the Portable Appliance Experts. What Size Portable Air Conditioner do You Need? (Last accessed September 8 , 2014. ) < http://www.air

- n

- water.com/portable

- ac

size.htm >

.

4 The Ho me Depot. (Last accessed September 3, 2014 .)

< http://www.homedepot.com/c/air_conditioners_HT_BG_AP >

.

5 U.S. Department of Energy

– Office of Energy Efficiency and Renewable Energy. Energy Conservation Program for Consumer Products: Energy Conservation Standards for Clothes Dryers and Room Air Conditioners; Final Rule. 10 CFR Part 430

. Federal Registe r. August 19, 2011. Vol. 76

, n o. 16 4: pp. 52854

– 52862. (Last accessed September 8, 20 14.) < http://www.regulations.gov/#!documentDetail;D=EERE

- 2007

- BT

- STD

- 0010

- 0067 >

.

6 T. Burke, et al. , Using Field

- Metered Data to Quantify Annual Energy Use of P ortable Air Conditioners, Lawrence Berkeley National Laboratory, Report No. LBNL

- 6868E (December 2014). Available at: < www.osti.gov/scitech/servlets/purl/1166989 >

.

7 NOAA Data. National Climatic Data Center (NCDC). < http://www.ncdc.noaa.gov/data

access/land

- based

- station

- data/land

- based

- datasets/quality

- controlled

- local

climatological

- data

- qclcd>.

8 Energy Information Administration. Annual Energy Outlook 2014 with P rojections to 2014 . Building Shell Index Factor. April 2014

.

9 American National Standards Institute & American Society of Heating, Refrigeration, and Air

- Conditioning Engineers, Inc. ANSI/ASHRAE 55

- 2004 Thermal Environmental Conditions for Human Occupancy . 2004

.

10 National Renewable Energy Laboratory

. National Solar Radiation Database 1991

– 2005 Update: User’s Manual

. 2007. < http://www.nrel.gov/docs/fy07osti/41364.pdf >

.

11 Consumer Rep orts. Are Portable Air Conditioner Claims a Lot of Hot Air? Published online June 12, 2014. (Last accessed June 12, August 31, 2014.)

< http://www.consumerreports.org/cro/news/2014/06/are

- portableair

- conditioner

- claims

a

- lot

- of

- hot

- air/index.htm >.