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Thermal and health outcomes of energy efficiency retrofits of homes of older adults

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Indoor Air
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Mitigation of thermal stress and adverse indoor climatic conditions is important to older low-income populations whose age, health, and economic circumstances make them vulnerable to indoor environmental conditions. This research examines whether energy retrofits in affordable housing for older adults can also improve indoor climatic (i.e. temperature, humidity, air infiltration) conditions; and whether such improvements correspond with improved health and comfort of residents. An apartment complex for low-income older adults in Phoenix was the study site. In 2010, renovations were undertaken to make it more energy efficient and to replace interior cabinetry, flooring, and paint with materials that had low or no volatile organize compounds (VOCs). Fifty-seven residents from 53 apartment units participated in both baseline (pre-renovation) and one-year post-renovation data collection trials. Environmental measures included temperature, relative humidity, and air infiltration. Health measures included general health, emotional distress, and sleep. Four questions addressed residents' perceptions of temperature quality. Results demonstrated a 19% reduction in energy consumption following the retrofit. In addition, fixed effects statistical models of the panel data showed significant stabilization of unit temperature from pre-retrofit to one year post-retrofit. Reductions in an apartment's temperature extremes of 27.2°C (81°F) and above also corresponded with improvement in occupant's reported health over the same time period, although not with occupant's perceptions of thermal comfort. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Thermal and health outcomes of energy efficiency retrofits of
homes of older adults
Abstract Mitigation of thermal stress and adverse indoor climatic conditions
is important to older low-income populations whose age, health, and
economic circumstances make them vulnerable to indoor environmental
conditions. This research examines whether energy retrofits in affordable
housing for older adults can also improve indoor climatic (i.e., temperature,
humidity, air infiltration) conditions and whether such improvements
correspond with improved health and comfort of residents. An apartment
complex for low-income older adults in Phoenix was the study site. In 2010,
renovations were undertaken to make it more energy efficient and to replace
interior cabinetry, flooring, and paint with materials that had low or no
volatile organic compounds (VOCs). Fifty-seven residents from 53
apartment units participated in both baseline (pre-renovation) and 1 year
post-renovation data collection trials. Environmental measures included
temperature, relative humidity, and air infiltration. Health measures
included general health, emotional distress, and sleep. Four questions
addressed residents’ perceptions of temperature quality. Results
demonstrated a 19% reduction in energy consumption following the retrofit.
In addition, fixed effects statistical models of the panel data showed
significant stabilization of unit temperature from pre-retrofit to 1 year post-
retrofit. Reductions in an apartment’s temperature extremes of 27.2°C
(81°F) and above also corresponded with improvement in occupant’s
reported health over the same time period, although not with occupant’s
perceptions of thermal comfort.
S. Ahrentzen
1
, J. Erickson
2
,
E. Fonseca
3
1
Shimberg Center for Housing Studies, University of
Florida, Gainesville, FL, USA,
2
Arizona State University,
Tempe, AZ, USA,
3
The Elemental Group, Phoenix, AZ,
USA
Key words: Indoor temperature; Older adults; Retrofit;
Health; Indoor environmental quality.
S. Ahrentzen
Shimberg Center for Housing Studies, University of
Florida, PO Box 115703, Gainesville
FL 32511-5703, USA
Tel.: +1 (352) 273-1229
Fax: +1 (352) 392-4364
e-mail: ahrentzen@ufl.edu
Received for review 8 July 2014. Accepted for
publication 31 July 2015.
Practical Implications
To date, ventilation, insulation, materials, and mechanical systems in senior housing have been designed and con-
structed with present standards and climatic conditions in mind to assure occupant comfort and operational efficiency.
With climate changes imminent, older buildings may need sufficient retrofitting not only for mitigating increases in
energy consumption but also to maintain suitable indoor environmental quality conditions. The results of this study
argue for the need to rethink and revise indoor environmental conditions and technologies particularly those affect-
ing indoor temperature to enhance not only energy efficiency but also health conditions of older adults as they age
in place.
Introduction
The environmental challenge of climate change has
spurred engineers, architects, and the construction
industry to rethink conventional building practices
and energy sources. The soaring growth of an aging
population in the USA has likewise fostered con-
cern among planners and policy officials in health-
care management to reconsider the health aspects
of residential living (Federal Interagency Forum on
Aging Related Statistics, 2010). Only recently have
building and healthcare professionals begun to con-
sider the consequences of the coincidence of these
environmental and demographic projections (e.g.,
Calthorpe, 2011).
While much of the building research on climate
change has focused on carbon emissions and energy
efficiency responses, recent attention has been paid to
how climate change may degrade indoor environmen-
tal quality (IEQ), including the thermal environment of
buildings (e.g., Institute of Medicine, 2011). Mitigation
of thermal stress and other climatic conditions inside
homes is important to older low-income populations
whose age, health, and economic circumstances make
them vulnerable to environmental conditions. As older
adults spend between 80% and 90% of their time in
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Indoor Air 2016; 26: 582–593 ©2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
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doi:10.1111/ina.12239
their homes (Klepeis et al., 2001), indoor thermal con-
ditions are contributors to their health and well-being.
Design and building interventions implemented in
places that currently experience extreme temperatures
provide opportunities to assess thermal impact on
occupants’ health and comfort by examining how such
retrofits affect indoor climate conditions in homes and
consequently occupants’ health and well-being. The
research questions we pose in this article are as follows:
Can energy retrofits in affordable housing for older
adults also improve indoor climatic (i.e., tempera-
ture, humidity, airflow) conditions?
Do such improvements in one’s home correspond
with improved health and comfort of its residents?
We examine these questions by drawing on data
from a larger study that focused on health and IEQ
changes resulting from a green retrofit of an apartment
complex for low-income older adults in Phoenix, Ari-
zona (Ahrentzen et al., 2013; Frey et al., 2015). The
panel study gathered data before and after the retrofit
on the same residential units and occupants, providing
the opportunity to look at changes over time.
Before addressing these research questions, we
review the research literature to examine how physio-
logical and behavioral conditions of older adults are
particularly susceptible to thermal, airflow, and relative
humidity (RH) conditions. As age parameters of what
constitutes ‘older adults’ vary by country and by indus-
try (e.g., medical, economic security) and over time, we
included studies that self-defined their samples as
‘older adults’ within the context of their industry and
country. For the most part, these samples did not
include anyone under 60 years of age; and the most
common age filter was 65 years and above.
Given that our research study is located in Phoenix,
Arizona, our review of the research focused on extre-
mely hot and dry conditions. In this article, we primar-
ily use the term ‘older adults’ following the
nomenclature of the Older Americans Act of 1965, but
other terms regularly used in the literature include
elderly, seniors, and aged.
Literature review: aging, health, and indoor thermal conditions
The rapid aging of the population in the United States
and many other developed countries has been likened
to a crisis, a silver tsunami, and other catastrophic
Armageddons. By 2030, an estimated 72 million Amer-
icans, representing 20% of the US population, will be
over the age of 64 (Federal Interagency, 2010). These
large numbers alone are not the cause for concern.
Rather, the impending challenge involves the many
buildings, transportation and land-use patterns, financ-
ing arrangements, and social and healthcare programs
that currently exist but were never designed or con-
structed with older populations in mind.
The homes in which older adults live are central to
how they live their lives. As noted previously, older
adults spend between 80% and 90% of their day inside
in their residences. Consequently, they are particularly
susceptible to effects of detrimental indoor environ-
mental conditions and hazards because of greater
exposure as well as declining physiological capacities.
But compared to research on children and families, rel-
atively little research has examined adverse health
effects facing this population from potential environ-
mental exposures and hazards in the residential envi-
ronments where they live. One exception is the field of
thermal comfort and stress (e.g., Novieto and Zhang,
2010).
Older adults are more prone to temperature-related
illnesses. In some cases, extreme temperatures can be
deadly. According to Basu and Samet (2002), an aver-
age of 274 Americans are direct victims of heat-related
mortality each year, with the highest death rates
among those older than 65. But while heat-related
deaths make news headlines, higher temperatures can
also have non-fatal health consequences, such as
hyperthermia, heat stroke, heat edema, and stress.
Coping with extreme thermal conditions, particularly
over long periods of time, involves complex physiologi-
cal arousal marked by changes in blood pressure, respi-
ration rates, skin conductance, cardiac output, and
heart rate, as well as task performance and emotional
and affective behavior (Bell and Greene, 1984; Evans
and Cohen, 1987). Heat-related illnesses and symptoms
can be exacerbated by dehydration and fatigue. Sleep
onset and disruptions can also be a consequence of
thermal conditions, with health impacts for older
adults (Alapin et al., 2000; Floyd et al., 2000).
A number of physiological aspects of normal aging
make it difficult for older adults to cope with tempera-
ture extremes and fluctuations. As the body’s primary
communication relay system between the brain and
other organs and extremities, the peripheral nervous
system begins to deteriorate as one grows older. As a
consequence, thermoregulation slows, delaying neural
messages informing the body to feel hot and cold and
how to cope by adjusting heart rate, vasodilating, and
sweating. Age-related changes in autonomic and
behavioral thermoregulation occur under both extreme
and non-extreme thermal circumstances (Van Som-
eren, 2006).
In addition, core body temperatures decrease with
age. Medical and physiological studies in natural built
settings (i.e., not laboratory chambers) have found that
older adults generally have mean oral body tempera-
tures lower than the conventional 37°C (98.6°F) (Go-
molin et al., 2005; Havenith, 2001; van Hoof and
Hensen, 2006; Tochihara et al., 1993).
As a result of these physiological changes of aging, air
and room temperature changes especially temperature
swings and fluctuations in short periods of time affect
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Thermal and health outcomes of energy retrofits
older adults disproportionately (Gomolin et al., 2005;
Havenith, 2001; Novieto and Zhang, 2010). Turnquist
and Volmer (1980) found an optimal indoor tempera-
ture for older adults of 25.3°C(77.5°F), much higher
than the optimal temperature of 24.4°C(76°F) that
ASHRAE-55 2010 recommends for summer season.
Their study was one of the first that examined indoor
thermal preferences of older adults in a housing project,
asking them to rate their thermal satisfaction. Novieto
and Zhang (2010) suggest that as older adults have
lower core body temperatures, they prefer and need
more insulation or warmer and more stable indoor envi-
ronments. In a series of laboratory experiments and
mail questionnaires, Rohles and Johnson (1972) con-
cluded that mean preferred temperatures of older adults
were one-half degree higher than the middle-age group
(23.8 and 23.2°C, respectively) and the latter mean pref-
erence was identical to that expressed by college-age
adults. Differences were also noticeable when comparing
modal values: Modal temperature preference of college-
age adults, middle-age respondents, and older adults
was 22.2, 23.3, and 24.4°C, respectively.
While the number of sweat glands does not decrease
with age, sweat production does, making it more chal-
lenging to reduce the body’s core temperature (Verd
u
et al., 2000). Other chronic health conditions associ-
ated with aging such as diabetes, cardiovascular dis-
ease, chronic obstructive pulmonary disease,
hypertension increase the risk factor for heat stroke
and other adverse heat symptoms (Basu and Samet,
2002; Dematte et al., 1998; Kenney and Munce, 2003;
Kenny et al., 2010; Khalaj et al., 2010). Also common
among many older adults, hypertension may reduce
blood flow to the dermis, weakening temperature regu-
lation by reducing heat transfer from core to the skin
(Carberry et al., 1992; Kenny et al., 2010). Cardiovas-
cular diseases, like other diseases that disrupt cardio-
vascular flow, impair body-temperature regulation.
In addition to physiological conditions, many older
adults are taking medications that may adversely affect
body thermoregulation. Psychotropic drugs are associ-
ated with increased hospitalization due to hyperther-
mia among older adults (Lopez and Goldoftas, 2009).
Nonsteroidal anti-inflammatory drugs taken for
myocardial infarction prevention block prostaglandins
that help control body temperature and blood pressure
(Carmichael and Shankel, 1985). Other common medi-
cations that affect thermoregulation are noted in
Kenney and Munce (2003).
Older adults also tend to be less physically active as
they age, suggesting that any activity they perform
becomes more stressful, producing more strain on the
cardiovascular system and leaving less cardiovascular
reserve. The latter is especially relevant for effective
thermoregulation as it determines the capacity to move
heat for dissipation from the body core to the skin by
skin blood flow (Havenith, 2001).
In addition to temperature, another indoor thermal
condition affecting health is RH. Much health atten-
tion is paid to high RH as it induces conditions that
foster mold, allergens, and dust-mites. For our study in
Phoenix, low RH levels were more typical and poten-
tially problematic than high levels. Low levels can pro-
duce dry noses and throats that make people more
susceptible to upper respiratory illnesses; low levels can
also facilitate skin dryness and irritation (Sunwoo
et al., 2006; Wolkoff and Kjærgaard, 2007). Wolkoff
and Kjærgaard (2007) suggest a 10% change of RH
from 30% to 40% is better for occupant health in the
indoor environment. D
ıaz et al. (2002) found that low
RH can exacerbate adverse health effects of older occu-
pants who have difficulty with thermoregulation.
ASHRAE has developed statistically based thermal
comfort standards derived from laboratory and field
data for healthy adults under stable indoor environ-
mental conditions (ASHRAE 55-2010), which means
that thermal variability should be minimal for these
existing standards to accurately predict occupant ther-
mal comfort. ASHRAE 55-2010 recommends a mini-
mum of 20°C(68°F) during the winter, and a minimum
of 24.4°C(76°F) and maximum of 27.2°C(81°F) during
the summer for all buildings with human occupancy.
However, ASHRAE acknowledges the limitations of
Standard-55 2010, stating that available ‘...data does
not contain significant information regarding comfort
requirements of children, the disabled or the infirmed’
(p. 4), and that the standard does not apply ‘to sleeping
or bed rest’ (p. 4) conditions, or levels above sedentary
or near-sedentary activity (ASHRAE 55-2010).
Nonetheless, while some researchers such as
Havenith (2001) call for standards or temperature pre-
dictors targeted specifically for older adults, no stan-
dard-setting agency has established thermal standards
targeted towards this older, community-dwelling popu-
lation, a large proportion who spend their days in
sedentary behavior. Given the lack of an alternative
indoor thermal standard or threshold for older adults,
we used ASHRAE 55-2010 standards in our hypothe-
ses and analyses.
Hypotheses
Based on the existing research on thermophysiological
conditions and related behaviors of older adults, we
examined the following four hypotheses in this study:
1. Energy retrofits will result in reduced energy con-
sumption of the building overall
2. Energy retrofits will result in improvements in
indoor climate stabilization of residents’ apartments
3. Improved thermal stabilization of a resident’s apart-
ment will correspond with improved reported health
conditions of that resident, particularly of sleep,
emotional health, and general health/quality of life
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Ahrentzen et al.
4. Improved thermal stabilization of a resident’s apart-
ment will correspond with greater thermal comfort
expressed by that resident
Methods
Research context and site
This study was conducted at an apartment complex,
operated by the City of Phoenix Housing Department,
for older adults who qualify for subsidized rent (HUD
Section 8 Housing Choice Voucher program). The
apartment complex is a three-story, 116-unit building
completed in 1970. The one-bedroom apartment units
were all the same size (57.5 m
2
) and configuration, with
the living room and bedroom having outdoor views.
Kitchens and bathrooms were located towards the core
of the building, sharing a common wall with the build-
ing’s double-loaded corridor.
The apartment complex was selected as the research
site due to funding from the US Department of Hous-
ing and Urban Development (HUD) and plans by the
city of Phoenix for a green retrofit of the 40-year-old
building. The project schedule and funding provided
researchers the opportunity to conduct a longitudinal
study of multiple panels of data collection of resident
health, perceptions, and behaviors as well as environ-
mental/air quality (including temperature, humidity,
aldehydes, particulate matter, air infiltration). The
methods and data collection and analyses described
below focus only on those aspects of the larger study
relevant to the hypotheses in this article. For a descrip-
tion of the larger study, see Ahrentzen et al. (2013).
Green retrofit
The retrofit included both cosmetic and major renova-
tion work. Major renovations included roof upgrades
(insulation, primer, coating); upgrades and replace-
ment of each apartment’s packaged thermal air condi-
tioner (PTAC) heating and cooling units in
apartments; entire kitchen and bathroom remodel; new
ceiling fans in apartments; window replacements (low-
E coated, double pane); new flooring, paint, and cabi-
netry containing low or no volatile organic compounds
(VOC); and updates to bathrooms and kitchens in a
few units to meet the Americans with Disabilities Act
(ADA) requirements. Examples of renovations are
shown in Figures 1 and 2. It took 6 months to reno-
vate all residents’ units. Further information about the
renovation process is described in Frey et al. (2015)
and Ahrentzen et al. (2013).
Research design and methodology
Given the nature of this study, this research utilized a
one-group panel research design. We collected data
from the same residents and apartment units once
before the renovation (referred to as Panel 1, or P1, or
baseline) and twice after the renovation was completed
(panels 2 and 3, or P2 and P3). The second panel
occurred approximately 3 months after a resident’s
apartment had been renovated. Data from the second
panel are not reported here as the brief amount of time
of occupancy in the renovated home (approximately
3 months) may be a notable confounding factor (i.e.,
novelty), with residents not adjusting yet to their sub-
stantially renovated homes. The third panel (P3) of
data collection occurred approximately a year after the
retrofit, a substantial period of time for residents to
make such adjustments and become more familiar with
their new home conditions.
Lacking a control or comparison group because of
time and funding restrictions in locating a similar resi-
dential complex undergoing a ‘non-green’ retrofit,
potential confounding variables were minimized using
a panel design (also known as repeated-measures
design). Two key features of panel studies are that they
collect repeated measures from the same individual
units in a sample at different points in time and that
they measure change over time for the unit of analysis.
In this case, the unit of analysis is the apartment unit
and resident. Each unit’s data point or response score
at the baseline panel is compared to the same individ-
ual’s data point or score at the subsequent panel(s).
Panel studies thus control for invariant personal/indi-
vidual variables such as clothing, gender, body mass
index (factors that may influence one’s thermal com-
fort, for example) as they are stable or non-changing
for an individual over time (a person’s gender, for
example, does not change from baseline to subsequent
panel). Thus, it accounts for individual heterogeneity.
Sample size and characteristics
While 77 residents from 74 units participated in the
baseline (P1) panel, attrition occurred during the
course of the study. Attrition was largely due to resi-
dents moving or death. For data analyses of a panel
study, only data from those residents who participated
in baseline (i.e., P1) and final (P3) data collection pan-
els were used. This comprised 57 residents from
53 units.
The participants included older adults from diverse
ethnic backgrounds who all qualified for housing assis-
tance. The mean age was 73, and ranged from 62 to 92.
Eighty-eight percent lived alone, 21% smoked, and
74% were female.
Data collection
Data collection in each panel consisted of interviews of
residents and temperature, humidity, and air infiltra-
tion testing of all residents’ apartment units. Research
585
Thermal and health outcomes of energy retrofits
technicians/assistants collected the following data at
each panel:
Absolute air temperature was monitored and
recorded every 15 min in the kitchen, bedroom, and
living area, utilizing mobile Onset HOBO data log-
gers, over a 5-day period. One of the three HOBOs
(located in the living room) also monitored RH in
addition to air temperature. Onset HOBO data log-
gers U10-001 and U10-003 are very accurate with a
margin of accuracy of 0.21°C(0.38°F).
Blower door tests for measuring air infiltration at 50
pascals pressure (CFM50) (liters per minute at 50
pascals of pressure)
Resident-reported health conditions from interviews
with the resident at his/her home when the HOBOs
were installed. A questionnaire of over 150 items
(Health at Home survey) was developed from appli-
cable questions of the National Health Interview
Survey (NHIS) and from the Behavioral Risk Factor
Surveillance System (BRFSS) for Arizona. Most of
the health-related questions had dichotomous
response sets or were 4- and 5-point scaled items.
Not all questions were pertinent to each participant.
The interview took place in the resident’s home,
while air and temperature sampling equipment was
installed or operating. Interviews were conducted in
the language of resident’s choice, which included
English, Romanian, Spanish, Russian, and Farsi.
While the questionnaire covered a range of health
conditions, those relevant to our analyses here
include general health and life quality; emotional dis-
tress; and sleep.
In addition to health questions, the Health at Home
survey also addressed residents’ perceptions and
assessments of the environmental quality of their
apartments. These items were derived from two
sources: University of California Berkeley Center for
the Built Environment’s (CBE) Occupant IEQ Sur-
vey, residential version (http://www.cbe.berke-
ley.edu/research/survey.htm); and Healthy Housing
Inspection Manual (HHIM), developed by the
Centers for Disease Control (CDC) and the Depart-
ment of Housing and Urban Development (HUD).
Four items pertaining to thermal comfort of the
CBE’s IEQ survey were used for measuring resi-
dents’ thermal perceptions and satisfaction in this
study (described in Measurements section below).
Fig. 1 Kitchen after renovation, with Energy Star appliances and new cabinetry
Fig. 2 Ceiling fans newly installed in bedrooms
586
Ahrentzen et al.
Data collection primarily occurred during the June
August summer months over 3 years (20102012).
Measurements
Energy consumption. Monthly electricity consumption
for the apartment complex was obtained from local
utility companies, from the period of July 2009 to
September 2012 (electricity was the only energy source
at the residential complex). Individual metered data for
each unit was not available, limiting the analysis to the
whole building energy use. Metered data were also
evaluated against corresponding monthly weather data
obtained from the National Oceanic and Atmospheric
Administration’s (NOAA) National Climatic Data
Center for Phoenix Sky Harbor Airport (http://
www.ncdc.noaa.gov/cdo-web/).
Temperature and RH. Absolute air temperatures were
monitored and recorded every 15 min in kitchen,
bedroom, and living area, utilizing mobile Onset
HOBO data loggers. For the kitchen and bedroom,
a HOBO U-10-001 was used, and for the living
room, a HOBO U-10-003 was used. This latter
HOBO is capable of measuring absolute air tempera-
ture and RH; the others in the bedroom and kitchen
measured air temperatures alone. Each HOBO was
installed at approximately 1.2 m (4 ft), midway
between floor and ceiling against an interior parti-
tion wall.
The HOBO data loggers were placed on interior par-
tition walls, limiting any influence of thermal conduc-
tance through walls that served as thermal barriers
between indoor and outdoor environments (Figure 3).
Only three apartments in our sample had more than
one wall serving as thermal envelope barrier (these
were either on west or east wing; see Figure 4 for build-
ing layout). Although these three units did have a
greater exposed surface area than typical single-wall
exposure units, it was an invariant factor in the panel
study design (i.e., the same exterior wall conditions
applied to these three units at P1 and P3 panels) and,
hence, this factor was not treated separately as a
covariate in our analyses.
All HOBOs remained in place for 5 days, recording
a total of 448 usable data points. From the 448 data
points for each unit, five metrics of temperature were
calculated and used in analyses:
mean temperature (calculated from 448 data
points)
standard deviation of temperature (we refer to this
as ‘thermal variability.’)
maximum temperature of the 448 data points
minimum temperature of the 448 data points
the number of data points at 27.2°C (81°F) and
higher (corresponding to ASHRAE-55 2010 maxi-
mum summer allowable temperature) (we refer to
this as ‘Exceed 27.’)
In addition, metrics for mean, variability, minimum,
and maximum RH of each unit were also calculated.
Air infiltration. Blower door tests were performed in
each resident’s unit at each panel. All fenestrations of
conditioned spaces were closed. All exhaust fans,
vented dryers, air conditioners, ventilation system fans,
and air handler fans were turned off. All interior doors
to rooms that are conditioned were opened. The bath-
room door was closed to minimize air infiltration
through the exhaust fan to the roof. There was no
practical means of closing the kitchen range hood
exhaust fan to prevent the same occurrence.
Appliances were not operating during the blower door
test.
Resident reported health. As mentioned earlier, ques-
tionnaire items on health were drawn from two
national, annually administered surveys. For this
study, the variable of ‘quality of life/health’ was con-
structed from scoring responses to three separate ques-
tionnaire items. ‘Emotional distress’ was constructed
from weighted sum of six interval-level questionnaire
items (Pilkonis et al., 2011). One question on sleep
asked the resident, on average how many hours of
sleep did he or she get in a 24-h period.
Resident thermal comfort. In addition to reported
health questions, the survey also asked residents to
assess their satisfaction and/or comfort with various
environmental quality aspects (i.e., lighting, air quality,
temperature) of their apartments. In assessing resi-
dents’ perceptions of their home’s temperature, four
Fig. 3 Location of blower door test (dashed square) and
HOBOs (gray and white dot) in apartments for air exchange,
temperature, and relative humidity sampling. (*The larger study
also included air sampling for aldehydes and particulate matter
represented by dashed squares indicating those sampling devices
respective locations)
587
Thermal and health outcomes of energy retrofits
questions were included in the survey (derived from the
CBE survey mentioned in Data collection). All items
were based on 7-point response scales. They included
(i) satisfaction with temperature of unit; (ii) satisfaction
with temperature in kitchen; (iii) satisfaction with effec-
tiveness of thermostat; and (iv) extent to which thermal
condition in unit enhances or interferes with one’s
comfort.
Statistical analyses
When examining changes in indoor thermal conditions
(i.e., absolute air temperature, RH, and air infiltration)
from Panel 1 to Panel 3 (or ‘P1P3’), we used a class of
regression methods called fixed effects models (Allison,
2009; Gujarati and Porter, 2009). As we did not have a
control group but did have a longitudinal panel
research design, these models were appropriate to our
study design, where each individual (or the individual’s
apartment) acts as his or her own control. Potential
mediating or moderating variables (such as floor level
of unit) were handled by entering them as covariates
into these regression models. Repeated-measures
ANOVA or pairwise t-tests could also have been used
with the two time periods here and would have
achieved the same statistical results. Because the larger
study was constructed to examine some hypotheses
over three time periods (e.g., Frey et al., 2015), and
because we also wanted to control for possible con-
founding variables, fixed effects regression was chosen
to accommodate these conditions.
When examining correspondence between change in
a resident’s health factor and change in thermal condi-
tions of the resident’s home, fixed effects models were
used for analyzing hypotheses 2 and 3, considering the
health variables as interval-level data. Because thermal
comfort variables were considered ordinal-level data,
ordinal regression was used for the analysis of hypoth-
esis 4.
Results
Energy consumption changes following retrofit
To examine the first hypothesis, reported energy con-
sumption over 39 months of metered data was
separated into three panels including before (July
2009January 2011), during (February 2011August
2011), and after the building retrofit (September 2011
October 2012). Changes in energy consumption are
notable in the second and third data panels, where a
comparison of pre- and post-renovation metered data
shows energy consumption during the peak load sum-
mer months reduced by an average of 32.2 MWh per
month (Figure 5). Annual savings are reduced from a
pre-renovation high of 1042 MWh for 2010 to 845
MWh in 2012, the first year after renovation work was
completed, a 19% reduction.
Although indoor conditions are affected by varied
outdoor temperatures, because this study was a panel
design in which each unit’s data is measured against
itself and not against other units, and because outdoor
air temperature would be the same for all residents in
this building, it was not necessary to control for out-
door weather conditions.
To account for differences in climate effects on
metered energy, monthly weather data obtained at
Phoenix Sky Harbor Airport is referenced. Variance
between the months during each panel reveals some
difference in weather conditions, with the three summer
months of peak cooling loads identified as July,
August, and September, showing an average monthly
temperature during post-construction panel of 33.3°C
(92°F), approximately 1°C (1.8°F) cooler than the
same peak cooling months of the preceding 3 years
34.7°C (94.5°F). This suggests that post-construction
months were slightly cooler than pre-construction.
Using base 18°C (65°F) heating degree-days (HDD)
and cooling degree-days (CDD) calculated from
Fig. 4 Aerial view of three-story apartment complex on site of fieldwork
588
Ahrentzen et al.
measured weather data, post-construction weather
shows an additional 30°C-day/year (54°F-day/year)
HDD and 84.4°C-day/year (152°F-day/year) fewer
CDD than the three proceeding years, a difference of
only 2% in total H/C °C-day/year.
Two points of interest where answers remain elusive
due to the lack of submetered energy data should be
noted from Figure 5: Changes in energy consumption
during the heating months are less pronounced than
changes observed during the months requiring cooling;
and several months (February, June, and November)
show similar energy consumption levels both before
and after the renovation. Speculative explanations for
these values include occupant behavior and/or energy
usage of the building’s common spaces (i.e., all non-
apartment unit spaces such as activity room, common
kitchen, laundry room, indoor lounge) dominating the
meter with limited energy consumption by the individ-
ual apartments. It may likely be the case that many res-
idents limit their use of indoor heating as the winter
Phoenix climate is not unpleasantly cold compared to
high cooling demands during the very hot Phoenix
summer months. However, this does not necessarily
account for what is observed between January and
February, 2 months that have similar average monthly
temperatures but very different energy consumption
levels. Months with similar energy usage may be
reflecting the apartment building’s base energy use; a
base energy usage consisting of lighting loads, constant
demand appliances such as refrigerators, and heating
and cooling loads for common and office spaces met by
the apartment buildings central air-conditioning sys-
tem. Absent from this base load would be any energy
used by individual units for seasonal heating/cooling
loads. As for effects of occupant behavior on energy
consumption, it was impossible to assess given the lack
of individual submetered data.
Nonetheless, given these minor differences in heating
and cooling loads over 4 years of metered energy usage
data, overall, the energy renovations appear effective in
reducing peak cooling loads.
Temperature, RH, and air infiltration changes
Table 1 provides descriptive summary statistics of the
temperature variables averaged across all units in the
sample at baseline and Panel 3 (at least 1 year of occu-
pancy after retrofit).
To examine the second hypothesis, fixed effects
regression was used. Comparing each unit’s baseline
measure to its measure at P3, the fixed effects regres-
sion results showed that temperatures stabilized over
time, with fewer recorded temperature extremes
exceeding 27.2°C(t=2.358, P<0.05) and thermal
variability marginally increased (t=1.753, P<0.1).
Changes in apartment’s mean and minimum tempera-
tures were also found to be statistically significant
(t=2.208, P<0.05, D=0.55°C(0.99°F); and
t=1.952, P<0.1, D=1.14°C(2.05°F), respec-
tively). These thermal changes remained statistically
significant even after controlling for building charac-
teristics of floor level, wing orientation (eastwest), and
northsouth orientation. However, when entering resi-
dent characteristics into the regression models, a
greater reduction in mean temperature change and
Exceed 27 change occurred in those units occupied by
residents who had resided longer at the apartment
complex (t=3.554, P<0.001; t=4.729, P<0.001).
0
5
10
15
20
25
30
35
40
0
20
40
60
80
100
120
140
160
Temperature [°C]
Energy use [MWh]
Pre-construction '09 Construction '11
Post-construction '11+ Monthly mean outdoor temperature [°C]
Fig. 5 Monthly energy use (bars) of the apartment complex and mean outdoor temperature (circles), from July 2009 to October 2012
589
Thermal and health outcomes of energy retrofits
It should be noted that although these variables were
found to be statistically significant, these changes may
not necessarily translate into meaningful or perceptibly
significant temperature changes. Box plots illustrate
the change (P3P1) in recorded temperature values of
each unit from P1 to P3. Figure 6a shows the change
in Exceed 27 counts between panels distribution. Over-
all, there was a mean decrease of 55.6 (s.d. =152.21)
recorded Exceed 27 occurrences per unit (i.e., almost
14 h over a 112-h period when temperature was being
recorded), with median of 4. Variability of this
change is evident when examining quartiles separately.
The apartment units falling within the second quartile
(Q
2
) experienced a decrease in Exceed 27 occurrences
between 4 and 162 (140 h), while the first quartile
(Q
1
) experienced a decrease between 162 and 439
occurrences (40109 h). Units that recorded increases
in Exceed 27 occurrences in the third (Q
3
) and fourth
(Q
4
) quartiles were marked at 19 (4.75 h) or less, and
150 (37.5 h) or less, respectively.
Figure 6b shows the observed increase for thermal
variability (mean =0.61, median =0.04, s.d. =2.21)
where Q
4
shows 25% of the units experienced an
increase between 1.69 and an outlier of 8.54 in their
variability. Figure 6c illustrates that many units experi-
enced a decrease in their mean temperatures
(mean =0.57, median =0.44, s.d. =1.62) with
<25% of the units experiencing an increase >1°C. And
Table 1 Mean and standard deviation of temperature and RH measures across all apartments, at P1 and P3
Unit temperature Unit RH (%)
P1 P3 P1 P3
Mean s.d. Mean s.d. Mean s.d. Mean s.d.
Maximum (°C) 28.0 1.5 28.2 1.72 39 5.67 39 7.06
Minimum (°C) 24.2 1.87 22.9 3.93 27 3.91 24 4.82
Mean (°C) 26.0 1.31 25.4 1.27 31 3.61 30 4.65
Median (°C) 26.1 1.27 25.4 1.37 31 3.59 30 4.92
Variability 0.91 1.42 1.16 2.19 3.63 2.19 8.75 10.12
Exceed 27 (count in %) 97.3 (23.19) 139.39 (0.31) 41.7 (9.56) 77.95 (0.18) n/a n/a n/a n/a
RH, relative humidity.
Due to instrument precision, temperature values were rounded to one decimal place and RH% values rounded to nearest whole % number.
n=53.
(a) (b) (c) (d)
Fig. 6 Distribution of each unit’s change in observed data from baseline (P1) to P3 (N=53). Note: Outliers (where
H
3
+step x
i
<Q
3
+19step and H
1
-1.5 9step <x
i
Q
1
+19step) are marked with a , while extreme outliers (where
x
i
H
3
+29step and x
i
H
1
-2 9step) are marked by *
590
Ahrentzen et al.
Figure 6d shows that several units experienced signifi-
cant decreases in their average minimum temperatures,
four units with decreases >5°C, and Q
1
with represent-
ing units with decreases between 4 and 1.5°C
(mean =1.14, median =0.48, s.d. =3.7).
In examining changes in a unit’s RH between panels
1 and 3, the mean, minimum, and maximum RH values
of the 53 units remain consistent, but a statistically sig-
nificant increase in RH variability was noted
(t =3.466, P<0.01). This increase was significant even
after controlling for building characteristics of floor
level and wing orientation (eastwest), as well as per-
sonal characteristics of resident age and length of stay
at the apartment complex. The cause of this change is
unclear and may be due to a combination of factors
including slight changes to the unit’s air exchange, and
possible changes to occupant behavior that produced
varying amounts of moisture given significant renova-
tions to kitchen and bathroom that may have resulted
in increased bathing and cooking. These remain specu-
lative suggestions as data were not collected on these
factors.
Changes in air infiltration rates were not statistically
significant between panels, and so will not be discussed
further.
Correspondence with changed health conditions
In examining whether significant temperature improve-
ments in a unit corresponded with reported health
changes of its occupants (hypothesis 3), we chose a
temperature measure that demonstrated some of the
most dramatic changes described above: How often
unit temperatures exceeded ASHRAE standard of
27.2°C (81°F). We reconstructed a new dataset that
paired an apartment’s temperature data at baseline
and Panel 3 with its resident’s survey data at baseline
and P3. Using fixed effects regression, we examined
whether the changes of Exceed 27 between P1 and P3
in a resident’s apartment contributed to changes in that
resident’s reported health over the same time period.
Table 2 reports these results. Between baseline and
P3, changes in an apartment’s number of excessive
temperatures (i.e., Exceed 27) also corresponded with
the resident’s improved quality health/life, reduced
emotional distress, and increased number of hours
sleeping, as reported in survey data between P1 and
P3.
Correspondence with thermal comfort
Also examined were changes in reported quality of resi-
dents’ homes in terms of (i) satisfaction with tempera-
ture in the unit; (ii) satisfaction with temperature
conditions in the kitchen; (iii) satisfaction with effec-
tiveness of the thermostats; and (iv) extent to which
thermal conditions in the unit enhance or interfere with
one’s comfort. As described in the Methods section,
these were seven-point response sets and treated as
ordinal scale. Because of lack of participants’ response
on lower end of the response sets, the seven-point
scales were converted into four-point scales (1, 2, and
3; 4 and 5; 6; 7).
As marginally to strong statistically significant
results were found for changes in the apartments on
thermal variability, RH variability, and Exceed 27 (see
Temperature, RH, and air infiltration changes), the
extent to which changes in these indoor climate condi-
tions corresponded to changes in these four perception
items was examined. Also examined was whether the
perception was not only contingent upon the actual
indoor climate condition at that panel, but also on the
extent of change in the condition from baseline to
panel 3.
Table 2 Fixed effects regression results of reductions in excessive temperatures (Exceed
27) on changes in reported health variables, between P1 and P3
Quality of health/
life Emotional distress No. hours sleep
tP-value tP-value tP-value
Exceed 27 3.179 <0.01 2.085 <0.05 2.150 <0.05
t: Studentst-test value from fixed effects regression analysis.
Table 3 Summary of study findings
Hypothesis Results
1. Energy retrofits result in reduced
energy consumption of building
(Research context and site)
19% reduction in energy use
2. Energy retrofits result in thermal
improvements in resident units (Green retrofit)
Mean temperature reduction:
confirmed
Maximum temperature: no
Minimum temperature
reduction: confirmed
Thermal variability: marginally
significant increase
Exceed 27 reduction: confirmed
Mean RH: no
Maximum RH: no
Minimum RH: no
RH variability increase:
marginally significant
3. Thermal improvements Exceed 27 in
residents unit correspond with improved
health of resident (Research design and methodology)
Quality of health/life: confirmed
Emotional distress: confirmed
No. hours sleep: confirmed
4. Thermal improvements in residents unit Exceed 27,
thermal variability, RH variability correspond
with greater thermal comfort of resident
(Sample size and characteristics)
Satisfaction with unit
temperature: no
Satisfaction with kitchen
temperature: only for RH
variability
Satisfaction with thermostat:
marginally for RH variability
Enhance thermal comfort: no
RH, relative humidity.
591
Thermal and health outcomes of energy retrofits
There were no significant relationships with changes
in a unit’s Exceed 27 and changes in its resident’s
responses on any of the four thermal comfort mea-
sures; similarly, there were no significant relationships
between the changes in thermal variability and resi-
dent’s thermal comfort scores. However, changes in
RH variability between panels 1 and 3 were associated
with resident’s satisfaction with kitchen temperature
(Wald =5.232, P<0.05) and marginally so with ther-
mostat satisfaction (Wald =2.802, P<0.1).
Summary and conclusions
As summarized in Table 3, the findings of this study
suggest that the benefits of renovation to improve
energy efficiency include, but go beyond, energy
consumption reductions. In this particular case study,
benefits also include a more stabilized thermal environ-
ment for older residents, as indicated by reduced
Exceed 27 counts, in reduced mean and minimum tem-
peratures that are more consistent with existing ASH-
RAE recommendations, and marginally so for reduced
thermal variability. Renovation work, including
improved roof insulation and Uni-Seal coat, new
PTAC heating/cooling units, and thermostats, in addi-
tion to improved weatherization of the envelope to
decrease air infiltration, all likely contributed to the
stabilization of indoor temperatures and reduction in
temperature extremes.
In addition, reductions in an apartment’s extreme
indoor temperature conditions correspond with
improvements in its resident’s reported health mea-
sures of general quality life/health, emotional distress,
and sleep key health issues for older adults. In
another component of the larger study, reductions in
formaldehyde levels marginally corresponded with
reduced emotional distress and had no correspondence
with quality life/health or sleep over the 1-year time
period (Frey et al., 2015). But formaldehyde reduc-
tions in the short term (i.e., 3-month post-renovation)
did correspond with improvements in quality of
health/life and reductions in emotional distress.
Together, these findings of formaldehyde in conjunc-
tion with the findings here on temperature suggest the
complex temporal nature of various environmental
quality (EQ) factors on reported health outcomes.
Because of the small sample sizes, statistical modeling
of multiple EQ factors over three time periods was not
feasible, however.
Surprisingly, the improvements in the thermal envi-
ronment did not affect resident perceptions of their
unit’s thermal conditions. This may be the result of one
key factor: the resident’s ability to control their indoor
thermal environment. Olesen and Brager (2004) recog-
nized that users’ perceptions of thermal comfort were
changed or affected by whether they had control of
their indoor environmental conditions. While the resi-
dents in this study experienced less temperature
extremes and marginally more thermal variability in
their homes after the renovation, their units were also
equipped with an accessible thermostat that allowed
them to control their indoor temperature conditions.
Extrapolation of the study findings to populations
and residential settings beyond this particular senior
housing complex in Phoenix must be tempered by some
of the limitations of the study. This was a single case
study: Green renovations in other climate situations
and other housing types may not show similar results,
although recent and similar research by Noris et al.
(2013) in California and J. Breysse and D. Jacobs (un-
published data, Columbia, MD, National Center for
Healthy Housing) in Minnesota does suggest a pattern
that cuts across climate zones. In addition, self-report
health data may not have direct correspondence to
actual physiological conditions. Attrition rates were
not insignificant although not uncommon for a sample
of low-income older adults over a 2-year period. We
found use of the NHIS and BRFSS survey questions
problematic for assessing health conditions when
examining intervention effects, as did Breysse et al.
These questions which primarily ask about existence
of conditions with dichotomous response sets (i.e., yes/
no) are not sufficiently robust to measure changes in
degree or episodic occurrences of many relevant health
conditions and so were not included for examination in
this study’s analysis.
Further, our study did not have the strong internal
validity of an experimental or quasi-experimental
design as we did not have a control case study site
being renovated without the array of green building
features. Nonetheless, the panel research design of this
study where each unit and resident is its own ‘control’
group on repeated measures minimizes error in com-
parison to cross-sectional data.
Acknowledgements
We wish to acknowledge the contribution and assistance
of our collaborators on the larger project: John Ball,
Hugo Destaillats, Sarah Dwyer, Matthew Fraser, Sarah
Frey, William Johnson, Mookesh Patel, Kimberly Shea,
Siva Srinivasan. Funding for this research was provided
by the U.S. Department of Housing and Urban Devel-
opment, Office of Healthy Homes and Lead Hazard
Control, Grant Number AZLHH0200-09. We are grate-
ful for the City of Phoenix, and the property managers
and residents of the apartment complex, for their partic-
ipation and interest in the study.
592
Ahrentzen et al.
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Thermal and health outcomes of energy retrofits
... Thirdly, improved thermal stabilization can lead to better health outcomes for occupants, including improved sleep, emotional health and overall quality of life. Finally, improved thermal stabilization through energy retrofits is associated with increased thermal comfort for occupants (Ahrentzen et al., 2016). ...
... With β 5 0.693; t 5 3.854, and p 5 0.002, the results suggest that thermal upgrade has the largest influence on the perception of quality of life of occupants in Prishtina, Kosovo. In this regard, as Ahrentzen et al. (2016) argue that the perception of occupants about the quality of life is improved through thermal comfort. To this end, structural building upgrades such as envelope retrofitting affect both the building performance and the users' satisfaction, health and wellbeing (Belussi et al., 2019;Chen et al., 2020) and overall indoor environmental quality as a function of thermal comfort (Danza et al., 2020;Kuusk et al., 2014;Kuusk and Kalamees, 2015;Prasauskas et al., 2014). ...
... The implication of this could be that Kosovo building occupants perceive the quality of life through thermal comfort as one of the key measures of the quality of life. Without thermal stabilization as argued by Ahrentzen et al. (2016), other criteria for quality of life cannot be met in Kosovo. Given the high energy costs in Kosovo and interrupted supply of electricity in Kosovo, the reduction of energy bills achieved through thermal retrofitting saves the pockets of building occupants, thereby affecting their economic well-being and quality of life. ...
Article
Full-text available
Purpose The aim of this research is to investigate the impact of thermal, acoustic and HVAC upgrades on the perception of the quality of life among residential building occupants. Design/methodology/approach The present study used a quantitative research approach, utilizing a questionnaire as the research instrument. A survey was conducted with 1,119 residential apartment building occupants in Prishtina, Kosovo, using a stratified random sampling method for selection of participants. Findings The present study used quantitative research with a questionnaire as the research instrument. The survey was conducted with 1,119 residential apartment building occupants in Prishtina, Kosovo, using stratified random sampling. The study found that thermal retrofits, acoustic retrofits and HVAC upgrades as a whole model affect the perception of the quality of life of residential building occupants in Prishtina, Kosovo. However, the study found that not all dimensions of the constructed research model (thermal, acoustic and HVAC) affect the perception of the quality of life of residential building occupants. Specifically, thermal retrofitting seems to strongly influence the perception of quality of life, while HVAC upgrades do not seem to have an impact on the quality of life of occupants. Finally, acoustic retrofits also influence the perception of the quality of life, although not to the same degree as thermal retrofitting. Research limitations/implications The present study contributes to understanding the role that thermal retrofits, acoustic retrofits and HVAC upgrades play in the perception of quality of life by building occupants in an understudied region with a booming real estate sector such as Kosovo. The study also highlights the need for further analysis to understand why HVAC upgrades do not seem to influence the perception of quality of life by residential building occupants in Kosovo. Originality/value The present study is the first to quantify the impact of thermal, acoustic and HVAC upgrades on the perception of the quality of life of residential building occupants in Prishtina, Kosovo.
... Ahrentzen et al. [20], Kenny et al. [21], and Beckmann et al. [22] analyzed the impact of indoor thermal environments on human health, suggesting that temperatures exceeding the critical threshold of 27 • C could be particularly harmful to vulnerable groups. Kenny [23] further highlighted that heat-sensitive populations should avoid continuous exposure to temperatures above 31 • C. ...
... Table 9 provides a summary of key studies, standards, and recommendations related to indoor temperatures affecting heat-vulnerable populations. Several studies, including those by Ahrentzen et al. [20], Beckmann et al. [22], and Kenny [23], have reported that indoor temperatures exceeding 27 • C can adversely affect the health and quality of life of elderly individuals and those with chronic conditions. Additionally, the Health in Aging Foundation [34] advises that elderly people take preventive actions when indoor temperatures surpass 27 • C to reduce the risk of heat-related illnesses. ...
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This study investigates the impact of building insulation standards on indoor thermal environments and the risk of heat-related illnesses during heatwaves in South Korea. Indoor temperatures were measured in residential buildings located in Chuncheon and Gwangju during the 2022 heatwave, with outdoor temperature data sourced from the Korea Meteorological Administration. Probability distribution fitting was used to estimate the likelihood of indoor temperatures exceeding the critical threshold of 27 °C. Additionally, a linear regression analysis was conducted to examine the relationship between the probability of exceeding the threshold and heat-related illness data from 2017 to 2023 provided by the Korea Disease Control and Prevention Agency. The findings reveal significant variations in indoor thermal conditions during heatwaves, influenced by factors such as building type, year of construction, and climate region, which affect the thermal insulation performance. Buildings with a lower thermal insulation performance were associated with higher indoor temperatures, increasing the likelihood of exceeding the critical threshold and contributing to a higher incidence of heat-related illnesses, particularly in provincial non-metropolitan areas. These results underscore the need for region-specific building insulation standards that address both winter energy efficiency and summer heatwave resilience. Enhancing thermal insulation in vulnerable regions could significantly reduce the risk of heat-related illnesses and improve public health resilience to extreme heat events.
... One quasi-experimental study of 57 older people (age 62-92, average 73) before and after retrofits of a low-income senior housing complex in Phoenix, Arizona found that reductions in the number of days of indoor temperature above 27.2°C and reductions in mean and minimum indoor temperatures after the retrofits corresponded with improved reported occupant health and increased hours of sleep (Ahrentzen et al., 2016). ...
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Heat is a leading weather-related cause of death worldwide and heat waves are increasing globally in terms of frequency, duration, and intensity. Global heat-related deaths could quadruple by midcentury. As with many environmental hazards, numerous factors impact how heat might affect any given person and there are significant gaps in our understanding related to indoor heat and its effect on health. Despite growing interest in establishing standards and guidelines, there is currently no clear consensus on a safe maximum upper limit for indoor temperature. There is conclusive evidence of links between high outdoor temperatures and human health yet research on this correlation does not typically explicitly consider indoor heat exposure. Considerably more research has been completed on healthy, active individuals than for more heat-susceptible populations and the impacts of moderate heat stress on the health of large populations are not well understood. We conducted a literature review on the impact of indoor thermal conditions on health, recognizing that air temperature alone cannot describe thermal exposure. We introduce the concept of a standardized maximum safe indoor temperature, defined for still air conditions, 50% relative humidity and mean radiant temperature equal to air temperature. Equivalent temperatures with respect to the thermal load on the body can then be calculated for various air velocities, humidities or mean radiant temperatures using the standard effective temperature (SET) model. For U.S. policymakers, we propose adopting a standardized maximum safe indoor temperature of 28 °C. We recognize that the adoption of standardized maximum safe indoor temperatures may vary around the world, but the framework we propose to adjust the standardized upper limit for humidity, air motion, and radiant temperature could be used globally. We also identify important knowledge gaps to guide future research on the relationships between heat and health that could support informed cost-benefit analyses.
... Adequate thermal comfort reduces the risk of cold-related illnesses and respiratory conditions, particularly among vulnerable populations (Ormandy and Ezratty, 2016). Additionally, by reducing exposure to indoor pollutants and allergens, retrofit policies contribute to better overall health outcomes and quality of life for occupants (Ahrentzen et al., 2016). During the Warm Front scheme, for instance, residents reported greater thermal comfort after retrofitting (Gilbertson and Green, 2008 n.d.). ...
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The Climate Change Act committed the UK to reduce GHG emissions by at least 80 percent in 2050. This ambitious target requires millions of homes to be retrofitted and, in response, the Government has implemented multiple retrofit policies and funding mechanisms, including supplier obligations. This study reviews retrofit policies and compares the objectives and the carbon/energy savings achieved. The review focuses specifically on the 4 iterations of the supplier obligations that have been implemented since 1994. It finds that the supplier obligations have had similar objectives and followed similar trends in the retrofit measures installed. The study further identified the benefits and challenges of the Suppliers' Obligations. The paper concludes by discussing lessons learned for the design of future policies and implementation strategies to improve the energy efficiency of homes in the UK to achieve net zero by 2050.
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Understanding when and where heat adversely influences health outcomes is critical for targeting interventions and adaptations. However, few studies have analyzed the role of indoor heat exposures on acute health outcomes. To address this research gap, the study partnered with the New York City Fire Department Emergency Medical Services. Paramedics carried portable sensors that passively measured indoor temperatures at 3-min intervals while responding to calls during summer, 2016. Patient care reports provided the patient’s chief health complaint and sociodemographic and health status information. Propensity score matching increased comparability between groups exposed to elevated indoor temperature versus those unexposed. To assess indoor heat-health associations, we conducted independent case–control studies between indoor heat exposures and cardiovascular (n = 735) and respiratory (n = 296) emergency medical calls when compared to heat-insensitive controls (n = 1611). Patients experiencing heat exposures (indoor temperature ≥ 28 °C) were not significantly more likely (OR, 1.15; 95% CI, 0.64–2.09) to receive care for respiratory conditions. Both outdoor and indoor temperatures increased the odds of receiving care for cardiovascular versus comparison calls. Outdoor temperatures consistently elevated cardiovascular risks (OR, 1.12; 95% CI, 1.05–1.19). There was some evidence that indoor temperatures further increased the odds of cardiovascular distress (OR, 1.44; 95% CI, 0.97–2.13). Sensitivity testing suggested indoor temperatures at a lower threshold (≥ 26 °C) were unrelated to either health outcome. Along with converging lines of evidence linking extreme heat to adverse cardiovascular outcomes, we present one of the first indoor heat observational studies.
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This study assessed the usability of three readily available Personalized Thermal Control Systems (PECS)—an electric blanket, a small personal fan, and a large pedestal fan—among individuals with intellectual disabilities living independently in energy poverty conditions in Chile. The research aimed to identify the primary usability challenges that affect the adoption and operational effectiveness of these technologies and, consequently, their potential to enhance thermal comfort. Results indicated that devices with more advanced control features, i.e. the large pedestal fan, presented the most significant usability challenges, followed by the electric blanket and the small personal fan. Key usability issues included poor visibility, inadequate material choice, ineffective communication, bad affordance, and inadequate levels of touch sensitivity of the control interface in these PECS. The study also showed a large variance in the level of adoption of the PECS among participants, thereby indicating that users have different individual attitudes, ranging from passive acceptance to proactive exploration and use. To conclude, this study advocates for the necessity of developing easily operable PECS that cater to the specific needs of individuals with intellectual disabilities, thereby supporting their autonomy and improving their quality of life in thermally comfortable environments.
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The indoor environment affects occupants' health and comfort. Poor environmental conditions and indoor contaminants are estimated to cost the U.S. economy tens of billions of dollars a year in exacerbation of illnesses like asthma, allergic symptoms, and subsequent lost productivity. Climate change has the potential to affect the indoor environment because conditions inside buildings are influenced by conditions outside them. Climate Change, the Indoor Environment, and Health addresses the impacts that climate change may have on the indoor environment and the resulting health effects. It finds that steps taken to mitigate climate change may cause or exacerbate harmful indoor environmental conditions. The book discusses the role the Environmental Protection Agency (EPA) should take in informing the public, health professionals, and those in the building industry about potential risks and what can be done to address them. The study also recommends that building codes account for climate change projections; that federal agencies join to develop or refine protocols and testing standards for evaluating emissions from materials, furnishings, and appliances used in buildings; and that building weatherization efforts include consideration of health effects. Climate Change, the Indoor Environment, and Health is written primarily for the EPA and other federal agencies, organizations, and researchers with interests in public health; the environment; building design, construction, and operation; and climate issues. © 2011 by the National Academy of Sciences. All rights reserved.
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Standard 55-2004, Thermal Environmental Conditions for Human Occupancy, incorporates advances in the understanding of human response to thermal environments. The standard specifies conditions of the indoor thermal environment that occupants will find acceptable. It is intended for use in design, commissioning, and testing of buildings and other occupied spaces and their HVAC systems, and for the evaluation of existing thermal environments. This new standard includes an analytical method based on the PMV-PPD indices and introduction of the concept of adaptation with a separate method for naturally conditioned buildings.
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Further research is needed before the complex effects of thermal stress on comfort, performance and social behaviour are understood, especially for the moderately warm and cold temperate range. Sufficient is known to provide some theoretical underpinnings and guidelines for further enquiry.-J.Sheail