Sulaimano a, Bu ulcha; Azhgaliye a, Dina; Holzhacke , Hans; Ø e land, Ind a
Wo king Pape
Hea adap a ion in cen al Asia: Household cooling choices
ADB Economics Wo king Pape Se ies, No. 787
P o ided in Coope a ion wi h:
Asian De elopmen Bank (ADB), Manila
Sugges ed Ci a ion: Sulaimano a, Bu ulcha; Azhgaliye a, Dina; Holzhacke , Hans; Ø e land, Ind a
(2025) : Hea adap a ion in cen al Asia: Household cooling choices, ADB Economics Wo king Pape
Se ies, No. 787, Asian De elopmen Bank (ADB), Manila,
h ps://doi.o g/10.22617/WPS250245-2
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/322384
S anda d-Nu zungsbedingungen:
Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen
Zwecken und zum P i a geb auch gespeiche und kopie we den.
Sie dü en die Dokumen e nich ü ö en liche ode komme zielle
Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich
machen, e eiben ode ande wei ig nu zen.
So e n die Ve asse die Dokumen e un e Open-Con en -Lizenzen
(insbesonde e CC-Lizenzen) zu Ve ügung ges ell haben soll en,
gel en abweichend on diesen Nu zungsbedingungen die in de do
genann en Lizenz gewäh en Nu zungs ech e.
Te ms o use:
Documen s in EconS o may be sa ed and copied o you pe sonal
and schola ly pu poses.
You a e no o copy documen s o public o comme cial pu poses, o
exhibi he documen s publicly, o make hem publicly a ailable on he
in e ne , o o dis ibu e o o he wise use he documen s in public.
I he documen s ha e been made a ailable unde an Open Con en
Licence (especially C ea i e Commons Licences), you may exe cise
u he usage igh s as speci ied in he indica ed licence.
h ps://c ea i ecommons.o g/licenses/by/3.0/igo/
ASIAN DEVELOPMENT BANK
ASIAN DEVELOPMENT BANK
6 ADB A enue, Mandaluyong Ci y
1550 Me o Manila, Philippines
www.adb.o g
ADB ECONOMICS
WORKING PAPER SERIES
NO. 787
June 2025
Hea Adap a ion in Cen al Asia
Household Cooling Choices
This s udy examines how households in he Ky gyz Republic, Tajikis an, and Uzbekis an adap hei cooling
s a egies o powe ou ages and inc easing empe a u es. I p o ides insigh s in o he socioeconomic and
beha io al dimensions o ene gy esilience in Cen al Asia. I no es he impo ance o a eliable powe supply
and he po en ial o sola panels o mee summe ene gy demands.
Abou he Asian De elopmen Bank
ADB is a leading mul ila e al de elopmen bank suppo ing inclusi e, esilien , and sus ainable g ow h ac oss
Asia and he Paci ic. Wo king wi h i s membe s and pa ne s o sol e complex challenges oge he , ADB
ha nesses inno a i e inancial ools and s a egic pa ne ships o ans o m li es, build quali y in as uc u e,
and sa egua d ou plane . Founded in 1966, ADB is owned by 69 membe s—50 om he egion. HEAT ADAPTATION
IN CENTRAL ASIA
HOUSEHOLD COOLING CHOICES
Bu ulcha Sulaimano a, Dina Azhgaliye a, Hans Holzhacke , and Ind a O e land
ASIAN DEVELOPMENT BANK
The ADB Economics Wo king Pape Se ies
p esen s esea ch in p og ess o elici commen s
and encou age deba e on de elopmen issues
in Asia and he Paci ic. The iews exp essed
a e hose o he au ho s and do no necessa ily
e lec he iews and policies o ADB o
i s Boa d o Go e no s o he go e nmen s
hey ep esen .
ADB Economics Wo king Pape Se ies
Bu ulcha Sulaimano a, Dina Azhgaliye a,
Hans Holzhacke , and Ind a O e land
No. 787 | June 2025
Bu ulcha Sulaimano a (b.sulaimano [email protected] )
is head o Resea ch and T aining Depa men ,
OSCE Academy, Bishkek. Dina Azhgaliye a
(dazhgaliye [email protected] g) is a senio economis a
he Economic Resea ch and De elopmen Impac
Depa men , Asian De elopmen Bank. Hans Holzhacke
(hans.holzhacke @ca ecins i u e.o g) was chie
economis and is cu en ly a consul an a Cen al Asia
Regional Economic Coope a ion Ins i u e.
Ind a O e land ([email p o ec ed]) is head o he Cen e o
Ene gy Resea ch, No wegian Ins i u e o In e na ional
A ai s and a esea ch associa e a he Ox o d Ins i u e
o Ene gy S udies.
Hea Adap a ion in Cen al Asia: Household Cooling Choices
C ea i e Commons A ibu ion 3.0 IGO license (CC BY 3.0 IGO)
© 2025 Asian De elopmen Bank
6 ADB A enue, Mandaluyong Ci y, 1550 Me o Manila, Philippines
Tel +63 2 8632 4444; Fax +63 2 8636 2444
www.adb.o g
Some igh s ese ed. Published in 2025.
ISSN 2313-6537 (p in ), 2313-6545 (PDF)
Publica ion S ock No. WPS250245-2
DOI: h p://dx.doi.o g/10.22617/WPS250245-2
The iews exp essed in his publica ion a e hose o he au ho s and do no necessa ily e lec he iews and policies
o he Asian De elopmen Bank (ADB) o i s Boa d o Go e no s o he go e nmen s hey ep esen .
ADB does no gua an ee he accu acy o he da a included in his publica ion and accep s no esponsibili y o any
consequence o hei use. The men ion o speci ic companies o p oduc s o manu ac u e s does no imply ha hey
a e endo sed o ecommended by ADB in p e e ence o o he s o a simila na u e ha a e no men ioned.
By making any designa ion o o e e ence o a pa icula e i o y o geog aphic a ea in his documen , ADB does no
in end o make any judgmen s as o he legal o o he s a us o any e i o y o a ea.
This publica ion is a ailable unde he C ea i e Commons A ibu ion 3.0 IGO license (CC BY 3.0 IGO)
h ps://c ea i ecommons.o g/licenses/by/3.0/igo/. By using he con en o his publica ion, you ag ee o be bound
by he e ms o his license. Fo a ibu ion, ansla ions, adap a ions, and pe missions, please ead he p o isions
and e ms o use a h ps://www.adb.o g/ e ms-use#openaccess.
This CC license does no apply o non-ADB copy igh ma e ials in his publica ion. I he ma e ial is a ibu ed
oano he sou ce, please con ac he copy igh owne o publishe o ha sou ce o pe mission o ep oduce i .
ADB canno be held liable o any claims ha a ise as a esul o you use o he ma e ial.
Please con ac pubsma ke [email protected] g i you ha e ques ions o commen s wi h espec o con en , o i you wish
oob ain copy igh pe mission o you in ended use ha does no all wi hin hese e ms, o o pe mission o use
heADB logo.
Co igenda o ADB publica ions may be ound a h p://www.adb.o g/publica ions/co igenda.
No e:
ADB ecognizes “China” as he People’s Republic o China.
ABSTRACT
This s udy in es iga es ac o s in luencing household cooling choices in Cen al Asia, ocusing on
ai -condi ioning and ans/sunsc een ilms. Using da a om he 2023 “Household Access o Ene gy
in he Fe gana Valley” su ey in he Ky gyz Republic, Tajikis an, and Uzbekis an, he analysis
employs a mul inomial p obi model o examine socioeconomic, en i onmen al, and powe supply
ac o s. Ac oss he h ee coun ies, i inds ha 48% o households use ans o sunsc een ilms
(wi hou ai -condi ioning), 30% use no cooling, and 22% use ai -condi ioning, no ing signi ican
a ia ions be ween coun ies. Cooling deg ee days (CDD) signi ican ly impac cooling appliance
adop ion, wi h highe CDD egions mo e likely o use cooling solu ions. Powe ou ages nega i ely
a ec ai -condi ioning adop ion bu no ans/sunsc een ilms, highligh ing he impo ance o powe
s abili y. Robus ness checks con i m ha powe supply eliabili y is c ucial o cooling choices.
The indings sugges policy implica ions, including he po en ial o sola panels o mee summe
ene gy demands. This esea ch unde sco es he need o add ess powe sec o eliabili y and
clima e adap a ion in ulne able egions.
Keywo ds: hea wa es, en i onmen al ex emes, in as uc u al adap a ions, powe ou ages,
cooling echnologies, Cen al Asia
JEL codes: Q41, R21, Q54
_______________________
Acknowledgmen : Au ho s a e g a e ul o Al ynai Toleno a, a isi ing esea ch ellow a No wegian Ins i u e
o In e na ional A ai s (NUPI) and Nomin Ba sukh, a isi ing OSSE ellow a NUPI, bo h pa o he Clima e
and Ene gy Resea ch G oup, o hei excellen assis ance wi h wea he da a collec ion. Au ho s a e also
g a e ul o all pa icipan s o hyb id public lec u e a OSCE Academy in Bishkek on 25 Ap il 2025. Special
app ecia ion o Aya Ullah, pos doc o al esea ch ellow a OSCE Academy in Bishkek, o his de ailed
discussion o his pape .
1. In oduc ion
The apid global empe a u e ise due o clima e change has signi ican ly inc eased demand o
cooling echnologies, pa icula ly in egions suscep ible o ex eme hea wa es (Thomson e al.,
2019; A ia e al., 2021; Pa anello e al., 2021; Zhang e al., 2020). Cen al Asia, wi h i s ising
summe empe a u es, aces g owing isks o hea s ess (Wang, e al., 2023), highligh ing he
u gen need o e ec i e adap a ion s a egies, pa icula ly in households. While much esea ch
on he adap a ion o Cen al Asian households has ocused on he b oade impac s o hea wa es
on ag icul u e (Liu, e al., 2020; Li e al., 2020) and public heal h (Tu sumbaye a e al., 2023), less
a en ion has been gi en o how households in he egion adap o ex eme hea , pa icula ly
h ough hei cooling choices. This gap is signi ican since household cooling s a egies play a
c ucial ole in mi iga ing he ad e se e ec s o hea , p omo ing ene gy esilience, and educing he
heal h isks associa ed wi h high empe a u es (Lee e al., 2024; Musho e e al., 2017). Mo eo e ,
Cen al Asia’s ene gy access landscape is o en cha ac e ized by equen powe ou ages and g id
ins abili y, pa icula ly in u al a eas (Meh a e al., 2024), al hough i has 100% elec ici y access.
These in e up ions may pose a signi ican ba ie o he adop ion o some cooling echnologies.
Unde s anding how hese ac o s in e ac is c ucial o in o ming policies ha p omo e ene gy
e icien cooling solu ions while imp o ing household esilience o hea s ess.
This s udy in es iga es he ac o s ha in luence household cooling choices, ocusing on he
adop ion o ai -condi ioning, ans, and sunsc een ilms, which a e he p ima y cooling op ions
u ilized in Cen al Asia. By analyzing da a om he “Household Access o Ene gy in he Fe gana
Valley” su ey, which was conduc ed ac oss he Ky gyz Republic, Tajikis an, and Uzbekis an in
2023, his s udy in es iga es he socioeconomic, en i onmen al, and powe supply de e minan s
o cooling choices. The s udy add esses he ollowing esea ch ques ions: (1) Wha a e he
de e minan s o household cooling choices in Cen al Asia? (2) How do clima ic s ess ac o s,
pa icula ly cooling deg ee days (CDD), in luence household cooling echnology choices? (3) In
wha ways does he eliabili y o he powe supply a ec households’ decisions o adop pa icula
cooling echnologies?
This s udy makes se e al con ibu ions o he exis ing li e a u e on en i onmen al ex emes,
household cooling choices, and in as uc u e in Cen al Asia and o he a id egions. Fi s ly, while
much o he cu en li e a u e has examined hea ing choices, his s udy shi s he ocus o cooling
echnologies, ecognizing hei inc easing ele ance in he con ex o ising global empe a u es.
To he bes o ou knowledge, his is he i s s udy on cooling in Cen al Asia. Secondly, i assesses
he ole o powe ou ages in cooling echnology adop ion. While ai -condi ioning is o en seen as
he mos e ec i e solu ion o hea adap a ion, his esea ch highligh s ha i s adop ion is limi ed
in a eas wi h equen powe dis up ions. Las ly, he s udy explo es he impac o clima ic ac o s,
speci ically CDD, on household cooling choices. By inco po a ing CDD as a key a iable, he
esea ch p o ides a clea e unde s anding o how clima ic condi ions in luence household beha io
and ene gy consump ion pa e ns in esponse o hea s ess.
The li e a u e e iew p o ides an o e iew o exis ing esea ch on he de e minan s o cooling
echnology adop ion. The me hodology sec ion hen ou lines he da a sou ces and empi ical
s a egy, including he speci ica ion o he mul inomial p obi model. A en ion is gi en o he
a iables o in e es (cooling deg ee days and powe ou ages), along wi h a de ailed desc ip ion o
con ol a iables. A discussion o empi ical indings is ollowed by a obus ness analysis o e alua e
he impac o he du a ion o powe ou ages on household cooling choices. Finally, he conclusion
summa izes he key indings and highligh s policy implica ions.
2
2. Li e a u e Re iew
The g owing global demand o cooling echnologies in esponse o hea wa es is ex ensi ely
analyzed in he li e a u e, pa icula ly in he con ex o u baniza ion and i s socioeconomic
implica ions (Thomson e al., 2019; A ia e al., 2021; Zhang e al., 2020; Pa anello e al., 2021;
Nema choua e al., 2019). As ci ies expand and hea wa es become mo e equen and se e e,
he need o e ec i e cooling solu ions is becoming inc easingly p essing (Musho e e al., 2017;
Ba dhan e al., 2020; Jia e al., 2024).
Hu e al. (2020) conduc ed a na ionwide online su ey in he People's Republic o China o explo e
he changing pa e ns o cooling in u ban households and he ac o s ha in luence his ansi ion.
Yan and Liu (2020) modeled esiden ial ai -condi ione usage, emphasizing he ole o his o ical
empe a u e da a in o ecas ing ene gy consump ion. Zhang e al. (2020) explo ed he implica ions
o clima e change on ai -condi ioning (AC) usage in u al a eas, highligh ing he need o p omo e
high e iciency AC uni s since low e iciency echnologies we e exace ba ing ising ene gy demand.
Pa anello e al. (2021) d ew a en ion o he isks posed by ising global empe a u es, pa icula ly
o popula ions in low- and middle-income coun ies. While AC is iewed as a c i ical adap a ion
ool, access emains limi ed o lowe income households. They ind ha AC adop ion ollows an
S-shaped cu e, in luenced by socioeconomic condi ions. This sugges s ha many low-income
households will emain unable o a o d such echnologies, he eby c ea ing an “adap a ion cooling
de ici ”. These indings highligh he ulne abili y o low-income popula ions, who o en lack access
o ai -condi ioning and he eby become mo e suscep ible o he ad e se heal h impac s o ex eme
hea (Musho e e al., 2017).
Resea ch by Zande e al (2023) on he socioeconomic dimensions o cooling p e e ences e eals
signi ican a ia ion in beha io s, in luenced by ac o s such as age, household composi ion, and
hea ole ance. Thei wo k sugges s ha a ge ing ene gy e icien cooling solu ions based on hese
demog aphic ac o s could enhance ene gy esilience. Zhang e al. (2020) highligh he ole o
CDDs in d i ing ai -condi ione use in u al a eas, wi h socioeconomic a iables such as dwelling
cha ac e is ics in luencing beha io .
In he con ex o access o elec ici y and demand o cooling, Falche a and Mis y (2021)
emphasize he necessi y o decision-make s o in eg a e cooling needs in o elec ici y access
policies and powe gene a ion planning. They a gue ha ecognizing hese needs is c i ical o
o ecas ing u u e esiden ial elec ici y demand.
Thomson e al. (2019) a gue o a ee alua ion o ene gy policy amewo ks, pa icula ly in he
con ex o yea - ound ulne abili y o hea . Meles (2020) highligh s he o en o e looked issue o
elec ici y supply eliabili y in de eloping coun ies. Focusing on u ban households, he s udy
c i iques he p e ailing na a i e ha equa es elec ici y access wi h e ec i e elec i ica ion. Meles
emphasizes ha wi hou a eliable elec ici y supply, he bene i s o elec i ica ion a e no ully
ealized since equen powe ou ages esul in households incu ing addi ional expendi u es o
compensa e.
Powe ou ages p esen a unique challenge o households in de eloping coun ies. Lee e al. (2024)
highligh he sho comings o passi e cooling measu es unde ex eme hea condi ions and he
c i ical ole o ai -condi ioning o ensu e he mal com o du ing powe ou ages. Thei s udy
unde sco es he need o bo h passi e and ac i e cooling solu ions o p o ec ulne able
popula ions om hea - ela ed heal h isks.
3
Despi e he ex ensi e li e a u e on cooling demands and ene gy esilience, s udies on he in luence
o powe ou ages on household cooling decisions emain limi ed, pa icula ly wi h espec o
Cen al Asia. This s udy aims o ill his gap by examining he in e play be ween CDDs, powe
ou ages, and household cooling choices in he Ky gyz Republic, Uzbekis an, and Tajikis an. By
explo ing how households in hese coun ies adap hei cooling s a egies o powe ou ages and
inc easing empe a u es, his esea ch o e s insigh s in o he socioeconomic and beha io al
dimensions o ene gy esilience in Cen al Asia.
3. Me hodology
3.1 Da a
This s udy u ilizes da a om he 2023 Household Access o Ene gy in he Fe gana Valley su ey,
which was conduc ed by he Cen al Asia Regional Economic Coope a ion Ins i u e (CAREC) in
pa ne ship wi h he Asian De elopmen Bank Ins i u e (ADBI) and he Public Opinion Resea ch
Ins i u e in Kazakhs an. A o al o 1,522 esponden s we e in e iewed in July-Augus 2023,
comp ising 522 esponden s in he Ky gyz Republic, 500 in Tajikis an and 500 in Uzbekis an. The
su ey aimed o gene a e de ailed da a abou ene gy access in a ela i ely compac and
compa able a ea ha spans pa s o Uzbekis an, he Ky gyz Republic, and Tajikis an. I ga he ed
de ailed in o ma ion on ene gy use o a ious pu poses, as well as he sociodemog aphic
cha ac e is ics o heads o households. Among o he hings, he su ey included de ailed
in o ma ion on household cooling sys ems and he eliabili y o powe . Mo e in o ma ion abou he
su ey can be ound in Holzhacke e al. (2024); Sulaimano a, Azhgaliye a and Holzhacke
(2024); Azhgaliye a, Holzhacke , Rahu , and Co eia (2024); and Azhgaliye a, Kodama and
Holzhacke (2025).
To analyze cooling demand in he con ex o clima e change, CDD da a we e inco po a ed in o he
s udy. These me eo ological da a, sou ced om he NASA POWER P ojec , a e eely a ailable.
3.2 Model Speci ica ion
To analyze he ac o s in luencing household cooling choices, we employ a mul inomial p obi
model, which accoun s o mul iple ca ego ical ou comes. In his s udy, he ca ego ical ou comes
ep esen he choice o cooling sys em. The base ca ego y is households wi hou any cooling
sys em, agains which he likelihood o adop ing (i) ai -condi ioning and/o (ii) ans and/o
sunsc een ilms (wi hou ai -condi ioning) is es ima ed. The model allows he es ima ion o he
p obabili y ha a household will selec one o he a ailable cooling op ions based on a se o
explana o y a iables. The gene al o m o he mul inomial p obi model is as ollows:
P �𝑦𝑦𝑖𝑖=𝑚𝑚𝑚 𝑋𝑋𝑖𝑖,𝛽𝛽,𝑢𝑢𝑖𝑖𝑖𝑖�=Φ�𝑦𝑦𝑖𝑖=𝑚𝑚, 𝑋𝑋𝑖𝑖𝛽𝛽𝑖𝑖+𝑢𝑢𝑖𝑖𝑖𝑖�=
exp ( 𝑋𝑋
𝑖𝑖
𝛽𝛽
𝑚𝑚
+𝑢𝑢
𝑖𝑖𝑚𝑚
)
∑exp ( 𝑋𝑋𝑖𝑖𝑖𝑖𝛽𝛽𝑖𝑖+𝑢𝑢𝑖𝑖𝑖𝑖)
𝐽𝐽
𝑖𝑖=1
(1)
whe e:
• P �𝑦𝑦𝑖𝑖=𝑚𝑚𝑚 𝑋𝑋𝑖𝑖𝑖𝑖,𝛽𝛽,𝑢𝑢𝑖𝑖𝑖𝑖� is he p obabili y ha household i adop s cooling echnology j, whe e
m=1 e e s o ai -condi ioning, m=2 e e s o ans o sunsc een ilms (wi hou ai -
condi ioning), and m=3 e e s o no cooling sys em (base ou come).
• 𝑋𝑋𝑖𝑖 ep esen s he se o explana o y a iables o household i.
• 𝛽𝛽𝑖𝑖 a e he coe icien s o be es ima ed o each cooling echnology j.
4
• Φ deno es he cumula i e dis ibu ion unc ion o he s anda d no mal dis ibu ion, used o
model he likelihood o di e en ou comes.
The mul inomial p obi model is es ima ed using maximum likelihood es ima ion (MLE), which
enables he simul aneous es ima ion o he p obabili ies o each household choosing one o he
h ee cooling sys em op ions. These p obabili ies a e condi ioned on household cha ac e is ics,
powe supply a iables, and CDD condi ions.
The analysis is pe o med on bo h he o al sample and subsamples, including u ban e sus u al
households and male-headed e sus emale-headed households. This app oach allows he
explo a ion o he e ogenei y in cooling echnology adop ion ac oss di e en demog aphic and
geog aphic g oups.
Sensi i i y analyses a e conduc ed o assess he s abili y o he es ima ed coe icien s in he main
model. This is done by inco po a ing he du a ion o powe ou ages, hus p o iding a mo e nuanced
unde s anding o he ela ionship be ween elec ici y eliabili y and he adop ion o cooling
echnologies, as well as es ing he obus ness o he es ima ed coe icien s.
Ou come Va iable
Table 1 p esen s he desc ip i e s a is ics o he ou come a iable, summa izing household
cooling p e e ences ac oss he h ee coun ies as well as o he o al sample. Op ion 1, ai -
condi ioning, is he leas common in he Ky gyz Republic, whe e only 9.20% o households ha e
selec ed i as hei p ima y cooling me hod. Adop ion a es o ai -condi ioning a e highe in
Tajikis an (35.40%) and Uzbekis an (20.60%).
Table 1. Desc ip i e S a is ics o Ou come Va iable–Household Cooling Op ions
Ou come Va iable
Coun y
Household cooling choices
Ky gyz
Republic
Tajikis an
Uzbekis an
To al
Op ion 1 - ai -condi ioning
48
177
103
328
9.20%
35.40%
20.60%
21.55%
Op ion 2 - an o sunsc een ilms o windows
(wi hou ai -condi ioning)
264
147
325
736
50.57%
29.40%
65.00%
48.36%
Op ion 3 - no cooling sys em
210
176
72
458
40.23%
35.20%
14.40%
30.09%
To al
522
500
500
1522
100%
100%
100%
100%
No e: Fi s ow has equencies and second ow has column pe cen ages.
Sou ce: Au ho s’ calcula ions using da a om 2023 Household Access o Ene gy in he Fe gana Valley su ey.
Op ion 2, ans and/o sunsc een ilms o windows (wi hou ai -condi ioning), is mo e p e alen ,
accoun ing o 48.36% o households co e ed by he su ey. In Uzbekis an, 65% o households
ha e adop ed his me hod, while he p opo ion d ops o 50.57% in he Ky gyz Republic and
29.40% in Tajikis an.
11
Unlike he case o ai -condi ioning, powe ou ages (scheduled o olling blackou s) do no
signi ican ly de e households om selec ing ans o sunsc een ilms, e lec ing he lowe ene gy
dependency o hese al e na i es.
The p e e ence o ans o sunsc een ilms (wi hou ai -condi ioning) as a cooling me hod is
in luenced by household size, wi h la ge households mo e likely o op o his al e na i e. This
may be a ibu able o he ela i ely lowe cos s and ene gy demands associa ed wi h hese
op ions, making hem mo e sui able o households wi h g ea e economic cons ain s. Though
less in luen ial (only a 10% le el o signi icance) han o ai -condi ioning (a 5% le el o
signi icance), income s ill plays a ole, wi h middle-income households showing a posi i e bu
weake associa ion wi h he adop ion o ans o sc eens (as opposed o ha ing no cooling me hod).
Income has no signi ican impac a 5% le el o signi icance on he likelihood o ha ing ans o
sunsc eens, p obably due o hei g ea e a o dabili y han ai -condi ioning. An inc ease in
household size is associa ed wi h a highe p obabili y o adop ing ans and/o sunsc een ilms as
cooling echnologies. Howe e , a g ea e numbe o child en in he household nega i ely a ec s
he likelihood o choosing hese cooling me hods, mi o ing he pa e n obse ed o ai -
condi ioning. In o he wo ds, households wi h mo e child en a e mo e likely o ha e no cooling
me hod a all.
These empi ical indings e eal ha he adop ion o ai -condi ioning is p edominan ly d i en by
highe educa ion and income, along wi h u ban esidency and eliable powe supply and clima ic
condi ions, while he adop ion o ans o sunsc een ilms is p edominan ly d i en by household size
and clima ic ac o s. These indings unde sco e he impo ance o add essing he in as uc u al
challenges such as he un eliabili y o elec ici y supply o ensu e equi able access o cooling
solu ions in Cen al Asia.
12
Table 6. Mul inomial P obi Model Coe icien Es ima es o Household Cooling Choices
(Main Model)
To al
Sample
HH Residence
HH Head Gende
U ban
Ru al
Male
Female
(1)
(2)
(3)
(4)
(5)
Ai -condi ioning
HH head age
-0.005
-0.001
-0.008
-0.007
-0.004
(0.004)
(0.007)
(0.005)
(0.006)
(0.006)
HH head gende (1=male)
0.026
0.109
0.007
(0.116)
(0.190)
(0.150)
Te ia y educa ion le el
0.755***
1.125***
0.563***
0.429**
1.188***
(0.128)
(0.214)
(0.166)
(0.174)
(0.196)
Household size
0.032
0.079
0.020
-0.029
0.099**
(0.030)
(0.052)
(0.038)
(0.043)
(0.045)
Sha e o child en in HH
-0.950***
-1.698***
-0.548
-0.822*
-1.034**
(0.329)
(0.524)
(0.431)
(0.459)
(0.486)
Sha e o senio s in HH
0.538*
0.102
0.761*
0.308
0.831*
(0.322)
(0.536)
(0.412)
(0.454)
(0.461)
Middle income le el
0.401**
0.667**
0.370*
0.252
0.587**
(0.174)
(0.302)
(0.224)
(0.246)
(0.254)
Highes income le el
0.475***
0.170
0.680***
0.374*
0.572***
(0.146)
(0.235)
(0.192)
(0.208)
(0.212)
Residence (1=u ban)
0.456***
0.528***
0.417**
(0.126)
(0.175)
(0.183)
Log CDD
0.381***
0.614**
0.287*
0.542***
0.177
(0.145)
(0.289)
(0.173)
(0.197)
(0.221)
Scheduled o olling blackou s
(1 = powe ou ages)
-0.260**
-0.219
-0.288*
-0.240
-0.302*
(0.121)
(0.196)
(0.157)
(0.169)
(0.176)
Coun y ixed e ec s
+
+
+
+
+
Cons an
-3.942***
-4.940**
-3.463***
-4.376***
-3.312**
(0.993)
(1.975)
(1.184)
(1.329)
(1.512)
Fans and/o sunsc een ilms (wi hou ai -condi ioning)
HH head age
-0.002
-0.000
-0.003
-0.004
-0.000
(0.004)
(0.007)
(0.004)
(0.005)
(0.005)
HH head gende (1=male)
-0.001
0.126
-0.057
(0.101)
(0.179)
(0.124)
Te ia y educa ion le el
0.068
0.273
-0.007
-0.046
0.191
(0.122)
(0.216)
(0.151)
(0.165)
(0.186)
Household size
0.079***
0.116**
0.059*
0.024
0.130***
(0.026)
(0.048)
(0.031)
(0.035)
(0.039)
Sha e o child en in HH
-0.694**
-1.438***
-0.288
-0.357
-0.956**
(0.287)
(0.483)
(0.363)
(0.413)
(0.407)
Sha e o senio s in HH
0.160
-0.464
0.463
0.238
0.124
(0.298)
(0.516)
(0.367)
(0.427)
(0.414)
Middle income le el
0.275*
0.491*
0.255
0.287
0.235
(0.151)
(0.277)
(0.187)
(0.221)
(0.209)
Highes income le el
0.011
-0.253
0.178
-0.026
0.027
(0.131)
(0.224)
(0.165)
(0.191)
(0.183)
Residence (1=u ban)
-0.114
-0.044
-0.159
(0.113)
(0.160)
(0.163)
Log CDD
0.435***
0.181
0.553***
0.520***
0.352*
(0.130)
(0.256)
(0.153)
(0.181)
(0.188)
Scheduled o olling blackou s
(1 = powe ou ages)
0.025
0.095
-0.039
-0.010
0.068
(0.107)
(0.187)
(0.132)
(0.148)
(0.155)
Coun y ixed e ec s
+
+
+
+
+
Cons an
-2.947***
-1.333
-3.777***
-3.198**
-2.670**
(0.910)
(1.791)
(1.073)
(1.250)
(1.328)
Con inued on he nex page
13
To al
Sample
HH Residence
HH Head Gende
U ban
Ru al
Male
Female
(1)
(2)
(3)
(4)
(5)
Numbe o obs.
1522
557
965
763
759
Log likelihood
-1405.14
-516.69
-875.18
-706.23
-687.05
Chi2
337.83
138.08
199.27
179.18
174.87
P obabili y
0.000
0.000
0.000
0.000
0.000
CDD=cooling deg ee days, HH=households.
No e: Base ou come is “no cooling sys em”. Robus s anda d e o s a e p esen ed in pa en heses. *p<0.10; **p<0.05;
***p<0.010
Sou ce: Au ho s’ calcula ions using da a om 2023 Household Access o Ene gy in he Fe gana Valley su ey.
4.2 Robus ness Analysis: Powe Ou age Du a ion
The mul inomial p obi model es ima es in Table 7 examine he ac o s in luencing households’
choices o cooling sys ems unde a ying powe ou age du a ions. To es he obus ness and
sensi i i y o ou indings, we eplace he bina y dummy a iable o powe ou ages used in he
main model wi h a ca ego ical a iable ep esen ing di e en du a ions: (i) 1–16 hou s, (ii) 17–50
hou s, and (iii) 50–200 hou s.
I is impo an o no e ha da a on powe ou age du a ion was incomple e, as 126 households
esponded wi h “di icul o answe ,” esul ing in missing obse a ions. Consequen ly, he
es ima ion sample is educed o 1,398 obse a ions. Despi e he educ ion in he numbe o
obse a ions, he es ima ed e ec s o he con ol a iables emain consis en and s a is ically
signi ican . This sugges s ha inco po a ing a mo e de ailed measu e o powe ou age du a ion
does no al e he key ela ionships iden i ied in he main model, ein o cing he obus ness o ou
esul s.
As in he main model, he du a ion o powe ou ages signi ican ly and nega i ely in luences
households’ likelihood o adop ing ai -condi ioning sys ems, pa icula ly in u al a eas. This inding
highligh s he p ac ical cons ain s ha p olonged powe ou ages impose on he unc ionali y and
u ili y o ene gy-in ensi e appliances, making hem less easible o households ha ace equen
o ex ended powe dis up ions. By con as , he in luence o powe ou age du a ion on he adop ion
o less ene gy-in ensi e cooling op ions ( ans o sunsc een ilms), is less p onounced, as i is in
he main model indings. This sugges s ha households acing p olonged powe ou ages may
p io i ize al e na i e cooling me hods ha a e less dependen on a s able elec ici y supply.
The CDD a iable also exhibi s esul s simila o hose in he main model when he dummy a iable
o powe ou ages is eplaced. CDD emains posi i ely signi ican , indica ing ha households a e
mo e likely o adop cooling solu ions in esponse o clima ic s ess and he immedia e need o
he mal com o .
14
Table 7. Mul inomial P obi Model Coe icien Es ima es (Powe Ou age Du a ion)
To al
Sample
HH Residence
HH Head Gende
U ban
Ru al
Male
Female
Ai -condi ioning
HH head age
-0.006
-0.000
-0.010*
-0.005
-0.007
(0.004)
(0.007)
(0.006)
(0.006)
(0.007)
HH head gende (1=male)
0.121
0.144
0.138
(0.123)
(0.199)
(0.161)
Te ia y educa ion le el
0.786***
1.070***
0.622***
0.421**
1.237***
(0.136)
(0.223)
(0.179)
(0.185)
(0.208)
Household size
0.029
0.021
0.040
-0.028
0.084*
(0.032)
(0.054)
(0.039)
(0.045)
(0.047)
Sha e o child en in HH
-0.838**
-1.410***
-0.570
-0.552
-1.208**
(0.346)
(0.539)
(0.463)
(0.485)
(0.503)
Sha e o senio s in HH
0.517
-0.172
0.876**
0.410
0.632
(0.339)
(0.548)
(0.440)
(0.475)
(0.481)
Middle income le el
0.368**
0.660**
0.310
0.222
0.547**
(0.186)
(0.315)
(0.242)
(0.263)
(0.271)
Highes income le el
0.318**
0.157
0.467**
0.249
0.415*
(0.158)
(0.249)
(0.212)
(0.227)
(0.228)
Residence (1=u ban)
0.463***
0.466**
0.497**
(0.132)
(0.183)
(0.194)
Log CDD
0.414***
0.538*
0.311*
0.604***
0.193
(0.154)
(0.304)
(0.187)
(0.204)
(0.242)
Du a ion o powe ou ages: 1-16 hou s
-0.051
-0.209
0.007
0.207
-0.325
(0.164)
(0.275)
(0.204)
(0.228)
(0.238)
Du a ion o powe ou ages: 17-50 hou s
-0.455**
-0.119
-0.736**
-0.413
-0.544*
(0.201)
(0.292)
(0.302)
(0.262)
(0.320)
Du a ion o powe ou ages: 50-200 hou s
-0.132
0.001
-0.221
-0.234
-0.098
(0.187)
(0.280)
(0.263)
(0.264)
(0.276)
Coun y ixed e ec s
+
+
+
+
+
Cons an
-4.128***
-4.306**
-3.583***
-4.879***
-3.045*
(1.063)
(2.079)
(1.287)
(1.383)
(1.664)
Fand and/o Sunsc een Films
HH head age
-0.005
-0.003
-0.006
-0.005
-0.005
(0.004)
(0.007)
(0.005)
(0.005)
(0.005)
HH head gende (1=male)
0.066
0.138
0.036
(0.105)
(0.186)
(0.130)
Te ia y educa ion le el
0.086
0.262
0.020
-0.082
0.253
(0.128)
(0.225)
(0.161)
(0.174)
(0.196)
Household size
0.075***
0.095*
0.055*
0.019
0.119***
(0.027)
(0.050)
(0.033)
(0.036)
(0.040)
Sha e o child en in HH
-0.566*
-1.390***
-0.102
-0.144
-0.992**
(0.301)
(0.504)
(0.382)
(0.430)
(0.432)
Sha e o senio s in HH
0.122
-0.651
0.531
0.294
-0.051
(0.312)
(0.525)
(0.392)
(0.448)
(0.430)
Middle income le el
0.082
0.339
0.035
0.085
0.050
(0.162)
(0.292)
(0.202)
(0.239)
(0.223)
Highes income le el
-0.208
-0.390
-0.064
-0.224
-0.204
(0.142)
(0.238)
(0.181)
(0.209)
(0.196)
Residence (1=u ban)
-0.112
-0.087
-0.114
(0.118)
(0.167)
(0.169)
Log CDD
0.481***
0.228
0.564***
0.608***
0.363*
(0.137)
(0.269)
(0.162)
(0.190)
Con inued on he nex page
15
To al
Sample
HH Residence
HH Head Gende
U ban
Ru al
Male
Female
Du a ion o powe ou ages: 1-16 hou s
0.197
-0.055
0.261
0.318
0.095
(0.151)
(0.278)
(0.182)
(0.220)
(0.209)
Du a ion o powe ou ages: 17-50 hou s
0.066
0.353
-0.133
-0.073
0.207
(0.162)
(0.261)
(0.209)
(0.225)
(0.238)
Du a ion o powe ou ages: 50-200 hou s
0.160
0.347
0.013
0.133
0.200
(0.151)
(0.258)
(0.190)
(0.211)
(0.219)
Coun y ixed e ec s
+
+
+
+
+
Cons an
-3.077***
-1.385
-3.672***
-3.691***
-2.366*
(0.956)
(1.886)
(1.131)
(1.312)
(1.408)
Numbe o obs.
1398
524
874
704
694
Log likelihood
-
1279.55
-484.21 -781.72 -645.67 -622.49
Chi2
314.69
126.73
187.85
170.49
157.59
P obabili y
0.000
0.000
0.000
0.000
0.000
CDD=cooling deg ee days, HH=households.
No e: Base ou come is “no cooling sys em”. Robus s anda d e o s a e p esen ed in pa en heses. *p<0.10; **p<0.05;
***p<0.010.
Sou ce: Au ho s’ calcula ions using da a om 2023 Household Access o Ene gy in he Fe gana Valley su ey.
5. Conclusion and Policy Implica ions
This s udy in es iga es he ac o s in luencing household choices ega ding cooling echnologies
in Cen al Asia, ocusing on ai -condi ioning and ans/sunsc een ilms. U ilizing da a om he
“Household Access o Ene gy in he Fe gana Valley” su ey conduc ed in he Ky gyz Republic,
Tajikis an, and Uzbekis an, he analysis examines how socioeconomic, en i onmen al, and powe
supply ac o s shape household decisions. Employing a mul inomial p obi model, his s udy
analyzes he de e minan s o adop ing di e en cooling echnologies, highligh ing he in e ac ion
be ween clima ic condi ions and powe supply eliabili y. The esea ch p o ides aluable insigh s
in o he ac o s shaping household cooling choices in Cen al Asia, wi h pa icula emphasis on he
ole o powe supply in as uc u e and clima ic condi ions. The indings unde sco e he impo ance
o add essing bo h powe sec o eliabili y and clima e adap a ion in ulne able egions. Key esul s
include he signi ican impac o cooling deg ee days on cooling appliance adop ion and he c i ical
ole o powe ou ages in in luencing he choice o cooling echnologies.
Fi s , a signi ican numbe o su eyed households (48.36%) ely on ans and/o sunsc een ilms
o windows o cooling (wi hou ai -condi ioning). In Uzbekis an, 65% o su eyed households
ha e adop ed his me hod, while he p opo ion d ops o 50.57% in he Ky gyz Republic and
29.40% in Tajikis an. Addi ionally, 14.40% o su eyed households in Uzbekis an ha e no cooling
sys em. The co esponding igu es in Tajikis an and he Ky gyz Republic a e highe a 35.20% and
40.23%, espec i ely, sugges ing inc eased household ulne abili y o hea in hese wo coun ies.
Second, cooling deg ee days signi ican ly impac he adop ion o cooling appliances. The cooling
season p ima ily spans om May o Sep embe , wi h CDD anging om 246 o 1,641 in he
Fe gana Valley. App oxima ely one- hi d o su eyed households li e in egions wi h CDD 1,500
and abo e, which is conside ed high. Households in a eas wi h highe CDD a e mo e likely o
adop cooling solu ions (ai -condi ioning, ans, o sunsc een ilms). The analysis unde sco es he
impo ance o clima ic condi ions, pa icula ly CDDs, in in luencing cooling echnology adop ion.
This inding highligh s households’ adap i e beha io in esponse o clima ic s ess, demons a ing
ha cooling choices a e shaped by bo h socioeconomic ac o s and en i onmen al cons ain s.
16
In eg a ing clima ic da a such as CDD in o he analysis o household ene gy choices p o ides
c i ical insigh s in o adap i e beha io unde di e en en i onmen al condi ions.
Thi d, powe ou ages nega i ely impac he adop ion o ene gy-in ensi e cooling echnologies like
ai -condi ioning bu ha e no e ec on less ene gy-in ensi e op ions like ans and sunsc een ilms.
Powe s abili y is c ucial o adap ing o hea using ene gy-in ensi e echnologies (e.g., ai -
condi ioning) in ho e a eas du ing he peak cooling mon hs (May–Sep embe ) in Cen al Asia.
Fans and sunsc een ilms, which a e less ene gy-in ensi e han ai -condi ioning, a e mo e
commonly used in a eas whe e powe ou ages a e a signi ican conce n. This esul highligh s he
impo ance o powe eliabili y o adop ing ene gy-in ensi e cooling echnologies, sugges ing ha
ai -condi ioning adop ion is cons ained by economic and in as uc u al ba ie s. I also
emphasizes he impo ance o less ene gy-in ensi e cooling echnologies (e.g., ans, sunsc een
ilms, and o he op ions no included in his s udy, such as ene gy e iciency measu es and
cou ya ds in building design) in egions wi h un eliable elec ici y access.
The s udy assessed he obus ness o i s indings by conside ing he du a ion o powe ou ages
wi h h ee dummy a iables ep esen ing di e en ou age du a ions. This analysis con i med ha
he eliabili y o powe supply plays a c i ical ole in shaping cooling choices. Speci ically,
households in a eas p one o equen o p olonged powe ou ages a e less likely o adop ai -
condi ioning.
The e a e many measu es o adap ing o hea s ess (Shen, Azhgaliye a, and Baño Leal, 2024).
We sugges se e al based on he s udy's esul s. Enhanced powe supply eliabili y is c ucial o
suppo ing he adop ion o ene gy-in ensi e cooling echnologies like ai -condi ioning. Sola
panels can help mee summe ene gy demand, as sola i adia ion co ela es wi h cooling needs,
pa icula ly in egions wi h high cooling equi emen s. Suppo can p io i ize ulne able households
in egions wi h high hea exposu e and un eliable powe supply.
Based on his s udy, he ollowing sugges ions o u u e esea ch a e p oposed. Fi s , his s udy
ocused on a limi ed ange o cooling solu ions: ai -condi ioning, ans, and sunsc een ilms. Fu u e
esea ch should explo e addi ional hea adap a ion op ions, such as building codes and passi e
cooling echniques in building design. These include imp o ed insula ion (Sulaimano a,
Azhgaliye a, and Holzhacke , 2024), e lec i e oo ing, and na u al en ila ion, which can
signi ican ly educe ene gy demand o cooling and aid in hea wa e adap a ion. I he e is a need
o such suppo , i should be accompanied by aining o echnicians and o he s akeholde s on
he ins alla ion and main enance o ene gy-e icien and passi e cooling echnologies. Addi ionally,
loca ion-speci ic cooling measu es a e impo an . U ban planning s a egies, such as inco po a ing
g een spaces and wa e bodies, can educe u ban hea island e ec s and lowe cooling demands.
Communi y cooling cen e s can also p o ide immedia e elie du ing hea wa es. Second, while
we iden i ied he signi ican impac o powe ou ages on cooling choices, we did no in es iga e he
causes o hese ou ages. Unde s anding he causes can help p o ide be e policy
ecommenda ions o add ess powe ou ages. Thi d, we did no ake in o accoun elec ici y a i s
and he impac o hei g ow h. While he pape highligh s powe ou ages and g id ins abili y as key
ba ie s o adop ing ene gy-in ensi e cooling echnologies, ano he c i ical ac o wo h conside ing
is he cos o elec ici y and i s g ow h. The inc ease in elec ici y a i s could signi ican ly hinde
he adop ion and sus ained use o ai -condi ioning, pa icula ly among low- and middle-income
households in u al a eas, who a e al eady inancially cons ained. Many u al households may
al eady be op ing o lowe ene gy al e na i es—such as ans and sunsc een ilms— o minimize
elec ici y expenses.
17
APPENDIX
Table A1. Ma ix o Co ela ions
HH
head
age
HH head
gende
(1=male)
Te ia y
educa ion
le el
HH size
Sha e o
child en
in HH
Sha e
o
senio s
in HH
Middle
income
le el
Highes
income
le el
Residence
(1=ci y) CDD
Blackou s
(1 = powe
ou ages)
Du a ion
o powe
ou ages
(hou s)
HH head age
1
HH head gende (1=male)
-0.008
1
Te ia y educa ion le el
-0.067
0.078
1
Household size
0.042
0.043
-0.067
1
Sha e o child en in HH
-0.049
-0.033
0.043
0.389
1
Sha e o senio s in HH
0.329
0.032
-0.017
-0.043
-0.324
1
Middle income le el
-0.01
0.006
-0.043
-0.01
0.041
0.003
1
Highes income le el
-0.023
0.028
0.074
0.18
0.063
-0.097
-0.573
1
Residence (1=ci y)
0.078
-0.042
0.04
-0.104
-0.04
-0.01
-0.083
0.008
1
CDD
0.074
-0.053
0.011
-0.102
-0.153
0.096
-0.087
-0.132
0.171
1
Scheduled o olling
blackou s
(1 = powe ou ages)
0.125
-0.017
-0.029
0.119
0.032
-0.032
-0.004
0.023
0.013
0.044
1
A e age mon hly du a ion
o powe ou ages (hou s)
0.143
-0.008
-0.05
0.051
-0.031
0.003
-0.001
-0.019
0.053
0.181
0.61
1
CDD=cooling deg ee days, HH=households.
Sou ce: Au ho s’ calcula ions using da a om 2023 Household Access o Ene gy in he Fe gana Valley su ey.
18
Table A2. Desc ip i e S a is ics o Cooling Deg ee Days by Region in 2023
Ky gyz Republic
Tajikis an
Uzbekis an
35 egions
CDD
N
8 egions
CDD
N
50 egions
CDD
N
Achi
739.14
13
Ash
1,500.06
54
Akhunboboe
1,525.67
10
Ak-Tu pak pa ially
246.07
15
B. Ga u o
585.8
120
Ami abod
1,640.78
10
Andijan
1,183.37
13
Is a a
434.61
17
Andijan
1,183.37
10
A al
1005.7
13
Is a a shan
1,088.72
89
A al
1,005.7
10
Asanchek
468.36
13
J.Rasulo
944.34
45
Asaka
1,005.7
9
Ba ken
434.61
20
Khujand
1,292.56
61
Baghdad
1,640.78
10
Baza -Ko gon
297.58
12
Konibodom
1,500.06
68
Besa ang
1,525.67
10
Bege
1,183.37
13
Spi amen
944.34
46
Bozo boshi
1,525.67
10
Byu gendyu
1,183.37
13
Cha ak
1,625.48
10
Changy -Tash
1,183.37
13
Chinabad
1,625.48
10
Dzhany-Abad
1,183.37
12
Chus
1,251.78
10
Jalal-Abad
739.14
20
E epa
1,625.48
10
Ka a-Sege
468.36
13
Ezgulik
1,251.78
10
Ka a-Suu
468.36
20
Fe gana
1,525.67
10
Khauz
1005.7
13
Gais on
1,625.48
10
Kochko -A a
1,183.37
25
Ga midan
1,525.67
10
Kolo
1,183.37
12
Gi on
1,625.48
10
Ky gyz-Kysh ak
1,640.78
15
Ka askan
1,625.48
10
Kyumyush-Aziz
739.14
13
Khojaabad
1005.7
10
Kyzyl-Abad
468.36
13
Kokand
1,500.06
10
Langa
468.36
13
Ko asu
468.36
9
Madaniya
468.36
13
Ko ayan ok
1,005.7
10
Min-Chyna
1,640.78
15
Ku gan eppa
1,005.7
10
Mogol-Ko gon
1,183.37
13
Ku a
1,525.67
10
Munduz (Kyzyl-Tuu)
739.14
13
Ku asai
1,525.67
10
Munduz (Saipidin A abek)
667.19
13
Loison
1,525.67
10
Naiman
1,251.78
13
Ma gilan
1,525.67
10
Ok yab
1,005.7
13
Maslaha
1,625.48
10
Osh ci y
1,005.7
45
Mi abad
1,183.37
10
Pakh achi
1,005.7
13
Naiman
1,251.78
10
Telman
468.36
13
Namangan
1,625.48
10
Tepe Ko gon
1,005.7
13
Naza mah am
1,525.67
10
Za -Tash
1,640.78
15
Okbilol
1,525.67
10
Za balik
468.36
13
Okmozo
1,183.37
10
Zhapalak
1005.7
10
Ok osh
1,251.78
10
Olmos
1,251.78
10
Poy ug
1,183.37
12
Rish an
1,640.78
10
.
Sa iku gan
1,525.67
10
Shah ikhan
1,525.67
10
Tepaku gan
1,251.78
10
Tinchlik
1,640.78
10
Tulaboi
1,500.06
10
Tu aku gan
1,251.78
10
Uchkuza
1,183.37
10
Uychi
1,625.48
10
Yaipan
1,500.06
10
Yangiku gan
1,625.48
10
Yozyo on
1,525.67
10
Z u kan
1,251.78
10
To al
892.5696
522
To al
1,044.738
500
To al
1,403.894
500
CDD=cooling deg ee days.
Sou ce: Au ho s’ calcula ions using he da a was ob ained om POWER P ojec 's Hou ly 2.4.9 on 2025/02/21
h ps://powe .la c.nasa.go /da a-access- iewe /.
19
REFERENCES
A ia, S., Le inson, R., Ndongo, E., Holze , P., Kazanci, O. B., Homaei, S., ... and Heiselbe g, P.
2021. Resilien cooling o buildings o p o ec agains hea wa es and powe ou ages:
Key concep s and de ini ion. Ene gy and Buildings, 239, 110869.
Azhgaliye a, D., Kodama, W., and Holzhacke , H. 2025. Does awa eness and p io i iza ion o
en i onmen and heal h ma e o household uel choice? Empi ical e idence om
Cen al Asia. Ene gy Resea ch & Social Science, 120,
h ps://doi.o g/10.1016/j.e ss.2024.103898.
Azhgaliye a, D., Holzhacke , H., Rahu , D., and Co eia, J. 2024. Empowe ed Women P io i ize
he En i onmen al and Heal h Impac s o Fuel Choice: Empi ical E idence om Cen al
Asia. ADBI Wo king Pape 1482. Tokyo: Asian De elopmen Bank Ins i u e. A ailable:
h ps://doi.o g/10.56506/HDYJ7785
Ba dhan, R., Debna h, R., Gama, J., and Vijay, U. 2020. REST amewo k: A modelling
app oach owa ds cooling ene gy s ess mi iga ion plans o u u e ci ies in wa ming
Global Sou h. Sus ainable Ci ies and Socie y, 61, 102315.
Falche a, G. and Mis y, M. N. 2021. The ole o esiden ial ai ci cula ion and cooling demand
o elec i ica ion planning: Implica ions o clima e change in sub-Saha an A ica. Ene gy
Economics, 99, 105307.
Falche a, G., De Cian, E., Sue Wing, I., and Ca , D. 2024. Global p ojec ions o hea exposu e
o olde adul s. Na u e Communica ions, 15(1), 3678.
Holzhacke , H., Azhgaliye a D., Rakishe a, B., Ib aye a, A., Ku mangazhino a, A., Yessimo a,
K., e al. 2024. Household Access o Ene gy in he Fe gana Valley: A Mul idimensional
Su ey-based Assessmen in Th ee CAREC Coun ies, CAREC Ins i u e.
h ps://opinions.kz/images/books/P ojec -Repo -Fe gana-Valley.pd
Hu, S., Yan, D., Dong, B., and Fu, J. 2020. Explo ing key ac o s impac ing cooling usage
pa e ns o Chinese u ban household based on a la ge-scale ques ionnai e
su ey. Ene gy and Buildings, 214, 109885.
Jia, S., Weng, Q., Yoo, C., Xiao, H., & Zhong, Q. 2024. Building ene gy sa ings by g een oo s
and cool oo s in cu en and u u e clima es. npj U ban Sus ainabili y, 4(1), 23.
Lee, S. H., Hong, T., Le, M., Medina, L., Xu, Y., Robinson, A., and Pie e, M. A. 2024.
Assessmen o ene gy and he mal esilience pe o mance o in o m clima e mi iga ion o
mul i amily buildings in disad an aged communi ies. Sus ainable Ci ies and Socie y, 104,
105319.
Li, Z., Fang, G., Chen, Y., Duan, W., and Mukano , Y. 2020. Ag icul u al wa e demands in
Cen al Asia unde 1.5 C and 2.0 C global wa ming. Ag icul u al Wa e
Managemen , 231, 106020.
Liu, Y., Geng, X., Hao, Z., and Zheng, J. (2020). Changes in clima e ex emes in Cen al Asia
unde 1.5 and 2 C global wa ming and hei impac s on ag icul u al
p oduc ions. A mosphe e, 11(10), 1076.
20
Meh a, K., Eh enwi h, M., T inkl, C., Zö ne , W., & G eenough, R. 2021. The ene gy si ua ion in
Cen al Asia: A comp ehensi e ene gy e iew ocusing on u al a eas. Ene gies, 14(10),
2805.
Meles, T. H. 2020. Impac o powe ou ages on households in de eloping coun ies: E idence
om E hiopia. Ene gy Economics, 91, 104882.
Musho e, T. D., Odindi, J., Dube, T., and Mu anga, O. 2017. Unde s anding he ela ionship
be ween u ban ou doo empe a u es and indoo ai -condi ioning ene gy demand in
Zimbabwe. Sus ainable Ci ies and Socie y, 34, 97-108.
Nema choua, M. K., Y on, A., Kalameu, O., Asadi, S., Choudha y, R., and Rei e , S. 2019.
Impac o clima e change on demands o hea ing and cooling ene gy in hospi als: An in-
dep h case s udy o six islands loca ed in he Indian Ocean egion. Sus ainable Ci ies
and Socie y, 44, 629-645.
Pa anello, F., De Cian, E., Da ide, M., Mis y, M., C uz, T., Beze a, P., ... and Lucena, A. F.
2021. Ai -condi ioning and he adap a ion cooling de ici in eme ging economies. Na u e
communica ions, 12(1), 6460.
Radhi, H., & Sha ples, S. 2013. Quan i ying he domes ic elec ici y consump ion o ai -
condi ioning due o u ban hea islands in ho a id egions. Applied Ene gy, 112, 371-380.
Shen, B., Azhgaliye a, D., Baño Leal, A. 2024 Sus ainable Cooling: How o Cool he Wo ld
Wi hou Wa ming he Plane , ADBI P ess, h ps://doi.o g/10.56506/MAGR4101
Sulaimano a, B., Azhgaliye a, D., and Holzhacke , H. 2024. House insula ion: Pe cei ed needs
and willingness in Cen al Asia, ADBI Wo king Pape , No. 1478, Asian De elopmen
Bank Ins i u e, Tokyo, h ps://doi.o g/10.56506/NLWV6429
Thomson, H., Simcock, N., Bouza o ski, S., and Pe o a, S. 2019. Ene gy po e y and indoo
cooling: An o e looked issue in Eu ope. Ene gy and Buildings, 196, 21-29.
Tu sumbaye a, M., Mu a uly, A., Baima o a, N., Ka aca, F., and Ke im ay, A. 2023. Ci ies o
Cen al Asia: New ho spo s o ai pollu ion in he wo ld. A mosphe ic En i onmen , 309,
119901.
Wang, X., Li, Y., Chen, Y., Li, Y., Wang, C., Kaldybaye , A., ... and Duan, W. 2023.
In ensi ica ion o hea wa es in Cen al Asia om 1981 o 2020–Role o soil mois u e
educ ion. Jou nal o Hyd ology, 627, 130395.
Yan, L., and Liu, M. (2020). A simpli ied p edic ion model o ene gy use o ai condi ione in
esiden ial buildings based on moni o ing da a om he cloud pla o m. Sus ainable
Ci ies and Socie y, 60, 102194.
Zande , K. K., Van Hoo , J., Ca e , S., and Ga ne , S. T. 2023. Li ing com o ably wi h hea in
Aus alia–p e e ed indoo empe a u es and clima e zones. Sus ainable Ci ies and
Socie y, 96, 104706.
Zhang, X. B., Sun, J., Fei, Y., and Wei, C. 2020. Coole ooms on a ho e plane ? Household
coping s a egies, clima e change, and ai condi ioning usage in u al China. Ene gy
Resea ch & Social Science, 68, 101605.
