Accoun ing and managemen o ci y ca bon emissions: T ajec o ies owa ds
ad anced da a use
Will B own
*
, K is en MacAskill
Uni e si y o Camb idge, Cen e o Sus ainable De elopmen , Depa men o Enginee ing, T umping on S ee , Camb idge CB2 1PZ, Uni ed Kingdom
ARTICLE INFO
Keywo ds:
U ban ca bon accoun ing
Ca bon emissions
Da a
Li e a u e e iew
ABSTRACT
Ci ies simul aneously play a signi ican ole in he p oduc ion o global ca bon emissions, whils being essen ial
in acili a ing hei educ ion. I is common p ac ice o ci ies o moni o , assess and manage hei ca bon
emissions o in o m app oaches o educing emissions. Whils ca bon accoun ing p ac ice is e ol ing alongside
accessibili y o da a and a ailabili y o esou ces, ci y au ho i ies emain limi ed in hei abili y o accu a ely
assess he ca bon emissions p oduced wi hin hei espec i e ci y – o en being cons ained by poli ical, inancial
and capaci y ac o s. This pape e iews academic li e a u e conce ning he u ilisa ion o ca bon emission da a o
es ablish ajec o ies o ad ancing u ban ca bon accoun ing p ac ice. The cases e iewed expand mo e ypical
con empo a y u ban ca bon accoun ing p ac ice h ough a leas one o i e ajec o ies: combining di e en
da a sou ces, isualising ca bon emissions, de eloping dis ic le el mi iga ion policies, accoun ing o p ojec
le el emissions, o es ima ing policy emission impac s. These a e discussed in ela ion o b oade na a i es
wi hin u ban ca bon accoun ing esea ch. Each ajec o y o e s po en ial de elopmen ou es o ci y au ho i ies
as hei u ban ca bon accoun ing p ac ices ma u e, he eby wo king owa ds closing he gap be ween ca bon
accoun ing p ac ice and academic esea ch.
1. In oduc ion
Ci ies a e simul aneously esponsible o an es ima ed 70 % o he
wo ld’s emissions (IPCC, 2023) whils being c i ically impo an o he
educ ion o global ca bon emissions. Ci y au ho i ies ha e been
conside ed o be mo e ac i e in pu suing mi iga ion policies when
compa ed o na ional go e nmen s (Lo, 2014), suppo ed by hei local
knowledge, c ea i i y, and esou ces o educe hem (Kennedy e al.,
2009). Howe e , ci ies a e undamen ally complex (Albe i e al., 2018),
which p oduces signi ican challenges o u ban go e nance and poli-
cymaking (McPhea son e al., 2016). This complexi y inc eases he
likelihood o undesi able ou comes eme ging om well-in en ioned in-
e en ions (Pak e al., 2017), he eby equi ing sys emic app oaches o
conside he connec ions be ween di e en sys ems (Ca , 1996) and he
u ilisa ion o ca bon emission da a o in o m and enhance decision
making.
Whils many ci y au ho i ies a e ac i ely wo king o accoun o
ca bon emissions, hei ac ions a e limi ed. Ci y emission baselines a e
p edomina ely cons uc ed h ough accoun ing o scope 1 and scope 2
emissions (GPC, 2021), whils scope 3 emissions, o en he mos
signi ican u ban emission sou ces (Goodwin e al., 2023), a e seldom
accoun ed o . This is owing o he complexi ies o accoun ing o hem,
wi h ci y au ho i ies lacking di ec con ol o e hese emission sou ces
and eliable da a o accoun o hem (Millwa d-Hopkins e al., 2017), as
well as complexi ies a ound how o measu e a ci y’s consump ion o
goods and se ices; he d i e o u ban scope 3 emissions (Do e al.,
2022).
Ano he elemen o conside wi hin u ban ca bon emission educ ion
is he ma u i y o a ci y’s abili y o conduc ca bon accoun ing and
u ilise emission da a o in o m decision making. Ci y au ho i ies o en
u ilise ci y-wide ca bon emission in en o ies, usually p oduced h ough
a combina ion o app oaches, including: he ‘downscaling’ o na ional
ca bon emission da a, p oduced ia he use o inpu –ou pu me hods
based on na ional economic da a (Da ey, 2025); le e aging connec ions
wi h local u ili y p o ide s o es ima e household emissions (Bal a de
Souza Le˜
ao e al., 2020); and, es ima ing anspo a ion emissions ia
he applica ion o an emission ac o o ci y-wide uel sales da a
(Kongboon e al., 2022).
Whils ci y-wide emission da a is use ul a he ci y-wide scale, i is
limi ed in applica ion a smalle scales, owing o he complexi y o
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (W. B own).
Con en s lis s a ailable a ScienceDi ec
Sus ainable Ci ies and Socie y
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h ps://doi.o g/10.1016/j.scs.2025.106677
Recei ed 2 Decembe 2024; Recei ed in e ised o m 24 July 2025; Accep ed 24 July 2025
Sus ainable Ci ies and Socie y 131 (2025) 106677
A ailable online 25 July 2025
2210-6707/© 2025 The Au ho s. Published by Else ie L d. This is an open access a icle unde he CC BY license ( h p://c ea i ecommons.o g/licenses/by/4.0/ ).
accu a ely ‘downscaling’ he da a (Ga ely & Hu y a, 2017). Whils he e
a e examples o ci ies pu suing mo e ad anced ca bon accoun ing, he
minimal s anda d o u ban ca bon accoun ing (GPC, 2021) equi es
ci ies o de elop ci y-wide ca bon emission in en o ies (Da ey, 2025),
esul ing in his le el o accoun ing being he mos p e alen globally.
To add ess hese limi a ions, a li e a u e e iew o academic esea ch
on he applica ion o ca bon emission da a in ci ies has been conduc ed.
In compa ison o he cu en p ac ices adop ed by many ci ies such
esea ch ep esen s he ‘s a e o he a ’, de ined as ‘ e y mode n and
using he mos ecen ideas and me hods’ (Camb idge Dic iona y, 2025).
This pape demons a es o ci y au ho i ies, p ac i ione s, and
academia po en ial ajec o ies associa ed wi h ad ancing ca bon ac-
coun ing in he u ban ealm. These ajec o ies cha ac e ise he appli-
ca ion and use o ca bon emissions da a, ma king an impo an
con ibu ion owa ds b idging he gap be ween academic esea ch and
ca bon accoun ing p ac ice applied by ci y au ho i ies.
This pape has conduc ed a li e a u e e iew o su ace he di e en
app oaches o using u ban ca bon emission da a by e iewing 41 case
s udies co e ing di e en ci ies om ac oss he globe. Du ing he e iew
p ocess, i e dis inc ajec o ies we e e ealed, each o which can be
pu sued by ci ies o de elop hei ca bon accoun ing p ac ice. Each is
discussed in ela ion o he ele an li e a u e in Sec ion 3, wi h he
a icle concluding by discussing he key insigh s de i ed om his e-
iew. The nex sec ion p o ides an o e iew o he me hodological
app oach used.
2. Me hodology
This li e a u e e iew is an ‘ex ending e iew’ (Xiao & Wa son,
2019) and whils being s uc u ed a ound a igo ous sea ch p ocess, i is
in en ionally no a sys ema ic e iew. This is owing o he pu pose o he
sea ch. A ypical goal o a sys ema ic li e a u e e iews is o quan i y he
esul s o he li e a u e sea ch, he e he au ho s sough o iden i y aca-
demic a icles which place a de ailed ocus upon he applica ion o
ca bon emission da a in he u ban ealm.
Key e ms om he Global P o ocol o Communi y-Scale G eenhouse
Gas In en o ies (GPC) (GPC, 2021), he leading s anda d o s uc u ing
u ban ca bon emission in en o ies, used by o e 13,000 ci ies wo ld-
wide (Global Co enan o Mayo s, 2024), we e applied as a sea ch e m
amewo k (Dixon-Woods, 2011). This s anda d is p emised upon he
iden i ica ion o six sec o s: S a iona y ene gy, T anspo a ion, Was e, In-
dus ial p ocesses and p oduc use, Ag icul u e, o es y, and o he land use
and o he scope 3 (GPC, 2021). These sec o s we e used as ini ial sea ch
e ms ( he Web o Science jou nal da abase was u ilised o all sea ches)
wi h eigh indi idual sea ches being conduc ed by applying ei he En-
e gy, T anspo , Was e, Indus ial, P oduc Use, Ag icul u e, Fo es y o
Scope 3 o he below sea ch e m:
“U ban [GPC sec o ] Ca bon Emissions”
A e iew p ocess ocused on long-lis ing ci y-speci ic case s udies.
This selec ion c i e ia was included o e lec he ocus on ci y ap-
p oaches o ca bon accoun ing. Subsequen e inemen s (desc ibed in
Fig. 1). led o 41 a icles o e iew. A pape was selec ed o e iew i i
ea u ed a ci y-speci ic case s udy whe e ca bon accoun ing was con-
duc ed, wi h he esul ing emission da a being applied o p oduce mo e
nuanced o de ailed indings beyond he ini ial c ea ion o an in en o y.
The i e mani es a ions o his da a applica ion o med he ajec o ies
discussed in Sec ion 3.
An example o a leading pape which did no mee his equi emen
was Lenk e al.’s s udy compa ing e i o ial and consump ion ca bon
accoun ing in Be lin, p oducing an emission in en o y which was no
subsequen ly applied o he ci y o p oduce mo e nuanced o de ailed
indings (Lenk e al., 2021). This pape and o he s like i (See: Appendix)
we e emo ed a he ‘ e inemen 4
′
s age. Con e sely, Ma chi e al.
(2023) o example, p oduced simila insigh s in o he I alian munici-
pali y o G osse o, bu used hem o map he emission p o iles o
di e en dis ic s and p oposing speci ic policies o comba hem
(Ma chi e al., 2023).
This de elopmen o he i e ajec o ies (de ailed in Sec ion 3) was
suppo ed by de eloping a se ies o codes which ocused on he con ex ,
use o emission da a, me hods used, go e nance, u ban en i onmen and
ype o ansi ion in es iga ed wi hin each pape . This e iew includes
olde pape s da ing back o 2010. Despi e he ela i e in age o his
esea ch, he me hods included emain mo e ad anced han he p e-
ailing no m o u ban ca bon accoun ing oday.
Th oughou , he e m ‘ca bon emissions’ is used o desc ibe he
gasses being accoun ed o , owing o all a icles e iewed ei he solely,
o in combina ion wi h o he g eenhouse gasses, accoun ing o ca bon
dioxide emissions. The e is he po en ial o he selec i e epo ing o
cases, whe e less success ul examples o a emp s a e less likely o be
o mally epo ed. The ole o his pape is o cap u e po en ial ajec-
o ies o ad ancing u ban ca bon accoun ing. In doing so i does no
claim o explo e all he complexi ies o hei implemen a ion o p o ide
a comp ehensi e e iew o cu en p ac ices used wi hin ci ies.
The au ho s a e awa e o nume ous go e nance ba ie s, beyond
issues ela ing o da a, which can mani es hemsel es wi hin he con ex
o ad ancing u ban ca bon accoun ing. The Eu opean Union’s Ne Ze o
Ci ies p ojec has iden i ied h ee ba ie s which p e en he ad ance-
men o ca bon neu ali y – ins i u ional, beha iou al and in a-
s uc u al ba ie s (Ne Ze o Ci ies, 2024). A e lec ion o u ban
go e nance and capaci y limi a ions is p o ided in he discussion sec-
ion, bu conce ns o go e nance a e no a cen al ocus o his e iew.
Ano he elemen o aise is ha whils di e en echnological ap-
p oaches o ca bon accoun ing a e discussed in he con ex o se ing he
scene o di e en case-s udies, he scope o his pape is o ocus upon
he po en ial ajec o ies o u u e applica ions o ca bon emission da a
wi hin ci ies, a he han on he me i s o di e en echnologies in
p oducing emission da a. The e o e, he di e en o ms o sensing
echnologies and echniques a e solely discussed in he con ex o hei
applica ion o p oduce ca bon emission da a.
3. Findings
Wi hin he 41 case s udies (summa ised hema ically in Table 2)
mos o he e iewed a icles use he ci y as a case s udy, a he han
being a ep esen a ion o he ac ions o a ci y au ho i y – al hough he e
a e examples o collabo a ion be ween esea che and au ho i y
(Goodwin e al., 2023; Kelle e al., 2023; Ma chi e al., 2023). The e is a
di e si y o ci ies ep esen ed, demons a ed by Fig. 2, which maps each
case s udy and ca bon accoun ing ajec o y on o Loughbo ough Uni-
e si y’s Globaliza ion and Wo ld Ci ies esea ch ne wo k’s (GaWC)
anking (GaWC, 2024). This anking classi ies ci ies in o 12 le els o
wo ld ci y ne wo k in eg a ion, om alpha ++ ( he mos economically
in eg a ed ci ies) h ough o su iciency (ci ies wi h hei own se ices
ha a e no elian on o he wo ld ci ies), based on he p e alence o
leading inancial i ms wi hin he ci y and he connec ions be ween
hem. Owing o he mul iplici y o ac o s which make a pa icula ci y
a ac i e o in es men (Mu ay, 2022) he wo ld ci y anking p o ides
a mul i ace ed means o ca ego ising he ci y case s udies e iewed he e.
While alpha ci ies sligh ly domina e he analysis, he e is gene ally a
easonable sp ead ac oss he ci y ankings, sugges ing he indings o he
pape could be gene alized beyond a pa icula ci y ype. Al hough, he
signi ican majo i y o cases a e based in high-income coun ies, a poin
ha will be e u ned o in wide discussion in Sec ion 4.
The majo i y o case s udies included in his e iew a e based upon
bo om-up accoun ing p ac ices as opposed o he op-down app oach
adop ed by many ci ies oday. This dis inc ion is impo an conside ing
he ime and skillse equi ed o conduc a bo om-up analysis in com-
pa ison o he ela i e simplici y o a op-down assessmen (Da ey,
2025), especially wi hin he cons ain s o u ban go e nance. The i e
ajec o ies a e p esen ed wi hin he con ex o a s a ing poin scena io,
wi h his pape explo ing how each ajec o y builds on his scena io.
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
2
While he e is a iabili y in exis ing p ac ice, o he pu pose o his
pape his scena io (Table 1) is amed as a ci y cu en ly conduc ing he
‘BASIC’ le el o ca bon accoun ing con ained wi hin he GPC s anda d
(scope 1 and 2 emissions o s a iona y ene gy, anspo a ion and
was e) using ei he op-down o bo om-up accoun ing. Owing o he
less labou -in ensi e na u e o ‘ op-down’ ca bon accoun ing, his
s a ing poin will be based on a ci y pe o ming op-down accoun ing.
The i s wo ajec o ies cen e upon be e ways o u ilise p e-
exis ing da a, i s ly by combining emission da a wi h o he da a sou -
ces o suppo mo e enhanced, holis ic decision making, and secondly
h ough de ailing app oaches o he isualisa ion o ca bon emissions.
The ajec o ies subsequen ly expand om cu en p ac ice by applying
emission da a in a mo e a ge ed manne o de elop neighbou hood/
dis ic le el ca bon educ ion policies ( a he han a a ci y-wide scale),
h ough conduc ing ca bon accoun ing o p ojec emissions o assess
hei emission educing po en ial and impac , and by es ima ing he
emission impac s o p oposed and al eady exis ing go e nmen al ac ions
h ough he ca bon accoun ing o policy ini ia i es.
Each ajec o y is discussed h ough he ele an cases. Ini ially wi h
a hema ic o e iew in ol ing a b ie desc ip ion o case s udies and a
e lec ion upon u ban ca bon accoun ing ma u i y, be o e del ing
deepe in o a ea u ed case s udy. This expanded analysis unpicks spe-
ci ic hema ic elemen s, wi h suppo ing cases ha mo e widely
demons a e applica ion o he ajec o y in ques ion.
3.1. T ajec o y 1: Combining da a sou ces
A c ucial elemen o enhancing u ban ca bon accoun ing is he
alignmen and combina ion o di e en da a sou ces. Be his h ough:
he combina ion o di e en scales o op-down emission da a (ci y-
wide, egional and na ional), as demons a ed by Wiedmann e al.
(2016) de elopmen o Melbou ne’s ‘ca bon map’, a cha -based ool
which demons a es he link be ween emission sou ces and consump ion
wi hin he ci y; he implemen a ion o bo om-up accoun ing p ac ices,
whe eby ac i i y da a is u ilised o calcula e and es ima e a ci y’s ca bon
emissions ia he applica ion o an emission ac o (Do e al., 2022;
McPhe son & Kendall, 2014; Sigu ða d´
o i e al., 2023); he combina-
ion o socio-economic o census da a o u he in e oga e he p o-
duc ion o u ban emissions (Goodwin e al., 2023; Millwa d-Hopkins
e al., 2017; Pa a asuk e al., 2016); o he use o ca bon emission da a
wi h economic o inancial da a o suppo he p io i isa ion o ca bon
neu ali y e o s wi hin a ci y. A New Yo k case s udy (explo ed below)
(Eicke e al., 2020) no only demons a es an app oach o combining
di e en o ms o u ban da a o suppo decision making, bu also p o-
poses an app oach o de eloping be e da a in eg a ion.
3.1.1. New Yo k
Whils Ame ica’s la ges ci y has passed legisla ion o educe hei
ca bon emissions by 80 % un il 2050, i is essen ial ha he da a u ilised
o in o m mi iga ion policies e lec s New Yo k’s dense complexi y,
en ailing a di e si y o da a o ms, sou ces and applica ions. Eicke e al.
Fig. 1. Diag am o li e a u e sea ch p ocess.
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
3
Fig. 2. Re iewed pape s’ case s udy ci y wo ld ci y ankings mapped acco ding o key ajec o y hemes (some o he 41 cases ea u e mo e han once). Ci ies lis ed
as ‘no included’ (pu ple) a e deemed o be non-wo ld ci ies by GaWC and he e o e do no ea u e in he wo ld ci y anking.
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
4
(2020) iden i ied hese challenges acing New Yo k and p oposed he
de elopmen an open u ban da a pla o m, which cen es upon u ban
da a collec ion and analysis om a di e se ange o sou ces, such as
senso s, municipal da a eco ds, knowledge eposi o ies and social
media s eams. Ye , hese a e o en siloed, disconnec ed om each o he ,
a ely exchanging da a. The e o e, he ole o an open u ban da a pla -
o m is o in e connec da a om mul iple u ban in as uc u es – such
as buil en i onmen , anspo a ion, na u al en i onmen and u ili ies.
To o e come da a siloisa ion, he Ci yGML building modelling s anda d
was u ilised wi hin he pla o m as a common o ma o da a exchange
be ween da ase s. The pla o m analyses and op imises u ban in-
as uc u es (ene gy, wa e and ood o goods consump ion) and was
applied o in es iga e he ood-wa e -ene gy nexus o Bo ough Hall
(B ooklyn).
Open-sou ce da a ela ed o he ene gy demand o he building, ood
and wa e sec o was collec ed and combined, suppo ing a ange o
nuanced policy ecommenda ions, wi h he au ho s a guing ha dis-
ic s wi h a high a io o home owne ship and high-income popula ion
could a o d o mode nise hei buil en i onmen mo e easily in com-
pa ison wi h low income o ci y-owned apa men s, whe e o he ap-
p oaches a e needed. Ano he insigh conce ns he impo ance o
building age, whe e in o med e u bishmen and sys em mode niza ion
decisions can be made. Howe e , as is a gued byEicke e al. (2020), he
use o mul iple da a sou ces can be challenging, because hey a e no
always on he same le el and scale and a e usually in di e en da a
Table 1
O e iew o s a ing poin ci y scena io.
Elemen Ci y Scena io
Da a Sou ce Top-down na ional le el da a downscaled o ci y
Scope GPC scopes 1 and 2 - BASIC accoun ing
Ad ancemen s Limi ed awa eness o po en ial ca bon accoun ing ad ancemen s/
nex s eps +Limi ed da a a ailabili y and expe ise o conduc
bo om-up accoun ing
Da a Use No connec ion be ween deca bonisa ion ac ions and cu en ly
a ailable ca bon emission da a
Table 2
Summa y o he ajec o ies and he 41 sho lis ed cases.
T ajec o y Sub-Theme Fea u ed Case S udy O he Rele an Cases
Combining Da a Sou ces Combining Da a Sou ces Eicke , Weile , Schumache and B aun (2020) - New Yo k
Demons a es he combina ion o di e en o ms o u ban da a
o suppo decision making, p oposes an app oach o
de eloping be e da a in eg a ion
Do e al. (2022) Mon euil, McPhe son and Kendall (2014)
Los Angeles, Sigu ða d´
o i e al. (2023) Reykja ik,
Pa a asuk e al. (2016) Sal Lake Ci y, Goodwin e al. (2023)
Canbe a, Millwa d-Hopkins e al. (2017) B is ol,
Wiedmann e al. (2021) Melbou ne
Mapping Emissions Dis ic /
Neighbou hood Mapping
Tan e al. (2021) - Shenzhen
Demons a es he mapping o emissions a dis ic le el and
ac oss di e en communi ies.
Ma chi e al. (2023) G osse o, Han & Ge (2021) Suzhou
Fine-Scale Mapping Kelle e al. (2022) - Auckland
Rep esen s he ine-scale ca bon emissions o a geog aphically
complex a ea, demons a ing he need o his ype o
app oach.
Cai e al. (2020) Hong Kong, Zhou and Gu ney (2010)
Indianapolis, Boi o e al. (2019) Cluj-Napoca, Schandl,
Ma cos-Ma inez, Baynes, Yu, Mia o and Tan (2020)
Canbe a
Rep esen ing Building
Le el Emissions
Zhang e al. (2022) - Xi’an
Models building emissions ac oss a ci y, iden i ying hemes
which expand beyond poli ical bounda ies
Kelle e al. (2013) Vancou e , Wu, Tao, Cao, Fan and
Ramaswami (2019) Shanghai, Lo enzo-S´
aez e al. (2020)
Qua de Poble
Mapping Di ec ly
Moni o ed Emissions
Doukalianou e al. (2020) - Xan hi
Lee e al. (2017) - Vancou e
Pugliese e al. (2018) - To on o
G anula Neighbou hood
/Dis ic Speci ic
Policies
G anula Neighbou hood
/Dis ic Speci ic Policies
Cheng e al. (2022) - Chongqing
An in o ma i e example o c ea ing g anula policies which
e lec he speci ic con ex s o he a eas hey a e p oposed o .
Ri e a-Ma ín, Al onso-Sola , Va gas-Salgado and
Ca al`
a-Mo es (2023) Valencia
Ma chi e al. (2023) - G osse o
C ea es new o ms o unde s anding ca bon educ ion h ough
de ising new dis ic s o ocus policies and ac ions.
Do e al. (2022) Mon euil
Pa a asuk e al. (2016) - Sal Lake Ci y
B ings in socio-economic da a which p oposes c ea ing policies
along no only physical o ene gy consump ion lines, bu also
social ac o s such as weal h.
Tan e al. (2021) Shenzen, Kelle e al. (2013) Vancou e ,
Huang e al. (2017) Adelaide
Assessing P ojec
Emissions
Buil En i onmen /
Re o i
Kaando p e al. (2022) - Ams e dam
Example o assessing he impac o ins alling ene gy e iciency
echnologies in e o i scena ios ac oss di e en con ex s.
Sigu ða d´
o i e al. (2023) Reykja ik, Lin e al. (2017)
Tainan
Na u e Based Solu ions McPhe son and Kendall (2014) - Los Angeles
An in-dep h analysis o he ca bon cos s, and bene i s, o
plan ing ees wi hin he u ban ealm. Emphasises he
impo ance o sys emic bene i s o ees, ia he educ ion o
HVAC associa ed emissions.
G´
omez-Villa ino e al. (2021) Mad id, Li e al. (2020)
Singapo e, Liu e al. (2023) Xiamen
New App oaches Dong e al. (2014) - Kawasaki
An illus a i e example o assessing he emission educ ions
associa ed wi h adop ing ci cula economy p ac ices in he
u ban ealm.
Kumdok ub e al. (2023) I haca, Hsu e al. (2010) Los
Angeles
Es ima ing Policy
Emissions
Es ima ing P oposed
Policy Impac s
Do e al. (2022) - Mon e euil
An example o combining he accoun ing o u ban emissions
and neighbou hood le el analysis. This is combined wi h
es ima ing he impac o he policies on emissions ac oss he
a ea.
(Millwa d-Hopkins e al., 2017) B is ol, Goodwin e al.
(2023) Canbe a, Yang, Wang, Liu and Zhou (2018) Ningbo,
Suga and Kennedy (2013) To on o
Assessing Go e nmen
Policies
Chen, Zhang, Chen, Li and Cui (2023) - Nanjing
Es ima es he e ec i eness o na ional policy on a ci y’s e o s
o become ca bon neu al. Fu he assesses wha would be
equi ed o achie e his end goal.
P oposes Policies, bu
does no assess hei
impac s
Lomba di, Laiola, T icase and Rana (2018) Foggia, (Lwasa,
2017) Kampala, Gu, Fu, Th i eni, Fuji a and Ahn (2019)
Shanghai, Zhang e al. (2015) Beijing
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
5
o ma s. Combining hese di e se da a sou ces howe e p o ides in-
o ma ion ha can be c ucial o making sensible scena ios o a u u e
enewable and CO2- educed ci y planning.
This case s udy illus a es he bene i s o using di e en o ms o da a
o c ea e mo e in o med analysis o complex u ban en i onmen s,
ma king an impo an s ep owa ds he de elopmen o holis ically
in o med deca bonisa ion decisions, and ep esen s he i s ajec o y
owa ds ad ancing ca bon accoun ing p ac ice.
3.2. T ajec o y 2: Mapping emissions
Ano he de elopmen owa ds enhanced u ban ca bon accoun ing is
he isualisa ion o a ci y’s ca bon emissions. Gi en he impe cep ible
na u e o ca bon emissions, he su acing o hei dis ibu ion ac oss a
ci y can suppo mo e in o med decision making (Ma chi e al., 2023;
Wiedmann e al., 2016). Fou o ms o emission isualisa ion we e
iden i ied in he e iew, ep esen ing: dis ic /neighbou hood le el
emissions; ci y emissions a ine scale; emissions a he building le el;
and he ep esen a ion o emission da a collec ed h ough di ec sensing
(Fig. 3).
3.2.1. Dis ic /Neighbou hood mapping
A o m o emission mapping conce ns hose which ep esen he
ela i e di e ences ac oss neighbou hoods. Tan e al. (2021) analysis o
emissions om passenge anspo in Shenzhen is an example o his.
He e, he au ho s analysed i e communi ies wi hin he ci y, which we e
spli in o a o al o 34 ‘ a ic analysis zones’ (TAZ). Bo om-up da a was
collec ed h ough using local au ho i ies and esea ch ins i u es and
accessing s a is ical epo s, li e a u e and o he online esou ces (ibid).
This da a collec ion iden i ied he equisi e a iables o he s udy,
which we e di ided in o ou ca ego ies: ehicula ene gy, land use,
socioeconomic ac o s, and anspo accessibili y. A e asce aining he
a el demand o each TAZ, he au ho s applied emission ac o s o he
ehicle ac i i y da a o es ima e he ca and bus emissions ac oss he
s udy a ea. The s udy p o ides maps ela ing o he dis ibu ion o
ehicula emissions, pe capi a emissions and emission in ensi y ac oss
he 34 TAZs, e ealing he impac o ca s and he signi ican ole o
‘spa ial inequali ies’ o a el demand, anspo emissions and land use
layou s on passenge anspo emissions. This o m o mapping is also
demons a ed in he wo k o Ma chi e al. in G osse o and, a a less
g anula scale, by Han and Ge’s in es iga ion in o he ole o land-use
and u ban ca bon emissions in Suzhou (Han & Ge, 2023).
3.2.2. Fine-Scale mapping
Auckland is wo king o hal i s ca bon emissions by 2030 and o
each ne -ze o emissions by 2050 (Kelle e al., 2023). Kelle e al.
(2023) a gue ha de ailed, sec o -speci ic emission moni o ing is
equi ed. In 2016, he ci y p oduced a ci y-wide emissions in en o y,
se ing as he basis o he de elopmen o Mahuika-Auckland, a spa ially
and empo ally esol ed ossil uel CO2 emissions da a p oduc o he
ci y. The genus o his ool came om he inadequacy o p e-exis ing
ools o e ec i ely moni o u ban ca bon emissions a a scale which
accu a ely ep esen s geog aphic complexi y.
Using he ci y’s emission in en o y, he scope 1 emissions o a ious
sec o s we e mapped a a scale o 500 ×500 m ac oss he poli ical
bounda y o Auckland: ope a ing a a ine scale han hose a he dis-
ic /neighbou hood le el. One pa icula bene i is he abili y o his
o m o mapping o e eal di e en concep ualisa ions o u ban ca bon
emissions, mo ing beyond compa ison o dis ic s o census da a zones,
p o iding a isual means o ca ego ising a eas o a ci y along mo e
nuanced lines.
O he pape s which de elop a ine esolu ion o isualisa ion a e Cai
e al.’s (2020) s udy o Hong Kong and Zhou and Gu ney’s (2010)
analysis o Indianapolis. Bo h adop ed a combina ion o op-down and
bo om-up me hods, wi h he o me modelling building and ans-
po a ion emissions h ough accessing open da a (Cai e al., 2020) and
he la e downscaling US na ional da a and combining i wi h
bo om-up da ase s and conduc ing building ene gy simula ions (Zhou &
Gu ney, 2010). Ano he example o ine scale ca bon emission mapping,
bu solely om he pe spec i e o hose p oduced h ough mobili y and
a ic, is Boi o e al.’s (2019) use o GPS acking and ehicle speed
assessmen o es ima e ehicle emission ho spo s in he Romanian ci y o
Cluj-Napoca, obse ing ha he spaces which ea u e bo h conges ed
s ee s and high-speed oads a e hose which p oduce he mos ca bon
emissions.
3.2.3. Rep esen ing building le el emissions
Ano he scale is a he le el o buildings. This o m o mapping is
o en conduc ed h ough c ea ing ‘building a chi ypes’, a bo om-up
app oach o accoun ing o ca bon emissions based on he geome y o
Fig. 3. A isual ep esen a ion o he ou di e en o ms o ca bon emission isualisa ion, p oduced by he au ho s using Google Ea h as a base image: Dis ic /
neighbou hood le el emissions (G een); Ci y emissions a ‘ ine scale’
(Blue); Emissions a he building le el (Yellow); Emission da a collec ed h ough di ec sensing (Wi i symbol).
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
6
he building s ock and building cha ac e is ics (building a ea, heigh ,
ype) by combining emissions om he manu ac u e o cons uc ion
ma e ials, building s ock and he cons uc ion indus y (Zhang e al.,
2015). A che ypes a e p oduced ia Geog aphic In o ma ion Sys em
(GIS) maps (Kaando p e al., 2022), LIDAR (Kelle e al., 2013), ma-
chine lea ning (Wu e al., 2019) and sa elli e image y p og ammes such
as Google Ea h (Zhang e al., 2022). Schandl e al. (2020) used building
a che ypes o assess he ca bon impac s o land-use change o e ime in
he Aus alian subu b o B addon (Canbe a), es ima ing he embodied
ca bon emissions p oduced o e a 60-yea pe iod.
Ano he example is Zhang e al.’s (2022) case s udy o Xi’an.
Applying a hypo hesis ha each building is de ined by i s land use o
es ima e he ci y’s building ca bon oo p in , he au ho s u ilised GIS
mapping so wa e o loca e buildings wi hin di e en land-use da a
zones. Eigh building ypes, wi h a combined o al o 17 a che ypes,
we e iden i ied. These we e u ilised o iden i y 15 emission ho spo s
ac oss he ci y. Whils his sec ion commenced wi h an o e iew o
dis ic o neighbou hood le el mapping, Zhang e al. iden i ied a end
o he building emissions o Xi’an o c oss such bounda ies, obse ing
he in luence o building ype o e ha o unc ional and adminis a i e
zones. Whils his does no in alida e dis ic /neighbou hood le el
mapping as an app oach, o local decision making is o en conduc ed a
he dis ic le el as is he alloca ion o ci y budge s, i does ep esen he
bene i s o di e en app oaches o isualising ca bon emissions wi hin
ci ies.
I is o no e ha whils building a che ypes a e o en u ilised o
calcula e building emissions, no all s udies which map building emis-
sions use a che ypes as an app oach. An example o his is he use o p e-
exis ing building ene gy ce i ica e da a o calcula e building emissions
in he Valencian subu b o Qua de P obe (Lo enzo-S´
aez e al., 2020).
3.2.4. Mapping di ec ly moni o ed emissions
Despi e he di icul ies o di ec ly measu ing ca bon emissions in he
u ban ealm, ou pape s included in his e iew applied senso -based
app oaches o di ec ly measu e ca bon emissions– h ee o which
mapped hei indings ( he ou h case ia Hsu e al. (2010) is co e ed in
Sec ion 3.4).
Doukalianou e al. (2020) assessed he po en ial o ca bon mi iga-
ion in he pe i‑u ban hillside o es s o Xan hi, G eece, by u ilising he
s a ic closed chambe echnique, assessing gas exchanges be ween he
soil below and abo e he chambe . This was conduc ed o assess he
impac s o no el o es hinning ac i i ies on ca bon seques a ion.
Ano he pape which di ec ly assessed u ban emissions was Pugliese
e al. (2018) de elopmen o he ‘Sou he n On a io CO2 Emissions’ in-
en o y h ough moni o ing he ca bon emissions o To on o om ou
local si es. He e, he au ho s used op ical echniques o de ec ing gases
o moni o ca bon emissions and c ea e a new emission in en o y o
Canada’s la ges ci y. Lee e al. (2017) de eloped a mobile senso
ne wo k in Vancou e , by modi ying i e ca s and a single bicycle o
assess he ca bon lux ac oss a ange o di e en neighbou hoods wi hin
he ci y.
Each o hese pape s conduc ed di e en o ms o assessmen : one
emo e (Pugliese e al., 2018), one mobile (Lee e al., 2017) and one in
he g ound (Doukalianou e al., 2020). Whils each pape ope a es a
di e en scales, he wo Canadian ci y s udies p oduced simila maps
based a ound iden i ying emission ho spo s. Whils hese Canadian
s udies p oduced ine scale maps, he analysis o Xan hi’s pe i‑u ban
o es ollowed an app oach akin o dis ic /neighbou hood mapping, by
iden i ying nine plo s whe e di e en o ms o ee hinning would ake
place and u ilising GIS o map hei impac s (Doukalianou e al., 2020).
Whils he o ms o mapping desc ibed in his sec ion possess
di e ing a ibu es and limi a ions, hey each p o ide a means o isu-
ally demons a ing he in a-ci y eali y o u ban ca bon emissions.
Owing o he adop ion o sys emic pe spec i es being suppo ed by i-
sual a e ac s and he isualisa ion o complex phenomena, he isual-
isa ion and mapping o a ci y’s ca bon emissions se es an impo an
unc ion in he pu sui o ad anced ca bon accoun ing.
3.3. T ajec o y 3: The de elopmen o mo e g anula , neighbou hood/
dis ic speci ic emission educ ion policies
The d i e o educe u ban ca bon emissions is p omo ed and
in o med by he ac ions o he local o ci y au ho i y and is o en man-
i es ed h ough he de elopmen o ‘ oadmaps’ o he en i e ci y. Whils
his p ocess is impo an , hey do no necessa ily ela e o he complex
di e ences p esen wi hin a ci y’s bounda ies. Policies which e lec
such in a-ci y di e ences a e be e posi ioned o succeed (Chandle ,
2014), wi h se e al pape s u ilising local ca bon emission da a o c ea e
g anula , local-scale policy ecommenda ions.
This ma ks he i s ajec o y which ad ances p ac ice owa ds he
need o mo e ad anced o ms o da a collec ion. Many ci ies elian
upon downscaled na ional le el da a may ace challenges in inding
app op ia e me hods o downscale u he o he neighbou hood le el.
Ri e a-Ma ín e al. (2023) wo k in Valencia a emp ed such down-
scaling, whe e he au ho s u ilised a downscaling app oach o accoun
o he deca bonisa ion po en ial o he scope 1, 2 and 3 emissions o he
ci y’s La Ca asca neighbou hood— ocusing upon he buil en i on-
men , anspo a ion, consump ion o goods, was e managemen and
g een a eas. This wo k p oduced an emission in en o y o he neigh-
bou hood, enabling he au ho s o p opose policies o educe he emis-
sions con ained wi hin. A simila s udy in geog aphical scope, bu
di e en in me hodology, was conduc ed by Do e al. (2022) in he
Pa isian subu b o Mon euil, whe e building e o i , anspo a ion and
ood ela ed s a egies we e assessed—which will be co e ed in mo e
de ail in Sec ion 3.4.
In ano he Valencian neighbou hood, Lo enzo-S´
aez e al. (2020)
de eloped a me hodology o map p ima y ene gy consump ion and
ca bon emissions in buildings, wi h he indings u ilised o suppo he
implemen a ion o he ci y au ho i y’s building e o i policy. In he
Aus alian ci y o Adelaide, Huang e al. (2017) used LCA o model he
emissions o he buil en i onmen (bo h embodied and ac i i y) and
anspo a ion in wo p ecinc s. The au ho s obse ed es ima ed e-
duc ions in emissions i esiden s inc eased public anspo a ion use
and inc eased ins alla ion o pho o ol aics, wi h a signi ican di e ence
be ween he wo loca ions—emphasising he impo ance o inco po-
a ing local ea u es in ca bon neu ali y policy se ing.
In Shenzhen, Tan e al. (2021) applied a de elopmen model o assess
he ca bon emissions om passenge anspo , iden i ying ha a lack o
mixed land use con ibu es o mo e in ensi e p i a e ehicle use.
Ano he pape which p oposes neighbou hood speci ic app oaches o
educing emissions is Kelle e al.’s (2013) bo om-up modelling o a
esiden ial neighbou hood in Vancou e , p oduced by ocusing on
buildings, anspo , people ( ood, was e and he ca bon emissions o he
human body i sel ) and plan s. The impac s o h ee scena ios we e
modelled in compa ison o he baseline scena io, wi h op imising
exis ing app oaches, ansi -o ien ed de elopmen and maximising low
ca bon app oaches, wi h he la e p oducing 31 % o he baseline
emissions. Below a e h ee case s udies which apply neighbou hood and
dis ic le el policies h ough di e en app oaches.
3.3.1. Chongqing
Cheng e al. (2022) de eloped a ca bon accoun ing me hodology and
an e iciency assessmen model designed o be applicable a he neigh-
bou hood le el o measu e he ca bon emission cha ac e is ics and
educ ion po en ial o each neighbou hood. The au ho s iden i ied 19
emission sou ces and sinks ac oss 15 communi ies. Bo om-up ac i i y
da a was collec ed om a a ie y o sou ces, h ough di e en me hods,
om s a is ical yea books and da a om neighbou hood commi ees,
alongside su eys and semi-s uc u ed in e iews wi h esiden s, me -
chan s and local ins i u ions. This da a was con e ed in o emission da a
by using emission ac o s and used o assess each communi y’s ca bon
oo p in and e iciency. The au ho s ca ego ised communi ies in o ou
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
7
‘quad an s’ ela ing o whe he hey had high o low emissions and
emission e iciency. This esul ed in ailo ed policy ecommenda ions,
om p omo ing highly ene gy-e icien li es yles o esiden s, ehabil-
i a ing he building en elope and op imising he anspo a ion ne wo k
o hose wi h high emissions and emission in ensi y, o p omo ing
esiden awa eness o en i onmen al conse a ion, imp o ing land use
e iciency and op imizing communi y esou ce alloca ion o hose wi h
low emissions and e iciency.
3.3.2. G osse o
In 2018, he I alian municipali y o G osse o de eloped a ca bon
emissions in en o y which was in eg a ed wi h Geog aphic In o ma ion
Sys ems based maps, o isualize he spa ial dis ibu ion o he ‘g een-
house gas balance’ (Ma chi e al., 2023). This in en o y was c ea ed
using he IPCC Guidelines o Na ional G eenhouse Gas in en o ies, map-
ping p e alence o emissions ac oss he municipali y using p ima y da a
co e ing 46 emission sou ces p o ided by local au ho i ies, companies,
and sec o ope a o s. Acco ding o he au ho s hese enable he
connec ion o “human ac i i ies, GHG [g eenhouse gas] emissions and
landscape, p o iding ools o o ien possible deca boniza ion measu es
o ci ies and u al a eas” (ibid, p9). I was h ough hese maps ha ou
GHG ‘ac ion zones’ we e iden i ied: he Ci y o G osse o, ag icul u al
a eas, coas al a eas and ag o- o es y su aces. Each zone was subse-
quen ly pai ed wi h policy sugges ions and he depa men s and s ake-
holde s able o assis in hei deli e y.
3.3.3. Sal Lake Ci y
Pa a asuk e al. (2016) quan i ied Sal Lake Coun y’s ossil uel
ca bon emissions ac oss eigh sec o s o asce ain he main d i e s o he
ci y’s emissions. To his end, he au ho s applied a bespoke bo om-up
da ase and conduc ed eg ession analysis conce ning popula ion s a-
is ics, esiden a luence and building age; mapping he esul s ac oss
he Sal Lake Ci y egion. Whils he au ho s obse ed ha popula ion
le els ha e he g ea es p opo ional in luence on ca bon emissions,
hey also a gued ha esiden weal h is an impo an ac o . The policy
implica ions o his inding sugges “ ha emissions educ ions may ind
g ea es e icacy among he high-income census block g oups” (p1032).
This illus a es ano he o m o g anula policy de elopmen . Ra he
han a ge ing di e en neighbou hoods o dis ic s wi hin a ci y, an
au ho i y could ailo hei emission mi iga ion policies o di e en
socio-economic g oups. Gi en he p opo ional signi icance o con-
sump ion emissions wi hin he u ban ealm (see: Goodwin e al., 2023),
and he well obse ed link be ween weal h and inc eased emissions,
ailo ing policies owa ds weal hie esiden s may be a ui ul policy
app oach o educe ci y emissions, as well as suppo ing mo e jus
deca bonisa ion p ac ices (Fulle , 2017).
3.4. T ajec o y 4: Assessing p ojec emissions
A u he s ep in he enhancemen o a ci y’s ca bon accoun ing
p ac ice lies in assessing and quan i ying he emission impac s o ac ions
en isaged o educe a ci y’s ca bon oo p in . I is a his s age ha a ci y
expands om moni o ing i s ca bon emissions, owa ds unde s anding
he impac o hei ac ions o educe hem. The gap be ween he moni-
o ing o ci ywide emissions and hose om educ ion app oaches ep-
esen s a signi ican hu dle o ci ies o o e come. Howe e , he e a e
examples o ci ies wo king owa ds he closing o his.
Fo example, some No dic ci ies, such as Oslo (Ci y o Oslo, 2024) a e
applying emission ac o s o ci y council p ocu emen da a o calcula e
hei o ganisa ional scope 3 emissions, an app oach which can lay he
ounda ions o calcula ing bo om-up p ojec le el emission da a.
Wi hin he e iew, examples o accoun ing o a p ojec ’s ca bon emis-
sions include Liu e al.’s (2023) assessmen o he impac o we land
eno a ion o u al was ewa e ea men h ough conduc ing a LCA in
he Chinese ci y egion o Xiamen. By using he da a o es ima e he
long- e m emission impac s o he p ojec , he au ho s es ima e he
ca bon impac s o he p ojec and he co esponding ca bon eco e y
pe iod. Ano he na u e-based p ojec is co e ed in G´
omez-Villa ino
e al.’s (2021) assessmen o he ca bon emission mi iga ion po en ial o
an ag icul u al and o es y p ojec in Mad id, iden i ying he ne
seques a ion bene i s o he p ojec ou weighing he emissions p o-
duced h ough i s implemen a ion. On a di e en scale, Li e al. (2020)
assessed he ca bon impac s o indoo a ming sys ems in Singapo e, by
modelling di e en ene gy sou ces and c op choices, iden i ying he
impo ance o sola ene gy and ecycling ma e ials in educing ca bon
impac s.
Wi hin he buil en i onmen sec o , Sigu ða d´
o i e al. (2023)
analysed he embodied emissions o he de elopmen o a new neigh-
bou hood in Iceland’s capi al ci y, Reykja ik, by u ilising planning
documen a ion o conduc an LCA. He e he au ho s es ima ed he
emission impac s o using imbe ins ead o ein o ced conc e e, iden-
i ying po en ial emission educ ions o 43 % wi hin he neighbou -
hood’s cons uc ion. Lin e al. (2017) explo e building ene gy
consump ion by modelling he impac s o sola panel ins alla ion, using
building a che ypes o analysis in Tainan. Ano he app oach o
assessing p ojec emissions is o alida e new app oaches o educing
emissions. One such example is (Kumdok ub e al., 2023) acking o he
ene gy and ma e ial lows in he ene gy, ood was e, and cons uc ion
ma e ials sec o s o Co nell Uni e si y o assess he me abolism and he
easibili y o a ci cula economy app oach o educing emissions,
highligh ing he impo ance o enewable ene gy gene a ion and com-
pos ing o ood was e as key elemen s.
Beyond assessing he emissions o a p ojec , Hsu e al. (2010) ook
he s ep o alida e he emission da a i sel , by conduc ing a e i ica ion
s udy o a ca bon and me hane in en o y which co e ed he Los Angeles
a ea. The au ho s used a sui e o senso s a he M Wilson obse a o y o
p oduce a op-down in en o y and compa ed i wi h a p io , bo om-up
in en o y p oduced by he Cali o nia Ai Resou ces Boa d, obse ing
ha he op-down in en o y epo ed a hi d-g ea e le el o emissions
in compa ison wi h he bo om-up app oach. Below a e h ee examples
which highligh he assessing o emissions bound in p ojec s a di e en
scales—building e o i , ci y-wide na u e-based solu ions, and he
adop ion o new p ac ices o educe emissions.
3.4.1. Ams e dam
Kaando p e al.’s (2022) analysis o building insula ion and elec-
ici y deca bonisa ion ac oss h ee si es in Ams e dam exempli ies he
assessmen o no el app oaches ac oss di e en con ex s wi hin a ci y.
The au ho s in es iga ed he con igu a ion o u ban hea sys ems o
iden i y he lowes cumula i e ca bon emissions o e ime. To asce ain
he emission impac o he assessed hea sys ems, a bo om-up hea
demand model was de eloped, comp ising o GIS in o med, building
a che ype de i ed models o hea ing demand, hea ing sys em emission
ac o s and insula ion and deca bonisa ion ajec o ies. Based on he
s udy’s indings he au ho s a gue ha he iabili ies o echnologies o
hea supply depends on he ambi iousness o he policy o deca bonise
elec ici y as well as he a e o building insula ion. This inding has a
sys emic quali y, equi ing conside a ion o he a ailable echnology is
equi ed as well as how i ope a es wi hin i s con ex .
3.4.2. Los Angeles
McPhe son and Kendall’s (2014) LCA esea ch in o Los Angeles’
‘Million T ees’ p og amme assesses uel use, ma e ial inpu s, and
biogenic ca bon lows o each li e s age o he p og amme o e 40
yea s. This analysis co e s plan ing, main enance, g ow h, emo al and
disposal o h ee ypes o ee plan ing, s ee , pa k and ya d ees. This
in en o y accoun ed o he impac o shading om ees on ene gy
demand, e ealing ha whils he p ojec o e all would be a ne ca bon
emission sink, his was no ue o all ypes o ee plan ing, wi h pa k
ees p ojec ed o be ne ca bon emission sou ces; owing o he emissions
associa ed wi h hei plan ing, main enance and emo al no being
balanced by hei seques a ion. No do hey p o ide seconda y bene i s,
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
8
like in building shading, which could educe building hea ing, en ing
and ai condi ioning emissions. This inding u he illus a es he i ue
o accoun ing o p ojec emissions. The con en ional wisdom is he
mo e ees plan ed wi hin a ci y, he mo e ca bon will be seques e ed,
ye , i he p ocesses behind he ac ual implemen a ion and managemen
o he ees is accoun ed o , hen hey could be a ne sou ce o ca bon
emissions.
3.4.3. Kawasaki
Dong e al. (2014) analysed ca bon emission educ ion h ough in-
dus ial and u ban symbiosis in he Japanese indus ial ci y o Kawasaki.
U ban symbiosis is he use o by-p oduc s (was e) om ci ies as al e -
na i e aw ma e ials o ene gy sou ces in indus ial ope a ions. This
o m o ‘ci cula economy’ is o impo ance wi hin educing u ban
ca bon emissions, gi en he signi ican embodied emissions con ained
wi hin ma e ials such as s eel and conc e e. The au ho s e alua ed he
ca bon oo p in om a li ecycle pe spec i e along h ee li ecycle s ages:
ups eam, onsi e and downs eam. I emissions occu ed wi hin he
adminis a i e bounda y, hey we e classi ied as onsi e di ec ca bon
oo p in , whils emissions which occu ed ou side he adminis a i e
bounda y we e classi ied as ups eam o downs eam depending on
whe he hey we e p oduced be o e o a e hose onsi e. The au ho s
ca ego ised he ca bon oo p in in o six ‘pa s’ and collec ed ac i i y
da a om echnical documen s, published li e a u e and an onsi e su -
ey, hen applied emission ac o s. Rega ding he educ ion o emissions
om u ban symbiosis, i s la ges impac s conce ned he ci y’s i on and
s eel indus y, whe e emission educ ions we e mainly ound in ma e ial
ca bon oo p in educ ion, which con ibu ed o he posi i e impac o
u ban symbiosis on educing o e all emissions. In opposi ion o
consuming new ma e ials, he ecycling o ma e ials cen al o u ban
symbiosis educed he eco- own’s ca bon oo p in .
3.5. T ajec o y 5: Modelling u u e policy impac s
Beyond assessing p ojec emissions, he de elopmen o policy le el
emission da a is a complex, bu impo an ask o conduc o unde s and
he possible emission impac s o policies going o wa d. This is owing o
he in luence ci y au ho i ies ha e on educing emissions cu en ly being
unaccoun ed o in e ms o hei ca bon impac . Despi e ci y councils
o en being cons ained by na ional le el policies— o example he
inabili y o in oduce ca bon axes— he passing o local, ci y le el ca -
bon neu ali y policies, especially in ela ion o educing consump ion
and scope 3 emissions, is a key sou ce o le e age o ci y au ho i ies o
educe hei ci y’s ca bon emissions. Howe e , he abili y o a ci y
au ho i y o es ima e he ca bon impac s o a policy o ange o policies
is a pa icula ly ad anced and complex o m o ca bon accoun ing. This
is in pa due o he complexi ies o se ing he bounda y o accoun ing,
he eby aising ques ions o wha is de e mined o be impac ed by a
policy and wha is no , as well as he equi emen o do specula i e
accoun ing g ounded in assump ions which is p edomina ely beyond he
capaci y o ci y au ho i ies.
Howe e , wi hin academia, se e al pape s ha e es ima ed he
emission impac o di e en policies upon a ci y’s ca bon oo p in .
Adop ing a b oad pe spec i e on u ban emission educ ion app oaches,
Suga and Kennedy (2013) modelled a ange o di e en in e en ions
wi hin building e o i , g een in as uc u e, al e na i e ene gy supply
and anspo a ion. The es ima ed impac s o which we e assessed in line
wi h cu en policy and mo e agg essi e policies in 2031 o he ci y o
To on o (Suga & Kennedy, 2013).
In B is ol, Millwa d-Hopkins e al. (2017) calcula ed he p oduc ion
and consump ion emissions o he B i ish ci y, as well as es ima ing i s
u u e emission ajec o y up o 2035. The au ho s p oposed mi iga ion
scena ios o educe p oduc ion emissions bu ind ha hese measu es
will ha e a limi ed impac on he consump ion emissions o he ci y,
which a e es ima ed o be h ee imes la ge han p oduc ion emissions.
Ano he pape which a ge ed consump ion emissions was an
assessmen o Canbe a’s emissions, iden i ying ha consump ion
emissions o he Aus alian capi al we e 83 % o i s o al ca bon oo p in
(Goodwin e al., 2023). The au ho s es ima ed ha by implemen ing
policies designed o a 1.5 ◦C wa ming scena io, he ci y’s emissions
could be educed by 85 % by 2045.
Ano he pape which sough o es ima e he po en ial impac s o
policies was Yang e al.’s (2018) assessmen o he Chinese ci y o
Ningbo in ela ion o he na ional go e nmen ’s launching o a
low-ca bon ci y pilo p og am. This assessmen was conduc ed h ough
he de elopmen o a long- ange ene gy al e na i es planning sys em
model which simula ed he emission impac s o six ene gy sec o s, wi h
he au ho s obse ing he need o bo h emphasise inc easing ene gy
e iciency and educing consump ion a es.
The e iew also iden i ied pape s which p opose policies o educe
ca bon emissions, bu do no es ima e hei impac s. Examples o his
include: Lomba di e al. (2018) de eloping an ac ion plan o he I alian
municipali y o Foggia, based upon he calcula ion o he ci y’s e i o-
ial (scopes 1 and 2) ca bon oo p in ; Lwasa (2017) accoun ing o
Kampala’s e i o ial ca bon oo p in iden i ied in e en ions om he
building, anspo a ion and na u e based solu ions sec o s; Zhang
e al.’s (2015) analysis o he ca bon emissions o he di e en sec o s o
Beijing’s economy; and Gu e al. (2019) sys em dynamics modelling o
Shanghai’s ca bon oo p in , iden i ying ha imp o ing ene gy in ensi y
would be he mos e ec i e means o educing emissions.
3.5.1. Mon euil
Owing o he de ailed ca bon da a collec ed and ocus on consump-
ion emissions, Do e al. (2022) assessmen o he Pa isian subu b o
Mon euil’s ca bon emissions ea u es an insigh ul es ima ion o policy
induced emission educ ions. Th ough applying en i onmen al model-
ling ac oss di e en sec o s— combining ood, mobili y and buil-
dings— he au ho s e alua ed he impac o a ious clima e mi iga ion
in e en ions, in ol ing da a collec ion om a ange o sou ces. Fo
ood, na ional le el da a was downscaled o use a a ci y le el, using
socio-economic da a o acili a e his p ocess. Mobili y and esiden ial
buildings we e modelled by adop ing he widely used ou -s ep ans-
po a ion modelling p ocess ( o gene a e esiden ips and associa ed
emissions) and by applying a building ene gy simula ion model (which
c ea ed 14 building a che ypes ep esen ing a ious hea ing loads and
en i onmen al impac s ac oss building li ecycles).
These models p oduced an emissions baseline agains which o assess
eigh policies ac oss he h ee sec o s: educing ood was e and eplacing
ed mea in local die s; inc easing elec ic and hyb id ehicle use as well
as implemen ing a speed limi o 15 km/h and no allowing ca jou neys
below 3 km; and he eplacemen o windows, enewal o gas boile s and
he insula ion o building acades. The s udy p edic ed a 23 % educ ion
o Mon euil’s ca bon emissions as a combined impac o hese policies.
The au ho s ound ha he building sec o emissions educ ion had he
mos impac om local in e en ion. Howe e , he ood sec o emissions
a e mos ly c ea ed by ag icul u al si es ou side he ci y’s bounda ies and
hus a e no unde he di ec in luence o elec ed o icials.
3.5.2. Nanjing
Whils he abo e pape s es ima ed he impac s o hypo he ical
emission educ ions, ano he o m o es ima ing policy impac s is o
model cu en ly enac ed policies. Conside ed o be a i al economic
cen e in Eas China, Nanjing is home o hea y indus y which accoun s
o >90 % o ci y ene gy consump ion—a c i ical issue gi en he i s
eliance on ene gy de i ed om coal and oil (Chen e al., 2020). To his
end, he Chinese go e nmen has p oposed emission educ ion policies
designed o con ol indus ial ene gy consump ion, p omo e new powe
sys em cons uc ion, was e classi ica ion managemen , he de elopmen
o g een anspo a ion and indus y es uc u ing. Wi hin hei case
s udy, Chen e al. (2020) coupled hese policy app oaches wi h h ee
con ex ual ac o s: economic de elopmen , popula ion g ow h and he
u banisa ion a e. They hen se ou scena ios co e ing he
W. B own and K. MacAskill
Sus ainable Ci ies and Socie y 131 (2025) 106677
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