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Ci y-le el p ocess- ela ed CO2
emissions in China 2000–2021
Sijia Cai1,2, Jinghang Xu2, Yu u Guan 2, Miaomaio Liu1,3 ✉ , Chang an 4, Jun Bi1,3
& Yuli Shan 2,5 ✉
As he wo ld’s la ges CO2 emi e , China needs accu a e ci y-le el CO2 emission accoun s o o mula e
e ec i e low-ca bon policies. Howe e , p e ious s udies mainly accoun ed o emissions om ossil uel
combus ion and o e looked p ocess- ela ed CO2 emissions om indus ial p oduc ion (e.g., mine al,
chemical, me al p oduc s), which accoun o app oxima ely 13% o China’s o al emissions. In his
s udy, we buil he i s ime-se ies da ase o p ocess- ela ed CO2 emissions o 289 Chinese ci ies om
2000 o 2021. The da ase co e s 11 indus ial p oduc s and adhe es o he me hodology ecommended
by he In e go e nmen al Panel on Clima e Change (IPCC). We applied China-speci ic emission ac o s
and compiled indus ial ou pu da a om ci y s a is ical yea books and bulle ins. Missing ou pu da a
we e impu ed using missFo es models. The es ima ed unce ain y o he p ocess- ela ed emissions
in ou da ase anges om 3.87% o 3.91%. Ou da ase p o ides a obus ounda ion o analyzing
emission pa e ns a he ci y le el and o designing a ge ed low-ca bon policies.
Backg ound & Summa y
Clima e change is one o he mos u gen challenges, and coun ies a e ac i ely seeking solu ions o educe ca -
bon dioxide (CO2) emissions1,2. To design e ec i e solu ions, accu a e and de ailed CO2 emission in en o ies
a e essen ial3,4. Acco ding o he In e go e nmen al Panel on Clima e Change (IPCC), CO2 emissions in a ci y
may o igina e om wo main sou ces: ene gy- ela ed emissions om ossil uel combus ion and p ocess- ela ed
emissions om chemical o physical ans o ma ions o aw ma e ials wi hou combus ion, such as ca bona e
decomposi ion o me al educ ion5. While ene gy- ela ed CO2 emissions ha e been ex ensi ely s udied and
widely inco po a ed in o policy-making, la gely due o hei la ge sha e and he a ailabili y o ma u e accoun -
ing me hods, p ocess- ela ed emissions ha e ecei ed a less a en ion6–8. Acco ding o he IPCC, mo e han 30
indus ial p ocesses wo ldwide gene a e p ocess- ela ed CO2 emissions5. O e looking p ocess- ela ed emissions
in policy-making may lea e majo emission sou ces (e.g., cemen and c ude s eel) un egula ed.
As he wo ld’s la ges emi e o CO2, China plays a pi o al ole in global clima e mi iga ion9. In esponse,
China has p oposed “dual-ca bon” goals— o peak CO2 emissions be o e 2030 and achie e ca bon neu ali y
be o e 2060. China’s accoun ing o o e 50% o global ou pu in key indus ial p oduc s—such as cemen ,
la glass, c ude s eel, and aluminum10— highligh ing i s ole as he global manu ac u ing hub. The coun y’s
la ge-scale indus ial ac i i ies and subs an ial demand o aw ma e ial p ocessing, has led o high le els o
p ocess- ela ed emissions11,12. Acco ding o China’s Fi s Biennial T anspa ency Repo on Clima e Change,
China’s p ocess- ela ed CO2 emissions eached 1,524 million onnes (M ) in 2021, making up 13% o he na ion’s
o al emissions13. This igu e is app oxima ely 3.2 imes as la ge as he o al ossil CO2 emissions o Russia, he
wo ld’s ou h-la ges emi e 14. Gi en he subs an ial a ia ion in esou ce endowmen and de elopmen s age
among Chinese ci ies, he con ibu ion o p ocess- ela ed CO2 emissions also a ies ac oss ci ies15,16. I hese
emissions a e no p ope ly accoun ed o , ci y-le el ca bon in en o ies may unde es ima e o al emissions.
In ecen yea s, schola s ha e inc easingly ecognized he impo ance o accu a ely accoun ing o
p ocess- ela ed CO2 emissions. Howe e , exis ing s udies ace h ee majo limi a ions. Fi s , mos p e ious
s udies usually use global de aul emission ac o s ecommended by he IPCC, such as hose used by Cui e al.17
and Hu e al.18. Howe e , hese de aul emission ac o s can no e lec coun y-speci ic indus ial p ocesses,
1S a e Key Labo a o y o Pollu ion con ol and Resou ce Reuse, School o he en i onmen , nanjing Uni e si y,
Nanjing, 210023, China. 2School o Geog aphy, ea h and en i onmen al Sciences, Uni e si y o Bi mingham,
Bi mingham, B15 2TT, UK. 3Basic Science Cen e o Ene gy and Clima e Change, Beijing, 100081, China.
4Depa men o Ea h Sys em Science, Tsinghua Uni e si y, Beijing, 100084, China. 5Bi mingham ins i u e o
Sus ainabili y and Clima e Ac ion (BISCA), Uni e si y o Bi mingham, Bi mingham, B15 2TT, UK. ✉e-mail: liumm@
nju.edu.cn; y[email p o ec ed]
DATA DeSC IPTO
OPeN
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echnologies, and aw ma e ial s uc u es. China-speci ic emission ac o s a e subs an ially lowe han IPCC
de aul alues—by 79% o e oalloys and 65% o pla e glass5,19,20. As a esul , applying global de aul ac o s o
China may lead o o e es ima ion o emissions om ce ain p oduc s. Second, mos exis ing s udies ocus on he
na ional scale, making i di icul o cap u e ci y-le el di e ences in emission ends and pa e ns. S udies such
as hose by Bi gi e al.21 and Tan e al.22 p o ide only na ional-le el es ima es o egions like he EU o China.
Thi d, he co e age o indus ial p oduc ypes emains limi ed. E en a he na ional le el, many s udies ocus
only on a small numbe o ep esen a i e p oduc s. Fo example, Xiao e al. es ima ed p ocess- ela ed emissions
o a single indus ial p oduc in Russia23, while Liu included i e p oduc s in China24. Sys ema ic accoun ing
ac oss a b oade ange o indus ial sec o s is s ill lacking, making i di icul o ully e lec he sec o al s uc u e
o p ocess- ela ed emissions. Fou h, al hough some ecen s udies ha e a emp ed ci y-le el es ima ions, hey
ha e p ima ily ocused on he cemen p oduc ion while neglec ing o he indus ial p oduc s. Examples include
he wo k by Guo e al.25 and Shan e al.6. Such na ow scope limi s ou unde s anding o he ull landscape o
p ocess- ela ed emissions a he ci y le el.
A key challenge in cons uc ing a ci y-le el in en o y o p ocess- ela ed CO2 emissions lies in he limi ed
a ailabili y o comple e indus ial ou pu da a and coun y-speci ic emission ac o s. To add ess hese issues,
his s udy unde ook comp ehensi e da a compila ion and p ep ocessing, an ex ensi e li e a u e e iew, and
an unce ain y analysis. Speci ically, we compiled ou pu da a o 11 p oduc s ac oss 289 Chinese ci ies o he
pe iod 2000–2021. Missing alues we e impu ed using ou missFo es models o ensu e da a comple eness and
consis ency. The selec ed p oduc s—cemen , pla e glass, calcium ca bide, e hylene, ammonia, soda ash, c ude
s eel, e oalloy, aluminum, lead, and zinc—accoun o o e 77% o China’s p ocess- ela ed CO2 emissions, and
he 289 ci ies ep esen mo e han 90% o he na ional g oss domes ic p oduc (GDP)13. Se e al o he indus ial
p oduc s (e.g., lime, pig i on, ca bon black, luo ochemicals, and ce amics) we e excluded due o ex ensi e da a
gaps a he ci y le el. In pa allel, we conduc ed an ex ensi e e iew o he li e a u e o collec coun y-speci ic
emission ac o s ha be e e lec China’s indus ial p ocesses. To e alua e he obus ness o he emission es i-
ma es, we inco po a ed he coe icien s o a ia ion (CVs) o bo h ac i i y da a and emission ac o s in o a
Mon e Ca lo simula ion o quan i y he unce ain y in he CO2 emission es ima es.
Building on his e o , we cons uc ed he i s long- e m, consis en da ase co e ing 289 Chinese ci ies. To
ensu e anspa ency, ou da ase includes no only he es ima ed emissions bu also he unde lying indus ial
ou pu da a used in he calcula ions, comp ising a o al o 139,876 eco ds. Ou da ase , he e o e, p o ides
obus da a suppo o ci y-le el low-ca bon policy design and implemen a ion.
Me hods
Scope and accoun ing bounda y. This s udy es ima es p ocess- ela ed CO2 emissions om 11 indus ial
p oduc s ac oss 289 Chinese ci ies o e he pe iod 2000–2021. These p oduc s span h ee majo indus ial sec o s:
he mine al indus y (cemen and pla e glass), he chemical indus y (calcium ca bide, e hylene, ammonia, and
soda ash), and he me al indus y (c ude s eel, e oalloy, aluminum, lead, and zinc).
To pe o m he es ima ion, we adop he IPCC- ecommended adminis a i e e i o ial-based app oach,
which accoun s o emissions gene a ed wi hin he geog aphical bounda ies o each ci y. Figu e1 p esen s he
amewo k used o cons uc he annual ci y-le el in en o y o p ocess- ela ed CO2 emissions.
P ocess- ela ed CO2 emission accoun ing app oach. The emission ac o app oach is cu en ly he
mos widely used me hod o es ima ing CO2 emissions. I calcula es emissions by mul iplying he ac i i y da a
by he co esponding emission ac o s, making i sui able o la ge-scale assessmen s and o con ex s whe e
Fig. 1 Me hodological amewo k o annual ci y-le el e i o ial CO2 emissions om indus ial p ocesses.
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di ec moni o ing da a a e una ailable22,25. The IPCC p o ide wo app oaches o selec ing emission ac o s: Tie
1, which uses global de aul alues, and Tie 2, which applies coun y-speci ic emission ac o s ha be e e lec
local p oduc ion p ocesses5,26. To enhance he accu acy and eliabili y o ou es ima es, his s udy adop s he Tie
2 app oach o all 11 indus ial p oduc s, inco po a ing China-speci ic emission ac o s. The gene al o mula used
o emission es ima ion is p esen ed as ollows:
EADEF(1)
iii
=×
whe e
Ei
ep esen s CO2 emissions om p oduc i.
ADi
ep esen s he ac i i y da a (i.e., he ou pu o p oduc i),
and
EFi
is he emission ac o , indica ing he amoun o CO2 emi ed pe onne o p oduc i.
Fo ce ain p oduc s such as soda ash, c ude s eel, lead, and zinc, we ollow he me hodology p oposed by
Yu e al.27, using a weigh ed a e age o emission ac o s based on he sha e o di e en p oduc ion p ocesses o
imp o e es ima ion accu acy. The speci ic calcula ion me hods o hese p oduc s a e desc ibed below:
(1) Soda ash: Among he h ee soda ash p oduc ion p ocesses, only he na u al soda p ocess gene a es CO2
emissions. Acco ding o he China Soda Ash Indus y Associa ion (CSIA), his p ocess accoun s o 5% o
China’s o al soda ash p oduc ion. Emissions a e calcula ed as:
EADEF5% (2)
soda ashsodaash soda ash
=∗∗
whe e
ADsoda ash
is he o al ou pu o soda ash, and
EFsoda ash
is he emission ac o o soda ash.
(2) C ude s eel: P ocess- ela ed CO2 emissions om c ude s eel p oduc ion a ise om ca bon oxida ion du ing
he con e sion o pig i on o c ude s eel, and limes one decomposi ion used as a lux in s eelmaking. C ude
s eel is p ima ily p oduced ia wo echnological ou es: he blas u nace-basic oxygen u nace (BF-BOF)
and he elec ic a c u nace (EAF). The i s componen is calcula ed by assessing he di e ence in ca bon
con en be ween pig i on (4.1%) and c ude s eel (0.25%), and con e ing o CO2 using he molecula
weigh a io (44/12):
=+∗. −. ∗
−
EADAD()(4 1% 025%)
44
12 (3)
c udes eel c udes eel BF BOFc ude s eel EAF(1)()()
whe e
ADc udes eel BF BOF()
− and
ADc udes eel EAF()
a e he ou pu s o c ude s eel om each espec i e p ocess.
The second componen a ises om limes one decomposi ion. The speci ic limes one consump ion is 0.3
onnes pe onne o c ude s eel o BF–BOF and 0.064 onnes o EAF28. Emissions om his sou ce a e
calcula ed as:
=∗.+ ∗. ∗
−
EADADEF(030064) (4)
c udes eel c udes eel BF BOFc ude s eel EAFlimes one(2)()()
whe e
EFlimes one
is he emission ac o o limes one decomposi ion.
(3) Lead: Lead p oduc ion in China consis s o p ima y and seconda y sou ces. Among p ima y sou ces,
he impe ial smel ing u nace (ISF) accoun s o 2.5% o ou pu , while di ec smel ing (DS) con ibu es
97.5%29. Seconda y lead is p ima ily eco e ed ia ba e y p ocessing (BP) om used lead-acid ba e ies.
The o al emissions om lead p oduc ion a e calcula ed as:
EADEFADEFADEF25%975%(5)
lead lead lead ISFleadleadDSleadseconda y lead BP() () () ()
=∗.∗ +∗.∗ +∗
whe e
ADlead
and
ADlead seconda y()
deno e o al and seconda y lead ou pu s, espec i ely.
EFlead ISF()
,
EFlead DS()
and
EFlead IBP()
a e he emission ac o s o ISF, DS, and BP p ocesses, espec i ely.
(4) Zinc: In China, zinc is mainly p oduced h ough ISF, elec o- he mic dis illa ion (ETD), and py ome allu -
gical p ocessing (PMP). Only he ISF p ocess gene a es CO2 emissions, accoun ing o 5% o na ional zinc
ou pu 29. Thus, emissions a e calcula ed as:
=∗∗EAD5%EF(6)
zinc zinc ISFzinc ()
whe e
ADzinc
is he o al zinc ou pu , and
EFzinc ISF()
is he emission ac o o zinc p oduc ion using he ISF
p ocess.
Ac i i y da a and emission ac o s. In his s udy, ac i i y da a e e o he annual ou pu o 11 indus-
ial p oduc s om indus ial en e p ises abo e designa ed size ac oss 289 ci ies. These da a we e collec ed om
ci y-le el s a is ical yea books and bulle ins30. Each ci y’s yea book was accessed ia i s o icial go e nmen web-
si e (e.g., h p:// jj.beijing.go .cn/; h p:// jj.nanjing.go .cn/). Howe e , due o inconsis encies in da a quali y a he
ci y le el, app oxima ely 2% o he ou pu da a a e missing. To o e come his p oblem, we applied missFo es , a
nonpa ame ic impu a ion me hod based on andom o es s, o da a in e pola ion31. This me hod is well-sui ed
o impu ing bo h con inuous and ca ego ical a iables, pa icula ly in da ase s wi h complex in e ac ions and
nonlinea ela ionships32,33.
To imp o e impu a ion accu acy, we de eloped ou sepa a e missFo es models based on he indus y clas-
si ica ion in oduced ea lie . Speci ically, he mine al and chemical sec o s each used a single model, while he
me al sec o was u he di ided in o e ous and non- e ous smel ing and olling. This sec o al di ision is
in o med by well-es ablished dis inc ions in p oduc ion echnologies, s a is ical epo ing p ac ices, and da a
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dis ibu ions be ween e ous and non- e ous me als, which may lead o di e gen pa e ns o missingness and
a ia ion in ou pu da a. Each model inco po a ed sec o -speci ic p edic o s, including o al indus ial ou pu
alue, a e age numbe o employees, main business income, main business cos , and ci y ype. The i s ou a -
iables we e ob ained om ci y-le el s a is ical yea books30, and ci y ypes we e de i ed using K-means clus e ing
based on he employmen and GDP s uc u e.
Fo emission ac o s, we conduc ed a comp ehensi e e iew o he exis ing li e a u e and compiled alues
om mul iple sou ces (see Table1). Due o he lack o empi ical da a a he ci y le el and o e ime, hese emis-
sion ac o s a e assumed o be uni o m and ime-in a ian h oughou he s udy pe iod and ac oss all ci ies.
Da a Reco d
The da ase is a ailable as open access ia Figsha e (h ps://doi.o g/10.6084/m9. igsha e.29085002. 3)34 and con-
ains 139,876 eco ds on p ocess- ela ed CO2 emissions and indus ial p oduc ou pu . Speci ically:
• 69,938 eco ds documen he ou pu o 11 indus ial p oduc s in 289 ci ies om 2000 o 2021 (File “China
indus ial p oduc ou pu in en o y a he ci y le el”);
• 69,938 eco ds documen p ocess- ela ed CO2 emissions o he same 11 p oduc s ac oss 289 ci ies om 2000
o 2021 (File “China p ocess- ela ed CO2 emission in en o y a he ci y le el”).
The CO2 emission in en o y ollows a s anda dized o ma and is o ganized ac oss mul iple sp eadshee
shee s, wi h each shee co esponding o a speci ic yea om 2000 o 2021. Wi hin each shee , he da a a e s uc-
u ed in o 12 columns and 289 ows. The columns ep esen p ocess- ela ed emissions o each o he 11 indus-
ial p oduc s, along wi h he o al p ocess- ela ed emissions o each ci y. The ows ep esen he 289 ci ies. Each
en y eco ds he emissions associa ed wi h p oducing a speci ic p oduc in a gi en ci y.
echnical Valida ion
S a is ical o e iew o he da ase . Be ween 2000 and 2021, p ocess- ela ed CO2 emissions om he 11
indus ial p oduc s showed a no able inc ease. To al emissions ose om 294 M in 2000 o 1,110 M in 2021, wi h
an a e age annual g ow h a e o 6.5% and an annual inc ease o 39 M . Among he h ee indus ies, he mine al
indus y con ibu ed he la ges absolu e inc ease in emissions, he me al indus y exhibi ed he highes ela i e
g ow h a e, while he chemical indus y expe ienced compa a i ely slowe g ow h.
The mine al indus y was he la ges con ibu o o p ocess- ela ed CO2 emissions. Emissions inc eased om
168 M in 2000 o 632 M in 2021, wi h an a e age annual inc ease o 22 M and a g ow h a e o 6.5%. Figu e2a
shows ha be ween 2014 and 2021, emission ho spo s in his indus y g adually shi ed om no he n and
no heas e n China o sou he n and sou hwes e n egions. This spa ial shi is la gely d i en by apid economic
g ow h and ising cons uc ion demand in sou he n p o inces a e 201435,36. The as es -g owing ci ies we e
Meizhou in Guangdong p o ince (0.4 M /y ), Sanming in Fujian (0.36 M /y ), and Chengde in Sichuan (0.32
M /y ). In con as , Shijiazhuang in Hebei (−0.7 M /y ), Xuzhou in Jiangsu (−0.59 M /y ), and Changchun in
Jilin (−0.39 M /y ) expe ienced subs an ial declines. Figu e2d p esen s he emission composi ion o he mine al
indus y in 2021, showing ha cemen accoun ed o 99%, while he con ibu ion om pla e glass was ela i ely
mino .
Indus ial p oduc P oduc ion p ocess Value Uni Sou ce
Cemen / 0.29 CO2/ Liu e al.19
Pla e glass / 0.0737 CO2/ Hu e al.20
Calcium ca bide / 1.15 CO2/ NDRC, 201146
E hylene / 2.25 CO2/ IPCC, 20065
Ammonia / 2.97 CO2/ Yu e al.27
Soda ash Na u al soda 0.14 CO2/ IPCC, 20065
IPCC, 20065
IPCC, 20065
Sol ay soda 0.00 CO2/
Hou’s soda 0.00 CO2/
Limes one use / 0.43 CO2/ Limes one NDRC, 201146
Ca bon con en o pig i on / 4.10 % NDRC, 201146
Ca bon con en o s eel / 0.25 % NDRC, 201146
Fe oalloy / 0.28 CO2/ NDRC, 202047
Aluminum / 1.50 CO2/ NDRC, 202047
Lead Impe ial smel ing u nace 0.66 CO2/ Sja din, 200348
Di ec smel ing 0.25 CO2/ Sja din, 200348
Ba e y p ocessing 0.20 CO2/ Sja din, 200348
Zinc Impe ial smel ing u nace 3.12 CO2/ Sja din, 200348
Elec o- he mic dis illa ion 0.00 CO2/ Sja din, 200348
Py ome allu gical p ocess 0.00 CO2/ Sja din, 200348
Table 1. Emission ac o s o 11 indus ial p oduc s.
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The chemical indus y showed slowe g ow h, wi h o al emissions inc easing om 93 M in 2000 o 185
M in 2021. The a e age annual g ow h a e was 3.3%, wi h an annual inc ease o 4 M . As illus a ed in Fig.2b,
emission g ow h was concen a ed in no he n ci ies, including O dos in Inne Mongolia (0.32 M /y ), Dalian
in Liaoning (0.31 M /y ), and Yulin in Shaanxi (0.3 M /y ). Meanwhile, emissions declined in Shijiazhuang in
Hebei (−0.26 M /y ), Liuzhou in Guangxi (−0.13 M /y ), and Hengshui in Hebei (−0.12 M /y ). Figu e2e
shows he 2021 emission composi ion: ammonia con ibu ed 65%, e hylene 25%, while calcium ca bide and
soda ash accoun ed o smalle sha es.
The me al indus y expe ienced he la ges ela i e g ow h, wi h emissions ising om 32 M in 2000 o 293
M in 2021. The a e age annual g ow h a e eached 11.1%, wi h an annual inc ease o 12 M . As shown in Fig.2c,
be ween 2014 and 2021, emission g ow h was concen a ed in esou ce-in ensi e ci ies. The as es -g owing
ci ies we e Tangshan in Hebei (1.39 M /y ), Binzhou in Shandong (0.86 M /y ), and Bao ou in Inne Mongolia
(0.48 M /y ). In con as , emissions declined in Shanghai (−0.16 M /y ), Beijing (−0.1 M /y ), and Tianjin
(−0.09 M /y ). Figu e2 p esen s he 2021 emission composi ion o he me al indus y: c ude s eel accoun ed
o 82%, ollowed by aluminum (15%), while lead, zinc, and o he me als con ibu ed ela i ely mino sha es.
Unce ain y analysis. Unce ain y analysis is a key ool o e alua ing he quali y o CO2 emission in en-
o ies37,38. Acco ding o he IPCC, unce ain ies p ima ily o igina e om ac i i y da a and emission ac o s5.
Two commonly used me hods o unce ain y assessmen in p e ious s udies a e e o p opaga ion and Mon e
Ca lo simula ion. Al hough e o p opaga ion is ela i ely easy o implemen , i elies on he assump ions o
linea i y and no mally dis ibu ed inpu a iables. These assump ions make i unsui able when inpu pa ame e s
ha e la ge unce ain ies o skewed dis ibu ions27. In con as , Mon e Ca lo simula ion does no depend on such
assump ions and can lexibly accommoda e p obabili y densi y unc ions o any shape and ange, p o iding a
mo e accu a e ep esen a ion o inpu unce ain ies and hei p opaga ion in emission es ima es39. The e o e, his
s udy adop s he Mon e Ca lo me hod o assess unce ain ies in he es ima ion o p ocess- ela ed CO2 emissions.
In ou analysis, we assigned a coe icien o a ia ion (CV) o 5% o ac i i y da a ob ained om o icial s a is-
ical yea books and bull ins27,40. Fo da a impu ed using missFo es models, he CV was se a 15%5,41. Emission
ac o CVs ollow he alues ecommended by he IPCC (see Table2)5. Emissions om e oalloy p oduc ion
we e excluded om he unce ain y analysis due o he complexi y o i s ca bon sou ces (e.g., pe oleum coke,
g aphi e, biomass), which makes he quan i ica ion o i s emission ac o unce ain y pa icula ly challenging.
P obabili y dis ibu ions we e de i ed based on a comp ehensi e li e a u e e iew42,43. When he unce -
ain y ange is less han ±60%, i is ypically assumed o ollow a no mal dis ibu ion44,45. Acco dingly, we
assumed no mal dis ibu ions o bo h ac i i y da a and emission ac o s. A o al o 20,000 andom samples
Fig. 2 Spa ial dis ibu ion and s uc u e o p ocess- ela ed CO2 emissions. (a–c) A e age annual g ow h o
p ocess- ela ed CO2 emissions in he mine al, chemical, and me al indus ies om 2014 o 2021. Wa me
colo s (yellow o ed) indica e emission inc eases, while coole colo s (ligh blue o blue) ep esen emission
educ ions. d- P ocess- ela ed CO2 emissions composi ion o he mine al, chemical, and me al indus ies
in 2021.
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we e gene a ed o es ima e he unce ain y ange o p ocess- ela ed CO2 emissions a he 95% con idence le el.
The esul s show ha he o al in en o y unce ain y anges om −3.87% o +3.91%. A he ci y le el, Zhoushan
(Zhejiang p o ince) exhibi ed he highes unce ain y (−18.74% o +18.78%), while Ü ümqi (Xinjiang Uygu
Au onomous Region) had he lowes (−1.90% o +1.93%).
To e alua e he po en ial impac o excluding e oalloy emissions, we conduc ed a sensi i i y analysis assum-
ing a conse a i e CV o 50%, which showed ha hei inclusion would al e he o al unce ain y ange by less
han 0.1 pe cen age poin .
Compa ison wi h exis ing emission es ima es. In addi ion o unce ain y analysis, we u he e al-
ua ed he eliabili y o ou ac i i y da a and emission es ima es by compa ing hem wi h na ional s a is ics
and esul s om p e ious s udies. Fi s , we compa ed he collec ed ou pu da a o 11 indus ial p oduc s wi h
na ional-le el s a is ics (see Fig.3). Since his s udy co e s 289 ci ies and no he en i e coun y, he ac i i y da a
o all 11 p oduc s a e gene ally lowe han na ional s a is ics. This disc epancy is p ima ily due o he exclusion
o ci ies no included in ou s udy.
Among all p oduc s, he ou pu s o calcium ca bide, aluminum, lead, and zinc in ou da ase a e mo e
han 20% lowe han he co esponding na ional o als. These p oduc s a e likely p oduced in smalle o
less-de eloped ci ies ha a e no pa o ou s udy. Addi ionally, ou da a a e p ima ily sou ced om s a is ical
yea books and bulle ins, which only include indus ial en e p ises abo e he designa ed size. As a esul , ou pu s
om small en e p ises a e o en excluded, leading o u he unde epo ing. In con as , he epo ed ou pu s
o cemen , pla e glass, e hylene, ammonia, soda ash, c ude s eel, and e oalloy in his s udy a e only sligh ly
lowe han he na ional o als. This consis en unde es ima ion sugges s ha he da ase is eliable—i does no
o e epo indus ial ou pu , which is c ucial o ensu ing he accu acy o CO2 emission es ima es.
To u he assess he accu acy o ou emission es ima es, we compa ed hem wi h hose epo ed by Yu e al.27
and Hu e al.18, wo o he mos comp ehensi e na ional-scale s udies on China’s p ocess- ela ed CO2 emissions.
Indus ial p oduc CV (%)
Cemen 5.5
Glass 30
Calcium ca bide 10
E hylene 30
Ammonia 6
Soda ash 0
Limes one use 6
C ude S eel 5
Aluminum 10
Lead 50
Zinc 50
Table 2. CVs o emission ac o s.
Fig. 3 Rela i e di e ences in ac i i y da a be ween his s udy and na ional s a is ics. The ela i e di e ence in
ac i i y da a is calcula ed as ( his s udy’s da a/na ional da a) − 1. A nega i e alue indica es ha he ac i i y da a
collec ed in his s udy a e lowe han he na ional s a is ics.
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Since no exis ing da ase p o ides ci y-le el co e age o mul iple indus ial p oduc s, hese na ional-le el es i-
ma es se e as he mos app op ia e e e ence poin o alida ing ou esul s. As shown in Fig.4, ou ela i ely
lowe emission es ima es e lec a na owe spa ial co e age by design, a he han an unde es ima ion. Unlike
na ional-le el s udies, ou s udy imp o es spa ial esolu ion by p o iding ci y-le el CO2 emission es ima es.
Fu he mo e, he use o localized emission ac o s and mo e comple e ou pu da a u he imp o es he accu acy
and comple eness o he es ima es.
In he mine al indus y (Fig.4a–b), ou es ima es o cemen and pla e glass a e consis en ly lowe han hose
o Yu e al. and Hu e al. du ing 2000–2020. Fo cemen , his is mainly due o me hodological a ia ion—ou s udy
calcula es emissions based on cemen ou pu , whe eas bo h Yu e al. and Hu e al. use clinke -based es ima es.
On a e age, ou cemen emissions a e 16% lowe han hose o Yu e al. and 22% lowe han hose o Hu e al. Fo
pla e glass, bo h ou s udy and Yu e al. bo h apply a China-speci ic emission ac o (0.07 CO2/ ), while Hu e al.
Fig. 4 P ocess- ela ed CO2 emissions om 11 indus ial p oduc s compa ed wi h o he s udies. Please no e ha
he anges o he y-axis a e di e en in each subplo .
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adop s he de aul alue (0.1 CO2/ ), esul ing in es ima es ha a e 39% highe han ou s. The 13% lowe es ima e
compa ed o Yu e al. is mainly a ibu able o ci ies no included in ou sample.
In he chemical indus y (Fig.4c– ), ou emission es ima es o calcium ca bide, e hylene, ammonia, and
soda ash a e consis en ly lowe han hose o Yu e al. and Hu e al. All h ee s udies use he same emission ac o
o calcium ca bide (1.15 CO2/ ), so he 33% lowe es ima e in ou s udy is due o uns udied ci ies. Simila ly, we
use he same emission ac o o e hylene (2.25 CO2/ ) as Hu e al., ye ou esul s a e app oxima ely 10% lowe .
Fo ammonia, bo h ou s udy and Yu e al. use a China-speci ic emission ac o (2.97 CO2/ ), while Hu e al.
adop s he lowe de aul emission ac o (2.77 CO2/ ). As a esul , ou es ima es a e 14% lowe han Yu e al. and
8% lowe han Hu e al. In he case o soda ash, al hough all h ee s udies adop he same emission ac o (0.67
CO2/ ), Hu e al. does no accoun o he ac ha only 5% o China’s soda ash is p oduced ia he na u al soda
p ocess, which is he only one ha gene a es CO2 emissions. This omission leads o subs an ial o e es ima ion—
Hu e al.’s es ima e is 96% highe han ou s, while ou s a e 20% lowe han Yu e al.’s.
In he me al indus y (Fig.4g–k), ou emission es ima es o e oalloy, aluminum, lead, and zinc a e con-
sis en ly lowe han hose o Yu e al. and Hu e al., whe eas ou es ima es o c ude s eel a e sligh ly highe
in ce ain yea s. The highe es ima es o c ude s eel a e due o da a limi a ions: we lack ci y-le el da a on pig
i on consump ion and he echnological b eakdown o c ude s eel p oduc ion ia BF–BOF and EAF ou es.
The e o e, we use o al c ude s eel ou pu as a p oxy and apply na ional-le el p ocess sha es o es ima e emis-
sions. Fo e oalloy, aluminum, and zinc (Fig.4h,i,k), we use he same emission ac o s as Yu e al. (0.28, 1.5,
and 3.12 CO2/ espec i ely). Howe e , ou esul s a e 21%, 35%, and 29% lowe , espec i ely, due o di e ences
in spa ial co e age. By con as , Hu e al. adop s de aul emission ac o s (1.3, 1.6, and 1.72 CO2/ ), which do
no align well wi h China’s ac ual indus ial p ac ices. Consequen ly, ou es ima es a e 83%, 29%, and 94% lowe
han hose o Hu e al., espec i ely. Fo lead (Fig.4j), we ollow he same me hodology as Yu e al., applying a
weigh ed a e age based on di e en smel ing p ocesses. Bu due o he lack o ci y-le el p ocess sha es, we ely
on na ional-le el p opo ions. Hu e al., on he o he hand, uses a single de aul emission ac o wi hou dis in-
guishing be ween smel ing p ocesses, esul ing in 63% highe emissions compa ed o ou s udy.
Code a ailabili y
All code used o cons uc he indus ial p oduc ou pu da ase is published unde h ps://gi hub.com/sijcai/
Indus ial-P oduc -Ou pu . The code is w i en in R 4.3.0.
Recei ed: 21 May 2025; Accep ed: 6 Augus 2025;
Published: xx xx xxxx
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Acknowledgemen s
This wo k was suppo ed by he Na ional Na u al Science Founda ion o China (72222012, 72174084, 72234003
and 72488101), he Na u al Science Founda ion o Jiangsu P o ince (BK20220125), Ho izon Eu ope P ojec EU-
CHINA-BRIDGE (101137971), which is unded by UKRI g an (10132630) a he Uni e si y o Bi mingham, and
Na ional Key Resea ch and De elopmen P og am o China (2022YFE0208500).
Au ho con ibu ions
S.C., M.L. and Y.S. designed he esea ch. S.C. led he da a collec ion, model de elopmen , and esul analysis. J.X.
and Y.G. assis ed wi h he li e a u e e iew. C.T. p o ided me hodological and echnical suppo . S.C. d a ed he
ini ial manusc ip , and M.L., Y.S. and J.B. e ised he pape . All au ho s e iewed and app o ed he inal e sion
o he manusc ip .
Compe ing in e es s
The au ho s decla e no compe ing in e es s.
addi ional in o ma ion
Co espondence and eques s o ma e ials should be add essed o M.L. o Y.S.
Rep in s and pe missions in o ma ion is a ailable a www.na u e.com/ ep in s.
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