With the progression of urban renewal, the functional transformation of numerous old industrial heritage buildings has imposed new demands on their indoor physical environments. This paper focuses on the adaptive renovation of thermal environments in old industrial buildings, using two case studies: Welding Workshop (Before Renovation) and the Cylinder Casting Workshop (After Renovation) of Hefei Motor Factory and Diesel Engine Factory. By integrating on-site thermal environment measurements and subjective thermal sensation questionnaires, we employs statistical regression methods to analyze the relationship between operative temperature and actual thermal sensation (MTS) and subjective thermal discomfort. The study identifies the acceptable temperature range and duration proportion in old industrial buildings, and further compares objective and subjective differences in human thermal comfort between summer and transitional seasons in the same workshop. Based on the acceptable duration proportion, a quantitative relationship between subjective sensations and operative temperature is established. These findings offer theoretical and empirical support for green renovation strategies of existing industrial buildings and design optimization of new constructions.
Practical application
This study provides empirical, decision-support evidence for the green renovation of industrial heritage. At its core, it establishes operative temperature as a critical design parameter and adopts the acceptable duration proportion of thermal comfort as a quantifiable target—thereby translating comfort needs into actionable design language. The data support a practical approach combining enhanced building envelope performance with flexible indoor environmental adjustments to balance heritage preservation and thermal comfort improvements. This research framework can be integrated into the design justification, scheme comparison, and post-occupancy evaluation processes of similar projects, offering a scientific and operational reference for enhancing environmental performance in the adaptive reuse of industrial heritage.
Martínez-MolinaATort-AusinaIChoS, et al.Energy efficiency and thermal comfort in historic buildings: a review. Renew Sust Energy Rev2016; 61: 70–85. https://doi.org/10.1016/j.rser.2016.03.018
2.
Martinez-MolinaABoarinPTort-AusinaI, et al.Assessing visitors’ thermal comfort in historic museum buildings: results from a post-occupancy evaluation on a case study. Build Environ2018; 132: 291–301. https://doi.org/10.1016/j.buildenv.2018.02.003
3.
JiaCZhangZWangM, et al.Investigation on indoor thermal environment of industrial heritage during the cooling season and its impacts on thermal comfort. Case Stud Therm Eng2023; 52: 103769. https://doi.org/10.1016/j.csite.2023.103769
4.
RicciardiPZilettiABurattiC. Evaluation of thermal comfort in an historical Italian opera theatre by the calculation of the neutral comfort temperature. Build Environ2016; 102: 116–127. https://doi.org/10.1016/j.buildenv.2016.03.011
5.
ZhuangLLiJLiZ, et al.Psychological adaptation to thermal environments and its effects on thermal sensation. Physiol Behav2022; 247: 113724. https://doi.org/10.1016/j.physbeh.2022.113724
6.
YukHParkJHKangY, et al.Advancing retrofitting practices for heritage masonry: the role of insulation materials in thermal and hygrothermal performance. Appl Therm Eng2025; 279: 127570. https://doi.org/10.1016/j.applthermaleng.2025.127570
7.
JiangWHuHTangX, et al.Protective energy-saving retrofits of rammed earth heritage buildings using multi-objective optimization. Case Stud Therm Eng2022; 38: 102343. https://doi.org/10.1016/j.csite.2022.102343
8.
BjellandDCollinsDGullbrekkenL, et al.Energy retrofitting of heritage-protected buildings: establishing representative case studies. Energy Rep2025; 13: 2752–2763. https://doi.org/10.1016/j.egyr.2025.02.010
9.
RobertiFFilippi ObereggerULucchiE, et al.Energy retrofit and conservation of a historic building using multi-objective optimization and an analytic hierarchy process. Energy Build2017; 138: 1–10. https://doi.org/10.1016/j.enbuild.2016.12.028
10.
WangYZhenYNingQ. Four-objective optimization of historic building renovation considering climate change: a trade-off in energy, economy, environment, and thermal comfort. J Build Eng2025; 110: 113017. https://doi.org/10.1016/j.jobe.2025.113017
11.
MohamedBMarzoukM. Post-adaptive reuse evaluation of heritage buildings using multi-criteria decision-making techniques. J Build Eng2025; 99: 111485. https://doi.org/10.1016/j.jobe.2024.111485
12.
ChaeYKimSH. Selection of retrofit measures for reasonable energy and hygrothermal performances of modern heritage building under dry cold and hot humid climate: a case of modern heritage school in Korea. Case Stud Therm Eng2022; 36: 102243. https://doi.org/10.1016/j.csite.2022.102243
13.
CoelhoGBHenriquesFM. Performance of passive retrofit measures for historic buildings that house artefacts viable for future conditions. Sustain Cities Soc2021; 71: 102982. https://doi.org/10.1016/j.scs.2021.102982
14.
BeccaliMStrazzeriVGermanàML, et al.Vernacular and bioclimatic architecture and indoor thermal comfort implications in hot-humid climates: an overview. Renew Sust Energy Rev2018; 82: 1726–1736. https://doi.org/10.1016/j.rser.2017.06.062
15.
MaYRoosliRCaoZ, et al.From isolation to integration: a methodological review of adaptive reuse in industrial heritage buildings. Energy Build2025; 348: 116474. https://doi.org/10.1016/j.enbuild.2025.116474
16.
LiuFZhaoQYangY. An approach to assess the value of industrial heritage based on Dempster–Shafer theory. J Cult Herit2018; 32: 210–220. https://doi.org/10.1016/j.culher.2018.01.011
17.
DaiJWangJBartD, et al.The impact of building enclosure type and building orientation on indoor thermal comfort---a case study of Kashgar in China. Case Stud Therm Eng2023; 49: 103291. https://doi.org/10.1016/j.csite.2023.103291
18.
ChandelSSSharmaVMarwahBM. Review of energy efficient features in vernacular architecture for improving indoor thermal comfort conditions. Renew Sust Energy Rev2016; 65: 459–477. https://doi.org/10.1016/j.rser.2016.07.038
19.
LiQSunXChenC, et al.Characterizing the household energy consumption in heritage Nanjing Tulou buildings, China: a comparative field survey study. Energy Build2012; 49: 317–326. https://doi.org/10.1016/j.enbuild.2012.02.023
20.
Martinez-MolinaAWilliamsonKDupontW. Thermal comfort assessment of stone historic religious buildings in a hot and humid climate during cooling season. A case study. Energy Build2022; 262: 111997. https://doi.org/10.1016/j.enbuild.2022.111997
21.
DilerYTurhanCArsanZD, et al.Thermal comfort analysis of historical mosques. Case study: the Ulu mosque, Manisa, Turkey. Energy Build2021; 252: 111441. https://doi.org/10.1016/j.enbuild.2021.111441
22.
CoelhoGBSilvaHEHenriquesFM. Impact of climate change in cultural heritage: from energy consumption to artefacts’ conservation and building rehabilitation. Energy Build2020; 224: 110250. https://doi.org/10.1016/j.enbuild.2020.110250
23.
XiongJGuoSWuY, et al.Predicting the response of heating and cooling demands of residential buildings with various thermal performances in China to climate change. Energy2023; 269: 126789. https://doi.org/10.1016/j.energy.2023.126789
24.
LucchiETuratiFColomboB, et al.Climate-responsive design practices: a transdisciplinary methodology for achieving sustainable development goals in cultural and natural heritage. J Clean Prod2024; 457: 142431. https://doi.org/10.1016/j.jclepro.2024.142431
25.
HanWZhangYXieY, et al.Sustainable and protection renovation of Hui traditional dwellings in China: thermal comfort on-site testing and investigation. Case Stud Therm Eng2025; 73: 106625. https://doi.org/10.1016/j.csite.2025.106625
26.
LiuHWuYLiB, et al.Seasonal variation of thermal sensations in residential buildings in the hot summer and cold winter zone of China. Energy Build2017; 140: 9–18. https://doi.org/10.1016/j.enbuild.2017.01.035
27.
YangLZhangYWangH, et al.Subjective thermal comfort in adaptive-reuse industrial spaces: a mixed-methods approach with young adults. Indoor Air2021; 31(4): 1234–1245. https://doi.org/10.1111/ina.12936
28.
ZhongXYuHTangY, et al.Local thermal comfort and physiological responses in uniform environments. Buildings2023; 14(1): 59. https://doi.org/10.3390/buildings14010059
29.
ZhangYWangHLiuX. Post-occupancy evaluation of adaptive reuse industrial spaces: a mixed-methods approach integrating subjective surveys and environmental monitoring. Build Environ2022; 218: 108765. https://doi.org/10.1016/j.buildenv.2022.108765
30.
LiuHZhangYChenW. Developing an adaptive thermal comfort model for naturally ventilated buildings in hot-humid climates: a comparative analysis of ASHRAE RP-884 and the Chinese database. Build Environ2023; 235(2): 112–125. https://doi.org/10.1016/j.buildenv.2023.112345
31.
WagnerASchmidtMMüllerF. Evaluation of operative temperature in low-air-speed environments: implications for industrial heritage spaces with non-uniform thermal sources. Build Environ2018; 242: 105678. https://doi.org/10.1016/j.buildenv.2018.04.023
Martínez-MolinaAGómez-AceboTGarcía-SánchezA. Accuracy of multi-sensor field measurements in heritage buildings: implications for thermal comfort assessment under ASHRAE 55. Energy Build2019; 198: 109876. https://doi.org/10.1016/j.enbuild.2019.109876
34.
LiRLiuYYuG, et al.Establishment of a thermal comfort model for spectator areas of air-supported membrane ice rinks in severe cold regions: a case study in Harbin, China. Energies2023; 16(12): 4598. https://doi.org/10.3390/en16124598
35.
MajewskiGOrmanŁJTelejkoM, et al.Assessment of thermal comfort in the intelligent buildings in view of providing high quality indoor environment. Energies2020; 13(8): 1973. https://doi.org/10.3390/en13081973
36.
WangHZhangYLiuX. A refined thermal comfort assessment method for rural houses in hot-humid climates: insights from East Guangdong, China. Indoor Air2022; 32(3): 1234–1245. https://doi.org/10.1111/ina.12936
37.
LiXWangH. Seasonal variation in thermal sensation: a bin method approach to analyzing indoor air temperature effects. Energy Build2021; 242: 110876. https://doi.org/10.1016/j.enbuild.2021.110876
38.
ChenJSChengCH. Extracting classification rule of software diagnosis using modified MEPA. Expert Syst Appl2008; 34(1): 411–418. https://doi.org/10.1016/j.eswa.2006.09.029
39.
DuCLiBYuW, et al.Energy flexibility for heating and cooling based on seasonal occupant thermal adaptation in mixed-mode residential buildings. Energy2019; 189: 116339. https://doi.org/10.1016/j.energy.2019.116339
40.
WangXYangLGaoS, et al.Thermal comfort in naturally ventilated university classrooms: a seasonal field study in Xi'an, China. Energy Build2021; 247: 111126. https://doi.org/10.1016/j.enbuild.2021.111126
41.
LiuHWangZ. Thermal comfort in industrial heritage spaces: a regression-based approach to understanding operative temperature effects. Energy Build2020; 242: 110876. https://doi.org/10.1016/j.enbuild.2020.110876
42.
GuoYWangY. Investigative study on adaptive thermal comfort in office buildings with evaporative cooling systems (ECS) under dry hot climate. Buildings2022; 12(11): 1827. https://doi.org/10.3390/buildings12111827
DuX. Space design for thermal comfort and energy efficiency in summer: passive cooling strategies for hot humid climates, inspired by Chinese vernacular architecture. A+BE Arch Built Environ2019; 9(10): 1–322. https://doi.org/10.7480/abe.19.10.4101
