Abstract
Carbon mitigation in the building sector is crucial for China to fulfill its commitments towards achieving a carbon peak and carbon neutrality. However, the impact of societal development and ecological indicators on building carbon emissions remains unclear. This study employs the panel smooth transition regression model to investigate the complex implications of societal development comprehensive indicators, characterized by harmonious development, decoupling, and technological advances, on buildings’ total carbon emissions, based on the evidence from China’s 30 provinces for the period between 2007 and 2020. Additionally, the robustness of the model confirms that the conclusion is still valid. The empirical results indicate a strongly non-linear relationship between societal development comprehensive indicators and building carbon emissions. Both the harmonious development and technological advances exhibit two transition functions, and decoupling features a single transition function. Harmonious development is more sensitive to the impact of building carbon emissions, while technological advances have tremendous emission reduction potential. From the time dimension, fluctuation trends and ranges are different. From the spatial dimension, the inhibiting and promoting effects on each province have regional heterogeneity. Our results entail suggestions for reduced building total carbon emissions and practical strategies for regional climate resilience and efficiency in mitigating climate change.
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The data and materials used to support the findings of this study are available from the corresponding author upon request.
Notes
Carbon in the paper represents carbon dioxide.
References
Aghdam KA, Rad AF, Shakeri H, Sardroud JM (2018) Approaching green buildings using eco-efficient construction materials: a review of the state-of-the-art. J Constr Eng Project Manag. https://doi.org/10.6106/JCEPM.2018.8.3.001
Ahmad M, Zhao ZY, Li H (2018) Revealing stylized empirical interactions among construction sector, urbanization, energy consumption, economic growth and CO2 emissions in China. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2018.12.112
Alqadhi S, Bindajam AA, Mallick J et al (2023) Map** and evaluating sustainable and unsustainable urban areas for ecological management towards achieving low-carbon city: an empirical study of Asir Region, Saudi Arabia. Environ Sci Pollut Reshttps://doi.org/10.1007/s11356-023-27129-4
Ara R, Sohag K, Mastura S, Abdullah S, Jaafar M (2015) CO2 emissions, energy consumption, economic and population growth in Malaysia. Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2014.07.205
Basbagill J, Flager F, Lepech M, Fischer M (2013) Application of life-cycle assessment to early stage building design for reduced embodied environmental impacts. Build Environ. https://doi.org/10.1016/j.buildenv.2012.11.009
Batool Z, Ahmed N, Luqman M (2023) Examining the role of ict, transportation energy consumption, and urbanization in co2emissions in asia: a threshold analysis. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-023-27995-y
Bhamare DK, Rathod MK, Banerjee J (2019) Passive cooling techniques for building and their applicability in different climatic zones-the state of art. Energy Buildings. https://doi.org/10.1016/j.enbuild.2019.06.023
Cai WG, Wu Y, Zhong Y, Ren H (2009) China building energy consumption: situation, challenges and corresponding measures. Energy Policy. https://doi.org/10.1016/j.enpol.2008.11.037
Cansino JM, Román R, Ordóñez M (2016) Main drivers of changes in CO2 emissions in the Spanish economy: a structural decomposition analysis. Energy Policy. https://doi.org/10.1016/j.enpol.2015.11.020
Chai J, Yang Y, Wang S, Lai KK (2016) Fuel efficiency and emission in China’s road transport sector: induced effect and rebound effect. Technol Forecast Soc Chang. https://doi.org/10.1016/j.techfore.2016.07.005
Chen CY, Bi LL (2022) Study on spatio-temporal changes and driving factors of carbon emissions at the building operation stage- a case study of China. Build Environ. https://doi.org/10.1016/j.buildenv.2022.109147
Cheng B, Lu K, Li J, Chen H, Luo X, Shafique M (2022) Comprehensive assessment of embodied environmental impacts of buildings using normalized environmental impact factors. J Clean Prod. https://doi.org/10.1016/j.jclepro.2021.130083
Chertow MR (2000) The IPAT equation and its variants. J Ind Ecol. https://doi.org/10.1162/10881980052541927
Colletaz G, Hurlin C (2008) Threshold effects in the public capital productivity: an international panel smooth transition approach. Working Papers halshs-00724208, HAL SHS. https://shs.hal.science/halshs-00724208. Accessed 20 Aug 2012
Dahlbo H, Koskela S, Pihkola H, Nors M, Federley M, Sepp€al€ aJ (2013) Comparison of different normalised LCIA results and their feasibility in communication. Int J Life Cycle Assess. https://doi.org/10.1007/s11367-012-0498-4
Das A, Paul SK (2014) CO2 emissions from household consumption in India between 1993–94 and 2006–07: A decomposition analysis. Energy Econ. https://doi.org/10.1016/j.eneco.2013.10.019
Dietz T, Rosa EA (1994) Rethinking the environmental impacts of population, affluence and technology. Human Ecol Rev. https://doi.org/10.2307/24706840. Accessed Jan 1994
Dong F, Wang Y, Su B, Hua YF, Zhang YQ (2019) The process of peak CO2 emissions in developed economies: a perspective of industrialization and urbanization. Resour Conserv Recycl. https://doi.org/10.1016/j.resconrec.2018.10.010
Duan H, Zhou S, Jiang K, et al (2021) Assessing China’s efforts to pursue the 1.5°C warming limit. Science. https://doi.org/10.1126/science.aba8767
Duarte R, Mainar A, Sánchez-Chóliz J (2013) The role of consumption patterns, demand and technological factors on the recent evolution of CO2 emissions in a group of advanced economies. Ecol Econ. https://doi.org/10.1016/j.ecolecon.2013.09.007
Ehrlich PR, Holdren JP (1971) Impact of population growth. Scienec. https://doi.org/10.1126/science.171.3977.1212
Erdogan S (2021) Dynamic nexus between technological innovation and buildings sector’s carbon emission in BRICS countries. J Environ Manage. https://doi.org/10.1016/j.jenvman.2021.112780
Fan JL, Zhang YJ, Wang B (2017) The impact of urbanization on residential energy consumption in China: an aggregated and disaggregated analysis. Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2016.10.066
Gao S, Zhang H (2020) Urban planning for low-carbon sustainable development. Sustain Comput: Inform Syst. https://doi.org/10.1016/j.suscom.2020.100398
Gonz ́alez A, Terasvirta T, van Dijk D (2005) Panel smooth transition regression models. SEE/EFI Working Paper Series in Economics and Finance 604, Stockholm School of Economics. https://swopec.hhs.se/hastef/papers/hastef0604.pdf. Revised 11 Oct 2017
Guo X, Chuai X (2023) Tracking the spatial–temporal distribution and regional differences of carbon footprint in grid scale of China’s construction industry. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-023-27149-0
Guo S, Zheng S, Hu Y et al (2019) Embodied energy use in the global construction industry. Appl Energy. https://doi.org/10.1016/j.apenergy.2019.113838
Hansen BE (1999) Threshold effects in non-dynamic panels: estimation, testing, and inference. J Econ. https://doi.org/10.1016/S0304-4076(99)00025-1
Hao J, Gao F, Fang X, Nong X, Zhang Y, Hong F (2022) Multi-factor decomposition and multi-scenario prediction decoupling analysis of China’s carbon emission under dual carbon goal. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2022.156788
Hao Y, Ba N, Ren S, Wu H (2020) How does international technology spillover affect China’s carbon emissions? A new perspective through intellectual property protection. Sustain Prod Consum. https://doi.org/10.1016/j.spc.2020.12.008
Hepburn C, Adlen E, Beddington J, Carter EA, Fuss S, Dowell NM et al (2019) The technological and economic prospects for CO2 utilization and removal. Nature. https://doi.org/10.1038/s41586-019-1681-6
Hong J, Shen GQ, Guo S, Xue F, Zheng W (2016) Energy use embodied in China’s construction industry: a multi-regional input-output analysis. Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2015.09.068
Huo T, Cao R, Du H et al (2021) Nonlinear influence of urbanization on China’s urban residential building carbon emissions: new evidence from panel threshold model. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2021.145058
Huo T, Li X, Cai WG et al (2020a) Exploring the impact of urbanization on urban building carbon emissions in China: evidence from a provincial panel data model. Sustain Cities Soc. https://doi.org/10.1016/j.scs.2020.102068
Huo T, Ma Y, Cai W, Liu B, Mu L (2020b) Will the urbanization process influence the peak of carbon emissions in the building sector? a dynamic scenario simulation. Energy Buildings. https://doi.org/10.1016/j.enbuild.2020.110590
Huo T, Ma Y, Yu T, Cai W, Ren H (2020c) Decoupling and decomposition analysis of residential building carbon emissions from residential income evidence from the provincial level in China. Environ Impact Assess Rev. https://doi.org/10.1016/j.eiar.2020.106487
Huo T, Ren H, Cai W (2019) Estimating urban residential building-related energy consumption and energy intensity in China based on improved building stock turnover model. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2018.09.008
Huo T, Cai W, Ren H, Feng W, Zhu M, Lang N et al (2018a) China’s building stock estimation and energy intensity analysis. J Clean Prod. https://doi.org/10.1016/j.jclepro.2018.10.060
Huo T, Ren H, Zhang XL et al (2018b) China’s energy consumption in the building sector: a statistical yearbook-energy balance sheet based splitting method. J Clean Prod. https://doi.org/10.1016/j.jclepro.2018.02.283
IEA (2012) World energy outlook 2012. Int Energy Agency. https://doi.org/10.1787/20725302
Jay HA, Jim H, Francesco P, Bernardino DA (2021) Carbon sequestration and storage in the built environment. Sustain Prod Consum. https://doi.org/10.1016/j.spc.2021.02.028
Kelly S, Shipworth M, Shipworth D et al (2013) Predicting the diversity of internal temperatures from the English residential sector using panel methods. Appl Energy. https://doi.org/10.1016/j.apenergy.2012.08.015
Lamrani B, Johannes K, Kuznik F (2021) Phase change materials integrated into building walls: an updated review. Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2021.110751
Li K, Ma M, **ang X, Feng W, Ma Z, Cai W et al (2022) Carbon reduction in commercial building operations: a provincial retrospection in China. Appl Energy. https://doi.org/10.1016/j.apenergy.2021.118098
Liang L, Zhang F, Wu F, Chen Y, Qin K (2022) Coupling coordination degree spatial analysis and driving factor between socio-economic and eco-environment in northern China. Ecol Ind. https://doi.org/10.1016/j.ecolind.2022.108555
Liang Y, Cai W, Ma M (2019) Carbon dioxide intensity and income level in the Chinese megacities’ residential building sector: decomposition and decoupling analyses. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2019.04.289
Liao B, Li L (2022) Spatial division of labor, specialization of green technology innovation process and urban coordinated green development: evidence from China. Sustain Cities Soc. https://doi.org/10.1016/j.scs.2022.103778
Ma M, Ma X, Cai W et al (2019) Carbon-dioxide mitigation in the residential building sector: a household scale-based assessment. Energy Convers Manage. https://doi.org/10.1016/j.enconman.2019.111915
Ma M, Yan R, Cai W (2017a) An extended STIRPAT model-based methodology for evaluating the driving forces affecting carbon emissions in existing public building sector: evidence from China in 2000–2015. Nat Hazards. https://doi.org/10.1007/s11069-017-2990-4
Ma M, Yan R, Du Y et al (2017b) A methodology to assess China’s building energy savings at the national level: an IPAT–LMDI model approach. J Clean Prod. https://doi.org/10.1016/j.jclepro.2016.12.046
McNeil MA, Feng W, de la Rue du Can S, Khanna NZ, Ke J, Zhou N (2016) Energy efficiency outlook in China’s urban buildings sector through 2030. Energy Policy. https://doi.org/10.1016/j.enpol.2016.07.033
Moutinho V, Moreira AC, Silva PM (2015) The driving forces of change in energy-related CO2 emissions in Eastern, Western, Northern and Southern Europe: the LMDI approach to decomposition analysis. Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2015.05.072
Nejat P, Jomehzadeh F, Taheri MM et al (2015) A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries). Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2014.11.066
Nissinen A, Gr€ onroos J, Heiskanen E, Honkanen A, Katajajuuri J-M, Kurppa S, Voutilainen P (2007) Develo** benchmarks for consumer-oriented life cycle assessment-based environmental information on products, services and consumption patterns. J Clean Prod.https://doi.org/10.1016/j.jclepro.2006.05.016
Norman J, Maclean HL, Kennedy CA (2006) Comparing high and low residential density: life-cycle analysis of energy use and greenhouse gas emissions. J Urban Plan Dev. https://doi.org/10.1061/(ASCE)0733-9488(2006)132:1(10)
Peng C, Jiang Y, Qin Y (2018) Low-carbon building and cities. China Environment Publishing Group, Bei**g
Ren S, Li L, Han Y, Hao Y, Wu H (2022) The emerging driving force of inclusive green growth: does digital economy agglomeration work? Bus Strateg Environ. https://doi.org/10.1002/bse.2975
Richard WE (2001) Natural capital and the theory of economic growth. Economics. https://doi.org/10.1016/S0921-8009(00)00187-7
Rogelj J, Geden O, Cowie A et al (2021) Three ways to improve net-zero emissions targets. Nature. https://doi.org/10.1038/d41586-021-00662-3
Roh S, Tae S, Suk SJ, Ford G (2017) Evaluating the embodied environmental impacts of major building tasks and materials of apartment buildings in Korea. Renew. Renew Sustain Energy Rev https://doi.org/10.1016/j.rser.2017.01.081
Satola D, Houlihanwiberg A, Gustavsen A (2020) Life cycle GHG emissions of residential buildings in humid subtropical and tropical climates: systematic review and analysis. Buildings. https://doi.org/10.3390/buildings11010006
Shafiei S, Salim RA (2014) Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: a comparative analysis. Energy Policy. https://doi.org/10.1016/j.enpol.2013.10.064
Shahbaz M, Loganathan N, Muzaffar AT, et al (2016) How urbanization affects CO2 emissions in Malaysia? The application of STIRPAT model. Renew Sustain Energy Rev https://doi.org/10.1016/j.rser.2015.12.096
Shan Y, Guan D, Hubacek K et al (2018) City-level climate change mitigation in China. Sci Adv. https://doi.org/10.1126/sciadv.aaq0390
Sharma A, Saxena A, Sethi M, Shree V (2011) Life cycle assessment of buildings: a review. Renew Sustain Energy Rev. https://doi.org/10.1016/j.rser.2010.09.008
Shen Y, Ren Y (2022) Construction and evaluation of a system to measure the coordinated development of the ecological environment and the economy of the construction industry. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-16274-3
Sorrell S, Dimitropoulos J (2008) The rebound effect: microeconomic definitions, limitations and extensions. Ecol Econ. https://doi.org/10.1016/j.ecolecon.2007.08.013
Ulucak R, Emrah K, Seyfettin E, Kassouri Y (2020) Investigating the non-linear effects of globalization on material consumption in the EU countries: evidence from PSTR estimation. Res Policy 67:101667
United Nations Environment Programme (2021) 2021 global status report for buildings and construction: towards a zero‑emission, efficient and resilient buildings and construction sector. Nairob, China. https://www.globalabc.org
Wang J, Hao S (2023) The spatial impact of carbon trading on harmonious economic and environmental development: evidence from China. Environ Geochem Health. https://doi.org/10.1007/s10653-023-01601-z
Wang L, Chen Y, Ramsey TS, Hewings GJD (2021) Will researching digital technology really empower green development? Technol Soc. https://doi.org/10.1016/j.techsoc.2021.101638
Wang J, Yang Y (2020) A regional-scale decomposition of energy-related carbon emission and its decoupling from economic growth in China. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-08567-w
Wang H, Wei W (2019) Coordinating technological progress and environmental regulation in CO2 mitigation: the optimal levels for OECD countries & emerging economies. Energy Econ. https://doi.org/10.1016/j.eneco.2019.104510
Wang H, Chen W, Shi J (2018) Low carbon transition of global building sector under 2- and 1.5-degree targets. Appl Energy. https://doi.org/10.1016/j.apenergy.2018.03.090
Wen Q, Chen Y, Hong J et al (2020) Spillover effect of technological innovation on CO2 emissions in China’s construction industry. Build Environ. https://doi.org/10.1016/j.buildenv.2020.106653
William FL, Thomas W, Julia P, Robbie A, Monica C, Jos G, Dominik W, Giulio M, Alaa AK, Jo H (2021) A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018. Environ Res Lett. https://doi.org/10.1088/1748-9326/abee4e
World Resources Institute (n.d.). GHG Accounting tool for Chinese cities 2.2. https://www.wri.org/data. Accessed 26 Apr 2023
Xu Q, Dong YX, Yang R (2018) Urbanization impact on carbon emissions in the Pearl River Delta region: Kuznets curve relationships. J Clean Prod. https://doi.org/10.1016/j.jclepro.2018.01.194
Yan R, ** world: historical cases from China. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2022.157679
Yang J, Hao Y, Feng C (2021) A race between economic growth and carbon emissions: what play important roles towards global low-carbon development? Energy Econ. https://doi.org/10.1016/10.1016/j.eneco.2021.105327
Yang T, Pan Y, Yang Y et al (2017) Co2 emissions in China’s building sector through 2050: a scenario analysis based on a bottom-up model. Energy. https://doi.org/10.1016/j.energy.2017.03.098
Yu S, Eom J, Zhou Y, Evans M, Clarke L (2014) Scenarios of building energy demand for China with a detailed regional representation. Energy. https://doi.org/10.1016/j.energy.2013.12.072
Zhang M, Chen F, Liu L et al (2023) How does functional division within urban agglomeration affect CO2 emissions? An empirical study. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-023-27191-y
Zhang SF, Ma MD, **ang X et al (2022) Potential to decarbonize the commercial building operation of the top two emitters by 2060. Resour Conserv Recycl. https://doi.org/10.1016/j.resconrec.2022.106481
Zhang M, Zhang S, Lee CC et al (2021) Effects of trade openness on renewable energy consumption in OECD countries: new insights from panel smooth transition regression modelling. Energy Econ. https://doi.org/10.1016/j.eneco.2021.105649
Zhang W, Li G, Uddin MK, Guo S (2019a) Environmental regulation, foreign investment behavior, and carbon emissions for 30 provinces in China. J Clean Prod. https://doi.org/10.1016/j.jclepro.2019.119208
Zhang XC, Zheng RY, Wang FL (2019b) Uncertainty in the life cycle assessment of building emissions: a comparative case study of stochastic approaches. Build Environ. https://doi.org/10.1016/j.buildenv.2018.10.016
Zhang Y, He CQ, Tang BJ, Wei YM (2015) China’s energy consumption in the building sector: a life cycle approach. Energy Buildings. https://doi.org/10.1016/j.enbuild.2015.03.011
Zhang YJ, Zhao L, Zhang H, Tan TD (2014) The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China. Nat Hazards. https://doi.org/10.1007/s11069-014-1091-x
Zhao X, Jiang M, Zhang W (2022) Decoupling between economic development and carbon emissions and its driving factors: evidence from China. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph19052893
Zhou N, Fridley D, Khanna NZ et al (2013) China’s energy and emissions outlook to 2050: perspectives from bottom-up energy end-use model. Energy Policy. https://doi.org/10.1016/j.enpol.2012.09.065
Zhu C, Chang Y, Li X et al (2022) Factors influencing embodied carbon emissions of China’s building sector: an analysis based on extended STIRPAT modeling. Energy Buildings. https://doi.org/10.1016/j.enbuild.2021.111607
Zhu WN, Feng W, Li XD, Zhang ZH (2020) Analysis of the embodied carbon dioxide in the building sector: a case of China. J Clean Prod. https://doi.org/10.1016/j.jclepro.2020.122438
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This research was funded by the National Natural Science Foundation of China (No. 72374164) and the 2022 Independent Innovation Foundation of Wuhan University of Technology (No. 2022-zy-083).
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All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Qing Yang, **mei Wang, **ngxing Liu, and Yang Liu. The first draft of the manuscript was written by Qing Yang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Appendices
Appendix 1
This research mainly considers the harmonious development of the economy (EC) and environment (EN). The corresponding indicators and weights of the subsystem are shown in Tables
11 and
12.
The harmonious development index HDI is shown in Eq. (10).
C means coupling degree calculated in Eq. (11).
R means development degree of the system calculated in Eq. (12).
EC and EN represent the comprehensive assessment value of the economy and environment, respectively. WEC and WEN, respectively, represent the weight. Considering that this study aims to achieve the coordinated development of building economy and building carbon emissions, they are given equal weight, respectively.
This paper uses the Tapio decoupling model to measure the decoupling relationships between building economics and building carbon emissions. Equation (13) can be used to calculate the decoupling elasticity value.
CO2 denotes building total carbon emissions (calculation in this paper), CO20 and CO2T represent total building carbon emissions in the base year 0 and year T, respectively. IGDP denotes the gross output value of the construction industry (from China Statistical Yearbook on Construction), and IGDP0 and IGDPT represent the gross output value of the construction industry in the base year 0 and year T, respectively. ∆CO2 and ∆IGDP indicate the change in total building carbon emissions and gross output value of construction between the base year and year T, respectively.
Figure
10 shows the decoupling statuses according to the size of the coefficients. It is important to emphasize that a strong decoupling state ensures low-carbon development, while strong negative decoupling predicts the worst.
This article uses the proportion of TCE to GRP to indicate the degree of technological advances.
Appendix 2
The building total carbon emission can be defined as Eq. (14):
In Eq. (14), Cmp, Cc, and Cbo separately represent carbon emissions of material production, construction, and building operation, defined as Eqs. (15)–(17).
Cc1 and Cc2 separately represent the direct and indirect emissions in construction. Cbo1, Cbo2, Cbo3, Cbo4, and Cbo5 individually refer to coal total, natural gas, liquefied petroleum gas, electricity (including public buildings, which consist mainly of wholesale and retail trades, hotels and catering services, and others, urban housing operation, rural housing operation), and heating in northern towns’ carbon emissions. Ci, Cj, Ce, Ch, Cct, Cng, Cpg, Cboe, and Che are the amounts of building materials, fossil fuel, construction electricity, heat, coal total, natural gas, liquefied petroleum gas, operation electricity, and heating in northern towns. αi, αj, αe, αh, αct, αng, and αpg represent the carbon emission factors of building materials, fossil fuel, electricity, heat, coal total, natural gas, and liquefied petroleum gas.
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Yang, Q., Wang, J., Liu, X. et al. Complexity influence of societal development comprehensive indicators on building carbon emission: empirical evidence from China. Environ Sci Pollut Res 30, 117179–117200 (2023). https://doi.org/10.1007/s11356-023-30397-9
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DOI: https://doi.org/10.1007/s11356-023-30397-9