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This paper is aimed at making a review of the recent research situation in-situ on the carbon emission( CE) account and analysis of the influential factors( IFs) through summing up the applications and relevant analysis methods. And,then,a brief review has to be made on the research status and trends of the aforementioned aspects in the field of building industry so as to provide references for further studies on the energy conservation and carbon emission reduction. To achieve the above mentioned purposes,the paper of ours has briefly introduced 3 general methods of CE accounting especially by highlighting the accounting manner of the single building CE and macro-building embodiment and operational CE. The CE accounting method for the individual building evaluation should be mainly done on the basis of the framework of the life cycle assessment,e. g. BEES,ENVEST and BEPAS. And,in regard to the macroscopic features,it would be possible for us to classify or categorize the accounting ideas of building embodiment and operational CE into methods of top-down approach and bottom-up one with their differences being illustrated. The bottom-up approach seems to be more detailed,visible as well as accurate or precise,yet,it is more complex and complicated to fulfil their calculations and acquire a lot of data investigations. On the contrary,the topdown approach just goes opposite by nature. In terms of CE-IFs analysis,there can be found 3 main types of methods( i. e.IPAT series model,index decomposition analysis and the structural decomposition analysis). And,we have also illustrated and elaborated their advantages,disadvantages as well as the application procedures in addition to a vivid comparison. Focusing on the building of CE IFs,we have also summarized a few key issues in this way:( 1) The research scopes can be mainly focused on the CE/IFs of the building industry or the building operations;( 2) The model of IPAT series has been widely adopted in combination with LMDI;( 3) The key IFs are mainly related to the society,economics and building operations. Thus,in final analysis,the paper has mainly illustrated the drawbacks of the current studies and presented prospects for their further research in 3 aspects: building CE accounting scope, the accounting methodologies and perspectives of IFs analysis.
[1] International Energy Agency. Statistics data browser[EB/OL].[2018-12-15]. https://www. iea. org/statistics/?country=CHINA&year=2016&category=Key%20indicators&indicator=Tot CO2&mode=chart&category Browse=false&data Table=INDICATORS&show Data Table=true.
[2] PENG Cheng(彭琛)，JIANG Yi(江亿)，QIN Youguo(秦佑国)．Low carbon buildings and low carbon cities(低碳建筑和低碳城市)[M]. Beijing:China Environment Publishing Group,2018.
[3] Building Energy Conservation Research Center,Tsinghua University(清华大学建筑节能研究中心)．Annual development report of building energy conservation in China(中国建筑节能年度发展研究报告2018)[M]. Beijing:China Environmental Science Press,2018.
[4] ZHOU N,KHANNA N,FENG W,et al. Scenarios of energy efficiency and CO2emissions reduction potential in the buildings sector in China to year 2050[J]. Nature Energy,2018,3(11):978-984.
[5] Intergovernmental Panel on Climate Change. Climate change 2007:synthesis report. Contribution of working groups I,II and III to the fourth assessment report of the intergovernmental panel on climate change[R]. Geneva,Switzerland:Intergovernmental Panel on Climate Change,2007.
[6] CAI Weiguang(蔡伟光)．Analyzing impact factors of building energy consumption:modeling and empirical study(中国建筑能耗影响因素分析模型与实证研究)[D].Chongqing:Chongqing University,2011.
[7] LIU Mingda(刘明达)，MENG Jijun(蒙吉军)，LIU Bihan(刘碧寒)．Progress in the studies of carbon emission estimation[J]. Tropical Geography(热带地理)，2014,34(2):248-258.
[8] Intergovernmental Panel on Climate Change. Revised 1996IPCC guidelines for national greenhouse gas inventories[R]. Paris:Intergovernmental Panel on Climate Change,1997.
[9] YING Huaquan(应华权)．Scenario-based prediction of building carbon emissions and peak control strategies in Hubei Province(湖北省建筑碳排放情景预测与峰值调控研究)[D]. Wuhan:Huazhong University of Science&Technology,2015.
[10] National Institute of Standards and Technology. BEES[EB/OL].(2016-12-23)[2018-12-20]. https://www. nist. gov/services-resources/software/bees.
[11] German Sustainable Building Council. DGNB system[EB/OL].[2018-12-20]. https://www. dgnb-system. de/en/system/version2018/criteria/building-lifecycle-assessment/．
[12] ZHANG Z,WU X,YANG X,et al. BEPAS—a life cycle building environmental performance assessment model[J]. Building and Environment,2006,41(5):669-675.
[13] LI X,SU S,ZHANG Z,et al. An integrated environmental and health performance quantification model for pre-occupancy phase of buildings in China[J]. Environmental Impact Assessment Review,2017,63:1-11.
[14] LU H R,HANANDEH E A,GILBERT B P. A comparative life cycle study of alternative materials for Australian multi-storey apartment building frame constructions:environmental and economic perspective[J]. Journal of Cleaner Production,2017,166:458-473.
[15] WANG J,TINGLEY D D,MAYFIELD M,et al. Life cycle impact comparison of different concrete floor slabs considering uncertainty and sensitivity analysis[J].Journal of Cleaner Production,2018,189:374-385.
[16] OH B K,GLISIC B,LEE S H,et al. Comprehensive investigation of embodied carbon emissions,costs,design parameters,and serviceability in optimum green construction of two-way slabs in buildings[J]. Journal of Cleaner Production,2019,222:111-128.
[17] MOUSSAVI NADOUSHANI Z S,AKBARNEZHAD A.Effects of structural system on the life cycle carbon footprint of buildings[J]. Energy and Buildings,2015,102:337-346.
[18] AZARI R,ABBASABADI N. Embodied energy of buildings:a review of data,methods,challenges,and research trends[J]. Energy and Buildings,2018,168:225-235.
[19] LEONTIEF W. The structure of American economy,1919-1939:an empirical application of equilibrium analysis[M]. New York:Oxford University Press,1951.
[20] LEONTIEF W. Environmental repercussions and the economic structure:an input-output approach[J]. The Review of Economics and Statistics,1970,52(3):262-271.
[21] BAUMERT N,KANDER A,JIBORN M,et al. Global outsourcing of carbon emissions 1995-2009:a reassessment[J]. Environmental Science&Policy,2019,92:228-236.
[22] GUO J,ZHANG Y,ZHANG K. The key sectors for energy conservation and carbon emissions reduction in China:evidence from the input-output method[J]. Journal of Cleaner Production,2018,179:180-190.
[23] PAN W,PAN W,SHI Y,et al. China's inter-regional carbon emissions:an input-output analysis under considering national economic strategy[J]. Journal of Cleaner Production,2018,197:794-803.
[24] HUANG L,KRIGSVOLL G,JOHANSEN F,et al. Carbon emission of global construction sector[J]. Renewable and Sustainable Energy Reviews, 2018, 81:1906-1916.
[25] NSSN J,HOLMBERG J,WADESKOG A,et al. Direct and indirect energy use and carbon emissions in the production phase of buildings:an input-output analysis[J]. Energy,2007,32(9):1593-1602.
[26] ZHANG X,WANG F. Hybrid input-output analysis for life-cycle energy consumption and carbon emissions of China’s building sector[J]. Building and Environment,2016,104:188-197.
[27] ONAT N C,KUCUKVAR M,TATARI O. Scope-based carbon footprint analysis of U. S. residential and commercial buildings:an input-output hybrid life cycle assessment approach[J]. Building and Environment,2014,72:53-62.
[28] HONG Jingke(洪竞科)，WANG Yaowu(王要武)，CHANG Yuan(常远)．Life cycle assessment and its application in building sustainability[J]. Journal of Engineering Management(工程管理学报)，2012,26(1):17-22.
[29] ZHANG X,WANG F. Life-cycle carbon emission assessment and permit allocation methods:a multi-region case study of China’s construction sector[J]. Ecological Indicators,2017,72:910-920.
[30] FENG Bo(冯博)．Reaserch on the calculation CO2emission and energy and analysis of environmental efficiency of construction industry(建筑业二氧化碳排放及能源环境效率测算分析研究)[D]. Tianjin:Tianjin University,2015.
[31] YANG Xiu(杨秀)，WEI Qingpeng(魏庆芃)，JIANG Yi(江亿)．Study on statistical method for building energy consumption[J]. Energy of China(中国能源)，2006,28(10):12-16.
[32] WANG Qingyi(王庆一)．China building energy consumption statistics and calculation research[J]. Energy Conservation&Environmental Protection(节能与环保)，2007(8):9-10.
[33] CAI Weiguang(蔡伟光)，LI Xiaohui(李晓辉)，WANG Xia(王霞)，et al. Split model and application of building energy consumption based on energy balance table[J]. Heating Ventilating&Air Conditioning(暖通空调)，2017,47(11):27-34.
[34] HUO T,REN H,ZHANG X,et al. China's energy consumption in the building sector:a statistical yearbookenergy balance sheet based splitting method[J]. Journal of Cleaner Production,2018,185:665-679.
[35] YANG Xiu(杨秀)．Research on building energy conservation in China based on energy consumption data(基于能耗数据的中国建筑节能问题研究)[D]. Beijing:Tsinghua University,2009.
[36] ZHOU N,MCNEIL M,FRIDLEY D,et al. Energy use in china:sectoral trends and future outlook[R]. Berkeley:Lawrence Berkeley National Laboratory,2008.
[37] ZHOU Dadi(周大地)．China's sustainable energy scenarios in 2020(2020中国可持续能源情景)[M].Beijing:China Environmental Science Press,2003.
[38] PENG Chen(彭琛)，JIANG Yi(江亿)．Road map of building energy conservation in China(中国建筑节能路线图)[M]. Beijing:China Architecture&Building Press,2016.
[39] EHRLICH P R,HOLDREN J P. Impact of population growth[J]. Science,1971,171(3977):1212-1217.
[40] YORK R,ROSA E A,DIETZ T. STIRPAT,IPAT and Im PACT:analytic tools for unpacking the driving forces of environmental impacts[J]. Ecological Economics,2003,46(3):351-365.
[41] WAGGONER P E,AUSUBEL J H. A framework for sustainability science:a renovated IPAT identity[J].Proceedings of the National Academy of Sciences of the United States of America,2002,99(12):7860-7865.
[42] DIETZ T,ROSA E A. Rethinking the environmental impacts of population,affluence and technology[J]. Human Ecology Review,1994,1(2):277-300.
[43] KAYA Y. Impact of carbon dioxide emission control on GNP growth:interpretation of proposed scenarios[R].Paris:Intergovernmental Panel on Climate Change/Response Strategies Working Group,1989.
[44] WANG C,WANG F,ZHANG X,et al. Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang[J]. Renewable and Sustainable Energy Reviews,2017,67:51-61.
[45] MA M,YAN R,DU Y,et al. A methodology to assess China's building energy savings at the national level:an IPAT-LMDI model approach[J]. Journal of Cleaner Production,2017,143:784-793.
[46] LI H,MU H,ZHANG M,et al. Analysis on influence factors of China's CO2emissions based on path-STIRPAT model[J]. Energy Policy, 2011, 39(11):6906-6911.
[47] LIU D,XIAO B. Can China achieve its carbon emission peaking? A scenario analysis based on STIRPAT and system dynamics model[J]. Ecological Indicators,2018,93:647-657.
[48] YUE T,LONG R,CHEN H,et al. The optimal CO2emissions reduction path in Jiangsu province:an expanded IPAT approach[J]. Applied Energy,2013,112:1510-1517.
[49] LI F,XU Z,MA H. Can China achieve its CO2emissions peak by 2030?[J]. Ecological Indicators,2018,84:337-344.
[50] BRIZGA J,FENG K,HUBACEK K. Drivers of CO2emissions in the former Soviet Union:a country level IPAT analysis from 1990 to 2010[J]. Energy,2013,59:743-753.
[51] XIA C,LI Y,YE Y,et al. Decomposed driving factors of carbon emissions and scenario analyses of low-carbon transformation in 2020 and 2030 for Zhejiang Province[J]. Energies,2017,10(11):1747.
[52] YUAN R,ZHAO T,XU X,et al. Regional characteristics of impact factors for energy-related CO2emissions in China,1997-2010:evidence from tests for threshold effects based on the STIRPAT model[J]. Environmental Modeling&Assessment,2015,20(2):129-144.
[53] ZHOU Y,ZHAO L. Impact analysis of the implementation of cleaner production for achieving the low-carbon transition for SMEs in the Inner Mongolian coal industry[J]. Journal of Cleaner Production, 2016, 127:418-424.
[54] CUI H,ZHAO T,SHI H. STIRPAT-based driving factor decomposition analysis of agricultural carbon emissions in Hebei,China[J]. Polish Journal of Environmental Studies,2018,27(4):1449-1461.
[55] LIU Y,KUANG Y,HUANG N,et al. CO2emission from cement manufacturing and its driving forces in China[J]. International Journal of Environment and Pollution,2009,37(4):369-382.
[56] MA M,CAI W. What drives the carbon mitigation in Chinese commercial building sector? Evidence from decomposing an extended Kaya identity[J]. Science of The Total Environment,2018,634:884-899.
[57] HOEKSTRA R,VAN DEN BERGH J C J M. Comparing structural decomposition analysis and index[J]. Energy Economics,2003,25(1):39-64.
[58] TORVANGER A. Manufacturing sector carbon dioxide emissions in nine OECD countries,1973-87:a divisia index decomposition to changes in fuel mix,emission coefficients,industry structure,energy intensities and international structure[J]. Energy Economics,1991,13(3):168-186.
[59] BOYD G,MCDONALD J,ROSS M,et al. Separating the changing composition of U. S. manufacturing production from energy efficiency improvements:a divisia index approach[J]. The Energy Journal,1987,8(2):77-96.
[60] ANG B W,CHOI K. Decomposition of aggregate energy and gas emission intensities for industry:a refined divisia index method[J]. The Energy Journal,1997,18(3):59-73.
[61] DE-FREITAS L C,KANEKO S. Decomposing the decoupling of CO2emissions and economic growth in Brazil[J]. Ecological Economics,2011,70(8):1459-1469.
[62] DONG K,JIANG H,SUN R,et al. Driving forces and mitigation potential of global CO2emissions from 1980through 2030:evidence from countries with different income levels[J]. Science of The Total Environment,2019,649:335-343.
[63] WANG C,CHEN J,ZOU J. Decomposition of energyrelated CO2emission in China:1957-2000[J]. Energy,2005,30(1):73-83.
[64] YE B,JIANG J,LI C,et al. Quantification and driving force analysis of provincial-level carbon emissions in China[J]. Applied Energy,2017,198:223-238.
[65] LIAO C,WANG S,FANG J,et al. Driving forces of provincial-level CO2emissions in China’s power sector based on LMDI method[J]. Energy Procedia,2019,158:3859-3864.
[66] LIN B,LONG H. Emissions reduction in China’s chemical industry—based on LMDI[J]. Renewable and Sustainable Energy Reviews,2016,53:1348-1355.
[67] GUO M,MENG J. Exploring the driving factors of carbon dioxide emission from transport sector in BeijingTianjin-Hebei region[J]. Journal of Cleaner Production,2019,226:692-705.
[68] LU Y,CUI P,LI D. Carbon emissions and policies in China's building and construction industry:evidence from 1994 to 2012[J]. Building and Environment,2016,95:94-103.
[69] JIANG J,YE B,XIE D,et al. Provincial-level carbon emission drivers and emission reduction strategies in China:combining multi-layer LMDI decomposition with hierarchical clustering[J]. Journal of Cleaner Production,2017,169:178-190.
[70] CANSINO J M,ROMN R,ORDEZ M. Main drivers of changes in CO2emissions in the Spanish economy:a structural decomposition analysis[J]. Energy Policy,2016,89:150-159.
[71] BAIOCCHI G,MINX J C. Understanding changes in the UK’s CO2emissions:a global perspective[J]. Environmental Science&Technology, 2010, 44(4):1177-1184.
[72] WOOD R. Structural decomposition analysis of Australia's greenhouse gas emissions[J]. Energy Policy,2009,37(11):4943-4948.
[73] LIANG S,WANG H,QU S,et al. Socioeconomic drivers of greenhouse gas emissions in the United States[J]. Environmental Science&Technology,2016,50(14):7535-7545.
[74] WEI J,HUANG K,YANG S,et al. Driving forces analysis of energy-related carbon dioxide(CO2)emissions in Beijing:an input-output structural decomposition analysis[J]. Journal of Cleaner Production,2017,163:58-68.
[75] AKPAN U S. Effect of technology change on CO2emissions in Japan’s industrial sectors in the period 1995-2005:an input-output structural decomposition analysis[J]. Environmental and Resource Economics,2015,61(2):165-189.
[76] WEI Y,ZHU X,LI Y,et al. Influential factors of national and regional CO2emission in China based on combined model of DPSIR and PLS-SEM[J]. Journal of Cleaner Production,2019,212:698-712.
[77] PAN X,UDDIN M K,AI B,et al. Influential factors of carbon emissions intensity in OECD countries:evidence from symbolic regression[J]. Journal of Cleaner Production,2019,220:1194-1201.
[78] WEN L,SHAO H Y. Influencing factors of the carbon dioxide emissions in China's commercial department:a non-parametric additive regression model[J]. Science of The Total Environment,2019,668:1-12.
[79] CHEN J,SHI Q,SHEN L,et al. What makes the difference in construction carbon emissions between China and USA?[J]. Sustainable Cities and Society,2019,44:604-613.
[80] MA M,CAI W,CAI W. Carbon abatement in China's commercial building sector:a bottom-up measurement model based on Kaya-LMDI methods[J]. Energy,2018,165:350-368.
[81] LU Y,CUI P,LI D. Which activities contribute most to building energy consumption in China? A hybrid LMDI decomposition analysis from year 2007 to 2015[J]. Energy and Buildings,2018,165:259-269.
[82] MA M,YAN R,CAI W. An extended STIRPAT modelbased methodology for evaluating the driving forces affecting carbon emissions in existing public building sector:evidence from China in 2000-2015[J]. Natural Hazards,2017,89(2):741-756.
[83] JIANG R,LI R. Decomposition and decoupling analysis of life-cycle carbon emission in China’s building sector[J]. Sustainability,2017,9(5):193.
[84] ZHA D L,ZHOU D Q,ZHOU P. Driving forces of residential CO2emissions in urban and rural China:an index decomposition analysis[J]. Energy Policy,2010,38(7):3377-3383.
[85] LIN B,LIU H. CO2mitigation potential in China's building construction industry:a comparison of energy performance[J]. Building and Environment,2015,94:239-251.
Basic Information:
DOI：10.13637/j.issn.1009-6094.2019.0306
China Classification Code:X799.1;TU-023
Citation Information:
[1]LI Xiao-dong,ZHU Chen.Summary of research on account of carbon emission in building industry and analysis of its influential factors[J].Journal of Safety and Environment,2020,20(01):317-327.DOI:10.13637/j.issn.1009-6094.2019.0306.
Fund Information:
国家重点研发计划项目(2018YFC0704400)
2020-02-25
2020-02-25