基于数智化生产线的木质建材生产碳排放评估

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Abstract In order to understand carbon emissions from wooden building materials produced in digital and intelligent factories and to provide ground references and benchmarks for carbon reduction strategies, a life-cycle assessment (LCA) was conducted in this study to quantify the carbon footprints of main wooden building materials. The results show that the carbon footprints (per unit mass:kg CO₂e/kg) for a wood floor tile, a wood door, and a wood door frame are 1.21, 1.26, and 0.47, respectively. The carbon footprints of the floor tile and the door are greater than their domestic counterparts in the literature. The raw materials and production processes are the main sources of carbon emissions for wooden building materials, accounting for 54.74%~77.47% and 18.57%~38.94% of the total carbon emissions, respectively, while the carbon emissions during transportation and waste gas treatment process account for less than 9% of the total carbon emissions. The Monte Carlo simulations show a relatively low uncertainty of the calculated carbon emissions in this study. Digital and intelligent factories could potentially reduce carbon emissions in the future by procuring low-carbon raw materials, optimizing the product designs, improving the energy efficiency of equipment, and using clean energy like solar and wind.

Key words： wooden building materials life cycle assessment carbon emissions low-carbon strategy intelligent manufacturing

Received: 05 February 2022

PACS:

X820.3

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	Articles by authors
	LI Pei-xian
	SONG Guang-han
	YANG Xiao-lu
	SONG Xiang-nan
	LU Yu-jie

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LI Pei-xian,SONG Guang-han,YANG Xiao-lu等. Carbon emissions assessment of wooden building materials manufactured from a digital and intelligent production line[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(8): 3922-3930.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I8/3922

[1]	中国建筑节能协会.中国建筑能耗研究报告2020[J]. 建筑节能, 2021,49(2):1-6. China Association of Building Energy Efficiency. China building energy consumption annual report 2020[J]. Building Energy Efficiency, 2021,49(2):1-6.
[2]	Linkosalmi L, Husgafvel R, Fomkin A, et al. Main factors influencing greenhouse gas emissions of wood-based furniture industry in Finland[J]. Journal of Cleaner Production, 2016,113:596-605.
[3]	Iritani D R, Silva D A L, Saavedra Y M B, et al. Sustainable strategies analysis through Life Cycle Assessment:A case study in a furniture industry[J]. Journal of Cleaner Production, 2015,96:308-318.
[4]	Medeiros D L, Tavares A O D, Rapôso ÁLQRES, et al. Life cycle assessment in the furniture industry:the case study of an office cabinet[J]. International Journal of Life Cycle Assessment, 2017,22(11):1823-1836.
[5]	Suter F, Steubing B, Hellweg S. et al. Life cycle impacts and benefits of wood along the value chain:The case of Switzerland[J]. Journal of Industrial Ecology, 2017,21(4):874-886.
[6]	Hussain M, Malik RN, Taylor A.et al. Carbon footprint as an environmental sustainability indicator for the particleboard produced in Pakistan[J]. Environmental Research, 2017,155:385-393.
[7]	王珊珊,张寒,杨红强.中国人造板行业的生命周期碳足迹和能源耗用评估[J]. 资源科学, 2019,41(3):521-531. Wang S S, Zhang H, Yang H Q. Carbon footprint and energy consumption based on life cycle assessment of wood-based panel industry in China[J]. Resources Science, 2019,41(3):521-531.
[8]	Geng A X, Zhang H, Yang H Q. Greenhouse gas reduction and cost efficiency of using wood flooring as an alternative to ceramic tile:A case study in China[J]. Journal of Cleaner Production, 2017,166:438-448.
[9]	张南,李楠,刘一,等.生态设计家具的碳足迹核算与减排效果分析——以木质家具为例[J]. 生态学报, 2016,36(22):7235-7243. Zhang N, Li N, Liu Y, et al. Calculation of the carbon footprint of eco-design furniture and measures for its mitigation:a case study of wooden furniture[J]. Acta Ecologica Sinica, 2016,36(22):7235-7243.
[10]	林立平,黄圣游.木基材料产品碳足迹的核算与分析[J]. 中南林业科技大学学报, 2016,36(12):135-139. Lin L P, Huang S Y. Carbon footprint assessment of wood-based product[J]. Journal of Central South University of Forestry & Technology, 2016,36(12):135-139.
[11]	陈硕,胡继梅,沈乃强,等.强化木地板的"碳足迹"计算分析[J]. 木材工业, 2014,28(2):36-38. Chen S, Hu J M, Shen N Q, et al. "Carbon footprint" calculation and analysis for laminate flooring[J]. China Wood Industry, 2014,28(2):36-38.
[12]	黄娜,王洪涛,范辞冬,等.基于不确定度和敏感度分析的LCA数据质量评估与控制方法[J]. 环境科学学报, 2012,32(6):1529-1536. Huang N, Wang H T, Fan C D, et al. LCA data quality assessment and control based on uncertainty and sensitivity analysis[J]. Acta Scientiae Circumstantiae, 2012,32(6):1529-1536.
[13]	陈莎,李燚佩,曹磊,等.产品碳足迹评价中不确定度与敏感度相结合的数据质量分析[J]. 中国环境科学, 2014,34(4):1067-1072. Chen S, Li Y P, Cao L, et al. Data quality analysis with combination uncertainty and sensitivity for carbon footprint assessment of products[J]. China Environmental Science, 2014,34(4):1067-1072.
[14]	Zadeh L A. Outline of a new approach to the analysis of complex systems and decision processes[J]. IEEE Transactions on Systems Man and Cybernetics, 1973,SMC-3(1):28-44.
[15]	Djekic I, Petrovic J, Božičković A,et al. Main environmental impacts associated with production and consumption of milk and yogurt in Serbia-Monte Carlo approach[J]. Science of the Total Environment, 2019,695:133917.
[16]	Yu S R, Tao J. Economic, energy and environmental evaluations of biomass-based fuel ethanol projects based on life cycle assessment and simulation[J]. Applied Energy, 2009,86:S178-S188.
[17]	碳阻迹.碳智汇碳排放因子数据库[DB/OL].[2022-05-01]. Carbonstop. Carbon Intelligence database[DB/OL].[2022-05-01].
[18]	Geng A X, Ning Z, Zhang H, et al. Quantifying the climate change mitigation potential of China's furniture sector:Wood substitution benefits on emission reduction[J]. Ecological Indicators, 2019,103:363-372.
[19]	白伟荣.木质家具碳排放特征及碳减排策略研究[D]. 北京:北京林业大学, 2013. Bai W R. Analysis of carbon emission characteristics and carbon reduction strategies of wood furniture products[D]. Beijing:Beijing Forestry University, 2013.
[20]	thinkstep. GaBi LCA databases[DB/OL].[2022-05-01]
[21]	Simapro. Simapro LCI databases[DB/OL].[2022-05-01]
[22]	Bayus J A. Environmental life cycle comparison of aluminum-based high barrier flexible packaging laminates[D]. Rochester:Rochester Institute of Technology, 2015.
[23]	Guo M, Murphy R J. LCA data quality:Sensitivity and uncertainty analysis[J]. Science of the Total Environment, 2012,435-436:230-243.
[24]	Robati M, Mccarthy T, Kokogiannakis G. A method of uncertainty analysis for life cycle embodied CO2-e of building and structural materials in Australia[C]. Adelaide:28th Biennial National Conference of the Concrete Institute of Australia 2017, 2017:22-25October.
[25]	Nesheim S, Malo K A, Labonnote N. Competitiveness of timber floor elements:An assessment of structural properties, production, costs, and carbon emissions[J]. Forest Products Journal, 2021,71(2):111-123.
[26]	张春华,王莉媛,宋茜薇,等.1973~2013年黑龙江省森林碳储量及其动态变化[J]. 中国环境科学, 2018,38(12):4678-4686. Zhang C H, Wang L Y, Song Q W, et al. Biomass carbon stocks and dynamics of forests in Heilongjiang Province from 1973 to 2013[J]. China Environmental Science, 2018,38(12):4678-4686.
[27]	CSA Group. EPD 794H Panel Doors[Z]. 2017.
[28]	ift Rosenheim GmbH. EPD Steel/stainless steel doors[Z]. 2013.
[29]	赵若楠,董莉,白璐,等.光伏行业生命周期碳排放清单分析[J]. 中国环境科学, 2020,40(6):2751-2757. Zhao R N, Dong L, Bai L, et al. Inventoryanalysis on carbon emissions of photovoltaicindustry[J]. China Environmental Science, 2020,40(6):2751-2757.
[30]	姜雷,胡忆南.工业厂房光伏屋顶构造形态对发电效益的影响[J]. 济南大学学报:自然科学版, 2022,36(2):183-188,195. Jiang L, Hu Y N. Influence of photovoltaic roof structural forms of industrial plants on power generation efficiency[J]. Journal of University of Jinan (Science and Technology), 2022,36(2):183-188,195.
[31]	李建林,方知进,谭宇良,等.电化学储能系统在整县制屋顶光伏中应用前景分析[J]. 太阳能学报, 2022,43(4):1-12. Li J L, Fang Z J, Tan Y L, et al. Analysis of application prospect of energy storage technology in county-wide rooftop photovoltaic system[J]. Acta Energiae Solaris Sinica, 2022,43(4):1-12.