基于材料基因的不同钢渣处理方式下的水泥碳核算方法

doi:10.16552/j.cnki.issn1001-1625.2026.0050

摘要/Abstract

摘要：

传统碳排放计算方法通常采用行业或国家的平均排放因子，无法精准反映水泥在反应过程中各矿物形成特性对碳排放的调控机制。本文基于水泥四种主要矿物，提出了材料基因碳排放核算方法，并以此方法计算了钢渣在水泥中不同应用方式的碳排放差异，与传统碳排放计算方法进行了对比。结果表明，材料基因核算方法与传统方法计算结果相近，在钢渣用作水泥生产替代原料、水泥混合材、碳化胶凝材料等不同应用案例中，利用碳化钢渣粉制备水泥的碳排放强度比最低，在去除运输的影响后，碳排放强度比为16.04 kgCO₂/MPa。尤其当公路运输距离超过300 km时，各类钢渣处理方式制备水泥的减碳效果差异减小，均趋近于零，应用意义不大。材料基因方法能反映材料在反应过程中的热力学特性对碳排放的调控机制，可以为水泥企业筛选和优化钢渣利用方案提供数据依据。

关键词: 材料基因, 钢渣, 水泥, 水泥矿物, 碳核算, 碳排放强度比

Abstract:

Traditional carbon emission calculation methods typically employ industry or national average emission factors， which cannot accurately reflect the regulatory mechanism of cement’s mineral formation characteristics on carbon emissions during the reaction process. These methods focus on inventory analysis and aggregation of energy consumption and emissions in processes such as raw material grinding， clinker calcination， and cement grinding， but fail to address the fundamental issue of where energy is consumed at the molecular level. However， the final performance and environmental impact of cement are fundamentally determined by its mineral composition.

Based on the concept of material genome， generally understood as the basic structural unit that maintains the intrinsic characteristics of materials， this paper proposed a material genome-based carbon emission accounting method utilizing the four main minerals of cement. By incorporating the regulatory mechanism of thermodynamic characteristics of materials during the reaction process on carbon emissions， a material genome-based carbon emission accounting model was constructed. This model linked microscopic mineral thermodynamic data with macroscopic industrial production parameters to reveal the impact pathways of different steel slag utilization methods in cement production on carbon emissions， and compared them with traditional calculation methods.

The results show that carbon emission values calculated by the material genome accounting method fluctuate within 2.86% to 4.07% compared to those calculated by traditional methods， indicating close agreement. Meanwhile， compared to traditional methods， it better reflects the impact of changes in mineral composition ratios on carbon emission values and more accurately calculates carbon emissions for various types of solid waste cement. This facilitates direct accounting of product carbon emissions through terminal product composition and guides formula design. In different application cases such as using steel slag as alternative raw material for cement production， cement admixture， and carbonated cementitious material， cement prepared using carbonated steel slag powder exhibits the lowest carbon emission intensity ratio. After excluding the impact of transportation， the carbon emission intensity ratio is 16.04 kgCO₂/MPa. Meanwhile， without considering variable factors such as transport distance， its overall carbon emission is also relatively the lowest， with only 726.62 kgCO₂ emitted per ton of cement. For steel slag used as alternative raw material and steel slag phase-separated clinker technology， the carbon emission values of the two are similar， but the carbon emission of steel slag phase-separated clinker technology in the process and fuel stages is 3.47 kgCO₂/t lower than that of steel slag as alternative raw material. Additionally， if road transportation is adopted， when the transport distance exceeds 140 km for steel slag as alternative raw material， the carbon reduction effect of steel slag approaches zero； for cement prepared with steel slag treated by high-temperature reconstruction， cement admixture， carbonated cementitious material， and phase-separated clinker technology， these distances are 233， 240， 263， and 109 km， respectively. Therefore， the transportation distance radius for steel slag utilization should not exceed 300 km. The material genome method can reflect the regulatory mechanism of thermodynamic characteristics of materials on carbon emissions during the reaction process， providing data basis for cement enterprises to screen and optimize steel slag utilization schemes.

Key words: material gene, steel slag, cement, cement mineral, carbon accounting, carbon emission intensity ratio

中图分类号:

TU525

杜礼文韬, 任雪红, 张洪滔, 叶家元, 张文生. 基于材料基因的不同钢渣处理方式下的水泥碳核算方法[J]. 硅酸盐通报, 2026, 45(7): 2368-2378.

DU Liwentao, REN Xuehong, ZHANG Hongtao, YE Jiayuan, ZHANG Wensheng. Carbon Accounting Method for Cement under Different Steel Slag Treatment Methods Based on Material Genes[J]. BULLETIN OF THE CHINESE CERAMIC SOCIETY, 2026, 45(7): 2368-2378.

图/表 14

参考文献 30

[1]	CHENG D Y， REINER D M， YANG F， et al. Projecting future carbon emissions from cement production in developing countries［J］. Nature Communications， 2023， 14： 8213. DOI PMID
[2]	FU S T， KWON E E， LEE J. Upcycling steel slag into construction materials［J］. Construction and Building Materials， 2024， 444： 137882. DOI URL
[3]	CHEN Z H， CANG Z Z， YANG F M， et al. Carbonation of steelmaking slag presents an opportunity for carbon neutral： a review［J］. Journal of CO₂ Utilization， 2021， 54： 101738.
[4]	ZHOU F F， PAN G H， WANG Q P， et al. Effects of the surface nano-reconstruction of steel slag on the performance of cement-based materials［J］. Construction and Building Materials， 2025， 475： 141172. DOI URL
[5]	FAN C L， WEI R F， CHENG T， et al. The positive contributions of steel slag in reducing carbon dioxide emissions in the steel industry： waste heat recovery， carbon sequestration， and resource utilization［J］. Chemical Engineering Journal， 2024， 498： 155379. DOI URL
[6]	DUAN W J， DONG X Y， GAO L H， et al. Chemical utilization of slag waste heat for carbon emission reduction in the iron and steel industry［J］. Journal of Environmental Chemical Engineering， 2025， 13（4）： 117224. DOI URL
[7]	谭忆秋，吕慧杰，徐慧宁. 材料基因思想在沥青路面材料领域的应用展望［J］. 交通运输研究， 2020， 6（5）： 2-12.
	TAN Y Q， LÜ H J， XU H N. Application prospect of material genetics idea in asphalt pavement materials［J］. Transport Research， 2020， 6（5）： 2-12 （in Chinese）. DOI
[8]	GARTNER E. Industrially interesting approaches to “low-CO₂” cements［J］. Cement and Concrete Research， 2004， 34（9）： 1489-1498. DOI URL
[9]	BARCELO L， KLINE J， WALENTA G， et al. Cement and carbon emissions［J］. Materials and Structures， 2014， 47（6）： 1055-1065. DOI URL
[10]	SCHNEIDER M， ROMER M， TSCHUDIN M， et al. Sustainable cement production： present and future［J］. Cement and Concrete Research， 2011， 41（7）： 642-650. DOI URL
[11]	赵乃仁，周文轶. 采用辊压机的粉磨系统的选型计算讨论［J］. 水泥工程， 2007（4）： 1-12+22.
	ZHAO N R， ZHOU W Y. Discussion on selection and calculation of grinding system using roller press［J］. Cement Engineering， 2007（4）： 1-12+22 （in Chinese）.
[12]	LI R， WEI Y C， CAI W G， et al. Tracking cement transportation carbon emissions in China： historical assessment and future simulation［J］. Environmental Impact Assessment Review， 2025， 110： 107696. DOI URL
[13]	JU J T， CAO H B， GUO W K， et al. Experimental study on calcination of Portland cement clinker using different contents of stainless steel slag［J］. Materials， 2024， 17（10）： 2305. DOI URL
[14]	TSAKIRIDIS P E， PAPADIMITRIOU G D， TSIVILIS S， et al. Utilization of steel slag for Portland cement clinker production［J］. Journal of Hazardous Materials， 2008， 152（2）： 805-811. DOI URL
[15]	蒋亮，韩霄，李茂辉，等. 高温重构钢渣复合水泥的制备与性能研究［J］. 金属矿山， 2018（8）： 185-190.
	JIANG L， HAN X， LI M H， et al. Preparation and properties of Portland cement mixed with high temperature reconstituted steel slag［J］. Metal Mine， 2018（8）： 185-190 （in Chinese）.
[16]	YANG S Q， DONG X W， ZHAO X D， et al. High value-added utilization of waste glass powder and steel slag for a novel zero-clinker cement： coactivation mechanism and environmental impact［J］. Construction and Building Materials， 2025， 474： 141032. DOI URL
[17]	张恒飞，刘茂举，王东哲，等. 钢渣碳化技术影响因素的研究进展［J］. 中国建材科技， 2023， 32（1）： 74-78.
	ZHANG H F， LIU M J， WANG D Z， et al. Research progress of influencing factors of steel slag carbonation technology［J］. China Building Materials Science & Technology， 2023， 32（1）： 74-78 （in Chinese）.
[18]	LIU P， GU Y H， ZHONG J K， et al. Carbonated steel slag powder in cement： retardation mechanism and triethanolamine-enhanced hydration strategy［J］. Construction and Building Materials， 2025， 492： 142881. DOI URL
[19]	ZHAO D Q， ZHANG D， SHEN W G， et al. Investigation on industrial trial production of multi-phased clinker with crude granular steel slag［J］. Journal of Cleaner Production， 2022， 337： 130467. DOI URL
[20]	ZHAO D Q， SHEN W G， WANG Y N， et al. Direct use of original granular steel slag to prepare multi-phased clinker： sintering mechanism and properties［J］. Construction and Building Materials， 2023， 390： 131575. DOI URL
[21]	GAO P， ZHA W， CHU Y T， et al. Calculation model for CO₂ emissions of blended cement production［J］. Journal of Cleaner Production， 2025， 489： 144646. DOI URL
[22]	廖晓樱，罗　帆，刘　昊. 物料相对易磨性与粉磨功指数的比较［J］. 水泥， 2003（4）： 22-25.
	LIAO X Y， LUO F， LIU H. Comparison between stuff relative grindability and grinding power index［J］. Cement， 2003（4）： 22-25 （in Chinese）.
[23]	GAO T M， SHEN L， SHEN M， et al. Analysis on differences of carbon dioxide emission from cement production and their major determinants［J］. Journal of Cleaner Production， 2015， 103： 160-170. DOI URL
[24]	YU J， WANG K B. Study on characteristics of steel slag for CO₂ capture［J］. Energy & Fuels， 2011， 25（11）： 5483-5492. DOI URL
[25]	BONENFANT D， KHAROUNE L， SAUVE S， et al. CO₂ sequestration potential of steel slags at ambient pressure and temperature［J］. Industrial & Engineering Chemistry Research， 2008， 47（20）： 7610-7616. DOI URL
[26]	HEDMAN B. Waste heat recovery in Turkish cement industry review of existing installations and assessment of remaining potential［M］. Washington： IFC， 2019.
[27]	LYKAS P， BELLOS E， ATSONIOS K， et al. Thermodynamic and economic investigation of a waste heat recovery system with thermoelectric generators in the cement industry［J］. Thermal Science and Engineering Progress， 2025， 60： 103431. DOI URL
[28]	MOSSIE A T， KHATIWADA D， PALM B， et al. Techno-economic analysis of waste heat recovery power plants in cement industry： a case study in Ethiopia［J］. Next Energy， 2025， 8： 100339. DOI URL
[29]	KOOKOS I K， PONTIKES Y， ANGELOPOULOS G N， et al. Classical and alternative fuel mix optimization in cement production using mathematical programming［J］. Fuel， 2011， 90（3）： 1277-1284. DOI URL
[30]	LU H Y， PRICE L， ZHANG Q. Capturing the invisible resource： analysis of waste heat potential in Chinese industry［J］. Applied Energy， 2016， 161： 497-511. DOI URL

Mineral	ΔH/（GJ·t^-1）	CO₂ emission from fuel/（kg·t^-1）	CO₂ emission from feedstock decomposition/（kg·t^-1）	Total CO₂emission/（kg·t^-1）
C₃S	1.85	282	578	860
C₂S	1.34	204	511	715
C₃A	1.95	298	489	787
C₄AF	1.36	208	362	570

Mineral	ΔH/（GJ·t^-1）	CO₂ emission from fuel/（kg·t^-1）	CO₂ emission from feedstock decomposition/（kg·t^-1）	Total CO₂emission/（kg·t^-1）
C₃S	1.85	282	578	860
C₂S	1.34	204	511	715
C₃A	1.95	298	489	787
C₄AF	1.36	208	362	570

Transportation mode	Carbon emission factor/［kgCO₂e·（t·km）^-1］
Light-duty gasoline truck transportation （2 t payload）	0.334
Medium-duty gasoline truck transportation （8 t payload）	0.115
Heavy-duty gasoline truck transportation （10 t payload）	0.104
Heavy-duty gasoline truck transportation （18 t payload）	0.104
Light-duty diesel truck transportation （2 t payload）	0.286
Medium-duty diesel truck transportation （8 t payload）	0.179
Heavy-duty diesel truck transportation （10 t payload）	0.162
Heavy-duty diesel truck transportation （18 t payload）	0.129
Heavy-duty diesel truck transportation （30 t payload）	0.078
Heavy-duty diesel truck transportation （46 t payload）	0.057
Electric locomotive transportation	0.010
Diesel locomotive transportation	0.011
Railway transportation （China market average）	0.010
Liquid cargo ship transportation （2 000 t payload）	0.019
Dry bulk carrier transportation （2 500 t payload）	0.015
Container ship transportation （200 TEU payload）	0.012

Transportation mode	Carbon emission factor/［kgCO₂e·（t·km）^-1］
Light-duty gasoline truck transportation （2 t payload）	0.334
Medium-duty gasoline truck transportation （8 t payload）	0.115
Heavy-duty gasoline truck transportation （10 t payload）	0.104
Heavy-duty gasoline truck transportation （18 t payload）	0.104
Light-duty diesel truck transportation （2 t payload）	0.286
Medium-duty diesel truck transportation （8 t payload）	0.179
Heavy-duty diesel truck transportation （10 t payload）	0.162
Heavy-duty diesel truck transportation （18 t payload）	0.129
Heavy-duty diesel truck transportation （30 t payload）	0.078
Heavy-duty diesel truck transportation （46 t payload）	0.057
Electric locomotive transportation	0.010
Diesel locomotive transportation	0.011
Railway transportation （China market average）	0.010
Liquid cargo ship transportation （2 000 t payload）	0.019
Dry bulk carrier transportation （2 500 t payload）	0.015
Container ship transportation （200 TEU payload）	0.012

Type	Mass fraction/%
Type	SiO₂	Al₂O₃	Fe₂O₃	CaO	MgO	Other	Loss
Limestone	4.40	0.64	0.32	52.41	0.47	0.35	41.30
Fly ash	46.34	44.77	2.29	2.55	0.37	0.37	0.92
Steel slag	33.30	7.48	38.56	12.34	2.44	7.36	-2.1
Sandstone	87.35	3.92	3.10	0.35	0.11	0.02	2.08