Lifecycle carbon footprint and cost assessment for coal-to-liquid coupled with carbon capture, storage, and utilization technology in China

doi:10.1007/s11708-023-0879-3

Front. Energy

2023, Vol. 17

Issue (3) : 412-427 https://doi.org/10.1007/s11708-023-0879-3

RESEARCH ARTICLE

Lifecycle carbon footprint and cost assessment for coal-to-liquid coupled with carbon capture, storage, and utilization technology in China

Jingjing XIE¹, Kai LI¹, Jingli FAN²(

), Xueting PENG³, Jia LI⁴, Yujiao XIAN⁵(

)

¹. Centre for Sustainable Development and Energy Policy Research, School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
². Centre for Sustainable Development and Energy Policy Research, School of Energy and Mining Engineering; State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China
³. The Administrative Centre for China’s Agenda 21, Ministry of Science and Technology, Beijing 100038, China
⁴. The Hong Kong University of Science and Technology (Guangzhou), Carbon Neutrality and Climate Change Thrust, Guangzhou 511400, China; Jiangmen Laboratory of Carbon Science and Technology, The Hong Kong University of Science and Technology, Jiangmen 529199, China
⁵. Centre for Sustainable Development and Energy Policy Research, School of Energy and Mining Engineering; State Key Laboratory of Coal Resources and Safe Mining; School of Management, China University of Mining and Technology, Beijing 100083, China

Download: PDF(6290 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

The coal-to-liquid coupled with carbon capture, utilization, and storage technology has the potential to reduce CO₂ emissions, but its carbon footprint and cost assessment are still insufficient. In this paper, coal mining to oil production is taken as a life cycle to evaluate the carbon footprint and levelized costs of direct-coal-to-liquid and indirect-coal-to-liquid coupled with the carbon capture utilization and storage technology under three scenarios: non capture, process capture, process and public capture throughout the life cycle. The results show that, first, the coupling carbon capture utilization and storage technology can reduce CO₂ footprint by 28%–57% from 5.91 t CO₂/t·oil of direct-coal-to-liquid and 24%–49% from 7.10 t CO₂/t·oil of indirect-coal-to-liquid. Next, the levelized cost of direct-coal-to-liquid is 648–1027 $/t of oil, whereas that of indirect-coal-to-liquid is 653–1065 $/t of oil. When coupled with the carbon capture utilization and storage technology, the levelized cost of direct-coal-to-liquid is 285–1364 $/t of oil, compared to 1101–9793 $/t of oil for indirect-coal-to-liquid. Finally, sensitivity analysis shows that CO₂ transportation distance has the greatest impact on carbon footprint, while coal price and initial investment cost significantly affect the levelized cost of coal-to-liquid.

Keywords coal-to-liquid carbon capture utilization and storage (CCUS) carbon footprint levelized cost of liquid lifecycle assessment

Corresponding Author(s): Jingli FAN,Yujiao XIAN

Online First Date: 14 July 2023 Issue Date: 09 August 2023

Cite this article:

Jingjing XIE,Kai LI,Jingli FAN, et al. Lifecycle carbon footprint and cost assessment for coal-to-liquid coupled with carbon capture, storage, and utilization technology in China[J]. Front. Energy, 2023, 17(3): 412-427.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-023-0879-3
https://academic.hep.com.cn/fie/EN/Y2023/V17/I3/412

Fig.1 Study boundary of DCL.

Fig.2 Study boundary of ICL.

Parameters	Parameter description	Value	Unit	Data source
$R r$	Percentage of railway transportation of coal	70.1%	–	Refs. [17,23,24]
$R s$	Percentage of waterway transportation of coal	11.75%	–	Refs. [17,23,24]
$R h$	Percentage of highway transportation of coal	18.15%	–	Refs. [17,23,24]
$D r$	Average transportation distance of coal by railway	696.27	km	Ref. [25]
$D s$	Average transportation distance of coal by waterway	1402.69	km	Ref. [25]
$D h$	Average transportation distance of coal by highway	176.52	km	Ref. [25]
$E r$	Carbon emission factor of railway transportation	101.78	kg/(10⁴ t·km)	Ref. [26]
$E s$	Carbon emission factor of highway transportation	1406.16	kg/(10⁴ t·km)	Ref. [27]
$E h$	Carbon emission factor of waterway transportation	58.92	kg/(10⁴ t·km)	Ref. [28]

Tab.1 Main parameters of carbon footprint assessment of coal transportation

Tab.2 Carbon balance sheet

Parameters	Parameter description	Value	Unit	Data source
$E c c 1 c c s$	Energy consumption of per unit CO₂ of process capture	220	kWh/t	Refs. [20,31]
$E c c 2 c c s$	Energy consumption of per unit CO₂ of public capture	720	kWh/t	Refs. [20,31]
$E c t c c s$	CO₂ energy consumption of per unit transportation	1.3	kWh/(t?km)	Ref. [32]
$E c s E c c s$	Oilfield CO₂ storage energy consumption	15.6	kWh/t	Ref. [16]
$E c s c c s$	Brackish water layer CO₂ sequestration energy consumption	12	kWh/t	Ref. [32]

Tab.3 Main parameters of carbon footprint assessment for the CCUS technology

Tab.4 Unit transportation cost of coal

Tab.5 Cost parameters of CTL projects

Tab.6 Feedstock consumption of CTL

Parameters	Description	Data	Unit	Data source
C_w	Capture cost of process emission source	18.58	$/t	Ref. [51]
C_b	Capture cost of Boiler emission source	51.30	$/t	Ref. [46]
C_T	Transportation cost	0.15	$/(t?km)	Ref. [46]
C_DSF	DSF cost	8.92	$/t	Ref. [46]
C_EOR	EOR cost	11.15	$/t	Ref. [52]
$P C O 2$	Carbon price	6.68	$/t	National average carbon price
e	Oil change rate	0.04	t oil/t CO₂	Ref. [53]
P_oil	Oil price	459.51	$/t	Ref. [44]

Tab.7 CCUS-related cost parameters

Tab.8 CO₂ capture by coal-to-liquid coupled CCUS technology

Fig.3 (a) Carbon footprint and (b) cost of DCL and ICL (Trans representing the cost of coal transportation, CAP representing initial investment cost, OPEX representing operation and maintenance costs, Fuel representing raw material cost, CCUS representing CCUS cost, and Income representing carbon market revenue or oil displacement revenue).

Fig.4 Carbon footprint of DCL coupled CCUS under (a) S2 and (b) S3 scenarios (M&W representing coal mining and washing process emissions, Trans representing the coal transportation process emissions, and CTL representing coal to oil process emissions).

Fig.5 LCOL of DCL in different conditions (unit: $/t of oil; L/M/H respectively representing the low/middle/high price of coal, and D1/D2/D3 respectively representing the CO₂ transportation distance of 0/100/250 km).

Fig.6 Cost components of DCL (Trans representing the cost of coal transportation, CAP representing initial investment cost, OPEX representing operation and maintenance costs, Fuel representing raw material cost, CCUS representing CCUS cost, and Income representing carbon market revenue or oil displacement revenue).

Fig.7 Carbon footprint of ICL coupled CCUS under (a) S2 and (b) S3 scenarios.

Fig.8 LCOL of ICL in different conditions (unit: $/t of oil; L/M/H respectively representing the low/middle/high price of coal, and D1/D2/D3 respectively representing the CO₂ transportation distance of 0/100/250 km).

Fig.9 Cost components of ICL (Trans represents the cost of coal transportation, CAP represents initial investment cost, OPEX represents operation and maintenance costs, Fuel represents raw material cost, CCUS represents CCUS cost, Income represents carbon market revenue or oil displacement revenue).

Fig.10 Sensitivity of carbon footprint to CO₂ transportation distance of CTL.

Fig.11 Sensitivity of LCOL to various factors under the S2 scenario.

1	Bureau of Statistics NationalChina. China Energy Statistical Yearbook 2021. Beijing: China Statistics Press, 2022 (in Chinese)
2	L Zhang, Q Shen, M Wang. et al.. Driving factors and predictions of CO2 emission in China’s coal chemical industry. Journal of Cleaner Production, 2019, 210: 1131–1140 https://doi.org/10.1016/j.jclepro.2018.10.352
3	X Yao, Y Fan, Y Xu. et al.. Is it worth to invest? — An evaluation of CTL-CCS project in China based on real options.. Energy, 2019, 182: 920–931 https://doi.org/10.1016/j.energy.2019.06.100
4	P Jaramillo. A life cycle comparison of coal and natural gas for electricity generation and the production of transportation fuels. Dissertation for the Doctoral Degree. Pittsburgh, Pennsylvania: Carnegie Mellon University, 2007
5	M Guo, Y Xu. Coal-to-liquids projects in China under water and carbon constraints. Energy Policy, 2018, 117: 58–65 https://doi.org/10.1016/j.enpol.2018.02.038
6	J L Fan, M Xu, S Wei. et al.. Carbon reduction potential of China’s coal-fired power plants based on a CCUS source-sink matching model. Resources, Conservation and Recycling, 2021, 168: 105320 https://doi.org/10.1016/j.resconrec.2020.105320
7	E Kawai, A Ozawa, B D Leibowicz. Role of carbon capture and utilization (CCU) for decarbonization of industrial sector: A case study of Japan. Applied Energy, 2022, 328: 120183 https://doi.org/10.1016/j.apenergy.2022.120183
8	K Li, S Shen, J L Fan. et al.. The role of carbon capture, utilization and storage in realizing China’s carbon neutrality: A source-sink matching analysis for existing coal-fired power plants. Resources, Conservation and Recycling, 2022, 178: 106070 https://doi.org/10.1016/j.resconrec.2021.106070
9	F Wang, J D Harindintwali, Z Z Yuan. et al.. Technologies and perspectives for achieving carbon neutrality. Innovation, 2021, 2(4): 100180 https://doi.org/10.1016/j.xinn.2021.100180
10	S Budinis, S Krevor, N M Dowell. et al.. An assessment of CCS costs, barriers and potential. Energy Strategy Reviews, 2018, 22: 61–81 https://doi.org/10.1016/j.esr.2018.08.003
11	J L Fan, S Wei, L Yang. et al.. Comparison of the LCOE between coal-fired power plants with CCS and main low-carbon generation technologies: Evidence from China. Energy, 2019, 176: 143–155 https://doi.org/10.1016/j.energy.2019.04.003
12	C Bassano, P Deiana, G Vilardi. et al.. Modeling and economic evaluation of carbon capture and storage technologies integrated into synthetic natural gas and power-to-gas plants. Applied Energy, 2020, 263: 114590 https://doi.org/10.1016/j.apenergy.2020.114590
13	S Yang, Z Xiao, C Deng. et al.. Techno-economic analysis of coal-to-liquid processes with different gasifier alternatives. Journal of Cleaner Production, 2020, 253: 120006 https://doi.org/10.1016/j.jclepro.2020.120006
14	H C Mantripragada. Techno-economic evaluation of coal-to-liquids (CTL) plants and their effects on environment and resources. Dissertation for the Doctoral Degree. Pittsburgh, PA: Carnegie Mellon University, 2010
15	P Jaramillo, W M Griffin, H S Matthews. Comparative analysis of the production costs and life-cycle GHG emissions of FT liquid fuels from coal and natural gas. Environmental Science & Technology, 2008, 42(20): 7559–7565 https://doi.org/10.1021/es8002074
16	D Gao, C Ye, X Ren. et al.. Life cycle analysis of direct and indirect coal liquefaction for vehicle power in China. Fuel Processing Technology, 2018, 169: 42–49 https://doi.org/10.1016/j.fuproc.2017.09.007
17	Y Zhang, J Li, X Yang. Comprehensive competitiveness assessment of four coal-to-liquid routes and conventional oil refining route in China. Energy, 2021, 235: 121442 https://doi.org/10.1016/j.energy.2021.121442
18	L El Joumri, N Labjar, M Dalimi. et al.. Life cycle assessment (LCA) in the olive oil value chain: A descriptive review. Environmental Development, 2023, 45: 100800 https://doi.org/10.1016/j.envdev.2022.100800
19	IPCC. Carbon Dioxide Capture and Storage. Cambridge, UK: Cambridge University Press, 2005
20	K Fu, S Qi. Accounting method and application of provincial electricity carbon emission responsibility in China. China Population Resources and Environment, 2014, 24(4): 27–34
21	Y Shan, D Guan, J Liu. et al.. Methodology and applications of city level CO2 emission accounts in China. Journal of Cleaner Production, 2017, 161: 1215–1225 https://doi.org/10.1016/j.jclepro.2017.06.075
22	of Ecology Ministry(MEE) EnvironmentChina. Notice on key tasks related to the management of greenhouse gas emission reports for enterprises in 2022. 2022-03-15, available at the website of MEE (in Chinese)
23	Bureau of Statistics NationalChina. China Statistical Yearbook 2021. Beijing: China Statistics Press, 2022 (in Chinese)
24	Bureau of Statistics NationalChina. China Transport Statistical Yearbook 2021. Beijing: China Statistics Press, 2022 (in Chinese)
25	Bureau of Statistics NationalChina. CPI moderately rising in 2022, PPI growth falling back. 2023-01-18, available at the website of National Bureau of Statistics (in Chinese)
26	Y Zhang, M Cheng, X Liu. Research on greenhouse gas emissions during the life cycle of coal railway transportation in China. Resources Science, 2021, 43(03): 601–611 https://doi.org/10.18402/resci.2021.03.16
27	G Jiang. Research on comprehensive evaluation and optimization of China’s energy transport corridor system. Dissertation for the Doctoral Degree. Beijing: China University of Mining and Technology, 2021 (in Chinese)
28	A Gan, L Men, K Chen. Carbon footprint prediction and policy recommendations for China’s international shipping industry. Water Transport Management, 2014, 36(10): 9–11
29	X Wu. The First Exploration of Carbon Dioxide Capture and Geological Storage in China on a Large Scale. Beijing: Science Press, 2013 (in Chinese)
30	Academy of Sciences Chinese. The Administrative Center for China’s Agenda 21—China carbon capture, utilization and storage (CCUS) technology assessment report. 2021 (in Chinese)
31	J Huang. Assessment Report on Carbon Capture, Utilization and Storage Technologies in China. Beijing: Science Press, 2021 (in Chinese)
32	B CaiQ LiG Liu, et al.. Carbon dioxide capture, utilization and storage (CCUS) report in China. Institute of Environmental Planning, Ministry of Ecology and Environment, China, 2020 (in Chinese)
33	X Ouyang, B Lin. Levelized cost of electricity (LCOE) of renewable energies and required subsidies in China. Energy Policy, 2014, 70: 64–73 https://doi.org/10.1016/j.enpol.2014.03.030
34	IEAOECD. Projected costs of generating electricity 2015 edition. International Energy Agency, Nuclear Energy Agency and Organization for Economic Co-operation and Development, France, 2015
35	Baike Network Jiaotong. Unified railway freight rate (national railway freight price list). 2022 (in Chinese)
36	of Transport (MoT) of the People’s Republic of China Ministry. Statistical bulletin on the development of the transportation industry in 2021. 2022-05-22, available at the website of the website of MoT (in Chinese)
37	Logistics Information Center (CLIC) China. China highway logistics freight rate weekly index report. 2023-04-28, available at the website of CLIC (in Chinese)
38	C Fu, X F Bai, H Ding. et al.. Basic requirements for coal quality in China’s power coal and coal chemical industry. Coal Quality Technology, 2019, 34(05): 1–8
39	Coal Network Qinhuangdao. Overall stabilization of coal prices in 2022. 2023 (in Chinese)
40	CCTD. Resource base of index business. 2021 (in Chinese)
41	International E-Coumerce Network China. Commodity Price Index (CPPI) 2022. 2022 (in Chinese)
42	G Li, Z Liu, T Liu. et al.. Techno-economic analysis of a coal to hydrogen process based on ash agglomerating fluidized bed gasification. Energy Conversion and Management, 2018, 164: 552–559 https://doi.org/10.1016/j.enconman.2018.03.035
43	Y Wang, G Li, Z Liu. et al.. Techno-economic analysis of biomass-to-hydrogen process in comparison with coal-to-hydrogen process. Energy, 2019, 185: 1063–1075 https://doi.org/10.1016/j.energy.2019.07.119
44	Price Information Network China. Latest year’s price data. 2021-07-13, available at the website of Chinaprice (in Chinese)
45	J L Fan, P Yu, K Li. et al.. A levelized cost of hydrogen (LCOH) comparison of coal-to-hydrogen with CCS and water electrolysis powered by renewable energy in China. Energy, 2022, 242: 123003 https://doi.org/10.1016/j.energy.2021.123003
46	D KearnsH LiuC Consoli. Technology readiness and costs of CCS. Global CCS Institute, Australia. 2021
47	Y Zhao, J Li, S Zhang. et al.. Amidoxime-functionalized magnetic mesoporous silica for selective sorption of U(VI). RSC Advances, 2014, 4(62): 32710–32717 https://doi.org/10.1039/C4RA05128A
48	R T Dahowski, C L Davidson, X C Li. et al.. Examining CCS deployment potential in China via application of an integrated CCS cost curve. Energy Procedia, 2013, 37: 2487–2494 https://doi.org/10.1016/j.egypro.2013.06.130
49	United Environment Exchange Sichuan. Domestic market. 2022-12-31, available at the website of Carbon Emission Trading (in Chinese)
50	No.1 Source for Oil & Energy New The. Oil price charts WTI crude. 2021-12-31, available at the website of oilprice
51	M Hu. Study on the development characteristics and cost boundaries of CCUS industry. Oil and Gas Reservoir Evaluation and Development, 2020, 10(03): 15–22+2
52	Turan Alex Zapantis Guloran. The global statue of CCS 2021. Global CCS Institute, Australia, 2021
53	H C Mantripragada, E S Rubin. CO2 implications of coal-to-liquids (CTL) plants. International Journal of Greenhouse Gas Control, 2013, 16: 50–60 https://doi.org/10.1016/j.ijggc.2013.03.007
54	H C Mantripragada, E S Rubin. Techno-economic evaluation of coal-to-liquids (CTL) plants with carbon capture and sequestration. Energy Policy, 2011, 39(5): 2808–2816 https://doi.org/10.1016/j.enpol.2011.02.053
55	L Zhou, M Duan, Y Yu. Exergy and economic analyses of indirect coal-to-liquid technology coupling carbon capture and storage. Journal of Cleaner Production, 2018, 174: 87–95 https://doi.org/10.1016/j.jclepro.2017.10.229
56	S Budinis, S Krevor, N M Dowell. et al.. An assessment of CCS costs, barriers and potential. Energy Strategy Reviews, 2018, 22: 61–81 https://doi.org/10.1016/j.esr.2018.08.003

[1]	Qiao MA, Shan WANG, Yan FU, Wenlong ZHOU, Mingwei SHI, Xueting PENG, Haodong LV, Weichen ZHAO, Xian ZHANG. China’s policy framework for carbon capture, utilization and storage: Review, analysis, and outlook[J]. Front. Energy, 2023, 17(3): 400-411.
[2]	Haoming MA, Zhe SUN, Zhenqian XUE, Chi ZHANG, Zhangxin CHEN. A systemic review of hydrogen supply chain in energy transition[J]. Front. Energy, 2023, 17(1): 102-122.
[3]	Naushita SHARMA, Udayan SINGH, Siba Sankar MAHAPATRA. Prediction of cost and emission from Indian coal-fired power plants with CO₂ capture and storage using artificial intelligence techniques[J]. Front. Energy, 2019, 13(1): 149-162.
[4]	Lu SUN, Zhaoling LI, Minoru FUJII, Yasuaki HIJIOKA, Tsuyoshi FUJITA. Carbon footprint assessment for the waste management sector: A comparative analysis of China and Japan[J]. Front. Energy, 2018, 12(3): 400-410.

Viewed

Full text

Abstract

Cited

Shared

Discussed