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Appendix I: activity-based models

TICCS subclass

Sector name

Model for each emission scope

Emission Factor (EF)


Note [Ref]

Scope 1

Scope 2

Scope 3

Model 1: Power Production (IC10 and IC70)


Power Generation x-Renewables

ABMs using fuel type and electricity generation or power capacity



Varies by type of fuel

Varies by type of fuel and country

EFs for various resources [1], EF for heat and power [3], 2021 CFs for the US [2; 4], 2021 heat and power load factors in the UK [18]


Renewable Power

Negligible except for Biomass (IC704010)



(Close to) zero

Varies by type of technology

EFs for various resources [1],  2021 CFs for the US [2; 4], EU reporting guidelines [5]

Model 2: Water and Water Treatment (IC20) 


Waste Treatment

ABM using waste mass

NA or negligible

NA or negligible

Based on reported example


EF for waste management in China [6]


Water Supply and Treatment

ABM using water mass or negligible

ABM using water mass

ABM using water volume or negligible

Based on volume or mass of (waste)water


EF for wastewater treatment in China [7], S3: [8], carbon footprint of water reuse [9]


Wastewater Treatment

Model 3: Social Infrastructure (IC30)


Social Infrastructure

ABMs using area size, location, and electricity consumption


Depends on countries and years

Depends on scopes, TICCS subclasses, + countries

Energy/ electricity use of commercial [10], residential [11, 13], and domestic [12] buildings, buildings in Malaysia [14] and Chile [15]

Model 4: Pipelines (IC4010)


Natural Resources Transportation

ABM using pipeline length or NA


ABMs using capacity or volume or NA

Depends on the scope and the nature of input data


S3: [8], pipeline GHG assessment [16]

Model 5: LNG and Oil (IC4020)


Energy Resource Processing

ABMs using throughput mass


ABMs using throughput volume

Depends on the TICCS subclass and scopes


S3: [8], emission intensity of LNG plant [17]

Model 6: Storage (IC4030) 


Gas Storage

ABM using storage volume


ABM using storage volume

Depends on scopes


S3: [8], emission intensity of LNG plant [17]

Model 8: Airports



Regression-based model

ABM using air traffic data

Emissions per amount of fuel burnt

Depends on type of aircraft, based on fuel table

Carbon footprints of airports [19]

Note: While we provide predictions or reported emissions for all listed asset subclasses, we do not have predictions for all assets due to missing data points. If the model is listed as “negligible,” the respective CO2 emissions are close to zero; if models are listed as “NA,” we did not build a model. References indicate some of the literature reviewed during the research, model design, and validation of predictions.

[1] Our World in Data (2017). CO2 emissions factors.

[2] US Energy Information Administration (2021). U.S. capacity factor by energy source – 2021. Office of Nuclear Energy.

[3] Oria, J., Madariaga, E., Ortega, A., Diaz, E., & Mateo, M. (2015). Influence of characteristics of marine auxiliary power system in the energy efficiency design index. Journal of Maritime Transport and Engineering, 4, 67-76.

[4] Statista (2023). Capacity factors for selected energy sources in the United States in 2021. Statista.

[5] Neves, A., Blondel, L., Brand, K., Hendel Blackford, S., Rivas Calvete, S., Iancu, A., … Kona, A. (2016). The covenant of mayors for climate and energy reporting guidelines. Luxembourg: Publications Office of the European Union.

[6] Guo, J., Ma, F., Qu, Y., Li, A., & Wang, L. (2012). Systematical strategies for wastewater treatment and the generated wastes and greenhouse gases in China. Frontiers of Environmental Science & Engineering, 6, 271-279.

[7] Hua, H., Jiang, S., Yuan, Z., Liu, X., Zhang, Y., & Cai, Z. (2022). Advancing greenhouse gas emission factors for municipal wastewater treatment plants in China. Environmental Pollution, 295.

[8] World Resources Institute & World Business Council for Sustainable Development (2013). Technical guidance for calculating Scope 3 emissions (version 1.0). Greenhouse Gas Protocol.

[9] Cornejo, P.K., Santana, M.V., Hokanson, D.R., Mihelcic, J.R., & Zhang, Q. (2014). Carbon footprint of water reuse and desalination: A review of greenhouse gas emissions and estimation tools. Journal of Water Reuse and Desalination, 4, 238-252.

[10] Hinge, A., Bertoldi, P., & Waide, P. (2004). Comparing commercial building energy use around the world. Proceedings of the 2004 ACEEE Summer Study on Energy Efficiency in Buildings, 4, 136-147.

[11] Skarbek, A. & Malos, A. (2018, September 6). Tracking progress to net zero emissions. Climateworks Centre.

[12] Department for Business, Energy & Industrial Strategy (2019). Energy consumption in new domestic buildings 2015 to 2017 (England and Wales). UK Government.

[13] Gaglia, A.G., Dialynas, E.N., Argiriou, A.A., Kostopoulou, E., Tsiamitros, D., Stimoniaris, D., & Laskos, K.M. (2019). Energy performance of European residential buildings: Energy use, technical and environmental characteristics of the Greek residential sector – energy conservation and CO₂ reduction. Energy and Buildings, 183, 86-104.

[14] Mohsenzadeh. M., Marzbali, M.H., Tilaki , M.J. & Abdullah, A. (2021). Building form and energy efficiency in tropical climates: A case study of Penang, Malaysia. urbe. Revista Brasileira de Gestão Urbana, 13, 1-19.

[15] Martinez-Soto, A., Saldias-Lagos, Y., Marincioni, V., & Nix, E. (2020). Affordable, energy-efficient housing design for Chile: Achieving passivhaus standard with the Chilean state housing subsidy. Applied Sciences, 10, 1-25.

[16] Worley Parsons Resources & Energy (2013, April 29). Katherine to Gove gas pipeline. Appendix H. Pipeline greenhouse gas assessment.

[17] Antweiler, W. (2014, November 11). Liquefied natural gas: technology choices and emissions. Werner’s Blog – Opinion, Analysis, Commentary.

[18] UK Department for Business, Energy and Industrial Strategy (2022). Load factor of combined heat and power (CHP) schemes in the United Kingdom (UK) from 2000 to 2021. Statista.

[19] Nugier, F., Marcelo, D., & Blanc-Brude, F. (2022). Carbon footprints and financial performance of transport infrastructures: The case of airports. Transition risk assessment using traffic and geospatial data. EDHECinfra Publication.

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