A Sustainable Asset Valuation of the Mass Rapid Transit System in Bogota, Colombia
Summary
The report evaluates the Bogota MRT system using the SAVi methodology, which integrates externalities like health, carbon emissions, and retail growth into a cost-benefit analysis. The analysis considers two demand scenarios (8% and 16% modal shift from private transport) over a 35-year period (2022–2058). While conventional benefit-cost ratios (BCR) are low (0.4 to 0.6), the sustainable BCR (S-BCR) ranges from 1.5 to 2.9, indicating the project is highly profitable from a societal perspective. Key benefits include significant retail revenue increases, health improvements from walking and reduced pollution, and a reduction in CO2 emissions by up to 10.79 million tonnes in the high-demand scenario.
Key insights
- The MRT system is economically viable from a societal perspective, with a sustainable benefit-cost ratio (S-BCR) ranging from 1.5 to 2.2 for the 8% MRT scenario and 1.9 to 2.9 for the 16% MRT scenario, significantly higher than the conventional BCR of 0.4 to 0.6.
- The highest discounted cumulative added benefit is attributed to retail revenues, valued at COP 7,904 billion in the 8% MRT scenario and COP 15,897 billion in the 16% MRT scenario.
- The MRT system is projected to reduce greenhouse gas emissions, with avoided CO2 emissions valued at COP 316 billion (5.85 million tonnes) in the 8% scenario and COP 583 billion (10.79 million tonnes) in the 16% scenario.
- Health benefits, comprising increased physical activity and reduced air pollution, are valued between COP 3,829 billion and COP 5,306 billion for the 8% scenario, and between COP 7,711 billion and COP 10,852 billion for the 16% scenario.
- The economic value of time saved due to improved mobility ranges from COP 1,029 billion to COP 10,287 billion in the 8% scenario and COP 1,992 billion to COP 19,920 billion in the 16% scenario.
- Avoided costs from a reduction in traffic accidents are estimated at COP 1,606 billion to COP 2,513 billion for the 8% scenario and COP 3,157 billion to COP 4,941 billion for the 16% scenario.
- The project is expected to create significant employment, with 8,000 direct and 20,000 indirect jobs during construction (2021–2028), resulting in a cumulative discounted income creation of COP 1,044 billion.
- Property value increases near MRT stations are estimated as a one-time benefit, ranging from COP 957 billion (low estimate) to COP 1,915 billion (high estimate) across both demand scenarios.
Cite the original document
- APA
- Kapetanakis, M., Niño, N., Casier, L., & Bassi, A. M. (2024). A Sustainable Asset Valuation of the Mass Rapid Transit System in Bogota, Colombia. International Institute for Sustainable Development. https://www.iisd.org/system/files/2024-10/savi-mass-rapid-transit-system-bogota-colombia.pdf
- Chicago
- Kapetanakis, Michail, Nathalia Niño, Liesbeth Casier, and Andrea M. Bassi. A Sustainable Asset Valuation of the Mass Rapid Transit System in Bogota, Colombia. International Institute for Sustainable Development, 2024. https://www.iisd.org/system/files/2024-10/savi-mass-rapid-transit-system-bogota-colombia.pdf.
- Wikipedia
- {{cite report |last1=Kapetanakis |first1=Michail |last2=Niño |first2=Nathalia |last3=Casier |first3=Liesbeth |last4=Bassi |first4=Andrea M. |title=A Sustainable Asset Valuation of the Mass Rapid Transit System in Bogota, Colombia |publisher=International Institute for Sustainable Development |date=March 2024 |url=https://www.iisd.org/system/files/2024-10/savi-mass-rapid-transit-system-bogota-colombia.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}
- BibTeX
- @techreport{kapetanakis2024sustainable, author = {Kapetanakis, Michail and Niño, Nathalia and Casier, Liesbeth and Bassi, Andrea M.}, title = {{A Sustainable Asset Valuation of the Mass Rapid Transit System in Bogota, Colombia}}, institution = {International Institute for Sustainable Development}, year = {2024}, month = mar, url = {https://www.iisd.org/system/files/2024-10/savi-mass-rapid-transit-system-bogota-colombia.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }
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