Methanol is becoming more exciting than hydrogen as a clean fuel to help decarbonize transport. Specifically, blue methanol and bio-methanol are 65-75% less CO2-intensive than oil products, while they can already earn 10% IRRs at c$3/gallon-equivalent prices. Unlike hydrogen, it is simple to transport and integrate methanol with pre-existing vehicles. Hence this 21-page note outlines the opportunity.
The objectives and challenges of hydrogen are summarized on pages 2-3. We show that clean methanol can satisfy the objectives without incurring the challenges.
An overview of the methanol market is given on pages 4-5, to frame the opportunity, particularly in transportation fuels and cleaner chemicals.
Conventional methanol production is described on 6-8. We focus upon the chemistry, the costs, the economics and the CO2 intensity.
Bio-methanol is modelled on pages 9-10. We also focus upon the costs, economics and CO2 intensity, including an opportunity for carbon-negative fuels.
Blue methanol is outlined on pages 11-15. Converting CO2 and hydrogen into methanol is fully commercial, based on recent case studies, which we also use to model the economics and CO2 credentials.
Green methanol is more expensive for little incremental CO2 reduction, and indeed some routes to green methanol production are actually higher-CO2 (pages 16-18).
Companies in the methanol value chain are profiled on pages 19-20. We focus upon leading incumbents, technology providers and private companies commercializing clean methanol.
Our conclusion is that methanol could excite decision-makers in 2021, the way that hydrogen excited in 2020. This thesis is spelled out on page 21.
Fuel retailers have a game-changing opportunity seeding new forests, ourlined in our 26-page note. They could offset c15bn tons of CO2 per annum, enough to accommodate 85Mbpd of oil and 400TCF of annual gas use in a fully decarbonized energy system. The cost is competitive, well below c$50/ton. It is natural to sell carbon credits alongside fuels and earn a margin on both. Hence, we calculate 15-25% uplifts in the value of fuel retail stations, allaying fears over CO2, and benefitting as road fuel demand surges after COVID.
The advatages of forestry projects are articulated on pages 2-7, explaining why fuel-retailers may be best placed to commercialise genuine carbon credits.
Current costs of carbon credits are assessed on pages 8-10, adjusting for the drawback that some of these carbon credits are not “real” CO2-offsets.
The economics of future forest projects to capture CO2 are laid out on 11-14, including opportunities to deflate costs using new business models and digital technologies. We find c10% unlevered IRRs well below $50/ton CO2 costs.
What model should fuel-retailers use, to collect CO2 credits at the point of fuel-sale? We lay out three options on pages 15-18. Two uplift NPVs 15-25%. One could double or treble valuations, but requires more risk, and trust.
The ultimate scalability of forest projects is assessed on pages 19-25, calculating the total acreage, total CO2 absorption and total fossil fuels that can thus be preserved in the mix. Next-generation bioscience technologies provide upside.
A summary of different companies forest/retail initiatives so far is outlined on page 26.
E-scooters can transform urban mobility, eliminating 2Mbpd of oil demand by 2030, competing amidst the ascent of “electric vehicles” and re-shaping urban economies. These implications follow from e-scooters having 25-50x higher energy efficiencies, higher convenience and c50% lower costs than gasoline vehicles, over short 1-2 mile journeys. Our 12-page note explores the consequences.
Page 2 charts the meteoric ascent of e-scooters. In their first year of deployment, they matched the peak growth rate of taxi-apps (e.g., Uber) and overtook ride-sharing bicycles which have been under commercialisation for quarter-of-a-century.
Page 3 assesses the leading companies, all of which launched in late-2017 or early-2018, and have since raised $1.5bn.
Pages 4-5 compares the energy-economics of electric scooters with fourteen other vehicle concepts, explaining the physics of e-scooters’ 25-50x higher efficiencies.
Page 6 compares the relative benefits of e-scooters versus electric cars, which are clearest when comparing the relative strain on grid infrastructure.
Pages 7-8 show how e-scooters displace oil demand, outlining our projections for 2Mbpd of demand destruction globally by 2030. This oil demand is not “replaced” by electricity demand. c95-98% of it is simply eliminated.
Pages 9-11 model the per-mile costs of e-scooters, as a function of multiple input variables, showing the most competitive contexts relative to cars and taxis.
Page 12 ends by exploring potential consequences for urban economies. Most of all, we expect economic growth to be supported, particularly for retail; conversely e-mobility may embolden policymakers to ban gasoline vehicles from cities.