We estimate costs and carbon intensities per usefor twenty low-utilisation household objects: the average is $13 per use and 1.3kg of CO2, respectively. Both are high numbers.
The biggest determinantis the number of uses per item. We fear that once purchased by a consumer, the average item on our list will be used just c20 times in its entire lifetime.
More extensive “sharing” will be enabled by drone delivery technologies, potentially saving $150bn of annual sales and 15MTpa of CO2 emissions across these 20 items items alone. Across the entire US economy the savings could reach $1trn and 100MT per year.
This data-file breaks down the financial and carbon costsassociated with a typical US consumer’s purchasing habits. It covers container-ships, trucks, rail freight, cars and last-mile delivery vans; based on the ton-miles associated with each vehicle and its fuel economy.
We estimate the distribution chain for the typical US consumer costs 1.5bbls of fuel, 600kg of CO2 and $1,000 per annum.
The costs will increase 20-40% in the next decade, as the share of online retail doubles to c20%. New technologies are needed in last-mile delivery.
Please download the modelto for a full breakdown of the data, and its sensitivity to oil prices, consumption patterns, international trade and exciting new delivery technologies.
This data-file quantifies the fuel economies of typical military vehicle-types, as $1.7 trn per annum of global military activity consumes c0.7Mbpd of total oil demand on our estimates, which are also included in the data-file.
Military drones are transformational. Almost all the incumbent military vehicles in our data-file have fuel economies below 1 mpg. But the Reaper and Predator drones, famous for their deployment in recent conflicts, have achieved 3mpg and 8mpg respectively. But small, next-generation electric drones will achieve well above 1,000 mpg-equivalent.
Swarms of small-scale electric dronescould emerge as the most devastating military weapon of the 21st century, according to a book we read last year on the topic, arguing that “A swarm of armed drones is like a flying minefield…they are so numerous that they are impossible to defeat… each one presents a target just 4-inches across… and shooting down a $1,000 drone with a $5,000 missile is not a winning strategy”. Our notes on the book are included in the data-file.
This data-file tabulates c10 examples for the fuel economy of container vessels, which is a function of their size and speed.
The most efficient container shipsare 2x more efficient than typical trains and 20x more efficient than typical trucks.
We calculate that moving goods from overseas to the developed world’s c1bn consumers accounts for c0.5% of global CO2 emissions (c50% in ships, c50% in trucks). These calculations are also shown in the data-file.
This data-file tabulates over 20 next-generation subsea robots, being pioneered around the industry. Each one is described and categorized, including by technical readiness.
These electric solutions could be very materialfor offshore economics, improving oilfield decline rates and maintenance costs. Innovations include:
Residing subseafor c1-year at a time, by re-charging in subsea “docking” stations. This provides greater availability for lower cost.
Increasing autonomymeans these robots can be free-swimming, as a communications tether is no longer necessary, improving ranges.
More intervention work will be conducted, rather than just inspections.
8 of the conceptsin our database have all three of these capabilities above. They are at TRLs 5-6, and should be commercially ready in the early 2020s.
The leading companiesare tabulated in the data-file, by Major and Service firm (chart below).
These solutions can save c$0.5-1/boe for a typical offshore oilfield, we estimate: performing inspection tasks 2-6x faster than incumbents, as well as halving costs and eliminating the weather-dependency associated with launching-recovering traditional ROVs. For full details, please download the data-file.
This data-file breaks down US gasoline demand, as a function of vehicle miles traveled (urban and rural), GDP growth, gasoline prices and fuel economy across the US vehicle fleet. It contains monthly data on each variable, going back to 2002, so correlations can be explored.
Gasoline demand is stalling in 2019, down -0.4% YoY versus a prior 15-year trend for 0.4% pa growth.
The cause is urban vehicle miles driven, where growth has slowed by 1.4pp, defying historical correlations with GDP (strong) and gasoline prices (reasonable). Structural explanations could include the rapid rise of alternative vehicles (e.g., e-scooters), ride-sharing and policy decisions.
Please download the fileto view the data or test your own regressions.
This data-file compares diesel trains, electric trains and hydrogen trains, according to their energy consumption, carbon emissions and fuel costs. The data are presented apples-to-apples, per passenger mile, based on worked examples. Seven train routes are compared on 20 metrics overall.
Travelling by train should be 2-15x more fuel-efficient, and 3-20x less carbon intensive than travelling by car.
Electric trainsare most efficient and cost-effective. The drawback is that electrifying tracks can cost c$1.4M/km. Nevertheless, we are most positive on the electrification opportunity around railways, particularly using next-generation combustion technologies.
The world’s first hydrogen trainslaunched in Germany in September-2018. To be cost-competitive with entry-level diesel trains requires c$12/kg hydrogen, $6/gallon diesel and a $50/ton carbon price.
Relative costs and economicscan be compared by varying inputs in the file.
Electric Cars are being overtaken by new electric vehicles, which achieve c3x greater decarbonisation per unit of battery material. This metric matters if one believes that battery materials are a limiting factor in the energy transition. To illustrate our case, our new Excel-file models two scenarios…
In the first scenario, 400kg of battery materials can be used to produce 1 electric vehicle, which displaces 1 gasoline taxi. The calculations show that 28 bbls of oil-equivalent energy and 12T of CO2 emissions are avoided each year.
In the second scenario, 400kg of battery materials can be used to produce 120 electric scooters, which displace 2.5 gasoline taxis. The calculations show that 96bbls of oil-equivalent energy and 37T of CO2 emissions are avoided. I.e., the scooters achieve 3x more decarbonisation than the electric car.
Moreover, our numbersabove only assume that one-in-three scooter trips displaces a car-trip, while the other two-in-three are deemed to be “new demand”. Per mile travelled, the scooters achieve 9x more decarbonisation than putting the same 400kg of battery materials into the electric car.
Please download the data-fileto interrogate our assumptions and stress-test your own scenarios. We argue the “electric revolution” goes beyond replacing today’s ground cars with electric ground cars. The opportunities are in new vehicle types.
E-scooters can re-shape 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.