This data-file provides an overview of the 3.5Mbpd global biofuels industry, across its main components: corn ethanol, sugarcane ethanol, vegetable oils, palm oil, waste oils (renewable diesel), cellulosic biomass, algal biofuels, biogas and landfill gas.
For each biofuel technology, we describe the production process, advantages and drawbacks; plus we quantify the market size, typical costs, CO2 intensities and yields per acre.
While biofuels can be lower carbonthan fossil fuels, they are not zero-carbon, hence continued progress is needed to improve both their economics and their process-efficiencies.
Our long-term estimateis that the total biofuels market could reach 20Mboed (chart below), however this would require another 100M of land and oil prices would need to rise to $125/bbl to justify this switch.
The data-file also contains an overviewof sustainable aviation fuels, summarizing the opportunity set, then estimating the costs and CO2 intensities of different options.
This data-file quantifies the cost per mile of vehicle ownership for different categories of vehicles. Our methodology looks across the prices of 1,200 second hand vehicles, to correlate how the re-sale value of each make and model degrades per mile that has accumulated on its odometer (chart above).
Hybrids and basic passenger cars are most economical. Trucks and SUVs are 2x more costly. EVs are another 25% more costly again, and will have lost c60% of their value after 100,000 miles. Hydrogen cars have the highest costs and will have lost over 90% of their value after 100,000 miles (chart below).
Underlying data are shown in the input tabacross ten makes and models, to see how the re-sale value of each vehicle degrades with mileage. This may help you appraise what a particular second hand purchase “should” cost (example below) if you are among the many non-drivers considering a vehicle purchase as a result of the COVID crisis.
The impacts of COVID-19 on global oil demand are extremely uncertain. However, this model aims to help you bound the uncertainties, disaggregating 2020 oil demand in the developed and the developing world, as a function of some simplifying assumptions: GDP declines, flight cancellations, travel reductions and the pace of the crisis’s resolution.
Please note this model has been superceded by our more granular estimates, here. The model may still be useful to stress test influences on quarterly oil demand due to different COVID-related variables.
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 modestly slower-than-expected in 2019, rising just +1.0% YoY, which is above the prior 15-year trend for 0.4% pa growth, but below the 1.8% expected basesd on regressions to fuel prices and GDP.
One cause is urban vehicle miles driven, where growth has slowed, 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 quantifies the energy efficiency of fourteen different transportation types, in mpg, miles per kWh, passenger miles per kWh and CO2 intensity per passenger mile.
“Efficiency”is calculated using an apples-to-apples methodology, comparing real-world fuel consumption to equations of mechanics (i.e., stop-starts and air resistance, per Tab 3 in the model).
Electrification generally offers a c4x efficiency gain, jumping from c15-20% on conventional oil-powered vehicles to c60-80% on electric vehicles. Hybrids and hydrogen also yield modest efficiency improvements.
Most exciting is the set of emerging, electric transportation technologies, which are faster than incumbents, yet also achieve 4-120x efficiency gains per passenger mile (chart below).
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