What are the top technologies to transform the global energy industry and the world? This data-file summarises where we have conducted differentiated analysis, across c80 technologies (and counting).
For each technology, we summarise the opportunity in two-lines. Then we score its economic impact, its technical maturity (TRL), and the depth of our work to-date. The output is a ranking of the top technologies, by category; and a “cost curve” for the total costs to decarbonise global energy.
Download this data-fileand you will also receive updates for a year, as we add more technologies; and we will also be happy to dig into any technologies you would like to see added to the list.
This data-file aggregates the labor intensityof different energy sources: wind, solar, oil, gas, coal and nuclear, based on data from the United States and from underlying projects.
Direct labor intensity tends to vary between 75-150 workers per TWH of useful energy. The gas industry is among the most efficient power sectors, providing 100 jobs per TWH of useful energy. Oil-fired transportation is less efficient at 135 workers per TWH, rising to 730 per TWH if you include service station staff.
Renewables have a jagged profile. A typical wind and solar project creates 250-500 jobs per TWH during the construction phase, but only just 20-30 during the operational phase. So in the short-run, jobs may be creatd by expanding renewables but in the long-run, they may be destroyed.
We have modeled the global climate system from 1750-2065, to simplify the climate-science of the energy transition into an easily understandable format.
‘Net zero’ is achievable by 2050, with atmospheric CO2 remaining below 450ppm, the level consistent with 2-degrees C of warming.
Fossil fuel use is 10% higherthan today, but the industry has transformed itself, towards the most efficient, lowest-carbon fossil fuels (especially natural gas), with the remaining CO2 captured or offset. This is the most economical route to an energy transition, per all of our research.
Please download the modelto stress-test your own input assumptions. Notes from Academic papers follow in the ‘Sources’ tab, drawn largely from the IPCC, to explain the ocean, soil and plant fluxes in our model.
This data-file quantifies and disaggregate the CO2 emissions from a typical coal mining operation, across mining processes, coal-processing, methane emissions and freight/transportation.
We estimate that producing a ton of coal emits 0.19T of CO2, equivalent to 50kg/boe. The data are based on USGS technical papers, EPA disclosures from US coal mines and EIA disclosures on mine sizes and coal heat contents.
The conclusion is that domestic coal productionwill tend to emit 2x more CO2 than domestic natural gas production, in addition to coal combustion emitting around 2x more CO2 than gas combustion.
However, numbers vary widely based on input assumptions, such as methane lakage rates, btu content and transportation distances, which can be flexed in the model.
Molten Carbonate Fuel Cellscould be extremely promising, generating electrical power from natural gas as an input, while also capturing CO2 from industrial flue gases through an electrochemical process.
We model competitive economics can be achieved, under our base case assumptions, making it possible to retrofit units next to carbon-intensive industrial facilities, while also helping to power them.
Our full modelruns off 18 input variables, which you can flex, to stress test your own assumptions.
This data-file models the economics of constructing a new coal-to-power project, based on past projects around the industry.
A dozen input variables can be flexed in the model, to stress test economic sensitivity to: coal prices, power prices, carbon price, gas distribution costs, conversion efficiency, capex costs, opex costs, utilization and tax rates.
Indicative inputs, and sensible ranges, are suggested for each of these input variables in the data-file.
Greenfield coal projects in the developed world are no longer economic, as meeting stringent air standards inflates capex costs around 3x, while juxtaposition with renewables dents utilization.
This model estimates European gas demand in the 2020s, as a function of a dozen input assumptions, which you can flex. They include: renewables’ growth, the rise of electric vehicles, the phase out of coal and nuclear, industrial activity, efficiency gains and LNG-transport fuel.
Our conclusionis that European gas demand will likely grow at its fastest pace since the early-2000s, largely driven by the electricity sector.
The data-file also contains granular data, decomposing gas demand across 8 major categories, plus 13 industrial segments, going back to 1990 (albeit some of the latest data-points are lagged).
Please download the modelto run your own scenarios…
This data-file provides an overview of eleven different processes for commercial hydrogen production: including their energy-economics, costs and CO2 emissions; plus a qualitative description of their opportunities, challenges and technical readiness.
Covered technologiesinclude steam methane reforming, fossil fuel gasification, pyrolysis, renewable electrolysis, fuel cell electrolysis, solar photoelectrocatalysis and solar photocatalysis.
Our conclusionis that natural gas remains the most viable fuel source on a weighted basis, considering both cost and carbon emissions, It may also be easier to de-carbonise natural gas directly than via the hydrogen route.
This data-file breaks down global CO2 emissionsinto 35 distinct categories, based on prior publications, our own models and calculations.
The long tail illustrates the complexity of decarbonisation. The largest single component of global emissions is passenger vehicles, but this comprises just c14% of the total CO2e.
A further 30 line-itemsall account for at least 1% of the world’s total emissions including electricity, heating, cement, metals, plastics, food, fertilizers, paper, manufacturing, livestock, agriculture, military, oil refining, fossil fuel production and landfill.
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