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 rise of heat pumps, the phase out of coal and nuclear, industrial activity, efficiency gains, LNG-transport fuel and hydrogen.
Our conclusionis that European gas demand would be likely grow at its fastest pace since the early-2000s, largely driven by the electricity sector, if there were sufficient supplies. However, as indigenous production wanes, there is a risk of persistent gas shortages, and prices will need to rise to the point of demand destruction.
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); as well as 15 different supply sources, with monthly data going back a decade (chart below).
Please download the modelto run your own scenarios…
This data-file aims to approximate the economics of a new coal mine, using simple rules of thumb and data from past projects, capex (in $/Tpa) and opex (in $/ton).
Coal is ridiculously cheap, providing thermal energy at around 1c/kWh while also generating a 10% IRR on the new investment. 1 MWH pa of new energy can be produced for an up-front investment of around $10.
A high CO2 intensity of 0.55kg/kWh is also quantified in the data-file, including combustion emissions, methane leaks, diesel fuel and electricity usage at the mine.
Please download the data-file to stress test the economics and sensitivity to coal prices in $/ton.
This data-file aims to bound the potential market-size for CCS in the US, which is most likely around 500MTpa.
Our bottom up calculations look industry-by-industry, and conclude that c20% of industrial and power-sector emissions could be captured, across coal-power, gas-power, ethanol, steel, cement, chemicals and smaller manufacturing.
To put this in perspective, we also quantified how many million tons of oil and gas have been extracted out of subsurface reservoirs in the US over the past 40-years, across different resource types.
This data-file has aggregated the annual CO2 emissions from 2,500 facilities, in eight industries, which explain one-third of all US CO2 emissions. Our aim is to quantify the emissions by facility, to understand whether CCS can ‘take the edge off’?
Our conclusions are that many coal plants may be ‘too large’ to decarbonize with CCS, whereas many ethanol plants are likely too small. The best candidates are c100 specific facilities in the cement, steel and ammonia industries, which are the “right size”, have concentrated CO2 emissions and explain around 2% of all US CO2 emissions.
Our models of the energy transition ease coal production back from 8GTpa in 2019 to 5GTpa by 2030, in the interests of decarbonization. However, this model explores what is required to meet this ambition.
Around 1GTpa of new coal projects are in planning or under construction, of which half are in China. Thus to hit our numbers, an additional 70bcfd of gas must be supplied to China by 2030, in order that it can actually turn off 1.5GTpa of coal capacity.
In the meantime, we are concerned about coal shortages, because one-third of all global coal production comes from underground mines, i.e., confined and hard-to-ventilate spaces containing 300-1,500 workers per MTpa of output, which may be disrupted by COVID.
Please download the data-file to stress-test our assumptions around mine adds, decline rates, phase-downs and coal-to-gas switching.
What are the top technologies to transform the global energy industry and the world? This data-file summarizes where we have conducted differentiated analysis, across c100 technologies (and counting).
For each technology, we summarize 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 decarbonize global energy.
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, of which 1.2C has already occurred.
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.
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