The purpose of this data-file is simply to chart the typical pressures of various industrial processes that have featured in our research, as a useful reference.
Pressures rangefrom around 1 atmosphere to around 4,000 atmospheres (at which point structural steel fails).
One conclusionis that conventional energy and chemical companies have good pre-existing experience with engineering and managing pressure-vessels, as may be needed in the energy transition, especially for CCS.
H2 vehicles may be more demanding, if these tanks require 10,000 psi, which is actually more than that of a standard hydraulic fracturing operation.
The purpose of this data-file is to summarize the main problems and solutions in power-electronics, and how they will evolve amidst the ramp-up of renewables and electrification.
We describe c15 problems that are incurred by power consumers, all of which will be amplified amidst the build-out of renewables, some more than others.
In turn, this means we expect c$100bn pa growth in the market for compensatory power-electronics solutions by 2030 (this number excludes grid-scale batteries). Different devices, examples, market sizes and costs are summarized in the equipment tab.
Back-up data follows from technical papers in the final tab.
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.
The purpose of this data-file is to aggregate and clean data into the energy and electricity consumption of 180,000 US industrial facilities, according to key sectors such as refineries, chemicals, steel, other metals, fertilizers, auto plants and other manufacturing categories.
The average factoryconsumes 9GWH of energy per year, of which 5GWH is thermal heat and 4GWH is as electricity. Of the electricity c50% is for rotating machinery, c10% for electric heat, c10% for process cooling, c7% for electrochemical processes, c10% for facility HVAC and c6% for facility lighting.
The average of these facilities requires a 700kW power connection, we estimate, but this is as high as 10MW at typical auto plants and 25MW at typical steel mills, with further order-of-magnitude upside at the largest facilities in each category.
This data-file aggregates granular data from seven solar assets around Western Europe (Netherlands, Germany, Belgium, Switzerland), to understand their volatility and inter-correlation, over a sample week in August-2021.
Across the entire week, the average solar plant generated at 12% of its nominal capacity, the 90th percentile was 40% and the maximum was 75%; which may suggest that the panels have been oversized relative to inverters or MPPT is not fully optimized.
Volatility and inter-correlations are quantified in the data-file, but are generally high. For example, over >500km distances, different solar generators’ 15-min by 15-min output is 60-80% correlated, which is even greater than for offshore wind (data here).
These issuessuggest solar can provide a meaningful portion of decarbonizing grids, but surpassing 20% requires back-ups.
This data-file compiles the estimated calorific and financial yields of tree crops versus conventional crops such as corn and soybean. There is strong economic potential to produce food while absorbing CO2 in trees, although calorific yields are 50-90% lower.
On average, conventional agricultural will yield high calorific yields of 5-15M kcal and moderate value of $1,000 per acre, after decades of agricultural improvements.
Heavily ‘farmed’ tree crops, such as almond and pistachio will have calorific yields in the low end of this range, but generate 5-10x more value per acre.
Less intensively farmed tree crops will produce 1-2M kcal per acre, but their value is nevertheless around 2x higher than conventional agriculture.
Species-by-species considerations are discussed in the data-file.
This data-file considers how to supply 100MWe and 1,000GWH pa of energy to a mid-sized consumer: reliably, at a low-cost and with zeronet CO2 emissions. We think this is possible at a delivered power price below 10c/kWh, which is highly competitive.
The model capturesthe costs, gross CO2 intensity and nature-based offset requirements from a mixture of wind, solar, CHPs and gas turbines.
Following this modelcould create great potential for an integrated gas and power company, while supplying a complete, zero-carbon energy solution to consumers in the energy transition.
Well-crafted afforestation and reforestation projects may be able to absorb atmospheric CO2 25% more rapidly than in the past, by aligning species and site selection with the world’s changing climate and plant bio-chemistry.
Less well optimized projects may be leaving money on the table, especially if the drawbacks of warming climates outweigh the benefits or CO2 fertilization. This note and data-file outlines the science and its implications, which we will be taking into account at our own reforestation project (link below).
The purpose of this note and data-file is to outline the biochemistry of CO2 fertilization, temperatures and photo-respiration, tabulate technical papers that have measured these issues, and compile other technical data for assessing this photosynthesis-related opportunity.
The purpose of this data-file is to estimate the ‘reforestation potential’ by country, across 170 countries globally, based on their climate, total area available, risk levels and economic costs.
These factors are cross-plotted on the chart above. Variables we tabulated and considered included land area, coast line, current forest cover, historical forest loss, rainfall, temperature ranges, population, population density, ease of doing business, corruption perceptions, income per capita and land costs.
A caveat: clearly these different variables are broad-brush, if they are meant to reflect entire countries in a single summary number, in some cases we have had to make best-estimates, and the variables also need to be weighted together, but we have taken a stab at a ranking.
Our conclusionis that many of the most attractive geographies to reforest will require navigating a somewhat challenging business climate. There are outlier countries in the developed world that also have excellent potential. Our note quantifying total realistic reforestation potential is here.
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