This data-file compiles all of our insights into publicly listed companies and their edge in the energy transition: commercialising economic technologies that advance the world towards ‘net zero’ CO2 by 2050.
Each insight is a differentiated conclusion, derived from a specific piece of research, data-analysis or modelling on the TSE web portal; summarized alongside links to our work. Next, the data-file ranks each insight according to its economic implications, technical readiness, its ability to accelerate the energy transition and the edge it confers on the company in question.
Each company can then be assessed by adding up the number of differentiated insights that feature in our work, and the average ‘score’ of each insight. The file is intended as a summary of our differentiated views on each company.
The screen is updated monthly. At the latest update, in October-2020, it contains 180 differentiated views on 90 public companies.
This model captures the economics and CO2 intensity of methanol production in different chemical pathways.
Different tabs of the modelcover grey methanol production from gas reforming, blue methanol from blue hydrogen and industrially captured CO2, green methanol from green hydrogen and direct air capture CO2, and finally bio-methanol.
Inputs are takenfrom a wide survey of technical papers, cost breakdowns and energy intensity data. These are also broken down in the data-file.
Based on the analysis, we see interesting potential for bio-methanol and blue methanol as liquid fuels with lower carbon intensity than conventional oil products. You can stress-test input assumptions in the underlying model tabs.
Which refiners are least CO2 intensive, and which refiners are most CO2 intensive? This spreadsheet answers the question, by aggregating data from 130 US refineries, based on EPA regulatory disclosures.
The full databasecontains a granular breakdown, facility-by-facility, showing each refinery, its owner, its capacity, throughput, utilisation rate and CO2 emissions across six categories: combustion, refining, hydrogen, CoGen, methane emissions and NOx (chart below).
This data-file tabulates the details of companiesin the methanol value chain. For incumbents, we have quantified market shares. For technology providers, we have simply tabulated the numbers of patents filed into methanol production since the year 2000. For new, lower-carbon methanol producers, we have compiled a screen, noting each company’s size, patent library and a short description (chart above).
Almost 1% of global CO2 comes from distillation to separate crude oil fractions at refineries. An alternative is to separate these fractions using precisely engineered polymer membranes, eliminating 50-80% of the costs and 97% of the CO2. We reviewed 1,000 patents, including a major breakthrough in 2020, which takes the technology to TRL5. Refinery membranes also comprise the bottom of the hydrogen cost curve. This 14-page note presents the opportunity and leading companies.
This data-file reviews over 1,000 patents to identify the technology leaders aiming to use membranes instead of other separation processes (e.g., distillation) within refineries.
Covered companies in the screen include Air Liquide, Air Products, Aramco, BASF, BP, Chevron, Dow, ExxonMobil, GE, Honeywell, IFP, MTR, Praxair, Shell, WR Grace and Zeon. A brief overview is prented for each company, along with a summary of their recent patent filings, and all the underlying details.
Operational data are also presented for two interesting cases: Exxon’s recent refinery membrane breakthrough (chart below) and Air Products’s PRISM membranes for hydrogen separation.
This model captures the energy economics of a pipeline carrying oil or water. Specifically, we have modelled energy requirements using simple fluid mechanics, and modelled costs using past projects and technical papers, which are tabulated in the data-file.
Our conclusionsshow the requisite costs, energy and CO2 intensities of different pipelines (below).
You can stress test the economicsdirectly in the model, by varying pipeline tariffs, capex costs, energy costs, CO2 prices, maintenance costs, pipeline diameter, pipeline distance, pipeline elevation, pipeline materials, fluid viscosity and compressor efficiencies.
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 c90 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.
Industrial heat comprises around 20% of global CO2 emissions, but around half of all the heat generated may ultimately be wasted.
Hence, this model simplifies the economics of using a heat exchanger to recover waste heat from an industrial facility, based on the engineering equations of heat exchange and recent technical papers.
Our base case IRR is 6%, in the US, due to low, $3/mcf gas prices. This is uplifted to above 20%, either if we assume European gas prices (around $6/mcf) or a $50/ton CO2 price. IRRs can reach 40% if we assume both.
High IRRs may be necessary to unlock waste heat recovery. First, each project is complex, with large amounts of engineering, and implementation disrupts operations at a plant. Second, although IRRs are high, NPVs are low, as many projects will be small-scale. For example, the NPV10 may be less than $1M on a single, small heat exchanger project, even if it achieves a 40% IRR.
This data-file models the economics of a new renewable diesel plant, converting waste oils into green diesel. It is based on technical papers and cost estimates from past projects.
A strong, c25% IRR isattainableif renewable diesel maintains a $1.0/gallon pricing premium to conventional diesel, as has been historically supported by the blenders tax credit.
The IRR is obliterated and falls to zero if this premium is lost, for example, due to emerging competition from carbon offsets. Please download the model to flex our input assumptions and stress test the economics.
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