Managed reforestation: growth rates by tree species over time?

We have tabulated data into the growth rates of over 2,500 trees, in over a dozen locations globally, based on tree ring measurements, reported by the National Center for Environmental Information.

The objective is to assess whether growth rates are faster at younger or older trees, given that biomass accumulation is correlated with tree widths. We find that tree widths continue rising steadily over 100-500 years, with radiuses growing at an average pace around 2mm per year.

However, growth rates are fastest in early years. As a rule of thumb, they will slow down by 25% after 20-years, 40% after 40-years and 50% after 60-years. This may be an argument for forest management and sustainable harvesting as more reforestation projects are undertaken to combat climate change (note here).

Relatively faster growing species tend to remain relatively faster growing even after longer time-frames. This may be an argument for rigorous species selection, as discussed further in our data-file here.

Economic costs of climate change?

This data-file contains our estimates into the economic costs of unmitigated climate change, using the latest disclosures from the IPCC as a framework. We estimate the total costs could reach $1.5trn per annum.

Our numbers include losses of labor productivity in hot countries, increased air conditioning demand (offset by lower heating demand), granular data into the cost of natural disasters, which could become increasingly prevalent (chart below), losses in the tourism industry, water scarcity, healthcare costs, et al.

Numbers in the data-file are discussed in more detail in our recent research report, into the paradoxical costs of climate change.

Combustion fuels: energy economics and carbon content?

The purpose of this data-file is to disaggregate the energy economics of combusting different fuels, including natural gas, different oil products, NGLs, coal, hydrogen, methanol, ammonia et al.

In each case, we derive the enthalpies of combustion, the contributing share of carbon and hydrogen oxidation, and thus the CO2 emissions per unit of energy. We also derive the fuels’ energy density, expressed in kWh/kg, kWh/mcf and kWh/gallon.

There is recent enthusiasm to lower combustion emissions by blending hydrogen into gas grids. But materially greater decarbonization occurs by replacing coal/biomass with gas, or even replacing oil products with NGLs.

Global manufacturing: value added by country and region over time?

This data-file estimates the GDP generated by manufacturing across 200 countries, each year from 1960-2019.

The data are derived from international organizations, government statistics and technical papers, and then extensively cleaned.

Our conclusion is that policies have long-term consequences. The largest decline is in former Soviet countries, which have lost c15pp of market share from peak. Conversely, China has risen from 1% to 30% of global manufacturing over the same period.

The US and Europe have declined from c65% of global manufacturing in 1960 to c35%, as absolute value add from manufacturing has effectively stagnated since 2000. The data may be worth considering, as energy policies intensify.

Market sizing: commodities and themes in the energy transition?

This data-file calculates the likely market sizes of different themes and commodities that have featured in our research towards a decarbonized global energy system in 2050.

Included are conventional energy, renewables, demand-side technologies, capital goods,  hydrogen and nature-based carbon offsets. The total data file contains over 30 commodities and themes.

Estimates are made for each market in 2021 and 2050; plus notes on our underlying assumptions, links to our research, and a tool to interpolate market sizes between different years.


Hydrogen blending: costs and complexities?

This data-file estimate the costs of blending hydrogen into pre-existing natural gas pipeline networks. Costs are relatively low per mcf of gas, but very high per ton of CO2 abated. Costs also rise exponentially, as more hydrogen is blended into the mix.

Our estimates are based upon technical papers and TSE’s economic models, and they cover capacity degradation, maintenance costs and upgrading boilers, appliances and turbines.

Nickel, manganese, cobalt: sufficient reserves for the rise of EVs?

This data-file models whether there will be enough nickel, manganese and cobalt, to build the batteries behind the vast rise of electric vehicles embedded in our oil demand forecasts.

Our conclusion is that the outlooks for nickel and manganese are unconcerning, due to strong recent reserve replacement ratios. But the need to ramp up, reduce and recycle cobalt will be a challenge.

You can stress-test the input assumptions in the model, varying the ultimate sales of electric vehicles, other demand growth, recycling rates and reserve replacement ratios.

Room for reforestation: a database of global land use?

The purpose of this data-file is to provide helpful data on how land is used globally, and thus to quantify how much land is available for nature based solutions such as reforestation.

The work includes a breakdown of land use, across 40 different categories, estimates of carbon stocks across these different land types, and more granular detail into agricultural lands, grasslands, degraded lands and reforestable lands.

Estimates are mostly derived from technical papers. Notes from select technical papers are also included in the data-file.

UK grid volatility as renewable gain share?

This data-file contains the output from some enormous data-pulls, evaluating UK grid power generation by source, its volatility, and the relationship to hourly traded power prices. We conclude the grid is growing more expensive and volatile, particularly for ‘downside volatility’.

Different tabs in the data-file cover the total monthly demand of the UK power grid since 2016, broken down by generation source, month-by-month and smoothed over trailing twelve-month timeframes; statistical analysis of hourly power prices, by day and by quarter; and an hourly cross-correlation of wind generation with power prices (chart below).

The data-file is also regularly updated and we are happy to run bespoke analysis on the underlying data-sets for TSE clients.

Investment bubbles and manias?

This data-file tabulates key details of prior investment bubbles, such as their timing, price performance, causes of the boom and causes of the bust. We pick out five factors common to all prior bubbles.

Covered bubbles include the Dutch Tulip mania, British South Sea bubble, French Mississippi bubble, British Railway mania, Roaring Twenties boom, Dot Com and the lead-up to the 2008 Financial Crisis. Each is described in detail.

It is interesting to compare the characteristics of these past bubbles to New Energies today. We argue several transition technologies are at risk of becoming bubbles.