The carbon credentials of wood are not black-and-white. They depend on context. This 13-page note draws out the numbers and five key conclusions. They count against deforestation, in favor of using waste wood, in favor of wood materials (with some debate around paper) and strongly in favor of natural gas.
This data-file calculates the CO2 intensity of wood in the energy transition. Context matters, and can sway the net climate impacts from -2 tons of emissions reductions per ton of wood through to +2 tons of incremental emissions per ton of wood.
Covered contexts include deforestation, sustainable forestry, commercial thinnings and gathering fallen biomass; which is cross-plotted against wood fuel displacing gas, wood fuel displacing coal, wood material displacing steel/cement, wood products displacing plastics and paper.
Calculations can be stress-tested in the data-file…
This data-file quantifies the global wood harvest, county-by-country, category-by-category, back to 1960, using granular data from the FAO. About 4,000 m3 of wood are harvested per year (2GTpa by mass).
The split is that 50% is used as fuel, 20% as paper/pulp and 30% as longer-lasting materials which may help remove CO2 from atmospheric circulation.
It varies greatly by economic development levels. Africa and India use 90% of their wood as fuel. The US and Europe use 20%. As Korea industrialized, wood use as fuel fell from 70% in 1960 to 7% in 2020.
Overall, wood energy has declined from 11% of the world’s primary energy mix in 1960 to c4% today. However, it remains stubbornly high in less developed countries (e.g., 30% in Africa, data below).
Deforestation remains the largest source of CO2 emissions globally, and the data suggest shortages of oil, gas and coal could exacerbate this ecological disaster. If coal, oil and gas prices all treble, then by extension, the relative value of wood-based fuels approximately trebles too.
This data-base aggregates interesting numbers from the Natural Resources Institute of Finland, which is effectively a ‘gold standard’ for forestry data.
It spans across a national industry that produces 75 mmcm of wood per year, while having also accumulated 1bn tons of biomass over the past century. The industry generates €20bn per annum in value while supporting 60,000 jobs.
A good rule of thumb is that a Finnish forest will accumulate around 5 m3 of biomass per year, mainly pine and spruce, worth around €60/m3 (gross), while the costs of forestry are around €20/hectare/year and the costs of harvesting are around €20/m3.
Splits are also given in later tabs of the data-file between pines, spruce, birch, other species, saw wood, pulp wood and thinnings.
This data-file reviews 25 examples of forestation projects in the United Kingdom, which have followed the UK Woodland Carbon Code.
Our conclusion is that the projects are high-quality. They are largely ‘incremental’ in the sense that most are situated on abandoned or marginal grazing land. They are conservative, mostly placing c20% of expected CO2 credits into a buffer account.
Many also cite co-benefits providing habitats for wildlife (in some cases, plans are quite detailed), recreational enjoyment, tourism, intercepting flood-water and creating employment.
Our conclusion remains that you have to somewhat ‘hate nature’ to not want more reforestation projects like these on a sensible roadmap to net zero.
Another key to the data-file is to plot the typical distribution of parameters such as project size, CO2 uptake (per acre), intended life-span, species diversity, prior land use, intended use of wood, buffer reserves and other forestry practices (charts below).
The purpose of this data-file is to estimate the impacts of bio-diversity on carbon absorption in forests. We have done this by reviewing ten technical papers.
The average result in global meta-studies is that bio-diverse forests take up 15-25% more CO2 than mono-culture counterparts.
The best studies found that highly bio-diverse restoration projects can take up 50-70% more CO2, which was also correlated with the total number of species in a classic ‘log’ relationship.
Full details of individual studies, and our notes, follow in the data-file.
Learning curves and cost deflation are widely assumed in new energies but overlooked for nature-based CO2 removals. This 15-page note finds the CO2 uptake of well-run reforestation projects could double again from here. Support for NBS has already stepped up sharply in 2021. Beneficiaries include the supply chain, leading projects and some energy companies.
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 conclusion is 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.
Measuring forest carbon is uncertain. Pessimistically, estimation errors could be as high as 25%. So does this disqualify nature based carbon credits? This 12-page note explores solutions, borrowing risk-pricing from credit markets, preferring bio-diversity and looking to drone/LiDAR technology.