"Instead of leaving such work to volunteers, global institutions should marshal the funding & expertise to collect crucial data, & mandate their publication"
💯agree with @_HannahRitchie. No one wants to fund the giant who's shoulders we stand on.
The approach to science is to fund big models, expensive observations, etc. All this is needed, but somehow science seems to have forgotten the importance careful curation & maintenance of data.
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Science is full of projects that improve models, do model comparisons, process some satellite data, etc, & if you are lucky there might be a task that scrapes together some data to feed the models.
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A nice example is Norway (coincidentally) spotted two errors in its emissions data, to 2% of its national total. This did not require modelling or satellites, just someone checking consistency in data sources... Very cheap, but undervalued. 4/
Many may just naively download some data, assuming it is correct. But, emission statistics are a tricky beast. Some datasets are just wrong (for explainable reasons).
Eg, some have linked the drop in the blue curve to the Norwegian carbon price (no, it is a data problem).
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These two examples are from Norway, one of the richest countries in the world with a well funded statistical agency.
Start looking at under resourced countries, or CH4 or N2O emissions... Fgas emissions, well, there is another story.
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Climate is supposedly one of the greatest challenges facing society, but we essentially have a crisis in basic energy & emission statistics to feed expensive climate models, to independently track progress under the Paris Agreement, etc.
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As @_HannahRitchie explains, the @IEA has an incredible source of energy & CO2 emissions data, but it is expensive with strict licencing.
Some compile GHG statistics (EDGAR, CEDS, PRIMAP), but datasets vary in duration, independence, frequency, etc. essd.copernicus.org/articles/12/14…
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The work we do in @gcarbonproject has *zero* direct funding, we have to align with other project activities to cover costs. Yet, we persist in updating annually.
These seem to be standard issues for anyone working on data.
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I think the issues go beyond institutional. The research community (funders, researchers, reviewers) has something to answer here too. It is a matter of what to prioritise as important to fund, to write into successful proposals, to be evaluate as "innovative", ...
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Scientific studies (eg IPCC Assessment Reports) generally consider CO₂ emissions from 'Net Conversions' as the emissions, while government reporting to the UNFCCC combines the conversions & sink (black line).
The 'sink' is not the total sink, only a part of the forest sink.
There are two facilities (capturing in 2019), but very different stories:
* Boundary Dam: Operates ~60% capacity, used for EOR
* Quest: Operates ~90% capacity, permanent storage, but the generated H₂ is used to upgrade oilsands
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Boundary Dam is CCS on coal power, with the goal of capturing CO₂ for Enhanced Oil Recovery.
In short, it has not lived up to expectations. How much CO₂ gets stored is unknown, & in any case, the CO₂ is used for EOR (more CO₂).
Norway is known for its Carbon Capture & Storage (CCS) & is best in class.
Even the best in class does not run at capacity. Currently ~80% of capacity is used, but Sleipner has dropped to ~65%.
But, Norwegian CCS is the easy type, removing CO₂ from extracted gas.
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The extracted gas at Sleipner Vest contains ~9% CO₂, but has to be reduced to ~2.5% to meet sales specifications.
The extracted gas in the Snøhvit field contains ~5-7.5% CO₂, and this has to be removed to avoid it freezing out in the downstream liquefaction process.
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The CO₂ has to be removed for market or technical reasons. You would therefore expect the facilities to run at a high capacity, as they have to!
The CO₂ is captured & stored, presumably to avoid paying the Norwegian CO₂ tax. This is great, but a different issue.
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