Talk:Biomass (energy)

Conversion of efn templates into sfn templates

Sorry EMsmile I've had to undo you conversions from {{efn}} to {{sfn}} tempaltes. This isn't how sfn templates are meant to be used, see the templates documentation and the resulting errors type you were causing Category:Harv and Sfn no-target errors. Specifically the sole purpose of a sfn template is to link with a full cite elsewhere in the article, using the |last= and |date= fields in the cite (or the |ref= field if necessary). -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 14:20, 9 January 2023 (UTC)

Yes, I know, it was work in progress. I was trying to find a way of getting this fixed up in an automated manner, rather than manually one by one. Can it be done in an automated manner? We want to delete the quotes but keep the refs that are inside of the footnotes. EMsmile (talk) 14:34, 9 January 2023 (UTC)

Moving the earlier discussion to here: EMsmile (talk) 14:34, 9 January 2023 (UTC)

Hi User:VQuakr: I've just reverted this edit of yours because (whilst I agree those quotes and comments were far too lengthy) I do worry that by taking out all the quotes and comments in one go you have also deleted the refs that were embedded in those "comments". I agree with you that we don't need the quotes and notes but we do need those in-line citations, don't you think? By deleting everything, this would create a lot of unsourced content. EMsmile (talk) 09:21, 9 January 2023 (UTC)

@EMsmile: I mean, when WP:TNTing an article some stuff is going to get broken before it gets fixed. VQuakr (talk) 09:46, 9 January 2023 (UTC)

Yes but re-finding all the deleted in-line citations will be very cumbersome later, won't it? I'll me try to delete some of the quotes now and see how it looks then. EMsmile (talk) 11:59, 9 January 2023 (UTC)

I've now converted the notes into refs and corrected the formatting for the first few (the ref list is now temporarily messed up as a result). It's doable but it's very time consuming. So I wonder if I am on the right track here or if I am barking up the wrong tree. A whole-sale deletion would be faster, sure, but I want to keep any of the useful content with regards to in-line citation. What's the best way forward from here? Continue like I have done? Or is that a waste of time? EMsmile (talk) 12:42, 9 January 2023 (UTC)

Hi ‎User:ActivelyDisinterested, I see you have reverted me. Can you please provide guidance on the fastest way of converting the refs that are inside of those notes into refs? That's what I was trying to do... i.e. to delete the quotes and text but to keep the refs that are inside of those footnotes. EMsmile (talk) 14:17, 9 January 2023 (UTC)

I added a section below before I saw this comment. Short answe this isn't a correct use of the sfn template. -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 14:21, 9 January 2023 (UTC)

If you turn on the error messages for short form refs (details are in ten category Category:Harv and Sfn no-target errors, ask if you have any questions), then you will see your version was a sea of red error messages. -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 14:24, 9 January 2023 (UTC)

OK I've done a couple of examples of how removing the notes while keeping the refs could work. In example one the inline note is replaced with a refname, and the ref is added to the reflist. This way means that any note that's re-used many times only has to be defined once. In the second example the inline is replaced with a direct link to cite using a {{sfn}} template. This is cleaner but each inline use of a note needs slightly more conversion. I'd suggest anyone doing the conversion turns on the error messages so they can check their work. Any questions just let me know. -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 14:53, 9 January 2023 (UTC)

Thanks a lot, User:ActivelyDisinterested. I've tried to follow your first example but got myself into a knot. So it seems each one would have to be converted manually one by one. This is quite time consuming (especially for me because I keep getting confused). I might just leave it for now as we're probably going to cull and condense a lot of the content anyhow. This would then remove a lot of the notes anyway. We could can just convert the ones that actually remain manually. It must have taken the person who set this up originally ages to set this all up! EMsmile (talk) 17:41, 9 January 2023 (UTC)

A lot of the time it's easier to setup complicated referencing than it is to maintain it. I agree it's likely a better idea to cull content and then convert any notes that remain. -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 17:51, 9 January 2023 (UTC)

Hi ActivelyDisinterested, now that I have done a lot of culling from this article, is there an easy way (ideally with a bot?) to remove all of the unused ref names, sources and notes from the article? It would be rather time consuming to do it all manually. EMsmile (talk) 12:58, 16 January 2023 (UTC)

EMsmile I've removed all the unused notes, which clears all the error messages. There's no automation for any of this, with all the complexities of referencing that are allowed by Wikipedia it just wouldn't be possible. Are the rest of the notes still be to be convert to just the references? -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 13:51, 16 January 2023 (UTC)

Thanks for that! I am still in the process of deleting & culling more and also converting more of the notes to refs (I'll use the long ref style). At the end, there will likely be no notes remaining. How about those publications that are listed under "Bibliography" which are no longer in use now: is there an easy way to identify which ones are now superfluous or does that have to be done manually as well? EMsmile (talk) 14:52, 16 January 2023 (UTC)

There's a script that can help you identify them (see Category:Harv and Sfn template errors, in particular "User:Trappist the monk/HarvErrors.js"). I've gone ahead and moved all the cites not currently used by referencing to a "Further reading " section. Feel free to trim or delete as you see necessary. -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 15:49, 16 January 2023 (UTC)

Thanks a lot for your help! I've now removed the "further reading" list and placed it on the talk page in case it needs discussion later. I've also installed that HarvErrors script and will see how it works. EMsmile (talk) 10:18, 17 January 2023 (UTC)

Anytime. If you have any questions just let me know. -- LCU ActivelyDisinterested ∆transmissions∆ °co-ords° 13:15, 17 January 2023 (UTC)

The correct way to delete or move content containing SFN and EFN-based footnotes

There seems to be some confusion regarding the correct way to delete or move content containing SFN and EFN-based footnotes. Here is how to do it correctly (use Source editing):

Footnotes based on the SFN (Shortened FootNotes) template consist of 2 pieces of text. The first piece is the SFN template itself, the second is its citation counterpart.

The SFN template is inserted into the main text, for instance {{sfn|EIA|2021a}}

This code tells the computer to go look for a citation further down below where the author is IEA and the date is 2021a. (The "a" is added to the year since there are two or more EIA citations from that particular year.) The computer then races towards the bottom of the article and finds this:

{{cite web | author=EIA | title=Biomass explained | website=U.S. Energy Information Administration | date=2021a | url=https://www.eia.gov/energyexplained/?page=biomass_home | access-date=2021-11-02}}

The computer sees that the author is EIA and the date is 2021a, and is satisfied. It then generates the correct footnote.

If you want to delete SFN-based footnotes, you have to delete both pieces of text. Otherwise you will generate error messages. (Exception: If other footnotes uses that same citation, you should not delete it. If you actually delete it, the computer will generate an error message when you preview the result. Go back and reinstate the citation.)

If you want to copy a SFN-based footnote to another article, you have to put the SFN template into the main text, and its citation counterpart between {{refbegin}} and {{refend}} in the References section.

Footnotes based on the EFN (Explanatory FootNotes) template consists of 3 pieces of text. The first piece is the EFN template, the second is the note counterpart, the third is the citation counterpart.

The EFN template is inserted into the main text, for instance

{{efn|name=EIA-2021b}}

This code tells the computer to go look for its note counterpart, which has the name EIA-2021b (you choose this name yourself). Here it is:

{{efn|name=EIA-2021b|"Biofuels are transportation fuels such as ethanol and biodiesel that are made from biomass materials." {{harvnb|EIA|2021b}}.}}

The first part of the note (the quote) can now be generated. But it is not complete; we also need the citation. However, the last part of the note gives the computer the information it needs in this regard; it tells the computer that the author is EIA, and that the date is 2021b. The computer then looks further down the article to find a citation that matches these requirements, and finds this:

{{cite web | author=EIA | title=Biofuels explained | website=U.S. Energy Information Administration | date=2021b | url=https://www.eia.gov/energyexplained/biofuels/ | access-date=2021-11-02}}

The computer here sees that the author is EIA and the date is 2021b, and is satisfied. It then generates the correct footnote.

If you want to delete EFN-based footnotes, you have to delete all the three pieces of text. Otherwise the computer will generate an error message. (Exception: If other footnotes use the same citation, you should not delete it. If you actually delete it, the computer will generate an error message. Go back and reinstate the citation.)

If you want to copy an EFN-based footnote to another article, you have to

1.) put the EFN template in the main text

2. put the note counterpart between

{{notelist|40em|refs=

and

}}

(Note that the 40em parameter above is not essential, it only tells the computer how wide the columns should become.)

3. put the citation counterpart between {{refbegin}} and {{refend}} in the References section.

If you are looking for the easiest way to edit and move content, consider NOT converting SFN and EFN-based footnotes manually to inline (that is, only one piece of text) REF-based footnotes. Inline REF-based footnotes can later be added at will, with SFN and EFN-based footnotes co-existing. If you keep the SFN and EFN-based footnotes, these footnotes will be presented in two layers like they are today, with the quote/comment first and citation second, but on the plus side you will not have to do any manual labor converting them. However, since they are presented in two layers, you might want to consider keeping just a tiny fraction of the quote or comment, what you consider the most essential part. In Source editing mode, it is super easy to delete the part of the footnote you find excessive. Just scroll down to the notelist and start editing. I have found that for big jobs, I work faster by simply copying the article code over to several text documents, which I work on at the same time. For instance when I work on EFN-based footnotes, I have one text document for the main text, one for the notelist, and one for the citations. That way, I save myself a lot of scrolling back and forth. When you are done, simply merge these three documents together. The Perennial Hugger (talk) 17:33, 10 January 2023 (UTC)

Culled content on climate impact

I'm going to cull all the content on climate impact for now and then take another look to see if anything can be salvaged.

culled content on climate impact

Carbon accounting principles Main article: Carbon accounting Different carbon accounting methodologies have a significant impact on the calculated results and therefore on the scientific arguments. Generally, the purpose of carbon accounting is to determine the carbon intensity of an energy scenario, i.e. whether it is carbon positive, carbon neutral or carbon negative. Carbon positive scenarios are likely to be net emitters of CO2, carbon negative projects are net absorbers of CO2, while carbon neutral projects balance emissions and absorption perfectly. As a consequence of both natural causes and human practices, carbon continually flows between carbon pools, for instance the atmospheric carbon pool, the forest carbon pool, the harvested wood products carbon pool, and the fossil fuels carbon pool. When the carbon level in pools other than the atmospheric carbon pool increase, the carbon level in the atmosphere decrease, which helps mitigate global warming. If a researcher measures the amount of carbon moving from one pool to another, they can gain insight and recommend practices that maximize the amount of carbon stored in carbon pools other than the atmospheric carbon pool. Three concepts are especially important, namely carbon debt, carbon payback time and carbon parity time: Carbon debt accrues when biomass is removed from growing sites, for instance forests. It is counted when the trees are felled because the UNFCCC (the UN organization that countries report their emissions to) has decided that emissions should be counted already at this point in time, instead of at the combustion event. Carbon payback time is the time it takes before this carbon is "paid back" to the forest, by having the forest re-absorb an equivalent amount of carbon from the atmosphere. Carbon parity time is the time it takes for one energy scenario to reach carbon parity with another scenario (i.e. store the same amount of carbon as another scenario.) One of these scenarios can for instance be a bioenergy scenario, with carbon counted as stored in the part of the forest that was not harvested, and carbon counted as lost for the amount of forest that were harvested (cf. the UNFCCC rule mentioned above.) However, the amount of carbon that resides in woody construction materials and biofuels made from this harvest can be "counted back" into the bioenergy scenario's carbon pools for the amount of time it takes before this carbon decays naturally or are burnt for energy. The alternative scenario can for instance be a forest protection scenario, with carbon counted as stored in the whole forest – a forest that is bigger than in the bioenergy scenario because no trees were harvested at all, and in addition also continued to grow (while waiting for the carbon stored in the bioenergy scenario to catch up to its own carbon level.) However, the implied "lock-in" of carbon in the forest also means that this carbon no longer is available for production of woody construction materials and biofuels, which means that these have to be replaced by other sources. In most cases, the most realistic sources are fossil sources, which means that the forest protection scenario here will be "punished" by having the fossil fuel emissions it is responsible for subtracted from its carbon pool. (Note that this fossil carbon is often instead technically speaking counted as added to the bioenergy carbon pool (instead of subtracted from the no-bioenergy carbon pool), and called "displaced" or "avoided" fossil carbon.) A net carbon debt for the bioenergy scenario is calculated when the net amount of carbon stored in the forest protection scenario's carbon pool is larger than the net amount of carbon stored in the bioenergy scenario's carbon pools. A net carbon credit for the bioenergy scenario is calculated when the net amount of carbon stored in the forest protection scenario's carbon pool is smaller than the net amount of carbon stored in the bioenergy scenario's carbon pools. The carbon parity time then is the time it takes for the bioenergy scenario to go from debt to credit. To recap, a project or scenario can be assessed solely on its own merits, specifically the time it takes to pay back removed carbon (carbon payback time.) However, it is common to include alternative scenarios (also called "reference scenarios" or "counterfactuals") for comparison. When there is more than one scenario, carbon parity times between these scenarios can be calculated. The alternative scenarios range from scenarios with only modest changes compared to the existing project, all the way to radically different ones (i.e. forest protection or "no-bioenergy" counterfactuals.) Generally, the difference between scenarios is seen as the actual carbon mitigation potential of the scenarios. In other words, quoted emission savings are relative savings; savings relative to some alternative scenario the researcher suggest. This gives the researcher a large amount of influence over the calculated results. Carbon accounting system boundaries System boundaries for carbon accounting: Option 1 (black) limits the carbon calculation to stack emissions, option 2 (green) limits the calculation to the forest carbon stock, option 3 (blue) limits the calculation to forest and stack emissions combined (the supply chain) and option 4 (red ) includes both stack emissions, forest and the bioeconomy (carbon storage in wood products and displaced fossil fuels.) In addition to the choice of alternative scenario, other choices has to be made as well. The so-called "system boundaries" determine which carbon emissions/absorptions that will be included in the actual calculation, and which that will be excluded. System boundaries include temporal, spatial, efficiency-related and economic boundaries: Temporal system boundaries The temporal boundaries define when to start and end carbon counting. Sometimes "early" events are included in the calculation, for instance carbon absorption going on in the forest before the initial harvest. Sometimes "late" events are included as well, for instance emissions caused by end-of-life activities for the infrastructure involved, e.g. demolition of factories. Since the emission and absorption of carbon related to a project or scenario changes with time, the net carbon emission can either be presented as time-dependent (for instance a curve which moves along a time axis), or as a static value; this shows average emissions calculated over a defined time period. The time-dependent net emission curve will typically show high emissions at the beginning (if the counting starts when the biomass is harvested.) Alternatively, the starting point can be moved back to the planting event; in this case the curve can potentially move below zero (into carbon negative territory) if there is no carbon debt from land use change to pay back, and in addition more and more carbon is absorbed by the planted trees. The emission curve then spikes upward at harvest. The harvested carbon is then being distributed into other carbon pools, and the curve moves in tandem with the amount of carbon that is moved into these new pools (Y axis), and the time it takes for the carbon to move out of the pools and return to the forest via the atmosphere (X axis). As described above, the carbon payback time is the time it takes for the harvested carbon to be returned to the forest, and the carbon parity time is the time it takes for the carbon stored in two competing scenarios to reach the same level. The static carbon emission value is produced by calculating the average annual net emission for a specific time period. The specific time period can be the expected lifetime of the infrastructure involved (typical for life cycle assessments; LCA's), policy relevant time horizons inspired by the Paris agreement (for instance remaining time until 2030, 2050 or 2100), time spans based on different global warming potentials (GWP; typically 20 or 100 years), or other time spans. In the EU, a time span of 20 years is used when quantifying the net carbon effects of a land use change. Generally in legislation, the static number approach is preferred over the dynamic, time-dependent curve approach. The number is expressed as a so-called "emission factor" (net emission per produced energy unit, for instance kg CO2e per GJ), or even simpler as an average greenhouse gas savings percentage for specific bioenergy pathways. The EU's published greenhouse gas savings percentages for specific bioenergy pathways used in the Renewable Energy Directive (RED) and other legal documents are based on life cycle assessments (LCA's). Spatial system boundaries The spatial boundaries define "geographical" borders for carbon emission/absorption calculations. The two most common spatial boundaries for CO2 absorption and emission in forests are 1.) along the edges of a particular forest stand and 2.) along the edges of a whole forest landscape, which include many forest stands of increasing age (the forest stands are harvested and replanted, one after the other, over as many years as there are stands.) A third option is the so-called increasing stand level carbon accounting method: – In stand level carbon accounting, the researcher may count a large emission event when the stand is harvested, followed by smaller, annual absorption amounts during the accumulation phase that continues until the stand has reached a mature age and is harvested again. – Likewise, in increasing stand level accounting, the researcher counts a large emission event when the stand is harvested, followed by absorption of smaller quantities of carbon each year during the accumulation period. However, one year after the first harvest, a new stand is harvested. The researcher do not count the carbon that was absorbed in this second stand after the first, neighbouring stand was harvested, only the large emission at the harvest event of the second stand. The next year the same procedure repeats for the third stand; the carbon that was absorbed by this stand after the harvest of the first and second stand is not counted, while a large emission amount is counted when the third stand is harvested. In other words, in increasing stand level accounting the whole carbon account is composed of a number of individual stand-level accounts, each with its own, individual starting point. – In landscape level accounting, the researcher counts a large emission event when the first stand is harvested, followed by absorption of smaller quantities of carbon each year during the accumulation period for this particular stand. Like with increasing stand level accounting, a new stand is harvested the second and third year etc., and these emission events are all counted. Unlike with increasing stand level accounting however, the researcher also counts the carbon that is absorbed by all stands after the harvest of the first stand in the forest landscape. In other words, instead of calculating carbon emissions from a lot of different starting points, forest landscape accounting uses only one, common starting point for the whole forest landscape, namely the year the first stand was harvested. So, the researcher has to decide whether to focus on the individual stand, an increasing number of stands, or the whole forest landscape. According to Lamers et al., the stand level spatial boundary choice is typical for early carbon modeling, and it leads to carbon cycles that resemble sawteeth (dramatic increases in emissions at harvest, followed by slow declines as the forest stand absorb carbon.) The key benefit of stand-level analysis is its simplicity, and this is the primary reason for it still being part of today's carbon analyses. However, while the study of single stands provide easily comprehensible results (for example on the carbon effects of different harvesting choices), real-world timber/woody biomass supply areas consist of several stands of different maturity, for instance 80. Over a time period of 80 years then, all stands are successively harvested and replanted. To accurately calculate the carbon flow over such large areas the spatial boundary of the calculation has to increase from stand level to landscape level, as the forest "landscape" contains all the individual forest stands. Cowie et al. argue that landscape level accounting is more representative of the way the forestry sector manages to produce a continuous supply of wood products. The IPCC recommends landscape-level carbon accounting as well (see Short-term urgency below). Further, the researcher has to decide whether emissions from direct/indirect land use change should be included in the calculation. Most researchers include emissions from direct land use change, for instance the emissions caused by cutting down a forest in order to start some agricultural project there instead. The inclusion of indirect land use change effects is more controversial, as they are difficult to quantify accurately. Other choices involve defining the likely spatial boundaries of forests in the future. For instance, is increased harvesting and perhaps even forest expansion more realistic than forest protection in a situation with high demand for forest products? Or alternatively, is smaller forests perhaps more realistic than forest protection in a situation with low demand for forest products and high demand for new land or new areas for housing and urban development? Lamers & Junginger argue that from a nature conservation and carbon strategy evaluation perspective, forest protection is a valid option. However, protection is unlikely for forest plantations – in the absence of demand for forest products (e.g., timber, pulp or pellets), "[...] options such as conversion to agriculture or urban development may be more realistic alternatives [...]." Cowie et al. argue that privately owned forests are often used to create income and therefore generally sensitive to market developments. Forest protection is an unrealistic scenario for most of the privately owned forests, unless forest owners can be compensated for their loss of income. According to the EU's Joint Research Centre, 60% of the European forests are privately owned. In the US, over 80% is privately owned in the east, and over 80% publicly owned in the west. Efficiency-related system boundaries Bioenergy displacement factors for substituted fossil fuels. Woody materials displacement factors for substituted fossil based materials. The efficiency-related boundaries define a range of fuel substitution efficiencies for different biomass-combustion pathways. Different supply chains emit different amounts of carbon per supplied energy unit, and different combustion facilities convert the chemical energy stored in different fuels to heat or electrical energy with different efficiencies. The researcher has to know about this and choose a realistic efficiency range for the different biomass-combustion paths under consideration. The chosen efficiencies are used to calculate so-called "displacement factors" – single numbers that shows how efficient fossil carbon is substituted by biogenic carbon. If for instance 10 tonnes of carbon are combusted with an efficiency half that of a modern coal plant, only 5 tonnes of coal would actually be counted as displaced (displacement factor 0.5). Schlamadinger & Marland describes how such low efficiency lead to high parity times when bioenergy and coal-based forest protection scenarios are compared, and on the other hand how an efficiency identical to the coal scenario lead to low parity times. Generally, fuel burned in inefficient (old or small) combustion facilities gets assigned lower displacement factors than fuel burned in efficient (new or large) facilities, since more fuel has to be burned (and therefore more CO2 released) in order to produce the same amount of energy. Likewise, since the production of wood based construction materials demand lower fossil fuel input than the production of fossil based construction materials (e.g. cement or steel), the wood based construction materials get assigned displacement factors when substitution of cement and steel based construction materials is realistic, i.e. when they have the same utility in construction. The more fossil fuel emissions avoided by using utility-equivalent wood construction products, the higher the assigned displacement factors. Additionally, the carbon stored in wood products during the products' service life, and the fossil carbon that is displaced when the wood products are combusted for energy at the end of their service life, can both be included in the displacement factor calculations. However, so far this is not common practice. (52% of the harvested forest biomass in the EU is used for materials.) Sathre & O'Connor examined 21 individual studies and found displacement factors of between −2.3 and 15 for construction wood products, with the average at 2.1, which means that for each tonne of biogenic carbon produced, on average 2.1 tonnes of fossil carbon is displaced. For wood based biofuels, the displacement factors varied between roughly 0.5 and 1, "[...] depending largely on the type of fossil fuel replaced and the relative combustion efficiencies." The authors write that when construction wood products are combusted for energy at the end of their service life, the displacement effect is sometimes added to the calculation, "[...] as the GHG benefits of both material substitution and fuel substitution accrue." In another meta study on construction wood products, where this additional end-of-life combustion substitution effect was excluded, the authors found somewhat lower displacement factors. The combustion-specific displacement factors were similar but with a wider range (see charts on the right.) The displacement factor varies with the carbon intensity of both the biomass fuel and the displaced fossil fuel. If or when bioenergy can achieve negative emissions (e.g. from afforestation, energy grass plantations and/or bioenergy with carbon capture and storage (BECCS), or if fossil fuel energy sources with higher emissions in the supply chain start to come online (e.g. because of fracking, or increased use of shale gas), the displacement factor will start to rise. On the other hand, if or when new baseload energy sources with lower emissions than fossil fuels start to come online, the displacement factor will start to drop. Whether a displacement factor change is included in the calculation or not, depends on whether or not it is expected to take place within the time period covered by the relevant scenario's temporal system boundaries. Economic system boundaries The economic boundaries define which market effects to include in the calculation, if any. Changed market conditions can lead to small or large changes in carbon emissions and absorptions from supply chains and forests, for instance changes in forest area as a response to changes in demand. Miner et al. describe how researchers have begun to examine forest bioenergy in a broader, integrated framework that also addresses market impacts. Based both on empirical data and modeling, these studies have determined that increased demand often leads to investments in forestry that increase forest area and incentivize improvements in forest management. Depending on circumstances, this dynamic can increase forest carbon stocks. Where growth rates are relatively high and the investment response strong, net GHG benefits from increased use of trees for energy can be realized within a decade or two, depending on the fossil fuel being displaced and the timing of the investment response. Where tree growth is slow and the investment response is lacking, many decades may be required to see the net benefits from using roundwood for energy. The investment response has been found to be especially important in places such as the US South, where economic returns to land have been shown to directly affect gains and losses in forest area. Abt et al. argue that the US South is the world's largest timber producer, and that the forest is privately owned and therefore market driven. Further, EU's Joint Research Centre argue that macroeconomic events/policy changes can have impacts on forest carbon stock. Like with indirect land use changes, economic changes can be difficult to quantify however, so some researchers prefer to leave them out of the calculation. System boundary impacts The chosen system boundaries are very important for the calculated results. Shorter payback/parity times are calculated when fossil carbon intensity, forest growth rate and biomass conversion efficiency increases, or when the initial forest carbon stock and/or harvest level decreases. Shorter payback/parity times are also calculated when the researcher choose landscape level over stand level carbon accounting (if carbon accounting starts at the harvest rather than at the planting event.) Conversely, longer payback/parity times are calculated when carbon intensity, growth rate and conversion efficiency decreases, or when the initial carbon stock and/or harvest level increases, or the researcher choose stand level over landscape level carbon accounting. Critics argue that unrealistic system boundary choices are made, or that narrow system boundaries lead to misleading conclusions. Others argue that the wide range of results shows that there is too much leeway available and that the calculations therefore are useless for policy development. EU's Join Research Center agrees that different methodologies produce different results, but also argue that this is to be expected, since different researchers consciously or unconsciously choose different alternative scenarios/methodologies as a result of their ethical ideals regarding man's optimal relationship with nature. The ethical core of the sustainability debate should be made explicit by researchers, rather than hidden away. Climate impacts expressed as varying with time Time-dependent net emission estimates for forest bioenergy pathways, compared against coal and natural gas alternative scenarios. Plus signs represents positive climate effects, minus signs negative climate effects. According to EU's Joint Research Centre, the use of boreal stemwood harvested exclusively for bioenergy have a positive climate impact only in the long term, while the use of wood residues have a positive climate impact also in the short to medium term. See chart on the right for an overview over expected emission reductions from different forest bioenergy pathways, including stemwood, residues and new plantations, compared against energy generation from coal and natural gas in the alternative scenarios. Stems from short-rotation coppices or short-rotation forests also have positive climate effects in the short to medium term (see below.) Short carbon payback/parity times for forest residues Short carbon payback/parity times are produced when the most realistic no-bioenergy scenario is a traditional forestry scenario where "good" wood stems are harvested for lumber production, and residues are burned or left behind in the forest or in landfills. The collection of such residues provides material which "[...] would have released its carbon (via decay or burning) back to the atmosphere anyway (over time spans defined by the biome's decay rate) [...]." In other words, payback and parity times depend on the decay speed. The decay speed depends on a.) location (because decay speed is "[...] roughly proportional to temperature and rainfall [...]"), and b.) the thickness of the residues. Residues decay faster in warm and wet areas, and thin residues decay faster than thick residues. Thin residues in warm and wet temperate forests therefore have the fastest decay, while thick residues in cold and dry boreal forests have the slowest decay. If the residues instead are burned in the no-bioenergy scenario, e.g. outside the factories or at roadside in the forests, emissions are instant. In this case, parity times approach zero. Madsen & Bentsen examined emissions from both forest residues and coal, combusted in the same, real Northern European CHP (combined heat and power) plant, and found that the carbon parity time was 1 year. The low parity time was mainly the result of the use of residues, the generally high conversion efficiencies of CHP plants compared to regular power plants (in this case 85.9%), and longer transport distance for coal. The authors note that most bioenergy emission studies use hypothetical rather than real field data, and that 16 times more biomass is combusted in CHP plants than in pure electricity plants in the EU. In other words, it is heat-related payback/parity times such as these that are the most relevant for the current situation. Holmgren studied climate effects from actual forestry practices in a whole country over a 40-year time period (Sweden 1980–2019), and found that at the national landscape level, no carbon debt accrued at any point in time during this period. The actual forestry practice was compared to two alternative forest protection scenarios. The counted emissions caused by the initial harvest in the actual forestry scenario did not lead to a carbon debt because 1.) the initial harvest-related carbon emission was outweighed by carbon absorption caused by growth elsewhere in the forest (a trend that is expected to continue in the future), and 2.) because a national forest protection policy would cause large initial emissions from the national wood-based products and energy infrastructure when it is converted to work with fossil fuels. The conversion is described as a "[...] one-off transformation, representing major and required modifications to energy systems, infrastructure, industrial processing, building sector, manufacturing of consumer products and other economic activities towards fossil-based production if a no-harvest scenario were to be implemented." Of course, if the bioenergy scenario's initial harvest-related emission event is outweighed by 1.) forest growth elsewhere, and 2.) infrastructure conversion emissions (in the forest protection scenario), no carbon debt accrues at all, and the payback and parity times reduce to zero. The author argue that since forest protection most likely will cause fossil carbon to be emitted instead of biogenic carbon, the practical effect of forest protection is simply a transfer of carbon from the underground fossil carbon pool via combustion to the atmospheric carbon pool, and then via photosynthesis to the forest carbon pool. However, when carbon is stored in forests instead of underground fossil reservoirs, it is more unstable, that is, easier to convert to CO2 because of natural disturbances. A conservative displacement factor of 0.78 tonnes of fossil carbon displaced per tonne of biogenic carbon produced is used for both harvested wood products (HWP) and energy combined. The author criticizes studies that limit carbon accounting to the carbon flows within the forests themselves and leave out fossil displacement effects, and argues that this narrow system boundary essentially works as "[...] a justification for continued fossil emissions elsewhere with no net gain for the global climate." In Sweden, the biomass that is available for energy is mainly used in heating facilities (7.85 Mtoe used for heating, 0.84 Mtoe for electricity.) In the US, Walker et al. found parity times of 10 years or less when using forest residues in New England to replace coal in a regular, utility-scaled electricity plant. Likewise, Miner et al. argue that in the eastern parts of the US, all kinds of forest residues can be used for bioenergy with climate benefits within 10 years compared to a coal-based alternative scenario, and within 20 years compared to a natural gas-based alternative scenario. Carbon parity times for wood-pellet electricity from different feedstocks (Hanssen et al. 2017). Hanssen et al. compared a bioenergy scenario that included continued pellet production in the Southeast USA to three alternative fossil fuel mix scenarios, all seen as more realistic scenarios than forest protection: 1.) Use all harvested biomass to produce paper, pulp or wood panels, 2.) quit the thinning practice, i.e., leave the small trees alone, so more of their growth potential is realized, and 3.) leave the residues alone, so they decay naturally over time, rather than being burned almost immediately in power plants. Three different levels of demand (low, average, high) was included for each alternative scenario. Parity times ranged from 0–21 years in all demand scenarios, and 0–6 years in the average demand scenarios (see chart on the right). The authors used landscape level carbon accounting, rotation time was 25 years, and market effects were included. Carbon parity times for various residues-based energy systems, compared to alternative scenarios. Time-dependent global warming mitigation potentials for forest residues, cereal straw and biogas slurry. Time-dependent emission levels from decaying forest residues with different thicknesses: stumps (30 cm), thinnings (10 cm) and branches (2 cm). Dotted lines = North Finland, solid lines = South Finland. Lamers & Junginger examined a number of studies on (sub)-boreal forest residues (including stumps in some cases), and found carbon parity times of between 0 and 16 years. The bioenergy scenario was compared against an alternative reference scenario where the residues either were left in the forests to decay naturally, or was incinerated at the roadside. The parity time was 0 years compared to a scenario where the residues was burned at roadside and electricity instead produced by coal plants. However, parity times increased to 3–24 years when roadside burning was exchanged with natural decay, and coal exchanged with oil. Parity times increased further to 4–44 years when oil was replaced with natural gas. All bioenergy scenarios used landscape level carbon accounting. Zanchi et al. agree that there are climate benefits from the beginning when using easily decomposable forest residues for bioenergy. They also write that "[...] new bioenergy plantations on lands with low initial C [carbon] stocks, such as marginal agricultural land, has the clearest advantages in terms of emission reductions." The reason is that newly planted areas (which now has a large growing stock of trees or other plants), absorb much more carbon than earlier. Such areas build up a carbon credit instead of a carbon debt, where the credit is used later (at harvest) to acquire "debt free" biomass. In general, "early" carbon accounting like this, which starts at the planting event rather than at the harvest event (cf. Temporal system boundaries above), is seen as uncontroversial for new bioenergy plantations on land areas with very little vegetation. On the other hand, for areas where there already is a large amount of vegetation in place, "late" carbon accounting is often preferred. In this case, carbon accounting starts at harvest, with no build-up of a prior carbon credit. With this type of carbon accounting, the calculated results show that there are short to medium term negative impacts when trees are felled exclusively for bioenergy (so-called "additional fellings"). The situation gets worse if residues are left to rot on the forest floor. There is also a risk for negative impacts if areas with large amounts of biomass such as forests are clear-cut in order to make room for low-productivity forest plantations. The assessment of such "additional fellings" from "new" bioenergy plantations after the first rotation is complete, depends on the chosen carbon accounting method. If the "early" carbon accounting continues, there will be a build-up of a carbon credit also after the first rotation, i.e. from the moment in time when the trees have been replanted. If the researcher at that time change to "late" carbon accounting, no carbon credit will be calculated, and at the end of the second rotation (at harvest) a large carbon debt will be created instead, causing payback and parity times to increase dramatically. Long carbon payback/parity times for forest residues EU's Joint Research Centre provides time-dependent emission estimates for electricity production on a large scale from residue-based wood pellets, cereal straw and biogas from slurry, compared against a no-bioenergy scenario with emissions equal to EU's current electricity mix. Conversion efficiencies are 34%, 29% and 36% for wood pellets, straw and biogas, respectively. If not used for electricity production, the forest residues would have been left to decay on the forest floor, the straw residues would also have been left behind in the fields, and the raw manure would have been used as organic fertilizer. The results show that if these biomass types instead were used to produce electricity, a global warming mitigation effect would start after approximately 50, 10 and 5 years of use, for wood, straw and biogas respectively. The main cause for the long parity time for wood pellets is the comparison with electricity from EU's electricity mix (which includes electricity from solar, wind and fossil fuels with lower emissions than coal). Also, the forest residue category includes stumps. The JRC also found parity times ranging from 0 to 35 years for harvest residues (including branches, thinnings and stumps), when compared to some other alternative scenarios. In Finland, parity times for stumps were 22 years compared against oil, and 35 years compared against natural gas, with stand level carbon accounting. In Canada, parity time increased from 16 to 74 years when the harvested biomass was used to produce ethanol instead of wood pellets, and compared against a gasoline-based alternative scenario instead of a coal-based alternative scenario. Ethanol production from whole trees removed from old-growth forests in Oregon, USA, (categorized as residues because the trees were felled to prevent wildfire) increased parity time dramatically, with the worst-case scenario at 459 years. The authors used stand level carbon accounting starting with the harvest event, assumed an additional, controlled burning every 25 years, and compared this to a scenario with no wildfire-preventive fellings and a severe wildfire every 230 years. The trees in question were huge western hemlock and coast Douglas fir trees which both take hundreds of years to mature and can withstand wildfires due to very thick stems. Since energy-intensive ethanol production caused a low displacement factor of only 0.39, a long parity time was calculated. Generally, the JRC's reported parity times were influenced by displacement factor, alternative scenario, residue size and climate type. See chart above. Short carbon payback/parity times for stemwood If an existing natural forest is clear-cut in order to make room for forest plantations, the implied carbon change create a significant carbon debt roughly equal to the amount of carbon residing in the felled trees (fossil based forestry operations create an additional, small debt.) But for new plantations on "empty" land like agricultural or marginal land, with no standing vegetation, no carbon is removed. In this case, a carbon credit is instead soon built up as the trees mature. When those trees later are felled, the amount of carbon that resides in the trees is subtracted from the built up carbon credit (not the carbon amount in the standing trees), so in this case no carbon debt is created. With no carbon debt created at harvest, carbon payback/parity times will be zero or very low, for residues and stemwood alike. Jonker et al. calculated both carbon payback and carbon parity times for stemwood with rotation times of 20–25 years harvested from southeastern forests in the US, using both stand level, increasing stand level, and landscape level carbon accounting. With stand-level carbon accounting, the authors found carbon payback times of 5, 7 and 11 years in the high, medium and low yield scenario, respectively. With increasing stand level accounting, the payback times were 12, 13 and 18 years in the high, medium and low yield scenario, respectively. With landscape level accounting, the payback time was below 1 year for all yield scenarios. The authors also calculated parity times for a scenario where wood pellets from stems only (no residue collection) were used for co-firing in an average, coal-based electricity plant. The conversion efficiency was 41%, which together with an efficient supply chain leads to a relatively high displacement factor of 0.92. The alternative scenario was a no-bioenergy scenario where the stemwood was instead used for lumber production, so no co-firing at all in this case (electricity from coal exclusively.) When using the increasing stand level accounting principle, the authors calculated parity times of 17, 22 and 39 years for the high, medium and low yield scenario, respectively. When using the landscape level accounting principle, the authors calculated parity times of 12, 27 and 46 years for the high, medium and low yield scenario, respectively. A different alternative scenario was a forest protection scenario where no biomass was extracted from the forest at all; not for lumber, and not for bioenergy. The forest was simply left to itself and therefore regrew rather slowly. Landscape level parity times for this scenario was 3, 3, and 30 years for the high, medium and low yield scenario, respectively (stand level or increasing stand level parity times were not provided.) The authors note that "the result of the carbon balances clearly demonstrate that the choice of carbon accounting method has a significant impact on the carbon payback and carbon offset parity point calculations." They argue that the short parity times are caused by the fast growth rates (10–12 tonnes dry mass per hectare per year) in softwood plantations in the southeastern USA. Other researchers have often based their calculations on the slow growth rates typical for hardwood in natural boreal forests, which generates much higher payback and parity times. The authors also argue that for established softwood plantations, there is no carbon debt caused by land use change. Also, the displacement factor is higher here than in some other studies, due to the efficient supply chain and the high conversion efficiency achieved when wood pellets are used for co-firing in regular coal plants rather than in small-scale bioenergy plants; the latter often assumed to be the case in other studies. In effect, these favourable system boundaries cause the parity time to reduce to one or two rotations. The carbon debt is small before the parity point, and the subsequent carbon credit rises high after the parity point has been passed: "It is also clear that the absolute size of the temporary negative carbon balance is limited, whereas the positive carbon balance after break-even soon reaches levels many times greater." The authors argue that the no-bioenergy and the forest protection scenario is unrealistic in the study area, since the forests here are privately owned and there is a large wood processing industry already in place. In this situation (without viable alternative scenarios) the authors argue that the most relevant temporal metric is the carbon payback time of below 1 year for all yield scenarios, based on the landscape level carbon accounting principle. Abt et al. also argue that in the southeastern USA, forest protection scenarios are unrealistic since the forests are privately owned. Carbon parity times for stemwood harvested exclusively for bioenergy, compared against various alternative fossil-based scenarios. EU's Joint Research Centre reviewed a number of studies and found that if stemwood is harvested for both bioenergy and wood products, continued harvesting works better for the climate than forest protection given a 40 years timeframe. The reason is the larger displacement effect of wood products compared to bioenergy. If wood products are used for energy when reaching their end of life (so-called "cascading"), the displacement effect grows even larger, and under optimal conditions, parity times can reduce from several centuries to zero. The JRC therefore argue that studies that fail to include the wood for material displacement effect may come to misleading conclusions. On the other hand, if a forest is harvested exclusively for bioenergy, there is no displacement effects happening for wood products, which means a lower displacement factor and therefore a net increase in calculated CO2 emissions "[...] in the short-and medium term (decades) [...]" when compared to fossil fuels, except when it is harvested from new plantations on marginal, agricultural or grazing land. In this case there is an immediate net increase in carbon at the site, as planting without prior tree felling increases the amount of biomass there. Again, when there is no carbon debt, the payback and parity times reduce to zero. Long carbon payback/parity times for stemwood Zanchi et al. found that parity times can reach 175 years with a coal-based alternative scenario and 300 years with a natural gas-based alternative scenario if spruce stems in the Austrian Alps are harvested exclusively for bioenergy. The main reason is the long rotation time for these trees (90 years). Generally, trees take 70–120 years to mature in boreal forests. Critics reply that stems that meet quality requirements are used to produce high-value products such as sawn wood and engineered wood products such as cross laminated timber, rather than low-value products such as wood pellets. In a different scenario where forests of this type is clear-cut and used 50/50 for bioenergy and solid wood products, and then subsequently replaced with short rotation forest, parity times varies between 17 and 114 years for the coal alternative scenario, with the shortest parity time achieved by the forest with the shortest rotation time and highest yield (10 years rotation time with a yield of 16 tonnes per hectare per year.) Parity times increased to between 20 and 145 years when compared to an oil-based electricity alternative case, and between 25 and 197 years when compared to a natural gas-based electricity alternative case. For an afforestation vs. fossil fuel mix scenario, a parity time of 0 years was reported. The authors note that these scenarios are "illustrative examples" and that "results are strongly influenced by the assumptions made." The authors assumed that residues were left un-collected on the forest floor, where they decay and therefore produce emissions. If these residues instead are collected and used for bioenergy, the parity times decrease by 100 years. The extra emissions produced by the longer supply routes for fossil fuels compared to wood fuel were not included in the calculation. Extra emissions from pests, windthrows and forest fires (normally expected to increase when unmanaged forests age), were also not included in the calculation. Market effects were not included. On the other hand, landscape level carbon accounting was used, and the assumed conversion efficiency for bioenergy and coal were the same. Like other scientists, the JRC staff note the high variability in carbon accounting results, and attribute this to different methodologies. In the studies examined, the JRC found carbon parity times of 0 to 400 years (see chart on the right) for stemwood harvested exclusively for bioenergy, depending on different characteristics and assumptions for both the forest/bioenergy system and the alternative fossil system, with the emission intensity of the displaced fossil fuels seen as the most important factor, followed by conversion efficiency and biomass growth rate/rotation time. Other factors relevant for the carbon parity time are the initial carbon stock and the existing harvest level; both higher initial carbon stock and higher harvest level means longer parity times. Liquid biofuels have high parity times because about half of the energy content of the biomass is lost in the processing. Climate impacts expressed as static numbers Net emissions from various biofuel pathways (heat production). Stippled lines show net emissions for EU coal, light fuel oil, most relevant fossil fuel alternative, and natural gas. Dotted areas show emission savings percentages compared to the most relevant fossil fuel alternative (white 70–80%, green 80–85%, blue 85–100%. Net emissions from various biofuel pathways (transportation). The stippled line show net emissions for the most relevant fossil fuel alternative. Dotted areas show emission savings percentages also compared to the most relevant fossil fuel alternative (white 50–60%, green 60–70%, blue 70–100%. Net emissions from various biofuel pathways (electricity production). Stippled lines show net emissions for EU coal (black), most relevant fossil fuel alternative (green), electricity mix (red) and natural gas (blue). Dotted areas show emission savings percentages compared to the most relevant fossil fuel alternative (white 70–80%, green 80–85%, blue 85–100%. Greenhouse gas emissions from wood pellet production and transport from the US to the EU (Hanssen et al. 2017). EU's Joint Research Centre has examined a number of bioenergy emission estimates found in literature, and calculated greenhouse gas savings percentages for bioenergy pathways in heat production, transportation fuel production and electricity production, based on those studies (see charts on the right). The calculations are based on the attributional LCA accounting principle. It includes all supply chain emissions, from raw material extraction, through energy and material production and manufacturing, to end-of-life treatment and final disposal. It also includes emissions related to the production of the fossil fuels used in the supply chain. It excludes emission/absorption effects that takes place outside its system boundaries, for instance market related, biogeophysical (e.g. albedo), and time-dependent effects. Because market related calculations are excluded, the results are only seen as valid for small-scale energy production. Also, the bioenergy pathways have typical small-scale conversion efficiencies. Solid biofuels for electricity production have 25% efficiency in most cases, and 21–34% in a few cases. Biogas for electricity production have 32–38%. Heat pathways have 76–85%. The forest residue category include logs and stumps, which increases carbon intensity especially in forests with slow decay rates. The charts have vertical bars that represent the emission range found for each bioenergy pathway (since emissions for the same pathway vary from study to study.) The higher end of the range represents emission levels found in studies that assume for instance long transport distances, low conversion efficiencies and no fossil fuel displacement effect. The lower end of the range represents emission levels found in studies that assume optimized logistics, higher conversion efficiencies, use of renewable energy to supply process-heat and process-electricity, and include displacement effects from the substitution of fossil fuels. The bars can be compared with emission levels associated with multiple alternative energy systems available in the EU. The dotted, coloured areas represent emission savings percentages for the pathways when compared to fossil fuel alternatives. The authors conclude that "[m]ost bio-based commodities release less GHG than fossil products along their supply chain; but the magnitude of GHG emissions vary greatly with logistics, type of feedstocks, land and ecosystem management, resource efficiency, and technology." Because of the varied climate mitigation potential for different biofuel pathways, governments and organizations set up different certification schemes to ensure that biomass use is sustainable, for instance the RED (Renewable Energy Directive) in the EU and the ISO standard 13065 by the International Organization for Standardization. In the US, the RFS (Renewables Fuel Standard) limit the use of traditional biofuels and defines the minimum life-cycle GHG emissions that are acceptable. Biofuels are considered traditional if they achieve up to 20% GHG emission reduction compared to the petrochemical equivalent, advanced if they save at least 50%, and cellulosic if the save more than 60%. Consistent with the charts, the EU's Renewable Energy Directive (RED) states that the typical greenhouse gas emissions savings when replacing fossil fuels with wood pellets from forest residues for heat production varies between 69% and 77%, depending on transport distance: When the distance is between 0 and 2500 km, emission savings is 77%. Emission savings drop to 75% when the distance is between 2500 and 10 000 km, and to 69% when the distance is above 10 000 km. When stemwood is used, emission savings varies between 70% and 77%, depending on transport distance. When wood industry residues are used, savings varies between 79% and 87%. Based on a similar methodology, Hanssen et al. found that greenhouse gas emissions savings from electricity production based on wood pellets produced in the US southeast and shipped to the EU, varies between 65% and 75%, compared to EU's fossil fuel mix. They estimate that average net GHG emission from wood pellets imported from the US and burnt for electricity in the EU amounts to approximately 0.2 kg CO2 equivalents per kWh, while average emissions from the mix of fossil fuels that is currently burnt for electricity in the EU amounts to 0.67 kg CO2-eq per kWh (see chart on the right). Ocean transport emissions amounts to 7% of the displaced fossil fuel mix emissions per produced kWh. Likewise, IEA Bioenergy estimates that in a scenario where Canadian wood pellets totally replace coal in a European coal plant, the ocean transport related emissions (for the distance Vancouver – Rotterdam) amounts to approximately 2% of the plant's total coal-related emissions. The lower percentage here is caused by the alternative scenario being a particular coal plant, not EU's fossil fuel mix. Cowie et al. argue that calculations from actual supply chains show low emissions from intercontinental biomass transport, for instance the optimized wood pellet supply chain from the southeastern USA to Europe. Lamers & Junginger argue that future EU import of wood pellets "[...] will likely continue to be dominated by North America, especially from the South-East USA [...]." In 2015, 77% of the imported pellets came from the USA. While regular forest stands have rotation times spanning decades, short rotation forestry (SRF) stands have a rotation time of 8–20 years, and short rotation coppicing (SRC) stands 2–4 years. 12% of the EU forests is coppice forests. Perennial grasses have a rotation time of one year in temperate areas, and 4–12 months in tropical areas. Food crops like wheat and maize also have rotation times of one year. Because short rotation energy crops only have managed to grow/accumulate carbon for a short amount of time before they are harvested, it is relatively easy to pay back the harvest-related carbon debt, provided that there is no additional large carbon debt from land use change to deal with (for instance created by clear-cutting a natural forest in order to use this land area for energy crops), and no better climate-related use for the areas in question. Schlamadinger & Marland write that "[...] short-rotation energy crops will provide much earlier and larger C [carbon] mitigation benefits if implemented on previously unforested land than if an initial forest is harvested to provide space for the plantation." EU's Joint Research Centre state: "In case that there is no raw material displacement from other sectors such as food, feed, fibers or changes in land carbon stocks due to direct or indirect land use change, the assumption of carbon neutrality can still be considered valid for annual crops, agriresidues, short-rotation coppices and energy grasses with short rotation cycles. This can also be valid for analysis with time horizons much longer than the feedstock growth cycles." Other researchers argue that the small carbon debts associated with energy crop harvests means short carbon payback and parity times, often less than a year. IRENA argues that short-rotation energy crops and agricultural residues are carbon neutral since they are harvested annually. IEA writes in its special report on how to reach net zero emissions in 2050 that the "[...] energy‐sector transformation in the NZE [Net Zero Emissions scenario) would reduce CO2 emissions from AFLOU [Agriculture, Forestry and Other Land Use] in 2050 by around 150 Mt CO2 given the switch away from conventional crops and the increase in short rotation advanced‐bioenergy crop production on marginal lands and pasture land." Since the long payback and parity times calculated for some forestry projects is seen as a non-issue for energy crops (except in the cases mentioned above), researchers instead calculate static climate mitigation potentials for these crops, using LCA-based carbon accounting methods. A particular energy crop-based bioenergy project is considered carbon positive, carbon neutral or carbon negative based on the total amount of CO2 equivalent emissions and absorptions accumulated throughout its entire lifetime: If emissions during agriculture, processing, transport and combustion are higher than what is absorbed (and stored) by the plants, both above and below ground, during the project's lifetime, the project is carbon positive. Likewise, if total absorption is higher than total emissions, the project is carbon negative. In other words, carbon negativity is possible when net carbon accumulation more than compensates for net lifecycle greenhouse gas emissions. Miscanthus × giganteus is a perennial energy grass. The most climate friendly energy crops seems to be perennial energy grasses, because of low energy inputs and large amounts of carbon stored in the soil. Researchers argue that the mean energy input/output ratios for the perennial crop miscanthus is 10 times better than for annual crops, and that greenhouse gas emissions are 20-30 times better than for fossil fuels. Miscanthus chips for heating saved 22.3 tonnes of CO2 emissions per hectare per year in the UK, while maize for heating and power saved 6.3. Rapeseed for biodiesel saved 3.2. Other researchers have similar conclusions. Typically, perennial crops sequester more carbon than annual crops because the root buildup is allowed to continue undisturbed over many years. Also, perennial crops avoid the yearly tillage procedures (plowing, digging) associated with growing annual crops. Tilling helps the soil microbe populations to decompose the available carbon, producing CO2. Soil organic carbon has been observed to be greater below switchgrass crops than under cultivated cropland, especially at depths below 30 cm (12 in). A meta-study of 138 individual studies, done by Harris et al., revealed that the perennial grasses miscanthus and switchgrass planted on arable land on average store five times more carbon in the ground than short rotation coppice or short rotation forestry plantations (poplar and willow). McCalmont et al. compared a number of individual European reports on Miscanthus × giganteus carbon sequestration, and found accumulation rates ranging from 0.42 to 3.8 tonnes per hectare per year, with a mean accumulation rate of 1.84 tonne, or 25% of total harvested carbon per year. Fundamentally, the below-ground carbon accumulation works as a greenhouse gas mitigation tool because it removes carbon from the above-ground carbon circulation (the circulation from plant to atmosphere and back into new plants.) The circulation is driven by photosynthesis and combustion: First, a plant absorbs CO2 and assimilates it as carbon in its tissue both above and below ground. When the above-ground carbon is harvested and then burned, the CO2 molecule is formed yet again and released back into the atmosphere. Then, an equivalent amount of CO2 is absorbed back by next season's growth, and the cycle repeats. Carbon negative (miscanthus) and carbon positive (poplar) production pathways. This above-ground circulation has the potential to be carbon neutral, but of course the human involvement in operating and guiding it means additional energy input, often coming from fossil sources. If the fossil energy spent on the operation is high compared to the amount of energy produced, the total CO2 footprint can approach, match or even exceed the CO2 footprint originating from burning fossil fuels exclusively, as has been shown to be the case for several first-generation biofuel projects. Transport fuels might be worse than solid fuels in this regard. The problem can be dealt with both from the perspective of increasing the amount of carbon that is stored below ground, and from the perspective of decreasing fossil fuel input to the above-ground operation. If enough carbon is stored below ground, it can compensate for the total lifecycle emissions of a particular biofuel. Likewise, if the above-ground emissions decreases, less below-ground carbon storage is needed for the biofuel to become carbon neutral or negative. Relationship between above-ground yield (diagonal lines), soil organic carbon (X axis), and soil's potential for successful/unsuccessful carbon sequestration (Y axis). Basically, the higher the yield, the more land is usable as a GHG mitigation tool (including relatively carbon-rich land). Whitaker et al. argue that a miscanthus crop with a yield of 10 tonnes per hectare per year store enough carbon to compensate for both agriculture, processing and transport related emissions. The chart on the right displays two carbon negative miscanthus production pathways, and two carbon positive poplar production pathways, represented in gram CO2-equivalents per megajoule. The bars are sequential and move up and down as atmospheric CO2 is estimated to increase and decrease. The grey/blue bars represent agriculture, processing and transport related emissions, the green bars represents soil carbon change, and the yellow diamonds represent total final emissions. The second chart displays the mean yields necessary to achieve long-term carbon negativity for soils with different amounts of existing carbon. The higher the yield, the more likely carbon negativity becomes. Other researchers make the same claim about carbon negativity for miscanthus in Germany, with a yield of 15 dry tonnes per hectare per year, and carbon storage of 1.1 tonnes per hectare per year. Successful storage is dependent on planting sites, as the best soils are those that are currently low in carbon. For the UK, successful storage is expected for arable land over most of England and Wales, with unsuccessful storage expected in parts of Scotland, due to already carbon rich soils (existing woodland). Also, for Scotland, the relatively lower yields in this colder climate makes carbon negativity harder to achieve. Soils already rich in carbon include peatland and mature forest. The most successful carbon storage in the UK takes place below improved grassland. However, since the carbon content of grasslands vary considerably, so does the success rate of land use changes from grasslands to perennial. Even though the net carbon storage below perennial energy crops like miscanthus and switchtgrass greatly exceeds the net carbon storage below regular grassland, forest and arable crops, the carbon input is simply too low to compensate for the loss of existing soil carbon during the early establishment phase. Over time however, soil carbon may increase, also for grassland. Researchers argue that after some initial discussion, there is now (2018) consensus in the scientific community that "[...] the GHG [greenhouse gas] balance of perennial bioenergy crop cultivation will often be favourable [...]", also when considering the implicit direct and indirect land use changes. References

Content removed about soil + carbon

I've removed this content because I felt it was digressing. Maybe it could be moved to carbon farming? What do you think, User:Lfstevens? EMsmile (talk) 12:09, 16 January 2023 (UTC) EMsmile (talk) 12:09, 16 January 2023 (UTC)

Don't see it belonging here. Possibly Carbon sequestration? — Preceding unsigned comment added by Lfstevens (talk • contribs)

Pinging User:ASRASR as they have worked on the carbon sequestration article. EMsmile (talk) 10:07, 17 January 2023 (UTC)

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Soil organic carbon has been observed to be greater below switchgrass crops than under cultivated cropland, especially at depths below 30 cm (12 in). A meta-study of 138 individual studies, done by Harris et al., revealed that the perennial grasses miscanthus and switchgrass planted on arable land on average store five times more carbon in the ground than short rotation coppice or short rotation forestry plantations (poplar and willow).

Fundamentally, the below-ground carbon accumulation works as a greenhouse gas mitigation tool because it removes carbon from the above-ground carbon circulation (the circulation from plant to atmosphere and back into new plants.) The circulation is driven by photosynthesis and combustion: First, a plant absorbs CO₂ and assimilates it as carbon in its tissue both above and below ground. When the above-ground carbon is harvested and then burned, the CO₂ molecule is formed yet again and released back into the atmosphere. Then, an equivalent amount of CO₂ is absorbed back by next season's growth, and the cycle repeats.

The problem can be dealt with both from the perspective of increasing the amount of carbon that is stored below ground, and from the perspective of decreasing fossil fuel input to the above-ground operation. If enough carbon is stored below ground, it can compensate for the total lifecycle emissions of a particular biofuel. Likewise, if the above-ground emissions decreases, less below-ground carbon storage is needed for the biofuel to become carbon neutral or negative.

Successful storage is dependent on planting sites, as the best soils are those that are currently low in carbon. For the UK, successful storage is expected for arable land over most of England and Wales, with unsuccessful storage expected in parts of Scotland, due to already carbon rich soils (existing woodland). Also, for Scotland, the relatively lower yields in this colder climate makes carbon negativity harder to achieve. Soils already rich in carbon include peatland and mature forest. The most successful carbon storage in the UK takes place below improved grassland. However, since the carbon content of grasslands vary considerably, so does the success rate of land use changes from grasslands to perennial. Even though the net carbon storage below perennial energy crops like miscanthus and switchtgrass greatly exceeds the net carbon storage below regular grassland, forest and arable crops, the carbon input is simply too low to compensate for the loss of existing soil carbon during the early establishment phase. Over time however, soil carbon may increase, also for grassland.

References

Removed "Further reading" list

I've removed the "further reading" list. These publications used to be in the sources for content that has in the meantime be removed. I don't think we need them anymore now. EMsmile (talk) 10:11, 17 January 2023 (UTC)

• Kahle, Petra; Beuch, Steffen; Boelcke, Barbara; Leinweber, Peter; Schulten, Hans-Rolf (November 2001). "Cropping of Miscanthus in Central Europe: biomass production and influence on nutrients and soil organic matter". European Journal of Agronomy. 15 (3): 171–184. doi:10.1016/S1161-0301(01)00102-2.
• Milner, Suzanne; Holland, Robert A.; Lovett, Andrew; Sunnenberg, Gilla; Hastings, Astley; Smith, Pete; Wang, Shifeng; Taylor, Gail (March 2016). "Potential impacts on ecosystem services of land use transitions to second-generation bioenergy crops in GB". GCB Bioenergy. 8 (2): 317–333. doi:10.1111/gcbb.12263. PMC 4974899. PMID 27547244.
• Harris, Z.M.; Spake, R.; Taylor, G. (November 2015). "Land use change to bioenergy: A meta-analysis of soil carbon and GHG emissions". Biomass and Bioenergy. 82: 27–39. doi:10.1016/j.biombioe.2015.05.008.
• Anderson, Eric; Arundale, Rebecca; Maughan, Matthew; Oladeinde, Adebosola; Wycislo, Andrew; Voigt, Thomas (9 April 2014). "Growth and agronomy of Miscanthus x giganteus for biomass production". Biofuels. 2 (1): 71–87. doi:10.4155/bfs.10.80.
• Felten, Daniel; Emmerling, Christoph (October 2012). "Accumulation of Miscanthus‐derived carbon in soils in relation to soil depth and duration of land use under commercial farming conditions". Journal of Plant Nutrition and Soil Science. 175 (5): 661–670. doi:10.1002/jpln.201100250.
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Wiki Education assignment: Plant Ecology Winter 2023

This article was the subject of a Wiki Education Foundation-supported course assignment, between 16 January 2023 and 10 April 2023. Further details are available on the course page. Student editor(s): Zenturaa (article contribs).

— Assignment last updated by Zenturaa (talk) 22:03, 24 February 2023 (UTC)

Radical drop in reader interest after article cleanup

I compared page views for the old Biomass article and the updated version between March 01 and May 27 for both last year and this year. Reader interest has dropped 72% on average for this three month time period (956 pageviews per day on average last year for the original Biomass article, 267 pageviews per day on average this year for the new Biomass (energy) article).

Reader interest for the new Biomass (energy) and the new Bioenergy article combined has dropped 51% (433 daily pageviews for both articles combined this year, compared to 956 daily pageviews for the original Biomass article.)

The Biomass (ecology) page has unchanged reader interest; 216 daily views last year vs 211 this year (same time period as above.) Even if these pageviews are subtracted from the original Biomass article (assuming that all the Biomass (ecology) readers mistakenly opened the Biomass page first and therefore helped it score higher than it actually deserved), we get a 42% drop (740 pageviews for the original Biomass page vs 433 for the now split up Biomass (energy) and Bioenergy pages.)

In light of this rather harsh judgment from the people the article is meant to serve, is it perhaps time to become more pragmatic regarding your criticism of the old version? You know, about it being way too complicated and essay-like and long-winded for instance, with way too long footnotes? Yes, with its form and length it pushed against some general rules of thumb, but the readers clearly doesn't seem to care. It seems they agree with my earlier argument that the biomass debate is so complicated that it warrants a lengthy and dense article.

link to pageview resource The Perennial Hugger (talk) 18:13, 27 May 2023 (UTC)

I propose to wait and see a little longer, but if reader interest does not seriously pick up, we should revert back to the old version (update: too radical, we should revert back to a "long" version), and possibly also system, where bioenergy is forwarded to biomass and biomass (ecology) is linked to from the top of the biomass page. The Perennial Hugger (talk) 08:54, 29 May 2023 (UTC)

No. This isn't a popularity contest and the idea that we would tweak content to increase pageviews (correlation vs causality issues aside) has no basis in policy. VQuakr (talk) 20:16, 31 May 2023 (UTC)

What I mean is that the article should be written so that it is of interest to the general public. Don't misrepresent what I'm saying. The Perennial Hugger (talk) 20:27, 31 May 2023 (UTC)

No misrepresentation. We just don't and won't use pageviews to inform article content. VQuakr (talk) 21:45, 31 May 2023 (UTC)

I'm not saying that the readers should be able to "vote" about what content we put in an article. But reader interest should not be totallly irrelevant either. It should for instance be of relevance when we assess the consequences of a radical article change; was this beneficial to the readers or not? I agree with WP:COMMONSENSE which says: "Our goal is to improve Wikipedia so that it better informs readers. [...] The principle of the rules—to make Wikipedia and its sister projects thrive—is more important than the letter." So my argument is basically this: When reader interest drop after following article rules more to the letter, the rules are undermining the goal of the rules, which is to inform readers and help Wikipedia thrive. (Yes, you can technically argue that the interest drop is not caused by the recent radical article change but something unknown, but do you really want to go there?) The Perennial Hugger (talk) 07:54, 1 June 2023 (UTC)

I understand the argument, and there is no way I know to be clearer that we're not doing this. The only circumstance that would result in a rollback of article content would be consensus on the talk page to do so, and such a consensus would be grounded in policy not a new criterion you made up one day. VQuakr (talk) 16:21, 1 June 2023 (UTC)

There are many factors other than article quality that influence traffic. FWIW, traffic to Biomass fluctuates greatly and has seen a general downward trend in the past few years: https://pageviews.wmcloud.org/?project=wiki.riteme.site&platform=all-access&agent=user&redirects=0&start=2018-01&end=2023-04&pages=Biomass_(energy)%7CBiomass Clayoquot (talk | contribs) 20:11, 1 June 2023 (UTC)

I do not suggest an actual rollback. Regarding traffic, it follows seasons, with peaks in the spring and in the autumn. That's why I chose to compare to the same period one year ago. There is a slight decline from 2018, but a very steep decline from january 2023. The Perennial Hugger (talk) 08:41, 5 June 2023 (UTC)

I disagree with The Perennial Hugger, and agree with User:Clayoquot and User:VQuakr. Pageviews are an interesting statistic but they tell us very little about article quality. They can be influenced by all sorts of things. Also, you don't know if the people who have viewed an article have actually understood / liked/ benefitted from reading that article. You don't know if they've spent 10 seconds on it or 10 minutes.

If there are specific suggestions on how to improve this article and also the bioenergy article, I would be interested to hear them. I have asked on both talk pages before about help with improving them further but it's not easy to find suitably qualified people who have time & energy and who can write in an encyclopedic fashion (I currently don't have the time to immerse myself in the relevant literature). The old version that you are referring to was - in my opinion - much worse than the current version and I think we've spent ample and sufficient time on the talk pages to go through all of the issues. Reverting back or just "making it longer" is not the solution. EMsmile (talk) 21:16, 12 June 2023 (UTC)