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References

1. Akhtar, Krepl & Ivanova 2018.
2. Liu et al. 2011.
3. Conversion technologies . Biomassenergycentre.org.uk. Retrieved on 2012-02-28. http://www.biomassenergycentre.org.uk/portal/page?_pageid=75,15179&_dad=portal&_schema=PORTAL
4. "Biochemical Conversion of Biomass" (in en-US). BioEnergy Consult. 2014-05-29. http://www.bioenergyconsult.com/biochemical-conversion-technologies/. 
5. Pishvaee, Mohseni & Bairamzadeh 2021, pp. 1–20.
6. Smil 2015, pp. 26-27, 211, box 7.1.
7. Van Zalk, John; Behrens, Paul (2018-12-01). "The spatial extent of renewable and non-renewable power generation: A review and meta-analysis of power densities and their application in the U.S." (in en). Energy Policy 123: 86. doi:10.1016/j.enpol.2018.08.023. ISSN 0301-4215.  https://dx.doi.org/10.1016%2Fj.enpol.2018.08.023
8. Smil 2015, p. 170.
9. Smil 2015, p. 2095 (kindle location).
10. Smil 2015, p. 228.
11. Smil 2015, p. 89.
12. Smil 2015, p. 91.
13. Smil 2015, p. 227.
14. Smil 2015, p. 90.
15. Smil 2015, p. 229.
16. Smil 2015, pp. 80, 89.
17. Schwarz 1993, p. 413.
18. Flores et al. 2012, p. 831.
19. Ghose 2011, p. 263.
20. Cf. Smil's estimate of 0.60 W/m2 for the 10 t/ha yield above. The calculation is: Yield (t/ha) multiplied with energy content (GJ/t) divided by seconds in a year (31 556 926) multiplied with the number of square metres in one hectare (10 000).
21. Smil 2015, p. 85.
22. Smil 2015, p. 86.
23. For yield estimates see FAO's "The global outlook for future wood supply from forest plantations", section 2.7.2 – 2.7.3. Scot's pine, native to Europe and northern Asia, weighs 390 kg/m3 oven dry (moisture content 0%). The oven dry weight of eucalyptus species commonly grown in plantations in South America is 487 kg/m3 (average of Lyptus, Rose Gum and Deglupta). The average weight of poplar species commonly grown in plantations in Europe is 335 kg/m3 (average of White Poplar and Black Poplar. http://www.fao.org/3/X8423E/X8423E08.htm#TopOfPage
24. Smil 2008, p. 75-76.
25. IPCC 2019f, p. 4.34 – 4.41.
26. "The raw material for wood pellets is woody biomass in accordance with Table 1 of ISO 17225‑1. Pellets are usually manufactured in a die, with total moisture content usually less than 10 % of their mass on wet basis." ISO (International Organization for Standardization) 2014a.
27. "The raw material for non-woody pellets can be herbaceous biomass, fruit biomass, aquatic biomass or biomass blends and mixtures. These blends and mixtures can also include woody biomass. They are usually manufactured in a die with total moisture content usually less than 15 % of their mass." ISO (International Organization for Standardization) 2014b.
28. Transmission loss data from the World Bank, sourced from IEA. The World Bank 2010.
29. van den Broek 1996, p. 271.
30. Additionally, Smil estimates that newly installed photovoltaic solar parks reaches 7–11 W/m2 in sunny regions of the world. Smil 2015, p. 191.
31. Hanssen et al. 2017, p. 3 (Figure S3 in the Supporting Information document, link to document available at the bottom of the article).
32. IEA 2020.
33. The estimates are for the "medium case" considered (case 2a); a pellet mill that uses wood for processing heat, but sources electricity from the grid. Estimates (for forest residue based pellets) reduce to 50–58% when fossil fuels is used for processing heat (case 1), but increase to 84-92% when electricity is sourced from a CHP biomass power plant (case 3a). See EUR-Lex 2018, p. Annex VI.
34. "[...] GHG emission reductions of wood-pellet electricity compared to fossil EU grid electricity are 71% (for small roundwood and harvest residues), 69% (for commercial thinnings) or 65% (for mill residues), as shown in more detail in Fig. S3. The GHG reduction percentage of wood-pellet electricity from mill residues was [...] 75% [...]." Hanssen et al. 2017, pp. 1415-1416.
35. Hanssen et al. 2017, pp. 3-4 (Figure S3 and Table S1 in the Supporting Information document, link to document available at the bottom of the article).
36. IEA Bioenergy 2006, pp. 1, 4 (table 4).
37. See EPA 2020, p. 1. The emission factors are based on the higher heating value (HHV) of the different fuels. The HHV value reflects the actual chemical energy stored in the fuel, without taking moisture content into consideration. The fuel’s lower heating value (LHV) is the energy that remains after the necessary amount of energy has been spent to vaporize the fuel’s moisture (so that the fuel is able to reach the ignition point).
38. Chatham House 2017, p. 2.
39. IEA Bioenergy 2019, p. 3.
40. See FutureMetrics 2015a, pp. 1–2. Chatham House notes that modern CHP plants (Combined Heat and Power) achieve much higher efficiencies, above 80%, for both fossil fuels and biomass. Chatham House 2017, p. 16.
41. FutureMetrics 2012, p. 2.
42. ISO (International Organization for Standardization) 2014.
43. Indiana Center for Coal Technology Research 2008, p. 13.
44. "EURACOAL statistics". 2019. https://euracoal.eu/info/euracoal-eu-statistics/. 
45. The Manomet Center for Conservation Sciences 2010, p. 103-104.
46. The individual emission rates are: Wood 112 000 kg CO2eq per TJ, anthracite 98 300, coking coal 94 600, other bituminous 94 600, sub-bituminous 96 100, lignite 101 000. IPCC 2006a, pp. 2.16–2.17.
47. IPCC 2019a, p. 368.
48. IEA Bioenergy 2019, p. 4.
49. IPCC 2019a, p. 351.
50. IPCC 2019a, p. 348.
51. Reid Miner 2010, p. 39–40.
52. FAO 2020, p. 16, 52.
53. «The trends of productivity shown by several remote-sensing studies (see previous section) are largely consistent with mapping of forest cover and change using a 34-year time series of coarse resolution satellite data (NOAA AVHRR) (Song et al. 2018). This study, based on a thematic classification of satellite data, suggests that (i) global tree canopy cover increased by 2.24 million km² between 1982 and 2016 (corresponding to +7.1%) but with regional differences that contribute a net loss in the tropics and a net gain at higher latitudes, and (ii) the fraction of bare ground decreased by 1.16 million km² (corresponding to –3.1%), mainly in agricultural regions of Asia (Song et al. 2018), see Figure 4.5. Other tree or land cover datasets show opposite global net trends (Li et al. 2018b), but high agreement in terms of net losses in the tropics and large net gains in the temperate and boreal zones (Li et al. 2018b; Song et al. 2018; Hansen et al. 2013).» IPCC 2019a, p. 367.
54. IPCC 2019a, p. 385.
55. EASAC 2017, p. 33.
56. EASAC 2017, p. 1.
57. Chatham House 2017, p. 3.
58. Stephenson et al. 2014.
59. Stephenson et al. continue: «Second, our findings are similarly compatible with the well-known age-related decline in productivity at the scale of even-aged forest stands. […] We highlight the fact that increasing individual tree growth rate does not automatically result in increasing stand productivity because tree mortality can drive orders-of-magnitude reductions in population density. That is, even though the large trees in older, even-aged stands may be growing more rapidly, such stands have fewer trees. Tree population dynamics, especially mortality, can thus be a significant contributor to declining productivity at the scale of the forest stand. Stephenson et al. 2014, p. 92.
60. IPCC 2019b, p. B.1.4.
61. IPCC 2019a, p. 386.
62. IPCC 2019f, p. 4.6.
63. Reid Miner 2010, p. 39.
64. IEA Bioenergy 2019, p. 4–5.
65. IPCC 2019b.
66. NAUFRP 2014, p. 2.
67. Favero, Daigneault & Sohngen 2020, p. 6.
68. According to FAO, tree cover in Australia is increasing, but carbon stock is only provided for Oceania as a whole. FAO 2020, p. 136.
69. Wood chips, mainly used in the paper industry, have similar data; Europe (including Russia) produced 33% and North America 22%, while forest carbon stock increased in both areas. West, Central and East Asia combined produced 18%, and the forest carbon stock in this areas increased from 31.3 to 43.3 Gt. Wood chips production in the areas of the world were carbon stock is decreasing, was 26.9% in 2019. For wood pellet and wood chips production data, see FAOSTAT 2020. For carbon stock data, see FAO 2020, p. 52, table 43.
70. Chatham House 2017, p. 7.
71. «The potentially very long payback periods for forest biomass raise important issues given the UNFCCC’s aspiration of limiting warming to 1.5 °C above preindustrial levels to ‘significantly reduce the risks and impacts of climate change’. On current trends, this may be exceeded in around a decade. Relying on forest biomass for the EU’s renewable energy, with its associated initial increase in atmospheric carbon dioxide levels, increases the risk of overshooting the 1.5°C target if payback periods are longer than this. The European Commission should consider the extent to which large-scale forest biomass energy use is compatible with UNFCCC targets and whether a maximum allowable payback period should be set in its sustainability criteria.» EASAC 2017, p. 34.
72. EASAC 2017, p. 23, 26, 35.
73. «Some have argued that the length of the carbon payback period does not matter as long as all emissions are eventually absorbed. This ignores the potential impact in the short term on climate tipping points (a concept for which there is some evidence) and on the world’s ability to meet the target set in the 2015 Paris Agreement to limit temperature increase to 1.5°C above pre-industrial levels, which requires greenhouse gas emissions to peak in the near term. This suggests that only biomass energy with the shortest carbon payback periods should be eligible for financial and regulatory support.» EASAC 2017, p. 4.
74. Chatham House 2017, p. 21–22.
75. FutureMetrics 2016, p. 5–9.
76. «In many locations sawmill residuals from structural lumber production are abundant and they supply much of the raw material needed to produce wood pellets. In other locations, there are insufficient sawmill residuals. In those locations, the pellet mills, just like the pulp mills, use the non-sawlog portions of the tree.» FutureMetrics 2017, p. 8.
77. Chatham House 2017, p. 19.
78. Chatham House 2017, p. 68.
79. «Harvesting immediately reduces the standing forest carbon stock compared with less (or no) harvesting (Bellassen and Luyssaert, 2014; Sievänen et al., 2014) and it may take from decades to centuries until regrowth restores carbon stocks to their former level—especially if oldgrowth forests are harvested.» EASAC 2017, p. 21.
80. «Following this argument, the carbon dioxide (and other greenhouse gases) released by the burning of woody biomass for energy, along with their associated life-cycle emissions, create what is termed a ‘carbon debt’ – i.e. the additional emissions caused by burning biomass instead of the fossil fuels it replaces, plus the emissions absorption foregone from the harvesting of the forests. Over time, regrowth of the harvested forest removes this carbon from the atmosphere, reducing the carbon debt. The period until carbon parity is achieved (i.e. the point at which the net cumulative emissions from biomass use are equivalent to those from a fossil fuel plant generating the same amount of energy) is usually termed the ‘carbon payback period’. After this point, as regrowth continues biomass may begin to yield ‘carbon dividends’ in the form of atmospheric greenhouse gas levels lower than would have occurred if fossil fuels had been used. Eventually carbon levels in the forest return to the level at which they would have been if they had been left unharvested. (Some of the literature employs the term ‘carbon payback period’ to describe this longer period, but it is more commonly used to mean the time to parity with fossil fuels; this meaning is used in this paper.)» Chatham House 2017, p. 27.
81. «There is no such thing as a carbon debt if the stock of carbon held in the forest [is] not reduced.» FutureMetrics 2017, p. 7.
82. FutureMetrics 2011a, p. 5.
83. John Gunn 2011.
84. Hanssen et al. 2017, p. 1416.
85. «It has been argued that carbon balances should not be assessed at the stand level since at landscape level depletion of carbon in one stand may be compensated by growth in a stand elsewhere. For scientific analysis of the impact on climate forcing, however, it is necessary to compare the effects of various bioenergy harvest options against a baseline of no bioenergy harvest (or other credible counterfactual scenarios) for the same area of forest. Such studies provide information on the impacts of changes at the stand level, which can then be integrated with other factors (economic, regulatory and social) that may influence effects at landscape level.» EASAC 2017, p. 23.
86. «It is important to realize that our 3650 ton per year CHP plant does not receive 3650 tons in one delivery and does not release 3650 tons of wood’s worth of carbon in one lump either. In fact, the forest products industry can be characterized as a just-in-time manufacturing system. For our CHP plant, 10 tons per day are sustainably harvested and delivered off of our 3650 acre FSC or SFI certified forest. So the carbon released into the atmosphere that day is from 10 tons of wood. The atmosphere “sees” new carbon. But during that same day on our 3650 acre plot, 10 new tons of wood grow and sequester the amount of carbon that was just released.» FutureMetrics 2011b, p. 2.
87. «Forests are generally managed as a series of stands of different ages, harvested at different times, to produce a constant supply of wood products. When considered at plot level, long-rotation forests take many years to regrow after harvest, and the EASAC statement indicates this as a time gap between releasing forest carbon and its reabsorption from the atmosphere. However, across the whole forest estate or landscape, the temporal fluctuations are evened out since other stands continue to grow and sequester carbon, making the time gap as indicated by EASAC less relevant. If annual harvest does not exceed the annual growth in the forest, there is no net reduction in forest carbon.» IEA Bioenergy 2019: «The use of forest biomass for climate change mitigation: response to statements of EASAC» IEA Bioenergy 2019, p. 2.
88. IPCC 2007, p. 549.
89. «The natural disturbance component is subtracted from the total estimate of […] emissions and removals, yielding an estimate of the emissions and removals associated with human activity on managed land.» See IPCC 2019c, p. 2.72. «The 2006 IPCC Guidelines are designed to assist in estimating and reporting national inventories of anthropogenic greenhouse gas emissions and removals. For the AFOLU Sector, anthropogenic greenhouse gas emissions and removals by sinks are defined as all those occurring on ‘managed land’. Managed land is land where human interventions and practices have been applied to perform production, ecological or social functions. [...] This approach, i.e., the use of managed land as a proxy for anthropogenic effects, was adopted in the GPG–LULUCF and that use is maintained in the present guidelines. The key rationale for this approach is that the preponderance of anthropogenic effects occurs on managed lands. By definition, all direct human-induced effects on greenhouse gas emissions and removals occur on managed lands only. While it is recognized that no area of the Earth’s surface is entirely free of human influence (e.g., CO2 fertilization), many indirect human influences on greenhouse gases (e.g., increased N deposition, accidental fire) will be manifested predominately on managed lands, where human activities are concentrated. Finally, while local and short-term variability in emissions and removals due to natural causes can be substantial (e.g., emissions from fire, see footnote 1), the natural ‘background’ of greenhouse gas emissions and removals by sinks tends to average out over time and space. This leaves the greenhouse gas emissions and removals from managed lands as the dominant result of human activity. Guidance and methods for estimating greenhouse gas emissions and removals for the AFOLU Sector now include: • CO2 emissions and removals resulting from C stock changes in biomass, dead organic matter and mineral soils, for all managed lands; • CO2 and non-CO2 emissions from fire on all managed land; • N2O emissions from all managed soils; • CO2 emissions associated with liming and urea application to managed soils; • CH4 emissions from rice cultivation; • CO2 and N2O emissions from cultivated organic soils; • CO2 and N2O emissions from managed wetlands (with a basis for methodological development for CH4 emissions from flooded land in an Appendix 3); • CH4 emission from livestock (enteric fermentation); • CH4 and N2O emissions from manure management systems; and • C stock change associated with harvested wood products.» See IPCC 2006b, p. 1.5.
90. IPCC 2019c, p. 2.67.
91. Hanssen et al. 2017, pp. 1408–1410.
92. IPCC 2019d, p. 194.
93. IPCC 2019b, p. B 7.4.
94. «For example, limiting deployment of a mitigation response option will either result in increased climate change or additional mitigation in other sectors. A number of studies have examined limiting bioenergy and BECCS. Some such studies show increased emissions (Reilly et al. 2012). Other studies meet the same climate goal, but reduce emissions elsewhere via reduced energy demand (Grubler et al. 2018; Van Vuuren et al. 2018), increased fossil carbon capture and storage (CCS), nuclear energy, energy efficiency and/or renewable energy (Van Vuuren et al. 2018; Rose et al. 2014; Calvin et al. 2014; Van Vuuren et al. 2017b), dietary change (Van Vuuren et al. 2018), reduced non-CO2 emissions (Van Vuuren et al. 2018), or lower population (Van Vuuren et al. 2018).» IPCC 2019e, p. 637.
95. «Limitations on bioenergy and BECCS can result in increases in the cost of mitigation (Kriegler et al. 2014; Edmonds et al. 2013). Studies have also examined limiting CDR, including reforestation, afforestation, and bioenergy and BECCS (Kriegler et al. 2018a,b). These studies find that limiting CDR can increase mitigation costs, increase food prices, and even preclude limiting warming to less than 1.5°C above pre-industrial levels (Kriegler et al. 2018a,b; Muratori et al. 2016).» IPCC 2019e, p. 638.
96. IEA 2017.
97. "Bioenergy has an essential and major role to play in a low-carbon energy system. For instance, modern bioenergy in final global energy consumption should increase four-fold by 2060 in the IEA's 2°C scenario (2DS), which seeks to limit global average temperatures from rising more than 2°C by 2100 to avoid some of the worst effects of climate change. It plays a particularly important role in the transport sector where it helps to decarbonize long-haul transport (aviation, marine and long-haul road freight), with a ten-fold increase in final energy demand from today’s 3 EJ to nearly 30 EJ. Bioenergy is responsible for nearly 20% of the additional carbon savings needed in the 2DS compared to an emissions trajectory based on meeting existing and announced policies. But the current rate of bioenergy deployment is well below these 2DS levels. In the transport sector, biofuel consumption must triple by 2030, with two-thirds of that coming from advanced biofuels. That means scaling up current advanced biofuels production by at least 50 times to keep pace with the 2DS requirements by 2030. In scenarios with more ambitious carbon reduction objectives, such as the IEA’s Beyond 2 Degree Scenario (B2DS), bioenergy linked to carbon capture and storage also becomes necessary. [...] The roadmap also points out the need for a five-fold increase in sustainable bioenergy feedstock supply, much of which can be obtained from mobilising the potential of wastes and residues." IEA 2017a.
98. NAUFRP 2014, p. 1–2.
99. «Bioenergy from dedicated crops are in some cases held responsible for GHG emissions resulting from indirect land use change (iLUC), that is the bioenergy activity may lead to displacement of agricultural or forest activities into other locations, driven by market-mediated effects. Other mitigation options may also cause iLUC. At a global level of analysis, indirect effects are not relevant because all land-use emissions are direct. iLUC emissions are potentially more significant for crop-based feedstocks such as corn, wheat and soybean, than for advanced biofuels from lignocellulosic materials (Chum et al. 2011; Wicke et al. 2012; Valin et al. 2015; Ahlgren and Di Lucia 2014). Estimates of emissions from iLUC are inherently uncertain, widely debated in the scientific community and are highly dependent on modelling assumptions, such as supply/demand elasticities, productivity estimates, incorporation or exclusion of emission credits for coproducts and scale of biofuel deployment (Rajagopal and Plevin 2013; Finkbeiner 2014; Kim et al. 2014; Zilberman 2017). In some cases, iLUC effects are estimated to result in emission reductions. For example, market-mediated effects of bioenergy in North America showed potential for increased carbon stocks by inducing conversion of pasture or marginal land to forestland (Cintas et al. 2017; Duden et al. 2017; Dale et al. 2017; Baker et al. 2019). There is a wide range of variability in iLUC values for different types of biofuels, from –75–55 gCO2 MJ–1 (Ahlgren and Di Lucia 2014; Valin et al. 2015; Plevin et al. 2015; Taheripour and Tyner 2013; Bento and Klotz 2014). There is low confidence in attribution of emissions from iLUC to bioenergy.» IPCC 2019c.
100. "The environmental costs and benefits of bioenergy have been the subject of significant debate, particularly for first‐generation biofuels produced from food (e.g. grain and oil seed). Studies have reported life‐cycle GHG savings ranging from an 86% reduction to a 93% increase in GHG emissions compared with fossil fuels (Searchinger et al., 2008; Davis et al., 2009; Liska et al., 2009; Whitaker et al., 2010). In addition, concerns have been raised that N2O emissions from biofuel feedstock cultivation could have been underestimated (Crutzen et al., 2008; Smith & Searchinger, 2012) and that expansion of feedstock cultivation on agricultural land might displace food production onto land with high carbon stocks or high conservation value (i.e. iLUC) creating a carbon debt which could take decades to repay (Fargione et al., 2008). Other studies have shown that direct nitrogen‐related emissions from annual crop feedstocks can be mitigated through optimized management practices (Davis et al., 2013) or that payback times are less significant than proposed (Mello et al., 2014). However, there are still significant concerns over the impacts of iLUC, despite policy developments aimed at reducing the risk of iLUC occurring (Ahlgren & Di Lucia, 2014; Del Grosso et al., 2014)." Whitaker et al. 2018, p. 151.
101. "The impact of growing bioenergy and biofuel feedstock crops has been of particular concern, with some suggesting the greenhouse gas (GHG) balance of food crops used for ethanol and biodiesel may be no better or worse than fossil fuels (Fargione et al., 2008; Searchinger et al., 2008). This is controversial, as the allocation of GHG emissions to the management and the use of coproducts can have a large effect on the total carbon footprint of resulting bioenergy products (Whitaker et al., 2010; Davis et al., 2013). The potential consequences of land use change (LUC) to bioenergy on GHG balance through food crop displacement or 'indirect' land use change (iLUC) are also an important consideration (Searchinger et al., 2008)." Milner et al. 2016, pp. 317–318.
102. "While the initial premise regarding bioenergy was that carbon recently captured from the atmosphere into plants would deliver an immediate reduction in GHG emission from fossil fuel use, the reality proved less straightforward. Studies suggested that GHG emission from energy crop production and land-use change might outweigh any CO2 mitigation (Searchinger et al., 2008; Lange, 2011). Nitrous oxide (N2O) production, with its powerful global warming potential (GWP), could be a significant factor in offsetting CO2 gains (Crutzen et al., 2008) as well as possible acidification and eutrophication of the surrounding environment (Kim & Dale, 2005). However, not all biomass feedstocks are equal, and most studies critical of bioenergy production are concerned with biofuels produced from annual food crops at high fertilizer cost, sometimes using land cleared from natural ecosystems or in direct competition with food production (Naik et al., 2010). Dedicated perennial energy crops, produced on existing, lower grade, agricultural land, offer a sustainable alternative with significant savings in greenhouse gas emissions and soil carbon sequestration when produced with appropriate management (Crutzen et al., 2008; Hastings et al., 2008, 2012; Cherubini et al., 2009; Dondini et al., 2009a; Don et al., 2012; Zatta et al., 2014; Richter et al., 2015)." McCalmont et al. 2017, p. 490.
103. "Significant reductions in GHG emissions have been demonstrated in many LCA studies across a range of bioenergy technologies and scales (Thornley et al., 2009, 2015). The most significant reductions have been noted for heat and power cases. However, some other studies (particularly on transport fuels) have indicated the opposite, that is that bioenergy systems can increase GHG emissions (Smith & Searchinger, 2012) or fail to achieve increasingly stringent GHG savings thresholds. A number of factors drive this variability in calculated savings, but we know that where significant reductions are not achieved or wide variability is reported there is often associated data uncertainty or variations in the LCA methodology applied (Rowe et al., 2011). For example, data uncertainty in soil carbon stock change following LUC has been shown to significantly influence the GHG intensity of biofuel production pathways (Fig. 3), whilst the shorter term radiative forcing impact of black carbon particles from the combustion of biomass and biofuels also represents significant data uncertainty (Bond et al., 2013)." Whitaker et al. 2018, pp. 156–157.
104. "Biomass explained". U.S. Energy Information Administration Federal Statistical System of the United States. 25 October 2019. https://www.eia.gov/energyexplained/biomass/biomass-and-the-environment.php#:~:text=Burning%20either%20fossil%20fuels%20or,a%20carbon%2Dneutral%20energy%20source.. 
105. "Short rotation forestry". 2018-05-29. http://www.forestresearch.gov.uk/tools-and-resources/biomass-energy-resources/fuel/energy-crops/short-rotation-forestry/. 
106. "Soil carbon stocks are a balance between the soil organic matter decomposition rate and the organic material input each year by vegetation, animal manure, or any other organic input." McCalmont et al. 2017, p. 496.
107. "Any soil disturbance, such as ploughing and cultivation, is likely to result in short-term respiration losses of soil organic carbon, decomposed by stimulated soil microbe populations (Cheng, 2009; Kuzyakov, 2010). Annual disturbance under arable cropping repeats this year after year resulting in reduced SOC levels. Perennial agricultural systems, such as grassland, have time to replace their infrequent disturbance losses which can result in higher steady-state soil carbon contents (Gelfand et al., 2011; Zenone et al., 2013)." McCalmont et al. 2017, p. 493.
108. "Tillage breaks apart soil aggregates which, among other functions, are thought to inhibit soil bacteria, fungi and other microbes from consuming and decomposing SOM (Grandy and Neff 2008). Aggregates reduce microbial access to organic matter by restricting physical access to mineral-stabilised organic compounds as well as reducing oxygen availability (Cotrufo et al. 2015; Lehmann and Kleber 2015). When soil aggregates are broken open with tillage in the conversion of native ecosystems to agriculture, microbial consumption of SOC and subsequent respiration of CO2 increase dramatically, reducing soil carbon stocks (Grandy and Robertson 2006; Grandy and Neff 2008)." IPCC 2019a, p. 393.
109. Soil Carbon under Switchgrass Stands and Cultivated Cropland (Interpretive Summary and Technical Abstract). USDA Agricultural Research Service, April 1, 2005 http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=164741,
110. "A systematic review and meta-analysis were used to assess the current state of knowledge and quantify the effects of land use change (LUC) to second generation (2G), non-food bioenergy crops on soil organic carbon (SOC) and greenhouse gas (GHG) emissions of relevance to temperate zone agriculture. Following analysis from 138 original studies, transitions from arable to short rotation coppice (SRC, poplar or willow) or perennial grasses (mostly Miscanthus or switchgrass) resulted in increased SOC (+5.0 ± 7.8% and +25.7 ± 6.7% respectively)." Harris, Spake & Taylor 2015, p. 27.
111. "[...] it seems likely that arable land converted to Miscanthus will sequester soil carbon; of the 14 comparisons, 11 showed overall increases in SOC over their total sample depths with suggested accumulation rates ranging from 0.42 to 3.8 Mg C ha−1 yr−1. Only three arable comparisons showed lower SOC stocks under Miscanthus, and these suggested insignificant losses between 0.1 and 0.26 Mg ha−1 yr−1." McCalmont et al. 2017, p. 493.
112. "The correlation between plantation age and SOC can be seen in Fig. 6, [...] the trendline suggests a net accumulation rate of 1.84 Mg C ha−1 yr−1 with similar levels to grassland at equilibrium." McCalmont et al. 2017, p. 496.
113. Given the EU average peak yield of 22 tonnes dry matter per hectare per year (approximately 15 tonnes during spring harvest). See Anderson et al. 2014, p. 79). 15 tonnes also explicitly quoted as the mean spring yield in Germany, see Felten & Emmerling 2012, p. 662. 48% carbon content; see Kahle et al. 2001, table 3, page 176.
114. "Our work shows that crop establishment, yield and harvesting method affect the C. cost of Miscanthus solid fuel which for baled harvesting is 0.4 g CO2 eq. C MJ−1 for rhizome establishment and 0.74 g CO2 eq. C MJ−1 for seed plug establishment. If the harvested biomass is chipped and pelletized, then the emissions rise to 1.2 and 1.6 g CO2 eq. C MJ−1, respectively. The energy requirements for harvesting and chipping from this study that were used to estimate the GHG emissions are in line with the findings of Meehan et al. (2013). These estimates of GHG emissions for Miscanthus fuel confirm the findings of other life-cycle assessment (LCA) studies (e.g., Styles and Jones, 2008) and spatial estimates of GHG savings using Miscanthus fuel (Hastings et al., 2009). They also confirm that Miscanthus has a comparatively small GHG footprint due to its perennial nature, nutrient recycling efficiency and need for less chemical input and soil tillage over its 20-year life-cycle than annual crops (Heaton et al., 2004, 2008; Clifton-Brown et al., 2008; Gelfand et al., 2013; McCalmont et al., 2015a; Milner et al., 2015). In this analysis, we did not consider the GHG flux of soil which was shown to sequester on average in the United Kingdom 0.5 g of C per MJ of Miscanthus derived fuel by McCalmont et al. (2015a). Changes in SOC resulting from the cultivation of Miscanthus depend on the previous land use and associated initial SOC. If high carbon soils such as peatland, permanent grassland, and mature forest are avoided and only arable and rotational grassland with mineral soil is used for Miscanthus then the mean increase in SOC for the first 20-year crop rotation in the United Kingdom is ∼ 1–1.4 Mg C ha−1 y−1 (Milner et al., 2015). In spite of ignoring this additional benefit, these GHG cost estimates compare very favorably with coal (33 g CO2 eq. C MJ−1), North Sea Gas (16), liquefied natural gas (22), and wood chips imported from the United States (4). In addition, although Miscanthus production C. cost is only < 1/16 of the GHG cost of natural gas as a fuel (16–22 g CO2 eq. C MJ-1), it is mostly due to the carbon embedded in the machinery, chemicals and fossil fuel used in its production. As the economy moves away from dependence on these fossil fuels for temperature regulation (heat for glasshouse temperature control or chilling for rhizome storage) or transport, then these GHG costs begin to fall away from bioenergy production. It should be noted, the estimates in this paper do not consider either the potential to sequester C. in the soil nor any impact or ILUC (Hastings et al., 2009)." Hastings et al. 2017, pp. 12–13.
115. See Whitaker et al. 2018, pp. 156, Appendix S1
116. "Whilst these values represent the extremes, they demonstrate that site selection for bioenergy crop cultivation can make the difference between large GHG [greenhouse gas] savings or losses, shifting life‐cycle GHG emissions above or below mandated thresholds. Reducing uncertainties in ∆C [carbon increase or decrease] following LUC [land use change] is therefore more important than refining N2O [nitrous oxide] emission estimates (Berhongaray et al., 2017). Knowledge on initial soil carbon stocks could improve GHG savings achieved through targeted deployment of perennial bioenergy crops on low carbon soils (see section 2). [...] The assumption that annual cropland provides greater potential for soil carbon sequestration than grassland appears to be over‐simplistic, but there is an opportunity to improve predictions of soil carbon sequestration potential using information on the initial soil carbon stock as a stronger predictor of ∆C [change in carbon amount] than prior land use." Whitaker et al. 2018, pp. 156, 160.
117. "Fig. 3 confirmed either no change or a gain of SOC [soil organic carbon] (positive) through planting Miscanthus on arable land across England and Wales and only a loss of SOC (negative) in parts of Scotland. The total annual SOC change across GB in the transition from arable to Miscanthus if all nonconstrained land was planted with would be 3.3 Tg C yr−1 [3.3 million tonnes carbon per year]. The mean changes for SOC for the different land uses were all positive when histosols were excluded, with improved grasslands yielding the highest Mg C ha−1 yr−1 [tonnes carbon per hectare per year] at 1.49, followed by arable lands at 1.28 and forest at 1. Separating this SOC change by original land use (Fig. 4) reveals that there are large regions of improved grasslands which, if planted with bioenergy crops, are predicted to result in an increase in SOC. A similar result was found when considering the transition from arable land; however for central eastern England, there was a predicted neutral effect on SOC. Scotland, however, is predicted to have a decrease for all land uses, particularly for woodland due mainly to higher SOC and lower Miscanthus yields and hence less input." Milner et al. 2016, p. 123.
118. "In summary, we have quantified the impacts of LUC [land use change] to bioenergy cropping on SOC and GHG balance. This has identified LUC from arable, in general to lead to increased SOC, with LUC from forests to be associated with reduced SOC and enhanced GHG emissions. Grasslands are highly variable and uncertain in their response to LUC to bioenergy and given their widespread occurrence across the temperate landscape, they remain a cause for concern and one of the main areas where future research efforts should be focussed." Harris, Spake & Taylor 2015, p. 37 (see also p. 33 regarding SOC variations). The authors note however that "[t]he average time since transition across all studies was 5.5 years (Xmax 16, Xmin 1) for SOC" and that "[...] the majority of studies considered SOC at the 0–30 cm profile only [...]." Harris, Spake & Taylor 2015, pp. 29–30. Low carbon accumulation rates for young plantations are to be expected, because of accelerated carbon decay at the time of planting (due to soil aeration), and relatively low mean carbon input to the soil during the establishment phase (2-3 years). Also, since dedicated energy crops like miscanthus produce significantly more biomass per year than regular grasslands, and roughly 25% of the carbon content of that biomass is successfully added to the soil carbon stock every year (see Net annual carbon accumulation), it seems reasonable to expect that over time, soil organic carbon will increase also on converted grasslands. The authors quote a carbon building phase of 30-50 years for perennials on converted grasslands, see Harris, Spake & Taylor 2015, p. 31.
119. Gasparatos et al. 2017, p. 174.
120. Gasparatos et al. 2017, p. 166.
121. Gasparatos et al. 2017, p. 172.
122. Gasparatos et al. 2017, p. 167.
123. Gasparatos et al. 2017, p. 168.
124. Gasparatos et al. 2017, p. 173.
125. «Traditional biomass (fuelwood, charcoal, agricultural residues, animal dung) used for cooking and heating by some 2.8 billion people (38% of global population) in non-OECD countries accounts for more than half of all bioenergy used worldwide (IEA 2017; REN21 2018) (Cross-Chapter Box 7 in Chapter 6). Cooking with traditional biomass has multiple negative impacts on human health, particularly for women, children and youth (Machisa et al. 2013; Sinha and Ray 2015; Price 2017; Mendum and Njenga 2018; Adefuye et al. 2007) and on household productivity, including high workloads for women and youth (Mendum and Njenga 2018; Brunner et al. 2018; Hou et al. 2018; Njenga et al. 2019). Traditional biomass is land-intensive due to reliance on open fires, inefficient stoves and overharvesting of woodfuel, contributing to land degradation, losses in biodiversity and reduced ecosystem services (IEA 2017; Bailis et al. 2015; Masera et al. 2015; Specht et al. 2015; Fritsche et al. 2017; Fuso Nerini et al. 2017). Traditional woodfuels account for 1.9–2.3% of global GHG emissions, particularly in ‘hotspots’ of land degradation and fuelwood depletion in eastern Africa and South Asia, such that one-third of traditional woodfuels globally are harvested unsustainably (Bailis et al. 2015). Scenarios to significantly reduce reliance on traditional biomass in developing countries present multiple co-benefits (high evidence, high agreement), including reduced emissions of black carbon, a short-lived climate forcer that also causes respiratory disease (Shindell et al. 2012). A shift from traditional to modern bioenergy, especially in the African context, contributes to improved livelihoods and can reduce land degradation and impacts on ecosystem services (Smeets et al. 2012; Gasparatos et al. 2018; Mudombi et al. 2018).» IPCC 2019a.
126. IPCC 2019d, p. 628.
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