Collapse

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This is the place for discussing the potential collapse of modern civilization and the environment.


Collapse, in this context, refers to the significant loss of an established level or complexity towards a much simpler state. It can occur differently within many areas, orderly or chaotically, and be willing or unwilling. It does not necessarily imply human extinction or a singular, global event. Although, the longer the duration, the more it resembles a ‘decline’ instead of collapse.


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submitted 2 months ago* (last edited 2 months ago) by eleitl@lemm.ee to c/collapse@lemm.ee
 
 

Abstract

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020.

The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches.

For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters.

The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified.

For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget.

We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning.

The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024). How to cite.

Saunois, M., Martinez, A., Poulter, B., Zhang, Z., Raymond, P. A., Regnier, P., Canadell, J. G., Jackson, R. B., Patra, P. K., Bousquet, P., Ciais, P., Dlugokencky, E. J., Lan, X., Allen, G. H., Bastviken, D., Beerling, D. J., Belikov, D. A., Blake, D. R., Castaldi, S., Crippa, M., Deemer, B. R., Dennison, F., Etiope, G., Gedney, N., Höglund-Isaksson, L., Holgerson, M. A., Hopcroft, P. O., Hugelius, G., Ito, A., Jain, A. K., Janardanan, R., Johnson, M. S., Kleinen, T., Krummel, P. B., Lauerwald, R., Li, T., Liu, X., McDonald, K. C., Melton, J. R., Mühle, J., Müller, J., Murguia-Flores, F., Niwa, Y., Noce, S., Pan, S., Parker, R. J., Peng, C., Ramonet, M., Riley, W. J., Rocher-Ros, G., Rosentreter, J. A., Sasakawa, M., Segers, A., Smith, S. J., Stanley, E. H., Thanwerdas, J., Tian, H., Tsuruta, A., Tubiello, F. N., Weber, T. S., van der Werf, G. R., Worthy, D. E. J., Xi, Y., Yoshida, Y., Zhang, W., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: Global Methane Budget 2000–2020, Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, 2025.

Received: 02 May 2024 – Discussion started: 06 Jun 2024 – Revised: 22 Jan 2025 – Accepted: 03 Feb 2025 – Published: 09 May 2025

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We can't be in this situation where every couple of years we're facing crisis levels and people are scrambling," Berggren said. "It reinforces the need for a more robust, long-term and resilient set of guidelines for managing the river."

But that does seem the plan :)

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Abstract

Seaweed farming has emerged as a potential Blue Carbon strategy, yet empirical estimates of carbon burial from such farms remain lacking in the literature. Here, we quantify carbon burial in 20 seaweed farms distributed globally, ranging from 2 to 300 years in operation and from 1 to 15,000 ha in size. The thickness of sediment layers and stocks of organic carbon accumulated below the farms increased with farm age, reaching 140 tC ha−1 for the oldest farm. Organic carbon burial rates averaged 1.87 ± 0.73 tCO2e ha−1 yr−1 in farm sediments, twice that in reference sediments. The excess CO2e burial attributable to the seaweed farms averaged 1.06 ± 0.74 CO2e ha−1 yr−1, confirming that seaweed farming in depositional environments buries carbon in the underlying sediments at rates towards the low range of that of Blue Carbon habitats, but increasing with farm age.

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Year 2050 sea level projections, Linear rate plot and Acceleration rate plots for coastal cities and towns.

Rises are not uniform. The southeast / gulf areas show rapid acceleration.

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On Preempting Collapse (thehonestsorcerer.substack.com)
submitted 2 months ago by eleitl@lemm.ee to c/collapse@lemm.ee
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A plain english news version https://www.livescience.com/planet-earth/plants/scientists-find-the-best-crops-to-grow-during-the-apocalypse

Resilience to abrupt global catastrophic risks disrupting trade: Combining urban and near-urban agriculture in a quantified case study of a globally median-sized city Abstract Background Abrupt global catastrophic risks (GCRs) are not improbable and could massively disrupt global trade leading to shortages of critical commodities, such as liquid fuels, upon which industrial food production, processing and distribution depends. Previous studies have suggested urban agriculture as a resilience measure in the context of climate change and other natural hazards.

Aims To estimate the contribution a radical pivot to urban agriculture could have in building resilience to GCRs and the near-urban industrial agriculture needed to supplement urban food production.

Methods We determined optimum crops through mathematical optimization for food calorie and protein supply per land area for both urban and near-urban (industrial) agriculture. We calculated the land area available for food production within a temperate globally median-sized city using Google Earth image analysis of residential lots and open city spaces. We calculated the population that could be fed through urban agriculture alone, and the extra near-urban land required for cropping with industrial agriculture to feed the remaining city population, under both normal climate, and potential nuclear winter conditions.

Results The optimal crops for urban agriculture were peas (normal climate), and sugar beet/spinach (nuclear winter); while those optimal for industrial near-urban production were potatoes (normal climate), and wheat/carrots (nuclear winter). Urban agriculture could feed a fifth (20%) of the population. At least 1140 hectares of near-urban cultivation could make up the shortfall. Another 110 hectares of biofuel feedstock like canola (rapeseed) could provide biodiesel to run agricultural machinery without fuel trade. Significantly more cultivated area is needed in nuclear winter scenarios due to reduced yields.

Conclusion Relatively little optimized near-urban industrial agriculture, along with intensified urban agriculture could feed a median-sized city in a GCR, while minimizing fuel requirements. Governments and municipal authorities could consider land use policy that encourages development of urban agriculture and near-urban cultivation of optimal crops, along with processing and local biofuel refining capacity.

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This is AI generated because i was bored and playing with AI to see if its useful yet

The Biophysical Economics of Wood as a Primary Fuel

Introduction

Wood fuel (firewood, charcoal, etc.) has been humanity’s dominant energy source since prehistoric times. Burning wood yields by far the largest share of solid-biomass energy even today. Globally, roughly half of all wood harvested from forests is used as fuel. In this wood-powered “biomass era,” energy availability, transport effort, and land use were all tightly coupled. Societies managed forests intensively (e.g. through coppicing) to sustain fuel supplies, and settlements grew only as far as wood resources would allow. We survey this history (with emphasis on Europe and the United States) and the underlying energetics, then apply the lessons to a hypothetical rapid decline of fossil fuels over ten years. This scenario analysis uses biophysical constraints and EROI concepts to project impacts on settlement patterns, densities, and infrastructure. We conclude with a practical guide – informed by history and energy theory – for community resilience and rebuilding in a post-fossil-fuel world.

Historical Use of Wood Fuel

Global perspective (Medieval to Pre-Industrial)

Since the discovery of fire, wood has been humanity’s principal fuel. In many cultures, “firewood played an indispensable role in socio-economic systems from prehistory until the nineteenth century”. Pre-industrial Europe, for example, developed complex woodland management (especially coppicing) to produce a steady wood supply for heating and cooking. Over centuries of clearing and coppicing, even densely settled regions supported households on local wood. As one source notes, “about half of wood extracted from forests worldwide is used as fuelwood”. Wood – in the form of bundled twigs (“faggots”) or charcoal – was the norm for hearths and for industrial processes (e.g. iron smelting) until the 19th century. Charcoal, made by slowly burning wood under cover, was especially prized in metalworking for its high heat value. Traditional charcoal burning sites (such as the bricked kilns of Europe or covered platforms like that shown) were once common wherever iron was smelted or gunpowder made.

Figure: Traditional charcoal-burning kiln in British woodlands (rusty iron cover over a woodpile), illustrating the old practice of converting wood into charcoal for fuel. Charcoal was “an important fuel in ironmaking” and other industries in the pre-coal era.

In temperate Europe, staple fuels included the felled wood of coppiced woodlands. Over time these “managed woodlands” supplied local markets even into the early 20th century. For example, in England and Central Europe the same coppice systems supported urban fuel demand until about World War II. Only with the Industrial Revolution did a new fuel take over: burgeoning coal mining replaced most coal-for-wood in large-scale industry. But until roughly 1900, cities and villages largely relied on nearby forests. In Italy and Japan, too, 17th–19th century governments explicitly regulated forests because of fuel pressures. Edo-period Japan, faced with over-harvesting, created strict state forestry policies and reforestation initiatives to maintain timber and fuel supplies. These examples show that heavy wood use often drove deforestation and policy changes; energy scarcity could loom even as late as the early 1900s.

Wood Fuel in Early America

In colonial and early-American times, settlers also used wood almost exclusively. North America was settled amid vast forests, and in the 1700–1800s felling trees served multiple ends. Settlers cleared land for farms and sold timber and firewood to pay for clearing costs. By 1850, frontier clearance and local fuel sales had already stripped much of the eastern U.S. “By 1850, the lowland forests of the Atlantic seaboard, New England and much of the Midwest had largely been cleared,” largely for agriculture and fuel. Selling firewood and charcoal helped finance land clearing, and early American homes (often with open-hearth fireplaces) consumed vast amounts of wood. For example, an 18th-century Philadelphia house burned on the order of 20–30 cords of wood per year. (A cord is 128 cubic feet of wood.) From 1800 onward, as steam engines and locomotives spread, wood still heated rural homes and powered early steamships and trains, even as urban boilers began to adopt coal. The EIA notes that by 1860 wood was “the primary fuel for heating and cooking in homes and businesses”. But by 1890, coal had largely displaced wood in steam generation, and by 1930 most Americans in towns burned coal while rural Americans still used wood. After 1950, advances in natural gas and electricity ended wood’s role in most buildings.

Worldwide today, wood is still a major fuel in poorer regions. In much of sub-Saharan Africa and South Asia, for example, households still cook on open wood fires or charcoal stoves. Wood and charcoal economies persist in urban markets of the tropics, employing large numbers of people. Thus the historical patterns have continuing relevance: wood may seem “traditional,” but efficient local practices (like using deadwood or agro-forest trees) often stretch supplies in practice. Nevertheless, in every case wood energy is constrained by the biophysical limits of forests.

Biophysical Economics of Wood Fuel

Wood’s role as fuel is fundamentally a biophysical-economic issue. Key parameters include energy content per mass, calorific yield, and the ratio of energy obtained to energy (or labor) invested – the EROI. Typical oven-dry firewood has an energy density around 15–20 MJ/kg, significantly less than coal (~24 MJ/kg) or oil (~45 MJ/kg). Wood is bulky and heavy for the heat it provides, making transport energy-intensive. In practice, traditional fuelwood gathering often involves carrying heavy bundles by foot or animal over rough terrain. Studies of hunter-gatherer fuel use emphasize this cost: one simulation in a Californian forest estimated that a central-place family would exhaust the available wood fuel within a year’s constant harvesting. In other words, the nearest wood supplies were quickly depleted and limited how far a village could spread.

Another biophysical measure is return on energy investment. Historically, gathering wood required human (or animal) energy. When computed in modern terms, EROI of simple fuelwood is surprisingly low if one counts all labor; estimates vary widely depending on assumptions. (By some accounts, intensive woodchip production can have EROI in the 20:1–30:1 range, but other analyses note that woodfuel can sometimes be energy-negative if all processes are counted.) In any case, wood’s EROI is modest compared to fossil fuels. Early oil in the 20th century had very high EROI, which has since declined. In general, an energy source with EROI below ~1:1 is worthless (it takes more energy to obtain than it yields). A sustainable civilization requires a net surplus; analysts suggest a bare minimum extended EROI of ~3:1 just to maintain basic infrastructure, with values of 8–12:1 or more needed for higher services. Present global energy (fossil+bio) is around 6:1, aided by remaining oil. By contrast, simple biomass fuels in an unmechanized economy barely exceed that threshold. Historical wood economies typically consumed a large fraction of society’s labor and captured little surplus.

Wood is also renewable, but with limits set by forest growth rates. Unmanaged forests add only a few percent of biomass per year. Traditional management (coppicing) accelerated supply by cutting stems at intervals, but even that cycle was on the order of 7–30 years. Thus woodfuel systems could be sustainable only if harvests roughly equaled regrowth. In practice, rising demand often outstripped growth, causing deforestation. Across pre-industrial Europe and America, forests retreated as farmland expanded for food and fuel. This deforestation eventually constrained fuel access: by medieval times many regions were managed as wood-production forests (e.g. coppice) to sustain heat needs. Wood scarcity even prompted social conflict and policy intervention (for example, castle forests or charters limiting cutting).

Energy Services and Technology

The way wood’s energy was used also shapes its effective value. Open fires waste most heat up the chimney. Technological advances (chimneys, enclosed stoves) improved efficiency by recirculating heat. For instance, Franklin stoves and later cast-iron wood stoves greatly increased warmth per cord burned. Still, wood heating in pre-modern times was inefficient: one source notes colonial American fireplaces were so leaky that room heating was “next to impossible”, necessitating huge wood consumption. Thus part of the “cost” of wood fuel was sheer inefficiency. In contrast, fossil fuel and electric heating today deliver far more usable heat per energy unit. Any biophysical analysis of wood must account for these efficiencies.

Wood Fuel, Settlement Patterns, and Transport Costs

Because wood must be transported from forest to settlement, transport costs critically shaped pre-fossil landscapes. In an agrarian society, land was organized around central markets. Classical spatial-economic theory (Von Thünen’s model, 1826) postulates concentric rings of land use around a city. Importantly, the second ring outward was forestry: fuelwood and timber zones close to the city. Von Thünen reasoned that bulky, heavy goods (like wood) must come from nearby to minimize transport cost. In his model, dairy and market gardens lay closest to town, then a ring of forests supplying wood and timber, then more distant fields and finally grazing lands. This pattern matches historical reality in the wood era: cities were often ringed by managed forests for fuel. (By the late 19th century in North America, the pattern changed as coal and railroads supplanted local wood, but in a wood-dependent society the forest zone would be economically essential.)

In practical terms, firewood procurement constrained settlement density. Villagers often spent many hours per week gathering wood. One experimental study found forager families might walk kilometers daily to collect fuel, and could spend 10–20% of their workday in fuel gathering. This daily cost limited how dispersed communities could be: if wood had to come from too far away, more labor would be required than a family could spare. In effect, each household radius was capped by the time-investment people were willing to devote to wood. Archaeological data support this: in medieval Europe and rural colonies, populations remained clustered in forested valleys or along riverines where wood (and timber transport via water) was available. Only when coal, gas, or electricity became cheap could cities sprawl far beyond former wood limits.

For example, colonial New England villages were typically built near forests, and early towns often bought common woodlots for public use. When nearby woodlands were cleared, fuel had to be hauled from increasingly distant hills. People documented “firewood shortages” in growing American towns by the mid-1700s; rising wood prices in cities like Philadelphia suggest local forests had been overused. In such a context, transport cost is a literal lifeline. Likewise, in medieval London authorities regulated forest leases to guarantee supply, since distantly-supplied wood (even by river) was costly. Thus reliance on wood strongly influenced where people settled and how dense those settlements could be: clusters tended to stay near fuel, and urban footprints stayed limited until fossil fuels expanded.

The Von Thünen Model in the Biomass Era

Von Thünen’s agricultural-land-use model provides a useful conceptual lens for a wood-powered economy. In the model, land uses are determined by distance-from-market (transport cost) and land rent. Importantly, as noted above, Von Thünen placed a “forest for fuel” zone immediately outside high-density farming. This reflects the fact that wood is heavy relative to its value, so it must be produced close by. In practice, a medieval or pre-industrial region might see precisely this pattern: the innermost ring (closest to a town) was intensive perishable agriculture; just beyond it, managed forest coppices and woodlots supplied fuel. Further out lay grain fields and grazing. (For example, 19th-century English land planners often described ringed landscapes: suburban market gardens near cities, a band of wood-pasture or coppice, then arable crops and finally open commons or heath.)

We illustrate Von Thünen’s classical scheme in Figure 1: concentric land-use rings centered on a market city. Zone 2 (green) is explicitly designated for timber and firewood. This idealized pattern collapses in the modern era, where oil-powered transport and electricity freed cities from local-wood constraints; indeed, today “forests no longer occupy a zone close to the market” because coal and gas replaced wood. But in evaluating a post-fossil future or interpreting the wood era, Von Thünen’s rings remain illustrative. They show how energy transport costs structure land use: when wood is the main fuel, proximity to forests determines urban form.

Fossil Fuel Descent Scenario: Biophysical Constraints and Spatial Impacts

Let us now imagine a 10-year “fossil fuel descent” – a rapid decline in global oil, coal, and gas availability. This extreme scenario (perhaps due to resource depletion or global crises) would thrust society back onto low-EROI, locally sourced fuels. Energy constraints become paramount. Biophysically, the same logic as in the wood era comes into play, but now applied to modern settlements.

First, energetic constraints tighten. As existing fields deplete, extraction rates must fall: “for each [oil or gas] reservoir, a maximum rate of extraction is eventually reached…after which production plateaus before an immutable decline”. Decline is governed by geology, not politics: most mature basins are past peak production. In effect, society will have less net energy (the surplus after paying the energy cost of extraction) to sustain non-energy sectors. As net EROI falls, less surplus remains for transportation, industry, and non-essential services. Hall et al. suggest a threshold: extended EROI below ~3:1 cannot support a complex economy. A rapid descent could push net EROI near that boundary, forcing contraction of infrastructure and services.

Second, higher transport costs will reshape settlement. With expensive oil, everyone pays more for gasoline and shipping. Commuting by car becomes unaffordable for many, so cities begin to densify – as predicted by peak-oil studies. Even moderate fuel price increases tend to favor urban infill, mixed-use development, and public transit. In our scenario, we assume fuel scarcity will cause a pronounced shift toward high-density nodes (cities or urban villages) and away from auto-dependent sprawl. Governments would face pressure to promote compact housing and mass transit, and to re-localize food production. The trend in research is that “peak oil is likely to result in… increases in urban densities”. (Of course, local factors matter: not every city will densify if blocked by rigid zoning, but overall the pressure favors clustering.)

At the same time, some de-urbanization may occur in fringe areas. Outlying suburbs and exurbs – built on the premise of cheap cars – could partially revert or decline. Some households might abandon distant suburbs and move into or near core cities or smaller towns with local energy supplies. Long-haul trucking will shrink, so goods must be produced regionally. Agricultural products will come from closer farms, reducing rural depopulation in some cases as peri-urban farming becomes viable again. However, infrastructure in far-flung areas will deteriorate: long-distance pipelines, highways and transmission lines might be neglected without fuel for maintenance. Consequently, hinterlands may see a gradual return to low-density, agrarian living reminiscent of the pre-motor era – though likely at much lower technological level, due to diminished energy.

The net effect on population density is complex. On one hand, cities may regain economic importance and critical mass (encouraging migration into urban cores). On the other, basic necessities may need rural production (encouraging small-town or village living near farmland). Overall, key amenities (especially energy and food supply) will re-impose limits on spread. We can anticipate a restructuring toward shorter supply chains: people living near their work or farm, smaller local industries, and networks of towns spaced to match renewable-resource zones (e.g. woodlands, rivers). In other words, some high-density centers will expand (to exploit remaining infrastructure), but the outer fringe of exurban development will contract. This hybrid pattern loosely mirrors the concentric model but in reverse: core areas densify for efficiency, while the outermost regions revert to extensive, low-density (locally-self-sufficient) settlement.

Biophysical Constraints (EROI and Net Energy)

Underlying these trends is the steep decline in net energy. As fossil EROI collapses, society must rely more on ever-lower-EROI sources. The rapid ascent of solar and wind faces the same issue: new energy technologies do not escape physics. Critics caution that many renewables (and all biofuels) have far lower EROI than conventional oil. If global average EROI falls below, say, 5:1 or 3:1, only minimal energy services can be maintained. Urban infrastructures (water purification, freight delivery, high-tech medicine) would be strained. In effect, modern society’s complexity – from hospitals to supply chains – is built on abundant net energy. A ten-year descent would not allow a smooth transition: even if renewables ramped up, they would take years to scale. In the interim, energy rationing or allocation would become necessary.

This constraint has direct spatial implications. Fuel transport will contract to the most energy-efficient routes. Heavy goods might be relegated to rail or ships (if fuel still available), while light goods rely on local production. Long pipelines may be phased out in favor of local boilers and biomass plants. Many smaller communities could become effectively energy islands, reliant on local grids or microgrids and on biomass. Meanwhile, rich cities with remaining infrastructure (e.g. hydroelectric dams, nuclear plants) may have a temporary advantage, drawing population from poorer countryside. However, as overall energy declines, even large cities would eventually suffer, forcing further decentralization.

In summary, the biophysical constraints of a rapid fossil-fuel descent will likely push societies into a hybrid pattern: intensified cities and towns supported by shrunken hinterlands of local resource use. Denser settlement becomes necessary to reduce per-capita transport costs; yet without modern long-distance energy, some reversion to agrarian village life (reminiscent of the pre-industrial era) will occur in less-dense areas. This scenario poses enormous challenges for infrastructure – requiring re-localization of food, water, and services – but it is constrained by familiar limits (fuelwood radius, crop yields, human labor capacity) that shaped past societies.

Surviving and Rebuilding: A Practical Guide

Even as an extreme scenario, a ten-year energy crash invites proactive planning. History offers lessons: past societies managed wood and agriculture at village scales, and we can draw on those models. The following guide sketches survival and rebuilding strategies at household, community, and regional levels, grounded in biophysical realities and historical precedent.

  • Local Fuel Stewardship: Where wood remains available, communities must manage forests as a commons. This means planning coppice cycles and woodlots so that each household has access to a sustainable annual allotment of fuel. (In medieval Europe, legal commons often ensured villagers a right to limited wood for heating.) Replanting and selective cutting will be essential. At the household level, switch to the most efficient wood-burning technologies possible (mass-fired masonry heaters, rocket stoves) to maximize heat per cord. Recover and use all available biomass: wood scraps, fallen branches, agricultural residues, and even brush. Any surviving charcoal processes should be highly organized and regulated, since charcoal is far more energy-dense than raw wood.

  • Food and Agriculture: Communities must localize food production to avoid petroleum-based transport and fertilizers. Revive mixed farming and orchards near villages. Use labor-intensive but land-sparing methods (e.g. biodiverse polycultures, terrace or raised-bed gardens, draft animal plowing) rather than mechanized monocultures. Where possible, rotate fields out of production so woodlands or pastures can recover (medieval “forest farming” techniques). Preserve local seed stocks and traditional crop varieties adapted to low-energy farming. Develop community-based storage and processing (e.g. drying, fermenting) to deal with harvest variability. This echoes historical patterns: once, each village supplied its own grains, legumes, and vegetables, with limited long-distance trade.

  • Settlement Design and Transport: Reinforce settlement clustering. Urban design should shift to high density: infill empty lots, convert wide roads into shared lanes, and prioritize pedestrian and bicycle access. Residents will need to live near work and shops; mixed-use neighborhoods (combining housing, food markets, workshops) reduce travel. In towns, relocate or rebuild infrastructure (water, power, waste) around central hubs. Abandoned suburbs could be allowed to revert to farm or forest. At the regional level, create networks of smaller towns spaced by a day’s ride or walk; these can serve as nodes for trade of goods like timber or harvests, reducing the need for long hauls. Historically, empires like Rome or China operated via waystations and local provisioning; similar logic applies now.

  • Community Organization: Grassroots cooperatives can manage local resources and share labor. For example, communal woodcutting teams can harvest timber efficiently, and rotating duties could ensure all households get firewood. Community gardens, tool libraries, and shared kilns or workshops multiply productivity. Learning and re-learning “traditional” skills (carpentry with hand tools, blacksmithing with charcoal, hand-threshing) becomes survival work. Education should focus on these skills and on practical sciences (agroecology, permaculture, renewable energy basics). Psychological and social resilience is also crucial: planning for energy descent requires public buy-in. Historical analogs include monastic or communal settlements that organized daily life around local resources – a pattern that might be revived at a larger scale.

  • Infrastructure and Policy: At the regional/policy level, governments must adapt regulations. Possible measures include: rationing fuel and gasoline (to equitable ends), subsidizing renewable installations (like village-scale solar or wind, as far as possible), protecting remnant forests with strict cutting permits, and converting vacant land into communal woodlots. Transportation policy would pivot away from highways toward rail and river barges (if still operable). Energy-intensive industries (steel, petrochemicals) may be phased out or retooled to smaller scales using local inputs (for instance, small charcoal iron furnaces for toolmaking). Zoning laws should be relaxed to allow urban gardening and livestock in city neighborhoods, mirroring medieval practices of inner-city horticulture. Health and education budgets will need drastic revision as transport costs rise; telemedicine and remote learning (where electricity survives) can help.

  • Economic Adjustments: Price all remaining energy to reflect true cost: remove any fossil-fuel subsidies immediately to avoid wasteful consumption. Encourage barter and local currencies that reduce reliance on fuel-derived GDP. Protect vulnerable populations by community food banks, mutual aid, and decentralized healthcare. Disaster-preparedness will be vital (for example, winterizing homes since heating fuel may be limited).

All these actions are supported by historical precedent. For instance, 17th-century landowners used documented forest management plans to allocate coppice stands between villages. Edo-period Japan compiled detailed land registers and enforced timber permits to avoid fires and famines. In New England, towns once funded schools and mills by selling common woodlots. These are transferable lessons: equitable, planned resource use at the local level ensures survival of the community as a whole.

Finally, renewable energy (solar, wind, hydro) will play a role where possible, but note its constraints. Manufacturing solar panels and wind turbines may be bottlenecked by the energy descent itself. Thus, most rebuilding will rely on low-tech, proven methods: wood energy, muscle (human/animal), and simple machinery (watermill, hand mill, etc.). Communities should “prefamiliarize” themselves with lower-consumption lifestyles before crises fully hit.

Table 1 (for illustration): Comparison of Energy Sources (indicative)

Fuel Type Approx. Energy Density (MJ/kg) Typical EROI (modern) Typical Usage Context
Wood (dry) 15–20 ~10:1–30:1 [varies; see text] Home heating; small cogeneration
Charcoal ~30 Low (energy-intensive to produce) Iron smelting (historical)
Coal (bituminous) ~24 30:1–80:1 (historical) Power plants, industry
Oil (crude) ~42–45 ~100:1 (1930s) → 10:1 (now) Transport, petrochemicals
Natural Gas ~50 (MJ/kg) High (since 1970s) Heating, power, feedstock
Wind/Solar (LCOE) Varies; low net output early on Electricity (future)

Notes: EROI = Energy Return on Energy Invested. Values depend on technology, scale, and location. Fossil EROI historically far exceeded wood’s; as Hall et al. note, oil’s EROI has “relentlessly declined” while many renewables and biomass fuels remain low.

Conclusion: Toward a Bioeconomy

Wood energy underpins a deep history of human settlement and economy. Its biophysical realities – low density, finite regrowth, and modest EROI – forced past societies to cluster and manage resources carefully. In a coming post-fossil era, these lessons must be relearned on a global scale. Communities will have to align land use with energy transport costs much like the concentric model of Von Thünen: essentials nearest to population centers, with renewable resource zones (wood, water, fields) organized around them. The transition will be at least as dramatic as the original Industrial Revolution, requiring system-wide preparation. By studying history and energy science, we can anticipate the constraints and begin building resilient communities now – before the woodpile runs out and we must restart by the light of the hearth.

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  • Climate change is colliding with land use practices, deforestation and biodiversity loss to drive a rapidly growing threat of crop pests.
  • Future warming of 2° Celsius (3.6° Fahrenheit) above preindustrial levels (likely by the 2040s or 2050s, according to current projections) could see substantial losses of staple crop yields for wheat (an estimated 46% loss), rice (19%) and maize (31%) due to pest infestations, according to a recent paper.
  • Temperate regions are likely to see the greatest increases in crop pests as warming creates conditions for migrating subtropical species to establish themselves in previously unhabitable areas.
  • The authors underline the need for more pest monitoring, diversification of farmland crops and biotechnological solutions to meet this growing threat.

Note that future warming is likely to be up to 50% greater than stated in this article.

archived (Wayback Machine):

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How the Evolution to the New Economy Works (chattingaboutlocalism.wordpress.com)
submitted 2 months ago by eleitl@lemm.ee to c/collapse@lemm.ee
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The Day After. (aurelien2022.substack.com)
submitted 2 months ago by eleitl@lemm.ee to c/collapse@lemm.ee
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Abstract

Climate extremes are escalating under anthropogenic climate change1. Yet, how this translates into unprecedented cumulative extreme event exposure in a person’s lifetime remains unclear. Here we use climate models, impact models and demographic data to project the number of people experiencing cumulative lifetime exposure to climate extremes above the 99.99th percentile of exposure expected in a pre-industrial climate. We project that the birth cohort fraction facing this unprecedented lifetime exposure to heatwaves, crop failures, river floods, droughts, wildfires and tropical cyclones will at least double from 1960 to 2020 under current mitigation policies aligned with a global warming pathway reaching 2.7 °C above pre-industrial temperatures by 2100. Under a 1.5 °C pathway, 52% of people born in 2020 will experience unprecedented lifetime exposure to heatwaves. If global warming reaches 3.5 °C by 2100, this fraction rises to 92% for heatwaves, 29% for crop failures and 14% for river floods. The chance of facing unprecedented lifetime exposure to heatwaves is substantially larger among population groups characterized by high socioeconomic vulnerabilities. Our results call for deep and sustained greenhouse gas emissions reductions to lower the burden of climate change on current young generations.

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Abstract

Climate injustice persists as those least responsible often bear the greatest impacts, both between and within countries. Here we show how GHG emissions from consumption and investments attributable to the wealthiest population groups have disproportionately influenced present-day climate change. We link emissions inequality over the period 1990–2020 to regional climate extremes using an emulator-based framework. We find that two-thirds (one-fifth) of warming is attributable to the wealthiest 10% (1%), meaning that individual contributions are 6.5 (20) times the average per capita contribution. For extreme events, the top 10% (1%) contributed 7 (26) times the average to increases in monthly 1-in-100-year heat extremes globally and 6 (17) times more to Amazon droughts. Emissions from the wealthiest 10% in the United States and China led to a two- to threefold increase in heat extremes across vulnerable regions. Quantifying the link between wealth disparities and climate impacts can assist in the discourse on climate equity and justice.

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"If everyone had emitted like the bottom 50% of the global population, the world would have seen minimal additional warming since 1990,"

The study assesses the contribution of the highest emitting groups within societies and finds that the top 1% of the wealthiest individuals globally contributed 26 times the global average to increases in monthly 1-in-100-year heat extremes globally and 17 times more to Amazon droughts.

The research sheds new light on the links between income-based emissions inequality and climate injustice, illustrating how the consumption and investments of wealthy individuals have had disproportionate impacts on extreme weather events

Our study shows that extreme climate impacts are not just the result of abstract global emissions, instead we can directly link them to our lifestyle and investment choices, which in turn are linked to wealth,"

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#302: At the end of modernity, part one (surplusenergyeconomics.wordpress.com)
submitted 3 months ago by eleitl@lemm.ee to c/collapse@lemm.ee
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This was published a couple of weeks ago, but not yet posted in this community.

It's a much-needed skewering of the idea that low birth rates are an existential crisis and that somehow what we need is more human beings on our stressed planet. This crazymaking meme is quickly becoming received wisdom. As the article describes, it's being propagated by a bunch of disparate thought leaders:

  • millenarianist billionnaires who are completely unexposed to our planet's ecological limits (Elon Musk, obviously)
  • pronatalist religious types, both conservative (Ross Douthat) and progressive (Elizabeth Bruenig)
  • liberals (Ezra Klein) and eccentric libertarians (Tyler Cowen) who apparently believe "abundance" is the only way to save democracy

Their talking points are pretty well recapitulated here. There's a legitimate argument to be had about the speed of any population decline (because of the stress on welfare systems). But the pronatalists are not talking about that, they're genuinely worried about human underpopulation. This article is full of stats and demonstrations that show that this concern is completely delusional and is helping to make our planet less liveable. We need to fight back by stating this fact more loudly.

[I]f 95 percent of today’s human beings were to evaporate overnight, we would still have a global population higher than 400 million. That’s more people than existed during Rome’s greatest territorial extent, a time after Homer, Herodotus, Pythagoras, Pericles, Socrates, Plato, Thucydides, Alexander, Aristotle, Julius Caesar, Livy, Virgil, Jesus, and many other important figures had all made their contributions to the Western world. This population level, which amounts to five percent or one-twentieth that of today (at most), was hardly a threat to civilization, and much less to the human species.

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A Clash of Titans (thehonestsorcerer.substack.com)
submitted 3 months ago by eleitl@lemm.ee to c/collapse@lemm.ee
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Abstract

Since the late 20th century, an emerging atmospheric teleconnection pattern, the trans-Eurasian heatwave-drought train, has intensified remarkably during summer, correlating with a surge in concurrent heatwave-drought events from Eastern Europe to East Asia. Tree-ring proxies, spanning three centuries, reveal that the recent intensity of this pattern is unprecedented in the historical records. In contrast, the circumglobal teleconnection, which historically dominated the continental-scale Eurasian heatwave occurrences, has shown no discernible trend amid global warming. Consequently, this emerging pattern signifies a radical shift in Eurasian heatwave-drought climatologies. The mechanism involves Rossby wave propagation linked to warming sea surface temperatures in the Northwestern Atlantic and enhanced Sahel precipitation, both amplified recently by overlapping effects of anthropogenic warming and natural variability. Land-atmosphere interactions driven by soil moisture deficits further intensified the pattern regionally. Climate models predict that anthropogenic forcings will continue to strengthen the pattern throughout this century.

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