Shorting the Climate: Fossil Fuel Finance Report Card 2016

This seventh annual report card on energy financing evaluates top global private sector banks based on their financing for the fossil fuel industry. For 2016, the report has been expanded to high-risk subsectors of the oil and gas industry. It also analyzes patterns of private bank financing for coal, oil, and gas projects that have been financially disastrous and inflicted severe damage on communities, ecosystems, and the climate. The report identifies pervasive risk management failures across the North American and European banking sector on fossil fuel financing and calls for a fundamental realignment of bank energy financing to end support for fossil fuel projects and companies that are incompatible with climate stabilization.In the past three years, the North American and European commercial and investment banking sector has engaged in fossil fuel financing practices that are deeply at odds with the global climate agreement reached at COP 21 last December. The Paris Climate Agreement's target of limiting warming to 1.5°C (or, at most, 2°C) above pre-industrial levels will require a rapid decarbonization of the global energy system. Distressingly, levels of fossil fuel financing by major North American and European banks between 2013 and 2015 are incompatible with these climate stabilization targets:Coal mining - As leaders of climate-vulnerable states called for a global moratorium on new coal mines, top banks financed $42.39 billion for companies active in coal mining, led by Deutsche Bank with$6.73 billion.Coal power - In spite of a recent study concluding that the current pipeline of planned coal power plants would put the 2°C climate target out of reach by the end of 2017, these banks financed $154 billion for top operators of coal power plants, led by Citigroup with$24.06 billion.Extreme oil (Arctic, tar sands, and ultra-deep offshore) - Future development of most of these high-cost, highrisk oil reserves is incompatible with even the 2°C target, but banks financed $307 billion for the top owners of the world's untapped "extreme oil" reserves, led by JPMorgan Chase with$37.77 billion.Liquefied Natural Gas (LNG) export - Banks financed $283 billion, led by JPMorgan Chase with$30.58 billion, for companies involved with LNG export terminals in North America, which have enormous carbon footprints and are stranded assets in the making based on a 2°C climate scenario.Under pressure from global civil society, several U.S. and European banks have announced restrictions on financing for coal since last year. However, most of these policies fall well short of the necessary full phase-out of financing for coal mining and coal power production; as the report's grades for extreme oil and LNG export finance indicate, banks continue to finance these sectors on a nearly unrestricted basis. Banks also continue to fall distressingly short of their human rights obligations according to the United Nations Guiding Principles on Business and Human Rights, leaving banks complicit in human rights abuses by several of their corporate clients in the fossil fuel industry

Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plotlevel. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage

Forest Biomass Density across Large Climate Gradients in Northern South America is related to Water Availability but not with Temperature

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage

Distribution of plots used to estimate aboveground biomass in the studied Northwest South American region (Colombia, Brazil, Peru and Ecuador).

<p>Color of the symbols represent the forest types in the region: Blue for forest plots in Amazonia; yellow for forest plots in the Andean uplands; red for plots in the inter-andean valleys; Orange for the Caribbean plots; Green for the Orinoco region and the green triangles for the forest plot in the Choco region. The grey scale is displayed to denote altitude (m. a.s.l).</p

Explanatory models of aboveground biomass.

<p>Explanatory models of aboveground biomass.</p

Relationship between Aboveground Biomass (AGB) and (a) Water Availability (WA), (b) Precipitation Variability (PV), Actual Evapotranspiration (AET) and (d) Annual Mean Temperature (AMT).

<p>Bioregions are shown with different colors. Solid lines represent the trend of relationships, based on the original data (without transformation), according to the best models (highest AIC scores) presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171072#pone.0171072.t002" target="_blank">Table 2</a>; pR² is a partial regression coefficient for each of the relationships.</p

Plots of forest structure parameters and aboveground biomass.

<p>The Coefficient of determination is showed in each plot. *P<0.01; **P<0.001; ***P<0.000; ns: non-significant.</p

Mean and standard deviation of aboveground biomass (AGB) across geographic regions of Northwest South America.

<p>Mean and standard deviation of aboveground biomass (AGB) across geographic regions of Northwest South America.</p

Climatic space represented for each vegetation plot used in this analysis.

<p>The climatic space is shown as principal components analysis to reduce climatic variables used. The first axis represents temperature variability and second axis represents precipitation variability. Gray points represent the climatic space availability across Northwest South America. Blue points represent actual climatic conditions of each of the vegetation plots sampled.</p

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating.Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 7