Search Results
Early retirement of power plants in climate mitigation scenarios
International efforts to avoid dangerous climate change aim for large and rapid reductions of fossil fuel CO2 emissions worldwide, including nearly complete decarbonization of the electric power sector. However, achieving such rapid reductions may depend on early retirement of coal- and natural gas-fired power plants. Here, we analyze future fossil fuel electricity demand in 171 energy-emissions scenarios from Integrated Assessment Models (IAMs), evaluating the implicit retirements and/or reduced operation of generating infrastructure. Although IAMs calculate retirements endogenously, the structure and methods of each model differ; we use a standard approach to infer retirements in outputs from all six major IAMs and—unlike the IAMs themselves—we begin with the age distribution and region-specific operating capacities of the existing power fleet. We find that coal-fired power plants in scenarios consistent with international climate targets (i.e. keeping global warming well-below 2 °C or 1.5 °C) retire one to three decades earlier than historically has been the case. If plants are built to meet projected fossil electricity demand and instead allowed to operate at the level and over the lifetimes they have historically, the roughly 200 Gt CO2 of additional emissions this century would be incompatible with keeping global warming well-below 2 °C. Thus, ambitious climate mitigation scenarios entail drastic, and perhaps un-appreciated, changes in the operating and/or retirement schedules of power infrastructure.
Rootzone storage capacity reveals drought coping strategies along rainforest-savanna transitions
Climate change and deforestation have increased the risk of drought-induced forest-to-savanna transitions across the tropics and subtropics. However, the present understanding of forest-savanna transitions is generally focused on the influence of rainfall and fire regime changes, but does not take into account the adaptability of vegetation to droughts by utilizing subsoil moisture in a quantifiable metric. Using rootzone storage capacity (Sr), which is a novel metric to represent the vegetation's ability to utilize subsoil moisture storage and tree cover (TC), we analyze and quantify the occurrence of these forest-savanna transitions along transects in South America and Africa. We found forest-savanna transition thresholds to occur around a Sr of 550–750 mm for South America and 400–600 mm for Africa in the range of 30%–40% TC. Analysis of empirical and statistical patterns allowed us to classify the ecosystem's adaptability to droughts into four classes of drought coping strategies: lowly water-stressed forest (shallow roots, high TC), moderately water-stressed forest (investing in Sr, high TC), highly water-stressed forest (trade-off between investments in Sr and TC) and savanna-grassland regime (competitive rooting strategy, low TC). The insights from this study are useful for improved understanding of tropical eco-hydrological adaptation, drought coping strategies, and forest ecosystem regime shifts under future climate change.
Extreme weather events in early summer 2018 connected by a recurrent hemispheric wave-7 pattern
The summer of 2018 witnessed a number of extreme weather events such as heatwaves in North America, Western Europe and the Caspian Sea region, and rainfall extremes in South-East Europe and Japan that occurred near-simultaneously. Here we show that some of these extremes were connected by an amplified hemisphere-wide wavenumber 7 circulation pattern. We show that this pattern constitutes an important teleconnection in Northern Hemisphere summer associated with prolonged and above-normal temperatures in North America, Western Europe and the Caspian Sea region. This pattern was also observed during the European heatwaves of 2003, 2006 and 2015 among others. We show that the occurrence of this wave 7 pattern has increased over recent decades.
Corrigendum: The role of storage dynamics in annual wheat prices (2017 Environ. Res. Lett. 12 054005)
[no abstract available]
The CO2 reduction potential for the European industry via direct electrification of heat supply (power-to-heat)
The decarbonisation of industry is a bottleneck for the EU's 2050 target of climate neutrality. Replacing fossil fuels with low-carbon electricity is at the core of this challenge; however, the aggregate electrification potential and resulting system-wide CO2 reductions for diverse industrial processes are unknown. Here, we present the results from a comprehensive bottom-up analysis of the energy use in 11 industrial sectors (accounting for 92% of Europe's industry CO2 emissions), and estimate the technological potential for industry electrification in three stages. Seventy-eight per cent of the energy demand is electrifiable with technologies that are already established, while 99% electrification can be achieved with the addition of technologies currently under development. Such a deep electrification reduces CO2 emissions already based on the carbon intensity of today's electricity (∼300 gCO2 kWhel−1). With an increasing decarbonisation of the power sector IEA: 12 gCO2 kWhel−1 in 2050), electrification could cut CO2 emissions by 78%, and almost entirely abate the energy-related CO2 emissions, reducing the industry bottleneck to only residual process emissions. Despite its decarbonisation potential, the extent to which direct electrification will be deployed in industry remains uncertain and depends on the relative cost of electric technologies compared to other low-carbon options.
Implications of non-linearities between cumulative CO2 emissions and CO2-induced warming for assessing the remaining carbon budget
To determine the remaining carbon budget, a new framework was introduced in the Intergovernmental Panel on Climate Change's Special Report on Global Warming of 1.5 °C (SR1.5). We refer to this as a 'segmented' framework because it considers the various components of the carbon budget derivation independently from one another. Whilst implementing this segmented framework, in SR1.5 the assumption was that there is a strictly linear relationship between cumulative CO2 emissions and CO2-induced warming i.e. the TCRE is constant and can be applied to a range of emissions scenarios. Here we test whether such an approach is able to replicate results from model simulations that take the climate system's internal feedbacks and non-linearities into account. Within our modelling framework, following the SR1.5's choices leads to smaller carbon budgets than using simulations with interacting climate components. For 1.5 °C and 2 °C warming targets, the differences are 50 GtCO2 (or 10%) and 260 GtCO2 (or 17%), respectively. However, by relaxing the assumption of strict linearity, we find that this difference can be reduced to around 0 GtCO2 for 1.5 °C of warming and 80 GtCO2 (or 5%) for 2.0 °C of warming (for middle of the range estimates of the carbon cycle and warming response to anthropogenic emissions). We propose an updated implementation of the segmented framework that allows for the consideration of non-linearities between cumulative CO2 emissions and CO2-induced warming.
Common but differentiated leadership: strategies and challenges for carbon neutrality by 2050 across industrialized economies
Given their historic emissions and economic capability, we analyze a leadership role for representative industrialized regions (EU, US, Japan, and Australia) in the global climate mitigation effort. Using the global integrated assessment model REMIND, we systematically compare region-specific mitigation strategies and challenges of reaching domestic net-zero carbon emissions in 2050. Embarking from different emission profiles and trends, we find that all of the regions have technological options and mitigation strategies to reach carbon neutrality by 2050. Regional characteristics are mostly related to different land availability, population density and population trends: While Japan is resource limited with respect to onshore wind and solar power and has constrained options for carbon dioxide removal (CDR), their declining population significantly decreases future energy demand. In contrast, Australia and the US benefit from abundant renewable resources, but face challenges to curb industry and transport emissions given increasing populations and high per-capita energy use. In the EU, lack of social acceptance or EU-wide cooperation might endanger the ongoing transition to a renewable-based power system. CDR technologies are necessary for all regions, as residual emissions cannot be fully avoided by 2050. For Australia and the US, in particular, CDR could reduce the required transition pace, depth and costs. At the same time, this creates the risk of a carbon lock-in, if decarbonization ambition is scaled down in anticipation of CDR technologies that fail to deliver. Our results suggest that industrialized economies can benefit from cooperation based on common themes and complementary strengths. This may include trade of electricity-based fuels and materials as well as the exchange of regional experience on technology scale-up and policy implementation.
Corrigendum: Projections for headwater catchments of the Tarim River reveal glacier retreat and decreasing surface water availability but uncertainties are large (2016 Environ. Res. Lett. 11 054024)
This is a correction for 2016 Environ. Res. Lett. 11 054024
Inconsistent recognition of uncertainty in studies of climate change impacts on forests
Background. Uncertainty about climate change impacts on forests can hinder mitigation and adaptation actions. Scientific enquiry typically involves assessments of uncertainties, yet different uncertainty components emerge in different studies. Consequently, inconsistent understanding of uncertainty among different climate impact studies (from the impact analysis to implementing solutions) can be an additional reason for delaying action. In this review we (a) expanded existing uncertainty assessment frameworks into one harmonised framework for characterizing uncertainty, (b) used this framework to identify and classify uncertainties in climate change impacts studies on forests, and (c) summarised the uncertainty assessment methods applied in those studies. Methods. We systematically reviewed climate change impact studies published between 1994 and 2016. We separated these studies into those generating information about climate change impacts on forests using models –'modelling studies', and those that used this information to design management actions—'decision-making studies'. We classified uncertainty across three dimensions: nature, level, and location, which can be further categorised into specific uncertainty types. Results. We found that different uncertainties prevail in modelling versus decision-making studies. Epistemic uncertainty is the most common nature of uncertainty covered by both types of studies, whereas ambiguity plays a pronounced role only in decision-making studies. Modelling studies equally investigate all levels of uncertainty, whereas decision-making studies mainly address scenario uncertainty and recognised ignorance. Finally, the main location of uncertainty for both modelling and decision-making studies is within the driving forces—representing, e.g. socioeconomic or policy changes. The most frequently used methods to assess uncertainty are expert elicitation, sensitivity and scenario analysis, but a full suite of methods exists that seems currently underutilized. Discussion & Synthesis. The misalignment of uncertainty types addressed by modelling and decision-making studies may complicate adaptation actions early in the implementation pathway. Furthermore, these differences can be a potential barrier for communicating research findings to decision-makers.
An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures
Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.