Learning and climate feedbacks: Optimal climate insurance and fat tails

We study the effect of potentially severe climate change on optimal climate change policy, accounting for learning and uncertainty in the climate system. In particular, we test how fat upper tailed uncertainty over the temperature change from a doubling of greenhouse gases (the climate sensitivity), affects economic growth and emissions policy. In addition, we examine whether and how fast uncertainties could be diminished through Bayesian learning. Our results indicate that while overall learning is slow, the mass of the fat tail diminishes quickly, since observations near the mean provide evidence against fat tails. We denote as “tail learning” the case where the planner rejects high values of the climate sensitivity with high confidence, even though significant uncertainty remains. Fat tailed uncertainty without learning reduces current emissions by 38% relative to certainty, indicating significant climate insurance, or paying to limit emissions today to reduce the risk of very high temperature changes, is optimal. However, learning reduces climate insurance by about 50%. The optimal abatement policy is strongly influenced by the current state of knowledge, even though greenhouse gas (GHG) emissions are difficult to reverse. Once the mass of the fat tail diminishes, the remaining uncertainty is largely irrelevant for optimal emissions policy.     

Cumulative carbon emissions and economic policy: In search of general principles

We exploit recent advances in climate science to develop a physically consistent, yet surprisingly simple, model of climate policy. It seems that key economic models have greatly overestimated the delay between carbon emissions and warming, and ignored the saturation of carbon sinks that takes place when the atmospheric concentration of carbon dioxide rises. This has important implications for climate policy. If carbon emissions are abated, damages are avoided almost immediately. Therefore it is optimal to reduce emissions significantly in the near term and bring about a slow transition to optimal peak warming, even if optimal steady-state/peak warming is high. The optimal carbon price should start relatively high and grow relatively fast.     

Linking species- and ecosystem-level impacts of climate change in lakes with a complex and a minimal model

To study the interaction between species- and ecosystem-level impacts of climate change, we focus on the question of how climate-induced shifts in key species affect the positive feedback loops that lock shallow lakes either in a transparent, macrophyte-dominated state or, alternatively, in a turbid, phytoplankton-dominated state. We hypothesize that climate warming will weaken the resilience of the macrophyte-dominated clear state. For the turbid state, we hypothesize that climate warming and climate-induced eutrophication will increase the dominance of cyanobacteria. Climate change will also affect shallow lakes through a changing hydrology and through climate change-induced eutrophication. We study these phenomena using two models, the full ecosystem model PCLake and a minimal dynamic model of lake phosphorus dynamics. Quantitative predictions with the complex model show that changes in nutrient loading, hydraulic loading and climate warming can all lead to shifts in ecosystem state. The minimal model helped in interpreting the non-linear behaviour of the complex model. The main output parameters of interest for water quality managers are the critical nutrient loading at which the system will switch from clear to turbid and the much lower critical nutrient loading – due to hysteresis – at which the system switches back. Another important output parameter is the chlorophyll-a level in the turbid state. For each of these three output parameters we performed a sensitivity analysis to further understand the dynamics of the complex model PCLake. This analysis showed that our model results are most sensitive to changes in temperature-dependence of cyanobacteria, planktivorous fish and zooplankton. We argue that by combining models at various levels of complexity and looking at multiple aspects of climate changes simultaneously we can develop an integrated view of the potential impact of climate change on freshwater ecosystems.     

Inclusive development,oil extraction and climate change: a multilevel analysis of Kenya

There has been considerable research on North–South issues on climate change; however, little work has been done on how the recent discovery of oil in some developing countries could affect North–South relations, the prospects for development for the South, climate change and local socio-environmental issues. Using the theory of inclusive development, the concept of the Right to Development, and their relation to stranded assets, this paper addresses the question: what does inclusive development imply at the national and global level in dealing with oil extraction in the context of climate change? Based on a literature review and a layered case study of Kenya, this paper concludes that (a) Kenyans argue that Kenya has a right to extract and use oil resources and that rich countries should reduce their extraction and use; (b) such a claim could be integrated in an appropriate emissions trading scheme; and that (c) Kenya should also account for the national and local socioecological aspects to reduce potential local conflict, yet the conditions favoring inclusive development are not yet established. However, such an argument may also lead to perverse results. If addressing climate change requires phasing out fossil fuels, this argument may lead to stranded assets in both developed and developing countries, and may ironically leave developing countries poorer off as stranded assets are possibly more expensive than having stranded resources.     

Predicting extinctions as a result of climate change

Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that extinction vulnerability increases with decreasing distribution size. We also found that model fit decreases with decreasing distribution size, resulting in high prediction uncertainty among narrowly distributed species. High prediction uncertainty creates a conservation dilemma in that excluding these species under-predicts extinction risk and favors mistaken inaction on global warming. By contrast, including narrow endemics results in over-predicting extinction risk and promotes mistaken inaction on behalf of individual species prematurely considered doomed to extinction.     

Effects of boreal forest management practices on the climate impact of CO2 emissions from bioenergy

In Life Cycle Assessment (LCA), carbon dioxide (CO₂) emissions from biomass combustion are traditionally assumed climate neutral if the bioenergy system is CO₂ flux neutral, i.e. the quantity of CO₂ released approximately equals the amount of CO₂ sequestered in biomass. This convention is a plausible assumption for fast growing biomass species, but is inappropriate for slower growing biomass, like forests. In this case, the climate impact from biomass combustion can be potentially underestimated if CO₂ emissions are ignored, or overestimated, if biogenic CO₂ is considered equal to anthropogenic CO₂. The estimation of the effective climate impact should take into account how the CO₂ fluxes are distributed over time: the emission of CO₂ from bioenergy approximately occurs at a single point in time, while the absorption by the new trees is spread over several decades. Our research target is to include this dynamic time dimension in unit-based impact analysis, using a boreal forest stand as case study. The boreal forest growth is modelled with an appropriate function, and is investigated under different forestry regimes (affecting the growth rate and the year of harvest). Specific atmospheric decay functions for biomass-derived CO₂ are then elaborated for selected combinations of forest management options. The contribution to global warming is finally quantified using the GWP_bio index as climate metric. Results estimates the effects of these practices on the characterization factor used for the global warming potential of CO₂ from bioenergy, and point out the key role played by the selected time horizon.     

Phenological tracking enables positive species responses to climate change

Earlier spring phenology observed in many plant species in recent decades provides compelling evidence that species are already responding to the rising global temperatures associated with anthropogenic climate change. There is great variability among species, however, in their phenological sensitivity to temperature. Species that do not phenologically "track" climate change may be at a disadvantage if their growth becomes limited by missed interactions with mutualists, or a shorter growing season relative to earlier-active competitors. Here, we set out to test the hypothesis that phenological sensitivity could be used to predict species performance in a warming climate, by synthesizing results across terrestrial warming experiments. We assembled data for 57 species across 24 studies where flowering or vegetative phenology was matched with a measure of species performance. Performance metrics included biomass, percent cover, number of flowers, or individual growth. We found that species that advanced their phenology with warming also increased their performance, whereas those that did not advance tended to decline in performance with warming. This indicates that species that cannot phenologically "track" climate may be at increased risk with future climate change, and it suggests that phenological monitoring may provide an important tool for setting future conservation priorities.     

Weather,salience of climate change and congressional voting

Climate change is a complex long-run phenomenon. The speed and severity with which it is occurring is difficult to observe, complicating the formation of beliefs for individuals. We use Google search intensity data as a proxy for the salience of climate change and examine how search patterns vary with unusual local weather. We find that searches for “climate change” and “global warming” increase with extreme temperatures and unusual lack of snow. Furthermore, we demonstrate that effects of abnormal weather extend beyond search behavior to observable action on environmental issues. We examine the voting records of members of the U.S. Congress from 2004 to 2011 and find that members are more likely to take a pro-environment stance on votes when their home state experiences unusual weather.     

The social cost of carbon revisited

An estimate of the social cost of carbon (SCC) is crucial to climate policy. But how should we estimate the SCC? A common approach uses an integrated assessment model (IAM) to simulate time paths for the atmospheric CO₂ concentration, its impact on temperature, and resulting reductions in GDP. I have argued that IAMs have deficiencies that make them poorly suited for this job, but what is the alternative? I present an approach to estimating an average SCC, which I argue can be a useful guide for policy. I rely on a survey of experts to elicit opinions regarding (1) probabilities of alternative economic outcomes of climate change, but not the causes of those outcomes; and (2) the reduction in emissions required to avert an extreme outcome, i.e., a large climate-induced reduction in GDP. The average SCC is the ratio of the present value of lost GDP from an extreme outcome to the total emission reduction needed to avert that outcome. I discuss the survey instrument, explain how experts were identified, and present results. I obtain SCC estimates of $200/mt or higher, but the variation across experts is large. Trimming outliers and focusing on experts who expressed a high degree of confidence in their answers yields lower SCCs, $80 to $100/mt, but still well above the IAM-based estimates used by the U.S. government.     

气候变化对亚高山暗针叶林土壤温室气体排放的影响

利用生物地球化学模犁Forest-DNDC模拟气候变化对贡嘎山亚高山暗针叶林土壤温室气体的释放的影响.以位于贡嘎山东坡海拔3 000 m的峨眉冷杉(Abies fabri)中龄林为研究对象,以1999-2006年8年的日气候数据进行平均得到的日平均最高温度、日平均最低温度和日平均降水总最作为基线(Base)气候情景,另外设置了温度+2℃(升)、温度.2℃(T-)、降水量+20%(P+)、降水量-20%(P-)、温度十2℃同时降水量+20%(T+P+)、温度-2℃同时降水量-20%(T-P-)、温度+2℃同时降水量-20%(T+P-)、温度-2℃同时降水量+20%(T-P+)8种气候变化情景.结果显示:贡嘎山峨眉冷杉林土壤CO_2释放随着温度增加而增加,土壤N_2O释放对降水量改变敏感,而土壤NO的释放对温度和降水的改变均比较敏感,二者表现为协同作用.温度+2℃同时降水量+20%(升P+)情景下土壤CO_2释放最高,高于基线情景的36.08%;温度-2℃同时降水量+20%(T-P+)情景下土壤CO_2释放最低,低于基线情景的36.89%.土壤N_2O释放随着降水量的增加而升高,随着降水量减少而降低;温度和降水最同时增加时土壤NO释放均高于单一增加温度或降水量情景,而温度和降水量同时降低时土壤NO释放均低于单一降低温度或降水量情景.     

Rewilding in the face of climate change

Expansion of the global protected-area network has been proposed as a strategy to address threats from accelerating climate change and species extinction. A key step in increasing the effectiveness of such expansion is understanding how novel threats to biodiversity from climate change alter concepts such as rewilding, which have underpinned many proposals for large interconnected reserves. We reviewed potential challenges that climate change poses to rewilding and found that the conservation value of large protected areas persists under climate change. Nevertheless, more attention should be given to protection of microrefugia, macrorefugia, complete environmental gradients, and areas that connect current and future suitable climates and to maintaining ecosystem processes and stabilizing feedbacks via conservation strategies that are resilient to uncertainty regarding climate trends. Because a major element of the threat from climate change stems from its novel geographic patterns, we examined, as an example, the implications for climate-adaptation planning of latitudinal, longitudinal (continental to maritime), and elevational gradients in climate-change exposure across the Yellowstone-to-Yukon region, the locus of an iconic conservation proposal initially designed to conserve wide-ranging carnivore species. In addition to a continued emphasis on conserving intact landscapes, restoration of degraded low-elevation areas within the region is needed to capture sites important for landscape-level climate resilience. Extreme climate exposure projected for boreal North America suggests the need for ambitious goals for expansion of the protected-area network there to include refugia created by topography and ecological features, such as peatlands, whose conservation can also reduce emissions from carbon stored in soil. Qualitative understanding of underlying reserve design rules and the geography of climate-change exposure can strengthen the outcomes of inclusive regional planning processes that identify specific sites for protection.     

Cost,environmental impact,and resilience of renewable energy under a changing climate: a review

Energy derived from fossil fuels contributes significantly to global climate change, accounting for more than 75% of global greenhouse gas emissions and approximately 90% of all carbon dioxide emissions. Alternative energy from renewable sources must be utilized to decarbonize the energy sector. However, the adverse effects of climate change, such as increasing temperatures, extreme winds, rising sea levels, and decreased precipitation, may impact renewable energies. Here we review renewable energies with a focus on costs, the impact of climate on renewable energies, the impact of renewable energies on the environment, economy, and on decarbonization in different countries. We focus on solar, wind, biomass, hydropower, and geothermal energy. We observe that the price of solar photovoltaic energy has declined from $0.417 in 2010 to $0.048/kilowatt-hour in 2021. Similarly, prices have declined by 68% for onshore wind, 60% for offshore wind, 68% for concentrated solar power, and 14% for biomass energy. Wind energy and hydropower production could decrease by as much as 40% in some regions due to climate change, whereas solar energy appears the least impacted energy source. Climate change can also modify biomass productivity, growth, chemical composition, and soil microbial communities. Hydroelectric power plants are the most damaging to the environment; and solar photovoltaics must be carefully installed to reduce their impact. Wind turbines and biomass power plants have a minimal environmental impact; therefore, they should be implemented extensively. Renewable energy sources could decarbonize 90% of the electricity industry by 2050, drastically reducing carbon emissions, and contributing to climate change mitigation. By establishing the zero carbon emission decarbonization concept, the future of renewable energy is promising, with the potential to replace fossil fuel-derived energy and limit global temperature rise to 1.5 °C by 2050.

     

Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system

A fully non-linear analysis of forcing influences on temperatures is performed in the climate system by means of neural network modelling. Two case studies are investigated, in order to establish the main factors that drove the temperature behaviour at both global and regional scales in the last 140 years. In particular, our neural network model shows the ability to catch non-linear relationships among these variables and to reconstruct temperature records with a high degree of accuracy. In this framework, we clearly show the need of including anthropogenic inputs for explaining the temperature behaviour at global scale and recognise the role of El Niño southern oscillation for catching the inter-annual variability of temperature data. Furthermore, we analyse the relative influence of global forcing and a regional circulation pattern in determining the winter temperatures in Central England, showing that the North Atlantic oscillation represents the driven element in this case study. Our modelling activity and results can be very useful for simple assessments of relationships in the complex climate system and for identifying the fundamental elements leading to a successful downscaling of atmosphere–ocean general circulation models.     

Stadtklima

This two-part review paper is attended to the urban climate. After referring to the spatial and temporal scales as well as to the historical developments in urban climate, Part 1 introduces the methods of measuring urban climate parameters and the characteristics of the urban climate in relation to its rural surroundings. Examples are given for some central-European cities. The premises and causes of the urban climate are discussed: the conversion of natural ground cover into sealed surfaces, anthropogenic heat release and emissions of air pollutants. The importance of factors like the behaviour of thermal and hydrological properties of urban surfaces which influence urban climate in the micro-and mesoscale are described by means of some examples. Implications for the resulting energy balance of urban surfaces are quantified in terms of the sub-surface heat flux, the sensible and latent heat flux densites. Part 2 (Main features and effects) describes the features and human-biometeorological effects of the urban climate, takes up planning aspects and discusses the impact of global warming to urban climate.     

Airborne black carbon variations during the COVID-19 lockdown in the Yangtze River Delta megacities suggest actions to curb global warming

Environmental Chemistry Letters - Airborne black carbon is a strong warming component of the atmosphere. Therefore, curbing black carbon emissions should slow down global warming. The 2019...     

Understanding Recent Climate Change

Abstract:  The Earth's atmosphere has a natural greenhouse effect, without which the global mean surface temperature would be about 33 °C lower and life would not be possible. Human activities have increased atmospheric concentrations of carbon dioxide, methane, and other gases in trace amounts. This has enhanced the greenhouse effect, resulting in surface warming. Were it not for the partly offsetting effects of increased aerosol concentrations, the increase in global mean surface temperature over the past 100 years would be larger than observed. Continued surface warming through the 21st century is inevitable and will likely have widespread ecological impacts. The magnitude and rate of warming for the global average will be largely dictated by the strength and direction of climate feedbacks, thermal inertia of the oceans, the rate of greenhouse gas emissions, and aerosol concentrations. Because of regional expressions of climate feedbacks, changes in atmospheric circulation, and a suite of other factors, the magnitude and rate of warming and changes in other key climate elements, such as precipitation, will not be uniform across the planet. For example, due to loss of its floating sea-ice cover, the Arctic will warm the most .     

Impact of climate changes on pollution levels in Denmark

The impact of climate changes on the pollution levels in Denmark is the major topic of this paper. Variations of the Danish air pollution levels that are caused by climatic changes are studied together with variations caused by other factors (emissions, inter-annual variability of meteorological conditions, etc.). The Unified Danish Eulerian Model (UNI-DEM) was run on a fine, 10 km × 10 km, grid over a space domain covering all of Europe to minimize the influence of the boundary conditions on the Danish pollution levels. This study is based on four categories of scenarios: (i) traditional scenarios, (ii) climatic scenarios, (iii) scenarios with variations of the human-made (anthropogenic) emissions and (iv) scenarios in which the biogenic emissions were varied. The total number of applied scenarios was 14, and a time-period of 16 years was used. The results show clearly that although the concentrations of the major pollutants do not depend too much on the climatic changes, some quantities, in particular quantities related to high ozone levels, might be increased significantly as a result of the warming trends in the future climate. The reason for this phenomenon is explained.     

土壤微生物呼吸热适应性与微生物群落及多样性对全球气候变化响应研究

土壤微生物呼吸热适应性被认为是决定陆地生态系统对全球变暖反馈作用的潜在重要机制,可能显著改变未来的气候变化趋势,然而,土壤微生物群落结构变化如何引起土壤微生物呼吸热适应性的研究目前尚存争议.该文针对气候变化对土壤微生物呼吸的影响研究,梳理了当前对土壤微生物呼吸的热适应性是否存在的争议和不同观点与结论,综述了气候变化对土...     

Cost-effective unilateral climate policy design: Size matters

Given the bleak prospects for a global agreement on mitigating climate change, pressure for unilateral abatement is increasing. A major challenge is emissions leakage. Border carbon adjustments and output-based allocation of emissions allowances can increase effectiveness of unilateral action but introduce distortions of their own. We assess antileakage measures as a function of abatement coalition size. We first develop a partial equilibrium analytical framework to see how these instruments affect emissions within and outside the coalition. We then employ a computable general equilibrium model of international trade and energy use to assess the strategies as the coalition grows. We find that full border adjustments rank first in global cost-effectiveness, followed by import tariffs and output-based rebates. The differences across measures and their overall appeal decline as the abatement coalition grows. In terms of cost, the coalition countries prefer border carbon adjustments; countries outside the coalition prefer output-based rebates.     

Revealing climate change opinions through investment behavior: Evidence from Fukushima

In this study we present a novel research approach to obtaining behavior-based evidence of regional climate change attitudes, using the 2011 Fukushima nuclear plant incident as a natural experiment. Our approach allows us to produce the first non-survey-based empirical evidence of a trans-Atlantic divide in public opinion on the environment and climate change that investors assign to fossil-based and renewable energy. This value is based on the perceived potential of these fuel types to substitute for nuclear generation in the aftermath of the Fukushima crisis. We carry out an event study to examine differences in abnormal returns of global coal and renewable energy companies on European and American stock exchanges. We find that investors trading on U.S. markets exhibit a significantly more favorable perception of coal stock profitability, while investors trading on European exchanges display a more favorable perception about profitability of renewable energy stocks.