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- ItemGreen transition, investment horizon, and dynamic portfolio decisions(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2022) Semmler, Willi; Lessmann, Kai; Tahri, Ibrahim; Braga, Joao Paulo; Boros, EndreThis paper analyzes the implications of investors’ short-term oriented asset holding and portfolio decisions (or short-termism), and its consequences on green investments. We adopt a dynamic portfolio model, which contrary to conventional static mean-variance models, allows us to study optimal portfolios for different decision horizons. Our baseline model contains two assets, one asset with fluctuating returns and another asset with a constant risk-free return. The asset with fluctuating returns can arise from fossil-fuel based sectors or from clean energy related sectors. We consider different drivers of short-termism: the discount rate, the nature of discounting (exponential vs. hyperbolic), and the decision horizon of investors itself. We study first the implications of these determinants of short-termism on the portfolio wealth dynamics of the baseline model. We find that portfolio wealth declines faster with a higher discount rate, with hyperbolic discounting, and with shorter decision horizon. We extend our model to include a portfolio of two assets with fluctuating returns. For both model variants, we explore the cases where innovation efforts are spent on fossil fuel or clean energy sources. Detailing dynamic portfolio decisions in such a way may allow us for better pathways to empirical tests and may provide guidance to some online financial decision making.
- ItemImpact of methane and black carbon mitigation on forcing and temperature: a multi-model scenario analysis(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Smith, Steven J.; Chateau, Jean; Dorheim, Kalyn; Drouet, Laurent; Durand-Lasserve, Olivier; Fricko, Oliver; Fujimori, Shinichiro; Hanaoka, Tatsuya; Harmsen, Mathijs; Hilaire, Jérôme; Keramidas, Kimon; Klimont, Zbigniew; Luderer, Gunnar; Moura, Maria Cecilia P.; Riahi, Keywan; Rogelj, Joeri; Sano, Fuminori; van Vuuren, Detlef P.; Wada, KenichiThe relatively short atmospheric lifetimes of methane (CH4) and black carbon (BC) have focused attention on the potential for reducing anthropogenic climate change by reducing Short-Lived Climate Forcer (SLCF) emissions. This paper examines radiative forcing and global mean temperature results from the Energy Modeling Forum (EMF)-30 multi-model suite of scenarios addressing CH4 and BC mitigation, the two major short-lived climate forcers. Central estimates of temperature reductions in 2040 from an idealized scenario focused on reductions in methane and black carbon emissions ranged from 0.18–0.26 °C across the nine participating models. Reductions in methane emissions drive 60% or more of these temperature reductions by 2040, although the methane impact also depends on auxiliary reductions that depend on the economic structure of the model. Climate model parameter uncertainty has a large impact on results, with SLCF reductions resulting in as much as 0.3–0.7 °C by 2040. We find that the substantial overlap between a SLCF-focused policy and a stringent and comprehensive climate policy that reduces greenhouse gas emissions means that additional SLCF emission reductions result in, at most, a small additional benefit of ~ 0.1 °C in the 2030–2040 time frame. © 2020, Battelle Memorial Institute.
- ItemPerformance evaluation of global hydrological models in six large Pan-Arctic watersheds(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Gädeke, Anne; Krysanova, Valentina; Aryal, Aashutosh; Chang, Jinfeng; Grillakis, Manolis; Hanasaki, Naota; Koutroulis, Aristeidis; Pokhrel, Yadu; Satoh, Yusuke; Schaphoff, Sibyll; Müller Schmied, Hannes; Stacke, Tobias; Tang, Qiuhong; Wada, Yoshihide; Thonicke, KirstenGlobal Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds. © 2020, The Author(s).
- ItemFood security under high bioenergy demand toward long-term climate goals(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Hasegawa, Tomoko; Sands, Ronald D.; Brunelle, Thierry; Cui, Yiyun; Frank, Stefan; Fujimori, Shinichiro; Popp, AlexanderBioenergy is expected to play an important role in the achievement of stringent climate-change mitigation targets requiring the application of negative emissions technology. Using a multi-model framework, we assess the effects of high bioenergy demand on global food production, food security, and competition for agricultural land. Various scenarios simulate global bioenergy demands of 100, 200, 300, and 400 exajoules (EJ) by 2100, with and without a carbon price. Six global energy-economy-agriculture models contribute to this study, with different methodologies and technologies used for bioenergy supply and greenhouse-gas mitigation options for agriculture. We find that the large-scale use of bioenergy, if not implemented properly, would raise food prices and increase the number of people at risk of hunger in many areas of the world. For example, an increase in global bioenergy demand from 200 to 300 EJ causes a − 11% to + 40% change in food crop prices and decreases food consumption from − 45 to − 2 kcal person−1 day−1, leading to an additional 0 to 25 million people at risk of hunger compared with the case of no bioenergy demand (90th percentile range across models). This risk does not rule out the intensive use of bioenergy but shows the importance of its careful implementation, potentially including regulations that protect cropland for food production or for the use of bioenergy feedstock on land that is not competitive with food production. © 2020, The Author(s).
- ItemHow evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Krysanova, Valentina; Zaherpour, Jamal; Didovets, Iulii; Gosling, Simon N.; Gerten, Dieter; Hanasaki, Naota; Müller Schmied, Hannes; Pokhrel, Yadu; Satoh, Yusuke; Tang, Qiuhong; Wada, YoshihideImportance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections. © 2020, The Author(s).
- ItemA statistical analysis of time trends in atmospheric ethane(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Friedrich, Marina; Beutner, Eric; Reuvers, Hanno; Smeekes, Stephan; Urbain, Jean-Pierre; Bader, Whitney; Franco, Bruno; Lejeune, Bernard; Mahieu, EmmanuelEthane is the most abundant non-methane hydrocarbon in the Earth’s atmosphere and an important precursor of tropospheric ozone through various chemical pathways. Ethane is also an indirect greenhouse gas (global warming potential), influencing the atmospheric lifetime of methane through the consumption of the hydroxyl radical (OH). Understanding the development of trends and identifying trend reversals in atmospheric ethane is therefore crucial. Our dataset consists of four series of daily ethane columns. As with many other decadal time series, our data are characterized by autocorrelation, heteroskedasticity, and seasonal effects. Additionally, missing observations due to instrument failure or unfavorable measurement conditions are common in such series. The goal of this paper is therefore to analyze trends in atmospheric ethane with statistical tools that correctly address these data features. We present selected methods designed for the analysis of time trends and trend reversals. We consider bootstrap inference on broken linear trends and smoothly varying nonlinear trends. In particular, for the broken trend model, we propose a bootstrap method for inference on the break location and the corresponding changes in slope. For the smooth trend model, we construct simultaneous confidence bands around the nonparametrically estimated trend. Our autoregressive wild bootstrap approach, combined with a seasonal filter, is able to handle all issues mentioned above (we provide R code for all proposed methods on https://www.stephansmeekes.nl/code.). © 2020, The Author(s).
- ItemImplications of climate change mitigation strategies on international bioenergy trade(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Daioglou, Vassilis; Muratori, Matteo; Lamers, Patrick; Fujimori, Shinichiro; Kitous, Alban; Köberle, Alexandre C.; Bauer, Nico; Junginger, Martin; Kato, Etsushi; Leblanc, Florian; Mima, Silvana; Wise, Marshal; van Vuuren, Detlef P.Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade. © 2020, The Author(s).
- ItemThe value of climate-resilient seeds for smallholder adaptation in sub-Saharan Africa(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Cacho, Oscar J.; Moss, Jonathan; Thornton, Philip K.; Herrero, Mario; Henderson, Ben; Bodirsky, Benjamin L.; Humpenöder, Florian; Popp, Alexander; Lipper, LeslieClimate change is threatening food security in many tropical countries, where a large proportion of food is produced by vulnerable smallholder farmers. Interventions are available to offset many of the negative impacts of climate change on agriculture, and they can be tailored to local conditions often through relative modest investments. However, little quantitative information is available to guide investment or policy choices at a time when countries and development agencies are under pressure to implement policies that can help achieve Sustainable Development Goals while coping with climate change. Among smallholder adaptation options, developing seeds resilient to current and future climate shocks expected locally is one of the most important actions available now. In this paper, we used national and local data to estimate the costs of climate change to smallholder farmers in Malawi and Tanzania. We found that the benefits from adopting resilient seeds ranged between 984 million and 2.1 billion USD during 2020–2050. Our analysis demonstrates the benefits of establishing and maintaining a flexible national seed sector with participation by communities in the breeding, delivery, and adoption cycle. © 2020, The Author(s).
- ItemInverse learning in Hilbert scales(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2023) Rastogi, Abhishake; Mathé, PeterWe study linear ill-posed inverse problems with noisy data in the framework of statistical learning. The corresponding linear operator equation is assumed to fit a given Hilbert scale, generated by some unbounded self-adjoint operator. Approximate reconstructions from random noisy data are obtained with general regularization schemes in such a way that these belong to the domain of the generator. The analysis has thus to distinguish two cases, the regular one, when the true solution also belongs to the domain of the generator, and the ‘oversmoothing’ one, when this is not the case. Rates of convergence for the regularized solutions will be expressed in terms of certain distance functions. For solutions with smoothness given in terms of source conditions with respect to the scale generating operator, then the error bounds can then be made explicit in terms of the sample size.
- ItemIntegrating climate change adaptation in coastal governance of the Barcelona metropolitan area(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2021) Sauer, Inga J.; Roca, Elisabet; Villares, MíriamCoastal cities are exposed to high risks due to climate change, as they are potentially affected by both rising sea levels and increasingly intense and frequent coastal storms. Socio-economic drivers also increase exposure to natural hazards, accelerate environmental degradation, and require adaptive governance structures to moderate negative impacts. Here, we use a social network analysis (SNA) combined with further qualitative information to identify barriers and enablers of adaptive governance in the Barcelona metropolitan area. By analyzing how climate change adaptation is mainstreamed between different administrative scales as well as different societal actors, we can determine the governance structures and external conditions that hamper or foster strategical adaptation plans from being used as operational adaptation tools. We identify a diverse set of stakeholders acting at different administrative levels (local to national), in public administration, science, civil society, and the tourism economy. The metropolitan administration acts as an important bridging organization by promoting climate change adaptation to different interest groups and by passing knowledge between actors. Nonetheless, national adaptation planning fails to take into account local experiences in coastal protection, which leads to an ineffective science policy interaction and limits adaptive management and learning opportunities. Overcoming this is difficult, however, as the effectiveness of local adaptation strategies in the Barcelona metropolitan area is very limited due to a strong centralization of power at the national level and a lack of polycentricity. Due to the high touristic pressure, the legal framework is currently oriented to primarily meet the demands of recreational use and tourism, prioritizing these aspects in daily management practice. Therefore, touristic and economic activities need to be aligned to adaptation efforts, to convert them from barriers into drivers for adaptation action. Our work strongly suggests that more effectively embedding adaptation planning and action into existing legal structures of coastal management would allow strategic adaptation plans to be an effective operational tool for local coastal governance.