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- ItemAerial river management by smart cross-border reforestation(Amsterdam [u.a.] : Elsevier Science, 2019) Weng, Wei; Costa, Luís; Lüdeke, Matthias K.B.; Zemp, Delphine C.In the face of increasing socio-economic and climatic pressures in growing cities, it is rational for managers to consider multiple approaches for securing water availability. One often disregarded option is the promotion of reforestation in source regions supplying important quantities of atmospheric moisture transported over long distances through aerial rivers, affecting water resources of a city via precipitation and runoff (‘smart reforestation’). Here we present a case demonstrating smart reforestation's potential as a water management option. Using numerical moisture back-tracking models, we identify important upwind regions contributing to the aerial river of Santa Cruz de la Sierra (Bolivia). Simulating the effect of reforestation in the identified regions, annual precipitation and runoff reception in the city was found to increase by 1.25% and 2.30% respectively, while runoff gain during the dry season reached 26.93%. Given the city's population growth scenarios, the increase of the renewable water resource by smart reforestation could cover 22–59% of the additional demand by 2030. Building on the findings, we argue for a more systematic consideration of aerial river connections between regions in reforestation and land planning for future challenges. © 2019 The Authors
- ItemProducing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change(Amsterdam [u.a.] : Elsevier Science, 2019) Warren, R.F.; Edwards, N.R.; Babonneau, F.; Bacon, P.M.; Dietrich, J.P.; Ford, R.W.; Garthwaite, P.; Gerten, D.; Goswami, S.; Haurie, A.; Hiscock, K.; Holden, P.B.; Hyde, M.R.; Joshi, S.R.; Kanudia, A.; Labriet, M.; Leimbach, M.; Oyebamiji, O.K.; Osborn, T.; Pizzileo, B.; Popp, A.; Price, J.; Riley, G.D.; Schaphoff, S.; Slavin, P.; Vielle, M.; Wallace, C.We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal. © 2018 The Authors
- ItemWeb technologies for environmental Big Data(Amsterdam [u.a.] : Elsevier Science, 2014) Vitolo, Claudia; Elkhatib, Yehia; Reusser, Dominik; Macleod, Christopher J.A.; Buytaert, WouterRecent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources.
- ItemAvailable and missing data to model impact of climate change on European forests(Amsterdam [u.a.] : Elsevier Science, 2019) Ruiz-Benito, Paloma; Vacchiano, Giorgio; Lines, Emily R.; Reyer, Christopher P.O.; Ratcliffe, Sophia; Morin, Xavier; Hartig, Florian; Mäkelä, Annikki; Yousefpour, Rasoul; Chaves, Jimena E.; Palacios-Orueta, Alicia; Benito-Garzón, Marta; Morales-Molino, Cesar; Camarero, J. Julio; Jump, Alistair S.; Kattge, Jens; Lehtonen, Aleksi; Ibrom, Andreas; Owen, Harry J.F.; Zavala, Miguel A.Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests. © 2019 The Author(s)
- ItemLooking under the hood: A comparison of techno-economic assumptions across national and global integrated assessment models(Amsterdam [u.a.] : Elsevier Science, 2018) Krey, Volker; Guo, Fei; Kolp, Peter; Zhou, Wenji; Schaeffer, Roberto; Awasthy, Aayushi; Bertram, Christoph; de Boer, Harmen-Sytze; Fragkos, Panagiotis; Fujimori, Shinichiro; He, Chenmin; Iyer, Gokul; Keramidas, Kimon; Köberle, Alexandre C.; Oshiro, Ken; Reis, Lara Aleluia; Shoai-Tehrani, Bianka; Vishwanathan, Saritha; Capros, Pantelis; Drouet, Laurent; Edmonds, James E.; Garg, Amit; Gernaat, David E.H.J.; Jiang, Kejun; Kannavou, Maria; Kitous, Alban; Kriegler, Elmar; Luderer, Gunnar; Mathur, Ritu; Muratori, Matteo; Sano, Fuminori; van Vuuren, Detlef P.Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. © 2019 The Authors
- ItemHow global climate policy could affect competitiveness(Amsterdam [u.a.] : Elsevier Science, 2019) Ward, Hauke; Steckel, Jan Christoph; Jakob, MichaelA global uniform carbon price would be economically efficient and at the same time avoid ‘carbon-leakage’. Still, it will affect the competitiveness of specific industries, economic activity and employment across countries. This paper assesses short-term economic shocks following the introduction of a global carbon price that would be in line with the Paris Agreement. Based on the World Input-Output Database (WIOD), we trace the carbon content of final output through global supply chains. This allows us to estimate how prices of the final output would react to the introduction of a global carbon price. We find that impacts on industrial competitiveness are highly heterogeneous across regions and economic sectors. The competitive position of Brazil, Japan, the USA and advanced economies of the EU is likely to improve, whereas industries and labor markets in newly industrializing Asian economies as well as Eastern Europe are likely to experience substantial adverse impacts. © 2019 The Author(s)
- ItemRapid aggregation of global gridded crop model outputs to facilitate cross-disciplinary analysis of climate change impacts in agriculture(Amsterdam [u.a.] : Elsevier Science, 2015) Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, CarolWe discuss an on-line tool that facilitates access to the large collection of climate impacts on crop yields produced by the Agricultural Model Intercomparison and Improvement Project. This collection comprises the output of seven crop models which were run on a global grid using climate data from five different general circulation models under the current set of representative pathways. The output of this modeling endeavor consists of more than 36,000 publicly available global grids at a spatial resolution of one half degree. We offer flexible ways to aggregate these data while reducing the technical barriers implied by learning new download platforms and specialized formats. The tool is accessed trough any standard web browser without any special bandwidth requirement.
- ItemTo what extent is climate change adaptation a novel challenge for agricultural modellers?(Amsterdam [u.a.] : Elsevier Science, 2019) Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Özkan Gülzari, Ş.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sándor, R.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V.Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. © 2019 The Authors
- ItemThe implications of initiating immediate climate change mitigation - A potential for co-benefits?(Amsterdam [u.a.] : Elsevier Science, 2014) Schwanitz, Valeria Jana; Longden, Thomas; Knopf, Brigitte; Capros, PantelisFragmented climate policies across parties of the United Nations Framework on Climate Change have led to the question of whether initiating significant and immediate climate change mitigation can support the achievement of other non-climate objectives. We analyze such potential co-benefits in connection with a range of mitigation efforts using results from eleven integrated assessment models. These model results suggest that an immediate mitigation of climate change coincide for Europe with an increase in energy security and a higher utilization of non-biomass renewable energy technologies. In addition, the importance of phasing out coal is highlighted with external cost estimates showing substantial health benefits consistent with the range of mitigation efforts.
- ItemCO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies(Amsterdam [u.a.] : Elsevier Science, 2013) Bauer, Nico; Bosetti, Valentina; Hamdi-Cherif, Meriem; Kitous, Alban; McCollum, David; Méjean, Aurélie; Rao, Shilpa; Turton, Hal; Paroussos, Leonidas; Ashina, Shuichi; Calvin, Katherine; Wada, Kenichi; van Vuuren, DetlefThis paper explores a multi-model scenario ensemble to assess the impacts of idealized and non-idealized climate change stabilization policies on fossil fuel markets. Under idealized conditions climate policies significantly reduce coal use in the short- and long-term. Reductions in oil and gas use are much smaller, particularly until 2030, but revenues decrease much more because oil and gas prices are higher than coal prices. A first deviation from optimal transition pathways is delayed action that relaxes global emission targets until 2030 in accordance with the Copenhagen pledges. Fossil fuel markets revert back to the no-policy case: though coal use increases strongest, revenue gains are higher for oil and gas. To balance the carbon budget over the 21st century, the long-term reallocation of fossil fuels is significantly larger—twice and more—than the short-term distortion. This amplifying effect results from coal lock-in and inter-fuel substitution effects to balance the full-century carbon budget. The second deviation from the optimal transition pathway relaxes the global participation assumption. The result here is less clear-cut across models, as we find carbon leakage effects ranging from positive to negative because trade and substitution patterns of coal, oil, and gas differ across models. In summary, distortions of fossil fuel markets resulting from relaxed short-term global emission targets are more important and less uncertain than the issue of carbon leakage from early mover action.