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    A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
    (Katlenburg-Lindau : Copernicus, 2020) Laj, Paolo; Bigi, Alessandro; Rose, Clémence; Andrews, Elisabeth; Lund Myhre, Cathrine; Collaud Coen, Martine; Lin, Yong; Wiedensohler, Alfred; Schulz, Michael; Ogren, John A.; Fiebig, Markus; Prenni, Anthony; Reisen, Fabienne; Romano, Salvatore; Sellegri, Karine; Sharma, Sangeeta; Schauer, Gerhard; Sheridan, Patrick; Sherman, James Patrick; Schütze, Maik; Schwerin, Andreas; Tuch, Thomas; Sohmer, Ralf; Sorribas, Mar; Steinbacher, Martin; Sun, Junying; Titos, Gloria; Toczko, Barbara; Tulet, Pierre; Tunved, Peter; Vakkari, Ville; Velarde, Fernando; Velasquez, Patricio; Villani, Paolo; Vratolis, Sterios; Wang, Sheng-Hsiang; Weinhold, Kay; Gliß, Jonas; Weller, Rolf; Yela, Margarita; Yus-Diez, Jesus; Zdimal, Vladimir; Zieger, Paul; Zikova, Nadezda; Mortier, Augustin; Pandolfi, Marco; Petäja, Tuukka; Kim, Sang-Woo; Aas, Wenche; Putaud, Jean-Philippe; Mayol-Bracero, Olga; Keywood, Melita; Labrador, Lorenzo; Aalto, Pasi; Ahlberg, Erik; Alados Arboledas, Lucas; Alastuey, Andrés; Andrade, Marcos; Artíñano, Begoña; Ausmeel, Stina; Arsov, Todor; Asmi, Eija; Backman, John; Baltensperger, Urs; Bastian, Susanne; Bath, Olaf; Beukes, Johan Paul; Brem, Benjamin T.; Bukowiecki, Nicolas; Conil, Sébastien; Couret, Cedric; Day, Derek; Dayantolis, Wan; Degorska, Anna; Eleftheriadis, Konstantinos; Fetfatzis, Prodromos; Favez, Olivier; Flentje, Harald; Gini, Maria I.; Gregorič, Asta; Gysel-Beer, Martin; Hallar, A. Gannet; Hand, Jenny; Hoffer, Andras; Hueglin, Christoph; Hooda, Rakesh K.; Hyvärinen, Antti; Kalapov, Ivo; Kalivitis, Nikos; Kasper-Giebl, Anne; Kim, Jeong Eun; Kouvarakis, Giorgos; Kranjc, Irena; Krejci, Radovan; Kulmala, Markku; Labuschagne, Casper; Lee, Hae-Jung; Lihavainen, Heikki; Lin, Neng-Huei; Löschau, Gunter; Luoma, Krista; Marinoni, Angela; Martins Dos Santos, Sebastiao; Meinhardt, Frank; Merkel, Maik; Metzger, Jean-Marc; Mihalopoulos, Nikolaos; Nguyen, Nhat Anh; Ondracek, Jakub; Pérez, Noemi; Perrone, Maria Rita; Petit, Jean-Eudes; Picard, David; Pichon, Jean-Marc; Pont, Veronique; Prats, Natalia
    Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.
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    Impacts of enhanced weathering on biomass production for negative emission technologies and soil hydrology
    (Katlenburg-Lindau [u.a.] : Copernicus, 2020) De Oliveira Garcia, Wagner; Amann, Thorben; Hartmann, Jens; Karstens, Kristine; Popp, Alexander; Boysen, Lena R.; Smith, Pete; Goll, Daniel
    Limiting global mean temperature changes to well below 2 °C likely requires a rapid and large-scale deployment of negative emission technologies (NETs). Assessments so far have shown a high potential of biomass-based terrestrial NETs, but only a few assessments have included effects of the commonly found nutrient-deficient soils on biomass production. Here, we investigate the deployment of enhanced weathering (EW) to supply nutrients to areas of afforestation-reforestation and naturally growing forests (AR) and bioenergy grasses (BG) that are deficient in phosphorus (P), besides the impacts on soil hydrology. Using stoichiometric ratios and biomass estimates from two established vegetation models, we calculated the nutrient demand of AR and BG. Insufficient geogenic P supply limits C storage in biomass. For a mean P demand by AR and a lowgeogenic-P-supply scenario, AR would sequester 119 Gt C in biomass; for a high-geogenic-P-supply and low-AR-Pdemand scenario, 187 Gt C would be sequestered in biomass; and for a low geogenic P supply and high AR P demand, only 92 GtC would be accumulated by biomass. An average amount of ∼ 150 Gt basalt powder applied for EW would be needed to close global P gaps and completely sequester projected amounts of 190 Gt C during the years 2006-2099 for the mean AR P demand scenario (2-362 Gt basalt powder for the low-AR-P-demand and for the high-AR-P-demand scenarios would be necessary, respectively). The average potential of carbon sequestration by EW until 2099 is ∼ 12 GtC (∼ 0:2-∼ 27 Gt C) for the specified scenarios (excluding additional carbon sequestration via alkalinity production). For BG, 8 kg basaltm2 a1 might, on average, replenish the exported potassium (K) and P by harvest. Using pedotransfer functions, we show that the impacts of basalt powder application on soil hydraulic conductivity and plant-Available water, to close predicted P gaps, would depend on basalt and soil texture, but in general the impacts are marginal. We show that EW could potentially close the projected P gaps of an AR scenario and nutrients exported by BG harvest, which would decrease or replace the use of industrial fertilizers. Besides that, EW ameliorates the soil's capacity to retain nutrients and soil pH and replenish soil nutrient pools. Lastly, EW application could improve plant-Available-water capacity depending on deployed amounts of rock powder - adding a new dimension to the coupling of land-based biomass NETs with EW. © 2020 Royal Society of Chemistry. All rights reserved.
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    Climate and air quality impacts due to mitigation of non-methane near-term climate forcers
    (Katlenburg-Lindau : EGU, 2020) Allen, Robert J.; Turnock, Steven; Nabat, Pierre; Neubauer, David; Lohmann, Ulrike; Olivié, Dirk; Oshima, Naga; Michou, Martine; Wu, Tongwen; Zhang, Jie; Takemura, Toshihiko; Schulz, Michael; Tsigaridis, Kostas; Bauer, Susanne E.; Emmons, Louisa; Horowitz, Larry; Naik, Vaishali; van Noije, Twan; Bergman, Tommi; Lamarque, Jean-Francois; Zanis, Prodromos; Tegen, Ina; Westervelt, Daniel M.; Le Sager, Philippe; Good, Peter; Shim, Sungbo; O’Connor, Fiona; Akritidis, Dimitris; Georgoulias, Aristeidis K.; Deushi, Makoto; Sentman, Lori T.; John, Jasmin G.; Fujimori, Shinichiro; Collins, William J.
    It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015-2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry-climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with weak (SSP3-7.0) versus strong (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2:5) and ozone (O3) decrease by 2:20:32 ugm3 and 4:60:88 ppb, respectively (changes quoted here are for the entire 2015-2055 time period; uncertainty represents the 95% confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0:250:12K and 0:030:012mmd1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0:660:20K and 0:030:02mmd1), south Asia (0:470:16K and 0:170:09mmd1), and east Asia (0:460:20K and 0:150:06mmd1). Relatively large warming and wetting of the Arctic also occur at 0:590:36K and 0:040:02mmd1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
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    Perspectives from CO+RE: How COVID-19 changed our food systems and food security paradigms
    (Amsterdam : Elsevier, 2020) Bakalis, Serafim; Valdramidis, Vasilis P.; Argyropoulos, Dimitrios; Ahrne, Lilia; Chen, Jianshe; Cullen, P.J.; Cummins, Enda; Datta, Ashim K.; Emmanouilidis, Christos; Foster, Tim; Fryer, Peter J.; Gouseti, Ourania; Hospido, Almudena; Knoerzer, Kai; LeBail, Alain; Marangoni, Alejandro G.; Rao, Pingfan; Schlüter, Oliver K.; Taoukis, Petros; Xanthakis, Epameinondas; Van Impe, Jan F.M.
    [no abstract available]
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    The GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
    (Katlenburg-Lindau : Copernicus, 2020) Franke, James A.; Müller, Christoph; Elliott, Joshua; Ruane, Alex C.; Jägermeyr, Jonas; Balkovic, Juraj; Ciais, Philippe; Dury, Marie; Falloon, Pete D.; Folberth, Christian; François, Louis; Hank, Tobias; Hoffmann, Munir; Izaurralde, R. Cesar; Jacquemin, Ingrid; Jones, Curtis; Khabarov, Nikolay; Koch, Marian; Li, Michelle; Liu, Wenfeng; Olin, Stefan; Phillips, Meridel; Pugh, Thomas A. M.; Reddy, Ashwan; Wang, Xuhui; Williams, Karina; Zabel, Florian; Moyer, Elisabeth J.
    Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.
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    Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
    (Katlenburg-Lindau : Copernicus, 2020) Lasch-Born, Petra; Suckow, Felicitas; Reyer, Christopher P. O.; Gutsch, Martin; Kollas, Chris; Badeck, Franz-Werner; Bugmann, Harald K. M.; Grote, Rüdiger; Fürstenau, Cornelia; Lindner, Marcus; Schaber, Jörg
    The process-based model 4C (FORESEE) has been developed over the past 20 years to study climate impacts on forests and is now freely available as an open-source tool. The objective of this paper is to provide a comprehensive description of this 4C version (v2.2) for scientific users of the model and to present an evaluation of 4C at four different forest sites across Europe. The evaluation focuses on forest growth as well as carbon (net ecosystem exchange, gross primary production), water (actual evapotranspiration, soil water content), and heat fluxes (soil temperature) using data from the PROFOUND database. We applied different evaluation metrics and compared the daily, monthly, and annual variability of observed and simulated values. The ability to reproduce forest growth (stem diameter and biomass) differs from site to site and is best for a pine stand in Germany (Peitz, model efficiency ME=0.98). 4C is able to reproduce soil temperature at different depths in Sorø and Hyytiälä with good accuracy (for all soil depths ME > 0.8). The dynamics in simulating carbon and water fluxes are well captured on daily and monthly timescales (0.51 < ME < 0.983) but less so on an annual timescale (ME < 0). This model–data mismatch is possibly due to the accumulation of errors because of processes that are missing or represented in a very general way in 4C but not with enough specific detail to cover strong, site-specific dependencies such as ground vegetation growth. These processes need to be further elaborated to improve the projections of climate change on forests. We conclude that, despite shortcomings, 4C is widely applicable, reliable, and therefore ready to be released to the scientific community to use and further develop the model.
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    A Gini approach to spatial CO2 emissions
    (San Francisco, California, US : PLOS, 2020) Zhou, Bin; Thies, Stephan; Gudipudi, Ramana; Lüdeke, Matthias K.B.; Kropp, Jürgen P.; Rybski, Diego
    Combining global gridded population and fossil fuel based CO2 emission data at 1 km scale, we investigate the spatial origin of CO2 emissions in relation to the population distribution within countries. We depict the correlations between these two datasets by a quasi-Lorenz curve which enables us to discern the individual contributions of densely and sparsely populated regions to the national CO2 emissions. We observe pronounced country-specific characteristics and quantify them using an indicator resembling the Gini-index. As demonstrated by a robustness test, the Gini-index for each country arise from a compound distribution between the population and emissions which differs among countries. Relating these indices with the degree of socio-economic development measured by per capita Gross Domestic Product (GDP) at purchase power parity, we find a strong negative correlation between the two quantities with a Pearson correlation coefficient of -0.71. More specifically, this implies that in developing countries locations with large population tend to emit relatively more CO2, and in developed countries the opposite tends to be the case. Based on the relation to urban scaling, we discuss the implications for CO2 emissions from cities. Our results show that general statements with regard to the (in)efficiency of large cities should be avoided as it is subject to the socio-economic development of respective countries. Concerning the political relevance, our results suggest a differentiated spatial prioritization in deploying climate change mitigation measures in cities for developed and developing countries.
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    Social tipping dynamics for stabilizing Earth's climate by 2050
    (2020) Otto, Ilona M.; Donges, Jonathan F.; Cremades, Roger; Bhowmik, Avit; Hewitt, Richard J.; Lucht, Wolfgang; Rockström, Johan; Allerberger, Franziska; McCaffrey, Mark; Doe, Sylvanus S.P.; Lenferna, Alex; Morán, Nerea; van Vuuren, Detlef P.; Schellnhuber, Hans Joachim
    Safely achieving the goals of the Paris Climate Agreement requires a worldwide transformation to carbon-neutral societies within the next 30 y. Accelerated technological progress and policy implementations are required to deliver emissions reductions at rates sufficiently fast to avoid crossing dangerous tipping points in the Earth's climate system. Here, we discuss and evaluate the potential of social tipping interventions (STIs) that can activate contagious processes of rapidly spreading technologies, behaviors, social norms, and structural reorganization within their functional domains that we refer to as social tipping elements (STEs). STEs are subdomains of the planetary socioeconomic system where the required disruptive change may take place and lead to a sufficiently fast reduction in anthropogenic greenhouse gas emissions. The results are based on online expert elicitation, a subsequent expert workshop, and a literature review. The STIs that could trigger the tipping of STE subsystems include 1) removing fossil-fuel subsidies and incentivizing decentralized energy generation (STE1, energy production and storage systems), 2) building carbon-neutral cities (STE2, human settlements), 3) divesting from assets linked to fossil fuels (STE3, financial markets), 4) revealing the moral implications of fossil fuels (STE4, norms and value systems), 5) strengthening climate education and engagement (STE5, education system), and 6) disclosing information on greenhouse gas emissions (STE6, information feedbacks). Our research reveals important areas of focus for larger-scale empirical and modeling efforts to better understand the potentials of harnessing social tipping dynamics for climate change mitigation.
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    Communicating sentiment and outlook reverses inaction against collective risks
    (Washington, DC : National Acad. of Sciences, 2020) Wang, Zhen; Jusup, Marko; Guo, Hao; Shi, Lei; Geček, Sunčana; Anand, Madhur; Perc, Matjaž; Bauch, Chris T.; Kurths, Jürgen; Boccaletti, Stefano; Schellnhuber, Hans Joachim
    Collective risks permeate society, triggering social dilemmas in which working toward a common goal is impeded by selfish interests. One such dilemma is mitigating runaway climate change. To study the social aspects of climate-change mitigation, we organized an experimental game and asked volunteer groups of three different sizes to invest toward a common mitigation goal. If investments reached a preset target, volunteers would avoid all consequences and convert their remaining capital into monetary payouts. In the opposite case, however, volunteers would lose all their capital with 50% probability. The dilemma was, therefore, whether to invest one's own capital or wait for others to step in. We find that communicating sentiment and outlook helps to resolve the dilemma by a fundamental shift in investment patterns. Groups in which communication is allowed invest persistently and hardly ever give up, even when their current investment deficits are substantial. The improved investment patterns are robust to group size, although larger groups are harder to coordinate, as evidenced by their overall lower success frequencies. A clustering algorithm reveals three behavioral types and shows that communication reduces the abundance of the free-riding type. Climate-change mitigation, however, is achieved mainly by cooperator and altruist types stepping up and increasing contributions as the failure looms. Meanwhile, contributions from free riders remain flat throughout the game. This reveals that the mechanisms behind avoiding collective risks depend on an interaction between behavioral type, communication, and timing.
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    Paris Climate Agreement passes the cost-benefit test
    ([London] : Nature Publishing Group UK, 2020) Glanemann, Nicole; Willner, Sven N.; Levermann, Anders
    The Paris Climate Agreement aims to keep temperature rise well below 2 °C. This implies mitigation costs as well as avoided climate damages. Here we show that independent of the normative assumptions of inequality aversion and time preferences, the agreement constitutes the economically optimal policy pathway for the century. To this end we consistently incorporate a damage-cost curve reproducing the observed relation between temperature and economic growth into the integrated assessment model DICE. We thus provide an inter-temporally optimizing cost-benefit analysis of this century’s climate problem. We account for uncertainties regarding the damage curve, climate sensitivity, socioeconomic future, and mitigation costs. The resulting optimal temperature is robust as can be understood from the generic temperature-dependence of the mitigation costs and the level of damages inferred from the observed temperature-growth relationship. Our results show that the politically motivated Paris Climate Agreement also represents the economically favourable pathway, if carried out properly.