212 research outputs found

    Stakeholder-designed scenarios for global food security assessments

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    To guide policymaking, decision makers require a good understanding of the long-term drivers of food security and their interactions. Scenario analysis is widely considered as the appropriate tool to assess ‘wicked problems’, such as ensuring global food security, that are characterized by a high level of complexity and uncertainty. This paper describes the development process, storylines and drivers of four new global scenarios that are specifically designed to explore global food security up to the year 2050. To ensure the relevance, credibility and legitimacy of the scenarios, they have been developed using a participatory process, involving a diverse group of stakeholders. The scenarios consist of storylines and a scenario database that presents projections for key drivers, which can be used as an input into global simulation models

    IMAGE and MESSAGE Scenarios Limiting GHG Concentration to Low Levels

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    This report discusses the attainability of low greenhouse gas concentrations levels based on an analysis using two integrated assessment models (MESSAGE and IMAGE). Model runs were preformed which explored the feasibility of reaching radiative forcing levels in 2100 between 2.6 to 2.9 W/m2 above pre-industrial levels. Such low targets are necessary to limit global mean temperature increase to below 2oC compared to pre-industrial levels with high probability. The analysis examines the attainability of low targets systematically with respect to key uncertainties, including alternative baseline development pathways, availability of different technologies, emissions of bio-energy, and impacts of forestry and land use assumptions. A number of sensitivity tests were carried out to test the robustness of achieving low GHG concentration targets. The results from the two models are discussed in detail comprising energy profiles and emission pathways consistent with such low stabilization targets

    Scenarios to explore global food security up to 2050: Development process, storylines and quantification of drivers

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    To guide policymaking, decision makers require a good understanding of the long-term drivers of food security and their interactions. Scenario analysis is widely considered as the appropriate tool to assess complex and uncertain problems, such as food security. This paper describes the development process, storylines and drivers of four new global scenarios up to the year 2050 that are specifically designed for food security modelling. To ensure the relevance, credibility and legitimacy of the scenarios a highly participatory process is used, involving a diverse group of stakeholders. A novel approach is introduced to quantify a selection of key drivers that directly can be used as input in global integrated assessment models to assess the impact of aid, trade, agricultural and science policies on global food and nutrition security

    Future air pollution in the Shared Socio-economic Pathways

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    Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high, central, and low pollution control ambitions over the 21st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. The resulting pollutant emission trajectories under the SSP scenarios cover a wider range than the scenarios used in previous international climate model comparisons. In the SSP3 and SSP4 scenarios, where economic, institutional and technological limitations slow air quality improvements, global pollutant emissions over the 21st century can be comparable to current levels. Pollutant emissions in the SSP1 scenarios fall to low levels due to the assumption of technological advances and successful global action to control emissions

    Interactions between social learning and technological learning in electric vehicle futures

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    The transition to electric vehicles is an important strategy for reducing greenhouse gas emissions from passenger cars. Modelling transition pathways helps identify critical drivers and uncertainties. Global integrated assessment models (IAMs) have been used extensively to analyse climate mitigation policy. IAMs emphasise technological change processes but are largely silent on important social and behavioural dimensions to technological transitions. Here, we develop a novel conceptual framing and empirical evidence base on social learning processes relevant for vehicle adoption. We then implement this formulation of social learning in IMAGE, a widely-used global IAM. We apply this new modelling approach to analyse how technological learning and social learning interact to influence electric vehicle transition dynamics. We find that technological learning and social learning processes can be mutually reinforcing. Increased electric vehicle market shares can induce technological learning which reduces technology costs while social learning stimulates diffusion from early adopters to more risk-averse adopter groups. In this way, both types of learning process interact to stimulate each other. In the absence of social learning, however, the perceived risks of electric vehicle adoption among later adopting groups remains prohibitively high. In the absence of technological learning, electric vehicles remain relatively expensive and therefore only for early adopters an attractive choice. This first-of-its-kind model formulation of both social and technological learning is a significant contribution to improving the behavioural realism of global IAMs. Applying this new modelling approach emphasises the importance of market heterogeneity, real-world consumer decision-making, and social dynamics as well as technology parameters, to understand climate mitigation potentials

    The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: An overview

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    This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and a middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 500-1100 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than 120 GtCO2 per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: 1) the policy assumptions, 2) the socio-economic narrative, and 3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m2 differs in our analysis thus by about a factor of three across the SSP scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitigation and adaptation challenges, the resulting narratives and quantifications span a wide range of different futures broadly representative of the current literature. This allows their subsequent use and development in new assessments and research projects. Critical next steps for the community scenario process will, among others, involve regional and sectorial extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP scenarios with the new generation of earth system models as part of the 6th climate model intercomparison project (CMIP6)

    Quantum dynamics in strong fluctuating fields

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    A large number of multifaceted quantum transport processes in molecular systems and physical nanosystems can be treated in terms of quantum relaxation processes which couple to one or several fluctuating environments. A thermal equilibrium environment can conveniently be modelled by a thermal bath of harmonic oscillators. An archetype situation provides a two-state dissipative quantum dynamics, commonly known under the label of a spin-boson dynamics. An interesting and nontrivial physical situation emerges, however, when the quantum dynamics evolves far away from thermal equilibrium. This occurs, for example, when a charge transferring medium possesses nonequilibrium degrees of freedom, or when a strong time-dependent control field is applied externally. Accordingly, certain parameters of underlying quantum subsystem acquire stochastic character. Herein, we review the general theoretical framework which is based on the method of projector operators, yielding the quantum master equations for systems that are exposed to strong external fields. This allows one to investigate on a common basis the influence of nonequilibrium fluctuations and periodic electrical fields on quantum transport processes. Most importantly, such strong fluctuating fields induce a whole variety of nonlinear and nonequilibrium phenomena. A characteristic feature of such dynamics is the absence of thermal (quantum) detailed balance.Comment: review article, Advances in Physics (2005), in pres

    Sampling frequency affects estimates of annual nitrous oxide fluxes

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    Quantifying nitrous oxide (N2O) fluxes, a potent greenhouse gas, from soils is necessary to improve our knowledge of terrestrial N2O losses. Developing universal sampling frequencies for calculating annual N2O fluxes is difficult, as fluxes are renowned for their high temporal variability. We demonstrate daily sampling was largely required to achieve annual N2O fluxes within 10% of the "best" estimate for 28 annual datasets collected from three continents - Australia, Europe and Asia. Decreasing the regularity of measurements either under- or overestimated annual N2O fluxes, with a maximum overestimation of 935%. Measurement frequency was lowered using a sampling strategy based on environmental factors known to affect temporal variability, but still required sampling more than once a week. Consequently, uncertainty in current global terrestrial N2O budgets associated with the upscaling of field-based datasets can be decreased significantly using adequate sampling frequencies

    Ecosystem resistance in the face of climate change: a case study from the freshwater marshes of the Florida Everglades

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    Shaped by the hydrology of the Kissimmee-Okeechobee-Everglades watershed, the Florida Everglades is composed of a conglomerate of wetland ecosystems that have varying capacities to sequester and store carbon. Hydrology, which is a product of the region’s precipitation and temperature patterns combined with water management policy, drives community composition and productivity. As shifts in both precipitation and air temperature are expected over the next 100 years as a consequence of climate change, CO2 dynamics in the greater Everglades are expected to change. To reduce uncertainties associated with climate change and to explore how projected changes in atmospheric CO2 concentration and climate can alter current CO2 exchange rates in Everglades freshwater marsh ecosystems, we simulated fluxes of carbon among the atmosphere, vegetation, and soil using the DAYCENT model. We explored the effects of low, moderate, and high scenarios for atmospheric CO2 (550, 850, and 950 ppm), mean annual air temperature (ĂŸ1, ĂŸ2.5, and ĂŸ4.28C) and precipitation (2, ĂŸ7, and ĂŸ14%), as predicted by the IPCC for the year 2100 for the region, on CO2 exchange rates in short- and long-hydroperiod wetland ecosystems. Under 100 years of current climate and atmospheric CO2 concentration, Everglades freshwater marsh ecosystems were estimated to be CO2-neutral. As atmospheric CO2 concentration increased and under climate change projections, there were slight shifts in the start and length of the wet season (1 to ĂŸ7 days) and a small enhancement in the sink capacity (by 169 to 573 g C m2 century1 ) occurred at both short- and longhydroperiod ecosystems compared to CO2 dynamics under the current climate regime. Over 100 years, rising temperatures increased net CO2 exchange rates (ĂŸ1 to 13 g C m2 century1 ) and shifts in precipitation patterns altered cumulative net carbon uptake by ĂŸ13 to 46 g C m2 century1 . While changes in ecosystem structure, species composition, and disturbance regimes were beyond the scope of this research, results do indicate that climate change will produce small changes in CO2 dynamics in Everglades freshwater marsh ecosystems and suggest that the hydrologic regime and oligotrophic conditions of Everglades freshwater marshes lowers the ecosystem sensitivity to climate change. Key word
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