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Riahi, K.; van Vuuren, D.P.; Kriegler, E.; Edmonds, J.; O’Neill, B.C.; Fujimori, S.; Bauer, N.; Calvin, K.; Dellink, R.; Fricko, O.; Lutz, W.; Popp, A.; Cuaresma, J.C.; KC, S.; Leimbach, M.; Jiang, L.; Kram, T.; Rao, S.; Emmerling, J.; Ebi, K.; Hasegawa, T.; Havlik, P.; Humpenöder, F.; Da Silva, L.A.; Smith, S.; Stehfest, E.; Bosetti, V.; Eom, J.; Gernaat, D.; Masui, T.; Rogelj, J.; Strefler, J.; Drouet, L.; Krey, V.; Luderer, G.; Harmsen, M.; Takahashi, K.; Baumstark, L.; Doelman, J.C.; Kainuma, M.; Klimont, Z.; Marangoni, G.; Lotze-Campen, H.; Obersteiner, M.; Tabeau, A.; Tavoni, M. |
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Title |
The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview |
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Journal Article |
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Year |
2017 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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Volume |
42 |
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153-168 |
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Keywords |
Shared Socioeconomic Pathways; SSP; Climate change; RCP; Community scenarios; Mitigation; Adaptation |
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Abstract |
Abstract 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 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 400–1200 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 that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker 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 sectoral 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). |
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2017-06-13 |
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0959-3780 |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5008 |
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Author |
Below, T.B.; Mutabazi, K.D.; Kirschke, D.; Franke, C.; Sieber, S.; Siebert, R.; Tscherning, K. |
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Title |
Can farmers’ adaptation to climate change be explained by socio-economic household-level variables |
Type |
Journal Article |
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Year |
2012 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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Volume |
22 |
Issue |
1 |
Pages |
223-235 |
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Keywords |
Sub-Saharan Africa; Tanzania; Adaptive capacity; Index; Vulnerability; Adaptation; adaptive capacity; environmental-change; south-africa; vulnerability; variability; resilience; tanzania; framework; drought; policy |
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Abstract |
A better understanding of processes that shape farmers’ adaptation to climate change is critical to identify vulnerable entities and to develop well-targeted adaptation policies. However, it is currently poorly understood what determines farmers’ adaptation and how to measure it. In this study, we develop an activity-based adaptation index (AAI) and explore the relationship between socioeconomic variables and farmers’ adaptation behavior by means of an explanatory factor analysis and a multiple linear regression model using latent variables. The model was tested in six villages situated in two administrative wards in the Morogoro region of Tanzania. The Mlali ward represents a system of relatively high agricultural potential, whereas the Gairo ward represents a system of low agricultural potential. A household survey, a rapid rural appraisal and, a stakeholder workshop were used for data collection. The data were analyzed using factor analysis, multiple linear regression, descriptive statistical methods and qualitative content analysis. The empirical results are discussed in the context of theoretical concepts of adaptation and the sustainable livelihood approach. We found that public investment in rural infrastructure, in the availability and technically efficient use of inputs, in a good education system that provides equal chances for women, and in the strengthening of social capital, agricultural extension and, microcredit services are the best means of improving the adaptation of the farmers from the six villages in Gairo and Mlali. We conclude that the newly developed AAI is a simple but promising way to capture the complexity of adaptation processes that addresses a number of shortcomings of previous index studies. |
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English |
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0959-3780 |
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TradeM |
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MA @ admin @ |
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4467 |
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