What do near-term observations tell us about long-term developments in greenhouse gas emissions? A letter

Long-term scenarios developed by integrated assessment models are used in climate research to provide an indication of plausible long-term emissions of greenhouse gases and other radiatively active substances based on developments in the global energy system, land-use and the emissions associated with these systems The phenomena that determine these long-term developments (several decades or even centuries) are very different than those that operate on a shorter time-scales (a few years) Nevertheless, in the literature, we still often find direct comparisons between short-term observations and long-term developments that do not take into account the differing dynamics over these time scales In this letter, we discuss some of the differences between the factors that operate in the short term and those that operate in the long term We use long-term historical emissions trends to show that short-term observations are very poor indicators of long-term future emissions developments Based on this, we conclude that the performance of long-term scenarios should be evaluated against the appropriate, corresponding long-term variables and trends The research community may facilitate this by developing appropriate data sets and protocols that can be used to test the performance of long-term scenarios and the models that produce the

Phase equilibria and Heusler phase stability in the Cu-rich portion of the Cu-Al-Mn system

Results pertaining to the phase equilibria between the phases alpha (A1), beta (A2, B2 or L2(1)(D0(3))) and gamma (gamma-bronze type), and the two-stage order-disorder transition and decomposition reaction A2-B2-L2(1) in the ternary system Cu-Al-Mn are reported. Ternary isothermal section diagrams at 800, 700, 600 and 550 degrees C have been constructed using Energy Dispersion X-ray Spectrometry (EDX) analysis results, and it is found that the beta single-phase region in the Cu-Al system is very significantly widened on increasing the Mn content. The critical temperatures (T-c) of the A2-B2-L2, order-disorder transitions, determined by Differential Scanning Carolimetory (DSC) analysis are found to be strongly dependent on the Al content rather than on the Mn content. It is confirmed by DSC measurements and TEM-EDX analysis that a miscibility gap island between Cu3Al and Cu2AlMn phases exists in the L2(1) phase region. The second order ordering reaction between D0(3) and L2(1) structures has also been detected by X-ray diffraction. The stability of the bcc beta phase is discussed in terms of atomic and magnetic ordering. (C) 1998 Elsevier Science S.A

Chapter 7 - Energy systems

Stabilizing greenhouse gas (GHG) concentrations will require large-scale transformations in human societies, from the way that we produce and consume energy to how we use the land surface. A natural question in this context is what will be the .transformation pathway. towards stabilization; that is, how do we get from here to there? The topic of this chapter is transformation pathways. The chapter is primarily motivated by three questions. First, what are the near-term and future choices that define transformation pathways, including the goal itself, the emissions pathway to the goal, technologies used for and sectors contributing to mitigation, the nature of international coordination, and mitigation policies? Second, what are the key characteristics of different transformation pathways, including the rates of emissions reductions and deployment of low-carbon energy, the magnitude and timing of aggregate economic costs, and the implications for other policy objectives such as those generally associated with sustainable development? Third, how will actions taken today influence the options that might be available in the future? As part of the assessment in this chapter, data from over 1000 new scenarios published since the IPCC Fourth Assessment Report (AR4) were collected from integrated modelling research groups, many from large-scale model intercomparison studies. In comparison to AR4, new scenarios, both in this AR5 dataset and more broadly in the literature assessed in this chapter, consider more ambitious concentration goals, a wider range of assumptions about technology, and more possibilities for delays in additional global mitigation beyond that of today and fragmented international action

Managing uncertainty: a review of food system scenario analysis and modelling

Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address