Carbon price variations in 2°C scenarios explored

AIM AND SCOPE Clarify the variations in carbon prices found in mitigation scenarios that limit global mean surface temperature increase to below 2°C relative to preindustrial levels. CONTEXT Integrated assessment models1 (IAM) are dominant tools for the development of long-term emissions scenarios in line with climate objectives. There is a large variety of IAMs and, together with variations in socioeconomic and technological assumptions, this variety results in important differences in model behavior. For the achievement of low emissions scenarios, models typically assume or produce an implicit shadow price for carbon or represent policy instruments, including carbon pricing. This briefing aims at exploring and understanding the variation in these carbon price estimates for stringent climate change mitigation scenarios. The focus of this exercise will be on scenarios that limit global mean temperature surface increase (henceforth, warming) to below 2°C relative to preindustrial levels with a greater than 66% probability. This choice is driven by data availability for this particular temperature objective, and does not represent an official or scientific interpretation of the Paris Agreement long-term temperature goal. The assumption is that the qualitative insights would also to

Evaluating Process-Based Integrated Assessment Models of Climate Change Mitigation

Process-based integrated assessment models (IAMs) analyse transformation pathways to mitigate climate change. Confidence in models is established by testing their structural assumptions and comparing their behaviour against observations as well as other models. Climate model evaluation is concerted, and prominently reported in a dedicated chapter in the IPCC WG1 assessments. By comparison, evaluation of process-based IAMs tends to be less visible and more dispersed among modelling teams, with the exception of model inter-comparison projects. We contribute the first comprehensive analysis of process-based IAM evaluation, drawing on a wide range of examples across eight different evaluation methods testing both structural and behavioural validity. For each evaluation method, we compare its application to process-based IAMs with its application to climate models, noting similarities and differences, and seeking useful insights for strengthening the evaluation of process-based IAMs. We find that each evaluation method has distinctive strengths and limitations, as well as constraints on their application. We develop a systematic evaluation framework combining multiple methods that should be embedded within the development and use of process-based IAMs

PRACTICAL IMPLEMENTATION OF PHOTOGRAMMETRY FOR THE MODELLING OF A CYLINDRICAL HISTORICAL BUILDING

This work deals with the image capture for close-range photogrammetry in the context of the modelling of a round tower with repetitive texture (made of bricks), both inside and outside. For that purpose we test different acquisition strategies that differ in terms of camera path (straight or circular) and number of images acquired at each camera position, that is with or without oblique images. Besides, the formula to compute the curvilinear base according to a given overlap rate between successive frontal photos are written for each strategy. The comparisons rely on the observation of the aspect of the different dense point clouds (noise, holes), the deformation seen in the orthomosaics and values extracted from the photogrammetric projects such as metric accuracies with GCP. Our results confirm some art rules

Systematic map of the literature on carbon lock-in induced by long-lived capital

Long-lived capital-stocks (LLCS) such as infrastructure and buildings have significant and long-lasting implications for greenhouse gas emissions. They contribute to carbon lock-in and may hinder a rapid decarbonization of energy systems. Here we provide a systematic map of the literature on carbon lock-in induced by LLCS. Based on a structured search of the Web of Science and Scopus, we identified 226 publications from 38 095 search results using a supervised machine learning approach. We show biases toward power generation and toward developed countries. We also identify 11 indicators used to quantify carbon lock-in. Quantifications of committed emissions (cumulative emissions that would occur over the remaining operational lifetime of an asset) or stranded assets (premature retirement/retrofitting or under-utilization of assets along a given pathway) are the most commonly used metrics, whereas institutional indicators are scarcely represented. The synthesis of quantifications shows that (i) global committed emissions have slightly increased over time, (ii) coal power plants are a major source of committed emissions and are exposed to risk of becoming stranded, (iii) delayed mitigation action increases stranded assets and (iv) sectoral distribution and amount of stranded assets differ between countries. A thematic analysis of policy implications highlights the need to assure stability and legitimacy of climate policies and to enable coordination between stakeholders. Carbon pricing is one of the most cited policy instrument, but the literature emphasizes that it should not be the only instrument used and should instead be complemented with other policy instruments, such as technical regulations and financial support for low carbon capital deployment. Further research is warranted on urban-scale, in developing countries and outside the electricity generation sector, notably on buildings, where stranded assets could be high.BMBF, 01LA1826A, Ökonomie des Klimawandels - Verbundprojekt: Die politische Ökonomie eines globalen Kohleausstiegs (PEGASOS) - Teilprojekt 1: Koordination, Analyse der politischen Ökonomie vergangener KohleausstiegeEC/H2020/821124/EU/Next generation of AdVanced InteGrated Assessment modelling to support climaTE policy making/NAVIGAT

The cost of mitigation revisited

Estimates of economic implications of climate policy are important inputs into policy-making. Despite care to contextualize quantitative assessments of mitigation costs, one strong view outside academic climate economics is that achieving Paris Agreement goals implies sizable macroeconomic losses. Here, we argue that this notion results from unwarranted simplification or omission of the complexities of quantifying mitigation costs, which generates ambiguity in communication and interpretation. We synthesize key factors influencing mitigation cost estimates to guide interpretation of estimates, for example from the Intergovernmental Panel on Climate Change, and suggest ways to improve the underlying models. We propose alternatives for the scenario design framework, the framing of mitigation costs and the methods used to derive them, to better inform public debate and policy

Enhancing global climate policy ambition towards a 1.5 °C stabilization: a short-term multi-model assessment

The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO2eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios

Exploring the possibility space: taking stock of the diverse capabilities and gaps in integrated assessment models

Integrated assessment models (IAMs) have emerged as key tools for building and assessing long term climate mitigation scenarios. Due to their central role in the recent IPCC assessments, and international climate policy analyses more generally, and the high uncertainties related to future projections, IAMs have been critically assessed by scholars from different fields receiving various critiques ranging from adequacy of their methods to how their results are used and communicated. Although IAMs are conceptually diverse and evolved in very different directions, they tend to be criticised under the umbrella of 'IAMs'. Here we first briefly summarise the IAM landscape and how models differ from each other. We then proceed to discuss six prominent critiques emerging from the recent literature, reflect and respond to them in the light of IAM diversity and ongoing work and suggest ways forward. The six critiques relate to (a) representation of heterogeneous actors in the models, (b) modelling of technology diffusion and dynamics, (c) representation of capital markets, (d) energy-economy feedbacks, (e) policy scenarios, and (f) interpretation and use of model results

Geometry of GL_n(C) on infinity: complete collineations, projective compactifications, and universal boundary

Consider a finite dimensional (generally reducible) polynomial representation \rho of GL_n. A projective compactification of GL_n is the closure of \rho(GL_n) in the space of all operators defined up to a factor (this class of spaces can be characterized as equivariant projective normal compactifications of GL_n). We give an expicit description for all projective compactifications. We also construct explicitly (in elementary geometrical terms) a universal object for all projective compactifications of GL_n.Comment: 24 pages, corrected varian

Mitigation Pathways Compatible with Long-term Goals (Chapter 3)

Chapter 3 assesses the emissions pathways literature in order to identify their key characteristics (both in commonalities and differences) and to understand how societal choices may steer the system into a particular direction (high confidence). More than 2000 quantitative emissions pathways were submitted to the IPCC’s Sixth Assessment Report AR6 scenarios database, out of which 1202 scenarios included sufficient information for assessing the associated warming consistent with WGI

Annex III: Scenarios and modelling methods

The use of scenarios and modelling methods are pillars in IPCC Working Group III (WGIII) Assessment Reports. Past WGIII assessment report cycles identified knowledge gaps about the integration of modelling across scales and disciplines, mainly between global integrated assessment modelling methods and bottom-up modelling insights of mitigation responses. The need to improve the transparency of model assumptions and enhance the communication of scenario results was also recognised. This annex on Scenarios and Modelling Methods aims to address some of these gaps by detailing the modelling frameworks applied in the WGIII Sixth Assessment Report (AR6) chapters and disclose scenario assumptions and its key parameters. It has been explicitly included in the Scoping Meeting Report of the WGIII contribution to the AR6 and approved by the IPCC Panel at the 46th Session of the Panel