Bridging analytical approaches for low-carbon transitions

Low-carbon transitions are long-term multi-faceted processes. Although integrated assessment models have many strengths for analysing such transitions, their mathematical representation requires a simplification of the causes, dynamics and scope of such societal transformations. We suggest that integrated assessment model-based analysis should be complemented with insights from socio-technical transition analysis and practice-based action research. We discuss the underlying assumptions, strengths and weaknesses of these three analytical approaches. We argue that full integration of these approaches is not feasible, because of foundational differences in philosophies of science and ontological assumptions. Instead, we suggest that bridging, based on sequential and interactive articulation of different approaches, may generate a more comprehensive and useful chain of assessments to support policy formation and action. We also show how these approaches address knowledge needs of different policymakers (international, national and local), relate to different dimensions of policy processes and speak to different policy-relevant criteria such as cost-effectiveness, socio-political feasibility, social acceptance and legitimacy, and flexibility. A more differentiated set of analytical approaches thus enables a more differentiated approach to climate policy making.</p

Quantifying biodiversity impacts of climate change and bioenergy: the role of integrated global scenarios

The role of bioenergy in climate change mitigation is a topic of heated debate, as the demand for land may result in social and ecological conflicts. Biodiversity impacts are a key controversy, given that biodiversity conservation is a globally agreed goal under pressure due to both climate change and land use. Impact assessment of bioenergy in various socio-economic and policy scenarios is a crucial basis for planning sound climate mitigation policy. Empirical studies have identified positive and negative local impacts of different bioenergy types on biodiversity, but ignored indirect impacts caused by displacement of other human activities. Integrated assessment models (IAMs) provide land-use scenarios based on socio-economic and policy storylines. Global scenarios capture both direct and indirect land-use change, and are therefore an appealing tool for assessing the impacts of bioenergy on biodiversity. However, IAMs have been originally designed to address questions of a different nature. Here, we illustrate the properties of IAMs from the biodiversity conservation perspective and discuss the set of questions they could answer. We find IAMs are a useful starting point for more detailed regional planning and assessment. However, they have important limitations that should not be overlooked. Global scenarios may not capture all impacts, such as changes in forest habitat quality or small-scale landscape structure, identified as key factors in empirical studies. We recommend increasing spatial accuracy of IAMs through region-specific, complementary modelling, including climate change into predictive assessments, and considering future biodiversity conservation needs in assessments of impacts and sustainable potentials of bioenergy.Peer reviewe

From Planetary Boundaries to national fair shares of the global safe operating space — How can the scales be bridged?

The planetary boundaries framework proposes quantitative global limits to the anthropogenic perturbation of crucial Earth system processes, and thus marks out a planetary safe operating space for human activities. Yet, decisions regarding resource use and emissions are mostly made at less aggregated scales, by national and sub-national governments, businesses, and other local actors. To operationalize the planetary boundaries concept, the boundaries need to be translated into and aligned with targets that are relevant at these decision-making scales. In this paper, we develop a framework that addresses the biophysical, socio-economic, and ethical dimensions of bridging across scales, to provide a consistently applicable approach for translating the planetary boundaries into national-level fair shares of Earth’s safe operating space. We discuss our findings in the context of previous studies and their implications for future analyses and policymaking. In this way, we link the planetary boundaries framework to widely-applied operational and policy concepts for more robust strong sustainability decision-making

Modelling global material stocks and flows for residential and service sector buildings towards 2050

Residential buildings and service sector buildings have an important contribution to climate change, directly via energy use in these buildings and indirectly through construction activities and the production and disposal of buildings materials. In this paper, we introduce a model that looks at total global building stock for 26 regions between 1970 and 2050 and calculates the floor space and building materials both in new buildings and in demolished buildings. For residential buildings, we build upon the work of Marinova et al. (2019, this issue), who used a building material database to come up with scenarios for materials in the residential building stock. This paper adds two things. First, we introduce a new regression-based model for service building floor space, recognizing 4 different types of service-related buildings. Secondly, we use a dynamic stock model, based on lifetime distributions found in literature, to calculate the construction (inflow) and demolition (outflow) of building floor space for both residential and service-related purposes. We combine this with data from the building material database to come up with scenarios for the annual demand for construction materials worldwide as well as an estimation of the availability of waste materials after building demolition towards 2050. The model can thus be used to assess the potential for closing the material cycles in the construction sector, while distinguishing urban and rural areas explicitly. The results show that demand for construction materials will continue to increase in most regions, even in developed countries. Global demand for steel and cement for the building sector is estimated to be 769 Mt/yr and 11.9 Gt/yr respectively, by the end of the modelling period. This represents a respective growth of 31% and 14% compared to today. Drivers behind this are an expected growth of global residential building stock of about 50%, and a growth of about 150% in the building stock for services. Our model projects that by 2050, only 55% of construction-related demand for copper, wood and steel could potentially be covered by recycled building materials. For other materials the availability of scrap may be higher, reaching up to 71% of new demand in the case of aluminium. This means that in most regions urban mining cannot cover the growing demand for construction materials

Modeling the Effects of Future Growing Demand for Charcoal in the Tropics

Global demand for charcoal is increasing mainly due to urban population in developing countries. More than half the global population now lives in cities, and urban-dwellers are restricted to charcoal use because of easiness of production, access, transport, and tradition. Increasing demand for charcoal, however, may lead to increasing impacts on forests, food, and water resources, and may even create additional pressures on the climate system. Here we assess how different charcoal scenarios based on the Shared Socio-economic Pathways (SSP) relate to potential biomass supply. For this, we use the energy model TIMER to project the demand for fuelwood and charcoal for different socio-economic pathways for urban and rural populations, globally, and for four tropical regions (Central America, South America, Africa and Indonesia). Second, we assess whether the biomass demands for each scenario can be met with current and projected forest biomass estimated with remote sensing and modeled Net Primary Productivity (NPP) using a Dynamic Global Vegetation Model (LPJ-GUESS). Currently one third of residential energy use is based on traditional bioenergy, including charcoal. Globally, biomass needs by urban households by 2100 under the most sustainable scenario, SSP1, are of 14.4 mi ton biomass for charcoal plus 17.1 mi ton biomass for fuelwood (31.5 mi ton biomass in total). Under SSP3, the least sustainable scenario, we project a need of 205 mi tons biomass for charcoal plus 243.8 mi ton biomass for fuelwood by 2100 (total of 450 mi ton biomass). Africa and South America contribute the most for this biomass demand, however, all areas are able to meet the demand. We find that the future of the charcoal sector is not dire. Charcoal represents a small fraction of the energy requirements, but its biomass demands are disproportionate and in some regions require a large fraction of forest. This could be because of large growing populations moving to urban areas, conversion rates, production inefficiencies, and regions that despite available alternative energy sources still use a substantial amount of charcoal. We present a framework that combines Integrated Assessment Models and local conditions to assess whether a sustainable sector can be achieved

Особенности разработки термостабилизированных германиевых фотодиодов

Рассмотрены подходы к конструированию лавинных и нелавинных германиевых фотодиодов с применением эпитаксиальных структур и термоэлектрического охлаждения

Comparing future patterns of energy system change in 2 °C scenarios to expert projections

Integrated assessment models (IAMs) are computer-based instruments used to assess the implications of human activity on the human and earth system. They are simultaneously also used to explore possible response strategies to climate change. As IAMs operate simplified representations of real-world processes within their model structures, they have been frequently criticised to insufficiently represent the opportunities and challenges in future energy systems over time. To test whether projections by IAMs diverge in systematic ways from projections made by technology experts we elicited expert opinion on prospective change for two indicators and compared these with the outcomes of IAM studies. We specifically focused on five (energy) technology families (solar, wind, biomass, nuclear, and carbon capture and storage or CCS) and compared the considered implications of the presence or absence of climate policy on the growth and diffusion of these technologies over the short (2030) to medium (2050) term. IAMs and experts were found to be in relatively high agreement on system change in a business-as-usual scenario, albeit with significant differences in the estimated magnitude of technology deployment over time. Under stringent climate policy assumptions, such as the internationally agreed upon objective to limit global mean temperature increase to no more than 2 °C, we found that the differences in estimated magnitudes became smaller for some technologies and larger for others. Compared to experts, IAM simulations projected a greater reliance on nuclear power and CCS to meet a 2 °C climate target. In contrast, experts projected a stronger growth in renewable energy technologies, particularly solar power. We close by discussing several factors that are considered influential to the alignment of the IAM and expert perspectives in this study

Signal detection in global mean temperatures after "Paris": An uncertainty and sensitivity analysis

In December 2015, 195 countries agreed in Paris to hold the increase in global mean surface temperature (GMST) well below 2.0 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C. Since large financial flows will be needed to keep GMSTs below these targets, it is important to know how GMST has progressed since pre-industrial times. However, the Paris Agreement is not conclusive as regards methods to calculate it. Should trend progression be deduced from GCM simulations or from instrumental records by (statistical) trend methods? Which simulations or GMST datasets should be chosen, and which trend models? What is pre-industrial and, finally, are the Paris targets formulated for total warming, originating from both natural and anthropogenic forcing, or do they refer to anthropogenic warming only? To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets and model choices have been varied. For all cases we evaluated trend progression along with uncertainty information. To do so, we analysed four trend approaches and applied these to the five leading observational GMST products. We find GMST progression to be largely independent of various trend model approaches. However, GMST progression is significantly influenced by the choice of GMST datasets. Uncertainties due to natural variability are largest in size. As a parallel path, we calculated GMST progression from an ensemble of 42 GCM simulations. Mean progression derived from GCM-based GMSTs appears to lie in the range of trend–dataset combinations. A difference between both approaches appears to be the width of uncertainty bands: GCM simulations show a much wider spread. Finally, we discuss various choices for pre-industrial baselines and the role of warming definitions. Based on these findings we propose an estimate for signal progression in GMSTs since pre-industrial

Translating global integrated assessment model output into lifestyle change pathways at the country and household level

Countries’ emission reduction commitments under the Paris Agreement have significant implications for lifestyles. National planning to meet emission targets is based on modelling and analysis specific to individual countries, whereas global integrated assessment models provide scenario projections in a consistent framework but with less granular output. We contribute a novel methodology for translating global scenarios into lifestyle implications at the national and household levels, which is generalisable to any service or country and versatile to work with any model or scenario. Our 5Ds method post-processes Integrated Assessment Model projections of sectoral energy demand for the global region to derive energy-service-specific lifestyle change at the household level. We illustrate the methodology for two energy services (mobility, heating) in two countries (UK, Sweden), showing how effort to reach zero carbon targets varies between countries and households. Our method creates an analytical bridge between global model output and information that can be used at national and local levels, making clear the lifestyle implications of climate targets

Disutility of climate change damages may warrant much stricter climate targets

Cost-benefit integrated assessment models (IAMs) inform the policy deliberation process by determining cost-optimal greenhouse gas emission reduction pathways based on economic considerations. These models seek to maximise economic utility and treat estimates of climate impacts (damages) and mitigation costs at par as GDP losses, having the same impact on utility reduction. However, prospect theory suggests that a certain level of climate damages could be valued higher by society than the same level of mitigation costs, as climate damages often occur as sudden unexpected events. In this paper, we show how this concept could be taken into account in cost-benefit IAMs and explore possible consequences on optimal mitigation pathways. Our results suggest that compared to the standard utility approach, capturing explicit aversion to climate impact incidence shows optimal pathways with earlier and deeper emission reduction, lowering both net-negative emissions and mid-century temperature peaks in line with stringent Paris Agreement targets