Modelling social influence and cultural variation in global low-carbon vehicle transitions

We present a unique and transparent approach for incorporating social influence effects into global integrated assessment models used to analyse climate change mitigation. We draw conceptually on Rogers (2003) diffusion of innovations, introducing heterogeneous and interconnected consumers who vary in their aversion to new technologies. Focussing on vehicle choice, we conduct novel empirical research to parameterise consumer risk aversion and how this is shaped by social and cultural influences. We find robust evidence for social influence effects, and variation between countries as a function of cultural differences. We then formulate an approach to modelling social influence which is implementable in both simulation and optimisation-type models. We use two global integrated assessment models (IMAGE and MESSAGE) to analyse four scenarios that introduce social influence and cultural differences between regions. These scenarios allow us to explore the interactions between consumer preferences and social influence. We find that incorporating social influence effects into global models accelerates the early deployment of electric vehicles and stimulates more widespread deployment across adopter groups. Incorporating cultural variation leads to significant differences in deployment between culturally divergent regions such as the USA and China. Our analysis significantly extends the ability of global integrated assessment models to provide policy-relevant analysis grounded in real world processes

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

Improved modelling of lifestyle changes in Integrated Assessment Models : Cross-disciplinary insights from methodologies and theories

Recent studies show that lifestyle changes can provide an essential contribution to achieving the Paris climate targets. While some efforts have been made to incorporate lifestyle changes into model-based scenarios, the attempts are currently very stylised and included exogenously. This paper discusses current efforts to represent lifestyle change in models, and analyses potential insights from relevant scientific disciplines to improve the representation of lifestyle changes in models – including modelling specific behaviour changes, identifying cross-cutting lifestyle solutions, representing the intentions behind the changes and quantifying their impacts. As such, this research attempts to bridge the gap between qualitative and quantitative theories and methodologies. Based on the results of this literature analysis, we recommend defining lifestyle changes more harmoniously, exploring an expanded range of approaches, domains and transformative solutions, adopting a whole-systems approach, and addressing the trade-offs between the use of exogenous inputs and endogenous modelling. © 2019 The AuthorsPeer reviewe

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

High-resolution Global Pathways to Achieve 100% Electricity Access in 2030

Universal access to electricity is a crucial component of achieving the sustainable development goals. However, model projections suggest that under current policies, this goal will not be reached by 2030. There is still little understanding of electrification strategies and investment needs across global regions. To address this gap, we explore scenarios for achieving universal access globally, considering decent living standards and synergies with climate change mitigation. The analysis integrates high-resolution population GIS data with socioeconomic and energy system data from the integrated assessment model IMAGE to analyse the least-cost optimised pathways for universal access by 2030. The results indicate that universal access requires an additional investment of around 19 billion USD annually, with renewable off-grid systems playing a major role. Combining universal access with climate mitigation policies would require 15% more investment but would reduce CO2 emissions by nearly 30% relative to the default electrification scenario

Decarbonising the critical sectors of aviation, shipping, road freight and industry to limit warming to 1.5–2°C

Limiting warming to well below 2°C requires rapid and complete decarbonisation of energy systems. We compare economy-wide modelling of 1.5°C and 2°C scenarios with sector-focused analyses of four critical sectors that are difficult to decarbonise: aviation, shipping, road freight transport, and industry. We develop and apply a novel framework to analyse and track mitigation progress in these sectors. We find that emission reductions in the 1.5°C and 2°C scenarios of the IMAGE model come from deep cuts in CO2 intensities and lower energy intensities, with minimal demand reductions in these sectors’ activity. We identify a range of additional measures and policy levers that are not explicitly captured in modelled scenarios but could contribute significant emission reductions. These are demand reduction options, and include less air travel (aviation), reduced transportation of fossil fuels (shipping), more locally produced goods combined with high load factors (road freight), and a shift to a circular economy (industry). We discuss the challenges of reducing demand both for economy-wide modelling and for policy. Based on our sectoral analysis framework, we suggest modelling improvements and policy recommendations, calling on the relevant UN agencies to start tracking mitigation progress through monitoring key elements of the framework (CO2 intensity, energy efficiency, and demand for sectoral activity, as well as the underlying drivers), as a matter of urgency

Pesticide use under the influence of socio-economic and climate change: Pest-Agri-SSPs

Pesticide use is a crucial human-driven change in the Anthropocene that negatively impacts the environment and ecosystems. While pesticides are essential to agriculture to sustain crop production and ensure global food security, they also lead to significant environmental impacts. The export of pesticides after application from the agricultural fields threatens the soil, groundwater and surface water quality in many world regions. Pesticide use is constantly increasing globally, driven mainly by agricultural intensification, despite stricter regulations and higher pesticide effectiveness. To enhance the understanding of future pesticide use and emissions and make informed farm-to-policy decisions, we developed Pesticide Agricultural Shared Socio-Economic Pathways (Pest-Agri-SSPs) in six steps. The Pest-Agri-SSPs are based on an extensive literature review and expert knowledge, considering significant climate and socio-economic drivers from farm to continental scale in combination with multiple actors impacting them. In the literature, pesticide use is associated with farmer behaviour and agricultural practices, pest damage, technique and efficiency of pesticide application, agricultural policy and demand for agricultural products. Here, we developed Pest-Agri-SSPs upon this understanding of pesticide use drivers and relating them to plausible sectoral developments, as described by the Shared Socio-economic Pathways for European agriculture and food systems (Eur-Agri-SSPs). The Pest-Agri-SSPs present European pesticide use in five scenarios with low to high challenges to climate change adaptation and mitigation up to 2050. The most sustainable scenario (Pest-Agri-SSP1) shows a decrease in pesticide use owing to sustainable agricultural practices, technological advances and a pro-environmental orientation of agricultural policies. On the contrary, the Pest-Agri-SSP3 and Pest-Agri-SSP4 show an increase in pesticide use resulting from high challenges from pest pressure, resource depletion and relaxed agricultural policies. Pest-Agri-SSP2 presents a stabilised pesticide use resulting from strict policies and slow transitions by farmers to sustainable agricultural practices. Pest-Agri-SSP5 shows a decrease in pesticide use for most drivers, influenced mainly by rapid technological development and the application of sustainable agricultural practices. However, Pest-Agri-SSP5 also shows a relatively low rise in pesticide use driven by agricultural demand, production, and climate change. Our results highlight the need for a holistic approach to tackle pesticide use and emissions, considering the identified drivers and future developments. The storylines and qualitative assessment provide a platform to make quantitative assumptions for numerical modelling and evaluating policy targets

Decomposition analysis of per capita emissions : a tool for assessing consumption changes and technology changes within scenarios

Recent studies show that behaviour changes can provide an essential contribution to achieving the Paris climate targets. Existing climate change mitigation scenarios primarily focus on technological change and underrepresent the possible contribution of behaviour change. This paper presents and applies a methodology to decompose the factors contributing to changes in per capita emissions in scenarios. With this approach, we determine the relative contribution to total emissions from changes in activity, the way activities are carried out, the intensity of activities, as well as fuel choice. The decomposition tool breaks down per capita emissions loosely following the Kaya Identity, allowing a comparison between the contributions of technology and consumption changes among regions and between various scenarios. We illustrate the use of the tool by applying it to three previously-published scenarios; a baseline scenario, a scenario with a selection of behaviour changes, and a 2 degrees C scenario with the same selection of behaviour changes. Within these scenarios, we explore the contribution of technology and consumption changes to total emission changes in the transport and residential sector, for a selection of both developed and developing regions. In doing so, the tool helps identify where specifically (i.e. via consumption or technology factors) different measures play a role in mitigating emissions and expose opportunities for improved representation of behaviour changes in integrated assessment models. This research shows the value of the decomposition tool and how the approach could be flexibly replicated for different global models based on available variables and aims. The application of the tool to previously-published scenarios shows substantial differences in consumption and technology changes from CO2 price and behaviour changes, in transport and residential per capita emissions and between developing and developed regions. Furthermore, the tool's application can highlight opportunities for future scenario development of a more nuanced and heterogeneous representation of behaviour and lifestyle changes in global models.Peer reviewe