Background: The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. Results: The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. Conclusions: This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.

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Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.@en

In the version of this Article originally published, the units of ‘Total electricity yield’ and ‘Potential electricity gain’ in Table 1 were incorrectly presented as GWh yr^–1; they should have been TWh yr^–1. These errors have now been corrected.

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China is the largest worldwide consumer of solar photovoltaic (PV) electricity, with 130 GW of installed capacity as of 2017. China’s PV capacity is expected to reach at least 400 GW by 2030, to provide 10% of its primary energy. However, anthropogenic aerosol emissions and changes in cloud cover affect solar radiation in China. Here, we use observational radiation data from 119 stations across China to show that the PV potential decreased on average by 11–15% between 1960 and 2015. The relationship between observed surface radiation and emissions of sulfur dioxide and black carbon suggests that strict air pollution control measures, combined with reduced fossil fuel consumption, would allow surface radiation to increase. We find that reverting back to 1960s radiation levels in China could yield a 12–13% increase in electricity generation, equivalent to an additional 14 TWh produced with 2016 PV capacities, and 51–74 TWh with the expected 2030 capacities. The corresponding economic benefits could amount to US$1.9 billion in 2016 and US$4.6–6.7 billion in 2030.@en

We studied the possibility of converting waste toilet paper (WTP) into electricity. WTP is a waste stream with continuous availability and negative cost, but it is difficult to handle, as it contains fecal matter. The process we explored had two stages: WTP gasification followed by direct conversion into electricity in a high-temperature solid-oxide fuel cell (SOFC). The process was studied on a 10 ktpa scale by using real-life parameter values obtained from industrial sources. We presented the basic system design, as well as its electricity yield and overall efficiency on the basis of detailed mass- and energy-balance calculations. By explorative technoeconomic analysis and sensitivity analysis, we found an electric efficiency of 57 %, which is similar to that of a natural gas combined cycle plant. The levelized cost of electricity (LCOE) was 20.3 ¢ kWh⁻¹, which is comparable at present to that of residential photovoltaic installations. The system's capital costs are relatively high, mainly as a result of SOFC investment costs, but we expect these costs to decrease as the market of cells develops. The operating costs are relatively low, partly thanks to the high thermodynamic efficiency (≈70 %). Currently, the fuel costs are negative (because we use waste as a raw material), yet this could change if the value of WTP would increase as a result of this process. Learning effects could make the system more competitive in the future with an LCOE of approximately 11 ¢ kWh⁻¹.

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