Linking models for land use analysis: experiences from the SENSOR project

In order to quantify the effects of a comprehensive set of policies on land use, interaction between sectors needs to be accounted for, while maintaining a high level of detail for each sector. This calls for a combination of sector specific and sector wide models. This paper describes such a modelling system, with emphasis on the linking of the models to a coherent system. Five sectors of significant importance for land use are modelled individually: Forestry, agriculture, urban land use, transport infrastructure, and tourism. All models are connected as sub-modules to an economy-wide partial econometric model. In addition, a land cover model is used to disaggregate land use down to 1km grid resolution. The linking of such a diverse set of models in a consistent way poses conceptual as well as practical issues. The conceptual issues concern questions such as which items of the models to link, how to obtain a stable joint baseline scenario, and how to obtain a joint equilibrium solution for all models simultaneously in simulation. Practical issues concern the actual implementation of the conceptually sound linkages and provision of a workable technical solution. The linked system allows us to introduce a shock in either of the models, and the set of results will provide a joint solution for all sectors modelled in SENSOR. In this manner, the models take a complex policy scenario as argument and compute a comprehensive set of variables involving all five land use sectors on regional level, which in turn forms a basis for distilling out the impact on sustainability in the form of indicators. Without the extensive automation and technical linkages, it would not have been possible to obtain a joint equilibrium, or it would have required exorbitant amounts of working time.Model linking, sustainable land use, cross sector modelling, iterative recalibration, Land Economics/Use,

Expert perceptions of game-changing innovations towards net zero

Current technological improvements are yet to put the world on track to net-zero, which will require the uptake of transformative low-carbon innovations to supplement mitigation efforts. However, the role of such innovations is not yet fully understood; some of these ‘miracles’ are considered indispensable to Paris Agreement-compliant mitigation, but their limitations, availability, and potential remain a source of debate. We evaluate such potentially game-changing innovations from the experts' perspective, aiming to support the design of realistic decarbonisation scenarios and better-informed net-zero policy strategies. In a worldwide survey, 260 climate and energy experts assessed transformative innovations against their mitigation potential, at-scale availability and/or widescale adoption, and risk of delayed diffusion. Hierarchical clustering and multi-criteria decision-making revealed differences in perceptions of core technological innovations, with next-generation energy storage, alternative building materials, iron-ore electrolysis, and hydrogen in steelmaking emerging as top priorities. Instead, technologies highly represented in well-below-2°C scenarios seemingly feature considerable and impactful delays, hinting at the need to re-evaluate their role in future pathways. Experts' assessments appear to converge more on the potential role of other disruptive innovations, including lifestyle shifts and alternative economic models, indicating the importance of scenarios including non-technological and demand-side innovations. To provide insights for expert elicitation processes, we finally note caveats related to the level of representativeness among the 260 engaged experts, the level of their expertise that may have varied across the examined innovations, and the potential for subjective interpretation to which the employed linguistic scales may be prone to

Photon extrabunching in ultrabright twin beams measured by two-photon counting in a semiconductor

For many years twin beams originating from parametric down-converted light beams have aroused great interest and attention in the photonics community. One particular aspect of the twin beams is their peculiar intensity correlation functions, which are related to the coincidence rate of photon pairs. Here we take advantage of the huge bandwidth offered by two-photon absorption in a semiconductor to quantitatively determine correlation functions of twin beams generated by spontaneous parametric down-conversion. Compared with classical incoherent sources, photon extrabunching is unambiguously and precisely measured, originating from exact coincidence between down-converted pairs of photons, travelling in unison. These results strongly establish that two-photon counting in semiconductors is a powerful tool for the absolute measurement of light beam photon correlations at ultrashort timescales

Where is the EU headed given its current climate policy? A stakeholder-driven model inter-comparison.

Recent calls to do climate policy research with, rather than for, stakeholders have been answered in non-modelling science. Notwithstanding progress in modelling literature, however, very little of the scenario space traces back to what stakeholders are ultimately concerned about. With a suite of eleven integrated assessment, energy system and sectoral models, we carry out a model inter-comparison for the EU, the scenario logic and research questions of which have been formulated based on stakeholders' concerns. The output of this process is a scenario framework exploring where the region is headed rather than how to achieve its goals, extrapolating its current policy efforts into the future. We find that Europe is currently on track to overperforming its pre-2020 40% target yet far from its newest ambition of 55% emissions cuts by 2030, as well as looking at a 1.0-2.35 GtCO2 emissions range in 2050. Aside from the importance of transport electrification, deployment levels of carbon capture and storage are found intertwined with deeper emissions cuts and with hydrogen diffusion, with most hydrogen produced post-2040 being blue. Finally, the multi-model exercise has highlighted benefits from deeper decarbonisation in terms of energy security and jobs, and moderate to high renewables-dominated investment needs

The contribution of large genomic deletions at the CDKN2A locus to the burden of familial melanoma

Mutations in two genes encoding cell cycle regulatory proteins have been shown to cause familial cutaneous malignant melanoma (CMM). About 20% of melanoma-prone families bear a point mutation in the CDKN2A locus at 9p21, which encodes two unrelated proteins, p16INK4a and p14ARF. Rare mutations in CDK4 have also been linked to the disease. Although the CDKN2A gene has been shown to be the major melanoma predisposing gene, there remains a significant proportion of melanoma kindreds linked to 9p21 in which germline mutations of CDKN2A have not been identified through direct exon sequencing. The purpose of this study was to assess the contribution of large rearrangements in CDKN2A to the disease in melanoma-prone families using multiplex ligation-dependent probe amplification. We examined 214 patients from independent pedigrees with at least two CMM cases. All had been tested for CDKN2A and CDK4 point mutation, and 47 were found positive. Among the remaining 167 negative patients, one carried a novel genomic deletion of CDKN2A exon 2. Overall, genomic deletions represented 2.1% of total mutations in this series (1 of 48), confirming that they explain a very small proportion of CMM susceptibility. In addition, we excluded a new gene on 9p21, KLHL9, as being a major CMM gene

Pathway-Based Analysis of a Melanoma Genome-Wide Association Study: Analysis of Genes Related to Tumour-Immunosuppression

Systemic immunosuppression is a risk factor for melanoma, and sunburn-induced immunosuppression is thought to be causal. Genes in immunosuppression pathways are therefore candidate melanoma-susceptibility genes. If variants within these genes individually have a small effect on disease risk, the association may be undetected in genome-wide association (GWA) studies due to low power to reach a high significance level. Pathway-based approaches have been suggested as a method of incorporating a priori knowledge into the analysis of GWA studies. In this study, the association of 1113 single nucleotide polymorphisms (SNPs) in 43 genes (39 genomic regions) related to immunosuppression have been analysed using a gene-set approach in 1539 melanoma cases and 3917 controls from the GenoMEL consortium GWA study. The association between melanoma susceptibility and the whole set of tumour-immunosuppression genes, and also predefined functional subgroups of genes, was considered. The analysis was based on a measure formed by summing the evidence from the most significant SNP in each gene, and significance was evaluated empirically by case-control label permutation. An association was found between melanoma and the complete set of genes (pemp = 0.002), as well as the subgroups related to the generation of tolerogenic dendritic cells (pemp = 0.006) and secretion of suppressive factors (pemp = 0.0004), thus providing preliminary evidence of involvement of tumour-immunosuppression gene polymorphisms in melanoma susceptibility. The analysis was repeated on a second phase of the GenoMEL study, which showed no evidence of an association. As one of the first attempts to replicate a pathway-level association, our results suggest that low power and heterogeneity may present challenges