Search

The Ocean Heat-Carbon Nexus, linking ocean heat and carbon uptake, is crucial for understanding climate responses to cumulative carbon dioxide (CO2) emissions and to net zero CO2 emissions. It results from a suite of processes involving the exchange of heat and carbon across the sea-air interface as well as their storage below the mixed layer and redistribution by the ocean large-scale circulation. The Ocean Heat and Carbon Nexus is assumed to be consistently represented across two modelling platforms used in the latest IPCC assessments: the Earth System Models (ESMs) and the Simple Climate Models (SCMs). However, our research shows significant deficiencies in state-of-the-art SCMs in replicating the ocean heat-carbon nexus of ESMs due to a crude treatment of the ocean thermal and carbon cycle coupling. With one SCM, we show that a more realistic heat-to-carbon uptake ratio exacerbates the projected warming by 0.1 °C in low overshoot scenarios and up to 0.2 °C in high overshoot scenarios. It is therefore critical to explore how SCMs’ physical inconsistencies, such as the representation of the ocean heat-carbon nexus, can affect future warming projections used in climate assessments, not just by SCMs in Working Group 3 but also by ESMs in Working Group 1 via SCM-driven emission-to-concentration translation.

The 6th Assessment Report from the Intergovernmental Panel on Climate Change lacked sufficient land-sector scenario information to estimate total carbon dioxide removal deployment. Here, using a dataset of land-based carbon dioxide removal based on the scenarios assessed by the Intergovernmental Panel on Climate Change, we show that removals via afforestation and reforestation play a critical near-term role in mitigation, accounting for around 10% (median) of the net greenhouse gas emission reductions between 2020 and 2030 in scenarios that limit warming to 1.5 °C with limited overshoot. Novel carbon dioxide removal technologies such as direct air carbon capture and storage scale to multi-gigatonne levels by 2050 and beyond to balance residual emissions and draw down warming. We show that reducing fossil fuel and deforestation emissions (gross emissions) accounts for over 80% of net greenhouse gas reductions until global net zero carbon dioxide (CO2) independent of climate objective stringency. We explore the regional distributions of gross emissions and total carbon dioxide removal in cost-effective mitigation pathways and highlight the importance of incorporating fairness and broader sustainability considerations in future assessments of mitigation pathways with carbon dioxide removal.

Background: Information on the predictive determinants of abdominal aortic aneurysm rupture from CT angiography are scarce. The aim of this study was to investigate biomechanical parameters in abdominal aortic aneurysms and their association with risk of subsequent rupture. Methods: In this retrospective study, the digital radiological archive was searched for 363 patients with ruptured abdominal aortic aneurysms. All patients who underwent at least one CT angiography examination before aneurysm rupture were included. CT angiography results were analysed to determine maximum aneurysm diameter, aneurysm volume, and biomechanical parameters (peak wall stress and peak wall rupture index). In the primary survival analysis, patients with abdominal aortic aneurysms less than 70mm were considered. Sensitivity analyses including control patients and abdominal aortic aneurysms of all sizes were performed. Results: A total of 67 patients who underwent 109 CT angiography examinations before aneurysm rupture were identified. The majority were men (47, 70%) and the median age at the time of CTA examination was 77 (71-83) years. The median maximum aneurysm diameter was 56 (interquartile range 46-65) mm and the median time to rupture was 2.13 (interquartile range 0.64-4.72) years. In univariable analysis, maximum aneurysm diameter, aneurysm volume, peak wall stress, and peak wall rupture index were all associated with risk of rupture. Women had an increased HR for rupture when adjusted for maximum aneurysm diameter or aneurysm volume (HR 2.16, 95% c.i. 1.23 to 3.78 (P = 0.007) and HR 1.92, 95% c.i. 1.06 to 3.50 (P = 0.033) respectively). In multivariable analysis, the peak wall rupture index was associated with risk of rupture. The HR for peak wall rupture index was 1.05 (95% c.i. 1.03 to 1.08) per % (P < 0.001) when adjusted for maximum aneurysm diameter and 1.05 (95% c.i. 1.02 to 1.08) per % (P < 0.001) when adjusted for aneurysm volume. Conclusion: Biomechanical factors a, QC 20240612

Rapid emissions reductions, including reductions in deforestation-based land emissions, are the dominant source of global climate mitigation potential in the coming decades. However, carbon dioxide removal (CDR) will also have an important role to play. Despite this, it remains unclear whether current national proposals for CDR align with temperature targets. Here we show the ‘CDR gap’, that is, CDR efforts proposed by countries fall short of those in integrated assessment model scenarios that limit warming to 1.5 °C. However, the most ambitious proposals for CDR are close to levels in a low-energy demand scenario with the most-limited CDR scaling and aggressive near-term emissions reductions. Further, we observe that many countries propose to expand land-based removals, but none yet commit to substantively scaling novel methods such as bioenergy carbon capture and storage, biochar or direct air carbon capture and storage.

Meeting the Paris Agreement targets requires deep emissions reductions supported by a scale-up in carbon dioxide removal. However, current country-reported mitigation pledges are off track to meet carbon dioxide removal needs, unless countries dramatically reduce emissions consistent with low-energy-demand scenarios.

Each run of an integrated assessment models produces a single mitigation pathway consistent with stated objectives (e.g. maximum temperature) and optimizing some objective function (e.g. minimizing total discounted costs of mitigation). Even though models can be run thousands of times, it is unclear how built-in assumptions constrain the final set of pathways. Here we aim at broadly exploring the space of possible mitigation scenarios for a given mitigation target, and at characterizing the sets of pathways that are (near-)optimal, taking uncertainties into account. We produce an extensive set of CO2 emission pathways that stay below 2 °C of warming using a reduced-form climate-carbon model with a 1000 different physical states. We then identify 18 sets of quasi 'least-cost' mitigation pathways, under six assumptions about cost functions and three different cost minimization functions embarking different visions of intergenerational cost distribution. A first key outcome is that the absence or presence of inertia in the cost function plays a pivotal role in the resulting set of least-cost pathways. Second, despite inherent structural differences, we find common pathways across the 18 combinations in 96% of the physical states studied. Interpreting these common pathways as robust economically and in terms of intergenerational distribution, we shed light on some of their characteristics, even though these robust pathways differ for each physical state.

Global mitigation pathways play a critical role in informing climate policies and targets that are in line with international climate goals. However, it is not possible to directly compare modelled results with national inventories used to assess progress under the UNFCCC due to differences in how land-based fluxes are accounted for. National inventories consider carbon flux on managed land using an area-based approach with managed land-areas determined by nations. Emissions scenarios consider a different managed land area and are calibrated against data from detailed global carbon cycle models that account for natural (indirect) and anthropogenic (direct) fluxes separately by design. To disentangle the direct and indirect components of land-based carbon fluxes, we use a reduced complexity climate model with explicit treatment of the land-use sector, OSCAR, one of the models used by the Global Carbon Project. We find the discrepancy between model and NGHGI-based accounting methods globally to be 4.4 ± 1.0 Gt CO2 yr-1 averaged over the 2000-2020 time period, which is in line with existing estimates. We then apply OSCAR to the set of pathways assessed by the IPCC to quantify how this gap evolves over time and estimate how key mitigation benchmarks change. Across both 1.5°C and 2°C scenarios, LULUCF emissions pathways aligned with NGHGI accounting practices show a strong increase in the total land sink until around mid-century. However, the ‘NGHGI alignment gap’ decreases over this period, converging in the 2050-2060s for 1.5°C scenarios and 2070s-2080s for 2°C scenarios. The convergence is primarily a result of the simulated stabilization and then decrease of the CO2-fertilization effect as well as background climate warming reducing the overall effectiveness of the land sink, which in turn reduces the indirect removals considered by NGHGIs. These dynamics lead to land-based emissions reversing their downward trend in most NGHGI-aligned scenarios by mid-century, and r

Background: Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective: We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods: We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. Results: We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven b