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Abstract Despite the increasing relevance of temperature overshoot and the rather ambitious country pledges on Afforestation/Reforestation globally, the mitigation potential and the Earth system responses to large-scale non-idealized Afforestation/Reforestation patterns under a high overshoot scenario remain elusive. Here, we develop an ambitious Afforestation/Reforestation scenario by harnessing 1259 Integrated Assessment Model scenarios, restoration potential maps, and biodiversity constraints, reaching 595 Mha by 2060 and 935 Mha by 2100. We then force the Max Planck Institute’s Earth System Model with this scenario which yields a reduction of peak temperature by 0.08 oC, end-of-century temperature by 0.2 oC, and overshoot duration by 13 years. Afforestation/Reforestation in the range of country pledges globally could thus constitute a useful mitigation tool in overshoot scenarios in addition to fossil fuel emission reductions, but socio-ecological implications need to be scrutinized to avoid severe side effects.

Abstract Accurate estimates of CO2 emissions from anthropogenic land-use change (E LUC) and of the natural terrestrial CO2 sink (S LAND) are crucial to precisely know how much CO2 can still be emitted to meet the goals of the Paris Agreement. In current carbon budgets, E LUC and S LAND stem from two model families that differ in how CO2 fluxes are attributed to environmental and land-use changes, making their estimates conceptually inconsistent. Here we provide consistent estimates of E LUC and S LAND by integrating environmental effects on land carbon into a spatially explicit bookkeeping model. We find that state-of-the-art process-based models overestimate S LAND by 23% (min: 8%, max: 33%) in 2012–2021, as they include hypothetical sinks that in reality are lost through historical ecosystem degradation. Additionally, E LUC increases by 14% (8%, 23%) in 2012–2021 when considering environmental effects. Altogether, we find a weaker net land sink, which makes reaching carbon neutrality even more ambitious. These results highlight that a consistent estimation of terrestrial carbon fluxes is essential to assess the progress of net-zero emission commitments and the remaining carbon budget.

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.11388387, Smith et al., 2024a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO2e yr−1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

In the education sector, blockchain is currently at the end of the peak of inflated expectations in Gartner’s Hype Cycle. Thus, it is crucial to understand whether this technology meets the expectations of Higher Education Institutions (HEIs). We go on an expedition to identify blockchain application scenarios and its potential for HEI administration—the universities are digitalized to just 23.3%.Current information systems research addresses classifications of blockchain-based projects (application level) rather than their technical realization (protocol level). Thus, when evaluating blockchain application scenarios in HEI administration, we intensively consider the technical side of blockchain-based projects. We perform a three-step approach: (1) systematic literature review, (2) qualitative exploratory semi-structured interviews to supplement information on market-ready solutions, and (3) an evaluation of the potential of the blockchain-based projects identified, based on HEI administration requirements.We find that the leading blockchain application scenarios are credential verification and record-sharing. At the protocol level, we obtain equivocal results regarding the technical realization of projects, e.g., their underlying blockchain types and storage models. At the application level, when discussing the potential of different projects, we find that most of them address adaptability, complexity decomposition, and cost reduction requirements between HEIs; interest diversity and stakeholder collaboration between HEIs and business actors; privacy and trust between HEIs and students.

Abstract Background Osteoarthritis (OA) is a chronic degenerative joint disease causing limited mobility and pain, with no curative treatment available. Recent in vivo studies suggested autonomic alterations during OA progression in patients, yet clinical evidence is scarce. Therefore, autonomic tone was analyzed in OA patients via heart rate variability (HRV) measurements. Methods Time-domain (SDRR, RMSSD, pRR50) and frequency-domain (LF, HF, LF/HF) HRV indices were determined to quantify sympathetic and parasympathetic activities. In addition, perceived stress, WOMAC pain as well as serum catecholamines, cortisol and dehydroepiandrosterone-sulphate (DHEA-S) were analyzed. The impact of the grade of disease (GoD) was evaluated by linear regression analysis and correlations with clinical data were performed. Results GoD significantly impacted the autonomic tone in OA patients. All time-domain parameters reflected slightly decreased HRV in early OA patients and significantly reduced HRV in late OA patients. Moreover, frequency-domain analysis revealed decreased HF and LF power in all OA patients, reflecting diminished parasympathetic and sympathetic activities. However, LF/HF ratio was significantly higher in early OA patients compared to late OA patients and implied a clear sympathetic dominance. Furthermore, OA patients perceived significantly higher chronic stress and WOMAC pain levels compared to healthy controls. Serum cortisol and cortisol/DHEA-S ratio significantly increased with GoD and positively correlated with WOMAC pain. In contrast, serum catecholamines only trended to increase with GoD and pain level. Conclusions This prospective study provides compelling evidence of an autonomic dysfunction with indirect sympathetic dominance in early and late knee OA patients for the first time based on HRV analyses and further confirmed by serum stress hormone measurements. Increased sympathetic activity and chronic low-grade inflammation in OA as well as in its major comorbidities reinforce each other and might therefore create a vicious cycle. The observed autonomic alterations coupled with increased stress and pain levels highlight the potential of HRV as a prognostic marker. In addition, modulation of autonomic activity represents an attractive future therapeutic option. Graphical abstract

The response of the global climate–carbon-cycle system to anthropogenic perturbations happens differently at different timescales. The unravelling of the memory structure underlying this timescale dependence is a major challenge in climate research. Recently the widely applied α–β–γ framework proposed by Friedlingstein et al. (2003) to quantify climate–carbon-cycle feedbacks has been generalized to account also for such internal memory. By means of this generalized framework, we investigate the timescale dependence of the airborne fraction for a set of Earth system models that participated in CMIP5 (Coupled Model Intercomparison Project Phase 5). The analysis is based on published simulation data from C4MIP-type (Coupled Climate–Carbon Cycle Model Intercomparison) experiments with these models. Independently of the considered scenario, the proposed generalization describes at global scale the reaction of the climate–carbon system to sufficiently weak perturbations. One prediction from this theory is how the timescale-resolved airborne fraction depends on the underlying feedbacks between climate and the carbon cycle. These feedbacks are expressed as timescale-resolved functions depending solely on analogues of the α, β, and γ sensitivities, introduced in the generalized framework as linear response functions. In this way a feedback-dependent quantity (airborne fraction) is predicted from feedback-independent quantities (the sensitivities). This is the key relation underlying our study. As a preparatory step, we demonstrate the predictive power of the generalized framework exemplarily for simulations with the Max Planck Institute (MPI) Earth System Model. The whole approach turns out to be valid for perturbations of up to an about 100 ppm CO2 rise above the pre-industrial level; beyond this value the response becomes non-linear. By means of the generalized framework we then derive the timescale dependence of the airborne fraction from the underlying climate–carbon-cycle feedbacks for an ensemble of CMIP5 models. Our analysis reveals that for all studied CMIP5 models (1) the total climate–carbon-cycle feedback is negative at all investigated timescales, (2) the airborne fraction generally decreases for increasing timescales, and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all these timescales. Qualitatively similar results were previously found by employing the original α–β–γ framework to particular perturbation scenarios, but our study demonstrates that, although obtained from particular scenario simulations, they are characteristics of the coupled climate–carbon-cycle system as such, valid at all considered timescales. These more general conclusions are obtained by accounting for the internal memory of the system as encoded in the generalized sensitivities, which in contrast to the original α, β, and γ are scenario-independent.

Land cover and land management changes (LCLMCs) play an important role in achieving low-end warming scenarios through land-based mitigation. However, their effects on moisture fluxes and recycling remain uncertain, although they have important implications for the future viability of such strategies. Here, we analyse the impact of idealized LCLMC scenarios on atmospheric moisture transport in three different Earth system model (ESMs): the Community Earth System Model (CESM), the Max Planck Institute Earth System Model (MPI-ESM), and the European Consortium Earth System Model (EC-EARTH). The LCLMC scenarios comprise of a full cropland world, a fully afforested world, and a cropland world with unlimited irrigation expansion. The effects of these LCLMC in the different ESMs are analysed for precipitation, evaporation, and vertically integrated moisture flux convergence to understand the LCLMC-induced changes in the atmospheric moisture cycle. Then, a moisture tracking algorithm is applied to assess the effects of LCLMC on moisture recycling at the local (grid cell level) and the global scale (continental moisture recycling). By applying a moisture tracking algorithm on fully coupled ESM simulations we are able to quantify the complete effects of LCLMC on moisture recycling (including circulation changes), which are generally not considered in moisture recycling studies. Our results indicate that cropland expansion is generally causing a drying and reduced local moisture recycling, while afforestation and irrigation expansion generally cause wetting and increased local moisture recycling. However, the strength of this effect varies across ESMs and shows a large dependency on the dominant driver. Some ESMs show a dominance of large-scale atmospheric circulation changes while other ESMs show a dominance of local to regional changes in the atmospheric water cycle only within the vicinity of the LCLMC. Overall, these results corroborate that LCLMC can induce substantial effects on the atmospheric water cycle and moisture recycling, both through local effects and changes in atmospheric circulation. However, more research is needed to constrain the uncertainty of these effects within ESMs to better inform future land-based mitigation strategies.

Non-technical summary: We identify a set of essential recent advances in climate change research with high policy relevance, across natural and social sciences: (1) looming inevitability and implications of overshooting the 1.5°C warming limit, (2) urgent need for a rapid and managed fossil fuel phase-out, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future contribution of natural carbon sinks, (5) intertwinedness of the crises of biodiversity loss and climate change, (6) compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems. Technical summary The IPCC Assessment Reports offer the scientific foundation for international climate negotiations and constitute an unmatched resource for climate change researchers. However, the assessment cycles take multiple years. As a contribution to cross- and interdisciplinary understanding across diverse climate change research communities, we have streamlined an annual process to identify and synthesise essential research advances. We collected input from experts on different fields using an online questionnaire and prioritised a set of ten key research insights with high policy relevance. This year we focus on: (1) looming overshoot of the 1.5°C warming limit, (2) urgency of phasing-out fossil fuels, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future of natural carbon sinks, (5) need for join governance of biodiversity loss and climate change, (6) advances in the science of compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems. We first present a succinct account of these Insights, reflect on their policy implications, and offer an integrated set of policy relevant messages. This science synthesis and science communication effort is also the basis for a report targeted to policymakers as a contribution to elevate climate science every year, in time for the UNFCCC COP. Social media summary We highlight recent and policy-relevant advances in climate change research - with input from more than 200 experts 1.

We explore the ability of the atmospheric CO2 record since 1900 to constrain the source of CO2 from land use and land cover change (hereafter "land use"), taking account of uncertainties in other terms in the global carbon budget. We find that the atmospheric constraint favors land use CO2 flux estimates with lower decadal variability and can identify potentially erroneous features, such as emission peaks around 1960 and after 2000, in some published estimates. Furthermore, we resolve an offset in the global carbon budget that is most plausibly attributed to the land use flux. This correction shifts the mean land use flux since 1900 across 20 published estimates down by 0.35 PgC year-1 to 1.04 ± 0.57 PgC year-1 , which is within the range but at the low end of these estimates. We show that the atmospheric CO2 record can provide insights into the time history of the land use flux that may reduce uncertainty in this term and improve current understanding and projections of the global carbon cycle.

Abstract The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole Biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top-down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought.

The reduction of CO2 emissions and the enhancement of CO2 removals related to land use are considered essential for future pathways towards net-zero emissions and mitigating climate change. With the growing pressure under global climate treaties, country-level land-use CO2 flux data are becoming increasingly important. So far, country-level estimates are mainly available through official country reports, such as the greenhouse gas inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Recently, different modelling approaches, namely dynamic global vegetation models (DGVMs) and bookkeeping models, have moved to higher spatial resolutions, which makes it possible to obtain model-based country-level estimates that are globally consistent in their methodology. To progress towards a largely independent assessment of country reports using models, we analyse the robustness of country-level CO2 flux estimates from different modelling approaches in the period 1950–2021 and compare them with estimates from country reports. Our results highlight the general ability of modelling approaches to estimate land-use CO2 fluxes at the country level and at higher spatial resolution. Modelled land-use CO2 flux estimates generally agree well, but the investigation of multiple DGVMs and bookkeeping models reveals that the robustness of their estimates strongly varies across countries, and substantial uncertainties remain, even for top emitters. Similarly, modelled land-use CO2 flux estimates and country-report-based estimates agree reasonably well in many countries once their differing definitions are accounted for, although differences remain in some other countries. A separate analysis of CO2 emissions and removals from land use using bookkeeping models also shows that historical peaks in net fluxes stem from emission peaks in most countries, whereas the long-term trends are more connected to removal dynamics. The ratio of the net flux to the sum of CO2 emissions and removals from land use (the net-to-gross flux ratio) underlines the spatio-temporal heterogeneity in the drivers of net land-use CO2 flux trends. In many tropical regions, net-to-gross flux ratios of about 50 % are due to much larger emissions than removals; in many temperate countries, ratios close to zero show that emissions and removals largely offset each other. Considering only the net flux thus potentially masks large emissions and removals and the different timescales upon which they act, particularly if averaged over countries or larger regions, highlighting the need for future studies to focus more on the gross fluxes. Data from this study are openly available via the Zenodo portal at https://doi.org/10.5281/zenodo.8144174 (Obermeier et al., 2023).

Abstract Globally, solar projects are being rapidly built or planned, particularly in high solar potential regions with high energy demand. However, their energy generation potential is highly related to the weather condition. Here we use state-of-the-art Earth system model simulations to investigate how large photovoltaic solar farms in the Sahara Desert could impact the global cloud cover and solar generation potential through disturbed atmospheric teleconnections. The results indicate negative impacts on solar potential in North Africa (locally), Middle East, Southern Europe, India, Eastern China, Japan, Eastern Australia, and Southwestern US, and positive impacts in Central and South America, the Caribbean, Central & Eastern US, Scandinavia and South Africa, reaching a magnitude of ±5% in remote regions seasonally. Diagnostics suggest that large-scale atmospheric circulation changes are responsible for the global impacts. International cooperation is essential to mitigate the potential risks of future large-scale solar projects in drylands, which could impact energy production.

Objective This post hoc analysis of the FINCH 1–3 (NCT02889796, NCT02873936 and NCT02886728) studies assessed specific effects of filgotinib on pain control and their relationship with other aspects of efficacy in patients with rheumatoid arthritis (RA).Methods Assessments included: residual pain responses of ≤10 and ≤20 mm on a 100 mm visual analogue scale (VAS); the proportion of patients who achieved VAS pain responses in addition to remission or low disease activity by Disease Activity Score-28 with C-reactive protein (DAS28-CRP) or Clinical Disease Activity Index (CDAI) criteria.Results Across studies, filgotinib reduced pain from week 2, with responses sustained throughout the studies. In FINCH 1, at week 24, 35.8%, 25.0%, 24.6% and 11.6% of patients in the filgotinib 200 mg, filgotinib 100 mg, adalimumab and placebo arms (each plus methotrexate) achieved VAS pain ≤20 mm in addition to DAS28-CRP remission; 26.3%, 17.9%, 17.2% and 7.6% achieved VAS pain ≤10 mm in addition to DAS28-CRP remission. A similar pattern was seen for CDAI remission. Time during which VAS pain was ≤10 or ≤20 mm was longest with filgotinib 200 mg and comparable between adalimumab and filgotinib 100 mg. Similar findings were reported for filgotinib in FINCH 2 and 3.Conclusion In all RA populations studied, pain improvements occurred from week 2 and were sustained over time. In FINCH 1, filgotinib 100 mg provided similar pain amelioration to adalimumab, whereas filgotinib 200 mg resulted in greater pain improvement and higher proportion of patients with residual pain ≤10 or ≤20 mm and meeting DAS28-CRP remission criteria.

This corrigendum resolves an error in figure 17 and clarifies the scope of the cement sector in figure 2. Figure 17 in the original published manuscript depicts a Kaya identity for the agriculture, forestry and other land uses (AFOLU) sector. We unintentionally excluded land-use CO2 emissions from total greenhouse gas (GHG) emissions in this identity, and depicted only agricultural GHG emissions.

Quantification of land surface–atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 926 ± 13 Tg C yr−1, while eight other BU sources report a mean value of 948 [937,961] Tg C yr−1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875 Tg C in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for −91 ± 32 Tg C yr−1, while six other BU approaches reported a mean sink of −62 [-117,-49] Tg C yr−1, and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported −69 [-152,-5] Tg C yr−1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of −73 Tg C yr−1 has a slightly smaller spread (0th–100th percentiles of [-135,+45] Tg C yr−1), and it was calculated after removing net land–atmosphere CO2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (−0.61) Tg C yr−2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000 Tg C yr−1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.8148461 (McGrath et al., 2023).

Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.

The 1:1 resveratrol–piperazine cocrystal was successfully synthesized and scaled-up to 300 g scale with the mechanochemical method, as a result of investigating key process parameters, namely the solvent and the grinding time. The use of water, ethanol or ethanol–water mixtures and reaction times up to 50 min were evaluated relative to the dry grinding process. Cocrystal formation and purity were monitored through X-ray diffraction and calorimetry measurements. The dry grinding resulted in an incomplete cocrystal formation, while the use of water or water–ethanol mixture yielded a monohydrate solid phase. Pure ethanol was found to be the optimal solvent for large-scale cocrystallization, as it delivered cocrystals with high crystallinity and purity after 10–30 min grinding time at the laboratory scale. Notably, a relatively fast reaction time (30–60 min) was sufficient for the completion of cocrystallization at larger scales, using a planetary ball mill and a plant reactor. Also, the obtained cocrystal increases the aqueous solubility of resveratrol by 6%–16% at pH = 6.8. Overall, this study highlights the potential of solvent-assisted mechanochemical synthesis as a promising new approach for the efficient production of pure resveratrol–piperazine cocrystals.

Land cover changes have been proposed to play a significant role, alongside emission reductions, in achieving the temperature goals agreed upon under the Paris Agreement. Such changes carry both global implications, pertaining to the biogeochemical effects of land cover change and thus the global carbon budget, and regional or local implications, pertaining to the biogeophysical effects arising within the immediate area of land cover change. Biogeophysical effects of land cover change are of high relevance to national policy and decision makers, and accounting for them is essential for effective deployment of land cover practices that optimise between global and regional impacts. To this end, Earth system model (ESM) outputs that isolate the biogeophysical responses of climate to land cover changes are key in informing impact assessments and supporting scenario development exercises. However, generating multiple such ESM outputs in a manner that allows comprehensive exploration of all plausible land cover scenarios is computationally untenable. This study proposes a framework to explore in an agile manner the local biogeophysical responses of climate under customised tree cover change scenarios by means of a computationally inexpensive emulator, the Tree cover change clIMate Biophysical responses EmulatoR (TIMBER) v0.1. The emulator is novel in that it solely represents the biogeophysical responses of climate to tree cover changes, and it can be used as either a standalone device or as a supplement to existing climate model emulators that represent the climate responses from greenhouse gas (GHG) or global mean temperature (GMT) forcings. We start off by modelling local minimum, mean, and maximum surface temperature responses to tree cover changes by means of a month- and Earth system model (ESM)-specific generalised additive model (GAM) trained over the whole globe; 2 m air temperature responses are then diagnosed from the modelled minimum and maximum surface temperature responses using observationally derived relationships. Such a two-step procedure accounts for the different physical representations of surface temperature responses to tree cover changes under different ESMs whilst respecting a definition of 2 m air temperature that is more consistent across ESMs and with observational datasets. In exploring new tree cover change scenarios, we employ a parametric bootstrap sampling method to generate multiple possible temperature responses, such that the parametric uncertainty within the GAM is also quantified. The output of the final emulator is demonstrated for the Shared Socioeconomic Pathway (SSP) 1-2.6 and 3-7.0 scenarios. Relevant temperature responses are identified as those displaying a clear signal in relation to their surrounding parametric uncertainty, calculated as the signal-to-noise ratio between the sample set mean and sample set variability. The emulator framework developed in this study thus provides a first step towards bridging the information gap surrounding biogeophysical implications of land cover changes, allowing for smarter land use decision making.

Abstract Land-based mitigation is essential in reducing net carbon emissions. Yet, the attribution of carbon fluxes remains highly uncertain, in particular for the forest-rich region of Eastern Europe (incl. Western Russia). Here we integrate various data sources to show that Eastern Europe accounted for an above-ground biomass carbon sink of ~0.41 gigatons of carbon per year over the period 2010–2019, that is 78% of the entire European carbon sink. We find that this carbon sink is declining, mainly driven by changes in land use and land management, but also by increasing natural disturbances. Based on a random forest model, we show that land use and management changes are main drivers of the declining carbon sink in Eastern Europe, although soil moisture variability is also important. Specifically, the saturation effect of tree regrowth in abandoned agricultural areas, combined with increasing wood harvest removals, particularly in European Russia, contributed to the decrease in the Eastern European carbon sink.

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth's energy imbalance, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.8000192, Smith et al., 2023a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human-induced warming reached 1.14 [0.9 to 1.4] ∘C averaged over the 2013–2022 decade and 1.26 [1.0 to 1.6] ∘C in 2022. Over the 2013–2022 period, human-induced warming has been increasing at an unprecedented rate of over 0.2 ∘C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 54 ± 5.3 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that increases in greenhouse gas emissions have slowed, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for human influence on climate.

Land cover and land management change (LCLMC) has been highlighted for its critical role in mitigation scenarios, both in terms of global mitigation and local adaptation. Yet, the climate effect of individual LCLMC options, their dependence on the background climate and the local vs. non-local responses are still poorly understood across different Earth system models (ESMs). Here we simulate the climatic effects of LCLMC using three state-of-the-art ESMs, including the Community Earth System Model (CESM), the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) and the European Consortium Earth System Model (EC-EARTH). We assess the LCLMC effects using the following four idealized experiments: (i) a fully afforested world, (ii) a world fully covered by cropland, (ii) a fully afforested world with extensive wood harvesting and (iv) a full-cropland world with extensive irrigation. In these idealized sensitivity experiments, performed under present-day climate conditions, the effects of the different LCLMC strategies represent an upper bound for the potential of global mitigation and local adaptation. To disentangle the local and non-local effects from the LCLMC, a checkerboard-like LCLMC perturbation, i.e. alternating grid boxes with and without LCLMC, is applied. The local effects of deforestation on surface temperature are largely consistent across the ESMs and the observations, with a cooling in boreal latitudes and a warming in the tropics. However, the energy balance components driving the change in surface temperature show less consistency across the ESMs and the observations. Additionally, some biases exist in specific ESMs, such as a strong albedo response in CESM mid-latitudes and a soil-thawing-driven warming in boreal latitudes in EC-EARTH. The non-local effects on surface temperature are broadly consistent across ESMs for afforestation, though larger model uncertainty exists for cropland expansion. Irrigation clearly induces a cooling effect; however, the ESMs disagree whether these are mainly local or non-local effects. Wood harvesting is found to have no discernible biogeophysical effects on climate. Overall, our results underline the potential of ensemble simulations to inform decision making regarding future climate consequences of land-based mitigation and adaptation strategies.

Global greenhouse gas (GHG) emissions can be traced to five economic sectors: energy, industry, buildings, transport and AFOLU (agriculture, forestry and other land uses). In this topical review, we synthesise the literature to explain recent trends in global and regional emissions in each of these sectors. To contextualise our review, we present estimates of GHG emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions. Overall, the literature and data emphasise that progress towards reducing GHG emissions has been limited. The prominent global pattern is a continuation of underlying drivers with few signs of emerging limits to demand, nor of a deep shift towards the delivery of low and zero carbon services across sectors. We observe a moderate decarbonisation of energy systems in Europe and North America, driven by fuel switching and the increasing penetration of renewables. By contrast, in rapidly industrialising regions, fossil-based energy systems have continuously expanded, only very recently slowing down in their growth. Strong demand for materials, floor area, energy services and travel have driven emissions growth in the industry, buildings and transport sectors, particularly in Eastern Asia, Southern Asia and South-East Asia. An expansion of agriculture into carbon-dense tropical forest areas has driven recent increases in AFOLU emissions in Latin America, South-East Asia and Africa. Identifying, understanding, and tackling the most persistent and climate-damaging trends across sectors is a fundamental concern for research and policy as humanity treads deeper into the Anthropocene.

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO2 yr−1) in global land-use CO2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO2 yr−1 for the period 2000–2020, and NGHGIs, which estimate a sink of −1.9 GtCO2 yr−1 in the same period. Most of the gap is found on forest land (3.5 GtCO2 yr−1), with differences also for deforestation (2.4 GtCO2 yr−1), for fluxes from other land uses (1.0 GtCO2 yr−1) and to a lesser extent for fluxes from organic soils (0.2 GtCO2 yr−1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (−6.4 GtCO2 yr−1) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO2 yr−1) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement. Data from this study are openly available online via the Zenodo portal (Grassi et al., 2023) at https://doi.org/10.5281/zenodo.7650360.

Abstract Anthropogenic emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) have made significant contributions to global warming since the pre-industrial period and are therefore targeted in international climate policy. There is substantial interest in tracking and apportioning national contributions to climate change and informing equitable commitments to decarbonisation. Here, we introduce a new dataset of national contributions to global warming caused by historical emissions of carbon dioxide, methane, and nitrous oxide during the years 1851–2021, which are consistent with the latest findings of the IPCC. We calculate the global mean surface temperature response to historical emissions of the three gases, including recent refinements which account for the short atmospheric lifetime of CH4. We report national contributions to global warming resulting from emissions of each gas, including a disaggregation to fossil and land use sectors. This dataset will be updated annually as national emissions datasets are updated.

Abstract Background Catecholamines are major neurotransmitters of the sympathetic nervous system (SNS) and they are of pivotal importance in regulating numerous physiological and pathological processes. Rheumatoid arthritis (RA) is influenced by the activity of the SNS and its neurotransmitters norepinephrine (NE) and dopamine (DA) and early sympathectomy alleviates experimental arthritis in mice. In contrast, late sympathectomy aggravates RA, since this procedure eliminates anti-inflammatory, tyrosine hydroxylase (TH) positive cells that appear in the course of RA. While it has been shown that B cells can take up, degrade and synthesize catecholamines it is still unclear whether this also applies to synovial fibroblasts, a mesenchymal cell that is actively engaged in propagating inflammation and cartilage destruction in RA. Therefore, this study aims to present a detailed description of the catecholamine pathway and its influence on human RA synovial fibroblasts (RASFs). Results RASFs express all catecholamine-related targets including the synthesizing enzymes TH, DOPA decarboxylase, dopamine beta-hydroxylase, and phenylethanolamine N-methyltransferase. Furthermore, vesicular monoamine transporters 1/2 (VMAT1/2), dopamine transporter (DAT) and norepinephrine transporter (NET) were detected. RASFs are also able to degrade catecholamines as they express monoaminoxidase A and B (MAO-A/MAO-B) and catechol-O-methyltransferase (COMT). TNF upregulated VMAT2, MAO-B and NET levels in RASFs. DA, NE and epinephrine (EPI) were produced by RASFs and extracellular levels were augmented by either MAO, COMT, VMAT or DAT/NET inhibition but also by tumor necrosis factor (TNF) stimulation. While exogenous DA decreased interleukin-6 (IL-6) production and cell viability at the highest concentration (100 μM), NE above 1 μM increased IL-6 levels with a concomitant decrease in cell viability. MAO-A and MAO-B inhibition had differential effects on unstimulated and TNF treated RASFs. The MAO-A inhibitor clorgyline fostered IL-6 production in unstimulated but not TNF stimulated RASFs (10 nM-1 μM) while reducing IL-6 at 100 μM with a dose-dependent decrease in cell viability in both groups. The MAO-B inhibitor lazabemide hydrochloride did only modestly decrease cell viability at 100 μM while enhancing IL-6 production in unstimulated RASFs and decreasing IL-6 in TNF stimulated cells. Conclusions RASFs possess a complete and functional catecholamine machinery whose function is altered under inflammatory conditions. Results from this study shed further light on the involvement of sympathetic neurotransmitters in RA pathology and might open therapeutic avenues to counteract inflammation with the MAO enzymes being key candidates.

Abstract Background Pyronaridine, a Mannich base anti-malarial with high efficacy against drug resistant Plasmodium falciparum, is currently evaluated as a fixed dose combination with artesunate for the treatment of uncomplicated malaria. In this study, the in vitro activity of pyronaridine against clinical isolates of P. falciparum from Lambaréné, Gabon, was assessed in order to obtain baseline data on its activity prior to its future use in routine therapy. Moreover, follow-up assessment on the in vitro activity of chloroquine, artesunate and quinine was performed. Methods In vitro response of field isolates of P. falciparum to pyronaridine, chloroquine, artesunate and quinine was assessed using the traditional WHO microtest. In addition, the histidine-rich protein 2 (HRP-2) assay was performed and evaluated for its future implementation for follow-up of drug susceptibility testing. Results Pyronaridine exhibited a high in vitro activity against P. falciparum, with a geometric mean cut-off concentration of 9.3 nmol/l. Fifty percent effective concentrations were 1.9 nmol/l and 2.0 nmol/l in the WHO microtest and HRP-2 assay, respectively. Results matched closely in vivo findings from a recent clinical trial on pyronaridine-artesunate treatment. One isolate showed diminished sensitivity to artesunate. For chloroquine and quinine resistance levels were comparable to prior studies from Lambaréné. Results from the novel HRP-2 assay corresponded well to those obtained by the WHO microtest. Conclusion Pyronaridine is highly active in chloroquine-resistant parasites and seems a promising partner drug for artemisinin-based combination therapy in Africa.

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1%yr-1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon-concentration and carbon-climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77±0.37 ° C EgC-1 and is similar to that found in CMIP5 models (1.63±0.48 °C EgC-1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1%yr-1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon-concentration and carbon-climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77±0.37 ° C EgC-1 and is similar to that found in CMIP5 models (1.63±0.48 °C EgC-1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

The global carbon budget (GCB) – including fluxes of CO2 between the atmosphere, land, and ocean and its atmospheric growth rate – show large interannual to decadal variations. Reconstructing and predicting the variable GCB is essential for tracing the fate of carbon and understanding the global carbon cycle in a changing climate. We use a novel approach to reconstruct and predict the variations in GCB in the next few years based on our decadal prediction system enhanced with an interactive carbon cycle. By assimilating physical atmospheric and oceanic data products into the Max Planck Institute Earth System Model (MPI-ESM), we are able to reproduce the annual mean historical GCB variations from 1970–2018, with high correlations of 0.75, 0.75, and 0.97 for atmospheric CO2 growth, air–land CO2 fluxes, and air–sea CO2 fluxes, respectively, relative to the assessments from the Global Carbon Project (GCP). Such a fully coupled decadal prediction system, with an interactive carbon cycle, enables the representation of the GCB within a closed Earth system and therefore provides an additional line of evidence for the ongoing assessments of the anthropogenic GCB. Retrospective predictions initialized from the simulation in which physical atmospheric and oceanic data products are assimilated show high confidence in predicting the following year's GCB. The predictive skill is up to 5 years for the air–sea CO2 fluxes, and 2 years for the air–land CO2 fluxes and atmospheric carbon growth rate. This is the first study investigating the GCB variations and predictions with an emission-driven prediction system. Such a system also enables the reconstruction of the past and prediction of the evolution of near-future atmospheric CO2 concentration changes. The Earth system predictions in this study provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.

Abstract Brain atrophy in multiple sclerosis (MS), as measured by percentage brain volume change (PBVC) from brain magnetic resonance imaging (MRI), has been established as an outcome parameter in clinical trials. It is unknown to what extent volume changes within different brain tissue compartments contribute to PBVC. We analyzed pairs of MRI scans (at least 6 months apart) in 600 patients with relapsing–remitting MS. Multiple regression revealed that PBVC mainly reflects volume loss of white and cortical gray matter, while deep gray matter and white matter lesions were less represented. Our findings aid the interpretation of PBVC changes in MS.

In a world of deepening inequalities, climate polices might be feasible in high-income countries only. Here the authors find that overcoming global inequality through sustainable socio-economic development is critical for land-based mitigation in line with the Paris Agreement.

Land cover and land management change (LCLMC) has been highlighted for its critical role in mitigation scenarios in terms of both global mitigation and local adaptation. Yet, the climate effect of individual LCLMC options, their dependence on the background climate, and the local vs. non-local responses are still poorly understood across different Earth system models (ESMs). Here we simulate the climatic effects of LCLMC using three state-of-the-art ESMs, including the Community Earth System Model (CESM), the Max Planck Institute for Meteorology Earth System Model (MPI-ESM), and the European Consortium Earth System Model (EC-EARTH). We assess the LCLMC effects using four idealized experiments: (i) a fully afforested world, (ii) a world fully covered by cropland, (iii) a fully afforested world with extensive wood harvesting, and (iv) a full cropland world with extensive irrigation. In these idealized sensitivity experiments performed under present-day climate conditions, the effects of the different LCLMC strategies represent an upper bound for the potential of global mitigation and local adaptation. To disentangle the local and non-local effects from the LCLMC, a checkerboard-like LCLMC perturbation, i.e. alternating grid boxes with and without LCLMC, is applied. The local effects of deforestation on surface temperature are largely consistent across the ESMs and the observations, with a cooling in boreal latitudes and a warming in the tropics. However, the energy balance components driving the change in surface temperature show less consistency across the ESMs and the observations. Additionally, some biases exist in specific ESMs, such as a strong albedo response in CESM mid-latitudes and a soil-thawing-driven warming in boreal latitudes in EC-EARTH. The non-local effects on surface temperature are broadly consistent across ESMs for afforestation, though larger model uncertainty exists for cropland expansion. Irrigation clearly induces a cooling effect; however, the ESMs disagree regarding whether these are mainly local or non-local effects. Wood harvesting is found to have no discernible biogeophysical effects on climate. Our results overall underline the potential of ensemble simulations to inform decision-making regarding future climate consequences of land-based mitigation and adaptation strategies.

PurposePulmonary vein isolation (PVI) is the cornerstone of atrial fibrillation (AF) ablation in persistent AF (persAF), and cryoballoon PVI emerged as an initial ablation strategy. Symptomatic atrial arrhythmia recurrence following successful PVI in persAF is observed more frequently than in paroxysmal AF. Predictors for arrhythmia recurrence following cryoballoon PVI for persAF are not well described, and the role of left atrial appendage (LAA) anatomy is uncertain.MethodsPatients with symptomatic persAF and pre-procedural cardiac computed tomography angiography (CCTA) images undergoing initial second-generation cryoballoon (CBG2) were enrolled. Left atrial (LA), pulmonary vein (PV) and LAA anatomical data were assessed. Clinical outcome and predictors for atrial arrhythmia recurrence were evaluated by univariate and multivariate regression analysis.ResultsFrom May 2012 to September 2016, 488 consecutive persAF patients underwent CBG2-PVI. CCTA with sufficient quality for measurements was available in 196 (60.4%) patients. Mean age was 65.7 ± 9.5 years. Freedom from arrhythmia was 58.2% after a median follow-up of 19 (13; 29) months. No major complications occurred. Independent predictors for arrhythmia recurrence were LAA volume (HR 1.082; 95% CI, 1.032 to 1.134; p = 0.001) and mitral regurgitation ≥ grade 2 (HR, 2.49; 95% CI 1.207 to 5.126; p = 0.013). LA volumes ≥110.35 ml [sensitivity: 0.81, specificity: 0.40, area under the curve (AUC) = 0.62] and LAA volumes ≥9.75 ml (sensitivity: 0.56, specificity 0.70, AUC = 0.64) were associated with recurrence. LAA-morphology, classified as chicken-wing (21.9%), windsock (52.6%), cactus (10.2%) and cauliflower (15.3%), did not predict outcome (log-rank, p = 0.832).ConclusionLAA volume and mitral regurgitation were independent predictors for arrhythmia recurrence following cryoballoon ablation in persAF. LA volume was less predictive and correlated with LAA volume. LAA morphology did not predict the clinical outcome. To improve outcomes in persAF ablation, further studies should focus on treatment strategies for persAF patients with large LAA and mitral regurgitation.