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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.

Long-term measurements at the Mauna Loa Observatory (MLO) show that the CO2 seasonal cycle amplitude (SCA) increased from 1959 to 2019 at an overall rate of 0.22  ±  0.034 ppm decade-1 while also varying on interannual to decadal time scales. These SCA changes are a signature of changes in land ecological CO2 fluxes as well as shifting winds. Simulations with the TM3 tracer transport model and CO2 fluxes from the Jena CarboScope CO2 Inversion suggest that shifting winds alone have contributed to a decrease in SCA of -0.10  ±  0.022 ppm decade-1 from 1959 to 2019, partly offsetting the observed long-term SCA increase associated with enhanced ecosystem net primary production. According to these simulations and MIROC-ACTM simulations, the shorter-term variability of MLO SCA is nearly equally driven by varying ecological CO2 fluxes (49%) and varying winds (51%). We also show that the MLO SCA is strongly correlated with the Pacific Decadal Oscillation (PDO) due to varying winds, as well as with a closely related wind index (U-PDO). Since 1980, 44% of the wind-driven SCA decrease has been tied to a secular trend in the U-PDO, which is associated with a progressive weakening of westerly winds at 700 mbar over the central Pacific from 20°N to 40°N. Similar impacts of varying winds on the SCA are seen in simulations at other low-latitude Pacific stations, illustrating the difficulty of constraining trend and variability of land CO2 fluxes using observations from low latitudes due to the complexity of circulation changes.

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 ongoing development of the Global Carbon Project (GCP) global methane (CH4 ) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions-China, Southeast Asia, USA, South Asia, and Brazil-account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH4  yr-1 in 2008-2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.

Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

The post-monsoon agricultural biomass burning activities in Northwest India have been recognized as a significant socio-environmental problem in recent years, primarily due to their severe impacts on air quality degradation across a wide area, including the capital New Delhi. Although these biomass burning activities have been extensively studied from an air quality perspective, their potential impacts on the climate system, particularly through their influences on cloud and radiation fields, have been largely overlooked. In this study, we aim to address this research gap by analyzing fire, meteorological parameters, aerosol, cloud, and radiation data spanning nearly two decades (2002–2021), obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite, Modern-Era Retrospective Analysis Research and Applications, Version 2 (MERRA-2), and the Fifth Generation of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5). Our analysis reveals a notable increase in agricultural biomass burning intensity in Northwest India over the past two decades, contributing significantly to air quality degradation. Our analysis further indicates a delay in peak burning time (day of the year) and a shortening of the period of intense burning, reflecting changes in farming practices and agricultural biomass burning in Northwest India over the past two decades. These agricultural biomass burning activities substantially elevate total and light-absorbing aerosols, thereby affecting cloud properties and altering the radiation budget. The intensification of these burning activities can cause an increase in cloud droplet size and a decrease in cloud optical thickness, suggesting an enhancement of the cloud droplet collision-coalescence process during the period of intense burning. Similarly, the intensification of burning activities leads to increased cooling effects at the surface and top-of-the-atmosphere across shortwave and longwave spectral ranges, while inducing a heating effect within the atmosphere. These findings highlight the potential impacts of agricultural biomass burning activities on the regional climate system and hydrological cycle, emphasizing the need for more detailed studies in the future. [ABSTRACT FROM AUTHOR]

Air pollution impacts on human health are of serious concern in northern India, and over the Delhi National Capital Region (NCR) in particular. The Kharif crop residue burning (CRB) is often blamed for degradation of Delhi-NCR's seasonal air quality. However, the concentration of fine particulate matter (PM2.5) remained stable in Delhi, while the fire detection counts (FDCs) from satellites over Punjab and Haryana declined by 50% or more during 2015–2023. We measured PM2.5, carbon monoxide (CO) and related parameters over Delhi-NCR, Haryana and Punjab from a network of 30 low-cost sensors (CUPI-Gs) in a selected period (September–November) of 2022 and 2023. Measured PM2.5 showed lower concentration in 2023 compared to 2022 at Punjab and Haryana sites, in compliance with FDC reductions. Using the CUPI-G measurements, airmass trajectories, particle dispersion and chemical-transport model simulations, we show that the CRB emissions over Punjab contributed only a meagre ~14% to the overall PM2.5 over Delhi-NCR during October-November 2022. This indicates that there exists only a very weak coupling between PM2.5 mass over Delhi-NCR and the CRB over Punjab, highlighting the effectiveness of the Graded Response Action Plan (GRAP) in controlling air pollution in the region. [ABSTRACT FROM AUTHOR]

An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.

Monitoring the spatial distribution and trends in surface greenhouse gas (GHG) fluxes, as well as flux attribution to natural and anthropogenic processes, is essential to track progress under the Paris Agreement and to inform its global stocktake. This study updates earlier syntheses (Petrescu et al., 2020, 2021, 2023), provides a consolidated synthesis of CH 4 emissions using bottom-up (BU) and top-down (TD) approaches for the European Union (EU), and is expanded to include seven additional countries with large anthropogenic and/or natural emissions (the USA, Brazil, China, India, Indonesia, Russia, and the Democratic Republic of the Congo (DR Congo)). Our aim is to demonstrate the use of different emission estimates to help improve national GHG emission inventories for a diverse geographical range of stakeholders. We use updated national GHG inventories (NGHGIs) reported by Annex I parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2023 and the latest available biennial update reports (BURs) reported by non-Annex I parties. Comparing NGHGIs with other approaches highlights that different system boundaries are a key source of divergence. A key system boundary difference is whether anthropogenic and natural fluxes are included and, if they are, how fluxes belonging to these two sources are partitioned. Over the studied period, the total CH 4 emission estimates in the EU, the USA, and Russia show a steady decreasing trend since 1990, while for the non-Annex I emitters analyzed in this study, Brazil, China, India, Indonesia, and DR Congo, CH 4 emissions have generally increased. Quantitatively, in the EU the mean of 2015–2020 anthropogenic UNFCCC NGHGIs (15±1.8 Tg CH 4 yr -1) and the mean of the BU CH 4 emissions (17.8 (16–19) Tg CH 4 yr -1) generally agree on the magnitude, while inversions show higher emission estimates (medians of 21 (19–22) Tg CH 4 yr -1 and 24 (22–25) Tg CH 4 yr -1 for the three regional and six global inversions, respectively), as they include natural emissions, which for the EU were quantified at 6.6 Tg CH 4 yr -1 (Petrescu et al., 2023). Similarly, for the other Annex I parties in this study (the USA and Russia), the gap between the BU anthropogenic and total TD emissions is partly explained by the natural emissions. For the non-Annex I parties, anthropogenic CH 4 estimates from UNFCCC BURs show large differences compared to the other global-inventory-based estimates and even more compared to atmospheric ones. This poses an important potential challenge to monitoring the progress of the global CH 4 pledge and the global stocktake. Our analysis provides a useful baseline to prepare for the influx of inventories from non-Annex I parties as regular reporting starts under the enhanced transparency framework of the Paris Agreement. By systematically comparing the BU and TD methods, this study provides recommendations for more robust comparisons of available data sources and hopes to steadily engage more parties in using observational methods to complement their UNFCCC inventories, as well as considering their natural emissions. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, future development needs to resolve knowledge gaps in the BU and TD approaches and to better quantify the remaining uncertainty. TD methods may emerge as a powerful tool to help improve NGHGIs of CH 4 emissions, but further confidence is needed in the comparability and robustness of the estimates. The referenced datasets related to figures are available at 10.5281/zenodo.12818506 (Petrescu et al., 2024). [ABSTRACT FROM AUTHOR]

Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000-2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32]Tg CH4yr-1 higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

Abstract. The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (~biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (T-D, exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories, and data-driven approaches (B-U, including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by T-D inversions at 558 Tg CH4 yr−1 (range [540–568]). About 60 % of global emissions are anthropogenic (range [50–65 %]). B-U approaches suggest larger global emissions (736 Tg CH4 yr−1 [596–884]) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the T-D budget, it is likely that some of the individual emissions reported by the B-U approaches are overestimated, leading to too large global emissions. Latitudinal data from T-D emissions indicate a predominance of tropical emissions (~64 % of the global budget,