Josep G. Canadell’s research while affiliated with CSIRO Manufacturing and other places

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC) are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO2-products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements and Earth System Models. The sum of all sources and sinks results in the carbon budget imbalance (BIM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2023, EFOS increased by 1.3 % relative to 2022, with fossil emissions at 10.1 ± 0.5 GtC yr-1 (10.3 ± 0.5 GtC yr-1 when the cement carbonation sink is not included), ELUC was 1.0 ± 0.7 GtC yr-1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.9 GtC yr-1 (40.6 ± 3.2 GtCO2 yr-1). Also, for 2023, GATM was 5.9 ± 0.2 GtC yr-1 (2.79 ± 0.1 ppm yr-1), SOCEAN was 2.9 ± 0.4 GtC yr-1 and SLAND was 2.3 ± 1.0 GtC yr-1, with a near zero BIM (-0.02 GtC yr-1). The global atmospheric CO2 concentration averaged over 2023 reached 419.3 ± 0.1 ppm. Preliminary data for 2024, suggest an increase in EFOS relative to 2023 of +0.8 % (-0.3 % to 1.9 %) globally, and atmospheric CO2 concentration increased by 2.8 ppm reaching 422.5 ppm, 52 % above pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2023, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living data update documents changes in methods and datasets applied to this most-recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2024 (Friedlingstein et al., 2024).

Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present‐day greenhouse gas (GHG) budgets. We compare bottom‐up (data‐driven upscaling and process‐based models) and top‐down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom‐up approaches estimate higher land‐to‐atmosphere fluxes for all GHGs. Both bottom‐up and top‐down approaches show a sink of CO2 in natural ecosystems (bottom‐up: −29 (−709, 455), top‐down: −587 (−862, −312) Tg CO2‐C yr⁻¹) and sources of CH4 (bottom‐up: 38 (22, 53), top‐down: 15 (11, 18) Tg CH4‐C yr⁻¹) and N2O (bottom‐up: 0.7 (0.1, 1.3), top‐down: 0.09 (−0.19, 0.37) Tg N2O‐N yr⁻¹). The combined global warming potential of all three gases (GWP‐100) cannot be distinguished from neutral. Over shorter timescales (GWP‐20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process‐based models and the compilation of process‐model ensembles for CH4 and N2O. Discrepancies between bottom‐up and top‐down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well‐distributed in situ GHG measurements and improved resolution in upscaling techniques.

Climate change research is broad, diverse and constantly growing. Cross- and interdisciplinary understanding is essential for generating robust science advice for policy. However, it is challenging to prioritise and navigate the ever-expanding peer-reviewed literature. To address this, we gathered input from experts across various research fields through an online questionnaire and prioritised a set of 10 key research advances with high policy relevance. This year, we focus on: (1) Declining aerosol emissions, (2) soaring methane emissions, (3) concerning ocean dynamics, (4) diversity and resilience of Amazon forests, (5) expanding risk of “uninhabitability”, (6) climate impacts to maternal and reproductive health, (7) climate-resilient development for cities, (8) vulnerability of critical infrastructure, (9) governance of the energy transition minerals value chain, and (10) public acceptance of climate policies. This science synthesis and science communication effort is also the basis for a policy report which aims to elevate climate science every year ahead of the UN Climate Summit.

Rice cultivation constitutes a significant anthropogenic methane (CH4) source and a crucial target for CH4 mitigation. However, global and regional emissions remain poorly constrained. In this study, we validated a global-process-based methane model for rice paddies (CH4MOD), analyzed the sensitivity of major emission drivers, and simulated management scenarios involving four water regimes and three organic matter amendments. CH4MOD simulations achieved a correlation coefficient of 0.76 across 986 CH4 flux observations globally, demonstrating its capability under different environmental conditions and management practices. The sensitivity analysis revealed water regime as the primary driver, followed by organic matter amendment and temperature. Under different crop management, CH4 emissions varied significantly from 8 to 78 Tg CH4/yr. This wide range of emissions demonstrates the need to use and improve rice-specific emission models and spatiotemporal data on rice distribution, water, and residue management for accurately assessing local to global emissions and their climate mitigation potential.

Aquaculture is a major emission source of atmospheric methane (CH4) and nitrous oxide (N2O). However, its contribution remains highly uncertain because the source has been neglected in global and national greenhouse gas inventories. Here, we present an inventory of CH4 and N2O fluxes from five freshwater aquaculture systems in China, which accounted for more than half of global freshwater aquaculture production during 2000-2020. We show that total CH4 and N2O emissions were 2.5 (0.6-4.2) Tg CH4 yr⁻¹ and 18.3 (3.8-32.2) Gg N2O yr⁻¹, respectively, with 75% coming from ponds and paddy fields. CH4 and N2O effluxes from freshwater aquaculture were 5 and 2 times higher than the average from other inland water bodies, respectively. Aquaculture accounts for half of the national inland water emissions, and outweighs the land soil methane sink. We suggest that tracking aquacultural emissions and their reduction through aerated systems could provide additional opportunity to reduce agricultural non-CO2 emissions without compromising food security.

Effective nitrogen fertilizer management is crucial for reducing nitrous oxide (N 2 O) emissions while ensuring food security within planetary boundaries. However, climate change might also interact with management practices to alter N 2 O emission and emission factors (EFs), adding further uncertainties to estimating mitigation potentials. Here, we developed a new hybrid modeling framework that integrates a machine learning model with an ensemble of eight process‐based models to project EFs under different climate and nitrogen policy scenarios. Our findings reveal that EFs are dynamically modulated by environmental changes, including climate, soil properties, and nitrogen management practices. Under low‐ambition nitrogen regulation policies, EF would increase from 1.18%–1.22% in 2010 to 1.27%–1.34% by 2050, representing a relative increase of 4.4%–11.4% and exceeding the IPCC tier‐1 EF of 1%. This trend is particularly pronounced in tropical and subtropical regions with high nitrogen inputs, where EFs could increase by 0.14%–0.35% (relative increase of 11.9%–17%). In contrast, high‐ambition policies have the potential to mitigate the increases in EF caused by climate change, possibly leading to slight decreases in EFs. Furthermore, our results demonstrate that global EFs are expected to continue rising due to warming and regional drying–wetting cycles, even in the absence of changes in nitrogen management practices. This asymmetrical influence of nitrogen fertilizers on EFs, driven by climate change, underscores the urgent need for immediate N 2 O emission reductions and further assessments of mitigation potentials. This hybrid modeling framework offers a computationally efficient approach to projecting future N 2 O emissions across various climate, soil, and nitrogen management scenarios, facilitating socio‐economic assessments and policy‐making efforts.

In recognition of the importance of inland waters, numerous datasets mapping their extents, types, or changes have been created using sources ranging from historical wetland maps to real-time satellite remote sensing. However, differences in definitions and methods have led to spatial and typological inconsistencies among individual data sources, confounding their complementary use and integration. The Global Lakes and Wetlands Database (GLWD), published in 2004, with its globally seamless gridded depiction of major vegetated and non-vegetated wetland classes, has emerged over the last decades as a foundational reference map that has advanced research and conservation planning addressing freshwater biodiversity, ecosystem services, greenhouse gas emissions, land surface processes, hydrology, and human health. Here, we present a new iteration of this map, termed GLWD version 2, generated by harmonizing the latest ground- and satellite-based data products into one single database. Following the same design principle as its predecessor, GLWD v2 aims to avoid double-counting of overlapping surface water features while differentiating between natural and non-natural lakes, rivers of multiple sizes, and several other wetland types. The classification of GLWD v2 incorporates information on seasonality (i.e., permanent vs. intermittent vs. ephemeral); inundation vs. saturation (i.e., flooding vs. waterlogged soils); vegetation cover (e.g., forested swamps vs. non-forested marshes); salinity (e.g., salt pans); natural vs. non-natural origins (e.g., rice paddies); and a stratification of landscape position and water source (e.g., riverine, lacustrine, palustrine, coastal/marine). GLWD v2 represents 33 wetland classes and—including all intermittent classes—depicts a maximum of 18.2 million km2 of wetlands (13.4 % of the global land area excluding Antarctica). The spatial extent of each class is provided as the fractional coverage within each grid cell at a resolution of 15 arc-seconds (approximately 500 m at the equator), with cell fractions derived from input data at resolutions as small as 10 m. The updated GLWD v2 offers an improved representation of inland surface water extents and their classification for contemporary conditions. Despite being a static map, it includes classes that denote intrinsic temporal dynamics. GLWD v2 is designed to facilitate large-scale hydrological, ecological, biogeochemical, and conservation applications, aiming to support the study and protection of wetland ecosystems around the world.

The terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land‐atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio‐temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO2, climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote‐sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (−0.58 ± 0.54 PgC/yr). Forests and semi‐arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi‐arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (−1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land‐atmosphere exchange is simulated in the extratropical regions.

Nitrous oxide (N2O) is a long-lived potent greenhouse gas and stratospheric ozone-depleting substance that has been accumulating in the atmosphere since the preindustrial period. The mole fraction of atmospheric N2O has increased by nearly 25 % from 270 ppb (parts per billion) in 1750 to 336 ppb in 2022, with the fastest annual growth rate since 1980 of more than 1.3 ppb yr-1 in both 2020 and 2021. According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6), the relative contribution of N2O to the total enhanced effective radiative forcing of greenhouse gases was 6.4 % for 1750–2022. As a core component of our global greenhouse gas assessments coordinated by the Global Carbon Project (GCP), our global N2O budget incorporates both natural and anthropogenic sources and sinks and accounts for the interactions between nitrogen additions and the biogeochemical processes that control N2O emissions. We use bottom-up (BU: inventory, statistical extrapolation of flux measurements, and process-based land and ocean modeling) and top-down (TD: atmospheric measurement-based inversion) approaches. We provide a comprehensive quantification of global N2O sources and sinks in 21 natural and anthropogenic categories in 18 regions between 1980 and 2020. We estimate that total annual anthropogenic N2O emissions have increased 40 % (or 1.9 Tg N yr-1) in the past 4 decades (1980–2020). Direct agricultural emissions in 2020 (3.9 Tg N yr-1, best estimate) represent the large majority of anthropogenic emissions, followed by other direct anthropogenic sources, including fossil fuel and industry, waste and wastewater, and biomass burning (2.1 Tg N yr-1), and indirect anthropogenic sources (1.3 Tg N yr-1) . For the year 2020, our best estimate of total BU emissions for natural and anthropogenic sources was 18.5 (lower–upper bounds: 10.6–27.0) Tg N yr-1, close to our TD estimate of 17.0 (16.6–17.4) Tg N yr-1. For the 2010–2019 period, the annual BU decadal-average emissions for both natural and anthropogenic sources were 18.2 (10.6–25.9) Tg N yr-1 and TD emissions were 17.4 (15.8–19.20) Tg N yr-1. The once top emitter Europe has reduced its emissions by 31 % since the 1980s, while those of emerging economies have grown, making China the top emitter since the 2010s. The observed atmospheric N2O concentrations in recent years have exceeded projected levels under all scenarios in the Coupled Model Intercomparison Project Phase 6 (CMIP6), underscoring the importance of reducing anthropogenic N2O emissions. To evaluate mitigation efforts and contribute to the Global Stocktake of the United Nations Framework Convention on Climate Change, we propose the establishment of a global network for monitoring and modeling N2O from the surface through to the stratosphere. The data presented in this work can be downloaded from 10.18160/RQ8P-2Z4R (Tian et al., 2023).