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Taking stock of global progress towards achieving the Paris Agreement requires measuring aggregate national action against modelled mitigation pathways. A key gap exists, however, in how scientific studies and national inventories account for the role of anthropogenic land-based carbon fluxes, resulting in a 5.5-6.0 GtCO2yr-1 difference between the respective present-day land-use estimates. Modelled pathways mainly include direct human-induced fluxes, while inventories submitted by countries to the UNFCCC (NGHGIs) generally include a wider definition of managed land area as well as the indirect removals on that land caused by environmental changes (e.g., the CO2 fertilization effect). This difference hinders comparability between targets set by countries and scientific benchmarks. Scenarios assessed in AR6 show that a combination of deep near-term gross emissions reductions and medium-term carbon removal from the atmosphere are needed to reach net-zero and eventually net-negative CO2 emissions to limit warming in line with the Paris Agreement temperature goal. However, scenarios lacked key information needed to estimate land-based removals and to align their LULUCF projections with NGHGIs. Here, we estimate the land-based removals consistent with NGHGIs using a reduced complexity climate model with explicit treatment of the land-use sector, OSCAR, one of the models used by the Global Carbon Project. Of the 1202 pathways that passed IPCC vetting, 914 provide sufficient land-use change data to allow us to fill this information gap and enable alignment between pathways and inventories.Across both 1.5°C and 2°C scenarios, pathways aligned with NGHGIs show a strong increase in the total land sink until around mid-century. However, the ‘NGHGI alignment gap’ decreases over this period, converging in the 2050-2060s for 1.5°C scenarios and 2070s-2080s for 2°C scenarios. These dynamics lead to land-based emissions reversing their downward trend in most NGHGI-aligned scenarios by mid-century, and result in the LULUCF sector becoming a net-source of emissions by 2100 in about 25% of deep mitigation scenarios.Our results do not change any climate outcome or mitigation benchmark produced by the IPCC, but rather provide a translational lens to view those outcomes. We find that net-zero timings on average advance by around 5 years; however, this does not imply that 5 years have been lost in the race to net-zero, but rather that following the reporting conventions for natural sinks results in net-zero being reached 5 years earlier. Understanding how these different accounting frameworks can be mutually interpreted is a fundamental challenge for evaluating progress towards the Paris Agreement, given the reality that direct and indirect carbon removals cannot be estimated separately with direct observations.We propose three primary ways to address this science-policy gap. First, targets can be formulated separately for gross emission reductions, land-based removals, and technical carbon removals, allowing for nations to clearly define their expected contributions and to measure progress in each domain separately. Second, nations can clarify the nature of their deforestation pledges. Third, modelling teams can provide their assumptions for the NGHGI correction as part of their standard output which future IPCC assessments can use to vet scenarios.

Steep emissions reductions are needed in the coming decades to limit warming to 2°C or lower, followed by multiple gigatons of annual carbon dioxide removal (CDR) in the second half of the 21st century. In this presentation we make a first assessment of the “CDR gap” and ask whether countries are preparing for the CDR scale-up challenge. We find that most countries pledge only a small expansion of CDR by 2030 in their nationally determined contributions (NDCs), while only a subset have proposed CDR in their long-term mitigation strategies. There is a significant gap between these proposed CDR levels and levels in scenarios that limit warming to 2°C or lower. While some scenarios have low CDR requirements, these require even steeper emissions reductions that we are not on track to achieve. Most countries prioritize conventional CDR on land (i.e. the management of forest sinks) which has low permanence and may raise land use conflicts. Conventional CDR on land will be extremely difficult just to maintain, let alone expand to meet net zero emissions targets. By contrast, countries focus far less in their NDCs and long-term strategies on novel CDR methods such as bioenergy with carbon capture and storage, direct air capture, or blue carbon. For these technologies to make a meaningful contribution to long-term climate mitigation, urgent support is required in the formative phases of their development. Above all, rapid emissions reductions are needed to reduce our dependence on CDR and prevent a widening CDR gap by 2050.

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 base this update on the assessment methods used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report, updating the monitoring datasets and to produce updated estimates for key climate indicators including emissions, 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.7883758, Smith et al., 2023). As they are traceable and consistent with 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 over the 2013–2022 period and 1.26 [1.0 to 1.6] °C in 2022. Human induced warming is 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 57 ± 5.6 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there are signs that emission levels are starting to stabilise, and we can hope that a continued series of these annual updates might track a real-world change of direction for the climate over this critical decade.

Researchers have incentives to search for and selectively report findings that appear to be statistically significant and/or conform to prior beliefs. Such selective reporting practices, including p-hacking and publication bias, can lead to a distorted set of results being published, potentially undermining the process of knowledge accumulation and evidence-based decision making. We take stock of the state of empirical research in the environmental sciences using 67,947 statistical tests obtained from 547 meta-analyses. We find that 59% of the p-values that were reported as significant are not actually expected to be statistically significant. The median power of these tests is between 6% to 12%, which is the lowest yet identified for any discipline. Only 8% of tests are adequately powered with statistical power of 80% or more. Exploratory regressions suggest that increased statistical power and the use of experimental research designs reduce the extent of selective reporting. Differences between subfields can be mostly explained by methodological differences. To improve the environmental sciences evidence base, researchers should pay more attention to statistical power, but incentives for selective reporting may remain even with adequate statistical power. Ultimately, a paradigm shift towards open science is needed to ensure the reliability of published empirical research.

Taking stock of global progress towards achieving the Paris Agreement requires measuring aggregate national action against modelled mitigation pathways. Because of differences in how land-based carbon removals are defined, scientific sources report higher global carbon emissions than national emissions inventories, a gap which will evolve in the future. We establish a first estimate aligning IPCC-assessed pathways with inventories using a climate model to explicitly include indirect carbon removal dynamics on land area reported as managed for by countries. After alignment, we find that key global mitigation benchmarks can appear more ambitious when considering this extra land sink, though changes vary amongst world regions and temperature outcomes. Our results highlight the need to enhance communication between scientific and policy communities to enable more robust alignment in the future.

Context: It is now widely accepted that the climate is changing, and that societal response will need to be rapid and comprehensive to prevent the most severe impacts. A key milestone in global climate governance is to assess progress on adaptation. To-date, however, there has been negligible robust, systematic synthesis of progress on adaptation or adaptation-relevant responses globally. Aim: The purpose of this review protocol is to outline the methods used by the Global Adaptation Mapping Initiative (GAMI) to systematically review human adaptation responses to climate-related changes that have been documented globally since 2013 in the scientific literature. The broad question underpinning this review is: Are we adapting to climate change? More specifically, we ask ‘what is the evidence relating to human adaptation-related responses that can (or are) directly reducing risk, exposure, and/or vulnerability to climate change?’ Methods: We review scientific literature 2013-2019 to identify documents empirically reporting on observed adaptation-related responses to climate change in human systems that can directly reduce risk. We exclude non-empirical (theoretical & conceptual) literature and adaptation in natural systems that occurs without human intervention. Included documents were coded across a set of questions focused on: Who is responding? What responses are documented? What is the extent of the adaptation-related response? What is the evidence that adaptation-related responses reduce risk, exposure and/or vulnerability? Once articles are coded, we conduct a quality appraisal of the coding and develop ‘evidence packages’ for regions and sectors. We supplement this systematic mapping with an expert elicitation exercise, undertaken to assess bias and validity of insights from included/coded literature vis a vis perceptions of real-world adaptation for global regions and sectors, with associated confidence assessments. Related protocols: This protocol represents Part 3 of a 5-part series outlining the phases of this initiative. Part 3 outlines the methods used to extract data on adaptation from documents (coding), as well as procedures for data quality assurance. See Figure 1.

Climate mitigation solutions are often evaluated in terms of their costs and potentials. This accounting, however, shortcuts a comprehensive evaluation of how climate solutions affect human well-being, which, at best, may only be crudely related to cost considerations. Here, we systematically list key sectoral mitigation options on the demand side, and categorize them into avoid, shift and improve categories. We show that these options, bridging socio-behavioral, infrastructural and technological domains, can reduce counterfactual sectoral emissions by 50-80% in end use sectors. Based on expert judgement and literature survey, we then evaluate 324 combinations of wellbeing outcomes and demand side options. We find that these are largely beneficial in improving wellbeing across all measures combined (76% have positive, 22% neutral, and 2.4% have negative effects), even though confidence level is low in the social dimensions of wellbeing. Implementing demand-side solution requires i) an understanding of malleable not fixed preferences, ii) consistently measuring and evaluating constituents of wellbeing, and iii) addressing concerns of incumbents in supply-side industries. Our results shift the emphasis in the climate mitigation solution space from supply-side technologies to demand-side service provision.

The global rise of greenhouse gas (GHG) emissions and its potentially devastating consequences require a comprehensive regulatory framework for reducing emissions, including those from the transport sector. Alternative fuels and technologies have been promoted as means for reducing the carbon intensity of the transport sector. However, the overall transport policy framework in major world economies is geared towards the use of conventional fossil fuels. This paper evaluates the effectiveness and efficiency of current climate policies for road transport that (1) target fuel producers and/or car manufacturers, and (2) influence use of alternative fuels and technologies. With diversifying fuel supply chains, carbon intensity of fuels and energy efficiency of vehicles cannot be regulated by a single instrument. We demonstrate that vehicles are best regulated across all fuels in terms of energy per distance. We conclude that price-based policies and a cap on total emissions are essential for alleviating rebound effects and perverse incentives of fuel efficiency standards and low carbon fuel standards. In tandem with existing policy tools, cap and price signal policies incentivize all emissions reduction options. Design and effects of cap and trade in the transport sector are investigated in the companion article (Flachsland et al., 2010).