Mercator Research Institute on Global Commons and Climate Change

The current study aims to quantify the moderating role of gasoline price on the effectiveness of interventions targeting healthier and more sustainable transport modes. This multi-level meta-analysis provides an analysis of 52 interventions targeting a change in driving, public and active transport across four continents in interventions mixing “carrot/stick” strategies. Gasoline price significantly moderates the effectiveness of interventions targeting healthier transport modes in Europe (standardized mean difference 4·43, 95% CI 1·11 to 7·74) but not in the other continents. Interventions conducted in Europe were more effective with higher gasoline price. Gasoline price also significantly interacted with access to public transport in the four continents, with the moderating role of gasoline price on interventions’ effectiveness being stronger in places with higher access to public transport. Gasoline price is a significant moderator of interventions’ effectiveness but mostly in context where infrastructures are available.

Global mitigation pathways play a critical role in informing climate policies and targets that are in line with international climate goals. However, it is not possible to directly compare modelled results with national inventories used to assess progress under the UNFCCC due to differences in how land-based fluxes are accounted for.National inventories consider carbon flux on managed land using an area-based approach with managed land-areas determined by nations. Emissions scenarios consider a different managed land area and are calibrated against data from detailed global carbon cycle models that account for natural (indirect) and anthropogenic (direct) fluxes separately by design. To disentangle the direct and indirect components of land-based carbon fluxes, we use a reduced complexity climate model with explicit treatment of the land-use sector, OSCAR, one of the models used by the Global Carbon Project. We find the discrepancy between model and NGHGI-based accounting methods globally to be 4.4 ± 1.0 Gt CO2 yr-1 averaged over the 2000-2020 time period, which is in line with existing estimates. We then apply OSCAR to the set of pathways assessed by the IPCC to quantify how this gap evolves over time and estimate how key mitigation benchmarks change.Across both 1.5°C and 2°C scenarios, LULUCF emissions pathways aligned with NGHGI accounting practices show a strong increase in the total land sink until around mid-century. However, the ‘NGHGI alignment gap’  decreases over this period, converging in the 2050-2060s for 1.5°C scenarios and 2070s-2080s for 2°C scenarios. The convergence is primarily a result of the simulated stabilization and then decrease of the CO2-fertilization effect as well as background climate warming reducing the overall effectiveness of the land sink, which in turn reduces the indirect removals considered by NGHGIs. These dynamics lead to land-based emissions reversing their downward trend in most NGHGI-aligned scenarios by mid-century, and result in the LULUCF sector becoming a net-source of emissions by 2100 in about 25% of both 1.5°C and 2°C scenarios.Assessing emission pathways using LULUCF definitions from national inventory accounting results in downward revisions to emissions benchmarks derived from scenarios. NGHGI-aligned pathways result in earlier net-zero CO2 emissions by around 2-5 years for both 1.5°C and 2°C scenarios, and 2030 emission reductions relative to 2020 are enhanced by about 5 percentage points for both pathway categories. When incorporating the additional land removals considered by NGHGIs, the assessed cumulative net CO2 emissions to global net-zero CO2 also decreases systematically by 15-18% for both 1.5°C and 2°C scenarios.We find that increasing removals from direct fluxes in 1.5C scenarios overtake estimated removals using NGHGI conventions in the near term. However, by midcentury, the strengthening of direct removals is balanced by weakening of indirect removals, meaning that, on average, carbon removal on land accounted for using NGHGI conventions in 1.5C scenarios results in about half of the LULUCF removals in current policy scenarios. We discuss the implications of our results for future Global Stocktakes and market mechanisms under the Paris Agreement.

Many sovereign wealth funds have expansive portfolios that give them the chance to influence markets through their investment choices. In this study, we analyze how oil extraction as a source of wealth influences portfolio allocation. We find that revenues from oil extraction affect the speculative motive and the hedging motives in opposite ways and create a portfolio allocation bias for oil-based funds. A numerical application of the model disentangles the motives and quantifies the bias. We find a positive bias in the portfolio allocation of an oil-based fund, which is increasing in the correlation of assets. Sensitivity analyzes show which parameters reduce the portfolio bias, turning the bias from "dirty" to "green" for large deviations from the default calibration. When a price on carbon is introduced, the intended reallocation of assets away from the oil-intensive sector is dampened by an amplification of the portfolio bias.

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

The AR6 Scenario Database is a vital repository of climate change mitigation pathways used in the latest IPCC assessment cycle. In its current version, several scenarios in the database lack information about the level of gross carbon removal on land, as net and gross removals on land are not always separated and consistently reported across models. This makes scenario analyses focusing on carbon removals challenging. We test and compare the performance of different regression models to impute missing data on land carbon sequestration from available data on net CO2 emissions in agriculture, forestry, and other land use. We find that a gradient boosting regression performs best among the tested regression models and provide a publicly available imputation dataset [https://doi.org/10.5281/zenodo.10696654] (Prütz et al., 2024) on carbon removal on land for 404 incomplete scenarios in the AR6 Scenario Database. We discuss the limitations of our approach, its use cases, and how this approach compares to other recent AR6 data re-analyses. Climate change mitigation pathways, created with integrated assessment models (IAMs), have come to take up a critical role in the assessment work of Working Group III of the Intergovernmental Panel on Climate Change (IPCC) (Riahi et al., 2022; Guivarch et al., 2022) . The AR6 Scenario Database hosted by the International Institute for Applied Systems Analysis (IIASA) contains climate change mitigation pathways compiled for and considered in the Working Group III Contribution to the IPCC