Net-zero emission targets for major emitting countries consistent with the Paris Agreement

The Paris Agreement aims to limit global warming to well below 2°C, preferably to 1.5°C, above pre-industrial levels. Achieving this requires significant reductions in greenhouse gas (GHG) emissions globally, with many countries adopting or considering net-zero emissions targets. However, most information on emissions neutrality focuses on global levels, lacking detailed analysis at the national level. This research addresses this gap by investigating the timing of domestic net-zero emissions targets for major emitting countries, considering both cost-effectiveness and equity principles. Understanding the variation in these targets across countries is crucial for informing effective climate policy and ensuring equitable global efforts towards climate change mitigation. The study's importance lies in its potential to guide policymakers in setting realistic and impactful net-zero targets, contributing to the global pursuit of climate goals.

The paper references previous research on zero-emission targets as long-term global goals (Rogelj et al., 2015), examining the consistency of the Paris Agreement's zero-emissions goal with temperature targets (Tanaka & O'Neill, 2018). It also acknowledges the IPCC Special Report on 1.5°C, which includes numerous models and scenarios but lacks the required national-level detail. The study builds on existing work by providing a detailed national-level analysis of net-zero emission targets, incorporating various factors influencing the timing of these targets.

The study employs a set of globally coordinated scenarios from six integrated assessment models (IAMs): AIM, IMAGE, MESSAGE-GLOBIOM, POLIS, REMIND-MAgPIE, and WITCH. These models provide detailed national-level results for both 1.5°C and 2°C scenarios, assuming global climate policy implementation from 2000 onwards. The analysis focuses on the projected phase-out years for GHG emissions, CO₂ emissions, and fossil CO₂ emissions (excluding land use) for several major emitting countries. The impact of different definitions on projected phase-out years is investigated, including the use of inventory data for land-use, land-use change, and forestry (LULUCF) emissions; allocation of negative emissions; global warming potentials (GWPs); and equity considerations. Multiple linear regression is used to identify factors influencing the variation in phase-out years across countries, considering variables like population density, non-CO₂ emissions share, productive area per capita, afforestation/deforestation rates, CCS share of total emissions, GDP per capita, land cover characteristics, emission intensity, transport emissions, and baseline emission growth. The study compares cost-optimal scenarios with an alternative approach based on equity rules to establish target years.

The analysis reveals significant variations in projected national net-zero emission phase-out years. In cost-optimal 2°C scenarios, Brazil and the USA reach net-zero GHG emissions earlier than the global average, while India and Indonesia reach it later. China and the EU are relatively similar to the global average. The differences in phase-out years are influenced by several factors: * **Land-use emissions accounting:** Harmonizing model projections with national GHG inventory data generally leads to earlier net-zero years, except for Brazil. * **Allocation of negative emissions:** Allocating negative emissions from BECCS to the biomass-producing country results in earlier phase-out years for countries like Brazil, Indonesia, Canada, India, and Russia but later years for the EU, Japan, and Turkey. * **Multiple linear regression:** Factors such as afforestation, CCS capacity, and the share of non-CO₂ emissions significantly explain the variance in phase-out years. Higher GDP per capita tends to correlate with later phase-out years. Countries with early phase-outs (e.g., Brazil, USA) typically have a high potential for negative emissions. Countries with late phase-outs (e.g., India, Indonesia) have significantly higher GHG emissions. The study also highlights the substantial contribution of the energy supply sector (especially BECCS) and afforestation to negative emissions in most countries. The comparison with an equity-based approach suggests earlier phase-out years for countries with lower per-capita emissions and developing economies.

The findings highlight the importance of clear definitions and political agreement on issues such as land-use emissions accounting and the allocation of negative emissions. The significant role of mitigation potential, particularly negative emissions (through afforestation and CCS), in determining the timing of net-zero emissions is evident. The study underscores the complex interplay between economic development, emission profiles, and the potential for negative emissions in shaping national net-zero targets. While the cost-optimal approach offers a valuable benchmark, integrating equity principles into target setting is crucial for ensuring fair and effective climate action. The results inform the ongoing discussions surrounding the Paris Agreement, particularly Article 6 and the methodological choices in accounting for LULUCF and BECCS.

This research provides valuable insights into national-level net-zero emission targets, bridging the gap between global-level assessments and national-level policy needs. The findings demonstrate the significant variations in projected phase-out years and the influence of various factors, highlighting the importance of clear definitions, consistent accounting methods, and the consideration of equity principles in target setting. Future work should investigate additional factors, expand the range of models and scenarios, and integrate social science perspectives to enhance the understanding of political feasibility and social acceptance of net-zero targets. The study's implications extend to national policymaking, international negotiations, and the efforts of non-state actors to support ambitious climate action.

The scenarios used in this study were created between 2016 and 2018, and assume cost-optimal policies implemented from 2020 onwards. This may not fully reflect the political realities in all countries. The analysis relies on a limited set of IAMs, potentially limiting the generalizability of the findings. The models used may not completely capture all relevant factors and complexities of national-level mitigation pathways. The analysis focuses on cost-optimal scenarios and may not fully incorporate all equity considerations.