Methane mitigation, especially in the near-term, is critical for meeting global climate goals. The U.S. and China, as two of the largest global methane emitters, will play a significant role in global mitigation efforts through national methane emissions reduction, as well as by collaborating on key methane topics, as outlined in recent joint statements issued by both countries. Current methane emission estimates are highly uncertain, given that methane emission factors (i.e. the emissions intensity of different activities) are highly dependent on local conditions. This analysis evaluated around 50 estimates of methane emissions in the U.S. and China across all major sectors to identify areas of uncertainty and highlight opportunities for cross-country collaboration. Shared sources of emissions with high uncertainty include waste and livestock emissions, as well as abandoned fossil production sites (coal mines and oil wells), which present opportunities for knowledge sharing and joint leadership. Key areas for collaboration include improving data collection, monitoring and availability to develop more detailed emission factors that take into account local conditions and temporal sources of emissions. The U.S. and China can jointly collaborate on developing a transparent, multi-scale approach to emissions inventory development and mechanism for integrating multiple methodologies into national emissions estimates, to improve accuracy of emissions estimates and better inform mitigation strategies and policy discussions.

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialised research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7{degree sign}C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8{degree sign}C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community’s goal to contain warming to below 1.5{degree sign}C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Polycyclic aromatic hydrocarbons (PAHs), emitted from combustion of biofuels and fossil fuels, are toxic compounds and known to cause lung-cancer. Integrating a global atmospheric chemistry model and plausible future emissions trajectories, we assess how global PAHs and their associated lung cancer risk will likely change in the future. Benzo(a)pyrene (BaP) is used as an indicator of cancer risk from PAH mixtures. From 2008 to 2050, the population-weighted global average BaP concentrations under all RCPs consistently exceeded the WHO-recommended limits, primarily attributed to residential biofuel use. In developing regions of Africa and South Asia, PAH-associated lung-cancer risk increased by 30-64% from 2008 to 2050, due to increasing use of traditional biofuels with population growth. With the stringent air quality policy, PAH lung-cancer risk substantially decreases by ~80% in developed countries. Climate change is likely to have minor effects on PAH lung-cancer risk compared with the impact of emissions.