Rapid estimation of climate-air quality interactions in integrated assessment using a response surface model

Air quality and climate change are substantial and linked sustainability challenges, and there is a need for improved tools to assess the implications of addressing them in combination. High-fidelity chemistry-climate simulations can capture combined climate-air quality responses to policy change, but computational cost has prevented integration of accurate air quality impacts into integrated assessment models (IAMs) used to inform policy development. Instead, IAMs often use global- or regional-scale marginal response factors to calculate air quality impacts of climate scenarios. To bridge this gap, we develop a computationally-efficient approach to quantify air quality impacts of combined climate and air quality interventions, capable of capturing spatial heterogeneity and complex atmospheric chemistry. We fit individual response surfaces to high-fidelity model simulation output for 1,525 locations worldwide under a variety of perturbation scenarios. Our intermediate-fidelity approach captures known differences in atmospheric chemical regimes, and can estimate location-by-location air quality under different scenarios within milliseconds. It can also be straightforwardly implemented in IAMs, enabling researchers to rapidly estimate how air quality in different locations, and related equity-based metrics, will respond to large-scale changes in emissions policy.Using this approach we find that the sensitivity of air quality to climate change and air pollutant emissions reductions differs in sign and magnitude by region, suggesting that calculations of “co-benefits” of climate policy that do not account for the existence of simultaneous air quality interventions can lead to inaccurate conclusions. Although reductions in global mean temperature are effective in improving air quality in many locations and sometimes yield compounding benefits, we show that the air quality impact of climate policy depends on air quality precursor emissions stringency.Our approach can be extended to include results from higher-resolution modeling, but also to incorporate other interventions towards sustainable development which interact with climate action and have spatially-distributed equity dimensions.