Clean air policies are key for successfully mitigating Arctic warming

The Arctic is warming at a rate three times faster than the global average, posing significant environmental and societal risks. Reducing greenhouse gas (GHG) emissions, particularly CO2, is crucial to limit Arctic warming and sea ice melt. However, the world is not currently on track to meet the Paris Agreement goals. Simultaneously, many regions are implementing policies to reduce transboundary air pollution, a major health concern. Air pollutants, such as particulate matter and tropospheric ozone, act as Short-Lived Climate Forcers (SLCFs), influencing both air quality and climate. While the linkages between air quality and climate are well-established, these aspects are often treated separately. SLCFs, including methane (CH4), have short atmospheric lifetimes and their control offers significant potential for rapidly mitigating warming. However, the climate mitigation potential of SLCFs, particularly concerning Arctic warming, is still poorly understood. Existing climate models often struggle to accurately capture the competing influences of CO2 and short-lived particulate matter, leading to uncertainties in projections. This research addresses these limitations by integrating climate and air quality models to assess the co-benefits and trade-offs of emissions reductions, providing more comprehensive insights into the effectiveness of clean air policies in mitigating Arctic warming.

The literature highlights the importance of both GHG and SLCF reductions in mitigating Arctic warming. Studies show the significant role of black carbon (BC) and methane in Arctic amplification. However, existing research often lacks integrated assessments that consider the complex interplay between different pollutants and their combined climate effects. While the need for integrated approaches is widely acknowledged, the lack of robust assessments of SLCF mitigation actions compared with GHG mitigation remains a significant gap. There is also a need for more realistic scenarios that incorporate technological changes and development pathways to better understand the efficacy of various mitigation strategies. Studies have shown that declines in sulfur emissions, while beneficial for air quality, can lead to increased warming through the unmasking effect. These complexities underscore the need for a comprehensive approach that considers multiple pollutants and their interactions.

This study utilized a novel model approach that integrates climate and air quality models to assess the impacts of emissions reductions on both climate and human health. The researchers combined a new model approach to assess climate and human health co-benefits of emissions reductions. Four Shared Socioeconomic Pathways (SSPs) scenarios from CMIP6, capturing a wide range of GHG and other anthropogenic drivers, were used. In addition to SSP scenarios, four new Arctic Monitoring and Assessment Programme (AMAP) scenarios were developed to explore the impacts of dedicated air quality and SLCF policies for two distinct socio-economic futures, consistent with SSP2-4.5 and SSP1-2.6. These included current legislation (CLE), maximum technically feasible reduction (MFR), MFR with sustainable development (MFR_SDS), and climate forcing mitigation (CFM) scenarios. The models used for assessing climate change included Earth System Models (ESMs). Air quality changes were assessed using ten global models, including four ESMs and other chemical transport models. The researchers distinguished between pollutants with cooling or warming impacts, analyzing the individual contributions of sulfur dioxide (SO2), black carbon (BC), organic carbon (OC), and methane (CH4). The study used multiple models to assess uncertainties in simulations of air pollution dynamics, considering various radiative forcing processes (radiation, surface albedo, and clouds). Mortality impacts were assessed using the TM5-FASST model. The study further refined their methodology using an Earth System Model (ESM) emulator to improve the accuracy and efficiency of the simulations, especially for regional-level impacts on Arctic warming.

The study’s key findings demonstrate that while reducing sulfur emissions leads to significant human health benefits, this can paradoxically enhance Arctic warming. The unmasking effect of decreasing sulfate aerosols leads to approximately 0.8 °C of additional warming by 2050 compared to 1995–2014. However, the researchers found that reducing black carbon (BC) and methane emissions can effectively offset this warming effect. Specifically, BC emission reductions would reduce Arctic warming by 0.3 °C in the MFR scenario compared to the CLE scenario. Simultaneous reductions in CH4 would further reduce warming by 0.2 °C. In a scenario prioritizing BC and CH4 reductions (CFM), Arctic warming could be reduced by 0.4 °C in 2050, comparable to the warming reduction from global CO2 emission reductions in the SSP1-2.6 scenario (0.5 °C). The study also found that reducing BC emissions from Arctic Council countries was particularly efficient in slowing Arctic warming due to diminished absorption of solar radiation by BC in snow and ice. Concerning air quality and human health, the maximum feasible reductions in air pollutants (MFR and MFR_SDS scenarios) would lead to substantial reductions in PM2.5 concentrations globally, with the most significant reductions in Asian countries. These reductions are projected to occur mainly before 2030. Mortality rates attributable to PM2.5 and ozone would also decline significantly under the MFR and MFR_SDS scenarios, preventing hundreds of thousands of premature deaths. The study highlights that an integrated approach addressing air quality, development, and climate policies is essential to achieving both climate and health goals.

The study's findings underscore the importance of considering the complex interactions between different pollutants and their climate impacts when designing emission reduction strategies. The paradoxical effect of reduced sulfur emissions on Arctic warming highlights the need for a holistic approach that goes beyond simply targeting CO2 reductions. The significant potential of BC and CH4 emission reductions to mitigate Arctic warming emphasizes the need to prioritize these pollutants in mitigation strategies. The study’s results demonstrate that ambitious emission reductions can yield substantial co-benefits for both climate and human health. The findings support the Arctic Council's goal of reducing black carbon emissions, highlighting its potential for significant climate benefits. The study also acknowledges limitations associated with model uncertainties but emphasizes the robustness of the key findings within plausible uncertainty ranges. The combined use of different models helps to assess model uncertainties and to strengthen the overall findings. The study’s conclusion underscores the need for integrated policies that address air quality, development, and climate to achieve long-term sustainability goals.

This research demonstrates that integrating climate and air quality models provides valuable insights into the complex interplay of pollutants and their effects on Arctic warming. While reducing sulfur emissions improves air quality and human health, it can paradoxically exacerbate Arctic warming. This study demonstrates that ambitious reductions in black carbon and methane emissions are essential to offset this warming effect and achieve significant co-benefits for both climate and human health. Future research should focus on further refining models to reduce uncertainties and exploring the feasibility and effectiveness of various policy instruments for achieving the necessary emission reductions. A truly integrated approach is essential for achieving global sustainability goals.

The study acknowledges limitations related to model uncertainties, particularly regarding the interactions between aerosols and clouds, and the representation of complex climate feedbacks. While multiple models were used, uncertainties remain, especially concerning the regional-scale impacts of specific pollutants. The scenarios considered may not fully capture future technological advancements or socio-economic changes that could influence emission trajectories. The study's reliance on model simulations, rather than direct observations, implies that model uncertainty may affect the precision of the quantitative results, although the overall qualitative trends are robust.