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The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple “equifinal” models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model–observation agreement could give a misleading impression of model robustness.

Atmospheric black carbon makes an important but poorly quantified contribution to the warming of the global atmosphere. Laboratory and modelling studies have shown that the addition of non-black-carbon materials to black-carbon particles may enhance the particles’ light absorption by 50 to 60% by refracting and reflecting light. Real-world experimental evidence for this ‘lensing’ effect is scant and conflicting, showing that absorption enhancements can be less than 5% or as large as 140%. Here we present simultaneous quantifications of the composition and optical properties of individual atmospheric black-carbon particles. We show that particles with a mass ratio of non-black carbon to black carbon of less than 1.5, which is typical of fresh traffic sources, are best represented as having no absorption enhancement. In contrast, black-carbon particles with a ratio greater than 3, which is typical of biomass-burning emissions, are best described assuming optical lensing leading to an absorption enhancement. We introduce a generalized hybrid model approach for estimating scattering and absorption enhancements based on laboratory and atmospheric observations. We conclude that the occurrence of the absorption enhancement of black-carbon particles is determined by the particles’ mass ratio of non-black carbon to black carbon. Mixing with non-black carbon can enhance the radiative effect of black-carbon aerosols. Lab and field measurements of aerosol properties reveal that the mass ratio of black to non-black carbon determines the amount of enhancement.

Vegetation fires emit large quantities of aerosol into the atmosphere, impacting regional air quality and climate. Previous work has used comparisons of simulated and observed aerosol optical depth (AOD) in regions heavily impacted by fires to suggest that emissions of aerosol particles from fires may be underestimated by a factor of 2–5. Here we use surface, aircraft and satellite observations made over the Amazon during September 2012, along with a global aerosol model to improve understanding of aerosol emissions from vegetation fires. We apply three different satellite-derived fire emission datasets (FINN, GFED, GFAS) in the model. Daily mean aerosol emissions in these datasets vary by up to a factor of 3.7 over the Amazon during this period, highlighting the considerable uncertainty in emissions. We find variable agreement between the model and observed aerosol mass concentrations. The model reproduces observed aerosol concentrations over deforestation fires well in the western Amazon during dry season conditions with FINN or GFED emissions and during dry–wet transition season conditions with GFAS emissions. In contrast, the model underestimates aerosol concentrations over savanna fires in the Cerrado environment east of the Amazon Basin with all three fire emission datasets. The model generally underestimates AOD compared to satellite and ground stations, even when the model reproduces the observed vertical profile of aerosol mass concentration. We suggest it is likely caused by uncertainties in the calculation of AOD, which are as large as ∼90 %, with the largest sensitivities due to uncertainties in water uptake and relative humidity. Overall, we do not find evidence that particulate emissions from fires are systematically underestimated in the Amazon region and we caution against using comparison with AOD to constrain particulate emissions from fires.

Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in anthropogenic aerosol−cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present-day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions—the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty. Significance Uncertainty in aerosol forcing of climate since the preindustrial era hampers efforts to quantify the sensitivity of global temperature to radiative perturbations caused by human activity. Because forcings are referenced to preindustrial conditions, a large part of the uncertainty will be reduced only by accurately defining pristine aerosol conditions before air pollution. We show that pristine conditions should still be observable on a few days per month in many regions of the Earth. However, pristine cloudy regions, which are of most importance for forcing uncertainty, occur almost entirely in the Southern Hemisphere. Reduction in uncertainty of predominantly Northern Hemisphere forcing may therefore have to rely on measurements from a different hemisphere, which will limit the extent to which uncertainties can be reduced.

Indonesia contains large areas of peatland that have been drained and cleared of natural vegetation, making them susceptible to burning. Peat fires emit considerable amounts of carbon dioxide, particulate matter (PM) and other trace gases, contributing to climate change and causing regional air pollution. However, emissions from peat fires are uncertain, due to uncertainties in emission factors and fuel consumption. We used the Weather Research and Forecasting model with chemistry and measurements of PM concentrations to constrain PM emissions from Indonesian fires during 2015, one of the largest fire seasons in recent decades. We estimate primary PM2.5 (particles with diameters less than 2.5 µm) emissions from fires across Sumatra and Borneo during September–October 2015 were 7.33 Tg, a factor 3.5 greater than those in the Fire Inventory from NCAR (FINNv1.5), which does not include peat burning. We estimate similar dry fuel consumption and CO2 emissions to those in the Global Fire Emissions Database (GFED4s, including small fires) but PM2.5 emissions that are a factor of 1.8 greater, due to updated PM2.5 emission factors for Indonesian peat. Fires were responsible for an additional 3.12 Tg of secondary organic aerosol formation. Through comparing simulated and measured PM concentrations, our work provides independent support of these updated emission factors. We estimate peat burning contributed 71 % of total primary PM2.5 emissions from fires in Indonesia during September–October 2015. We show that using satellite-retrieved soil moisture to modify the assumed depth of peat burn improves the simulation of PM, increasing the correlation between simulated and observed PM from 0.48 to 0.56. Overall, our work suggests that peat fires in Indonesia produce substantially greater PM emissions than estimated in current emission inventories, with implications for the predicted air quality impacts of peat burning.

Forest and vegetation fires, used as tools for agriculture and deforestation, are a major source of air pollutants and can cause serious air quality issues in many parts of Asia. Actions to reduce fire may offer considerable, yet largely unrecognized, options for rapid improvements in air quality. In this study, we used a combination of regional and global air quality models and observations to examine the impact of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south‐eastern China). We found that eliminating fire could substantially improve regional air quality across Southeast Asia by reducing the population exposure to fine particulate matter (PM2.5) concentrations by 7% and surface ozone concentrations by 5%. These reductions in PM2.5 exposures would yield a considerable public health benefit across the region; averting 59,000 (95% uncertainty interval (95UI): 55,200–62,900) premature deaths annually. Analysis of subnational infant mortality rate data and PM2.5 exposure suggested that PM2.5 from fires disproportionately impacts poorer populations across Southeast Asia. We identified two key regions in northern Laos and western Myanmar where particularly high levels of poverty coincide with exposure to relatively high levels of PM2.5 from fires. Our results show that reducing forest and vegetation fires should be a public health priority for the Southeast Asia region. Plain Language Summary Forest and vegetation fires, used for forest clearance and agriculture in Southeast Asia, are a major source of air pollutants and can cause serious air quality issues. In this study, we used computer models and measurements of air pollution to examine the effect of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south‐eastern China). We found that preventing these fires could substantially improve regional air quality and yield a considerable public health benefit across the region; avoiding around 59,000 premature deaths every year. Furthermore, our analysis of poverty data suggests that particulate pollution from fires disproportionately impacts poorer populations across Southeast Asia. Our results show that reducing forest and vegetation fires should be a public health priority for the Southeast Asia region. Key Points Eliminating forest and vegetation fires could substantially improve regional air quality in Mainland Southeast Asia Reducing exposure to particulate and ozone pollution from fires would yield a considerable public health benefit across Southeast Asia Particulate air pollution from fires disproportionately impacts poorer populations across Southeast Asia

Particulate matter (PM) emissions from vegetation and peat fires in Equatorial Asia cause poor regional air quality. Burning is greatest during drought years, resulting in strong inter-annual variability in emissions. We make the first consistent estimate of the emissions, air quality and public health impacts of Equatorial Asian fires during 2004-2015. The largest dry season (August-October) emissions occurred in 2015, with PM emissions estimated as 9.4 Tg, more than triple the average dry season emission (2.7 Tg). Fires in Sumatra and Kalimantan caused 94% of PM emissions from fires in Equatorial Asia. Peat combustion in Indonesian peatlands contributed 45% of PM emissions, with a greater contribution of 68% in 2015. We used the WRF-chem model to simulate dry season PM for the 6 biggest fire years during this period (2004, 2006, 2009, 2012, 2014, 2015). The model reproduces PM concentrations from a measurement network across Malaysia and Indonesia, suggesting our PM emissions are realistic. We estimate long-term exposure to PM resulted in 44 040 excess deaths in 2015, with more than 15 000 excess deaths annually in 2004, 2006, and 2009. Exposure to PM from dry season fires resulted in an estimated 131 700 excess deaths during 2004-2015. Our work highlights that Indonesian vegetation and peat fires frequently cause adverse impacts to public health across the region.

Air pollution exposure is a leading public health problem in China. Despite recent air quality improvements, fine particulate matter (PM 2.5 ) exposure remains large, the associated disease burden is substantial, and population ageing is projected to increase the susceptibility to disease. Here, we used emulators of a regional chemical transport model to quantify the impacts of future emission scenarios on air pollution exposure in China. We estimated how key emission sectors contribute to these future health impacts from air pollution exposure. We found that PM 2.5 exposure declines in all scenarios across China over 2020–2050, with reductions of 15% under current air quality legislation, 36% when exploiting the full potential of air pollutant emission reduction technologies, and 39% when that technical mitigation potential is combined with emission controls for climate mitigation. However, population ageing means that the PM 2.5 disease burden under current legislation (CLE) increases by 17% in 2050 relative to 2020. In comparison to CLE in 2050, the application of the best air pollution technologies provides substantial health benefits, reducing the PM 2.5 disease burden by 16%, avoiding 536 600 (95% uncertainty interval, 95UI: 497 800–573 300) premature deaths per year. These public health benefits are mainly due to reductions in industrial (43%) and residential (30%) emissions. Climate mitigation efforts combined with the best air pollution technologies leads to an additional 2% reduction in the PM 2.5 disease burden, avoiding 57 000 (95UI: 52 800–61 100) premature deaths per year. Up to 90% of the 2020–2050 reductions in PM 2.5 exposure are already achieved by 2030, assuming efficient implementation and enforcement of currently committed air quality policies in key sectors. Achieving reductions in PM 2.5 exposure and the associated disease burden after 2030 will require further tightening of emission limits for regulated sectors, addressing other sources including agriculture and waste management, and international coordinated action to mitigate air pollution across Asia.

Rapid warming at high latitudes, particularly in Siberia, has led to large wildfires in recent years that cause widespread smoke plumes. These fires lead to substantial deterioration in summer air quality in the region, with a factor 4 increase in summer fine particulate matter (PM 2.5 ) concentrations in parts of Siberia during 1998–2020. Exposure to PM 2.5 is associated with increased risk of mortality due to cardiovascular and respiratory disease, and the atmospheric lifetime of PM 2.5 means that it can be efficiently transported between regions and nations. We used the Community Earth System Model to quantify the fraction of PM 2.5 attributed to high latitude wildfires that occur in the Arctic Council member states and estimated the attributable health impact locally and in neighbouring countries. During 2001–2020 we attribute ~21,000 excess deaths to Arctic Council wildfires on average each year, of which ~8000 occur in countries outside the Arctic Council. Our analysis shows that the health impact of Arctic wildfires decreased during 2001–2020, despite the increase of wildfire-sourced PM 2.5 , which we suggest is due to a northwards shift in the average latitude of Siberian wildfires, reducing their impact on more densely populated regions.

Elevated surface concentrations of ozone and fine particulate matter (PM2.5) can lead to poor air quality and detrimental impacts on human health. These pollutants are also termed Near‐Term Climate Forcers (NTCFs) as they can also influence the Earth's radiative balance on timescales shorter than long‐lived greenhouse gases. Here we use the Earth system model, UKESM1, to simulate the change in surface ozone and PM2.5 concentrations from different NTCF mitigation scenarios, conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). These are then combined with relative risk estimates and projected changes in population demographics, to estimate the mortality burden attributable to long‐term exposure to ambient air pollution. Scenarios that involve the strong mitigation of air pollutant emissions yield large future benefits to human health (25%), particularly across Asia for black carbon (7%), when compared to the future reference pathway. However, if anthropogenic emissions follow the reference pathway, then impacts to human health worsen over South Asia in the short term (11%) and across Africa (20%) in the longer term. Future climate change impacts on air pollutants can offset some of the health benefits achieved by emission mitigation measures over Europe for PM2.5 and East Asia for ozone. In addition, differences in the future chemical environment over regions are important considerations for mitigation measures to achieve the largest benefit to human health. Future policy measures to mitigate climate warming need to also consider the impact on air quality and human health across different regions to achieve the maximum co‐benefits. Plain Language Summary Ground level ozone (O3) and fine particulate matter (PM2.5) are two major air pollutants that are associated with adverse effects to human health. In addition, changes in their atmospheric concentrations can also influence the rate of climate change on a timeframe shorter than that for long‐lived greenhouse gases. In this study we use a global Earth system model to simulate the change in concentrations of surface O3 and PM2.5 across numerous future mitigation scenarios, which are then used to quantify the impact on the air pollution health burden. A large reduction in the air pollutant health burden of the population, particularly across Asia, is calculated in scenarios that have large reductions in air pollutant sources. However, impacts on health can increase across large parts of Africa in a scenario where emissions of air pollutants are not reduced. Future climate warming increases the exposure to air pollutants across regions such as Europe and East Asia, with a detrimental impact on human health. Measures to limit future climate warming and improve regional air pollutant health burdens are interconnected and important to consider together when designing future policies. Key Points Strong mitigation of aerosols and ozone precursors leads to large future benefits to the air pollution health burden, particularly over Asia Future climate change can offset the health benefits of a reduced air pollution health burden from emissions mitigation over Europe and East Asia It is important to consider future chemical environments when designing measures to maximize benefits to climate, air quality, and health