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Climate change has increased the vulnerability of boreal forests and grasslands to wildfires. An increase in high-latitude wildfires has resulted in the deterioration of air quality, particularly in Western Siberia, where PM2.5 levels have increased at >1 µg m-3 year-1 during 1998−2020. Arctic wildfire carbon emissions have doubled during the last 20 years, and in Siberia they have shifted northwards. Using fire air pollutant emissions data from the Quick Fire Emissions Dataset (QFED), we create two emissions scenarios for Arctic Council member nations, with and without wildfires. PM2.5 is simulated for the two scenarios using the Community Earth System Model, which we evaluate using in-situ measurement data, finding a large negative bias in wildfire plumes. To correct this underestimation we use a high resolution PM2.5 reanalysis dataset, improving agreement with observations. Bias-corrected scenarios are used to estimate air quality degradation and resulting health impacts due to Arctic Council nation wildfires across the Northern Hemisphere high- and mid-latitudes for the period 2001-2020. We use the Global Exposure Mortality Model to estimate the health impacts of chronic exposure to Arctic wildfire-attributed PM2.5­. We find that health impacts are highly variable, with 25,000−55,000 premature deaths yearly, with most of the health burden falling on nations outside the Arctic Council, particularly China, due to transboundary transport of Siberian wildfire PM2.5. Health impacts have decreased during our study period partly due to the northwards shift in wildfires.

Understanding the health co-benefits of climate change mitigation and how they manifest across different socioeconomic groups is crucial to justify and prioritise future decarbonisation pathways to achieve net zero. In this work, we quantify future worldwide air quality and public health co-benefits of decarbonisation to limit end-of-century warming to either 2ºC (scenario SSP1-2.6) or 1.5ºC (scenario SSP1-1.9), relative to the middle-of-the-road pathway with a medium long-term radiative forcing target of 4.5 W m-2 (scenario SSP2-4.5). We use simulated ambient fine particulate matter (PM2.5) concentrations for the period 2015-2100 from the Coupled Model Intercomparison Project (CMIP6) experiments. We estimate the mortality burden attributable to exposure to ambient PM2.5 using population attributable fractions of relative risk, incorporating projected changes in population demographics and per-capita GDP. We find that following a future decarbonisation pathway could produce substantial global reductions in population exposure to PM2.5 pollution and associated premature mortality across all socioeconomic groups, with maximum health benefits achieved for middle-income populations (predominantly in Asia) around mid-century. Overall, the more moderate 2ºC-compliant mitigation scenario (SSP1-2.6) could reduce the global PM2.5-attributable mortality burden by 24% in 2050 relative to SSP2-4.5, averting ~2.5M (95% uncertainty interval (UI): 2.1-2.8M) annual deaths worldwide. The more stringent 1.5ºC scenario (SSP1-1.9) could reduce the PM2.5 mortality burden by 29% in 2050, averting ~2.9M (UI: 2.5-3.4M) annual deaths. The magnitude of the air quality and health benefits of reduced PM2.5 pollution through decarbonisation vary with the socioeconomic status of the exposed population, with greater reductions in the PM2.5 mortality burden in middle- and high-income regions (22%) than in the low-income region (15%). Overall, the disparity in PM2.5 exposure between low- and high-income populations is predicted to reduce by 2100 under all three future scenarios. However, the global PM2.5 exposure disparity is projected to increase up to mid-century under the SSP2-4.5 scenario, thus, immediate reduction in the disparity in the near term, is only achieved under a decarbonisation scenario. Despite overall reductions in global PM2.5 exposure inequalities by the end of the century, the disparity in PM2.5 exposure remains around 30%, with the low- and lower-middle-income populations continuing to experience PM2.5 exposures that are over three times the WHO Air Quality Guideline.

We use a regional chemistry transport model (Weather Research and Forecasting model coupled with chemistry, WRF-Chem) in conjunction with surface observations of tropospheric ozone and Ozone Monitoring Instrument (OMI) satellite retrievals of tropospheric column NO2 to evaluate processes controlling the regional distribution of tropospheric ozone over western Siberia for late spring and summer in 2011. This region hosts a range of anthropogenic and natural ozone precursor sources, and it serves as a gateway for near-surface transport of Eurasian pollution to the Arctic. However, there is a severe lack of in situ observations to constrain tropospheric ozone sources and sinks in the region. We show widespread negative bias in WRF-Chem tropospheric column NO2 when compared to OMI satellite observations from May–August, which is reduced when using ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) v5a emissions (fractional mean bias (FMB) = −0.82 to −0.73) compared with the EDGAR (Emissions Database for Global Atmospheric Research)-HTAP (Hemispheric Transport of Air Pollution) v2.2 emissions data (FMB = −0.80 to −0.70). Despite the large negative bias, the spatial correlations between model and observed NO2 columns suggest that the spatial pattern of NOx sources in the region is well represented. Scaling transport and energy emissions in the ECLIPSE v5a inventory by a factor of 2 reduces column NO2 bias (FMB = −0.66 to −0.35), but with overestimates in some urban regions and little change to a persistent underestimate in background regions. Based on the scaled ECLIPSE v5a emissions, we assess the influence of the two dominant anthropogenic emission sectors (transport and energy) and vegetation fires on surface NOx and ozone over Siberia and the Russian Arctic. Our results suggest regional ozone is more sensitive to anthropogenic emissions, particularly from the transport sector, and the contribution from fire emissions maximises in June and is largely confined to latitudes south of 60∘ N. Ozone dry deposition fluxes from the model simulations show that the dominant ozone dry deposition sink in the region is to forest vegetation, averaging 8.0 Tg of ozone per month, peaking at 10.3 Tg of ozone deposition during June. The impact of fires on ozone dry deposition within the domain is small compared to anthropogenic emissions and is negligible north of 60∘ N. Overall, our results suggest that surface ozone in the region is controlled by an interplay between seasonality in atmospheric transport patterns, vegetation dry deposition, and a dominance of transport and energy sector emissions.

Deforestation and drainage has made Indonesian peatlands susceptible to burning. Large fires occur regularly, destroying agricultural crops and forest, emitting large amounts of CO2 and air pollutants, resulting in adverse health effects. In order to reduce fire, the Indonesian government has committed to restore 2.49 Mha of degraded peatland, with an estimated cost of US$3.2-7 billion. Here we combine fire emissions and land cover data to estimate the 2015 fires, the largest in recent years, resulted in economic losses totalling US$28 billion, whilst the six largest fire events between 2004 and 2015 caused a total of US$93.9 billion in economic losses. We estimate that if restoration had already been completed, the area burned in 2015 would have been reduced by 6%, reducing CO2 emissions by 18%, and PM2.5 emissions by 24%, preventing 12,000 premature mortalities. Peatland restoration could have resulted in economic savings of US$8.4 billion for 2004–2015, making it a cost-effective strategy for reducing the impacts of peatland fires to the environment, climate and human health., Deforestation and drainage have made Indonesian peatlands susceptible to burning. Here the authors find that Indonesia’s 2015 fires resulted in economic losses totaling US$28 billion, while the area burned and emissions released could have been significantly reduced had restoration been completed.

Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry‐climate model combined with exposure‐response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300–3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003–2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600–8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon., Key Points Increases in deforestation among states analyzed in the Brazilian Legal Amazon since 2012 increased the dry season fire count by 39% in 2019This increase in fire resulted in 3,400 (3,300–3,550) additional deaths in 2019 due to increased exposure to particulate air pollutionOur analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon

To improve poor air quality in Asia and inform effective emission-reduction strategies, it is vital to understand the contributions of different pollution sources and their associated human health burdens. In this study, we use the WRF-Chem regional atmospheric model to explore the air quality and human health benefits of eliminating emissions from six different anthropogenic sectors (transport, industry, shipping, electricity generation, residential combustion, and open biomass burning) over South and East Asia in 2014. We evaluate WRF-Chem against measurements from air quality monitoring stations across the region and find the model captures the spatial distribution and magnitude of PM2.5 (particulate matter with an aerodynamic diameter of no greater than 2.5 µm). We find that eliminating emissions from residential energy use, industry, or open biomass burning yields the largest reductions in population-weighted PM2.5 concentrations across the region. The largest human health benefit is achieved by eliminating either residential or industrial emissions, averting 467 000 (95 % uncertainty interval (95UI): 409 000–542 000) or 283 000 (95UI: 226 000–358 000) annual premature mortalities, respectively, in India, China, and South-east Asia, with fire prevention averting 28 000 (95UI: 24 000–32 000) annual premature mortalities across the region. We compare our results to previous sector-specific emission studies. Across these studies, residential emissions are the dominant cause of particulate pollution in India, with a multi-model mean contribution of 42 % to population-weighted annual mean PM2.5. Residential and industrial emissions cause the dominant contributions in China, with multi-model mean contributions of 29 % for both sectors to population-weighted annual mean PM2.5. Future work should focus on identifying the most effective options within the residential, industrial, and open biomass-burning emission sectors to improve air quality across South and East Asia.

The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern‐Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 μm (PM2.5) concentrations and the associated health impact from short‐term population exposure to bushfire PM2.5. The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to “Poor” or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle‐Maitland, Canberra‐Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66–291) deaths were brought forward due to short‐term exposure to bushfire PM2.5. The health burden was largest in New South Wales (NSW) (109 (95% CI: 41–176) deaths brought forward), Queensland (15 (95% CI: 5–24)), and Victoria (35 (95% CI: 13–56)). This represents 38%, 13% and 30% of the total deaths brought forward by short‐term exposure to all PM2.5. At a city‐level 65 (95% CI: 24–105), 23 (95% CI: 9–38) and 9 (95% CI: 4–14) deaths were brought forward from short‐term exposure to bushfire PM2.5, accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM2.5. Thus, the bushfires caused substantial AQ and health impacts across eastern‐Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this., Key Points The fires led to widespread exposure to “Poor” or worse Air Quality Index levels across eastern‐AustraliaThe highest all‐cause, all‐age mortality from short‐term exposure to bushfire particulate matter with a diameter less than 2.5 μm (PM2.5) was seen in the states of New South Wales, Queensland, and VictoriaAll‐cause, all‐age mortality from short‐term exposure to bushfire PM2.5 was highest in the cities of Sydney, Melbourne, and Canberra

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51%–94% of first‐order sensitivity index), industrial (7%–31%), and agricultural emissions (0%–24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68%–81%, down to 15.3–25.9 μg m−3, remaining above the World Health Organization annual guideline of 10 μg m−3. The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 μg m−3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors., Key Points We developed accurate and fast emulators to predict air quality in China from emission changesWinter ambient fine particulate matter concentrations were primarily sensitive to residential, industrial, and agricultural emissionsThe National Air Quality Target is unlikely to be met in winter without large emission reductions in the residential and industrial sectors

Air pollution exposure is a leading public health problem in China. The majority of the total air pollution disease burden is from fine particulate matter (PM2.5) exposure, with smaller contributions from ozone (O3) exposure. Recent emission reductions have reduced PM2.5 exposure. However, levels of exposure and the associated risk remain high, some pollutant emissions have increased, and some sectors lack effective emission control measures. We quantified the potential impacts of relevant policy scenarios on ambient air quality and public health across China. We show that PM2.5 exposure inside the Greater Bay Area (GBA) is strongly controlled by emissions outside the GBA. We find that reductions in residential solid fuel use and agricultural fertilizer emissions result in the greatest reductions in PM2.5 exposure and the largest health benefits. A 50% transition from residential solid fuel use to liquefied petroleum gas outside the GBA reduced PM2.5 exposure by 15% in China and 3% within the GBA, and avoided 191,400 premature deaths each year across China. Reducing agricultural fertilizer emissions of ammonia by 30% outside the GBA reduced PM2.5 exposure by 4% in China and 3% in the GBA, avoiding 56,500 annual premature deaths across China. Our simulations suggest that reducing residential solid fuel or industrial emissions will reduce both PM2.5 and O3 exposure, whereas other policies may increase O3 exposure. Improving particulate air quality inside the GBA will require consideration of residential solid fuel and agricultural sectors, which currently lack targeted policies, and regional cooperation both inside and outside the GBA., Key Points Ambient fine particulate matter exposure inside the Greater Bay Area is strongly controlled by emissions outside the Greater Bay AreaResidential solid fuel and agricultural emissions lack effective controls that could improve air quality and public health across ChinaImproving particulate air quality inside the Greater Bay Area will require regional cooperation inside and outside the Greater Bay Area

Vegetation fires across the tropics emit fine particulate matter (PM2.5) to the atmosphere, degrading regional air quality and impacting human health. Extensive vegetation fires occur regularly across the Amazon basin, but there have been no detailed assessments of the impacts on air quality or human health. We used updated exposure-response relationships and a regional climate-chemistry model, evaluated against a comprehensive set of observational data, to provide the first in-depth assessment of the potential public health benefits due to fire prevention across the Amazon Basin. We focused on 2012, a year with emissions similar to the 11-year average (2008 to 2018). Vegetation fires contributed >80% of simulated dry season mean surface PM2.5 in the western Amazon region particularly in Bolivia and Brazilian states of Rondônia, Acre, and Mato Grosso. We estimate that the prevention of vegetation fires would have averted 16 800 (95UI: 16 300–17 400) premature deaths and 641 000 (95UI: 551 900–741 300) disability adjusted life years (DALYs) across South America, with 26% of the avoided health burden located within the Amazon Basin. The health benefits of fire prevention in the Amazon are comparable to those found in Equatorial Asia.

On June 24th 2018 one of the largest UK wildfires in recent history broke out on Saddleworth Moor, close to Manchester, in north-west England. Since wildfires close to large populations in the UK have been relatively small and rare in the past, there is little knowledge about the impacts. This has prevented the development of effective strategies to reduce them. This paper uses a high-resolution coupled atmospheric-chemistry model to assess the impact of the fires on particulate matter with a diameter less than 2.5 µm (PM2.5) across the region and the impact on health from short-term exposure. We find that the fires substantially degraded air quality. PM2.5 concentrations increased by more than 300% in Oldham and Manchester and up to 50% in areas up to 80 km away such as Liverpool and Wigan. This led to one quarter of the population (2.9 million people) in the simulation domain (−4.9–0.7°E and 53.0–54.4°N) being exposed to moderate PM2.5 concentrations on at least one day, according to the Daily Air Quality Index (36–53 µg m−3), between June 23rd and 30th 2018. This equates to 4.5 million people being exposed to PM2.5 above the WHO 24-hour guideline of 25 µg m−3 on at least one day. Using a concentration-response function we calculate the short-term health impact, which indicates that in total over the 7-day period 28 (95% CI: 14.1–42.1) deaths were brought forward, with a mean daily excess mortality of 3.5 deaths per day (95% CI: 1.8–5.3). The excess mortalities from PM2.5 from the fires represented up to 60% of the total excess mortality (5.7 of 9.5 excess deaths), representing an increase of 3.8 excess mortalities (165% increase) compared to if there were no fires. We find the impact of mortality due to PM2.5 from the fires on the economy was also substantial (£21.1 m).

Air pollution is a serious environmental issue and leading contributor to the disease burden in China. Following severe air pollution episodes during the 2012-2013 winter, the Chinese government has prioritised efforts to reduce PM2.5 emissions, and established a national monitoring network to record air quality trends. Rapid reductions in fine particulate matter (PM2.5) concentrations and increased ozone concentrations have occurred across China, during 2015 to 2017. We used measurements of particulate matter with a diameter < 2.5 µm (PM2.5) and Ozone (O3) from >1000 stations across China combined with similar datasets from Hong Kong and Taiwan to calculate trends in PM2.5, Nitrogen Dioxide, Sulphur Dioxide and O3 across the greater China region during 2015-2019. We then use the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) regional air quality simulations, to explore the drivers and impacts of observed trends. Using annually varying emissions from the Multi-resolution Emission Inventory for China, we simulate air quality across China during 2015-2017, and calculate a median PM2.5 trends of -3.9 µg m-3 year-1. The measured nationwide median PM2.5 trend of -3.4 µg m-3 year-. With anthropogenic emissions fixed at 2015-levels, the simulated trend was much weaker (-0.6 µg m-3 year-1), demonstrating interannual variability in meteorology played a minor role in the observed PM2.5 trend. The model simulated increased ozone concentrations in line with the measurements, but underestimated the magnitude of the observed absolute trend by a factor of 2. We combined simulated trends in PM2.5 concentrations with an exposure-response function to estimate that reductions in PM2.5 concentrations over this period have reduced PM2.5-attribrutable premature morality across China by 150 000 deaths year-1.

Air pollution is a serious environmental issue and leading contributor to disease burden in China. Rapid reductions in fine particulate matter (PM2.5) concentrations and increased ozone concentrations occurred across China during 2015 to 2017. We used measurements of particulate matter with a diameter

Long‐term ambient ozone (O3) exposure is a risk factor for human health. We estimate the source‐specific disease burden associated with long‐term O3 exposure in India at high spatial resolution using updated risk functions from the American Cancer Society Cancer Prevention Study II. We estimate 374,000 (95UI: 140,000–554,000) annual premature mortalities using the updated risk function in India in 2015, 200% larger than estimates using the earlier American Cancer Society Cancer Prevention Study II risk function. We find that land transport emissions dominate the source contribution to this disease burden (35%), followed by emissions from power generation (23%). With no change in emissions by 2050, we estimate 1,126,000 (95UI: 421,000–1,667,000) annual premature mortalities, an increase of 200% relative to 2015 due to population aging and growth increasing the number of people susceptible to air pollution. We find that the International Energy Agency New Policy Scenario provides small changes (+1%) to this increasing disease burden from the demographic transition. Under the International Energy Agency Clean Air Scenario we estimate 791,000 (95UI: 202,000–1,336,000) annual premature mortalities in 2050, avoiding 335,000 annual premature mortalities (45% of the increase) compared to the scenario of no emission change. Our study highlights that critical public health benefits are possible with stringent emission reductions, despite population growth and aging increasing the attributable disease burden from O3 exposure even under such strong emission reductions. The disease burden attributable to ambient fine particulate matter exposure dominates that from ambient O3 exposure in the present day, while in the future, they may be similar in magnitude., Key Points The disease burden associated with ozone exposure in India is larger using updated risk functions relative to earlier risk functionsStringent emission controls offset part of the increasing future disease burden from ozone exposure caused by population aging and growthThe present‐day disease burden from ambient PM2.5 exposure dominates ambient O3, while in the future, they may be similar in magnitude

Exposure to high concentrations of ambient fine particulate matter (PM2.5) is a leading risk factor for public health in India causing a large burden of disease. Business‐as‐usual economic and industrial growth in India is predicted to increase emissions, worsen air quality, and increase the associated disease burden in future decades. Here we use a high‐resolution online‐coupled model to estimate the impacts of different air pollution control pathways on ambient PM2.5 concentrations and human health in India. We find that with no change in emissions, the disease burden from exposure to ambient PM2.5 in 2050 will increase by 75% relative to 2015, due to population aging and growth increasing the number of people susceptible to air pollution. We estimate that the International Energy Agencies New Policy Scenario (NPS) and Clean Air Scenario (CAS) in 2050 can reduce ambient PM2.5 concentrations below 2015 levels by 9% and 68%, respectively, offsetting 61,000 and 610,000 premature mortalities a year, which is 9% and 91% of the projected increase in premature mortalities due to population growth and aging. Throughout India, the CAS stands out as the most effective scenario to reduce ambient PM2.5 concentrations and the associated disease burden, reducing the 2050 mortality rate per 100,000 below 2015 control levels by 15%. However, even under such stringent emission control policies, population growth and aging results in premature mortality estimates from exposure to particulate air pollution to increase by 7% compared to 2015, highlighting the challenge facing efforts to improve public health in India., Key Points Air pollution is a major risk factor for human health in IndiaPopulation aging and growth will increase the disease burden due to exposure to particulate air pollution even under no emission changeStringent emission control reduces mortality rate in 2050 below 2015 levels although total premature mortality increases

Public health in India is gravely threatened by severe PM2.5 exposure. This study presents an analysis of long-term PM2.5 exposure in four Indian megacities (Delhi, Chennai, Hyderabad and Mumbai) based on in-situ observations during 2015–2018, and quantifies the health risks of short-term exposure during Diwali Fest (usually lasting for ~5 days in October or November and celebrating with lots of fireworks) in Delhi for the first time. The population-weighted annual-mean PM2.5 across the four cities was 72 μg/m3, ~3.5 times the global level of 20 μg/m3 and 1.8 times the annual criterion defined in the Indian National Ambient Air Quality Standards (NAAQS). Delhi suffers the worst air quality among the four cities, with citizens exposed to ‘severely polluted’ air for 10% of the time and to unhealthy conditions for 70% of the time. Across the four cities, long-term PM2.5 exposure caused about 28,000 (95% confidence interval: 17,200–39,400) premature mortality and 670,000 (428,900–935,200) years of life lost each year. During Diwali Fest in Delhi, average PM2.5 increased by ~75% and hourly concentrations reached 1676 μg/m3. These high pollutant levels led to an additional 20 (13–25) daily premature mortality in Delhi, an increase of 56% compared to the average over October–November. Distinct seasonal and diurnal variations in PM2.5 were found in all cities. PM2.5 mass concentrations peak during the morning rush hour in all cities. This indicates local traffic could be an important source of PM2.5, the control of which would be essential to improve air quality. We report an interesting seasonal variation in the diurnal pattern of PM2.5 concentrations, which suggests a 1–2 h shift in the morning rush hour from 8 a.m. in pre-monsoon/summer to 9–10 a.m. in winter. The difference between PM2.5 concentrations on weekdays and weekend, namely weekend effect, is negligible in Delhi and Hyderabad, but noticeable in Mumbai and Chennai where ~10% higher PM2.5 concentrations were observed in morning rush hour on weekdays. These local characteristics provide essential information for air quality modelling studies and are critical for tailoring the design of effective mitigation strategies for each city. Keywords: PM2.5, Health effect, Diwali festival effect, Weekend effect, Long-term, Short-term

Indonesia contains large areas of peatland which are being 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 burn depth of peat. 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 PM2.5 (particles with diameters less than 2.5 μm) emissions from fires across Sumatra and Borneo during September to October 2015 were 7.33 Tg, a factor 3.5 greater than those in 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), but a factor 1.8 greater PM2.5 emissions, due to updated PM2.5 emission factors for Indonesian peat. Through comparing simulated and measured PM concentrations, our work provides an independent confirmation of these updated emission factors. We estimate peat burning contributes 71 % of total PM2.5 emissions from fire 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 datasets, with implications for the predicted air quality impacts of peat burning.

To improve poor air quality in Asia and inform effective emission-reduction strategies, it is vital to understand the contributions of different pollution sources and their associated human health burdens. In this study, we use the WRF-Chem regional atmospheric model to explore the air quality and human health benefits of eliminating emissions from seven different anthropogenic sectors (transport, industry, shipping, agriculture, energy generation, residential combustion and open biomass burning) over South and East Asia in 2014. We evaluate WRF-Chem against measurements from air quality monitoring stations across the region and find the model captures the spatial distribution and magnitude of PM2.5 (particulate matter

Exposure to fine particulate matter (PM2.5) is a leading contributor to the disease burden in India, largely due to widespread household solid fuel use. The transition from solid to clean fuels in households has the potential to substantially improve public health. India has implemented large initiatives to promote clean fuel access, but how these initiatives will reduce PM2.5 exposure and the associated health benefits have not yet been established. We quantified the impacts of a transition of household energy from solid fuel use to liquefied petroleum gas (LPG) on public health in India from ambient and household PM2.5 exposure. We estimate that the transition to LPG would reduce ambient PM2.5 concentrations by 25%. Reduced exposure to total PM2.5 results in a 29% reduction in the loss of healthy life, preventing 348 000 (95% uncertainty interval, UI: 284 000–373 000) premature mortalities every year. Achieving these benefits requires a complete transition to LPG. If access to LPG is restricted to within 15 km of urban centres, then the health benefits of the clean fuel transition are reduced by 50%. If half of original solid fuel users continue to use solid fuels in addition to LPG, then the health benefits of the clean fuel transition are reduced by 75%. As the exposure–outcome associations are non–linear, it is critical for air pollution studies to consider the disease burden attributed to total PM2.5 exposure, and not only the portion attributed to either ambient or household PM2.5 exposure. Our work shows that a transition to clean household energy can substantially improve public health in India, however, these large public health benefits are dependent on the complete transition to clean fuels for all.

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.

Each year more than 29,000 premature deaths in the UK are linked to long term-exposure to ambient particulate matter (PM) with a diameter less than 2.5 μm (PM2.5). Many studies have focused on the long-term impacts of exposure to PM, but short-term increases in pollution can also exacerbate health effects, leading to deaths brought forward within exposed populations. This study investigates the impact of different atmospheric circulation patterns on UK PM2.5 concentrations and the relative contribution of local and transboundary pollutants to variations in PM2.5 concentrations. Daily mean PM2.5 observations from 42 UK background sites indicate that easterly, south-easterly and southerly wind directions and anticyclonic circulation patterns enhance background concentrations of PM2.5 at all UK sites by up to 12 μg m-3. Results from back trajectory analysis and the European Monitoring and Evaluation Programme for UK model (EMEP4UK) show this is due to the transboundary transport of pollutants from continental Europe. While back trajectories indicate under easterly, south-easterly and southerly flow 25–50% of the total accumulated primary PM2.5 emissions originate outside of the UK, with a very polluted footprint (0.25–0.35 μg m-2). Anticyclonic conditions, which occur frequently (21%), also lead to increases in PM2.5 concentrations (UK multi-annual mean 14.7 μg m-3). EMEP4UK results indicate this is likely due the build-up of local emissions due to slack winds. Under westerly and north-westerly flow 15–30% of the total accumulated primary PM2.5 emissions originate outside of the UK, and are much less polluted (0.1 μg m-2) with model results indicating transport of clean maritime air masses from the Atlantic. Results indicate that both wind-direction and stability under anticyclonic conditions are important in controlling ambient PM2.5 concentrations across the UK. There is also a strong dependence of high PM2.5 Daily Air Quality Index (DAQI) values on easterly, south-easterly and southerly wind-directions, with >70% of occurrences of observed 48–71+ μg m-3 concentrations occurring under these wind directions. While north-westerly and cyclonic conditions reduce PM2.5 concentrations at all sites by up to 8 μg m-3. PM2.5 DAQI values are also lowest under these conditions, with >80% of 0–11 μg m-3 concentrations and >50% of 12–23 μg m-3 concentrations observed during westerly, north-westerly and northerly wind directions. Indicating that these conditions are likely to be associated with a reduction in the potential health effects from exposure to ambient levels of PM2.5. Keywords: LWT, PM2.5, long-range transport, Air quality, Emissions, AURN

Combustion of wood and other biomass is a significant contributor to poor air quality in many developing countries. Emissions of particulates and Polycyclic Aromatic Hydrocarbons (PAH) are a major health hazard, particularly in Africa where the use of domestic cookstoves has increased alongside population expansion. Because of economic factors firewood is commonly used in place of the more expensive charcoal; particularly in rural areas. This work conducts a study of PAH emissions from an African cookstove comparing the combustion of both charcoal and firewood. It is demonstrated that PAH and particulate emissions are much higher from the firewood compared to the charcoal. The difference in levels can be interpreted due to the importance of the pyrolysis reactions of the volatile components of wood in PAH formation, whereas these volatiles emissions are much smaller from charcoal. Analysis of the combustion phases (flaming, smouldering) is undertaken and a computer model has been developed to link the composition of the fuels to the emissions of the PAH and particulates. The modelled PAH levels are shown to follow a similar trend to the experimental results.

Exposure to ambient fine particulate matter (PM2.5) is a leading contributor to diseases in India. Previous studies analysing emission source attributions were restricted by coarse model resolution and limited PM2.5 observations. We use a regional model informed by new observations to make the first high-resolution study of the sector-specific disease burden from ambient PM2.5 exposure in India. Observed annual mean PM2.5 concentrations exceed 100 μg m−3 and are well simulated by the model. We calculate that the emissions from residential energy use dominate (52%) population-weighted annual mean PM2.5 concentrations, and are attributed to 511,000 (95UI: 340,000–697,000) premature mortalities annually. However, removing residential energy use emissions would avert only 256,000 (95UI: 162,000–340,000), due to the non-linear exposure–response relationship causing health effects to saturate at high PM2.5 concentrations. Consequently, large reductions in emissions will be required to reduce the health burden from ambient PM2.5 exposure in India., Exposure to ambient particulate matter is a key contributor to disease in India and source attribution is vital for pollution control. Here the authors use a high-resolution regional model to show residential emissions dominate particulate matter concentrations and associated premature mortality.