Exposure to ambient fine particulate matter (PM
) is a leading contributor to diseases in India. Previous studies analysing emission source attributions were restricted by coarse model resolution and ...limited PM
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 PM
exposure in India. Observed annual mean PM
concentrations exceed 100 μg m
and are well simulated by the model. We calculate that the emissions from residential energy use dominate (52%) population-weighted annual mean PM
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 PM
concentrations. Consequently, large reductions in emissions will be required to reduce the health burden from ambient PM
exposure in India.
Organic aerosol (OA) is an important fraction of submicron aerosols. However,
it is challenging to predict and attribute the specific organic compounds and
sources that lead to observed OA loadings, ...largely due to contributions from
secondary production. This is especially true for megacities surrounded by
numerous regional sources that create an OA background. Here, we utilize
in situ gas and aerosol observations collected on board the NASA DC-8 during
the NASA–NIER KORUS-AQ (Korea–United States Air Quality) campaign to
investigate the sources and hydrocarbon precursors that led to the secondary
OA (SOA) production observed over Seoul. First, we investigate the
contribution of transported OA to total loadings observed over Seoul by
using observations over the Yellow Sea coupled to FLEXPART Lagrangian
simulations. During KORUS-AQ, the average OA loading advected into Seoul was
∼1–3 µg sm−3. Second, taking this background into
account, the dilution-corrected SOA concentration observed over Seoul was
∼140 µgsm-3ppmv-1 at 0.5 equivalent photochemical
days. This value is at the high end of what has been observed in other
megacities around the world (20–70 µgsm-3ppmv-1 at 0.5
equivalent days). For the average OA concentration observed over Seoul
(13 µg sm−3), it is clear that production of SOA from locally
emitted precursors is the major source in the region. The importance
of local SOA production was supported by the following observations.
(1) FLEXPART source contribution calculations indicate any
hydrocarbons with a lifetime of less than 1 day, which are shown to dominate the
observed SOA production, mainly originate from South Korea. (2) SOA
correlated strongly with other secondary photochemical species, including
short-lived species (formaldehyde, peroxy acetyl nitrate, sum of acyl peroxy
nitrates, dihydroxytoluene, and nitrate aerosol). (3) Results from
an airborne oxidation flow reactor (OFR), flown for the first time, show a
factor of 4.5 increase in potential SOA concentrations over Seoul versus over
the Yellow Sea, a region where background air masses that are advected into
Seoul can be measured. (4) Box model simulations reproduce SOA
observed over Seoul within 11 % on average and suggest that short-lived
hydrocarbons (i.e., xylenes, trimethylbenzenes, and semi-volatile and intermediate-volatility compounds) were the main SOA precursors over Seoul. Toluene
alone contributes 9 % of the modeled SOA over Seoul. Finally, along with
these results, we use the metric ΔOA/ΔCO2 to
examine the amount of OA produced per fuel consumed in a megacity, which
shows less variability across the world than ΔOA∕ΔCO.
Significance Atmospheric secondary organic aerosol has substantial impacts on climate, air quality, and human health. However, the formation mechanisms of secondary organic aerosol remain uncertain, ...especially on how anthropogenic pollutants (from human activities) control aerosol formation from biogenic volatile organic compounds (emitted by vegetation) and the magnitude of anthropogenic influences. Although possible mechanisms have been proposed based on laboratories studies, a coherent understanding of anthropogenic−biogenic interactions in ambient environments has not emerged. Here, we provide direct observational evidence that secondary organic aerosol formed from biogenic isoprene and monoterpenes is greatly mediated by anthropogenic SO ₂ and NO ₓ emissions based on integrated ambient measurements and laboratory studies.
Secondary organic aerosol (SOA) constitutes a substantial fraction of fine particulate matter and has important impacts on climate and human health. The extent to which human activities alter SOA formation from biogenic emissions in the atmosphere is largely undetermined. Here, we present direct observational evidence on the magnitude of anthropogenic influence on biogenic SOA formation based on comprehensive ambient measurements in the southeastern United States (US). Multiple high-time-resolution mass spectrometry organic aerosol measurements were made during different seasons at various locations, including urban and rural sites in the greater Atlanta area and Centreville in rural Alabama. Our results provide a quantitative understanding of the roles of anthropogenic SO ₂ and NO ₓ in ambient SOA formation. We show that isoprene-derived SOA is directly mediated by the abundance of sulfate, instead of the particle water content and/or particle acidity as suggested by prior laboratory studies. Anthropogenic NO ₓ is shown to enhance nighttime SOA formation via nitrate radical oxidation of monoterpenes, resulting in the formation of condensable organic nitrates. Together, anthropogenic sulfate and NO ₓ can mediate 43–70% of total measured organic aerosol (29–49% of submicron particulate matter, PM ₁) in the southeastern US during summer. These measurements imply that future reduction in SO ₂ and NO ₓ emissions can considerably reduce the SOA burden in the southeastern US. Updating current modeling frameworks with these observational constraints will also lead to more accurate treatment of aerosol formation for regions with substantial anthropogenic−biogenic interactions and consequently improve air quality and climate simulations.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
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.
Nitrogen oxides are essential for the formation of secondary atmospheric aerosols and of atmospheric oxidants such as ozone and the hydroxyl radical, which controls the self-cleansing capacity of the ...atmosphere. Nitric acid, a major oxidation product of nitrogen oxides, has traditionally been considered to be a permanent sink of nitrogen oxides. However, model studies predict higher ratios of nitric acid to nitrogen oxides in the troposphere than are observed. A 'renoxification' process that recycles nitric acid into nitrogen oxides has been proposed to reconcile observations with model studies, but the mechanisms responsible for this process remain uncertain. Here we present data from an aircraft measurement campaign over the North Atlantic Ocean and find evidence for rapid recycling of nitric acid to nitrous acid and nitrogen oxides in the clean marine boundary layer via particulate nitrate photolysis. Laboratory experiments further demonstrate the photolysis of particulate nitrate collected on filters at a rate more than two orders of magnitude greater than that of gaseous nitric acid, with nitrous acid as the main product. Box model calculations based on the Master Chemical Mechanism suggest that particulate nitrate photolysis mainly sustains the observed levels of nitrous acid and nitrogen oxides at midday under typical marine boundary layer conditions. Given that oceans account for more than 70 per cent of Earth's surface, we propose that particulate nitrate photolysis could be a substantial tropospheric nitrogen oxide source. Recycling of nitrogen oxides in remote oceanic regions with minimal direct nitrogen oxide emissions could increase the formation of tropospheric oxidants and secondary atmospheric aerosols on a global scale.
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IJS, KISLJ, NUK, SBMB, UL, UM, UPUK
Oxidation flow reactors (OFRs) containing low-pressure mercury (Hg) lamps that emit UV light at both 185 and 254 nm (“OFR185”) to generate OH radicals and O3 are used in many areas of atmospheric ...science and in pollution control devices. The widely used potential aerosol mass (PAM) OFR was designed for studies on the formation and oxidation of secondary organic aerosols (SOA), allowing for a wide range of oxidant exposures and short experiment duration with reduced wall loss effects. Although fundamental photochemical and kinetic data applicable to these reactors are available, the radical chemistry and its sensitivities have not been modeled in detail before; thus, experimental verification of our understanding of this chemistry has been very limited. To better understand the chemistry in the OFR185, a model has been developed to simulate the formation, recycling, and destruction of radicals and to allow the quantification of OH exposure (OHexp) in the reactor and its sensitivities. The model outputs of OHexp were evaluated against laboratory calibration experiments by estimating OHexp from trace gas removal and were shown to agree within a factor of 2. A sensitivity study was performed to characterize the dependence of the OHexp, HO2/OH ratio, and O3 and H2O2 output concentrations on reactor parameters. OHexp is strongly affected by the UV photon flux, absolute humidity, reactor residence time, and the OH reactivity (OHR) of the sampled air, and more weakly by pressure and temperature. OHexp can be strongly suppressed by high OHR, especially under low UV light conditions. A OHexp estimation equation as a function of easily measurable quantities was shown to reproduce model results within 10% (average absolute value of the relative errors) over the whole operating range of the reactor. OHexp from the estimation equation was compared with measurements in several field campaigns and shows agreement within a factor of 3. The improved understanding of the OFR185 and quantification of OHexp resulting from this work further establish the usefulness of such reactors for research studies, especially where quantifying the oxidation exposure is important.
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IJS, KILJ, NUK, PNG, UL, UM
The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together seventeen modeling groups from Europe and North America, running eight operational ...online-coupled air quality models over Europe and North America using common emissions and boundary conditions. The simulated annual, seasonal, continental and sub-regional particulate matter (PM) surface concentrations for the year 2010 have been evaluated against a large observational database from different measurement networks operating in Europe and North America. The results show a systematic underestimation for all models in almost all seasons and sub-regions, with the largest underestimations for the Mediterranean region. The rural PM10 concentrations over Europe are underestimated by all models by up to 66% while the underestimations are much larger for the urban PM10 concentrations (up to 75%). On the other hand, there are overestimations in PM2.5 levels suggesting that the large underestimations in the PM10 levels can be attributed to the natural dust emissions. Over North America, there is a general underestimation in PM10 in all seasons and sub-regions by up to ∼90% due mainly to the underpredictions in soil dust. SO42− levels over EU are underestimated by majority of the models while NO3− levels are largely overestimated, particularly in east and south Europe. NH4+ levels are also underestimated largely in south Europe. SO4 levels over North America are particularly overestimated over the western US that is characterized by large anthropogenic emissions while the eastern USA is characterized by underestimated SO4 levels by the majority of the models. Daytime AOD levels at 555 nm is simulated within the 50% error range over both continents with differences attributed to differences in concentrations of the relevant species as well as in approaches in estimating the AOD. Results show that the simulated dry deposition can lead to substantial differences among the models. Overall, the results show that representation of dust and sea-salt emissions can largely impact the simulated PM concentrations and that there are still major challenges and uncertainties in simulating the PM levels.
•Seventeen modeling groups from EU and NA simulated PM for 2010 under AQMEII phase 2.•A general model underestimation of surface PM over both continents up to 80%.•Natural PM emissions may lead to large underestimations in simulated PM10.•Dry deposition can introduce large differences among models.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The formulations of tropospheric gas-phase chemistry ("mechanisms") used in the regional-scale chemistry-transport models participating in the Air Quality Modelling Evaluation International ...Initiative (AQMEII) Phase 2 are intercompared by the means of box model studies. Simulations were conducted under idealized meteorological conditions, and the results are representative of mean boundary layer concentrations. Three sets of meteorological conditions - winter, spring/autumn and summer - were used to capture the annual variability, similar to the 3-D model simulations in AQMEII Phase 2. We also employed the same emissions input data used in the 3-D model intercomparison, and sample from these datasets employing different strategies to evaluate mechanism performance under a realistic range of pollution conditions. Box model simulations using the different mechanisms are conducted with tight constraints on all relevant processes and boundary conditions (photolysis, temperature, entrainment, etc.) to ensure that differences in predicted concentrations of pollutants can be attributed to differences in the formulation of gas-phase chemistry. The results are then compared with each other (but not to measurements), leading to an understanding of mechanism-specific biases compared to the multi-model mean. Our results allow us to quantify the uncertainty in predictions of a given compound in the 3-D simulations introduced by the choice of gas-phase mechanisms, to determine mechanism-specific biases under certain pollution conditions, and to identify (or rule out) the gas-phase mechanism as the cause of an observed discrepancy in 3-D model predictions. We find that the predictions of the median diurnal cycle of O3 over a set of emission conditions representing a network of station observations is within 4 ppbv (5%) across the different mechanisms. This variability is found to be very similar on both continents. There are considerably larger differences in predicted concentrations of NOx (up to plus or minus 25%), key radicals like OH (40%), HO2 (25%) and especially NO3 (>100%). Secondary substances like H2O2 (25%) or HNO3 (10%), as well as key volatile organic compounds like isoprene (>100%) or CH2O (20%) differ substantially as well. Calculation of an indicator of the chemical regime leads to up to 20% of simulations being classified differently by different mechanism, which would lead to different predictions of the most efficient emission reduction strategies. All these differences are despite identical meteorological boundary conditions, photolysis rates, as well as identical biogenic and inorganic anthropogenic emissions. Anthropogenic VOC emissions only vary in the way they are translated in mechanism-specific compounds, but are identical in the total emitted carbon mass and its spatial distribution. Our findings highlight that the choice of gas-phase mechanism is crucial in simulations for regulatory purposes, emission scenarios, as well as process studies that investigate other components like secondary formed aerosol components. We find that biogenic VOCs create considerable variability in mechanism predictions and suggest that these, together with nighttime chemistry should be areas of further mechanism improvement.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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.
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
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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