Thermodynamic models predict that sulfate aerosol (S(VI) ≡ H2SO4(aq) + HSO4−+ SO42−) should take up available ammonia (NH3) quantitatively as ammonium (NH4+) until the ammonium sulfate stoichiometry (NH4)2SO4 is close to being reached. This uptake of ammonia has important implications for aerosol mass, hygroscopicity, and acidity. When ammonia is in excess, the ammonium–sulfate aerosol ratio R = [NH4+] ∕ [S(VI)] should approach 2, with excess ammonia remaining in the gas phase. When ammonia is in deficit, it should be fully taken up by the aerosol as ammonium and no significant ammonia should remain in the gas phase. Here we report that sulfate aerosol in the eastern US in summer has a low ammonium–sulfate ratio despite excess ammonia, and we show that this is at odds with thermodynamic models. The ammonium–sulfate ratio averages only 1.04 ± 0.21 mol mol−1 in the Southeast, even though ammonia is in large excess, as shown by the ammonium–sulfate ratio in wet deposition and by the presence of gas-phase ammonia. It further appears that the ammonium–sulfate aerosol ratio is insensitive to the supply of ammonia, remaining low even as the wet deposition ratio exceeds 6 mol mol−1. While the ammonium–sulfate ratio in wet deposition has increased by 5.8 % yr−1 from 2003 to 2013 in the Southeast, consistent with SO2 emission controls, the ammonium–sulfate aerosol ratio decreased by 1.4–3.0 % yr−1. Thus, the aerosol is becoming more acidic even as SO2 emissions decrease and ammonia emissions stay constant; this is incompatible with simple sulfate–ammonium thermodynamics. A tentative explanation is that sulfate particles are increasingly coated by organic material, retarding the uptake of ammonia. Indeed, the ratio of organic aerosol (OA) to sulfate in the Southeast increased from 1.1 to 2.4 g g−1 over the 2003–2013 period as sulfate decreased. We implement a simple kinetic mass transfer limitation for ammonia uptake to sulfate aerosols in the GEOS-Chem chemical transport model and find that we can reproduce both the observed ammonium–sulfate aerosol ratios and the concurrent presence of gas-phase ammonia. If sulfate aerosol becomes more acidic as OA ∕ sulfate ratios increase, then controlling SO2 emissions to decrease sulfate aerosol will not have the co-benefit of suppressing acid-catalyzed secondary organic aerosol (SOA) formation.
Glyoxal (CHOCHO) is produced in the atmosphere by the oxidation of volatile organic compounds (VOCs). Like formaldehyde (HCHO), another VOC oxidation product, it is measurable from space by solar backscatter. Isoprene emitted by vegetation is the dominant source of CHOCHO and HCHO in most of the world. We use aircraft observations of CHOCHO and HCHO from the SENEX campaign over the southeast US in summer 2013 to better understand the CHOCHO time-dependent yield from isoprene oxidation, its dependence on nitrogen oxides (NOx ≡ NO + NO2), the behavior of the CHOCHO–HCHO relationship, the quality of OMI CHOCHO satellite observations, and the implications for using CHOCHO observations from space as constraints on isoprene emissions. We simulate the SENEX and OMI observations with the Goddard Earth Observing System chemical transport model (GEOS-Chem) featuring a new chemical mechanism for CHOCHO formation from isoprene. The mechanism includes prompt CHOCHO formation under low-NOx conditions following the isomerization of the isoprene peroxy radical (ISOPO2). The SENEX observations provide support for this prompt CHOCHO formation pathway, and are generally consistent with the GEOS-Chem mechanism. Boundary layer CHOCHO and HCHO are strongly correlated in the observations and the model, with some departure under low-NOx conditions due to prompt CHOCHO formation. SENEX vertical profiles indicate a free-tropospheric CHOCHO background that is absent from the model. The OMI CHOCHO data provide some support for this free-tropospheric background and show southeast US enhancements consistent with the isoprene source but a factor of 2 too low. Part of this OMI bias is due to excessive surface reflectivities assumed in the retrieval. The OMI CHOCHO and HCHO seasonal data over the southeast US are tightly correlated and provide redundant proxies of isoprene emissions. Higher temporal resolution in future geostationary satellite observations may enable detection of the prompt CHOCHO production under low-NOx conditions apparent in the SENEX data.
The global budget of tropospheric ozone is governed by a complicated ensemble of coupled chemical and dynamical processes. Simulation of tropospheric ozone has been a major focus of the GEOS-Chem chemical transport model (CTM) over the past 20 years, and many developments over the years have affected the model representation of the ozone budget. Here we conduct a comprehensive evaluation of the standard version of GEOS-Chem (v10-01) with ozone observations from ozonesondes, the OMI satellite instrument, and MOZAIC-IAGOS commercial aircraft for 2012-2013. Global validation of the OMI 700-400 hPa data with ozonesondes shows that OMI maintained persistent high quality and no significant drift over the 2006-2013 period. GEOS-Chem shows no significant seasonal or latitudinal bias relative to OMI and strong correlations in all seasons on the 2 degrees x 2.5 degrees horizontal scale (r = 0.88-0.95), improving on previous model versions. The most pronounced model bias revealed by ozonesondes and MOZAIC-IAGOS is at high northern latitudes in winter-spring where the model is 10-20 ppbv too low. This appears to be due to insufficient stratosphere-troposphere exchange (STE). Model updates to lightning NOx, Asian anthropogenic emissions, bromine chemistry, isoprene chemistry, and meteorological fields over the past decade have overall led to gradual increase in the simulated global tropospheric ozone burden and more active ozone production and loss. From simulations with different versions of GEOS meteorological fields we find that tropospheric ozone in GEOS-Chem v10-01 has a global production rate of 4960-5530 Tg a(-1), lifetime of 20.9-24.2 days, burden of 345-357 Tg, and STE of 325-492 Tg a(-1). Change in the intensity of tropical deep convection between these different meteorological fields is a major factor driving differences in the ozone budget. (C) 2017 Elsevier Ltd. All rights reserved.
It is essential to evaluate and refine aerosol classification methods applied to passive satellite remote sensing. We have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground-based passive remote sensing instruments [1]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrialdeveloped economy, urban-industrialdeveloping economy, dark biomass smoke, light biomass smoke and pure marine. We apply the SCMC method to inversions from the ground-based AErosol RObotic NETwork (AERONET [2]) and retrievals from the space-borne Polarization and Directionality of Earths Reflectances instrument (POLDER, [3]). The POLDER retrievals that we use differ from the standard POLDER retrievals [4] as they make full use of multi-angle, multispectral polarimetric data [5]. We analyze agreement in the aerosol types inferred from both AERONET and POLDER and evaluate GEOS-Chem [6] simulations over the globe. Finally, we use in-situ observations from the SEAC4RS airborne field experiment to bridge the gap between remote sensing-inferred qualitative SCMC aerosol types and their corresponding quantitative chemical speciation. We apply the SCMC method to airborne in-situ observations from the NASA Langley Aerosol Research Group Experiment (LARGE, [7]) and the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP, [8]) instruments; we then relate each coarsely defined SCMC type to a sum of percentage of individual aerosol species, using in-situ observations from the Particle Analysis by Laser Mass Spectrometry (PALMS, [9]), the Soluble Acidic Gases and Aerosol (SAGA, [10]), and the High - Resolution Time - of - Flight Aerosol Mass Spectrometer (HR ToF AMS, [11]).
Risk analysis is a method used to determine the probability of disaster in the current and future. This research analyse of fire risk in West Kalimantan by using extreme climate and vulnerability analysis. Extreme climate was calculated based on the extreme dry rainfall from regional climate model RegCM4.4 outputs. Vulnerability analysis was conducted by using a composite mapping analysis used hotspot data and eleven indicators of vulnerability. We found that very high level of extreme dry rainfall located in the southern region and the western coast area of West Kalimantan. This condition was influenced by environment factors such as topography and land use. Extreme dry rainfall also associated with the pattern of annual rainfall in West Kalimantan which ranges between 1753-4861 mm. Modelling of the vulnerability of land and forest fires in West Kalimantan showed that the land use has impact 24% on the vulnerability model. The results of the vulnerability model analysis shows that the plantations areas and secondary swamp forests are highly vulnerable, particularly on the peat area with depth about 50-200 cm. The analysis of land and forest fires risk found that the vulnerable areas have high risk which is largely unmanaged plantation areas and peatlands.
Acid-base neutralization of sulfate aerosol (S(VI) ≡ H 2 SO 4 (aq) + HSO 4 - + SO 4 2- ) by ammonia (NH 3 ) has important implications for aerosol mass, hygroscopicity, and acidity. Surface network and aircraft observations across the eastern US show that sulfate aerosol is not fully neutralized even in the presence of excess ammonia, at odds with thermodynamic equilibrium models. The sulfate aerosol 15
Abstract. Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx ≡ NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model (CTM) at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high in the Southeast and nationally by 50 %. This is demonstrated by SEAC4RS observations of NOx and its oxidation products, by surface network observations of nitrate wet deposition fluxes, and by OMI satellite observations of tropospheric NO2 columns. Upper tropospheric NO2 from lightning makes a large contribution to the satellite observations that must be accounted for when using these data to estimate surface NOx emissions. Aircraft observations of upper tropospheric NO2 are higher than simulated by GEOS-Chem or expected from NO-NO2-O3 photochemical stationary state. NOx levels in the Southeast US are sufficiently low that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft and from ozonesondes, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8 ± 13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to 0.2 km altitude, whereas GEOS-Chem has no such gradient because of efficient boundary layer mixing. We conclude that model biases in simulating surface ozone over the Southeast US may be due to a combination of excessive NOx emissions and excessive boundary layer vertical mixing.
In September–October 2015, El Niño and positive Indian Ocean Dipole conditions set the stage for massive fires in Sumatra and Kalimantan (Indonesian Borneo), leading to persistently hazardous levels of smoke pollution across much of Equatorial Asia. Here we quantify the emission sources and health impacts of this haze episode and compare the sources and impacts to an event of similar magnitude occurring under similar meteorological conditions in September–October 2006. Using the adjoint of the GEOS-Chem chemical transport model, we first calculate the influence of potential fire emissions across the domain on smoke concentrations in three receptor areas downwind—Indonesia, Malaysia, and Singapore—during the 2006 event. This step maps the sensitivity of each receptor to fire emissions in each grid cell upwind. We then combine these sensitivities with 2006 and 2015 fire emission inventories from the Global Fire Assimilation System (GFAS) to estimate the resulting population-weighted smoke exposure. This method, which assumes similar smoke transport pathways in 2006 and 2015, allows near real-time assessment of smoke pollution exposure, and therefore the consequent morbidity and premature mortality, due to severe haze. Our approach also provides rapid assessment of the relative contribution of fire emissions generated in a specific province to smoke-related health impacts in the receptor areas. We estimate that haze in 2015 resulted in 100 300 excess deaths across Indonesia, Malaysia and Singapore, more than double those of the 2006 event, with much of the increase due to fires in Indonesia's South Sumatra Province. The model framework we introduce in this study can rapidly identify those areas where land use management to reduce and/or avoid fires would yield the greatest benefit to human health, both nationally and regionally.
Isoprene emitted by vegetation is an important precursor of secondary organic aerosol (SOA), but the mechanism and yields are uncertain. Aerosol is prevailingly aqueous under the humid conditions typical of isoprene-emitting regions. Here we develop an aqueous-phase mechanism for isoprene SOA formation coupled to a detailed gas-phase isoprene oxidation scheme. The mechanism is based on aerosol reactive uptake coefficients (γ) for water-soluble isoprene oxidation products, including sensitivity to aerosol acidity and nucleophile concentrations. We apply this mechanism to simulation of aircraft (SEAC4RS) and ground-based (SOAS) observations over the Southeast US in summer 2013 using the GEOS-Chem chemical transport model. Emissions of nitrogen oxides (NOx ≡ NO + NO2) over the Southeast US are such that the peroxy radicals produced from isoprene oxidation (ISOPO2) react significantly with both NO (high-NOx pathway) and HO2 (low-NOx pathway), leading to different suites of isoprene SOA precursors. We find a mean SOA mass yield of 3.3 % from isoprene oxidation, consistent with the observed relationship of total fine organic aerosol (OA) and formaldehyde (a product of isoprene oxidation). Isoprene SOA production is mainly contributed by two immediate gas-phase precursors, isoprene epoxydiols (IEPOX, 58% of isoprene SOA) from the low-NOx pathway and glyoxal (28%) from both low- and high-NOx pathways. This speciation is consistent with observations of IEPOX SOA from SOAS and SEAC4RS. Observations show a strong relationship between IEPOX SOA and sulfate aerosol that we explain as due to the effect of sulfate on aerosol acidity and volume. Isoprene SOA concentrations increase as NOx emissions decrease (favoring the low-NOx pathway for isoprene oxidation), but decrease more strongly as SO2 emissions decrease (due to the effect of sulfate on aerosol acidity and volume). The US EPA projects 2013-2025 decreases in anthropogenic emissions of 34% for NOx (leading to 7% increase in isoprene SOA) and 48% for SO2 (35% decrease in isoprene SOA). Reducing SO2 emissions decreases sulfate and isoprene SOA by a similar magnitude, representing a factor of 2 co-benefit for PM2.5 from SO2 emission controls.
Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx ≡ NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NOx emissions. Upper tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.
Formaldehyde (HCHO) column data from satellites are widely used as a proxy for emissions of volatile organic compounds (VOCs) but validation of the data has been extremely limited. Here we use highly accurate HCHO aircraft observations from the NASA SEAC4RS campaign over the Southeast US in August-September 2013 to validate and intercompare six retrievals of HCHO columns from four different satellite instruments (OMI, GOME2A, GOME2B and OMPS) and three different research groups. The GEOS-Chem chemical transport model is used as a common intercomparison platform. All retrievals feature a HCHO maximum over Arkansas and Louisiana, consistent with the aircraft observations and reflecting high emissions of biogenic isoprene. The retrievals are also interconsistent in their spatial variability over the Southeast US (r=0.4-0.8 on a 0.5°×0.5° grid) and in their day-to-day variability (r=0.5-0.8). However, all retrievals are biased low in the mean by 20-51%, which would lead to corresponding bias in estimates of isoprene emissions from the satellite data. The smallest bias is for OMI-BIRA, which has high corrected slant columns relative to the other retrievals and low scattering weights in its air mass factor (AMF) calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shape profiles for the AMF calculation and correcting this would eliminate its bias relative to the SEAC4RS data. Our results support the use of satellite HCHO data as a quantitative proxy for isoprene emission after correction of the low mean bias. There is no evident pattern in the bias, suggesting that a uniform correction factor may be applied to the data until better understanding is achieved.
Formation of organic nitrates (RONO2) during oxidation of biogenic volatile organic compounds (BVOCs: isoprene, monoterpenes) is a significant loss pathway for atmospheric nitrogen oxide radicals (NOx), but the chemistry of RONO2 formation and degradation remains uncertain. Here we implement a new BVOC oxidation mechanism (including updated isoprene chemistry, new monoterpene chemistry, and particle uptake of RONO2) in the GEOS-Chem global chemical transport model with ∼ 25 × 25 km2 resolution over North America. We evaluate the model using aircraft (SEAC4RS) and ground-based (SOAS) observations of NOx, BVOCs, and RONO2 from the Southeast US in summer 2013. The updated simulation successfully reproduces the concentrations of individual gas- and particle-phase RONO2 species measured during the campaigns. Gas-phase isoprene nitrates account for 25–50 % of observed RONO2 in surface air, and we find that another 10 % is contributed by gas-phase monoterpene nitrates. Observations in the free troposphere show an important contribution from long-lived nitrates derived from anthropogenic VOCs. During both campaigns, at least 10 % of observed boundary layer RONO2 were in the particle phase. We find that aerosol uptake followed by hydrolysis to HNO3 accounts for 60 % of simulated gas-phase RONO2 loss in the boundary layer. Other losses are 20 % by photolysis to recycle NOx and 15 % by dry deposition. RONO2 production accounts for 20 % of the net regional NOx sink in the Southeast US in summer, limited by the spatial segregation between BVOC and NOx emissions. This segregation implies that RONO2 production will remain a minor sink for NOx in the Southeast US in the future even as NOx emissions continue to decline.
Formation of ozone and organic aerosol in continental atmospheres depends on whether isoprene emitted by vegetation is oxidized by the high-NOx pathway (where peroxy radicals react with NO) or by low-NOx pathways (where peroxy radicals react by alternate channels, mostly with HO2). We used mixed layer observations from the SEAC4RS aircraft campaign over the Southeast US to test the ability of the GEOS-Chem chemical transport model at different grid resolutions (0.25° × 0.3125°, 2° × 2.5°, 4° × 5°) to simulate this chemistry under high-isoprene, variable-NOx conditions. Observations of isoprene and NOx over the Southeast US show a negative correlation, reflecting the spatial segregation of emissions; this negative correlation is captured in the model at 0.25° × 0.3125° resolution but not at coarser resolutions. As a result, less isoprene oxidation takes place by the high-NOx pathway in the model at 0.25° × 0.3125° resolution (54 %) than at coarser resolution (59 %). The cumulative probability distribution functions (CDFs) of NOx, isoprene, and ozone concentrations show little difference across model resolutions and good agreement with observations, while formaldehyde is overestimated at coarse resolution because excessive isoprene oxidation takes place by the high-NOx pathway with high formaldehyde yield. The good agreement of simulated and observed concentration variances implies that smaller-scale non-linearities (urban and power plant plumes) are not important on the regional scale. Correlations of simulated vs. observed concentrations do not improve with grid resolution because finer modes of variability are intrinsically more difficult to capture. Higher model resolution leads to decreased conversion of NOx to organic nitrates and increased conversion to nitric acid, with total reactive nitrogen oxides (NOy) changing little across model resolutions. Model concentrations in the lower free troposphere are also insensitive to grid resolution. The overall low sensitivity of modeled concentrations to grid resolution implies that coarse resolution is adequate when modeling continental boundary layer chemistry for global applications.
Fires associated with agricultural and plantation development in Indonesia impact ecosystem services and release emissions into the atmosphere that degrade regional air quality and contribute to greenhouse gas concentrations. In this study, we estimate the relative contributions of the oil palm, timber (for wood pulp and paper), and logging industries in Sumatra and Kalimantan to land cover change, fire activity, and regional population exposure to smoke concentrations. Concessions for these three industries cover 21% and 49% of the land area in Sumatra and Kalimantan respectively, with the highest overall area in lowlands on mineral soils instead of more carbon-rich peatlands. In 2012, most remaining forest area was located in logging concessions for both islands, and for all combined concessions, there was higher remaining lowland and peatland forest area in Kalimantan (45% and 46%, respectively) versus Sumatra (20% and 27%, respectively). Emissions from all combined concessions comprised 41% of total fire emissions (within and outside of concession boundaries) in Sumatra and 27% in Kalimantan for the 2006 burning season, which had high fire activity relative to decadal emissions. Most fire emissions were observed in concessions located on peatlands and non-forested lowlands, the latter of which could include concessions that are currently under production, cleared in preparation for production, or abandoned lands. For the 2006 burning season, timber concessions from Sumatra (47% of area and 88% of emissions) and oil palm concessions from Kalimantan (33% of area and 67% of emissions) contributed the most to concession-related fire emissions from each island. Although fire emissions from concessions were higher in Kalimantan, emissions from Sumatra contributed 63% of concession-related smoke concentrations for the population-weighted region because fire sources were located closer to population centers. In order to protect regional public health, our results highlight the importance of limiting the use of fire by the timber and oil palm industries, particularly on concessions that contain peatlands and non-forest, by such methods as improving monitoring systems, local-level management, and enforcement of existing fire bans.
Fire emissions associated with land cover change and land management contribute to the concentrations of atmospheric pollutants, which can affect regional air quality and climate. Mitigating these impacts requires a comprehensive understanding of the relationship between fires and different land cover change trajectories and land management strategies. We develop future fire emissions inventories from 2010–2030 for Sumatra and Kalimantan (Indonesian Borneo) to assess the impact of varying levels of forest and peatland conservation on air quality in Equatorial Asia. To compile these inventories, we combine detailed land cover information from published maps of forest extent, satellite fire radiative power observations, fire emissions from the Global Fire Emissions Database, and spatially explicit future land cover projections using a land cover change model. We apply the sensitivities of mean smoke concentrations to Indonesian fire emissions, calculated by the GEOS-Chem adjoint model, to our scenario-based future fire emissions inventories to quantify the different impacts of fires on surface air quality across Equatorial Asia. We find that public health impacts are highly sensitive to the location of fires, with emissions from Sumatra contributing more to smoke concentrations at population centers across the region than Kalimantan, which had higher emissions by more than a factor of two. Compared to business-as-usual projections, protecting peatlands from fires reduces smoke concentrations in the cities of Singapore and Palembang by 70% and 40%, and by 60% for the Equatorial Asian region, weighted by the population in each grid cell. Our results indicate the importance of focusing conservation priorities on protecting both forested (intact or logged) peatlands and non-forested peatlands from fire, even after considering potential leakage of deforestation pressure to other areas, in order to limit the impact of fire emissions on atmospheric smoke concentrations and subsequent health effects.
We use an ensemble of surface (EPA CSN, IMPROVE, SEARCH, AERONET), aircraft (SEAC4RS), and satellite (MODIS, MISR) observations over the southeast US during the summer–fall of 2013 to better understand aerosol sources in the region and the relationship between surface particulate matter (PM) and aerosol optical depth (AOD). The GEOS-Chem global chemical transport model (CTM) with 25 × 25 km2 resolution over North America is used as a common platform to interpret measurements of different aerosol variables made at different times and locations. Sulfate and organic aerosol (OA) are the main contributors to surface PM2.5 (mass concentration of PM finer than 2.5 μm aerodynamic diameter) and AOD over the southeast US. OA is simulated successfully with a simple parameterization, assuming irreversible uptake of low-volatility products of hydrocarbon oxidation. Biogenic isoprene and monoterpenes account for 60 % of OA, anthropogenic sources for 30 %, and open fires for 10 %. 60 % of total aerosol mass is in the mixed layer below 1.5 km, 25 % in the cloud convective layer at 1.5–3 km, and 15 % in the free troposphere above 3 km. This vertical profile is well captured by GEOS-Chem, arguing against a high-altitude source of OA. The extent of sulfate neutralization (f = [NH4+]/(2[SO42−] + [NO3−]) is only 0.5–0.7 mol mol−1 in the observations, despite an excess of ammonia present, which could reflect suppression of ammonia uptake by OA. This would explain the long-term decline of ammonium aerosol in the southeast US, paralleling that of sulfate. The vertical profile of aerosol extinction over the southeast US follows closely that of aerosol mass. GEOS-Chem reproduces observed total column aerosol mass over the southeast US within 6 %, column aerosol extinction within 16 %, and space-based AOD within 8–28 % (consistently biased low). The large AOD decline observed from summer to winter is driven by sharp declines in both sulfate and OA from August to October. These declines are due to shutdowns in both biogenic emissions and UV-driven photochemistry. Surface PM2.5 shows far less summer-to-winter decrease than AOD and we attribute this in part to the offsetting effect of weaker boundary layer ventilation. The SEAC4RS aircraft data demonstrate that AODs measured from space are consistent with surface PM2.5. This implies that satellites can be used reliably to infer surface PM2.5 over monthly timescales if a good CTM representation of the aerosol vertical profile is available.