Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin.

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin for the year 2015. We identified spatial hot spots in Milwaukee County both individually (using local Moran's I) and through clusters (using K-means clustering) across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The cluster with the highest exposures within the urban area was largely characterized by low socioeconomic status and an overrepresentation of the Non-Hispanic Black population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics. Simultaneously, this cluster had an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.

Secondary Organic Aerosol Formation from Volatile Chemical Product Emissions: Model Parameters and Contributions to Anthropogenic Aerosol.

Volatile chemical products (VCP) are an increasingly important source of hydrocarbon and oxygenated volatile organic compound (OVOC) emissions to the atmosphere, and these emissions are likely to play an important role as anthropogenic precursors for secondary organic aerosol (SOA). While the SOA from VCP hydrocarbons is often accounted for in models, the formation, evolution, and properties of SOA from VCP OVOCs remain uncertain. We use environmental chamber data and a kinetic model to develop SOA parameters for 10 OVOCs representing glycols, glycol ethers, esters, oxygenated aromatics, and amines. Model simulations suggest that the SOA mass yields for these OVOCs are of the same magnitude as widely studied SOA precursors (e.g., long-chain alkanes, monoterpenes, and single-ring aromatics), and these yields exhibit a linear correlation with the carbon number of the precursor. When combined with emissions inventories for two megacities in the United States (US) and a US-wide inventory, we find that VCP VOCs react with OH to form 0.8-2.5× as much SOA, by mass, as mobile sources. Hydrocarbons (terpenes, branched and cyclic alkanes) and OVOCs (terpenoids, glycols, glycol ethers) make up 60-75 and 25-40% of the SOA arising from VCP use, respectively. This work contributes to the growing body of knowledge focused on studying VCP VOC contributions to urban air pollution.

Vapors Are Lost to Walls, Not to Particles on the Wall: Artifact-Corrected Parameters from Chamber Experiments and Implications for Global Secondary Organic Aerosol.

Atmospheric models of secondary organic aerosol (OA) (SOA) typically rely on parameters derived from environmental chambers. Chambers are subject to experimental artifacts, including losses of (1) particles to the walls (PWL), (2) vapors to the particles on the wall (V2PWL), and (3) vapors to the wall directly (VWL). We present a method for deriving artifact-corrected SOA parameters and translating these to volatility basis set (VBS) parameters for use in chemical transport models (CTMs). Our process involves combining a box model that accounts for chamber artifacts (Statistical Oxidation Model with a TwO-Moment Aerosol Sectional model (SOM-TOMAS)) with a pseudo-atmospheric simulation to develop VBS parameters that are fit across a range of OA mass concentrations. We found that VWL led to the highest percentage change in chamber SOA mass yields (high NOx: 36-680%; low NOx: 55-250%), followed by PWL (high NOx: 8-39%; low NOx: 10-37%), while the effects of V2PWL are negligible. In contrast to earlier work that assumed that V2PWL was a meaningful loss pathway, we show that V2PWL is an unimportant SOA loss pathway and can be ignored when analyzing chamber data. Using our updated VBS parameters, we found that not accounting for VWL may lead surface-level OA to be underestimated by 24% (0.25 µg m-3) as a global average or up to 130% (9.0 µg m-3) in regions of high biogenic or anthropogenic activity. Finally, we found that accurately accounting for PWL and VWL improves model-measurement agreement for fine mode aerosol mass concentrations (PM2.5) in the GEOS-Chem model.

Process-Level Modeling Can Simultaneously Explain Secondary Organic Aerosol Evolution in Chambers and Flow Reactors.

Secondary organic aerosol (SOA) data gathered in environmental chambers (ECs) have been used extensively to develop parameters to represent SOA formation and evolution. The EC-based parameters are usually constrained to less than one day of photochemical aging but extrapolated to predict SOA aging over much longer timescales in atmospheric models. Recently, SOA has been increasingly studied in oxidation flow reactors (OFRs) over aging timescales of one to multiple days. However, these OFR data have been rarely used to validate or update the EC-based parameters. The simultaneous use of EC and OFR data is challenging because the processes relevant to SOA formation and evolution proceed over very different timescales, and both reactor types exhibit distinct experimental artifacts. In this work, we show that a kinetic SOA chemistry and microphysics model that accounts for various processes, including wall losses, aerosol phase state, heterogeneous oxidation, oligomerization, and new particle formation, can simultaneously explain SOA evolution in EC and OFR experiments, using a single consistent set of SOA parameters. With α-pinene as an example, we first developed parameters by fitting the model output to the measured SOA mass concentration and oxygen-to-carbon (O:C) ratio from an EC experiment (<1 day of aging). We then used these parameters to simulate SOA formation in OFR experiments and found that the model overestimated SOA formation (by a factor of 3-16) over photochemical ages ranging from 0.4 to 13 days, when excluding the abovementioned processes. By comprehensively accounting for these processes, the model was able to explain the observed evolution in SOA mass, composition (i.e., O:C), and size distribution in the OFR experiments. This work suggests that EC and OFR SOA data can be modeled consistently, and a synergistic use of EC and OFR data can aid in developing more refined SOA parameters for use in atmospheric models.

Design and Testing of a Low-Cost Sensor and Sampling Platform for Indoor Air Quality.

Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 µg m-3 (6.1% relative standard deviation [RSD]) and 40.1 µg m-3 (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).

Heterogeneous Nucleation Drives Particle Size Segregation in Sequential Ozone and Nitrate Radical Oxidation of Catechol.

Secondary organic aerosol formation via condensation of organic vapors onto existing aerosol transforms the chemical composition and size distribution of ambient aerosol, with implications for air quality and Earth's radiative balance. Gas-to-particle conversion is generally thought to occur on a continuum between equilibrium-driven partitioning of semivolatile molecules to the pre-existing mass size distribution and kinetic-driven condensation of low volatility molecules to the pre-existing surface area size distribution. However, we offer experimental evidence in contrast to this framework. When catechol is sequentially oxidized by O3 and NO3 in the presence of (NH4)2SO4 seed particles with a single size mode, we observe a bimodal organic aerosol mass size distribution with two size modes of distinct chemical composition with nitrocatechol from NO3 oxidation preferentially condensing onto the large end of the pre-existing size distribution (∼750 nm). A size-resolved chemistry and microphysics model reproduces the evolution of the two distinct organic aerosol size modes─heterogeneous nucleation to an independent, nitrocatechol-rich aerosol phase.

Quantifying Proximity, Confinement, and Interventions in Disease Outbreaks: A Decision Support Framework for Air-Transported Pathogens.

The inability to communicate how infectious diseases are transmitted in human environments has triggered avoidance of interactions during the COVID-19 pandemic. We define a metric, Effective ReBreathed Volume (ERBV), that encapsulates how infectious pathogens, including SARS-CoV-2, transport in air. ERBV separates environmental transport from other factors in the chain of infection, allowing quantitative comparisons among situations. Particle size affects transport, removal onto surfaces, and elimination by mitigation measures, so ERBV is presented for a range of exhaled particle diameters: 1, 10, and 100 µm. Pathogen transport depends on both proximity and confinement. If interpersonal distancing of 2 m is maintained, then confinement, not proximity, dominates rebreathing after 10-15 min in enclosed spaces for all but 100 µm particles. We analyze strategies to reduce this confinement effect. Ventilation and filtration reduce person-to-person transport of 1 µm particles (ERBV1) by 13-85% in residential and office situations. Deposition to surfaces competes with intentional removal for 10 and 100 µm particles, so the same interventions reduce ERBV10 by only 3-50%, and ERBV100 is unaffected. Prior knowledge of size-dependent ERBV would help identify transmission modes and effective interventions. This framework supports mitigation decisions in emerging situations, even before other infectious parameters are known.

Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol.

Particle phase state is a property of atmospheric aerosols that has important implications for the formation, evolution, and gas/particle partitioning of secondary organic aerosol (SOA). In this work, we use a size-resolved chemistry and microphysics model (Statistical Oxidation Model coupled to the TwO Moment Aerosol Sectional (SOM-TOMAS)), updated to include an explicit treatment of particle phase state, to constrain the bulk diffusion coefficient (Db) of SOA produced from α-pinene ozonolysis. By leveraging data from laboratory experiments performed in the absence of a seed and under dry conditions, we find that the Db for SOA can be constrained ((1-7) × 10-15 cm2 s-1 in these experiments) by simultaneously reproducing the time-varying SOA mass concentrations and the evolution of the particle size distribution. Another version of our model that used the predicted SOA composition to calculate the glass-transition temperature, viscosity, and, ultimately, Db (∼10-15 cm2 s-1) of the SOA was able to reproduce the mass and size distribution measurements when we included oligomer formation (oligomers accounted for about a fifth of the SOA mass). Our work highlights the potential of a size-resolved SOA model to constrain the particle phase state of SOA using historical measurements of the evolution of the particle size distribution.

Secondary organic aerosol formation from evaporated biofuels: comparison to gasoline and correction for vapor wall losses.

With an ongoing interest in displacing petroleum-based sources of energy with biofuels, there is a need to measure and model the formation and composition of secondary organic aerosol (SOA) from organic compounds present in biofuels. We performed chamber experiments to study SOA formation from four recently identified biofuel molecules and mixtures and commercial gasoline under high NOx conditions: diisobutylene, cyclopentanone, an alkylfuran mixture, and an ethanol-to-hydrocarbon (ETH) mixture. Cyclopentanone and diisobutylene had a significantly lower potential to form SOA compared to commercial gasoline, with SOA mass yields lower than or equal to 0.2%. The alkylfuran mixture had an SOA mass yield (1.6%) roughly equal to that of gasoline (2.0%) but ETH had an average SOA mass yield (11.5%) that was six times higher than that of gasoline. We used a state-of-the-science model to parameterize or simulate the SOA formation in the chamber experiments while accounting for the influence of vapor wall losses. Simulations performed with vapor wall losses turned off and at atmospherically relevant conditions showed that the SOA mass yields were higher than those measured in the chamber at the same photochemical exposure and were also higher than those estimated using a volatility basis set that was fit to the chamber data. The modeled SOA mass yields were higher primarily because they were corrected for vapor wall losses to the Teflon® chamber.

Oxygenated Aromatic Compounds are Important Precursors of Secondary Organic Aerosol in Biomass-Burning Emissions.

Biomass burning is the largest combustion-related source of volatile organic compounds (VOCs) to the atmosphere. We describe the development of a state-of-the-science model to simulate the photochemical formation of secondary organic aerosol (SOA) from biomass-burning emissions observed in dry (RH <20%) environmental chamber experiments. The modeling is supported by (i) new oxidation chamber measurements, (ii) detailed concurrent measurements of SOA precursors in biomass-burning emissions, and (iii) development of SOA parameters for heterocyclic and oxygenated aromatic compounds based on historical chamber experiments. We find that oxygenated aromatic compounds, including phenols and methoxyphenols, account for slightly less than 60% of the SOA formed and help our model explain the variability in the organic aerosol mass (R2 = 0.68) and O/C (R2 = 0.69) enhancement ratios observed across 11 chamber experiments. Despite abundant emissions, heterocyclic compounds that included furans contribute to ∼20% of the total SOA. The use of pyrolysis-temperature-based or averaged emission profiles to represent SOA precursors, rather than those specific to each fire, provide similar results to within 20%. Our findings demonstrate the necessity of accounting for oxygenated aromatics from biomass-burning emissions and their SOA formation in chemical mechanisms.

Aging Effects on Biomass Burning Aerosol Mass and Composition: A Critical Review of Field and Laboratory Studies.

Biomass burning is a major source of atmospheric particulate matter (PM) with impacts on health, climate, and air quality. The particles and vapors within biomass burning plumes undergo chemical and physical aging as they are transported downwind. Field measurements of the evolution of PM with plume age range from net decreases to net increases, with most showing little to no change. In contrast, laboratory studies tend to show significant mass increases on average. On the other hand, similar effects of aging on the average PM composition (e.g., oxygen-to-carbon ratio) are reported for lab and field studies. Currently, there is no consensus on the mechanisms that lead to these observed similarities and differences. This review summarizes available observations of aging-related biomass burning aerosol mass concentrations and composition markers, and discusses four broad hypotheses to explain variability within and between field and laboratory campaigns: (1) variability in emissions and chemistry, (2) differences in dilution/entrainment, (3) losses in chambers and lines, and (4) differences in the timing of the initial measurement, the baseline from which changes are estimated. We conclude with a concise set of research needs for advancing our understanding of the aging of biomass burning aerosol.

Emerging investigator series: oxidative potential of diesel exhaust particles: role of fuel, engine load, and emissions control.

Exposure to diesel exhaust particles (DEP) has been linked to adverse human health outcomes. DEPs are reactive and can directly or indirectly lead to oxidative stress, which promotes inflammation in the body. The oxidative potential (OP) of DEPs is not well understood, particularly for combustion with alternative fuels, under different engine loads, and in combination with modern emissions control devices. In this study, we measured the OP of DEPs using a dithiothreitol assay (OP-DTT) from a modern-day non-road diesel engine for two different fuels (conventional diesel and soy-based biodiesel), two different engine loads (idle and 50% load), and with and without an emissions control system. The OP-DTT of DEPs was sensitive to the fuel used and the presence of an emissions control system but not to the engine load. On average, the use of biodiesel resulted in factor of ∼6 reduction in OP-DTT normalized to the DEP mass and a factor of ∼12 reduction in OP-DTT normalized to the fuel consumed. The use of the emissions control, on average, resulted in a factor of ∼6 reduction in OP-DTT normalized to the DEP mass and a three order of magnitude decrease in OP-DTT normalized to the fuel consumed. When studied in conjunction with the DEP composition, the OP-DTT seemed to correlate most strongly with elemental carbon (EC), followed by semi-volatile organic vapors. Assays performed on DEPs where EC was deliberately filtered out suggested that the species responsible for the OP-DTT might be correlated with EC but would need to be water soluble (e.g., quinones). The semi-volatile organic vapors accounted for more than a quarter of the OP-DTT of DEPs collected on the quartz filters. Finally, sensitivity studies performed with a different filter membrane (i.e., Teflon®) and solvent (i.e., dichloromethane) tended to increase the OP-DTT value. OP-DTT is emerging as an important metric for studying the adverse effects of DEPs and PM2.5 on human health; results of this work help define the sources and components of diesel PM2.5 that contribute to OP-DTT.

Urban pollution greatly enhances formation of natural aerosols over the Amazon rainforest.

One of the least understood aspects in atmospheric chemistry is how urban emissions influence the formation of natural organic aerosols, which affect Earth's energy budget. The Amazon rainforest, during its wet season, is one of the few remaining places on Earth where atmospheric chemistry transitions between preindustrial and urban-influenced conditions. Here, we integrate insights from several laboratory measurements and simulate the formation of secondary organic aerosols (SOA) in the Amazon using a high-resolution chemical transport model. Simulations show that emissions of nitrogen-oxides from Manaus, a city of ~2 million people, greatly enhance production of biogenic SOA by 60-200% on average with peak enhancements of 400%, through the increased oxidation of gas-phase organic carbon emitted by the forests. Simulated enhancements agree with aircraft measurements, and are much larger than those reported over other locations. The implication is that increasing anthropogenic emissions in the future might substantially enhance biogenic SOA in pristine locations like the Amazon.

Volatile chemical products emerging as largest petrochemical source of urban organic emissions.

A gap in emission inventories of urban volatile organic compound (VOC) sources, which contribute to regional ozone and aerosol burdens, has increased as transportation emissions in the United States and Europe have declined rapidly. A detailed mass balance demonstrates that the use of volatile chemical products (VCPs)-including pesticides, coatings, printing inks, adhesives, cleaning agents, and personal care products-now constitutes half of fossil fuel VOC emissions in industrialized cities. The high fraction of VCP emissions is consistent with observed urban outdoor and indoor air measurements. We show that human exposure to carbonaceous aerosols of fossil origin is transitioning away from transportation-related sources and toward VCPs. Existing U.S. regulations on VCPs emphasize mitigating ozone and air toxics, but they currently exempt many chemicals that lead to secondary organic aerosols.

Primary and Secondary Sources of Gas-Phase Organic Acids from Diesel Exhaust.

Organic acids have primary and secondary sources in the atmosphere, impact ecosystem health, and are useful metrics for identifying gaps in organic oxidation chemistry through model-measurement comparisons. We photooxidized (OH oxidation) primary emissions from diesel and biodiesel fuel types under two engine loads in an oxidative flow reactor. formic, butyric, and propanoic acids, but not methacrylic acid, have primary and secondary sources. Emission factors for these gas-phase acids varied from 0.3-8.4 mg kg-1 fuel. Secondary chemistry enhanced these emissions by 1.1 (load) to 4.4 (idle) × after two OH-equivalent days. The relative enhancement in secondary organic acids in idle versus loaded conditions was due to increased precursor emissions, not faster reaction rates. Increased hydrocarbon emissions in idle conditions due to less complete combustion (associated with less oxidized gas-phase molecules) correlated to higher primary organic acid emissions. The lack of correlation between organic aerosol and organic acid concentrations downstream of the flow reactor indicates that the secondary products formed on different oxidation time scales and that despite being photochemical products, organic acids are poor tracers for secondary organic aerosol formation from diesel exhaust. Ignoring secondary chemistry from diesel exhaust would lead to underestimates of both organic aerosol and gas-phase organic acids.

Linking Load, Fuel, and Emission Controls to Photochemical Production of Secondary Organic Aerosol from a Diesel Engine.

Diesel engines are important sources of fine particle pollution in urban environments, but their contribution to the atmospheric formation of secondary organic aerosol (SOA) is not well constrained. We investigated direct emissions of primary organic aerosol (POA) and photochemical production of SOA from a diesel engine using an oxidation flow reactor (OFR). In less than a day of simulated atmospheric aging, SOA production exceeded POA emissions by an order of magnitude or more. Efficient combustion at higher engine loads coupled to the removal of SOA precursors and particle emissions by aftertreatment systems reduced POA emission factors by an order of magnitude and SOA production factors by factors of 2-10. The only exception was that the retrofitted aftertreatment did not reduce SOA production at idle loads where exhaust temperatures were low enough to limit removal of SOA precursors in the oxidation catalyst. Use of biodiesel resulted in nearly identical POA and SOA compared to diesel. The effective SOA yield of diesel exhaust was similar to that of unburned diesel fuel. While OFRs can help study the multiday evolution, at low particle concentrations OFRs may not allow for complete gas/particle partitioning and bias the potential of precursors to form SOA.

Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions.

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA-SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30-40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

Review of Urban Secondary Organic Aerosol Formation from Gasoline and Diesel Motor Vehicle Emissions.

Secondary organic aerosol (SOA) is formed from the atmospheric oxidation of gas-phase organic compounds leading to the formation of particle mass. Gasoline- and diesel-powered motor vehicles, both on/off-road, are important sources of SOA precursors. They emit complex mixtures of gas-phase organic compounds that vary in volatility and molecular structure-factors that influence their contributions to urban SOA. However, the relative importance of each vehicle type with respect to SOA formation remains unclear due to conflicting evidence from recent laboratory, field, and modeling studies. Both are likely important, with evolving contributions that vary with location and over short time scales. This review summarizes evidence, research needs, and discrepancies between top-down and bottom-up approaches used to estimate SOA from motor vehicles, focusing on inconsistencies between molecular-level understanding and regional observations. The effect of emission controls (e.g., exhaust aftertreatment technologies, fuel formulation) on SOA precursor emissions needs comprehensive evaluation, especially with international perspective given heterogeneity in regulations and technology penetration. Novel studies are needed to identify and quantify "missing" emissions that appear to contribute substantially to SOA production, especially in gasoline vehicles with the most advanced aftertreatment. Initial evidence suggests catalyzed diesel particulate filters greatly reduce emissions of SOA precursors along with primary aerosol.

Quantifying the effect of organic aerosol aging and intermediate-volatility emissions on regional-scale aerosol pollution in China.

Secondary organic aerosol (SOA) is one of the least understood constituents of fine particles; current widely-used models cannot predict its loadings or oxidation state. Recent laboratory experiments demonstrated the importance of several new processes, including aging of SOA from traditional precursors, aging of primary organic aerosol (POA), and photo-oxidation of intermediate volatility organic compounds (IVOCs). However, evaluating the effect of these processes in the real atmosphere is challenging. Most models used in previous studies are over-simplified and some key reaction trajectories are not captured, and model parameters are usually phenomenological and lack experimental constraints. Here we comprehensively assess the effect of organic aerosol (OA) aging and intermediate-volatility emissions on regional-scale OA pollution with a state-of-the-art model framework and experimentally constrained parameters. We find that OA aging and intermediate-volatility emissions together increase OA and SOA concentrations in Eastern China by about 40% and a factor of 10, respectively, thereby improving model-measurement agreement significantly. POA and IVOCs both constitute over 40% of OA concentrations, and IVOCs constitute over half of SOA concentrations; this differs significantly from previous apportionment of SOA sources. This study facilitates an improved estimate of aerosol-induced climate and health impacts, and implies a shift from current fine-particle control policies.