Experimental and model estimates of the contributions from biogenic monoterpenes and sesquiterpenes to secondary organic aerosol in the southeastern United States

Volatile organic compound emissions from a multi-unit residential building to ambient air

Emerging sources, such as volatile chemical products (VCPs) and other non-traditional emission categories, are becoming increasingly important in urban air pollution as the contributions of recognized sources such as traffic and industrial emissions decline. Indoor emissions constitute a large fraction of organic gaseous species from these sources, making buildings potential contributors to ambient air pollution. This study illustrates building emissions by presenting findings from a sampling campaign in downtown Toronto, analyzing volatile organic compounds (VOCs) from the mechanical ventilation inlet and exhaust air streams of a multi-unit residential building (110 units). Due to indoor emissions, VOCs were detected more frequently and at higher concentrations (median levels higher by about 22%) in the exhaust stream than in the inlet stream, indicating that the building serves as a net VOC source to the ambient air. VCP-related species were consistently more abundant in the exhaust air, confirming the influence of indoor sources. In particular, median concentrations of volatile methyl siloxanes and monoterpenoids associated with emissions from adhesives, personal care products, and cleaning agents ranged from about 2-5 μg m-3 in the exhaust stream in comparison with 0.2-0.5 μg m-3 within the inlet stream. Source apportionment analysis of VOC concentrations across the exhaust and inlet airstreams revealed indoor emissions of siloxanes, monoterpenoids, and oxygenated VOCs from coatings, cleaners, and personal care products as primary contributors to exhaust stream trends. Net building VOC emissions, defined as the rate of outflowing minus the inflowing VOCs, were calculated from the measured concentrations and ventilation rates. The resulting values aligned with indoor emissions predicted from a published VCP emission inventory for Canada, emphasizing the pivotal impact of VCP indoor sources on urban air quality. Exhaust and inlet stream concentrations of VCP-related species were found to be significantly (p < 0.05) correlated, suggesting the building emissions influencing outdoor VOC levels. These results highlight the crucial impact of indoor emissions, especially from VCPs, on ambient air quality and the need for further research into indoor-to-outdoor pollutant transfer mechanisms to address urban air pollution.

Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study

Exceedances of critical loads for deposition of sulfur (S) and nitrogen (N) in different ecosystems were estimated using European and North American ensembles of air quality models, under the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4), to identify where the risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and European 0.125° resolution domains, which were then used to calculate critical load exceedances. Targeted deposition diagnostics implemented in AQMEII4 allowed for an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. Datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were created for this analysis. These were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2% to 6.1 %; aquatic ecosystems: 21.2% to 11.4 %). All models agreed regarding the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both the severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5% to 75.8 %). The exceedances for herbaceous-community richness also decreased between 2010 and 2016, from 13.9% to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in predictions of both total N deposition and the change in N deposition and hence in the predicted eutrophication exceedances between the 2 years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48% to 4.32% from 2009 to 2010), while eutrophication exceedance increased slightly (60.2% to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the 2 years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulfur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to the observed wet deposition of sulfate, nitrate, and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulfate, nitrate, and ammonium deposition fluxes between models was linked to the use of updated particle dry-deposition parameterizations in some models. However, recent literature and the further development of some of the models within the ensemble suggest these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulfur and nitrogen deposition prediction variability was linked to SO2 and HNO3 dry-deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying-gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine-mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest- and the smallest-magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH3 performance may underestimate the extent of NH3 emission fluxes from forested areas. Model-measurement fusion in the form of a simple bias correction was applied to the 2016 critical loads. This generally reduced variability between models. However, the bias correction exercise illustrated the need for observations which close the sulfur and nitrogen budgets in carrying out model-measurement fusion. Chemical transformations between different forms of sulfur and nitrogen in the atmosphere sometimes result in compensating biases in the resulting total sulfur and nitrogen deposition flux fields. If model-measurement fusion is only applied to some but not all of the fields contributing to the total deposition of sulfur or nitrogen, the corrections may result in greater variability between models or less accurate results for an ensemble of models, for those cases where an unobserved or unused observed component contributes significantly to predicted total deposition. Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH3 bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH3 emission sources should be included in regional chemical transport models. The choice of a land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.

3DVar sectoral emission inversion based on source apportionment and machine learning

Air quality models are increasingly important in air pollution forecasting and control. Sectoral emissions significantly impact the accuracy of air quality models and source apportionment. This paper studied the 3DVar (three-dimensional variational) emission inversion method, which is based on machine learning, and then expanded it to sectoral emission inversion combined with source apportionment. Two machine learning conversion matrices were established to implement this method: a matrix that converts the total pollutant concentration to sectoral source apportionment results and a matrix that converts the sectoral source apportionment results to corresponding emissions. Combined with the O3 (ozone) concentration contributed by VOCs (volatile organic compounds) and NOx (nitrogen oxides) precursors in source apportionment, the inversion ability for O3-NOx-VOCs nonlinear processes was improved. Taking the BTH (Beijing‒Tianjin-Hebei) region from January 15 to 30, 2019, as an example, the results revealed that the regional errors of PM2.5 and O3 in the inversion experiment were reduced by 47% and 45%, respectively, and the temporal errors were reduced by 44% and 16%, respectively.

Impact of Heatwaves and Declining NOx on Nocturnal Monoterpene Oxidation in the Urban Southeastern United States

Nighttime oxidation of monoterpenes (MT) via the nitrate radical (NO3) and ozone (O3) contributes to the formation of secondary organic aerosol (SOA). This study uses observations in Atlanta, Georgia from 2011-2022 to quantify trends in nighttime production of NO3 (PNO3) and O3 concentrations and compare to model outputs from the EPA's Air QUAlity TimE Series Project (EQUATES). We present urban-suburban gradients in nighttime NO3 and O3 concentrations and quantify their fractional importance (F) for MT oxidation. Both observations and EQUATES show a decline in PNO3, with modeled PNO3 declining faster than observations. Despite decreasing PNO3, we find that NO3 continues to dominate nocturnal boundary layer (NBL) MT oxidation (FNO3 = 60%) in 2017, 2021, and 2022, which is consistent with EQUATES (FNO3 = 80%) from 2013-2019. This contrasts an anticipated decline in FNO3 based on prior observations in the nighttime residual layer, where O3 is the dominant oxidant. Using two case studies of heatwaves in summer 2022, we show that extreme heat events can increase NO3 concentrations and FNO3, leading to short MT lifetimes (<1 h) and high gas-phase organic nitrate production. Regardless of the presence of heatwaves, our findings suggest sustained organic nitrate aerosol formation in the urban SE US under declining NOx emissions, and highlight the need for improved representation of extreme heat events in chemistry-transport models and additional observations along urban to rural gradients.

Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002-2020

In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality-Integrated Source Apportionment Method (CMAQ-ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21-40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> -20 μg/m3) after 2011 due to pollution control measures.

Missing Measurements of Sesquiterpene Ozonolysis Rates and Composition Limit Understanding of Atmospheric Reactivity

Emissions of biogenic reactive carbon significantly influence atmospheric chemistry, contributing to the formation and destruction of secondary pollutants, such as secondary organic aerosol and ozone. While isoprene and monoterpenes are a major fraction of emissions and have been extensively studied, substantially less is known about the atmospheric impacts of higher-molecular-weight terpenes such as sesquiterpenes. In particular, sesquiterpenes have been proposed to play a significant role in ozone chemical loss due to the very high ozone reaction rates of certain isomers. However, relatively little data are available on the isomer-resolved composition of this compound class or its role in ozone chemistry. This study examines the chemical diversity of sesquiterpenes and availability of ozone reaction rate constants to evaluate the current understanding of their ozone reactivity. Sesquiterpenes are found to be highly diverse, with 72 different isomers reported and relatively few isomers that contribute a large mass fraction across all studies. For the small number of isomers with known ozone reaction rates, estimated rates may be 25 times higher or lower than measurements, indicating that estimated reaction rates are highly uncertain. Isomers with known ozone reaction rates make up approximately half of the mass of sesquiterpenes in concentration and emission measurements. Consequently, the current state of the knowledge suggests that the total ozone reactivity of sesquiterpenes cannot be quantified without very high uncertainty, even if isomer-resolved composition is known. These results are in contrast to monoterpenes, which are less diverse and for which ozone reaction rates are well-known, and in contrast to hydroxyl reactivity of monoterpenes and sesquiterpenes, for which reaction rates can be reasonably well estimated. Improved measurements of a relatively small number of sesquiterpene isomers would reduce uncertainties and improve our understanding of their role in regional and global ozone chemistry.

An updated modeling framework to simulate Los Angeles air quality - Part 1: Model development, evaluation, and source apportionment

This study describes a modeling framework, model evaluation, and source apportionment to understand the causes of Los Angeles (LA) air pollution. A few major updates are applied to the Community Multiscale Air Quality (CMAQ) model with a high spatial resolution (1 km × 1 km). The updates include dynamic traffic emissions based on real-time, on-road information and recent emission factors and secondary organic aerosol (SOA) schemes to represent volatile chemical products (VCPs). Meteorology is well predicted compared to ground-based observations, and the emission rates from multiple sources (i.e., on-road, volatile chemical products, area, point, biogenic, and sea spray) are quantified. Evaluation of the CMAQ model shows that ozone is well predicted despite inaccuracies in nitrogen oxide (NO x ) predictions. Particle matter (PM) is underpredicted compared to concurrent measurements made with an aerosol mass spectrometer (AMS) in Pasadena. Inorganic aerosol is well predicted, while SOA is underpredicted. Modeled SOA consists of mostly organic nitrates and products from oxidation of alkane-like intermediate volatility organic compounds (IVOCs) and has missing components that behave like less-oxidized oxygenated organic aerosol (LO-OOA). Source apportionment demonstrates that the urban areas of the LA Basin and vicinity are NO x -saturated (VOC-sensitive), with the largest sensitivity of O3 to changes in VOCs in the urban core. Differing oxidative capacities in different regions impact the nonlinear chemistry leading to PM and SOA formation, which is quantified in this study.

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging

Secondary organic aerosol (SOA) is an important component of atmospheric fine particulate matter (PM2.5), with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policymakers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remain uncertain. Findings from existing SOA modeling studies have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. To address some of the inconsistencies, we investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. SOA generated from BVOC (i.e., BSOA) is found to be more important in southern China. In contrast, SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions compared to other precursors. In July, when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e., SOA produced from IVOC) and ASOA (i.e., SOA produced from anthropogenic VOC). In contrast, in November, IVOC became the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA, while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November, while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in the CAMx VBS (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations, and this effect increases with the ambient organic aerosol (OA) concentrations. The CMAQ aerosol module implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts on total OA. Different structures and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. In addition, aging schemes are the major driver in CMAQ vs. CAMx treatments of ASOA and their resulting predicted mass. More sophisticated measurement data (e.g., with resolved OA components) and/or chamber experiments (e.g., investigating how aging influences SOA yields) are needed to better characterize SOA aging and constrain model parameterizations.

Can the UK meet the World Health Organization PM2.5 interim target of 10 μg m-3 by 2030?

The recent United Kingdom (UK) Environment Act consultation had the intention of setting two targets for PM2.5 (particles with an aerodynamic diameter less than 2.5 μm), one related to meeting an annual average concentration and the second to reducing population exposure. As part of the consultation, predictions of PM2.5 concentrations in 2030 were made by combining European Union (EU) and UK government's emissions forecasts, with the Climate Change Committee's (CCC) Net Zero vehicle forecasts, and in London with the addition of local policies based on the London Environment Strategy (LES). Predictions in 2018 showed 6.4% of the UK's area and 82.6% of London's area had PM2.5 concentrations above the World Health Organization (WHO) interim target of 10 μg m-3, but by 2030, over 99% of the UK's area was predicted to be below it. However, kerbside concentrations in London and other major cities were still at risk of exceeding 10 μg m-3. With local action on PM2.5 in London, population weighted concentrations showed full compliance with the WHO interim target of 10 μg m-3 in 2030. However, predicting future PM2.5 concentrations and interpreting the results will always be difficult and uncertain for many reasons, such as imperfect models and the difficulty in estimating future emissions. To help understand the sensitivity of the model's PM2.5 predictions in 2030, current uncertainty was quantified using PM2.5 measurements and showed large areas in the UK that were still at risk of exceeding the WHO interim target despite the model predictions being below 10 μg m-3. Our results do however point to the benefits that policy at EU, UK and city level can have on achieving the WHO interim target of 10 μg m-3. These results were submitted to the UK Environment Act consultation. Nevertheless, the issues addressed here could be applicable to other European cities.

Severe level of photochemical oxidants (Ox) over the western coast of Japan during autumn after typhoon passing

Photochemical oxidants (Ox; mainly O3) are a concern in East Asia. Because of the prevailing westerly wind in the midlatitudes, O3 concentration generally shows a high in spring over Kyushu Island, western Japan, and Ox warnings have been issued in spring. However, the record from 2000 to 2021 of Ox warning days in Kyushu Island contains one warning case in autumn 2020. Interestingly, a typhoon had passed the day before this Ox warning. To relate these events, a modelling simulation was conducted and it showed the transboundary O3 transport from the Asian continent to the western coast of Japan due to the strong wind field determined by the location of Typhoon Haishen (2020). The sensitivity simulations for changing Chinese anthropogenic sources suggested that both nitrogen oxides (NOx) and volatile organic compound (VOC) emission regulations in China could decrease high O3 over the downwind region of Japan. Furthermore, VOC emission regulation in China led to an overall O3 decrease in East Asia, whereas NOx emission regulation in China had complex effects of decreasing (increasing) O3 during the daytime (nighttime) over China. The association between air quality and meteorology related to typhoons should be considered along with global warming in the future.

Oxidized and Unsaturated: Key Organic Aerosol Traits Associated with Cellular Reactive Oxygen Species Production in the Southeastern United States

Exposure to ambient fine particulate matter (PM2.5) is associated with millions of premature deaths annually. Oxidative stress through overproduction of reactive oxygen species (ROS) is a possible mechanism for PM2.5-induced health effects. Organic aerosol (OA) is a dominant component of PM2.5 worldwide, yet its role in PM2.5 toxicity is poorly understood due to its chemical complexity. Here, through integrated cellular ROS measurements and detailed multi-instrument chemical characterization of PM in urban southeastern United States, we show that oxygenated OA (OOA), especially more-oxidized OOA, is the main OA type associated with cellular ROS production. We further reveal that highly unsaturated species containing carbon-oxygen double bonds and aromatic rings in OOA are major contributors to cellular ROS production. These results highlight the key chemical features of ambient OA driving its toxicity. As more-oxidized OOA is ubiquitous and abundant in the atmosphere, this emphasizes the need to understand its sources and chemical processing when formulating effective strategies to mitigate PM2.5 health impacts.

Sensitivity of northeastern US surface ozone predictions to the representation of atmospheric chemistry in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0)

Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O3) across the northeastern US during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O3 predictions of hourly and maximum daily 8 h average (MDA8) ozone were lower than those estimated by the Regional Atmospheric Chemistry Mechanism with aerosol module 6 (RACM2_ae6), which better matched surface network observations in the northeastern US (RACM2_ae6 mean bias of +4.2 ppb for all hours and +4.3 ppb for MDA8; CRACMMv1.0 mean bias of +2.1 ppb for all hours and +2.7 ppb for MDA8). Box model calculations combined with results from CMAQ emission reduction simulations indicated a high sensitivity of O3 to compounds with biogenic sources. In addition, these calculations indicated the differences between CRACMMv1.0 and RACM2_ae6 O3 predictions were largely explained by updates to the inorganic rate constants (reflecting the latest assessment values) and by updates to the representation of monoterpene chemistry. Updates to other reactive organic carbon systems between RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene, and xylene chemistry led to efficient NO x cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O3 disbenefits. In contrast, semivolatile and intermediate-volatility alkanes introduced in CRACMMv1.0 acted to suppress O3 formation across the regional background through the sequestration of nitrogen oxides (NO x ) in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone concentrations in the northeastern US during the summer of 2018 with similar magnitude and diurnal variation as the current operational Carbon Bond (CB6r3_ae7) mechanism and good model performance compared to recent modeling studies in the literature.

Volatility of Secondary Organic Aerosol from β-Caryophyllene Ozonolysis over a Wide Tropospheric Temperature Range

We investigated secondary organic aerosol (SOA) from β-caryophyllene oxidation generated over a wide tropospheric temperature range (213-313 K) from ozonolysis. Positive matrix factorization (PMF) was used to deconvolute the desorption data (thermograms) of SOA products detected by a chemical ionization mass spectrometer (FIGAERO-CIMS). A nonmonotonic dependence of particle volatility (saturation concentration at 298 K, C298K*) on formation temperature (213-313 K) was observed, primarily due to temperature-dependent formation pathways of β-caryophyllene oxidation products. The PMF analysis grouped detected ions into 11 compound groups (factors) with characteristic volatility. These compound groups act as indicators for the underlying SOA formation mechanisms. Their different temperature responses revealed that the relevant chemical pathways (e.g., autoxidation, oligomer formation, and isomer formation) had distinct optimal temperatures between 213 and 313 K, significantly beyond the effect of temperature-dependent partitioning. Furthermore, PMF-resolved volatility groups were compared with volatility basis set (VBS) distributions based on different vapor pressure estimation methods. The variation of the volatilities predicted by different methods is affected by highly oxygenated molecules, isomers, and thermal decomposition of oligomers with long carbon chains. This work distinguishes multiple isomers and identifies compound groups of varying volatilities, providing new insights into the temperature-dependent formation mechanisms of β-caryophyllene-derived SOA particles.

Linking gas, particulate, and toxic endpoints to air emissions in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM)

Chemical mechanisms describe the atmospheric transformations of organic and inorganic species and connect air emissions to secondary species such as ozone, fine particles, and hazardous air pollutants (HAPs) like formaldehyde. Recent advances in our understanding of several chemical systems and shifts in the drivers of atmospheric chemistry warrant updates to mechanisms used in chemical transport models such as the Community Multiscale Air Quality (CMAQ) modeling system. This work builds on the Regional Atmospheric Chemistry Mechanism version 2 (RACM2) and develops the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 1.0, which demonstrates a fully coupled representation of chemistry leading to ozone and secondary organic aerosol (SOA) with consideration of HAPs. CRACMMv1.0 includes 178 gas-phase species, 51 particulate species, and 508 reactions spanning gas-phase and heterogeneous pathways. To support estimation of health risks associated with HAPs, nine species in CRACMM cover 50 % of the total cancer and 60 % of the total non-cancer emission-weighted toxicity estimated for primary HAPs from anthropogenic and biomass burning sources in the US, with the coverage of toxicity higher (>80 %) when secondary formaldehyde and acrolein are considered. In addition, new mechanism species were added based on the importance of their emissions for the ozone, organic aerosol, or atmospheric burden of total reactive organic carbon (ROC): sesquiterpenes, furans, propylene glycol, alkane-like low- to intermediate-volatility organic compounds (9 species), low- to intermediate-volatility oxygenated species (16 species), intermediate-volatility aromatic hydrocarbons (2 species), and slowly reacting organic carbon. Intermediate- and lower-volatility organic compounds were estimated to increase the coverage of anthropogenic and biomass burning ROC emissions by 40 % compared to current operational mechanisms. Autoxidation, a gas-phase reaction particularly effective in producing SOA, was added for C10 and larger alkanes, aromatic hydrocarbons, sesquiterpenes, and monoterpene systems including second-generation aldehydes. Integrating the radical and SOA chemistry put additional constraints on both systems and enabled the implementation of previously unconsidered SOA pathways from phenolic and furanone compounds, which were predicted to account for ~ 30 % of total aromatic hydrocarbon SOA under typical atmospheric conditions. CRACMM organic aerosol species were found to span the atmospherically relevant range of species carbon number, number of oxygens per carbon, and oxidation state with a slight high bias in the number of hydrogens per carbon. In total, 11 new emitted species were implemented as precursors to SOA compared to current CMAQv5.3.3 representations, resulting in a bottom-up prediction of SOA, which is required for accurate source attribution and the design of control strategies. CRACMMv1.0 is available in CMAQv5.4.

Chronic Exposure to Secondary Organic Aerosols Causes Lung Tissue Damage

Recently, secondary organic aerosols (SOAs) emerged as a predominant component of fine particulate matter. However, the pathogenic mechanism(s) of SOAs are still poorly understood. Herein, we show that chronic exposure of mice to SOAs resulted in lung inflammation and tissue destruction. Histological analyses found lung airspace enlargement associated with massive inflammatory cell recruitment predominated by macrophages. Concomitant with such cell influx, our results found changes in the levels of a series of inflammatory mediators in response to SOA. Interestingly, we observed that the expression of the genes encoding for TNF-α and IL-6 increased significantly after one month of exposure to SOAs; mediators that have been largely documented to play a role in chronic pulmonary inflammatory pathologies. Cell culture studies confirmed these in vivo findings. Of importance as well, our study indicates increased matrix metalloproteinase proteolytic activity suggesting its contribution to lung tissue inflammation and degradation. Our work represents the first in vivo study, which reports that chronic exposure to SOAs leads to lung inflammation and tissue injury. Thus, we hope that these data will foster new studies to enhance our understanding of the underlying pathogenic mechanisms of SOAs and perhaps help in the design of therapeutic strategies against SOA-mediated lung injury.

Photolysis of Gas-Phase Atmospherically Relevant Monoterpene-Derived Organic Nitrates

Organic nitrates (ONs) can impact spatial distribution of reactive nitrogen species and ozone formation in the atmosphere. While photolysis of ONs is known to result in the release of NO₂ back to the atmosphere, the photolysis rate constants and mechanisms of monoterpene-derived ONs (MT-ONs) have not been well constrained. We investigated the gas-phase photolysis of three synthetic ONs derived from α-pinene, β-pinene, and d-limonene through chamber experiments. The measured photolysis rate constants ranged from (0.55 ± 0.10) × 10^-5 to (2.3 ± 0.80) × 10^-5 s^-1 under chamber black lights. When extrapolated to solar spectral photon flux at a solar zenith angle of 28.14° in summer, the photolysis rate constants were in the range of (4.1 ± 1.4) × 10^-5 to (14 ± 6.7) × 10^-5 s^-1 (corresponding to lifetimes of 2.0 ± 0.96 to 6.8 ± 2.4 h) and (1.7 ± 0.60) × 10^-5 to (8.3 ± 4.0) ×10^-5 s^-1 (3.3 ± 1.6 to 17 ± 6.0 h lifetimes) by using wavelength-dependent and average quantum yields, respectively. Photolysis mechanisms were proposed based on major products detected during photolysis. A zero-dimensional box model was further employed to simulate the photolysis of α-pinene-derived ON under ambient conditions. We found that more than 99% of α-pinene-derived ON can be converted to inorganic nitrogen within 12 h of irradiation and ozone was formed correspondingly. Together, these findings show that photolysis is an important atmospheric sink for MT-ONs and highlight their role in NO_x recycling and ozone chemistry.

Non-linear effects of secondary organic aerosol formation and properties in multi-precursor systems

Secondary organic aerosol (SOA) contributes significantly to ambient fine particulate matter that affects climate and human health. Monoterpenes represent an important class of biogenic volatile organic compounds (VOCs) and their oxidation by nitrate radicals poses a substantial source of SOA globally. Here, we investigate the formation and properties of SOA from nitrate radical oxidation of two common monoterpenes, α-pinene and limonene. When two monoterpenes are oxidized simultaneously, we observe a ~50% enhancement in the formation of SOA from α-pinene and a ~20% reduction in limonene SOA formation. The change in SOA yields is accompanied by pronounced changes in aerosol chemical composition and volatility. These non-linear effects are not observed in a sequential oxidation experiment. Our results highlight that unlike currently assumed in atmospheric models, the interaction of products formed from individual VOCs should be accounted for to accurately describe SOA formation and its climate and health impacts.

Inferring and evaluating satellite-based constraints on NO x emissions estimates in air quality simulations

Satellite observations of tropospheric NO2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NO x ). Mass-balance-based methods are often applied for this purpose but do not isolate near-surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model. In the framework, satellite-constrained emissions totals are inferred using model simulations with and without data assimilation in the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to separately estimate lightning and anthropogenic NO x emissions over the Northern Hemisphere for 2019. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare separate NO x emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO2 and O3. OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO2 retrievals. Updated lightning NO x emissions from either satellite improve the chemical transport model's low tropospheric O3 bias. The combined lighting and anthropogenic emissions updates improve the model's ability to reproduce measured ozone by adjusting natural, long-range, and local pollution contributions. Thus, the framework informs and supports the design of domestic and international control strategies.

Emissions of Condensable Organic Aerosols from Stationary Combustion Sources over Japan

Treatment of condensable particulate matter (CPM) is key for accurate simulation of atmospheric particulate matter (PM), because conventional stationary combustion source emission surveys do not measure CPM in many countries. This study updates previously estimated CPM emissions from stationary combustion sources in Japan by considering the relationship between the CPM fraction and filterable PM (FPM) concentrations for individual sources rather than using a uniform CPM/FPM ratio for all sources. As a result, the total emissions ratio of condensable organic aerosol (OA) and filterable PM2.5 (OA CPM ∕ PM 2.5 FPM ) from stationary combustion sources, based on this update, changes from ~2.0 to 0.20, and the estimated concentrations of condensable OA, averaged over winter and over summer, changes from up to 3 μg m-3 to up to 0.2 μg m-3. The normalized mean bias for concentration of the simulated organic carbon (OC) in winter changes from -78% ~ -9% to -83% ~ -28%), although the proportion of modern carbon in total carbon is better estimated. The CPM contribution is likely to be overestimated when the source-dependent relationship between the CPM/FPM ratio and FPM concentration is not considered. Thus, accurate knowledge of the CPM/FPM ratio, particularly for sources with high FPM concentrations, is critical to improve CPM emission estimation.

Improving the particle dry deposition scheme in the CMAQ photochemical modeling system

Dry deposition of atmospheric aerosols in large-scale models is a critical, but highly uncertain, sink process with a strong dependence on particle size, meteorological conditions, and land surface properties. This study investigates the particle dry deposition scheme implemented in the standard Community Multiscale Air Quality (CMAQ) model v5.2.1, characterizes its underlying parameterized components with comparison to a similar scheme in a contemporary regional-scale model, and proposes two updated schemes that are then evaluated with available ambient particle deposition velocity (Vd) measurements. Both updated schemes reduce the surprisingly strong dependence of deposition velocity on the aerosol mode width, with one scheme further introducing a dependence on vegetation coverage that is broadly consistent with variability in observations between vegetated and non-vegetated surfaces. Compared to the base scheme, the updated scheme with vegetation dependence increases Vd for submicron particles and decreases it for larger particles by an average of 37% and -66%, respectively. This scheme performs statistically better than the base scheme, reducing fractional biases by 56%-97% for vegetated land-use types and has roughly equivalent performance over water. The base and updated schemes are tested with three annual CMAQ (v5.2.1) simulations for the year 2011; predicted ambient aerosol concentrations are evaluated with routine monitoring network observations and predicted dry deposition fluxes are evaluated with data from the Clean Air Status and Trends Network (CASTNET). The updated scheme with vegetation dependence reduces negative fractional biases for PM10 by 41% and positive fractional biases for PM2.5 organic carbon by 15%. This scheme has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3 and beyond) to replace the scheme used in previous versions of CMAQ (v4.5 through v5.2.1).

Acylperoxy Radicals as Key Intermediates in the Formation of Dimeric Compounds in α-Pinene Secondary Organic Aerosol

High molecular weight dimeric compounds constitute a significant fraction of secondary organic aerosol (SOA) and have profound impacts on the properties and lifecycle of particles in the atmosphere. Although different formation mechanisms involving reactive intermediates and/or closed-shell monomeric species have been proposed for the particle-phase dimers, their relative importance remains in debate. Here, we report unambiguous experimental evidence of the important role of acyl organic peroxy radicals (RO₂) and a small but non-negligible contribution from stabilized Criegee intermediates (SCIs) in the formation of particle-phase dimers during ozonolysis of α-pinene, one of the most important precursors for biogenic SOA. Specifically, we find that acyl RO₂-involved reactions explain 50-80% of total oxygenated dimer signals (C₁₅-C₂₀, O/C ≥ 0.4) and 20-30% of the total less oxygenated (O/C < 0.4) dimer signals. In particular, they contribute to 70% of C₁₅-C₁₉ dimer ester formation, likely mainly via the decarboxylation of diacyl peroxides arising from acyl RO₂ cross-reactions. In comparison, SCIs play a minor role in the formation of C₁₅-C₁₉ dimer esters but react noticeably with the most abundant C₉ and C₁₀ carboxylic acids and/or carbonyl products to form C₁₉ and C₂₀ dimeric peroxides, which are prone to particle-phase transformation to form more stable dimers without the peroxide functionality. This work provides a clearer view of the formation pathways of particle-phase dimers from α-pinene oxidation and would help reduce the uncertainties in future atmospheric modeling of the budget, properties, and health and climate impacts of SOA.

Pronounced increases in nitrogen emissions and deposition due to the historic 2020 wildfires in the western U.S

Wildfire outbreaks can lead to extreme biomass burning (BB) emissions of both oxidized (e.g., nitrogen oxides; NO_x = NO+NO₂) and reduced form (e.g., ammonia; NH₃) nitrogen (N) compounds. High N emissions are major concerns for air quality, atmospheric deposition, and consequential human and ecosystem health impacts. In this study, we use both satellite-based observations and modeling results to quantify the contribution of BB to the total emissions, and approximate the impact on total N deposition in the western U.S. Our results show that during the 2020 wildfire season of August-October, BB contributes significantly to the total emissions, with a satellite-derived fraction of NH₃ to the total reactive N emissions (median ~ 40%) in the range of aircraft observations. During the peak of the western August Complex Fires in September, BB contributed to ~55% (for the contiguous U.S.) and ~ 83% (for the western U.S.) of the monthly total NO_x and NH₃ emissions. Overall, there is good model performance of the George Mason University-Wildfire Forecasting System (GMU-WFS) used in this work. The extreme BB emissions lead to significant contributions to the total N deposition for different ecosystems in California, with an average August - October 2020 relative increase of ~78% (from 7.1 to 12.6 kg ha^-1 year^-1) in deposition rate to major vegetation types (mixed forests + grasslands/shrublands/savanna) compared to the GMU-WFS simulations without BB emissions. For mixed forest types only, the average N deposition rate increases (from 6.2 to 16.9 kg ha^-1 year^-1) are even larger at ~173%. Such large N deposition due to extreme BB emissions are much (~6-12 times) larger than low-end critical load thresholds for major vegetation types (e.g., forests at 1.5-3 kg ha^-1 year^-1), and thus may result in adverse N deposition effects across larger areas of lichen communities found in California's mixed conifer forests.

Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM2.5) in China

Condensable particulate matter (CPM) emitted from stationary combustion and mobile sources exhibits high emissions and a large proportion of organic components. However, CPM is not generally measured when conducting emission surveys of PM in most countries, including China. Consequently, previous emission inventories have not included emission rates for CPM. Here, we construct an emission inventory of CPM in China with a focus on organic aerosols (OAs) based on collected CPM emission information. Results show that OA emissions are enhanced twofold after the inclusion of CPM in a new inventory for China for the years 2014 and 2017. Considering organic CPM emissions and model representations of secondary OA (SOA) formation from CPM, a series of sensitivity cases have been simulated here using the three-dimensional Community Multiscale Air Quality (CMAQ) model to estimate the contributions of CPM emissions to atmospheric OA and fine PM (PM2.5, particulate matter with aerodynamic diameter not exceeding 2.5 μm) concentrations in China. Compared with observations at a Beijing site during a haze episode from 14 October to 14 November 2014, estimates of the temporal average primary OA (POA) and SOA concentrations were greatly improved after including the CPM effects. These scenarios demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to the POA (51 %-85 %), SOA (42 %-58 %), and total OA concentrations (45 %-75 %). Furthermore, the contributions of CPM emissions to total OA concentrations were demonstrated over the 2 major cities and 26 other cities of the Beijing-Tianjin-Hebei region (hereafter referred to as the "BTH2 + 26 cities") in December 2018, with average contributions of up to 49 %, 53 %, 54 %, and 50 % for Handan, Shijiazhuang, Xingtai, and Dezhou, respectively. Correspondingly, the inclusion of CPM emissions also narrowed the gap between simulated and observed PM2.5 concentrations over the BTH2 + 26 cities. These results improve the simulation performance of atmospheric OA and PM2.5 and may also provide important implications for the sources of OA.

Pathogenic Mechanisms of Secondary Organic Aerosols

Air pollution represents a major health problem and an economic burden. In recent years, advances in air pollution research has allowed particle fractionation and identification of secondary organic aerosol (SOA). SOA is formed from either biogenic or anthropogenic emissions, through a mass transfer from the gaseous mass to the particulate phase in the atmosphere. They can have deleterious impact on health and the mortality of individuals with chronic inflammatory diseases. The pleiotropic effects of SOA could involve different and interconnected pathogenic mechanisms ranging from oxidative stress, inflammation, and immune system dysfunction. The purpose of this review is to present recent findings about SOA pathogenic roles and potential underlying mechanisms focusing on the lungs; the latter being the primary exposed organ to atmospheric pollutants.

Investigating the Sources of Urban Air Pollution Using Low-Cost Air Quality Sensors at an Urban Atlanta Site

Advances in low-cost sensors (LCS) for monitoring air quality have opened new opportunities to characterize air quality in finer spatial and temporal resolutions. In this study, we deployed LCS that measure both gas (CO, NO, NO₂, and O₃) and particle concentrations and co-located research-grade instruments in Atlanta, GA, to investigate the capability of LCS in resolving air pollutant sources using non-negative matrix factorization (NMF) in a moderately polluted urban area. We provide a comparison of applying the NMF technique to both normalized and non-normalized data sets. We identify four factors with different temporal trends and properties for both normalized and non-normalized data sets. Both normalized and non-normalized LCS data sets can resolve primary organic aerosol (POA) factors identified from research-grade instruments. However, applying normalization provides factors with more diverse compositions and can resolve secondary organic aerosol (SOA). Results from this study demonstrate that LCS not only can be used to provide basic mass concentration information but also can be used for in-depth source apportionment studies even in an urban setting with complex pollution mixtures and relatively low aerosol loadings.

Hygroscopic growth and CCN activity of secondary organic aerosol produced from dark ozonolysis of γ-terpinene

The hygroscopic growth factor (GF) and cloud condensation nuclei (CCN) activity of secondary organic aerosol (SOA) particles produced during dark ozonolysis of γ-terpinene under different reaction conditions were investigated. The SOA particles were produced in the presence or absence of cyclohexane, an OH scavenger; 1,3,5-trimethylbenzene, an anthropogenic volatile organic compound; and (NH₄)₂SO₄ seed particles. A hygroscopicity tandem differential mobility analyzer was used to determine the GFs of the SOA particles at RHs ≤ 93%. For some experiments, a CCN counter was used for size-resolved measurement of CCN activation at supersaturation (S) in the range of 0.1 to 1%. The single hygroscopicity parameter κ was derived from both the GF and CCN measurements. Under subsaturated conditions, all the SOA (except those in the presence of the (NH₄)₂SO₄ seeds) showed small GF values. These GFs demonstrated that SOA mass loading affected the GF. A decrease in the SOA mass loading led to increased GF and corresponding κ_GFvalues. However, in a supersaturation regime, the SOA mass loading and the size of the particles did not significantly alter the CCN activity of the SOA. Our CCN measurements showed higher κ_CCN values (κ_CCN = 0.20-0.24) than those observed in most monoterpene ozonolysis studies (κ_CCN = 0.1-0.14). This difference may have been due to the presence of the two endocyclic double bonds in the γ-terpinene structure, which may have affected the SOA chemical composition, in contrast to monoterpenes that contain an exocyclic double bond. Our comparisons of sub- and supersaturated conditions showed a larger range of κ values than other experiments. Average κ_CCN/κ_GF ratios of ~7 and 14 were obtained in the unseeded SOA experiments at low and high SOA mass loadings, respectively. The average κ_CCN of 0.23 indicated that the SOA produced during ozonolysis of γ-terpinene exhibited fairly high CCN activity.

Secondary organic aerosol association with cardiorespiratory disease mortality in the United States

Fine particle pollution, PM2.5, is associated with increased risk of death from cardiorespiratory diseases. A multidecadal shift in the United States (U.S.) PM2.5 composition towards organic aerosol as well as advances in predictive algorithms for secondary organic aerosol (SOA) allows for novel examinations of the role of PM2.5 components on mortality. Here we show SOA is strongly associated with county-level cardiorespiratory death rates in the U.S. independent of the total PM2.5 mass association with the largest associations located in the southeastern U.S. Compared to PM2.5, county-level variability in SOA across the U.S. is associated with 3.5× greater per capita county-level cardiorespiratory mortality. On a per mass basis, SOA is associated with a 6.5× higher rate of mortality than PM2.5, and biogenic and anthropogenic carbon sources both play a role in the overall SOA association with mortality. Our results suggest reducing the health impacts of PM2.5 requires consideration of SOA.

Improving the representation of HONO chemistry in CMAQ and examining its impact on haze over China

We compare Community Multiscale Air Quality (CMAQ) model predictions with measured nitrous acid (HONO) concentrations in Beijing, China for December 2015. The model with the existing HONO chemistry in CMAQ severely under-estimates the observed HONO concentrations with a normalized mean bias of -97%. We revise the HONO chemistry in the model by implementing six additional heterogeneous reactions in the model: reaction of nitrogen dioxide (NO2) on ground surfaces, reaction of NO2 on aerosol surfaces, reaction of NO2 on soot surfaces, photolysis of aerosol nitrate, nitric acid displacement reaction, and hydrochloric acid displacement reaction. The model with the revised chemistry substantially increases HONO predictions and improves the comparison with observed data with a normalized mean bias of -5%. The photolysis of HONO enhances day-time hydroxyl radical by almost a factor of two. The enhanced hydroxyl radical concentrations compare favourably with observed data and produce additional sulfate via the reaction with sulfur dioxide, aerosol nitrate via the reaction with nitrogen dioxide, and secondary organic aerosols via the reactions with volatile organic compounds. The additional sulfate stemming from revised HONO chemistry improves the comparison with observed concentration; however, it does not close the gap between model prediction and the observation during polluted days.

Estimation of Aromatic Secondary Organic Aerosol Using a Molecular Tracer-A Chemical Transport Model Assessment

A modified community multiscale air quality model, which can simulate the regional distributions of 2,3-dihydroxy-4-oxopentanoic acid (DHOPA), a marker species for monoaromatic secondary organic aerosol (SOA), was applied to assess the applicability of using the DHOPA to aromatic SOA mass ratio (f_SOA) from smog chamber experiments to estimate aromatic SOA during a three-week wintertime air quality campaign in urban Shanghai. The modeled daily DHOPA concentrations based on the chamber-derived mass yields agree well with the organic marker field measurements (R = 0.79; MFB = 0.152; and MFE = 0.440). Two-thirds of the DHOPA are from the oxidation of ARO1 (lumped less-reactive aromatic species; mostly toluene), with the rest from ARO2 (lumped more-reactive aromatic species; mostly xylenes). Modeled DHOPA is mainly in the particle phase under ambient organic aerosol (OA) loading but could exhibit significant gas-particle partitioning when a higher estimation of the DHOPA vapor pressure is used. The modeled f_SOA shows a strong dependence on the OA loading when only semivolatile aromatic SOA components are included in the f_SOA calculations. However, this OA dependence becomes weaker when non-volatile oligomers and dicarbonyl SOA products are considered. A constant f_SOA value of ∼0.002 is determined when all aromatic SOA components are included, which is a factor of 2 smaller than the commonly applied chamber-based f_SOA value of 0.004 for toluene. This model-derived f_SOA value does not show much spatial variation and is not sensitive to alternative estimates of DHOPA vapor pressures and SOA yields, and thus provides an appropriate scaling factor to assess aromatic SOA from DHOPA measurements. This result helps refine the quantification of SOA attributable to monoaromatic hydrocarbons in urban environments and thereby facilitates the evaluation of control measures targeting these specific precursors.

Predicting the Nonlinear Response of PM2.5 and Ozone to Precursor Emission Changes with a Response Surface Model

Reducing PM2.5 and ozone concentrations is important to protect human health and the environment. Chemical transport models, such as the Community Multiscale Air Quality (CMAQ) model, are valuable tools for exploring policy options for improving air quality but are computationally expensive. Here, we statistically fit an efficient polynomial function in a response surface model (pf-RSM) to CMAQ simulations over the eastern U.S. for January and July 2016. The pf-RSM predictions were evaluated using out-of-sample CMAQ simulations and used to examine the nonlinear response of air quality to emission changes. Predictions of the pf-RSM are in good agreement with the out-of-sample CMAQ simulations, with some exceptions for cases with anthropogenic emission reductions approaching 100%. NOX emission reductions were more effective for reducing PM2.5 and ozone concentrations than SO2, NH3, or traditional VOC emission reductions. NH3 emission reductions effectively reduced nitrate concentrations in January but increased secondary organic aerosol (SOA) concentrations in July. More work is needed on SOA formation under conditions of low NH3 emissions to verify the responses of SOA to NH3 emission changes predicted here. Overall, the pf-RSM performs well in the eastern U.S., but next-generation RSMs based on deep learning may be needed to meet the computational requirements of typical regulatory applications.

Evaluation of the offline-coupled GFSv15-FV3-CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States

As a candidate for the next-generation National Air Quality Forecast Capability (NAQFC), the meteorological forecast from the Global Forecast System with the new Finite Volume Cube-Sphere dynamical core (GFS-FV3) will be applied to drive the chemical evolution of gases and particles described by the Community Multiscale Air Quality modeling system. CMAQv5.0.2, a historical version of CMAQ, has been coupled with the North American Mesoscale Forecast System (NAM) model in the current operational NAQFC. An experimental version of the NAQFC based on the offline-coupled GFS-FV3 version 15 with CMAQv5.0.2 modeling system (GFSv15-CMAQv5.0.2) has been developed by the National Oceanic and Atmospheric Administration (NOAA) to provide real-time air quality forecasts over the contiguous United States (CONUS) since 2018. In this work, comprehensive region-specific, time-specific, and categorical evaluations are conducted for meteorological and chemical forecasts from the offline-coupled GFSv15-CMAQv5.0.2 for the year 2019. The forecast system shows good overall performance in forecasting meteorological variables with the annual mean biases of -0.2 °C for temperature at 2 m, 0.4% for relative humidity at 2 m, and 0.4 m s-1 for wind speed at 10 m compared to the METeorological Aerodrome Reports (METAR) dataset. Larger biases occur in seasonal and monthly mean forecasts, particularly in spring. Although the monthly accumulated precipitation forecasts show generally consistent spatial distributions with those from the remote-sensing and ensemble datasets, moderate-to-large biases exist in hourly precipitation forecasts compared to the Clean Air Status and Trends Network (CASTNET) and METAR. While the forecast system performs well in forecasting ozone (O3) throughout the year and fine particles with a diameter of 2.5 μm or less (PM2.5) for warm months (May-September), it significantly overpredicts annual mean concentrations of PM2.5. This is due mainly to the high predicted concentrations of fine fugitive and coarse-mode particle components. Underpredictions in the southeastern US and California during summer are attributed to missing sources and mechanisms of secondary organic aerosol formation from biogenic volatile organic compounds (VOCs) and semivolatile or intermediate-volatility organic compounds. This work demonstrates the ability of FV3-based GFS in driving the air quality forecasting. It identifies possible underlying causes for systematic region- and time-specific model biases, which will provide a scientific basis for further development of the next-generation NAQFC.

The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation

The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O₃ and daily PM_2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O₃, CMAQ531 has higher O₃ in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O₃ bias (2-4 ppbv monthly average). MDA8 O₃ is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O₃ from the lateral boundary conditions (BCs), which generally increases MDA8 O₃ bias in spring and fall ( 0.5 μg m^-3). For daily 24 h average PM_2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O₃ mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O₃ dry deposition to snow in CMAQ53) and lower O₃ mixing ratios in middle and lower latitudes year-round (due to reduced O₃ over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O₃ mixing ratios and higher PM_2.5 concentrations (0.1-0.25 μg m^-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O₃ is generally higher with M3Dry outside of summer, while PM_2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH₃, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.

Evaluating trends and seasonality in modeled PM2.5 concentrations using empirical mode decomposition

Regional-scale air quality models are being used for studying the sources, composition, transport, transformation, and deposition of fine particulate matter (PM_2.5). The availability of decadal air quality simulations provides a unique opportunity to explore sophisticated model evaluation techniques rather than relying solely on traditional operational evaluations. In this study, we propose a new approach for process-based model evaluation of speciated PM_2.5 using improved complete ensemble empirical mode decomposition with adaptive noise (improved CEEMDAN) to assess how well version 5.0.2 of the coupled Weather Research and Forecasting model-Community Multiscale Air Quality model (WRF-CMAQ) simulates the time-dependent long-term trend and cyclical variations in daily average PM_2.5 and its species, including sulfate (SO₄), nitrate (NO₃), ammonium (NH₄), chloride (Cl), organic carbon (OC), and elemental carbon (EC). The utility of the proposed approach for model evaluation is demonstrated using PM_2.5 data at three monitoring locations. At these locations, the model is generally more capable of simulating the rate of change in the long-term trend component than its absolute magnitude. Amplitudes of the sub-seasonal and annual cycles of total PM_2.5, SO₄, and OC are well reproduced. However, the time-dependent phase difference in the annual cycles for total PM_2.5, OC, and EC reveals a phase shift of up to half a year, indicating the need for proper temporal allocation of emissions and for updating the treatment of organic aerosols compared to the model version used for this set of simulations. Evaluation of sub-seasonal and interannual variations indicates that CMAQ is more capable of replicating the sub-seasonal cycles than interannual variations in magnitude and phase.

Impact of dimethylsulfide chemistry on air quality over the Northern Hemisphere

We implement oceanic dimethylsulfide (DMS) emissions and its atmospheric chemical reactions into the Community Multiscale Air Quality (CMAQv53) model and perform annual simulations without and with DMS chemistry to quantify its impact on tropospheric composition and air quality over the Northern Hemisphere. DMS chemistry enhances both sulfur dioxide (SO2) and sulfate (S O 4 2 - ) over seawater and coastal areas. It enhances annual mean surface SO2 concentration by +46 pptv andS O 4 2 - by +0.33 μg/m3 and decreases aerosol nitrate concentration by -0.07 μg/m3 over seawater compared to the simulation without DMS chemistry. The changes decrease with altitude and are limited to the lower atmosphere. Impacts of DMS chemistry onS O 4 2 - are largest in the summer and lowest in the fall due to the seasonality of DMS emissions, atmospheric photochemistry and resultant oxidant levels. Hydroxyl and nitrate radical-initiated pathways oxidize 75% of the DMS while halogen-initiated pathways oxidize 25%. DMS chemistry leads to more acidic particles over seawater by decreasing aerosol pH. IncreasedS O 4 2 - from DMS enhances atmospheric extinction while lower aerosol nitrate reduces the extinction so that the net effect of DMS chemistry on visibility tends to remain unchanged over most of the seawater.

Criteria pollutant impacts of volatile chemical products informed by near-field modeling

Consumer, industrial, and commercial product usage is a source of exposure to potentially hazardous chemicals. In addition, cleaning agents, personal care products, coatings, and other volatile chemical products (VCPs), evaporate and react in the atmosphere producing secondary pollutants. Here, we show high air emissions from VCP usage (≥ 14 kg person^-1 yr^-1, at least 1.7× higher than current operational estimates) are supported by multiple estimation methods and constraints imposed by ambient levels of ozone, hydroxyl radical (OH) reactivity, and the organic component of fine particulate matter (PM_2.5) in Pasadena, California. A near-field model, which estimates human chemical exposure during or in the vicinity of product use, indicates these high air emissions are consistent with organic product usage up to ~75 kg person^-1 yr^-1, and inhalation of consumer products could be a non-negligible exposure pathway. After constraining the PM_2.5 yield to 5% by mass, VCPs produce ~41% of the photochemical organic PM_2.5 (1.1 ± 0.3 μg m^-3) and ~17% of maximum daily 8-hr average ozone (9 ± 2 ppb) in summer Los Angeles. Therefore, both toxicity and ambient criteria pollutant formation should be considered when organic substituents are developed for VCPs in pursuit of safer and sustainable products and cleaner air.

Predicting secondary organic aerosol phase state and viscosity and its effect on multiphase chemistry in a regional-scale air quality model

Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (T _g), oxygen to carbon (O : C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core-shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4 % of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported ~ 70 % in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 10²-10¹² Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity < 10² Pa s. Phase separation while in a liquid phase state, i.e., liquid-liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution rate of isoprene epoxydiol (IEPOX) into the particle phase in CMAQ can have varying impact on fine particulate matter (PM_2.5) organic mass, in terms of bias and error compared to field data collected during the 2013 SOAS. This highlights the need to better constrain the parameters that govern phase state and morphology of SOA, as well as expand mechanistic representation of multiphase chemistry for non-IEPOX SOA formation in models aided by novel experimental insights.

Simulation of organic aerosol formation during the CalNex study: updated mobile emissions and secondary organic aerosol parameterization for intermediate-volatility organic compounds

We describe simulations using an updated version of the Community Multiscale Air Quality model version 5.3 (CMAQ v5.3) to investigate the contribution of intermediate-volatility organic compounds (IVOCs) to secondary organic aerosol (SOA) formation in southern California during the CalNex study. We first derive a model-ready parameterization for SOA formation from IVOC emissions from mobile sources. To account for SOA formation from both diesel and gasoline sources, the parameterization has six lumped precursor species that resolve both volatility and molecular structure (aromatic versus aliphatic). We also implement new mobile-source emission profiles that quantify all IVOCs based on direct measurements. The profiles have been released in SPECIATE 5.0. By incorporating both comprehensive mobile-source emission profiles for semivolatile organic compounds (SVOCs) and IVOCs and experimentally constrained SOA yields, this CMAQ configuration best represents the contribution of mobile sources to urban and regional ambient organic aerosol (OA). In the Los Angeles region, gasoline sources emit 4 times more non-methane organic gases (NMOGs) than diesel sources, but diesel emits roughly 3 times more IVOCs on an absolute basis. The revised model predicts all mobile sources (including on- and off-road gasoline, aircraft, and on- and off-road diesel) contribute ~ 1 μgm-3 to the daily peak SOA concentration in Pasadena. This represents a ~ 70% increase in predicted daily peak SOA formation compared to the base version of CMAQ. Therefore, IVOCs in mobile-source emissions contribute almost as much SOA as traditional precursors such as single-ring aromatics. However, accounting for these emissions in CMAQ does not reproduce measurements of either ambient SOA or IVOCs. To investigate the potential contribution of other IVOC sources, we performed two exploratory simulations with varying amounts of IVOC emissions from nonmobile sources. To close the mass balance of primary hydrocarbon IVOCs, IVOCs would need to account for 12% of NMOG emissions from nonmobile sources (or equivalently 30.7 t d-1 in the Los Angeles-Pasadena region), a value that is well within the reported range of IVOC content from volatile chemical products. To close the SOA mass balance and also explain the mildly oxygenated IVOCs in Pasadena, an additional 14.8% of nonmobile-source NMOG emissions would need to be IVOCs (assuming SOA yields from the mobile IVOCs apply to nonmobile IVOCs). However, an IVOC-to-NMOG ratio of 26.8% (or equivalently 68.5 t d-1 in the Los Angeles-Pasadena region) for nonmobile sources is likely unrealistically high. Our results highlight the important contribution of IVOCs to SOA production in the Los Angeles region but underscore that other uncertainties must be addressed (multigenerational aging, aqueous chemistry and vapor wall losses) to close the SOA mass balance. This research also highlights the effectiveness of regulations to reduce mobile-source emissions, which have in turn increased the relative importance of other sources, such as volatile chemical products.

Resolving ambient organic aerosol formation and aging pathways with simultaneous molecular composition and volatility observations

Organic aerosol (OA) constitutes a significant fraction of atmospheric fine particle mass. However, the precursors and chemical processes responsible for a majority of OA are rarely conclusively identified. We use online observations of hundreds of simultaneously measured molecular components obtained from 15 laboratory OA formation experiments with constraints on their effective saturation vapor concentrations to attribute the VOC precursors and subsequent chemical pathways giving rise to the vast majority of OA mass measured in two forested regions. We find that precursors and chemical pathways regulating OA composition and volatility are dynamic over hours to days, with their variations driven by coupled interactions between multiple oxidants. The extent of physical and photochemical aging, and its modulation by NOx, were key to a uniquely comprehensive combined composition-volatility description of OA. Our findings thus provide some of the most complete mechanistic-level guidance to the development of OA descriptions in air quality and Earth system models.

Anthropogenic enhancements to production of highly oxygenated molecules from autoxidation

Atmospheric oxidation of natural and anthropogenic volatile organic compounds (VOCs) leads to secondary organic aerosol (SOA), which constitutes a major and often dominant component of atmospheric fine particulate matter (PM2.5). Recent work demonstrates that rapid autoxidation of organic peroxy radicals (RO2) formed during VOC oxidation results in highly oxygenated organic molecules (HOM) that efficiently form SOA. As NOx emissions decrease, the chemical regime of the atmosphere changes to one in which RO2 autoxidation becomes increasingly important, potentially increasing PM2.5, while oxidant availability driving RO2 formation rates simultaneously declines, possibly slowing regional PM2.5 formation. Using a suite of in situ aircraft observations and laboratory studies of HOM, together with a detailed molecular mechanism, we show that although autoxidation in an archetypal biogenic VOC system becomes more competitive as NOx decreases, absolute HOM production rates decrease due to oxidant reductions, leading to an overall positive coupling between anthropogenic NOx and localized biogenic SOA from autoxidation. This effect is observed in the Atlanta, Georgia, urban plume where HOM is enhanced in the presence of elevated NO, and predictions for Guangzhou, China, where increasing HOM-RO2 production coincides with increases in NO from 1990 to 2010. These results suggest added benefits to PM2.5 abatement strategies come with NOx emission reductions and have implications for aerosol-climate interactions due to changes in global SOA resulting from NOx interactions since the preindustrial era.

Spatial variation of modelled total, dry and wet nitrogen deposition to forests at global scale

Forests are an important biome that covers about one third of the global land surface and provides important ecosystem services. Since atmospheric deposition of nitrogen (N) can have both beneficial and deleterious effects, it is important to quantify the amount of N deposition to forest ecosystems. Measurements of N deposition to the numerous forest biomes across the globe are scarce, so chemical transport models are often used to provide estimates of atmospheric N inputs to these ecosystems. We provide an overview of approaches used to calculate N deposition in commonly used chemical transport models. The Task Force on Hemispheric Transport of Air Pollution (HTAP2) study intercompared N deposition values from a number of global chemical transport models. Using a multi-model mean calculated from the HTAP2 deposition values, we map N deposition to global forests to examine spatial variations in total, dry and wet deposition. Highest total N deposition occurs in eastern and southern China, Japan, Eastern U.S. and Europe while the highest dry deposition occurs in tropical forests. The European Monitoring and Evaluation Program (EMEP) model predicts grid-average deposition, but also produces deposition by land use type allowing us to compare deposition specifically to forests with the grid-average value. We found that, for this study, differences between the grid-average and forest specific could be as much as a factor of two and up to more than a factor of five in extreme cases. This suggests that consideration should be given to using forest-specific deposition for input to ecosystem assessments such as critical loads determinations.