On the implications of aerosol liquid water and phase separation for organic aerosol mass

Analyzing the Role of Chemical Mechanism Choice in Wintertime PM2.5 Modeling for Temperature Inversion-Prone Areas

Chemical transport models are used for federal compliance demonstrations when areas are out of attainment, but there is no guidance for choosing a chemical mechanism. With the 2024 change of the annual PM2.5 standard and the prevalence of multiday wintertime inversion episodes in the western U.S., understanding the wintertime performance of chemical transport models is important. This study explores the impact of chemical mechanism choice on the Community Multiscale Air Quality (CMAQ) model performance for PM2.5 and implications for attainment demonstration in inversion-prone areas in the western United States. Total and speciated PM2.5 observations were used to evaluate wintertime CMAQ simulations using four chemical mechanisms. The study evaluated intermechanism differences in total and secondary PM2.5 and the impact of meteorology at sites with observed multiday temperature inversions. Model performance for total PM2.5 was similar across chemical mechanisms, but intermechanism differences for total and secondary PM2.5 were exacerbated during inversion periods, suggesting that modeled chemistry contributes to the model bias. Results suggest that nitrate, ammonium, and organic carbon are secondary species for which model results do not agree or perform to standard evaluation metrics in scientific literature. These findings show a need for mechanistic investigations of the causes of these differences.

Regional-specific trends of PM2.5 and O3 temperature sensitivity in the United States

Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, the influence of rising temperature on air quality remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here, we examined the sensitivity of surface-level fine particulate matter (PM2.5) and ozone (O3) to summer temperature anomalies in the contiguous US as well as their decadal changes using high-resolution datasets generated by machine learning. Our findings demonstrate that in the eastern US, stringent emission control strategies have significantly reduced the positive responses of PM2.5 and O3 to summer temperature, thereby lowering the population exposure associated with warming-induced air quality deterioration. In contrast, PM2.5 in the western US became more sensitive to temperature, highlighting the urgent need to manage and mitigate the impact of worsening wildfires. Our results have important implications for air quality management and risk assessments of future climate change.

High Viscosity and Two Phases Observed over a Range of Relative Humidities in Biomass Burning Organic Aerosol from Canadian Wildfires

Biomass burning organic aerosol (BBOA) is a major contributor to organic aerosol in the atmosphere. The impacts of BBOA on climate and health depend strongly upon their physicochemical properties, including viscosity and phase behavior (number and types of phases); these properties are not yet fully characterized. We collected BBOA field samples during the 2021 British Columbia wildfire season to constrain the viscosity and phase behavior at a range of relative humidities and compared them to previous studies on BBOA. Particles from all samples exhibited two-phased behavior with a polar hydrophilic phase and a nonpolar hydrophobic phase. We used the poke-flow viscosity technique to estimate the viscosity of the particles. Both phases of the BBOA had viscosities of >108 Pa s at relative humidities up to 50%. Such high viscosities correspond to mixing times within 200 nm BBOA particles of >5 h. Two phases and high viscosity have implications for how BBOA should be treated in atmospheric models.

Spatiotemporally Detailed Quantification of Air Quality Benefits of Emissions Reductions-Part I: Benefit-per-Ton Estimates for Canada and the U.S

The U.S. EPA's Community Multiscale Air Quality (CMAQ)-adjoint model is used to map monetized health benefits (defined here as benefits of reduced mortality from chronic PM2.5 exposure) in the form of benefits per ton (of emissions reduced) for the U.S. and Canada for NOx, SO2, ammonia, and primary PM2.5 emissions. The adjoint model provides benefits per ton (BPTs) that are location-specific and applicable to various sectors. BPTs show significant variability across locations, such that only 20% of primary PM2.5 emissions in each country makes up more than half of its burden. The greatest benefits in terms of BPTs are for primary PM2.5 reductions, followed by ammonia. Seasonal differences in benefits vary by pollutant: while PM2.5 benefits remain high across seasons, BPTs for reducing ammonia are much higher in the winter due to the increased ammonium nitrate formation efficiency. Based on our location-specific BPTs, we estimate a total of 91,000 U.S. premature mortalities attributable to natural and anthropogenic emissions.

Modeling the molecular composition of secondary organic aerosol under highly polluted conditions: A case study in the Yangtze River Delta Region in China

A near-explicit mechanism, the master chemical mechanism (MCMv3.3.1), coupled with the Community Multiscale Air Quality (CMAQ) model (CMAQ-MCM-SOA), was applied to investigate the characteristics of secondary organic aerosol (SOA) during a pollution event in the Yangtze River Delta (YRD) region in summer 2018. Model performances in predicting explicit volatile organic compounds (VOCs), organic aerosol (OA), secondary organic carbon (SOC), and other related pollutants in Taizhou, as well as ozone (O3) and fine particulate matter (PM2.5) in multiple cities in this region, were evaluated against observations and model predictions by the CMAQ model coupled with a lumped photochemical mechanism (SAPRC07tic, S07). MCM and S07 exhibited similar performances in predicting gaseous species, while MCM better captured the observed PM2.5 and inorganic aerosols. Both models underpredicted OA concentrations. When excluding data during biomass burning events, SOC concentrations were underpredicted by the CMAQ-MCM-SOA model (-28.4 %) and overpredicted by the CMAQ-S07 model (134.4 %), with better agreement with observations in the trend captured by the CMAQ-MCM-SOA model. Dicarbonyl SOA accounted for a significant fraction of total SOA in the YRD, while organic nitrates originating from aromatics were the most abundant species contributing to the SOA formation from gas-particle partitioning. The oxygen-to‑carbon ratio (O/C) for SOA and OA were 0.68-0.75 and 0.20-0.65, respectively, indicating a higher oxidation state in the areas influenced by biogenic emissions. Finally, the phase state of SOA was examined by calculating the glass transition temperature (Tg) based on its molecular composition. It was found that semi-solid state characterized SOA in the YRD, which could potentially impact their chemical transformation and lifetimes along with those of their precursors.

Air quality assessment of a mass deployment of microgrids

Microgrids are emerging to mitigate the degradation in grid resiliency and reliability resulting from an increasing frequency of grid outages. Because microgrids incorporate a local source of power generation, the production of electricity is shifting from a centralized to distributed topology, thereby installing power generation resources and the concomitant emissions into heavily populated urban air sheds and residential communities. In this paper, the air quality and public health impacts of a mass deployment of microgrids in an urban air shed are assessed. Candidates to become microgrids are identified for both the near- and long-term deployment, and two microgrid scenarios are considered, differing by the 24/7 prime source of power: (1) combustion gas turbine (CGT)-based microgrids and (2) zero-emission fuel cell (FC)-based microgrids complemented by solar PV and battery energy storage. Spatially and temporally resolved emissions from the microgrids are input to an air quality model and assessed for health impacts. The results show that (1) a mass deployment of CGT-based or FC-based microgrids in both the near- and long-term has a relatively small impact on air quality, (2) the health impacts are nonetheless significant for CGT-based microgrids due to the large and dense population of the area, and (3) disadvantaged communities are disproportionately impacted with the deployment of CTG-based microgrids. For example, near-term deployment of CGT-based microgrids results in an increase in the incidence of premature mortality (1 to 5 incidences per month) and an increase of $33 to $56 million per month in health costs. Deploying zero-emission FC-based microgrids mitigates the adverse health impact, prevents several incidences of premature mortality, and results in saving of ~$36M per month rather than a cost per month of ~$50M.

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.

Contribution of fossil and biomass-derived secondary organic carbon to winter water-soluble organic aerosols in Delhi, India

Delhi, among the world's most polluted megacities, is a hotspot of particulate matter emissions, with high contribution from organic aerosol (OA), affecting health and climate in the entire northern India. While the primary organic aerosol (POA) sources can be effectively identified, an incomplete source apportionment of secondary organic aerosol (SOA) causes significant ambiguity in the management of air quality and the assessment of climate change. Present study uses positive matrix factorization analysis on the water-soluble organic aerosol (WSOA) data from the offline-aerosol mass spectrometry (AMS). It revealed POA as the dominant source of WSOA, with biomass-burning OA (31-34 %) and solid fuel combustion OA (∼21 %) being two major contributors. Here we use water-solubility fingerprints to track the SOA precursors, such as oxalates or organic nitrates, instead of identifying them based on their O:C ratio. Non-fossil precursors dominate in more oxidized oxygenated organic carbon (MO-OOC) (∼90 %), a proxy for aged secondary organic carbon (SOC), by coupling offline-AMS with 14C measurements. On the contrary, the oxidation of fossil fuel emissions produces a large quantity of fresh fossil SOC, which accounts for ∼75 % of less oxidized oxygenated organic carbon (LO-OOC). Our study reveals that apart from major POA contributions, large fractions of fossil (10-14 %) and biomass-derived SOA (23-30 %) contribute significantly to the total WSOA load, having impact on climate and air quality of the Delhi megacity. Our study reveals that large-scale unregulated biomass burning was not only found to dominate in POA but was also observed to be a significant contributor to SOA with implications on human health, highlighting the need for effective control strategies.

A review of the CAMx, CMAQ, WRF-Chem and NAQPMS models: Application, evaluation and uncertainty factors

With the gradual deepening of the research and governance of air pollution, chemical transport models (CTMs), especially the third-generation CTMs based on the "1 atm" theory, have been recognized as important tools for atmospheric environment research and air quality management. In this review article, we screened 2396 peer-reviewed manuscripts on the application of four pre-selected regional CTMs in the past five years. CAMx, CMAQ, WRF-Chem and NAQPMS models are well used in the simulation of atmospheric pollutants. In the simulation study of secondary pollutants such as O3, secondary organic aerosol (SOA), sulfates, nitrates, and ammonium (SNA), the CMAQ model has been widely applied. Secondly, model evaluation indicators are diverse, and the establishment of evaluation criteria has gone through the long-term efforts of predecessors. However, the model performance evaluation system still needs further specification. Furthermore, temporal-spatial resolution, emission inventory, meteorological field and atmospheric chemical mechanism are the main sources of uncertainty, and have certain interference with the simulation results. Among them, the inventory and mechanism are particularly important, and are also the top priorities in future simulation research.

Temperature-dependent composition of summertime PM2.5 in observations and model predictions across the Eastern U.S

Throughout the U.S., summertime fine particulate matter (PM2.5) exhibits a strong temperature (T) dependence. Reducing the PM2.5 enhancement with T could reduce the public health burden of PM2.5 now and in a warmer future. Atmospheric models are a critical tool for probing the processes and components driving observed behaviors. In this work, we describe how observed and modeled aerosol abundance and composition varies with T in the present-day Eastern U.S. with specific attention to the two major PM2.5 components: sulfate (SO4 2-) and organic carbon (OC). Observations in the Eastern U.S. show an average measured summertime PM2.5-T sensitivity of 0.67 μg/m3/K, with CMAQ v5.4 regional model predictions closely matching this value. Observed SO4 2- and OC also increase with T; however, the model has component-specific discrepancies with observations. Specifically, the model underestimates SO4 2- concentrations and their increase with T while overestimating OC concentrations and their increase with T. Here, we explore a series of model interventions aimed at correcting these deviations. We conclude that the PM2.5-T relationship is driven by inorganic and organic systems that are highly coupled, and it is possible to design model interventions to simultaneously address biases in PM2.5 component concentrations as well as their response to T.

Assessment of tropospheric ozone simulations in a regional chemical transport model using GEOS-Chem outputs as chemical boundary conditions

Regional chemical transport models (e.g., Community Multiscale Air Quality (CMAQ) Modeling System) are widely used to simulate the physical and chemical process of regional ozone (O3) pollution and its variation trend in recent years. However, chemical boundary condition (CBC) is an important input of these models and contributes to the model bias against observations. In this study, we develop a tool named GC2CMAQ that provides the CMAQ model with the CBCs from the GEOS-Chem simulation. Two experiments using different CBCs were conducted to evaluate their effect on seasonal O3 simulation in China. The Default experiment utilized the model-default static condition (the relatively clean atmosphere in the eastern United States), and the GC experiment employed the GEOS-Chem simulation results. Compared with the observation, the GC experiment has a much better performance in reproducing elevated O3 levels in the higher troposphere and lower stratosphere during different seasons. Near the earth's surface, the simulated concentrations of pollutants O3 (and PM2.5) in the GC experiment were also closer to the observation in April and July. The accuracy of simulation results in provinces close to the boundary was improved by approximately 20 %-30 % relative to the Default experiment. The CBCs provided by GEOS-Chem enabled a better simulation of stratosphere-troposphere O3 exchange in late spring and early summer, which then affected the pollutant concentration near surfaces through vertical transport. This finding was confirmed by a case study in southwestern Tibet on April 28, 2017, in which we quantified the contributions of different physical and chemical processes to O3 variations at different altitudes using the process analysis method. This study highlights the importance of using a reliable CBC for the regional chemical transport model to derive a better performance of O3 simulation.

Source apportionment of anthropogenic and biogenic organic aerosol over the Tokyo metropolitan area from forward and receptor models

Organic aerosol (OA) is a dominant component of PM2.5, and accurate knowledge of its sources is critical for identification of cost-effective measures to reduce PM2.5. For accurate source apportionment of OA, we conducted field measurements of organic tracers at three sites (one urban, one suburban, and one forest) in the Tokyo Metropolitan Area and numerical simulations of forward and receptor models. We estimated the source contributions of OA by calculating three receptor models (positive matrix factorization, chemical mass balance, and secondary organic aerosol (SOA)-tracer method) using the ambient concentrations, source profiles, and production yields of OA tracers. Sensitivity simulations of the forward model (chemical transport model) for precursor emissions and SOA formation pathways were conducted. Cross-validation between the receptor and forward models demonstrated that biogenic and anthropogenic SOA were better reproduced by the forward model with updated modules for emissions of biogenic volatile organic compounds (VOC) and for SOA formation from biogenic VOC and intermediate-volatility organic compounds than by the default setup. The source contributions estimated by the forward model generally agreed with those of the receptor models for the major OA sources: mobile sources, biomass combustion, biogenic SOA, and anthropogenic SOA. The contributions of anthropogenic SOA, which are the main focus of this study, were estimated by the forward and receptor models to have been between 9 % and 15 % in summer 2019. The observed percent modern carbon data indicate that the amounts of anthropogenic SOA produced during daytime have substantially declined from 2007 to 2019. This trend is consistent with the decreasing trend of anthropogenic VOC, suggesting that reduction of anthropogenic VOC has been effective in reducing anthropogenic SOA in the atmosphere.

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.

Predicting Atmospheric Water-Soluble Organic Mass Reversibly Partitioned to Aerosol Liquid Water in the Eastern United States

Water-soluble organic matter (WSOM) formed through aqueous processes contributes substantially to total atmospheric aerosol, however, the impact of water evaporation on particle concentrations is highly uncertain. Herein, we present a novel approach to predict the amount of evaporated organic mass induced by sample drying using multivariate polynomial regression and random forest (RF) machine learning models. The impact of particle drying on fine WSOM was monitored during three consecutive summers in Baltimore, MD (2015, 2016, and 2017). The amount of evaporated organic mass was dependent on relative humidity (RH), WSOM concentrations, isoprene concentrations, and NOx/isoprene ratios. Different models corresponding to each class were fitted (trained and tested) to data from the summers of 2015 and 2016 while model validation was performed using summer 2017 data. Using the coefficient of determination (R2) and the root-mean-square error (RMSE), it was concluded that an RF model with 100 decision trees had the best performance (R2 of 0.81) and the lowest normalized mean error (NME < 1%) leading to low model uncertainties. The relative feature importance for the RF model was calculated to be 0.55, 0.2, 0.15, and 0.1 for WSOM concentrations, RH levels, isoprene concentrations, and NOx/isoprene ratios, respectively. The machine learning model was thus used to predict summertime concentrations of evaporated organics in Yorkville, Georgia, and Centerville, Alabama in 2016 and 2013, respectively. Results presented herein have implications for measurements that rely on sample drying using a machine learning approach for the analysis and interpretation of atmospheric data sets to elucidate their complex behavior.

Model Framework for Predicting Semivolatile Organic Material Emissions Indoors from Organic Aerosol Measurements: Applications to HOMEChem Stir-Frying

Cooking activities emit myriad low-volatility, semivolatile, and highly volatile organic compounds that together form particles that can accumulate to large indoor concentrations. Absorptive partitioning thermodynamics governs the particle-phase organic aerosol concentration mainly via temperature and sorbing mass impacts. Cooking activities can increase the organic sorbing mass by 1-2 orders of magnitude, increasing particle-phase concentrations and affecting emission rate calculations. Although recent studies have begun to probe the volatility characteristics of indoor cooking particles, parametrizations of cooking particle mass emissions have largely neglected these thermodynamic considerations. Here, we present an improved thermodynamics-based model framework for estimating condensable organic material emission rates from a time series of observed concentrations, given that adequate measurements or assumptions can be made about the volatility of the emitted species. We demonstrate the performance of this methodology by applying data from stir-frying experiments performed during the House Observations of Microbial and Environmental Chemistry (HOMEChem) campaign to a two-zone box model representing the UTest House. Preliminary estimates of organic mass emitted on a per-stir-fry basis for three types of organic aerosol factors are presented. Our analysis highlights that using traditional nonvolatile particle models and emission characterizations for some organic aerosol emitting activities can incorrectly attribute concentration changes to emissions rather than thermodynamic effects.

Climate Penalty on Air Pollution Abated by Anthropogenic Emission Reductions in the United States

Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, how a warmer temperature deteriorates air quality, known as the "climate penalty" effect, remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here we examined the sensitivity of surface-level fine particulate matter (PM2.5) and ozone (O3) to summer temperature anomalies in the contiguous US and their decadal changes using high-resolution datasets generated by machine learning models. Our findings demonstrate that, in the eastern US, efficient emission control strategies have significantly reduced the climate penalty effects on PM2.5 and O3, lowering the associated population exposure. In contrast, summer and annual PM2.5 in the western US became more sensitive to temperature, highlighting the urgent need for the management and mitigation of worsening wildfires. Our results have important implications for air quality management and risk assessments of future climate change.

An Analysis of CMAQ Gas Phase Dry Deposition over North America Through Grid-Scale and Land-Use Specific Diagnostics in the Context of AQMEII4

The fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4) is conducting a diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality models over North America and Europe. In this study, we analyze annual AQMEII4 simulations performed with the Community Multiscale Air Quality Model (CMAQ) version 5.3.1 over North America. These simulations were configured with both the M3Dry and Surface Tiled Aerosol and Gas Exchange (STAGE) dry deposition schemes available in CMAQ. A comparison of observed and modeled concentrations and wet deposition fluxes shows that the AQMEII4 CMAQ simulations perform similarly to other contemporary regional-scale modeling studies. During summer, M3Dry has higher ozone (O3) deposition velocities (Vd) and lower mixing ratios than STAGE for much of the eastern U.S. while the reverse is the case over eastern Canada and along the West Coast. In contrast, during winter STAGE has higher O3 Vd and lower mixing ratios than M3Dry over most of the southern half of the modeling domain while the reverse is the case for much of the northern U.S. and southern Canada. Analysis of the diagnostic variables defined for the AQMEII4 project, i.e. grid-scale and land-use (LU) specific effective conductances and deposition fluxes for the major dry deposition pathways, reveals generally higher summertime stomatal and wintertime cuticular grid-scale effective conductances for M3Dry and generally higher soil grid-scale effective conductances (for both vegetated and bare soil) for STAGE in both summer and winter. On a domain-wide basis, the stomatal grid-scale effective conductances account for about half of the total O3 Vd during daytime hours in summer for both schemes. Employing LU-specific diagnostics, results show that daytime Vd varies by a factor of 2 between LU categories. Furthermore, M3Dry vs. STAGE differences are most pronounced for the stomatal and vegetated soil pathway for the forest LU categories, with M3Dry estimating larger effective conductances for the stomatal pathway and STAGE estimating larger effective conductances for the vegetated soil pathway for these LU categories. Annual domain total O3 deposition fluxes differ only slightly between M3Dry (74.4 Tg/year) and STAGE (76.2 Tg/yr), but pathway-specific fluxes to individual LU types can vary more substantially on both annual and seasonal scales which would affect estimates of O3 damages to sensitive vegetation. A comparison of two simulations differing only in their LU classification scheme shows that the differences in LU cause seasonal mean O3 mixing ratio differences on the order of 1 ppb across large portions of the domain, with the differences generally largest during summer and in areas characterized by the largest differences in the fractional coverages of the forest, planted/cultivated, and grassland LU categories. These differences are generally smaller than the M3Dry vs. STAGE differences outside the summer season but have a similar magnitude during summer. Results indicate that the deposition impacts of LU differences are caused both by differences in the fractional coverages and spatial distributions of different LU categories as well as the characterization of these categories through variables like surface roughness and vegetation fraction in look-up tables used in the land-surface model and deposition schemes. Overall, the analyses and results presented in this study illustrate how the diagnostic grid-scale and LU-specific dry deposition variables adopted for AQMEII4 can provide insights into similarities and differences between the CMAQ M3Dry and STAGE dry deposition schemes that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.

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.

Unexpected deterioration of O3 pollution in the South Coast Air Basin of California: The role of meteorology and emissions

Tropospheric ozone (O₃) pollution has long been a prominent environmental threat due to its adverse impacts on vulnerable populations and ecosystems. In recent years, an unexpected increase in O₃ levels over the South Coast Air Basin (SoCAB) of California has been observed despite reduced precursor emissions and the driving factors behind this abnormal condition remain unclear. In this work, we combine ambient measurements, satellite data, and air quality modeling to investigate O₃ and precursor emission trends and explore the impacts of meteorological variability and emission changes on O₃ over the SoCAB from 2012 to 2020. Changes in O₃ trends were characterized by declining O₃ in 2012-2015, and increasing O₃ afterwards with the most extreme O₃ exceedances in 2020. Basin-wide increases of MDA8 O₃ concentrations over warm season were depicted between 2012 and 2020, with the most significant enhancements (5-10 ppb) observed in San Bernardino County. Persistent heatwaves and weak ventilation on consecutive days were closely correlated with O₃ exceedances (r² above 0.6) over inland SoCAB. While decreasing trends in NO_x (-4.1%/yr) and VOC emissions (-1.8%/yr) inferred from emission inventory and satellites during 2012-2020 resulted in a slow transition for O₃ sensitivity from VOCs-limited to NO_x-limited, model simulations performed with fixed meteorology indicate that unfavorable meteorological conditions could largely offset regulation benefits, with meteorology anomaly-induced monthly O₃ changes reaching 20 ppb (May 2020) and the deterioration of O₃ pollution in 2016, 2017, and 2020 was largely attributed to unfavorable meteorological conditions. Nevertheless, anthropogenic emission changes may act as the dominant factor in governing O₃ variations across the SoCAB when net effects of meteorology are neutral (typically 2018). This work provides a comprehensive assessment of O₃ pollution and contributes valuable insights into understanding the long-term changes of O₃ and precursors in guiding future regulation efforts in the SoCAB.

Developed compositional source profile and estimated emissions of condensable particulate matter from coal-fired power plants: A case study of Yantai, China

The emission and environmental impact of condensable particulate matter (CPM) from coal-fired power plants (CFPPs) are of increasing concern worldwide. Many studies on the characteristics of CPM emission have been conducted in China, but its source profile remains unclear, and its emission inventory remains high uncertainty. In this work, the latest measurements reported in the latest 33 studies for CPM inorganic and organic species emitted from CFPPs in China were summarized, and then a compositional source profile of CPM for CFPPs was developed for the first time in China, which involved 10 inorganic species and 71 organic species. In addition, the CPM emission inventory of CFPPs in Yantai of China was developed based on surveyed activity data, continuous emission monitoring system (CEMS), and the latest measurement data. The results show that: (1) Inorganic species accounted for 77.64 % of CPM emitted from CFPPs in Yantai, among which SO₄^2- had the highest content, accounting for 23.74 % of CPM, followed by Cl^-, accounting for 11.95 %; (2) Organic matter accounted for 22.36 % of CPM, among which alkanes accounted for the largest proportion of organic fraction (72.7 %); (3) Emission concentration method (EC) and CEMS-based emission ratio method (ER_FPM,CEMS) were recommended to estimate CPM emissions for CFPPs; (4) The estimated CPM emission inventories of Yantai CFPPs in 2020 by the EC method and the ER_FPM,CEMS method were 1231 tons and 929 tons, respectively, with uncertainties of -34 % ∼ 33 % and -27 % ∼ 57 %, respectively; (5) CPM emissions were mainly distributed in the northern coastal areas of Yantai. This developed CPM source profile and emission inventory can provide basic data for assessing the impacts of CPM on air quality and health. In addition, this study can provide an important methodology for developing CPM emission inventories and CPM emission source profiles for stationary combustion sources in other regions.

Drivers of High Concentrations of Secondary Organic Aerosols in Northern China during the COVID-19 Lockdowns

During the COVID-19 lockdown in early 2020, observations in Beijing indicate that secondary organic aerosol (SOA) concentrations increased despite substantial emission reduction, but the reasons are not fully explained. Here, we integrate the two-dimensional volatility basis set into a state-of-the-art chemical transport model, which unprecedentedly reproduces organic aerosol (OA) components resolved by the positive matrix factorization based on aerosol mass spectrometer observations. The model shows that, for Beijing, the emission reduction during the lockdown lowered primary organic aerosol (POA)/SOA concentrations by 50%/18%, while deteriorated meteorological conditions increased them by 30%/119%, resulting in a net decrease in the POA concentration and a net increase in the SOA concentration. Emission reduction and meteorological changes both led to an increased OH concentration, which accounts for their distinct effects on POA and SOA. SOA from anthropogenic volatile organic compounds and organics with lower volatility contributed 28 and 62%, respectively, to the net SOA increase. Different from Beijing, the SOA concentration decreased in southern Hebei during the lockdown because of more favorable meteorology. Our findings confirm the effectiveness of organic emission reductions and meanwhile reveal the challenge in controlling SOA pollution that calls for large organic precursor emission reductions to rival the adverse impact of OH increase.

AMORE-Isoprene v1.0: a new reduced mechanism for gas-phase isoprene oxidation

Gas-phase oxidation of isoprene by ozone (O3) and the hydroxyl (OH) and nitrate (NO3) radicals significantly impacts tropospheric oxidant levels and secondary organic aerosol formation. The most comprehensive and up-to-date chemical mechanism for isoprene oxidation consists of several hundred species and over 800 reactions. Therefore, the computational expense of including the entire mechanism in large-scale atmospheric chemical transport models is usually prohibitive, and most models employ reduced isoprene mechanisms ranging in size from ~ 10 to ~ 200 species. We have developed a new reduced isoprene oxidation mechanism using a directed-graph path-based automated model reduction approach, with minimal manual adjustment of the output mechanism. The approach takes as inputs a full isoprene oxidation mechanism, the environmental parameter space, and a list of priority species which are protected from elimination during the reduction process. Our reduced mechanism, AMORE-Isoprene (where AMORE stands for Automated Model Reduction), consists of 12 species which are unique to the isoprene mechanism as well as 22 reactions. We demonstrate its performance in a box model in comparison with experimental data from the literature and other current isoprene oxidation mechanisms. AMORE-Isoprene's performance with respect to predicting the time evolution of isoprene oxidation products, including isoprene epoxydiols (IEPOX) and formaldehyde, is favorable compared with other similarly sized mechanisms. When AMORE-Isoprene is included in the Community Regional Atmospheric Chemistry Multiphase Mechanism 1.0 (CRACMM1AMORE) in the Community Multiscale Air Quality Model (CMAQ, v5.3.3), O3 and formaldehyde agreement with Environmental Protection Agency (EPA) Air Quality System observations is improved. O3 bias is reduced by 3.4ppb under daytime conditions for O3 concentrations over 50 ppb. Formaldehyde bias is reduced by 0.26 ppb on average for all formaldehyde measurements compared with the base CRACMM1. There was no significant change in computation time between CRACMM1AMORE and the base CRACMM. AMORE-Isoprene shows a 35 % improvement in agreement between simulated IEPOX concentrations and chamber data over the base CRACMM1 mechanism when compared in the Framework for 0-D Atmospheric Modeling (F0AM) box model framework. This work demonstrates a new highly reduced isoprene mechanism and shows the potential value of automated model reduction for complex reaction systems.

Size Dependence of Liquid-Liquid Phase Separation by in Situ Study of Flowing Submicron Aerosol Particles

Liquid-liquid phase separation (LLPS) of atmospheric particles impacts a range of atmospheric processes. Driven by thermodynamics, LLPS occurs in mixed organic-inorganic particles when high inorganic salt concentrations exclude organic compounds, which develop into a separate phase. The effect of particle size on the thermodynamic and kinetic drivers of LLPS, however, remains incompletely understood. Here, the size dependence was studied for the separation relative humidity (SRH) of LLPS. Submicron organic-inorganic aerosol particles of ammonium sulfate mixed with 1,2,6-hexanetriol and polyethylene glycol (PEG) were studied. In a flow configuration, upstream size selection was coupled to a downstream fluorescence aerosol flow tube (F-AFT) at 293 ± 1 K. For both mixed particle types, the SRH values for submicron particle diameters of 260-410 nm agreed with previous measurements reported in the literature for supermicron particles. For smaller particles, the SRH values decreased by approximately 5% RH for diameters of 130-260 nm for PEG-sulfate particles and of 70-190 nm for hexanetriol-sulfate particles. From these observations, the nucleation rate in the hexanetriol-sulfate system was constrained, implying an activation barrier to nucleation of +1.4 to +2.0 × 10^-19 J at 70% RH and 293 K. Quantifying the activation barrier is an approach for predicting size-dependent LLPS in the atmosphere.

Exploring the effects of land use and land cover changes on meteorology and air quality over Sichuan Basin, southwestern China

Accurate characterization of land use and land cover changes (LULCC) is essential for numerical models to capture LULCC-induced effects on regional meteorology and air quality, while outdated LULC dataset largely limits model capability in reproducing land surface parameters, particularly for complex terrain. In this study, we incorporate land cover data from MODIS in 2019 into the Weather Research and Forecasting (WRF) model to simulate the impacts of LULC on meteorological parameters over the Sichuan Basin (SCB). Further, we conduct Community Multiscale Air Quality (CMAQ) simulations with WRF default LULC and MODIS 2019 to probe the effects on regional air quality. Despite consistency found between meteorological observations and WRF-CMAQ simulations, the default WRF land cover data does not accurately capture rapid urbanization over time compared with MODIS. Modeling results indicate that magnitude changes trigged by LULCC are highly varied across SCB and the impacts of LULCC are more pronounced over extended metropolitan areas due to alteration by urbanization, featured by elevating 2-m temperature up to 2°C and increased planetary boundary layer height (PBLH) up to 400 m. For air quality implications, it is found that LULCC leads to basin-wide O3 enhancements with maximum reaching 21.6 μg/m3 and 57.2 μg/m3 in the daytime and nighttime, respectively, which is mainly attributed to weakening NOx titration effects at night. This work contributes modeling insights into quantitative assessment for impacts of LULCC on regional meteorology and air quality which pinpoints optimization of the meteorology-air quality model.

Striking impacts of biomass burning on PM2.5 concentrations in Northeast China through the emission inventory improvement

Biomass burning exerts substantial influences on air quality and climate, which in turn to further aggravate air quality. The biomass burning emissions in particular of the agricultural burning may suffer large uncertainties which limits the understanding of their impact on air quality. Based on an improved emission inventory of the Visible Infrared Imaging Radiometer Suite (VIIRS) relative to commonly used Global Fire Emissions Database (GFED), we thoroughly evaluate the impact of biomass burning on air quality and climate during the episodes of November 2017 in Northeast China which is rich in agriculture burning. The results first indicate substantial underestimates in simulated PM_2.5 concentrations without the inclusion of biomass burning emission inventory, based on a regional air quality model Weather Research and Forecasting model and Community Multiscale Air Quality model (WRF-CMAQ). The addition of biomass burning emissions from GFED then reduces the bias to a certain extent, which is further reduced by replacing the agricultural fires data in GFED with VIIRS. Numerical sensitivity experiments show that based on the improved emission inventory, the contribution of biomass burning emissions to PM_2.5 concentrations in Northeast China reaches 32%, contrasting to 15% based on GFED, during the episode from November 1 to 7, 2017. Aerosol direct radiative effects from biomass burning are finally elucidated, which not only reduce downward surface shortwave radiation and planetary boundary layer height, but also affect the vertical distribution of air temperature, wind speed and relative humidity, favorable to the accumulation of PM_2.5. During November 1-7, 2017, the mean daily PM_2.5 enhancement due to aerosol radiative effects from VIIRS_G is 16 μg m^-3, a few times higher than that of 2.8 μg m^-3 from GFED. The study stresses the critical role of biomass burning, particularly of small fires easily missed in the traditional low-resolution satellite products, on air quality.

Organic Peroxides in Aerosol: Key Reactive Intermediates for Multiphase Processes in the Atmosphere

Organic peroxides (POs) are organic molecules with one or more peroxide (-O-O-) functional groups. POs are commonly regarded as chemically labile termination products from gas-phase radical chemistry and therefore serve as temporary reservoirs for oxidative radicals (HOx and ROx) in the atmosphere. Owing to their ubiquity, active gas-particle partitioning behavior, and reactivity, POs are key reactive intermediates in atmospheric multiphase processes determining the life cycle (formation, growth, and aging), climate, and health impacts of aerosol. However, there remain substantial gaps in the origin, molecular diversity, and fate of POs due to their complex nature and dynamic behavior. Here, we summarize the current understanding on atmospheric POs, with a focus on their identification and quantification, state-of-the-art analytical developments, molecular-level formation mechanisms, multiphase chemical transformation pathways, as well as environmental and health impacts. We find that interactions with SO2 and transition metal ions are generally the fast PO transformation pathways in atmospheric liquid water, with lifetimes estimated to be minutes to hours, while hydrolysis is particularly important for α-substituted hydroperoxides. Meanwhile, photolysis and thermolysis are likely minor sinks for POs. These multiphase PO transformation pathways are distinctly different from their gas-phase fates, such as photolysis and reaction with OH radicals, which highlights the need to understand the multiphase partitioning of POs. By summarizing the current advances and remaining challenges for the investigation of POs, we propose future research priorities regarding their origin, fate, and impacts in the atmosphere.

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).

Assessment of summertime ozone formation in the Sichuan Basin, southwestern China

The alarming increase of ambient ozone (O3) levels across China raises an urgent need in understanding underlying mechanisms of regional O3 events for highly urbanized city clusters. Sichuan Basin (SCB) situated in southwestern China has experienced severe O3 pollution at times in summer from 2013 to 2020. Here, we use the WRF-CMAQ model with the Integrated Source Apportionment Method (ISAM) to investigate the evolution mechanism and conduct source attribution of an extreme O3 episode in the SCB from June 1 to 8, 2019. This typical summer O3 episode is associated with the synoptic-driven meteorological phenomenon and transboundary flow of O3 and precursors across the SCB. Weak ventilation in combination with stagnant conditions triggered the basin-wide high O3 concentrations and enhanced BVOC emissions substantially contribute up to 57.9 μg/m3 MDA8 O3. CMAQ-ISAM indicates that precursor emissions from industrial and transportation have the largest impacts on elevating ambient O3 concentrations, while power plant emissions exhibit insignificant contributions to basin-wide O3 episodes. These results improve the understanding of the summertime O3 episode in the SCB and contribute insights into designing O3 mitigation policy.

Decarbonization will lead to more equitable air quality in California

Air quality associated public health co-benefit may emerge from climate and energy policies aimed at reducing greenhouse gas (GHG) emissions. However, the distribution of these co-benefits has not been carefully studied, despite the opportunity to tailor mitigation efforts so they achieve maximum benefits within socially and economically disadvantaged communities (DACs). Here, we quantify such health co-benefits from different long-term, low-carbon scenarios in California and their distribution in the context of social vulnerability. The magnitude and distribution of health benefits, including within impacted communities, is found to varies among scenarios which reduce economy wide GHG emissions by 80% in 2050 depending on the technology- and fuel-switching decisions in individual end-use sectors. The building electrification focused decarbonization strategy achieves ~15% greater total health benefits than the truck electrification focused strategy which uses renewable fuels to meet building demands. Conversely, the enhanced electrification of the truck sector is shown to benefit DACs more effectively. Such tradeoffs highlight the importance of considering environmental justice implications in the development of climate mitigation planning.

Air quality is found to be more equitable through two salient decarbonization pathways for California in 2050 with the relative justice of decarbonization scenarios quantified at the neighborhood level and the tradeoffs between pathways evaluated.

The C5-Alkene Triol Conundrum: Structural Characterization and Quantitation of Isoprene-Derived C5H10O3 Reactive Uptake Products

2-Methyltetrols and C5H10O3 compounds, referred to as "C5-alkene triols," are chemical tracers used to estimate isoprene-derived epoxydiol (IEPOX) contributions to atmospheric PM2.5. For nearly two decades, "C5-alkene triol" molecular structures and PM2.5 mass contributions remain uncertain, and their origin as analytical artifacts is unclear. Thus, we synthesized C5H10O3 reactive uptake product candidates (3-methyltetrahydrofuran-2,4-diol and 3-methylenebutane-1,2,4-triol) and investigated their behavior under conventional gas chromatography/electron impact-mass spectrometry (GC/EI-MS) with prior trimethylsilylation and, in parallel, by non-destructive hydrophilic-interaction liquid chromatography coupled with electrospray ionization interfaced to high-resolution quadrupole-time-of-flight mass spectrometry (HILIC/ESI-HR-QTOFMS). Using novel synthetic standards, we confirmed their presence in laboratory-generated IEPOX SOA. In atmospheric SOA, both synthetic targets were confirmed and quantified by GC/EI-MS. Based on HILIC/ESI-HR-QTOFMS analysis of chamber-generated SOA, we estimate ~10% and ~50% of GC/EI-MS measured 3-methylenebutane-1,2,4-triol and 3-methyltetrahydrofuran-2,4-diols, respectively, are not analytical artifacts, but arise from acid-driven particle-phase IEPOX isomerization. Significant quantities were also detected in impingers downstream from filters, demonstrating "C5-alkene triols" are semivolatile. Using chamber-derived yields, we tentatively estimate that atmospheric 3-methyltetrahydrofuran-2,4-diols and 3-methylenebutane-1,2,4-triol could contribute 8.7 Tg C yr-1. Therefore, to resolve their significance on air quality and climate, future studies should examine their gas-to-particle partitioning, yields, and atmospheric oxidation chemistry under varying environmental conditions.

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.

Modeling Biogenic Volatile Organic Compounds Emissions and Subsequent Impacts on Ozone Air Quality in the Sichuan Basin, Southwestern China

Biogenic volatile organic compounds (BVOCs) impact atmospheric oxidation capacity and regional air quality through various biogeochemistry processes. Accurate estimation of BVOC emissions is crucial for modeling the fate and transport of air pollutants in chemical transport models. Previous modeling characterizes the spatial variability of BVOCs while estimated BVOC emissions show large uncertainties, and the impacts of BVOC emissions on ozone (O3) air quality are not well understood. In this study, we estimate the BVOC emissions by model of emissions of gases and aerosols from nature (MEGAN) v2.1 and MEGAN v3.1 over the Sichuan Basin (SCB) situated in southwestern China for 2017. Further, the critical role of BVOC emissions on regional O3 pollution is illustrated with a CMAQ modeled O3 episode in summer 2017. Annual BVOC emissions over the SCB in 2017 are estimated to be 1.8 × 106 tons with isoprene emissions as high as 7.3 × 105 tons. Abundant BVOC emissions are depicted over the southern and southeastern SCB, in contrast to the relatively low emissions of BVOC over the Chengdu Plain and northeastern SCB. CMAQ simulations depict a strong influence of BVOC on ambient O3 formation over densely forested regions including southern SCB and Chongqing city, accounting for 10% of daily maximum hourly O3 concentration (DM1h O3) and 6% of daily maximum 8-h average O3 (MDA8h O3) concentrations in July 2017. Over the severe O3 episode in summer 2017, sensitivity experiments indicate that enhanced BVOC emissions contribute substantially to basin-wide O3 concentrations and elevate peak O3 levels by 36.5 and 31.2 μg/m3 for the southern SCB and Chengdu Plain, respectively. This work identifies robustly important effects of BVOC emissions on O3 exceedance events over the SCB and contributes insight into pursuing an O3 abatement strategy with full consideration of potential contributions from BVOC emissions.

Impact of Urbanization on Meteorology and Air Quality in Chengdu, a Basin City of Southwestern China

Rapid urbanization has the potential to fundamentally perturb energy budget and alter urban air quality. While it is clear that urban meteorological parameters are sensitive to urbanization-induced changes in landscapes, a gap exists in our knowledge about how changes in land use and land cover affect the dynamics of urban air quality. Herein, we simulated a severe O3 episode (10–16 July 2017) and a highly polluted PM2.5 episode (25–30 December 2017) and assessed the changes of meteorological phenomenon and evolution of air pollutants induced by urbanization. We found that the urban expansion area (i.e., land use transition from natural to urban surfaces between 2000 and 2017, UEA) has a significant increase in nocturnal 2-m temperature (T2) with maximum values reaching 3 and 4°C in summer and winter, respectively. In contrast, UEA experienced cooling in the daytime with stronger reductions of T2 in winter than in summer. The T2 variability is primarily attributed to the intense thermal inertia and high heat capacity of the urban canopy and the shadowing effect caused by urbanization. Owing to increased surface roughness and decreased surface albedo as well as shadowing effects, the ventilation index (VI) of UEA increased up to 1,200 m2/s in winter while decreased up to 950 m2/s in summer. Changes in meteorological phenomenon alter physical and chemical processes associated with variations in PM2.5 and O3 concentrations. Urbanization leads to enhanced vertical advection process and weakened aerosol production, subsequently causing PM2.5 levels to decrease by 33.2 μg/m3 during the day and 4.6 μg/m3 at night, respectively. Meanwhile, O3 levels increased by 61.4 μg/m3 at 20:00 due to the reduction of horizontal advection induced by urbanization, while O3 concentrations changed insignificantly at other times. This work provides valuable insights into the effects of urbanization on urban meteorology and air quality over typical megacities, which support informed decision-making for urban heat and air pollution mitigation.

Drivers of 2013-2020 ozone trends in the Sichuan Basin, China: Impacts of meteorology and precursor emission changes

The Sichuan Basin (SCB) of China is known for excessive ozone (O₃) pollution owing to high anthropogenic emissions combined with terrain-induced poor ventilation and weak wind fields against the surrounding mountains. While O₃ pollution has emerged as a prominent concern in southwestern China yet variations in O₃ levels during 2013-2020 are still unclear and the dominant factor in explaining the long-term O₃ trend throughout the SCB remains elusive due to uncertainties in emission inventory and variability associated with meteorological conditions. Here, we use extensive basin-wide ambient measurements to examine the spatial pattern and trend of O₃ and leverage OMI and TROPOMI satellites in conjunction with MEIC emission inventory to track emission changes. Sensitivity simulations are conducted by using WRF-CMAQ model to investigate the impacts of meteorological variability and emission changes on O₃ changes over 2013-2020. O₃ concentrations exhibit obvious interannual increases during 2013-2019 and a slight decrease in 2020. Both decreases in the MEIC emission inventory (-2.9% yr^-1) and OMI NO₂ column density (-3.1% yr^-1) reflects the declining trend in NO_x emissions over 2013-2020, while anthropogenic VOCs were not adequately regulated during 2013-2017, which explained the majority of deteriorated O₃ pollution from 2013 to 2017. Furthermore, attribution analysis based on CMAQ simulations indicate that the unexpected aggravated O₃ levels in 2019 is not only modulated by disproportional reductions in VOCs and NO_x emissions, but also associated with unfavorable meteorological conditions featured by profound heatwaves and frequent stagnant conditions. In 2020, the abnormal meteorological conditions in May leads to substantial increase of O₃ by 26.8 μg m^-3 as compared to May 2019, while the considerable enhancement was fully offset by low O₃ levels over the whole period which attributes to substantial emission reductions. This study reveals the long-term trend of O₃ levels and precursor emissions and highlights the effects of meteorological variability and emission changes on O₃ pollution over the SCB, with strong implications for designing effective O₃ control measures.

Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a "state-of-the-science" CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM_2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM_2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

Gas-to-Aerosol Phase Partitioning of Atmospheric Water-Soluble Organic Compounds at a Rural Site in China: An Enhancing Effect of NH3 on SOA Formation

Partitioning gaseous water-soluble organic compounds (WSOC) to the aerosol phase is a major formation pathway of atmospheric secondary organic aerosols (SOA). However, the fundamental mechanism of the WSOC-partitioning process remains elusive. By simultaneous measurements of both gas-phase WSOC (WSOCg) and aerosol-phase WSOC (WSOCp) and formic and acetic acids at a rural site in the Yangtze River Delta (YRD) region of China during winter 2019, we showed that WSOCg during the campaign dominantly partitioned to the organic phase in the dry period (relative humidity (RH) < 80%) but to aerosol liquid water (ALW) in the humid period (RH > 80%), suggesting two distinct SOA formation processes in the region. In the dry period, temperature was the driving factor for the uptake of WSOCg. In contrast, in the humid period, the factors controlling WSOCg absorption were ALW content and pH, both of which were significantly elevated by NH₃ through the formation of NH₄NO₃ and neutralization with organic acids. Additionally, we found that the relative abundances of WSOCp and NH₄NO₃ showed a strong linear correlation throughout China with a spatial distribution consistent with that of NH₃, further indicating a key role of NH₃ in WSOCp formation at a national scale. Since WSOCp constitutes the major part of SOA, such a promoting effect of NH₃ on SOA production by elevating ALW formation and WSOCg partitioning suggests that emission control of NH₃ is necessary for mitigating haze pollution, especially SOA, in China.

Organic Coating Reduces Hygroscopic Growth of Phase-Separated Aerosol Particles

A large fraction of secondary aerosol particles are liquid-liquid phase-separated with an organic shell and an inorganic core. This has the potential to regulate the hygroscopicity of such particles, with significant implications for their optical properties, reactivity, and lifetime. However, it is unclear how this phase separation affects the hygroscopic growth of the particles. Here, we showed a large variation in hygroscopic growth (e.g., 1.14-1.32 under a relative humidity (RH) of 90%) of particles from the forest and urban atmosphere, which had different average core-shell ratios. For this reason, a controlled laboratory experiment further quantifies the impact of the organic shell on particle growth with different RH values. Laboratory experiments demonstrated that (NH₄)₂SO₄ particles with thicker secondary organic shells have a lower growth factor at an RH below 94%. Organic shells started to deliquesce first (RH > 50%) and the phase changes of sulfate cores from solid to liquid took place at an RH higher than 80% as deliquescence relative humidity of pure (NH₄)₂SO₄. Our study provides the first direct evidence on an individual particle basis that hygroscopic growth behavior of phase-separated particles is dependent on the thickness of organic shells, highlighting the importance of organic coating in water uptake and possible heterogeneous reactions of the phase-separated particles.

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.

Modeling secondary organic aerosol formation from volatile chemical products

Volatile chemical products (VCPs) are commonly-used consumer and industrial items that are an important source of anthropogenic emissions. Organic compounds from VCPs evaporate on atmospherically relevant time scales and include many species that are secondary organic aerosol (SOA) precursors. However, the chemistry leading to SOA, particularly that of intermediate volatility organic compounds (IVOCs), has not been fully represented in regional-scale models such as the Community Multiscale Air Quality (CMAQ) model, which tend to underpredict SOA concentrations in urban areas. Here we develop a model to represent SOA formation from VCP emissions. The model incorporates a new VCP emissions inventory and employs three new classes of emissions: siloxanes, oxygenated IVOCs, and nonoxygenated IVOCs. VCPs are estimated to produce 1.67 μg m^-3 of noontime SOA, doubling the current model predictions and reducing the SOA mass concentration bias from -75% to -58% when compared to observations in Los Angeles in 2010. While oxygenated and nonoxygenated intermediate volatility VCP species are emitted in similar quantities, SOA formation is dominated by the nonoxygenated IVOCs. Formaldehyde and SOA show similar relationships to temperature and bias signatures indicating common sources and/or chemistry. This work suggests that VCPs contribute up to half of anthropogenic SOA in Los Angeles and models must better represent SOA precursors from VCPs to predict the urban enhancement of SOA.

GPS-ZTD data assimilation and its impact on wintertime haze prediction over North China Plain using WRF 3DVAR and CMAQ modeling system

Severe haze frequently hits the North China Plain (NCP), especially in winter during recent years. Meteorological factors affect aerosol formation and its optical properties, and accurate meteorological fields are imperative for accurate aerosol simulations. The impacts of Global Positioning System Zenith Total Delay (GPS-ZTD) data assimilation on meteorology and aerosol simulations were evaluated in this study using the WRF-CMAQ (the Weather Research and Forecasting model and Community Multiscale Air Quality) modelling system over the NCP during 01-31 December 2019. After bias correction, GSP-ZTD data were assimilated into the WRF model using the 3DVAR technique. Two sensitivity tests (CTR and ZTD) were conducted. The WRF model had generally acceptable performance for surface and upper air meteorological variables, PM_2.5 and visibility. From the aspect of BIAS, STDE, RMSE, and R, the assimilation of ZTD data improved the underestimation of ground relative humidity (RH). The improvement was more pronounced in the first 18 forecast hours. The mean RH BIAS decreased by 8%. Surface pressure was also improved in ZTD. The influence of ZTD data assimilation on ground temperature and wind tended to be neutral. The BIAS of ZTD decreased by 3% after data assimilation while STED or RMSE increased slightly. After ZTD data assimilation, the PM_2.5 underestimation decreased by 3.4% over NCP. And station mean BIAS or RMSE of PM_2.5 decreased at more than 70% stations. After ZTD data assimilation, the visibility overestimation was reduced by 2.5%. And more than 81% stations over had lower visibility BIAS or RMSE. Station mean PM_2.5 mass concentration increased by 1.5% in ZTD. The primary aerosol species increased by approximately 1%, and most secondary aerosol species increased by greater than 2% affected by both aerosol physical and chemical process. Although the improvement of PM_2.5 seems marginal from the perspective of regional or temporal average, the contribution of ZTD data assimilation on specific pollution episodes at specific stations can be great. The improvement of PM_2.5 troughs was in the range of 1-5 μg/m³, while the overestimation of PM_2.5 peaks was reduced by few up to dozens μg/m³. This will contribute to the extreme value prediction during pollution episode.

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, elemental carbon, tropospheric O₃ residual, and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀ that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO _x ), volatile organic compounds (VOCs), and PM_2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, elemental carbon, tropospheric O₃ residual, and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀ that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO _x ), volatile organic compounds (VOCs), and PM_2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

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.

Diverse response of surface ozone to COVID-19 lockdown in China

Ozone (O3) is a key oxidant and pollutant in the lower atmosphere. Significant increases in surface O3 have been reported in many cities during the COVID-19 lockdown. Here we conduct comprehensive observation and modeling analyses of surface O3 across China for periods before and during the lockdown. We find that daytime O3 decreased in the subtropical south, in contrast to increases in most other regions. Meteorological changes and emission reductions both contributed to the O3 changes, with a larger impact from the former especially in central China. The plunge in nitrogen oxide (NOx) emission contributed to O3 increases in populated regions, whereas the reduction in volatile organic compounds (VOC) contributed to O3 decreases across the country. Due to a decreasing level of NOx saturation from north to south, the emission reduction in NOx (46%) and VOC (32%) contributed to net O3 increases in north China; the opposite effects of NOx decrease (49%) and VOC decrease (24%) balanced out in central China, whereas the comparable decreases (45-55%) in these two precursors contributed to net O3 declines in south China. Our study highlights the complex dependence of O3 on its precursors and the importance of meteorology in the short-term O3 variability.

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.

Study on the variation of air pollutant concentration and its formation mechanism during the COVID-19 period in Wuhan

To prevent the spread of COVID-19 (2019 novel coronavirus), from January 23 to April 8 in 2020, the highest Class 1 Response was ordered in Wuhan, requiring all residents to stay at home unless absolutely necessary. This action was implemented to cut down all unnecessary human activities, including industry, agriculture and transportation. Reducing these activities to a very low level during these hard times meant that some unprecedented naturally occurring measures of controlling emissions were executed. Ironically, however, after these measures were implemented, ozone levels increased by 43.9%. Also worthy of note, PM_2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8th Feb. to 8th Apr. in 2020 with the same periods in 2019. Utilizing CMAQ (The Community Multiscale Air Quality modeling system), this article investigated the reason for these phenomena based on four sets of numerical simulations with different schemes of emission reduction. Comparing the four sets of simulations with observation, it was deduced that the emissions should decrease to approximately 20% from the typical industrial output, and 10% from agriculture and transportation sources, attributed to the COVID-19 lockdown in Wuhan. More importantly, through the CMAQ process analysis, this study quantitatively analyzed differences of the physical and chemical processes that were affected by the COVID-19 lockdown. It then examined the differences of the COVID-19 lockdown impact and determined the physical and chemical processes between when the pollution increased and decreased, determining the most affected period of the day. As a result, this paper found that (1) PM_2.5 decreased mainly due to the reduction of emission and the contrary contribution of aerosol processes. The North-East wind was also in favor of the decreasing of PM_2.5. (2) O₃ increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O₃ pollution higher at about 4 p.m.-7 p.m. of the day, while increasing the concentration of O₃ at night during the COVID-19 lockdown in Wuhan. The higher O₃ concentration in the North-East of the main urban area also contributed to the increasing of O₃ with unfavorable wind direction.

Study on the variation of air pollutant concentration and its formation mechanism during the COVID-19 period in Wuhan

To prevent the spread of COVID-19 (2019 novel coronavirus), from January 23 to April 8 in 2020, the highest Class 1 Response was ordered in Wuhan, requiring all residents to stay at home unless absolutely necessary. This action was implemented to cut down all unnecessary human activities, including industry, agriculture and transportation. Reducing these activities to a very low level during these hard times meant that some unprecedented naturally occurring measures of controlling emissions were executed. Ironically, however, after these measures were implemented, ozone levels increased by 43.9%. Also worthy of note, PM_2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8th Feb. to 8th Apr. in 2020 with the same periods in 2019. Utilizing CMAQ (The Community Multiscale Air Quality modeling system), this article investigated the reason for these phenomena based on four sets of numerical simulations with different schemes of emission reduction. Comparing the four sets of simulations with observation, it was deduced that the emissions should decrease to approximately 20% from the typical industrial output, and 10% from agriculture and transportation sources, attributed to the COVID-19 lockdown in Wuhan. More importantly, through the CMAQ process analysis, this study quantitatively analyzed differences of the physical and chemical processes that were affected by the COVID-19 lockdown. It then examined the differences of the COVID-19 lockdown impact and determined the physical and chemical processes between when the pollution increased and decreased, determining the most affected period of the day. As a result, this paper found that (1) PM_2.5 decreased mainly due to the reduction of emission and the contrary contribution of aerosol processes. The North-East wind was also in favor of the decreasing of PM_2.5. (2) O₃ increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O₃ pollution higher at about 4 p.m.-7 p.m. of the day, while increasing the concentration of O₃ at night during the COVID-19 lockdown in Wuhan. The higher O₃ concentration in the North-East of the main urban area also contributed to the increasing of O₃ with unfavorable wind direction.