To better characterize how increasing numerical accuracy translates to improvements in large-scale forcing’s over the Northern Hemisphere, two CMAQ simulations with differing grid spacing (108 km versus 36 km) will be compared for the year 2019 using the EPA’s Air QUAlity TimE Series (EQUATES; US (Foley et al. Data Brief 47:109022) modelling platform. When model simulations are evaluated against various surface, aloft, and remote sensing observations, it is found that both simulations produce similar large-scale forcing’s. However, in regions of complex terrain or weather (e.g., dust storms, intrusion events, convection). Some localized differences are seen. But the gains in increasing numerical accuracy must be weighted against the additional computational resources required to simulate with finer grid spacing (e.g., the 36 km simulation required significantly more computational resources than the 108 km simulation). This indicates that the gains in representing large-scale air pollution forcing through improvements in numerical accuracy via grid spacing improvements may not outweigh the computational cost.

For more than a decade the Environmental Protection Agency’s (EPA) flagship chemical transport model, the Community Multiscale Air Quality (CMAQ) model, has relied on meteorological input from the Weather Research and Forecasting (WRF) model that is maintained by the National Center for Atmospheric Research (NCAR). The EPA has recently been developing support for coupling CMAQ with NCAR’s new meteorological option, the Model for Prediction Across Scales (MPAS). MPAS provides new and unique scientific capabilities and workflow advantages that benefit its application for air quality modeling. Here we document our most recent configuration of MPAS with CMAQ (MPAS-CMAQ) and present results from multi-year simulations. Surface ozone and fine particles (PM2.5) simulated by MPAS-CMAQ compares reasonably well with observations. July surface ozone shares similar patterns and magnitudes with other similar modeling products. Comparison with ozonesondes shows that MPAS-CMAQ suffers from a low ozone bias in the free troposphere. We share a case study on emissions of nitrogen oxides (NOx) from lightning to demonstrate the extended capabilities of MPAS-CMAQ for development and testing of CMAQ features.

In this study, we present the first evaluation of grid model results of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII-4). The focus of this phase is deposition, a topic long neglected by the atmospheric modelling community in intercomparison studies that this time has been tackled with a detail that is unparalleled in regional scale modelling. Four modeling systems were run in different configurations using common anthropogenic, biomass burning, and lightning emissions, for the years 2010 and 2016 for North America (NA), and 2009 and 2010 for Europe (EU). The ensemble members used their own driving meteorology and biogenic emissions data in these simulations. Using a large database of monitoring data matched to model output, this study covers the operational evaluation of modelled concentration fields, which is of paramount importance prior to the analysis of the deposition. The PM10 concentrations were generally underestimated in both continents, yielding average normalized RMSE 0.5 in EU and 0.6 in NA. Model performance was better for the overestimated O3 concentrations, with an average normalized RMSE of 0.2. Work in progress focuses on an in-depth attribution of the errors (e.g. missing emission sources, mis-represented processes, meteorological biases) with the ultimate goal of assessing the impact these sources of error on the deposition schemes and calculated deposition fluxes.

A substantial portion of tropospheric O 3 dry deposition occurs after diffusion of O 3 through plant stomata. Simulating stomatal uptake of O 3 in 3D atmospheric chemistry models is important in the face of increasing drought induced declines in stomatal conductance and enhanced ambient O 3 . Here, we present a comparison of the stomatal component of O 3 dry deposition eg s from chemical transport models and estimates of eg s from observed CO 2 , latent heat, and O 3 flux. The dry deposition schemes were configured as single-point models forced with data collected at flux towers. We conducted sensitivity analyses to study the impact of model parameters that control stomatal moisture stress on modeled eg s . Examining six sites around the northern hemisphere, we find that the seasonality of observed flux-based eg s agrees with the seasonality of simulated eg s at times during the growing season with disagreements occurring during the later part of the growing season at some sites. We find that modeled water stress effects are too strong in a temperate-boreal transition forest. Some single-point models overestimate summertime eg s in a seasonally water-limited Mediterranean shrubland. At all sites examined, modeled eg s was sensitive to parameters that control the vapor pressure deficit stress. At specific sites that experienced substantial declines in soil moisture, the simulation of eg s was highly sensitive to parameters that control the soil moisture stress. The findings demonstrate the challenges in accurately representing the effects of moisture stress on the stomatal sink of O 3 during observed increases in dryness due to ecosystem specific plant-resource interactions.

We present the collective evaluation of the regional scale models that took part in the fourth edition of the Air Quality Model Evaluation International Initiative (AQMEII). The activity consists of the evaluation and intercomparison of regional scale air quality models run over North American (NA) and European (EU) domains for 2016 (NA) and 2010 (EU). The focus of the paper is ozone dry deposition. Dry deposition is among the most important processes of removal of chemical compounds from the atmosphere and an important contributor to the overall chemical budget of the latter. Furthermore ozone dry deposition is very important as it can be severely detrimental to vegetation physiology. The collective evaluation begins with an operational evaluation, namely a direct comparison of model-simulated predictions with monitoring data aiming at assessing model performance (Dennis et al., 2010). Following the AQMEII protocol and Dennis et al. (2010), we also perform a probabilistic evaluation in the form of ensemble analyses and an introductory diagnostic evaluation. The latter, analyses the role of dry deposition in comparison with dynamic and radiative processes and land-use/land-cover types (LULC), in determining surface ozone variability. Important differences are found across dry deposition results when the same LULC is considered. Furthermore, we found that models use very different LULC masks, thus introducing an additional level of diversity in the model results. The study stresses that, as for other kinds of prior and problem-defining information (emissions, topography or land-water masks), the choice of a LULC mask should not be at modeller's discretion. Furthermore, LULC should be considered as a variable to be evaluated in any future model intercomparison, unless set as common input information. The differences in LULC selection can have a substantial impact on model results, making the task of evaluating dry deposition modules across different regional-scale models very difficult.

The Community Multiscale Air Quality (CMAQ) model is a multi-phase chemical transport modeling system that combines state of the art computing techniques with the latest air quality science to simulate atmospheric pollutants across scales. CMAQ was developed and first released in 1998 and since then has undergone continual science enhancements and model structure updates. CMAQ version 5.4, a major update to the CMAQ version 5.3 series, was released in 2022. The featured updates include revisions to the carbon bond chemical mechanism and its representation of halogen chemistry, improvements to aerosol dry deposition in both the M3Dry and Surface Tiled Aerosol and Gaseous Exchange (STAGE) deposition schemes, modifications to the inline wind-blown dust emissions scheme to address the persistent underprediction seen with recent versions, and addition of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) as a new online biogenic emissions option. A summary and evaluation on a hemispheric scale of these updates in CMAQv5.4 is presented.

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

The Community Multiscale Air Quality (CMAQ) model has been used for regulatory purposes at the U.S. EPA and in the research community for decades. In 2012, we released the Weather Research and Forecasting (WRF)-CMAQ coupled model that enables aerosol information from CMAQ to affect meteorological processes through direct effects on shortwave radiation. Both CMAQ and WRF-CMAQ are considered limited-area models. Recently, we have extended domain coverage to the global scale by linking the meteorological Model for Prediction Across Scales - Atmosphere (MPAS-A, hereafter referred simply to as MPAS) with CMAQ to form the MPAS-CMAQ global coupled model. To configure these three different models, i.e., CMAQ (offline), WRF-CMAQ, and MPAS-CMAQ, we have developed the Advanced Air Quality Modeling System (AAQMS) for constructing each of them effortlessly. We evaluate this newly built MPAS-CMAQ coupled model using two global configurations: a 120 km uniform mesh and a 92-25 km variable mesh with the finer area over North America. Preliminary computational tests show good scalability and model evaluation, when using a 3-year simulation (2014-2016) for the uniform mesh case and a monthly simulation of January and July 2016 for the variable mesh case, on ozone and PM2.5 and show reasonable performance with respect to observations. The 92-25 km configuration has a high bias in wintertime surface ozone across the United States, and this bias is consistent with the 120 km result. Summertime surface ozone in the 92-25 km configuration is less biased than the 120 km case. The MPAS-CMAQ system reasonably reproduces the daily variability of daily average PM from the Air Quality System (AQS) network.

Using a high-resolution, 1.33 km by 1.33 km coupled Weather Research and Forecasting-Community Multi-scale Air Quality Model (WRF-CMAQ), we quantify the impact of emissions of nitrogen oxides (NOx) from high energy demand day (HEDD) electricity generating units (EGU) and onroad vehicles on ambient ozone air quality in the Long Island Sound Tropospheric Ozone Study (LISTOS) region covering New York City (NYC); Long Island, NY; coastal Connecticut; and neighboring areas. We test sensitivity scenarios to quantify HEDD EGU NOx contributions to ozone: (1) zero out HEDD EGU emissions, (2) dispatch HEDD EGUs starting with the lowest NOx emitting units first, (3) reduce onroad emissions by 90%, (4) combine zero out HEDD EGU emissions and reducing onroad emissions by 90%, and (5) dispatch HEDD EGUs starting with the lowest emitting units coupled with a reduction in onroad emissions by 90%. Results determine that HEDD EGUs lead to highly localized impacts on ambient concentrations of ozone while onroad emission reductions lead to large-scale regional concentration impacts. Further, reducing onroad emissions by 90% leads to spatially smaller VOC-limited regions and spatially larger transitional and NOX-limited regions around NYC. Despite the limited scale at which the EGU emission reductions occur, modifying HEDD EGU NOX emissions still provides substantial benefits in reducing ozone concentrations in the region, particularly at elevated ozone concentrations above 70 ppb.Implications: High-resolution coupled meteorology-chemistry modeling was used to quantify the impacts of high energy demand day (HEDD) electricity generating units (EGUs) and onroad transportation emissions changes on ozone air quality in the LISTOS region. Despite being highly localized and variable, HEDD EGUs NOX emissions sensitivity tests led to quantifiable changes in ozone. Further, reducing onroad emissions by 90% produced large decreases in ozone concentrations and led to a more NOX-sensitive ozone photochemical regime. With a transition to greater NOX-sensitivity, urban NOX-titration weakens and ozone is more likely to decline with the removal of additional NOX from sources like HEDD EGUs.

Accurate fog prediction in densely urbanized cities poses a challenge due to the complex influence of urban morphology on meteorological conditions in the urban roughness sublayer. This study implemented a coupled WRF-Urban Asymmetric Convective Model (WRF-UACM) for Delhi, India, integrating explicit urban physics with Sentinel-updated USGS land-use and urban morphological parameters derived from the UT-GLOBUS dataset. When evaluated against the baseline Asymmetric Convective Model (WRF-BACM) using Winter Fog Experiment (WiFEX) data, WRF-UACM significantly improved urban meteorological variables like diurnal variation of 10-meter wind speed, 2-meter air temperature (T2), and 2-meter relative humidity (RH2) on a fog day. UACM also demonstrates improved accuracy in simulating temperature and a significant reduction in biases for RH2 and wind speed under clear sky conditions. UACM reproduced the nighttime urban heat island effect within the city, showing realistic diurnal heating and cooling patterns that are important for accurate fog onset and duration. UACM effectively predicts the onset, evolution, and dissipation of fog, aligning well with observed data and satellite imagery. Compared to WRF-BACM, WRF-UACM reduces the cold bias soon after the sunset, thus improving the fog onset error by ~4 hours. This study underscores the UACM’s potential in enhancing fog prediction, urging further exploration of various fog types and its application in operational settings, thus offering invaluable insights for preventive measures and mitigating disruptions in urban regions.

Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4) is focused on the diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality modeling systems and employs both grid and box modeling techniques to accomplish this goal. This study presents an analysis of CMAQv5.3.1 simulations that were performed in the context of AQMEII4 over a North American modeling domain. Results show that variability in the estimated dry deposition sink affected model performance and resulted from both differences in model process formulation and the representation of the underlying land use (LU). To gain mechanistic insights into model behavior, the study employs diagnostic variables defined for the AQMEII4 project, i.e., grid scale and land-use specific effective conductances and deposition fluxes for the major dry deposition pathways (stomatal, cuticular, lower canopy, and soil). Analysis of these variables indicates that there generally is a greater contribution to ozone dry deposition from the stomatal and cuticular pathways in the CMAQ M3DRY dry deposition scheme compared to CMAQ STAGE dry deposition scheme and that differences in LU classification schemes can have a pronounced impact on simulated fluxes.

A primary sink of air pollutants and their precursors is dry deposition. Dry deposition estimates differ across chemical transport models, yet an understanding of the model spread is incomplete. Here, we introduce Activity 2 of the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4). We examine 18 dry deposition schemes from regional and global chemical transport models as well as standalone models used for impact assessments or process understanding. We configure the schemes as single-point models at eight Northern Hemisphere locations with observed ozone fluxes. Single-point models are driven by a common set of site-specific meteorological and environmental conditions. Five of eight sites have at least 3 years and up to 12 years of ozone fluxes. The interquartile range across models in multiyear mean ozone deposition velocities ranges from a factor of 1.2 to 1.9 annually across sites and tends to be highest during winter compared with summer. No model is within 50 % of observed multiyear averages across all sites and seasons, but some models perform well for some sites and seasons. For the first time, we demonstrate how contributions from depositional pathways vary across models. Models can disagree with respect to relative contributions from the pathways, even when they predict similar deposition velocities, or agree with respect to the relative contributions but predict different deposition velocities. Both stomatal and nonstomatal uptake contribute to the large model spread across sites. Our findings are the beginning of results from AQMEII4 Activity 2, which brings scientists who model air quality and dry deposition together with scientists who measure ozone fluxes to evaluate and improve dry deposition schemes in the chemical transport models used for research, planning, and regulatory purposes.

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.

Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate 20 predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemical Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O 3 ) across the Northeast U.S. during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1

Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O3) across the northeastern US during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O3 predictions of hourly and maximum daily 8 h average (MDA8) ozone were lower than those estimated by the Regional Atmospheric Chemistry Mechanism with aerosol module 6 (RACM2_ae6), which better matched surface network observations in the northeastern US (RACM2_ae6 mean bias of +4.2 ppb for all hours and +4.3 ppb for MDA8; CRACMMv1.0 mean bias of +2.1 ppb for all hours and +2.7 ppb for MDA8). Box model calculations combined with results from CMAQ emission reduction simulations indicated a high sensitivity of O3 to compounds with biogenic sources. In addition, these calculations indicated the differences between CRACMMv1.0 and RACM2_ae6 O3 predictions were largely explained by updates to the inorganic rate constants (reflecting the latest assessment values) and by updates to the representation of monoterpene chemistry. Updates to other reactive organic carbon systems between RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene, and xylene chemistry led to efficient NOx cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O3 disbenefits. In contrast, semivolatile and intermediate-volatility alkanes introduced in CRACMMv1.0 acted to suppress O3 formation across the regional background through the sequestration of nitrogen oxides (NOx) in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone concentrations in the northeastern US during the summer of 2018 with similar magnitude and diurnal variation as the current operational Carbon Bond (CB6r3_ae7) mechanism and good model performance compared to recent modeling studies in the literature.

Black-carbon (BC) aerosol can strongly influence planetary boundary layer (PBL) development and thus severe haze formation, but its distinct role compared with scattering aerosols is not yet fully understood. Here, combining numerical simulation and field observation, we found a "tipping point,"where the daily maximum PBL height decreases abruptly when exceeding a critical threshold of aerosol optical depth (AOD), due to a BC-induced decoupling of mixing zones. Because the threshold AOD decreases with increasing BC mass fraction, our results suggest that the abrupt transition of PBL development to adverse conditions can be avoided by reducing the AOD below the threshold but can be avoided more efficiently by reducing the BC mass fraction to increase the threshold (e.g., up to four to six times more effective in extreme haze events in Beijing). To achieve co-benefits for air quality and climate change, our findings clearly demonstrate that high priority should be given to controlling BC emissions.

Airborne aerosols reduce surface solar radiation through light scattering and absorption (aerosol direct effects, ADEs), influence regional meteorology, and further affect atmospheric chemical reactions and aerosol concentrations. The inhibition of turbulence and the strengthened atmospheric stability induced by ADEs increases surface primary aerosol concentration, but the pathway of ADE impacts on secondary aerosol is still unclear. In this study, the online coupled meteorological and chemistry model (WRF–CMAQ; Weather Research and Forecasting–Community Multiscale Air Quality) with integrated process analysis was applied to explore how ADEs affect secondary aerosol formation through changes in atmospheric dynamics and photolysis processes. The meteorological condition and air quality in the Jing-Jin-Ji area (denoted JJJ, including Beijing, Tianjin, and Hebei Province in China) in January and July 2013 were simulated to represent winter and summer conditions, respectively. Our results show that ADEs through the photolysis pathway inhibit sulfate formation during winter in the JJJ region and promote sulfate formation in July. The differences are attributed to the alteration of effective actinic flux affected by single-scattering albedo (SSA). ADEs through the dynamics pathway act as an equally or even more important route compared with the photolysis pathway in affecting secondary aerosol concentration in both summer and winter. ADEs through dynamics traps formed sulfate within the planetary boundary layer (PBL) which increases sulfate concentration in winter. Meanwhile, the impact of ADEs through dynamics is mainly reflected in the increase of gaseous-precursor concentrations within the PBL which enhances secondary aerosol formation in summer. For nitrate, reduced upward transport of precursors restrains the formation at high altitude and eventually lowers the nitrate concentration within the PBL in winter, while such weakened vertical transport of precursors increases nitrate concentration within the PBL in summer, since nitrate is mainly formed near the surface ground.

Dry deposition of aerosols from the atmosphere is an important but poorly understood and inadequately modeled process in atmospheric systems for climate and air quality. Comparisons of currently used aerosol dry deposition models to a compendia of published field measurement studies in various landscapes show very poor agreement over a wide range of particle sizes. In this study, we develop and test a new aerosol dry deposition model that is a modification of the current model in the Community Multiscale Air Quality (CMAQ) model. The new model agrees much better with measured dry deposition velocities across particle sizes. The key innovation is the addition of a second inertial impaction term for microscale obstacles such as leaf hairs, microscale ridges, and needleleaf edge effects. The most significant effect of the new model is to increase the mass dry deposition of the accumulation mode aerosols in CMAQ. Accumulation mode mass dry deposition velocities increase by almost an order of magnitude in forested areas with lesser increases for shorter vegetation. Peak PM2.5 concentrations are reduced in some forested areas by up to 40% in CMAQ simulations. Over the continuous United States, the new model reduced PM2.5 by an average of 16% for July 2018 at the Air Quality System monitoring sites. For summer 2018 simulations, bias and error of PM2.5 concentrations are significantly reduced, especially in forested areas.

The lightning assimilation (LTA) technique in the Kain-Fritsch convective parameterization in the Weather Research and Forecasting (WRF) model has been updated and applied to continental and hemispheric simulations using lightning flash data obtained from the National Lightning Detection Network (NLDN) and the World Wide Lightning Location Network (WWLLN), respectively. The LTA technique uses lightning data to trigger the Kain-Fritsch convective parameterization via realistic temperature and moisture perturbations. The impact of different values for cumulus parameters associated with the Kain-Fritsch scheme on simulations with and without LTA were evaluated for both the continental and the hemispheric simulations. Comparisons to gauge-based rainfall products and near-surface meteorological observations indicated that the LTA improved the model's performance for most variables. The simulated precipitation with LTA, using WWLLN lightning flashes in the hemispheric applications, was significantly improved over the simulations without LTA when compared to precipitation from satellite observations in the equatorial regions. The simulations without LTA showed significant sensitivity to the cumulus parameters (i.e., user-toggled switches) for monthly precipitation that was as large as 40 % during convective seasons for monthly mean daily precipitation. With LTA, the differences in simulated precipitation due to the different cumulus parameters were minimized. The horizontal grid spacing of the modeling domain strongly influenced the LTA technique and the predicted total precipitation, especially in the coarser scales used for the hemispheric simulation. The user-definable cumulus parameters and domain resolution manifested the complexity of convective process modeling both with and without LTA. These results revealed sensitivities to domain resolution, geographic heterogeneity, and the source and quality of the lightning dataset.