Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ

United States (US) background ozone (O3) is the counterfactual O3 that would exist with zero US anthropogenic emissions. Estimates of US background O3 typically come from chemical transport models (CTMs), but different models vary in their estimates of both background and total O3. Here, a measurement-model data fusion approach is used to estimate CTM biases in US anthropogenic O3 and multiple US background O3 sources, including natural emissions, long-range international emissions, short-range international emissions from Canada and Mexico, and stratospheric O3. Spatially and temporally varying bias correction factors adjust each simulated O3 component so that the sum of the adjusted components evaluates better against observations compared to unadjusted estimates. The estimated correction factors suggest a seasonally consistent positive bias in US anthropogenic O3 in the eastern US, with the bias becoming higher with coarser model resolution and with higher simulated total O3, though the bias does not increase much with higher observed O3. Summer average US anthropogenic O3 in the eastern US was estimated to be biased high by 2, 7, and 11 ppb (11%, 32%, and 49%) for one set of simulations at 12, 36, and 108 km resolutions and 1 and 6 ppb (10% and 37%) for another set of simulations at 12 and 108 km resolutions. Correlation among different US background O3 components can increase the uncertainty in the estimation of the source-specific adjustment factors. Despite this, results indicate a negative bias in modeled estimates of the impact of stratospheric O3 at the surface, with a western US spring average bias of -3.5 ppb (-25%) estimated based on a stratospheric O3 tracer. This type of data fusion approach can be extended to include data from multiple models to leverage the strengths of different data sources while reducing uncertainty in the US background ozone estimates.

A cautious note advocating the use of ensembles of models and driving data in modeling of regional ozone burdens

We investigate the performance of two widely used chemistry-transport models (CTMs) with different chemical mechanisms in reproducing the ambient maximum daily 8-h average ozone (MDA8 O3) burden over Central Europe. We explore a base case setup with boundary conditions (BC) for meteorology from the ERA-Interim reanalysis and chemical BC from CAM-Chem as well as effects of alterations in these BC based on global model fields. Our results show that changes in meteorological BC strongly affect the correlation with observations but only marginally affect the model biases, while changes in chemical BC increase model biases while correlation patterns remain largely unchanged. Furthermore, our study highlights that CTM choice (and choice of chemical mechanism) has a similar or even larger impact on MDA8 O3 levels as the impact of altered BC. In summary, our study calls for a multi-model strategy combining different CTM and BC combinations to explore the bandwidth of MDA8 O3 distributions and thus uncertainty in hindcasts and future projections, in analogy to climate studies considering ensemble simulations under the same anthropogenic emissions but with slightly different initial conditions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11869-024-01516-3.

Dynamic evaluation of modeled ozone concentrations in Germany with four chemistry transport models

Simulating the ozone variability at regional scales using chemistry transport models (CTMs) remains a challenge. We designed a multi-model intercomparison to evaluate, for the first time, four regional CTMs on a national scale for Germany. Simulations were conducted with LOTOS-EUROS, REM-CALGRID, COSMO-MUSCAT and WRF-Chem for January 1st to December 31st, 2019, using prescribed emission information. In general, all models show good performance in the operational evaluation with average temporal correlations of MDA8 O3 in the range of 0.77-0.87 and RMSE values between 16.3 μg m-3 and 20.6 μg m-3. On average, better models' skill has been observed for rural background stations than for the urban background stations as well as for springtime compared to summertime. Our study confirms that the ensemble mean provides a better model-measurement agreement than individual models. All models capture the larger local photochemical production in summer compared to springtime and observed differences between the urban and the rural background. We introduce a new indicator to evaluate the dynamic response of ozone to temperature. During summertime a large ensemble spread in the ozone sensitivities to temperature is found with (on average) an underestimation of the ozone sensitivity to temperature, which can be linked to a systematic underestimation of mid-level ozone concentrations. During springtime we observed an ozone episode that is not covered by the models which is likely due to deficiencies in the representation of background ozone in the models. We recommend to focus on a diagnostic evaluation aimed at the model descriptions for biogenic emissions and dry deposition as a follow up and to repeat the operational and dynamic analysis for longer timeframes.

Terrain effect on atmospheric process in seasonal ozone variation over the Sichuan Basin, Southwest China

Terrain effect is challenging for understanding atmospheric environment changes under complex topography. This study targets the Sichuan Basin (SCB), a deep basin isolated by plateaus and mountains in Southwest China, by employing WRF-Chem with integrated process rates (IPR) analysis to characterize the terrain-driven seasonal variations of tropospheric ozone (O3) with atmospheric physical and chemical processes. Results show that the basin terrain exerts reversed impacts on regional air quality changes by aggravating summertime and alleviating wintertime near-surface O3 with the relative contributions oscillating seasonally between -40% and 40% in SCB. Similarly, a seasonal shift of vertical O3 structures is dominated by summertime positive and wintertime negative changes in the lower troposphere induced by basin terrain. The key contributions of atmospheric process to near-surface O3 are identified with vertical and horizontal transport, which is dominated by basin terrain with intensifying seasonal and diurnal variations. With the existence of basin, the daytime O3 productions at the near-surface layer are elevated in months of warm seasons (April and July) but inhibited in the cold seasons (October and January), presenting a seasonal transition of primary factor from meteorology to aerosol-radiation forcing on photochemical reactions. Driven by plateau-basin thermodynamic forcing, horizontal O3 transport between the SCB and eastern TP is enhanced by mountain-plains solenoid (MPS), and even nocturnal O3-rich layers contribute to the impacts of vertical exchange on near-surface O3 levels. The terrain effects of deep basin under the interaction of Asian monsoons and westerlies could jointly change atmospheric physical and chemical processes to construct the seasonal and diurnal O3 evolution patterns over the SCB region.

Effect of Future Climate Change on Stratosphere-to-Troposphere-Exchange Driven Ozone in the Northern Hemisphere

Future estimates of atmospheric pollutant concentrations serve as critical information for policy makers to formulate current policy indicators to achieve future targets. Tropospheric burden of O3 is modulated not only by anthropogenic and natural precursor emissions, but also by the downward transport of O3 associated with stratosphere to troposphere exchange (STE). Hence changes in the estimates of STE and its contributions are key to understand the nature and intensity of future ground level O3 concentrations. The difference in simulated O3 mixing ratios with and without the O3-Potential Vorticity (PV) parameterization scheme is used to represent the model estimated influence of STE on tropospheric O3 distributions. Though STE contributions remain constant in Northern hemisphere as a whole, regional differences exist with Europe (EUR) registering increased STE contribution in both spring and winter while Eastern China (ECH) reporting increased contribution in spring in 2050 (RCP8.5) as compared to 2015. Importance of climate change can be deduced from the fact that ECH and EUR recorded increased STE contribution to O3 in RCP8.5 compared to RCP4.5. Comparison of STE and non-STE meteorological process contributions to O3 due to climate change revealed that contributions of non-STE processes were highest in summer while STE contributions were highest in winter. EUR reported highest STE contribution while ECH reported highest non-STE contribution. None of the 3 regions show consistent low STE contribution due to future climate change (< 50%) in all seasons indicating the significance of STE to ground level O3.

A single-point modeling approach for the intercomparison and evaluation of ozone dry deposition across chemical transport models (Activity 2 of AQMEII4)

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.

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.

Divergent summertime surface O3 pollution formation mechanisms in two typical Chinese cities in the Beijing-Tianjin-Hebei region and Fenwei Plain

Recently, severe summertime ozone (O₃) pollution has swept across most areas of China, especially the Beijing-Tianjin-Hebei (BTH) region and Fenwei Plain. By focusing on Beijing and Yuncheng, which are two typical cities in the BTH region and the Fenwei Plain, we intended to reveal the neglected fact that they had disparate emission features and atmospheric movements but suffered from similar high-O₃ pollution levels. Field observations indicated that Yuncheng had lower volatile organic compound (VOC) and NO_x concentrations but higher background O₃ levels. The model simulation verified that both photochemical reactions and net O₃ generation were stronger in Beijing. Ultimately, faster net O₃ generation rates (8.4 ppbv/h) plus lower background O₃ values in Beijing and lower net O₃ generation rates (6.2 ppbv/h) plus higher background O₃ values in Yuncheng caused both regions to reach similar O₃ peak values in July 2020. However, different O₃ control measures were appropriate for the two cities according to the different simulated O₃-VOCs-NO_x responses. Additionally, as surface O₃ levels are greatly affected by the ongoing O₃ production/depletion process that occurs in three dimensions, exploring the effects of spatially distributed O₃ on surface O₃ should be high on the agenda in the future.

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.

How have Divergent Global Emission Trends Influenced Long-range Transported Ozone to North America?

Several locations across the United States in non-compliance with the national standard for ground-level ozone (O3) are thought to have sizeable influences from distant extra-regional emission sources or natural stratospheric O3, which complicates design of local emission control measures. To quantify the amount of long-range transported O3 (LRT O3), its origin, and change over time, we conduct and analyze detailed sensitivity calculations characterizing the response of O3 to emissions from different source regions across the Northern Hemisphere in conjunction with multi-decadal simulations of tropospheric O3 distributions and changes. Model calculations show that the amount of O3 at any location attributable to sources outside North America varies both spatially and seasonally. On a seasonal-mean basis, during 1990-2010, LRT O3 attributable to international sources steadily increased by 0.06-0.2 ppb yr-1 at locations across the United States and arose from superposition of unequal and contrasting trends in individual source-region contributions, which help inform attribution of the trend evident in O3 measurements. Contributions of emissions from Europe steadily declined through 2010, while those from Asian emissions increased and remained dominant. Steadily rising NOx emissions from international shipping resulted in increasing contributions to LRT O3, comparable to those from Asian emissions in recent years. Central American emissions contribute a significant fraction of LRT O3 in southwestern United States. In addition to the LRT O3 attributable to emissions outside of North America, background O3 across the continental United States is comprised of a sizeable and spatially variable fraction that is of stratospheric origin (29-78%).

Changes in the ozone chemical regime over the contiguous United States inferred by the inversion of NOx and VOC emissions using satellite observation

To investigate changes in the ozone (O3) chemical production regime over the contiguous United States (CONUS) with accurate knowledge of concentrations of its precursors, we applied an inverse modeling technique with Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) and total formaldehyde (HCHO) retrieval products in the summers of 2011, 2014, and 2017, years in which United States National Emission Inventory were based. The inclusion of dynamic chemical lateral boundary conditions and lightning-induced nitric oxide emissions significantly account for the contribution of background sources in the free troposphere. Satellite-constrained nitrogen oxide (NOx) and non-methane volatile organic compounds (NMVOCs) emissions mitigate the discrepancy between satellite and modeled columns: the inversion suggested 2.33-2.84 (1.07-1.34) times higher NOx over the CONUS (over urban regions) and 0.28-0.81 times fewer NMVOCs emissions over the southeastern United States. The model-derived HCHO/NO2 column ratio shows gradual spatial changes in the O3 production regime near urban cores relative to previously defined threshold values representing NOx and VOC sensitive conditions. We also found apparent shifts from the NOx-saturated regime to the transition regime (or the transition regime to the NOx-limited regime) over the major cities in the western United States. In contrast, rural areas, especially in the east-southeastern United States, exhibit a decreased HCHO/NO2 column ratio by -1.30 ± 1.71 with a reduction in HCHO column primarily driven by meteorology, becoming sensitive to VOC emissions. Results show that incorporating satellite observations into numerical modeling could help policymakers implement appropriate emission control policies for O3 pollution.

Technical note: AQMEII4 Activity 1: evaluation of wet and dry deposition schemes as an integral part of regional-scale air quality models

We present in this technical note the research protocol for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided into two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reduction of input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (to be described in future submissions as part of the special issue on AQMEII4). The scope of this paper is to present the scientific protocols for Activity 1, as well as to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving diagnostics specific to land use-land cover (LULC) and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

Incorporation of volcanic SO2 emissions in the Hemispheric CMAQ (H-CMAQ) version 5.2 modeling system and assessing their impacts on sulfate aerosol over the Northern Hemisphere

The state-of-the-science Community Multiscale Air Quality (CMAQ) Modeling System has recently been extended for hemispheric-scale modeling applications (referred to as H-CMAQ). In this study, satellite-constrained estimation of the degassing SO₂ emissions from 50 volcanoes over the Northern Hemisphere is incorporated into H-CMAQ, and their impact on tropospheric sulfate aerosol ( SO 4 2 - ) levels is assessed for 2010. The volcanic degassing improves predictions of observations from the Acid Deposition Monitoring Network in East Asia (EANET), the United States Clean Air Status and Trends Network (CASTNET), and the United States Integrated Monitoring of Protected Visual Environments (IMPROVE). Over Asia, the increased SO 4 2 - concentrations were seen to correspond to the locations of volcanoes, especially over Japan and Indonesia. Over the USA, the largest impacts that occurred over the central Pacific were caused by including the Hawaiian Kilauea volcano, while the impacts on the continental USA were limited to the western portion during summertime. The emissions of the Soufrière Hills volcano located on the island of Montserrat in the Caribbean Sea affected the southeastern USA during the winter season. The analysis at specific sites in Hawaii and Florida also confirmed improvements in regional performance for modeled SO 4 2 - by including volcanoes SO₂ emissions. At the edge of the western USA, monthly averaged SO 4 2 - enhancements greater than 0.1μgm^-3 were noted within the boundary layer (defined as surface to 750hPa) during June- September. Investigating the change on SO 4 2 - concentration throughout the free troposphere revealed that although the considered volcanic SO₂ emissions occurred at or below the middle of free troposphere (500hPa), compared to the simulation without the volcanic source, SO 4 2 - enhancements of more than 10% were detected up to the top of the free troposphere (250hPa). Our model simulations and comparisons with measurements across the Northern Hemisphere indicate that the degassing volcanic SO₂ emissions are an important source and should be considered in air quality model simulations assessing background SO 4 2 - levels and their source attribution.

A new approach for health-oriented ozone control strategy: Adjoint-based optimization of NOx emission reductions using metaheuristic algorithms

While levels of particulate matters in the Pearl River Delta Region (PRD) show a significant reduction, ozone (O₃) has an opposite increasing trend, becoming the critical air quality target in this decade. Emission control strategies are typically formulated sector by sector, spatial variability in emissions reductions and health impacts of air pollutants may not be taken into account, affecting the overall effectiveness of control strategies. This study proposes an adjoint-based optimization framework to facilitate health-oriented O₃ control over PRD. The location-specific adjoint sensitivity coefficients, which reflect the spatiotemporal influences from emissions of nitrogen dioxide (NO_x) on O₃ health impacts, are combined with metaheuristic algorithms to minimize the O₃-related premature mortalities over receptor regions. Using the proposed optimization methodology, the regional O₃ health benefits under current emission reduction policy can be increased by 16-27%. The results show that relatively larger NO_x emissions reductions occurred at highly developed and populated areas. Particularly, significant reductions in NO_x emissions are observed at Shenzhen and urban Guangzhou. Furthermore, implementing regional NO_x emissions abatement has advantages to achieve an overall O₃ health benefits for all cities. The interregional influences of NO_x emissions abatement between cities indicate a promising strategy of health-oriented O₃ control in PRD.

Establishing the Suitability of the Model for Prediction Across Scales for Global Retrospective Air Quality Modeling

The U.S. EPA is leveraging recent advances in meteorological modeling to construct an air quality modeling system to allow consistency from global to local scales. The Model for Prediction Across Scales-Atmosphere (MPAS-A or MPAS) has been developed by the National Center for Atmospheric Research (NCAR) as a global complement to the Weather Research and Forecasting model (WRF). Patterned after a regional coupled system with WRF, the Community Multiscale Air Quality (CMAQ) modeling system has been coupled within MPAS to explore global-to-local chemical transport modeling. Several options were implemented into MPAS for retrospective applications. Nudging-based data assimilation was added to support continuous simulations of past weather to minimize error growth that exists with a weather forecast configuration. The Pleim-Xiu land-surface model, the Asymmetric Convective Model 2 boundary layer scheme, and the Pleim surface layer scheme were added as the preferred options for retrospective air quality applications with WRF. Annual simulations were conducted using this EPA-enhanced MPAS configuration on two different mesh structures and compared against WRF. MPAS generally compares well with WRF over the conterminous United States. Errors in MPAS surface meteorology are comparable to WRF throughout the year. Precipitation statistics indicate MPAS performs slightly better than WRF. Solar radiation in MPAS is higher than WRF and measurements, suggesting fewer clouds in MPAS than WRF. Upper-air meteorology is well-simulated by MPAS, but errors are slightly higher than WRF. These comparisons lend confidence to use MPAS for retrospective air quality modeling and suggest ways it can be further improved in the future.

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.

Estimating US Background Ozone Using Data Fusion

US background (US-B) ozone (O3) is the O3 that would be present in the absence of US anthropogenic (US-A) emissions. US-B O3 varies by location and season and can make up a large, sometimes dominant, portion of total O3. Typically, US-B O3 is quantified using a chemical transport model (CTM) though results are uncertain due to potential errors in model process descriptions and inputs, and there are significant differences in various model estimates of US-B O3. We develop and apply a method to fuse observed O3 with US-B O3 simulated by a regional CTM (CMAQ). We apportion the model bias as a function of space and time to US-B and US-A O3. Trends in O3 bias are explored across different simulation years and varying model scales. We found that the CTM US-B O3 estimate was typically biased low in spring and high in fall across years (2016-2017) and model scales. US-A O3 was biased high on average, with bias increasing for coarser resolution simulations. With the application of our data fusion bias adjustment method, we estimate a 28% improvement in the agreement of adjusted US-B O3. Across the four estimates, we found annual mean CTM-simulated US-B O3 ranging from 30 to 37 ppb with the spring mean ranging from 32 to 39 ppb. After applying the bias adjustment, we found annual mean US-B O3 ranging from 32 to 33 ppb with the spring mean ranging from 37 to 39 ppb.

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.

Assessing the manageable portion of ground-level ozone in the contiguous United States

Regional air quality models are widely being used to understand the spatial extent and magnitude of the ozone non-attainment problem and to design emission control strategies needed to comply with the relevant ozone standard through direct emission perturbations. In this study, we examine the manageable portion of ground-level ozone using two simulations of the Community Multiscale Air Quality (CMAQ) model for the year 2010 and a probabilistic analysis approach involving 29 years (1990-2018) of historical ozone observations. The modeling results reveal that the reduction in the peak ozone levels from total elimination of anthropogenic emissions within the model domain is around 13-21 ppb for the 90th-100th percentile range of the daily maximum 8-hr ozone concentrations across the contiguous United States (CONUS). Large reductions in the 4th highest 8-hr ozone are seen in the regions of West (interquartile range (IQR) of 17-33%), South (IQR 22-34%), Central (IQR 19-31%), Southeast (IQR 25-34%), and Northeast (IQR 24-37%). However, sites in the western portion of the domain generally show smaller reductions even when all anthropogenic emissions are removed, possibly due to the strong influence of global background ozone, including sources such as intercontinental ozone transport, stratospheric ozone intrusions, wildfires, and biogenic precursor emissions. Probabilistic estimates of the exceedances for several hypothetical thresholds of the 4th highest 8-hr ozone indicate that, in some areas, exceedances of such hypothetical thresholds may occur even with no anthropogenic emissions due to the ever-present atmospheric stochasticity and the current global tropospheric ozone burden. Implications: Because air pollution is intricately linked to adverse health effects, National Ambient Air Quality Standards (NAAQS) have been established for criteria pollutants to safeguard human health and the environment. Areas not in compliance with the relevant standards are required to develop plans and policies to reduce their air pollution levels. Regional-scale air quality models are currently being used routinely to inform policies to identify the emissions reduction required to meet and maintain the NAAQS throughout the country. This paper examines the feasibility of the 4th highest ozone, which is used to derive the ozone design value for NAAQS, complying with various current and hypothetical 8-hr ozone thresholds over CONUS based on the information embedded in 29 years of historical ozone observations and two modeling scenarios with and without anthropogenic emissions loading.

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h O₃ with high resolution over both space (at 1 km × 1 km grid cells covering the contiguous United States) and time (daily estimates between 2000 and 2016). We further quantify monthly model uncertainty for our 1 km × 1 km gridded domain. The results demonstrate high overall model performance with an average cross-validated R² (coefficient of determination) against observations of 0.90 and 0.86 for annual averages. Overall, the model performance of the three machine learning algorithms was quite similar. The overall model performance from the ensemble model outperformed those from any single algorithm. The East North Central region of the United States had the highest R², 0.93, and performance was weakest for the western mountainous regions (R² of 0.86) and New England (R² of 0.87). For the cross validation by season, our model had the best performance during summer with an R² of 0.88. This study can be useful for the environmental health community to more accurately estimate the health impacts of O₃ over space and time, especially in health studies at an intra-urban scale.

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h O₃ with high resolution over both space (at 1 km × 1 km grid cells covering the contiguous United States) and time (daily estimates between 2000 and 2016). We further quantify monthly model uncertainty for our 1 km × 1 km gridded domain. The results demonstrate high overall model performance with an average cross-validated R² (coefficient of determination) against observations of 0.90 and 0.86 for annual averages. Overall, the model performance of the three machine learning algorithms was quite similar. The overall model performance from the ensemble model outperformed those from any single algorithm. The East North Central region of the United States had the highest R², 0.93, and performance was weakest for the western mountainous regions (R² of 0.86) and New England (R² of 0.87). For the cross validation by season, our model had the best performance during summer with an R² of 0.88. This study can be useful for the environmental health community to more accurately estimate the health impacts of O₃ over space and time, especially in health studies at an intra-urban scale.

Chemical Sensitivity Analysis and Uncertainty Analysis of Ozone Production in the Comprehensive Air Quality Model with Extensions Applied to Eastern Texas

Chemical sensitivity analysis (CSA) is a new probing tool for sampling sensitivities to chemistry parameters during a three-dimensional (3-D) simulation. CSA was applied to rank all of the parameters in the Carbon Bond 6 revision 4 (CB6r4) mechanism and to create an ensemble of six chemical mechanisms representing higher and lower O₃ formations than CB6r4. This ensemble of mechanisms was used to estimate the uncertainty from the chemistry in a 3-D simulation and combined with uncertainties from other model inputs obtained from calculations of their sensitivities. The overall uncertainty (1σ) in O₃ predictions for eastern Texas was 10-11 ppb in the Gulf of Mexico near Galveston and 7-8 ppb in much of the rest of the domain on the higher O₃ days of June 2012. As a percent of the O₃ concentration, the uncertainty was more uniform over the domain, 11-14%. Chemistry and emissions make the largest contributions to the O₃ uncertainty. Uncertainty in the dry deposition velocities is less important in urban areas and the Gulf, but it is similar in importance to the uncertainty in chemistry and emissions at most other locations. Uncertainty in O₃ boundary concentrations is the least important.

Modeling stratospheric intrusion and trans-Pacific transport on tropospheric ozone using hemispheric CMAQ during April 2010 - Part 2: Examination of emission impacts based on the higher-order decoupled direct method

The state-of-the-science Community Multiscale Air Quality (CMAQ) modeling system, which has recently been extended for hemispheric-scale modeling applications (referred to as H-CMAQ), is applied to study the trans-Pacific transport, a phenomenon recognized as a potential source of air pollution in the US, during April 2010. The results of this analysis are presented in two parts. In the previous paper (Part 1), model evaluation for tropospheric ozone (O3) was presented and an air mass characterization method was developed. Results from applying this newly established method pointed to the importance of emissions as the factor to enhance the surface O3 mixing ratio over the US. In this subsequent paper (Part 2), emission impacts are examined based on mathematically rigorous sensitivity analysis using the higher-order decoupled direct method (HDDM) implemented in H-CMAQ. The HDDM sensitivity coefficients indicate the presence of a NO x -sensitive regime during April 2010 over most of the Northern Hemisphere. By defining emission source regions over the US and east Asia, impacts from these emission sources are examined. At the surface, during April 2010, the emission impacts of the US and east Asia are comparable over the western US with a magnitude of about 3ppbv impacts on monthly mean O3 all-hour basis, whereas the impact of domestic emissions dominates over the eastern US with a magnitude of about 10ppbv impacts on monthly mean O3. The positive correlation (r = 0.63) between surface O3 mixing ratios and domestic emission impacts is confirmed. In contrast, the relationship between surface O3 mixing ratios and emission impacts from east Asia exhibits a flat slope when considering the entire US. However, this relationship has strong regional differences between the western and eastern US; the western region exhibits a positive correlation (r = 0.36-0.38), whereas the latter exhibits a flat slope (r <0.1). Based on the comprehensive evaluation of H-CMAQ, we extend the sensitivity analysis for O3 aloft. The results reveal the significant impacts of emissions from east Asia on the free troposphere (defined as 750 to 250hPa) over the US (impacts of more than 5ppbv) and the dominance of stratospheric air mass on upper model layer (defined as 250 to 50hPa) over the US (impacts greater than 10ppbv). Finally, we estimate changes of trans-Pacific transport by taking into account recent emission trends from 2010 to 2015 assuming the same meteorological condition. The analysis suggests that the impact of recent emission changes on changes in the contribution of trans-Pacific transport to US O3 levels was insignificant at the surface level and was small (less than 1ppbv) over the free troposphere.

Modeling stratospheric intrusion and trans-Pacific transport on tropospheric ozone using hemispheric CMAQ during April 2010 - Part 1: Model evaluation and air mass characterization for stratosphere-troposphere transport

Stratospheric intrusion and trans-Pacific transport have been recognized as a potential source of tropospheric ozone over the US. The state-of-the-science Community Multiscale Air Quality (CMAQ) modeling system has recently been extended for hemispheric-scale modeling applications (referred to as H-CMAQ). In this study, H-CMAQ is applied to study the stratospheric intrusion and trans-Pacific transport during April 2010. The results will be presented in two companion papers. In this Part 1 paper, model evaluation for tropospheric ozone (O3) is presented. Observations at the surface, by ozonesondes and airplane, and by satellite across the Northern Hemisphere are used to evaluate the model performance for O3. H-CMAQ is able to capture surface and boundary layer (defined as surface to 750hPa) O3 with a normalized mean bias (NMB) of -10%; however, a systematic underestimation with an NMB up to -30% is found in the free troposphere (defined as 750-250hPa). In addition, a new air mass characterization method is developed to distinguish influences of stratosphere-troposphere transport (STT) from the effects of photochemistry on O3 levels. This method is developed based on the ratio of O3 and an inert tracer indicating stratospheric O3 to examine the importance of photochemistry, and sequential intrusion from upper layer. During April 2010, on a monthly average basis, the relationship between surface O3 mixing ratios and estimated stratospheric air masses in the troposphere show a slight negative slope, indicating that high surface O3 values are primarily affected by other factors (i.e., emissions), whereas this relationship shows a slight positive slope at elevated sites, indicating that STT has a possible impact at elevated sites. STT shows large day-to-day variations, and STT impacts can either originate from the same air mass over the entire US with an eastward movement found during early April, or stem from different air masses at different locations indicated during late April. Based on this newly established air mass characterization technique, this study can contribute to understanding the role of STT and also the implied importance of emissions leading to high surface O3. Further research focused on emissions is discussed in a subsequent paper (Part 2).

Dry Deposition of Ozone over Land: Processes, Measurement, and Modeling

Dry deposition of ozone is an important sink of ozone in near surface air. When dry deposition occurs through plant stomata, ozone can injure the plant, altering water and carbon cycling and reducing crop yields. Quantifying both stomatal and nonstomatal uptake accurately is relevant for understanding ozone's impact on human health as an air pollutant and on climate as a potent short-lived greenhouse gas and primary control on the removal of several reactive greenhouse gases and air pollutants. Robust ozone dry deposition estimates require knowledge of the relative importance of individual deposition pathways, but spatiotemporal variability in nonstomatal deposition is poorly understood. Here we integrate understanding of ozone deposition processes by synthesizing research from fields such as atmospheric chemistry, ecology, and meteorology. We critically review methods for measurements and modeling, highlighting the empiricism that underpins modeling and thus the interpretation of observations. Our unprecedented synthesis of knowledge on deposition pathways, particularly soil and leaf cuticles, reveals process understanding not yet included in widely-used models. If coordinated with short-term field intensives, laboratory studies, and mechanistic modeling, measurements from a few long-term sites would bridge the molecular to ecosystem scales necessary to establish the relative importance of individual deposition pathways and the extent to which they vary in space and time. Our recommended approaches seek to close knowledge gaps that currently limit quantifying the impact of ozone dry deposition on air quality, ecosystems, and climate.

On ground truth in cross-border ozone transport

Cross-border transport of ozone is one of the most contentious issues of air pollution management in the U.S. Yet, both the modeling and observational studies are lacking. Models are normally validated by comparing predicted and observed ozone concentrations. However, proper validation of cross-border transport model requires a comparison of predictions against observation-based benchmarks of cross-border ozone transport. Such benchmarks are unavailable, as published observation-based studies always deal only with a combination of local production and cross-border transport, not a cross-border transport itself. We show how to extract necessary benchmarks from observations of rural monitoring sites near state borders. On example of the western border of New York, we find that in about two-thirds of the most polluted days all the ozone came in a steady cross-border inflow after previously passing over one or more large urban areas to the west. In all the enumerated days with direct cross-border inflow, daily maximum 8-hr concentrations of ozone just upwind of the border were over 60 ppb, with an average value of 68 ppb, just short of the 70 ppb ozone regulatory threshold, information also useful to state air pollution authorities. Implications: The purpose of the cross-border ozone pollution models is to predict cross-border transport of ozone, so the ability of the model to accurately represent observed ozone concentrations is necessary but not sufficient for model validation. The accuracy of predicted ozone concentrations is not necessarily the same as the accuracy of the predictions of ozone transport. Proper model validation requires comparisons against observation-based benchmarks of cross-border transport. Such observations, so far absent, can be obtained from rural monitoring sites near state borders, as illustrated by the example of western New York.

A New Method for Assessing the Efficacy of Emission Control Strategies

Regional-scale air quality models and observations at routine air quality monitoring sites are used to determine attainment/non-attainment of the ozone air quality standard in the United States. In current regulatory applications, a regional-scale air quality model is applied for a base year and a future year with reduced emissions using the same meteorological conditions as those in the base year. Because of the stochastic nature of the atmosphere, the same meteorological conditions would not prevail in the future year. Therefore, we use multi-decadal observations to develop a new method for estimating the confidence bounds for the future ozone design value (based on the 4^th highest value in the daily maximum 8-hr ozone concentration time series, DM8HR) for each emission loading scenario along with the probability of the design value exceeding a given ozone threshold concentration at all monitoring sites in the contiguous United States. To this end, we spectrally decompose the observed DM8HR ozone time series covering the period from 1981 to 2014 using the Kolmogorov-Zurbenko (KZ) filter and examine the variability in the relative strengths of the short-term variations (induced by synoptic-scale weather fluctuations; referred to as synoptic component, SY) and the long-term component (dictated by changes in emissions, seasonality and other slow-changing processes such as climate change; referred to as baseline component, BL). Results indicate that combining the projected change in the ozone baseline level with the adjusted synoptic forcing in historical ozone observations enables us to provide a probabilistic assessment of the efficacy of a selected emissions control strategy in complying with the ozone standard in future years. In addition, attainment demonstration is illustrated with a real-world application of the proposed methodology by using air quality model simulations, thereby helping build confidence in the use of regional-scale air quality models for supporting regulatory policies.

Attributing differences in the fate of lateral boundary ozone in AQMEII3 models to physical process representations

Increasing emphasis has been placed on characterizing the contributions and the uncertainties of ozone imported from outside the US. In chemical transport models (CTMs), the ozone transported through lateral boundaries (referred to as LB ozone hereafter) undergoes a series of physical and chemical processes in CTMs, which are important sources of the uncertainty in estimating the impact of LB ozone on ozone levels at the surface. By implementing inert tracers for LB ozone, the study seeks to better understand how differing representations of physical processes in regional CTMs may lead to differences in the simulated LB ozone that eventually reaches the surface across the US. For all the simulations in this study (including WRF/CMAQ, WRF/CAMx, COSMO-CLM/CMAQ, and WRF/DEHM), three chemically inert tracers that generally represent the altitude ranges of the planetary boundary layer (BC1), free troposphere (BC2), and upper troposphere-lower stratosphere (BC3) are tracked to assess the simulated impact of LB specification. Comparing WRF/CAMx with WRF/CMAQ, their differences in vertical grid structure explain 10 %-60 % of their seasonally averaged differences in inert tracers at the surface. Vertical turbulent mixing is the primary contributor to the remaining differences in inert tracers across the US in all seasons. Stronger vertical mixing in WRF/CAMx brings more BC2 downward, leading to higher BCT (BCT = BC1+BC2+BC3) and BC2/BCT at the surface in WRF/CAMx. Meanwhile, the differences in inert tracers due to vertical mixing are partially counteracted by their difference in sub-grid cloud mixing over the southeastern US and the Gulf Coast region during summer. The process of dry deposition adds extra gradients to the spatial distribution of the differences in DM8A BCT by 5-10 ppb during winter and summer. COSMO-CLM/CMAQ and WRF/CMAQ show similar performance in inert tracers both at the surface and aloft through most seasons, which suggests similarity between the two models at process level. The largest difference is found in summer. Sub-grid cloud mixing plays a primary role in their differences in inert tracers over the southeastern US and the oceans in summer. Our analysis of the vertical profiles of inert tracers also suggests that the model differences in dry deposition over certain regions are offset by the model differences in vertical turbulent mixing, leading to small differences in inert tracers at the surface in these regions.

Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions

This study evaluates simulated vertical ozone profiles produced in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) against ozonesonde observations in North America for the year 2010. Four research groups from the United States (US) and Europe have provided modeled ozone vertical profiles to conduct this analysis. Because some of the modeling systems differ in their meteorological drivers, wind speed and temperature are also included in the analysis. In addition to the seasonal ozone profile evaluation for 2010, we also analyze chemically inert tracers designed to track the influence of lateral boundary conditions on simulated ozone profiles within the modeling domain. Finally, cases of stratospheric ozone intrusions during May-June 2010 are investigated by analyzing ozonesonde measurements and the corresponding model simulations at Intercontinental Chemical Transport Experiment Ozonesonde Network Study (IONS) experiment sites in the western United States. The evaluation of the seasonal ozone profiles reveals that, at a majority of the stations, ozone mixing ratios are underestimated in the 1-6 km range. The seasonal change noted in the errors follows the one seen in the variance of ozone mixing ratios, with the majority of the models exhibiting less variability than the observations. The analysis of chemically inert tracers highlights the importance of lateral boundary conditions up to 250 hPa for the lower-tropospheric ozone mixing ratios (0-2 km). Finally, for the stratospheric intrusions, the models are generally able to reproduce the location and timing of most intrusions but underestimate the magnitude of the maximum mixing ratios in the 2-6 km range and overestimate ozone up to the first kilometer possibly due to marine air influences that are not accurately described by the models. The choice of meteorological driver appears to be a greater predictor of model skill in this altitude range than the choice of air quality model.

Modeling regional pollution transport events during KORUS-AQ: Progress and challenges in improving representation of land-atmosphere feedbacks

This study evaluates the impact of assimilating soil moisture data from NASA's Soil Moisture Active Passive (SMAP) on short-term regional weather and air quality modeling in East Asia during the Korea-US Air Quality Study (KORUS-AQ) airborne campaign. SMAP data are assimilated into the Noah land surface model using an ensemble Kalman filter approach in the Land Information System framework, which is semi-coupled with the NASA-Unified Weather Research and Forecasting model with online chemistry (NUWRF-Chem). With SMAP assimilation included, water vapor and carbon monoxide (CO) transport from northern-central China transitional climate zones to South Korea is better represented in NUWRF-Chem during two studied pollution events. Influenced by different synoptic conditions and emission patterns, impact of SMAP assimilation on modeled CO in South Korea is intense (>30 ppbv) during one event and less significant (<8 ppbv) during the other. SMAP assimilation impact on air quality modeling skill is complicated by other error sources such as the chemical initial and boundary conditions (IC/LBC) and emission inputs of NUWRF-Chem. Using a satellite-observation-constrained chemical IC/LBC instead of a free-running, coarser-resolution chemical IC/LBC reduces modeled CO by up to 80 ppbv over South Korea. Consequently, CO performance is improved in the middle-upper troposphere whereas degraded in the lower troposphere. Remaining negative CO biases result largely from the emissions inputs. The advancements in land surface modeling and chemical IC/LBC presented here are expected to benefit future investigations on constraining emissions using observations, which can in turn enable more accurate assessments of SMAP assimilation and chemical IC/LBC impacts.

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). The modeled surface concentrations of O3, CO, SO2 and PM2.5 are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs from each individual model. Along with a base case simulation, additional runs were performed introducing 20 % anthropogenic emission reductions both globally and regionally in Europe, North America and east Asia, as defined by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2). Health impacts estimated by using concentration inputs from different chemistry-transport models (CTMs) to the EVA system can vary up to a factor of 3 in Europe (12 models) and the United States (3 models). In Europe, the multi-model mean total number of premature deaths (acute and chronic) is calculated to be 414 000, while in the US, it is estimated to be 160 000, in agreement with previous global and regional studies. The economic valuation of these health impacts is calculated to be EUR 300 billion and 145 billion in Europe and the US, respectively. A subset of models that produce the smallest error compared to the surface observations at each time step against an all-model mean ensemble results in increase of health impacts by up to 30 % in Europe, while in the US, the optimal ensemble mean led to a decrease in the calculated health impacts by ~ 11 %. A total of 54 000 and 27 500 premature deaths can be avoided by a 20 % reduction of global anthropogenic emissions in Europe and the US, respectively. A 20 % reduction of North American anthropogenic emissions avoids a total of ~ 1000 premature deaths in Europe and 25 000 total premature deaths in the US. A 20 % decrease of anthropogenic emissions within the European source region avoids a total of 47 000 premature deaths in Europe. Reducing the east Asian anthropogenic emissions by 20 % avoids ~ 2000 total premature deaths in the US. These results show that the domestic anthropogenic emissions make the largest impacts on premature deaths on a continental scale, while foreign sources make a minor contribution to adverse impacts of air pollution.

Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3

In the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), and as contribution to the second phase of the Hemispheric Transport of Air Pollution (HTAP2) activities for Europe and North America, the impacts of a 20 % decrease of global and regional anthropogenic emissions on surface air pollutant levels in 2010 are simulated by an international community of regional-scale air quality modeling groups, using different state-of-the-art chemistry and transport models (CTMs). The emission perturbations at the global level, as well as over the HTAP2-defined regions of Europe, North America and East Asia, are first simulated by the global Composition Integrated Forecasting System (C-IFS) model from European Centre for Medium-Range Weather Forecasts (ECMWF), which provides boundary conditions to the various regional CTMs participating in AQMEII3. On top of the perturbed boundary conditions, the regional CTMs used the same set of perturbed emissions within the regional domain for the different perturbation scenarios that introduce a 20 % reduction of anthropogenic emissions globally as well as over the HTAP2-defined regions of Europe, North America and East Asia. Results show that the largest impacts over both domains are simulated in response to the global emission perturbation, mainly due to the impact of domestic emission reductions. The responses of NO2, SO2 and PM concentrations to a 20 % anthropogenic emission reduction are almost linear (~ 20 % decrease) within the global perturbation scenario with, however, large differences in the geographical distribution of the effect. NO2, CO and SO2 levels are strongly affected over the emission hot spots. O3 levels generally decrease in all scenarios by up to ~ 1 % over Europe, with increases over the hot spot regions, in particular in the Benelux region, by an increase up to ~ 6 % due to the reduced effect of NOx titration. O3 daily maximum of 8 h running average decreases in all scenarios over Europe, by up to ~ 1 %. Over the North American domain, the central-to-eastern part and the western coast of the US experience the largest response to emission perturbations. Similar but slightly smaller responses are found when domestic emissions are reduced. The impact of intercontinental transport is relatively small over both domains, however, still noticeable particularly close to the boundaries. The impact is noticeable up to a few percent, for the western parts of the North American domain in response to the emission reductions over East Asia. O3 daily maximum of 8 h running average decreases in all scenarios over north Europe by up to ~ 5 %. Much larger reductions are calculated over North America compared to Europe. In addition, values of the Response to Extra-Regional Emission Reductions (RERER) metric have been calculated in order to quantify the differences in the strengths of nonlocal source contributions to different species among the different models. We found large RERER values for O3 (~ 0.8) over both Europe and North America, indicating a large contribution from non-local sources, while for other pollutants including particles, low RERER values reflect a predominant control by local sources. A distinct seasonal variation in the local vs. non-local contributions has been found for both O3 and PM2.5, particularly reflecting the springtime long-range transport to both continents.

Scientific assessment of background ozone over the U.S.: Implications for air quality management

Ozone (O3) is a key air pollutant that is produced from precursor emissions and has adverse impacts on human health and ecosystems. In the U.S., the Clean Air Act (CAA) regulates O3 levels to protect public health and welfare, but unraveling the origins of surface O3 is complicated by the presence of contributions from multiple sources including background sources like stratospheric transport, wildfies, biogenic precursors, and international anthropogenic pollution, in addition to U.S. anthropogenic sources. In this report, we consider more than 100 published studies and assess current knowledge on the spatial and temporal distribution, trends, and sources of background O3 over the continental U.S., and evaluate how it inflattainment of the air quality standards. We conclude that spring and summer seasonal mean U.S. background O3 (USB O3), or O3 formed from natural sources plus anthropogenic sources in countries outside the U.S., is greatest at high elevation locations in the western U.S., with monthly mean maximum daily 8-hour average (MDA8) mole fractions approaching 50 parts per billion (ppb) and annual 4th highest MDA8s exceeding 60 ppb, at some locations. At lower elevation sites, e.g., along the West and East Coasts, seasonal mean MDA8 USB O3 is in the range of 20-40 ppb, with generally smaller contributions on the highest O3 days. The uncertainty in U.S. background O3 is around ±10 ppb for seasonal mean values and higher for individual days. Noncontrollable O3 sources, such as stratospheric intrusions or precursors from wildfires, can make significant contributions to O3 on some days, but it is challenging to quantify accurately these contributions. We recommend enhanced routine observations, focused fi studies, process-oriented modeling studies, and greater emphasis on the complex photochemistry in smoke plumes as key steps to reduce the uncertainty associated with background O3 in the U.S.