Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

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

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

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.

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

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

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

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

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.

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.

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.

On the mathematical modelling and data assimilation for air pollution assessment in the Tropical Andes

Air pollution assessment in the Tropical Andes requires a multidisciplinary approach. This can be supported from the understanding of the underlying biological dynamics and atmospheric behavior, to the mathematical approach for the proper use of all available information. This review paper touches on several aspects in which mathematical models can help to solve challenging problems regarding air pollution in reviewing the state-of-the-art at the global level and assessing the corresponding state of development as applied to the Tropical Andes. We address the complexities and challenges that modelling atmospheric dynamics in a mega-diverse region with abrupt topography entails. Understanding the relevance of monitoring and facing the problems of data scarcity, we call attention to the usefulness of data assimilation for uncertainty reduction, and how these techniques could help tackle the scarcity of regional monitoring networks to accelerate the implementation and development of modelling systems for air quality in the Tropical Andes. Finally, we suggest a cyberphysical framework for decision-making processes based on the data assimilation of chemical transport models, the forecast of scenarios, and their use in regulation and policy making.

Impact of the ‘13th Five-Year Plan’ Policy on Air Quality in Pearl River Delta, China: A Case Study of Haizhu District in Guangzhou City Using WRF-Chem

Due to increasingly stringent control policy, air quality has generally improved in major cities in China during the past decade. However, the standards of national regulation and the World Health Organization are yet to be fulfilled in certain areas (in some urban districts among the cities) and/or certain periods (during pollution episode event). A further control policy, hence, has been issued in the 13th Five-Year Plan (2016–2020, hereafter 13th FYP). It will be of interest to evaluate the air quality before the 13th FYP (2015) and to estimate the potential air quality by the end of the 13th FYP (2020) with a focus on the area of an urban district and the periods of severe pollution episodes. Based on observation data of major air pollutants, including SO2 (sulphur dioxide), NO2 (nitrogen dioxide), CO (carbon monoxide), PM10 (particulate matter with aerodynamic diameter equal to or less than 10 μm), PM2.5 (particulate matter with aerodynamic diameter equal to or less than 2.5 µm) and O3 (Ozone), the air quality of Haizhu district [an urban district in the Pearl River Delta (PRD), China] in 2015 suggested that typical heavy pollution occurred in winter and the hot season, with NO2 or PM2.5 as the key pollutants in winter and O3 as the key pollutant in the hot season. We also adopted a state-of-the-art chemical transport model, the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), to predict the air quality in Haizhu District 2020 under different scenarios. The simulation results suggested that among the emission control scenarios, comprehensive measures taken in the whole of Guangzhou city would improve air quality more significantly than measures taken just in Haizhu, under all conditions. In the urban district, vehicle emission control would account more than half of the influence of all source emission control on air quality. Based on our simulation, by the end of the 13th FYP, it is noticeable that O3 pollution would increase, which indicates that the control ratio of volatile organic compounds (VOCs) and nitrogen oxides (NOx) may be unsuitable and therefore should be adjusted. Our study highlights the significance of evaluating the efficacy of current policy in reducing the air pollutants and recommends possible directions for further air pollution control for urban areas during the 13th FYP.

High resolution temporal profiles in the Emissions Database for Global Atmospheric Research

Emissions into the atmosphere from human activities show marked temporal variations, from inter-annual to hourly levels. The consolidated practice of calculating yearly emissions follows the same temporal allocation of the underlying annual statistics. However, yearly emissions might not reflect heavy pollution episodes, seasonal trends, or any time-dependant atmospheric process. This study develops high-time resolution profiles for air pollutants and greenhouse gases co- emitted by anthropogenic sources in support of atmospheric modelling, Earth observation communities and decision makers. The key novelties of the Emissions Database for Global Atmospheric Research (EDGAR) temporal profiles are the development of (i) country/region- and sector- specific yearly profiles for all sources, (ii) time dependent yearly profiles for sources with inter-annual variability of their seasonal pattern, (iii) country- specific weekly and daily profiles to represent hourly emissions, (iv) a flexible system to compute hourly emissions including input from different users. This work creates a harmonized emission temporal distribution to be applied to any emission database as input for atmospheric models, thus promoting homogeneity in inter-comparison exercises.

Impact of halogen chemistry on summertime air quality in coastal and continental Europe: application of the CMAQ model and implications for regulation

Halogen (Cl, Br, and I) chemistry has been reported to influence the formation of secondary air pollutants. Previous studies mostly focused on the impact of chlorine species on air quality over large spatial scales. Very little attention has been paid to the effect of the combined halogen chemistry on air quality over Europe and its implications for control policy. In the present study, we apply a widely used regional model, the Community Multiscale Air Quality Modeling System (CMAQ), incorporated with the latest halogen sources and chemistry, to simulate the abundance of halogen species over Europe and to examine the role of halogens in the formation of secondary air pollution. The results suggest that the CMAQ model is able to reproduce the level of O₃, NO₂, and halogen species over Europe. Chlorine chemistry slightly increases the levels of OH, HO₂, NO₃, O₃, and NO₂ and substantially enhances the level of the Cl radical. Combined halogen chemistry induces complex effects on OH (ranging from -0.023 to 0.030 pptv) and HO₂ (in the range of -3.7 to 0.73 pptv), significantly reduces the concentrations of NO₃ (as much as 20 pptv) and O₃ (as much as 10 ppbv), and decreases NO₂ in highly polluted regions (as much as 1.7 ppbv); it increases NO₂ (up to 0.20 ppbv) in other areas. The maximum effects of halogen chemistry occur over oceanic and coastal regions, but some noticeable impacts also occur over continental Europe. Halogen chemistry affects the number of days exceeding the European Union target threshold for the protection of human beings and vegetation from ambient O₃. In light of the significant impact of halogen chemistry on air quality, we recommend that halogen chemistry be considered for inclusion in air quality policy assessments, particularly in coastal cities.

Unveiling tropospheric ozone by the traditional atmospheric model and machine learning, and their comparison:A case study in hangzhou, China

Tropospheric ozone in the surface air has become the primary atmospheric pollutant in Hangzhou, China, in recent years. Previous analysis is not enough to decode it for better regulation. Therefore, we use the traditional atmospheric model, Weather Research and Forecasting coupled with Community Multi-scale Air Quality (WRF-CMAQ), and machine learning models, Extreme Learning Machine (ELM), Multi-layer Perceptron (MLP), Random Forest (RF) and Recurrent Neural Network (RNN) to analyze and predict the ozone in the surface air in Hangzhou, China, using meteorology and air pollutants as input. We firstly quantitatively demonstrate that the dew-point deficit, instead of temperature and relative humidity, is the predominant meteorological factor in shaping tropospheric ozone. Urban heat island, daily direct solar radiation time, wind speed and wind direction play trivial role in impacting tropospheric ozone. NO₂ is the primary influential factors both for hourly ozone and daily O₃-8 h due to the titration effect. The most environmental-friendly way to mitigate the ozone pollution is to lower the volatile organic compounds (VOCs) with the highest ozone formation potentials. We deduce that the tropospheric ozone formation process tends to be not only non-linear but also non-smooth. Compared with the traditional atmospheric models, machine learning, whose characteristics are rapid convergence, short calculating time, adaptation of forecasting episodes, small program memory, higher accuracy and less cost, is able to predict tropospheric ozone more accurately.

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.

Model Performance Differences in Sulfate Aerosol in Winter over Japan Based on Regional Chemical Transport Models of CMAQ and CAMx

Sulfate aerosol (SO42−) is a major component of particulate matter in Japan. The Japanese model intercomparison study, J-STREAM, found that although SO42− is well captured by models, it is underestimated during winter. In the first phase of J-STREAM, we refined the Fe- and Mn-catalyzed oxidation and partly improved the underestimation. The winter haze in December 2016 was a target period in the second phase. The results from the Community Multiscale Air Quality (CMAQ) and Comprehensive Air quality Model with eXtentions (CAMx) regional chemical transport models were compared with observations from the network over Japan and intensive observations at Nagoya and Tokyo. Statistical analysis showed both models satisfied the suggested model performance criteria. CMAQ sensitivity simulations explained the improvements in model performance. CMAQ modeled lower SO42− concentrations than CAMx, despite increased aqueous oxidation via the metal catalysis pathway and NO2 reaction in CMAQ. Deposition explained this difference. A scatter plot demonstrated that the lower SO42− concentration in CMAQ than in CAMx arose from the lower SO2 concentration and higher SO42− wet deposition in CMAQ. The dry deposition velocity caused the difference in SO2 concentration. These results suggest the importance of deposition in improving our understanding of ambient concentration behavior.

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

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated sur face ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

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.