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Abstract. Air quality models such as the EPA Community Multiscale Air Quality (CMAQ) require meteorological data as part of the input to drive the chemistry and transport simulation. The Meteorology-Chemistry Interface Processor (MCIP) is used to convert meteorological data into CMAQ-ready input. Key shortcoming of such one-way coupling include: excessive temporal interpolation of coarsely saved meteorological input and lack of feedback of atmospheric pollutant loading on simulated dynamics. We have developed a two-way coupled system to address these issues. A single source code principle was used to construct this two-way coupling system so that CMAQ can be consistently executed as a stand-alone model or part of the coupled system without any code changes; this approach eliminates maintenance of separate code versions for the coupled and uncoupled systems. The design also provides the flexibility to permit users: (1) to adjust the call frequency of WRF and CMAQ to balance the accuracy of the simulation versus computational intensity of the system, and (2) to execute the two-way coupling system with feedbacks to study the effect of gases and aerosols on short wave radiation and subsequent simulated dynamics. Details on the development and implementation of this two-way coupled system are provided. When the coupled system is executed without radiative feedback, computational time is virtually identical when using the Community Atmospheric Model (CAM) radiation option and a slightly increased (∼8.5 %) when using the Rapid Radiative Transfer Model for GCMs (RRTMG) radiation option in the coupled system compared to the offline WRF-CMAQ system. Once the feedback mechanism is turned on, the execution time increases only slightly with CAM but increases about 60 % with RRTMG due to the use of a more detailed Mie calculation in this implementation of feedback mechanism. This two-way model with radiative feedback shows noticeably reduced bias in simulated surface shortwave radiation and 2-m temperatures as well improved correlation of simulated ambient ozone and PM 2.5 relative to observed values for a test case with significant tropospheric aerosol loading from California wildfires.

Abstract.Trends in air quality across the Northern Hemisphere over a 21-year period were simulated using the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting (WRF) simulations and internally consistent historical emission inventories obtained from EDGAR. Thorough comparison with several ground observation networks mostly over Europe and North America was conducted to evaluate the model performance as well as the ability of CMAQ to reproduce the observed trends in air quality over the past 2 decades in three regions: eastern China, the continental United States and Europe.The model successfully reproduced the observed decreasing trends in SO 2 , NO 2 , 8 h O 3 maxima, SO 2− 4 and elemental carbon (EC) in the US and Europe. However, the model fails to reproduce the decreasing trends in NO − 3 in the US, potentially pointing to uncertainties of NH 3 emissions. The model failed to capture the 6-year trends of SO 2 and NO 2 in CN-API (China -Air Pollution Index) from 2005 to 2010, but reproduced the observed pattern of O 3 trends shown in three World Data Centre for Greenhouse Gases (WDCGG) sites over eastern Asia. Due to the coarse spatial resolution employed in these calculations, predicted SO 2 and NO 2 concentrations are underestimated relative to all urban networks, i.e., US-AQS (US -Air Quality System; normalized mean bias (NMB) = −38 % and −48 %), EU-AIRBASE (European Air quality data Base; NMB = −18 and −54 %) and CN-API (NMB = −36 and −68 %). Conversely, at the rural network EU-EMEP (European Monitoring and Evaluation Programme), SO 2 is overestimated (NMB from 4 to 150 %) while NO 2 is simulated well (NMB within ±15 %) in all seasons. Correlations between simulated and observed O 3 wintertime daily 8 h maxima (DM8) are poor compared to other seasons for all networks. Better correlation between simulated and observed SO 2− 4 was found compared to that for SO 2 . Underestimation of summer SO 2− 4 in the US may be associated with the uncertainty in precipitation and associated wet scavenging representation in the model. The model exhibits worse performance for NO − 3 predictions, particularly in summer, due to high uncertainties in the gas/particle partitioning of NO − 3 as well as seasonal variations of NH 3 emissions. There are high correlations (R > 0.5) between observed and simulated EC, although the model underestimates the EC concentration by 65 % due to the coarse grid resolution as well as uncertainties in the PM speciation profile associated with EC emissions.The almost linear response seen in the trajectory of modeled O 3 changes in eastern China over the past 2 decades suggests that control strategies that focus on combined control of NO x and volatile organic compound (VOC) emissions with a ratio of 0.46 may provide the most effective means for O 3 reductions for the region devoid of nonlinear response potentially associated with NO x or VOC limitation resulting from alternate strategies. The response of O 3 is ...