The feedback between aerosol and meteorological variables in the atmospheric boundary layer over the North China Plain (NCP) is analyzed by conducting numerical experiments with and without the aerosol direct and indirect effects via a coupled meteorology and aerosol/chemistry model (WRF-Chem). The numerical experiments are performed for the period of 2–26 January 2013, during which a severe fog–haze event (10–15 January 2013) occurred, with the simulated maximum hourly surface PM_2.5 concentration of ~600 ug m⁻³, minimum atmospheric visibility of ~0.3 km, and 10–100 hours of simulated hourly surface PM_2.5 concentration above 300 ug m⁻³ over NCP. A comparison of model results with aerosol feedback against observations indicates that the model can reproduce the spatial and temporal characteristics of temperature, relative humidity (RH), wind, surface PM_2.5 concentration, atmospheric visibility, and aerosol optical depth reasonably well. Analysis of model results with and without aerosol feedback shows that during the fog–haze event aerosols lead to a significant negative radiative forcing of −20 to −140 W m⁻² at the surface and a large positive radiative forcing of 20–120 W m⁻² in the atmosphere and induce significant changes in meteorological variables with maximum changes during 09:00–18:00 local time (LT) over urban Beijing and Tianjin and south Hebei: the temperature decreases by 0.8–2.8 °C at the surface and increases by 0.1–0.5 °C at around 925 hPa, while RH increases by about 4–12% at the surface and decreases by 1–6% at around 925 hPa. As a result, the aerosol-induced equivalent potential temperature profile change shows that the atmosphere is much more stable and thus the surface wind speed decreases by up to 0.3 m s⁻¹ (10%) and the atmosphere boundary layer height decreases by 40–200 m (5–30%) during the daytime of this severe fog–haze event. Owing to this more stable atmosphere during 09:00–18:00, 10–15~January, compared to the surface PM_2.5 concentration from the model results without aerosol feedback, the average surface PM_2.5 concentration increases by 10–50 μg m⁻³ (2–30%) over Beijing, Tianjin, and south Hebei and the maximum increase of hourly surface PM_2.5 concentration is around 50 (70%), 90 (60%), and 80 μg m⁻³ (40%) over Beijing, Tianjin, and south Hebei, respectively. Although the aerosol concentration is maximum at nighttime, the mechanism of feedback, by which meteorological variables increase the aerosol concentration most, occurs during the daytime (around 10:00 and 16:00 LT). The results suggest that aerosol induces a more stable atmosphere, which is favorable for the accumulation of air pollutants, and thus contributes to the formation of fog–haze events.

A total of 14 chemical transport models (CTMs) participated in the first topic of the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. These model results are compared with each other and an extensive set of measurements, aiming to evaluate the current CTMs' ability in simulating aerosol concentrations, to document the similarities and differences among model performance, and to reveal the characteristics of aerosol components in large cities over East Asia. In general, these CTMs can well reproduce the spatial–temporal distributions of aerosols in East Asia during the year 2010. The multi-model ensemble mean (MMEM) shows better performance than most single-model predictions, with correlation coefficients (between MMEM and measurements) ranging from 0.65 (nitrate, ${\mathrm{NO}}_{\mathrm{3}}^{-}$ ) to 0.83 (PM_2.5). The concentrations of black carbon (BC), sulfate (${\mathrm{SO}}_{\mathrm{4}}^{\mathrm{2}-}$ ), and PM₁₀ are underestimated by MMEM, with normalized mean biases (NMBs) of −17.0 %, −19.1 %, and −32.6 %, respectively. Positive biases are simulated for ${\mathrm{NO}}_{\mathrm{3}}^{-}$ (NMB = 4.9 %), ammonium (${\mathrm{NH}}_{\mathrm{4}}^{+}$ ) (NMB = 14.0 %), and PM_2.5 (NMB = 4.4 %). In comparison with the statistics calculated from MICS-Asia phase II, frequent updates of chemical mechanisms in CTMs during recent years make the intermodel variability of simulated aerosol concentrations smaller, and better performance can be found in reproducing the temporal variations of observations. However, a large variation (about a factor of 2) in the ratios of SNA (sulfate, nitrate, and ammonium) to PM_2.5 is calculated among participant models. A more intense secondary formation of ${\mathrm{SO}}_{\mathrm{4}}^{\mathrm{2}-}$ is simulated by Community Multi-scale Air Quality (CMAQ) models, because of the higher SOR (sulfur oxidation ratio) than other models (0.51 versus 0.39). The NOR (nitric oxidation ratio) calculated by all CTMs has larger values (∼0.20) than the observations, indicating that overmuch ${\mathrm{NO}}_{\mathrm{3}}^{-}$ is simulated by current models. NH₃-limited condition (the mole ratio of ammonium to sulfate and nitrate is smaller than 1) can be successfully reproduced by all participant models, which indicates that a small reduction in ammonia may improve the air quality. A large coefficient of variation (CV > 1.0) is calculated for simulated coarse particles, especially over arid and semi-arid regions, which means that current CTMs have difficulty producing similar dust emissions by using different dust schemes. According to the simulation results of MMEM in six large Asian cities, different air-pollution control plans should be taken due to their different major air pollutants in different seasons. The MICS-Asia project gives an opportunity to discuss the similarities and differences of simulation results among CTMs in East Asian applications. In order to acquire a better understanding of aerosol properties and their impacts, more experiments should be designed to reduce the diversities among air quality models.

Spatiotemporal variations of ozone (O₃) and nitrogen oxide (NO_x) mixing ratios from 14 state-of-the-art chemical transport models (CTMs) are intercompared and evaluated with O₃ observations in East Asia, within the framework of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III). This study was designed to evaluate the capabilities and uncertainties of current CTMs simulations for Asia and to provide multi-model estimates of pollutant distributions. These models were run by 14 independent groups working in China, Japan, South Korea, the United States and other countries/regions. Compared with the previous phase of MICS-Asia (MICS-Asia II), the evaluation with observations was extended from 4 months to 1 full year across China and the western Pacific Rim. In general, model performance levels for O₃ varied widely by region and season. Most models captured the key patterns of monthly and diurnal variation of surface O₃ and its precursors in the North China Plain and western Pacific Rim but failed to do so for the Pearl River Delta. A significant overestimation of surface O₃ was evident from May to September/October and from January to May over the North China Plain, the western Pacific Rim and the Pearl River Delta. Comparisons drawn from observations show that the considerable diversity in O₃ photochemical production partly contributed to this overestimation and to high levels of inter-model variability in O₃ for North China. In terms of O₃ soundings, the ensemble average of models reproduced the vertical structure for the western Pacific, but overestimated O₃ levels to below 800 hPa in the summer. In the industrialized Pearl River Delta, the ensemble average presented an overestimation for the lower troposphere and an underestimation for the middle troposphere. The ensemble average of 13 models for O₃ did not always exhibit superior performance compared with certain individual models in contrast with its superior value for Europe. This finding suggests that the spread of ensemble-model values does not represent all of the uncertainties of O₃ or that most MICS-Asia III models missed key processes. This study improved the performance of modeling O₃ in March at Japanese sites compared with MICS-Asia II. However, it overpredicted surface O₃ concentrations for western Japan in July, which was not found by MICS-Asia II. Major challenges still remain with regard to identifying the sources of bias in surface O₃ over East Asia in CTMs.

The Model Inter-Comparison Study for Asia (MICS-Asia) phase III was conducted to promote understanding of regional air quality and climate change in Asia, which have received growing attention due to the huge amount of anthropogenic emissions worldwide. This study provides an overview of acid deposition. Specifically, dry and wet deposition of the following species was analyzed: S (sulfate aerosol, sulfur dioxide (SO₂), and sulfuric acid (H₂SO₄)), N (nitrate aerosol, nitrogen monoxide (NO), nitrogen dioxide (NO₂), and nitric acid (HNO₃)), and A (ammonium aerosol and ammonia (NH₃)). The wet deposition simulated by a total of nine models was analyzed and evaluated using ground observation data from the Acid Deposition Monitoring Network in East Asia (EANET). In the phase III study, the number of observation sites was increased from 37 in the phase II study to 54, and southeast Asian countries were newly added. Additionally, whereas the analysis period was limited to representative months of each season in MICS-Asia phase II, the phase III study analyzed the full year of 2010. The scope of this overview mainly focuses on the annual accumulated deposition. In general, models can capture the observed wet deposition over Asia but underestimate the wet deposition of S and A, and show large differences in the wet deposition of N. Furthermore, the ratio of wet deposition to the total deposition (the sum of dry and wet deposition) was investigated in order to understand the role of important processes in the total deposition. The general dominance of wet deposition over Asia and attributions from dry deposition over land were consistently found in all models. Then, total deposition maps over 13 countries participating in EANET were produced, and the balance between deposition and anthropogenic emissions was calculated. Excesses of deposition, rather than of anthropogenic emissions, were found over Japan, northern Asia, and southeast Asia, indicating the possibility of long-range transport within and outside of Asia, as well as other emission sources. To improve the ability of models to capture the observed wet deposition, two approaches were attempted, namely, ensemble and precipitation adjustment. The ensemble approach was effective at modulating the differences in performance among models, and the precipitation-adjusted approach demonstrated that the model performance for precipitation played a key role in better simulating wet deposition. Finally, the lessons learned from the phase III study and future perspectives for phase IV are summarized.

Beijing has experienced a rapid urbanization in the last few decades and has been suffering from serious air pollution during recent years. The Weather Research and Forecasting‐Chem model is used to quantify the effects of urbanization on regional climate and air quality and those of urban heat island (UHI) mitigation strategy on urban air quality in Beijing, with a special focus on the impacts under different weather conditions (heat waves in summer and polluted days in winter). The modification of rural land use into urban impervious surface significantly increases 2‐m temperature (T₂) and planetary boundary layer height but decreases 2‐m relative humidity (RH₂) and 10‐m wind speed (WS₁₀) in urban Beijing, which further leads to the increases in surface‐layer O₃ concentrations of 9.5 ppbv in summer and 1.8 ppbv in winter and the decreases in PM_2.5 concentrations of 16.6 μg m⁻³ in summer and 26.2 μg m⁻³ in winter. Compared with normal days (clean days), the UHI intensity is enhanced by 11.1% during heat waves in summer (by 16.7% during polluted days in winter). Although increasing urban albedo is an effective mitigation strategy to decrease UHI intensity, it worsens the urban air quality. When the urban albedo increases from 0.2 to 0.85, the daily average PM_2.5 concentrations are increased by 10.2 (6.1) μg m⁻³ in summer (in winter), and the daily maximum O₃ concentrations are increased by 12.8 ppbv under heat waves in summer.