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Increasing the model resolution is expected to be one way for improving air quality forecasts in urban areas. In this study, we evaluate the model performance in a large city at various resolutions to examine the best resolution for air pollution simulations. The comparison with measurements at a station near the traffic emissions shows the advantage of using high resolutions for capturing the extreme values. The statistical evaluation indicates that the highest model resolution (33 m) provides the best results for NOX concentration distributions near the traffic roads, while the improvement for roadside O3 with decreasing grid spacing stops at a certain point. The best model performance for the areas with a distance to the pollution sources is with the resolution of 100–300 m, at which the transport errors are equivalent to the emission biases. Plain Language Summary: As the increasing needs in the air quality forecasting in large cities, there is a trend in decreasing the model grid spacing to obtain more detailed pollutants distributions between neighborhoods or at street levels. To determine at which resolution the model can obtain the best representation of the pollutants' concentrations, we evaluate the model performance at different resolutions taking Hong Kong as an illustration. The analysis shows that the improvement with increasing model resolution is not monotonic for the areas far away from the intense emissions; however, the model with the highest resolution (33 m) reproduces the best results for the short‐lived species near the pollution sources. Key Points: Increasing horizontal resolution to 33 m improves the prediction of NOX near the traffic emissionsThe threshold of the model resolution is around 300 m for areas with a distance to the pollution sourcesThe changes of model performances with varied resolutions are different for NOX and O3 [ABSTRACT FROM AUTHOR]

Understanding the role of transport and photochemistry is essential to mitigate tropospheric ozone (O 3) pollution within a region. In previous studies, the O 3 concentration budget has been widely used to determine the contributions of two processes to the variations of O 3 concentrations. These studies often conclude that local photochemistry is the main cause of regional O 3 pollution; however, they fail to explain why O 3 in a targeted region is often primarily derived from O 3 and/or its precursors transported from the outside regions, as reported by many studies of O 3 source apportionment. Here, we present a method to calculate the hourly contributions of O 3 -related processes to the variations of not only the mean O 3 concentration but also the total O 3 mass (the corresponding budgets are noted as the O 3 concentration and mass budget, respectively) within the atmospheric boundary layer (ABL) of the concerned region. Based on the modelling results of WRF-CMAQ (Weather Research and Forecasting and Community Multiscale Air Quality), the two O 3 budgets were applied to comprehensively understand the effects of transport and photochemistry on the O 3 pollution over the Pearl River Delta (PRD) region in China. Quantified results demonstrate the different role of transport and photochemistry when comparing the two O 3 budgets: photochemistry drives the rapid increase of O 3 concentrations during the day, whereas transport, especially vertical exchange through the ABL top, controls both rapid O 3 mass increase in the morning and decrease in the afternoon. The diurnal changes of the transport contributions in the two O 3 budgets highlight the influences of the ABL diurnal cycle and regional wind fields on regional O 3 pollution. Through high contributions to the O 3 mass increase in the morning, transport determines that most O 3 in the PRD originates from the global background and emissions outside the region. However, due to the simultaneous rapid increase of ABL volumes, this process only has a relatively limited effect on O 3 concentration increase compared to photochemistry, and transport effect on the regional sources of O 3 cannot be illustrated by the O 3 concentration budget. For future studies targeting O 3 and other secondary pollutants with moderately long atmospheric lifetimes (e.g. fine particulate matter and some of its components), insights from both concentration and mass budgets are required to fully understand the role of transport, chemistry and other related processes. [ABSTRACT FROM AUTHOR]

Using the CAM‐chem Model, we simulate the response of chemical species in the free troposphere to scenarios of primary pollutant emission reductions during the COVID‐19 pandemic. Zonally averaged ozone in the free troposphere during Northern Hemisphere spring and summer is found to be 5%–15% lower than 19‐yr climatological values, in good agreement with observations. About one third of this anomaly is attributed to the reduction scenario of air traffic during the pandemic, another third to the reduction scenario of surface emissions, the remainder to 2020 meteorological conditions, including the exceptional springtime Arctic stratospheric ozone depletion. For the combined emission reductions, the overall COVID‐19 reduction in northern hemisphere tropospheric ozone in June is less than 5 ppb below 400 hPa, but reaches 8 ppb at 250 hPa. In the Southern Hemisphere, COVID‐19 related ozone reductions by 4%–6% were masked by comparable ozone increases due to other changes in 2020. Plain Language Summary: The reduction in the emissions of primary air pollutants during the 2020 COVID‐19 pandemic has generated perturbations in the chemical state of the atmosphere. A global Earth system model that accounts for chemical, physical, and dynamical processes in the atmosphere and for the coupling between the atmosphere, the ocean and the land surface, indicates that the abundance of tropospheric ozone was significantly reduced during the pandemic in response to realistic scenarios of reduced emissions of primary pollutants associated with restrictions of air traffic and economic activities. These simulated findings are consistent with observed ozone anomalies during the summer of 2020. Key Points: The ozone concentration in the northern extratropical free troposphere was 5%–15% lower in May and June 2020 relative to climatologyA third of this anomaly is attributed to meteorological conditions including stratospheric Arctic air with abnormally low ozoneThe assumed reduction in surface and aircraft emissions associated with the COVID‐19 pandemic can explain an ozone anomaly of 4%–8% [ABSTRACT FROM AUTHOR]

We use the global Community Earth System Model to investigate the response of secondary pollutants (ozone O3, secondary organic aerosols SOA) in different parts of the world in response to modified emissions of primary pollutants during the COVID‐19 pandemic. We quantify the respective effects of the reductions in NOx and in volatile organic carbon (VOC) emissions, which, in most cases, affect oxidants in opposite ways. Using model simulations, we show that the level of NOx has been reduced by typically 40% in China during February 2020 and by similar amounts in many areas of Europe and North America in mid‐March to mid‐April 2020, in good agreement with space and surface observations. We show that, relative to a situation in which the emission reductions are ignored and despite the calculated increase in hydroxyl and peroxy radicals, the ozone concentration increased only in a few NOx‐saturated regions (northern China, northern Europe, and the US) during the winter months of the pandemic when the titration of this molecule by NOx was reduced. In other regions, where ozone is NOx‐controlled, the concentration of ozone decreased. SOA concentrations decrease in response to the concurrent reduction in the NOx and VOC emissions. The model also shows that atmospheric meteorological anomalies produced substantial variations in the concentrations of chemical species during the pandemic. In Europe, for example, a large fraction of the ozone increase in February 2020 was associated with meteorological anomalies, while in the North China Plain, enhanced ozone concentrations resulted primarily from reduced emissions of primary pollutants. Plain Language Summary: With the reduction in economic activities following the COVID‐19 pandemic outbreak in early 2020, most emissions of air pollutants (i.e., nitrogen oxides [NOx], carbon monoxide [CO], sulfur dioxide [SO2], volatile organic carbon [VOC], black carbon [BC], organic carbon [OC]) have decreased substantially during several months in different regions of the world. This unintended global experiment offered a glimpse into a potential future in which air quality would be improved. Here, a global atmospheric model is used to assess the changes in the chemical composition of the atmosphere during the pandemic period and in the related chemical processes that lead to the formation of ozone (O3) and secondary organic aerosols (SOA). The study illustrates the nonlinearity of the air quality response to reduced NOx and VOC emissions, which depends on the chemical environment including the background level of nitrogen oxides. Meteorological variability can lead to anomalies in the concentration of chemical species with magnitudes that are as large or even larger than the perturbations due to COVID‐induced changes in the emissions. Key Points: During the COVID‐19 lockdown, the atmospheric concentration of primary pollutants (NOx, VOCs, CO, SO2) was considerably reducedThe concentration of secondary pollutants increased in NOx‐saturated areas and decreased in NOx‐limited areasThe response of the chemical system depends on the relative changes in NOx and VOC emissions, and is affected by weather variability [ABSTRACT FROM AUTHOR]

Global and regional chemical transport models of the atmosphere are based on the assumption that chemical species are completely mixed within each model grid box. However, in reality, these species are often segregated due to localized sources and the influence of topography. In order to investigate the degree to which the rates of chemical reactions between two reactive species are reduced due to the possible segregation of species within the convective boundary layer, we perform large-eddy simulations (LESs) in the mountainous region of Hong Kong Island. We adopt a simple chemical scheme with 15 primary and secondary chemical species, including ozone and its precursors. We calculate the segregation intensity due to inhomogeneity in the surface emissions of primary pollutants and due to turbulent motions related to topography. We show that the inhomogeneity in the emissions increases the segregation intensity by a factor of 2–5 relative to a case in which the emissions are assumed to be uniformly distributed. Topography has an important effect on the segregation locally, but this influence is relatively limited when considering the spatial domain as a whole. In the particular setting of our model, segregation reduces the ozone formation by 8 %–12 % compared to the case with complete mixing, implying that the coarse-resolution models may overestimate the surface ozone when ignoring the segregation effect. [ABSTRACT FROM AUTHOR]

During the COVID‐19 outbreak that took place in early 2020, the economic activities in China were drastically reduced and accompanied by a strong reduction in the emission of primary air pollutants. On the basis of measurements made at the monitoring stations operated by the China National Environmental Monitoring Center, we quantify the reduction in surface PM2.5, NO2, CO, and SO2 concentrations in northern China during the lockdown, which started on 23 January 2020. We find that, on the average, the levels of surface PM2.5 and NO2 have decreased by approximately 35% and 60%, respectively, between the period 1 and 22 January 2020 and the period 23 January and 29 February 2020. At the same time, the mean ozone concentration has increased by a factor 1.5–2. In urban area of Wuhan, where drastic measures were adopted to limit the spread of the coronavirus, similar changes in the concentrations of PM2.5, NO2, and ozone are found. Plain Language Summary: During the COVID‐19 outbreak that took place in China in early 2020, the surface emissions of air pollutants including nitrogen oxides (a product of combustion by traffic, industry, and residential activity) have been severely reduced following the lockdown of major cities. The level of aerosol pollution (particulate matter) has also been substantially reduced. These conditions have led to a substantial increase (a factor 1.5 to 2) in the concentration of surface ozone, a powerful oxidant that is responsible for severe health problems including pulmonary and cardiac diseases. The atmospheric concentration of tropospheric ozone results from complex photochemical processes that involve the presence of nitrogen oxides, hydrocarbons, and water vapor. Key Points: Surface measurements made at more than 800 monitoring stations show that the mean levels of PM2.5 and NO2 in northern China have decreased by approximately 35% and 60%, respectively, after the lockdown following the COVID‐19 outbreak of early 2020Simultaneously, the ozone concentration, a secondary pollutant responsible for severe health problems, has increased by a factor 1.5–2The same type of behavior was observed specifically in the city of Wuhan, where COVID‐19 outbreak was first reported [ABSTRACT FROM AUTHOR]

Tropospheric ozone affects the Earth's radiative balance, oxidative capacity, and air quality, yet the long‐term ozone trend in East Asia and its driver(s) remain poorly understood. Here we present ozone measurements obtained during 1994–2018 on China's southern coast. The measurement location intercepts China's outflow most of the time and the inflow of tropical maritime air during summer. We found an overall increase in the ozone level (0.35 ppbv/year), and the increase occurred mainly during the first half of the 25‐year period but appeared to level off in recent years in Chinese outflow. Large ozone increase (~20% per decade) was found in the maritime air. Model simulations show that recent weather conditions have reduced maritime ozone, counteracting the impact of the growing Southeast Asia's emissions. Our results fill the gap in the long‐term ozone trend in Asia and highlight the complex interaction of weather and emissions in driving the ozone change. Plain Language Summary: Tropospheric ozone has great influence on environmental issues ranging from air quality, to ecosystem productivity and to climate warming. Assessing the ozone impacts in fast‐developing Asia has been hindered by lacking long‐term measurements. We present here the longest continuous record of surface ozone in nonurban areas of tropical Asia. Using comprehensive tools, we reveal that the measurements on the south China's coast detected different ozone trends in air masses from eastern China (increasing in early years but stabilizing lately) and from Southeast Asia (continuously rising and at the largest rate). The latter finding is particularly striking, and we show that the recent weather patterns counteracted the expected increase of ozone due to emissions increases from Southeast Asia. Our results fill the gap in the long‐term ozone trends in Asia and highlight the complex interaction of weather and emission in driving the ozone trend. Key Points: We present the first long‐term record of ozone and CO in tropical East Asia, which shows that ozone has increased at the rate of 0.35 ppbv/yearThe ozone increase occurred during the first half of the 25‐year period and appears to have leveled off during recent years in the outflow from ChinaOzone shows the largest increase in maritime air mass, and weather change has counteracted the ozone increase associated with Southeast Asia's growing emissions [ABSTRACT FROM AUTHOR]

An operational multi-model forecasting system for air quality has been developed to provide air quality services for urban areas of China. The initial forecasting system included seven state-of-the-art computational models developed and executed in Europe and China (CHIMERE, IFS, EMEP MSC-W, WRF-Chem-MPIM, WRF-Chem-SMS, LOTOS-EUROS and SILAMtest). Several other models joined the prediction system recently, but are not considered in the present analysis. In addition to the individual models, a simple multi-model ensemble was constructed by deriving statistical quantities such as the median and the mean of the predicted concentrations. The prediction system provides daily forecasts and observational data of surface ozone, nitrogen dioxides and particulate matter for the 37 largest urban agglomerations in China (population higher than 3 million in 2010). These individual forecasts as well as the multi-model ensemble predictions for the next 72 hours are displayed as hourly outputs on a publicly accessible web site (www.marcopolo-panda.eu). In this paper, the performance of the predictions system (individual models and the multi-model ensemble) for the first operational year (April 2016 until June 2017) has been analysed through statistical indicators using the surface observational data reported at Chinese national monitoring stations. This evaluation aims to investigate a) the seasonal behavior, b) the geographical distribution and c) diurnal variations of the ensemble and model skills. Statistical indicators show that the ensemble product usually provides the best performance compared to the individual model forecasts. The ensemble product is robust even if occasionally some individual model results are missing. Overall and in spite of some discrepancies, the air quality forecasting system is well suited for the prediction of air pollution events and has the ability to provide alert warning (binary prediction) of air pollution events if bias corrections are applied to improve the ozone predictions. [ABSTRACT FROM AUTHOR]