Search Results (54)

The rapid formation of secondary nitrate (NO₃⁻) contributes significantly to the nocturnal increase of PM_2.5 and has been shown to be a critical factor for aerosol pollution in the North China Plain (NCP) region in summer. To explore the nocturnal NO₃⁻ formation pathways and the influence of ozone (O₃) on NO₃⁻ production, the WRF-CMAQ model was utilized to simulate O₃ and PM_2.5 co-pollution events in the NCP region. The simulation results demonstrated that heterogeneous hydrolysis of dinitrogen pentoxide (N₂O₅) accounts for 60% to 67% of NO₃⁻ production at night (22:00 to 05:00) and is the main source of nocturnal NO₃⁻. O₃ enhances the formation of NO₃ radicals, thereby further promoting nocturnal N₂O₅ production. In the evening (20:00 to 21:00), O₃ sustains the formation of hydroxyl (OH) radicals, resulting in the reaction between OH radicals and nitrogen dioxide (NO₂), which accounts for 48% to 64% of NO₃⁻ formation. Our results suggest that effective control of O₃ pollution in NCP can also reduce NO₃⁻ formation at night. Full article

The significant increase in ambient ozone (O₃) levels across China highlights the urgent need to investigate the sources and mechanisms driving regional O₃ events, particularly in densely populated urban areas. This study focuses on Xi’an, located in northwestern China on the Guanzhong Plain near the Qinling Mountains, where the unique topography contributes to pollutant accumulation. Urbanization and industrial activities have significantly increased pollutant emissions. Utilizing the Weather Research and Forecasting–Community Multiscale Air Quality Model (WRF-CMAQ), we analyzed the contributions of specific regional and industrial sources to rising O₃ levels, particularly during an atypical winter event characterized by unusually high concentrations. Our findings indicated that boundary conditions were the primary contributor to elevated O₃ levels during this event. Notably, Xianyang and Baoji accounted for 30% and 22% of the increased O₃ levels in Xi’an, respectively. Additionally, residential sources and transportation accounted for 31% and 28% of the O₃ increase. Within the Xi’an metropolitan area, Baqiao District (18–27%) and Weiyang District (23–30%) emerged as leading contributors. The primary industries contributing to this rise included residential sources (28–37%) and transportation (35–43%). These insights underscore the need for targeted regulatory measures to mitigate O₃ pollution in urban settings. Full article

Particulate matter (PM) in the atmosphere poses significant risks to both human health and the environment. Specifically, PM2.5, particulate matter with a diameter less than 2.5 micrometers, has been linked to increased rates of cardiovascular and respiratory diseases. In South Korea, concerns about PM2.5 exposure have grown due to its potential for causing premature death. This study aims to estimate high-resolution exposure concentrations of PM2.5 across South Korea from 2015 to 2021. We integrated data from the Community Multiscale Air Quality (CMAQ) model with surface air quality measurements, the Weather Research Forecast (WRF) model, the Normalized Difference Vegetation Index (NDVI), and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Optical Depth (AOD) satellite data. These data, combined with multiple regression analyses, allowed for the correction of PM2.5 estimates, particularly in suburban areas where ground measurements are sparse. The simulated PM2.5 concentration showed strong correlations with observed values R (ranging from 0.88 to 0.94). Spatial distributions of annual PM2.5 showed a significant decrease in PM2.5 concentrations from 2015 to 2021, with some fluctuation due to the COVID-19 pandemic, such as in 2020. The study produced highly accurate daily average high-resolution PM2.5 exposure concentrations. Full article

A severe ozone episode occurred in cities along the Yangtze River of Jiangsu Province (UAYRJS) from 6 to 8 September 2022, with daily maximum 8-h average ozone concentrations in the range of 65.8–119 ppb, peaking in Nanjing on 7 September. We used the air quality model WRF-CMAQ-ISAM and the Lagrange trajectory model HYSPLIT to quantify the ozone contribution of each region and analyze the causes and regional transmission pathways of ozone pollution in the UAYRJS. Based on simulated emissions, we also estimated the contribution of biogenic volatile organic compounds. We found that weather has a negative impact on pollution, and ozone pollution tracks the movement of the Western Pacific Subtropical High. UAYRJS was affected by oceanic pollution, and there was a mutual influence among the area’s cities. On 6 September, the ozone in UAYRJS was mostly locally generated (50–98%); on 7 September, it was dominated by extra-regional transport (50–80%). Isoprene concentrations in UAYRJS increased by 0.03–0.1 ppb on 6 and 7 September compared with 5 September. Sensitivity testing showed that the hourly ozone concentration increased by 0.1–27.8 ppb (7.6–19.1%) under the influence of biogenic emissions. The results provide a scientific basis for future ozone control measures. Full article

High-temporal resolution and timely emission estimates are essential for developing refined air quality management policies. Considering the advantages of extensive coverage, high reliability, and near real-time capabilities, in this work, electric power big data (EPBD) was first employed to obtain accurate hourly resolved facility-level air pollutant emissions information from the cement industries in Tangshan City, China. Then, the simulation optimization was elucidated by coupling the data with the weather research and forecasting (WRF)-community multiscale air quality (CMAQ) model. Simulation results based on estimated emissions effectively captured the hourly variation, with the NMB within ±50% for NO₂ and PM_2.5 and R greater than 0.6 for SO₂. Hourly PM_2.5 emissions from clinker production enterprises exhibited a relatively smooth pattern, whereas those from separate cement grinding stations displayed a distinct diurnal variation. Despite the remaining underestimation and/or overestimation of the simulation concentration, the emission inventory based on EPBD demonstrates an enhancement in simulation results, with RMSE, NMB, and NME decreasing by 9.6%, 15.8%, and 11.2%, respectively. Thus, the exploitation of the vast application potential of EPBD in the field of environmental protection could help to support the precise prevention and control of air pollution, with the possibility of the early achievement of carbon peaking and carbon neutrality targets in China and other developing countries. Full article

In recent years, O₃ pollution events have occurred frequently in Chinese cities. Utilizing the WRF-CMAQ model, this study analyzed the causes of an O₃ pollution event in Suqian on 18–21 June 2020, considering meteorological conditions, process analysis, and source analysis. It also designed 25 emission reduction scenarios to explore more effective O₃ emission reduction strategies. The results show that meteorological conditions such as temperature and wind field play an important role in the formation and accumulation of O₃. During the heavy pollution period, the contribution of vertical transport (VTRA) and horizontal transport (HTRA) to O₃ concentration is significantly enhanced. The photochemical reactions of precursors, such as NOx and VOCs transported from long distances and O₃ directly transported to Suqian from other regions, contribute greatly to O₃ pollution in Suqian; local sources contribute very little, between 12.22% and 18.33%. Based on the simulation of 25 emission reduction scenarios, it was found that excessive emission reduction of NOx is not conducive to the reduction of O₃ concentration, and it is best to control the emission reduction ratio at about 10%. Without affecting normal production and life, it is recommended to reduce VOCs as much as possible, particularly those generated by traffic sources. Full article

The escalating concern regarding increasing air pollution and its impact on the health risks associated with PM_2.5 in developing countries necessitates attention. Thus, this study utilizes the WRF-CMAQ model to simulate the effects of meteorological conditions on PM_2.5 levels in Changchun, a typical city in China, during January 2017 and January 2020. Additionally, it introduces a novel health risk-based air quality index (NHAQI) to assess the influence of meteorological parameters and associated health risks. The findings indicate that in January 2020, the 2-m temperature (T2), 10-m wind speed (WS10), and planetary boundary layer height (PBLH) were lower compared to those in 2017, while air pressure exhibited a slight increase. These meteorological parameters, characterized by reduced wind speed, heightened air pressure, and lower boundary layer height—factors unfavorable for pollutant dispersion—collectively contribute to the accumulation of PM_2.5 in the atmosphere. Moreover, the NHAQI proves to be more effective in evaluating health risks compared to the air quality index (AQI). The annual average decrease in NHAQI across six municipal districts from 2017 to 2020 amounts to 18.05%. Notably, the highest health risks are observed during the winter among the four seasons, particularly in densely populated areas. The pollutants contributing the most to the total excess risk (ERtotal) are PM_2.5 (45.46%), PM10 (33.30%), and O3 (13.57%) in 2017, and PM_2.5 (67.41%), PM10 (22.32%), and O3 (8.41%) in 2020. These results underscore the ongoing necessity for PM_2.5 emission control measures while emphasizing the importance of considering meteorological parameters in the development of PM_2.5 reduction strategies. Full article

Regional haze often occurs after the New Year holiday. To explore the characteristics of PM_2.5 pollutions under the influence of the New Year’s Day effect, this study analyzed the spatiotemporal changes relating to PM_2.5 during and around the New Year’s Day holiday in China from 2015 to 2022, and used the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to study the effects of human activities and meteorological factors on PM_2.5 pollutions, as well as the differences in the contributions of different industries to PM_2.5 pollutions. The results show that for the entire study period (i.e., before, during, and after the New Year’s Day holiday) from 2015 to 2022, the average concentrations of PM_2.5 in China decreased by 41.9% overall. In 2019~2022, the New Year’s Day effect was significant, meaning that the average concentrations of PM_2.5 increased by 18.9~46.8 μg/m³ from before to after the New Year’s Day holiday, with its peak occurring (64.3~74.9 μg/m³) after the holiday. In terms of spatial differences, the average concentrations of PM_2.5 were higher in the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and central China. Moreover, the Beijing–Tianjin–Hebei region and its surrounding areas, the Chengdu–Chongqing region, the Fenwei Plain, and the middle reaches of the Yangtze River region were greatly affected by the New Year’s Day effect. Human activities led to higher increases in PM_2.5 in Henan, Hubei, Hebei, and Anhui on 3 and 4 January 2022. If the haze was accompanied by cloudy days or weak precipitation, the accumulation of surface water vapor and atmospheric aerosols further increased the possibility of heavy pollution. It was found that, for the entire study period, PM_2.5 generated by residential sources contributed the vast majority (60~100 μg/m³) of PM_2.5 concentrations, and that the main industry sources that caused changes in time distributions were industrial and transportation sources. Full article

Cotton production in Xinjiang is increasing year by year, and the improved crop yields have had an impact on the environment. This study investigated the changes in six significant pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) from 2017 to 2022 in Xinjiang. We compiled a biomass burning emission inventory to make the MEIC emission inventory more complete. The Weather Research and Forecasting Community Multiscale Air Quality (WRF–CMAQ) model was employed to simulate air quality in different reduction scenarios in 2025, and it explored ways to alleviate air pollution in the main cotton areas of Xinjiang. The result shows that the main pollutant in Xinjiang is particulate matter (PM particles with aerodynamic diameters less than 2.5 µm and 10 µm), and the concentration of particulate matter decreased from the northern mountains toward the south. The concentrations of O₃ (ozone) were highest in summer, while the concentrations of other pollutants were high in autumn and winter. If the pollution is not strictly controlled in terms of emission reduction, it is impossible to achieve the target of a 35 μg/m³ PM_2.5 concentration in the planting area. In the scenario of enhanced emission reduction measures and the scenario of higher intensity emission reduction measures, there was a failure to reach the target, despite the reduction in the PM_2.5 concentration. In the best emission reduction scenario, PM_2.5 in Xinjiang is expected to drop to 22.5 μg/m³ in November and 34 μg/m³ in March, respectively. Therefore, in the optimal emission reduction scenario, the target of 35 μg/m³ will be reached. This study emphasized the importance of future air pollution mitigation and identified a feasible pathway to achieve the target of 35 μg/m³ PM_2.5 concentration by 2025. The research findings provide useful insights for the local government which can be used to develop strategies aimed at mitigating substantial pollution emissions. Full article

The problem of atmospheric complex pollution led by PM_2.5 and O₃ has become an important factor restricting the improvement of air quality in China. In drawing on observations and Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model simulations, this study analyzed the characteristics and causes of a regional PM_2.5-O₃ complex pollution episode in North China Plain, in the period from 3 to 5 April 2019. The results showed that in static and stable weather conditions with high temperature and low wind speed, despite photochemical reactions of O₃ near the ground being weakened by high PM_2.5 concentrations, a large amount of O₃ generated through gas-phase chemical reactions at high altitudes was transported downwards and increased the O₃ concentrations at the ground level. The high ground-level O₃ could facilitate both the conversion of SO₂ and NO₂ into secondary inorganic salts and volatile organic compounds into secondary organic aerosols, thereby amplifying PM_2.5 concentrations and exacerbating air pollution. The contributions of transport from outside sources to PM_2.5 (above 60%) and O₃ (above 46%) increased significantly during the episode. This study will play an instrumental role in helping researchers to comprehend the factors that contribute to complex pollution in China, and also offers valuable references for air pollution management. Full article

We conducted an evaluation of the impact of meteorological factor forecasts on the prediction of fine particles in Chengdu, China, during autumn and winter, utilizing the European Cooperation in Science and Technology (COST)733 objective weather classification software and the Community Multiscale Air Quality model. This analysis was performed under four prevailing weather patterns. Fine particle pollution tended to occur under high-pressure rear, homogeneous-pressure, and low-pressure conditions; by contrast, fine particle concentrations were lower under high-pressure bottom conditions. The forecasts of fine particle concentrations were more accurate under high-pressure bottom conditions than under high-pressure rear and homogeneous-pressure conditions. Moreover, under all conditions, the 24 h forecast of fine particle concentrations were more accurate than the 48 and 72 h forecasts. Regarding meteorological factors, forecasts of 2 m relative humidity and 10 m wind speed were more accurate under high-pressure bottom conditions than high-pressure rear and homogeneous-pressure conditions. Moreover, 2 m relative humidity and 10 m wind speed were important factors for forecasting fine particles, whereas 2 m air temperature was not. Finally, the 24 h forecasts of meteorological factors were more accurate than the 48 and 72 h forecasts, consistent with the forecasting of fine particles. Full article

As air quality has improved rapidly in recent years, the public has become more interested in whether a famous snow peak, Yaomei Feng on the Tibetan Plateau, can be seen from Chengdu, a megacity located on the western plain of the Sichuan Basin, east of the plateau. Therefore, a threshold-method-based forecasting system for snow peak sighting was developed in this study. Variables from numerical models, including cloud–water mixing ratio, cloud cover over snow peak, water mixing ratio, PM_2.5 concentration, and ground solar radiation, were used in the snow peak sighting forecast system. Terrain occlusion rate of each model grid was calculated. Monte Carlo simulations were applied for threshold determination. A WRF-CMAQ hindcast was conducted for 2020, owing to insufficient observation data, hindcast results on the snow peak sighting were compared with posts collected from social media. Estimations showed that the snow peak sighting forecast system performed well in reflecting the monthly trend of snow peak sightings, and the hindcast results matched the daily observations, especially from May to August. Accuracy of the snow peak sighting forecast model was 78.9%, recall value was 57.1%, and precision was 24.4%. Full article

This is the first study that quantifies explicitly the impact of present vegetation on concentrations and depositions, considering simultaneously its effects on meteorology, biogenic emissions, dispersion, and dry deposition in three European cities: Bologna, Milan, and Madrid. The behaviour of three pollutants (O₃, NO_2, and PM10) was investigated considering two different scenarios, with the actual vegetation (VEG) and without it (NOVEG) for two months, representative of summer and winter seasons: July and January. The evaluation is based on simulations performed with two state-of-the-art atmospheric modelling systems (AMS) that use similar but not identical descriptions of physical and chemical atmospheric processes: AMS-MINNI for the two Italian cities and WRF-CMAQ for the Spanish city. The choice of using two AMS and applying one of them in two cities has been made to ensure the robustness of the results needed for their further generalization. The analysis of the spatial distribution of the vegetation effects on air concentrations and depositions shows that they are highly variable from one grid cell to another in the city area, with positive/negative effects or high/low effects in adjacent cells being observed for the three pollutants investigated in all cities. According to the pollutant, on a monthly basis, the highest differences in concentrations (VEG-NOVEG) produced by vegetation were estimated in July for O₃ (−7.40 μg/m³ in Madrid and +2.67 μg/m³ in Milan) and NO₂ (−3.01 μg/m³ in Milan and +7.17 μg/m³ in Madrid) and in January for PM10 (−3.14 μg/m³ in Milan +2.01 μg/m³ in Madrid). Thus, in some parts of the cities, the presence of vegetation had produced an increase in pollutant concentrations despite its efficient removal action that ranges from ca. 17% for O₃ in Bologna (January) to ca. 77% for NO₂ in Madrid (July). Full article

The Community Multiscale Air Quality (CMAQ) model with the 7th generation aerosol module (AERO7) was employed to simulate organic aerosol (OA) in Seoul, Korea, for the year 2016. The goal of the present study includes the 1-year simulation of OA using WRF-CMAQ with recently EPA-developed AERO7 with pcVOC (potential VOC from combustion) scale factor revision and analysis of the seasonal behavior of OA surrogate species in Seoul. The AERO7, the most recent version of the aerosol module of the CMAQ model, includes a new secondary organic aerosol (SOA) species, pcSOA (potential SOA from combustion), to resolve the inherent under-prediction problem of OA. The AERO7 classified OA into three groups: primary organic aerosol (POA), anthropogenic SOA (ASOA), and biogenic SOA (BSOA). Each OA group was further classified into 6~15 individual OA surrogate species according to volatility and oxygen content to model the aging of OA and the formation of SOA. The hourly emissions of POA and SOA precursors were compiled and fed into the CMAQ to successfully simulate seasonal variations of OA compositions and ambient organic-matter to organic-carbon ratios (OM/OC). The model simulation showed that the POA and ASOA were major organic groups in the cool months (from November to March) while BSOA was a major organic group in the warm months (from April to October) in Seoul. The simulated OM/OCs ranged from 1.5~2.1 in Seoul, which agreed well with AMS measurements in Seoul in May 2016. Full article

This paper explored the changes of six significant pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) in Jilin City during the coronavirus disease 2019 (COVID-19) epidemic in 2022, and compared them with the same period of previous years to analyze the impact of anthropogenic emissions on the concentration of pollutants; The Weather Research and Forecasting Community Multiscale Air Quality (WRF–CMAQ) model was used to evaluate the effect of meteorological factors on pollutant concentration. The results showed that except for O₃, the concentrations of the other five pollutants decreased significantly, with a range of 21–47%, during the lockdown period caused by the government’s shutdown and travel restrictions. Compared with the same period in 2021, the decrease of PM_2.5 was only 25% of PM₁₀. That was because there was still a large amount of PM_2.5 produced by coal-fired heating during the blockade period, which made the decrease of PM_2.5 more minor. A heavy pollution event caused by adverse meteorological conditions was found during the lockdown period, indicating that only controlling artificial emissions cannot eliminate the occurrence of severe pollution events. The WRF–CMAQ results showed that the lower pollutant concentration in 2022 was not only caused by the reduction of anthropogenic emissions but also related to the influence of favorable meteorological factors (higher planetary boundary layer thickness, higher wind speed, and higher temperature). Full article