Heavy Air Pollution Event Research Articles

Intercomparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1–CMAQ v5.3.1, WRF–Chem v4.1.1, and WRF v3.7.1–CHIMERE v2020r1) in eastern China

Abstract. Two-way coupled meteorology and air quality models, which account for aerosol–radiation–cloud interactions, have been employed to simulate meteorology and air quality more realistically. Although numerous related studies have been conducted, none have compared the performances of multiple two-way coupled models in simulating meteorology and air quality over eastern China. Thus, we systematically evaluated annual and seasonal meteorological and air quality variables simulated by three open-source, widely utilized two-way coupled models (Weather Research and Forecasting (WRF)–Community Multiscale Air Quality (WRF–CMAQ), WRF coupled with chemistry (WRF–Chem), and WRF coupled with a regional chemistry-transport model named CHIMERE (WRF–CHIMERE)) by validating their results with surface and satellite observations for eastern China in 2017. Although we have made every effort to evaluate these three coupled models by using configurations that are as consistent as possible, there are still unavoidable differences between them in their treatments of physical and chemical processes. Our thorough evaluations revealed that all three two-way coupled models captured the annual and seasonal spatiotemporal characteristics of meteorology and air quality reasonably well. Notably, the role of the aerosol–cloud interaction (ACI) in improving the models' performances was limited compared to that of the aerosol–radiation interaction (ARI). The sources of uncertainties and bias in the different ACI schemes in the two-way coupled models were identified. With sufficient computational resources, these models can provide more accurate air quality forecasting to support atmospheric environment management and deliver timely warnings of heavy air pollution events. Finally, we propose potential improvements to two-way coupled models for future research.

A new implementation of FLEXPART with Enviro-HIRLAM meteorological input, and a case study during a heavy air pollution event

ABSTRACT We integrated Enviro-HIRLAM (Environment-High Resolution Limited Area Model) meteorological output into FLEXPART (FLEXible PARTicle dispersion model). A FLEXPART simulation requires meteorological input from a numerical weather prediction (NWP) model. The publicly available version of FLEXPART can utilize either ECMWF (European Centre for Medium-range Weather Forecasts) Integrated Forecast System (IFS) forecast or reanalysis NWP data, or NCEP (U.S. National Center for Environmental Prediction) Global Forecast System (GFS) forecast or reanalysis NWP data. The primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological fields. We compared backward trajectories generated with FLEXPART using Enviro-HIRLAM (both with and without aerosol effects) to trajectories generated using NCEP GFS and ECMWF IFS meteorological inputs, for a case study of a heavy haze event which occurred in Beijing, China in November 2018. We found that results from FLEXPART were considerably different when using different meteorological inputs. When aerosol effects were included in the NWP, there was a small but noticeable difference in calculated trajectories. Moreover, when looking at potential emission sensitivity instead of simply expressing trajectories as lines, additional information, which may have been missed when looking only at trajectories as lines, can be inferred.

PM2.5 Estimation in Day/Night-Time from Himawari-8 Infrared Bands via a Deep Learning Neural Network

Satellite-based PM2.5 estimation is an effective means to achieve large-scale and long-term PM2.5 monitoring and investigation. Currently, most of methods retrieve PM2.5 from satellite-derived aerosol optical depth (AOD) or top-of-atmosphere reflectance (TOAR) during daytime. A few algorithms are also developed to retrieve nighttime PM2.5 from the satellite day–night band and the accuracy is greatly limited by moonlight and artificial light sources. In this study, we utilize the properties of absorption pollutants in infrared spectrum to estimate PM2.5 concentrations from satellite infrared data, thus achieve the PM2.5 estimation in both day and night. Himawari-8 infrared bands data are used for PM2.5 estimation by a specifically designed neural network and loss function. Quantitative results show the satellite derived PM2.5 concentrations correlates with ground-based data well with R2 of 0.79 and RMSE of 15.43 μg · m−3 for hourly PM2.5 estimation. Spatiotemporal distributions of model-estimated PM2.5 over China are also analyzed, and exhibit a highly consistent with ground-based measurements. Dust storms, heavy air pollution and fire smoke events are examined to further demonstrate the efficacy of our model. Our method not only circumvents the intermediate retrievals of AOD, but also enables consistent estimation of PM2.5 concentrations during daytime and nighttime in real-time monitoring.

Considerable contribution of secondary aerosol to wintertime haze pollution in new target of the latest clean air actions in China

Fine particulate matter (PM2.5) in Northeast China was targeted by national-level clean air policy for the first time in 2022, with the release of Action Plan to eliminate heavy air pollution events. In this study, we investigated sources of PM2.5 during three successive winters in Harbin, a megacity in Northeast China, based on observational results from several recent campaigns in 2018–2021. During the 2020–2021 campaign, daytime and nighttime samples were collected in specific months in addition to 24-h integrated measurements, and the two sets of samples were combined in different ways to run a positive matrix factorization model. The source apportionment results suggested that the resolved secondary organic carbon (SOCPMF) had an uncertainty of ∼12%. Secondary aerosols were found to show the following features for the typical winters without agricultural fires. First, SOCPMF could be properly constrained by results from another widely-used approach for SOC estimation, the elemental carbon-tracer method. Second, secondary PM2.5 calculated using SOCPMF and secondary inorganic ions were generally in line with the independent estimations based on air quality data. Third, secondary components accounted for more than 50% of PM2.5 on average and contributed even more significantly during severe haze episodes, which were the focus of the latest Action Plan. This study also found that the wintertime PM2.5 decreased more slowly during 2017–2021 compared to 2013–2017, by ∼1 and 10 μg/m3 per year, respectively, for the metropolitan area where Harbin is located at. Our results highlighted the importance of secondary aerosols for further improving air quality in Northeast China, and for avoiding heavy pollution as required by the latest Action Plan.

Multilayer inversion formation and evolution during persistent heavy air pollution events in the Sichuan Basin, China

The Sichuan Basin (SB) is one of the most air-polluted areas in China. The deep mountain-basin orography and the unique geographic location on the leeward slope of the Tibetan Plateau cause multilayer inversions to occur frequently in winter, which greatly increases the possibility of local heavy pollution. However, the genesis and development mechanisms of the multilayer inversions during the heavy pollution event are unclear. In this study, radiosonde measurements, air quality data, and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data were employed to investigate the formation and evolution of the multilayer inversions during 10 persistent heavy pollution events from 2015 to 2019. The results revealed that >90% of the persistent heavy pollution events in the SB included multilayer inversions. The inversions occurred near the ground (i.e., boundary layer inversion) and at heights of approximately 2000–3800 m above the ground (i.e., lower troposphere inversion, LTI). The large-scale pressure patterns in the middle of the troposphere forced the formation and evolution of the multilayer inversions during the persistent heavy pollution events. Strong mid-level warm air advection induced by a large-scale warm high-pressure ridge was the dominant factor in the formation and maintenance of the multilayer inversion. Furthermore, strong cold advection associated with an approaching large-scale cold low-pressure trough played a prominent role in the weakening and disappearance of the multilayer inversion, leading to the end of the heavy pollution event. The warming over the SB peaked at two heights successively: 650–600 hPa at the start of an event and 700 hPa in the middle of an event. Accordingly, the LTI was enhanced from the start to the middle of an event, and its height decreased. The downward extension of the LTI compressed the diffusion space of pollutants within the basin, leading to further deterioration of the air quality. The southwesterly warm advection at 750–700 hPa triggered by the orographic forcing of the Tibetan Plateau also modulated the generation and development of the LTI.

Evolution of Meteorological Conditions during a Heavy Air Pollution Event under the Influence of Shallow Foehn in Urumqi, China

Evolution of Meteorological Conditions during a Heavy Air Pollution Event under the Influence of Shallow Foehn in Urumqi, China

Vertical changes of PM2.5 driven by meteorology in the atmospheric boundary layer during a heavy air pollution event in central China

Regional PM2.5 transport is a crucial factor affecting air quality, and the meteorological mechanism in the atmospheric boundary layer (ABL) has not been fully understood over the receptor region in the regional transport of air pollutants. Based on the intensive vertical measurements of air pollutants and meteorology in the ABL during a transport-induced heavy air pollution event in Xiangyang, an urban site over a receptor region in central China, we investigated the meteorological mechanism in vertical PM2.5 changes in the ABL for heavy air pollution over the receptor region. Driven by northerly winds, regional PM2.5 transport was built from upstream northern China to downstream central China, where the observed ABL structures were unstable throughout the air pollution event. We assessed the ABL structures with meteorological and PM2.5 profiles at growth, maintenance, and dissipation stages, and elucidated the mechanism of regional PM2.5 transport inducing air pollution over the receptor region with the contribution of thermal and mechanical factors. The regional PM2.5 transport was concentrated in the upper ABL over the downwind receptor region with high PM2.5 concentrations at altitudes of 600–800 m, where the transported PM2.5 peaks were downwards mixed by vertical wind shear, forming the vertical PM2.5 transport from the upper ABL to near-surface in the growth stage; the weakened winds and less unstable structures in the ABL favored the sustained pollution with slight vertical PM2.5 changes in the maintenance stage, which was dominated by thermal factors with 87 % contribution; the removal of PM2.5 was triggered by increasing winds from the upper ABL, activating the dissipation of heavy PM2.5 pollution with the mechanical effect accounting for 60 % in the dissipation stage. These findings could improve our understanding of ABL's influence on air pollution over the receptor region with implications for the regional transport of air pollutants in environmental changes.

A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations

Abstract. This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived AOT data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from 23 to 29 November 2018, during which a heavy air pollution event occurred in northern China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM2.5 concentrations to be closer to the real distribution in northern China, which is of great value for studying heavy air pollution events.

Vertical Changes of Pm2.5 Concentration Driven by Meteorology in the Atmospheric Boundary Layer During a Heavy Air Pollution Event in Central China

Vertical Changes of Pm2.5 Concentration Driven by Meteorology in the Atmospheric Boundary Layer During a Heavy Air Pollution Event in Central China

Meteorological mechanism of regional PM2.5 transport building a receptor region for heavy air pollution over Central China

Regional transport of air pollutants is a key factor affecting air quality over the receptor region, where the meteorological mechanism of regional transport influence has not been fully understood. The Twain-Hu Basin (THB) in central China is located in the downwind area of major pollutant sources over central and eastern China (CEC) under the East Asian winter monsoonal winds. To understand the meteorological mechanism of regional PM2.5 transport building a receptor region for heavy air pollution, an ensemble of 8 typical heavy air pollution events with regional PM2.5 transport in January of 2015–2019 were selected objectively by using the MV-EOF (multivariable empirical orthogonal function) decomposition with multi-source observations, and the meteorological configurations driving the regional PM2.5 transport and building a receptor in the THB with heavy air pollution were investigated. The results showed that PM2.5 from the source area in northern China to the THB was actuated by cold air southward invasion with strong northerly winds in the lower troposphere, and the vertical structure of atmospheric circulation was characterized with the typical pattern of southward advance of cold front with the cold air confronting the warm air mass over the THB area. The warm air mass and the windward side of THB's basin terrain formed a “barrier” in regional transport of PM2.5 over central China, which were conducive to accumulating PM2.5 for heavy air pollution in the THB. Furthermore, an abnormal warm air layer in the middle troposphere acted as the upper “warm lid”, suppressing the vertical PM2.5 diffusion over the receptor region. With such the 3-D atmospheric structure, a key receptor region in the THB for heavy air pollution was built in regional PM2.5 transport over China. These findings could enrich the scientific understanding of the meteorological mechanism on air pollution with regional transport of source-receptor air pollutants in atmospheric environment change.

Foraging trip duration of honeybee increases during a poor air quality episode and the increase persists thereafter.

Increased concentration of airborne particulate matter (PM) in the atmosphere alters the degree of polarization of skylight which is used by honeybees for navigation during their foraging trips. However, little has empirically shown whether poor air quality indeed affects foraging performance (foraging trip duration) of honeybee. Here, we show apparent increases in the average duration of honeybee foraging during and after a heavy air pollution event compared with that of the pre‐event period. The average foraging duration of honeybees during the event increased by 32 min compared with the pre‐event conditions, indicating that 71% more time was spent on foraging. Moreover, the average foraging duration measured after the event did not recover to its pre‐event level. We further investigated whether an optical property (Depolarization Ratio, DR) of dominant PM in the atmosphere and level of air pollution (fine PM mass concentration) affect foraging trip duration. The result demonstrates the DR and fine PM mass concentration have significant effects on honeybee foraging trip duration. Foraging trip duration increases with decreasing DR while it increases with increasing fine PM mass concentration. In addition, the effects of fine PM mass concentration are synergistic with overcast skies. Our study implies that poor air quality could pose a new threat to bee foraging.

Formation mechanism of a severe air pollution event: A case study in the Sichuan Basin, Southwest China

The formation mechanism of air pollution events in the Sichuan Basin (SB), which is the fourth most heavily polluted area in China, has not been fully revealed. This study investigated the formation mechanism of a severe air pollution event over the SB using synoptic approaches and model simulations. The results can be summarized as follows: (1) Heavy air pollution in the SB was characterized by low visibility, low atmospheric boundary layer (ABL) height, high temperature, high relative humidity, strong temperature inversion layer, subsidence in the troposphere, high water vapor content between 500 and 900 hPa, southerly winds in the low troposphere, and surface winds with low speed and irregular direction. (2) Air quality in the SB was closely related to the weather system at 700 hPa over the basin. When the 700 hPa weather system affecting the SB was a high-pressure system, the subsidence and stable atmospheric stratification increased the air pollutant concentrations near the ground. When the 700 hPa weather system affecting the SB was a low-pressure system and the basin was in front of this low-pressure system, southwesterly warm and moist airflow and adiabatic subsidence warming formed the thick temperature inversion layer over the basin. As a result, the temperature inversion layer trapped air pollutants in the basin and induced the heavy air pollution event. When the 700 hPa weather system over the SB was a low-pressure system and the basin was behind the low-pressure system, the dry and cold airflow from the north invaded southward to the basin and broke the temperature inversion layer. Consequently, air pollutants dispersed vertically, resulting in decreased concentrations near the ground. (3) Air pollutants from December 17, 2017 to January 4, 2018 were mainly from local emissions. (4) The WRF-Chem model not only reproduced the variations in PM2.5 concentrations, the ABL height, and the height-time cross-sections of temperature, water vapor content, and wind over Chengdu during the air pollution event, but also revealed the formation mechanism of this heavy air pollution event. The results of this study reveal the formation mechanism of winter heavy air pollution events over the SB and help develop effective regional air quality management strategies to reduce the likelihood of local air pollution events and minimize the adverse impacts of air pollution.

Importance of regional PM2.5 transport and precipitation washout in heavy air pollution in the Twain-Hu Basin over Central China: Observational analysis and WRF-Chem simulation

With observational analysis and WRF-Chem simulation on a heavy air pollution event in January 2019 over the Twain-Hu Basin (THB) in Central China, this study characterized the regional transport of PM2.5 emitted from the North China Plain (NCP) to the THB region in Central China and quantitatively assessed the influence of the regional PM2.5 transport and precipitation washout on PM2.5 change in the wintertime heavy air pollution over the THB. It was found that the THB's heavy air pollution event was exacerbated by the strong northeasterly winds driving a quasi 2-day time lag of regional PM2.5 transport from the NCP to the THB. The multi-scale atmospheric circulations of cold air invasion influenced by East Asian winter monsoon and the terrain block of THB altered the structures of regional PM2.5 transport in deteriorating air quality to the THB. It was assessed for the THB region that the enhancing contribution of regional PM2.5 transport to the high air pollution level reached up to 70.5% in the heavy air pollution, and the precipitation washout could contribute the 55.3% PM2.5 removal to dissipating the PM2.5 pollution over the THB with frequent precipitation and wet environment, distinguishing from the dominance of wind-cleaning air pollution in the other regions in China.

Wavelet periodic and compositional characteristics of atmospheric PM2.5 in a typical air pollution event at Jinzhong city, China

To investigate the contributions of atmospheric particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) to heavy air pollution events in Fen-Wei Plain, China and identify their sources, a combination of wavelet analysis and low-atomic number (Z) particle electron probe X-ray microanalysis (EPMA) was utilized in a typical haze episode lasting 10 days (from Nov. 11 to 20, 2016) at Jinzhong, an inland city adjacent to Taiyuan, the capital of Shanxi Province. A 3-layer wavelet decomposition filtration was performed using the daubechies wavelet functions (db6) and the distribution of the real wavelet transformation coefficients and variance of wavelet series for various pollutants within 240 h was plotted. Five dominant periods of PM2.5 in mass concentration were observed, peaking at 101 h, 144 h, 50–51 h, 27–28 h, and 18 h in sequence from high to low in the wavelet variance chart. They were similar to those of PM10, SO2, and CO and partially overlapped with those of NO2, but different from those of O3, implying that PM2.5 have the same sources as PM10, SO2, and CO and have complicated relations with O3 and NO2. It was further found that the chemical compositions of PM2.5 in the dominant periods made great changes compared to the non-dominant periods. The relative number abundance of elemental carbon (EC) and droplets rich in CNOS (likely the mixture of carbonaceous matter with secondary aerosols such as NH4NO3 and (NH4)2SO4/NH4HSO4) in the first and second dominant period were significantly higher than that in other periods. It is concluded that coal and biomass combustion and secondary particles are still the main contributors to the wintertime heavy air pollution events in Fen-Wei Plain, suggesting that the wavelet analysis combined with low-Z particle EPMA is useful in examination of atmospheric particulate matter's origin, evolution, and roles played in haze events.

Quantification of secondary particle loading during a heavy air pollution event in Beijing: A simplified method based on coal emission indicators

Secondary aerosol (SA) is considered to be an increasingly dangerous air pollutant. However, quantification of SA has suffered from considerable uncertainty due to its poorly understood formation mechanism. In this study, a simplified approach based on characterizing coal combustion emission indicators polonium-210 (210Po), selenium (Se) and arsenic (As) was used to estimate SA loading (increment) during a heavy air pollution event in December 2016 in Beijing. Due to the insignificant input and output of air pollutants as well as the assumption of non-local emissions during this heavy air pollution event, a steady-state method of severe air pollution has been proposed to estimate SA increment (the sum of newly formed secondary inorganic aerosols and secondary organic aerosols) during this typical air pollution event. Corresponding algorithm of the method was developed depending on the characteristics of coal combustion related pollutants (210Po, Se, and As). The results indicated that the median contribution of newly formed SA to total suspended particulates (TSP) during this heavy air pollution event was 42.4% (interquartile range [IQR]: 36.6%–48.8%), which quantitatively confirms the dominant contribution of substantial enhancement of SA to heavy air pollution. Although further verification is needed, this steady-state method of evaluating severe air pollution has potential for quantification of the SA increment.

Concentration Characteristics of PM2.5 and the Causes of Heavy Air Pollution Events in Beijing During Autumn and Winter

To study the changing of characteristics and formation mechanisms of PM2.5 in Beijing during the last two years, particulate matter concentrations, weather conditions, and air-mass trajectories were analyzed during severe pollution episodes in fall and winter 2016-2017 using routine observations and the TrajStat model. Results showed that 13 heavy pollution events, each lasting at least two days, occurred in Beijing. Of these, approximately 61.5% occurred in winter, characterized by heavier pollution concentrations and longer durations than those occurring in autumn. A low-pressure gradient, high humidity, low surface wind speed, low boundary layer, and particular terrain (i. e., being surrounded by mountains on three sides) all contributed to the high occurrence frequency of severe pollution episodes in autumn and winter. During the pollution episodes, the average ratio of PM2.5 to PM10 reached 0.86. The air-masses during the accumulation stage were mainly transported from the northwest, west, southwest, and southeast of Beijing. The southwestern and southeastern transmission paths accounted for 21.6% of the total pollution load. In addition, the WRF-CAMx model was used to quantitatively analyze the contributions of local and external sources to the concentrations of PM2.5 in Beijing during 16-22 December 2016. Based on this analysis, PM2.5 contributions notably varied with different air-masses; in the case of southern air-masses, external sources dominated the PM2.5 concentrations in Beijing and local contributions decreased rapidly; in contrast, in the case of northwestern air-masses, the opposite pattern occurred. Overall, the contribution of local sources to PM2.5 concentrations in Beijing varied from 16.5% to 69.3% during the monitored pollution episodes.

A temperature indicator for heavy air pollution risks (TIP)

This study presents a temperature indicator for heavy air pollution risks (TIP). This TIP indicator is a temperature threshold, at which the concentrations of air pollutants and air pollution indices easily reach their maxima. A connotation discussion ascertains that TIP is intrinsically associated with the atmospheric structure and static stability in the planetary boundary layer, especially during stagnant weather and moderately cold temperatures. Thus, TIP offers a simple measure of meteorological conditions that reflect the boundary layer static characteristics. It therefore provides a simple measure of air pollution potential, and can be used to quantify the potential air pollution severity for a given pollution emission level. From the data collected in China, TIP increases gradually from north to south and decreases slightly from east to west, which essentially indicates a function of latitude and altitude. A simple regressive function is built for TIP, and the resulting TIP index further confirms that it is indicative of the potential heavy air pollution events across the country. Being an easy-to-obtain and simple-to-use meteorological parameter, TIP can be used for air pollution potential assessment and prediction, as well as pollution prevention and control applications.

Characteristics of the factors influencing transportation and accumulation processes during a persistent pollution event in the middle reaches of the Yangtze River, China

Extreme pollution event is a major environmental concern in the middle reaches of the Yangtze River, which located at the position of a transportation hub connecting the four major air pollution areas in China. In this study, we focused on a continuous heavy air pollution event that affected Hubei from 12 to 24 January 2018, and examined the meteorological conditions, regional transport features, boundary-layer characteristics, and the evolution of PM and gaseous pollutants in Xiangyang (XY), Jingmen (JM), Jingzhou (JZ), Yichang (YC), Xiaogan (XG), and Wuhan (WH). The results showed that this pollution event was the result of joint action of fog, haze, and fog-haze transformation weather. The pure haze was mainly concentrated at the pollution-transport channel (XY and JM) of Hubei. The explosive growth of PM concentrations was more obvious in XY, JM, and JZ than that in YC, XG, and WH, with the growth and reduction rates of PM2.5 at XY station, at 20.11 and 19.50 μg/(m3·h), respectively. During the explosive growth period, northerly winds were dominant at XY, JM, JZ, XG, and WH stations, with large and weak wind speed (WS) resulted in significantly increased PM2.5 concentrations in XY and JM (transport), and in JM, JZ, and YC (accumulation), respectively. The height of northward airflow reached 2000 m in the main pollutant transport channel of Hubei. The upper and lower inversion layers would be enhanced before the explosive growth of PM concentration significantly, then be weakened by continuous transport of the northerly airflow. The concentrations of SO2, NO2, and CO decreased with the increase in WS during the explosive growth period, and O3 concentration reached maximum value at a WS of 3.5–5 m/s. The correlation analysis indicated significant differences in the effects of transport and accumulation.

Impact of low-pressure systems on winter heavy air pollution in the northwest Sichuan Basin, China

Abstract. The cities of Chengdu, Deyang, and Mianyang in the northwest Sichuan Basin are part of a rapidly developing urban agglomeration adjoining the eastern slopes of the Tibetan Plateau. Heavy air pollution events have frequently occurred over these cities in recent decades, but the effects of meteorological conditions on these pollution events are unclear. We explored the effects of weather systems on winter heavy air pollution from 1 January 2006 to 31 December 2012 and from 1 January 2014 to 28 February 2017. A total of 10 heavy air pollution events occurred during the research period and 8 of these took place while the region was affected by a dry low-pressure system at 700 hPa. When the urban agglomeration was in front of the low-pressure system and the weather conditions were controlled by a warm southerly air flow, a strong temperature inversion appeared above the atmospheric boundary layer acting as a lid. Forced by this strong inversion layer, the local secondary circulation was confined to the atmospheric boundary layer, and the horizontal wind speed in the lower troposphere was low. As a result, vertical mixing and horizontal dispersion in the atmosphere were poor, favoring the formation of heavy air pollution events. After the low-pressure system had transited over the region, the weather conditions in the urban agglomeration were controlled by a dry and cold air flow from the northwest at 700 hPa. The strong inversion layer gradually dissipated, the secondary circulation enhanced and uplifted, and the horizontal wind speed in the lower troposphere also increased, resulting in a sharp decrease in the concentration of air pollutants. The strong inversion layer above the atmospheric boundary layer induced by the low-pressure system at 700 hPa thus played a key role in the formation of heavy air pollution during the winter months in this urban agglomeration. This study provides scientific insights for forecasting heavy air pollution in this region of China.

TOF–SIMS surface analysis of chemical components of size–fractioned urban aerosols in a typical heavy air pollution event in Beijing

Size–fractioned atmospheric aerosol particles were collected during a typical heavy air pollution event in Beijing. The organic and inorganic components on the surfaces of the samples were analyzed using time–of–flight secondary ion mass spectrometry (TOF–SIMS). The variation characteristics of the surface chemical composition and influencing factors were studied, and the possible sources of these chemical compositions were identified through principal component analysis. The results showed that inorganic components such as crustal elements and sulfate, and organic components such as aliphatic hydrocarbons and oxygen–containing organic groups were present. Some surface components, such as polycyclic aromatic hydrocarbons, heavy metals and fluorides may exert adverse effects on human health. The species and relative percentages of the chemical components varied with particle size, diurnal and pollution progress. During a heavy pollution event, the species and relative percentages of secondary components such as oxygen–containing organic groups and sulfurous compounds increased, indicating that particles aged during this event. The surface chemical composition of the aerosol particles was affected mainly by emissions from coal combustion and motor vehicles. In addition, air pollution, meteorological factors, and air mass transport also exerted a significant effect on the surface chemical composition of aerosol particles.