Haze Pollution Events Research Articles

Daytime and night-time patterns in PM2.5 concentrations over Palembang City of Indonesia using MERRA-2 reanalysis data

ABSTRACT Palembang has sustained heavy haze pollution events that are related to decrease public health quality. Because ground-based PM2.5 observation in the city has some limitations, such as spatial and temporal coverages. Thus, in this study, we applied the potential of using the surface mass concentration PM2.5 data acquired by the MERRA-2 satellite to predict daytime and night-time PM2.5 levels during heavy haze events in Palembang City. Results of the study revealed that the highest PM2.5 level was about 160 µg/m3 at 02:00 (night-time), while the lowest PM2.5 level was about 50 µg/m3 at 14:00 (daytime). Spatiotemporal variation of PM2.5 over the study area showed that more than half of the area showed PM2.5 above 90 µg/m3 at night. Stable wind conditions (2 m/s) and air temperature (29°C), and relative humidity (74%) in the study area have contributed to particulate matter accumulation. The study concluded that PM2.5 acquired by the MERRA-2 satellite could provide a new reliable source for assessing severe air pollution events.

Impacts of Northward Typhoons on Autumn Haze Pollution Over North China Plain

AbstractAlthough air quality in China has improved substantially over recent years, haze pollution events still occur frequently, especially over the North China Plain (NCP). Previous studies showed that typhoons are conducive to regional pollution events in eastern China; however, the underlying mechanism and quantitative understanding of the typhoons' impact on haze pollution remain unclear there. Here, based on ground‐based and satellite observations, reanalysis data, and model simulations, we show that northward typhoons approaching China are essential for autumn haze pollution over NCP. Elevated relative humidity levels and enhanced pollution accumulation, caused by northward typhoons and the corresponding high‐pressure systems, are responsible for the pollution enhancements over NCP. Compared with episodes without typhoon influence, cities near Taihang and Yan Mountain suffer from heavier haze pollution when typhoons approach, with PM2.5 concentrations increasing from 87.1 to 106.4 μg m−3. More water vapor from the Yellow and Bohai Seas and pollutants from eastern China are transported to these cities by typhoon‐induced southeasterly wind anomalies, facilitating the chemical formation of aerosols there. In addition, by the block of mountains, these southeasterly wind anomalies also lead to stronger local accumulation over cities and an elevation of pollutants along the mountains. What is more, with the implementation of emission reduction, the relative changes of PM2.5 concentrations between typhoon‐induced episodes and no‐typhoon episodes increase. This work highlights the importance of understanding the impact of synoptical weather on PM2.5 transport, accumulation, and formation processes in haze pollution mitigation in eastern China.

Characteristics and Generation Mechanism of Secondary Inorganic Ions in PM2.5 in Changsha-Zhuzhou-Xiangtan City Group

Secondary inorganic ions, the main components of atmospheric PM2.5, are a dominant contributor to haze formation. The detailed characteristics and main generation mechanism of secondary inorganic ions in PM2.5 are still unclear in the Changsha-Zhuzhou-Xiangtan City Group, which is suffering from severe haze pollution, particularly in the autumn and winter seasons. For our study, we collected PM2.5 samples in November 2020 and January 2021 from four urban sites in the Changsha-Zhuzhou-Xiangtan City Group. Secondary inorganic components such as SO42-, NO3-, and NH4+ in PM2.5 were quantified. The average values(μg·m-3) of ρ(SO42-), ρ(NO3-), and ρ(NH4+) in autumn and winter were(5.2±2.5) and(7.9±4.8),(4.1±2.2) and(7.2±4.2), and(17.1±10.5) and(7.8±5.2), respectively. During the heavy haze pollution events in winter, the sum of ρ(SO42-), ρ(NO3-), and ρ(NH4+)(SNA) contributed 72.7% to the growth of PM2.5 mass concentration, and ρ(NO3-) accounted for 41.2%. This result suggested that the generation of NO3- was the key factor leading to the formation of winter haze pollution. In the polluted stage, high aerosol water content(AWC) promoted the rapid secondary generation of SNA, whereas adverse meteorological conditions also led to the accumulation of pollutants. The values of sulfur oxidation rate(SOR) and nitrogen oxidation rate(NOR) were still high in the dissipation stage. It indicated that the PM2.5 concentration fell due to the reduction in primary emissions and favorable weather conditions in dissipation, instead of the weakening of secondary generation of SNA. Compared to that in autumn, the higher AWC concentration, pH value, and lower temperature in winter were the main factors for the higher ρ(NO3-)/ρ(PM2.5) and NOR values in the Changsha-Zhuzhou-Xiangtan City Group. At the same time, the heterogeneous reaction was the main generation pathway of NO3-, when the AWC concentration was high in winter. Affected by aerosol pH value and generation rate, the liquid-phase oxidation reactions of H2O2 and SO2 were the main generation pathways of SO42- in autumn and winter in the Changsha-Zhuzhou-Xiangtan City Group. Compared to that in autumn, the higher AWC was more conducive to forming SO42-, which led to higher SOR in winter.

Response of PM2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model

In December 2019, the New Crown Pneumonia (the COVID-19) outbroke around the globe, and China imposed a nationwide lockdown starting as early as January 23, 2020. This decision has significantly impacted China's air quality, especially the sharp decrease in PM2.5 (aerodynamic equivalent diameter of particulate matter less than or equal to 2.5 μm) pollution. Hunan Province is located in the central and eastern part of China, with a “horseshoe basin” topography. The reduction rate of PM2.5 concentrations in Hunan province during the COVID-19 (24.8%) was significantly higher than the national average (20.3%). Through the analysis of the changing character and pollution sources of haze pollution events in Hunan Province, more scientific countermeasures can be provided for the government. We use the Weather Research and Forecasting with Chemistry (WRF-Chem, V4.0) model to predict and simulate the PM2.5 concentrations under seven scenarios before the lockdown (2020.1.1–2020.1.22) and during the lockdown (2020.1.23–2020.2.14). Then, the PM2.5 concentrations under different conditions is compared to differentiate the contribution of meteorological conditions and local human activities to PM2.5 pollution. The results indicate the most important cause of PM2.5 pollution reduction is anthropogenic emissions from the residential sector, followed by the industrial sector, while the influence of meteorological factors contribute only 0.5% to PM2.5. The explanation is that emission reductions from the residential sector contribute the most to the reduction of seven primary contaminants. Finally, we trace the source and transport path of the air mass in Hunan Province through the Concentration Weight Trajectory Analysis (CWT). We found that the external input of PM2.5 in Hunan Province is mainly from the air mass transported from the northeast, accounting for 28.6%–30.0%. To improve future air quality, there is an urgent need to burn clean energy, improve the industrial structure, rationalize energy use, and strengthen cross-regional air pollution synergy control.

Study of winter haze pollution events in Jinan (China)

A comprehensive study of the formation process of winter haze pollution in Jinan, China, was conducted using ground and satellite observation data from January 2 to January 13, 2022. According to the variations in the pollutant concentrations, three haze pollution events occurred in the Jinan area during this period. Compared to haze pollution event 1, event 2 lasted longer and exhibited a cumulative growth state with hourly PM2.5 values peaking at 250 μg/m3. This was primarily caused by a mixture of local and nearby pollutants emitted in Jinan. Haze pollution event 3 was shorter and showed a similar trend to event 2, but the event dissipated rapidly after it was generated. Moreover, unfavorable weather factors, such as lower wind speeds, a stable inversion layer, and higher relative humidity, contributed to pollution accumulation and haze event formations. In addition, important photochemical processes also influenced haze pollution formation. The results of this study revealed the haze pollution formation process in Jinan. These results are helpful for promoting the study of regional climate changes and provide a reference for the government to prevent and control haze pollution in eastern China.

Aircraft observations on a continuous haze pollution event in Shijiazhuang area

A continuous haze event was recorded on November 14th∼17th, 2020 over Shijiazhuang. Two flights of King-air 350 meteorological research aircraft were performed on November 14th and 16th for the retrieval and observations of meteorological elements, aerosols, and black carbon. In this study, we combined airborne data with air pollution data (PM2.5), ground meteorological data, and ERA-5 reanalysis data to describe the vertical distribution of aerosols (namely 0.1–3.0 μm) and black carbon. We further explicated the formation of this haze event. PM2.5 pollution dominated this haze event, and the highest concentration of PM2.5 was 209 μg/m3. The intensity and height of thermal layers highly linked with the vertical transport of pollution. The highest number concentration of aerosols and black carbon was found below the thermal layers on both airborne sounding days. On the 14th, both BC and aerosol concentrations showed unimodal distribution, and the highest concentrations of BC and aerosols were 12683 ng/m3 and 6965.125#/L at 250 m within layer Ⅰ. The intensity of the thermal layer near-ground was weaker on the 16th that the number concentrations of BC and aerosols also remained at high levels in layer Ⅱ. Backward trajectories of air mass indicated the long-range transport of pollution contributed to the high level of pollution on the 16th. Vapor conditions were more favorable for aerosols growth through moisture absorption. The maximum concentration of 943.58#/L was recorded at particles with a diameter of 0.4 μm on the 16th, while 749.26#/L was reached at 0.14 μm on the 14th. The corresponding height was consistent with the height of maximum concentration in the vertical distribution.

Seasonal and Diurnal Characteristics of the Vertical Profile of Aerosol Optical Properties in Urban Beijing, 2017–2021

Seasonal and diurnal characteristics of the vertical profiles of aerosol properties are essential for detecting the regional transport and the climatic radiative effects of aerosol particles. We have studied the seasonal and diurnal characteristics of the vertical distribution of aerosols in urban Beijing from 2017 to 2021 based on long-term Raman–Mie LiDAR observations. The influence of the vertical distribution of aerosols, the meteorological conditions within the boundary layer, the optical–radiometric properties of aerosols, and their interconnections, were investigated during a heavy haze pollution event in Beijing from 8 to 15 February 2020 using both meteorological and sun photometer data. The aerosol extinction coefficient was highest in summer (0.4 km−1), followed by winter (0.35 km−1), and roughly equal in spring and autumn (0.3 km−1). The aerosol extinction coefficient showed clear daily variations and was different in different seasons as a result of the variation in the height of the boundary layer. During the haze pollution event, the particulate matter mainly consisted of scattered spherical fine particles and the accumulation time of pollutants measured via the AOD440nm and PM2.5 mass concentration was different as a result of the hygroscopic growth of the aerosol particles. This growth increased scattering and led to an increase in the aerosol optical depth. The vertical transport of particulate matter also contributed to the increase in the aerosol optical depth.

A Novel Algorithm of Haze Identification Based on FY3D/MERSI-II Remote Sensing Data

Since 2013, frequent haze pollution events in China have been attracting public attention, generating a demand to identify the haze areas using satellite observations. Many studies of haze recognition algorithms are based on observations from space-borne imagers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Advanced Himawari Imager (AHI). Since the haze pixels are frequently misidentified as clouds in the official cloud detection products, these algorithms mainly focus on recovering them from clouds. There are just a few studies that provide a more precise distinction between haze and clear pixels. The Medium Resolution Imaging Spectrometer II (MERSI-II), the imager aboard the FY-3D satellite, has similar bands to those of MODIS, hence, it appears to have equivalent application potential. This study proposes a novel MERSI haze mask (MHAM) algorithm to directly categorize haze pixels in addition to cloudy and clear ones. This algorithm is based on the fact that cloudy and clear pixels exhibit opposing visible channel reflectance and infrared channel brightness temperature characteristics, and clear pixels are relative brighter, and as well as this, there is a positive difference between their apparent reflectance values, at 0.865 μm and 1.64 μm, respectively, over bright surfaces. Compared with the Aqua/MODIS and MERSI-II official cloud detection products, these two datasets treat the dense aerosol loadings as certain clouds, possible clouds and possible clear pixels, and they treat distinguished light or moderate haze as possible clouds, possible clear pixels and certainly clear pixels, while the novel algorithm is capable of demonstrating the haze region’s boundary in a manner that is more substantially consistent with the true color image. Using the PM2.5 (particle matter with a diameter that is less than 2.5 μm) data monitored by the national air quality monitoring stations as the test source, the results indicated that when the ground-based PM2.5 ≥ 35 μg/cm3 is considered to be haze days, the samples with the recognition rate that is higher than 85% accounted for 72.22% of the total samples. When PM2.5 ≥ 50 μg/cm3 is considered as haze days, 83.33% of the samples had an identification rate that was higher than 85%. A cross-comparison with similar research methods showed that the method proposed in this study had better sensitivity to bright surface clear and haze areas. This study will provide a haze mask for subsequent quantitative inversion of aerosol characteristics, and it will further exert the application benefits of MERSI-II instrument aboard on FY3D satellite.

Quantifying the formation pathways of nitrate in size-segregated aerosols during winter haze pollution

Nitrate (NO3−) is an important acidic component in haze pollution. The NO3− formation pathways for bulk aerosols have been studied thoroughly, leaving the size-segregated NO3− formation mechanisms underexplored. By coupling nitrate dual isotopes with aerosol chemical compositions, we studied size-segregated aerosols collected during winter haze pollution events at Chengdu, China. Different formation mechanisms for the size-segregated NO3− were analyzed. For fine particles (0.43–2.1 μm), NO3− was dominantly formed under NH4+ enriched conditions, during which the SIAR (stable isotope analysis in R) model suggested that N2O5 hydrolysis, NO3 + VOCs (volatile organic compounds) and NO2 + OH homogeneous reactions contributed 38–42 %, 32–38 %, and 22–30 % of NO3− production, respectively. For coarse particles (>3.3 μm), majority of NO3− was produced through the reaction of gas-phase HNO3 with CaCO3 (63–71 %). This work revealed differential formation pathways of size-segregated NO3− and provided quantitative insights on information on NO3− formation during the haze pollution.

Significant formation of sulfate aerosols contributed by the heterogeneous drivers of dust surface

Abstract. The importance of dust heterogeneous oxidation in the removal of atmospheric SO2 and formation of sulfate aerosols is not adequately understood. In this study, the Fe-, Ti-, and Al-bearing components, Na+, Cl−, K+, and Ca2+ of the dust surface, were discovered to be closely associated with the heterogeneous formation of sulfate. Regression models were then developed to make a reliable prediction of the heterogeneous reactivity based on the particle chemical compositions. Further, the recognized gas-phase, aqueous-phase, and heterogeneous oxidation routes were quantitatively assessed and kinetically compared by combining the laboratory work with a modelling study. In the presence of 55 µg m−3 airborne dust, heterogeneous oxidation accounts for approximately 28.6 % of the secondary sulfate aerosols during nighttime, while the proportion decreases to 13.1 % in the presence of solar irradiation. On the dust surface, heterogeneous drivers (e.g. transition metal constituents, water-soluble ions) are more efficient than surface-adsorbed oxidants (e.g. H2O2, NO2, O3) in the conversion of SO2, particularly during nighttime. Dust heterogeneous oxidation offers an opportunity to explain the missing sulfate source during severe haze pollution events, and its contribution proportion in the complex atmospheric environments could be even higher than the current calculation results. Overall, the dust surface drivers are responsible for the significant formation of sulfate aerosols and have profound impacts on the atmospheric sulfur cycling.

Coupled-decoupled turbulence structures of stable boundary layer during heavy haze pollution events

Heavy haze pollution events are closely related to the turbulent structure of the stable boundary layer (SBL). SBL can be divided into two regimes, weak(coupled) and strong(decoupled). The weak SBL conforms to the classical turbulent theory and couples with the surface and different heights, whereas the strong SBL does not conform and decouples. However, the thresholds between coupled and decoupled SBL have not been determined in haze pollution events. Five levels of turbulence observation data from two severe haze pollution cases observed at the 255 m meteorological tower in Tianjin were employed to address this dilemma. The first case was analyzed in detail, and the second case was used for verification. The occurrence frequency of SBL was approximately 50% during the two haze pollution cases. The wind speed thresholds distinguishing coupled and decoupled SBL are: 2.5 m s−1 at 40 m, 4.0 m s−1 at 80 m, and 5.0 m s−1 at 120 m. The decoupled SBLs accounted for >70% of SBLs in haze pollution events. The turbulent structures notably differed between coupled and decoupled SBL events. In a decoupled SBL, the scalar concentration at different heights was substantially higher, the strength and occurrence frequency of sub-mesoscale motion were larger, and turbulent barrier effects occurred. Moreover, there was an inverse gradient transport and a smaller spatiotemporal scale of turbulent eddies. Therefore, there was a weaker turbulent kinetic energy, flux, and turbulent correlation across the layers in the decoupled SBL. The results reveal the failure of Monin-Obukhov similarity theory and traditional turbulent energy spectrum theory in a decoupled SBL. Wind speed thresholds can be widely used in the severe haze pollution simulation. The results of this study also indicate that decoupled SBL requires further study and attention in haze pollution events to improve the accuracy of pollutant concentration forecasting.

Mechanism of the effect of vertically propagating internal gravity waves on turbulence barrier and pollutant diffusion during heavy haze episodes

During heavy haze episodes, especially the cumulative stage (CS) of pollutants, strong turbulence intermittency and the resulting turbulence barrier effect (i.e., a phenomenon that turbulence at certain heights may disappear forming a laminar flow as if there is a barrier layer impeding the vertical turbulent exchange) suppress the vertical diffusion of pollutants, leading to high PM2.5 concentrations. However, there are still some short-time removal processes of pollutants occurring at different heights in the CS, accompanied with interesting non-simultaneous drop or opposite variation of PM2.5 concentrations at different heights. The ubiquitous internal gravity waves (IGWs) in the stable boundary layer (SBL) may play a critical role in the above situation, as they are closely related to the intermittent turbulence bursts appearing in the persistent weak turbulent motions. In this study, two representative heavy haze pollution cases were chosen to demonstrate the above speculation using five layers of turbulence data, two layers of pressure fluctuations and three layers of PM2.5 concentrations. Results showed that the non-simultaneous drop or opposite variation of PM2.5 concentrations was associated with the destruction of turbulence barrier by the vertical propagation of IGWs. IGWs generated by some certain mechanisms, such as nonhomogeneous terrain and wind shear around the low-level jet (LLJ), can propagate upward or downward with the upward or downward development of the temperature inversion layer. The vertically propagating IGWs then triggered intermittent increasing turbulence layer by layer. Turbulence between layers reconnected sequentially and turbulence barriers were broken in turn. The enhanced turbulent exchange expedited the pollutant diffusion, thus the PM2.5 concentrations at different heights varied non-simultaneously even inversely. This study provides a good explanation for the positive effects of sub-mesoscale motions such as IGWs on triggering intermittent increasing turbulence and facilitating the diffusion of pollutants during heavy haze pollution events.

Characteristics, Sources, and SOAP of VOCs During Winter in Jiyuan

Haze pollution events often occur in the heavy industry city of Jiyuan. Volatile organic compounds (VOCs) are the precursors of secondary organic aerosol (SOA), which accounts for 15%-20% of particulate matter (PM2.5). Here, PM2.5, O3, VOCs, and trace gases were monitored by using online instruments in Jiyuan from December 1st to 31st. The characteristics, sources, and secondary organic aerosol potential (SOAP) of VOCs were analyzed. The mean concentrations of TVOC were (54.3±27.5)×10-9. Alkanes, halocarbons, and alkynes were the predominant VOCs. The positive matrix factorization model was used to identify and apportion VOCs sources. Eight major sources of VOCs were identified, which included liquefied petroleum gas (LPG) or natural gas (NG), the polyvinyl chloride (PVC) industry, vehicular exhaust, the coking industry, solvent usage, industry, technological process, and fuel evaporation. The SOAP of aromatics was the largest. Among them, BTEXs were the dominant contributors to SOAP.

Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ

Abstract. High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by −64 % but overestimates nitrate by +36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model, which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced PM2.5, implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate + nitrate + ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Quantitative verification of the turbulence barrier effect during heavy haze pollution events

Under calm and steady weather conditions with low wind speeds, turbulent intermittency frequently occurs in the atmospheric boundary layer (ABL), which can significantly weaken the turbulent diffusion of matter and energy between the surface and atmosphere. The turbulence barrier effect is defined as the phenomenon in which turbulence may disappear at certain heights, and during periods of heavy haze, creating what can seem like a barrier layer that hinders vertical transmissions. Although the turbulence barrier effect can explain the physical mechanisms behind the rapid accumulation of PM2.5 (fine particulate matter with diameters smaller than 2.5 μm) and the influence of turbulent diffusion conditions on the vertical distribution of PM2.5, more direct perspectives such as turbulent flux is still required for quantitative verification. Due of challenges in the acquisition of PM2.5 turbulent flux, carbon dioxide (CO2), which has relatively mature flux acquisition technology, was used as a substitute means of verifying and quantifying this phenomenon. The turbulence data collected during heavy haze events, at from five levels of a 255 m meteorological tower located in Tianjin, were analyzed and used to quantitatively verify the influence of the turbulent barrier effect on PM2.5. The results also revealed that the vertical changes in the turbulent barrier effect were consistent with those of the concentrations and flux of CO2. This means that this knowledge about the turbulent barrier effect can be extended to other mass-transfer processes. The analysis also found that the proportion of counter-gradient transport increases when the occurrences of the turbulent barrier effect are frequent. This work validates the presence of the turbulent barrier effect and is an important foundation for its future parameterization, which will help to accurately identify the matter transport processes in the stable boundary layer and under extreme weather conditions, such as intense pollution events.

Observation and Analysis of a Haze Pollution Event in Beijing by Spaceborne and Ground-based Lidars

Observation and Analysis of a Haze Pollution Event in Beijing by Spaceborne and Ground-based Lidars

Study of Persistent Haze Pollution in Winter over Jinan (China) Based on Ground-Based and Satellite Observations

A comprehensive study of the formation process of haze events in the Jinan area of China during winter is conducted based on the ground-based and satellite observation data from 1 December 2020 to 12 January 2021. According to variation of pollutant concentrations, two typical types of haze pollution are found in the Jinan area. During the type 1 haze pollution, the PM2.5 concentrations are greater than 75 μgm−3 and less than 115 μgm−3 with a short duration. The haze is mainly caused by local pollutant emissions and the accumulation of pollutants transported from areas around Jinan. By contrast, type 2 haze pollution episodes have a long duration and peak PM2.5 concentrations between 150 μgm−3 and 250 μgm−3, which is considered heavy pollution. Type 2 haze pollution is mainly caused by a mixture of long-range transported dust with locally emitted pollutants. Moreover, the unfavorable meteorological factors such as stable inversion layer, continuous cold high-pressure system, high relative humidity, and low wind speed play an important role in the formation of both types of haze pollution. In addition, there are significant photochemical processes during the haze pollutions. According to satellite data, the AOD in Jinan and surrounding areas is maintained at a high-level during haze pollution. It indicates that the local pollution is often accompanied by regional pollution during haze pollution events. This study reveals the formation process of haze pollution and promotes the study of regional climate change, which can provide guidance to the government in the prevention and control of haze pollution in East China.

Research on threshold characteristics and spatial effects of the agglomeration of electric power and thermal power industries on haze pollution

Since 2012, the frequent occurrence of haze pollution events in China has had a serious impact on people’s work and life. In this paper, the threshold effect, spatial autoregressive and spatial Dubin models are used to study the threshold characteristics and spatial effect of technological innovation, environmental regulation and the agglomeration of electric power and thermal power industries on haze pollution. It is concluded that the excessive agglomeration of electric power and thermal power industries is not conducive to the prevention and control of haze pollution, technological innovation is conducive to the control of haze pollution, and strengthening environmental regulation is conducive to the control of haze pollution. Electric power and thermal power industries are important sources of haze pollution and have obvious spatial spillover effects. Some policy suggestions are given, such as moderate control of the agglomeration scale of electric power and thermal power industries, strengthening the technological innovation of electric power and thermal power industries, systematic optimization of environmental regulation and strengthening the joint prevention and control of haze pollution in different regions to provide help for the scientific regulation and control of the agglomeration level of electric power and thermal power industries in different regions and effectively reduce the influence of haze pollution.

Boundary layer structure characteristics under objective classification of persistent pollution weather types in the Beijing area

Abstract. Different types of pollution boundary layer structures form via the coupling of different synoptic systems and local mesoscale circulation in the boundary layer; this coupling contributes toward the formation and continuation of haze pollution. In this study, we objectively classify the 32 heavy haze pollution events using integrated meteorological and environmental data and ERA-Interim analysis data based on the rotated empirical orthogonal function method. The thermodynamic and dynamic structures of the boundary layer for different pollution weather types are synthesized, and the corresponding three-dimensional boundary layer conceptual models for haze pollution are constructed. The results show that four weather types mainly influence haze pollution events in the Beijing area: (a) type 1 – southerly transport, (b) type 2 – easterly convergence, (c) type 3 – sinking compression, and (d) type 4 – local accumulation. The explained variances in the four pollution weather types are 43.69 % (type 1), 33.68 % (type 2), 16.51 % (type 3), and 3.92 % (type 4). In persistent haze pollution events, type 1 and type 2 surpass 80 % on the first and second days, while the other types are present alternately in later stages. The atmospheric structures of type 1, type 2, and type 3 have typical baroclinic characteristics at mid–high latitudes, indicating that the accumulation and transport of pollutants in the boundary layer are affected by coupled structures in synoptic-scale systems and local circulation. The atmospheric structure of type 4 has typical barotropic characteristics, indicating that the accumulation and transport of pollutants is primarily affected by local circulation. In type 1, southerly winds with a specific thickness and intensity prevail in the boundary layer, which is favorable for the accumulation of pollutants in plain areas along the Yan and Taihang Mountains, whereas haze pollution levels in other areas are relatively low. Due to the interaction between weak easterly winds and the western mountains, pollutants accumulate mainly in the plain areas along the Taihang Mountains in type 2. The atmospheric vertical structure is not conducive to upward pollutant diffusion. In type 3, the heights of the inversion and boundary layers are the lowest due to a weak sinking motion while relative humidity is the highest among the four types. The atmosphere has a small capacity for pollutant dispersion and is favorable to particulate matter hygroscopic growth; as a result, type 3 has the highest PM2.5 concentration. In type 4, the boundary layer is the highest among the four types, the relative humidity is the lowest, and the PM2.5 concentration is relatively lower under the influence of local mountain–plain winds. Different weather types will shape significantly different structures of the pollution boundary layer. The findings of this study allow us to understand the inherent difference among heavy pollution boundary layers; in addition, they reveal the formation mechanism of haze pollution from an integrated synoptic-scale and boundary layer structure perspective. We also provide scientific support for the scientific reduction of emissions and air quality prediction in the Beijing–Tianjin–Hebei region of China.

Control of particulate nitrate air pollution in China

The concentration of fine particulate matter (PM2.5) across China has decreased by 30–50% over the period 2013–2018 due to stringent emission controls. However, the nitrate component of PM2.5 has not responded effectively to decreasing emissions of nitrogen oxides and has actually increased during winter haze pollution events in the North China Plain. Here, we show that the GEOS-Chem atmospheric chemistry model successfully simulates the nitrate concentrations and trends. We find that winter mean nitrate would have increased over 2013–2018 were it not for favourable meteorology. The principal cause of this nitrate increase is weaker deposition. The fraction of total inorganic nitrate as particulate nitrate instead of gaseous nitric acid over the North China Plain in winter increased from 90% in 2013 to 98% in 2017, as emissions of nitrogen oxides and sulfur dioxide decreased while ammonia emissions remained high. This small increase in the particulate fraction greatly slows down deposition of total inorganic nitrate and hence drives the particulate nitrate increase. Our results suggest that decreasing ammonia emissions would decrease particulate nitrate by driving faster deposition of total inorganic nitrate. Decreasing nitrogen oxide emissions is less effective because it drives faster oxidation of nitrogen oxides and slower deposition of total inorganic nitrate. Reduction of ammonia emissions may be effective in reducing the nitrate component of fine particulate matter air pollution across the North China Plain, according to the simulation of nitrate trends using the GEOS-Chem atmospheric chemistry model.