Fog Haze Research Articles

Double Inversion Layers Affect Fog–Haze Events over Eastern China—Based on Unmanned Aerial Vehicles Observation

The goal of this work is to analyze how double inversion layers affect fog–haze events and boundary layers over Eastern China based on unmanned aerial vehicle observations. During 10–12 December 2020, two successive fog–haze events occurred in Eastern China. Based on the unmanned aerial vehicle (UAV), wind, temperature, relative humidity (RH), and aerosol mass concentration were monitored simultaneously in Lianyungang, China. Several observations were found after analyzing the physical fields of these data. The results show that the concentrations of air pollutants during fog events were negatively correlated with horizontal visibilities. The mass concentrations of particulate matter increased rapidly (After 08:00 BJT 11) in the fog dissipation stages (PM2.5 and PM10 increased from 97 and 150 μg/m3 to 213 and 300 μg/m3, respectively). Double temperature inversion significantly affected fog events, where the enhancement of the lower-level temperature inversion (where the inversion layer top height was between 150 and 300 m) corresponded to the explosive growth of fog and the dissipation of the upper-level inversion layer. (The bottom height of the inversion layer was between 350 m and 600 m) This indicates the end of fog events. Fog layer thicknesses are negatively correlated with the concentrations of air pollutants in the near-surface layer. The thickening of the inversion layer near the surface corresponds to an increase (after 05:00 BJT 11 and 03:00 BJT 12) in fog layer height. The fog event is maintained when water vapor conditions are favorable enough or when there is a deep near-surface temperature inversion but the maintenance of the near-surface temperature inversion at an intensity of above 2 °C (100 m)−1 mainly contributes to the durations of these two fog events. Calculations through the trajectory model reveal that the air pollutant source varied during these two events, which was the main reason for the difference in air pollutant concentrations between the two events.

The impacts of air quality and secondary organic aerosols formation on traffic accidents in heavy fog–haze weather

This study estimated changes in the levels of three components of regional haze, namely fine particulate matter (PM2.5), relative humidity (RH), and secondary organic aerosols (SOAs), at the time of two severe traffic accidents on a coastal expressway and a freeway in the Jianan Plain in southwestern Taiwan to understand the impact of weather and air quality factors on the low visibility. Monitoring data and surveillance images from four nearby air quality monitoring stations were collected to determine the precise causes of the poor visibility–related accidents. The study applied a haze extraction method to the images to achieve demisting, and the processed data were used to assess the relationship between the haze components and visibility during the accidents. The correlation between visibility and the haze components was assessed. The results revealed that the RH levels dropped significantly at the time of the accidents, signifying that moisture was not the main haze–fog component. The haze components can be ordered as follows in terms of their correlation with (and thus effect on) local visibility: PM2.5 > SOAs > RH. The spatial distributions and evolutions of the three components indicated that the PM2.5 concentrations remained high from midnight until early morning but decreased slightly at the time of both accidents. By contrast, the concentration of ultrafine SOA particles, which can scatter and absorb light to reduce road visibility, increased rapidly before both accidents. Therefore, PM2.5 and SOAs were two non-negligible factors of low visibility during the accidents, especially SOAs.

Research on the Spatial Effects of Green Process Innovation, Environmental Regulation, and Precipitation on Environmental Air Pollution

In recent years, air pollution events have occurred frequently in China and have had serious impacts on people’s work and life. The research objective of the article is to find out the spatial effects of green process innovation, environmental regulation, rainfall, and pollution from industrial development on air pollution by compiling a development index of the air pollution industry and constructing spatial autoregression and spatial Durbin models. The study found that green technology innovation significantly reduced sulfur dioxide emissions and fog haze pollution. The development of industrial air pollution is an important source of sulfur dioxide and pollutant haze and has significant spatial spillover effects. The strengthening of environmental regulations leads to a decrease in life pollution but causes a transfer of industrial pollution. Rainfall is conducive to reducing the concentrations of pollutants in the air, such as those from chimneys and smog. Policy recommendations are proposed, such as establishing different environmental policies for different green technological innovations to promote green technology innovation; constructing a joint defense control system for regional air pollution; increasing the construction of artificial wetlands in areas with serious air pollution; and creating scientific plans to coordinate the development of industry, technology, and the environment, to provide help for China to reduce the emission of atmospheric environmental pollutants.

2-tuple linguistic decision-making with consistency adjustment strategy and data envelopment analysis

2-tuple linguistic preference relations (2-TLPRs) are useful tools for addressing decision-making issues where the decision makers (DMs) are inclined to apply linguistic variables to express evaluation information. To retain the DM’s initial preference information as much as possible, this paper provides a 2-tuple linguistic decision-making method that incorporates a consistency adjustment algorithm and a 2-tuple linguistic data envelopment analysis (DEA) model. As two important aspects of decision-making, it is worthy to further study the improvements in consistency and weight generation for alternatives with 2-TLPRs. In this paper, in order to adjust the consistency of an original 2-TLPR to a predetermined level, a convergent consistency-improving algorithm is first presented, and we employ a minimum adjustment strategy to preserve the DM’s initial evaluation information. A 2-tuple linguistic DEA model is then developed to generate a vector of weights for the alternatives and we can derive reliable decision-making results. Finally, we provide a numerical example that can identify the most influential factor in Fog–haze weather to indicate the applicability of the 2-tuple linguistic decision-making method. The comparative analysis highlights the advantages and effectiveness of the 2-tuple linguistic decision-making method.

Development of self-cleaning polydimethylsiloxane/nano-calcium carbonate-titanium dioxide coating with fog-resistance response for building glass

PurposeThis paper introduced the simple synthesis process of self-cleaning coating with fog-resistance property using hydrophobic polydimethylsiloxane (PDMS) polymer and nano-calcium carbonate (nano-CaCO3) and titanium dioxide (TiO2).Design/methodology/approachThe synthesis method of PDMS/nano-CaCO3-TiO2 is based on sol-gel process. The crosslinking between PDMS and nanoparticles is driven by the covalent bond at temperature of 50°C. The 3-Aminopropyltriethoxysilane is used as binder for nanoparticles attachment in polymer matrix. Two fabrication methods are used, which are dip- and spray-coating methods.FindingsThe prepared coated glass fulfilled the requirement of standard self-cleaning and fog-resistance performance. For the self-cleaning test BS EN 1096-5:2016, the coated glasses exhibited the dust haze value around 20%–25% at tilt angle of 10°. For the antifog test, the coated glasses showed the fog haze value were below 2% and the gloss value were above 85%. The obtained results completely achieved the standard antifog value ASTM F659-06 protocol.Research limitations/implicationsFindings will provide an infrastructure support for the building glass to enhance building’s energy efficiency, cleaning performance and friendly environment.Practical implicationsThis study proposed the simple synthesis method using hydrophobic polymer and nano-CaCO3 and nano-TiO2, which can achieve optimum self-cleaning property at low tilt angle and fog-resistance performance for building glass.Social implicationsThe research findings have high potential for building company, cleaning building company and government sector. The proposed project capable to reduces the energy consumption about 20% per annum due to labor cost, time-consuming and safety during manual cleaning.Originality/valueThe novel method to develop self-cleaning coating with fog-resistance using simple synthesis process and fabrication method for building glass application.

The spatial and temporal effects of Fog–Haze pollution on the influenza transmission

The energy-intensive industrial economy results in frequent Fog–Haze weather which increases the risk of influenza spread and brings new challenges for the prevention and control of influenza. Therefore, the study of spread mechanics and controlling strategies of influenza based on Fog–Haze will be scientifically meaningful. Considering that when the concentration of Fog–Haze is low, Fog–Haze contributes to the number of infectious individuals and Fog–Haze suppresses the transmission of the influenza virus when the concentration of Fog–Haze is high, we establish the Fog–Haze dynamics model. Then we prove the global existence and boundedness of the solution, and the global asymptotic stability of the solution is given by constructing a suitable Lyapunov functional. Under the Fog–Haze weather, we study the influenza virus transmission model that incorporates the incidence rate to reflect the Fog–Haze-dependent saturation effect and investigate the effect of Fog–Haze pollution on the transmission of influenza. We show that the basic reproduction number [Formula: see text] determines the global dynamics of the system: if [Formula: see text], the disease-free equilibrium is global asymptotically stable; the unique endemic equilibrium is global asymptotically stable if [Formula: see text]. Simulations are carried out to validate the theoretical results. Our study provides further understanding of the dynamics of Fog–Haze and the effect of Fog–Haze pollution on the transmission of influenza.

Fog-Haze Transition and Drivers in the Coastal Region of the Yangtze River Delta.

Low-visibility events (LVEs) are severe weather phenomena that are closely linked with anthropogenic pollution, which negatively affects traffic, air quality, human health, and the environment. This study conducted a two-month (from October to December 2019) continuous measurement campaign on Chongming Island in Shanghai to characterize the LVEs transition and its drivers. The LVEs accounted for 38% of the time during the campaign, of which mist accounted for 14%, fog–haze for 13%, haze for 6%, and fog for 5%. The fog and mist mainly occurred from midnight to early morning, while haze mostly occurred during the daytime. Different LVEs were interdependent and transitioned from one to another. Fog generally turned into haze after sunrise, while haze turned into fog after sunset. Their formation and evolution were caused by the combined impacts of meteorological conditions and aerosol particles. It was found that temperature difference was the dominant meteorological factor driving the evolution of LVEs. Within the short term, cooling led to a greater increase in relative humidity than humidification. Radiative cooling during the night promoted the formation of fog and mist. During fog and mist events, cloud condensation nuclei (CCN) were mainly internally mixed due to the impact of fog droplet removal and aqueous/heterogeneous aerosol reactions occurring under high humidity. Increased CCN concentration appeared to increase the fog droplet number and liquid water content in fog events. Overall, conditions of high humidity and high particle loading were conducive to LVEs, whereas conditions of sufficient water vapor at a low particle level and sufficient particles at a low humidity level also caused LVEs. This study provided insights into LVEs classification, evolution scheme, and aerosol roles from a micro point of view. The findings could be useful for improving forecasts of local radiative fog and other LVEs.

Impacts of Boundary-Layer Structure and Turbulence on the Variations of PM2.5 During Fog\u2013Haze Episodes

The precise cause of PM2.5 (fine particular matter with a diameter smaller than 2.5 μm) explosive growth and the contribution of intermittent turbulence to the dispersion of PM2.5 are uncertain. Thus, the impact of boundary-layer structure and turbulence on the variations of surface PM2.5 during fog–haze episodes, especially during explosive growth and dispersion episodes, are investigated using turbulence data collected at a 255-m high meteorological tower in Tianjin from 2016 to 2018. Results suggest that the explosive growth of surface PM2.5 during fog–haze episodes is closely related to weak turbulent mixing, nocturnal inversions, or anomalous inversions, and the barrier effect of strong turbulent intermittency. Turbulent intermittency acts as a lid for hindering pollutant dispersion and is favourable for the fast accumulation of surface PM2.5. Apart from the potential causes mentioned above, the persistent moderate south-westerly flow is also a contributing factor for the explosive growth of surface PM2.5 during fog–haze episodes associated with regional transport. In addition, we demonstrate a possible mechanism of how intermittent turbulence affects the dispersion of PM2.5. Results verify that intermittent turbulence induced by the nocturnal low-level jet (LLJ) indeed plays an important role in the dispersion of PM2.5. However, the contribution of intermittent turbulence generated by the nocturnal LLJ to the dispersion of PM2.5 strongly relies on the intensity of the nocturnal LLJ.

Multiple Regression Analysis of Low Visibility Focusing on Severe Haze-Fog Pollution in Various Regions of China

Visibility degradation is a pervasive environmental problem in winter in China and its prediction accuracy is therefore important, especially in low visibility conditions. However, current visibility parameterization algorithms tend to overestimate low visibility (<5 km) during haze–fog events. The key point of low visibility calculation and prediction depends on a reasonable understanding of the correlation between visibility, PM2.5 concentration, and relative humidity (RH). Using the observations of PM2.5 concentration and meteorology from December 2016 to February 2017, under different RH levels, the relative contribution differences of PM2.5 concentrations and RH to visibility degradation are investigated in depth. On this basis, new multiple nonlinear regressions for low visibility are developed for eight regions of China. The results show that under relatively low RH conditions (<80% or 85%), PM2.5 concentration plays a leading role in visibility changes in China. With the increase in RH (80–90% or 85–95%), the PM2.5 concentration corresponding to the visibility of 10 and 5 km decreases and the contribution of RH becomes increasingly important. When the RH grows to >95%, a relatively low PM2.5 concentration could also lead to visibility decreasing to <5 km. Within this range, the PM2.5 concentration corresponding to the visibility of 5 km in Central China (CC), Sichuan Basin (SCB), and Yangtze River Delta (YRD) is approximately 50, 50, and 30 μg m−3, and that in Beijing-Tianjin-Hebei (BTH) and Guanzhong Plain (GZP) is approximately 125 μg m−3, respectively. Specifically, based on these contribution differences, new multiple nonlinear regression equations of visibility, PM2.5 concentration, temperature, and dew point temperature of the eight regions (Scheme A) are established respectively after grouping the datasets by setting different RH levels (BTH, GZP, and North Eastern China (NEC): RH < 80%, 80 ≤ RH < 90% and RH ≥ 90%; CC, SCB, YRD, and South China Coastal (SCC): RH < 85%, 85 ≤ RH < 95% and RH ≥ 95%; Xinjiang (XJ): RH < 90% and RH ≥ 90%). According to the previous regression methods, we directly established the multiple regression models between visibility and the same factors as a comparison (Scheme B). Statistical results show that the advantage of Scheme A for 5 and 3 km evaluation is more significant compared with Scheme B. For the five low visibility regions (BTH, GZP, CC, SCB, and YRD), RMSEs of Scheme A under visibility <5 and 3 km are 0.77–1.01 and 0.48–0.95 km, 16–43 and 24–57% lower than those of Scheme B, respectively. Moreover, Scheme A reproduced the winter visibility in BTH, GZP, CC, SCB, YRD, and SCC from 2016 to 2020 well. The MAEs, MBs, and RMSEs under visibility < 5 km are 0.44–1.41, −1.33–1.24, and 0.58–2.36 km, respectively. Overall, Scheme A is confirmed to be reliable and applicable for low visibility prediction in many regions of China. This study provides a new visibility parameterization algorithm for the haze–fog numerical prediction system.

Characteristics of Turbulence and Aerosol Optical and Radiative Properties during Haze–Fog Episodes in Shenyang, Northeast China

The characteristics of turbulence in the planetary boundary layer (PBL) and the aerosol optical and radiative properties during haze and haze–fog mixed episodes on 22–27 January 2021, in Shenyang, a provincial city in Northeast China, were analyzed using meteorological and aerosol observations. During the haze episode, the hourly mean PM2.5 concentration reached a maximum of 337 µg m−3 and visibility decreased to 1.6 km. The PM2.5 concentration decreased gradually during the haze–fog mixed episode as a result of the scavenging effects of fog, but visibility mostly remained below 1 km owing to high ambient relative humidity (>90%). During the haze–fog mixed episode, an increasing proportion of PM2.5 led to a higher ratio of the backward to the total scattering coefficient. As fog occurred, downward shortwave radiation arriving at the surface was significantly reduced, and upward longwave radiation increased and almost equaled the downward longwave radiation, which can be used as a good indicator for distinguishing haze and fog. Mechanical turbulence was weak during both episodes, and latent heat flux varied within a wider range during the haze–fog mixed episode. The PBL dynamic structure affected the vertical distribution of aerosols/fog droplets. Aerosol-rich layers appeared at altitudes below 0.5 km and above 0.6 km during the haze episode. The elevated aerosol layer was related to the aerosol transport from upstream polluted areas caused by strong upper-level turbulence, and it began to mix vertically after sunrise because of convective turbulence. Aerosols and fog droplets were mostly trapped in a shallower PBL with a height of 0.2–0.4 km during the haze–fog mixed episode because of weaker turbulence.

Distribution of bacterial concentration and viability in atmospheric aerosols under various weather conditions in the coastal region of China

Airborne bacteria have an important role in atmospheric processes and human health. However, there is still little information on the transmission and distribution of bacteria via the airborne route. To characterize the impact of foggy, haze, haze-fog (HF) and dust days on the concentration and viability of bacteria in atmospheric aerosols, size-segregated bioaerosol samples were collected in the Qingdao coastal region from March 2018 to February 2019. The total airborne microbes and viable/non-viable bacteria in the bioaerosol samples were measured using an epifluorescence microscope after staining with DAPI (4′, 6-diamidino-2-phenylindole) and a LIVE/DEAD® BacLight Bacterial Viability Kit. The average concentrations of total airborne microbes on haze and dust days were 6.75 × 105 and 1.03 × 106 cells/m3, respectively, which increased by a factor of 1.3 and 2.5 (on average), respectively, relative to those on sunny days. The concentrations of non-viable bacteria on haze and dust days increased by a factor of 1.2 and 3.6 (on average), respectively, relative to those on sunny days. In contrast, the concentrations of viable bacteria on foggy and HF days were 7.13 × 103 and 5.74 × 103 cells/m3, decreases of 38% and 50%, respectively, compared with those on sunny days. Foggy, haze, dust and HF days had a significant effect on the trend of the seasonal variation in the total airborne microbes and non-viable bacteria. Bacterial viability was 20.8% on sunny days and significantly higher than the 14.1% on foggy days, 11.2% on haze days, 8.6% during the HF phenomenon and 6.1% on dust days, indicating that special weather is harmful to some bacterial species. Correlation analysis showed that the factors that influenced the bacterial concentration and viability depended on different weather conditions. The main influential factors were temperature, NO2 and SO2 concentrations on haze days, and temperature, particulate matter (PM2.5) and NO2 concentrations on foggy days. The median size of particles containing viable bacteria was 1.94 μm on sunny days and decreased to 1.88 μm and 1.74 μm on foggy and haze days, respectively, but increased to 2.18 μm and 2.37 μm on dust and HF days, respectively.

Wintertime chemical characteristics of aerosol and their role in light extinction during clear and polluted days in rural Indo Gangetic plain

This paper reports the chemical and light extinction characteristics of fine aerosol (PM2.5) during the winter period (2017–18) at Lumbini, Nepal, a rural site on the Indo Gangetic Plains. A modified IMPROVE algorithm was employed to reconstruct light extinction by chemical constituents of aerosol. The fine aerosol levels impacted visibility adversely during daytime, but during nighttime visibility was controlled by fog droplets rather than by aerosols. The PM2.5 chemical constituents showed varying characteristics during clear and polluted days. The average NO3−/SO42− concentration ratio was 0.57 during clear and 1.36 and polluted days, signifying a change in secondary inorganics and formation processes mainly due to decreasing photochemical production and due to increased partitioning of nitrate particles at a lower temperature. The increased secondary organics contribution and the higher OM/OC ratio (2.2) during polluted days showed the vital role of aqueous processing and biomass burning emissions in determining the concentration of organics. Total light extinction was 2.3 times higher on polluted days compared to clear days, while the PM2.5 mass concentration was 1.5 times higher. This variation in mass and extinction order signifies that various chemical components in fine particles have a more considerable impact on light extinction. On clear days we found that carbonaceous particles (OM and EC) made a major contribution to light extinction. In contrast, the extinction contribution by secondary inorganic (especially NH4NO3) increased significantly during polluted days, with hygroscopic growth and enhanced scattering efficiency at higher RH conditions playing a major role. The comparison between clear and polluted days altogether suggests that regulating the nitrate sources can help significantly in improving the visibility levels and restrict fog haze development during wintertime in rural IGP.

Impacts of the meteorological condition versus emissions reduction on the PM2.5 concentration over Beijing–Tianjin–Hebei during the COVID-19 lockdown

The impacts of the meteorological condition and emissions reduction on the aerosol concentration over the Beijing–Tianjin–Hebei (BTH) region during the COVID-19 lockdown were analyzed by conducting three numerical experiments, including one with the meteorological field in 2019 and MEIC-2019 (2019 monthly Multi-resolution Emissions Inventory for China), one with the meteorological field in 2020 and MEIC-2019, and one with the meteorological field in 2020 and MEIC-2020, via a WRF-Chem model. The numerical experiments were performed from 3 to 16 February in 2019 and in 2020, during which a severe fog–haze event (3–16 February 2020) occurred in the BTH region, with a simulated maximum daily PM2.5 of 245 μg m−3 in Tangshan and 175 μg m−3 in Beijing. The results indicate that the daily PM2.5 decreased by 5–150 μg m−3 due to the emissions reduction and increased by 10–175 μg m−3 due to the meteorological condition in Beijing, Shijiazhuang, Cangzhou, Handan, Hengshui, Chengde, Zhangjiakou, and Tangshan from 7 to 14 February. For the horizontal distribution, PM2.5 and different aerosol species concentrations from 7 to 14 February 2020 increased compared with those during the same period in 2019, indicating that the accumulation of pollutants caused by the unfavorable meteorological condition offset the decreases caused by the emissions reduction, leading to the high aerosol concentration during the COVID-19 lockdown.摘要本研究从气象条件和减排两方面探讨了COVID-19封锁期间严重雾霾发生的原因[研究目的], 并定量的分析了气象条件和减排对PM2.5浓度的相对影响[创新点].使用WRF-Chem在2019年2月3日–16日和2020年2月3日–16日进行了三个数值模拟试验, 分别为2019年气象场与MEIC-2019 (2019年中国多分辨率月度排放清单) ,2020年气象场与MEIC-2019,2020年气象场与MEIC-2020[研究方法].结果表明COVID-19封锁期间严重雾霾的原因是不利气象条件增加的PM2.5浓度大于减排减少的PM2.5浓度[重要结论].

The formation and evolution of parent and oxygenated polycyclic aromatic hydrocarbons during a severe winter haze-fog event over Xi'an, China.

In this study, 3- or 4-h high time-resolved PM2.5 was observed during a severe winter haze-fog event (1 to 6 January 2017) to investigate the formation and evolution of parent polycyclic aromatic hydrocarbons (pPAHs) and oxygenated polycyclic aromatic hydrocarbons (OPAHs) in Xi'an, a typical city in northwestern China. Three episodes (episode I, episode II, and rainy day (EI, EII, and RD)) have been identified during this haze-fog event. Nine water-soluble ions, 8 carbonaceous fractions, 18 pPAHs, and 3 OPAHs in PM2.5 were measured. pPAHs showed two peaks at around 12:00 local standard time (LST) and 24:00 LST and two troughs at around 2:00 LST and 18:00 LST during EI. However, the OPAHs presented highest at around 18:00 LST and lowest at around 2:00 LST. During EII, pPAHs and OPAHs displayed similar diurnal variations with the highest values at noon but lowest values at around 2:00-5:00 LST.In addition, no obvious diurnal variations of pPAHs and OPAHs were observed during RDwere absent during RD. Diurnal variations of pPAH ring distributions demonstrated coal combustion, and vehicle emissions contributed to pPAHs for three episodes, which is further confirmed by diagnostic ratio results. High oxygenation (Ro) rates were found during the sampling time, which favored OPAH formation. The study herein indicates that OPAH formation through complex atmospheric reactions provides us new insights into the severe haze-fog events.

CFD-based analysis of urban haze-fog dispersion—A preliminary study

This paper proposes a computational fluid dynamics (CFD) model, along with dimensionless quantitative assessment standard—air pollution residual time (APRT) for the evaluation of local haze-fog (HF) dispersion in a built environment. A low APRT value ensures good ventilation. A building group model that comprises high-rise business building, mid-rise office buildings, low-mid-rise residential buildings (at the center of the building group), a mid-rise recreational center, and a local road (open terrain), was scaled down (1:100) to simulate the HF dispersion process. The orientation of the building group was numerically modified to generate a wind incidence normal to the high-rise building, mid-rise buildings, recreational center, and road. The results showed that the orientation of the building group largely determines the APRT. The most favorable orientation can reduce APRT by more than 50%. Our results strongly suggested that in order to reduce the consequential negative effect of air pollution, future urban designs should undergo a comprehensive ventilation assessment to ensure a low APRT value.

Decision-making model with fuzzy preference relations based on consistency local adjustment strategy and DEA

As one of the most useful tools, fuzzy preference relations (FPRs) can cope with the situations in which the experts are more comfortable providing their evaluation information with numerical values. Consistency-improving process and deriving the reliable priority weight vector for alternatives are two significant and challenging issues in decision making with FPRs. This paper investigates a novel decision-making model with FPRs on the basis of consistency local adjustment strategy and data envelopment analysis (DEA). Firstly, a new approach is proposed to generate the multiplicative consistent FPRs. Subsequently, a convergent consistency-improving algorithm for FPRs is developed to transform the unacceptable multiplicative consistent FPRs into the acceptable ones. In the consistency-improving process for FPRs, the local adjustment strategy is presented to employ decision-maker original evaluation information sufficiently. In order to determine the priority weight vector for alternatives, a novel fuzzy DEA model is constructed. Furthermore, a decision-making model with FPRs is designed to derive the reliable decision-making results. Finally, a numerical example of selecting the most important influence factor for fog–haze is provided, and the comparison with existing approaches is made to validate the rationality and effectiveness of the developed model.

Improved method of visibility parameterization focusing on high humidity and aerosol concentrations during fog–haze events: Application in the GRAPES_CAUCE model in Jing-Jin-Ji, China

Atmospheric visibility affects people's everyday lives and its simulation accuracy is therefore important, especially in low visibility conditions. Two fog–haze pollution episodes (episode 1, 16–21 December 2016 and episode 2, 30 December 2016–7 January 2017) in the Beijing–Tianjin–Hebei (Jing-Jin-Ji) region of China are simulated using the GRAPES_CUACE atmospheric chemistry model. The simulation of low visibility is significantly overestimated by the model. The observational data show that a decrease in visibility is closely related to the increase of the mass concentration of aerosol particles and the increase of the relative humidity. However, the contribution of aerosol particles to extremely low visibility is less than that of the relative humidity. When visibility is < 5 or even 2 km, the relative humidity is often >80% or near saturation. High humidity promotes the hygroscopic growth of aerosols, and it also favors the formation of fog droplets. Besides the strongly enhanced aerosol extinction coefficient due to hygroscopic growth at high relative humidity conditions that may be underestimated by the IMPROVE scheme, the further degradation of visibility may also depend on extinction from fog droplets which is absent in the IMPROVE scheme. An improved visibility parameterization focusing on low visibility is proposed based on the IMPROVE equation by including the direct extinction coefficient bf of fog droplets in the original parameterization. Focusing on the two fog–haze episodes, the simulation results with the improved parameterization show an overall improvement in the simulation of low visibility over the whole Jing-Jin-Ji region. The errors in the simulation of visibility by the improved parameterization averaged over the Jing-Jin-Ji region are reduced by 65%–88% relative to the original parameterization. In addition, the improved parameterization greatly improves the visibility simulation accuracies (VSAs) of 5 km, especially 3 km.

Enhanced heterogeneous uptake of sulfur dioxide on mineral particles through modification of iron speciation during simulated cloud processing

Abstract. Iron-containing mineral aerosols play a key role in the oxidation of sulfur species in the atmosphere. Simulated cloud processing (CP) of typical mineral particles, such as illite (IMt-2), nontronite (NAu-2), smectite (SWy-2) and Arizona Test Dust (ATD) is shown here to modify sulfur dioxide (SO2) uptake onto mineral surfaces. Heterogeneous oxidation of SO2 on particle surfaces was firstly investigated using an in situ DRIFTS apparatus (diffuse reflectance infrared Fourier transform spectroscopy). Our results showed that the Brunauer–Emmett–Teller (BET) surface area normalized uptake coefficients (γBET) of SO2 on the IMt-2, NAu-2, SWy-2 and ATD samples after CP were 2.2, 4.1, 1.5 and 1.4 times higher than the corresponding ones before CP, respectively. The DRIFTS results suggested that CP increased the amounts of reactive sites (e.g., surface OH groups) on the particle surfaces and thus enhanced the uptake of SO2. Transmission electron microscopy (TEM) showed that the particles broke up into smaller pieces after CP, and thus produced more active sites. The “free-Fe” measurements confirmed that more reactive Fe species were present after CP, which could enhance the SO2 uptake more effectively. Mössbauer spectroscopy further revealed that the formed Fe phases were amorphous Fe(III) and nanosized ferrihydrite hybridized with Al ∕ Si, which were possibly transformed from the Fe in the aluminosilicate lattice. The modification of Fe speciation was driven by the pH-dependent fluctuation coupling with Fe dissolution–precipitation cycles repeatedly during the experiment. Considering both the enhanced SO2 uptake and subsequent promotion of iron dissolution along with more active Fe formation, which in turn led to more SO2 uptake, it was proposed that there may be a positive feedback between SO2 uptake and iron mobilized on particle surfaces during CP, thereby affecting climate and biogeochemical cycles. This self-amplifying mechanism generated on the particle surfaces may also serve as the basis of high sulfate loading in severe fog–haze events observed recently in China.

Impacts of black carbon on the formation of advection–radiation fog during a haze pollution episode in eastern China

Abstract. Aerosols can not only participate in fog formation by acting as condensation nuclei of droplets but also modify the meteorological conditions such as air temperature and moisture, planetary boundary layer height (PBLH) and regional circulation during haze events. The impact of aerosols on fog formation, yet to be revealed, can be critical in understanding and predicting fog–haze events. In this study, we used the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to investigate a heavy fog event during a multiday intense haze pollution episode in early December 2013 in the Yangtze River Delta (YRD) region in eastern China. Using the WRF-Chem model, we conducted four parallel numerical experiments to evaluate the roles of aerosol–radiation interaction (ARI), aerosol–cloud interaction (ACI), black carbon (BC) and non-BC aerosols in the formation and maintenance of the heavy fog event. We find that only when the aerosols' feedback processes are considered can the model capture the haze pollution and the fog event well. And the effects of ARI during the fog–haze episode in early December 2013 played a dominant role, while the effects of ACI were negligible. Furthermore, our analyses show that BC was more important in inducing fog formation in the YRD region on 7 December than non-BC aerosols. The dome effect of BC leads to an increase in air moisture over the sea by reducing PBLH and weakening vertical mixing, thereby confining more water vapor to the near-surface layer. The strengthened daytime onshore flow by a cyclonic wind anomaly, induced by contrast temperature perturbation over land and sea, transported moister air to the YRD region, where the suppressed PBLH and weakened daytime vertical mixing maintained the high moisture level. Then heavy fog formed due to the surface cooling at night. This study highlights the importance of anthropogenic emissions in the formation of advection–radiation fog in the polluted coastal areas.

A severe fog-haze episode in Beijing-Tianjin-Hebei region: Characteristics, sources and impacts of boundary layer structure

Beijing–Tianjin–Hebei (BTH) region is recognized as one of the most polluted regions in China. In this study, characteristics, synoptic condition, boundary layer structure, and sources of a severe fog–haze episode during the December of 2016 and January of 2017 are investigated. The results show that BTH region is controlled by the uniform pressure field and southwest wind, and the average mass concentrations of PM2.5 in Beijing (BJ), Tianjin (TJ), and Shijiazhuang (SJZ) are 263.5, 192.7, and 296.1 μg/m3, respectively. Besides, the maximum hourly concentration and growth rate of PM2.5 are 578.8 μg/m3 and 13.1 μg/(m3·h), respectively for BJ. According to the wind profiler radar and L–band radar data, the maximum concentration of PM2.5 in two stages basically coincides with the minimum ventilation index (VI) value, and the minimum VI value in stage I and stage II are 5124 m2/s and 4524 m2/s. Moreover, the two stages are accompanied by significant inversion layer in the low levels. Although the maximum temperature inversion (10.8 °C) in stage I is higher that in stage II (8.3 °C) in the boundary layer, the maximum inversion strength in stage II (0.33 °C/hPa) is stronger than that in stage I (0.20 °C/hPa). Besides, weighted potential source contribution function (WPSCF) and conditional probability function analysis(CPF) are applied to investigate the potential source regions of PM2.5, the results show that southern BJ, as well as central and southern Hebei province (HB) are the main potential sources, and CPF values from the wind direction (180°–270°) are all over 0.3.