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Based on the global reanalysis data of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research, the surface meteorological observation data, sounding data and satellite observation data, this paper comprehensively analyzes the evolution process and formation mechanism of a persistent severe dense fog process occurred on February 15–17, 2015 in Yancheng, eastern China. Through the numerical simulation experiment of Weather Research and Forecast (WRF) model, we further analyze the impact of sea-land breeze on the formation and burst reinforcement of fog. Results show that the precipitation caused by the southwesterly airflow in front of the upper-level trough and the low-pressure inverted trough are conducive to the formation of early rain fog, while the nighttime clear radiance under the control of surface cold high and the infiltration of weak cold advection are conducive to the formation and development of later radiation-advection fog. The WRF model simulates the fog evolution process, which is basically consistent with the actual fog area, and the simulation results are credible to a certain extent. The simulation results show that the establishment of sea breeze has an advection cooling effect on the near surface layer, which is conducive to the formation and development of the inversion layer on the near surface, providing stable stratification conditions for the formation and burst reinforcement of fog. On one hand, the strengthening of sea breeze circulation can continuously transport water vapor to the study area. On the other, the occurrence of ultra-low level jet is favorable for the accumulation of low-level water vapor. At the same time, the inversion intensity further strengthens, which is in favor of the burst reinforcement and long-term maintenance of fog. [ABSTRACT FROM AUTHOR]

Aerosol–cloud interaction (ACI) in fog and planetary boundary layer (PBL) conditions plays critical roles in the fog life cycle. However, it is not clear how ACI in the first fog (Fog1) affects the PBL and subsequently affects ACI in the second fog (Fog2), which is important information for understanding the interaction between ACI and the PBL, as well as their effects on fog properties. To fill this knowledge gap, we simulate two successive radiation fog events in the Yangtze River Delta, China, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Our simulations indicate that the PBL conditions conducive to Fog2 formation are affected by ACI with high aerosol loading in Fog1; subsequently, the PBL promotes ACI in Fog2, resulting in a higher liquid water content, higher droplet number concentration, smaller droplet size, larger fog optical depth, wider fog distribution, and longer fog lifetime in Fog2 than in Fog1. This phenomenon is related to the following physical factors. The first factor involves meteorological conditions conducive to Fog2 formation, including low temperature, high humidity, and high stability. The second factor is the feedbacks between microphysics and radiative cooling. A higher fog droplet number concentration increases the liquid water path and fog optical depth, thereby enhancing long-wave radiative cooling and condensation near the fog top. The third factor is the feedbacks between macrophysics, radiation, and turbulence. A higher fog top presents stronger long-wave radiative cooling near the fog top than near the fog base, which weakens temperature inversion and strengthens turbulence, ultimately increasing the fog-top height and fog area. In summary, under polluted conditions, ACI postpones the dissipation of Fog1 owing to these two feedbacks and generates PBL meteorological conditions that are more conducive to the formation of Fog2 than those prior to Fog1. These conditions promote the earlier formation of Fog2, further enhancing the two feedbacks and strengthening the ACI in Fog2. Our findings are critical for studying the interaction between aerosols, fog, and the PBL; moreover, they shed new light on ACI. [ABSTRACT FROM AUTHOR]

Weak turbulence often occurs during heavy pollution events in eastern China. However, existing mesoscale models cannot accurately simulate turbulent diffusion under weakened turbulence, particularly under the nocturnal stable boundary layer (SBL), often leading to significant turbulent diffusivity underestimation and surface aerosol simulation overestimation. In this study, based on the Weather Research and Forecasting model coupled with the Chemistry model (WRF-Chem 3.9.1), a new parameterization of minimum turbulent diffusivity (Kzmin) is tested and applied in PM2.5 simulations in eastern China under SBL conditions. Sensitivity experiments show that there are different value ranges of available Kzmin over the northern (0.8 to 1.3 m2·s-1) and southern (1.0 to 1.5 m2·s-1) regions of East China. The geographically related Kzmin could be parameterized by means of two factors: sensible heat flux (H) and latent heat flux (LE), which also exhibited a regional difference related to the climate and underlying surface. The revised Kzmin scheme obviously enhanced the turbulent diffusion (north: 0.88 m2·s-1, south: 1.17 m2·s-1 on average) under the SBL, simultaneously improving the PM2.5 simulations, with the PM2.5 relative bias decreasing from 43.0 % to 15.6 % on the surface. The improvement in the mean bias of the surface simulation was more noticeable in the north (54.01 to 3.79 ug·m-3) than in the south (37.05 to 17.99 ug·m-3). It also increased the PM2.5 concentration in the upper SBL. Furthermore, we discussed the physical relationship between Kzmin and two factors. Kzmin was inversely correlated with sensible heat flux (negative) and latent heat flux (positive) in the SBL. Process analysis showed that vertical mixing is the key process to improve PM2.5 simulations on the surface in the revised scheme. The increase in the PM2.5 concentration in the upper SBL was attributed to vertical mixing, advection, and aerosol chemistry. This study highlights the importance of improving turbulent diffusion in current mesoscale models under the SBL and has great significance for aerosol simulation research under heavy air pollution events. [ABSTRACT FROM AUTHOR]

Understanding cloud droplet relative dispersion is critical for mitigating the confounding effect of aerosol‐cloud interactions in the simulation of the global climatic patterns. Diverse dispersion effects, meaning that the correlation between relative dispersion (ε) and fog droplet number concentration (Nf) changes from positive to negative as Nf increases at a fixed liquid water content (LWC) condition, were found in the urban fog observed during the winters of 2017 and 2018 in Nanjing, China. The dominant microphysical processes driving the diverse dispersion effects were found to be activation, condensation, deactivation, evaporation, and sedimentation. The critical first bin (diameter range of 2–4 μm) strength and volume‐mean diameter (Dv) for classifying the diverse dispersion effects are 0.3–0.4 and 10–12 μm, respectively. The mean dispersion offset (DO) was −27.6% for weakening the Twomey effect and 27.5% for enhancing it. Assuming the Gamma distribution for the fog droplet number size distribution, the mean dispersion effect was significantly underestimated at DO < 0. Based on the measured nonmonotonic relationship between ε and Dv, we establish ε parameterization using a Nelder function, which can be applied to the diverse dispersion effects. The mean deviation for diagnosing DO was less than 10% for DO > 0 and less than 50% for DO < 0. These results could shed new light on understanding the diverse dispersion effects, which cloud help reduce the uncertainties in the simulation of aerosol‐cloud interactions. Plain Language Summary: Cloud droplet relative dispersion, defined as the standard deviation over the mean droplet size, is of central importance in determining and understanding aerosol indirect effects. Field fog experiments are an effective way to study the dispersion effect; this is due to the ease of accessing fog, since it is essentially a grounded cloud. Diverse dispersion effects were found in urban fog observed in eastern China. The dominant microphysical processes driving the diverse dispersion effects were found to be activation, condensation, deactivation, evaporation, and sedimentation. Whether the small droplet segment of the fog maintains its peak in droplet number size distribution is a key factor in determining the various dispersion effects. A nonmonotonic parameterization of the relative dispersion was established to diagnose the dispersion effects. Our results could shed new light on the dispersion effects, in turn, improving simulation of aerosol‐cloud interactions. Key Points: Diverse dispersion effects were found in urban fogPossible microphysical mechanisms were proposed for explaining the elucidated dispersion effectsA nonmonotonic parameterization of relative dispersion was established to diagnose the dispersion effects [ABSTRACT FROM AUTHOR]

The aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) have notable influences on clouds, but their effects on fog are rarely analyzed before. Previous studies indicate that fog frequency in East China has been decreasing, and we further reveal that fog duration increases during 1960–2010. We hypothesize that this trend is related to the increase of aerosol pollution and perform WRF‐Chem simulations to study the ARI and ACI effects. Results show that ACI significantly advances fog formation, delays fog dissipation, and increases fog duration by about 1 h in a case study, while ARI has negligible effect. The more but smaller fog droplets produced in polluted conditions significantly inhibit droplet sedimentation and reduce solar radiation, therefore provide favorable conditions for the duration of fog. Under extremely polluted conditions, ACI effect also far overweighs ARI effect. To shorten the duration of dense fog, our findings suggest the necessity for mitigating emissions. Plain Language Summary: Aerosols, the suspensions of solid or liquid particles in the air, affect clouds through aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI). The ARI refers to that aerosols affect the meteorological conditions in clouds by scattering and absorbing radiation. The ACI refers to that clouds form on aerosols if aerosols absorb sufficient water vapor. Fog is a kind of near‐surface cloud. The ARI and ACI could have both notable influences on fog, but their effects are rarely analyzed before. Previous studies indicate that fog frequency in East China has been decreasing, and in this study we further reveal that fog duration increases during 1960–2010. We hypothesize that this trend is related to the increase of aerosol pollution and perform numerical simulations to study the ARI and ACI effects. Results show that ACI significantly advances fog formation, delays fog dissipation, and increases fog duration by about 1 h in the case study, while ARI has negligible effect. The ACI can significantly inhibit fog droplet sedimentation and reduce solar radiation, therefore provide favorable conditions for the duration of fog. Our findings suggest that reducing emissions could shorten fog duration and mitigate the hazards of fog. Key Points: Fog frequency in East China is decreasing, and fog duration is increasingThe increase in fog duration is mainly caused by aerosolsAerosol–cloud interaction plays a more important role in increasing fog duration than aerosol–radiation interaction [ABSTRACT FROM AUTHOR]

The remarkable development of China has resulted in rapid urbanization (urban heat island and dry island) and severe air pollution (aerosol pollution). Previous studies demonstrate that these two factors have either suppressing or promoting effects on fog, but what are the extents of their individual and combined effects? In this study, a dense radiation fog event in eastern China in January 2017 was reproduced by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and the individual and combined effects of urbanization and aerosols on fog (indicated by liquid water content – LWC) are quantitatively revealed. Results show that urbanization inhibits low-level fog, delays its formation and advances its dissipation due to higher temperatures and lower saturations. In contrast, upper-level fog could be enhanced because of the updraught-induced vapour convergence. Aerosols promote fog by increasing LWC, increasing droplet concentration and decreasing droplet effective radius. Further experiments show that the current pollution level in China could still be below the critical aerosol concentration that suppresses fog. Urbanization influences fog to a larger extent than aerosols do. When urbanization and aerosol pollution are combined, the much weaker aerosol-promoting effect is counteracted by the stronger urbanization-suppressing effect on fog. Budget analysis of LWC reveals that urban development (urbanization and aerosols) alters the LWC profile and fog structure mainly by modulating condensation–evaporation process. Our results infer that urban fog will be further reduced if urbanization keeps developing and air quality keeps deteriorating in the future. [ABSTRACT FROM AUTHOR]

During the past five decades, China has witnessed frequent fog and haze events. Previous studies have revealed that in polluted regions of East China, such as the Beijing‐Tianjin‐Hebei (BTH) region, the Yangtze River Delta (YRD) region, and the Pearl River Delta (PRD) region, fog frequencies are impacted not only by climate change but also by fast urbanization and increasing air pollution. In this study, we find that haze days increased markedly in the three regions. However, fog days showed an initially increasing and then decreasing trend, with the turning point in the 1980s; moreover, the turning point occurred 5–15 years earlier in large cities than in small cities. We further attribute the long‐term fog variations over East China to three factors: regional‐scale climate change, urbanization, and air pollution (aerosol pollution). We quantitatively show that urbanization and aerosol pollution contributed at least 1.6 times more than climate change, and their contributions varied with urban development stages. Fog was dominantly promoted by abundant aerosols (45–85%) during the slow urbanization stage, while it was dominantly inhibited by urban heat island and dry island (53–60%) effects during the rapid urbanization stage. In the 53‐year period, aerosol pollution promoted fog formation (20–40%). Key Points: Air pollution (aerosols) dominates the increase in fog days during the slow urbanization stageUrbanization dominates the decrease in fog days during the fast urbanization stageUrbanization and air pollution (aerosols) contribute at least 1.6 times more to fog variation than does climate change [ABSTRACT FROM AUTHOR]

Previous studies have developed a stable weather index (SWI) based on meteorological elements that adequately represent PM 2.5 pollution over the North China Plain (NCP). However, the SWI performs poorly over the Yangtze River Delta (YRD) region because air pollution over this region is affected not only by stagnant weather (STAG) but also by transport (TRANS). For example, air pollutants can be transported from the NCP to the YRD by cold fronts. In this study, an obliquely rotated principal component analysis in the T-model is applied to classify the synoptic patterns of winter weather over the YRD region from 2013 to 2018. Among the four identified synoptic patterns, two of which cause TRANS, one pattern is most likely to cause STAG, and one pattern can lead to either STAG or TRANS depending on the location of high pressure around Shandong province. Due to the large contribution (63%) of TRANS to the total PM 2.5 pollution events, a transport pollution index (TPI) is constructed to describe the transport features of PM 2.5 pollution over the YRD region. Our results show that, when considering the SWI alone, the correlation coefficients between the SWI and ln(PM 2.5) range from 0.50 to 0.57 in the main cities of the YRD. Excitingly, when considering both the TPI and SWI (TPI+SWI), the correlation coefficients increase significantly to 0.63–0.78, suggesting that TPI+SWI better reflects the wintertime PM 2.5 pollution level over the YRD region. In addition, satisfactory performance in validation also suggests that TPI+SWI can increase the accuracy of evaluating and forecasting of PM 2.5 pollution episodes over regions downstream of source emissions. Image 1 • Air Pollution is classified as stagnant (STAG) and transport (TRANS) over YRD. • We propose two indices (SWI and TPI) to reflect STAG pollution and TRANS pollution. • SWI and TPI combined can better represent the pollution level of PM 2.5 over YRD. [ABSTRACT FROM AUTHOR]

Regional transport is deemed the key physical process affecting air pollution formation. Previous studies have indicated that black carbon (BC) is abundant and unevenly distributed over eastern China, but the details of its three-dimensional (3-D) distributions and sources are still lacking. In this study, based on vertical observations and by using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) coupled with the BC-tagging technique, we explored the 3-D distributions and sources of BC under two typical winter pollution events in eastern China, namely, one induced by cold front transport (TRAN) and another induced by stagnant weather (STAG). During TRAN, cold air can transport BC from upwind (North China Plain, NCP) to downwind (Yangtze River Delta, YRD) regions, thereby making the source region components of BC more diversified over the YRD than during STAG. It also significantly increased the proportion of BC residential sources in the YRD. The higher the altitude is, the higher the ratios of BC sources originating from long-range transport are. In TRAN, except for horizontal advection, which plays a key role in the distribution of BC, a stronger vertical advection changes the BC profiles and raises the boundary layer height as the cold front moves through. In particular, high-concentration BC from regional transport arrives earlier at the upper BL of downwind regions than at the surface, thus exerting a distinct positive vertical mixing effect on the surface BC. This study implies that regional transport can significantly impact BC evolution and further affect meteorology and climate on a large scale. • Regional transport was the key process of BC's 3-D structure over eastern China. • Regional transport modulated the sectoral source distribution of BC in the downwind region. • BC from regional transport arrived earlier at the upper BL of downwind regions than at the surface. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) is one of the regions with air pollution and high ammonia (NH 3 ) emission in China. A high-resolution ammonia emission inventory for the YRD region was developed based on the updated source-specific emission factor (EFs) and the county-level activity data. The 1 × 1 km gridded emissions were allocated by using the appropriate spatial surrogate. The total NH 3 emissions changed insignificantly from 2006 to 2014 and varied in the range of 981.65 kt - 1014.30 kt. The fertilizer application and livestock were the major contributors of total emission. Humans, biomass burning and vehicles were the top three contributors of non-agricultural sources, accounting for 37.24%, 31.02% and 10.85%, respectively. Vehicles were calculated to be the non-agricultural source with the fastest annual growth rate. NH 3 emissions from the nitrogen fertilizer application generally peaked in summer, corresponding to the planting schedule and relatively high temperature. High NH 3 emissions occurred in the north as opposed to low emissions in the south of the YRD. The cities of Xuzhou, Yancheng and Nantong with more agricultural activities were demonstrated to have relatively high NH 3 emissions, contributing 10.0%, 9.0 and 7.1% of total emissions, respectively. The validity of the emission estimates was further evaluated based on the uncertainty analysis by Monte Carlo simulation, comparison with previous studies, and correlation analysis between NH 3 emission density and observed ground NH 3 concentration. A detailed NH 3 emission inventory is the basis of regional-scale air quality model simulation and can provide valuable information for understanding the formation mechanism of pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)