Abstract. The megacity of Beijing has experienced frequent severe fine particle pollution during the last decade. Although the sources and formation mechanisms of aerosol particles have been extensively investigated on the basis of ground measurements, real-time characterization of aerosol particle composition and sources above the urban canopy in Beijing is rare. In this study, we conducted real-time measurements of non-refractory submicron aerosol (NR-PM 1 ) composition at 260 m at the Beijing 325 m meteorological tower (BMT) from 10 October to 12 November 2014, by using an aerosol chemical speciation monitor (ACSM) along with synchronous measurements of size-resolved NR-PM 1 composition near ground level using a high-resolution timeof-flight aerosol mass spectrometer (HR-ToF-AMS). The NR-PM 1 composition above the urban canopy was dominated by organics (46 %), followed by nitrate (27 %) and sulfate (13 %). The high contribution of nitrate and high NO − 3 / SO 2− 4 mass ratios illustrates an important role of nitrate in particulate matter (PM) pollution during the study period. The organic aerosol (OA) was mainly composed of secondary OA (SOA), accounting for 61 % on an average. Different from that measured at the ground site, primary OA (POA) correlated moderately with SOA, likely suggesting a high contribution from regional transport above the urban canopy. The Asia-Pacific Economic Cooperation (APEC) summit with strict emission controls provides a unique opportunity to study the impacts of emission controls on aerosol chemistry. All aerosol species were shown to have significant decreases of 40-80 % during APEC from those measured before APEC, suggesting that emission controls over regional scales substantially reduced PM levels. However, the bulk aerosol composition was relatively similar before and during APEC as a result of synergetic controls of aerosol precursors. In addition to emission controls, the routine circulations of mountain-valley breezes were also found to play an important role in alleviating PM levels and achieving the "APEC blue" effect. The evolution of vertical differences between 260 m and the ground level was also investigated. Our results show complex vertical differences during the formation and evolution of severe haze episodes that are closely related to aerosol sources and boundary-layer dynamics.

Abstract. The megacity of Beijing has experienced frequent severe fine particle pollution during the last decade. Although the sources and formation mechanisms of aerosol particles have been extensively investigated on the basis of ground measurements, real-time characterization of aerosol particle composition and sources above the urban canopy in Beijing is rare. In this study, we conducted real-time measurements of non-refractory submicron aerosol (NR-PM1) composition at 260 m at the 325 m Beijing Meteorological Tower (BMT) from 10 October to 12 November 2014, by using an aerosol chemical speciation monitor (ACSM) along with synchronous measurements of size-resolved NR-PM1 composition at near ground level using a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR–ToF–AMS). The NR-PM1 composition above the urban canopy was dominated by organics (46 %), followed by nitrate (27 %) and sulfate (13 %). The high contribution of nitrate and high NO3−/SO42− mass ratios illustrate an important role of nitrate in particulate matter (PM) pollution during the study period. The organic aerosol (OA) was mainly composed by secondary OA (SOA), accounting for 61 % on an average. Different from that measured at the ground site, primary OA (POA) correlated moderately with SOA, likely suggesting a high contribution from regional transport above the urban canopy. The Asia–Pacific Economic Cooperation (APEC) summit with strict emission controls provides a unique opportunity to study the impacts of emission controls on aerosol chemistry. All aerosol species were shown to have significant decreases of 40–80 % during APEC from those measured before APEC, suggesting that emission controls over regional scales substantially reduced PM levels. However, the bulk aerosol composition was relatively similar before and during APEC as a result of synergetic controls of aerosol precursors such as SO2, NOx, and volatile organic compounds (VOCs). In addition to emission controls, the routine circulations of mountain–valley breezes were also found to play an important role in alleviating PM levels and achieving the "APEC blue" effect. The evolution of vertical differences between 260 m and the ground level was also investigated. Our results show complex vertical differences during the formation and evolution of severe haze episodes that are closely related to aerosol sources and boundary layer dynamics.

Facial expression recognition (FER) in-the-wild is challenging due to unconstraint settings such as varying head poses, illumination, and occlusions. In addition, the performance of a FER system significantly degrades due to large intra-class variation and inter-class similarity of facial expressions in real-world scenarios. To mitigate these problems, we propose a novel approach, Discriminative Attention-augmented Feature Learning Convolution Neural Network (DAF-CNN), which learns discriminative expression-related representations for FER. Firstly, we develop a 3D attention mechanism for feature refinement which selectively focuses on attentive channel entries and salient spatial regions of a convolution neural network feature map. Moreover, a deep metric loss termed Triplet-Centre (TC) loss is incorporated to further enhance the discriminative power of the deeply-learned features with an expression-similarity constraint. It simultaneously minimizes intra-class distance and maximizes inter-class distance to learn both compact and separate features. Extensive experiments have been conducted on two representative facial expression datasets (FER-2013 and SFEW 2.0) to demonstrate that DAF-CNN effectively captures discriminative feature representations and achieves competitive or even superior FER performance compared to state-of-the-art FER methods.

In the early December 2013, dense fog involving heavy pollutants lasted for 9 days in the Yancheng area. e characteristics, formation, and lasting mechanisms of this persistent fog were analyzed based on observational data at the Sheyang site, reanalysis data, and final analysis data from NCEP/NCAR, combining with the weather background and meteorological and physical variable fields. Results include that (1) the fog process was characterized by long duration, low visibility, and high pollutants concentration, (2) the atmospheric general circulation contributed to the sustainability and development of the heavily polluted fog, (3) deep inversion was the key thermal factor causing the heavily polluted fog, (4) the fog exhibited obvious outbreaks with good visibility weather turned to severe fog several times, and (5) the weak cold air invasion and radiative cooling were the triggering factors to the sudden enhancement of the fog.