No abstract

China experienced severe haze pollution in January 2013. Here we have a detailed characterization of the sources and evolution mechanisms of this haze pollution with a focus on four haze episodes that occurred during 10-14 January in Beijing. The main source of data analyzed is from submicron aerosol measurements by an Aerodyne Aerosol Chemical Speciation Monitor. The average PM1 mass concentration during the four haze episodes ranged from 144 to 300 μg m À3, which was more than 10 times higher than that observed during clean periods. All submicron aerosol species showed substantial increases during haze episodes with sulfate being the largest. Secondary inorganic species played enhanced roles in the haze formation as suggested by their elevated contributions during haze episodes. Positive matrix factorization analysis resolved six organic aerosol (OA) factors including three primary OA (POA) factors from traffic, cooking, and coal combustion emissions, respectively, and three secondary OA (SOA) factors. Overall, SOA contributed 41-59% of OA with the rest being POA. Coal combustion OA (CCOA) was the largest primary source, on average accounting for 20-32% of OA, and showed the most significant enhancement during haze episodes. A regional SOA (RSOA) was resolved for the first time which showed a pronounced peak only during the record-breaking haze episode (Ep3) on 12-13 January. The regional contributions estimated based on the steep evolution of air pollutants were found to play dominant roles for the formation of Ep3, on average accounting for 66% of PM1 during the peak of Ep3 with sulfate, CCOA, and RSOA being the largest fractions (>~75%). Our results suggest that stagnant meteorological conditions, coal combustion, secondary production, and regional transport are four main factors driving the formation and evolution of haze pollution in Beijing during wintertime.

Air pollution is a major environmental concern during all seasons in the megacity of Beijing, China. Here we present the results from a winter study that was conducted from 21 November 2011 to 20 January 2012 with an Aerodyne Aerosol Chemical Speciation Monitor (ACSM) and various collocated instruments. The non-refractory submicron aerosol (NR-PM₁) species vary dramatically with clean periods and pollution episodes alternating frequently. Compared to summer, wintertime submicron aerosols show much enhanced organics and chloride, which on average account for 52% and 5%, respectively, of the total NR-PM₁ mass. All NR-PM₁ species show quite different diurnal behaviors between summer and winter. For example, the wintertime nitrate presents a gradual increase during daytime and correlates well with secondary organic aerosol (OA), indicating a dominant role of photochemical production over gas–particle partitioning. Positive matrix factorization was performed on ACSM OA mass spectra, and identified three primary OA (POA) factors, i.e., hydrocarbon-like OA (HOA), cooking OA (COA), and coal combustion OA (CCOA), and one secondary factor, i.e., oxygenated OA (OOA). The POA dominates OA during wintertime, contributing 69%, with the other 31% being SOA. Further, all POA components show pronounced diurnal cycles with the highest concentrations occurring at nighttime. CCOA is the largest primary source during the heating season, on average accounting for 33% of OA and 17% of NR-PM₁. CCOA also plays a significant role in chemically resolved particulate matter (PM) pollution as its mass contribution increases linearly as a function of NR-PM₁ mass loadings. The SOA, however, presents a reverse trend, which might indicate the limited SOA formation during high PM pollution episodes in winter. The effects of meteorology on PM pollution and aerosol processing were also explored. In particular, the sulfate mass is largely enhanced during periods with high humidity because of fog processing of high concentration of precursor SO₂. In addition, the increased traffic-related HOA emission at low temperature is also highlighted

COVID-19 pandemic continues worldwide with many variants arising, especially those of variants of concern (VOCs). A recent VOC, Omicron (B.1.1.529), which obtains a large number of mutations in the receptor-binding domain (RBD) of the spike protein, has risen to intense scientific and public attention. Here we studied the binding properties between the human receptor ACE2 (hACE2) and the VOC RBDs and resolved the crystal and cryo- EM structures of the Omicron RBD-hACE2 complex, as well as the crystal structure of Delta RBD-hACE2 complex. We found that, unlike Alpha, Beta and Gamma, Omicron RBD binds to hACE2 at a similar affinity compared to that of the prototype RBD, which might be due to compensation of multiple mutations for both immune escape and transmissibility. The complex structures of Omicron-hACE2 and Delta-hACE2 reveal the structural basis of how RBD-specific mutations bind to hACE2.

Abstract. Winter has the worst air pollution of the year in the megacity of Beijing. Despite extensive winter studies in recent years, our knowledge of the sources, formation mechanisms and evolution of aerosol particles is not complete. Here we have a comprehensive characterization of the sources, variations and processes of submicron aerosols that were measured by an Aerodyne high-resolution aerosol mass spectrometer from 17 December 2013 to 17 January 2014 along with offline filter analysis by gas chromatography/mass spectrometry. Our results suggest that submicron aerosols composition was generally similar across the winter of different years and was mainly composed of organics (60 %), sulfate (15 %) and nitrate (11 %). Positive matrix factorization of high- and unit-mass resolution spectra identified four primary organic aerosol (POA) factors from traffic, cooking, biomass burning (BBOA) and coal combustion (CCOA) emissions as well as two secondary OA (SOA) factors. POA dominated OA, on average accounting for 56 %, with CCOA being the largest contributor (20 %). Both CCOA and BBOA showed distinct polycyclic aromatic hydrocarbons (PAHs) spectral signatures, indicating that PAHs in winter were mainly from coal combustion (66 %) and biomass burning emissions (18 %). BBOA was highly correlated with levoglucosan, a tracer compound for biomass burning (r2 = 0.93), and made a considerable contribution to OA in winter (9 %). An aqueous-phase-processed SOA (aq-OOA) that was strongly correlated with particle liquid water content, sulfate and S-containing ions (e.g. CH2SO2+) was identified. On average aq-OOA contributed 12 % to the total OA and played a dominant role in increasing oxidation degrees of OA at high RH levels (> 50 %). Our results illustrate that aqueous-phase processing can enhance SOA production and oxidation states of OA as well in winter. Further episode analyses highlighted the significant impacts of meteorological parameters on aerosol composition, size distributions, oxidation states of OA and evolutionary processes of secondary aerosols.

In conventional photolithography, diffraction limits the resolution to about one-quarter of the wavelength of the light used. We introduce an approach to photolithography in which multiphoton absorption of pulsed 800-nanometer (nm) light is used to initiate cross-linking in a polymer photoresist and one-photon absorption of continuous-wave 800-nm light is used simultaneously to deactivate the photopolymerization. By employing spatial phase-shaping of the deactivation beam, we demonstrate the fabrication of features with scalable resolution along the beam axis, down to a 40-nm minimum feature size. We anticipate application of this technique for the fabrication of diverse two- and three-dimensional structures with a feature size that is a small fraction of the wavelength of the light employed.

1] Total suspended particles (TSP) were collected at the summit of Mt. Tai (1534 m above sea level) on a daytime and nighttime basis during a summertime campaign (May-June 2006) and were characterized for organic molecular compositions using solvent extraction/derivatization and gas chromatography/mass spectrometry technique. The n-Alkanes, fatty acids, fatty alcohols, sugars, glycerol and polyacids, and phthalate esters were found as major organic compound classes, whereas lignin and resin products, sterols, aromatic acids, hopanes, and polycyclic aromatic hydrocarbons (PAHs) were detected as minor classes. Sugars (49.8-2115 ng m À3 , average 640 ng m À3 in daytime; 18.1-4348 ng m À3 , 799 ng m À3 in nighttime) were found to be the dominant compound class. Levoglucosan, a specific cellulose pyrolysis product, was detected as the most abundant single compound, followed by C 28 fatty alcohol, diisobutyl and di-n-butyl phthalates, C 29 n-alkane, C 16 and C 28 fatty acids, and malic acid. By grouping organic compounds based on their sources, we found that emission of terrestrial plant waxes was the most significant source (30-34%) of the TSP, followed by biomass burning products (25-27%) (e.g., levoglucosan and lignin and resin products), soil resuspension (15-18%) due to agricultural activities, secondary oxidation products (8-10%), plastic emission (3-10%), marine/microbial sources (6%), and urban/industrial emissions from fossil fuel use (4%). However, low molecular weight dicarboxylic acids (such as oxalic acid) of photochemical origin were not included in this study. Malic acid was found to be much higher than those reported in the ground level, suggesting an enhanced photochemical production in the free troposphere over mountain areas. Temporal variations of biomass burning tracers (e.g., levoglucosan, galactosan, mannosan) and some higher plant wax derived compound classes suggested that there were two major (E1 and E2) and one minor (E3) biomass-burning events during this campaign. Most of the compound classes showed higher concentrations in nighttime samples when organic aerosols can be long-range transported from different source regions to the summit of Mt. Tai above the planetary boundary layer (PBL). This study also demonstrates that the free troposphere over Mt. Tai is heavily influenced by field burning of agricultural wastes such as wheat straws in the North China Plain during the harvest season in early summer.

We present HERO, a novel framework for large-scale video+language omnirepresentation learning. HERO encodes multimodal inputs in a hierarchical structure, where local context of a video frame is captured by a Cross-modal Transformer via multimodal fusion, and global video context is captured by a Temporal Transformer. In addition to standard Masked Language Modeling (MLM) and Masked Frame Modeling (MFM) objectives, we design two new pre-training tasks: (i) Video-Subtitle Matching (VSM), where the model predicts both global and local temporal alignment; and (ii) Frame Order Modeling (FOM), where the model predicts the right order of shuffled video frames. HERO is jointly trained on HowTo100M and large-scale TV datasets to gain deep understanding of complex social dynamics with multi-character interactions. Comprehensive experiments demonstrate that HERO achieves new state of the art on multiple benchmarks over Text-based Video/Video-moment Retrieval, Video Question Answering (QA), Video-and-language Inference and Video Captioning tasks across different domains. We also introduce two new challenging benchmarks How2QA and How2R for Video QA and Retrieval, collected from diverse video content over multimodalities. 1