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New particle formation (NPF) plays a crucial role in the atmospheric aerosol population and has significant implications on climate dynamics, particularly in climate-sensitive zones such as the Tibetan Plateau (TP). However, our understanding of NPF on the TP is still limited due to a lack of comprehensive measurements and verified model simulations. To fill this knowledge gap, we conducted an integrated study combining comprehensive field measurements and chemical transport modeling to investigate NPF events on the southeastern TP during the pre-monsoon season. NPF was observed to occur frequently on clear-sky days on the southeastern TP, contributing significantly to the cloud condensation nuclei (CCN) budget in this region. The observational evidence suggests that highly oxygenated organic molecules (HOMs) from monoterpene oxidation participate in the nucleation on the southeastern TP. After updating the monoterpene oxidation chemistry and nucleation schemes in the meteorology–chemistry model, the model well reproduces observed NPF and reveals an extensive occurrence of NPF across the southeastern TP. The dominant nucleation mechanism is the synergistic nucleation of sulfuric acid, ammonia, and HOMs, driven by the transport of anthropogenic precursors from South Asia and the presence of abundant biogenic gases. By investigating the vertical distribution of NPF, we find a significant influence of vertical transport on the southeastern TP. More specifically, strong nucleation near the surface leads to an intense formation of small particles, which are subsequently transported upward. These particles experience enhanced growth to larger sizes in the upper planetary boundary layer (PBL) due to favorable conditions such as lower temperatures and a reduced condensation sink. As the PBL evolves, the particles in larger sizes are brought back to the ground, resulting in a pronounced increase in near-surface particle concentrations. This study highlights the important roles of anthropogenic–biogenic interactions and meteorological dynamics in NPF on the southeastern TP.

New particle formation contributes significantly to the number concentration of ultrafine particles (UFPs, d ≤ 100 nm) and has a great impact on human health and global climate. Iodine oxoacids (HIOx, including iodic acid, HIO3, and iodous acid, HIO2) have been observed in pristine regions and proved to dominate new particle formation (NPF) at some sites. However, the knowledge of HIOx in polluted urban areas is rather limited. Here, we conducted a long-term measurements of gaseous iodine oxoacids and sulfuric acid in Beijing from January 2019 to October 2021 and also in Nanjing from March 2019 to February 2020 and investigated the contribution of HIOx to UFP number concentration in both urban environments. HIO3 is highest in summer, up to 2.85 × 106 and 2.78 × 106 cm−3 in Beijing and Nanjing, respectively, and is lowest in winter by 96 % and 75 %, respectively. HIO3 exhibits more prominent variation than H2SO4 in both urban sites. HIO3 concentration shows a clear diurnal pattern at both sites with a daily maximum at around noontime, similar to the atmospheric temperature, solar radiation, and ozone (O3) levels. HIO2 concentration has the same diurnal and seasonal trend as HIO3 but is overall about an order of magnitude lower than HIO3 concentration. Back trajectory analysis suggests that the sources for inland iodine species could be a mix of marine and terrestrial origins, with both having peak iodine emission in warm seasons. While the contribution of HIO2 to particle growth is marginal in Beijing and Nanjing, our results demonstrate that HIO3 enhances the particle survival probability of sub-3 nm particles by about 40 % (median) and occasionally by more than 100 % in NPF events, suggesting HIOx are significant contributor to UFPs in polluted urban areas. As the growth contribution from HIO3 and H2SO4 is similar on a per-molecule basis, we propose that the sum of HIO3 and H2SO4 could be used to estimate sub-3 nm particle growth of inorganic acid origin in polluted atmospheres with a significant amount of HIOx.

Simultaneous Localization and Mapping (SLAM) technology, utilizing Light Detection and Ranging (LiDAR) sensors, is crucial for 3D environment perception and mapping. However, the absence of absolute observations and the inefficiency of single-robot perception present challenges for LiDAR SLAM in indoor environments. In this paper, we propose a multi-robot (MR) collaborative mapping method based on the Manhattan descriptor (MD) named MR-MD to overcome these limitations and improve the perception accuracy of LiDAR SLAM in indoor environments. The proposed method consists of two modules: MD generation and MD optimization. In the first module, each robot builds a local submap and constructs MD by parameterizing the planes in the submap. In the second module, the global main direction is updated using the historical MD of each robot, and constraints are built for each robot's horizontal and vertical directions according to their current MD and optimized. We conducted extensive comparisons with other multi-robot and single-robot LiDAR SLAM methods using real indoor data, and the results show that our method achieved higher mapping accuracy.

Terahertz (THz) imaging has long held promise for skin cancer detection but has been hampered by the lack of practical technological implementation. In this article, we introduce a technique for discriminating several skin pathologies using a coherent THz confocal system based on a THz quantum cascade laser. High resolution in vivo THz images (with diffraction limited to the order of 100 μm) of several different lesion types were acquired and compared against one another using the amplitude and phase values. Our system successfully separated pathologies using a combination of phase and amplitude information and their respective surface textures. The large scan field (50 × 40 mm) of the system allows macroscopic visualization of several skin lesions in a single frame. Utilizing THz imaging for dermatological assessment of skin lesions offers substantial additional diagnostic value for clinicians. THz images contain information complementary to the information contained in the conventional digital images.

Below-cloud wet scavenging is an important pathway to remove atmospheric aerosols. The below-cloud wet-scavenging coefficient (BWSC) is the value to describe the ability of rainfall to remove aerosols. The reported BWSCs obtained from the field measurements are much higher than the theory, but the reason for this remains unclear. Based on the long-term field measurements in the Yangtze River Delta of eastern China, we find that 28 % of the rainfall events are high-BWSC events. The high-BWSC events show the sudden decrease in the particle number concentration in all size bins near the end of rainfall. By investigating the simultaneously observed changes in carbon monoxide and aerosol chemical compositions during rainfall events, the circulation patterns, and backward trajectories, we find the cause of the high-BWSC events is the air mass changing but not the wet scavenging. The change in air masses is always followed by the rainfall processes and cannot be screened out by the traditional meteorological criteria, which would cause the overestimation of BWSC. After excluding the high-BWSC events, the observed BWSC is close to the theory and is correlated with the rainfall intensity and particle number concentrations prior to rainfall. This study highlights that the discrepancy between the observed BWSC and the theoretical value may not be as large as is currently believed. To obtain reasonable BWSCs and parameterization from field measurements, the effect of air mass changing during rainfall needs to be carefully considered.

Introduction: Despite the significant impact of clonal hematopoiesis (CH) on leukemogenesis, the pathogenesis of CH is still not fully understood. Methods: Utilizing a novel single-cell sequencing platform that allows for simultaneous detection of mutations and gene expression, we examined the gene expression profiles of hematopoietic stem and progenitor cells (HSPCs) harboring CH-related mutations from CH(+) cases, which was compared with that of wild-type (WT) cells from both CH(+) and CH(−) cases. Age-related changes in the bone marrow (BM) environment were also assessed using CH(−) cases. Results: In 12 patients with CH, genes associated with cell proliferation were upregulated in mutant cells. Significantly, mutant cells showed decreased expression of genes related to inflammatory responses, which were enhanced in BM cells from aged CH(−) cases, indicating the potential contribution of aged BM environment to the positive selection of mutant cells. Unexpectedly, WT cells from 3 TET2-CH(+) cases demonstrated significant upregulation of genes related to interferon response and cell proliferation, compared with those from age-matched CH(−) cases, suggesting the altered BM environments. Notably, when competitively transplanted with Tet2-knockout (KO) cells, WT HSPCs displayed enhanced expression of genes associated with cell proliferation and interferon signalling, compared with those transplanted with WT cells, implying non-cell autonomous effects of mutant cells. Conclusions: These results suggest that mutant cells in CH(+) BM may exert non-cell autonomous effects on WT cells. Alongside aged BM environments, these effects may contribute to the positive selection of CH clones, playing a pivotal role in the pathogenesis of CH.

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3–7 and 7–15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.

Oxygenated organic molecules (OOMs) are the crucial intermediates linking volatile organic compounds (VOCs) to secondary organic aerosols (SOAs) in the atmosphere, but comprehensive understanding of the characteristics of OOMs and their formation from VOCs is still missing. Ambient observations of OOMs using recently developed mass spectrometry techniques are still limited, especially in polluted urban atmospheres where VOCs and oxidants are extremely variable and complex. Here, we investigate OOMs, measured by a nitrate-ion-based chemical ionization mass spectrometer at Nanjing in eastern China, through performing positive matrix factorization on binned mass spectra (binPMF). The binPMF analysis reveals three factors about anthropogenic VOC (AVOC) daytime chemistry, three isoprene-related factors, three factors about biogenic VOC (BVOC) nighttime chemistry, and three factors about nitrated phenols. All factors are influenced by NOx in different ways and to different extents. Over 1000 non-nitro molecules have been identified and then reconstructed from the selected solution of binPMF, and about 72 % of the total signals are contributed by nitrogen-containing OOMs, mostly regarded as organic nitrates formed through peroxy radicals terminated by nitric oxide or nitrate-radical-initiated oxidations. Moreover, multi-nitrates account for about 24 % of the total signals, indicating the significant presence of multiple generations, especially for isoprene (e.g., C5H10O8N2 and C5H9O10N3). Additionally, the distribution of OOM concentration on the carbon number confirms their precursors are driven by AVOCs mixed with enhanced BVOCs during summer. Our results highlight the decisive role of NOx in OOM formation in densely populated areas, and we encourage more studies on the dramatic interactions between anthropogenic and biogenic emissions.

The high antibiotic tolerance of Staphylococcus aureus biofilms is associated with challenges for treating periprosthetic joint infection. The toxin–antitoxin system, YefM–YoeB, is thought to be a regulator for antibiotic tolerance, but its physiological role is unknown. The objective of this study was to determine the biofilm and antibiotic susceptibility phenotypes associated with S. aureus yoeB homologs. We hypothesized the toxin–antitoxin yoeB homologs contribute to biofilm formation and antibiotic susceptibility. Disruption of yoeB1 and yoeB2 resulted in decreased biofilm formation in comparison to Newman and JE2 wild-type (WT) S. aureus strains. In comparison to yoeB mutants, both Newman and JE2 WT strains had higher polysaccharide intercellular adhesin (PIA) production. Treatment with sodium metaperiodate increased biofilm formation in Newman WT, indicating biofilm formation may be increased under conditions of oxidative stress. DNase I treatment decreased biofilm formation in Newman WT but not in the absence of yoeB1 or yoeB2. Additionally, WT strains had a higher extracellular DNA (eDNA) content in comparison to yoeB mutants but no differences in biofilm protein content. Moreover, loss of yoeB1 and yoeB2 decreased biofilm survival in both Newman and JE2 strains. Finally, in a neutropenic mouse abscess model, deletion of yoeB1 and yoeB2 resulted in reduced bacterial burden. In conclusion, our data suggest that yoeB1 and yoeB2 are associated with S. aureus planktonic growth, extracellular dependent biofilm formation, antibiotic tolerance, and virulence.

Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regional climate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond East Asia and its S2S prediction. Preliminary studies and analysis have also shown that LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

An evaluation of social vulnerability to storm surges is important for any coastal city to provide marine disaster preparedness and mitigation procedures and to formulate post-disaster emergency plans for coastal communities. This study establishes an integrated evaluation system of social vulnerability by blending a variety of single-evaluation methods, which are subsequently combined by weighting in order to calculate a common social vulnerability index. Shenzhen has a current reputation of having considerable economic development potential and is a representative city in China. It is chosen for an evaluation of its social vulnerability to storm surges via a historical social and economic statistical dataset spanning the period 1986–2016. Exposure and sensitivity increased slowly with some fluctuation, leading to some alterations of the social vulnerability trend. Social vulnerability stayed almost constant during 1986–1991 and 1993–2004, while it decreased sharply afterwards to form a “stair-type” declining curve over the past 31 years. Resilience is progressively increasing by virtue of a continuous increase in medical services supply, fixed asset investments, and salary levels of employees. These determinants contribute to the overall downward trend of social vulnerability for Shenzhen.

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS  %, without any theoretical reasoning. The relationship between NCCN and AOPs was parameterized as NCCN≈((286±46)SAE ln(SS/(0.093±0.006))(BSF − BSFmin) + (5.2±3.3))σsp, where BSFmin is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS ≈0.1 %), the average bias, defined as the ratio of the AOP-derived and measured NCCN, varied from ∼0.7 to ∼1.9 at most sites except at a Himalayan site where the bias was >4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.

Haze pollution caused by PM2.5 is the largest air quality concern in China in recent years. Long-term measurements of PM2.5 and the precursors and chemical speciation are crucially important for evaluating the efficiency of emission control, understanding formation and transport of PM2.5 associated with the change of meteorology, and accessing the impact of human activities on regional climate change. Here we reported long-term continuous measurements of PM2.5, chemical components, and their precursors at a regional background station, the Station for Observing Regional Processes of the Earth System (SORPES), in Nanjing, eastern China, since 2011. We found that PM2.5 at the station has experienced a substantial decrease (−9.1 % yr−1), accompanied by even a very significant reduction of SO2 (−16.7 % yr−1), since the national “Ten Measures of Air” took action in 2013. Control of open biomass burning and fossil-fuel combustion are the two dominant factors that influence the PM2.5 reduction in early summer and winter, respectively. In the cold season (November–January), the nitrate fraction was significantly increased, especially when air masses were transported from the north. More NH3 available from a substantial reduction of SO2 and increased oxidization capacity are the main factors for the enhanced nitrate formation. The changes of year-to-year meteorology have contributed to 24 % of the PM2.5 decrease since 2013. This study highlights several important implications on air pollution control policy in China.

Particulate nitrate contributes a large fraction of secondary aerosols. Despite understanding of its important role in regional air quality and global climate, long-term continuous measurements are rather limited in China. In this study, we conducted online measurement of PM2.5 (particulate matter with diameters less than 2.5 µm) nitrate for 2 years from March 2014 to February 2016 using the Monitor for AeRosols and Gases in ambient Air (MARGA) in the western Yangtze River Delta (YRD), eastern China, and investigate the main factors that influenced its temporal variations and formation pathways. Compared to other sites in China, an overall high concentration of particulate nitrate was observed, with a mean value of 15.8 µg m−3 (0.5 to 92.6 µg m−3). Nitrate on average accounted for 32 % of the total mass of water-soluble ions and the proportion increased with PM loading, indicating that nitrate is a major driver of haze pollution episodes in this region. Sufficient ammonia drove most nitrate into the particle phase in the form of ammonium nitrate. A typical seasonal cycle of nitrate was observed, with the concentrations in winter on average 2 times higher than those in summer mainly due to different meteorological conditions. In summer, the diurnal variation of particulate nitrate was determined by thermodynamic equilibrium, resulting in a much lower concentration during daytime despite a considerable photochemical production. Air masses from the polluted YRD and biomass burning region contributed to the high nitrate concentration during summer. In winter, particulate nitrate did not reveal an evident diurnal variation. Regional transport from northern China played an important role in enhancing nitrate concentration. A total of 18 nitrate episodes were selected to understand the processes that drive the formation of high concentration of nitrate. Rapid nitrate formation was observed during the pre-episode (the day before nitrate episode day) nights, and dominated the increase of total water-soluble ions. Calculated nitrate from N2O5 hydrolysis was highly correlated to and accounted for 80 % of the observed nitrate, suggesting that N2O5 hydrolysis was a major contributor to the nitrate episodes. Our results suggested that rapid formation of nitrate could be a main cause for extreme aerosol pollution events in the YRD during winter, and illustrated the urgent need to control NOx emission.

Highly oxygenated multifunctional compounds (HOMs) play a key role in new particle formation (NPF), but their quantitative roles in different environments of the globe have not been well studied yet. Frequent NPF events were observed at two flagship stations under different environmental conditions, i.e. a remote boreal forest site (SMEAR II) in Finland and a suburban site (SORPES) in polluted eastern China. The averaged formation rate of 6 nm particles and the growth rate of 6–30 nm particles were 0.3 cm−3 s−1 and 4.5 nm h−1 at SMEAR II compared to 2.3 cm−3 s−1 and 8.7 nm h−1 at SORPES, respectively. To explore the differences of NPF at the two stations, the HOM concentrations and NPF events at two sites were simulated with the MALTE-BOX model, and their roles in NPF and particle growth in the two distinctly different environments are discussed. The model provides an acceptable agreement between the simulated and measured concentrations of sulfuric acid and HOMs at SMEAR II. The sulfuric acid and HOM organonitrate concentrations are significantly higher but other HOM monomers and dimers from monoterpene oxidation are lower at SORPES compared to SMEAR II. The model simulates the NPF events at SMEAR II with a good agreement but underestimates the growth of new particles at SORPES, indicating a dominant role of anthropogenic processes in the polluted environment. HOMs from monoterpene oxidation dominate the growth of ultrafine particles at SMEAR II while sulfuric acid and HOMs from aromatics oxidation play a more important role in particle growth. This study highlights the distinct roles of sulfuric acid and HOMs in NPF and particle growth in different environmental conditions and suggests the need for molecular-scale measurements in improving the understanding of NPF mechanisms in polluted areas like eastern China.

Brown carbon (BrC), a certain group of organic carbon (OC) with strong absorption from the visible (VIS) to ultraviolet (UV) wavelengths, makes a considerable contribution to light absorption on both global and regional scales. A high concentration and proportion of OC has been reported in China, but studies of BrC absorption based on long-term observations are rather limited in this region. In this study, we reported 3-year results of light absorption of BrC based on continuous measurement at the Station for Observing Regional Processes of the Earth System (SORPES) in the Yangtze River Delta, China, combined with Mie theory calculation. Light absorption of BrC was obtained using an improved absorption Ångström exponent (AAE) segregation method. The AAE of non-absorbing coated black carbon (BC) at each time step is calculated based on Mie theory simulation, together with single particle soot photometer (SP2) and aethalometer observations. By using this improved method, the variation of the AAE over time is taken into consideration, making it applicable for long-term analysis. The annual average light absorption coefficient of BrC (babs_BrC) at 370 nm was 6.3 Mm−1 at the SORPES station. The contribution of BrC to total aerosol absorption (PBrC) at 370 nm ranged from 10.4 to 23.9 % (10th and 90th percentiles, respectively), and reached up to ∼ 33 % in the open-biomass-burning-dominant season and winter. Both babs_BrC and PBrC exhibited clear seasonal cycles with two peaks in later spring/early summer (May–June, babs_BrC ∼ 6 Mm−1, PBrC ∼ 17 %) and winter (December, babs_BrC ∼ 15 Mm−1, PBrC ∼ 22 %), respectively. Lagrangian modeling and the chemical signature observed at the site suggested that open biomass burning and residential coal/biofuel burning were the dominant sources influencing BrC in the two seasons, respectively.

Aerosol optical properties (AOPs) and supporting parameters – particle number size distributions, PM2.5 mass concentrations, and the concentrations of trace gases (NOx and NOy) – were measured at SORPES, a regional background station in Nanjing, China from June 2013 to May 2015. The aerosol was highly scattering: the average scattering coefficient was σsp = 403 ± 314 Mm−1, the absorption coefficient σap = 26 ± 19 Mm−1, and the single-scattering albedo SSA = 0.93 ± 0.03 for green light. The SSA in Nanjing appears to be slightly higher than published values from several other sites in China and elsewhere. The average Ångström exponent of absorption (AAE) for the wavelength range 370–950 nm was 1.04 and the AAE range was 0.7–1.4. These AAE values can be explained with different amounts of non-absorbing coating on pure black carbon (BC) cores and different core sizes rather than contribution by brown carbon. The AOPs had typical seasonal cycles with high σsp and σap in winter and low ones in summer: the averages were σsp = 544 ± 422 and σap = 36 ± 24 Mm−1 in winter and σsp = 342 ± 281 and σap = 20 ± 13 Mm−1 in summer. The intensive AOPs had no clear seasonal cycles, the variations in them were rather related to the evolution of pollution episodes. The diurnal cycles of the intensive AOPs were clear and in agreement with the cycle of the particle number size distribution. The diurnal cycle of SSA was similar to that of the air photochemical age, suggesting that the darkest aerosol originated from fresh traffic emissions. A Lagrangian retroplume analysis showed that the potential source areas of high σsp and σap are mainly in eastern China. Synoptic weather phenomena dominated the cycle of AOPs on a temporal scale of 3–7 days. During pollution episodes, modeled boundary layer height decreased, whereas PM2.5 concentrations and σsp and σap typically increased gradually and remained high during several days but decreased faster, sometimes by even more than an order of magnitude within some hours. During the growth phase of the pollution episodes the intensive AOPs evolved clearly. The mass scattering efficiency MSE of PM2.5 grew during the extended pollution episodes from ∼ 4 to ∼ 6 m2 g−1 and the mass fraction of BCe decreased from ∼ 10 to ∼ 3 % during the growth phase of the episodes. Particle growth resulted in the backscatter fraction decreasing from more than 0.16 to less than 0.10, SSA growing from less than 0.9 to more than 0.95, and radiative forcing efficiency (RFE) changing from less than −26 W m−2 to more than −24 W m−2, which means that the magnitude of RFE decreased. The RFE probability distribution at SORPES was clearly narrower than at a clean background site which is in agreement with a published RFE climatology.

In this work, the spatial extent of new particle formation (NPF) events and the relative probability of observing particles originating from different spatial origins around three rural sites in eastern China were investigated using the NanoMap method, using particle number size distribution (PNSD) data and air mass back trajectories. The length of the datasets used were 7, 1.5, and 3 years at rural sites Shangdianzi (SDZ) in the North China Plain (NCP), Mt. Tai (TS) in central eastern China, and Lin'an (LAN) in the Yangtze River Delta region in eastern China, respectively. Regional NPF events were observed to occur with the horizontal extent larger than 500 km at SDZ and TS, favoured by the fast transport of northwesterly air masses. At LAN, however, the spatial footprint of NPF events was mostly observed around the site within 100–200 km. Difference in the horizontal spatial distribution of new particle source areas at different sites was connected to typical meteorological conditions at the sites. Consecutive large-scale regional NPF events were observed at SDZ and TS simultaneously and were associated with a high surface pressure system dominating over this area. Simultaneous NPF events at SDZ and LAN were seldom observed. At SDZ the polluted air masses arriving over the NCP were associated with higher particle growth rate (GR) and new particle formation rate (J) than air masses from Inner Mongolia (IM). At TS the same phenomenon was observed for J, but GR was somewhat lower in air masses arriving over the NCP compared to those arriving from IM. The capability of NanoMap to capture the NPF occurrence probability depends on the length of the dataset of PNSD measurement but also on topography around the measurement site and typical air mass advection speed during NPF events. Thus the long-term measurements of PNSD in the planetary boundary layer are necessary in the further study of spatial extent and the probability of NPF events. The spatial extent, relative probability of occurrence, and typical evolution of PNSD during NPF events presented in this study provide valuable information to further understand the climate and air quality effects of new particle formation.

Aerosol effects on low warm clouds over the Yangtze River Delta (YRD, eastern China) are examined using co-located MODIS, CALIOP and CloudSat observations. By taking the vertical locations of aerosol and cloud layers into account, we use simultaneously observed aerosol and cloud data to investigate relationships between cloud properties and the amount of aerosol particles (using aerosol optical depth, AOD, as a proxy). Also, we investigate the impact of aerosol types on the variation of cloud properties with AOD. Finally, we explore how meteorological conditions affect these relationships using ERA-Interim reanalysis data. This study shows that the relation between cloud properties and AOD depends on the aerosol abundance, with a different behaviour for low and high AOD (i.e. AOD 0.35). This applies to cloud droplet effective radius (CDR) and cloud fraction (CF), but not to cloud optical thickness (COT) and cloud top pressure (CTP). COT is found to decrease when AOD increases, which may be due to radiative effects and retrieval artefacts caused by absorbing aerosol. Conversely, CTP tends to increase with elevated AOD, indicating that the aerosol is not always prone to expand the vertical extension. It also shows that the COT–CDR and CWP (cloud liquid water path)–CDR relationships are not unique, but affected by atmospheric aerosol loading. Furthermore, separation of cases with either polluted dust or smoke aerosol shows that aerosol–cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust, which is ascribed to the higher absorption efficiency of smoke than dust. The variation of cloud properties with AOD is analysed for various relative humidity and boundary layer thermodynamic and dynamic conditions, showing that high relative humidity favours larger cloud droplet particles and increases cloud formation, irrespective of vertical or horizontal level. Stable atmospheric conditions enhance cloud cover horizontally. However, unstable atmospheric conditions favour thicker and higher clouds. Dynamically, upward motion of air parcels can also facilitate the formation of thicker and higher clouds. Overall, the present study provides an understanding of the impact of aerosols on cloud properties over the YRD. In addition to the amount of aerosol particles (or AOD), evidence is provided that aerosol types and ambient environmental conditions need to be considered to understand the observed relationships between cloud properties and AOD.

The measurement of sub-3 nm aerosol particles is technically challenging. Therefore, there is a lack of knowledge about the concentrations of atmospheric sub-3 nm particles and their variation in different environments. In this study, the concentrations of ∼ 1–3 nm particles measured with a particle size magnifier (PSM) were investigated at nine sites around the world. Sub-3 nm particle concentrations were highest at the sites with strong anthropogenic influence. In boreal forest, measured particle concentrations were clearly higher in summer than in winter, suggesting the importance of biogenic precursor vapors in this environment. At all sites, sub-3 nm particle concentrations had daytime maxima, which are likely linked to the photochemical production of precursor vapors and the emissions of precursor vapors or particles from different sources. When comparing ion concentrations to the total sub-3 nm particle concentrations, electrically neutral particles were observed to dominate in polluted environments and in boreal forest during spring and summer. Generally, the concentrations of sub-3 nm particles seem to be determined by the availability of precursor vapors rather than the level of the sink caused by preexisting aerosol particles. The results also indicate that the formation of the smallest particles and their subsequent growth to larger sizes are two separate processes, and therefore studying the concentration of sub-3 nm particles separately in different size ranges is essential.

Paired box 7 (Pax7) gene, a member of the paired box gene family, plays a critical role in animal growth and muscle development, especially in cell proliferation and self-renewal. The aim of this study was to detect the 10 base pair (bp) duplication insertion/deletion (indel) in the promoter region within the bovine Pax7 gene as well as its association with growth traits. Herein, a total of 718 individuals from five Chinese cattle breeds were sampled and detected. The 10 bp duplication indel was found in these cattle breeds and there were three genotypes: II (insertion/insertion), ID (insertion/deletion), and DD (deletion/deletion). Moreover, this indel was significantly associated with the body weight in Xianan cattle (P = 0.006), the body height in Jinjiang cattle (P = 0.046), and the hip width in Pi'nan cattle (P = 0.020). Consistently, the individuals with II genotype showed better phenotypic traits than those with the other genotypes in these five breeds. These findings suggest that the 10 bp duplication indel within the bovine Pax7 gene could be considered as an effective DNA molecular marker that provides valuable theoretical basis for marker-assisted selection (MAS) in beef cattle in the future.

The nitrogen (N) cycle has the potential to regulate climate change through its influence on carbon (C) sequestration. Although extensive research has explored whether or not progressive N limitation (PNL) occurs under CO2 enrichment, a comprehensive assessment of the processes that regulate PNL is still lacking. Here, we quantitatively synthesized the responses of all major processes and pools in the terrestrial N cycle with meta-analysis of CO2 experimental data available in the literature. The results showed that CO2 enrichment significantly increased N sequestration in the plant and litter pools but not in the soil pool, partially supporting one of the basic assumptions in the PNL hypothesis that elevated CO2 results in more N sequestered in organic pools. However, CO2 enrichment significantly increased the N influx via biological N fixation and the loss via N2O emission, but decreased the N efflux via leaching. In addition, no general diminished CO2 fertilization effect on plant growth was observed over time up to the longest experiment of 13 years. Overall, our analyses suggest that the extra N supply by the increased biological N fixation and decreased leaching may potentially alleviate PNL under elevated CO2 conditions in spite of the increases in plant N sequestration and N2O emission. Moreover, our syntheses indicate that CO2 enrichment increases soil ammonium (NH4+) to nitrate (NO3−) ratio. The changed NH4+/NO3− ratio and subsequent biological processes may result in changes in soil microenvironments, above-belowground community structures and associated interactions, which could potentially affect the terrestrial biogeochemical cycles. In addition, our data synthesis suggests that more long-term studies, especially in regions other than temperate ones, are needed for comprehensive assessments of the PNL hypothesis.

New particle formation (NPF) has been investigated intensively during the last 2 decades because of its influence on aerosol population and the possible contribution to cloud condensation nuclei. However, intensive measurements and modelling activities on this topic in urban metropolitan areas in China with frequent high-pollution episodes are still very limited. This study provides results from a comprehensive modelling study on the occurrence of NPF events in the western part of the Yangtze River Delta (YRD) region, China. The comprehensive modelling system, which combines the WRF-Chem (the Weather Research and Forecasting model coupled with Chemistry) regional chemical transport model and the MALTE-BOX sectional box model (the model to predict new aerosol formation in the lower troposphere), was shown to be capable of simulating atmospheric nucleation and subsequent growth. Here we present a detailed discussion of three typical NPF days, during which the measured air masses were notably influenced by either anthropogenic activities, biogenic emissions, or mixed ocean and continental sources. Overall, simulated NPF events were generally in good agreement with the corresponding measurements, enabling us to get further insights into NPF processes in the YRD region. Based on the simulations, we conclude that biogenic organic compounds, particularly monoterpenes, play an essential role in the initial condensational growth of newly formed clusters through their low-volatility oxidation products. Although some uncertainties remain in this modelling system, this method provides a possibility to better understand particle formation and growth processes.

Aerosol optical properties were measured with a seven-wavelength aethalometer and a three-wavelength nephelometer at the suburban site SORPES in Nanjing, China, in September 2013–January 2015. The aethalometer compensation parameter k, calculated with the Virkkula et al. (2007) method depended on the backscatter fraction, measured with an independent method, the integrating nephelometer. At λ = 660 nm the daily averaged compensation parameter k ≈ 0.0017 ± 0.0002 and 0.0042 ± 0.0013 when backscatter fraction at λ = 635 nm was in the ranges of 0.100 ± 0.005 and 0.160 ± 0.005, respectively. Also, the wavelength dependency of the compensation parameter depended on the backscatter fraction: when b(λ = 525 nm) was less than approximately 0.13 the compensation parameter decreased with wavelength and at larger b it increased with wavelength. This dependency has not been considered in any of the algorithms that are currently used for processing aethalometer data. The compensation parameter also depended on the single-scattering albedo ω0 so that k decreased with increasing ω0. For the green light (λ = 520 nm) in the ω0 range 0.870 ± 0.005, the average (± standard deviation) k ≈ 0.0047 ± 0.006 and in the ω0 range 0.960 ± 0.005, k ≈ 0.0028 ± 0.0007. This difference was larger for the near-infrared light (λ = 880 nm): in the ω0 range 0.860 ± 0.005, k ≈ 0.0055 ± 0.0023 and in the ω0 range 0.960 ± 0.005, k ≈ 0.0019 ± 0.0011. The negative dependence of k on ω0 was also shown with a simple theoretical analysis.

The mixture of toluene-methanol-water is difficult to separate because of the formation of toluene-methanol and toluene-water azeotropes. Extractive distillation process with two-column decanter (EDTCD) was improved to separate the system. The process was optimized by the software named Extractive Distillation Optimization Software (EDOS) which based on the minimum total annual cost (TAC). A comparison of the EDTCD and the traditional extractive distillation with triple-column (TEDT) indicated that the former was much more economical. In this comparison, n-methyl-2-pyrrolidone (NMP) and diethylene glycol (DEG) was used as a heavy entrainer in EDTCD and TEDT. The choice of thermodynamic model was discussed in this paper, and the model of UNIQUAC was used in the two processes. The results show that high purity of toluene, methanol and water can be obtained from the process of EDTCD, and it can save 34 % TAC than the process of TEDT.

Residential area detection is extremely important for supervision of rush-built and illegal construction behavior to protect arable land and basic farmland. Traditional manual recognition of illegal construction is simple but time-consuming. The specific research work in the thesis includes: the proposition and designing of a multi-scale segmentation method based on watershed segmentation combined with region merging algorithm, comparative experiments of the new algorithm and traditional algorithm. Then, architecture extraction experiment based on the multi-scale segmentation method is carried out and analysis of the precision of comparative experiment results of pixel-based and object-oriented extraction methods is made, all these steps facilitate the automatic mapping of the architecture.

Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.

Concrete beams are used to construct bridges and other structures. Due to the traffic overloading or the decaying state of structures, deformation of bridges or other structures occurs frequently. Therefore, the requirement to measure concrete beam deformation, as integral components of structures, is well recognized. Many imaging techniques such as digital cameras, laser scanners and range cameras have been proven to be accurate and cost-effective methods for large-area measurement of deformation under static loading conditions. However, for obtaining useful information about the behaviour of the beams or monitoring real-time bridge deformation, the ability to measurement deformation under dynamic loading conditions is also necessary. This paper presents a relatively low-cost and high accuracy imaging technique to measure the deformation of concrete beams in response to dynamic loading with range cameras. However, due to the range camera measurement principle, target movement could lead to motion artefacts that degrade range measurement accuracy. The results of simulated and real-data investigation into the motion artefacts show that the lower sampling frequency leads to the more significant motion artefact. The results from real data experiments have indicated that periodic deformation can be recovered with sub-millimetre accuracy when the 3 Hz and 4 mm amplitude target motion is sampled at a rate of least 20 Hz and with 31 MHz range camera modulation frequency. When the modulation frequency is 29 MHz, the best sampling frequency is 20 Hz to keep the error under sub-millimetre.

Due to implementation complexity, the transform domain channel estimation based on training symbols or comb-type pilots has been paid more attention because of its efficient algorithm FFT/IFFT. However, in a comb-type OFDM system, the length of the channel impulse response is much smaller than the pilot number. In this case, the comb-pilot transform domain channel estimation only works as interpolation like the Least Squares (LS) algorithm, but loses the noise suppression function. In this paper, we propose a novel frequency diversity channel estimation method via grouped pilots combining. With this estimator, not only the channel frequency response on non-pilot subcarriers can be interpolated, but also the noise can be better suppressed. Moreover, it does not need prior statistical characteristics of the wireless channel.

Simple sequence repeats (SSRs) were isolated from pearl millet bacterial artificial clones (BACs) without any subcloning steps. SSR sequences were targeted using 3′ end anchored SSR primers. Flanking sequences were isolated by suppression PCR. In this pilot study, 25 SSR markers have been developed from 40 BAC pools, comprising a total of 384 clones. This novel way to develop new markers has the added advantage that mapping the SSR markers will anchor individual BACs to the genetic maps and, thus, facilitate the construction of BAC contigs.

Abstract Results are presented from a search for new physics in high-mass diphoton events from proton-proton collisions at s $$ \sqrt{s} $$ = 13 TeV. The data set was collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb −1. Events with a diphoton invariant mass greater than 500 GeV are considered. Two different techniques are used to predict the standard model backgrounds: parametric fits to the smoothly-falling background and a first-principles calculation of the standard model diphoton spectrum at next-to-next-to-leading order in perturbative quantum chromodynamics calculations. The first technique is sensitive to resonant excesses while the second technique can identify broad differences in the invariant mass shape. The data are used to constrain the production of heavy Higgs bosons, Randall-Sundrum gravitons, the large extra dimensions model of Arkani-Hamed, Dimopoulos, and Dvali (ADD), and the continuum clockwork mechanism. No statistically significant excess is observed. The present results are the strongest limits to date on ADD extra dimensions and RS gravitons with a coupling parameter greater than 0.1.