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This paper proposes a path-planning method for 3D information collection on the space station surface via the hyper-redundant space robot (HSR). Firstly, to efficiently acquire information on the space station surface, the space station is reduced to a cylindrical model for modelling, and the initial mapping of the temperature field is carried out by a popular Gaussian process. Based on the active information collection method, the collision-free viewpoint trajectory of the space station surface can be planned to improve the efficiency of surface information collection. Then, the path planning of the space station surface information collection can be realized by importing the space station model and temperature field data and performing weight initialization, stochastic search, and continuous optimization. Finally, simulation experiments show that the root-mean-square errors in the surface information collection process are lower than 1 mm relative to the true value. It proves the effectiveness of the online information collection path-planning (IP) method.

Soil emissions of nitrogen compounds, including NO and HONO, play a significant role in the atmospheric nitrogen budget. However, HONO has been overlooked in previous research on soil reactive nitrogen (Nr) emissions and their impacts on air quality in China. This study estimates soil NOx and soil HONO emissions (SNOx and SHONO) in North China during July 2018 using an updated soil Nr emissions scheme in a chemical transport model, Unified Inputs (initial and boundary conditions) for Weather Research and Forecasting coupled with Chemistry (UI-WRF-Chem). The effects of soil Nr emissions on O3 pollution, air quality and temperature rise are also studied, with a focus on two key regions, Beijing–Tianjin–Hebei (BTH) and the Fenwei Plain (FWP), known for high soil Nr and anthropogenic emissions. We find that the flux of SNOx is nearly double that of SHONO. The monthly contributions of SNOx and SHONO account, respectively, for 37.3 % and 13.5 % of anthropogenic NOx emissions in BTH and for 29.2 % and 19.2 % in the FWP during July 2018. Soil Nr emissions have a significant impact on surface O3 and nitrate, exceeding SNOx or SHONO effects alone. On average, soil Nr emissions increase maximum daily 8 h (MDA8) O3 by 16.9 % and nitrate concentrations by 42.4 % in BTH, and they increase MDA8 O3 by 17.2 % and nitrate concentrations by 42.7 % in the FWP. Reducing anthropogenic NOx emissions leads to a more substantial suppressive effect of soil Nr emissions on O3 mitigation, particularly in BTH. Soil Nr emissions, through their role as precursors for secondary inorganic aerosols, can result in a slower increase rate of surface air temperature in future emissions reduction scenarios. This study suggests that mitigating O3 pollution and addressing climate change in China should consider the role of soil Nr emissions and their regional differences.

MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is a Swedish satellite designed to investigate atmospheric dynamics in the mesosphere and lower thermosphere (MLT). By observing structures in noctilucent clouds over polar regions and oxygen atmospheric-band (A-band) emissions globally, MATS will provide the research community with properties of the MLT atmospheric wave field. Individual A-band images taken by MATS's main instrument, a six-channel limb imager, are transformed through tomography and spectroscopy into three-dimensional temperature fields, within which the wave structures are embedded. To identify wave properties, particularly the gravity wave momentum flux, from the temperature field, smaller-scale perturbations (associated with the targeted waves) must be separated from large-scale background variations using a method of scale separation. This paper investigates the possibilities of employing a simple method based on smoothing polynomials to separate the smaller and larger scales. Using using synthetic tomography data based on the HIAMCM (HIgh Altitude Mechanistic general Circulation Model), we demonstrate that smoothing polynomials can be applied to MLT temperatures to obtain fields corresponding to global-scale separation at zonal wavenumber 18. The simplicity of the method makes it a promising candidate for studying wave dynamics in MATS temperature fields.

Cooking organic aerosol (COA) is one of the major constituents of particulate matter in urban areas. COA is oxidized by atmospheric oxidants such as ozone, changing its physical, chemical and toxicological properties. However, atmospheric chemical lifetimes of COA and its tracers such as oleic acid are typically longer than those that have been estimated by laboratory studies. We tackled the issue by considering temperature. Namely, we hypothesize that increased viscosity of COA at ambient temperature accounts for its prolonged atmospheric chemical lifetimes in wintertime. Laboratory-generated COA particles from cooking oil were exposed to ozone in an aerosol flow tube reactor for the temperature range of −20 to 35 °C. The pseudo-second-order chemical reaction rate constants (k2) were estimated from the experimental data by assuming a constant ozone concentration in the flow tube. The estimated values of k2 decreased by orders of magnitude for lower temperatures. The temperature dependence in k2 was fit well by considering the diffusion-limited chemical reaction mechanism. The result suggested that increased viscosity was likely the key factor to account for the decrease in chemical reactivity at the reduced temperature range, though the idea will still need to be verified by temperature-dependent viscosity data in the future. In combination with the observed global surface temperature, the atmospheric chemical lifetimes of COA were estimated to be much longer in wintertime (> 1 h) than in summertime (a few minutes) for temperate and boreal regions. Our present study demonstrates that the oxidation lifetimes of COA particles will need to be parameterized as a function of temperature in the future for estimating environmental impacts and fates of this category of particulate matter.

Abstract Transition from traditional high-fiber to Western diets in urbanizing communities of Sub-Saharan Africa is associated with increased risk of non-communicable diseases (NCD), exemplified by colorectal cancer (CRC) risk. To investigate how urbanization gives rise to microbial patterns that may be amenable by dietary intervention, we analyzed diet intake, fecal 16 S bacteriome, virome, and metabolome in a cross-sectional study in healthy rural and urban Xhosa people (South Africa). Urban Xhosa individuals had higher intakes of energy (urban: 3,578 ± 455; rural: 2,185 ± 179 kcal/d), fat and animal protein. This was associated with lower fecal bacteriome diversity and a shift from genera favoring degradation of complex carbohydrates (e.g., Prevotella) to taxa previously shown to be associated with bile acid metabolism and CRC. Urban Xhosa individuals had higher fecal levels of deoxycholic acid, shown to be associated with higher CRC risk, but similar short-chain fatty acid concentrations compared with rural individuals. Fecal virome composition was associated with distinct gut bacterial communities across urbanization, characterized by different dominant host bacteria (urban: Bacteriodota; rural: unassigned taxa) and variable correlation with fecal metabolites and dietary nutrients. Food and skin microbiota samples showed compositional differences along the urbanization gradient. Rural-urban dietary transition in South Africa is linked to major changes in the gut microbiome and metabolome. Further studies are needed to prove cause and identify whether restoration of specific components of the traditional diet will arrest the accelerating rise in NCDs in Sub-Saharan Africa.

Marine emissions of dimethyl sulfide (DMS) and the subsequent formation of its oxidation products methanesulfonic acid (MSA) and sulfuric acid (H2SO4) are well-known natural precursors of atmospheric aerosols, contributing to particle mass and cloud formation over ocean and coastal regions. Despite a long-recognized and well-studied role in the marine troposphere, DMS oxidation chemistry remains a work in progress within many current air quality and climate models, with recent advances exploring heterogeneous chemistry and uncovering previously unknown intermediate species. With the identification of additional DMS oxidation pathways and intermediate species that influence the eventual fate of DMS, it is important to understand the impact of these pathways on the overall sulfate aerosol budget and aerosol size distribution. In this work, we update and evaluate the DMS oxidation mechanism of the chemical transport model GEOS-Chem by implementing expanded DMS oxidation pathways in the model. These updates include gas- and aqueous-phase reactions, the formation of the intermediates dimethyl sulfoxide (DMSO) and methanesulfinic acid (MSIA), and cloud loss and aerosol uptake of the recently quantified intermediate hydroperoxymethyl thioformate (HPMTF). We find that this updated mechanism collectively decreases the global mean surface-layer gas-phase sulfur dioxide (SO2) mixing ratio by 40 % and enhances the sulfate aerosol (SO42-) mixing ratio by 17 %. We further perform sensitivity analyses exploring the contribution of cloud loss and aerosol uptake of HPMTF to the overall sulfur budget. Comparing modeled concentrations to available observations, we find improved biases relative to previous studies. To quantify the impacts of these chemistry updates on global particle size distributions and the mass concentration, we use the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics module coupled to GEOS-Chem and find that changes in particle formation and growth affect the size distribution of aerosol. With this new DMS-oxidation scheme, the global annual mean surface-layer number concentration of particles with diameters smaller than 80 nm decreases by 16.8 %, with cloud loss processes related to HPMTF being mostly responsible for this reduction. However, the global annual mean number of particles larger than 80 nm (corresponding to particles capable of acting as cloud condensation nuclei, CCN) increases by 3.8 %, suggesting that the new scheme promotes seasonal particle growth to these sizes.

Abstract The Fe80P x C20-x ingots and amorphous ribbons (4.5 ≤ x ≤ 6.5) are arc melted and melt spun respectively. The Rhodamine B degradation performance of as spun and annealed ribbons are investigated with various methods. In present alloys, increasing P content (c P) can inhibit the precipitation of primary α-Fe and graphite phases, and promote the formation of eutectic α-Fe + Fe3C + Fe3P phases in ingots and annealed ribbons. With increasing annealing temperature (T an), the primary α-Fe grain size of the ribbons with c P = 4.5 at.% increases gradually and that of the ribbons with c P = 6.5 at.% increases firstly and then decreases. The degradation performance and reusability of the ribbons show a similar T an-dependent behavior, which can be explained by the size effect of the galvanic cells. Meanwhile, the saturation magnetisation B s and coercivity H c of the ribbons with c P = 4.5 and 6.5 at.% increase with increasing T an, showing a near-linear change of the reaction rate constant k against ln (B s·H c). This work not only studies the mechanism of improving degradation performance for FePC amorphous alloys by annealing treatment, but also reveals a correlation between degradation performance and magnetization performance of FePC alloys.

Despite significant improvements in air quality in recent years, the Sichuan Basin (SCB) is still facing frequent haze pollution in winter, and the causes of severe haze formation have not yet been fully investigated. In this study, the chemical components of PM2.5 (i.e., particulate matter with an aerodynamic diameter of less than 2.5 µm) in a typical pollution period at the beginning of 2023 in Chengdu, a megacity in the SCB, were characterized by bulk-chemical and single-particle analysis, and the PM2.5 sources and formation mechanism of pollution were analyzed. The average mass concentration of PM2.5 during the study period was 95.6 ± 28.7 µg m−3. Organic matter (OM) was the most abundant component (35.3 %), followed by nitrate (22.0 %), sulfate (9.2 %) and ammonium (7.8 %). The individual aerosol particles were classified into five categories, i.e., mineral, OM, secondary inorganic aerosol (SIA), soot and fly ash/metal particles, and most of them were in the state of being internally mixed. The entire observation period could be divided into two non-pollution periods (NP-1 and NP-2) and two haze periods (Haze-1 and Haze-2). With the evolution of pollution, the bulk-chemical and single-particle analysis exhibited similar characteristics, suggesting that Haze-1 was mainly caused by pollutants related to fossil fuel combustion, especially local mobile sources, while Haze-2 was triggered by the rapidly increasing secondary pollutants, which mainly came from regional transmission. The PM2.5 sources included dust (8.5 %), biomass burning (3.5 %), coal combustion (15.4 %), industrial processes (6.5 %), vehicular emissions (25.6 %) and secondary sources (40.5 %). Analysis of Weather Research and Forecasting model with Chemistry (WRF-Chem) model results showed that the average contributions of local sources and regional transmission to pollution in Chengdu were the same (50 % vs. 50 %). In addition, the source composition and WRF-Chem simulation results in different periods confirmed our analysis of the formation mechanisms of the two haze events. This study confirms that further significant reductions in PM2.5 in Chengdu are still needed, and more effective policies for local emission reduction or joint prevention and control of regional air pollution will be necessary in the future.

Oxygenated organic molecules (OOMs) produced by the oxidation of aromatic compounds are key components of secondary organic aerosol (SOA) in urban environments. The steric effects of substitutions and rings and the role of key reaction pathways in altering the OOM distributions remain unclear because of the lack of systematic multi-precursor study over a wide range of OH exposure. In this study, we conducted flow-tube experiments and used the nitrate adduct time-of-flight chemical ionization mass spectrometer (NO3--TOF-CIMS) to measure the OOMs produced by the photooxidation of six key aromatic precursors under low-NOx conditions. For single aromatic precursors, the detected OOM peak clusters show an oxygen atom difference of one or two, indicating the involvement of multi-step auto-oxidation and alkoxy radical pathways. Multi-generation OH oxidation is needed to explain the diverse hydrogen numbers in the observed formulae. In particular, for double-ring precursors at higher OH exposure, multi-generation OH oxidation may have significantly enriched the dimer formulae. The results suggest that methyl substitutions in precursor lead to less fragmented OOM products, while the double-ring structure corresponds to less efficient formation of closed-shell monomeric and dimeric products, both highlighting significant steric effects of precursor molecular structure on the OOM formation. Naphthalene-derived OOMs however have lower volatilities and greater SOA contributions than the other-type of OOMs, which may be more important in initial particle growth. Overall, the OOMs identified by the NO3--TOF-CIMS may have contributed up to 30.0 % of the measured SOA mass, suggesting significant mass contributions of less oxygenated, undetected semi-volatile products. Our results highlight the key roles of progressive OH oxidation, methyl substitution and ring structure in the OOM formation from aromatic precursors, which need to be considered in future model developments to improve the model performance for organic aerosol.

Aiming at the large weight of automobile steel solid shaft, this paper innovates aluminum alloy hollow shaft. The rolling process of automobile hollow shaft was simulated by using the short process flexible precision forming process and the Finite Element Method (FEM). The variation of the shape and inner hole of the rolled piece, the roundness of the outer surface and the wall thickness during the rolling process were analyzed. The numerical results verify the feasibility of rolling aluminum alloy automobile hollow shaft by this process, and provide a theoretical basis for forming aluminum alloy automobile hollow shaft in China.

In the process of urban construction and development, the ecological environment has always been an important consideration factor. How to quickly monitor the long-term ecological environment quality changes in large urban areas is currently one of the main research hotspots. With the continuous development of remote sensing intelligent cloud computing technology, the application of remote sensing methods to monitor urban ecological environment quality changes is becoming more efficient and convenient. Based on the remote sensing ecological index (RSEI) on the remote sensing intelligent cloud platform Google Earth Engine (GEE), this article innovatively proposes an improved remote sensing ecological index (DS-RSEI, Downscale-RSEI). Using the normalized difference vegetation index (NDVI) and land cover data (LULC), terrain data as auxiliary data, the method of moving window and principal component analysis is used to implement spatial downscaling of the heat components in the index, which increases the resolution of the original MODIS land surface temperature (LST) 1000-meter resolution product to 500 meters. When fusing with other images, it can supplement missing image details and improve the ability to evaluate the ecological spatial details of complex urban blocks. Through a comparative analysis of the RSEI index and the DS-RSEI index proposed in this article, it can be seen that DS-RSEI can express the details of ecological environment changes better in complex blocks.

The litter trait is one of the most important economic traits, and increasing litter size is of great economic value in the pig industry. However, the molecular mechanisms underlying pig litter traits remain elusive. To identify molecular markers and candidate genes for pig litter traits, a genome-wide association study (GWAS) and selection signature analysis were conducted in a Yorkshire pig population. A total of 518 producing sows were genotyped with Illumina Porcine SNP 50 BeadChip, and 1969 farrowing records for the total number born (TNB), the number born alive (NBA), piglets born dead (PBD), and litter weight born alive (LWB) were collected. Then, a GWAS was performed for the four litter traits using a repeatability model. Based on the estimated breeding values (EBVs) of TNB, 15 high- and 15 low-prolificacy individuals were selected from the 518 sows to implement selection signature analysis. Subsequently, the selection signatures affecting the litter traits of sows were detected by using two methods including the fixation index (FST) and θπ. Combining the results of the GWAS and selection signature analysis, 20 promising candidate genes (NKAIN2, IGF1R, KISS1R, TYRO3, SPINT1, ADGRF5, APC2, PTBP1, CLCN3, CBR4, HPF1, FAM174A, SCP2, CLIC1, ZFYVE9, SPATA33, KIF5C, EPC2, GABRA2, and GABRA4) were identified. These findings provide novel insights into the genetic basis of pig litter traits and will be helpful for improving the reproductive performances of sows in pig breeding.

In the last few decades, various techniques, including spectroscopic, mass spectrometric, chemiluminescence and wet chemical methods, have been developed and applied for the detection of gaseous ammonia (NH3). We developed an online NH3 monitoring system – salicylic acid derivatization reaction and long-path absorption photometer (SAC-LOPAP) – based on a selective colorimetric reaction to form a highly absorbing reaction product and a LOPAP, which could run stably for a long time and be applied to the continuous online measurement of low concentrations of ambient NH3 by optimizing the reaction conditions, adding a constant-temperature module and liquid flow controller. The detection limit reached with this instrument was 40.5 parts per trillion (ppt) with a stripping liquid flow rate of 0.49 mL min−1 and a gas sample flow rate of 0.70 L min−1. An inter-comparison of our system with a commercial Picarro G2103 analyzer (Picarro, USA) in Beijing was presented, and the results showed that the two instruments had a good correlation with a slope of 1.00 and an R2 of 0.96, indicating that the SAC-LOPAP instrument involved in this study could be used for the accurate measurement of NH3.

The hydroxyl radical (OH) is the main atmospheric oxidant responsible for the removal of many reduced trace gases and the formation of secondary air pollutants. However, due to technical difficulties in measuring OH, the existing measurements of atmospheric OH concentrations are limited, and its sources and sinks are not well understood under low-nitrogen-oxide (NOx) conditions. In this study, we observed the OH concentrations using chemical ionization mass spectrometry at a coastal site in Hong Kong from October to November 2020. The average noontime OH concentration over the study period was measured at 4.9±2.1×106 cm−3. We found that a box model with comprehensive observational constraints reproduced the observed daytime OH concentrations when air parcels originated from the continental regions. However, this model overpredicted the observed daytime OH concentrations for coastal air parcels by 142 % on average. Unaccounted-for OH sinks in the model are proposed to be the cause of this overprediction. A missing OH reactivity, which is defined as the pseudo-first-order rate coefficient for OH loss by unmeasured trace gases, was estimated as 5.0±2.6 s−1 (lower limit) in the coastal air, and the missing reactivity increased with decreasing concentrations of NOx and volatile organic compounds (VOCs). Further studies are needed to find out the exact cause of the model overestimation and to identify the suspected unmeasured chemical species that contribute to the OH budget, in order to better quantify the formation of secondary air pollutants.

Downward long-wave radiation (DLR) affects energy exchange between the land surface and the atmosphere and plays an important role in weather forecasting, agricultural activities, and the development of climate models. Because DLR is seldom observed at conventional radiation stations, numerous empirical parameterizations have been presented to estimate DLR from screen-level meteorological variables. The reliability and representativeness of parameterization depend on the coefficients regressed from the simultaneous observations of DLR and meteorological variables. Only a few previous studies have attempted to build parameterizations over regions in China such as the Tibetan Plateau and East China. In this study, a long-term (2011–2022) hourly dataset of DLR and meteorological elements, obtained from seven stations of the China Baseline Surface Radiation Network, was used to recalculate the coefficients of the Brunt and Weng models and to develop a new model. Results showed that the mean bias error (MBE) and relative MBE (rMBE) between the measured clear-sky DLR and that estimated using the Brunt, Weng, and new models were −4.3, −5.1, and 3.7 W m−2 and −1.5 %, −1.8 %, and 1.3 %, respectively. The root mean square errors (RMSEs) were in the range of 13.8–14.3 W m−2, and the relative RMSEs (rRMSEs) were approximately 5.0 %. The MBEs (rMBEs) of the Brunt, Weng, and new models under all-sky conditions were −2.8 W m−2 (−1.0 %), −6.1 W m−2 (−2.1 %), and −1.5 W m−2 (−0.5 %), respectively. The RMSE (rRMSE) of the parameterization models in retrieving all-sky DLR was ∼ 17.5 W m−2 (∼ 6.1 %). Therefore, the models are considered suitable for retrieval of DLR over China.

This work investigated seasonal variation of aerosol iron (Fe) solubility for coarse (>1 µm) and fine ( µm) particles at Xi'an, a megacity in northwestern China impacted by anthropogenic emission and desert dust. Total Fe concentrations were lowest in summer and were similar in other seasons for coarse particles but lowest in summer and highest in spring for fine particles; for comparison, dissolved Fe concentrations were higher in fall and winter than spring and summer for coarse particles but highest in winter and lowest in spring and summer for fine particles. Desert-dust aerosol was always the major source of total Fe for both coarse and fine particles in all four seasons, but it may not be the dominant source of dissolved Fe. Fe solubility was lowest in spring for both coarse and fine particles and highest in winter for coarse particles and in fall for fine particles. In general, aerosol Fe solubility was found to be higher in air masses originating from local and nearby regions than those arriving from desert regions after long-distance transport. Compared to coarse particles, Fe solubility was similar for fine particles in spring but significantly higher in the other three seasons, and at a given aerosol pH range, Fe solubility was always higher in fine particles. Aerosol Fe solubility was well correlated with relative abundance of aerosol acidic species, implying aerosol Fe solubility enhancement by acid processing; moreover, such correlations were better for coarse particles than fine particles in all four seasons. Fe solubility was found to increase with relative humidity and acid acidity for both coarse and fine particles at Xi'an, underscoring the importance of aerosol liquid water and aerosol acidity in regulating Fe solubility via chemical processing.

Measurements of the molecular composition of organic aerosol (OA) constituents improve our understanding of sources, formation processes, and physicochemical properties of OA. One instrument providing such data at a time resolution of minutes to hours is the chemical ionization time-of-flight mass spectrometer with filter inlet for gases and aerosols (FIGAERO-CIMS). The technique collects particles on a filter, which are subsequently desorbed, and the evaporated molecules are ionized and analyzed in the mass spectrometer. However, long-term measurements using this technique and/or field deployments at several sites simultaneously require substantial human and financial resources. The analysis of filter samples collected outside the instrument (offline) may provide a more cost-efficient alternative and makes this technology available for the large number of particle filter samples collected routinely at many different sites globally. Filter-based offline use of the FIGAERO-CIMS limits this method, albeit to particle-phase analyses, which is likely at a reduced time resolution compared to online deployments. Here we present the application and assessment of offline FIGAERO-CIMS, using Teflon and quartz fiber filter samples that were collected in autumn 2018 in urban Beijing. We demonstrate the feasibility of the offline application with a “sandwich” sample preparation for the over 900 identified organic compounds with (1) high signal-to-noise ratios, (2) high repeatability, and (3) linear signal response to the filter loadings. Comparable overall signals were observed between the quartz fiber and Teflon filters for 12 and 24 h samples but with larger signals for semi-volatile compounds for the quartz fiber filters, likely due to adsorption artifacts. We also compare desorption profile (thermogram) shapes for the two filter materials. Thermograms are used to derive volatility qualitatively based on the desorption temperature at which the maximum signal intensity of a compound is observed (Tmax⁡). While we find that Tmax⁡ can be determined with high repeatability (±5.7 ∘C) from the duplicate tests for one filter type, we observe considerable differences in Tmax⁡ between the quartz and Teflon filters, warranting further investigation into the thermal desorption characteristics of different filter types. Overall, this study provides a basis for expanding OA molecular characterization by FIGAERO-CIMS to situations where and when deployment of the instrument itself is not possible.

With high emissions of aerosols and the known world's “Third Pole” of the Tibet Plateau (TP) in East Asia, knowledge on the energy budget over this region has been widely concerned. This study first attempts to estimate the present-day land energy balance over East Asia by combining surface and satellite observations as well as the atmospheric reanalysis and Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. Compared to the global land budget, a substantially larger fraction of atmospheric shortwave radiation of 5.2 % is reflected, highly associated with the higher aerosol loadings and more clouds over East Asian land. While a slightly smaller fraction of atmospheric shortwave absorption of 0.6 % is unexpectedly estimated, possibly related to the lower water vapor content effects due to the thinner air over the TP to overcompensate for the aerosol and cloud effects over East Asian land. The weaker greenhouse effect and fewer low clouds due to the TP are very likely the causes of the smaller fraction of East Asian land surface downward longwave radiation. Hence, high aerosol loadings, clouds, and the TP over East Asia play vital roles in the shortwave budgets, while the TP is responsible for the longwave budgets during this regional energy budget assessment. The further obtained cloud radiative effects suggest that the presence of clouds results in a larger cooling effect on the climate system over East Asian land than that over the globe. This study provides a perspective to understand fully the roles of potential factors in influencing the different energy budget assessments over regions.

In the recent decade it became evident that we need to revise our picture of how gravity waves (GWs) reach the mesosphere and lower thermosphere (MLT). This has consequences for our understanding not just of the properties of the GWs themselves, but in particular of the global circulation in the MLT. Information on spectral distribution, direction, and zonal mean GW momentum flux is required to test the theoretical and modeling findings. In this study, we propose a constellation of two CubeSats for observing mesoscale GWs in the MLT region by means of temperature limb sounding in order to derive such constraints. Each CubeSat deploys a highly miniaturized spatial heterodyne interferometer (SHI) for the measurement of global oxygen atmospheric band emissions. From these emissions, the 3-D temperature structure can be inferred. We propose obtaining four independent observation tracks by splitting the interferograms in the center and thus gaining two observation tracks for each satellite. We present a feasibility study of this concept based on self-consistent, high-resolution global model data. This yields a full chain of end-to-end (E2E) simulations incorporating (1) orbit simulation, (2) airglow forward modeling, (3) tomographic temperature retrieval, (4) 3-D wave analysis, and (5) GW momentum flux (GWMF) calculation. The simulation performance is evaluated by comparing the retrieved zonal mean GWMF with that computed directly from the model wind data. A major question to be considered in our assessment is the minimum number of tracks required for the derivation of 3-D GW parameters. The main result from our simulations is that the GW polarization relations are still valid in the MLT region and can thus be employed for inferring GWMF from the 3-D temperature distributions. Based on the E2E simulations for gaining zonal mean climatologies of GW momentum flux, we demonstrate that our approach is robust and stable, given a four-track observation geometry and the expected instrument noise under nominal operation conditions. Using phase speed and direction spectra we show also that the properties of individual wave events are recovered when employing four tracks. Finally, we discuss the potential of the proposed observations to address current topics in the GW research. We outline for which investigations ancillary data are required to answer science questions.

Sea salt aerosols play an important role in the radiation budget and atmospheric composition over the Arctic, where the climate is rapidly changing. Previous observational studies have shown that Arctic sea ice leads are an important source of sea salt aerosols, and modeling efforts have also proposed blowing snow sublimation as a source. In this study, size-resolved atmospheric particle number concentrations and chemical composition were measured at the Arctic coastal tundra site of Utqiaġvik, Alaska, during spring (3 April–7 May 2016). Blowing snow conditions were observed during 25 % of the 5-week study period and were overpredicted by a commonly used blowing snow parameterization based solely on wind speed and temperature. Throughout the study, open leads were present locally. During periods when blowing snow was observed, significant increases in the number concentrations of 0.01–0.06 µm particles (factor of 6, on average) and 0.06–0.3 µm particles (67 %, on average) and a significant decrease (82 %, on average) in 1–4 µm particles were observed compared to low wind speed periods. These size distribution changes were likely caused by the generation of ultrafine particles from leads and/or blowing snow, with scavenging of supermicron particles by blowing snow. At elevated wind speeds, both submicron and supermicron sodium and chloride mass concentrations were enhanced, consistent with wind-dependent local sea salt aerosol production. At moderate wind speeds below the threshold for blowing snow as well as during observed blowing snow, individual sea spray aerosol particles were measured. These individual salt particles were enriched in calcium relative to sodium in seawater due to the binding of this divalent cation with organic matter in the sea surface microlayer and subsequent enrichment during seawater bubble bursting. The chemical composition of the surface snowpack also showed contributions from sea spray aerosol deposition. Overall, these results show the contribution of sea spray aerosol production from leads on both aerosols and the surface snowpack. Therefore, if blowing snow sublimation contributed to the observed sea salt aerosol, the snow being sublimated would have been impacted by sea spray aerosol deposition rather than upward brine migration through the snowpack. Sea spray aerosol production from leads is expected to increase, with thinning and fracturing of sea ice in the rapidly warming Arctic.

Based on the sparsity of inverse synthetic aperture radar (ISAR) signal, in this paper, a novel high resolution imaging algorithm is proposed. In this method, an optimal ISAR signal model based on mixed norm is established by using compressed sensing theory. The high-resolution ISAR image with short coherent accumulation time is realized by solving the optimization model. The main advantages of the proposed approach are: The model makes use of the l2,0 mixed norm to realize faster convergence and improve the computational speed of the model solution obviously. Moreover, according to the result sparsity of each iteration under arbitrary noise, the regularization coefficient in the model can be adjusted adaptively, which avoids the complex process of repeated attempts, otherwise, the optimal coefficient needs to be estimated and attempted by the statistical characteristics of the noise and signal. The effectiveness of the proposed method is verified by simulated and measured data.

Reactive halogens play a prominent role in the atmospheric chemistry of the Arctic during springtime. Field measurements and modeling studies suggest that halogens are emitted into the atmosphere from snowpack and reactions on wind-blown snow-sourced aerosols. The relative importance of snowpack and blowing snow sources is still debated, both at local scales and regionally throughout the Arctic. To understand the implications of these halogen sources on a pan-Arctic scale, we simulate Arctic reactive bromine chemistry in the atmospheric chemical transport model GEOS-Chem. Two mechanisms are included: (1) a blowing snow sea salt aerosol formation mechanism and (2) a snowpack mechanism assuming uniform molecular bromine production from all snow surfaces. We compare simulations including neither mechanism, each mechanism individually, and both mechanisms to examine conditions where one process may dominate or the mechanisms may interact. We compare the models using these mechanisms to observations of bromine monoxide (BrO) derived from multiple-axis differential optical absorption spectroscopy (MAX-DOAS) instruments on O-Buoy platforms on the sea ice and at a coastal site in Utqiaġvik, Alaska, during spring 2015. Model estimations of hourly and monthly average BrO are improved by assuming a constant yield of 0.1 % molecular bromine from all snowpack surfaces on ozone deposition. The blowing snow aerosol mechanism increases modeled BrO by providing more bromide-rich aerosol surface area for reactive bromine recycling. The snowpack mechanism led to increased model BrO across the Arctic Ocean with maximum production in coastal regions, whereas the blowing snow aerosol mechanism increases BrO in specific areas due to high surface wind speeds. Our uniform snowpack source has a greater impact on BrO mixing ratios than the blowing snow source. Model results best replicate several features of BrO observations during spring 2015 when using both mechanisms in conjunction, adding evidence that these mechanisms are both active during the Arctic spring. Extending our transport model throughout the entire year leads to predictions of enhanced fall BrO that are not supported by observations.

Global sustainable agricultural systems are under threat, due to increasing and co-occurring drought and salinity stresses. Combined effects of these stresses on agricultural crops have traditionally been evaluated in small-scale experimental studies. Consequently, large-scale studies need to be performed to increase our understanding and assessment of the combined impacts in agricultural practice in real-life scenarios. This study aims to provide a new monitoring approach using remote-sensing observations to evaluate the joint impacts of drought and salinity on crop traits. In our tests over the Netherlands at large spatial scale (138.74 km2), we calculated five functional traits for both maize and potato from Sentinel-2 observations, namely leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), the fraction of vegetation cover (FVC), leaf chlorophyll content (Cab), and leaf water content (Cw). Individual and combined effects of the stresses on the seasonal dynamics in crop traits were determined using both one-way and two-way analyses of variance (ANOVAs). We found that both stresses (individual and co-occurring) affected the functional traits of both crops significantly (with R2 ranging from 0.326 to 0.796) though with stronger sensitivities to drought than to salinity. While we found exacerbating effects within co-occurrent stresses, the impact level depended strongly on the moment in the growing season. For both crops, LAI, FAPAR, and FVC dropped the most under severe drought stress conditions. The patterns for Cab and Cw were more inhibited by co-occurring drought and salinity. Consequently, our study constitutes a way towards evaluating drought and salinity impacts in agriculture, with the possibility of potential large-scale application for sustainable food security.

Engineering education professional certification is a training model for engineering professionals based on international models. This paper discusses the inspiration of domestic and foreign engineering education practice to talent training in China. Based on the core elements of engineering education professional certification, we propose a closed-loop collaborative education model for study and research with "four integrations-two innovations-one education reform" as the core elements. This may be helpful to train the technological ability of students of GIS major. The exploration and practice of talent training in our school have achieved good results in talent cultivation, providing ideas and cases for exploring student-centered talent training.

Characterization of the spatial distributions of air pollutants on an intracity scale is important for understanding local sources, secondary formation, and human exposure. In this study, we conducted in situ mobile measurements for the chemical composition of fine particles, volatile organic compounds (VOCs), oxygenated VOCs (OVOCs), and common gas pollutants in winter in the megacity of Beijing. The spatial patterns of these pollutants under different pollution conditions were investigated. During the non-haze days all pollutants showed significant spatial variability. Large spatial variations of secondary species including OVOCs and secondary aerosol species highlight the chemical heterogeneity. In particular, the inorganic chemical composition of fine particles varied greatly on the 65 km urban highway, suggesting a wide range of particle neutralization in the megacity of Beijing. Localized sources such as vehicle, cooking, and industrial emissions led to hot spots and nonuniform distributions of primary pollutants in the city. The spatial heterogeneity of air pollutants under less polluted conditions calls for a future need of using fine-resolution models to evaluate human exposure and to develop pollution control strategies. During the haze day the spatial variabilities of secondary gaseous and particulate pollutants were largely reduced, explained by both the elevated urban background of the polluted air mass and the enhanced secondary formation by elevated precursor concentrations and heterogeneous or aqueous pathways. Although localized primary emissions were accumulated under stagnant haze conditions, the chemical composition of fine particles became relatively homogeneous because of the predominant secondary contributions. A uniform spatial pattern of particle neutralization was observed. The concentrations of hydrocarbons and less oxygenated OVOCs showed good positive spatiotemporal correlations during the haze day, while the concentrations of more oxygenated OVOCs showed good positive correlations among themselves but moderate negative correlations with the concentrations of hydrocarbons, less oxygenated OVOCs, and aerosol species. Our results indicate a spatial chemical homogeneity on the megacity scale to promote efficient secondary organic aerosol (SOA) production under haze conditions.

Phase-modulated metasurfaces (PMMs) have attracted considerable attention because of their widespread application in many fields. However, the most existing PMMs are only available in a relatively narrow band. In this paper, we propose a design of a broadband PMM based on vanadium dioxide (VO2) patches. The unit cell of the proposed PMM is composed of a surface layer supported by a 0.5 mm F4B with a dielectric constant of εr = 2.65, and a dielectric layer with a metal ground on its back. The surface layer consists of two opposite T-shaped metal patches connected by a VO2 patch. The VO2 patch can be used as an active element due to the insulator-to-metal transition of VO2. The process of phase transition is achieved by direct heating with a heating plate, without additional feeders affecting the performance of the PMM. The designed PMM can achieve a broadband phase difference within 180° ± 37° from 6.94 to 20.84 GHz, with a fractional bandwidth of 100%. Both full wave simulation and measurement results show that the proposed metasurface presents a good phase reconstruction performance over a wideband frequency range.

Alkali-activated slag (AAS) materials activated by NaOH or waterglass has been long-term criticized for the developed substantial shrinkage. To this regard, this paper explored MgO as both an activator and an expansive agent to prepare shrinkage-free AAS. The setting time, mechanical strength, pore structure, autogenous shrinkage, drying shrinkage, and hydration products of MgO-activated AAS were studied. Experimental results confirmed that MgO can effectively mitigate the autogenous shrinkage and drying shrinkage of AAS via the expansive deformation caused by Mg(OH)2. Generally, AAS with a higher dosage of MgO developed less shrinkages and refiner pore structures with more gel pores. An optimal dosage of 9% MgO is recommended to prepare AAS with near zero shrinkage and the highest flexural strength.

Seawater intrusion and drinking-water fluorosis are frequently documented along coastal plains. Groundwater is characterized by high OH−, Na+, total dissolved solids, and low Ca2+ because of seawater intrusion, and such conditions favor sediment fluoride-leaching and fluorosis. But the geological process of seawater intrusion has not been noticed when high-fluoride groundwater along coastal areas is discussed. The groundwater and sediments in a typical seawater intrusion and fluorosis area are gained, and fluoride-leaching simulation experiments are performed. Sediment fluoride levels are equal to or lower than average sediment fluoride levels in China and Shandong province, but strong fluoride-leaching in aquifers is observed. Compared with the supplied water from the non-intruded neighboring area, the local groundwater has higher fluoride levels, together with higher pH, total dissolved solids, HCO3−, Cl−, Br−, SO42−, Na+, K+, and low Ca2+ because of seawater intrusion. Aquifer sediment fluoride-leaching ability increases with an increase in seawater (brine water) mixing ratios, and NaCl or NaHCO3 levels, but with a decrease in CaCl2 levels. This directly confirms that seawater (brine water) intrusion promotes sediment fluoride-leaching, and the high pH, Na+, HCO3−, and low Ca2+ levels caused by seawater intrusion are responsible for the high-fluoride groundwater along coastal plains. HIGHLIGHTS The local groundwater is characterized by seawater intrusion and high fluorine levels, while the aquifer sediments show low fluorine levels.; The fluorine-leaching ability of aquifer sediments increases with higher ratios of seawater or brine water, higher levels of NaCl and NaHCO3, and lower levels of CaCl2.; Seawater intrusion is an important dynamic of groundwater fluorine enrichment along coastal plains.;

To study the flow characteristics of a new swashplate rotary valve distribution double-row axial piston pump, an instantaneous flow model was developed for the pump, the influences of structural parameters on the flow pulsation and uneven coefficient of flow were determined, and the ideal plunger distribution parameters were derived. On this basis, a valve distribution model was developed for the pump, the flow superposition process in the plunger cavity was analyzed, and the high-speed switching valve's control strategy was optimized. Additionally, the effects of parameters such as the plunger motion frequency, the plunger cavity's dead zone volume, the spool valve's preloading force, and the spool's equivalent mass on the flow characteristics were studied. The results show that the new pump had a small flow pulsation when there were five plungers in both the inner and outer rows and the dislocation angle was 18∘. The plunger's reverse-suction effect at the moment when the discharge valve opened and the suction valve closed and the plunger cavity's dead zone volume size were the primary factors affecting the size of the pump's flow spike. The discharge valve's opening was delayed by 3 ms to be consistent with the suction valve's closing time; for this case, the flow peak was small and the volumetric efficiency was the highest. The discharge valve began to close 2 ms early and closed completely at the critical point when the plunger transferred from the discharge stroke to the suction stroke, which helped the suction valve to open on time and improved the pump's oil absorption capacity. The active opening and closing control of the discharge valve improved the coordination of the flow distribution to a large extent, reduced the hysteresis of the suction valve, and ultimately improved the pump's volumetric efficiency and flow stability. The results of this study can provide theoretical guidance for the flow control of balanced double-row axial piston pumps with valve distribution.

A positioning system for ultra-wideband (UWB) electric micro-tillers suitable for complex greenhouse environments was designed as the basis for realizing unmanned micro-tillers to address the problem of the frequent safety accidents of existing micro-tillers. First, the positioning base station and tag were designed on the basis of the STM32 and DW1000 chip hardware. The real-time coordinate display of the micro-tiller in the greenhouse could also be realized with the design of the upper computer software. Then, the realization method of the positioning function, including the analysis of time difference of arrival (TDOA) and two-way ranging (TWR) positioning methods, and the selection of the best Taylor positioning algorithm through a MATLAB simulation were studied to reduce the influence of noise and measurement errors on measurement accuracy. Finally, a positioning system accuracy test was conducted. Test results revealed that the maximum positioning error of the micro-tiller positioning system is no more than 6 cm, and the average error is 4.4 cm. The optimized positioning error is reduced by 10.2 %, considering that the influence of the base station location on the accuracy. The positioning system of the greenhouse electric micro-tiller designed in this paper demonstrates a stable performance and positioning accuracy to meet the needs of greenhouse rotary tillage operations. This system has certain theoretical importance and reference value for the development of precise positioning technology for working tools in the greenhouse and the further realization of unmanned rotary tillage operations.

The atmospheric multiphase reaction of dinitrogen pentoxide (N2O5) with chloride-containing aerosol particles produces nitryl chloride (ClNO2), which has been observed across the globe. The photolysis of ClNO2 produces chlorine radicals and nitrogen dioxide (NO2), which alter pollutant fates and air quality. However, the effects of local meteorology on near-surface ClNO2 production are not yet well understood, as most observational and modeling studies focus on periods of clear conditions. During a field campaign in Kalamazoo, Michigan, from January–February 2018, N2O5 and ClNO2 were measured using chemical ionization mass spectrometry, with simultaneous measurements of atmospheric particulate matter and meteorological parameters. We examine the impacts of atmospheric turbulence, precipitation (snow, rain) and fog, and ground cover (snow-covered and bare ground) on the abundances of ClNO2 and N2O5. N2O5 mole ratios were lowest during periods of lower turbulence and were not statistically significantly different between snow-covered and bare ground. In contrast, ClNO2 mole ratios were highest, on average, over snow-covered ground, due to saline snowpack ClNO2 production. Both N2O5 and ClNO2 mole ratios were lowest, on average, during rainfall and fog because of scavenging, with N2O5 scavenging by fog droplets likely contributing to observed increased particulate nitrate concentrations. These observations, specifically those during active precipitation and with snow-covered ground, highlight important processes, including N2O5 and ClNO2 wet scavenging, fog nitrate production, and snowpack ClNO2 production, that govern the variability in observed atmospheric chlorine and nitrogen chemistry and are missed when considering only clear conditions.

Organic aerosol (OA) is a major component of tropospheric submicron aerosol that contributes to air pollution and causes adverse effects on human health. Chemical transport models have difficulties in reproducing the variability in OA concentrations in polluted areas, hindering understanding of the OA budget and sources. Herein, we apply both process-based and observation-constrained schemes to simulate OA in GEOS-Chem. Comprehensive data sets of surface OA, OA components, secondary organic aerosol (SOA) precursors, and oxidants were used for model–observation comparisons. The base models generally underestimate the SOA concentrations in China. In the revised schemes, updates were made on the emissions, volatility distributions, and SOA yields of semivolatile and intermediate-volatility organic compounds (SVOCs and IVOCs) and additional nitrous acid sources. With all the model improvements, both the process-based and observation-constrained SOA schemes can reproduce the observed mass concentrations of SOA and show spatial and seasonal consistency with each other. Our best model simulations suggest that anthropogenic SVOCs and IVOCs are the dominant source of SOA, with a contribution of over 50 % in most of China, which should be considered for pollution mitigation in the future. The residential sector may be the predominant source of SVOCs and IVOCs in winter, despite large uncertainty remaining in the emissions of IVOCs from the residential sector in northern China. The industry sector is also an important source of IVOCs, especially in summer. More SVOC and IVOC measurements are needed to constrain their emissions. Besides, the results highlight the sensitivity of SOA to hydroxyl radical (OH) levels in winter in polluted environments. The addition of nitrous acid sources can lead to over 30 % greater SOA mass concentrations in winter in northern China. It is important to have good OH simulations in air quality models.

Abstract The low-noise amplification of weak microwave signals is crucial for countless protocols in quantum information processing. Quantum mechanics sets an ultimate lower limit of half a photon to the added input noise for phase-preserving amplification of narrowband signals, also known as the standard quantum limit (SQL). This limit, which is equivalent to a maximum quantum efficiency of 0.5, can be overcome by employing nondegenerate parametric amplification of broadband signals. We show that, in principle, a maximum quantum efficiency of unity can be reached. Experimentally, we find a quantum efficiency of 0.69 ± 0.02, well beyond the SQL, by employing a flux-driven Josephson parametric amplifier and broadband thermal signals. We expect that our results allow for fundamental improvements in the detection of ultraweak microwave signals.

Conservation tillage has attracted increasing attention over recent decades, mainly due to its benefits for improving soil organic matter content and reducing soil erosion. However, the effects of long-term straw mulching under a no-till system on soil physicochemical properties and bacterial communities at different soil depths are still unclear. In this 12-year experiment of straw removal (CK) and straw mulching (SM) treatments, soil samples were collected at 0–5, 5–10, 10–20, and 20–30 cm soil depths. The results showed that the contents of organic carbon (C), nitrogen (N), and phosphorus (P) fractions, and bacterial abundance significantly decreased, whereas pH significantly increased with soil depth. Compared with CK, SM significantly increased total N, inorganic N, available P, available potassium, and soil water content at 0–5 cm, total organic C content at 0–10 cm, and dissolved organic C and N contents at 0–20 cm. Regarding bacterial communities, SM increased the relative abundances of Proteobacteria, Bacteroidetes, and Acidobacteria but reduced those of Actinobacteria, Chloroflexi, and Cyanobacteria. Bacterial Shannon diversity and Shannon's evenness at 0–5 cm were reduced by SM treatment compared to CK treatment. Furthermore, SM increased the relative abundances of some C-cycling genera (such as Terracidiphilus and Acidibacter) and N-cycling genera (such as Rhodanobacter, Rhizomicrobium, Dokdonella, Reyranella, and Luteimonas) at 0–5 cm. Principal coordinate analysis showed that the largest difference in the composition of soil bacterial communities between CK and SM occurred at 0–5 cm. Soil pH and N and organic C fractions were the major drivers shaping soil bacterial communities. Overall, SM treatment is highly recommended under a no-till system because of its benefits to soil fertility and bacterial abundance.

A high-selectivity bandpass filter (BPF) based on two merged ring resonators is presented in this paper. The structure of this proposed BPF can be seen as the two one-wavelength ring resonators merged each other by sharing the common λg/2 microstrip line. Due to symmetric structure, it can be analyzed by even- and odd-mode method and the locations of six transmission zeros are calculated using input impedance deductions. For further demonstration, a BPF example centered at 2 GHz is fabricated with high frequency selectivity. The measured 3-dB fractional bandwidth is 11% (1.89-2.11 GHz) and insertion loss is less than 2 dB in the passband. Good agreement between simulation and measurement verifies the feasibility of the design method.

Atmospheric chromophoric organic matter (COM) plays a fundamental role in photochemistry and aerosol aging. However, the effects of photodegradation on chemical components and photochemical reactivity of COM remain unresolved. Here, we report the potential effects of photodegradation on carbon contents, optical properties, fluorophore components and photochemical reactivity in aerosol. After 7 d of photodegradation, fluorescent intensity and the absorption coefficient of COM decrease by 71.4 % and 32.0 %, respectively. Photodegradation makes a difference to the chemical component of chromophore and the degree of aerosol aging. Low-oxidation humic-like substance (HULIS) is converted into high-oxidation HULIS due to photooxidation. Photodegradation also changes the photochemical reactivity. The generation of triplet-state COM (3COM*) decreases slightly in ambient particulate matter (ambient PM) but increases in primary organic aerosol (POA) following photodegradation. The results highlight that the opposite effect of photodegradation on photochemical reactivity in POA and ambient PM. However, the generation of singlet-oxygen (1O2) decreases obviously in POA and ambient PM, which could be attributed to photodegradation of precursors of 1O2. The combination of optical property, chemical component and reactive oxygen species has an important impact on the air quality. The new insights on COM photodegradation in aerosol reinforce the importance of studying dissolved organic matter (DOM) related with the photochemistry and aerosol aging.

Oxidation of aromatic volatile organic compounds (VOCs) leads to the formation of tropospheric ozone and secondary organic aerosol, for which gaseous oxygenated products are important intermediates. We show, herein, the experimental results of highly oxygenated organic molecules (HOMs) produced by the oxidation of benzene and toluene in a wide range of OH exposure and NOx conditions. The results suggest that multigeneration OH oxidation plays an important role in the product distribution, which likely proceeds more preferably via H subtraction than OH addition for early generation products from light aromatics. More oxygenated products present in our study than in previous flow tube studies, highlighting the impact of experimental conditions on product distributions. The formation of dimeric products, however, was suppressed and might be unfavorable under conditions of high OH exposure and low NOx in toluene oxidation. Under high-NOx conditions, nitrogen-containing multifunctional products are formed, while the formation of other HOMs is suppressed. Products containing two nitrogen atoms become more important as the NOx level increases, and the concentrations of these compounds depend significantly on NO2. The highly oxygenated nitrogen-containing products might be peroxyacyl nitrates, implying a prolonged effective lifetime of RO2 that facilitates regional pollution. Our results call for further investigation on the roles of high-NO2 conditions in the oxidation of aromatic VOCs.

We present the WRF-GC model v2.0, an online two-way coupling of the Weather Research and Forecasting (WRF) meteorological model (v3.9.1.1) and the GEOS-Chem model (v12.7.2). WRF-GC v2.0 is built on the modular framework of WRF-GC v1.0 and further includes aerosol–radiation interaction (ARI) and aerosol–cloud interaction (ACI) based on bulk aerosol mass and composition, as well as the capability to nest multiple domains for high-resolution simulations. WRF-GC v2.0 is the first implementation of the GEOS-Chem model in an open-source dynamic model with chemical feedbacks to meteorology. In WRF-GC, meteorological and chemical calculations are performed on the exact same 3-D grid system; grid-scale advection of meteorological variables and chemical species uses the same transport scheme and time steps to ensure mass conservation. Prescribed size distributions are applied to the aerosol types simulated by GEOS-Chem to diagnose aerosol optical properties and activated cloud droplet numbers; the results are passed to the WRF model for radiative and cloud microphysics calculations. WRF-GC is computationally efficient and scalable to massively parallel architectures. We use WRF-GC v2.0 to conduct sensitivity simulations with different combinations of ARI and ACI over China during January 2015 and July 2016. Our sensitivity simulations show that including ARI and ACI improves the model's performance in simulating regional meteorology and air quality. WRF-GC generally reproduces the magnitudes and spatial variability of observed aerosol and cloud properties and surface meteorological variables over East Asia during January 2015 and July 2016, although WRF-GC consistently shows a low bias against observed aerosol optical depths over China. WRF-GC simulations including both ARI and ACI reproduce the observed surface concentrations of PM2.5 in January 2015 (normalized mean bias of −9.3 %, spatial correlation r of 0.77) and afternoon ozone in July 2016 (normalized mean bias of 25.6 %, spatial correlation r of 0.56) over eastern China. WRF-GC v2.0 is open source and freely available from http://wrf.geos-chem.org (last access: 20 June 2021).

Mineral dust is a major light-absorbing aerosol, which can significantly reduce snow albedo and accelerate snow/glacier melting via wet and dry deposition on snow. In this study, three scenarios of internal mixing of dust in ice grains were analyzed theoretically by combining asymptotic radiative transfer theory and (core–shell) Mie theory to evaluate the effects on absorption coefficient and albedo of the semi-infinite snowpack consisting of spherical snow grains. In general, snow albedo was substantially reduced at wavelengths of µm by internal dust–snow mixing, with stronger reductions at higher dust concentrations and larger snow grain sizes. Moreover, calculations showed that a nonuniform distribution of dust in snow grains can lead to significant differences in the values of the absorption coefficient and albedo of dust-contaminated snowpack at visible wavelengths relative to a uniform dust distribution in snow grains. Finally, using comprehensive in situ measurements across the Northern Hemisphere, we found that broadband snow albedo was further reduced by 5.2 % and 9.1 % due to the effects of internal dust–snow mixing on the Tibetan Plateau and North American mountains. This was higher than the reduction in snow albedo caused by black carbon in snow over most North American and Arctic regions. Our results suggest that significant dust–snow internal mixing is important for the melting and retreat of Tibetan glaciers and North American mountain snowpack.

In this article, the lightweight design of a palletizing manipulator arm structure is carried out. The optimization target is designed in 3D with Solid Works. To determine the optimization area and the secondary reconstruction model after the structure is optimized, the reliability and cost of the design structure are also considered. The meta-software performs mechanical performance simulation experiments under the corresponding working conditions for the lightweight structural design of the target structure via the topology optimization methods. Finally, with additive manufacturing technology, the design and printing of the filled skeletal Voronoi structure and the nested-external-removal Voronoi structure of the palletizing manipulator arm are performed.

Nitrated aromatic compounds (NACs) are a group of key chromophores for brown carbon (light-absorbing organic carbon, i.e., BrC) aerosol, which affects radiative forcing. The chemical composition and sources of NACs and their contributions to BrC absorption, however, are still not well understood. In this study, PM2.5-bound NACs in Xi'an, Northwest China, were investigated for 112 daily PM2.5 filter samples from 2015 to 2016. Both the total concentrations and contributions from individual species of NACs show distinct seasonal variations. The seasonally averaged concentrations of NACs are 2.1 (spring), 1.1 (summer), 12.9 (fall), and 56 ng m−3 (winter). Thereinto, 4-nitrophenol is the major NAC component in spring (58 %). The concentrations of 5-nitrosalicylic acid and 4-nitrophenol dominate in summer (70 %), and the concentrations of 4-nitrocatechol and 4-nitrophenol dominate in fall (58 %) and winter (55 %). The NAC species show different seasonal patterns in concentrations, indicating differences in emissions and formation pathways. Source apportionment results using positive matrix factorization (PMF) further show large seasonal differences in the sources of NACs. Specifically, in summer, NACs were highly influenced by secondary formation and vehicle emissions (∼ 80 %), while in winter, biomass burning and coal combustion contributed the most (∼ 75 %). Furthermore, the light absorption contributions of NACs to BrC are wavelength-dependent and vary greatly by season, with maximum contributions at ∼ 330 nm in winter and fall and ∼ 320 nm in summer and spring. The differences in the contribution to light absorption are associated with the higher mass fractions of 4-nitrocatechol (λmax⁡= 345 nm) and 4-nitrophenol (λmax⁡= 310 nm) in fall and winter, 4-nitrophenol in spring, and 5-nitrosalicylic acid (λmax⁡= 315 nm) and 4-nitrophenol in summer. The mean contributions of NACs to BrC light absorption at a wavelength of 365 nm in different seasons are 0.14 % (spring), 0.09 % (summer), 0.36 % (fall), and 0.91 % (winter), which are about 6–9 times higher than their mass fractional contributions of carbon in total organic carbon. Our results indicate that the composition and sources of NACs have profound impacts on the BrC light absorption.

As critical precursors of ozone (O3) and secondary organic aerosols, volatile organic compounds (VOCs) play a vital role in air quality, human health, and climate change. In this study, a campaign of comprehensive field observations and VOC grid sampling was conducted in Xi'an, China, from 20 June to 20 July 2019 to identify the spatiotemporal concentration levels, sources, and secondary transformation potential of VOCs. During the observation period, the average VOC concentrations at the Chanba (CB), Di Huan Suo (DHS), Qinling (QL), and gridded sampling sites were 27.8 ± 8.9, 33.8 ± 10.5, 15.5 ± 5.8, and 29.1 ± 8.4 ppb, respectively. Vehicle exhaust was the primary source of VOC emissions in Xi'an, and the contributions of vehicle exhaust to VOCs at the CB, DHS, and QL sites were 41.3 %, 30.6 %, and 23.6 %–41.4 %, respectively. While industrial emissions were the second-largest source of VOCs in urban areas, contributions from aging sources were high in rural areas. High potential source contribution function values primarily appeared in eastern and southern Xi'an near the sampling site, which indicates that Xi'an exhibits a strong local VOC source. Moreover, alkenes, aromatics, and oxygenated VOCs played a dominant role in secondary transformation, which is a major concern in reducing O3 pollution in Xi'an.

Environmentally persistent free radicals (EPFRs) are a new type of substance with potential health risks. EPFRs are widely present in atmospheric particulates, but there is a limited understanding of the size-resolved health risks of these radicals. This study reports the exposure risks and source of EPFRs in atmospheric particulate matter (PM) of different particle sizes ( µm) in Linfen, a typical coal-burning city in China. The type of EPFRs in fine particles (< 2.1 µm) is different from that in coarse particles (2.1–10 µm) in both winter and summer. However, the EPFR concentration is higher in coarse particles than in fine particles in summer, and the opposite trend is found in winter. In both seasons, combustion sources are the main sources of EPFRs, with coal combustion as the major contributor in winter, while other fuels are the major source in summer. Dust contributes part of the EPFRs, and it is mainly present in coarse particles in winter and the opposite in summer. The upper respiratory tract was found to be the area with the highest risk of exposure to EPFRs of the studied aerosols, with an exposure equivalent to that of approximately 21 cigarettes per person per day. Alveolar exposure to EPFRs is equivalent to 8 cigarettes per person per day, with combustion sources contributing the most to EPFRs in the alveoli. This study helps us to better understand the potential health risks of atmospheric PM with different particle sizes.

We introduced a sediment-induced light attenuation algorithm into a biogeochemical model of the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system. A fully coupled ocean–atmospheric–sediment–biogeochemical simulation was carried out to assess the impact of sediment-induced light attenuation on primary production in the northern Gulf of Mexico during the passage of Hurricane Gustav in 2008. When compared with model results without sediment-induced light attenuation, our new model showed a better agreement with satellite data on both the magnitude of nearshore chlorophyll concentration and the spatial distribution of offshore bloom. When Hurricane Gustav approached, resuspended sediment shifted the inner shelf ecosystem from a nutrient-limited one to a light-limited one. Only 1 week after Hurricane Gustav's landfall, accumulated nutrients and a favorable optical environment induced a posthurricane algal bloom in the top 20 m of the water column, while the productivity in the lower water column was still light-limited due to slow-settling sediment. Corresponding with the elevated offshore NO3 flux (38.71 mmol N m−1 s−1) and decreased chlorophyll flux (43.10 mg m−1 s−1), the outer shelf posthurricane bloom should have resulted from the cross-shelf nutrient supply instead of the lateral dispersed chlorophyll. Sensitivity tests indicated that sediment light attenuation efficiency affected primary production when sediment concentration was moderately high. Model uncertainties due to colored dissolved organic matter and parameterization of sediment-induced light attenuation are also discussed.

High concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) in China have caused severe visibility degradation. Accurate simulations of PM2.5 and its chemical components are essential for evaluating the effectiveness of pollution control strategies and the health and climate impacts of air pollution. In this study, we compared the GEOS-Chem model simulations with comprehensive datasets for organic aerosol (OA), sulfate, nitrate, and ammonium in China. Model results are evaluated spatially and temporally against observations. The new OA scheme with a simplified secondary organic aerosol (SOA) parameterization significantly improves the OA simulations in polluted urban areas, highlighting the important contributions of anthropogenic SOA from semivolatile and intermediate-volatility organic compounds. The model underestimates sulfate and overestimates nitrate for most of the sites throughout the year. More significant underestimation of sulfate occurs in winter, while the overestimation of nitrate is extremely large in summer. The model is unable to capture some of the main features in the diurnal pattern of the PM2.5 chemical components, suggesting inaccuracies in the presented processes. Potential model adjustments that may lead to a better representation of the boundary layer height, the precursor emissions, hydroxyl radical concentrations, the heterogeneous formation of sulfate and nitrate, and the wet deposition of nitric acid and nitrate have been tested in the sensitivity analysis. The results show that uncertainties in chemistry perhaps dominate the model biases. The proper implementation of heterogeneous sulfate formation and the good estimates of the concentrations of sulfur dioxide, hydroxyl radical, and aerosol liquid water are essential for the improvement of the sulfate simulation. The update of the heterogeneous uptake coefficient of nitrogen dioxide significantly reduces the modeled concentrations of nitrate. However, the large overestimation of nitrate concentrations remains in summer for all tested cases. The possible bias in the chemical production and the wet deposition of nitrate cannot fully explain the model overestimation of nitrate, suggesting issues related to the atmospheric removal of nitric acid and nitrate. A better understanding of the atmospheric nitrogen budget, in particular, the role of the photolysis of particulate nitrate, is needed for future model developments. Moreover, the results suggest that the remaining underestimation of OA in the model is associated with the underrepresented production of SOA.

Physical vulnerability is a challenging and fundamental issue in landslide risk assessment. Previous studies mostly focus on generalized vulnerability assessment from landslides or other types of slope failures, such as debris flow and rockfall, while the long-term damage induced by slow-moving landslides is usually ignored. In this study, a method was proposed to construct physical vulnerability curves for masonry buildings by taking the Manjiapo landslide as an example. The landslide's force acting on the buildings' foundation is calculated by applying the landslide residual-thrust calculation method. Considering four rainfall scenarios, the buildings' physical responses to the thrust are simulated in terms of potential inclination by using Timoshenko's deep-beam theory. By assuming the landslide safety factor to be landslide intensity and inclination ratio to be vulnerability, a physical vulnerability curve is fitted and the relative function is constructed by applying a Weibull distribution function. To investigate the effects of buildings' parameters that influence vulnerabilities, the length, width, height, and foundation depth and Young's modulus of the foundation are analysed. The validation results on the case building show that the physical vulnerability function can give a good result in accordance with the investigation in the field. The results demonstrate that the building length, width, and foundation depth are the three most critical factors that affect the physical vulnerability value. Also, the result shows that the higher the ratio of length to width of the building, the more serious the damage to the building. Similarly, the shallower the foundation depth is, the more serious the damage will be. We hope that the established physical vulnerability curves can serve as tools for the quantitative risk assessment of slow-moving landslides.

Thermal conductivity evidence of a spinon Fermi surface has been rare. Here, the authors report a finite linear increase of thermal conductivity with temperature in Na2BaCo(PO4)2 at ultra-low temperature, suggesting possible gapless quantum spin liquid behavior.

At present, automatic driving technology has become one of the development direction of the future intelligent transportation system. The high high-precision map, which is an important supplement of the on on-board sensors under the condition of shielding or the restriction of observation distance, provides a priori information for high high-precision positioning and path planning of the automatic driving with the level of L3 and above. The position and semantic information of the road markings, such as the absolute coordinates of th e solid line and the bro ken line, are the basic components of the high high-precision map. At present, point cloud data are still one of the most important data source of the high high-precision map. So, how to get road markings information from original point clouds automatically deserve study. In this paper, point cloud is sliced by the mileage of the road, then each slice is projected onto respective vertical section section. Random Sample Consensus (RANSAC) algorithm is applied to establish road surface buffer area . Finally, moving window filtering is used to extract road surface point cloud from road surface buffer area area. On this basis, the road surface point cloud image is transformed into raster image with a certain resolution by using the method of inverse distance weighted interpolation , and the grid image is converted into binary image by using the method of adaptive threshold segmentation based on the integral graph. Then the method of the Euclidean clustering is used to extract the road markings point cloud from the binary image. Characteristic attribute detection is applied to recognize solid line marking from all clusters. Deep learning network framework pointnet++ is applied to recognize remain road markings including guideline, broken line, straight arrow, and right turn arrow.

Although there are many studies of particulate matter (PM) pollution in Beijing, the sources and processes of secondary PM species during haze periods remain unclear. Limited studies have investigated the PM formation in highly polluted environments under low- and high-relative-humidity (RH) conditions. Herein, we present a systematic comparison of species in submicron particles (PM1) in wintertime Beijing (29 December 2014 to 28 February 2015) for clean periods and pollution periods under low- and high-RH conditions. PM1 species were measured with an aerosol chemical species monitor (ACSM) and an Aethalometer. Sources and processes for organic aerosol (OA) were resolved by positive matrix factorization (PMF) with a multilinear engine 2 (ME-2). The comparisons for clean, low-RH pollution and high-RH pollution periods are made from three different aspects, namely (a) mass concentration, (b) mass fraction and (c) growth rate in diurnal profiles. OA is the dominant component of PM1, with an average mass concentration of 56.7 µg m−3 (46 %) during high-RH pollution and 67.7 µg m−3 (54 %) during low-RH pollution periods. Sulfate had higher concentration and mass fraction during high-RH pollution periods, while nitrate had higher concentration and mass fraction during low-RH pollution periods. The diurnal variations of nitrate and oxygenated organic aerosol (OOA) showed a daytime increase in their concentrations during all three types of periods. Nitrate had similar growth rates during low-RH (0.40 µg m−3 h−1) and high-RH (0.55 µg m−3 h−1) pollution periods. OOA had a higher growth rate during low-RH pollution periods (1.0 µg m−3 h−1) than during high-RH pollution periods (0.40 µg m−3 h−1). In contrast, sulfate had a decreasing trend during low-RH pollution periods, while it increased significantly with a growth rate of 0.81 µg m−3 h−1 during high-RH pollution periods. These distinctions in mass concentrations, mass fractions and daytime growth rates may be explained by the difference in the formation processes affected by meteorological conditions. In particular, photochemical oxidation and aqueous-phase processes may both produce sulfate and nitrate. The relative importance of the two pathways, however, differs under different meteorological conditions. Additional OOA formation under high-RH (> 70 %) conditions suggests aqueous-related formation pathways. This study provides a general picture of the haze formation in Beijing under different meteorological conditions.

We use the GEOS-Chem chemical transport model to examine the influence of bromine release from blowing-snow sea salt aerosol (SSA) on springtime bromine activation and O3 depletion events (ODEs) in the Arctic lower troposphere. We evaluate our simulation against observations of tropospheric BrO vertical column densities (VCDtropo) from the GOME-2 (second Global Ozone Monitoring Experiment) and Ozone Monitoring Instrument (OMI) spaceborne instruments for 3 years (2007–2009), as well as against surface observations of O3. We conduct a simulation with blowing-snow SSA emissions from first-year sea ice (FYI; with a surface snow salinity of 0.1 psu) and multi-year sea ice (MYI; with a surface snow salinity of 0.05 psu), assuming a factor of 5 bromide enrichment of surface snow relative to seawater. This simulation captures the magnitude of observed March–April GOME-2 and OMI VCDtropo to within 17 %, as well as their spatiotemporal variability (r=0.76–0.85). Many of the large-scale bromine explosions are successfully reproduced, with the exception of events in May, which are absent or systematically underpredicted in the model. If we assume a lower salinity on MYI (0.01 psu), some of the bromine explosions events observed over MYI are not captured, suggesting that blowing snow over MYI is an important source of bromine activation. We find that the modeled atmospheric deposition onto snow-covered sea ice becomes highly enriched in bromide, increasing from enrichment factors of ∼5 in September–February to 10–60 in May, consistent with composition observations of freshly fallen snow. We propose that this progressive enrichment in deposition could enable blowing-snow-induced halogen activation to propagate into May and might explain our late-spring underestimate in VCDtropo. We estimate that the atmospheric deposition of SSA could increase snow salinity by up to 0.04 psu between February and April, which could be an important source of salinity for surface snow on MYI as well as FYI covered by deep snowpack. Inclusion of halogen release from blowing-snow SSA in our simulations decreases monthly mean Arctic surface O3 by 4–8 ppbv (15 %–30 %) in March and 8–14 ppbv (30 %–40 %) in April. We reproduce a transport event of depleted O3 Arctic air down to 40∘ N observed at many sub-Arctic surface sites in early April 2007. While our simulation captures 25 %–40 % of the ODEs observed at coastal Arctic surface sites, it underestimates the magnitude of many of these events and entirely misses 60 %–75 % of ODEs. This difficulty in reproducing observed surface ODEs could be related to the coarse horizontal resolution of the model, the known biases in simulating Arctic boundary layer exchange processes, the lack of detailed chlorine chemistry, and/or the fact that we did not include direct halogen activation by snowpack chemistry.