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Determining recent Antarctic ice volume changes from satellite altimeter measurements of ice surface height requires a correction for contemporaneous vertical crustal deformation. This correction must consider two main sources of crustal deformation: (1) ongoing glacial isostatic adjustment (GIA), that is, the deformational, gravitational, and rotational response to Late Pleistocene and Holocene ice and ocean mass changes and (2) modern ice mass change. In this study, we seek to quantify the uncertainties associated with each of these corrections. Corrections of ice surface height changes for correction 1 have generally involved the adoption of global models of GIA defined by some preferred combination of ice history and mantle viscoelastic structure. We have computed the GIA correction generated from a coupled ice sheet–sea level model and a realistic Earth model incorporating three-dimensional viscoelastic structure. Integrating the difference between this correction and those from recent GIA analyses widely adopted in the literature yields an uncertainty in total present-day ice volume change equivalent to approximately 10 % of Antarctic ice mass loss inferred for the period 2010–2020. This reinforces earlier work indicating that ice histories characterized by relatively high excess ice volume at the Last Glacial Maximum may be introducing a significant error in estimates of modern melt rates. Regarding correction 2, a spatially invariant scaling has commonly been used to convert GIA-corrected ice surface height changes obtained from satellite altimetry to ice volume estimates. We adopt modeling results based on a projection of Antarctic ice mass change over the period 2015–2055 to demonstrate a spatial variability in the scaling of up to 10 % across the ice sheet. Furthermore, using these calculations, we find a systematic error of ∼ 3 % in the projected net ice volume change, with most of the difference arising in areas of West Antarctica above mantle zones of low viscosity.

This study implements the least-squares inversion method for solving the exhumation history from the thermochronologic age–elevation relationship (AER) based on the linear equation among exhumation rate, age and total exhumation from the closure depth to the Earth surface. Modeling experiments suggest significant and systematic influence of initial geothermal model, the a priori exhumation rate and the time interval length on the a posteriori exhumation history. Lessons learned from the experiments include that (i) the modern geothermal gradient can be used for constraining the initial geothermal model, (ii) a relatively high a priori exhumation rate would lead to systematically lower a posteriori exhumation and vice versa, (iii) the variance of the a priori exhumation rate controls the variation in the inverted exhumation history, and (iv) the choice of time interval length should be optimized for resolving the potential temporal changes in exhumation. To mitigate the dependence of inverted erosion history on these initial parameters, we implemented a new stepwise inverse modeling method for optimizing the model parameters by comparing the observed and predicted thermochronologic data and modern geothermal gradients. Finally, method demonstration was performed using four synthetic datasets and three natural examples of different exhumation rates and histories. It is shown that the inverted rock exhumation histories from the synthetic datasets match the whole picture of the “truth”, although the temporal changes in the magnitude of exhumation are underestimated. Modeling of the datasets from natural samples produces geologically reasonable exhumation histories. The code and data used in this work are available on Zenodo (https://doi.org/10.5281/zenodo.10839275).

Abstract Chronic dysregulation of peripheral lipids has been found to be associated with depression and cognition, but their interaction has not been investigated. Growing evidence has highlighted the association between peripheral lipoprotein levels with depression and cognition with inconsistent results. We assessed the association between peripheral lipids, depression, and cognition while evaluating their potential interactions using robust clinically relevant predictors such as lipoprotein levels and chronic medical disorders that dysregulate lipoproteins. We report an association between peripheral lipids, depression, and cognition, suggesting a common underlying biological mechanism driven by lipid dysregulation in two independent studies. Analysis of a longitudinal study of a cohort at high or low familial risk for major depressive disorder (MDD) (n = 526) found metabolic diseases, including diabetes, hypertension, and other cardiovascular diseases, were associated with MDD and cognitive outcomes. Investigating a cross-sectional population survey of adults in the National Health and Nutrition Examination Survey 2011–2014 (NHANES) (n = 2377), depression was found to be associated with high density lipoprotein (HDL) and cognitive assessments. In the familial risk study, medical conditions were found to be associated with chronic lipid dysregulation and were significantly associated with MDD using the structural equation model. A positive association between chronic lipid dysregulation and cognitive scores was found in an exploratory analysis of the familial risk study. In a complementary study, analysis of NHANES revealed a positive association of HDL levels with cognition. Further analysis of the NHANES cohort indicated that depression status mediated the interaction between HDL levels and cognitive tests. Importantly, the protective effect of HDL on cognition was absent in those with depressive symptoms, which may ultimately result in worse outcomes leading to cognitive decline. These findings highlight the potential for the early predictive value of medical conditions with chronic lipid dyshomeostasis for the risk of depression and cognitive decline.

In September 2020, a global aerosol forecasting model was implemented as an ensemble member of the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Ensemble Forecasting System (GEFS) v12.0.1 (hereafter referred to as “GEFS-Aerosols”). In this study, GEFS-Aerosols simulation results from 1 September 2019 to 30 September 2020 were evaluated using an aerosol budget analysis. These results were compared with results from other global models as well as reanalysis data. From this analysis, the global average lifetimes of black carbon (BC), organic carbon (OC), dust, sea salt, and sulfate are 4.06, 4.29, 4.59, 0.34, and 3.3 d, respectively, with the annual average loads of 0.14, 1.29, 4.52, 6.80, and 0.51 Tg. Compared with the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System–Goddard Chemistry Aerosol and Radiation Transport (GEOS4-GOCART) model, the aerosols in GEFS-Aerosols have a relatively short lifetime because of the faster removal processes in GEFS-Aerosols. Meanwhile, in GEFS-Aerosols, aerosol emissions are the determining factor for the mass and composition of aerosols in the atmosphere. The size (bin) distribution of aerosol emissions is as important as its total emissions, especially in simulations of dust and sea salt. Moreover, most importantly, the strong monthly and interannual variations in natural sources of aerosols in GEFS-Aerosols suggest that improving the accuracy of the prognostic concentrations of aerosols is important for applying aerosol feedback to weather and climate predictions.

Idiopathic pulmonary fibrosis is a disease caused by persistent micro-injuries to the lung ultimately resulting in death. Here, the authors describe the use of a small molecule OGG1 inhibitor, TH5487, as a potent and potentially clinically relevant treatment for IPF.

To investigate the physical and chemical processes of fine particle matter (PM) at the mid-upper planetary boundary layer (PBL), we conducted 1-year continuous measurements of fine PM, the chemical composition of non-refractory submicron aerosol (NR-PM1), and some gas species (including sulfur dioxide, nitrogen oxides, and ozone) at an opening observatory (∼ 600 m) at the top of Shanghai Tower (SHT), which is China's first and the world's second highest building located in the typical financial central business district of Shanghai, China. This is the first report on the characteristics of fine particles based on continuous and sophisticated online measurements at the mid-upper level of the urban PBL. The observed PM2.5 and PM1 mass concentrations at SHT were 25.5 ± 17.7 and 17.3 ± 11.7 µg m−3, respectively. Organics, nitrate (NO3), and sulfate (SO4) occupied the first three leading contributions to NR-PM1 at SHT, accounting for 35.8 %, 28.6 %, and 20.8 %, respectively. The lower PM2.5 concentration was observed at SHT by 16.4 % compared with that near the surface during the observation period. It was attributed to the decreased nighttime PM2.5 concentrations (29.4 % lower than the surface) at SHT in all seasons due to the complete isolations from both emissions and gas precursors near the surface. However, daytime PM2.5 concentrations at SHT were 12.4 %–35.1 % higher than those near the surface from June to October, resulted from unexpected larger PM2.5 levels during early to middle afternoon at SHT than at the surface. We suppose the significant chemical production of secondary aerosols existed in the mid-upper PBL, because strong solar irradiance, adequate gas precursors (e.g., NOx), and lower temperature were observed at SHT, favorable for both photochemical production and gas-to-particle partitioning. This was further demonstrated by the significant increasing rate of oxygenated organic aerosols and NO3 observed at SHT during 08:00–12:00 in spring (7.4 % h−1 and 12.9 % h−1), fall (9.3 % h−1 and 9.1 % h−1), and summer (13.0 % h−1 and 11.4 % h−1), which cannot be fully explained by vertical mixing. It was noted that extremely high NO3 was observed at SHT both in daytime and nighttime in winter, accounting for 37.2 % in NR-PM1, suggesting the efficient pathway from heterogeneous and gas oxidation formation. Therefore, we highlight the priority of NOx reduction in Shanghai for the further improvement of air quality. This study reported greater daytime PM2.5 concentrations at the height of 600 m in the urban PBL compared with surface measurement, providing insight into their potential effects on local air quality, radiation forcing, and cloud and/or fog formations. We propose that the efficient production of secondary aerosol in the mid-upper PBL should be cognized and explored more comprehensively by synergetic observations in future.

The latest operational National Air Quality Forecast Capability (NAQFC) has been advanced to use the Community Multiscale Air Quality (CMAQ) model (version 5.3.1) with the CB6r3 (Carbon Bond 6 revision 3) AERO7 (version 7 of the aerosol module) chemical mechanism and is driven by the Finite-Volume Cubed-Sphere (FV3) Global Forecast System, version 16 (GFSv16). This update has been accomplished via the development of the meteorological preprocessor, NOAA-EPA Atmosphere–Chemistry Coupler (NACC), adapted from the existing Meteorology–Chemistry Interface Processor (MCIP). Differing from the typically used Weather Research and Forecasting (WRF) CMAQ system in the air quality research community, the interpolation-based NACC can use various meteorological outputs to drive the CMAQ model (e.g., FV3-GFSv16), even though they are on different grids. In this study, we compare and evaluate GFSv16-CMAQ and WRFv4.0.3-CMAQ using observations over the contiguous United States (CONUS) in summer 2019 that have been verified with surface meteorological and AIRNow observations. During this period, the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign was performed, and we compare the two models with airborne measurements from the NASA DC-8 aircraft. The GFS-CMAQ and WRF-CMAQ systems show similar performance overall with some differences for certain events, species and regions. The GFSv16 meteorology tends to have a stronger diurnal variability in the planetary boundary layer height (higher during daytime and lower at night) than WRF over the US Pacific coast, and it also predicted lower nighttime 10 m winds. In summer 2019, the GFS-CMAQ system showed better surface ozone (O3) than WRF-CMAQ at night over the CONUS domain; however, the models' fine particulate matter (PM2.5) predictions showed mixed verification results: GFS-CMAQ yielded better mean biases but poorer correlations over the Pacific coast. These results indicate that using global GFSv16 meteorology with NACC to directly drive CMAQ via interpolation is feasible and yields reasonable results compared to the commonly used WRF approach.

Based on the quality-controlled observational spectral width data of the Beijing mesosphere–stratosphere–troposphere (MST) radar in the altitudinal range of 3–19.8 km from 2012 to 2014, this paper analyses the relationship between the proportion of negative turbulent kinetic energy (N-TKE) and the horizontal wind speed and the vertical shear of horizontal wind domain and gives the distributional characteristics of atmospheric turbulence parameters obtained by using different calculation models. Three calculation models of the spectral width method were used in this study – namely the H model (Hocking, 1985), N-2D model (Nastrom, 1997) and D–H model (Dehghan and Hocking, 2011). The results showed that the proportion of N-TKE in the H model, N-2D model and D–H model increases with the horizontal wind speed u and/or the vertical shear of horizontal wind speed ∂u∂z, and the maximum values are 60 %, 45 % and 35 %, respectively. When the∂u∂z is greater than 0.006 s−1, the N-TKE of the H model increases sharply with ∂u∂z; the increase rate is about 20%0.002s-1. For these three models, the results are similar except that the vertical shear of the horizontal wind speed is greater than 0.006 s−1. When ∂u∂z>0.006 s−1, the proportion of N-TKE in the N-2D and H models increases with ∂u∂z, while the proportion in the D–H model is less than 10 % and has slight variation. However, it is still necessary to consider the applicability of the N-2D model and D–H model in some weather processes with strong winds. The distributional characteristics with height of the turbulent kinetic energy dissipation rate ε and the vertical eddy diffusion coefficient Kz derived by the three models are consistent with previous studies. Still, there are differences in the values of turbulence parameters. Also, the range resolution of the radar has little effect on the differences in the range of turbulence parameters' values. The median values of ε in the H model, N-2D model and D–H model is 10−3.2–10−2.7, 10−3.0–10−2.6 and 10−3.3–10−2.8 m2 s−3, respectively. The median values of Kz in these three models are 100.3–100.7, 100.4–100.7 and 100.1–100.5 m2 s−1.

The slip rates of active faults in the northeastern Tibetan Plateau (NETP) require clarification to understand the lateral expansion of the Tibetan Plateau and assess the seismic hazards in this region. To obtain the continuous slip rates of active faults at the NETP, we constructed a three-dimensional (3D) numerical geomechanics model that includes a complex 3D fault system. The model also accounts for the physical rock properties, gravity fields, fault friction coefficients, initial stress, and boundary conditions. Following this, we present the long-term kinematics of NETP based on the horizontal and vertical velocities and fault slip rates acquired from the model. The fault kinematic characteristics indicate that the Laohushan, middle–southern Liupanshan, and Guguan–Baoji faults, as well as the junction area of the Maxianshan and Zhuanglanghe faults, are potential hazard areas for strong earthquakes. However, as these faults are currently in the stress accumulation stage, they are unlikely to cause a strong earthquake in the short term. In contrast, it is likely that the Jinqiangshan–Maomaoshan fault will generate a earthquake with a surface-wave magnitude (MS) of 7.1–7.3 in the coming decades. In addition, the velocity profiles across the NETP imply that the plate rotation is the primary deformation mechanism of the NETP even though the intra-block straining and faulting are non-negligible.

The National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) is on its way to deploying various operational prediction applications using the Unified Forecast System (https://ufscommunity.org/, last access: 18 June 2022), a community-based coupled, comprehensive Earth modeling system. An aerosol model component developed in collaboration between the Global Systems Laboratory, Chemical Science Laboratory, Air Resources Laboratory, and Environmental Modeling Center (GSL, CSL, ARL, EMC) was coupled online with the FV3 Global Forecast System (FV3GFS) using the National Unified Operational Prediction Capability (NUOPC)-based NOAA Environmental Modeling System (NEMS) software framework. This aerosol prediction system replaced the NEMS GFS Aerosol Component version 2 (NGACv2) system in the National Center for Environment Prediction (NCEP) production suite in September 2020 as one of the ensemble members of the Global Ensemble Forecast System (GEFS), dubbed GEFS-Aerosols v1. The aerosol component of atmospheric composition in the GEFS is based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). GEFS-Aerosols includes bulk modules from the Goddard Chemistry Aerosol Radiation and Transport model (GOCART). Additionally, the biomass burning plume rise module from High-Resolution Rapid Refresh (HRRR)-Smoke based on WRF-Chem was implemented. The GOCART dust scheme was replaced by the FENGSHA dust scheme (developed by ARL). The Blended Global Biomass Burning Emissions Product (GBBEPx version 3) provides biomass burning emission and fire radiative power (FRP) data. The global anthropogenic emission inventories are derived from the Community Emissions Data System (CEDS). All sub-grid-scale transport and deposition are handled inside the atmospheric physics routines, which required consistent implementation of positive definite tracer transport and wet scavenging in the physics parameterizations used by the NCEP's operational FV3GFS. This paper describes the details of GEFS-Aerosols model development and evaluation of real-time and retrospective runs using different observations from in situ measurement and satellite and aircraft data. GEFS-Aerosols predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational NGACv2 system with the fundamental updates (e.g., dust and fire emission) in the atmospheric and chemical transport model.

The upper troposphere and lower stratosphere (UTLS) region during the summer monsoon season over North America (NAM) is influenced by the transport of air from a variety of source regions over a wide range of timescales (hours to years). Age spectra are useful for characterizing the transport into such a region, and in this study we use and build on recently developed techniques to infer age spectra from trace gas measurements with photochemical lifetimes from days to centuries. We show that the measurements taken by the whole-air sampler instrument during the SEAC4RS campaign can be used to derive not only age spectra, but also path-integrated lifetimes of each of the trace gases and partitioning between North American and tropical surface source origins. The method used here can also clearly identify and adjust for measurement outliers that were influenced by polluted surface source regions. The results are generally consistent with expected transport features of the NAM but also provide a range of transport diagnostics (age spectra, trace gas lifetimes and surface source regions) that have not previously been computed solely from in situ measurements. These methods may be applied to many other existing in situ datasets, and the transport diagnostics can be compared with chemistry–climate model transport in the UTLS.

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a “state-of-the-science” CMAQ model version 5.3.1. The GFS–CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere–Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

The National Air Quality Forecast Capability (NAQFC) operated in the US National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) over the contiguous 48 US states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions (CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to CMAQ's CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015. The simulated PM2.5 was improved from 0.18 to 0.37, and the mean bias was reduced from −6.74 to −2.96 µg m−3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the CLBCs of global models, such as GEOS CLBCs, are not available.

Multiple observation data sets – Interagency Monitoring of Protected Visual Environments (IMPROVE) network data, the Automated Smoke Detection and Tracking Algorithm (ASDTA), Hazard Mapping System (HMS) smoke plume shapefiles and aircraft acetonitrile (CH3CN) measurements from the NOAA Southeast Nexus (SENEX) field campaign – are used to evaluate the HMS–BlueSky–SMOKE (Sparse Matrix Operator Kernel Emission)–CMAQ (Community Multi-scale Air Quality Model) fire emissions and smoke plume prediction system. A similar configuration is used in the US National Air Quality Forecasting Capability (NAQFC). The system was found to capture most of the observed fire signals. Usage of HMS-detected fire hotspots and smoke plume information was valuable for deriving both fire emissions and forecast evaluation. This study also identified that the operational NAQFC did not include fire contributions through lateral boundary conditions, resulting in significant simulation uncertainties. In this study we focused both on system evaluation and evaluation methods. We discussed how to use observational data correctly to retrieve fire signals and synergistically use multiple data sets. We also addressed the limitations of each of the observation data sets and evaluation methods.

Nuclear magnetic resonance imaging (MRI) has became an unavoidable medical tool in spite of its poor sensitivity. This fact motivates the efforts to enhance the nuclear magnetic resonance (NMR) probe performance. Thus, the nuclear spin excitation and detection, classically performed using radio-frequency coils, are required to be highly sensitive and homogeneous. The space harmonics suppression (SHS) method, already demonstrated to construct coil producing homogenous static magnetic field, is used in this work to design radio-frequency coils. The SHS method is used to determine the distribution of the electrical conductive wires which are organized in a saddle-coil-like configuration. The theoretical study of these SHS coils allows one to expect an enhancement of the signal-to-noise ratio with respect to saddle coil. Coils prototypes were constructed and tested to measure 1H NMR signal at a low magnetic field (8 mT) and perform MRI acquired at a high magnetic field (3 T). The signal-to-noise ratios of these SHS coils are compared to the one of saddle coil and birdcage (in the 3 T case) of the same size under the same pulse sequence conditions demonstrating the performance enhancement allowed by the SHS coils.

Social contact during suckling, in an enriched social environment, can reduce the aggressive behaviours of piglets during regrouping at weaning, and improve their production performance and welfare. The aim of this study was to determine the possible impact of suckling social contact on gut microbes. We performed 16S rRNA sequencing to measure the faecal microbial structure and function in piglets experiencing social contact. Eighteen-litter piglets were allocated to two treatments: an early continuous social contact (CSC) group where piglets from adjacent pens shared a mutual pen starting at 14 days postpartum and a control (CON) group where piglets had no contact with individuals from adjacent pens during the suckling period. The piglets were regrouped at 36 days of age. The litter weights at 35 and 63 days of age were measured. Faecal samples were randomly collected at 16, 35, 42, and 63 days of age and faecal DNA was determined. The results showed that the litter weight of piglets in the CSC group was significantly decreased at 63 days compared with the CON group. Continuous social contact also significantly decreased the microbial richness at 16 and 35 days of age (P 3, P

In current nutrition requirements of swine, although the protein diets are formulated based on the ileal digestibility of protein and amino acid (AA), there is a difference in nitrogen utilisation among various protein diets, which might be related to the AA release kinetics. To evaluate the relationship between AA release kinetics of feed proteins and nitrogen balance in finishing pigs, pigs were fed diets based on casein (CAS) or corn gluten meal (CGM) at normal or low-protein concentrations, and the AA release patterns were assessed. A 2 × 2 full factorial experimental design was used. 24 pigs (Duroc × Landrace × Yorkshire) with an initial weight of 67.0 ± 1.8 kg were randomly assigned to consume a normal-protein casein-based diet (N.CAS, 10% CP), normal-protein corn gluten meal-based diet (N.CGM, 10% CP), low-protein casein-based diet (L.CAS, 8.5% CP), or low-protein corn gluten meal-based diet (L.CGM, 8.5% CP) for 14 days (n = 6 per group; pigs housed and fed separately). The low-protein diets were associated with a more rapid release of AAs in the early stages of gastric digestion than the normal-protein diets. The N.CAS and L.CAS diets were associated with a peak AA release at approximately 4 h during trypsin digestion, whereas N.CGM and L.CGM were at approximately 16 h. The N.CAS diet was associated with the least dispersed release curves and lowest synchronisation indexes, implying that it was associated with the best AA release synchronism, whereas the L.CGM diet was on the contrary. The nitrogen intake (NI), faecal nitrogen, urine nitrogen (UN), total nitrogen, net protein utilisation and apparent biological value (ABV) of protein of pigs fed the L.CAS or L.CGM diets were lower than those fed the N.CAS or N.CGM diets (P

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.

Antioxidants have been always used to improve post-slaughter meat quality in broilers subjected to stress. Forsythia suspensa extract (FSE), a traditional Chinese herbal medicine, is generally regarded as a natural source of antioxidants. Therefore, the objective of this study was to test the hypothesis that FSE could protect post-slaughter breast muscles against oxidative injury induced by dexamethasone (DEX) mimicking chronic physiological stress in poultry production. Average daily gain and feed efficiency of poultry were suppressed by DEX and improved by FSE (P < 0.05). Dexamethasone caused the decrease in the redness value and the increase in the lightness and yellowness values and drip loss of the breast muscles (P < 0.05), and FSE had the converse effects (P < 0.05). Dietary FSE supplementation decreased monounsaturated fatty acid (FA) and increased polyunsaturated FA in breast muscles of broilers (P < 0.05). In addition, FSE decreased malondialdehyde and carbonyl content in the breast muscles of DEX-treated broilers (P < 0.05). The inhibition of 1,1-diphenyl-2-picryl-hydrazyl in the breast muscles was decreased by DEX and increased by FSE (P < 0.05). Total-antioxidant capacity and glutathione peroxidase activity in the breast muscles were decreased in birds subjected to DEX and increased in birds supplemented with FSE (P < 0.05). Totally, DEX suppressed growth performance and induced breast muscle oxidative injury in broilers, and FSE supplementation improved antioxidant capacity to attenuate these adverse effects. Therefore, FSE could be a potential natural antioxidant to alleviate oxidative injury of the breast muscles in broilers and to improve the meat quality for human consumption.

In this study, we focused on the retrieval of atmospheric water vapor density by optimizing the tomography technique. First, we established a new atmospheric weighted average temperature model that considers the effects of temperature and height, assisted by Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) products. Next, we proposed a new method to determine the scale height of water vapor, which will improve the quality of vertical constraints. Finally, we determined the smoothing factor in the horizontal constraint based on Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) products. To evaluate the advantages of the optimized technique over the traditional method, we used GPS datasets collected in Hong Kong in August 2016 to estimate the vertical distribution of water vapor density using both methods. We further validated the tomography results from the optimized technique using radiosonde products. The results show that the water vapor density quality obtained by the optimized technique is 13.8 % better below 3.8 km and 8.1 % better above 3.8 km than that obtained by the traditional technique. We computed the success rate of the tomography technique based on the Pearson product-moment correlation coefficient (PCC) and root mean square (RMS). The success rate of the optimized topography technique was approximately 10 % higher than that of the traditional tomography method.

Shigu creek is a highly urbanized small watershed in Dongguan City. Due to rapid urbanization, quick flood response has been observed, which posted great threat to the flood security of Dongguan City. To evaluate the impact of urbanization on the flood changes of Shigu creek is very important for the flood mitigation of Shigu creek, which will provide insight for flood planners and managers for if to build a larger flood mitigation system. In this paper, the Land cover/use changes of Shigu creek from 1987–2015 induced by urbanization was first extracted from a local database, then, the Liuxihe model, a physically based distributed hydrological model, is employed to simulate the flood processes impacted by urbanization. Precipitation of 3 storms was used for flood processes simulation. The results show that the runoff coefficient and peak flow have increased sharply.

Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.

This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter 2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE). It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

Pathogenic Escherichia coli (E. coli) is severely threatening the rabbit industry in China, and the concern over antibiotic-resistant bacteria has given rise to an urgent need for antibiotic alternatives. In this study, a member (ZRP1) of the Myoviridae family was isolated from rabbit faeces using a strain of rabbit atypical enteropathogenic E. coli (ZR1) as host. The one-step growth curve indicated that the latent period was around 25 to 30 min and the burst size was 144±31 plaque-forming unit/cell. The rate of phage-resistant mutation was 7×10–5±4×10–5. When the bacteriophage input at the multiplicity of infection (MOI) was 0.1, 1 or 10, the growth of host E. coli in broth was inhibited for 5 h. A single intravenous injection of ZRP1 at MOI 0.1, 1 or 10 significantly prolonged the survival time of rabbits which simultaneously received a lethal dose of ZR1.

With increasing attention for the indoor environment and the development of low-cost RGB-D sensors, indoor RGB-D images are easily acquired. However, scene semantic segmentation is still an open area, which restricts indoor applications. The depth information can help to distinguish the regions which are difficult to be segmented out from the RGB images with similar color or texture in the indoor scenes. How to utilize the depth information is the key problem of semantic segmentation for RGB-D images. In this paper, we propose an Encode-Decoder Fully Convolutional Networks for RGB-D image classification. We use Multiple Kernel Maximum Mean Discrepancy (MK-MMD) as a distance measure to find common and special features of RGB and D images in the network to enhance performance of classification automatically. To explore better methods of applying MMD, we designed two strategies; the first calculates MMD for each feature map, and the other calculates MMD for whole batch features. Based on the result of classification, we use the full connect CRFs for the semantic segmentation. The experimental results show that our method can achieve a good performance on indoor RGB-D image semantic segmentation.

The ITER divertor, in its full-power operation phase, will need to withstand steady-state heat fluxes of up to 10 MW•m−2. In addition, “slow” plasma transients such as re-attachment events must be considered, during which the surface heat fluxes will increase significantly in a short period of time (∼few seconds). To mitigate such transients, ITER plans to use the divertor gas injection system (GIS) to introduce radiating impurity species (probably using a hydrogenic carrier gas to improve response time) into the divertor plasma. We consider here various aspects of this process. First, we assess the time needed for critical damage to occur to the vertical target monoblocks by considering two limits: surface tungsten melting and critical heat flux to the coolant channel. This provides us with the time limits before which the plasma heat flux must be reduced to tolerable values. A dedicated experimental test bench has been used to measure the travel time of the injected gas from the valve to the divertor subvolume, using a manifold with the same pipe length as envisaged for the actual ITER device and studying a wide range of gas mixtures and throughputs. Once the gas has arrived in the divertor, we use the existing database of SOLPS4.3 simulations of the ITER divertor to estimate, for the case of neon as radiative species, the neon residence time, together with some new time-dependent SOLPS-ITER simulations to assess the time response of the divertor vertical target heat flux.

Two experiments were conducted to evaluate effects of coated compound proteases (CC protease) on apparent total tract digestibility (ATTD) of nitrogen (N) and energy, and apparent ileal digestibility (AID) of amino acids (AA) and nutrients in diets for pigs. In Exp. 1, 12 crossbred barrows (initial body weight: 20.14±1.71 kg) were housed in individual metabolism crates and allotted into 2 treatments with 6 piglets per treatment according to weight in a randomized complete block design. The 2 diets were corn-soybean meal basal diets with (0.2 g/kg) or without CC protease supplementation. The CC protease supplementation increased (p

With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

Harbours are very important objects in civil and military fields. To detect them from high resolution remote sensing imagery is important in various fields and also a challenging task. Traditional methods of detecting harbours mainly focus on the segmentation of water and land and the manual selection of knowledge. They do not make enough use of other features of remote sensing imagery and often fail to describe the harbours completely. In order to improve the detection, a new method is proposed. First, the image is transformed to Hue, Saturation, Value (HSV) colour space and saliency analysis is processed via the generation and enhancement of the co-occurrence histogram to help detect and locate the regions of interest (ROIs) that is salient and may be parts of the harbour. Next, SIFT features are extracted and feature learning is processed to help represent the ROIs. Then, by using classified feature of the harbour, a classifier is trained and used to check the ROIs to find whether they belong to the harbour. Finally, if the ROIs belong to the harbour, a minimum bounding rectangle is formed to include all the harbour ROIs and detect and locate the harbour. The experiment on high resolution remote sensing imagery shows that the proposed method performs better than other methods in precision of classifying ROIs and accuracy of completely detecting and locating harbours.

Nitrogen dioxide vertical column density (NO2 VCD) measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measurement has been used as a proxy for surface nitrogen oxide (NOx) emission, especially for anthropogenic urban emission, so accurate comparison of satellite and modeled NO2 VCD is important in determining the future direction of NOx emission policy. The NASA Ozone Monitoring Instrument (OMI) NO2 VCD measurements, retrieved by the Royal Netherlands Meteorological Institute (KNMI), are compared with a 12 km Community Multi-scale Air Quality (CMAQ) simulation from the National Oceanic and Atmospheric Administration. We found that the OMI footprint-pixel sizes are too coarse to resolve urban NO2 plumes, resulting in a possible underestimation in the urban core and overestimation outside. In order to quantify this effect of resolution geometry, we have made two estimates. First, we constructed pseudo-OMI data using fine-scale outputs of the model simulation. Assuming the fine-scale model output is a true measurement, we then collected real OMI footprint coverages and performed conservative spatial regridding to generate a set of fake OMI pixels out of fine-scale model outputs. When compared to the original data, the pseudo-OMI data clearly showed smoothed signals over urban locations, resulting in roughly 20–30 % underestimation over major cities. Second, we further conducted conservative downscaling of OMI NO2 VCDs using spatial information from the fine-scale model to adjust the spatial distribution, and also applied averaging kernel (AK) information to adjust the vertical structure. Four-way comparisons were conducted between OMI with and without downscaling and CMAQ with and without AK information. Results show that OMI and CMAQ NO2 VCDs show the best agreement when both downscaling and AK methods are applied, with the correlation coefficient R = 0.89. This study suggests that satellite footprint sizes might have a considerable effect on the measurement of fine-scale urban NO2 plumes. The impact of satellite footprint resolution should be considered when using satellite observations in emission policy making, and the new downscaling approach can provide a reference uncertainty for the use of satellite NO2 measurements over most cities.

Abstract Kiwifruit are a popular fruit worldwide; however, plant growth is threatened by abiotic stresses such as drought and high temperatures. Niacin treatment in plants has been shown to increase NADPH levels, thus enhancing abiotic stresses tolerance. Here, we evaluate the effect of niacin solution spray treatment on NADPH levels in the kiwifruit cultivars Hayward and Xuxiang. We found that spray treatment with niacin solution promoted NADPH and NADP+ levels and decreased both O2·- production and H2O2 contents in leaves during a short period. In fruit, NADPH contents increased during early development, but decreased later. However, no effect on NADP+ levels has been observed throughout fruit development. In summary, this report suggests that niacin may be used to increase NADPH oxidases, thus increasing stress-tolerance in kiwifruit during encounter of short-term stressful conditions.

Dust aerosols affect human life, ecosystems, atmospheric chemistry and climate in various aspects. Some studies have revealed intensified dust activity in the western US during the past decades despite the weaker dust activity in non-US regions. It is important to extend the historical dust records, to better understand their temporal changes, and to use such information to improve the daily dust forecasting skill as well as the projection of future dust activity under the changing climate. This study develops dust records in Arizona in 2005–2013 using multiple observation data sets, including in situ measurements at the surface Air Quality System (AQS) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites, and level 2 deep blue aerosol product by the Moderate Resolution Imaging Spectroradiometer. The diurnal and inter-annual variability of identified dust events are shown related to observed weather patterns (e.g., wind and soil moisture) and surface conditions (e.g., land cover type and vegetation conditions), suggesting a potential for use of satellite soil moisture and land products to help interpret and predict dust activity. Backtrajectories computed using NOAA's Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicate that the Sonoran and Chihuahuan deserts are important dust source regions during identified dust events in Phoenix, Arizona. Finally, we assess the impact of a recent strong dust event on western US air quality, using various observational and modeling data sets, during a period with a stratospheric ozone intrusion event. The capability of the current US National Air Quality Forecasting Capability (NAQFC) Community Multi-scale Air Quality (CMAQ) modeling system to represent the magnitude and the temporal variability of aerosol concentrations is evaluated for this event. Directions for integrating observations to further improve dust emission modeling in CMAQ are also suggested.

A regional air-quality forecast system's model of surface ozone variability based on cloud coverage is evaluated using satellite-observed cloud fraction (CF) information and a surface air-quality monitoring system. We compared CF and daily maximum ozone from the National Oceanic and Atmospheric Administration's National Air Quality Forecast Capability (NOAA NAQFC) with CFs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Environmental Protection Agency's AirNow surface ozone measurements during May to October 2014. We found that observed surface ozone shows a negative correlation with the MODIS CFs, showing around 1 ppb decrease for 10 % MODIS CF change over the contiguous United States, while the correlation of modeled surface ozone with the model CFs is much weaker, showing only −0.5 ppb per 10 % NAQFC CF change. Further, daytime CF differences between MODIS and NAQFC are correlated with modeled surface-ozone biases between AirNow and NAQFC, showing −1.05 ppb per 10 % CF change, implying that spatial and temporal misplacement of the modeled cloud field might have biased modeled surface ozone level. Current NAQFC cloud fields seem to have fewer CFs compared to MODIS cloud fields (mean NAQFC CF = 0.38 and mean MODIS CF = 0.55), contributing up to 35 % of surface-ozone bias in the current NAQFC system.

A new concept of nuclear reactors, Pebble Bed Water Reactor (PBWR), has attracted wide attention due to the advantages in the inherent safety performance, high conversion efficiency and low power density design. In this paper, the RPI wall boiling model was applied to solve the local flow and heat transfer of subcooled flow boiling in a random pebble bed with the tube diameter to particle diameter ratio D/d of 4. The effects of inlet temperature and particle diameter on the subcooled flow boiling characteristics were analysed. It was found that the hot spots and bubbles began to appear at the downstream of the contact points between neighbour pebbles or between pebbles and tube wall. With a higher inlet temperature, the onset of boiling occurred earlier and the void fraction near walls increases obviously. With a smaller pebble diameter, the onset of boiling was delayed and the bubbles occupied a smaller fraction of pebble surfaces. This study can provide useful information to the design of the PBWR.

Although phosphoenolpyruvate carboxylases (PEPCs) are reported to be involved in fatty acid accumulation, nitrogen assimilation, and salt and drought stresses, knowledge regarding PEPC gene functions is still limited, particularly in peanuts (Arachis hypogaea L.). In this study, the antisense expression of the peanut PEPC isoform 1 (AhPEPC1) gene increased the lipid content by 5.7%–10.3%. This indicated that AhPEPC1 might be related to plant lipid accumulation. The transgenic plants underwent more root elongation than the wild-type under salinity stress. Additionally, the specific down regulation of the AhPEPC1 gene improved the salt tolerance in peanuts. This is the first report on the role of PEPC in lipid accumulation and salt tolerance in peanuts.

The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) modeling system. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO2) observations are used to evaluate the experimental predictions in 2010. It is found that both ozone and NO2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO2. For both species the overpredictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO2 in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO2 biases in August show distinctively high values in the Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO2. Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO2, the morning predictions agree with the AQS observations reasonably well, but nighttime concentrations are overpredicted by around 100%.

A solids conveying theory called double-flight driving theory was proposed for helically channeled single screw extruders. In the extruder, screw channel rotates against static barrel channel, which behaves as cooperative embedded twin-screws for the positive conveying. They turn as two parallel arc plates, between which an arc-plate solid-plug was assumed. By analyzing the forces on the solid-plug in the barrel channel and screw channel, the boundary conditions when the solid-plug is waived of being cut off on barrel wall, were found to have the capacity of the positive conveying. Experimental data were obtained using a specially designed extruder with a helically channeled barrel in the feeding zone and a pressure-adjustable die. The effects of the barrel channel geometry and friction coefficients on the conveying mechanism were presented and compared with the experimental results. The simulations showed that the positive conveying could be achieved after optimizing extruder designs. Compared with the traditional design with the friction-drag conveying, the throughput is higher while screw torque and energy consumption are decreased. Besides, the design criteria of the barrel channel were also discussed.

Pirfenidone is an orally active small molecule that has recently been evaluated in large clinical trials for the treatment of idiopathic pulmonary fibrosis, a fatal disease in which the uncontrolled deposition of extracellular matrix leads to progressive loss of lung function. This review describes the activity of pirfenidone in several well-characterised animal models of fibrosis in the lung, liver, heart and kidney. In these studies, treatment-related reductions in fibrosis are associated with modulation of cytokines and growth factors, with the most commonly reported effect being reduction of transforming growth factor-β. The consistent antifibrotic activity of pirfenidone in a broad array of animal models provides a strong preclinical rationale for the clinical characterisation of pirfenidone in pulmonary fibrosis and, potentially, other conditions with a significant fibrotic component.

This study investigated the decadal variation of the direct surface solar radiation (DiSR) and the diffuse surface solar radiation (DfSR) during 1961–2008 in the Shanghai megacity as well as their relationships to Aerosol Optical Depth (AOD) under clear-sky conditions. Three successive periods with unique features of long term variation of DiSR were identified for both clear-sky and all-sky conditions: a "dimming" period from the late 1960s to the mid 1980s, a "stabilization"/"slight brightening" period from the mid 1980s to the mid 1990s, and a "renewed dimming" period thereafter. During the two dimming periods of DiSR, DfSR brightened significantly under clear-sky conditions, indicating that change in atmospheric transparency resulting from aerosol emission has an important role on decadal variation of surface solar radiation (SSR) over this area. The analysis on the relationship between the Moderate-resolution Imaging Spectroradiometer (MODIS) retrieved AOD and the corresponding hourly measurements of DiSR and DfSR under clear-sky conditions clearly revealed that AOD is significantly correlated and anti-correlated with DfSR and DiSR, respectively, both above 99% confidence in all seasons, indicating the great impact of aerosols on SSR through absorption and/or scattering in the atmosphere. In addition, both AOD and the corresponding DiSR and DfSR measured during the satellite passage over Shanghai show obvious weekly cycles. On weekends, AOD is lower than the weekly average, corresponding to higher DiSR and lower DfSR, while the opposite pattern was true for weekdays. Less AOD on weekends due to the reduction of transportation and industrial activities results in enhancement of atmospheric transparency under cloud free conditions so as to increase DiSR and decrease DfSR simultaneously. Results show that aerosol loading from the anthropogenic emissions is an important modulator for the long term variation of SSR in Shanghai.

We report on total gaseous mercury (TGM) measurements made in Pudong, Shanghai in August/September 2009. The average TGM was 2.7 ± 1.7 ng m−3. This represents about 90% of the total atmospheric mercury. This is an underestimate for an annual-mean concentration because the meteorology in September favored predominantly easterly oceanic air, replaced in other seasons by airflow from industrial areas. The observed TGM follows a pattern seen in other cities around the world: a background elevated over mean hemispheric background (1.5 ng m−3), and pollution plumes of different magnitude and duration, interspersed with very sharp spikes of high concentration (60 ng m−3). The September 2009 Shanghai measurements are lower than those reported for most other Chinese cities and Mexico City, and similar to concentrations found in some Asian and in North American cities. Such comparisons are tenuous because of differences in season and year of the respective measurements. Our results should not be used for regulatory purposes. We find that the observed TGM are most likely coming from coal fired power plants, smelters and industrial sources, based on its high correlation with NOx, SO2, CO and wind directions.

East Asia contributes to nearly 50% of the global anthropogenic mercury emissions into the atmosphere. Recently, there have been concerns about the long-range transport of mercury from East Asia, which may lead to enhanced dry and wet depositions in other regions. In this study, we performed four monthly simulations (January, April, July and October in 2005) using CMAQ-Hg v4.6 for a number of emission inventory scenarios in an East Asian model domain. Coupled with mass balance analyses, the chemical transport of mercury in East Asia and the resulted mercury emission outflow were investigated. The total annual mercury deposition in the region was estimated to be 821 Mg, with 396 Mg contributed by wet deposition and 425 Mg by dry deposition. Anthropogenic emissions were responsible for most of the estimated deposition (75%). The deposition caused by emissions from natural sources was less important (25%). Regional mercury transport budgets showed strong seasonal variability, with a net removal of RGM (7–15 Mg month−1) and PHg (13–21 Mg month−1) in the domain, and a net export of GEM (60–130 Mg month−1) from the domain. The outflow caused by East Asian emissions (anthropogenic plus natural) was estimated to be in the range of 1369–1671 Mg yr−1, of which 50–60% was caused by emissions from natural sources. The emission outflow represented about 75% of the total mercury emissions in the region, and would contribute to 20–30% of mercury deposition in remote receptors.

sn-Glycerol-3-phosphate acyltransferase (GPAT) catalyzes the committed step in the production of glycerolipids. The functions of GPAT genes have been intensively studied in Arabidopsis, but not in peanuts (Arachis hypogaea L.). In this study, six AhGPAT genes were isolated from peanuts. Quantitative real-time RT-PCR analysis indicated that the AhGPAT9 transcript was more abundant in the stems, flowers, and seeds, whereas the transcript abundances of five other genes were higher in the leaves or flowers than in the other tissues examined. During seed development, the transcript levels of AhGPAT9 gradually increased, whereas the transcript levels of the other five genes decreased. In addition, the levels of AhGPAT2 transcript were distinctly enhanced after exposure to all four kinds of stress treatments except for ABA-treated leaves. The transcripts of AhGPAT1, AhGPAT6, AhGPAT8 and AhATS1 increased substantially in roots exposed to salt, drought, and ABA stress. The expressions of AhGPAT6, AhGPAT8, AhGPAT9 and AhATS1 were slightly higher in leaves under certain stress conditions than under normal conditions. The present study provides significant information for modifying oil deposition and improving the abiotic stress resistance of peanuts through molecular breeding.

Close talk between inflammatory mediators and immunological cytokines has been discovered and reported. In this study, the role of nuclear factor of activated T cell-2 (NFAT2) in regulation of high mobility group box-1 (HMGB1) release was investigated. THP-1 cell and HEK293T cell were incubated and stimulated by lipopolysaccharide (LPS). Firstly, binding site between HMGB1 and NFAT2 was identified by co-immunoprecipitation (IP). Box A, Box B and CT domain of HMGB1 were constructed, as well as Rel-homology-domain (RHD), pre-RHD and pro-RHD of NFAT2. THP-1 cell was harvested, cell lysate and culture medium were collected at appointed times. Binding between HMGB1 and NFAT2 was measured, HMGB1 protein level in culture medium was analyzed at the same time. Secondly, the role of NFAT2 in regulating HMGB1 release was investigated. When THP-1 cell was cultured for 24 h, HMGB1 protein level was measured at appointed times with or without siRNA to inhibit NFAT2 expression. Our data show that HMGB1 bound to NFAT2 in THP-1 cell cytoplasm. Further experiments showed that box B domain of HMGB1 could bind to pre-RHD of NFAT2. After stimulation by LPS, interaction between HMGB1 and NFAT2 was discovered decreasing gradually. However, HMGB1 protein level increased in culture medium at the same time. Furthermore, HMGB1 release could be enhanced by NFAT2 inhibition. Taken together, release of HMGB1 could be regulated by NFAT2 in human monocytes.