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A historic rainstorm occurred over Henan, China, in July 2021 (“7.20” extreme precipitation event), resulting in significant human casualties and socioeconomic losses. A global variable-resolution model (MPAS-Atmosphere v7.3) was employed to simulate this extreme precipitation event. A series of simulations have been done at both quasi-uniform (60 and 15 km) and variable-resolution (60–15 and 60–3 km) meshes from hydrostatic to nonhydrostatic scale with two parameterization scheme suites. For the 48 h peak precipitation duration (20–22 July), the 60–3 km variable-resolution simulation coupled with the scale-aware convection-permitting parameterization scheme suite stands out predominantly among other simulation experiments as it reproduces this extreme precipitation event most accurately. At 15 km resolution, the 60–15 km variable-resolution simulation achieves comparable forecasting skills to the 15 km quasi-uniform simulation but at a much reduced computing cost. In addition, we found that the default mesoscale suite generally outperforms the convection-permitting suite at 15 km resolution as simulations coupled with the convection-permitting suite missed the third peak of this extreme precipitation event, while the mesoscale suite did not. Furthermore, it is found that the large-scale circulation plays a critical role in the peak precipitation simulations at 15 km resolution, via influencing the simulated low-level wind. During the second peak precipitation period, simulations with the convection-permitting parameterization scheme suite at 15 km resolution generate a prominent low-level easterly wind component bias, which is largely attributed to the excessively evaporative cooling in the lower troposphere. This study further reveals that at 15 km resolution the diabatic heating from the grid-scale precipitation accounts more for the low-level wind bias than the convective-scale precipitation. Given that two different cloud microphysics schemes, namely Thompson and WSM6 schemes, are used in the convection-permitting and default mesoscale parameterization scheme suites, respectively, these microphysics schemes are found to be the primary contributor to the low-level wind simulation bias.

LuTan-1 (LT-1) satellite constellation is used to conduct surface deformation monitoring. Following the successful launch of two satellites, we began to use the independently developed LandSAR software for differential interferometric data processing and application at the beginning of 2022. In this paper, we tested the LandSAR software by assessing the DInSAR and stacking modules. We used 21 LT-1 single look complex (SLC) images from December 2022 to May 2023 to conduct DInSAR and stacking processing of Datong City, Shanxi Province. DInSAR revealed more subsidence funnels and larger relative deformation values compared to stacking. We tested the DInSAR technology with different parameter combination. Results show that multi-looking factor is the most important to detect the deformation details because of the phase gradient limitation of DInSAR. Compared multi-looking ratios of 2×2 and 4×4, the subsiding funnels that were detected decreased from 60 to 47. After deep testing and assessment, we found that the linear model used by stacking affects the result severely, meaning that most of the subsidence of coal mines were not linear. Stacking only found 32 subsidence funnels which were active coal mines during our observation time. The test result show that LandSAR was compatible for DInSAR and stacking. And it is useful to observe linear and nonlinear deformation in the coal mine regions.

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.

Land surface temperature (LST) is widely used in research fields such as numerical forecasting, global circulation models, and regional climate models. For the remote sensing data from satellites with thermal infrared detection capability, the land surface temperature (LST), land surface emissivity (LSE), and atmospheric influence are mixed together. Using different assumptions and approximations for the radiative transfer equations and surface emissivity, various LST algorithms have been proposed. Among these algorithms, the split-window (SW) algorithm is currently most widely used. Besides, with the rapid development of machine learning, new ideas have been emerged for quantitative remote sensing inversion. For a hyperspectral remote sensing satellite with over 20 thermal infrared channels, machine learning methods such as random forest and artificial neural network can be selected to build an integrated separation and inversion algorithm for LST and LSE.In this paper, the influencing factors of LST inversion using thermal infrared hyperspectral satellites data is discussed, taking the SW algorithm and integrated machine learning algorithm as examples, and the contribution of these factors to the LST inversion error is analysed. We hope this paper could provide valuable reference for the design, index analysis and error calculation for remote sensing satellites with thermal infrared hyperspectral detection capability.

Infrared hyperspectral imaging is an important technical means to obtain the emissivity spectra and temperature of land surface target, and is an important development direction of spaceborne optical remote sensing in the future. Under the natural rugged land surface condition, the quality of infrared hyperspectral imaging data is affected by terrain condition, atmospheric condition and instrument performance. Therefore, the instrument signal-to-noise ratio and the calibration accuracy could not directly describe the measurement accuracy of the hyperspectral characteristics of target. An uncertainty prediction model of spaceborne infrared hyperspectral images over rugged land surface is established, in this paper. This model could simulate the surface scene, the atmospheric radiation transfer over rugged land surface, and the imaging process of the spaceborne spectrometer. At the same time, the uncertainty transfer from the surface signal to the restored radiance data product could be realized. The generated uncertainty results include the fluctuation of the surface signal, the error of the atmospheric transmission model, the influence of topographic relief, the response characteristics of the imaging spectrometer and the calibration uncertainty. Based on this model, we can also realize the ranking of the uncertainty contribution of the above links, which could help to identify the weak link in the remote sensing measurement chain. The random simulation experiments over a rugged desert scene were conducted to verified the model. It is indicated that more than 99.9% of the stochastic simulation radiance spectra are in the range of the predicted uncertainty.

Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower in Guangzhou, the core megacity in South China, and interpret the measurements with a 1-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10, 118, 168, and 488 m, with the highest (488 m) measurement platform higher than the typical height of the nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with a vertical ozone gradient between the 10 and 488 m heights (ΔO3/ΔH10–488 m) of 3.6–6.4 ppbv hm−1 in nighttime and 4.4–5.8 ppbv hm−1 in daytime. We identify a high ozone residual ratio, defined as the ratio of ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 69 %–90 % in January, April, and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer. The tower-based measurement also indicates that the nighttime surface Ox (Ox= O3+NO2) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both the nighttime and the following day's daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe a significant decrease in ozone and an increase in NO2 and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to an NOE event by introducing ozone-rich and NOx-poor air into the RL to enter the nighttime stable boundary layer. The CMAQ model simulations also demonstrate an enhanced positive contribution of vertical diffusion (ΔVDIF) to ozone at the 10 and 118 m heights and a negative contribution at the 168 and 488 m heights during the NOE event. We also observe a strong correlation between nighttime RL ozone and the following day's surface maximum daily 8 h average (MDA8) ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of a convective mixing layer, which is supported by the CMAQ diagnosis of the ozone budget, suggesting that the mixing of ozone-rich air from nighttime RL downward to the surface via the entrainment is an important mechanism for aggravating ozone pollution the following day. We find that the bias in CMAQ-simulated surface MDA8 ozone the following day shows a strong correlation coefficient (r= 0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics.

China is facing the challenge of synergistic reduction of air pollutants and CO2 emissions. However, the studies on its historical progress and future priorities are insufficient. This study compiled China's emission inventory of air pollutants and CO2 from 2005 to 2021 (ABaCAS-EI v2.0 dataset) based on a unified emission-source framework by considering the influences of activity level, technology evolution, and emission control policies. The characteristics of air pollutants and CO2 emissions were comprehensively analyzed from multiple dimensions such as time, space, sector, and synergies between air pollutants and CO2 emissions. Mitigation policies have decoupled the emissions of air pollutants and CO2 with economic development in China since 2013. In the context of growing activity levels, energy structure adjustment and energy and material saving reduced the average annual increase rate of CO2 emissions by 7 % after 2011. Based on this, end-of-pipe control contributed 51 %–98 % of air pollutant emission reductions after 2013. Industrial boilers and residential fossil fuel combustion sectors in seven provinces (Beijing, Tianjin, Shanghai, Jilin, Henan, Sichuan, and Qinghai) achieved emission reductions in both air pollutants and CO2 during 2013–2021. The declining trends in both the sectoral and regional emission ratios of air pollutants to CO2 indicated that the potential for synergistic emission reduction in China declined from 2013 to 2021. The emission ratios in 2021 showed that residential fossil fuel combustion, iron and steel industry, and transportation exhibited relatively higher co-benefits of SO2, PM2.5, NOx, and VOC emission reductions when CO2 emissions were reduced. Most cities with a higher potential to synergistically reduce NOx, VOC, and CO2 emissions were within the Yangtze River Economic Belt, while those with a higher potential to co-control SO2 and CO2, and PM2.5 and CO2 were in southern and northeast China, respectively. Further deconstruction of the sectoral emissions in 2021 suggested future reduction measures: for example, controlling coal consumption in the energy field; promoting innovative technologies with low air pollutant emission intensities and coal-saving measures in the iron and steel industry; combining coal and carbonate replacement technologies with separated particle control measures in the cement industry; and controlling light-duty passenger vehicles, heavy-duty trucks, agricultural machinery, and inland water transport in the transportation sector. Our dataset and findings provide insights into the co-control of air pollutants and CO2 emissions in the future in China and other countries with the same demand. Our ABaCAS-EI v2.0 dataset can be accessed from https://doi.org/10.6084/m9.figshare.21777005.v1 (S. Li et al., 2022) by species, sector, and province.

Eastern China (EC), located in the downstream region of the Tibetan Plateau (TP), is a large area with frequent haze pollution. In addition to air pollutant emissions, meteorological conditions are a key inducement for air pollution episodes. Based on the study of the Great Smog of London in 1952 and haze pollution in EC over recent decades, it is found that the abnormal “warm cover” (air–temperature anomalies) in the middle troposphere, as a precursory strong signal, could be connected to severe air pollution events. The convection and vertical diffusion in the atmospheric boundary layer (ABL) were suppressed by a relatively stable structure of warm cover in the middle troposphere leading to ABL height decreases, which were favorable for the accumulation of air pollutants in the ambient atmosphere. The anomalous structure of the troposphere's warm cover not only exist in heavy haze pollution on the daily scale, but also provide seasonal, interannual and interdecadal strong signals for frequently occurring regional haze pollution. It is revealed that a close relationship existed between interannual variations of the TP's heat source and the warm cover strong signal in the middle troposphere over EC. The warming TP could lead to anomalous warm cover in the middle troposphere from the plateau to the downstream EC region and even the entire East Asian region, thus causing frequent winter haze pollution in EC region.

Abstract Background Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. Results Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. Conclusions This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

We present a novel airborne imaging differential optical absorption spectroscopy (DOAS) instrument: the Ultraviolet Visible Hyperspectral Imaging Spectrometer (UVHIS), which is developed for trace gas monitoring and pollution mapping. Within a broad spectral range of 200 to 500 nm and operating in three channels, the spectral resolution of UVHIS is better than 0.5 nm. The optical design of each channel comprises a fore-optics with a field of view (FOV) of 40∘, an Offner imaging spectrometer and a charge-coupled device (CCD) array detector of 1032×1072 pixels. A first demonstration flight using UVHIS was conducted on 23 June 2018, above an area of approximately 600 km2 in Feicheng, China, with a spatial resolution of about 25 m×22 m. Measurements of nadir backscattered solar radiation of channel 3 are used to retrieve tropospheric vertical column densities (VCDs) of NO2 with a mean total error of 3.0×1015 molec cm−2. The UVHIS instrument clearly detected several emission plumes transporting from south to north, with a peak value of 3×1016 molec cm−2 in the dominant one. The UVHIS NO2 vertical columns are consistent with the ground-based mobile DOAS observations, with a correlation coefficient of 0.65 for all co-located measurements, a correlation coefficient of 0.86 for the co-located measurements that only circled the steel factory and a slight underestimation for the polluted observations. This study demonstrates the capability of UVHIS for NO2 local emission and transmission monitoring.

Citrus trees of cv. Huangguogan, 8-, 30-, and 280-year-old (8s, 30s, and 280s, respectively), were used to explore the photosynthesis and related enzyme activity. In spring shoot leaves, net photosynthetic rate (PN) of the 280s was significantly lower than that of the 30s and 8s, but it was opposite in summer shoot leaves. PN of the summer shoots was higher than that of the spring shoots. PN was significantly positively correlated with stomatal conductance, intercellular CO2 concentration, and transpiration rate, but was negatively correlated with maximum photochemical quantum yield of PSII photochemistry. The effect of age on variable fluorescence/minimal fluorescence was similar to that of minimal fluorescence, variable fluorescence, maximal fluorescence yield of the dark-adapted state. Fruits of the 280s had significantly lower sugar components than those of the 8s and 30s. Results showed that fruits of the 8s and 30s actively accumulated photosynthesis products, which was verified by the higher PN in the spring shoots, lower acidic invertase and neutral invertase activities, and higher sucrose phosphate synthase than that of the 280s.

Comprehensive chlorine heterogeneous chemistry is incorporated into the Community Multiscale Air Quality (CMAQ) model to evaluate the impact of chlorine-related heterogeneous reaction on diurnal and nocturnal nitrate formation and quantify the nitrate formation from gas-to-particle partitioning of HNO3 and from different heterogeneous pathways. The results show that these heterogeneous reactions increase the atmospheric Cl2 and ClNO2 level (∼ 100 %), which further affects the nitrate formation. Sensitivity analyses of uptake coefficients show that the empirical uptake coefficient for the O3 heterogeneous reaction with chlorinated particles may lead to the large uncertainties in the predicted Cl2 and nitrate concentrations. The N2O5 uptake coefficient with particulate Cl− concentration dependence performs better in capturing the concentration of ClNO2 and nocturnal nitrate concentration. The reaction of OH and NO2 in the daytime increases the nitrate by ∼15 % when the heterogeneous chlorine chemistry is incorporated, resulting in more nitrate formation from HNO3 gas-to-particle partitioning. By contrast, the contribution of the heterogeneous reaction of N2O5 to nitrate concentrations decreases by about 27 % in the nighttime, when its reactions with chlorinated particles are considered. However, the generated gas-phase ClNO2 from the heterogeneous reaction of N2O5 and chlorine-containing particles further reacts with the particle surface to increase the nitrate by 6 %. In general, this study highlights the potential of significant underestimation of daytime concentrations and overestimation of nighttime nitrate concentrations for chemical transport models without proper chlorine chemistry in the gas and particle phases.

Pot experiments were conducted to determine the effects of nitrogen (N) fertilization rate on the photosynthetic efficiency of 'Huangguogan' (Citrus reticulata × Citrus sinensis). We observed that plant growth increased with increasing N. Maximum values for parameters evaluated were recorded for an N addition rate of 120 g per year. Leaf chlorophyll content was positively correlated with the leaf N content. The relative reduction in photosynthetic rate (PN) at high N (150 and 180 g) correlated with the parallel decreases in the leaf N content. Rubisco activity was positively correlated with the initial slope of the PN/Ci response curve.indicating that N supplement improved photosynthesis by enhancing carboxylation and CO2 diffusion, photosynthetic capacity increased with N supply up to 120 g. Thereafter, the rate of increase declined with any further increase in N supply. These results provide a reference for a rational application of nitrogen fertilizer in orchards of 'Huangguogan'.

Mitigation of multipactor in waveguides is of importance, and strategies have included the addition of external fields, materials engineering, or surface modifications. Here, geometry modifications of rectangular waveguide surfaces and the application of an axial magnetic field are investigated for suppressing multipactor growth. A Monte Carlo approach has been used to simulate electron dynamics. The empirical secondary electrons yield is modeled based on a modified Vaughan approach. The electric fields driving electron transport were derived from separate electromagnetic calculations to adequately include field perturbations due to the presence of surface patterns in the rectangular waveguide structure. Combinations of grooves and a DC magnetic field are shown to effectively mitigate multipactor growth at field strengths up to ∼105 V/m. Finding optimal combinations for an arbitrary field and operating frequency requires further work.

Water-soluble humic-like substances (HULISWS) are a major redox-active component of ambient fine particulate matter (PM2.5); however, information on their sources and associated redox activity is limited. In this study, HULISWS mass concentration, various HULISWS species, and dithiothreitol (DTT) activity of HULISWS were quantified in PM2.5 samples collected during a 1-year period in Beijing. Strong correlation was observed between HULISWS and DTT activity; both exhibited higher levels during the heating season than during the nonheating season. Positive matrix factorization analysis of both HULISWS and DTT activity was performed. Four combustion-related sources, namely coal combustion, biomass burning, waste incineration, and vehicle exhausts, and one secondary factor were resolved. In particular, waste incineration was identified as a source of HULISWS for the first time. Biomass burning and secondary aerosol formation were the major contributors ( > 59 %) to both HULISWS and associated DTT activity throughout the year. During the nonheating season, secondary aerosol formation was the most important source, whereas during the heating season, the predominant contributor was biomass burning. The four combustion-related sources accounted for > 70 % of HULISWS and DTT activity, implying that future reduction in PM2.5 emissions from combustion activities can substantially reduce the HULISWS burden and their potential health impact in Beijing.

Two speciated and spatially resolved emissions databases for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region (AOSR) were developed. The first database was derived from volatile organic compound (VOC) emissions data provided by the Cumulative Environmental Management Association (CEMA) and the second database was derived from additional data collected within the Joint Canada–Alberta Oil Sands Monitoring (JOSM) program. CALPUFF modelling results for atmospheric polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, and dibenzothiophenes (DBTs), obtained using each of the emissions databases, are presented and compared with measurements from a passive air monitoring network. The JOSM-derived emissions resulted in better model–measurement agreement in the total PAH concentrations and for most PAH species concentrations compared to results using CEMA-derived emissions. At local sites near oil sands mines, the percent error of the model compared to observations decreased from 30 % using the CEMA-derived emissions to 17 % using the JOSM-derived emissions. The improvement at local sites was likely attributed to the inclusion of updated tailings pond emissions estimated from JOSM activities. In either the CEMA-derived or JOSM-derived emissions scenario, the model underestimated PAH concentrations by a factor of 3 at remote locations. Potential reasons for the disagreement include forest fire emissions, re-emissions of previously deposited PAHs, and long-range transport not considered in the model. Alkylated PAH and DBT concentrations were also significantly underestimated. The CALPUFF model is expected to predict higher concentrations because of the limited chemistry and deposition modelling. Thus the model underestimation of PACs is likely due to gaps in the emissions database for these compounds and uncertainties in the methodology for estimating the emissions. Future work is required that focuses on improving the PAC emissions estimation and speciation methodologies and reducing the uncertainties in VOC emissions which are subsequently used in PAC emissions estimation.

Gaofen-3 is the first C-band fully polarimetric SAR satellite in China, which is widely used in various fields such as ocean monitoring, disaster reduction and so on. In this paper, a new satellite constellation is proposed based on the orbit of Gaofen-3 satellite. The constellation includes Gaofen-3 and other two duplicates. It is able to do repeat-pass interferometry, repeat-pass differential interferometry, along-track interferometry and stereo measurement. With these abilities, it can generate the earth DEM without ground control points and have better performance in moving target identification and monitoring. The performance and the system requirements are analysed, which provides a good reference for the design of spaceborne SAR constellation.

Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems.

Numerous existing satellites observe physical or environmental properties of the Earth system. Many of these satellites provide global-scale observations, but these observations are often sparse and noisy. By contrast, contiguous, global maps are often most useful to the scientific community (i.e., Level 3 products). We develop a spatio-temporal moving window block kriging method to create contiguous maps from sparse and/or noisy satellite observations. This approach exhibits several advantages over existing methods: (1) it allows for flexibility in setting the spatial resolution of the Level 3 map, (2) it is applicable to observations with variable density, (3) it produces a rigorous uncertainty estimate, (4) it exploits both spatial and temporal correlations in the data, and (5) it facilitates estimation in real time. Moreover, this approach only requires the assumption that the observable quantity exhibits spatial and temporal correlations that are inferable from the data. We test this method by creating Level 3 products from satellite observations of CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT), CH4 (XCH4) from the Infrared Atmospheric Sounding Interferometer (IASI) and solar-induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). We evaluate and analyze the difference in performance of spatio-temporal vs. recently developed spatial kriging methods.

Global gridded maps (a.k.a. Level 3 products) of Earth system properties observed by satellites are central to understanding the spatiotemporal variability of these properties. They also typically serve either as inputs into biogeochemical models or as independent data for evaluating such models. Spatial binning is a common method for generating contiguous maps, but this approach results in a loss of information, especially when the measurement noise is low relative to the degree of spatiotemporal variability. Such "binned" fields typically also lack a quantitative measure of uncertainty. Geostatistical mapping has previously been shown to make higher spatiotemporal resolution maps possible, and also provides a measure uncertainty associated with the gridded products. This study proposes a flexible moving window block kriging method that can be used as a tool for creating high spatiotemporal resolution maps from satellite data. It relies only on the assumption that the observed physical quantity exhibits spatial correlation that can be inferred from the observations. The method has several innovations relative to previously applied methods: (1) it provides flexibility in the spatial resolution of the contiguous maps, (2) it is applicable for physical quantities with varying spatiotemporal coverage (i.e., density of measurements) by utilizing a more general and versatile data sampling approach, and (3) it provides rigorous assessments of the uncertainty associated with the gridded products. The method is demonstrated by creating Level 3 products from observations of column-integrated carbon dioxide (XCO2) from the GOSAT (Greenhouse Gases Observing Satellite) satellite, and solar induced fluorescence (SIF) from the GOME-2 (Global Ozone Monitoring Experiment-2) instrument.

To quantify mercury dry deposition, the Atmospheric Mercury Network (AMNet) of the National Atmospheric Deposition Program (NADP) was established recently to monitor the speciated atmospheric mercury (i.e. gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM) and particulate-bound mercury (PBM)). However, the spatial coverage of AMNet is far less than the long-established Mercury Deposition Network (MDN) for wet deposition monitoring. The present study describes the first attempt linking ambient concentration of the oxidized mercury (GOM + PBM) with wet deposition aiming to estimate GOM + PBM roughly at locations and/or times where such measurement is not available but where wet deposition is monitored. The beta distribution function is used to describe the distribution of GOM + PBM and is used to predict GOM + PBM from monitored wet deposition. The mean, median, mode, standard deviation, and skewness of the fitted beta distribution parameters were generated using data collected in 2009 at multiple monitoring superstations. The established beta distribution function from the 2009 GOM + PBM data is used to construct a model that predicts GOM + PBM from wet deposition data. The model is validated using 2010 data at multiple stations, and the predicted monthly GOM + PBM concentrations agree reasonably well with measurements. The model has many potential applications after further improvements and validation using different data sets.

Referencia para la gestión de las redes de reservas naturales basada en la creación de modelos MaxEnt y el análisis de deficiencias: un estudio del faisán orejudo pardo en China La planificación de reservas naturales y la creación de redes son importantes para la conservación de los hábitats y la fauna silvestre. Los análisis de las deficiencias son instrumentos eficientes y fiables para establecer un orden de prioridad entre las iniciativas de conservación de hábitats, en especial por lo que respecta a las especies en peligro de extinción. Proponemos un plan de conservación para el faisán orejudo pardo, Crossoptilon mantchuricum, mediante la determinación de las zonas con una protección insuficiente en las 14 reservas naturales existentes. En total, se seleccionaron 45 localidades y 11 variables ambientales en función de las características del uso del hábitat del faisán orejudo pardo, y se utilizó un modelo de máxima entropía (MaxEnt) para obtener la distribución de la especie. Los resultados del modelo MaxEnt mostraron una elevada precisión de predicción. Los resultados del análisis de las deficiencias revelaron que en las montañas Luliang, en Shanxi, y las montañasXiaowutai, en Hebei, la protección era insuficiente. Encontramos 458 km2 de hábitat óptimo y 1.390 km2 de hábitat moderadamente adecuado dentro de los límites de la reserva natural nacional. No obstante, casi 1.861 km2 del hábitat óptimo y 17.035 km2 del hábitat moderadamente adecuado no estaban protegidos, lo que equivale al 9,0% y el 82,1%, respectivamente, del hábitat adecuado total. La mayor parte de la superficie sin protección estaba formada por hábitat moderadamente adecuado para el faisán orejudo pardo y debería considerarse prioritaria en las iniciativas futuras de conservación. Hay nueve reservas naturales a lo largo de un eje norte–sur en las montañas Luliang que forma un pasillo ecológico. Para mantener la integridad, originalidad y continuidad de estos hábitats y, por tanto, proteger el faisán orejudo pardo, deberían reforzarse los departamentos locales de conservación con miras a mejorar la gestión de la reserva natural a escala provincial y poner en práctica eficazmente las iniciativas de conservación.

Xenotropic MLV-Related Virus (XMRV) was recently reported to be associated with prostate cancer and chronic fatigue syndrome (CFS). Infection was also reported in 3.7% of healthy individuals. These highly reported frequencies of infection prompted concerns about the possibility of a new, widespread retroviral epidemic. The Multicenter AIDS Cohort Study (MACS) provides an opportunity to assess the prevalence of XMRV infection and its association with HIV-1 infection among men who have sex with men. Reliable detection of XMRV infection requires the application of multiple diagnostic methods, including detection of human antibodies to XMRV and detection of XMRV nucleic acid. We, therefore, tested 332 patient plasma and PBMC samples obtained from recent visits in a subset of patients in the MACS cohort for XMRV antibodies using Abbott prototype ARCHITECT chemiluminescent immunoassays (CMIAs) and for XMRV RNA and proviral DNA using a XMRV single-copy qPCR assay (X-SCA). Although 9 of 332 (2.7%) samples showed low positive reactivity against a single antigen in the CMIA, none of these samples or matched controls were positive for plasma XMRV RNA or PBMC XMRV DNA by X-SCA. Thus, we found no evidence of XMRV infection among men in the MACS regardless of HIV-1 serostatus.

We present the ultra-low-temperature heat-transport study of iron-based superconductors Ba(Fe_{1-x}Ru_{x})_{2}As_{2} and BaFe_{2}(As_{1-x}P_{x})_{2}. For optimally doped Ba(Fe_{0.64}Ru_{0.36})_{2}As_{2}, a large residual κ_{0}/T at zero field and a sqrt[H] dependence of κ_{0}(H)/T are observed, which provide strong evidences for nodes in the superconducting gap. This result demonstrates one more nodal superconductor in iron pnictides. The similarities between isovalent Fe and P dopings strongly suggest that the nodal superconductivity in Ba(Fe_{0.64}Ru_{0.36})_{2}As_{2} may have the same origin as in BaFe_{2}(As_{0.67}P_{0.33})_{2}. Furthermore, in underdoped Ba(Fe_{0.77}Ru_{0.23})_{2}As_{2} and strongly underdoped BaFe_{2}(As_{0.82}P_{0.18})_{2}, κ_{0}/T manifests similar nodal behavior, which result shows the robustness of nodal superconductivity in the underdoped regime and puts constraint on theoretical models.

The in-plane resistivity ρ and thermal conductivity κ of the heavy-fermion superconductor Ce_{2}PdIn_{8} single crystals were measured down to 50 mK. A field-induced quantum critical point, occurring at the upper critical field H_{c2}, is demonstrated from the ρ(T)∼T near H_{c2} and ρ(T)∼T^{2} when further increasing the field. The large residual linear term κ_{0}/T at zero field and the rapid increase of κ(H)/T at low field give evidence for nodal superconductivity in Ce_{2}PdIn_{8}. The jump of κ(H)/T near H_{c2} suggests a first-order-like phase transition at low temperature. These results mimic the features of the famous CeCoIn_{5} superconductor, implying that Ce_{2}PdIn_{8} may be another interesting compound to investigate for the interplay between magnetism and superconductivity.